repo_name
stringlengths 5
114
| repo_url
stringlengths 24
133
| snapshot_id
stringlengths 40
40
| revision_id
stringlengths 40
40
| directory_id
stringlengths 40
40
| branch_name
stringclasses 209
values | visit_date
timestamp[ns] | revision_date
timestamp[ns] | committer_date
timestamp[ns] | github_id
int64 9.83k
683M
⌀ | star_events_count
int64 0
22.6k
| fork_events_count
int64 0
4.15k
| gha_license_id
stringclasses 17
values | gha_created_at
timestamp[ns] | gha_updated_at
timestamp[ns] | gha_pushed_at
timestamp[ns] | gha_language
stringclasses 115
values | files
listlengths 1
13.2k
| num_files
int64 1
13.2k
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
QuixoteHY/stock
|
https://github.com/QuixoteHY/stock
|
4f05e62fbb2fd6f6cd612ee820cc32e033070d6c
|
7afea462cf19c6de887bff503e06370fd1dd4716
|
1240a3b10b703895c0e6bca293b5f7499c186a1b
|
refs/heads/master
| 2020-07-06T16:41:07.900042
| 2019-12-29T23:03:18
| 2019-12-29T23:03:18
| 203,076,311
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.594059407711029,
"alphanum_fraction": 0.6369637250900269,
"avg_line_length": 26.545454025268555,
"blob_id": "c308dc6c700d5e933ee6a02b216987e28669b67f",
"content_id": "ffc720514013f24e8e4a7ffbaf3607ea900e92ed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 303,
"license_type": "no_license",
"max_line_length": 111,
"num_lines": 11,
"path": "/common/logger.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n# @Time : 2019-06-05 16:11\n# @Author : huyuan@zingfront.com\n# @description :\n\nimport logging\n\nlogging.basicConfig(format='[%(asctime)s L:%(lineno)d][%(pathname)s] %(message)s', datefmt='%Y-%m-%d %H:%M:%S')\nlogger = logging.getLogger()\nlogger.setLevel(logging.INFO)\n"
},
{
"alpha_fraction": 0.4934810996055603,
"alphanum_fraction": 0.5019556879997253,
"avg_line_length": 24.566667556762695,
"blob_id": "52b8cd3e91fb6dfe987307fa613a93fdc4149775",
"content_id": "f46b40e49538e0f9af231eab207526258b2e09fc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2434,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 60,
"path": "/common/data_model.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-08 22:44\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\n\nasset_liability_rate = ['现金与约当现金比率', '应收账款比率', '存货比率', '流动资产比率', '应付账款比率',\n '流动负债比率', '长期负债比率', '股东权益比率']\nfinancial_structure = ['负债占资产比率', '长期资金占投资比率']\nsolvency = ['流动比率', '速动比率']\nbusiness_capability = ['应收账款周转率(次)', '平均收现日数', '存货周转率(次)', '平均销货日数(平均在库天数)',\n '固定资产周转率', '总资产周转率']\nprofitability = ['净资产收益率RoE', '总资产报酬率RoA', '销售毛利率', '销售净利率', '净利率', '基本每股收益',\n '税后净利(百万元)']\ncash_flow = ['现金流量比率', '营业活动现金流量(百万元)', '投资活动现金流量(百万元)', '筹资活动现金流量(百万元)']\n\n\nfina_indicators_dict = {\n # 资产负债比率(占总资产%)\n '现金与约当现金比率': dict(),\n '应收账款比率': dict(),\n '存货比率': dict(),\n '流动资产比率': dict(),\n '应付账款比率': dict(),\n '流动负债比率': dict(),\n '长期负债比率': dict(),\n '股东权益比率': dict(),\n # 五大财务比率\n # 财务结构\n '负债占资产比率': dict(),\n '长期资金占投资比率': dict(),\n # 偿债能力\n '流动比率': dict(),\n '速动比率': dict(),\n # 经营能力\n '应收账款周转率(次)': dict(),\n '平均收现日数': dict(),\n '存货周转率(次)': dict(),\n '平均销货日数(平均在库天数)': dict(),\n '固定资产周转率': dict(),\n '总资产周转率': dict(),\n # 获利能力\n '净资产收益率RoE': dict(),\n '总资产报酬率RoA': dict(),\n '销售毛利率': dict(),\n '销售净利率': dict(),\n # '经营安全边际率(%)': dict(),\n '净利率': dict(),\n '基本每股收益': dict(),\n '税后净利(百万元)': dict(),\n # 现金流量\n '现金流量比率': dict(),\n # '现金流量允当比率': dict(),\n # '现金再投资比率': dict(),\n '营业活动现金流量(百万元)': dict(),\n '投资活动现金流量(百万元)': dict(),\n '筹资活动现金流量(百万元)': dict(),\n}\n"
},
{
"alpha_fraction": 0.5969316363334656,
"alphanum_fraction": 0.65969318151474,
"avg_line_length": 28.875,
"blob_id": "aa61678dc27eaaf77ccb50df6080cc9a9057f7a1",
"content_id": "ddbf97b7bdebbad5c856c85745c6af4c5da42b46",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 721,
"license_type": "no_license",
"max_line_length": 108,
"num_lines": 24,
"path": "/stock/get_all_stock_list.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-08 21:04\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nimport datetime\n\nimport tushare\n\nfrom common.constant import data_path\n\ntushare.set_token('1e431dd1d92959eeec4ef91f58a3ec1f85b5b242d32f1c3a2b00df08')\npro = tushare.pro_api()\n\ndata = pro.stock_basic(exchange='', list_status='L',\n fields='ts_code,symbol,name,area,industry,fullname,enname,market,exchange,curr_type,'\n 'list_status,list_date,delist_date,is_hs')\n\ntoday = datetime.datetime.today().strftime('%Y%m%d')\nfile = data_path+'/stock_basic/all_stock_list_'+today+'.csv'\ndata.to_csv(file)\nprint('Stocks saved.')\n"
},
{
"alpha_fraction": 0.6354680061340332,
"alphanum_fraction": 0.7832512259483337,
"avg_line_length": 21.55555534362793,
"blob_id": "95adbcb0c2bdfd412eb4afd410880b7706d124d0",
"content_id": "c499db228d9e1625f79fa42c36f4674da0ffb563",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 307,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 9,
"path": "/README.md",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# stock\n目前已实现功能：A股上市公司部分财务信息查询。\n\n数据源：Tushare\n\n使用MongoDB做数据存储，使用aiohttp做web查询接口\n\n使用：http://119.29.152.194:8888/get/stock/fina_indicators/ + A股股票代码\n例子：http://119.29.152.194:8888/get/stock/fina_indicators/600699\n"
},
{
"alpha_fraction": 0.4533333480358124,
"alphanum_fraction": 0.5400000214576721,
"avg_line_length": 24,
"blob_id": "f1886793e829d19d2f0e6fe42e218d72582eee60",
"content_id": "cf939d1d9a2920064d8241d66c42a48563484831",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 154,
"license_type": "no_license",
"max_line_length": 42,
"num_lines": 6,
"path": "/data_server_interface/python3/__init__.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-08-18 11:15\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n"
},
{
"alpha_fraction": 0.5931510925292969,
"alphanum_fraction": 0.6063461899757385,
"avg_line_length": 40.33766174316406,
"blob_id": "558fc3ec32f7a688175805716100ace3035fc75e",
"content_id": "48bdfa2b776ae17959d9918942e92a7425226f49",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3279,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 77,
"path": "/common/fina_indicators.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-12 23:21\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nfrom common.data_model import asset_liability_rate\nfrom common.data_model import financial_structure\nfrom common.data_model import solvency\nfrom common.data_model import business_capability\nfrom common.data_model import profitability\nfrom common.data_model import cash_flow\n\n\ndef get_table_html(fina_indicators, category_name, category_list):\n html = \"\"\"\n<table class=\"fina_indicators\" border=\"4\" style=\"font-size:13px\">\n <caption style=\"color:blue;font-weight:bold;font-size:15px\"><i>%s</i></caption>\n %s\n</table>\n \"\"\"\n year_list = ['20' + str(i) + '1231' for i in range(10, 19)]\n table = '<tr style=\"font-weight:bold;font-size:15px\"><td align=center>类别</td>'\n table = table + '\\n'.join(['<td align=center>' + year + '</td>' for year in year_list]) + '</tr>'\n header_print = '类别' + 11 * ' ' + ' '.join(year_list)\n print(header_print)\n for indicator_name in category_list:\n indicators = fina_indicators[indicator_name]\n tr_indicator = '<tr><td align=center>' + indicator_name + '</td>'\n temp_string = indicator_name + (20 - len(indicator_name) * 2) * ' ' + '\\t'\n for year in year_list:\n if year in indicators:\n tr_indicator = tr_indicator + '<td>' + str(indicators[year]) + '</td>'\n temp_string = temp_string + str(indicators[year]) + (10 - len(str(indicators[year]))) * ' '\n else:\n tr_indicator = tr_indicator + '<td>--</td>'\n temp_string = temp_string + '' + (10 - len('')) * ' '\n tr_indicator += '</tr>'\n table += tr_indicator\n print(temp_string)\n return html % (category_name, table)\n\n\ndef get_html_table_code(fina_indicators, stock_basic):\n stock_basic_html = \"\"\"\n<div>\n <h3>%s</h3>\n <i>\n <span>行业:%s</span> \n <span>上市时间:%s</span> \n <span>%s</span> \n </i>\n</div>\n \"\"\" % (stock_basic['name']+' '+stock_basic['symbol'], stock_basic['industry'],\n stock_basic['list_date'], stock_basic['fullname'])\n html = \"\"\"\n<html>\n<head>\n <title>%s(%s)财务报表解读</title>\n <meta charset=\"utf-8\">\n</head>\n<body>\n %s\n <hr/><p></p>\n %s<p></p> %s<p></p> %s<p></p> %s<p></p> %s<p></p> %s\n</body>\n \"\"\"\n table_asset_liability_rate = get_table_html(fina_indicators, '资产负债比率(占总资产%)', asset_liability_rate)\n table_financial_structure = get_table_html(fina_indicators, '财务结构', financial_structure)\n table_solvency = get_table_html(fina_indicators, '偿债能力', solvency)\n table_business_capability = get_table_html(fina_indicators, '经营能力', business_capability)\n table_profitability = get_table_html(fina_indicators, '获利能力', profitability)\n table_cash_flow = get_table_html(fina_indicators, '现金流量', cash_flow)\n return html % (stock_basic['name'], stock_basic['symbol'], stock_basic_html, table_asset_liability_rate,\n table_financial_structure, table_solvency, table_business_capability, table_profitability,\n table_cash_flow)\n"
},
{
"alpha_fraction": 0.5378378629684448,
"alphanum_fraction": 0.6756756901741028,
"avg_line_length": 15.818181991577148,
"blob_id": "92c4521f203c24f0f899bd7c0776c4110842ddb9",
"content_id": "6cd212bd0a63b688e973d697f7325a04e6d2df16",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 494,
"license_type": "no_license",
"max_line_length": 86,
"num_lines": 22,
"path": "/data_server_interface/python3/README.md",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# 使用说明\n```text\n默认服务器：119.29.152.194\n默认端口：8888\n\n例子：http://119.29.152.194:8888/get/stock/fina_indicators/600699\n```\n\n## 一、Web接口API\n\n### API说明：\n\n- {financial_statement_type}：财务数据类型\n- {ts_code}：股票代码\n\n#### 获取某股票的财务数据\n```text\n/get/stock/{financial_statement_type}/{ts_code}\n```\n\n##### 例子：\n- http://119.29.152.194:8888/get/stock/fina_indicators/{ts_code} 获取股票代码为{ts_code}的财务指标\n"
},
{
"alpha_fraction": 0.53227698802948,
"alphanum_fraction": 0.5762910842895508,
"avg_line_length": 31.769229888916016,
"blob_id": "121b47ac401da859f55eecf42c52cc274f89981c",
"content_id": "6b27fe91093773ad19b7c7022a40aec92a080b40",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1736,
"license_type": "no_license",
"max_line_length": 103,
"num_lines": 52,
"path": "/stock/get_stock_income.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-08 21:21\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nimport time\nimport logging\nimport csv\n\nfrom common.constant import data_path\nfrom common.tushare_api import pro\n\n\ndef get_the_stock_history_income(_pro, ts_code, start_date='20050101', end_date='20190630', fields=''):\n # fields为空默认显示所有字段\n df = _pro.income(ts_code=ts_code, start_date=start_date, end_date=end_date, fields=fields)\n file = data_path+'/income/income_'+end_date+'_'+ts_code+'.csv'\n df.to_csv(file)\n\n\ndef run():\n date_str = '20190608'\n file = data_path + '/stock_basic/all_stock_list_' + date_str + '.csv'\n count = 0\n with open(file, newline='', encoding='UTF-8') as cf:\n reader = csv.DictReader(cf)\n for row in reader:\n count += 1\n try:\n get_the_stock_history_income(pro, row['ts_code'])\n print(str(count)+'\\t', row['ts_code'], row['fullname'], '\\t\\t\\t\\t\\t\\t成功')\n except Exception as e:\n logging.info(logging.exception(e))\n print(str(count)+'\\t', row['ts_code'], '\\t\\t失败')\n with open(data_path + '/err_log/err_income_' + date_str + '.log', 'a') as f:\n f.write(row['ts_code']+'\\n')\n time.sleep(2)\n\n\nif __name__ == '__main__':\n # run()\n get_the_stock_history_income(pro, '000001.SZ')\n time.sleep(2)\n get_the_stock_history_income(pro, '000988.SZ')\n time.sleep(2)\n get_the_stock_history_income(pro, '002129.SZ')\n time.sleep(2)\n get_the_stock_history_income(pro, '601010.SH')\n time.sleep(2)\n get_the_stock_history_income(pro, '601799.SH')\n"
},
{
"alpha_fraction": 0.8545454740524292,
"alphanum_fraction": 0.8727272748947144,
"avg_line_length": 6.857142925262451,
"blob_id": "028f8e8187328f5a958304ecdaa3d393ec42c5ff",
"content_id": "271ad75d3e41ef70a0151a5d3f716c33c5ad53a6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 55,
"license_type": "no_license",
"max_line_length": 10,
"num_lines": 7,
"path": "/data_server_interface/python3/requirements.txt",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "aiohttp\nrequests\ntushare\npandas\nsimplejson\nbs4\npymongo\n"
},
{
"alpha_fraction": 0.5130866169929504,
"alphanum_fraction": 0.5406137108802795,
"avg_line_length": 33.092308044433594,
"blob_id": "aba6cd0f39528bfd91b237eb5f1bed86b1e8e467",
"content_id": "f854b358f3d0cc8c3e7b050d9ddb418cb16de7ff",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2256,
"license_type": "no_license",
"max_line_length": 111,
"num_lines": 65,
"path": "/stock/get_fina_indicator.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-09 15:38\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe : fina_indicator\n\nimport time\nimport logging\nimport csv\n\nfrom common.constant import data_path\nfrom common.tushare_api import pro\n\n\ndef get_the_stock_history_fina_indicator(_pro, ts_code, start_date='20050101', end_date='20190630', fields=''):\n # fields为空默认显示所有字段\n df = _pro.fina_indicator(ts_code=ts_code, start_date=start_date, end_date=end_date, fields=fields)\n file = data_path+'/fina_indicator/fina_indicator_'+end_date+'_'+ts_code+'.csv'\n df.to_csv(file)\n\n\ndef run():\n date_str = '20190608'\n file = data_path + '/stock_basic/all_stock_list_' + date_str + '.csv'\n count = 0\n with open(file, newline='', encoding='UTF-8') as cf:\n reader = csv.DictReader(cf)\n for row in reader:\n count += 1\n try:\n get_the_stock_history_fina_indicator(pro, row['ts_code'])\n print(str(count)+'\\t', row['ts_code'], row['fullname'], '\\t\\t\\t\\t\\t\\t成功')\n except Exception as e:\n logging.info(logging.exception(e))\n print(str(count)+'\\t', row['ts_code'], '\\t\\t失败')\n with open(data_path + '/err_log/err_fina_indicator_' + date_str + '.log', 'a') as f:\n f.write(row['ts_code']+'\\n')\n time.sleep(2)\n\n\ndef repair():\n date_str = '20190608'\n file = data_path + '/err_log/err_fina_indicator_' + date_str + '.log'\n count = 0\n with open(file, encoding='UTF-8') as f:\n for line in f:\n ts_code = line.strip()\n if not ts_code:\n continue\n count += 1\n try:\n get_the_stock_history_fina_indicator(pro, ts_code)\n print(str(count)+'\\t', ts_code, '\\t\\t成功')\n except Exception as e:\n logging.info(logging.exception(e))\n print(str(count)+'\\t', ts_code, '\\t\\t失败')\n with open(data_path + '/err_log/err_fina_indicator_20190609.log', 'a') as f_err:\n f_err.write(ts_code+'\\n')\n time.sleep(2)\n\n\nif __name__ == '__main__':\n # run()\n repair()\n"
},
{
"alpha_fraction": 0.5481072664260864,
"alphanum_fraction": 0.6048895716667175,
"avg_line_length": 31.512821197509766,
"blob_id": "f1080f4d56b516101ca7ea5b3cae7c73c84f6da4",
"content_id": "f38864abdc757fc09f904dc79a1bfdb04d7579be",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1268,
"license_type": "no_license",
"max_line_length": 116,
"num_lines": 39,
"path": "/data_server_interface/nodejs/server.js",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "var express = require('express');\nvar app = express();\nvar MongoClient = require('mongodb').MongoClient;\nvar url = \"mongodb://localhost:27017/\";\n// --registry=https://registry.npm.taobao.org\n\napp.get('/get11', function (req, res) {\n exports.result = MongoClient.connect(url, { useNewUrlParser: true }, function(err, db) {\n if (err) throw err;\njjjj var where_str = {\"ts_code\": \"000001_SZ\", \"indicator_code\": \"0015\", \"time\": /20(1[876543210]|0[9])1231/i}\n var result = dbo.collection(\"fi\").find(where_str).toArray(function(err, result) {\n if (err) throw err;\n// console.log(result);\n db.close();\n return result;\n });\n return result;\n });\n console.log(result);\n res.send(result);\n})\n\napp.get('/get', function (req, res) {\n var db = MongoClient.connect('mongodb://localhost:27017/stock');\n var where_str = {\"ts_code\": \"000001_SZ\", \"indicator_code\": \"0015\", \"time\": /20(1[876543210]|0[9])1231/i};\n result = db.fi.find(where_str);\n console.log(result);\n db.close();\n res.send(result);\n})\n\nvar server = app.listen(8082, function () {\n\n var host = server.address().address\n var port = server.address().port\n\n console.log(\"web server: http://%s:%s\", host, port)\n\n})\n"
},
{
"alpha_fraction": 0.699999988079071,
"alphanum_fraction": 0.7149122953414917,
"avg_line_length": 26.780487060546875,
"blob_id": "8b1c01449cf0723c9bb87b552a4e74b526384a23",
"content_id": "04ae85bd8679d8a8419b31903acae28576f92a9f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1140,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 41,
"path": "/demo/Tutorial 04 CN - Get intraday.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "import tushare\nimport pandas\nimport datetime\nimport os\n\ndef stockPriceIntraday(ticker, folder):\n\t# Step 1. Get intraday data online\n\tintraday = tushare.get_hist_data(ticker, ktype='5')\n\n\t# Step 2. If the history exists, append\n\tfile = folder+'/'+ticker+'.csv'\n\tif os.path.exists(file):\n\t\thistory = pandas.read_csv(file, index_col=0)\n\t\tintraday.append(history)\n\n\t# Step 3. Inverse based on index\n\tintraday.sort_index(inplace=True)\n\tintraday.index.name = 'timestamp'\n\n\t# Step 4. Save\n\tintraday.to_csv(file)\n\tprint ('Intraday for ['+ticker+'] got.')\n\n# Step 1. Get tickers online\ntickersRawData = tushare.get_stock_basics()\ntickers = tickersRawData.index.tolist()\n\n# Step 2. Save the ticker list to a local file\ndateToday = datetime.datetime.today().strftime('%Y%m%d')\nfile = '../02. Data/00. TickerListCN/TickerList_'+dateToday+'.csv'\ntickersRawData.to_csv(file)\nprint ('Tickers saved.')\n\n# Step 3. Get stock price (intraday) for all\nfor i, ticker in enumerate(tickers):\n\ttry:\n\t\tprint ('Intraday', i, '/', len(tickers))\n\t\tstockPriceIntraday(ticker, folder='../02. Data/01. IntradayCN')\n\texcept:\n\t\tpass\nprint ('Intraday for all stocks got.')\n\n"
},
{
"alpha_fraction": 0.6194174885749817,
"alphanum_fraction": 0.6295145750045776,
"avg_line_length": 33.783782958984375,
"blob_id": "5e7f425b6859860895f2e3984efc0da8434de910",
"content_id": "be61c685d6e5c3b53ead0b01a5bfcf1ca421027d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2613,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 74,
"path": "/data_server_interface/python3/server_stock.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-08-18 11:33\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nimport asyncio\n\nfrom aiohttp import web\n\nfrom common.logger import logger\n\nfrom data_server_interface.python3.settings import SERVER_HOST, SERVER_PORT, HEARTBEAT_INTERVAL\nfrom data_server_interface.python3.controller import Controller\n\n\ndef _heartbeat(loop, interval):\n try:\n logger.info('心跳：'+str(interval)+'s')\n except Exception as e:\n logger.info(logger.exception(e))\n loop.call_later(interval, _heartbeat, loop, interval)\n\n\ndef start_heartbeat(loop, interval):\n _heartbeat(loop, interval)\n\n\nclass MainHandler:\n def __init__(self):\n self.controller = Controller()\n\n async def get_stock_info(self, request):\n remote = request.remote\n logger.info(str(remote))\n try:\n financial_statement_type = request.match_info.get('financial_statement_type', '')\n ts_code = request.match_info.get('ts_code', '')\n if not ts_code:\n return web.json_response({'status': 'no ts_code in your request url'})\n if financial_statement_type == 'balance_sheet':\n self.controller.get_balance_sheet(ts_code)\n return web.json_response({})\n elif financial_statement_type == 'fina_indicators':\n return web.Response(body=self.controller.get_fina_indicators(ts_code).encode('utf-8'),\n content_type='text/html')\n except Exception as e:\n logger.info(logger.exception(e))\n return web.json_response({'status': 'error in server'})\n\n\nasync def init(loop):\n app = web.Application(loop=loop)\n handler = MainHandler()\n #\n # 获取某上市公司资产负债表信息\n # http://127.0.0.1:8888/get/stock/{financial_statement_type}/{ts_code}\n app.router.add_get('/get/stock/{financial_statement_type}/{ts_code}', handler.get_stock_info)\n #\n # server = await loop.create_server(app.make_handler(), SERVER_HOST, SERVER_PORT)\n # logger.info('\\n\\tServer started at http://%s:%s...' % (SERVER_HOST, SERVER_PORT))\n # return server\n runner = web.AppRunner(app)\n await runner.setup()\n site = web.TCPSite(runner, SERVER_HOST, SERVER_PORT)\n logger.info('\\n\\tServer started at http://%s:%s...' % (SERVER_HOST, SERVER_PORT))\n await site.start()\n\nif __name__ == '__main__':\n _loop = asyncio.get_event_loop()\n _loop.run_until_complete(init(_loop))\n start_heartbeat(_loop, HEARTBEAT_INTERVAL)\n _loop.run_forever()\n\n"
},
{
"alpha_fraction": 0.6679734587669373,
"alphanum_fraction": 0.6815220713615417,
"avg_line_length": 41.4083137512207,
"blob_id": "4f74ffdd0d90368e03e29df632c01dedc8ce337e",
"content_id": "e97bc1885ee51bd809484b7829118fad1640c233",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 19506,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 409,
"path": "/common/calculate_financial_indicators.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-08 22:44\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe : Calculating financial indicators\n\nimport copy\n\nfrom common.constant import data_path\nfrom common.tushare_api import pro\nfrom common.utils import Utils\nfrom common.fina_indicators import get_html_table_code\nfrom common.data_model import fina_indicators_dict\n\n\ndef calculate_cash_to_total_assets_rate(balancesheet):\n # 现金与约当现金比率=现金占总资产比率=(货币资金+交易性金融资产)/总资产*100%\n money_cap = float(balancesheet['money_cap'] if balancesheet['money_cap'] else 0)\n trad_asset = float(balancesheet['trad_asset'] if balancesheet['trad_asset'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return (money_cap+trad_asset)/total_assets\n\n\ndef calculate_accounts_receivable_rate(balancesheet):\n # 应收账款比率=应收账款/总资产*100%\n accounts_receiv = float(balancesheet['accounts_receiv'] if balancesheet['accounts_receiv'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return accounts_receiv/total_assets\n\n\ndef calculate_inventory_rate(balancesheet):\n # 存货比率=存货/总资产*100%\n inventories = float(balancesheet['inventories'] if balancesheet['inventories'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return inventories/total_assets\n\n\ndef calculate_liquidity_rate(balancesheet):\n # 流动资产比率=流动资产合计/总资产*100%\n total_cur_assets = float(balancesheet['total_cur_assets'] if balancesheet['total_cur_assets'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return total_cur_assets/total_assets\n\n\ndef calculate_accounts_payable_rate(balancesheet):\n # 应付账款比率=应付账款/总资产*100%\n acct_payable = float(balancesheet['acct_payable'] if balancesheet['acct_payable'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return acct_payable/total_assets\n\n\ndef calculate_current_liability_rate(balancesheet):\n # 流动负债比率=流动负债合计/总资产*100%\n total_cur_liab = float(balancesheet['total_cur_liab'] if balancesheet['total_cur_liab'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return total_cur_liab/total_assets\n\n\ndef calculate_long_term_debt_rate(balancesheet):\n # 长期负债比率=非流动负债/总资产*100%\n total_ncl = float(balancesheet['total_ncl'] if balancesheet['total_ncl'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return total_ncl/total_assets\n\n\ndef calculate_shareholder_equity_rate(balancesheet):\n # 股东权益比率=股东权益合计(含少数股东权益)/总资产*100%\n total_hldr_eqy_inc_min_int = \\\n float(balancesheet['total_hldr_eqy_inc_min_int'] if balancesheet['total_hldr_eqy_inc_min_int'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return total_hldr_eqy_inc_min_int/total_assets\n\n\n# def calculate_total_debt_shareholders_equity_rate(balancesheet):\n# # 总资产/负债及股东权益总计*100%\n# total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n# total_liab_hldr_eqy = float(balancesheet['total_liab_hldr_eqy'] if balancesheet['total_liab_hldr_eqy'] else 0)\n# if not total_liab_hldr_eqy:\n# return 0\n# return total_assets/total_liab_hldr_eqy\n\n\ndef calculate_debt_to_asset_rate(balancesheet):\n # 负债占资产比率=总负债/总资产*100%\n total_liab = float(balancesheet['total_liab'] if balancesheet['total_liab'] else 0)\n total_assets = float(balancesheet['total_assets'] if balancesheet['total_assets'] else 0)\n if not total_assets:\n return 0\n return total_liab/total_assets\n\n\ndef calculate_long_term_capital_to_invest_rate(balancesheet):\n # 长期资金占不动产/厂房及设备比率=长期资金占投资比率=(长期负债+股东权益)/(固定资产+在建工程+工程物资)(不动产、厂房及设备)*100%\n # 长期资金占不动产、厂房及设备比率=（所有者权益（或股东权益）合计 + 非流动负债合计） / ( 固定资产 + 在建工程 + 工程物资)\n total_ncl = float(balancesheet['total_ncl'] if balancesheet['total_ncl'] else 0)\n total_hldr_eqy_inc_min_int = \\\n float(balancesheet['total_hldr_eqy_inc_min_int'] if balancesheet['total_hldr_eqy_inc_min_int'] else 0)\n fix_assets = float(balancesheet['fix_assets'] if balancesheet['fix_assets'] else 0)\n cip = float(balancesheet['cip'] if balancesheet['cip'] else 0)\n const_materials = float(balancesheet['const_materials'] if balancesheet['const_materials'] else 0)\n if fix_assets+cip+const_materials:\n return (total_ncl+total_hldr_eqy_inc_min_int)/(fix_assets+cip+const_materials)\n else:\n return total_ncl+total_hldr_eqy_inc_min_int\n\n\ndef calculate_liquidity_asset_to_liquidity_debt_rate(balancesheet):\n # 流动比率=流动资产/流动负债*100%\n total_cur_assets = float(balancesheet['total_cur_assets'] if balancesheet['total_cur_assets'] else 0)\n total_cur_liab = float(balancesheet['total_cur_liab'] if balancesheet['total_cur_liab'] else 0)\n if not total_cur_liab:\n return 0\n return total_cur_assets/total_cur_liab\n\n\ndef calculate_quick_moving_rate(balancesheet):\n # 速动比率=（流动资产-存货)/流动负债*100%\n # 速动资产=流动资产-存货，或：速动资产=流动资产-存货-预付账款-待摊费用\n total_cur_assets = float(balancesheet['total_cur_assets'] if balancesheet['total_cur_assets'] else 0)\n inventories = float(balancesheet['inventories'] if balancesheet['inventories'] else 0)\n prepayment = float(balancesheet['prepayment'] if balancesheet['prepayment'] else 0)\n amor_exp = float(balancesheet['amor_exp'] if balancesheet['amor_exp'] else 0)\n total_cur_liab = float(balancesheet['total_cur_liab'] if balancesheet['total_cur_liab'] else 0)\n if not total_cur_liab:\n return 0\n return (total_cur_assets-inventories-prepayment-amor_exp)/total_cur_liab\n\n\ndef calculate_receivable_turnover_rate(balancesheet, income):\n # 应收账款周转率(次)=营业收入/应收账款*100%\n total_cur_assets = float(income['revenue'] if income['revenue'] else 0)\n accounts_receiv = float(balancesheet['accounts_receiv'] if balancesheet['accounts_receiv'] else 0)\n if not accounts_receiv:\n return 0\n return total_cur_assets/accounts_receiv/100\n\n\ndef calculate_ave_receivable_days(balancesheet, income):\n # 平均收现日数=360/应收账款周转率=360/(营业收入/应收账款*100%)\n total_cur_assets = float(income['revenue'] if income['revenue'] else 0)\n accounts_receiv = float(balancesheet['accounts_receiv'] if balancesheet['accounts_receiv'] else 0)\n if not accounts_receiv:\n return 0\n return 360/((total_cur_assets/accounts_receiv)*100)\n\n\ndef calculate_inventory_turnover(balancesheet, income):\n # 存货周转率(次)=营业成本/存货\n total_cogs = float(income['total_cogs'] if income['total_cogs'] else 0)\n inventories = float(balancesheet['inventories'] if balancesheet['inventories'] else 0)\n if not inventories:\n return 0\n return (total_cogs/inventories)/100\n\n\ndef calculate_ave_sale_days(balancesheet, income):\n # 平均销货日数(平均在库天数)=360/存货周转率\n total_cogs = float(income['total_cogs'] if income['total_cogs'] else 0)\n inventories = float(balancesheet['inventories'] if balancesheet['inventories'] else 0)\n if not inventories:\n return 0\n return 360/((total_cogs/inventories)*100)\n\n\ndef calculate_fixed_invest_turnover_rate(fina_indicator):\n # 固定资产周转率\n fa_turn = float(fina_indicator['fa_turn'] if fina_indicator['fa_turn'] else 0)\n if 'fa_turn' not in fina_indicator:\n return 0\n return float(fa_turn)\n\n\ndef calculate_total_assert_turnover_rate(fina_indicator):\n # 总资产周转率\n assets_turn = float(fina_indicator['assets_turn'] if fina_indicator['assets_turn'] else 0)\n if 'assets_turn' not in fina_indicator:\n return 0\n return float(assets_turn)\n\n\ndef calculate_roe(fina_indicator):\n # 净资产收益率RoE\n roe = float(fina_indicator['roe'] if fina_indicator['roe'] else 0)\n if 'roe' not in fina_indicator:\n return 0\n return float(roe)\n\n\ndef calculate_roa(fina_indicator):\n # 总资产报酬率RoA=归属于母公司所有者的净利润/总资产\n roe = float(fina_indicator['roa'] if fina_indicator['roa'] else 0)\n if 'roa' not in fina_indicator:\n return 0\n return float(roe)\n\n\ndef calculate_operating_margin(fina_indicator):\n # 销售毛利率\n grossprofit_margin = float(fina_indicator['grossprofit_margin'] if fina_indicator['grossprofit_margin'] else 0)\n if 'grossprofit_margin' not in fina_indicator:\n return 0\n return float(grossprofit_margin)\n\n\ndef calculate_business_interest_rate(fina_indicator):\n # 销售净利率\n netprofit_margin = float(fina_indicator['netprofit_margin'] if fina_indicator['netprofit_margin'] else 0)\n if 'netprofit_margin' not in fina_indicator:\n return 0\n return float(netprofit_margin)\n\n\ndef calculate_marginal_rate_of_operational_safety():\n # 经营安全边际率(%) = 营业利益率/营业毛利率\n pass\n\n\ndef calculate_net_interest_rate(income):\n # 净利率=净利润/主营业务收入×100%=(利润总额-所得税费用)/主营业务收入*100%\n total_profit = income['total_profit'].strip()\n if not total_profit:\n total_profit = 0\n total_profit = float(total_profit)\n income_tax = income['income_tax'].strip()\n if not income_tax:\n income_tax = 0\n income_tax = float(income_tax)\n revenue = income['revenue'].strip()\n if not revenue:\n revenue = 0\n revenue = float(revenue)\n if not revenue:\n return 0\n return (total_profit-income_tax)/revenue\n\n\ndef calculate_eps(fina_indicator):\n # 基本每股收益=每股盈余(元)\n eps = float(fina_indicator['eps'] if fina_indicator['eps'] else 0)\n if 'eps' not in fina_indicator:\n return 0\n return float(eps)\n\n\ndef calculate_n_income(income):\n # 税后净利(百万元)\n n_income = float(income['n_income'] if income['n_income'] else 0)\n return float(n_income)/1000000\n\n\ndef calculate_cash_flow_rate(balancesheet, cash_flow):\n # 现金流量比率=经营活动产生的现金流量净额/流动负债\n n_cashflow_act = float(cash_flow['n_cashflow_act'] if cash_flow['n_cashflow_act'] else 0)\n total_cur_liab = float(balancesheet['total_cur_liab'] if balancesheet['total_cur_liab'] else 0)\n if not total_cur_liab:\n return 0\n return n_cashflow_act/total_cur_liab\n\n\ndef calculate_cash_flow(cash_flow):\n # 营业活动现金流量(百万元)=经营活动产生的现金流量净额\n n_cashflow_act = float(cash_flow['n_cashflow_act'] if cash_flow['n_cashflow_act'] else 0)\n return n_cashflow_act/1000000\n\n\ndef calculate_invest_cash_flow(cash_flow):\n # 投资活动现金流量(百万元)=投资活动产生的现金流量净额\n n_cashflow_inv_act = float(cash_flow['n_cashflow_inv_act'] if cash_flow['n_cashflow_inv_act'] else 0)\n return n_cashflow_inv_act/1000000\n\n\ndef calculate_finance_cash_flow(cash_flow):\n # 筹资活动现金流量(百万元)=筹资活动产生的现金流量净额\n n_cash_flows_fnc_act = float(cash_flow['n_cash_flows_fnc_act'] if cash_flow['n_cash_flows_fnc_act'] else 0)\n return n_cash_flows_fnc_act/1000000\n\n\ndef get_fina_indicator():\n df = pro.fina_indicator(ts_code='000040.SZ', start_date='20050101', end_date='20190630', fields='')\n file = data_path + '/test_data/fina_indicator_000040.SZ'+'.csv'\n df.to_csv(file)\n\n\ndef calculate(ts_code):\n fina_indicators = copy.deepcopy(fina_indicators_dict)\n mongodb_fi = Utils.get_conn_fi()\n stock_info = mongodb_fi.find_one({'_id': ts_code})\n financial_statements = stock_info['financial_statements']\n stock_basic = stock_info['stock_basic']\n for end_date, data in financial_statements.items():\n if not data['balance_sheet'] or not data['income'] or not data['cash_flow'] or not data['fifi']:\n continue\n # 资产负债表\n # 资产负债比率(占总资产%)\n # 现金与约当现金比率\n cash_to_total_assets_rate = calculate_cash_to_total_assets_rate(data['balance_sheet'])\n fina_indicators['现金与约当现金比率'][end_date] = Utils.get_rate(cash_to_total_assets_rate)\n # 应收账款比率\n accounts_receivable_rate = calculate_accounts_receivable_rate(data['balance_sheet'])\n fina_indicators['应收账款比率'][end_date] = Utils.get_rate(accounts_receivable_rate)\n # 存货比率\n inventory_rate = calculate_inventory_rate(data['balance_sheet'])\n fina_indicators['存货比率'][end_date] = Utils.get_rate(inventory_rate)\n # 流动资产比率\n liquidity_rate = calculate_liquidity_rate(data['balance_sheet'])\n fina_indicators['流动资产比率'][end_date] = Utils.get_rate(liquidity_rate)\n # 应付账款比率\n total_accounts_payable_rate = calculate_accounts_payable_rate(data['balance_sheet'])\n fina_indicators['应付账款比率'][end_date] = Utils.get_rate(total_accounts_payable_rate)\n # 流动负债比率\n total_current_liability_rate = calculate_current_liability_rate(data['balance_sheet'])\n fina_indicators['流动负债比率'][end_date] = Utils.get_rate(total_current_liability_rate)\n # 长期负债比率\n total_long_term_debt_rate = calculate_long_term_debt_rate(data['balance_sheet'])\n fina_indicators['长期负债比率'][end_date] = Utils.get_rate(total_long_term_debt_rate)\n # 股东权益比率\n total_shareholder_equity_rate = calculate_shareholder_equity_rate(data['balance_sheet'])\n fina_indicators['股东权益比率'][end_date] = Utils.get_rate(total_shareholder_equity_rate)\n # 五大财务比率\n # 五大财务比率--财务结构\n # 负债占资产比率\n total_debt_to_asset_rate = calculate_debt_to_asset_rate(data['balance_sheet'])\n fina_indicators['负债占资产比率'][end_date] = Utils.get_rate(total_debt_to_asset_rate)\n # 长期资金占不动产/厂房及设备比率 = 长期资金占投资比率\n long_term_capital_to_invest_rate = calculate_long_term_capital_to_invest_rate(data['balance_sheet'])\n fina_indicators['长期资金占投资比率'][end_date] = Utils.get_rate(long_term_capital_to_invest_rate)\n # 五大财务比率--偿债能力\n # 流动比率\n liquidity_asset_to_liquidity_debt_rate = calculate_liquidity_asset_to_liquidity_debt_rate(data['balance_sheet'])\n fina_indicators['流动比率'][end_date] = Utils.get_rate(liquidity_asset_to_liquidity_debt_rate)\n # 速动比率\n quick_moving_rate = calculate_quick_moving_rate(data['balance_sheet'])\n fina_indicators['速动比率'][end_date] = Utils.get_rate(quick_moving_rate)\n # 五大财务比率--经营能力\n # 应收账款周转率(次)\n receivable_turnover_rate = calculate_receivable_turnover_rate(data['balance_sheet'], data['income'])\n fina_indicators['应收账款周转率(次)'][end_date] = Utils.get_rate(receivable_turnover_rate)\n # 平均收现日数\n ave_receive_days = calculate_ave_receivable_days(data['balance_sheet'], data['income'])\n fina_indicators['平均收现日数'][end_date] = Utils.get_rate(ave_receive_days)\n # 存货周转率(次)\n inventory_turnover = calculate_inventory_turnover(data['balance_sheet'], data['income'])\n fina_indicators['存货周转率(次)'][end_date] = Utils.get_rate(inventory_turnover)\n # 平均销货日数(平均在库天数)\n ave_sale_days = calculate_ave_sale_days(data['balance_sheet'], data['income'])\n fina_indicators['平均销货日数(平均在库天数)'][end_date] = Utils.get_rate(ave_sale_days)\n # 固定资产周转率\n fixed_invest_turnover_rate = calculate_fixed_invest_turnover_rate(data['fifi'])\n fina_indicators['固定资产周转率'][end_date] = Utils.get_round(fixed_invest_turnover_rate)\n # 总资产周转率(次)\n total_assert_turnover_rate = calculate_total_assert_turnover_rate(data['fifi'])\n fina_indicators['总资产周转率'][end_date] = Utils.get_round(total_assert_turnover_rate)\n # 五大财务比率--获利能力\n # 净资产收益率RoE\n roe = calculate_roe(data['fifi'])\n fina_indicators['净资产收益率RoE'][end_date] = Utils.get_round(roe)\n # 总资产报酬率RoA\n roa = calculate_roa(data['fifi'])\n fina_indicators['总资产报酬率RoA'][end_date] = Utils.get_round(roa)\n # 销售毛利率\n roe = calculate_operating_margin(data['fifi'])\n fina_indicators['销售毛利率'][end_date] = Utils.get_round(roe)\n # 销售净利率\n roa = calculate_business_interest_rate(data['fifi'])\n fina_indicators['销售净利率'][end_date] = Utils.get_round(roa)\n # 净利率=纯益率\n net_interest_rate = calculate_net_interest_rate(data['income'])\n fina_indicators['净利率'][end_date] = Utils.get_rate(net_interest_rate)\n # 基本每股收益=每股盈余(元)\n surplus_rese_ps = calculate_eps(data['fifi'])\n fina_indicators['基本每股收益'][end_date] = Utils.get_round(surplus_rese_ps)\n # 税后净利(百万元)\n n_income = calculate_n_income(data['income'])\n fina_indicators['税后净利(百万元)'][end_date] = Utils.get_round(n_income)\n # 五大财务比率--现金流量\n # 现金流量比率\n cash_flow_rate = calculate_cash_flow_rate(data['balance_sheet'], data['cash_flow'])\n fina_indicators['现金流量比率'][end_date] = Utils.get_rate(cash_flow_rate)\n # 营业活动现金流量(百万元)\n cash_flow = calculate_cash_flow(data['cash_flow'])\n fina_indicators['营业活动现金流量(百万元)'][end_date] = Utils.get_round(cash_flow)\n # 投资活动现金流量(百万元)\n invest_cash_flow = calculate_invest_cash_flow(data['cash_flow'])\n fina_indicators['投资活动现金流量(百万元)'][end_date] = Utils.get_round(invest_cash_flow)\n # 筹资活动现金流量(百万元)\n finance_cash_flow = calculate_finance_cash_flow(data['cash_flow'])\n fina_indicators['筹资活动现金流量(百万元)'][end_date] = Utils.get_round(finance_cash_flow)\n return get_html_table_code(fina_indicators, stock_basic)\n\n\nif __name__ == '__main__':\n calculate('002087.SZ')\n"
},
{
"alpha_fraction": 0.5370051860809326,
"alphanum_fraction": 0.5869191288948059,
"avg_line_length": 20.518518447875977,
"blob_id": "21f53b95aebb836e41644437a3eeced4c84ff8b4",
"content_id": "e382ed5aff16ab9658437ab48ab688bc68e6a1c6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 625,
"license_type": "no_license",
"max_line_length": 42,
"num_lines": 27,
"path": "/common/utils.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-10 21:37\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nfrom pymongo import MongoClient\n\n\nclass Utils(object):\n @staticmethod\n def get_rate(value):\n return round(value*1000)/10.0\n\n @staticmethod\n def get_round(value):\n # 替换内置round函数,实现保留2位小数的精确四舍五入\n return round(value*10)/10.0\n\n @staticmethod\n def get_conn_fi():\n conn = MongoClient(\"localhost\")\n db = conn.stock\n set1 = db.fi\n # set1.remove(None)\n return set1\n"
},
{
"alpha_fraction": 0.555113673210144,
"alphanum_fraction": 0.5684691667556763,
"avg_line_length": 45.79722213745117,
"blob_id": "8174b357c02bea702b214a9cb472a43362e859ad",
"content_id": "4b0e2f4c47b2e85df6fdb10486cf2830e98353c0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 16939,
"license_type": "no_license",
"max_line_length": 119,
"num_lines": 360,
"path": "/data_server_interface/python3/facebook_account_server.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2018-06-05 11:08\n# @Author : huyuan@zingfront.com\n# @Software : SocialPeta\n# @description :\n\nimport sys\nimport asyncio\nimport json\n\nfrom aiohttp import web\n\nfrom facebook_account.logger import logger\nfrom facebook_account.settings import FACEBOOK_ACCOUNT_SERVER_HOST, FACEBOOK_ACCOUNT_SERVER_PORT\nfrom facebook_account.settings import BATCH_ACCOUNT_COUNT, BATCH_ACCOUNT_MAX_COUNT, HEARTBEAT_INTERVAL\nfrom facebook_account.facebook_cookies_controller import FacebookCookiesController\nfrom facebook_account.facebook_tokens_controller import FacebookTokensController\nfrom facebook_account.utils import Utils\n\nres = FacebookCookiesController.init_cookies()\nif res != 0:\n logger.info('初始化FacebookCookieController出错')\n sys.exit(1)\n\nres = FacebookTokensController.init_tokens()\nif res != 0:\n logger.info('初始化FacebookTokensController出错')\n sys.exit(1)\n\n\ndef _heartbeat(loop, interval):\n try:\n date_string = Utils.get_today_string()\n # 更新cookies\n if date_string != FacebookCookiesController.flag_date:\n logger.info('FacebookCookiesController更新flag_date字段：%s > %s' %\n (FacebookCookiesController.flag_date, date_string))\n FacebookCookiesController.flag_date = date_string\n FacebookCookiesController.reset_status_daily()\n count = FacebookCookiesController.get_all_cookies_use_count()\n logger.info('>>>>> ['+FacebookCookiesController.flag_date+'] all_cookies_use_count: '+str(count))\n count = FacebookCookiesController.get_audience_cookie_count()\n logger.info('>>>>> ['+FacebookCookiesController.flag_date+'] audience_cookie_count: '+str(count))\n # 更新tokens\n if date_string != FacebookTokensController.flag_date:\n logger.info('FacebookTokensController更新flag_date字段：%s > %s' %\n (FacebookTokensController.flag_date, date_string))\n FacebookTokensController.flag_date = date_string\n FacebookTokensController.reset_status_daily()\n count = FacebookTokensController.get_all_tokens_use_count()\n logger.info('>>>>> ['+FacebookTokensController.flag_date+'] all_tokens_use_count: '+str(count))\n except Exception as e:\n logger.info(logger.exception(e))\n loop.call_later(interval, _heartbeat, loop, interval)\n\n\ndef start_heartbeat(loop, interval):\n _heartbeat(loop, interval)\n\n\nclass FacebookAccountHandler:\n def __init__(self):\n pass\n\n @staticmethod\n def err_msg(err_code):\n return {'error': {'code': err_code, 'message': 'None'}}\n\n @staticmethod\n def new_account_model():\n return {'status': 0, 'account_type': '', 'account_id': '', 'account_str': '',\n 'fb_dtsg_ag': '', 'admarket_id': '', 'note': ''}\n\n @staticmethod\n def new_batch_accounts_model():\n \"\"\"\n accounts:\n if cookies: [{'account_id': '', 'account_str': ''}, {'account_id': '', 'account_str': ''}, ...]\n if audience_cookies: [{'account_id': '', 'account_str': '', 'fb_dtsg_ag': '', 'admarket_id': ''}, ...]\n if tokens: [{'account_id': '', 'account_str': ''}, {'account_id': '', 'account_str': ''}, ...]\n :return:\n \"\"\"\n return {'status': 0, 'account_type': '', 'accounts': list(), 'note': ''}\n\n @staticmethod\n def new_status_model():\n return {'status': 0, 'result': '', 'note': ''}\n\n async def get_account(self, request):\n data = self.new_account_model()\n remote = request.remote\n params = self._parse_qs(request.query_string)\n params['remote'] = remote\n if not params.get('func_type'):\n data = FacebookAccountHandler.err_msg(400)\n return web.json_response(data)\n try:\n account_type = request.match_info.get('account_type', 'None')\n data['account_type'] = account_type\n arg_account_id = request.match_info.get('account_id', None)\n if arg_account_id is None:\n account_id = None\n else:\n try:\n account_id = int(arg_account_id)\n except Exception as e:\n data = self.err_msg(400)\n data['error']['message'] = 'account_id can\\'t to int, account_id='+str(arg_account_id)\n logger.info(logger.exception(e))\n return web.json_response(data)\n fb_dtsg_ag, admarket_id = '', ''\n if account_type == 'cookie':\n account_id, account_str = FacebookCookiesController.get_cookie(cookie_id=account_id, **params)\n elif account_type == 'audience_cookie':\n account_id, account_str, fb_dtsg_ag, admarket_id = \\\n FacebookCookiesController.get_audience_cookie(cookie_id=account_id, **params)\n elif account_type == 'token':\n account_id, account_str = FacebookTokensController.get_token(token_id=account_id, **params)\n else:\n data['status'] = 3\n data['note'] = data['note'] + 'account_type is wrong, account_type='+account_type\n logger.info('account_type is wrong, account_type='+account_type)\n return web.json_response(data)\n if account_str is not None:\n data['account_id'] = account_id\n data['account_str'] = account_str\n data['fb_dtsg_ag'] = fb_dtsg_ag\n data['admarket_id'] = admarket_id\n return web.json_response(data)\n else:\n data['status'] = 2\n data['note'] = 'No account, account_id='+str(arg_account_id)\n return web.json_response(data)\n except Exception as e:\n data = self.err_msg(500)\n data['error']['message'] = 'Error in server, '+str(e)\n logger.info(logger.exception(e))\n return web.json_response(data)\n\n async def get_batch_accounts(self, request):\n data = self.new_batch_accounts_model()\n remote = request.remote\n params = self._parse_qs(request.query_string)\n params['remote'] = remote\n\n if not params.get('func_type'):\n data = FacebookAccountHandler.err_msg(400)\n return web.json_response(data)\n\n try:\n account_type = request.match_info.get('account_type', 'None')\n data['account_type'] = account_type\n arg_number = request.match_info.get('number', None)\n if arg_number is None:\n number = BATCH_ACCOUNT_COUNT\n else:\n try:\n number = int(arg_number)\n except Exception as e:\n data = self.err_msg(400)\n data['error']['message'] = 'number can\\'t to int, number='+str(arg_number)\n logger.info(logger.exception(e))\n return web.json_response(data)\n if number > BATCH_ACCOUNT_MAX_COUNT:\n number = BATCH_ACCOUNT_MAX_COUNT\n data['note'] = 'The number of accounts you require exceeds '+str(BATCH_ACCOUNT_MAX_COUNT) + \\\n ', so I just give you '+str(BATCH_ACCOUNT_MAX_COUNT)+'.'\n if account_type == 'cookie':\n cookie_list = FacebookCookiesController.get_batch_cookies(number, **params)\n elif account_type == 'audience_cookie':\n cookie_list = FacebookCookiesController.get_batch_audience_cookies(number, **params)\n elif account_type == 'token':\n cookie_list = FacebookTokensController.get_batch_tokens(number, **params)\n else:\n data['status'] = 3\n data['note'] = data['note'] + 'account_type is wrong, account_type='+account_type\n logger.info('account_type is wrong, account_type='+account_type)\n return web.json_response(data)\n if len(cookie_list) == number:\n data['accounts'] = cookie_list\n data['note'] = data['note']+'Accounts length = '+str(len(cookie_list))\n return web.json_response(data)\n else:\n data['status'] = 2\n data['accounts'] = cookie_list\n data['note'] = data['note']+'Accounts length = '+str(len(cookie_list))\n return web.json_response(data)\n except Exception as e:\n data = self.err_msg(500)\n data['error']['message'] = 'Error in server, '+str(e)\n logger.info(logger.exception(e))\n return web.json_response(data)\n\n async def search_accounts(self, request):\n data = self.new_batch_accounts_model()\n remote = request.remote\n params = self._parse_qs(request.query_string)\n params['remote'] = remote\n try:\n account_type = request.match_info.get('account_type', 'None')\n data['account_type'] = account_type\n arg_start_id = request.match_info.get('start_id', None)\n arg_number = request.match_info.get('number', None)\n if arg_start_id is None:\n start_id = 0\n else:\n try:\n start_id = int(arg_start_id)\n except Exception as e:\n data = self.err_msg(400)\n data['error']['message'] = 'start_id can\\'t to int, start_id='+str(arg_start_id)\n logger.info(logger.exception(e))\n return web.json_response(data)\n if arg_number is None:\n number = BATCH_ACCOUNT_COUNT\n else:\n try:\n number = int(arg_number)\n except Exception as e:\n data = self.err_msg(400)\n data['error']['message'] = 'number can\\'t to int, number='+str(arg_number)\n logger.info(logger.exception(e))\n return web.json_response(data)\n if number > BATCH_ACCOUNT_MAX_COUNT:\n number = BATCH_ACCOUNT_MAX_COUNT\n data['note'] = 'The number of accounts you require exceeds '+str(BATCH_ACCOUNT_MAX_COUNT) + \\\n ', so I just give you '+str(BATCH_ACCOUNT_MAX_COUNT)+'.'\n if account_type == 'token':\n cookie_list = FacebookTokensController.search_tokens(start_id, number, **params)\n else:\n data['status'] = 3\n data['note'] = data['note'] + 'account_type is wrong, account_type='+account_type\n logger.info('account_type is wrong, account_type='+account_type)\n return web.json_response(data)\n data['accounts'] = cookie_list\n data['note'] = data['note']+'Accounts length = '+str(len(cookie_list))\n return web.json_response(data)\n except Exception as e:\n data = self.err_msg(500)\n data['error']['message'] = 'Error in server, +'+str(e)\n logger.info(logger.exception(e))\n return web.json_response(data)\n\n async def get_status(self, request):\n data = self.new_status_model()\n try:\n arg_account_type = request.match_info.get('account_type', '')\n arg_operation_type = request.match_info.get('operation_type', '')\n if arg_operation_type == 'count':\n if arg_account_type == 'cookie':\n count = FacebookCookiesController.get_cookie_count()\n elif arg_account_type == 'token':\n count = FacebookTokensController.get_tokens_count()\n elif arg_account_type == 'audience_cookie':\n count = FacebookCookiesController.get_audience_cookie_count()\n else:\n data['status'] = 2\n data['note'] = 'I can\\'t recognize your instructions, account_type=' + str(arg_account_type)\n return web.json_response(data)\n data['result'] = json.dumps(count)\n return web.json_response(data)\n elif arg_operation_type == 'account_use_info':\n arg_account_id = request.match_info.get('account_id', None)\n try:\n account_id = int(arg_account_id)\n except Exception as e:\n data = self.err_msg(400)\n data['error']['message'] = 'account_id can\\'t to int, account_id='+str(arg_account_id)\n logger.info(e)\n return web.json_response(data)\n if arg_account_type == 'cookie':\n count = FacebookCookiesController.get_the_cookie_use_info(account_id)\n elif arg_account_type == 'token':\n count = FacebookTokensController.get_the_token_use_info(account_id)\n else:\n data['status'] = 2\n data['note'] = 'I can\\'t recognize your instructions, account_type=' + str(arg_account_type)\n return web.json_response(data)\n data['result'] = json.dumps(count)\n return web.json_response(data)\n elif arg_operation_type == 'all':\n if arg_account_type == 'cookie':\n result = FacebookCookiesController.get_all_cookie_using_status()\n data['result'] = json.dumps(result)\n return web.json_response(data)\n elif arg_account_type == 'token':\n result = FacebookTokensController.get_all_token_using_status()\n data['result'] = json.dumps(result)\n return web.json_response(data)\n else:\n data['status'] = 2\n data['note'] = 'I can\\'t recognize your instructions, operation_type='+str(arg_operation_type)\n return web.json_response(data)\n except Exception as e:\n data = self.err_msg(500)\n data['error']['message'] = 'Error in server, '+str(e)\n logger.info(logger.exception(e))\n return web.json_response(data)\n\n def _parse_qs(self, query_string) -> dict:\n params = dict()\n if not query_string:\n return params\n try:\n for query in query_string.split('&'):\n k_v = query.split('=')\n params[k_v[0]] = k_v[1]\n return params\n except Exception as e:\n logger.error(e)\n return params\n\n\nasync def init(loop):\n app = web.Application(loop=loop)\n handler = FacebookAccountHandler()\n #\n # 获取单个cookie、token\n # http://127.0.0.1:8080/cookie/get\n # http://192.168.3.13:8080/audience_cookie/get\n app.router.add_get('/{account_type}/get', handler.get_account)\n # http://192.168.3.13:8080/cookie/id/185247\n # http://127.0.0.1:8080/audience_cookie/id/185247\n app.router.add_get('/{account_type}/id/{account_id}', handler.get_account)\n #\n # 随机批量获取cookie、token\n # http://127.0.0.1:8080/cookie/batch\n app.router.add_get('/{account_type}/batch', handler.get_batch_accounts)\n # http://127.0.0.1:8080/cookie/batch/{number}\n app.router.add_get('/{account_type}/batch/{number}', handler.get_batch_accounts)\n\n # 顺序批量获取cookie、token\n # http://127.0.0.1:8080/token/search/0\n app.router.add_get('/{account_type}/search/{start_id}', handler.search_accounts)\n # http://127.0.0.1:8080/token/search/0/10\n app.router.add_get('/{account_type}/search/{start_id}/{number}', handler.search_accounts)\n # cookie、token状态\n # http://192.168.3.13:8080/status/cookie/count\n # http://127.0.0.1:8080/status/audience_cookie/count\n app.router.add_get('/status/{account_type}/{operation_type}', handler.get_status)\n # http://127.0.0.1:8080/status/cookie/account_use_info/185247\n app.router.add_get('/status/{account_type}/{operation_type}/{account_id}', handler.get_status)\n # http://127.0.0.1:8080/status/cookie/all\n # http://127.0.0.1:8080/status/token/all\n app.router.add_get('/status/{account_type}/{operation_type}', handler.get_status)\n #\n # server = await loop.create_server(app.make_handler(), FACEBOOK_COOKIE_SERVER_HOST, FACEBOOK_COOKIE_SERVER_PORT)\n # logger.info('\\n\\tServer started at http://%s:%s...' % (FACEBOOK_COOKIE_SERVER_HOST, FACEBOOK_COOKIE_SERVER_PORT))\n # return server\n runner = web.AppRunner(app)\n await runner.setup()\n site = web.TCPSite(runner, FACEBOOK_ACCOUNT_SERVER_HOST, FACEBOOK_ACCOUNT_SERVER_PORT)\n logger.info('\\n\\tServer started at http://%s:%s...' % (FACEBOOK_ACCOUNT_SERVER_HOST, FACEBOOK_ACCOUNT_SERVER_PORT))\n await site.start()\n\nif __name__ == '__main__':\n _loop = asyncio.get_event_loop()\n _loop.run_until_complete(init(_loop))\n start_heartbeat(_loop, HEARTBEAT_INTERVAL)\n _loop.run_forever()\n"
},
{
"alpha_fraction": 0.5155555605888367,
"alphanum_fraction": 0.6222222447395325,
"avg_line_length": 16.30769157409668,
"blob_id": "a9e76659c5c2a9fc2f52027a44f14f02162f2111",
"content_id": "998d083281979a99aa850961aa3c9c3bf3fdd732",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 261,
"license_type": "no_license",
"max_line_length": 30,
"num_lines": 13,
"path": "/data_server_interface/python3/settings.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2018-06-05 15:07\n# @Author : huyuan@zingfront.com\n# @Software : SocialPeta\n# @description :\n\n# web server监听主机地址、端口号\nSERVER_HOST = '0.0.0.0'\nSERVER_PORT = '8888'\n\n\n# 心跳函数间隔时间\nHEARTBEAT_INTERVAL = 300\n"
},
{
"alpha_fraction": 0.517350971698761,
"alphanum_fraction": 0.5332450270652771,
"avg_line_length": 42.895347595214844,
"blob_id": "7bd3995ba101360da6d53829f33b8fa760e470db",
"content_id": "44e707258345d53c74e60ec9f4713c42b03bfb56",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3821,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 86,
"path": "/stock/transfer_to_mongodb.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-06-20 22:20\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nimport csv\n\nfrom common.constant import data_path\nfrom common.utils import Utils\n\n\ndata = list()\n\n\ndef transfer_to_mongodb(stock_basic, mongodb_fi):\n ts_code = stock_basic['ts_code']\n bs_file = data_path + '/balancesheet/balancesheet_20190630_%s.csv' % ts_code\n ic_file = data_path + '/income/income_20190630_%s.csv' % ts_code\n cf_file = data_path + '/cashflow/cashflow_20190630_%s.csv' % ts_code\n fi_file = data_path + '/fina_indicator/fina_indicator_20190630_%s.csv' % ts_code\n financial_statements = dict()\n with open(bs_file, newline='', encoding='UTF-8') as bsf:\n # 资产负债表\n bs_reader = csv.DictReader(bsf)\n for row in bs_reader:\n row = dict(row)\n if row['end_date'] not in financial_statements:\n financial_statements[row['end_date']] = {'balance_sheet': dict(), 'income': dict(),\n 'cash_flow': dict(), 'fifi': dict(), }\n financial_statements[row['end_date']]['balance_sheet'] = row\n with open(ic_file, newline='', encoding='UTF-8') as icf:\n # 利润表\n ic_reader = csv.DictReader(icf)\n for row in ic_reader:\n row = dict(row)\n if row['end_date'] not in financial_statements:\n financial_statements[row['end_date']] = {'balance_sheet': dict(), 'income': dict(),\n 'cash_flow': dict(), 'fifi': dict(), }\n financial_statements[row['end_date']]['income'] = row\n with open(cf_file, newline='', encoding='UTF-8') as cff:\n # 现金流量表\n cf_reader = csv.DictReader(cff)\n for row in cf_reader:\n row = dict(row)\n if row['end_date'] not in financial_statements:\n financial_statements[row['end_date']] = {'balance_sheet': dict(), 'income': dict(),\n 'cash_flow': dict(), 'fifi': dict(), }\n financial_statements[row['end_date']]['cash_flow'] = row\n with open(fi_file, newline='', encoding='UTF-8') as fif:\n # 财务指标\n fi_reader = csv.DictReader(fif)\n for row in fi_reader:\n row = dict(row)\n if row['end_date'] not in financial_statements:\n financial_statements[row['end_date']] = {'balance_sheet': dict(), 'income': dict(),\n 'cash_flow': dict(), 'fifi': dict(), }\n financial_statements[row['end_date']]['fifi'] = row\n # print({'_id': ts_code, 'financial_statements': financial_statements})\n # data.append({'_id': ts_code, 'financial_statements': financial_statements, 'stock_basic': stock_basic})\n mongodb_fi.insert({'_id': ts_code, 'financial_statements': financial_statements, 'stock_basic': stock_basic})\n\n\ndef run():\n mongodb_fi = Utils.get_conn_fi()\n date_str = '20190608'\n file = data_path + '/stock_basic/all_stock_list_' + date_str + '.csv'\n count = 0\n with open(file, newline='', encoding='UTF-8') as cf:\n reader = csv.DictReader(cf)\n for row in reader:\n count += 1\n try:\n transfer_to_mongodb(row, mongodb_fi)\n print(str(count)+'\\t', row['ts_code'], row['fullname'], '\\t\\t\\t\\t\\t\\t成功')\n except Exception as e:\n print(e)\n print(str(count)+'\\t', row['ts_code'], '\\t\\t失败')\n with open(data_path + '/err_log/err_income_' + date_str + '.log', 'a') as f:\n f.write(row['ts_code']+'\\n')\n # mongodb_fi.insert(data)\n\n\nif __name__ == '__main__':\n run()\n"
},
{
"alpha_fraction": 0.5832061171531677,
"alphanum_fraction": 0.6061068773269653,
"avg_line_length": 26.33333396911621,
"blob_id": "e9acc487b6ae38915b5ce10aa1b3afbb655971eb",
"content_id": "32174c45af560ffd2cf8fe61d22978787d183c21",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 655,
"license_type": "no_license",
"max_line_length": 89,
"num_lines": 24,
"path": "/data_server_interface/python3/server_mongo.sh",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env bash\n\ncd /home/ubuntu/myprogram/mondodb/mongodb\nexport PATH=/home/ubuntu/myprogram/mondodb/mongodb/bin:$PATH\n\nlog_file_path=/home/ubuntu/myproject/stock/data_server_interface/python3/server_mongo.log\n\nif [ -f ${log_file_path} ];then\n echo \"file ${log_file_path} exists\"\n count=`du -s ${log_file_path}|awk '{print $1}'`\n if [ $((count)) -gt 1000 ];then\n echo \">>>>>>>>>>>> gt 1000\"\n echo ''>${log_file_path}\n else\n echo \">>>>>>>>>>>> lt 1000\"\n fi\nelse\n echo \"file ${log_file_path} not exists\"\nfi\n\nnum=`ps -ef|grep \"mongod\"|grep -v grep|wc -l`\nif [ ${num} -lt 1 ]; then\n mongod --dbpath data/db/ &\nfi"
},
{
"alpha_fraction": 0.5972350239753723,
"alphanum_fraction": 0.617511510848999,
"avg_line_length": 31.878787994384766,
"blob_id": "7a4c57054c16643a717ff2fffef405df42b7fa27",
"content_id": "bc09bc5e2d219db25d1349ff4b9ac74e403d96b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1099,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 33,
"path": "/data_server_interface/python3/controller.py",
"repo_name": "QuixoteHY/stock",
"src_encoding": "UTF-8",
"text": "# -*- coding:utf-8 -*-\n# @Time : 2019-08-18 16:24\n# @Author : 胡远\n# @Github : https://github.com/QuixoteHY\n# @Email : 1290482442@qq.com\n# @Describe :\n\nimport os\nimport csv\n\nfrom common.constant import data_path\nfrom common.calculate_financial_indicators import calculate\n\n\nclass Controller(object):\n def __init__(self):\n self.balance_sheet_data_path_model = data_path + '/balancesheet/balancesheet_20190630_%s.csv'\n\n def get_balance_sheet(self, ts_code):\n # 资产负债表\n with open(self.balance_sheet_data_path_model % ts_code, newline='', encoding='UTF-8') as bsf:\n bs_reader = csv.DictReader(bsf)\n for row in bs_reader:\n pass\n\n def get_fina_indicators(self, ts_code):\n _ts_code = ts_code+'.SZ'\n if os.path.exists(self.balance_sheet_data_path_model % _ts_code):\n return calculate(_ts_code)\n _ts_code = ts_code+'.SH'\n if os.path.exists(self.balance_sheet_data_path_model % _ts_code):\n return calculate(_ts_code)\n return 'The ts_code no data, or error in your ts_code'\n"
}
] | 20
|
jaschau/21datalab
|
https://github.com/jaschau/21datalab
|
2a9801726c98a062b68d5e19f47fd3c723aa4d14
|
5f9ad831273197f4fffc35b3d55a311d24a54307
|
3b2f99c25d0c62fd1365568df878c95edfe8cdaf
|
refs/heads/master
| 2022-03-10T22:41:55.794559
| 2020-10-08T22:18:54
| 2020-10-08T22:18:54
| 183,153,979
| 0
| 0
|
MIT
| 2019-04-24T05:24:53
| 2019-04-23T17:13:43
| 2019-04-23T17:13:42
| null |
[
{
"alpha_fraction": 0.549739420413971,
"alphanum_fraction": 0.5517241358757019,
"avg_line_length": 31.404361724853516,
"blob_id": "24b1e92e14226b64748653d79da4cface36e0b54",
"content_id": "c5bd8dcddf4e01d46965619e13792e1ece7f1574",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 57942,
"license_type": "permissive",
"max_line_length": 185,
"num_lines": 1788,
"path": "/web/js/index.js",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "var crtModelName = undefined;\n\nvar nodesMoving = {}; //here we store information from the tree plugin about the move, we grab in in the dnd_stop event and execute the move\nvar nodesMovingFromUpdate = false;\n\nvar eventSource = 0;\n\n\nfunction populate_settings() {\n // Try to retrieve the current setting from the local storage\n let data = localStorage.getItem(\"21dataSettings\");\n\n if (data != undefined) {\n try {\n // Try to deserialize the settings into an object\n let crtSettings = JSON.parse(data);\n\n // Set the appropriate parameters based on the configuration\n $('#themeSelect').val(crtSettings.theme);\n }\n catch {\n\n }\n }\n}\n\n\n\nfunction drop_nodes(nodeIds,path)\n{\n let query={\"nodes\":nodeIds,\"path\":path};\n http_post(\"/dropnodes\",JSON.stringify(query),null,null);\n}\n\n\nfunction populate_ui()\n{\n var divs = $(\"div[id^='ui-layout']\"); // all divs starting with \"ui-layout\"\n\n //for (var div of divs)\n //for (var index in divs)\n //for(const [index, div] of divs.entries())\n for (var index = 0; index < divs.length; index++)\n {\n\n var div = divs[index];\n let divTag = $(\"#\"+div.id)\n var path = JSON.parse(divTag.attr('uiinfo'))['path'];\n var isLast = (index == (divs.length-1));\n\n http_post(\"_getlayout\",JSON.stringify({\"layoutNode\":path}),div.id, isLast,function(isLast,status,data,params) {\n var id = params;\n if (status==200)\n {\n $('#'+id).html(data);\n }\n else\n {\n if (id.includes(\"workbench\"))\n {\n console.log(\"get layout failed, we take a tree as default fallback\")\n $('#'+id).html('<div id=\"ui-tree-'+id+'\">(loading of '+id+' failed, we provide the tree to fix things:)</div');\n }\n }\n //the trees\n var treeDivs = $(\"#\"+id+\" div[id^='ui-tree']\");\n for (var treeDiv of treeDivs)\n {\n var settings={};//check if there are local settings in the ui\n try\n {\n settings = JSON.parse($(\"#\"+treeDiv.id).attr('uiinfo'))['settings'];\n }\n catch{}\n var tree = new TreeCard(treeDiv.id,settings);\n }\n\n // the widgets\n var widgetDivs = $(\"#\"+id+\" div[id^='ui-component']\");\n for (var widgetDiv of widgetDivs)\n {\n var widgetAvatar = JSON.parse(widgetDiv.attributes.uiinfo.value).droppath;\n\n console.log(\"need a context menu for \",widgetDiv.id, \"=> \", widgetAvatar);\n hook_context_menu(widgetDiv.id,widgetAvatar);\n }\n\n //if (isLast) populate_ui_complete();\n\n });\n }\n\n //load the meter page\n var meter = $(\"#nav-meter\");\n if (meter.length>0)\n {\n var data=http_get(\"customui/meter.htm\");\n\n meter.empty();\n meter.html(data);\n meter_init();\n //var green = $(\"#traffic-lights-green\");\n //green.attr(\"fill\",\"#7CFC00\");\n }\n\n}\n\nfunction populate_file_list() {\n // Delete all files from the list\n $(\".filenameRow\").remove();\n\n // Get the list of files\n let data = http_get('/_upload');\n let files = []\n\n try {\n files = JSON.parse(data);\n }\n catch(err) {\n return;\n }\n\n for (let f of files) {\n $(`<div class=\"row filenameRow\"><div class=\"col\">` + f.name + `</div></div>`).insertBefore('#fileuploadRow');\n }\n}\n\nfunction initialize_upload() {\n // Get the files\n populate_file_list();\n\n // Initialize the file upload\n $('#fileupload').fileupload({\n dataType: 'text',\n add: function (e, data) {\n $('#fileuploadCol').append(`<button id=\"uploadButton\" class=\"btn btn-primary\" style=\"display: none\">Upload</button>`);\n $('#uploadButton').click(function() {\n data.submit();\n $('#uploadStatusRow').fadeIn();\n $('#uploadStatusProgress').text(\"Progress: 0%\");\n });\n $('#uploadButton').fadeIn();\n },\n done: function (e, data) {\n populate_file_list();\n\n console.log(\"successfully uploaded.\");\n\n $('#uploadStatusProgress').text(\"Successfully uploaded!\");\n },\n fail: function(e, data) {\n populate_file_list();\n\n console.log('failed uploading.');\n\n $('#uploadStatusProgress').text(\"Failed uploading!\");\n },\n always: function(e, data) {\n $('#uploadButton').fadeOut(() => {\n $('#uploadButton').remove();\n });\n\n window.setTimeout(() => {\n $('#uploadStatusRow').fadeOut();\n }, 3000);\n },\n\n progressall: function (e, data) {\n var progress = parseInt(data.loaded / data.total * 100, 10);\n\n $('#uploadStatusProgress').text(\"Progress: \" + progress + \" %\");\n }\n });\n}\n\nfunction initialize_progress_bar()\n{\n eventSource = new EventSource('/event/stream');\n\n // This callback handles messages that have no event field set, should not be used in our case\n eventSource.onmessage = (e) => {\n // Do something - event data etc will be in e.data\n console.log(\"event\",e,e.data);\n };\n\n // Handler for events of type 'system.progress' only\n eventSource.addEventListener('system.progress', (e) => {\n // Do something - event data will be in e.data,\n // message will be of type 'eventType'\n\n let data = e.data;\n //replace potential single quotes\n data = data.replace(/\\'/g, \"\\\"\");\n var valeur=JSON.parse(data).value;\n if (valeur <= 0)\n {\n\n $('.progress-bar').text(\"\");\n $('.progress-bar').css('width', valeur+'%').attr('aria-valuenow', 0);\n }\n\n else\n {\n valeur = valeur*100;\n console.log(\"EVENT system.progress\" + valeur );\n $('.progress-bar').css('width', valeur+'%').attr('aria-valuenow', valeur);\n if (valeur != 100)\n {\n $('.progress-bar').text(JSON.parse(data).function);\n }\n else\n {\n $('.progress-bar').text(\"\");\n }\n }\n });\n\n eventSource.addEventListener('system.status', (e) => {\n // Do something - event data will be in e.data,\n // message will be of type 'eventType'\n\n let data = e.data;\n //replace potential single quotes\n data = data.replace(/\\'/g, \"\\\"\");\n var parsed = JSON.parse(data);\n console.log(\"EVENT system-status\" + parsed.text );\n $('div[status-text=\"1\"]').text(parsed.text);\n });\n\n}\n\nfunction on_first_load () {\n\n\n\t//register menue calls#\n //$('.selectpicker').selectpicker();\n\n //populate_model_card_header();\n\n\t//tree_initialize();\n\n populate_settings();\n\n $('#applySettings').click(() => {\n let theme = $('#themeSelect').val();\n\n // Store all the settings into the local storage\n localStorage.setItem(\"21dataSettings\", JSON.stringify({\n \"theme\": theme\n }));\n\n // Store the theme settings also separately, this shall be read at the beginning to set the proper theme.\n localStorage.setItem(\"21datalabTheme\", theme);\n\n // Finally reload the page, which will trigger the theme change\n location.reload();\n });\n\n populate_ui();\n\n\n //myTree.tree_initialize();\n\n // This callback function is called when a node is dragged around, and moving\n $(document).on('dnd_move.vakata', function (e, data) {\n var t = $(data.event.target);\n let moveAllowed = false\n\n // First check if the node is moved inside the tree or outside\n if (!t.closest('.jstree').length) {\n // Node is moved outside the tree\n\n let nodes = data.data.nodes;\n // Some additional logic may be added here to determine whether the node can be moved or not,\n // some node types might support movig, drag and dropping, while others not\n\n // Check if the node is moved inside an item which supports dropping of nodes\n if (t.closest('.dropnodes').length) {\n // Node is moved over an allowed element which supports dropping of nodes\n moveAllowed = true;\n }\n else {\n moveAllowed = false;\n }\n }\n else {\n // Node is moved inside the tree, this shall be handled in the check_callback function of the tree,\n // because it provides more information about the drag and drop action\n moveAllowed = true;\n }\n\n if (moveAllowed) {\n // move allowed, remove the error icon and add the ok icon\n data.helper.find('.jstree-icon').removeClass('jstree-er').addClass('jstree-ok');\n }\n else {\n // move not allowed, remove the ok icon and add the error icon\n data.helper.find('.jstree-icon').removeClass('jstree-ok').addClass('jstree-er');\n }\n })\n\n $(document).on('dnd_start.vakata', function (e, data) {\n console.log(\"dnd_start.vakata\");\n nodesMoving = {\"vakata\":\"started\"};\n });\n\n $(document).on('dnd_stop.vakata', function (e, data) {\n var t = $(data.event.target);\n nodesMoving.vakata = \"stopped\";\n // First check if the node is dropped inside the tree or outside\n if (!t.closest('.jstree').length) {\n // Node is moved outside the tree\n\n // Some additional logic may be added here to determine whether the node can be moved or not,\n // some node types might support movig, drag and dropping, while others not\n if (t.closest('.dropnodes').length) {\n // Node is dropped on an allowed element which supports dropping of nodes\n\n let div = t.closest('.dropnodes')[0];\n let droppath = JSON.parse($(\"#\"+div.id).attr('uiinfo'))['droppath'];\n console.log(\"drop nodes outside of the tree, model path:\"+droppath);\n //alert(\"add nodes \"+String(nodes) + \"to target\"+String(info.path));\n drop_nodes(data.data.nodes,droppath);\n }\n }\n else\n {\n console.log(\"dnd_stop.vakata, moving in the tree\");\n\n /* Node is dropped inside the tree, we handle this here as\n - inside the tree, the move is already node\n - here, we can bulk-do the action\n - here, we can do it completely over the backend\n */\n\n if (!(\"newParent\" in nodesMoving))\n {\n console.log(\"we cant move without a parent\");\n return false;\n }\n\n if (nodesMoving.newParent.startsWith('j'))\n {\n console.log(\"we can't move onto referencee\");\n return false;\n }\n\n var nodesToMove = [];\n\n for (let nodeId of data.data.nodes)\n {\n\n if (nodeId.startsWith('j'))\n {\n //if node to be moved or the target is a referencee node, we can't\n console.log(\"can't move referencees, we skip this\",nodeId);\n }\n else\n {\n nodesToMove.push(nodeId);\n }\n }\n var query={\"nodes\":nodesToMove,\"parent\":nodesMoving.newParent};\n http_post(\"/move\",JSON.stringify(query),null,null);//,tree_update);\n }\n });\n\n initialize_upload();\n\n // right mouse click\n /*\n\tdocument.querySelector('#ui-layout-workbench').addEventListener('contextmenu', function(e) {\n\t\tshowContextMenu();\n\t e.preventDefault();\n\t});\n\t*/\n\n initialize_progress_bar();\n initialize_context_menu();\n initialize_alarms();\n\n} //on_first_load;\n\n\nfunction initialize_context_menu()\n{\n // make the modals needed\n var modal = document.createElement('div');\n modal.id = \"annotationedit\";\n modal.className = \"modal fade\";\n modal.setAttribute(\"tabindex\",\"-1\");\n modal.setAttribute(\"role\",\"dialog\");\n modal.setAttribute(\"aria-labelledby\",\"myModalLabel\");\n\n var modalCode = `\n <div class=\"modal-dialog\" role=\"document\">\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <h4 class=\"modal-title\" id=\"annotationedittitle\">Edit Selection</h4>\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\" aria-label=\"Close\"><span aria-hidden=\"true\">×</span></button>\n </div>\n\n <div class=\"modal-body\" id =\"annotationeditbody\">\n <div class=\"form-group row\">\n <div class=\"col-10\" id=\"annotationeditnodepath\">browsepath</div>\n </div>\n\n <div class=\"form-group row\" id=\"annotationeditmin\">\n <label class=\"col-3\">min</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationeditminval\" class=\"form-control edit-modal-input\" value=\"val\">\n </div>\n </div>\n <div class=\"form-group row\" id=\"annotationeditmax\">\n <label class=\"col-3\">max</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationeditmaxval\" class=\"form-control edit-modal-input\" value=\"val\">\n </div>\n </div>\n <div class=\"form-group row\" id=\"annotationeditstart\" hidden>\n <label class=\"col-3\">start</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationeditstartval\" class=\"form-control edit-modal-input\" value=\"start\">\n </div>\n </div>\n <div class=\"form-group row\" id=\"annotationeditend\" hidden>\n <label class=\"col-3\">end</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationeditendval\" class=\"form-control edit-modal-input\" value=\"start\">\n </div>\n </div>\n <div class=\"form-group row\" id=\"annotationedittags\" hidden>\n <label class=\"col-3\">tags</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationedittagsval\" class=\"form-control edit-modal-input\" value=\"start\">\n\n </div>\n </div>\n\n <div class=\"form-group row\" id=\"annotationedittagsselect\" hidden>\n <label class=\"col-3\">select tags</label>\n <div class=\"col-9\">\n <select class=\"selectpicker\" id=\"annotationeditselect\" multiple>\n </select>\n <br><br>\n </div>\n </div>\n\n\n\n\n <div class=\"form-group row\" id=\"annotationeditvariables\" hidden>\n <label class=\"col-3\">variables</label>\n <div class=\"col-9\">\n <input type=\"text\" id=\"annotationeditvariablesval\" class=\"form-control edit-modal-input\" value=\"start\">\n </div>\n </div>\n\n\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n <button type=\"button\" class=\"btn btn-primary\" data-dismiss=\"modal\" id =\"annotationeditButtonSave\">Save changes</button>\n </div>\n </div>\n </div>`;\n modal.innerHTML = modalCode;\n\n var targetDiv = $(\"#contextmenu\");\n targetDiv.append(modal);\n var saveButton=$(\"#annotationeditButtonSave\");\n saveButton.click(function(){\n //write the stuff back to the model\n console.log(\"edit ok\");\n //go over the non-hidden fields and take them\n var query = [];\n var nodePath = $('#annotationeditnodepath').text();\n var fields = {\"min\":\"min\",\"max\":\"max\",\"start\":\"startTime\",\"end\":\"endTime\",\"variables\":\"variables\",\"tags\":\"tags\"};\n for (let field in fields)\n {\n let hidden = $(\"#annotationedit\"+field).attr(\"hidden\");\n if (!hidden)\n {\n var value = JSON.parse($('#annotationedit'+field+\"val\").val());\n console.log(\"we have \"+field+value);\n var subQuery = {\"browsePath\":nodePath+\".\"+fields[field],\"value\":value}\n query.push(subQuery);\n }\n\n\n }\n console.log(\"query out\",query);\n http_post(\"/setProperties\",JSON.stringify(query),null,null,null);\n\n\n\n });\n}\n\n\n\n\n\nfunction showContextMenu (){\n console.log(\"here context menu\");\n}\n\n\n/*\nfunction populate_ui_complete(){\n\n console.log(\"populate_ui_complete, this should be called only once at the very end!\");\n var elem = $('#ui-component-workbench');\n\telem.on('contextmenu', function(e) {\n\n\t \n e.preventDefault();\n //var menu = prepare_context_menu(e);\n console.log(\"context\");\n show_context_menu(e);\n //superCm.createMenu(menu, e);\n //return false;\n });\n}\n*/\n\nfunction hook_context_menu(divId,modelPath)\n{\n console.log(\"hook_context_menu()\",divId,\" \",modelPath);\n var elem = $(\"#\"+divId);\n elem.on('contextmenu', function(e) {\n e.preventDefault();\n console.log(\"context\");\n show_context_menu(e,modelPath);\n });\n}\n\nfunction show_context_menu(e,modelPath)\n{\n console.log(\"show_context_menu() \",modelPath);\n var query = {\"node\":modelPath,\"depth\":100,\"ignore\":[\"observer\",\"hasAnnotation.anno\",\"hasAnnotation.new\"]}\n //get the current state from the backend\n http_post(\"_getbranchpretty\",JSON.stringify(query), e,null, function(obj,status,data,params)\n {\n if (status==200)\n {\n\n console.log(\"in show_context_menu(), back from http\");\n\n var menu = prepare_context_menu(data,modelPath);\n superCm.createMenu(menu,params);\n superCm.maxHeight = 1000;\n }\n }\n );\n\n}\n\n//path: the pointer to the widget.selected\nfunction get_variables(data)//selectableVariablesRoot,selectedIds)\n{\n\n var selectableVariablesRoot = data.selectableVariables[\".properties\"].forwardRefs[0];\n var selectedIds = data.selectedVariables[\".properties\"].leavesIds;\n var selectedVariablesId = data.selectedVariables[\".properties\"].id;\n\n var path = selectableVariablesRoot;\n var query = {\"node\":path,\"depth\":100,\"ignore\":[]};\n data = http_post_sync( \"_getbranchpretty\", true, query );\n var vars = JSON.parse(data.response);\n var menu = recursive_search(vars,selectedIds,selectedVariablesId);\n console.log(\"ready\");\n return menu;\n}\n\nfunction recursive_search(data,selectedIds,selectedVariablesId)\n{\n var menu = [];\n for(var key in data)\n {\n if (key == \".properties\") continue;\n\n var entry = data[key];\n\n if (entry[\".properties\"].type == \"folder\")\n {\n console.log(\"look deeper in \"+entry[\".properties\"].name);\n var submenu;\n submenu = recursive_search(entry,selectedIds,selectedVariablesId);\n var menuentry = {\n label:\"<i>\"+entry[\".properties\"].name+\"</i>\",\n submenu:submenu\n };\n menu.push(menuentry);\n\n }\n else if (entry[\".properties\"].type == \"timeseries\")\n {\n console.log(\"show\"+entry[\".properties\"].name);\n\n let icon = \"far fa-square\";\n if (selectedIds.includes(entry[\".properties\"].id)) icon = \"far fa-check-square\";\n var menuentry = {\n label:\"<i>\"+entry[\".properties\"].name+\"</i>\",\n icon:icon,\n nodeId:entry[\".properties\"].id,\n selectedVariablesId: selectedVariablesId,\n isVariable:true,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex;\n var optIdx = optionIndex;\n context_menu_variable_select_click(opt,idx,optIdx);\n }\n\n\n };\n menu.push(menuentry);\n }\n }\n return menu;\n}\n\n\n\nfunction context_menu_click_show(option,contextMenuIndex, optionIndex)\n{\n let element = option.element;\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n var data = option.data;\n data[element]=option.currentValue;\n\n console.log(\"switch show\",data);\n context_menu_set_visible_elements(option.path,data);\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n\n}\n\nfunction update_context_menu(index)\n{\n superCm.settings.maxHeight = \"100vh\" //hack to avoid the resizing\n //superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n superCm.updateMenuIndex(false,false,index);\n}\n\n\nfunction context_menu_set_visible_elements(modelPath,data)\n{\n var query = [{browsePath:modelPath+\".visibleElements\",value:data}];\n\n http_post('/setProperties',JSON.stringify(query), null, this, (self,status,data,params) => {\n if (status>201)\n {\n //backend responded bad, we must set the frontend back\n\n console.log(\"context_menu_set_visible_elements\",status);\n }\n else\n {\n console.log(\"context_menu_set_visible_elements ok\");\n\n }\n });\n\n\n}\n\nfunction context_menu_click_delete(option)\n{\n console.log(\"context_menu_click_delete \"+option.label+\" data\" + option.data);\n $('#doublecheck').modal(\"show\");\n $('#doublechecktext1').text(\"Deleting Annotation\");\n $('#doublechecktext2').text(option.data);\n var saveButton=$(\"#doublecheckButtonSave\");\n saveButton.click(function(){\n http_post(\"/_delete\",JSON.stringify(option.data),null,null,null);\n });\n superCm.destroyMenu(); // hide it\n}\n\nfunction context_menu_click_test(option, contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_click_test\");\n var option = {\n\n icon: 'fas fa-cog',\n label : \"settingsss\",\n action: function(option, contextMenuIndex, optionIndex){ var opt = option; var idx = contextMenuIndex; var optIdx = optionIndex;\n context_menu_click_test(opt,idx,optIdx);\n }\n\n };\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu();\n\n}\n\nfunction context_menu_tag_select_click(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_tag_select_click\",option);\n //make the true/false check box adjustment\n\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n option.data[option.entry]=option.currentValue;\n var query = [{browsePath:option.modelPath+\".hasAnnotation.visibleTags\",value:option.data}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n\nfunction context_menu_tag_select_click_event(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_tag_select_click\",option);\n //make the true/false check box adjustment\n\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n option.data[option.entry]=option.currentValue;\n var query = [{browsePath:option.modelPath+\".hasEvents.visibleEvents\",value:option.data}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n\n\nfunction context_menu_variable_select_click(option,contextMenuIndex, optionIndex)\n{\n\n console.log(\"context_menu_variable_select_click\",option);\n if (option.icon == \"far fa-check-square\")\n {\n option.icon = \"far fa-square\";\n var query = {parent:option.selectedVariablesId,remove:[option.nodeId]}\n }\n else\n {\n option.icon = \"far fa-check-square\";\n var query = {parent:option.selectedVariablesId,add:[option.nodeId]}\n //todo also remove potential score, expected etc.\n }\n http_post(\"/_references\",JSON.stringify(query),null,null,null);\n\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n //var index = 3;\n update_context_menu(contextMenuIndex); // we only update a single index here\n //superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n}\n\n\nfunction context_menu_variables_deselect_all(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_variables_deselect_all\");\n var query = {parent:option.selectedVariablesId,deleteExisting:true}\n http_post(\"/_references\",JSON.stringify(query),null,null,null);\n\n var options = superCm.getMenuOptions(contextMenuIndex);\n //iterate through all options and children, look for \"selectedVariablesId\" in the option, if it is there,\n // then it is a variable entry, and we set the icon to unselected\n var newOptions = deselect_variables(options);\n console.log(\"done\")\n superCm.setMenuOptions(contextMenuIndex,newOptions)\n}\n\nfunction deselect_variables(OptionList)\n{\n for (var option of OptionList)\n {\n if (option.hasOwnProperty(\"isVariable\"))\n {\n option.icon = \"far fa-square\"; // deselected\n }\n if (option.hasOwnProperty(\"submenu\"))\n {\n option.submenu=deselect_variables(option.submenu)\n }\n }\n return OptionList;\n}\n\n\nfunction context_menu_tag_select_click_all(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_tag_select_click all\",option);\n //make the true/false check box adjustment\n\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n //now set them all\n for(key in option.data)\n {\n option.data[key]=option.currentValue;\n }\n\n var query = [{browsePath:option.modelPath+\".hasAnnotation.visibleTags\",value:option.data}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n\n // now we also need to set all checkboxes accordingly\n // for all options: set current value and set icon\n\n allOptions = superCm.getMenuOptions(contextMenuIndex)\n for (key in allOptions)\n {\n let thisOption = allOptions[key];\n thisOption.currentValue = option.currentValue;\n thisOption.icon = option.icon;\n superCm.setMenuOption(contextMenuIndex, key, thisOption);\n }\n\n\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n\n\nfunction context_menu_tag_select_click_all_events(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_tag_select_click_all_events\",option);\n //make the true/false check box adjustment\n\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n //now set them all\n for(key in option.data)\n {\n option.data[key]=option.currentValue;\n }\n\n var query = [{browsePath:option.modelPath+\".hasEvents.visibleEvents\",value:option.data}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n\n // now we also need to set all checkboxes accordingly\n // for all options: set current value and set icon\n\n allOptions = superCm.getMenuOptions(contextMenuIndex)\n for (key in allOptions)\n {\n let thisOption = allOptions[key];\n thisOption.currentValue = option.currentValue;\n thisOption.icon = option.icon;\n superCm.setMenuOption(contextMenuIndex, key, thisOption);\n }\n\n\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n\n\n/*\nfunction context_menu_variable_select_click(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_variable_select_click\",option);\n //make the true/false check box adjustment\n\n var query = {parent:option.modelPath+\".selectedVariables\"};\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n //remove this one\n query.remove = [option.varPath];\n //also hide a potential score renderer\n let matchingString = option.name+\"_score\"\n for (let variablePath of option.selectedVariables)\n {\n if (variablePath.endsWith(matchingString))\n {\n query.remove.push(variablePath);\n }\n }\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n // add this one\n query.add = [option.varPath];\n }\n http_post(\"/_references\",JSON.stringify(query),null,null,null);\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n*/\n\nfunction context_menu_click_function(option)\n{\n console.log(\"context_menu_click_function, execute \" + option.data);\n http_post(\"/_execute\",JSON.stringify(option.data),null,null,null);\n superCm.destroyMenu(); // hide it\n}\n\nfunction context_menu_click_pipeline(option)\n{\n console.log(\"context_menu_click_pipeline, launch \" + option.data+\" from widget \"+option.widget);\n //show the cockpit\n var query = [option.data+\".cockpit\"];\n\n http_post(\"_getvalue\",JSON.stringify(query), option,null, function(obj,status,data,params)\n {\n if (status == 200)\n {\n var widget = option.widget;\n let path = params.data;\n console.log(\"data\");\n var cockpit = JSON.parse(data)[0];\n launch_cockpit(cockpit,path,widget);\n }\n });\n superCm.destroyMenu(); // hide it\n}\n\n\n\nfunction context_menu_new_annotation_click(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context menue new annotation\",option.setValue);\n var query = [{browsePath:option.modelPath+\".nextNewAnnotation\",value:option.setValue}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n superCm.destroyMenu();\n}\n\nfunction context_menu_bool_settings_click(option,contextMenuIndex, optionIndex)\n{\n console.log(\"context_menu_tag_select_click\",option);\n //make the true/false check box adjustment\n\n if (option.currentValue == true)\n {\n option.currentValue = false;\n option.icon = \"far fa-square\";\n }\n else\n {\n option.currentValue = true;\n option.icon = \"far fa-check-square\";\n }\n\n option.data[option.entry]=option.currentValue;\n var query = [{browsePath:option.nodePath,value:option.currentValue}];\n http_post('/setProperties',JSON.stringify(query), null, this, null);\n\n superCm.setMenuOption(contextMenuIndex, optionIndex, option);\n superCm.updateMenu(allowHorzReposition = false, allowVertReposition = false);\n\n}\n\nfunction context_menu_edit(option,contextMenuIndex,optionIndex)\n{\n //console.log(\"edit\"+option.data);\n //$('#annotationedit').modal('show');\n\n var option = option;\n superCm.destroyMenu();\n // get the children of the annotation\n http_post('/_getbranchpretty',option.data, null, this, (self,status,data,params) => {\n if (status>201)\n {\n //backend responded bad, we must set the frontend back\n\n console.log(\"context_menu_edit\",status);\n }\n else\n {\n console.log(\"context_menu_edit ok\");\n //take the data\n modal = $('#annotationedit');//.modal('show');\n\n var data = JSON.parse(data);\n var fields=[];\n if ((data.type['.properties'].value == \"time\") || (data.type['.properties'].value==\"motif\"))\n {\n //time annotations\n $('#annotationedittitle').text(\"Edit Annotation\")\n $('#annotationeditnodepath').text(option.data);\n\n $('#annotationeditmin').attr(\"hidden\",true);\n $('#annotationeditmax').attr(\"hidden\",true);\n $('#annotationeditstart').attr(\"hidden\",false);\n $('#annotationeditend').attr(\"hidden\",false);\n $('#annotationedittags').attr(\"hidden\",false);\n $('#annotationedittagsselect').attr(\"hidden\",false);\n\n\n $('#annotationeditstartval').val(JSON.stringify(data.startTime[\".properties\"].value));\n $('#annotationeditendval').val(JSON.stringify(data.endTime[\".properties\"].value));\n $('#annotationedittagsval').val(JSON.stringify(data.tags[\".properties\"].value));\n }\n else if (data.type['.properties'].value == \"threshold\")\n {\n $('#annotationedittitle').text(\"Edit Threshold\");\n $('#annotationeditnodepath').text(option.data);\n\n $('#annotationeditmin').attr(\"hidden\",false);\n $('#annotationeditmax').attr(\"hidden\",false);\n $('#annotationeditstart').attr(\"hidden\",true);\n $('#annotationeditend').attr(\"hidden\",true);\n $('#annotationedittags').attr(\"hidden\",false);\n $('#annotationedittagsselect').attr(\"hidden\",false);\n\n $('#annotationeditminval').val(JSON.stringify(data.min[\".properties\"].value));\n $('#annotationeditmaxval').val(JSON.stringify(data.max[\".properties\"].value));\n $('#annotationedittagsval').val(JSON.stringify(data.tags[\".properties\"].value));\n }\n else\n {\n console.log(\"unsupported tag type\");\n return;\n }\n\n\n //currently all support the tags\n\n var currentTags = data.tags[\".properties\"].value;\n $('#annotationeditselect').empty();\n $('#annotationeditselect').on('change', function(e){\n var all = [];\n for(var opt of this.options)\n {\n if (opt.selected) all.push(opt.label);\n }\n console.log(\"together\",all);\n $('#annotationedittagsval').val(JSON.stringify(all));\n });\n\n console.log(\"currenttags\",currentTags)\n for (let tag of option.tags)\n {\n if (currentTags.includes(tag))\n {\n $('#annotationeditselect').append('<option value=\"'+tag+'\" selected>'+tag+'</option>');\n }\n else\n {\n $('#annotationeditselect').append('<option>'+tag+'</option>');\n }\n\n }\n $('#annotationeditselect').selectpicker('refresh');\n\n\n modal.modal('show');\n\n\n }\n });\n\n\n\n}\n\n\nfunction prepare_context_menu(dataString,modelPath)\n{\n //data is a string json containing the widget info\n var data = JSON.parse(dataString);\n var disableDirectModification = true;\n\n try\n {\n var targets = data.hasAnnotation.selectedAnnotations[\".properties\"].leaves;\n if (targets.length != 0)\n {\n console.log(\"have selected annotation\");\n disableDirectModification = false;\n }\n }\n catch\n {\n }\n\n\n // let's create the context menue depending on the current status\n var menu= [\n\n // area direct modification, only if something is selected (annotation)\n {\n icon:\"far fa-trash-alt\",\n label:\"delete\",\n disabled : disableDirectModification,\n data: data.hasAnnotation.selectedAnnotations[\".properties\"].leaves,\n action : function(option, contextMenuIndex, optionIndex){context_menu_click_delete(option);}\n },\n {\n icon: 'fa fa-edit', //Icon for the option\n label: 'edit', //Label to be displayed for the option\n data: data.hasAnnotation.selectedAnnotations[\".properties\"].leaves,\n tags:data.hasAnnotation.tags[\".properties\"].value,\n action : function(option, contextMenuIndex, optionIndex){context_menu_edit(option,contextMenuIndex,optionIndex);},\n disabled: disableDirectModification\n },\n\n {\n separator : true\n }];\n\n\n //now comes the show/hide submenu\n /*\n let annotationsAction = \"show\";\n if (data.visibleElements[\".properties\"].value.annotations == true) annotationsAction = \"hide\";\n let backgroundAction = \"show\";\n if (data.visibleElements[\".properties\"].value.background == true) backgroundAction = \"hide\";\n let thresholdAction = \"show\";\n if (data.visibleElements[\".properties\"].value.thresholds == true) thresholdAction = \"hide\";\n let scoresAction = \"show\";\n if (data.visibleElements[\".properties\"].value.scores == true) scoresAction = \"hide\";\n */\n\n var visibleTags = data.hasAnnotation.visibleTags[\".properties\"].value;\n var colors = data.hasAnnotation.colors[\".properties\"].value;\n\n // for switching on and off the annotation tags\n let annotationsSubmenu = [];\n\n\n //the \"all\" entry\n var entry = {\n icon:\"far fa-check-square\",\n label:\"(all)\",\n entry:\" all\",\n data:visibleTags,\n modelPath:modelPath,\n currentValue:true,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_tag_select_click_all(opt,idx,optIdx);\n }\n }\n annotationsSubmenu.push(entry);\n\n for (tag in visibleTags)\n {\n let icon = \"far fa-square\";\n if (visibleTags[tag]== true) {icon = \"far fa-check-square\";}\n let mycolor = colors[tag].color;\n let mypattern = colors[tag].pattern;\n if (mypattern == null) mypattern = \"     \";\n else mypattern = \"  \"+mypattern + \"  \";\n let mycolorString = `<span style='background-color:${mycolor};text-color:red;font-family:monospace;'> <font color='white'> ${mypattern}</font> </span> <i>   ${tag}</i>`;\n //let mycolorString = `${tag}   <span style='textcolor:red;background-color:${mycolor}'> ${mypattern} </span>`;\n\n var entry = {\n icon:icon,\n label:mycolorString,\n entry:tag,\n data:visibleTags,\n modelPath:modelPath,\n currentValue:visibleTags[tag],\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_tag_select_click(opt,idx,optIdx);\n }\n }\n\n annotationsSubmenu.push(entry);\n }\n\n\n\n // events submenu, only if the events are part of the model\n var hasEvents;\n var eventsSubmenu = [];\n if (data.hasOwnProperty(\"hasEvents\"))\n {\n hasEvents = true;\n visibleEvents = data.hasEvents.visibleEvents[\".properties\"].value;\n colors = data.hasEvents.colors[\".properties\"].value;\n\n //the \"all\" entry\n var entry = {\n icon:\"far fa-check-square\",\n label:\"(all)\",\n entry:\" all\",\n data:visibleEvents,\n modelPath:modelPath,\n currentValue:true,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_tag_select_click_all_events(opt,idx,optIdx);\n }\n }\n eventsSubmenu.push(entry);\n\n for (tag in visibleEvents)\n {\n let icon = \"far fa-square\";\n if (visibleEvents[tag]== true) {icon = \"far fa-check-square\";}\n let mycolor = colors[tag].color;\n let mypattern = \"     \";\n let mycolorString = `<span style='background-color:${mycolor};text-color:red;font-family:monospace;'> <font color='white'> ${mypattern}</font> </span> <i>   ${tag}</i>`;\n\n var entry = {\n icon:icon,\n label:mycolorString,\n entry:tag,\n data:visibleEvents,\n modelPath:modelPath,\n currentValue:visibleEvents[tag],\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_tag_select_click_event(opt,idx,optIdx);\n }\n }\n\n eventsSubmenu.push(entry);\n }\n }\n else\n {\n hasEvents = false;\n }\n\n\n\n\n\n //create variables submenu\n\n try\n {\n var subMenuVariables = get_variables(data);//variablesRoot,data.selectedVariables[\".properties\"].leavesIds);//modelPath+\".selectableVariables\");\n }\n catch\n {\n console.log(\"error getting variables for context menu\")\n var subMenuVariables =[];\n }\n\n var entry = {\n label:\"(deselect all)\",\n entry:\" all\",\n selectedVariablesId : data.selectedVariables[\".properties\"].id,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_variables_deselect_all(opt,idx,optIdx);\n }\n }\n var variablesSubmenu = [entry];\n variablesSubmenu=variablesSubmenu.concat(subMenuVariables);\n\n\n\n\n var showSubmenu = [];\n //let elements = [\"variables\",\"annotations\",\"background\",\"thresholds\",\"scores\",\"motifs\"];\n let elements = Object.keys( data.visibleElements[\".properties\"].value);\n var jsonValue = data.visibleElements[\".properties\"].value;\n for (let element of elements)\n {\n let icon = \"far fa-square\";\n let visible = jsonValue[element];\n if (visible == true) icon = \"far fa-check-square\";\n\n var entry = {\n icon: icon,\n label:element,\n element : element,\n path : modelPath,\n data : jsonValue,\n currentValue : visible,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_click_show(opt,idx,optIdx);\n }\n };\n if (element == \"annotations\")\n {\n entry.submenu = annotationsSubmenu;\n }\n if (element == \"variables\")\n {\n entry.submenu = variablesSubmenu;\n delete entry.icon;\n }\n if ((element == \"events\") && (hasEvents == true))\n {\n entry.submenu = eventsSubmenu;\n }\n\n showSubmenu.push(entry);\n }\n\n var selectedVariables = data.selectedVariables[\".properties\"].leaves;\n\n /*\n //another entry for the variables\n var variablesSubmenu=[];\n var selectableVariables = data.selectableVariables[\".properties\"].leaves;\n\n for (variable of selectableVariables)\n {\n let icon = \"far fa-square\";\n var currentValue = false;\n if (selectedVariables.includes(variable)) {icon = \"far fa-check-square\";currentValue =true; }\n var splitted = variable.split('.');\n var name =splitted[splitted.length-1];\n\n\n var entry = {\n icon:icon,\n label:name,\n name:name,\n currentValue : currentValue,\n varPath:variable,\n selectedVariables:selectedVariables,\n modelPath:modelPath,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_variable_select_click(opt,idx,optIdx);\n }\n\n }\n variablesSubmenu.push(entry);\n }\n var entry = {\n //icon: icon,\n label:\"variables\",\n submenu:variablesSubmenu\n };\n showSubmenu.push(entry);\n */\n\n\n\n //add the show/hide to the menu\n menu.push({\n disabled: false,\n icon: 'fas fa-eye',\n label: 'show/hide',\n submenu: showSubmenu\n });\n\n\n\n\n //the \"new\" area\n\n // new annotation submenu\n var visibleTags = data.hasAnnotation.visibleTags[\".properties\"].value;\n var colors = data.hasAnnotation.colors[\".properties\"].value;\n\n let newAnnnotationsSubmenu = [];\n for (tag in visibleTags)\n {\n let mycolor = colors[tag].color;\n let mypattern = colors[tag].pattern;\n if (mypattern == null) mypattern = \"     \";\n else mypattern = \"  \"+mypattern + \"  \";\n //let mycolorString = `${tag}   <span style='background-color:${mycolor}'> ${mypattern} </span>`;\n let mycolorString = `<span style='background-color:${mycolor};text-color:red;font-family:monospace'> <font color='white'> ${mypattern}</font> </span>   ${tag}`;\n\n var entry = {\n label:mycolorString,\n data:visibleTags,\n modelPath:modelPath,\n setValue:{type:\"time\",tag:tag},\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex;\n var optIdx = optionIndex;\n context_menu_new_annotation_click(opt,idx,optIdx);\n }\n }\n\n newAnnnotationsSubmenu.push(entry);\n }\n\n let newThresholdsSubmenu = [];\n //selected variables?\n //let selectedVariables = data.selectedVariables[\".properties\"].leaves;\n let scoreVariables = data.scoreVariables[\".properties\"].leaves;\n\n let currentColors = data.currentColors[\".properties\"].value;\n for (variable of selectedVariables)\n {\n if (scoreVariables.includes(variable))\n {\n //skip score variables\n continue;\n }\n if (variable in currentColors)\n {\n var mycolor = currentColors[variable].lineColor;\n }\n else\n {\n var mycolor = \"black\";\n }\n let mycolorString = `<span style='background-color:${mycolor};text-color:red;font-family:monospace'> <font color='white'>   -   </font> </span>   ${variable}`;\n\n var entry = {\n label:mycolorString,\n setValue:{type:\"threshold\",variable:variable},\n modelPath:modelPath,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_new_annotation_click(opt,idx,optIdx);\n }\n }\n\n newThresholdsSubmenu.push(entry);\n }\n\n\n let newMotifSubmenu = [];\n //selected variables?\n //let selectedVariables = data.selectedVariables[\".properties\"].leaves;\n //let scoreVariables = data.scoreVariables[\".properties\"].leaves;\n\n //let currentColors = data.currentColors[\".properties\"].value;\n for (variable of selectedVariables)\n {\n if (scoreVariables.includes(variable))\n {\n //skip score variables\n continue;\n }\n if (variable in currentColors)\n {\n var mycolor = currentColors[variable].lineColor;\n }\n else\n {\n var mycolor = \"black\";\n }\n let mycolorString = `<span style='background-color:${mycolor};text-color:red;font-family:monospace'> <font color='white'>   -   </font> </span>   ${variable}`;\n\n var entry = {\n label:mycolorString,\n setValue:{type:\"motif\",variable:variable},\n modelPath:modelPath,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex; var\n optIdx = optionIndex;\n context_menu_new_annotation_click(opt,idx,optIdx);\n }\n }\n\n newMotifSubmenu.push(entry);\n }\n\n\n\n\n\n\n\n var menuNew = [\n {separator :true},\n\n {\n icon: 'fa fa-plus',\n label: 'new',\n disabled: false,\n submenu: [\n {\n icon: 'far fa-bookmark',\n label:\"annotation\",\n submenu: newAnnnotationsSubmenu\n },\n {\n icon: 'fas fa-arrows-alt-v',\n label: 'threshold',\n submenu: newThresholdsSubmenu\n },\n {\n icon : 'fas fa-water',\n label : 'motif',\n submenu:newMotifSubmenu\n }\n ]\n }\n ]\n menu=menu.concat(menuNew);\n\n\n //user functions\n var menuUserFunctions =[{\n separator: true\n }];\n\n for (fkt of data.contextMenuFunctions[\".properties\"].targets)\n {\n var splitted = fkt.split(\".\");\n var entry={\n icon: 'fas fa-play-circle',\n label: '<font size=\"3\" color=\"#d9b100\">'+splitted[splitted.length -1]+'</font>',\n data: fkt,\n action: function(option, contextMenuIndex, optionIndex){context_menu_click_function(option); }\n };\n menuUserFunctions.push(entry);\n }\n if (\"contextMenuPipelines\" in data)\n {\n for (pipeline of data.contextMenuPipelines[\".properties\"].targets)\n {\n var splitted = pipeline.split(\".\");\n var entry={\n icon: 'fas fa-gamepad',\n label: '<font size=\"3\" color=\"#d9b100\">'+splitted[splitted.length -1]+'</font>',\n data: pipeline,\n widget: data[\".properties\"].id,\n action: function(option, contextMenuIndex, optionIndex){context_menu_click_pipeline(option); }\n };\n menuUserFunctions.push(entry);\n }\n }\n if (menuUserFunctions.length>1)\n {\n menu=menu.concat(menuUserFunctions);\n }\n\n\n\n\n let tailSubMenu =[];\n\n // y scale\n for (let child in data.contextMenuSettings)\n {\n //console.log(entry);\n if (child == \".properties\") continue; // ignore this entry\n var entryPath = data.contextMenuSettings[child][\".properties\"].leaves[0];\n var value = data.contextMenuSettings[child][\".properties\"].leavesValues[0];\n var validation = data.contextMenuSettings[child][\".properties\"].leavesValidation[0];\n console.log(child + \" > \" + entryPath+ \":\"+value);\n\n let icon = \"far fa-square\";\n if (value == true) icon = \"far fa-check-square\";\n\n var entry = {\n label:child,\n icon:icon,\n currentValue:value,\n nodePath:entryPath,\n data:data,\n action: function(option, contextMenuIndex, optionIndex){\n var opt = option;\n var idx = contextMenuIndex;\n var optIdx = optionIndex;\n context_menu_bool_settings_click(opt,idx,optIdx);\n }\n }\n\n tailSubMenu.push(entry);\n }\n\n\n var menuTail = [\n {\n separator: true\n },\n {\n icon: 'fas fa-cog',\n label : \"settings\",\n disabled : false,\n submenu:tailSubMenu\n\n },\n /*\n {\n icon: 'fas fa-bug',\n label : \"debug\",\n disabled : false,\n action:function(opt,idx,optIdx){\n //my_test_insert();\n\n }\n\n }\n */\n ];\n\n menu = menu.concat(menuTail);\n return menu;\n}\n\n\n\n\n\nfunction launch_cockpit(url,path,widget)\n{\n if (url!=\"\")\n {\n var data=http_get(url);\n $(\"#cockpit\").remove();\n $(\"#cockpitplaceholder\").html(data);\n }\n\n var cockpit = $('#cockpit');\n cockpit.draggable({handle: \".modal-header\"}); //make it movable\n cockpit.modal({backdrop: 'static',keyboard: false, focus:false}); //don't close it on click outside\n cockpit.prepend('<style scoped> .modal-backdrop { display: none;}</style>'); //allow click outside\n cockpit.attr(\"path\",path);\n cockpit.attr(\"widget\",widget); //set the widget for some\n cockpit_init(path);\n\n $('#cockpit').one('hidden.bs.modal', cockpit_close);\n cockpit.modal('show');\n\n}\n\n\nfunction refresh_alarm_table()\n{\n console.log(\"refresh_alarm_table \");\n var query = {\"node\":\"root.system.alarms.messages\",\"depth\":4,\"ignore\":[]}\n\n\n http_post(\"_getbranchpretty\",JSON.stringify(query), null,null, function(obj,status,data,params)\n {\n if (status==200)\n {\n var table = $('#alarmcontainer');\n table.empty();\n\n var msgs = JSON.parse(data);\n for(var msg in msgs)\n {\n if (msg[0]==\".\") continue; //skip the .properties\n\n //make a row\n var row = document.createElement(\"div\");\n row.className = \"row mb-4\";\n\n var timeDiv = document.createElement(\"div\");\n timeDiv.className = \"col-3\";\n timeDiv.innerHTML = msgs[msg].startTime[\".properties\"].value;\n\n var msgDiv = document.createElement(\"div\");\n msgDiv.className = \"col-4\";\n msgDiv.innerHTML = msgs[msg].text[\".properties\"].value;\n\n var statusDiv = document.createElement(\"div\");\n statusDiv.className = \"col\";\n if (msgs[msg].confirmed[\".properties\"].value == true)\n {\n statusDiv.innerHTML = \"confirmed\";\n }\n else\n {\n statusDiv.style.color = \"red\";\n statusDiv.innerHTML = \"unconfirmed\";\n }\n\n var levelDiv = document.createElement(\"div\");\n levelDiv.className = \"col\";\n levelDiv.innerHTML = msgs[msg].level[\".properties\"].value;\n\n var buttonDiv = document.createElement(\"div\");\n buttonDiv.className = \"col\";\n if (statusDiv.innerHTML==\"unconfirmed\")\n {\n var btn = document.createElement(\"BUTTON\"); // Create a <button> element\n btn.className = \"btn btn-secondary\";\n btn.id = \"confirmAlarm-\"+msgs[msg].confirmed[\".properties\"].id;\n btn.innerHTML = '<i class=\"fas fa-check\"></i>';\n btn.onclick = confirmAlarm;\n buttonDiv.append(btn);\n }\n\n\n row.append(timeDiv,msgDiv,statusDiv,levelDiv,buttonDiv);\n //row.appendChild(msgDiv);\n table.append(row);\n }\n }\n }\n );\n\n\n}\n\nfunction confirmAlarm()\n{\n var id=$(this).attr('id');\n console.log(\"the node id is \",id.substr(13));\n\n var query = [{\"id\":id.substr(13),\"value\":true}];\n http_post(\"/setProperties\",JSON.stringify(query),null,null,null);\n\n}\n\nfunction initialize_alarms()\n{\n $('#refreshalarms').click(refresh_alarm_table);\n /// register event\n\n // Handler for events of type 'system.progress' only\n eventSource.addEventListener('alarms.update', (e) => {\n refresh_alarm_table();\n });\n // Do something - event data will be in e.data,\n // message will be of type 'eventType'\n refresh_alarm_table();\n}\n\n\n\n\n\n$( document ).ready(function() {\n console.log( \"ready!\" );\n on_first_load();\n});\n\n\n\n"
},
{
"alpha_fraction": 0.5951986908912659,
"alphanum_fraction": 0.5993377566337585,
"avg_line_length": 27.0930233001709,
"blob_id": "e3d3bb5bfcd21183d07d5a64cf44c88d5a26198d",
"content_id": "5491e6346b7a47b5bf334d549f07baf7ba82f95d",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1208,
"license_type": "permissive",
"max_line_length": 76,
"num_lines": 43,
"path": "/web/js/utils.js",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "function http_get( myUrl ) {\n\tvar xmlHttp = new XMLHttpRequest();\n xmlHttp.open( \"GET\", myUrl, false ); // syncronous request\n xmlHttp.send( null );\n return xmlHttp.responseText;\n}\n\nfunction http_post( url, data, params, obj, cb )\n{\n // construct an HTTP request\n var xhr = new XMLHttpRequest();\n xhr.open(\"POST\", url, true); //asynchronous call\n xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8');\n xhr.onreadystatechange = function() {\n if (xhr.readyState == XMLHttpRequest.DONE)\n {\n if (xhr.status > 201)\n {\n console.log(\"error calling \",url,xhr.status);\n }\n if (cb != null)\n {\n cb(obj,xhr.status,xhr.responseText,params);\n }\n }\n }\n // send the collected data as JSON\n xhr.send(data);\n}\n\nfunction http_post_sync( url, jsonStringify, data ) {\n let xhr = new XMLHttpRequest()\n let inputData\n if ( jsonStringify === true ) {\n inputData = JSON.stringify(data)\n } else {\n inputData = data\n }\n xhr.open(\"POST\", url, false)\n xhr.setRequestHeader('Content-Type', 'application/json; charset=UTF-8')\n xhr.send(inputData)\n return xhr\n}\n"
},
{
"alpha_fraction": 0.5740923881530762,
"alphanum_fraction": 0.5783749222755432,
"avg_line_length": 43.2144660949707,
"blob_id": "12b9378966538702f9f8fe0788a962ef145a56e3",
"content_id": "2ce171ecbf4cc224cb7da00c7d4463be181f48ab",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 176064,
"license_type": "permissive",
"max_line_length": 259,
"num_lines": 3982,
"path": "/bokeh_web/widgets.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "\n\nimport sys\nimport os\nimport time\nimport random\nimport numpy\nimport datetime\n\nsys.path.append(os.path.join(os.path.dirname(__file__), '..'))\n\nimport requests\nimport json\nimport logging\nimport copy\nimport random\nimport time\nimport threading\nimport sse\nimport pytz\nimport traceback\n\n\n\nfrom bokeh.models import DatetimeTickFormatter, ColumnDataSource, BoxSelectTool, BoxAnnotation, Label, LegendItem, Legend, HoverTool, BoxEditTool, TapTool, Circle\nfrom bokeh.models import Range1d,DataRange1d, Span,LinearAxis\nfrom bokeh import events\nfrom bokeh.models.widgets import RadioButtonGroup, Paragraph, Toggle, MultiSelect, Button, Select, CheckboxButtonGroup,Dropdown\nfrom bokeh.plotting import figure, curdoc\nfrom bokeh.layouts import layout,widgetbox, column, row, Spacer\nfrom bokeh.models import Range1d, PanTool, WheelZoomTool, ResetTool, ToolbarBox, Toolbar, Selection, BoxZoomTool\nfrom bokeh.models import FuncTickFormatter, CustomJSHover, SingleIntervalTicker, DatetimeTicker, CustomJS\nfrom bokeh.themes import Theme\nfrom pytz import timezone\nfrom bokeh.models.glyphs import Rect\nfrom bokeh.models.glyphs import Quad\nfrom bokeh.models.glyphs import VArea,VBar\n\nfrom bokeh.models.renderers import GlyphRenderer\n\n\n\n#RenderLevel = Enumeration(image, underlay, glyph, guide, annotation, overlay)\n\nhaveLogger = False\nglobalAlpha = 1.0#0.3\n\nglobalAnnotationLevel = \"image\"\nglobalBackgroundsLevel = \"underlay\"\nglobalThresholdsLevel = \"underlay\"\nglobalAnnotationsAlpha = 0.90\nglobalThresholdsAlpha = 0.5\nglobalBackgroundsAlpha = 0.2\nglobalBackgroundsHighlightAlpha = 0.6\n\nglobalRESTTimeout = 90\n\n\n\ndef setup_logging(loglevel=logging.DEBUG,tag = \"\"):\n global haveLogger\n print(\"setup_logging\",haveLogger)\n if not haveLogger:\n # fileName = 'C:/Users/al/devel/ARBEIT/testmyapp.log'\n #logging.basicConfig(format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s', level=loglevel)\n\n #remove all initial handlers, e.g. console\n allHandlers = logging.getLogger('').handlers\n for h in allHandlers:\n logging.getLogger('').removeHandler(h)\n\n\n formatter = logging.Formatter('%(asctime)s %(name)-12s thid%(thread)d %(levelname)-8s %(message)s')\n console = logging.StreamHandler()\n console.setLevel(loglevel)\n console.setFormatter(formatter)\n logging.getLogger('').addHandler(console)\n\n #logfile = logging.FileHandler('./log/widget_'+'%08x' % random.randrange(16 ** 8)+\".log\")\n #logfile = logging.FileHandler('./widget_' + '%08x' % random.randrange(16 ** 8) + \".log\")\n if tag == \"\":\n tag = '%08x' % random.randrange(16 ** 8)\n logfile = logging.FileHandler('./log/widget_' + tag+ \".log\")\n logfile.setLevel(loglevel)\n logfile.setFormatter(formatter)\n logging.getLogger('').addHandler(logfile)\n haveLogger = True\n\n\n\n\n#import model\nfrom dates import date2secs,secs2date, secs2dateString\nfrom dates import epochToIsoString\nimport themes #for nice colorsing\n\n\n\n#give a part tree of nodes, return a dict with const=value\ndef get_const_nodes_as_dict(tree):\n consts ={}\n for node in tree:\n if node[\"type\"] in [\"const\",\"variable\"]:\n consts[node[\"name\"]]=node[\"value\"]\n if node[\"type\"] == \"referencer\":\n if \"forwardPaths\" in node:\n consts[node[\"name\"]] = node[\"forwardPaths\"]\n\n return consts\n\n\n\n\nclass TimeSeriesWidgetDataServer():\n \"\"\"\n a helper class for the time series widget dealing with the connection to the backend rest model server\n it also caches settings which don't change over time\n \"\"\"\n def __init__(self,modelUrl,avatarPath):\n self.url = modelUrl # get the data from here\n self.path = avatarPath # here is the struct for the timeserieswidget\n #self.timeOffset = 0 # the timeoffset of display in seconds (from \".displayTimeZone)\n self.annotations = {}\n self.pendingScoreVariablesUpdate = False# is set to true if there has been a silent update of the score variables list without telling the ts widget\n self.scoreVariables = []\n self.events = None\n self.sseCb = None # the callbackfunction on event\n\n self.__init_logger(logging.DEBUG)\n self.__init_proxy()\n self.__get_settings()\n self.__init_sse()\n\n def __del__(self):\n print(\"del times series widget \") #try to understand what bokeh is doing :)\n\n def __init_sse(self):\n self.sse = sse.SSEReceiver(f'{self.url}event/stream',self.sse_cb)\n self.sse.start()\n\n def sse_cb(self,data):\n #self.logger.debug(f'sse {data}, {self.settings[\"observerIds\"]}, my id {id(self)}')\n #now we filter out the events which are for me\n if data[\"data\"]!=\"\":\n try:\n dataString = data[\"data\"]\n dataString = dataString.replace(\"'\",'\"') # json needs double quote for key/values entries\n parseData = json.loads(dataString)\n #self.logger.debug(f\"parsed event {parseData}\")\n if data[\"event\"].startswith(\"global\") or (\"nodeId\" in parseData and parseData[\"nodeId\"] in self.settings[\"observerIds\"]): #only my own observers are currently taken\n #self.logger.info(\"sse match\")\n data[\"data\"]=parseData # replace the string with the parsed info\n if self.sseCb:\n self.sseCb(data)\n except Exception as ex:\n self.logger.error(f\"sse_Cb error {ex}, {sys.exc_info()[0]}\")\n\n def sse_stop(self):\n self.sse.stop()\n def sse_register_cb(self,cb):\n self.sseCb = cb\n\n def __init_proxy(self):\n \"\"\"\n try to open the proxies file, set the local proxy if possible\n \"\"\"\n self.proxySetting = {}\n try:\n with open('proxies.json','r') as f:\n self.proxySetting = json.loads(f.read())\n self.logger.info(\"using a proxy!\")\n except:\n self.logger.info(\"no proxy used\")\n pass\n\n def __init_logger(self, level=logging.DEBUG):\n setup_logging(loglevel = level, tag=self.path)\n self.logger = logging.getLogger(\"TSServer\")\n self.logger.setLevel(level)\n #handler = logging.StreamHandler()\n #formatter = logging.Formatter('%(asctime)s %(name)-12s %(levelname)-8s %(message)s')\n #handler.setFormatter(formatter)\n #self.logger.addHandler(handler)\n #self.logger.setLevel(level)\n\n\n\n def __web_call(self,method,path,reqData):\n \"\"\"\n this functions makes a call to the backend model serer to get data\n Args:\n method(string) one of [\"GET\",\"POST\"]\n path: the nodepath to the time series widtet\n reqData: a dictionary with request data for te query like the list of variables, time limits etc.\n Returns (dict):\n the data from the backend as dict\n \"\"\"\n self.logger.info(\"__web_call %s @%s data:%s\",method,path,str(reqData))\n\n response = None\n now = datetime.datetime.now()\n if method.upper() == \"GET\":\n try:\n response = requests.get(self.url + path, timeout=globalRESTTimeout,proxies=self.proxySetting)\n except Exception as ex:\n self.logger.error(\"requests.get msg:\"+str(ex))\n\n elif method.upper() == \"POST\":\n now = datetime.datetime.now()\n try:\n response = requests.post(self.url + path, data=json.dumps(reqData), timeout=globalRESTTimeout,\n proxies=self.proxySetting)\n except Exception as ex:\n self.logger.error(\"requets.post \" + str(ex))\n\n after = datetime.datetime.now()\n diff = (after-now).total_seconds()\n self.logger.info(\"response \"+str(response)+\" took \"+ str(diff))\n if not response:\n self.logger.error(\"Error calling web \" + path )\n return None\n else:\n rData = json.loads(response.content.decode(\"utf-8\"))\n return rData\n\n def get_selected_variables_sync(self):\n request = self.path + \".selectedVariables\"\n selectedVars = []\n\n nodes = self.__web_call(\"post\", \"_getleaves\", request)\n selectedVars=[node[\"browsePath\"] for node in nodes]\n self.selectedVariables=copy.deepcopy(selectedVars)\n self.logger.debug(f\"get_selected_variables_sync => {self.selectedVariables}\")\n return selectedVars\n\n def get_path(self):\n return self.path\n\n def load_annotations(self):\n self.logger.debug(\"load_annotations\")\n if (self.settings[\"hasAnnotation\"] == True) or (self.settings[\"hasThreshold\"] == True):\n response = self.__web_call(\"post\",\"_get\",[self.path+\".\"+\"hasAnnotation\"])\n annotationsInfo = get_const_nodes_as_dict(response[0][\"children\"])\n self.settings.update(annotationsInfo)\n #now get all annotations\n nodes = self.__web_call(\"post\",\"_getleaves\",self.path+\".hasAnnotation.annotations\")\n self.logger.debug(\"ANNOTATIONS\"+json.dumps(nodes,indent=4))\n #now parse the stuff and build up our information\n self.annotations={}\n for node in nodes:\n if node[\"type\"]==\"annotation\":\n self.annotations[node[\"browsePath\"]]=get_const_nodes_as_dict(node[\"children\"])\n\n if \"startTime\" in self.annotations[node[\"browsePath\"]]:\n self.annotations[node[\"browsePath\"]][\"startTime\"] = date2secs(self.annotations[node[\"browsePath\"]][\"startTime\"])*1000\n if \"endTime\" in self.annotations[node[\"browsePath\"]]:\n self.annotations[node[\"browsePath\"]][\"endTime\"] = date2secs(self.annotations[node[\"browsePath\"]][\"endTime\"]) * 1000\n if self.annotations[node[\"browsePath\"]][\"type\"] in [\"threshold\",\"motif\"]:\n #we also pick the target, only the first!\n self.annotations[node[\"browsePath\"]][\"variable\"]=self.annotations[node[\"browsePath\"]][\"variable\"][0]\n self.logger.debug(\"server annotations\" + json.dumps(self.annotations, indent=4))\n\n\n\n\n\n def __get_settings(self):\n \"\"\"\n get all the settings of the widget and store them also in the self.settings cache\n Returns: none\n\n \"\"\"\n\n self.fetch_mirror()\n\n\n\n request = [self.path]\n info = self.__web_call(\"post\",\"_get\",request)\n self.logger.debug(\"initial settings %s\",json.dumps(info,indent=4))\n #self.originalInfo=copy.deepcopy(info)\n #grab some settings\n self.settings = get_const_nodes_as_dict(info[0][\"children\"])\n\n\n #also grab the selected\n request = self.path+\".selectedVariables\"\n self.selectedVariables=[]\n nodes = self.__web_call(\"post\",\"_getleaves\",request)\n for node in nodes:\n self.selectedVariables.append(node[\"browsePath\"])\n #get the selectable\n nodes = self.__web_call('POST',\"_getleaves\",self.path+'.selectableVariables')\n self.selectableVariables = []\n for node in nodes:\n self.selectableVariables.append(node[\"browsePath\"])\n #also remeber the timefield as path\n request = self.path+\".table\"\n nodes = self.__web_call(\"post\",\"_getleaves\",request)\n #this should return only one node\n #timerefpath = nodes[0][\"browsePath\"]+\".timeField\"\n #another call to get it right\n #nodes = self.__web_call(\"post\", \"_getleaves\", timerefpath)\n #self.timeNode = nodes[0][\"browsePath\"]\n \n\n #now for the annotations\n if (self.settings[\"hasAnnotation\"] == True) or (self.settings[\"hasThreshold\"] == True):\n response = self.__web_call(\"post\",\"_get\",[self.path+\".\"+\"hasAnnotation\"])\n annotationsInfo = get_const_nodes_as_dict(response[0][\"children\"])\n self.settings.update(annotationsInfo)\n self.annotations=self.fetch_annotations() # get all the annotations\n\n #for the events\n if \"hasEvents\" in self.settings and self.settings[\"hasEvents\"] == True:\n self.events = self.fetch_events()\n\n #grab the info for the buttons\n myButtons=[]\n for node in info[0][\"children\"]:\n if node[\"name\"]==\"buttons\":\n myButtons = node[\"children\"]\n\n #now get more info on the buttons\n if myButtons != []:\n buttonInfo = self.__web_call(\"post\",\"_get\",myButtons)\n self.settings[\"buttons\"]=[]\n for button in buttonInfo:\n #find the caption and target\n caption = \"\"\n target = \"\"\n for child in button[\"children\"]:\n if child[\"name\"] == \"caption\":\n caption=child[\"value\"]\n if child[\"name\"] == \"onClick\":\n targets = child[\"forwardRefs\"]\n if targets != \"\":\n #create that button\n self.settings[\"buttons\"].append({\"name\":caption,\"targets\":targets.copy()})\n\n\n # now compile info for the observer #new observers\n # we remeber all ids of observers in our widget\n self.settings[\"observerIds\"]=[]\n for node in info[0][\"children\"]:\n if node[\"type\"]==\"observer\":\n self.settings[\"observerIds\"].append(node[\"id\"])\n\n # now grab the info for the backgrounds\n try:\n background={}\n for node in info[0][\"children\"]:\n if node[\"name\"] == \"hasBackground\":\n background[\"hasBackground\"] = node[\"value\"]\n if node[\"name\"] == \"background\" and background[\"hasBackground\"]==True:\n # we take only the first entry (there should be only one) of the referencer:\n # this is the nodeId of the background values\n background[\"background\"]=node[\"forwardRefs\"][0]\n if node[\"name\"] == \"backgroundMap\":\n background[\"backgroundMap\"] = copy.deepcopy(node[\"value\"]) #the json map for background values and color mapping\n if all(key in background for key in [\"hasBackground\",\"background\",\"backgroundMap\"]):\n self.settings[\"background\"]=copy.deepcopy(background)\n else:\n self.settings[\"background\"]={\"hasBackground\":False}\n #we dont have a valid background definition\n except Exception as ex:\n self.logger.error(f\"problem loading background {ex}, {str(sys.exc_info()[1])}, disabling background\")\n self.settings[\"background\"] = {\"hasBackground\": False}\n\n\n self.logger.debug(\"SERVER.SETTINGS-------------------------\")\n self.logger.debug(\"%s\",json.dumps(self.settings,indent=4))\n\n\n def fetch_events(self):\n # return a dict with {id:eventdict}\n nodes = self.__web_call(\"post\", \"_getleaves\", self.path + \".hasEvents.events\")\n self.logger.debug(f\"fetch_events: {len(nodes)} events\")\n query = {\"nodes\":[node[\"id\"] for node in nodes if node[\"type\"]==\"eventseries\"]}\n events = self.__web_call(\"post\",\"_getEvents\",query)\n self.logger.debug(f\"events result {len(events)}\")\n self.events = events\n return events # dict \"nodeid\":{\"events\":{\"one\":....,\"two\":... }\"eventMap\"....},\"id2\":{}\n\n def get_events(self):\n return copy.deepcopy(self.events)\n\n\n def fetch_annotations(self):\n # return a dict with {id:annotationdict}\n #get a fresh copy of the annotations\n nodes = self.__web_call(\"post\", \"_getleaves\", self.path + \".hasAnnotation.annotations\")\n self.logger.debug(f\"_fetch_annotations(): {len(nodes)} annotations\")\n # now parse the stuff and build up our information\n annotations = {}\n for node in nodes:\n if node[\"type\"] == \"annotation\":\n try:\n annotation = get_const_nodes_as_dict(node[\"children\"])\n annotation[\"browsePath\"]=node[\"browsePath\"]\n annotation[\"id\"]=node[\"id\"]\n annotation[\"name\"] = node[\"name\"]\n #convert some stuff\n if \"startTime\" in annotation:\n annotation[\"startTime\"] = date2secs(\n annotation[\"startTime\"]) * 1000\n if \"endTime\" in annotation:\n annotation[\"endTime\"] = date2secs(\n annotation[\"endTime\"]) * 1000\n if annotation[\"type\"] in [\"threshold\",\"motif\"]:\n # we also pick the target, only the first\n annotation[\"variable\"] = annotation[\"variable\"][0]\n annotations[node[\"id\"]]=annotation\n except Exception as ex:\n self.logger.error(f\"problem loading annotations {ex}, {str(sys.exc_info()[1])}\")\n continue\n #self.logger.debug(\"server annotations\" + json.dumps(self.annotations, indent=4))\n self.annotations = copy.deepcopy(annotations)\n return annotations\n\n def fetch_annotations_differential(self,info):\n #args is a dict :{\"new\":[id1,id2], \"delete\":[id3,id4] \"modify\":[id5...] lists that contain ids where there have been changes\n\n #the deletes\n for id in info[\"delete\"]:\n if id in self.annotations:\n del self.annotations[id]\n\n\n #merge the new and modify and put them in our local info\n nodes = info[\"new\"]\n nodes.update(info[\"modify\"])\n\n for id,annotation in nodes.items():\n try:\n # convert some stuff\n if \"startTime\" in annotation:\n annotation[\"startTime\"] = date2secs(\n annotation[\"startTime\"]) * 1000\n if \"endTime\" in annotation:\n annotation[\"endTime\"] = date2secs(\n annotation[\"endTime\"]) * 1000\n if annotation[\"type\"] in [\"threshold\", \"motif\"]:\n # we also pick the target, only the first\n annotation[\"variable\"] = annotation[\"variable\"][0]\n self.annotations[id] = annotation #update or new entry\n except Exception as ex:\n self.logger.error(f\"problem loading annotations {ex}, {str(sys.exc_info()[1])}\")\n continue\n return self.annotations\n\n\n\n\n\n\n ##############################\n ## INTERFACE FOR THE WIDGET\n ##############################\n\n def execute_function(self,descriptor):\n \"\"\" trigger the execution of a registered function in the backend \"\"\"\n return self.__web_call(\"POST\",\"_execute\",descriptor)\n\n\n def get_values(self,varList):\n \"\"\" get a list of values of variables this is for type varialb, const \"\"\"\n return self.__web_call(\"POST\",\"_getvalue\",varList)\n\n\n def get_data(self,variables,start=None,end=None,bins=300):\n\n \"\"\"\n retrieve a data table from the backend\n Args:\n variables(list): the nodes from which the data is retrieved\n start (float): the startime in epoch ms\n end (float): the endtime in epoch ms\n bins (int): the number of samples to be retrieved between the start and end time\n Returns (dict):\n the body of the response of the data request of the backend\n \"\"\"\n self.logger.debug(\"server.get_data()\")\n\n varList = self.selectedVariables.copy()\n #include background values if it has background enabled\n if self.settings[\"background\"][\"hasBackground\"]==True:\n varList.append(self.settings[\"background\"][\"background\"]) # include the node it holding the backgrounds\n # now get data from server\n if start:\n start=start/1000\n if end:\n end=end/1000\n body = {\n \"nodes\": varList,\n \"startTime\" : start,\n \"endTime\" : end,\n \"bins\":bins,\n \"includeTimeStamps\": \"02:00\",\n \"includeIntervalLimits\" : True\n }\n r=self.__web_call(\"POST\",\"_getdata\",body)\n if not r:\n return None\n #convert the time to ms since epoch\n for entry in r:\n if entry.endswith(\"__time\"):\n times = numpy.asarray(r[entry])\n debug = copy.deepcopy(times.tolist())\n r[entry]=(times*1000).tolist()\n #print(f\"times {debug}\")\n #print(f\"times {entry} {[epochToIsoString(t) for t in debug]}\")\n #make them all lists and make all inf/nan etc to nan\n for k,v in r.items():\n r[k]=[value if numpy.isfinite(value) else numpy.nan for value in v]\n\n #self.logger.debug(str(r))\n return r\n\n\n def get_time_node(self):\n return self.timeNode\n\n def get_mirror(self):\n return self.mirror\n\n def fetch_mirror(self,small = False):\n if small:\n query = {\"node\":self.path,\"depth\":1,\"ignore\":[\"observer\"]}\n else:\n query = {\"node\":self.path,\"depth\":100,\"ignore\":[\"observer\",\"hasAnnotation.anno\",\"hasAnnotation.new\"]}\n self.mirror = self.__web_call(\"post\", \"_getbranchpretty\", query)\n self.update_score_variables_from_mirror()\n return self.mirror\n\n def fetch_score_variables(self):\n\n old = copy.deepcopy(self.scoreVariables)\n\n nodes = self.__web_call(\"post\", \"_getleaves\", self.path + \".scoreVariables\")\n scoreVariables = [node[\"browsePath\"] for node in nodes]\n self.scoreVariables = copy.deepcopy(scoreVariables)\n #self.logger.debug(f\"fetch_score_variables : old {old}, new:{self.scoreVariables}\")\n\n if old != self.scoreVariables or self.pendingScoreVariablesUpdate:\n self.pendingScoreVariablesUpdate = False\n return True # have something new\n else:\n return False\n\n def update_score_variables_from_mirror(self):\n scoreVars = []\n for id,node in self.mirror[\"scoreVariables\"][\".properties\"][\"leavesProperties\"].items():\n scoreVars.append(node[\"browsePath\"])\n self.pendingScoreVariablesUpdate = True # if the TSwidget asks later if there was a diff in the meantime, we better say yes to not skip updates\n self.scoreVariables = scoreVars\n\n\n\n def get_current_colors(self):\n return self.mirror[\"currentColors\"][\".properties\"][\"value\"]\n\n def update_current_colors(self,currentColors):\n if currentColors == self.mirror[\"currentColors\"][\".properties\"][\"value\"]:\n return # nothing to do\n nodesToModify = [{\"browsePath\": self.path + \".currentColors\", \"value\": currentColors}]\n self.mirror[\"currentColors\"][\".properties\"][\"value\"] = currentColors\n self.__web_call('POST', 'setProperties', nodesToModify)\n\n def get_variables_selectable(self):\n \"\"\" returns the selectable variables from the cache\"\"\"\n return copy.deepcopy(self.selectableVariables)\n\n def get_variables_selected(self):\n \"\"\" return list of selected variables from the cache\"\"\"\n return copy.deepcopy(self.selectedVariables)\n\n def get_annotations(self):\n return copy.deepcopy(self.annotations)\n #return copy.deepcopy(self.annotations)\n\n def bokeh_time_to_string(self,epoch):\n localtz = timezone(self.settings[\"timeZone\"])\n dt = datetime.datetime.fromtimestamp(epoch/1000, localtz)\n return dt.isoformat()\n\n def get_score_variables(self):\n return copy.deepcopy(self.scoreVariables)\n\n def is_score_variable(self,variableBrowsePath):\n return (variableBrowsePath in self.scoreVariables)\n\n\n #start and end are ms(!) sice epoch, tag is a string\n def add_annotation(self,start=0,end=0,tag=\"unknown\",type=\"time\",min=0,max=0, var = None):\n \"\"\"\n add a new user annotation to the model and also add it to the local cache\n Args:\n start(float): the start time in epcoh ms\n end(float): the end time in epoch ms\n tag (string) the tag to be set for this annotation\n Returns:\n the node browsePath of this new annotation\n \"\"\"\n\n #place a new annotation into path\n nodeName = '%08x' % random.randrange(16 ** 8)\n annoPath = self.path + \".\" + \"hasAnnotation.newAnnotations.\"+nodeName\n if type == \"time\":\n nodesToCreate = [\n {\"browsePath\": annoPath,\"type\":\"annotation\"},\n {\"browsePath\": annoPath + '.type',\"type\":\"const\",\"value\":\"time\"},\n {\"browsePath\": annoPath + '.startTime',\"type\":\"const\",\"value\":self.bokeh_time_to_string(start)},\n {\"browsePath\": annoPath + '.endTime', \"type\": \"const\", \"value\":self.bokeh_time_to_string(end)},\n {\"browsePath\": annoPath + '.tags', \"type\": \"const\", \"value\": [tag]}\n ]\n elif type ==\"threshold\":\n nodesToCreate = [\n {\"browsePath\": annoPath, \"type\": \"annotation\"},\n {\"browsePath\": annoPath + '.type', \"type\": \"const\", \"value\": \"threshold\"},\n {\"browsePath\": annoPath + '.min', \"type\": \"const\", \"value\": min},\n {\"browsePath\": annoPath + '.max', \"type\": \"const\", \"value\": max},\n {\"browsePath\": annoPath + '.tags', \"type\": \"const\", \"value\": [tag]},\n {\"browsePath\": annoPath + '.variable', \"type\": \"referencer\", \"targets\": [var]}\n\n ]\n elif type == \"motif\":\n nodesToCreate = [\n {\"browsePath\": annoPath, \"type\": \"annotation\"},\n {\"browsePath\": annoPath + '.type', \"type\": \"const\", \"value\": \"motif\"},\n {\"browsePath\": annoPath + '.startTime', \"type\": \"const\", \"value\": self.bokeh_time_to_string(start)},\n {\"browsePath\": annoPath + '.endTime', \"type\": \"const\", \"value\": self.bokeh_time_to_string(end)},\n {\"browsePath\": annoPath + '.tags', \"type\": \"const\", \"value\": [tag]},\n {\"browsePath\": annoPath + '.variable', \"type\": \"referencer\", \"targets\": [var]}\n\n ]\n else:\n self.logger.error(f\"can't create anno type {type}\")\n return None\n\n self.logger.debug(\"creating anno %s\",str(nodesToCreate))\n res = self.__web_call('POST','_create',nodesToCreate)\n\n if res:\n #the first is our node id\n #now also update our internal list\n anno = {\"startTime\":start,\"endTime\":end,\"tags\":[tag],\"min\":min,\"max\":max,\"type\":type,\"variable\":var,\"id\":res[0],\"name\":nodeName}\n self.annotations[anno[\"id\"]] = copy.deepcopy(anno)\n return anno\n else:\n return None\n\n\n def adjust_annotation(self,anno):\n \"\"\"\n change an exising annotation and write it back to the model via REST\n Args:\n anno [dict]: contains entries to be overwritten in the original annotation dict\n \"\"\"\n if anno[\"id\"] not in self.annotations:\n return False\n self.logger.debug(f\"ser .adjust_annotation {anno}\")\n self.annotations[anno[\"id\"]].update(anno)\n path = anno[\"id\"]# we build a \"fancy\" browsepath as nodeid.name.name\n if anno['type'] in [\"time\",\"motif\"]:\n #for time annotation we write the startTime and endTime\n nodesToModify =[\n {\"browsePath\": path + \".startTime\", \"value\":self.bokeh_time_to_string(anno[\"startTime\"])},\n {\"browsePath\": path + \".endTime\", \"value\": self.bokeh_time_to_string(anno[\"endTime\"])}\n ]\n elif anno['type'] == \"threshold\":\n nodesToModify = [\n {\"browsePath\": path + \".min\", \"value\": anno[\"min\"]},\n {\"browsePath\": path + \".max\", \"value\": anno[\"max\"]}\n\n ]\n else:\n self.logger.error(\"adjust_annotations : unsopported type\")\n return\n\n res = self.__web_call('POST', 'setProperties', nodesToModify)\n\n\n\n\n\n def delete_annotations(self,deleteList):\n \"\"\" delete existing annotation per browsePath from model and cache\"\"\"\n for nodePath in deleteList:\n del self.annotations[nodePath]\n self.__web_call(\"POST\",\"_delete\",deleteList)\n pass\n\n def set_variables_selected(self, varList, updateLocalNow=True):\n \"\"\" update the currently selected variables to cache and backend\n if we set updateLocalNow to False, we do not update the local list, that means we will\n only detect the changes in the next sse event\n \"\"\"\n query={\"deleteExisting\":True,\"parent\":self.path+\".selectedVariables\",\"add\":varList}\n self.__web_call(\"POST\",\"_references\",query)\n if updateLocalNow:\n self.selectedVariables=varList.copy()\n return\n\n def add_variables_selected(self,addList,updateLocalNow=True):\n\n selectedList = copy.deepcopy(self.get_variables_selected())\n selectedList.extend(addList)\n query={\"deleteExisting\":True,\"parent\":self.path+\".selectedVariables\",\"add\":selectedList}\n self.__web_call(\"POST\",\"_references\",query)\n if updateLocalNow:\n self.selectedVariables=selectedList\n return\n\n\n def get_settings(self):\n return copy.deepcopy(self.settings)\n\n def refresh_settings(self):\n self.__get_settings()\n\n def set_background_highlight(self,x,y,backStart,backEnd,remove=False):\n if remove:\n query = {\"browsePath\":self.path+\".backgroundHighlight\",\"type\":\"variable\",\"value\":{}}\n else:\n query = {\"browsePath\":self.path+\".backgroundHighlight\",\"type\":\"variable\",\"value\":{\n \"x\":x/1000,\n \"y\":y,\n \"left\":backStart/1000,\n \"right\":backEnd/1000,\n \"start\":self.bokeh_time_to_string(backStart),\n \"end\":self.bokeh_time_to_string(backEnd)\n }}\n self.__web_call(\"POST\",\"_create\",[query])\n\n\n def select_annotation(self,annoList):\n #anno list is a list of browsepaths\n query = {\"deleteExisting\": True, \"parent\": self.path + \".hasAnnotation.selectedAnnotations\", \"add\": annoList}\n self.__web_call(\"POST\", \"_references\", query)\n return\n\n def set_x_range(self,start,end):\n startTimeString = self.bokeh_time_to_string(start)\n endTimeString = self.bokeh_time_to_string(end)\n\n self.mirror[\"startTime\"][\".properties\"][\"value\"]=startTimeString\n self.mirror[\"endTime\"][\".properties\"][\"value\"] = endTimeString\n\n query= [\n {\"browsePath\": self.path+\".startTime\",\"value\":startTimeString},\n {\"browsePath\": self.path + \".endTime\", \"value\": endTimeString}]\n self.__web_call(\"POST\",\"setProperties\",query)\n return\n\n\n\nclass TimeSeriesWidget():\n def __init__(self, dataserver,curdoc=None):\n self.curdoc = curdoc\n self.id = \"id#\"+str('%8x'%random.randrange(16**8))\n self.__init_logger()\n self.logger.debug(\"__init TimeSeriesWidget()\")\n self.server = dataserver\n self.height = 600\n self.width = 900\n self.lines = {} #keeping the line objects\n self.legendItems ={} # keeping the legend items\n self.legend ={}\n self.hasLegend = False\n #self.data = None\n self.columnData = {}\n self.inPeriodicCb = False\n self.dispatchList = [] # a list of function to be executed in the bokeh app context\n # this is needed e.g. to assign values to renderes etc\n self.dispatchLock = threading.Lock() # need a lock for the dispatch list\n #self.dispatcherRunning = False # set to true if a function is still running\n self.annotationTags = []\n self.hoverTool = None\n self.showThresholds = True # initial value to show or not the thresholds (if they are enabled)\n self.showMotifs = False\n self.streamingMode = False # is set to true if streaming mode is on\n self.annotations = {} # holding the bokeh objects of the annotations\n self.userZoomRunning = False # set to true during user pan/zoom to avoid stream updates at that time\n self.inStreamUpdate = False # set true inside the execution of the stream update\n self.backgrounds = [] #list of current boxannotations dict entries: these are not the renderers\n self.threadsRunning = True # the threads are running: legend watch\n self.annotationsVisible = False # we are currently not showing annotations\n self.boxModifierVisible = False # we are currently no showing the modifiert lines\n self.backgroundHighlightVisible = False # we currently show a background hightlighted\n self.renderers = {} # each element is [\"id\":[\"renderer\":object,\"info\":annoDict] these are the created renderers to be later used e.g. annotations\n\n self.streamingUpdateData = None\n self.showBackgrounds = False\n self.showAnnotationTags = [] # a list with tags to display currently\n self.showAnnotations = False # curently displaying annotations\n self.currentAnnotationVariable = None\n self.currentAnnotationTag = None\n\n self.renderersLock = threading.Lock()\n self.renderersGarbage = [] # a list of renderers to be deleted when time allowes\n\n self.autoAdjustY = True # autoscaling of the y axis\n self.inPan = False #we are not currently in pan mode\n self.annoHovers=[] #holding the objects for hovering annotatios (extra glyph, eg. a circle)\n\n self.eventLines = {} #holding event line renderes and the columndatasources\n self.eventsVisible = False #set true if events are currently turned on\n\n\n\n self.__init_figure() #create the graphical output\n\n self.init_additional_elements() # we need the observer already here eg for the scores s we might modifiy the backend and rely on the callback\n\n self.__init_new_observer() #\n\n self.debug = None\n class ButtonCb():\n \"\"\"\n a wrapper class for the user button callbacks. we need this as we are keeping parameters with the callback\n and the bokehr callback system does not extend there\n \"\"\"\n def __init__(self,parent,parameter):\n self.parameter = parameter\n self.parent = parent\n def cb(self):\n self.parent.logger.info(\"user button callback to trigger %s\",str(self.parameter))\n self.parent.server.execute_function(self.parameter[0]) # we just trigger the first reference\n pass\n\n\n def __init_logger(self, level=logging.DEBUG):\n \"\"\"initialize the logging object\"\"\"\n setup_logging()\n self.logger = logging.getLogger(\"TSWidget\")\n self.logger.setLevel(logging.DEBUG)\n #handler = logging.StreamHandler()\n\n #formatter = logging.Formatter('%(asctime)s %(name)-12s %(levelname)-8s %(message)s')\n #handler.setFormatter(formatter)\n #self.logger.addHandler(handler)\n\n #self.logger.setLevel(level)\n\n\n def log_error(self):\n self.logger.error(f\"{sys.exc_info()[1]}, {traceback.format_exc()}\")\n\n def observer_cb(self,data):\n \"\"\"\n called by the ts server on reception of an event from the model server\n events are\n - update for lines (selection of lines, add, remove lines)\n - update in the backgrounds\n - streaming update\n we can do calls to the restservice here but can't work with the bokeh data, therefore we\n dispatch functions to be executed in the callback from the bokeh loop\n\n \"\"\"\n self.logger.debug(f\"observer_cb {data}\")\n if data[\"event\"] == \"timeSeriesWidget.variables\" or data[\"event\"] == \"global.timeSeries.values\":\n #refresh the lines\n self.server.get_selected_variables_sync() # get the new set of lines\n self.logger.debug(\"dispatch the refresh lines\")\n self.__dispatch_function(self.update_scores)\n self.__dispatch_function(self.refresh_plot) #this includes the backgrounds\n elif data[\"event\"] == \"timeSeriesWidget.background\":\n self.logger.debug(\"dispatch the refresh background\")\n self.__dispatch_function(self.refresh_backgrounds)\n\n elif data[\"event\"] == \"global.series.stream\":\n #this is a stream update, we only do something if the stream update in inside the visible area\n if self.stream_update_is_relevant(data):\n self.__dispatch_function(self.stream_update_new, arg=copy.deepcopy(data))\n else:\n self.logger.debug(\"stream update not relevant, ignore!\")\n\n elif data[\"event\"] == \"timeSeriesWidget.stream\":\n self.logger.debug(f\"self.streamingMode {self.streamingMode}\")\n if self.streamingMode and not self.streamingUpdateData:\n self.logger.debug(\"get stream data\")\n #we update the streaming every second\n #get fresh data, store it into a variable and make the update on dispatch in the context of bokeh\n variables = self.server.get_variables_selected()\n variablesRequest = variables.copy()\n #variablesRequest.append(\"__time\") # make sure we get the time included\n #self.logger.debug(f\"request stream data{self.streamingInterval}\")\n self.streamingUpdateDataInterval = self.streamingInterval #store this to check later if it has changed\n self.streamingUpdateData = self.server.get_data(variablesRequest, -self.streamingInterval, None,\n self.server.get_settings()[\"bins\"]) # for debug\n self.__dispatch_function(self.stream_update)\n elif not self.streamingMode:\n #do the same as for the \"timeseriesWidget.variables\" event\n # refresh the lines\n self.server.get_selected_variables_sync() # get the new set of lines\n self.logger.debug(\"dispatch the refresh lines\")\n self.__dispatch_function(self.update_scores)\n self.__dispatch_function(self.refresh_plot)\n\n elif data[\"event\"] == \"timeSeriesWidget.annotations\":\n self.logger.info(f\"must reload annotations\")\n #self.reInitAnnotationsVisible = self.annotationsVisible #store the state\n # sync from the server\n #self.__dispatch_function(self.reinit_annotations)\n self.__dispatch_function(self.update_annotations_and_thresholds,arg=copy.deepcopy(data))\n\n elif data[\"event\"] == \"global.annotations\":\n self.__dispatch_function(self.update_annotations_and_thresholds,arg=copy.deepcopy(data))\n\n elif data[\"event\"] == \"timeSeriesWidget.eventSeries\":\n self.logger.debug(f\"must reload events\")\n self.__dispatch_function(self.update_events,data)\n\n elif data[\"event\"] == \"global.evenSeries.value\":\n self.logger.debug(f\"must reload events\")\n self.__dispatch_function(self.update_events, data)\n\n elif data[\"event\"] == \"timeSeriesWidget.visibleElements\":\n self.logger.debug(\"update the visible Elements\")\n eventData = data[\"data\"]\n\n #check for start/EndTime\n if \"sourcePath\" in eventData:\n serverPath = self.server.get_path()\n for var in [\"startTime\",\"endTime\"]:\n if eventData[\"sourcePath\"] == serverPath+\".\"+var:\n if self.server.get_mirror()[var][\".properties\"][\"value\"] == eventData[\"value\"]:\n self.logger.info(\"sync x asis not needed\")\n return # ignore this event\n #must sync the x axis\n\n\n\n\n oldMirror = copy.deepcopy(self.server.get_mirror())\n visibleElementsOld = oldMirror[\"visibleElements\"][\".properties\"][\"value\"]\n visibleTagsOld =oldMirror[\"hasAnnotation\"][\"visibleTags\"][\".properties\"][\"value\"]\n if \"hasEvents\" in oldMirror:\n visibleEventsOld = oldMirror[\"hasEvents\"][\"visibleEvents\"][\".properties\"][\"value\"]\n else:\n visibleEventsOld = None\n\n newMirror = copy.deepcopy(self.server.fetch_mirror())\n visibleElementsNew = newMirror[\"visibleElements\"][\".properties\"][\"value\"]\n visibleTagsNew = newMirror[\"hasAnnotation\"][\"visibleTags\"][\".properties\"][\"value\"]\n if \"hasEvents\" in newMirror:\n visibleEventsNew = newMirror[\"hasEvents\"][\"visibleEvents\"][\".properties\"][\"value\"]\n else:\n visibleEventsNew = None\n\n for entry in [\"thresholds\",\"annotations\",\"scores\",\"background\",\"motifs\",\"events\"]:\n #check for turn on:\n if entry in visibleElementsNew and visibleElementsNew[entry] == True:\n if not entry in visibleElementsOld or visibleElementsOld[entry] == False:\n # element was turned on\n if entry == \"annotations\":\n self.__dispatch_function(self.show_annotations)\n elif entry == \"thresholds\":\n self.__dispatch_function(self.show_thresholds)\n elif entry == \"scores\":\n self.__dispatch_function(self.show_scores)\n elif entry == \"background\":\n self.__dispatch_function(self.show_backgrounds)\n elif entry == \"motifs\":\n self.__dispatch_function(self.show_motifs)\n elif entry == \"events\":\n self.__dispatch_function(self.show_all_events)\n\n if entry in visibleElementsOld and visibleElementsOld[entry] == True:\n if not entry in visibleElementsNew or visibleElementsNew[entry]== False:\n # element was turned off\n if entry == \"annotations\":\n self.__dispatch_function(self.hide_annotations)\n elif entry == \"thresholds\":\n self.__dispatch_function(self.hide_thresholds)\n elif entry == \"scores\":\n self.__dispatch_function(self.hide_scores)\n elif entry == \"background\":\n self.__dispatch_function(self.hide_backgrounds)\n elif entry == \"motifs\":\n self.__dispatch_function(self.hide_motifs)\n elif entry == \"events\":\n self.__dispatch_function(self.hide_all_events)\n\n\n #visible tag selections for annotations has changed\n if (visibleTagsOld != visibleTagsNew) and self.showAnnotations:\n self.__dispatch_function(self.show_annotations)\n\n if (visibleEventsOld != visibleEventsNew):\n self.__dispatch_function(self.show_all_events)\n #startime/endtime has changed\n\n if (oldMirror[\"startTime\"][\".properties\"][\"value\"] !=\n newMirror[\"startTime\"][\".properties\"][\"value\"]) or (\n oldMirror[\"endTime\"][\".properties\"][\"value\"] !=\n newMirror[\"endTime\"][\".properties\"][\"value\"]):\n start = date2secs(newMirror[\"startTime\"][\".properties\"][\"value\"])*1000\n end = date2secs(newMirror[\"endTime\"][\".properties\"][\"value\"])*1000\n #self.rangeStart = date2secs(newMirror[\"startTime\"][\".properties\"][\"value\"])*1000\n #self.rangeEnd = date2secs(newMirror[\"endTime\"][\".properties\"][\"value\"])*1000\n self.logger.debug(\"start/end changed\")\n times = {\"start\":start,\"end\":end}\n self.__dispatch_function(self.sync_x_axis,times)\n\n #check if streaming mode has changed\n if oldMirror[\"streamingMode\"][\".properties\"][\"value\"] != newMirror[\"streamingMode\"][\".properties\"][\"value\"]:\n if newMirror[\"streamingMode\"][\".properties\"][\"value\"]:\n self.start_streaming()\n else:\n self.stop_streaming()\n\n if oldMirror[\"panOnlyX\"][\".properties\"][\"value\"] != newMirror[\"panOnlyX\"][\".properties\"][\"value\"]:\n self.set_pan_tool(newMirror[\"panOnlyX\"][\".properties\"][\"value\"])\n\n if \"showMarker\" in newMirror:\n if oldMirror[\"showMarker\"][\".properties\"][\"value\"] != newMirror[\"showMarker\"][\".properties\"][\"value\"]:\n if newMirror[\"showMarker\"][\".properties\"][\"value\"]:\n self.__dispatch_function(self.show_marker)\n else:\n self.__dispatch_function(self.hide_marker)\n\n if \"showLegend\" in newMirror:\n if oldMirror[\"showLegend\"][\".properties\"][\"value\"] != newMirror[\"showLegend\"][\".properties\"][\"value\"]:\n if newMirror[\"showLegend\"][\".properties\"][\"value\"]:\n self.__dispatch_function(self.show_legend)\n else:\n self.__dispatch_function(self.hide_legend)\n\n if \"autoScaleY\" in newMirror:\n self.autoAdjustY = newMirror[\"autoScaleY\"][\".properties\"][\"value\"]\n\n elif data[\"event\"] == \"timeSeriesWidget.values\":\n #the data has changed, typically the score values?\n pass\n\n elif data[\"event\"] == \"timeSeriesWidget.newAnnotation\":\n #self.logger.debug(f\"draw anno!\")\n self.__dispatch_function(self.draw_new_annotation)\n\n def update_scores(self):\n if self.server.fetch_score_variables():\n if self.showScores:\n self.show_scores()\n\n def show_legend(self):\n self.plot.legend.visible = True\n\n def hide_legend(self):\n self.plot.legend.visible = False\n\n def hide_marker(self):\n self.remove_renderers([lin+\"_marker\" for lin in self.lines])\n def show_marker(self):\n self.logger.debug(\"show marker\")\n\n for variableName in self.lines:\n\n markerName = variableName + \"_marker\"\n color = self.lines[variableName].glyph.line_color\n marker = self.plot.circle(x=\"x\",y=\"y\", line_color=color, fill_color=color,\n source=self.columnData[variableName], name=markerName,\n size=3) # x:\"time\", y:variableName #the legend must havee different name than the source bug\n\n\n pass\n\n def update_column_datas(self,newData):\n\n if self.columnData =={}:\n self.logger.info(\"init the colum data\")\n for var in self.server.get_variables_selectable():\n self.columnData[var]=ColumnDataSource({\"x\":[],\"y\":[]})\n\n if \"__time\" in newData:\n del newData[\"time\"]\n\n\n for var in newData:\n if not var.endswith(\"__time\"):\n dic = {\"y\":newData[var],\n \"x\":newData[var+\"__time\"]}\n if var in self.columnData:\n self.columnData[var].data = dic #update\n else:\n self.columnData[var] = ColumnDataSource(dic)\n\n\n def sync_x_axis(self,times=None):\n self.logger.debug(f\"sync_x_axis x \")\n\n variables = self.server.get_variables_selected()\n start = times[\"start\"]\n end = times[\"end\"]\n #self.set_x_axis(start,end)\n variablesRequest = variables.copy()\n variablesRequest.append(\"__time\") # make sure we get the time included\n newData = self.server.get_data(variablesRequest, start, end,\n self.server.get_settings()[\"bins\"]) # for debug\n self.update_column_datas(newData)\n\n self.set_x_axis(start, end)\n #self.plot.x_range.start = start\n #self.plot.x_range.end = end\n self.autoAdjustY = self.server.get_mirror()[\"autoScaleY\"][\".properties\"][\"value\"]\n self.adjust_y_axis_limits()\n\n\n def draw_new_annotation(self):\n data = self.server.fetch_mirror()\n entry = data[\"nextNewAnnotation\"][\".properties\"][\"value\"]\n if entry[\"type\"] == \"time\":\n self.boxSelectTool.dimensions = \"width\"\n self.set_active_drag_tool(self.boxSelectTool)\n self.currentAnnotationTag = entry[\"tag\"]\n elif entry[\"type\"] == \"threshold\":\n self.boxSelectTool.dimensions = \"height\"\n self.set_active_drag_tool(self.boxSelectTool)\n self.currentAnnotationTag = \"threshold\"\n self.currentAnnotationVariable = entry[\"variable\"]\n elif entry[\"type\"] == \"motif\":\n self.boxSelectTool.dimensions = \"width\"\n self.set_active_drag_tool(self.boxSelectTool)\n self.currentAnnotationTag = \"motif\"\n self.currentAnnotationVariable = entry[\"variable\"]\n\n\n def _compare_anno(self,anno1,anno2):\n\n keysInBoth = set(anno1.keys()).intersection(set(anno2.keys()))\n\n for k in keysInBoth:\n if k == \"browsePath\":\n continue\n elif k in [\"startTime\", \"endTime\"]:\n diff = abs(anno1[k]-anno2[k])\n if diff < 0.1:\n continue\n else:\n self.logger.debug(f'compare failded time diff {diff}')\n return False\n else:\n if anno1[k] != anno2[k]:\n print(f\"compare failed {k}, {anno1[k]} {anno2[k]}\")\n return False\n return True\n\n\n\n def update_annotations_and_thresholds(self,arg=None):\n self.logger.debug(f\"update_annotations {arg}\")\n # this is called when the backend has changed annotation leaves or values, it adjusts annotations\n # and thresholds\n\n lastAnnotations = self.server.get_annotations()\n if \"data\" in arg and \"_eventInfo\" in arg[\"data\"]:\n newAnnotations = self.server.fetch_annotations_differential(arg[\"data\"][\"_eventInfo\"])\n else:\n newAnnotations = self.server.fetch_annotations()\n\n #check for deletes\n deleteList = [] # a list of ids\n for annoId,anno in lastAnnotations.items():\n if annoId not in newAnnotations:\n self.logger.debug(f\"update_annotations() -- annotations was deleted on server: {annoId}, {lastAnnotations[annoId]['name']}\")\n deleteList.append(annoId)\n if annoId in self.renderers:\n with self.renderersLock:\n self.renderersGarbage.append(self.renderers[annoId][\"renderer\"])\n del self.renderers[annoId]\n self.logger.debug(f\"update_annotations() -- must delete {deleteList}\")\n\n\n\n if self.boxModifierVisible:\n if self.boxModifierAnnotationName in deleteList:\n self.box_modifier_hide()\n\n #now the new ones\n createdTimeAnnos = []\n\n for annoId,anno in newAnnotations.items():\n\n if anno[\"type\"] == \"time\":\n if annoId not in self.renderers:# and self.showAnnotations:\n self.logger.debug(f\"new annotations {annoId}\")\n self.draw_annotation(anno,visible=False) #will be activated later with show_annotations\n createdTimeAnnos.append(annoId)\n else:\n #check if is has changed\n #if anno != self.renderers[annoId][\"info\"]:\n if not self._compare_anno(anno,self.renderers[annoId][\"info\"] ):\n self.logger.debug(f\"update_annotations() -- annotation has changed {annoId} {self.renderers[annoId]['info']} => {anno}\")\n\n isVisible = self.renderers[annoId][\"renderer\"] in self.plot.renderers # remember if the annotation was currently visible\n with self.renderersLock:\n self.renderersGarbage.append(self.renderers[annoId][\"renderer\"])\n del self.renderers[annoId]# kick out the entry,\n # if the currently selected is being changed, we hide the box modifier\n if self.boxModifierVisible:\n if self.boxModifierAnnotationName == annoId:\n self.box_modifier_hide()\n\n # now recreate: if the annotation was visible before (was in the plot.renderers\n # then we show it again, if not, we decide later in the show_annotations if it will be shown or not\n # depending on selected tags etc. this covers especially the exception case where a user\n # draws a new annotation, which is a currently NOT activated tag, then modifies that new annotation:\n # it should stay visible!\n if isVisible:\n self.draw_annotation(anno, visible=True) #show right away because it was visible before\n else:\n self.draw_annotation(anno, visible=False) # show later if allowed depending on tags etc.\n createdTimeAnnos.append(annoId) #show later if allowed\n if anno[\"type\"] in [\"threshold\",\"motif\"]:\n # for thresholds/motifs we do not support delete/create per backend, only modify\n # so check for modifications here\n # it might not be part of the renderers: maybe thresholds are currently off\n if annoId in self.renderers and not self._compare_anno(anno,self.renderers[annoId][\"info\"]):\n self.logger.debug(f\"update_annotations() -- thresholds has changed {annoId} {self.renderers[annoId]['info']} => {anno}\")\n with self.renderersLock:\n self.renderersGarbage.append(self.renderers[annoId][\"renderer\"])\n del self.renderers[annoId] # kick out the entry, the remaining invisible renderer will stay in bokeh as garbage\n #if the currently selected is being changed, we hide the box modifier\n if self.boxModifierVisible:\n if self.boxModifierAnnotationName == annoId:\n self.box_modifier_hide()\n # now recreate\n if anno[\"type\"] ==\"threshold\":\n self.draw_threshold(anno)\n else:\n self.draw_motif(anno)\n\n #now execute the changes\n if 0:\n for entry in deleteList:\n # we only switch it invisible for now, we don't delete the\n # renderer, as this takes too long\n r = self.find_renderer(entry)\n if r:\n r.visible = False\n\n if self.showAnnotations and createdTimeAnnos != []:\n self.show_annotations(createdTimeAnnos) # this will put them to the plot renderes\n\n #self.show_annotations()\n\n self.remove_renderers() # execute at least the deletes\n\n\n\n def reinit_annotations(self):\n self.hide_annotations()\n self.server.load_annotations()\n self.logger.debug(\"reinit_annotations=>init_annotations\")\n self.init_annotations()\n if self.reInitAnnotationsVisible:\n self.logger.debug(\"reinit_annotations=>init_annotations\")\n self.show_annotations()\n\n def __legend_check(self):\n try:\n # now we also check if we have a legend click which means that we must delete a variable from the selection\n # self.logger.debug(\"RENDERERS CHECK --------------------------\")\n deleteList = []\n for r in self.plot.renderers:\n if r.name and r.name in self.server.get_variables_selected() and r.visible == False:\n # there was a click on the legend to hide the variables\n self.logger.debug(\"=>>>>>>>>>>>>>>>>>DELETE FROM plot:\" + r.name)\n deleteList.append(r.name)\n\n\n if deleteList != []:\n # now make a second run and check the _score variables of the deletlist\n deleteScoreNames = [deletePath.split('.')[-1]+\"_score\" for deletePath in deleteList]\n deleteExpectedNames = [deletePath.split('.')[-1]+\"_expected\" for deletePath in deleteList]\n for r in self.plot.renderers:\n if r.name and (r.name.split('.')[-1] in deleteScoreNames or r.name.split('.')[-1] in deleteExpectedNames):\n deleteList.append(r.name) #take the according score as well\n\n\n # now prepare the new list:\n newVariablesSelected = [var for var in self.server.get_variables_selected() if var not in deleteList]\n self.logger.debug(\"new var list\" + str(newVariablesSelected))\n self.server.set_variables_selected(newVariablesSelected)\n # self.__dispatch_function(self.refresh_plot)\n\n #now delete potential markers and expected\n self.remove_renderers([lin+\"_marker\" for lin in deleteList])\n\n except Exception as ex:\n self.logger.error(\"problem during __legend_check\" + str(ex))\n\n return (deleteList != [])\n\n\n def __init_new_observer(self):\n self.server.sse_register_cb(self.observer_cb)\n\n\n def __init_figure(self):\n\n \"\"\"\n initialize the time series widget, plot the lines, create controls like buttons and menues\n also hook the callbacks\n \"\"\"\n\n self.hoverCounter = 0\n self.newHover = None\n self.hoverTool = None # forget the old hovers\n self.showBackgrounds = False\n self.showThresholds = False\n self.showMotifs = False\n self.showScores = False\n self.buttonWidth = 70\n\n #layoutControls = []# this will later be applied to layout() function\n\n settings = self.server.get_settings()\n mirror = self.server.get_mirror()\n\n if \"width\" in settings:\n self.width = settings[\"width\"]\n if \"height\" in settings:\n self.height = settings[\"height\"]\n\n \"\"\" \n #set the theme\n if settings[\"theme\"] == \"dark\":\n self.curdoc().theme = Theme(json=themes.darkTheme)\n self.lineColors = themes.darkLineColors\n self.plot.xaxis.major_label_text_color = themes.darkTickColor\n else:\n self.curdoc().theme = Theme(json=themes.whiteTheme)\n self.lineColors = themes.whiteLineColors\n self.plot.xaxis.major_label_text_color = themes.whiteTickColor\n \"\"\"\n #self.cssClasses = {\"button\":\"button_21\",\"groupButton\":\"group_button_21\",\"multiSelect\":\"multi_select_21\"}\n #self.cssClasses = {\"button\": \"button_21_sm\", \"groupButton\": \"group_button_21_sm\", \"multiSelect\": \"multi_select_21_sm\"}\n #self.layoutSettings = {\"controlPosition\":\"bottom\"} #support right and bottom, the location of the buttons and tools\n\n\n #initial values\n try:\n self.rangeStart = date2secs(settings[\"startTime\"])*1000\n self.rangeEnd = date2secs(settings[\"endTime\"])*1000\n except:\n self.rangeStart = None\n self.rangeEnd = None\n self.logger.error(\"range start, end error, use default full\")\n\n #create figure\n \"\"\"\n the creation of the figure was reworked as this is a work around for a well known bug (in 1.04), see here\n https://github.com/bokeh/bokeh/issues/7497\n\n it's a bokeh problem with internal sync problems of frontend and backend, so what we do now is:\n 1) use toolbar_location = None to avoid auto-creation of toolbar\n 2) create tools by hand\n 3) assign them to the figure with add_tools()\n 4) create a toolbar and add it to the layout by hand\n \"\"\"\n\n if self.server.get_mirror()[\"panOnlyX\"][\".properties\"][\"value\"]==True:\n self.wheelZoomTool = WheelZoomTool(dimensions=\"width\")\n self.panTool = PanTool(dimensions=\"width\")\n else:\n self.wheelZoomTool = WheelZoomTool()#dimensions=\"width\")\n self.panTool = PanTool()#dimensions=\"width\")\n\n tools = [self.wheelZoomTool, self.panTool]\n \"\"\"\n self.wheelZoomTool = WheelZoomTool()\n self.wheelZoomToolX = WheelZoomTool(dimensions = \"width\")\n self.panTool = PanTool()\n tools = [self.wheelZoomTool,self.wheelZoomToolX,self.panTool]\n \"\"\"\n\n if settings[\"hasAnnotation\"] == True:\n self.boxSelectTool = BoxSelectTool(dimensions=\"width\")\n tools.append(self.boxSelectTool)\n elif settings[\"hasThreshold\"] == True:\n self.boxSelectTool = BoxSelectTool(dimensions=\"height\")\n tools.append(self.boxSelectTool)\n tools.append(ResetTool())\n self.freeZoomTool = BoxZoomTool()\n tools.append(self.freeZoomTool)\n\n\n\n\n\n\n\n\n\n\n fig = figure(toolbar_location=None, plot_height=self.height,\n plot_width=self.width,\n sizing_mode=\"scale_width\",\n x_axis_type='datetime', y_range=Range1d(),x_range=(0,1))\n self.plot = fig\n\n # set the theme\n if settings[\"theme\"] == \"dark\":\n self.curdoc().theme = Theme(json=themes.darkTheme)\n self.lineColors = themes.darkLineColors\n self.plot.xaxis.major_label_text_color = themes.darkTickColor\n self.plot.yaxis.major_label_text_color = themes.darkTickColor\n else:\n self.curdoc().theme = Theme(json=themes.whiteTheme)\n self.lineColors = themes.whiteLineColors\n self.plot.xaxis.major_label_text_color = themes.whiteTickColor\n self.plot.yaxis.major_label_text_color = themes.whiteTickColor\n\n\n #b1 = date2secs(datetime.datetime(2015,2,13,3,tzinfo=pytz.UTC))*1000\n #b2 = date2secs(datetime.datetime(2015,2,13,4,tzinfo=pytz.UTC))*1000\n #wid = 20*60*1000 # 20 min\n #self.boxData = ColumnDataSource({'x': [b1,b2], 'y':[0,0],'width': [5, 5],'height':[300,300],\"alpha\":[1,1,0.2]})\n\n #self.boxRect = self.plot.rect(x=\"x\", y=\"y\", width=\"width\", height=\"height\",source=self.boxData)\n #self.boxRect = self.plot.rect('x', 'y', 'width', 'height', source=self.boxData,width_units=\"screen\")#, height_units=\"screen\")#, height_units=\"screen\")\n self.boxModifierTool=BoxEditTool( renderers=[],num_objects=0,empty_value=0.1)#,dimensions=\"width\")\n self.box_modifier_init()\n #self.box_modifier_show()\n\n # possible attribures to boxedittool:\n # custom_icon, custom_tooltip, dimensions, empty_value, js_event_callbacks, js_property_callbacks, name, num_objects, renderers, subscribed_events\n #self.plot.add_layout(self.boxRect)\n #self.boxModifierRect.data_source.on_change(\"selected\",self.box_cb)\n #self.boxRect.data_source.on_change(\"active\", self.box_cb_2)\n\n tools.append(self.boxModifierTool)\n\n\n\n\n\n for tool in tools:\n fig.add_tools(tool) # must assign them to the layout to have the actual use hooked\n toolBarBox = ToolbarBox() #we need the strange creation of the tools to avoid the toolbar to disappear after\n # reload of widget, then drawing an annotations (bokeh bug?)\n toolBarBox.toolbar = Toolbar(tools=tools,active_inspect=None,active_scroll=self.wheelZoomTool,active_drag = None)\n #active_inspect = [crosshair],\n # active_drag = # here you can assign the defaults\n # active_scroll = # wheel_zoom sometimes is not working if it is set here\n # active_tap\n toolBarBox.toolbar_location = \"right\"\n toolBarBox.toolbar.logo = None # no bokeh logo\n\n self.tools = toolBarBox\n self.toolBarBox = toolBarBox\n\n\n self.plot.xaxis.formatter = FuncTickFormatter(code = \"\"\"\n let local = moment(tick).tz('%s');\n let datestring = local.format();\n return datestring.slice(0,-6);\n \"\"\"%settings[\"timeZone\"])\n\n self.plot.xaxis.ticker = DatetimeTicker(desired_num_ticks=5)# give more room for the date time string (default was 6)\n\n self.plot.xgrid.ticker = self.plot.xaxis.ticker\n\n self.build_second_y_axis()\n\n self.refresh_plot()\n\n #hook in the callback of the figure\n self.plot.x_range.on_change('start', self.range_cb)\n self.plot.x_range.on_change('end', self.range_cb)\n self.plot.on_event(events.Pan, self.event_cb)\n self.plot.on_event(events.PanStart, self.event_cb)\n self.plot.on_event(events.PanEnd, self.event_cb)\n self.plot.on_event(events.LODEnd, self.event_cb)\n self.plot.on_event(events.Reset, self.event_cb)\n self.plot.on_event(events.SelectionGeometry, self.event_cb)\n self.plot.on_event(events.Tap,self.event_cb)\n\n\n #make the controls\n layoutControls =[]\n\n #Annotation drop down\n if 0: #no drop down for now\n labels=[]\n if settings[\"hasAnnotation\"] == True:\n labels = settings[\"tags\"]\n labels.append(\"-erase-\")\n if settings[\"hasThreshold\"] == True:\n labels.extend([\"threshold\",\"-erase threshold-\"])\n if labels:\n menu = [(label,label) for label in labels]\n self.annotationDropDown = Dropdown(label=\"Annotate: \"+str(labels[0]), menu=menu,width=self.buttonWidth,css_classes = ['dropdown_21'])\n self.currentAnnotationTag = labels[0]\n self.annotationDropDown.on_change('value', self.annotation_drop_down_on_change_cb)\n #self.annotation_drop_down_on_change_cb() #call it to set the box select tool right and the label\n layoutControls.append(self.annotationDropDown)\n\n \"\"\" \n currently disabled\n \n # show Buttons\n # initially everything is disabled\n # check background, threshold, annotation, streaming\n self.showGroupLabels = []\n self.showGroupLabelsDisplay=[]\n if self.server.get_settings()[\"hasAnnotation\"] == True:\n self.showGroupLabels.append(\"Annotation\")\n self.showGroupLabelsDisplay.append(\"Anno\")\n if self.server.get_settings()[\"background\"][\"hasBackground\"]:\n self.showGroupLabels.append(\"Background\")\n self.showGroupLabelsDisplay.append(\"Back\")\n self.showBackgrounds = False # initially off\n if self.server.get_settings()[\"hasThreshold\"] == True:\n self.showGroupLabels.append(\"Threshold\")\n self.showGroupLabelsDisplay.append(\"Thre\")\n self.showThresholds = False # initially off\n if self.server.get_settings()[\"hasStreaming\"] == True:\n self.showGroupLabels.append(\"Streaming\")\n self.showGroupLabelsDisplay.append(\"Stream\")\n self.streamingMode = False # initially off\n self.showGroup = CheckboxButtonGroup(labels=self.showGroupLabelsDisplay)\n self.showGroup.on_change(\"active\",self.show_group_on_click_cb)\n layoutControls.append(row(self.showGroup))\n \"\"\"\n\n #make the custom buttons\n buttonControls = []\n self.customButtonsInstances = []\n if \"buttons\" in settings:\n self.logger.debug(\"create user buttons\")\n #create the buttons\n for entry in settings[\"buttons\"]:\n button = Button(label=entry[\"name\"],width=self.buttonWidth)#,css_classes=['button_21'])\n instance = self.ButtonCb(self,entry[\"targets\"])\n button.on_click(instance.cb)\n buttonControls.append(button)\n self.customButtonsInstances.append(instance)\n\n #make the debug button\n if \"hasReloadButton\" in self.server.get_settings():\n if self.server.get_settings()[\"hasReloadButton\"] == True:\n #we must create a reload button\n button = Button(label=\"reload\",width=self.buttonWidth)#, css_classes=['button_21'])\n button.on_click(self.reset_all)\n buttonControls.append(button)\n\n\n if 0: # turn this helper button on to put some debug code\n self.debugButton= Button(label=\"debug\")\n self.debugButton.on_click(self.debug_button_cb)\n self.debugButton2 = Button(label=\"debug2\")\n self.debugButton2.on_click(self.debug_button_2_cb)\n buttonControls.append(self.debugButton)\n buttonControls.append(self.debugButton2)\n\n\n layoutControls.extend(buttonControls)\n\n #build the layout\n\n\n self.layout = layout([row(children=[self.plot, self.tools], sizing_mode=\"fixed\")], row(layoutControls, width=int(self.width*0.6),sizing_mode=\"scale_width\"))\n #self.layout = layout([row(children=[self.plot, self.tools], sizing_mode=\"fixed\")])\n\n if self.server.get_settings()[\"hasAnnotation\"] == True:\n self.init_annotations() # we create all annotations that we have into self.annotations\n\n if \"hasEvents\" in self.server.get_settings() and self.server.get_settings()[\"hasEvents\"] == True:\n self.init_events()\n\n\n def init_additional_elements(self):\n #now also display further elements\n visibleElements = self.server.get_mirror()[\"visibleElements\"][\".properties\"][\"value\"]\n if \"annotations\" in visibleElements and visibleElements[\"annotations\"] == True:\n self.show_annotations()\n\n if \"thresholds\" in visibleElements and visibleElements[\"thresholds\"] == True:\n self.show_thresholds()\n\n if \"background\" in visibleElements and visibleElements[\"background\"] == True:\n #self.showBackgrounds=True\n self.show_backgrounds()\n\n if \"scores\" in visibleElements and visibleElements[\"scores\"] == True:\n self.show_scores()\n\n if \"motifs\" in visibleElements and visibleElements[\"motifs\"] == True:\n self.show_motifs()\n\n if self.server.get_mirror()[\"streamingMode\"][\".properties\"][\"value\"] == True:\n self.start_streaming()\n\n def set_active_drag_tool(self,tool):\n #we need to change the default selection of active drag and then write the list of tools to the toolsbar\n # the list must be different, otherwise the write will not cause the \"rebuild\" of the tools\n # so we take the last from the list and hide it shortly\n self.logger.debug(f\"set active drag tool, {tool}\")\n\n if hasattr(self,\"toolBarBox\"): #check this: at the startup we are not yet fully supplied, so nothing to do here\n if self.toolBarBox.toolbar.active_drag == tool:\n self.logger.debug(\"active drag already active\")\n return\n store = self.toolBarBox.toolbar.tools\n self.toolBarBox.toolbar.tools = store[:-1] # write something else so we have a change to force the rebuild\n #now set the active drag\n self.toolBarBox.toolbar.active_drag = tool\n self.toolBarBox.toolbar.tools = store\n\n def set_pan_tool(self,panOnlyX=True):\n self.logger.debug(f\"set x only pan: {panOnlyX}\")\n if hasattr(self,\"toolBarBox\"): #check this: at the startup we are not yet fully supplied, so nothing to do here\n\n store = self.toolBarBox.toolbar.tools\n\n if panOnlyX==True:\n self.wheelZoomTool = WheelZoomTool(dimensions=\"width\")\n self.panTool = PanTool(dimensions=\"width\")\n else:\n self.wheelZoomTool = WheelZoomTool()#dimensions=\"width\")\n self.panTool = PanTool()#dimensions=\"width\")\n\n\n store =[self.wheelZoomTool,self.panTool]+store[2:]\n self.toolBarBox.toolbar.tools = store\n\n def build_second_y_axis(self):\n self.plot.extra_y_ranges = {\"y2\": Range1d(start=0, end=1)}\n self.y2Axis = LinearAxis(y_range_name=\"y2\")\n self.y2Axis.visible = False\n self.plot.add_layout(self.y2Axis, 'right')\n self.y2Axis.visible=False\n #self.plot.circle(list(range(len(new_df['zip']))), new_df['station count'], y_range_name='NumStations', color='blue')\n\n\n def debug_button_2_cb(self):\n\n if 0:\n source = copy.deepcopy(self.debugsource.data)\n\n infi = 1000000\n self.logger.debug(\"debug button cb\")\n basic = date2secs(\"20150214T12:00:00+02:00\")\n times=[]\n ys = []\n for n in range(500):\n tim = basic+n\n times.extend([tim,tim,numpy.nan])\n ys.extend([-infi,infi,numpy.nan])\n times=numpy.asarray(times)*1000\n dic = {\"x\":times,\"y\":ys}\n self.debugsource.data = dic # update\n\n\n if 1:\n self.evs.visible=False\n\n\n\n def debug_button_cb(self):\n\n if 1:\n infi = 1000000\n self.logger.debug(\"debug button cb\")\n basic = date2secs(\"20150214T00:00:00+02:00\")\n times=[]\n ys = []\n for n in range(10000):\n tim = basic+n\n times.extend([tim,tim,numpy.nan])\n ys.extend([-infi,infi,numpy.nan])\n times=numpy.asarray(times)*1000\n self.debugsource = ColumnDataSource({\"x\": times,\"y\":ys})\n self.logger.debug(f\"epoches {times}\")\n\n infinity = 1000000000\n\n self.evs = self.plot.line(x=\"x\",y=\"y\", source=self.debugsource,color=\"red\") # works\n\n if 0:\n basic = date2secs(\"20150214T00:00:00+02:00\")\n ss=[]\n self.logger.debug(\"start span createion\")\n for n in range(5000):\n s= Span(location=(basic+n)*1000, dimension='height', line_color='red', line_width=3)\n ss.append(s)\n self.logger.debug(\"add spans\")\n self.add_renderers(ss)\n self.ss = ss\n self.logger.debug(\"adding done\")\n\n\n\n\n\n\n\n\n\n\n def setup_toolbar(self):\n self.logger.debug(\"set back\")\n self.toolBarBox.toolbar.active_drag = self.debug[\"next\"]\n self.toolBarBox.toolbar.tools = self.debug[\"value\"]\n self.debug = None\n\n\n def box_cb(self,attr,old,new):\n self.debug(\"BOXCB\")\n\n def box_update(self,x1,x2):\n self.boxData.data[\"xs\"]=[x1,x2]\n\n def show_group_on_click_cb(self,attr,old,new):\n # in old, new we get a list of indices which are active\n self.logger.debug(\"show_group_on_click_cb \"+str(attr)+str(old)+str(new))\n turnOn = [self.showGroupLabels[index] for index in (set(new)-set(old))]\n turnOff = [self.showGroupLabels[index] for index in (set(old)-set(new))]\n if \"Background\" in turnOn:\n self.showBackgrounds = True\n self.refresh_backgrounds()\n if \"Background\" in turnOff:\n self.showBackgrounds = False\n self.refresh_backgrounds()\n if \"Annotation\" in turnOn:\n self.show_annotations()\n if \"Annotation\" in turnOff:\n self.hide_annotations()\n if \"Threshold\" in turnOn:\n self.showThresholds = True\n self.show_thresholds()\n if \"Threshold\" in turnOff:\n self.showThresholds = False\n self.hide_thresholds()\n if \"Streaming\" in turnOn:\n self.start_streaming()\n if \"Streaming\" in turnOff:\n self.stop_streaming()\n\n def start_streaming(self):\n self.logger.debug(f\"start_streaming {self.rangeEnd-self.rangeStart}\")\n #get data every second and push it to the graph\n self.streamingInterval = self.rangeEnd-self.rangeStart # this is the currently selected \"zoom\"\n self.streamingUpdateData = None\n self.streamingMode = True\n\n\n def stop_streaming(self):\n self.logger.debug(\"stop streaming\")\n self.streamingMode = False\n\n\n\n def annotation_drop_down_on_change_cb(self,attr,old,new):\n mytag = self.annotationDropDown.value\n self.logger.debug(\"annotation_drop_down_on_change_cb \" + str(mytag))\n self.annotationDropDown.label = \"Annotate: \"+mytag\n self.currentAnnotationTag = mytag\n if \"threshold\" in mytag:\n #we do a a threshold annotation, adjust the tool\n self.boxSelectTool.dimensions = \"height\"\n else:\n self.boxSelectTool.dimensions = \"width\"\n\n\n \"\"\"\n def annotations_radio_group_cb(self,args):\n #called when a selection is done on the radio button for the annoations\n option = self.annotationButtons.active # gives a 0,1 list, get the label now\n # tags = self.server.get_settings()[\"tags\"]\n mytag = self.annotationTags[option]\n self.logger.debug(\"annotations_radio_group_cb \"+str(mytag))\n if \"threshold\" in mytag:\n #we do a a threshold annotation, adjust the tool\n self.boxSelectTool.dimensions = \"height\"\n else:\n self.boxSelectTool.dimensions = \"width\"\n \"\"\"\n\n def testCb(self, attr, old, new):\n self.logger.debug(\"testCB \"+\"attr\"+str(attr)+\"\\n old\"+str(old)+\"\\n new\"+str(new))\n self.logger.debug(\"ACTIVE: \"+str(self.plot.toolbar.active_drag))\n\n def remove_hover(self):\n\n self.hoverTool.renderers=[]\n\n\n self.logger.debug(f\"remove hover\")\n\n #self.remove_hover_2()\n #self.__dispatch_function(self.remove_hover_2)\n #self.__dispatch_function(self.__make_tooltips)\n #self.__make_tooltips()\n\n def remove_hover_2(self):\n self.logger.debug(f\"remove hover2\")\n\n self.hoverTool.renderers = []\n store = self.toolBarBox.toolbar.tools\n newTools = []\n for entry in self.toolBarBox.toolbar.tools:\n if type(entry) != HoverTool:\n newTools.append(entry)\n self.toolBarBox.toolbar.tools = newTools\n self.hoverTool = None\n\n #self.__make_tooltips()\n\n\n def __make_tooltips(self):\n #make the hover tool\n \"\"\"\n if we create a hover tool, it only appears if we plot a line, we need to hook the hover tool to the figure and the toolbar separately:\n to the figure to get the hover functionality, there we also need to add all renderers to the hover by hand if we create line plots later on\n still haven't found a way to make the hover tool itself visible when we add it to the toolbar; it does appear when we draw a new line,\n if we change edit/del and add lines, (including their renderers, we need to del/add those renderes to the hover tools as well\n\n \"\"\"\n\n #check if lines have changed:\n if self.hoverTool:\n newLines = set([v for k,v in self.lines.items() if not self.server.is_score_variable(k) ]) # only the non-score lines\n newEventLines = set([ v[\"renderer\"] for k,v in self.eventLines.items()])\n newLines.update(newEventLines)\n hoverLines = set(self.hoverTool.renderers)\n if newLines != hoverLines:\n\n self.logger.debug(f\"reset hover tool MUSt UPDATE newLines {newLines}, hoverLines{hoverLines}\")\n self.hoverTool.renderers = []\n store = self.toolBarBox.toolbar.tools\n newTools = []\n for entry in self.toolBarBox.toolbar.tools:\n if type(entry) != HoverTool:\n newTools.append(entry)\n self.toolBarBox.toolbar.tools = newTools\n self.hoverTool = None\n\n if not self.hoverTool or newLines != hoverLines:\n renderers = []\n\n for k, v in self.eventLines.items():\n self.logger.debug(f\"add {k} to hover\")\n renderers.append(v[\"renderer\"])\n\n for k, v in self.lines.items():\n if not self.server.is_score_variable(k):\n self.logger.debug(f\"add line {k} t hover\")\n renderers.append(v)\n\n self.logger.info(f\"number of new hovers {len(renderers)}\")\n #for h in self.annoHovers:\n # #print(f\"add hover {h}\")\n # renderers.append(h)\n\n\n\n\n\n\n if not self.hoverTool:\n #we do this only once\n\n self.logger.info(\"MAKE TOOLTIPS\"+str(self.hoverCounter))\n hover = HoverTool(renderers=renderers) #must apply them here to be able to dynamically change them\n #hover.tooltips = [(\"name\",\"$name\"),(\"time\", \"@__time{%Y-%m-%d %H:%M:%S.%3N}\"),(\"value\",\"@$name{0.000}\")] #show one digit after dot\n #hover.tooltips = [(\"name\", \"$name\"), (\"time\", \"@{__time}{%f}\"),\n # (\"value\", \"@$name{0.000}\")] # show one digit after dot\n\n\n hover.tooltips = [(\"name\", \"$name\"), (\"time\", \"@{x}{%f}\"),\n (\"value\", \"@y{0.000}\")] # show one digit after dot\n if 0:\n mytooltip = \"\"\"\n <script>\n //.bk-tooltip>div:not(:first-child) {display:none;}\n console.log(\"hier hallo\");\n </script>\n \n <b>X: </b> @x <br>\n <b>Y: </b> @y\n \"\"\"\n #hover.tooltips = mytooltip\n\n #hover.formatters={'__time': 'datetime'}\n #custom = \"\"\"var local = moment(value).tz('%s'); return local.format();\"\"\"%self.server.get_settings()[\"timeZone\"]\n custom = \"\"\"var local = moment(value).tz('%s'); return local.format();\"\"\" % self.server.get_settings()[\"timeZone\"]\n #custom2 = \"\"\"var neu;neu = source.data['test'][0]; return String(value);\"\"\"\n #self.testSource = ColumnDataSource({\"test\":[67]*1000})\n #hover.formatters = {'__time': CustomJSHover(code=custom)}\n custom3 = \"\"\" console.log(cb_data);\"\"\"\n hover.formatters = {'x': CustomJSHover(code=custom)}#, 'z':CustomJSHover(args=dict(source=self.testSource),code=custom2)}\n #hover.callback=CustomJS(code=custom3)\n\n if self.server.get_settings()[\"hasHover\"] in ['vline','hline','mouse']:\n hover.mode = self.server.get_settings()[\"hasHover\"]\n hover.mode = \"mouse\"\n hover.line_policy = 'interp'#need this instead of nearest for the event lines: they end in +- infinity, with the \"nearest\", they would show their tooltip hover at the end of their line, outside the visible area\n self.plot.add_tools(hover)\n\n self.hoverTool = hover\n self.toolBarBox.toolbar.tools.append(hover) # apply he hover tool to the toolbar\n\n\n\n\n # we do this every time\n # reapply the renderers to the hover tool\n if 0:\n renderers = []\n self.hoverTool.renderers = []\n renderers = []\n for k, v in self.lines.items():\n\n if not self.server.is_score_variable(k):\n self.logger.debug(f\"add line {k} t hover\")\n renderers.append(v)\n self.hoverTool.renderers = renderers\n\n\n\n def stream_update_backgrounds(self):\n \"\"\" we update the background by following this algo:\n - take the last existing entry in the backgrounds\n - do we have a new one which starts inside the last existing?\n NO: find the\n \"\"\"\n #make current backgrounds from the latest data and check against the existing backgrounds, put those which we need to append\n newBackgrounds = self.make_background_entries(self.streamingUpdateData)\n addBackgrounds = [] # the backgrounds to be created new\n self.logger.debug(\"stream_update_backgrounds\")\n if self.backgrounds == []:\n #we don't have backgrounds yet, make them\n self.hide_backgrounds()\n else:\n # we have backgrounds\n # now see if we have to adjust the last background\n for entry in newBackgrounds:\n if entry[\"start\"] <= self.backgrounds[-1][\"end\"] and entry[\"end\"] > self.backgrounds[-1][\"end\"]:\n # this is the first to show, an overlapping or extending one, we cant' extend the existing easily, so\n # we put the new just right of the old\n addEntry = {\"start\": self.backgrounds[-1][\"end\"], \"end\": entry[\"end\"], \"value\":entry[\"value\"], \"color\": entry[\"color\"]}\n addBackgrounds.append(addEntry)\n if entry[\"start\"] > self.backgrounds[-1][\"end\"] and entry[\"end\"]> self.backgrounds[-1][\"end\"]:\n #these are on the right side of the old ones, just add them\n addBackgrounds.append(entry)\n\n boxes =[]\n\n for back in addBackgrounds:\n name = \"__background\"+str('%8x'%random.randrange(16**8))\n newBack = BoxAnnotation(left=back[\"start\"], right=back[\"end\"],\n fill_color=back[\"color\"],\n fill_alpha=globalBackgroundsAlpha,\n level = globalBackgroundsLevel,\n name=name) # +\"_annotaion\n boxes.append(newBack)\n back[\"rendererName\"]=name\n self.backgrounds.append(back) # put it in the list of backgrounds for later use\n\n self.plot.renderers.extend(boxes)\n\n #remove renderes out of sight\n deleteList = []\n for r in self.plot.renderers:\n if r.name and \"__background\" in r.name:\n #self.logger.debug(f\"check {r.name}, is is {r.right} vs starttime {self.plot.x_range.start}\")\n #this is a background, so let's see if it is out of sight\n if r.right < self.plot.x_range.start:\n #this one can go, we can't see it anymore\n deleteList.append(r.name)\n self.logger.debug(f\"remove background renderes out of sight{deleteList}\")\n if deleteList:\n self.remove_renderers(deleteList=deleteList)\n\n\n #newBackgrounds = self.make_background_entries(self.streamingUpdateData)\n #self.hide_backgrounds()\n #self.show_backgrounds()\n\n\n return\n\n def stream_update_new(self,data):\n \"\"\"\n this is triggered from the \"global.series.stream\" event, we first need to check if there is any id in this\n event which we want\n :return:\n \"\"\"\n\n #check for variable/score update\n if data[\"data\"][\"_eventInfo\"][\"startTime\"] < self.plot.x_range.end / 1000:\n for browsePath in data[\"data\"][\"_eventInfo\"][\"browsePaths\"]:\n if browsePath in self.lines and self.lines[browsePath].visible == True:\n self.refresh_plot()\n break\n\n allEventIds = [v[\"nodeId\"] for k, v in self.eventLines.items()]\n for id in data[\"data\"][\"_eventInfo\"][\"nodeIds\"]:\n if id in allEventIds:\n #must update the events\n self.update_events()\n break\n\n def stream_update_is_relevant(self,data):\n \"\"\"\n this is triggered from the \"global.series.stream\" event,\n we first need to check if it is relevant for us\n event which we want\n :return:\n \"\"\"\n try:\n #first check if we have an event update info, then we pick it\n allEventIds = [v[\"nodeId\"] for k,v in self.eventLines.items()]\n for id in data[\"data\"][\"_eventInfo\"][\"nodeIds\"]:\n if id in allEventIds:\n return True # a currently visible event type is updated\n\n if data[\"data\"][\"_eventInfo\"][\"startTime\"]>self.plot.x_range.end/1000:\n #the update is outside (to the right) of the visible area, so ignore\n return False\n # now check if any of the ids are relevant\n # they can be an line, a score, a background or an event\n for browsePath in data[\"data\"][\"_eventInfo\"][\"browsePaths\"]:\n if browsePath in self.lines and self.lines[browsePath].visible==True:\n return True # a variable or score is updated\n\n except:\n self.log_error()\n return False\n\n\n\n def stream_update(self):\n try:\n self.inStreamUpdate = True # to tell the range_cb that the range adjustment was not from the user\n self.logger.debug(\"stream update\")#+str(self.streamingUpdateData))\n if self.streamingUpdateData:\n if not self.userZoomRunning:\n if not self.streamingUpdateDataInterval == self.streamingInterval:\n #the interval has changed in the meantime due to user pan/zoom, we skip this data, get fresh one\n self.streamingUpdateData = None\n self.inStreamUpdate = False\n self.logger.warning(\"streaming interval has changed\")\n return\n\n self.logger.debug(f\"apply data {self.streamingUpdateData.keys()},\")\n self.update_column_datas(self.streamingUpdateData)\n mini,maxi = self.get_min_max_times(self.streamingUpdateData)\n self.logger.debug(f\"streaming x_range: start {mini} end {maxi}, interv {self.streamingInterval}, {maxi-self.streamingInterval} \")\n self.set_x_axis(maxi-self.streamingInterval,maxi)\n self.adjust_y_axis_limits()\n if self.showBackgrounds:\n self.stream_update_backgrounds()\n\n self.streamingUpdateData = None #the thread can get new data\n else:\n self.logger.info(\"user zoom running, try later\")\n #user is panning, zooming, we should wait and try again later\n self.__dispatch_function(self.stream_update)\n except Exception as ex:\n self.logger.error(f\"stream_update error {ex}\")\n self.inStreamUpdate = False\n self.streamingUpdateData = None\n def __check_observed(self,counter):\n \"\"\"\n this function is periodically called from a threading.thread\n we check if some data if the backend has changed and if we need to do something on change\n \"\"\"\n self.logger.debug(\"enter __check_observed() \"+str(counter))\n try:\n \"\"\"\n #now see what we have to do\n if \"background\" in self.observerStatus:\n #check the background counter for update\n backgroundCounter = self.server.get_values(self.server.get_settings()[\"observer\"][\"observerBackground\"])\n #self.logger.debug(\"background observer Val\"+str(backgroundCounter))\n if self.observerStatus[\"background\"] != None and self.observerStatus[\"background\"] != backgroundCounter:\n #we have a change in the background:\n self.logger.debug(\"observer background changed\")\n self.__dispatch_function(self.refresh_backgrounds)\n self.observerStatus[\"background\"] = backgroundCounter\n if \"variables\" in self.observerStatus:\n variables = self.server.get_selected_variables_sync()\n if self.observerStatus[\"variables\"] != None and self.observerStatus[\"variables\"]!=variables:\n #we have a change in the selected variables\n self.logger.debug(\"variables selection observer changed\"+str(self.observerStatus[\"variables\"] )+\"=>\"+str(variables))\n self.__dispatch_function(self.refresh_plot)\n self.observerStatus[\"variables\"] = variables\n \"\"\"\n #now we also check if we have a legend click which means that we must delete a variable from the selection\n self.logger.debug(\"RENDERERS CHECK --------------------------\")\n deleteList=[]\n for r in self.plot.renderers:\n if r.name and r.name in self.server.get_variables_selected() and r.visible == False:\n #there was a click on the legend to hide the variables\n self.logger.debug(\"=>>>>>>>>>>>>>>>>>DELETE FROM plot:\"+r.name)\n deleteList.append(r.name)\n if deleteList != []:\n #now prepare the new list:\n newVariablesSelected = [var for var in self.server.get_variables_selected() if var not in deleteList]\n self.logger.debug(\"new var list\"+str(newVariablesSelected))\n self.server.set_variables_selected(newVariablesSelected)\n #self.__dispatch_function(self.refresh_plot)\n except Exception as ex:\n self.logger.error(\"problem during __check_observed\"+str(ex)+str(sys.exc_info()[0]))\n\n self.logger.debug(\"leave __check_observed()\")\n\n def reset_all(self):\n \"\"\"\n this is an experimental function that reloads the widget in the frontend\n it should be executed as dispatched\n \"\"\"\n self.logger.debug(\"self.reset_all()\")\n self.server.refresh_settings()\n\n #clear out the figure\n self.hasLegend = False # to make sure the __init_figure makes a new legend\n self.plot.renderers = [] # no more renderers\n #self.data = None #no more data\n self.columnData={}\n self.lines = {} #no more lines\n\n\n\n self.__init_figure()\n #self.__init_observer()\n self.__init_new_observer()\n\n self.curdoc().clear()\n self.curdoc().add_root(self.get_layout())\n\n def __dispatch_function(self,function,arg=None):\n \"\"\"\n queue a function to be executed in the periodic callback from the bokeh app main loop\n this is needed for functions which are triggered from a separate thread but need to be\n executed in the context of the bokeh app loop\n\n Args:\n function: functionpointer to be executed\n \"\"\"\n with self.dispatchLock:\n self.logger.debug(f\"__dispatch_function {function.__name__}, arg: {arg}\")\n self.dispatchList.append({\"function\":function,\"arg\":arg})\n\n\n def is_second_axis(self,name):\n return \".score\" in name\n\n def adjust_y_axis_limits(self):\n \"\"\"\n this function automatically adjusts the limts of the y-axis that the data fits perfectly in the plot window\n \"\"\"\n self.logger.debug(f\"adjust_y_axis_limits self.autoAdjustY:{self.autoAdjustY}\")\n\n if not self.autoAdjustY:\n ## only rescale the box_modifier, this is needed in streaming to keep the left\n # and right limits\n self.box_modifier_rescale() # only rescale the box_modifier, this is needed in streaming to keep the left\n return\n\n lineData = []\n selected = self.server.get_variables_selected()\n for item in self.columnData:\n if item in selected and not self.is_second_axis(item):\n yData = self.columnData[item].data[\"y\"]\n if len(yData) >= 2:\n # the outer left and right are ignored in the scaling to avoid influence of\n # points that are included in the data query and which are far away due to a missin data area\n # if you have small variation of values and then a gap and than a totally different value\n # and that value is part of the query but only one point, the small variations can't be seen\n # now it's possible, this problem was introduced via the \"include borders\" style of the data\n # query to get the connecting lines to the next point OUT of the visible area\n yData=yData[1:-1]\n lineData.extend(yData)\n\n if len(lineData) > 0:\n all_data = numpy.asarray(lineData, dtype=numpy.float)\n dataMin = numpy.nanmin(lineData)\n dataMax = numpy.nanmax(lineData)\n if dataMin==dataMax:\n dataMin -= 1\n dataMax += 1\n # Adjust the Y min and max with 2% border\n yMin = dataMin - (dataMax - dataMin) * 0.02\n yMax = dataMax + (dataMax - dataMin) * 0.02\n self.logger.debug(\"current y axis limits\" + str(yMin)+\" \"+str(yMax))\n\n self.plot.y_range.start = yMin\n self.plot.y_range.end = yMax\n \n self.box_modifier_rescale()\n\n else:\n self.logger.warning(\"not y axix to arrange\")\n\n\n def box_modifier_init(self):\n self.logger.debug(\"box_modifier_init\")\n self.boxModifierWidth = 8\n\n b1 = date2secs(datetime.datetime(2015, 2, 13, 3, tzinfo=pytz.UTC)) * 1000\n b2 = date2secs(datetime.datetime(2015, 2, 13, 4, tzinfo=pytz.UTC)) * 1000\n wid = 20 * 60 * 1000 # 20 min\n self.boxModifierData = ColumnDataSource( {'x': [b1, b2], 'y': [0, 0], 'width': [self.boxModifierWidth, self.boxModifierWidth], 'height': [300, 300] })\n\n self.boxModifierRectHorizontal = self.plot.rect('x', 'y', 'width', 'height', source=self.boxModifierData, width_units=\"screen\",line_width=1,line_dash=\"dotted\",line_color=\"white\",fill_color=\"white\" ) # , height_units=\"screen\")#, height_units=\"screen\")\n self.boxModifierRectVertical = self.plot.rect('x', 'y', 'width', 'height', source=self.boxModifierData, height_units=\"screen\",line_width=1,line_dash=\"dotted\",line_color=\"white\",fill_color=\"white\") # , height_units=\"screen\")#, height_units=\"screen\")\n\n self.boxModifierRectHorizontal.data_source.on_change(\"selected\", self.box_cb)\n self.boxModifierRectVertical.data_source.on_change(\"selected\", self.box_cb)\n\n self.box_modifier_hide()# remove the renderers\n\n def box_modifier_tap(self, x=None, y=None):\n\n self.logger.debug(f\"box_modifier_tap x:{x} y:{y}\")\n candidates = []\n #check if we are inside a visible annotation\n for annoId, anno in self.server.get_annotations().items():\n #self.logger.debug(\"check anno \"+annoName+\" \"+anno[\"type\"])\n candidate = False\n if anno[\"type\"] in [\"time\",\"motif\"]:\n if anno[\"startTime\"]<x and anno[\"endTime\"]>x:\n #we are inside this annotation:\n candidate=True\n elif anno[\"type\"] == \"threshold\":\n if anno[\"min\"] < y and anno[\"max\"] > y:\n candidate = True\n if candidate:\n if self.find_renderer(anno[\"id\"]):\n #we are inside this anno and it is visible,\n candidates.append(annoId)\n if self.boxModifierVisible:\n pass # we rotate activation later\n else:\n self.box_modifier_show(annoId, anno)\n return\n\n if candidates:\n if self.boxModifierAnnotationName in candidates:\n\n candidates.append(candidates[0]) # if wrap around\n next = candidates.index(self.boxModifierAnnotationName)+1\n annoNext = candidates[next]\n #self.logger.debug(f\"candidates, next {annoNext}\")\n self.box_modifier_show(annoNext, self.server.get_annotations()[annoNext])\n return\n else:\n annoId = candidates[0]\n #self.logger.debug(f\"only {annoId}\")\n self.box_modifier_show(annoId,self.server.get_annotations()[annoId])\n return\n\n else:\n\n backgroundSelected = self.background_highlight_show(x,y)\n if backgroundSelected:\n return\n\n\n\n #we are not inside an annotation, we hide the box modifier\n self.box_modifier_hide(auto=True)\n\n def background_highlight_show(self,x,y):\n if self.backgroundHighlightVisible:\n #havent found one\n self.background_highlight_hide()\n\n for r in self.plot.renderers:\n if r.name:\n if r.name.startswith(\"__background\"):\n backStart = r.left\n backEnd = r.right\n if x >= backStart and x <= backEnd:\n #alphaNow = r.fill_alpha\n r.fill_alpha = globalBackgroundsHighlightAlpha#alphaNow + 0.5 * (1 - alphaNow)\n self.logger.debug(\"inside Background!\")\n self.server.set_background_highlight(x,y,backStart,backEnd)\n self.backgroundHighlightVisible = True\n return True\n\n\n\n return False\n\n def background_highlight_hide(self):\n if self.backgroundHighlightVisible:\n self.backgroundHighlightVisible=False\n for r in self.plot.renderers:\n if r.name:\n if r.name.startswith(\"__background\"):\n alphaNow = r.fill_alpha\n if alphaNow != globalBackgroundsAlpha:\n r.fill_alpha = globalBackgroundsAlpha\n self.server.set_background_highlight(0,0,0,0,remove=True)\n return\n\n\n def box_modifier_show(self,annoName,anno):\n \"\"\"\n Args:\n annoName: the key in the annotationlist (=id in the model)\n \"\"\"\n\n self.logger.debug(f\"box_modifier_show {annoName}\")\n\n if self.boxModifierVisible:\n if self.boxModifierAnnotationName == annoName:\n #this one is already visible, we are done\n return False\n else:\n # if another is already visible, we hide it first\n # but we keep the tool active, so don't call box_modifier_hide() here\n self.boxModifierRectVertical.visible = False # hide the renderer\n self.boxModifierRectHorizontal.visible = False # hide the renderer\n\n self.boxModifierAnnotationName = annoName\n #self.server.select_annotation(annoName)\n boxYCenter = float(self.plot.y_range.start + self.plot.y_range.end) / 2\n boxXCenter = float(self.plot.x_range.start + self.plot.x_range.end) / 2\n boxYHeight = (self.plot.y_range.end - self.plot.y_range.start) * 4\n boxXWidth = (self.plot.x_range.end - self.plot.x_range.start) *4\n\n if anno[\"type\"] in [\"time\",\"motif\"]:\n start = anno[\"startTime\"]\n end = anno[\"endTime\"]\n self.boxModifierData.data = {'x': [start, end], 'y': [boxYCenter, boxYCenter], 'width': [self.boxModifierWidth, self.boxModifierWidth], 'height': [boxYHeight, boxYHeight]}\n self.boxModifierRectHorizontal.visible=True\n self.boxModifierOldData = dict(copy.deepcopy(self.boxModifierData.data))\n self.boxModifierVisible = True\n #self.plot.renderers.append(self.boxModifierRectHorizontal)\n self.boxModifierTool.renderers = [self.boxModifierRectHorizontal] # ,self.boxModifierRectVertical]\n\n if anno[\"type\"] == \"threshold\":\n self.boxModifierData.data = {'x': [boxXCenter, boxXCenter], 'y': [anno['min'], anno['max']], 'width': [boxXWidth,boxXWidth], 'height': [self.boxModifierWidth, self.boxModifierWidth]}\n self.boxModifierRectVertical.visible=True\n self.boxModifierOldData = dict(copy.deepcopy(self.boxModifierData.data))\n self.boxModifierVisible = True\n #self.plot.renderers.append(self.boxModifierRectVertical)\n self.boxModifierTool.renderers = [self.boxModifierRectVertical]\n\n self.set_active_drag_tool(self.boxModifierTool)\n self.server.select_annotation(annoName)\n return True\n\n def box_modifier_hide(self,auto = False):\n \"\"\"\n if auto is set, we check if visible before\n \"\"\"\n if auto and not self.boxModifierVisible:\n self.set_active_drag_tool(self.panTool)\n return\n\n self.boxModifierVisible = False\n self.boxModifierRectVertical.visible = False #hide the renderer\n self.boxModifierRectHorizontal.visible = False #hide the renderer\n\n self.set_active_drag_tool(self.panTool) # this is actually pretty slow ~ 500ms\n\n self.server.select_annotation([]) # unselect all\n #also remove the renderer from the renderers\n #self.remove_renderers(renderers=[self.boxModifierRectHorizontal,self.boxModifierRectVertical])\n\n\n\n # this is called when we resize the plot via variable selection, mouse wheel etc\n def box_modifier_rescale(self):\n self.logger.info(f\"box_modifier_rescale self.boxModifierVisible{self.boxModifierVisible}, self.inPan{self.inPan}\")\n #self.logger.debug(f\"box_modifier_rescale self.boxModifierVisible={self.boxModifierVisible}\")\n if self.boxModifierVisible == False:\n return\n\n # also, if we currently move the boxmodifier around per drag and drop,\n # we don't want to touch it here until the user releases\n if self.inPan:\n self.logger.info(\"box_modifier_rescale skipped in pan\")\n return\n\n anno = self.server.get_annotations()[self.boxModifierAnnotationName]\n if anno[\"type\"] in [\"time\",\"motif\"]:\n #adjust the limits to span the rectangles on full view area\n boxYCenter = float((self.plot.y_range.start + self.plot.y_range.end)/2)\n boxYHeight = (self.plot.y_range.end - self.plot.y_range.start)*4\n data = dict(copy.deepcopy(self.boxModifierData.data))\n data['y'] = [boxYCenter, boxYCenter]\n data['height'] = [boxYHeight, boxYHeight]\n self.boxModifierData.data = data\n if anno[\"type\"] == \"threshold\":\n boxXCenter = float((self.plot.x_range.start + self.plot.x_range.end) / 2)\n data = dict(copy.deepcopy(self.boxModifierData.data))\n data['x'] = [boxXCenter, boxXCenter]\n self.boxModifierData.data = data\n\n def adjust_annotation(self,anno):\n if anno[\"type\"]==\"time\":\n if self.find_renderer(anno[\"id\"]):\n if anno[\"rendererType\"] == \"VArea\":\n source = self.renderers[anno[\"id\"]][\"source\"]\n source.patch({'x':[ (0,anno[\"startTime\"]),(1,anno[\"endTime\"]) ]})\n elif anno[\"rendererType\"] == \"VBar\":\n source = self.renderers[anno[\"id\"]][\"source\"]\n start = anno[\"startTime\"]\n end = anno[\"endTime\"]\n source.patch({'x':[(0,start + (end - start) / 2)],'w':[(0,end-start)]})\n else:\n #boxannotation must be recreated\n self.remove_renderers(anno[\"id\"])\n self.draw_annotation(anno,visible=True)\n\n #self.renderers[anno[\"id\"]][\"source\"][\"x\"]=[anno[\"startTime\"],anno[\"endTime\"]]\n\n def box_modifier_modify(self):\n self.logger.debug(f\"box_modifier_modify {self.boxModifierVisible}, now => {self.boxModifierData.data}\")\n if self.boxModifierVisible == False:\n return False\n\n anno = self.server.get_annotations()[self.boxModifierAnnotationName]\n self.logger.debug(f\" box_modifier_modify {anno}\")\n\n\n if anno[\"type\"] in [\"time\",\"motif\"]:\n if self.boxModifierData.data['x'][1] <= self.boxModifierData.data['x'][0]:\n #end before start not possible\n self.logger.warning(\"box_modifier_modify end before start error\")\n return False\n\n # re-center the y axis height to avoid vertical out-shifting\n boxYCenter = float(self.plot.y_range.start + self.plot.y_range.end) / 2\n boxYHeight = (self.plot.y_range.end - self.plot.y_range.start) * 4\n self.boxModifierData.data['y'] = [boxYCenter, boxYCenter]\n self.boxModifierData.data['height'] = [boxYHeight, boxYHeight]\n\n #now modify it:\n # adjust the local value in the timeseries server,\n # correct the visible glyph of the annotation\n # push it back to the model\n\n #may this is just a zoom, so check if start or endtime has changed\n if anno[\"startTime\"] != self.boxModifierData.data['x'][0] or anno[\"endTime\"] != self.boxModifierData.data['x'][1]:\n # sanity check: end not before start\n anno[\"startTime\"] = self.boxModifierData.data['x'][0]\n anno[\"endTime\"] = self.boxModifierData.data['x'][1]\n self.server.adjust_annotation(anno)#wait for observer to notify the real change\n\n\n elif anno[\"type\"] == \"threshold\":\n if self.boxModifierData.data['y'][1] <= self.boxModifierData.data['y'][0]:\n #end before start not possible\n self.logger.warning(\"box_modifier_modify min gt max error\")\n return False\n # sanity check: end not before start\n #now move the box back in\n boxXCenter = float(self.plot.x_range.start + self.plot.x_range.end) / 2\n self.boxModifierData.data['x'] = [boxXCenter, boxXCenter]\n\n #maybe just a zoom\n if anno[\"min\"] != self.boxModifierData.data['y'][0] or anno[\"max\"] != self.boxModifierData.data['y'][1]:\n anno[\"min\"] = self.boxModifierData.data['y'][0]\n anno[\"max\"] = self.boxModifierData.data['y'][1]\n self.server.adjust_annotation(anno)#s(self.boxModifierAnnotationName, anno)\n self.remove_renderers(deleteMatch=anno[\"id\"],deleteFromLocal=True)\n self.draw_threshold(anno)#self.boxModifierAnnotationName,anno['variable'])\n\n\n\n else:\n self.logger.error(f\"we don't support annos of type {anno['type']}\")\n return False\n\n\n\n return True\n\n\n def check_boxes(self):\n if self.inPan:\n self.logger.debug(\"check_boxes skip in pan\")\n return\n\n if self.boxModifierVisible:\n try:\n #self.logger.debug(self.boxData.data)\n #self.logger.debug(self.toolBarBox.toolbar.active_drag)\n\n if len(self.boxModifierData.data[\"x\"]) != 2:\n self.logger.warning(\"box modifier >2: restore\")\n self.boxModifierData.data = copy.deepcopy(self.boxModifierOldData)\n\n\n new = json.dumps(self.boxModifierData.data)\n old = json.dumps(self.boxModifierOldData)\n if old!= new:\n if not self.box_modifier_modify():\n self.logger.warning(\"box modifier invalid, restore\")\n self.boxModifierData.data = dict(copy.deepcopy(self.boxModifierOldData))\n\n\n self.boxModifierOldData = dict(copy.deepcopy(self.boxModifierData.data))\n\n except Exception as ex:\n self.logger.error(f\"check_boxes {ex}\")\n\n\n def periodic_cb(self):\n \"\"\"\n called periodiaclly by the bokeh system\n here, we execute function that modifiy bokeh variables etc via the dispatching list\n this is needed, as modifications to data or parameters in the bokeh objects\n are only possible withing the bokeh thread, not from any other.\n\n attention: make sure this functin does normally not last longer than the periodic call back period, otherwise\n bokeh with not do anything else than this function here\n\n \"\"\"\n #self.logger.debug(\"periodic_cb\")\n if self.inPeriodicCb:\n self.logger.error(\"in periodic cb\")\n return\n self.inPeriodicCb = True\n\n try:\n start = time.time()\n self.check_boxes()\n legendChange = self.__legend_check() # check if a user has deselected a variable\n #try: # we need this, otherwise the inPeriodicCb will not be reset\n\n #self.logger.debug(\"enter periodic_cb\")\n\n executelist=[]\n with self.dispatchLock:\n if self.dispatchList:\n executelist = self.dispatchList.copy()\n self.dispatchList = []\n\n for entry in executelist: # avoid double execution\n fkt = entry[\"function\"]\n arg = entry[\"arg\"]\n self.logger.info(f\"now executing dispatched fkt {fkt.__name__} arg {arg}\")\n if arg:\n fkt(arg) # execute the functions which wait for execution and must be executed from this context\n else:\n fkt()\n\n except Exception as ex: self.logger.error(f\"Error in periodic callback {ex} , {str(traceback.format_exc())}\")\n\n if legendChange or executelist != []:\n self.logger.debug(f\"periodic_cb was {time.time()-start}\")\n\n self.inPeriodicCb = False\n\n def __get_free_color(self,varName = None):\n \"\"\"\n get a currently unused color from the given palette, we need to make this a function, not just a mapping list\n as lines come and go and therefore colors become free again\n\n Returns:\n a free color code\n\n \"\"\"\n\n #try to find the color first:\n if varName:\n currentLinesColors = self.server.get_current_colors()\n if varName in currentLinesColors:\n return currentLinesColors[varName][\"lineColor\"]\n\n #not found, get a new one\n\n usedColors = [self.lines[lin].glyph.line_color for lin in self.lines]\n for color in self.lineColors:\n if color not in usedColors:\n return color\n return \"green\" # as default\n\n\n\n\n def __plot_lines(self,newVars = None):\n \"\"\" plot the currently selected variables as lines, update the legend\n if newVars are given, we only plot them and leave the old\n \"\"\"\n self.logger.debug(\"@__plot_lines\")\n\n if newVars == None:\n #take them all fresh\n newVars = self.server.get_variables_selected()\n\n #first, get fresh data\n settings= self.server.get_settings()\n variables = self.server.get_variables_selected()\n mirr = self.server.get_mirror()\n if \"autoScaleY\" in mirr:\n self.autoAdjustY = mirr[\"autoScaleY\"][\".properties\"][\"value\"]\n\n showMarker = False\n if \"showMarker\" in mirr:\n showMarker = mirr[\"showMarker\"][\".properties\"][\"value\"]\n #self.logger.debug(\"@__plot_lines:from server var selected %s\",str(newVars))\n variablesRequest = variables.copy()\n variablesRequest.append(\"__time\") #make sure we get the time included\n #self.logger.debug(\"@__plot_lines:self.variables, bins \"+str(variablesRequest)+str( settings[\"bins\"]))\n if not self.streamingMode:\n getData = self.server.get_data(variablesRequest,self.rangeStart,self.rangeEnd,settings[\"bins\"]) # for debug\n else:\n # avoid to send a different request between the streaming data requests, this causes \"jagged\" lines\n # still not the perfec solution as zooming out now causes a short empty plot\n getData = self.server.get_data(variablesRequest, -self.streamingInterval, None,\n self.server.get_settings()[\"bins\"]) # for debug\n #self.logger.debug(\"GETDATA:\"+str(getData))\n if not getData:\n self.logger.error(f\"no data received\")\n return\n if self.rangeStart == None:\n mini,maxi = self.get_min_max_times(getData)\n #write it back\n self.rangeStart = mini#getData[\"__time\"][0]\n self.rangeEnd = maxi#getData[\"__time\"][-1]\n self.server.set_x_range(self.rangeStart, self.rangeEnd)\n\n #del getData[\"__time\"]\n #getData[\"__time\"]=[0]*settings[\"bins\"] # dummy for the hover\n\n\n \"\"\"\n if newVars == []:\n #self.data.data = getData # also apply the data to magically update\n for k,v in getData.items():\n if not k.endswith(\"__time\"):\n self.columnData[k].data ={\"y\":v,\"x\":getData[k+\"__time\"]}\n else:\n self.logger.debug(\"new column data source\")\n if self.data is None:\n #first time\n self.data = ColumnDataSource(getData) # this will magically update the plot, we replace all data\n #also new store\n self.columnData = {}\n for k,v in getData.items():\n if not k.endswith(\"__time\"):\n self.columnData[k]=ColumnDataSource({\"y\":v,\"x\":getData[k+\"__time\"]})\n\n else:\n #add more data\n for variable in getData:\n if variable not in self.columnData:#data.data:\n self.columnData[variable]=ColumnDataSource({\"y\":v,\"x\":getData[k+\"__time\"]})\n #self.data.add(getData[variable],name=variable)\n \"\"\"\n self.update_column_datas(getData)\n\n #self.logger.debug(f\"self.columnData {self.columnData}\")\n self.adjust_y_axis_limits()\n #timeNode = \"__time\"\n #now plot var\n for variableName in newVars:\n if variableName.endswith('__time'):\n continue\n color = self.__get_free_color(variableName)\n self.logger.debug(\"new color ist\"+color)\n\n self.logger.debug(f\"plotting line {variableName}, is score: {self.server.is_score_variable(variableName)}\")\n if self.server.is_score_variable(variableName):\n #this is a red circle score varialbe\n self.lines[variableName] = self.plot.circle(x=\"x\", y=\"y\", line_color=\"red\", fill_color=None,\n source=self.columnData[variableName], name=variableName,size=7) # x:\"time\", y:variableName #the legend must havee different name than the source bug\n\n\n\n else:\n if \".score\" in variableName:\n # this is a score 0..1 line\n self.lines[variableName] = self.plot.line(x=\"x\", y=\"y\", color=\"gray\", line_dash=\"dotted\",\n source=self.columnData[variableName], name=variableName, line_width=2,\n y_range_name=\"y2\") # x:\n\n else:\n\n if variableName.endswith(\"_expected\"):\n # this is a special case of a line which we display dotted in the same color as the original one\n # try to find the corresponding variable\n thisLineColor = None\n originalVarName = variableName.split('.')[-1][:-len(\"_expected\")]\n for lineName in self.lines:\n if lineName.split('.')[-1] == originalVarName:\n thisLineColor = self.lines[lineName].glyph.line_color\n break\n if not thisLineColor:\n thisLineColor = color\n self.lines[variableName] = self.plot.line(x=\"x\", y=\"y\", color=thisLineColor,\n source=self.columnData[variableName], name=variableName,\n line_width=2, line_dash=\"dashed\")\n else:\n\n #this is a real line\n #self.debugStore =copy.deepcopy(getData)\n #self.lines[variableName] = self.plot.line(x=variableName+\"__time\", y=variableName, color=color,\n # source=self.data, name=variableName,line_width=2) # x:\"time\", y:variableName #the legend must havee different name than the source bug\n self.lines[variableName] = self.plot.line(x=\"x\", y=\"y\", color=color,source=self.columnData[variableName], name=variableName,line_width=2)\n\n if showMarker:\n markerName = variableName+\"_marker\"\n marker = self.plot.circle(x=\"x\",y=\"y\", line_color=color, fill_color=color,\n source=self.columnData[variableName], name=markerName,size=3) # x:\"time\", y:variableName #the legend must havee different name than the source bug\n #legend only for lines\n self.legendItems[variableName] = LegendItem(label='.'.join(variableName.split('.')[-2:]),\n renderers=[self.lines[variableName]])\n\n #we set the lines and glypsh to no change their behaviour when selections are done, unfortunately, this doesn't work, instead we now explicitly unselect in the columndatasource\n self.lines[variableName].nonselection_glyph = None # autofading of not selected lines/glyphs is suppressed\n self.lines[variableName].selection_glyph = None # self.data.selected = Selection(indices = [])\n\n #self.legendItems[variableName] = LegendItem(label=variableName,renderers=[self.lines[variableName]])\n\n if self.showThresholds:\n self.show_thresholds_of_line(variableName)\n if self.showMotifs:\n self.show_motifs_of_line(variableName)\n\n #compile the new colors\n nowColors = {}\n for variableName,glyph in self.lines.items():\n nowColors[variableName] = {\"lineColor\":glyph.glyph.line_color}\n self.server.update_current_colors(nowColors)\n\n #now make a legend\n #legendItems=[LegendItem(label=var,renderers=[self.lines[var]]) for var in self.lines]\n legendItems = [v for k,v in self.legendItems.items()]\n if not self.hasLegend:\n #at the first time, we create the \"Legend\" object\n self.plot.add_layout(Legend(items=legendItems))\n self.plot.legend.location = \"top_left\"\n self.plot.legend.click_policy = \"hide\"\n self.hasLegend = True\n #check if we need to hide it on start\n mirr = self.server.get_mirror()\n if \"showLegend\" in mirr:\n if mirr[\"showLegend\"][\".properties\"][\"value\"] == False:\n self.plot.legend.visible=False\n else:\n self.plot.legend.items = legendItems #replace them\n\n self.set_x_axis()\n #self.adjust_y_axis_limits()\n\n return getData # so that later executed function don't need to get the data again\n\n def range_cb(self, attribute,old, new):\n \"\"\"\n callback by bokeh system when the scaling have changed (roll the mouse wheel), see bokeh documentation\n \"\"\"\n #we only store the range, and wait for an LOD or PANEnd event to refresh\n #self.logger.debug(f\"range_cb {attribute}\")\n if attribute == \"start\":\n self.rangeStart = new\n if attribute == \"end\":\n self.rangeEnd = new\n if self.streamingMode == True and not self.inStreamUpdate:\n self.userZoomRunning = True\n #print(\"range cb\"+str(attribute),self.rangeStart,self.rangeEnd)\n #self.logger.debug(f\"leaving range_cb with userzoom running {self.userZoomRunning}\")\n\n def get_min_max_times(self,newData):\n mini = 1000*1000*1000*1000*1000\n maxi = 0\n for k,v in newData.items():\n if k.endswith(\"__time\"):\n check=[mini]\n check.extend(v[1:-1])\n mini = min(check)\n check=[maxi]\n check.extend(v[1:-1])\n maxi=max(check)\n return mini,maxi\n\n\n def set_x_axis(self,start=None,end=None):\n if start:\n self.rangeStart = start\n if end:\n self.rangeEnd = end\n self.plot.x_range.start = self.rangeStart\n self.plot.x_range.end = self.rangeEnd\n\n def refresh_plot(self):\n \"\"\"\n # get data from the server and plot the lines\n # if the current zoom is out of range, we will resize it:\n # zoom back to max zoom level shift\n # or shift left /right to the max positions possible\n # if there are new variables, we will rebuild the whole plot\n \"\"\"\n self.logger.debug(\"refresh_plot()\")\n #have the variables changed?\n\n #make the differential analysis: what do we currently show and what are we supposed to show?\n currentLines = [lin for lin in self.lines] #these are the names of the current vars\n backendLines = self.server.get_variables_selected()\n deleteLines = list(set(currentLines)-set(backendLines))\n newLines = list(set(backendLines)-set(currentLines))\n scoreVars = self.server.get_score_variables() # we assume ending in _score\n\n self.logger.debug(\"diffanalysis new\"+str(newLines)+\" del \"+str(deleteLines))\n\n\n # now delete the ones to delete\n\n # automatically add the score to the deletion if a variable has one\n\n \"\"\"\n additionalDeletes = []\n for key in deleteLines:\n if not key in scoreVars:\n #this line is not a score itself\n scoreNodeName = key.split('.')[-1]+'_score' # we assume root.myvariable.var1, then we build var1_score\n #now check\n for lineName in currentLines:\n if scoreNodeName in lineName:\n additionalDeletes.append(lineName)\n deleteLines.extend(additionalDeletes)\n deleteLines=list(set(deleteLines)) # avoid duplicates\n \"\"\"\n\n if deleteLines:\n removeLegendKeys = []\n removeSelfLines = []\n self.plot.legend.items=[] # avoid errors later, we might remove the glyph but the legend needs it\n for key in deleteLines:\n self.lines[key].visible = False\n removeSelfLines.append(key)\n removeLegendKeys.append(key)\n\n #remove the lines\n self.remove_renderers(deleteLines)\n #remove the according thresholds if any\n for lin in deleteLines:\n self.remove_renderers(self.find_thresholds_of_line(lin),deleteFromLocal=True)\n self.remove_renderers(self.find_motifs_of_line(lin),deleteFromLocal=True)\n #marker = self.find_renderer(lin+\"_marker\")\n #if marker:\n # self.remove_renderers(renderers=[marker])\n\n extraDeleteRenderers = self.find_extra_renderers_of_lines(deleteLines)\n for r in extraDeleteRenderers:\n if r.name in self.legendItems:\n #del self.legendItems[r.name]\n removeLegendKeys.append(r.name)\n\n self.remove_renderers(renderers=extraDeleteRenderers,deleteFromLocal=True)# remove scores, expected, markers\n\n #del self.columnData[lin] #delete the ColumnDataSource\n\n\n #rebuild the legend is done at the end of the plot_lines\n for key in removeLegendKeys:\n if key in self.legendItems:\n del self.legendItems[key]\n for key in removeSelfLines: # remove them after the legend remove\n if key in self.lines:\n del self.lines[key]\n\n #also delete the links from the model in the backend\n #put together all deletes\n serverDeletes = deleteLines.copy()\n serverDeletes.extend([r.name for r in extraDeleteRenderers])\n newServerSelection=[lin for lin in backendLines if lin not in serverDeletes]\n self.server.set_variables_selected(newServerSelection)\n\n\n\n\n #create the new ones\n\n #automatically add scores if needed: if the user adds a variable to the tree, we might need to add also the score\n if self.showScores:\n additionalLines=[]\n currentLineEndings = [name.split('.')[-1] for name in currentLines]\n for key in newLines:\n scoreName = key.split('.')[-1]+\"_score\"\n for scoreVar in scoreVars:\n if scoreName in scoreVar:\n #we add this one only if it is not there already\n if scoreName not in currentLineEndings:\n additionalLines.append(scoreVar)\n if additionalLines:\n additionalLines=list(set(additionalLines))# remove duplicates\n self.logger.debug(f\"MUST add scores: {additionalLines}.. in the next event\")\n self.server.add_variables_selected(additionalLines)\n #return # wait for next event\n\n\n data = self.__plot_lines(newLines) # the data contain all visible time series including the background\n #todo: make this differential as well\n if self.server.get_settings()[\"background\"][\"hasBackground\"]:\n self.refresh_backgrounds(data)\n\n if self.server.get_settings()[\"hasHover\"] not in [False,None]:\n self.__make_tooltips() #must be the last in the drawings\n\n def refresh_backgrounds_old(self):\n \"\"\" check if backgrounds must be drawn if not, we just hide them\"\"\"\n self.hide_backgrounds()\n if self.showBackgrounds:\n self.show_backgrounds()\n\n def refresh_backgrounds(self,data = None):\n if self.backgroundHighlightVisible:\n return #don't touch a running selection\n self.background_highlight_hide()\n # we show the new backgrounds first and then delete the old to avoid the short empty time, looks a bit better\n deleteList = []\n for r in self.plot.renderers:\n if r.name:\n if \"__background\" in r.name:\n deleteList.append(r.name)\n if self.showBackgrounds:\n self.show_backgrounds(data = data)\n if deleteList:\n self.remove_renderers(deleteList=deleteList)\n\n\n def var_select_button_cb(self):\n \"\"\"\n UI callback, called when the variable selection button was clicked\n \"\"\"\n #apply the selected vars to the plot and the backend\n currentSelection = self.variablesMultiSelect.value\n #write the changes to the backend\n self.server.set_variables_selected(currentSelection)\n self.refresh_plot()\n\n\n def event_cb(self,event):\n \"\"\"\n the event callback from the UI for any user interaction: zoom, select, annotate etc\n Args:\n event (bokeh event): the event that happened\n \"\"\"\n\n eventType = str(event.__class__.__name__)\n msg = \" \"\n for k in event.__dict__:\n msg += str(k) + \" \" + str(event.__dict__[k]) + \" \"\n self.logger.debug(\"event \" + eventType + msg)\n #print(\"event \" + eventType + msg)\n\n if eventType in [\"PanStart\",\"Pan\"]:\n if self.streamingMode:\n self.userZoomRunning = True # the user is starting with pannin, we old the ui updates during user pan\n self.inPan = True\n\n \"\"\"\n if eventType == \"PanEnd\":\n #self.refresh_plot()\n if self.streamingMode:\n self.userZoomRunning = False # the user is finished with zooming, we can now push data to the UI again\n #self.logger.debug(f\"{self.toolBarBox.toolbar.active_pan}\")\n self.autoAdjustY = False\n self.refresh_plot()\n \"\"\"\n\n #if eventType == \"LODEnd\":\n if eventType in [\"LODEnd\",\"PanEnd\"]:\n self.inPan = False\n if self.streamingMode:\n self.userZoomRunning = False # the user is finished with zooming, we can now push data to the UI again\n # also update the zoom level during streaming\n self.streamingInterval = self.plot.x_range.end - self.plot.x_range.start #.rangeEnd - self.rangeStart\n self.logger.debug(f\"new streaming interval: {self.streamingInterval}\")\n #if self.server.get_settings()[\"autoScaleY\"][\".properties\"][\"value\"] == True\n self.autoAdjustY = self.server.get_mirror()[\"autoScaleY\"][\".properties\"][\"value\"]\n self.server.set_x_range(self.rangeStart,self.rangeEnd)\n self.refresh_plot()\n\n if eventType == \"Reset\":\n self.reset_plot_cb()\n\n if eventType == \"SelectionGeometry\":\n #option = self.annotationButtons.active # gives a 0,1 list, get the label now\n #tags = self.server.get_settings()[\"tags\"]\n #mytag = self.annotationTags[option]\n for k,v in self.columnData.items():\n v.selected =Selection(indices=[]) #not allowed in bokeh 2.01 f\n pass\n\n mytag =self.currentAnnotationTag\n #self.logger.info(\"TAGS\"+str(self.annotationTags)+\" \"+str(option))\n\n #self.data.selected = Selection(indices=[]) # suppress real selection\n if mytag != None:\n self.edit_annotation_cb(event.__dict__[\"geometry\"][\"x0\"],event.__dict__[\"geometry\"][\"x1\"],mytag,event.__dict__[\"geometry\"][\"y0\"],event.__dict__[\"geometry\"][\"y1\"])\n if eventType == \"Tap\":\n #self.logger.debug(f\"TAP {self.annotationsVisible}, {event.__dict__['sx']}\")\n #plot all attributes\n #self.logger.debug(f\"legend {self.plot.legend.width}\")\n self.box_modifier_tap(event.__dict__[\"x\"],event.__dict__[\"y\"] )\n self.logger.debug(f\"TAP done\")\n\n\n self.logger.debug(f\"leave event with user zomm running{self.userZoomRunning}\")\n def reset_plot_cb(self):\n self.logger.debug(\"reset plot\")\n self.rangeStart = None\n self.rangeEnd = None\n self.box_modifier_hide() # reset the selection\n self.refresh_plot()\n\n\n def find_renderer(self,rendererName):\n for r in self.plot.renderers:\n if r.name:\n if r.name == rendererName:\n return r\n return None\n\n def add_renderers(self,addList):\n self.plot.renderers.extend(addList)\n\n def remove_renderers(self,deleteList=[],deleteMatch=\"\",renderers=[],deleteFromLocal = False):\n \"\"\"\n this functions removes renderers (plotted elements from the widget), we find the ones to delete based on their name attribute\n Args:\n deletelist: a list or set of renderer names to be deleted\n deleteMatch(string) a part of the name to be deleted, all renderer that have this string in their names will be removed\n renderers : a list of bokeh renderers to be deleted\n \"\"\"\n\n deletedRenderers = []\n #sanity check:\n with self.renderersLock:\n if self.renderersGarbage:\n self.logger.info(f\"renderers garbage collector {self.renderersGarbage}\")\n renderers.extend(self.renderersGarbage)\n self.renderersGarbage = []\n\n if deleteList == [] and deleteMatch == \"\" and renderers == []:\n return\n #self.logger.debug(f\"remove_renderers(), {deleteList}, {deleteMatch}, {renderers}\")\n\n deleteList = deleteList.copy() # we will modify it\n newRenderers = []\n for r in self.plot.renderers:\n if r in renderers:\n deletedRenderers.append(r)\n continue # we ignore this one and do NOT add it to the renderers, this will hide the object\n if r.name:\n if r.name in deleteList:\n self.logger.debug(f\"remove_renderers {r.name}\")\n deleteList.remove(r.name) # reduce the list to speed up looking later\n deletedRenderers.append(r)\n continue # we ignore this one and do NOT add it to the renderers, this will hide the object\n elif deleteMatch != \"\" and deleteMatch in r.name:\n deletedRenderers.append(r)\n continue # we ignore this one and do NOT add it to the renderers, this will hide the object\n else:\n newRenderers.append(r) # we keep this one, as it doesnt mathc the deletersl\n else:\n newRenderers.append(r) # if we have no name, we can't filter, keep this\n\n self.plot.renderers = newRenderers\n\n if deleteFromLocal:\n #delete this also from the local renderers list:\n delList = []\n for k,v in self.renderers.items():\n if v[\"renderer\"] in deletedRenderers:\n delList.append(k)\n for k in delList:\n del self.renderers[k]\n\n\n def annotation_toggle_click_cb(self,toggleState):\n \"\"\"\n callback from ui for turning on/off the annotations\n Args:\n toggleState (bool): true for set, false for unset\n \"\"\"\n if toggleState:\n self.showAnnotationToggle.label = \"hide Annotations\"\n self.show_annotations()\n else:\n #remove all annotations from plot\n self.showAnnotationToggle.label = \"show Annotations\"\n self.hide_annotations()\n\n def threshold_toggle_click_cb(self,toggleState):\n \"\"\"\n callback from ui for turning on/off the threshold annotations\n Args:\n toggleState (bool): true for set, false for unset\n \"\"\"\n if toggleState:\n self.showThresholdToggle.label = \"hide Thresholds\"\n self.showThresholds = True\n self.show_thresholds()\n else:\n #remove all annotations from plot\n self.showThresholdToggle.label = \"show Thresholds\"\n self.showThresholds = False\n self.hide_thresholds()\n\n def show_thresholds(self):\n \"\"\"\n check which lines are currently shown and show their thresholds as well\n \"\"\"\n #if not self.showThresholds:\n # return\n\n self.showThresholds = True\n\n for annoName,anno in self.server.get_annotations().items():\n #self.logger.debug(\"@show_thresholds \"+annoName+\" \"+anno[\"type\"])\n if anno[\"type\"]==\"threshold\":\n # we only show the annotations where the lines are also there\n self.logger.debug(\"@show_thresholds \"+annoName+\" \"+anno[\"type\"]+\"and the lines are currently\"+str(list(self.lines.keys())))\n if anno[\"variable\"] in self.lines:\n self.draw_threshold(anno)#,anno[\"variable\"])\n\n\n def show_motifs(self):\n self.showMotifs = True\n for annoName,anno in self.server.get_annotations().items():\n #self.logger.debug(\"@show_thresholds \"+annoName+\" \"+anno[\"type\"])\n if anno[\"type\"]==\"motif\":\n # we only show the annotations where the lines are also there\n self.logger.debug(\"@show_motifs \"+annoName+\" \"+anno[\"type\"]+\"and the lines are currently\"+str(list(self.lines.keys())))\n if anno[\"variable\"] in self.lines:\n self.draw_motif(anno)#,anno[\"variable\"])\n\n def hide_motifs(self):\n self.showMotifs = False\n self.box_modifier_hide()\n annotations = self.server.get_annotations()\n timeAnnos = [anno for anno in annotations.keys() if annotations[anno][\"type\"] == \"motif\"]\n self.remove_renderers(deleteList=timeAnnos, deleteFromLocal=True)\n\n\n def hide_thresholds(self):\n \"\"\" hide the current annotatios in the widget of type time\"\"\"\n self.showThresholds=False\n\n self.box_modifier_hide()\n annotations = self.server.get_annotations()\n timeAnnos = [anno for anno in annotations.keys() if annotations[anno][\"type\"]==\"threshold\" ]\n self.remove_renderers(deleteList=timeAnnos,deleteFromLocal=True)\n\n\n\n\n def backgroundbutton_cb(self,toggleState):\n \"\"\"\n event callback function triggered by the UI\n toggleStat(bool): True/False on toggle is set or not\n \"\"\"\n if toggleState:\n self.backgroundbutton.label = \"hide Backgrounds\"\n self.showBackgrounds = True\n self.show_backgrounds(None)\n else:\n self.backgroundbutton.label = \"show Backgrounds\"\n self.hide_backgrounds()\n self.showBackgrounds = False\n\n\n def init_annotations(self):\n # we assume that annotations are part of the model,\n ## get the annotations from the server and build the renderers, plot them if wanted\n ## but only the time annotations, the others are created and destroyed on demand\n #self.visibleAnnotations = set() # a set\n\n self.logger.debug(f\"init_annotations() {len(self.server.get_annotations())} annotations..\")\n\n #now we build all renderers for the time annos and don't show them now\n for annoname, anno in self.server.get_annotations().items():\n if anno[\"type\"] == \"time\":\n self.draw_annotation(anno,False)\n\n self.logger.debug(\"init annotations done\")\n\n\n def init_events(self):\n self.logger.debug(f\"init_events\")\n #create all renderers but don't show them\n visible = self.server.get_mirror()[\"visibleElements\"][\".properties\"][\"value\"]\n if \"events\" in visible and visible[\"events\"]==True:\n self.eventsVisible = True #currently turned on\n self.logger.debug(f\"init_events visible\")\n self.show_all_events()\n else:\n self.logger.debug(\"init events invisible\")\n\n\n def show_all_events(self):\n self.logger.debug(\"show_all_events\")\n data = self.server.get_events()\n self.eventsVisible = True\n if data:\n self.show_events(data)\n\n def init_annotations_old(self):\n \"\"\"\n chreate the actual bokeh objects based on existing annotations, this speeds up the process a lot when show\n ing the annotations later, we will keep the created objecs in the self.annotations list and apply it to\n the renderes later, this will only be used for \"time\" annotations, the others are called thresholds\n \"\"\"\n self.annotations={}\n self.logger.debug(f\"init {len(self.server.get_annotations())} annotations..\")\n for annoname, anno in self.server.get_annotations().items():\n if \"type\" in anno and anno[\"type\"] != \"time\":\n continue # ignore any other type\n self.draw_annotation(annoname,add_layout=False)\n #now we have all bokeh objects in the self.annotations\n self.logger.debug(\"init_annotations.. done\")\n\n def show_annotations(self, annoIdFilter=[]):\n \"\"\"\n show annotations and hide annotations according to their tags (compare with visibleTags\n \"\"\"\n\n self.logger.debug(\"show_annotations()\")\n self.showAnnotations = True\n\n mirror = self.server.fetch_mirror()\n allowedTags = mirror[\"hasAnnotation\"][\"visibleTags\"][\".properties\"][\"value\"]\n self.showAnnotationTags = [tag for tag in allowedTags if allowedTags[tag]]\n self.logger.debug(f\"show annotation tags {self.showAnnotationTags}\")\n\n addList = []\n removeList = []\n\n for k, v in self.renderers.items():\n if annoIdFilter:\n if k not in annoIdFilter:\n continue\n if v[\"info\"][\"type\"] != \"time\":\n continue # only the time annotations\n if not v[\"renderer\"] in self.plot.renderers:\n #this renderer is not yet in the renderers, check if we are allowed to show it\n if any ([True for tag in v[\"info\"][\"tags\"] if tag in self.showAnnotationTags ]):\n addList.append(v[\"renderer\"])\n if v[\"renderer\"] in self.plot.renderers:\n #this renderer is already there, check if we might need to hide it\n if not any([True for tag in v[\"info\"][\"tags\"] if tag in self.showAnnotationTags]):\n removeList.append(v[\"renderer\"])\n # is the box modifier on this currently active?\n # if the currently selected is being hidden, we hide the box modifier\n if self.boxModifierVisible:\n if self.boxModifierAnnotationName == k:\n self.box_modifier_hide()\n\n self.logger.debug(f\"add {len(addList)} annotations to plot\")\n self.plot.renderers.extend(addList)\n self.remove_renderers(renderers=removeList,deleteFromLocal=True) ## xxx new\n\n\n def hide_annotations(self):\n self.showAnnotations = False\n \"\"\" hide the current annotatios in the widget of type time\"\"\"\n annotations = self.server.get_annotations()\n timeAnnos = [anno for anno in annotations.keys() if annotations[anno][\"type\"]==\"time\" ]\n self.logger.debug(\"hide_annotations \"+str(timeAnnos))\n self.remove_renderers(deleteList=timeAnnos)\n #self.annotationsVisible = False\n self.box_modifier_hide()\n\n def get_layout(self):\n \"\"\" return the inner layout, used by the main\"\"\"\n return self.layout\n def set_curdoc(self,curdoc):\n self.curdoc = curdoc\n #curdoc().theme = Theme(json=themes.defaultTheme) # this is to switch the theme\n\n def remove_annotations(self,deleteList):\n \"\"\"\n remove annotation from plot, object list and from the server\n modelPath(list of string): the model path of the annotation, the modelPath-node must contain children startTime, endTime, colors, tags\n \"\"\"\n self.remove_renderers(deleteList=deleteList)\n self.server.delete_annotations(deleteList)\n for anno in deleteList:\n if anno in self.annotations:\n del self.annotations[anno]\n\n\n def draw_motif(self,anno):\n \"\"\" draw the boxannotation for a motif\n Args:\n modelPath(string): the path to the annotation, the modelPath-node must contain children startTime, endTime, colors, tags\n \"\"\"\n self.logger.debug(f\"draw motif {anno}\")\n try:\n #if the box is there already, then we skip\n if anno[\"id\"] in self.renderers:\n self.logger.warning(f\"have this already {anno['id']}\")\n return\n color = self.lines[anno[\"variable\"]].glyph.line_color\n\n start = anno[\"startTime\"]\n end = anno[\"endTime\"]\n\n infinity = 1000000\n # we must use varea, as this is the only one glyph that supports hatches and does not create a blue box when zooming out\n # self.logger.debug(f\"have pattern with hatch {pattern}, tag {tag}, color{color} \")\n\n \"\"\"\n source = ColumnDataSource(dict(x=[start, end], y1=[-infinity, -infinity], y2=[infinity, infinity]))\n area = VArea(x=\"x\", y1=\"y1\", y2=\"y2\",\n fill_color=\"black\",\n name=anno[\"id\"],\n fill_alpha=0.2,\n hatch_color=color,\n hatch_pattern=\"v\",\n hatch_alpha=0.5)\n \n \"\"\"\n # this overcomes the bokeh bug that on super zoom, the hatch pattern of varea disappears:\n # Vbar behaves correctly\n source = ColumnDataSource(dict(x=[start+(end-start)/2], t=[infinity], b=[-infinity],w=[end-start]))\n area = VBar(x=\"x\", top=\"t\", bottom=\"b\", width=\"w\", fill_color=\"black\",\n name=anno[\"id\"],\n fill_alpha=0.2,\n hatch_color=color,\n hatch_pattern=\"v\",\n hatch_alpha=0.5)\n\n\n # bokeh hack to avoid adding the renderers directly: we create a renderer from the glyph and store it for later bulk assing to the plot\n # which is a lot faster than one by one\n myrenderer = GlyphRenderer(data_source=source, glyph=area, name=anno['id'])\n self.add_renderers([myrenderer])\n\n self.renderers[anno[\"id\"]] = {\"renderer\": myrenderer, \"info\": copy.deepcopy(anno),\n \"source\": source} # we keep this renderer to speed up later\n\n except Exception as ex:\n self.logger.error(\"error draw motif\"+str(ex))\n return None\n\n\n def draw_annotation(self, anno, visible=False):\n \"\"\"\n draw one time annotation on the plot\n Args:\n anno: the annotation\n visible: true/false\n \"\"\"\n try:\n #self.logger.debug(f\"draw_annotation {anno['name']} visible {visible}\")\n\n tag = anno[\"tags\"][0]\n mirror = self.server.get_mirror()\n myColors = mirror[\"hasAnnotation\"][\"colors\"][\".properties\"][\"value\"]\n myTags = mirror[\"hasAnnotation\"][\"tags\"][\".properties\"][\"value\"]\n\n try: # to set color and pattern\n if type(myColors) is list:\n tagIndex = myTags.index(tag)\n pattern = None\n color = myColors[tagIndex]\n elif type(myColors) is dict:\n color = myColors[tag][\"color\"]\n pattern = myColors[tag][\"pattern\"]\n if not pattern is None:\n if pattern not in [\" \",\".\",\"o\",\"-\",\"|\",\"+\",\":\",\"@\",\"/\",\"\\\\\",\"x\",\",\",\"`\",\"v\",\">\",\"*\"]:\n pattern = 'x'\n except:\n color = None\n pattern = None\n if not color:\n self.logger.error(\"did not find color for boxannotation\")\n color = \"red\"\n\n start = anno[\"startTime\"]\n end = anno[\"endTime\"]\n\n infinity=1000000\n # we must use varea, as this is the only one glyph that supports hatches and does not create a blue box when zooming out\n #self.logger.debug(f\"have pattern with hatch {pattern}, tag {tag}, color{color} \")\n \n\n if not pattern is None:\n \"\"\"\n source = ColumnDataSource(dict(x=[start, end], y1=[-infinity, -infinity], y2=[infinity, infinity]))\n area = VArea(x=\"x\",y1=\"y1\",y2=\"y2\",\n fill_color=color,\n name=anno[\"id\"],\n fill_alpha=globalAnnotationsAlpha,\n hatch_color=\"black\",\n hatch_pattern=pattern,\n hatch_alpha=1.0)\n rendererType = \"VArea\"\n \"\"\"\n source = ColumnDataSource(dict(x=[start + (end - start) / 2], t=[infinity], b=[-infinity], w=[end - start]))\n area = VBar(x=\"x\", top=\"t\", bottom=\"b\", width=\"w\",\n fill_color=color,\n name=anno[\"id\"],\n fill_alpha=globalAnnotationsAlpha,\n hatch_color=\"black\",\n hatch_pattern=pattern,\n hatch_alpha=1.0)\n \n \n myrenderer = GlyphRenderer(data_source=source, glyph=area, name=anno['id'])\n myrenderer.level = globalThresholdsLevel\n rendererType = \"VBar\"\n else:\n #we use a Boxannotation as this is a lot more efficient in bokeh\n \"\"\" \n area = VArea(x=\"x\", y1=\"y1\", y2=\"y2\",\n fill_color=color,\n name=anno[\"id\"],\n fill_alpha=globalAlpha)\n \"\"\"\n source = None\n\n if any([True for tag in anno[\"tags\"] if \"anomaly\" in tag]):\n #if we have an anomaly to draw, we put it on top\n level = globalThresholdsLevel\n else:\n level = globalAnnotationLevel\n myrenderer = BoxAnnotation(left=start,right=end,fill_color=color,fill_alpha=globalAnnotationsAlpha,name=anno['id'],level=level)\n rendererType = \"BoxAnnotation\"\n\n # bokeh hack to avoid adding the renderers directly: we create a renderer from the glyph and store it for later bulk assing to the plot\n # which is a lot faster than one by one\n\n if 0: #this was a trial for an extra object to hover the annotations\n dic = {\"y\": [0],\n \"x\": [start+(end-start)/20],\n \"w\":[end-start],\n \"h\":[infinity],\n \"l\":[start],\n \"r\":[end-start],\n \"t\":[infinity],\n \"b\":[-infinity],\n \"f\":[0.9]}\n col = ColumnDataSource(dic)\n # the only glyph that worked for hovering was the circle, rect, quad did not work\n #annoHover = self.plot.circle(x=\"x\", y=\"f\",size=15, fill_color=\"white\",fill_alpha=0.5,source=col,name=\"annohover\",y_range_name=\"y2\",line_color=\"white\",line_width=2) #works\n #self.annoHovers.append(annoHover)\n\n if visible:\n self.add_renderers([myrenderer])\n\n self.renderers[anno[\"id\"]] = {\"renderer\": myrenderer, \"info\": copy.deepcopy(anno),\"source\": source,\"rendererType\":rendererType} # we keep this renderer to speed up later\n\n except Exception as ex:\n self.logger.error(f\"error draw annotation {anno}\"+str(ex))\n return None\n\n def hide_all_events(self):\n self.eventsVisible = False\n self.hide_events()\n\n def hide_events(self,keep=[],selectId=None):\n \"\"\"\n hide all events excpect the keep list\n keep: a list of event tags\n selectId: give a nodeid, we only work on the renderes of that node\n \"\"\"\n #hide the ones which are not here\n\n deleteList=[]\n for nodeId,entry in self.eventLines.items():\n if selectId and selectId != nodeId:\n continue# we have a id filter and it did not match\n if entry[\"eventString\"] not in keep:\n deleteList.append(nodeId)\n for id in deleteList:\n self.remove_renderers(renderers=[self.eventLines[id][\"renderer\"]])\n del self.eventLines[id]\n\n def __make_colum_data_for_events(self,times):\n times = numpy.asarray(times)\n times = times * 1000 # in ms for bokeh\n infi = 1000 * 1000\n x = []\n y = []\n for t in times:\n x.extend([t, t, numpy.nan]) #need the nan to avoid connecting diagonals between the vertical lines\n y.extend([-infi, infi, numpy.nan])\n return {\"x\": x, \"y\": y}\n\n def show_events(self,eventsData,redraw=False):\n \"\"\"\n show all currently visible event tags\n\n Args:\n nodeId: the node id\n redraw: if set to true, we delete the lines of a node and redraw them, if not, we keep them\n eventes: a dict containing {\"nodeid\":{\"events\":{\"one\":[t1,t2,t3],\"two\":[t1,t,2,t3]...}},\"nodeid2\":{}\n \"\"\"\n self.eventsVisible = True\n myColors = self.server.get_mirror()[\"hasEvents\"][\"colors\"][\".properties\"][\"value\"]\n visibleEvents = self.server.get_mirror()[\"hasEvents\"][\"visibleEvents\"][\".properties\"][\"value\"]\n visible = [k for k,v in visibleEvents.items() if v == True]\n\n #hide the ones which are not here\n self.hide_events(keep=visible)\n\n deliveredKeys = [] # build a list of all eventLines that we updated with the data\n #now show the ones to show\n for nodeId, eventInfo in eventsData.items():\n if redraw:\n #make sure we delete all lines of this node\n self.hide_events(selectId=nodeId) # delete all lines of this node\n\n for eventString,times in eventInfo[\"events\"].items():\n if eventString not in visible:\n continue\n key = nodeId+\".\"+eventString\n deliveredKeys.append(key) # remember that we got this in the data\n dic = self.__make_colum_data_for_events(times)\n\n if key not in self.eventLines:\n #only draw if it is not there yet\n if eventString in myColors:\n color = myColors[eventString][\"color\"]\n else:\n color = \"yellow\"\n source = ColumnDataSource(dic)\n li = self.plot.line(x=\"x\",y=\"y\", source=source,color=color,line_width=2,name=key)\n self.eventLines[key] = {\"renderer\":li,\"data\":source,\"eventString\":eventString,\"nodeId\":nodeId}\n else:\n #line is there already, update per bokeh data replacement\n self.eventLines[key]['data'].data = dic\n\n #now check the eventLines which have not been in the data delivered, those must be deleted, as the backend has no data for them anymore\n toBeDeleted = set(self.eventLines.keys())-set(deliveredKeys)\n for id in toBeDeleted:\n self.remove_renderers(renderers=[self.eventLines[id][\"renderer\"]])\n del self.eventLines[id]\n\n #now also update the hovers\n self.__make_tooltips()\n\n\n def update_events_old(self,observerEvent):\n \"\"\"\n observerEvent: the event data coming from the observer\n eventData contains [\"<nodeid>\":\"events:[]....} for one node\n \"\"\"\n self.logger.debug(f\"update_evetns {observerEvent}\")\n #simply kill and redraw all events\n self.hide_events()\n self.server.fetch_events()\n self.show_all_events()\n\n def update_events(self,observerEvent=None):\n \"\"\"\n observerEvent: the event data coming from the observer\n eventData contains [\"<nodeid>\":\"events:[]....} for one node\n \"\"\"\n self.logger.debug(f\"update_evetns {observerEvent}\")\n eventsData = self.server.fetch_events()\n\n\n self.show_events(eventsData)\n \"\"\"\n for nodeId, eventInfo in eventsData.items():\n if nodeId!=observerEvent[\"data\"][\"sourceId\"]:\n continue #only the new event series are touched\n #xxx also check if this event is new or update\n for eventString, times in eventInfo[\"events\"].items():\n self.logger.debug(f\"eventlines {self.eventLines.keys()}\")\n #prepare the update data\n key = nodeId + \".\" + eventString\n dic = self.__make_colum_data_for_events(times)\n #update the data\n self.eventLines[key]['data'].data = dic\n\n self.show_all_events()\n \"\"\"\n\n\n\n def find_thresholds_of_line(self,path):\n \"\"\"\n find the hreshold annotations that belong to a line given as model path\n Args:\n path: the path to the variable\n Returns:\n (list of strings of the threshold sannotations that belong to this variable\n \"\"\"\n result = []\n for k,v in self.server.get_annotations().items():\n if v[\"type\"] == \"threshold\":\n if v[\"variable\"] == path:\n result.append(k)\n self.logger.debug(\"@find_thresholds of line returns \"+path+\" => \"+str(result))\n return result\n\n\n\n\n\n def find_motifs_of_line(self,path):\n result = []\n for k,v in self.server.get_annotations().items():\n if v[\"type\"] == \"motif\":\n if v[\"variable\"] == path:\n result.append(k)\n self.logger.debug(\"@find_motifs_of_line of line returns \"+path+\" => \"+str(result))\n return result\n\n def find_extra_renderers_of_lines(self,lines,markers=True,scores=True,expected=True):\n if type(lines) is not list:\n lines = [lines]\n\n extraRenderes = []\n deleteNames = []\n for line in lines:\n name = line.split('.')[-1]\n if scores:\n deleteNames.append(name+\"_score\")\n if expected:\n deleteNames.append(name+\"_expected\")\n if markers:\n deleteNames.append(name + \"_marker\")\n for r in self.plot.renderers:\n if r.name and (r.name.split('.')[-1] in deleteNames):\n extraRenderes.append(r) # take the according score as well\n\n for r in extraRenderes:\n self.logger.debug(f\"remove extra {r.name}\")\n return extraRenderes\n\n def show_motifs_of_line(self,path):\n self.logger.debug(\"@show_motifs_of_line \" + path)\n motifs = self.find_motifs_of_line(path)\n annotations = self.server.get_annotations()\n for motif in motifs:\n self.draw_motif(annotations[motif]) # ,path)\n\n def show_thresholds_of_line(self,path):\n self.logger.debug(\"@show_threasholds_of_line \"+path)\n thresholds = self.find_thresholds_of_line(path)\n annotations = self.server.get_annotations()\n for threshold in thresholds:\n self.draw_threshold(annotations[threshold])#,path)\n\n \"\"\"\n def hide_thresholds_of_line(self,path):\n thresholds = self.find_thresholds_of_line(path)\n self.remove_renderers(deleteList=thresholds,deleteFromLocal=True)\n \"\"\"\n\n def draw_threshold(self, annoDict):#, linePath=None):\n \"\"\" draw the boxannotation for a threshold\n Args:\n modelPath(string): the path to the annotation, the modelPath-node must contain children startTime, endTime, colors, tags\n \"\"\"\n self.logger.debug(f\"draw thresholds {annoDict}\")\n try:\n #if the box is there already, then we skip\n if annoDict[\"id\"] in self.renderers:\n self.logger.warning(f\"have this already {annoDict['id']}\")\n return\n #foundRenderer = self.find_renderer(annoDict[\"id\"])\n #if foundRenderer:\n # #nothing to do\n # return\n\n\n\n #annotations = self.server.get_annotations()\n # now get the first tag, we only use the first\n #tag = annoDict[\"tags\"][0]\n\n\n\n color = self.lines[annoDict[\"variable\"]].glyph.line_color\n\n min = annoDict[\"min\"]\n max = annoDict[\"max\"]\n if min>max:\n max,min = min,max # swap them\n\n # print(\"draw new anno\",color,start,end,modelPath)\n\n newAnno = BoxAnnotation(top=max, bottom=min,\n fill_color=color,\n fill_alpha=globalThresholdsAlpha,\n level = globalThresholdsLevel,\n name=annoDict[\"id\"]) # +\"_annotaion\n\n self.add_renderers([newAnno])\n\n self.renderers[annoDict[\"id\"]] = {\"renderer\": newAnno, \"info\": copy.deepcopy(annoDict)} # we keep this renderer to speed up later\n\n\n except Exception as ex:\n self.logger.error(\"error draw threshold \"+str(annoDict[\"id\"])+str(ex))\n\n\n def draw_threshold2(self, anno,visible=False):\n \"\"\" draw the boxannotation for a threshold\n Args:\n anno\n \"\"\"\n\n try:\n tag = anno[\"tags\"][0]\n\n if linePath:\n color = self.lines[linePath].glyph.line_color\n else:\n color =\"blue\"\n\n min = annotations[modelPath][\"min\"]\n max = annotations[modelPath][\"max\"]\n if min>max:\n max,min = min,max # swap them\n\n # print(\"draw new anno\",color,start,end,modelPath)\n\n newAnno = BoxAnnotation(top=max, bottom=min,\n fill_color=color,\n fill_alpha=globalAlpha,\n name=modelPath) # +\"_annotaion\n\n self.add_renderers([newAnno])\n except Exception as ex:\n self.logger.error(\"error draw threshold \"+str(modelPath)+ \" \"+linePath+\" \"+str(ex))\n\n\n def make_background_entries(self, data, roundValues = True):\n \"\"\"\n create background entries from background colum of a table:\n we iterate through the data and create a list of entries\n {\"start\":startTime,\"end\":time,\"value\":value of the data,\"color\":color from the colormap}\n those entries can directly be used to draw backgrounds\n Args:\n data: dict with {backgroundId: list of data , __time: list of data\n roundValue [bool] if true, we round the values to int, floats are not useful for table lookups\n Returns:\n list of dict entries derived from the data\n \"\"\"\n backGroundNodeId = self.server.get_settings()[\"background\"][\"background\"]\n colorMap = self.server.get_settings()[\"background\"][\"backgroundMap\"]\n\n startTime = None\n backgrounds = []\n defaultColor = \"grey\"\n\n if roundValues:\n # round the values, it is not useful to have float values here, we use the background value\n # for lookup of coloring, so we need int\n #self.logger.debug(f\"before round {data[backGroundNodeId]}\")\n data[backGroundNodeId]=[ round(value) if numpy.isfinite(value) else value for value in data[backGroundNodeId] ]\n #self.logger.debug(f\"after round {data[backGroundNodeId]}\")\n\n\n for value, time in zip(data[backGroundNodeId], data[backGroundNodeId+\"__time\"]):\n # must set the startTime?\n if not startTime:\n if not numpy.isfinite(value):\n continue # can't use inf/nan\n else:\n startTime = time\n currentBackGroundValue = value\n else:\n # now we are inside a region, let's see when it ends\n if value != currentBackGroundValue:\n # a new entry starts, finish the last and add it to the list of background\n try:\n color = colorMap[str(int(currentBackGroundValue))]\n except:\n color = defaultColor\n entry = {\"start\": startTime, \"end\": time, \"value\": currentBackGroundValue, \"color\": color}\n self.logger.debug(\"ENTRY\" + json.dumps(entry))\n backgrounds.append(entry)\n # now check if current value is finite, then we can start\n if numpy.isfinite(value):\n currentBackGroundValue = value\n startTime = time\n else:\n startTime = None # look for the next start\n # now also add the last, if we have one running\n if startTime:\n try:\n color = colorMap[str(int(currentBackGroundValue))]\n except:\n color = defaultColor\n entry = {\"start\": startTime, \"end\": time, \"value\": currentBackGroundValue, \"color\": color}\n backgrounds.append(entry)\n\n return copy.deepcopy(backgrounds)\n\n\n def show_backgrounds(self,data=None):\n \"\"\"\n show the current backgrounds\n Args:\n data(dict): contains a dict holding the nodeid with of the background and the __time as keys and the lists of data\n if te data is not given, we get the backgrounds fresh from the data server\n \"\"\"\n self.showBackgrounds=True\n\n try:\n self.logger.debug(\"show_backgrounds()\")\n backGroundNodeId = self.server.get_settings()[\"background\"][\"background\"]\n\n if not data:\n #we have to pick up the background data first\n self.logger.debug(\"get fresh background data from the model server %s\",backGroundNodeId)\n bins = self.server.get_settings()[\"bins\"]\n getData = self.server.get_data([backGroundNodeId], start=self.rangeStart, end=self.rangeEnd,\n bins=bins) # for debug\n data = getData\n\n #now make the new backgrounds\n backgrounds = self.make_background_entries(data)\n #now we have a list of backgrounds\n self.logger.info(\"have %i background entries\",len(backgrounds))\n #now plot them\n\n boxes =[]\n\n self.backgrounds=[]\n\n for back in backgrounds:\n name = \"__background\"+str('%8x'%random.randrange(16**8))\n newBack = BoxAnnotation(left=back[\"start\"], right=back[\"end\"],\n fill_color=back[\"color\"],\n fill_alpha=globalBackgroundsAlpha,\n level = globalBackgroundsLevel,\n name=name) # +\"_annotaion\n boxes.append(newBack)\n back[\"rendererName\"] = name\n self.backgrounds.append(back) # put it in the list of backgrounds for later look up for streaming\n\n self.plot.renderers.extend(boxes)\n except Exception as ex:\n self.logger.error(f\"problem duringshow_backgrounds {ex} \")\n\n def hide_backgrounds(self):\n self.showBackgrounds = False\n \"\"\" remove all background from the plot \"\"\"\n self.remove_renderers(deleteMatch=\"__background\")\n\n\n def show_scores(self):\n self.logger.debug(\"show_scores()\")\n #adjust the current selected variables that they also contain the scores if they have any\n\n self.showScores=True\n\n additionalScores = [] # the list of score variables that should be displayed\n currentVariables = self.server.get_variables_selected()\n #now check if we need to add some scores\n for scoreVarName in self.server.get_score_variables():\n for var in currentVariables:\n scoreNameEnding = var.split('.')[-1]+\"_score\"\n if scoreNameEnding in scoreVarName:\n #this score should be displayed\n if scoreVarName not in currentVariables:\n additionalScores.append(scoreVarName)\n\n #now we have in additionalScores the missing variables to add\n #write it to the backend and wait for the event to plot them\n if additionalScores !=[]:\n currentVariables.extend(additionalScores)\n self.server.set_variables_selected(currentVariables,updateLocalNow=False)\n\n def hide_scores(self):\n #remove the \"score vars\" from the selected in the backend\n #hide the scores\n self.logger.debug(\"hide_scores()\")\n self.showScores=False\n\n currentVariables = self.server.get_variables_selected()\n scoreVars = self.server.get_score_variables() # we assume ending in _score\n\n newVars = [var for var in currentVariables if var not in scoreVars]\n if newVars != currentVariables:\n self.server.set_variables_selected(newVars)\n\n\n\n\n\n #called when the user dreates/removes annotations\n def edit_annotation_cb(self,start,end,tag,min,max):\n \"\"\"\n call as a callback from the UI when a user adds or removes an annotation\n Args:\n start(float): the start time in epoch ms\n end (float): the end time in epoch ms\n tag (string): the currently selected tag by the UI, for erase there is the \"-erase-\" tag\n \"\"\"\n self.logger.debug(\"edit anno %s %s %s\",str(start),str(end),str(tag))\n if tag == '-erase-':\n #remove all annotations which are inside the time\n deleteList = []\n annotations=self.server.get_annotations()\n for annoPath,annotation in annotations.items():\n if annotation[\"type\"] == \"time\":\n if annotation[\"startTime\"]>start and annotation[\"startTime\"]<end:\n self.logger.debug(\"delete \"+annoPath)\n deleteList.append(annoPath)\n #now hide the boxes\n self.remove_annotations(deleteList)\n elif tag ==\"-erase threshold-\":\n # remove all annotations which are inside the limits are are currently visible\n deleteList = []\n annotations = self.server.get_annotations()\n currentThresholds = [] # the list of threshold annotation currently visible\n for r in self.plot.renderers:\n if r.name in annotations:\n #this annotation is currenlty visible\n if annotations[r.name][\"type\"] == \"threshold\":\n #this annotation is a threshold\n currentThresholds.append(r.name)\n\n #now check if we have to delete it\n deleteList =[]\n for threshold in currentThresholds:\n tMin = annotations[threshold][\"min\"]\n tMax = annotations[threshold][\"max\"]\n if tMin>tMax:\n tMin,tMax = tMax,tMin\n if tMax<=max and tMax>=min: # we check against the top line of the annotation\n #must delete this one\n deleteList.append(threshold)\n # now hide the boxes\n self.logger.debug(f\"deletelist {deleteList}\")\n self.remove_renderers(deleteList=deleteList)\n self.server.delete_annotations(deleteList)\n\n elif tag ==\"motif\":\n variable = self.currentAnnotationVariable\n newAnno = self.server.add_annotation(start,end,tag,type=\"motif\",var=variable)\n self.draw_motif(newAnno)\n\n\n elif \"threshold\" not in tag:\n #create a time annotation one\n\n newAnno= self.server.add_annotation(start,end,tag,type=\"time\")\n #print(\"\\n now draw\"+newAnnotationPath)\n self.draw_annotation(newAnno,visible=True)\n #print(\"\\n draw done\")\n else:\n #create a threshold annotation, but only if ONE variable is currently selected\n variable = None\n if self.currentAnnotationVariable == None: # no variable given from context menu\n variables = self.server.get_variables_selected()\n scoreVariables = self.server.get_score_variables()\n vars=list(set(variables)-set(scoreVariables))\n if len(vars) != 1:\n self.logger.error(\"can't create threshold anno, len(vars\"+str(len(vars)))\n return\n variable = vars[0]\n else:\n variable = self.currentAnnotationVariable\n\n\n newAnnotation = self.server.add_annotation(start,end,tag,type =\"threshold\",min=min,max=max,var = variable )\n #self.currentAnnotationVariable = None\n self.draw_threshold(newAnnotation)# ,vars[0])\n\n def find_score_variable(self,variablePath):\n scoreVariables = self.server.get_score_variables()\n\n\n\n def session_destroyed_cb(self,context):\n # this still doesn't work\n self.id=self.id+\"destroyed\"\n self.logger.debug(f\"SEESION_DETROYED CB {self.id} id{self}\")\n self.server.sse_stop()\n\n\n\n\nif __name__ == '__main__':\n\n ts_server = TimeSeriesWidgetDataServer('http://localhost:6001/',\"root.visualization.widgets.timeseriesOne\")\n t=TimeSeriesWidget(ts_server)\n"
},
{
"alpha_fraction": 0.7831325531005859,
"alphanum_fraction": 0.7831325531005859,
"avg_line_length": 40.5,
"blob_id": "a56c155f12e6e446d78558abfe08835d87fd60b8",
"content_id": "c5441db801f07abb9bc36c4d1548d8ff9e8d9ecd",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 83,
"license_type": "permissive",
"max_line_length": 68,
"num_lines": 2,
"path": "/web/modules/README.md",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "# web/modules\n- put all other open source web frameworks under this /module folder\n"
},
{
"alpha_fraction": 0.7372881174087524,
"alphanum_fraction": 0.7478813529014587,
"avg_line_length": 22.549999237060547,
"blob_id": "ce4b185c274a8b8fb069b95e179b267906bb8c72",
"content_id": "d363878927d9146d35f2bc501f730ce1c22e01e6",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 472,
"license_type": "permissive",
"max_line_length": 76,
"num_lines": 20,
"path": "/bokeh_web/main.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "import sys\nfrom widgets import *\n\nfrom bokeh.themes import Theme\n\ntry:\n modelUrl = sys.argv[1]\n modelPath = sys.argv[2]\nexcept:\n pass\n\nprint(\"modelurl and path\",modelUrl,modelPath,type(modelUrl),type(modelPath))\n\n\nts_server = TimeSeriesWidgetDataServer(str(modelUrl),str(modelPath))\nt = TimeSeriesWidget(ts_server,curdoc)\ncurdoc().add_root(t.get_layout())\n\ncurdoc().add_periodic_callback(t.periodic_cb, 100)\ncurdoc().on_session_destroyed(t.session_destroyed_cb)\n\n"
},
{
"alpha_fraction": 0.5736822485923767,
"alphanum_fraction": 0.5831477642059326,
"avg_line_length": 42.09600067138672,
"blob_id": "2d66dd2076071c2b356b779a761636075c3fa56b",
"content_id": "6283241df05c16facbb1e4258c9f95f4e799ff3b",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5400,
"license_type": "permissive",
"max_line_length": 151,
"num_lines": 125,
"path": "/plugins/alarming.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "#21datalabplugin\nfrom system import __functioncontrolfolder\nimport zeep\nimport json\nfrom utils import str_lim\n\nalarmMessage = {\"name\":\"alarmMessage\",\"type\":\"alarm\",\"children\":[\n {\"name\": \"text\", \"type\":\"variable\",\"value\":\"this is the alarm message text\"},\n {\"name\": \"level\", \"type\":\"variable\",\"value\":\"medium\"},\n {\"name\": \"confirmed\", \"type\":\"variable\",\"value\":False},\n {\"name\": \"startTime\", \"type\": \"variable\", \"value\": \"2020-10-01T08:00:00+02:00\"},\n {\"name\": \"endTime\", \"type\": \"variable\", \"value\": None},\n {\"name\": \"confirmTime\", \"type\": \"variable\", \"value\": \"2020-10-01T18:00:00+02:00\"},\n {\"name\": \"mustEscalate\", \"type\": \"variable\", \"value\": False}\n ]\n}\n\nsendEmailWsdl = {\n \"name\":\"sendEmail\",\n \"type\":\"function\",\n \"functionPointer\":\"alarming.send_email_wsdl\",\n \"autoReload\":True,\n \"children\":[\n {\"name\":\"URL\",\"type\":\"const\",\"value\":\"http://domain:port/sendapp?wsdl\"},\n {\"name\":\"fromAddress\",\"type\":\"variable\",\"value\":\"noreply@domain.com\"},\n {\"name\":\"toAddress\",\"type\":\"variable\",\"value\":\"receiver@domain.com\"},\n {\"name\":\"subject\",\"type\":\"variable\",\"value\":\"alarm email from 21data workbench\"},\n {\"name\":\"body\",\"type\":\"variable\",\"value\":\"this is an automatic mail from the 21data workbench. re-thinking self service analytics\"},\n __functioncontrolfolder\n ]\n}\n\ncheckMails = {\n \"name\": \"checkMails\",\n \"type\": \"function\",\n \"functionPointer\": \"alarming.check_mail_sending\",\n \"autoReload\": True,\n \"children\": [\n {\"name\": \"messages\", \"type\": \"referencer\"},\n {\"name\": \"sendMailFunction\",\"type\":\"referencer\"},\n __functioncontrolfolder\n ]\n\n}\n\n\nalarmFolder = {\n \"name\":\"alarms\",\"type\":\"folder\",\"children\":[\n {\"name\":\"messages\",\"type\":\"folder\"},\n checkMails,\n sendEmailWsdl,\n {\n \"name\": \"emailObserver\",\"type\": \"observer\", \"children\": [\n {\"name\": \"enabled\", \"type\": \"const\", \"value\": True}, # turn on/off the observer\n {\"name\": \"triggerCounter\", \"type\": \"variable\", \"value\": 0}, # increased on each trigger\n {\"name\": \"lastTriggerTime\", \"type\": \"variable\", \"value\": \"\"}, # last datetime when it was triggered\n {\"name\": \"targets\", \"type\": \"referencer\",\"references\":[\"alarms.messages\"]}, # pointing to the nodes observed\n {\"name\": \"properties\", \"type\": \"const\", \"value\": [\"children\",\"value\"]},\n # properties to observe [“children”,“value”, “forwardRefs”]\n {\"name\": \"onTriggerFunction\", \"type\": \"referencer\",\"references\":[\"alarms.checkMails\"]}, # the function(s) to be called when triggering\n {\"name\": \"triggerSourceId\", \"type\": \"variable\"},\n # the sourceId of the node which caused the observer to trigger\n {\"name\": \"hasEvent\", \"type\": \"const\", \"value\": True},\n # set to event string iftrue if we want an event as well\n {\"name\": \"eventString\", \"type\": \"const\", \"value\": \"alarms.update\"}, # the string of the event\n ]\n }\n ]\n}\n#this is executed on load of the library!\n############################################\nalarmFolder[\"children\"][1][\"children\"][0][\"references\"]=[\"alarms.messages\"]\nalarmFolder[\"children\"][1][\"children\"][1][\"references\"]=[\"alarms.sendEmail\"]\n\n\n################################################\ndef send_email_wsdl(functionNode):\n \"\"\"\n send email via wsdl service\n \"\"\"\n logger = functionNode.get_logger()\n logger.info(f\">>>> in send_email_wsdl {functionNode.get_browse_path()}\")\n wsdl = functionNode.get_child(\"URL\").get_value()\n client = zeep.Client(wsdl=wsdl)\n try:\n\n req = {'FromAddress': functionNode.get_child(\"fromAddress\").get_value(),\n 'ToAddresses': functionNode.get_child(\"toAddress\").get_value(),\n 'Subject':functionNode.get_child(\"subject\").get_value(),\n 'Body': functionNode.get_child(\"body\").get_value()}\n logger.info(f\"send email {str_lim(req,200)}\")\n response = client.service.SvcSendMail(**req) #we dont' get any result here\n logger.debug(r\"send mail response {response}\")\n except Exception as ex:\n logger.error(r\"send_email_wsdl problem {ex}\")\n return False\n\n return True\n\n\ndef check_mail_sending(functionNode):\n \"\"\"\n check if we need to send any mail\n \"\"\"\n logger = functionNode.get_logger()\n model = functionNode.get_model()\n logger.info(f\">>>> in check_mail_sending {functionNode.get_browse_path()}\")\n sendMailFunction = functionNode.get_child(\"sendMailFunction\").get_target()\n messages = functionNode.get_child(\"messages\").get_leaves()\n for msg in messages:\n mustSend= msg.get_child(\"mustEscalate\")\n if mustSend and mustSend.get_value()== True:\n #prepare a mail from the message\n body = {child.get_name():child.get_value() for child in msg.get_children()}\n logger.debug(f\"email body {body}\")\n sendMailFunction.get_child(\"body\").set_value(json.dumps(body,indent=4))\n try:\n model.disable_observers()\n mustSend.set_value(False) # flag this message as done\n finally:\n model.enable_observers()\n #now send the email and wait for ready\n sendMailFunction.execute_synchronous()\n\n return True\n\n"
},
{
"alpha_fraction": 0.5984354615211487,
"alphanum_fraction": 0.6005541086196899,
"avg_line_length": 43.456520080566406,
"blob_id": "4d7366b9bdd2588454939a7284bc3e4f27ff6c98",
"content_id": "a5cad3dd974c47898be6f41f2ba023f6d368febb",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6148,
"license_type": "permissive",
"max_line_length": 196,
"num_lines": 138,
"path": "/plugins/system.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "import datetime\nimport time\nimport json\nimport copy\n\n__functioncontrolfolder = {\n \"name\":\"control\",\"type\":\"folder\",\"children\":[\n {\"name\":\"status\",\"type\":\"variable\",\"value\":\"idle\"}, # one of [\"finished\",\"running\"]\n {\"name\":\"progress\",\"type\":\"variable\",\"value\":0}, # a value between 0 and 1 ( for showing progress in the ui\n {\"name\":\"result\",\"type\":\"variable\",\"value\":\"ok\"}, # of [\"ok\",\"error\",\"pending\" or a last error message]\n {\"name\":\"signal\",\"type\":\"variable\",\"value\":\"nosignal\"}, # of [\"nosignal\",\"interrupt\"]\n {\"name\":\"executionCounter\",\"type\":\"variable\",\"value\":0}, # a counter which is increased on each execution of this function\n {\"name\":\"lastExecutionDuration\", \"type\": \"variable\", \"value\": 0}, #in float seconds\n {\"name\":\"lastStartTime\",\"type\":\"variable\",\"value\":\"not yet\"}, # in isoforma-string\n {\"name\":\"executionCounter\",\"type\":\"variable\",\"value\":0}, # increases on each SUCESSFUL completion\n {\"name\":\"executionType\",\"type\":\"const\",\"value\":\"async\"} # one of [\"sync\", \"async\"] sync: is executed on the main server thread, async: in separate thread\n ]\n}\n\n\n\n\n\nperiodicTimer = {\n \"name\":\"periodicTimer\",\n \"type\":\"function\",\n \"functionPointer\":\"system.periodic_timer\", #filename.functionname\n \"autoReload\":False, #set this to true to reload the module on each execution\n \"children\":[\n {\"name\":\"target\",\"type\":\"referencer\"},\n {\"name\":\"periodSeconds\",\"type\":\"const\",\"value\":1},\n {\"name\":\"description\",\"type\":\"const\",\"value\":\"periodic timer\"},\n {\"name\":\"lastTimeout\",\"type\":\"variable\",\"value\":\"not yet\"},\n {\"name\":\"lastDuration\",\"type\":\"variable\",\"value\":\"not yet\"},\n {\"name\":\"executionCounter\",\"type\":\"variable\",\"value\":0},\n __functioncontrolfolder,\n ]\n}\n\ncounter = {\n \"name\":\"counter\",\n \"type\":\"function\",\n \"functionPointer\":\"system.counter_f\", #filename.functionname\n \"autoReload\":False, #set this to true to reload the module on each execution\n \"children\":[\n {\"name\":\"counter\",\"type\":\"variable\"},\n __functioncontrolfolder,\n ]\n}\n\n\nobserver = {\n \"name\":\"observer\",\n \"type\":\"observer\",\n \"children\":[\n {\"name\": \"enabled\", \"type\": \"const\", \"value\": False}, # turn on/off the observer\n {\"name\": \"triggerCounter\",\"type\":\"variable\",\"value\":0}, # increased on each trigger\n {\"name\": \"lastTriggerTime\",\"type\":\"variable\",\"value\":\"\"}, # last datetime when it was triggered\n {\"name\": \"targets\",\"type\":\"referencer\"}, # pointing to the nodes observed\n {\"name\": \"properties\",\"type\":\"const\",\"value\":[\"value\"]}, # properties to observe [“children”,“value”, “forwardRefs”]\n {\"name\": \"onTriggerFunction\",\"type\":\"referencer\"}, # the function(s) to be called when triggering\n {\"name\": \"triggerSourceId\",\"type\":\"variable\"}, # the sourceId of the node which caused the observer to trigger\n {\"name\": \"hasEvent\",\"type\":\"const\",\"value\":False}, # set to event string iftrue if we want an event as well\n {\"name\": \"eventString\",\"type\":\"const\",\"value\":\"observerdefaultevent\"}, # the string of the event\n {\"name\": \"eventData\",\"type\":\"const\",\"value\":{\"text\":\"observer status update\"}} # the value-dict will be part of the SSE event[\"data\"] , the key \"text\": , this will appear on the page,\n ]\n}\n\n\n\n\n\n\n\n\ndef counter_f(functionNode):\n counterNode = functionNode.get_child(\"counter\")\n try:\n val = int(counterNode.get_value())\n except:\n val = 0\n counterNode.set_value(val+1)\n\n\n\ndef periodic_timer(functionNode):\n # this function never ends until we get the signal \"stop\"\n signalNode = functionNode.get_child(\"control\").get_child(\"signal\")\n timeoutNode = functionNode.get_child(\"lastTimeout\")\n durationNode = functionNode.get_child(\"lastDuration\")\n counterNode = functionNode.get_child(\"executionCounter\")\n\n sleep_time = float(functionNode.get_child(\"periodSeconds\").get_value())\n running = True\n while True:\n #execute the functions\n startTime = datetime.datetime.now()\n timeoutNode.set_value(startTime.isoformat())\n for node in functionNode.get_child(\"target\").get_leaves():\n print(\"execute\",node.get_name())\n node.execute()\n durationNode.set_value((datetime.datetime.now()-startTime).total_seconds())\n counterNode.set_value(counterNode.get_value()+1)\n if signalNode.get_value() == \"stop\":\n signalNode.set_value(\"nosignal\")\n break\n time.sleep(sleep_time)\n return True\n\n\n\ndef observer_function(functionNode):\n subjectNodes = functionNode.get_child(\"subject\").get_targets() # this is the subject to watch\n properties = functionNode.get_child(\"properties\").get_value()\n statusNode = functionNode.get_child(\"lastStatus\")\n currentStatus = {}\n for node in subjectNodes:\n nodeStatus = {}\n if \"leaves\" in properties:\n nodeStatus[\"leaves\"]=[child.get_id() for child in node.get_leaves()]\n if \"value\" in properties:\n nodeStatus[\"value\"]=node.get_value()\n if \"children\" in properties:\n nodeStatus[\"children\"] = [child.get_id() for child in node.get_children()]\n currentStatus[node.get_id()]=copy.deepcopy(nodeStatus)\n if statusNode.get_value() == None:\n #this is the first time\n statusNode.set_value(copy.deepcopy(currentStatus))\n else:\n #we must compare\n if json.dumps(statusNode.get_value()) != json.dumps(currentStatus):\n #a change!\n counterNode = functionNode.get_child(\"updateCounter\")\n counterNode.set_value(counterNode.get_value()+1)\n for node in functionNode.get_child(\"onUpdate\").get_leaves():\n node.execute()\n statusNode.set_value(copy.deepcopy(currentStatus))\n return True\n\n"
},
{
"alpha_fraction": 0.752713680267334,
"alphanum_fraction": 0.7686567306518555,
"avg_line_length": 67.53488159179688,
"blob_id": "7b0cfc1ac71f6358a1ea8731e9a29d55e67aec70",
"content_id": "26bc6aab90a65a79c013dc7726191daa95448eac",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 2948,
"license_type": "permissive",
"max_line_length": 195,
"num_lines": 43,
"path": "/README.md",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "# 21datalab\nThis project is an open source initiative for self-service analytics in industrial applications. It focusses on the collaboration between data scientists and expert users/operators. It will cover\n* import and handling of data\n* OPC-UA connectivity\n* data modelling \n* API to implement machine learning\n* microservice architecture\n* interactive graphical widgets for simple self-service analytics\nFurther reading:\n* project website: http://21data.io\n* architecture: https://docs.google.com/document/d/1wRY5CCxqMQUc9PZoYwd0hGqGEIbNxXPm5Qt8GsjM-l8/edit?usp=sharing\n\n# system requirements\nThe framework is prepared to run on edge, desktop or cloud and is a microservice architecure. The core software is based on python 3.6. Currently, only the source-code version is available\n## setup\n* install python 3.6, recommended https://www.anaconda.com/\n* install bokeh 1.3.4 for python (e.g. pip install bokeh==1.3.4), higher versions might work\n* install sseclient for python (e.g. pip install sseclient)\n* prepare the web applications folder, it needs some more packages which are placed under web/modules:\n * web/modules/bootstrap (MIT License): get the latest bootstrap dist https://getbootstrap.com/, place it here directly \n * web/modules/bootstrap-select/ (MIT License):https://developer.snapappointments.com/bootstrap-select/\n * web/modules/bootstrap-navbar-sidebar (MIT License): https://github.com/mladenplavsic/bootstrap-navbar-sidebar\n * web/modules/bootswatch (MIT License): https://github.com/thomaspark/bootswatch\n * web/modules/font-awesome/ (License: https://fontawesome.com/license/free) https://use.fontawesome.com/releases/v5.7.2/fontawesome-free-5.7.2-web.zip\n * web/modules/jquery/ (MIT License) https://jquery.com/download/\n * web/modules/jstree (MIT License) https://www.jstree.com/\n * web/modules/jsree-grid (MIT License) https://github.com/deitch/jstree-grid\n * web/modules/other contains:\n * popper.js (MIT License) https://popper.js.org/\n * web/modules/moment (MIT License) contains \n * moment.min.js https://momentjs.com/\n * moment-timezone-with-data.min.js https://momentjs.com/timezone/\n * web/modules/jQuery-File-Upload (MIT License): (https://github.com/blueimp/jQuery-File-Upload)\n * web/modules/jquery-ui (CC0-1.0 License): https://jqueryui.com/download/\n * web/modules/supercontextmenu-master (licence pending) (https://github.com/pwnedgod/supercontextmenu)\n\n## demo\n* under windows: start the model rest services with \"occupancydemo.bat\" \n* goto http://localhost:6001/index.html\n * you'll find the model tree under the tab model \n * you'll find the time UI under tab pipelines, then select the \"occupancy\" and open, it takes 10 seconds to load the UI\n * demo how to here: https://docs.google.com/document/d/1q7Ph-TBbDy314IkCoWfwP1www-dX2-i9EQaSTRKHtlc/edit?usp=sharing\n * this is how it looks: \n\n"
},
{
"alpha_fraction": 0.571761965751648,
"alphanum_fraction": 0.5740956664085388,
"avg_line_length": 17.933332443237305,
"blob_id": "cd2b20155b0fd8253161f5e18b7bc03489f3e08f",
"content_id": "a350c4a56cad43a326f843fdccc4dc69773c2736",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 857,
"license_type": "permissive",
"max_line_length": 55,
"num_lines": 45,
"path": "/plugins/streaming.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "#21datalabplugin\n\n\nfrom abc import ABC, abstractmethod\nimport utils\n\n\n\nclass Interface(ABC):\n\n @abstractmethod\n def flush(self,data = None):\n pass\n\n @abstractmethod\n def feed(self, data=None):\n pass\n\n @abstractmethod\n def reset(self, data=None):\n pass\n\n\n\nclass Pipeline():\n\n def __init__(self,processors=[]):\n self.processors=processors # these are Nodes()!\n\n def reset(self,data=None):\n for p in self.processors:\n p.get_object().reset(data)\n\n def feed(self,data):\n pro = utils.Profiling(\"pipee\")\n for p in self.processors:\n data = p.get_object().feed(data)\n pro.lap(p.get_name())\n print(pro)\n return data\n\n def flush(self,data):\n for p in self.processors:\n data = p.get_object().flush()\n return data\n\n\n\n\n\n"
},
{
"alpha_fraction": 0.6009089350700378,
"alphanum_fraction": 0.6046119928359985,
"avg_line_length": 38.08552551269531,
"blob_id": "2bdf8a16f45eadb4793f5c8456ac627f4e7dd9bc",
"content_id": "7fcbb5de092eed87ca938896e5af449bfa1c427a",
"detected_licenses": [
"MIT",
"LicenseRef-scancode-proprietary-license",
"CC0-1.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5953,
"license_type": "permissive",
"max_line_length": 153,
"num_lines": 152,
"path": "/plugins/importer.py",
"repo_name": "jaschau/21datalab",
"src_encoding": "UTF-8",
"text": "from system import __functioncontrolfolder\nfrom model import date2secs\n# from tqdm import tqdm\nimport logging\nimport pandas as pd \nimport os\nimport json\nimport datetime as dt\nimport time\n\npreviewFileTemplate = {\n \"name\":\"preview_file\",\n \"type\":\"function\",\n \"functionPointer\":\"importer.preview_file\", # filename.functionname\n \"autoReload\":True, # set this to true to reload the module on each execution\n \"children\":[\n {\"name\":\"previewdata\",\"type\":\"variable\"},\n {\"name\":\"filename\",\"type\":\"variable\"},\n __functioncontrolfolder\n ]\n}\n\nimportRunTemplate = {\n \"name\":\"import_run\",\n \"type\":\"function\",\n \"functionPointer\":\"importer.import_run\", # filename.functionname\n \"autoReload\":True, # set this to true to reload the module on each execution\n \"children\":[\n {\"name\":\"tablename\",\"type\":\"variable\"}, # ...\n {\"name\":\"metadata\",\"type\":\"variable\"}, # ...\n __functioncontrolfolder\n ]\n}\n\npipeline = {\n \"name\": \"pipeline\",\n \"type\": \"folder\",\n \"children\": [\n { \"name\": \"imports\", \"type\": \"folder\" },\n { \"name\": \"cockpit\", \"type\": \"const\", \"value\": \"customui/importer/index.htm\" },\n previewFileTemplate,\n { \"name\":\"preview_observer\",\n \"type\": \"observer\", \"children\": [ # observer for the selected variables (not the values)\n {\"name\": \"enabled\", \"type\": \"const\", \"value\": True}, # on by default to enable drag + drop\n {\"name\": \"triggerCounter\", \"type\": \"variable\", \"value\": 0}, # increased on each trigger\n {\"name\": \"lastTriggerTime\", \"type\": \"variable\", \"value\": \"\"}, # last datetime when it was triggered\n {\"name\": \"targets\", \"type\": \"referencer\", \"references\":[\"importer.preview_file.control.executionCounter\"]}, # pointing to the nodes observed\n {\"name\": \"properties\", \"type\": \"const\", \"value\": [\"value\"]}, # properties to observe [“children”,“value”, “forwardRefs”]\n {\"name\": \"onTriggerFunction\", \"type\": \"referencer\"}, # the function(s) to be called when triggering\n {\"name\": \"hasEvent\", \"type\": \"const\", \"value\": True}, # set to true if we want an event as well\n {\"name\": \"eventString\", \"type\": \"const\", \"value\": \"importer.preview_file.data_imported\"} # the string of the event\n ]\n },\n importRunTemplate,\n ]\n}\n\ndef preview_file(iN):\n\n _helper_log(f\"PREVIEW FILE STARTED\")\n\n # --- define vars\n observer = iN.get_parent().get_child(\"preview_observer\")\n event = observer.get_child(\"eventString\")\n parentName = iN.get_parent().get_name()\n event.set_value(f\"{parentName}.preview_file.data_imported\")\n\n # --- set vars\n filename = 'upload/' + iN.get_child(\"filename\").get_value()\n pathBase = os.getcwd()\n\n # --- load csv data\n dataFile = pd.read_csv(filename, nrows=5)\n previewData = dataFile.head()\n previewDataString = previewData.to_json(orient='table')\n\n # --- update node with preview data\n node = iN.get_child(\"previewdata\")\n node.set_value(previewDataString)\n\n _helper_log(f\"PREVIEW FILE FINISHED\")\n\n # --- return\n return True\n\ndef import_run(iN):\n\n _helper_log(f\"IMPORT STARTED\")\n timeStartImport = dt.datetime.now()\n\n # --- define vars\n importerNode = iN.get_parent()\n\n # --- [vars] define\n tablename = iN.get_child(\"tablename\").get_value()\n _helper_log(f\"tablename: {tablename}\")\n\n # # --- create needed nodes\n importerNode.create_child('imports', type=\"folder\")\n importsNode = importerNode.get_child(\"imports\")\n\n # TODO importsNode.get_child(tablename).delete()\n importsNode.create_child(tablename, type=\"table\")\n table = importsNode.get_child(tablename)\n table.create_child('variables', type=\"folder\")\n table.create_child('columns', type=\"referencer\")\n table.create_child('metadata', type=\"const\")\n vars = table.get_child(\"variables\")\n cols = table.get_child(\"columns\")\n\n # --- read metadata and fields\n metadataRaw = iN.get_child(\"metadata\").get_value()\n metadata = json.loads(metadataRaw)\n table.get_child(\"metadata\").set_value(metadata)\n fields = metadata[\"fields\"] \n timefield = int(metadata[\"timefield\"]) - 1\n filename = metadata[\"filename\"]\n headerexists = metadata[\"headerexists\"]\n filepath = 'upload/' + filename \n\n # --- load csv data\n # * https://www.shanelynn.ie/python-pandas-read_csv-load-data-from-csv-files/\n # * [ ] optimize speed? https://stackoverflow.com/questions/16476924/how-to-iterate-over-rows-in-a-dataframe-in-pandas\n # * [ ] vectorize a loop https://stackoverflow.com/questions/27575854/vectorizing-a-function-in-pandas\n df = pd.read_csv(filepath)\n\n # --- define time list\n # * select rows and columns from dataframe https://thispointer.com/select-rows-columns-by-name-or-index-in-dataframe-using-loc-iloc-python-pandas/\n timeList = df.iloc[:,timefield].to_list()\n epochs = [date2secs(time) for time in timeList]\n print(epochs) \n\n # --- import data, set vars and columns\n data = {}\n for field in fields:\n fieldno = int(field[\"no\"]) - 1\n fieldname = field[\"val\"]\n fieldvar = vars.create_child(fieldname, type=\"timeseries\")\n if timefield != fieldno:\n data[fieldname] = df.iloc[ :, fieldno].to_list()\n fieldvar.set_time_series(values=data[fieldname],times=epochs)\n cols.add_references(fieldvar)\n _helper_log(f\"val: {fieldname}\")\n print(fieldvar) \n\n _helper_log(f\"IMPORT DONE (seconds: {(dt.datetime.now()-timeStartImport).seconds})\")\n return True\n\ndef _helper_log(text):\n logging.warning('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')\n logging.warning(text)\n logging.warning('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')\n"
}
] | 10
|
yifengyan/CDN
|
https://github.com/yifengyan/CDN
|
14680e2da27b108f53eba06e4ddb79b5f9788fc1
|
389c6cd5701e1ffb378bd5189df4c400253282fc
|
b9fe0bae9eab573c8d22466e819f4938e44bb9f3
|
refs/heads/master
| 2021-01-13T03:33:58.623934
| 2016-12-25T06:14:03
| 2016-12-25T06:14:03
| 77,312,860
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.723865270614624,
"alphanum_fraction": 0.7642752528190613,
"avg_line_length": 42.769229888916016,
"blob_id": "ce1a5a71ae2640c37e30871328c83d2622d1c799",
"content_id": "e86277b5e277bc45464541f2f3c4696baedaa206",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 3425,
"license_type": "no_license",
"max_line_length": 265,
"num_lines": 78,
"path": "/README.md",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "EC2 Servers:\n\nec2-54-167-4-20.compute-1.amazonaws.com\tOrigin server (running Web server on port 8080)\n\nec2-54-210-1-206.compute-1.amazonaws.com\t\tN. Virginia\n\nec2-54-67-25-76.us-west-1.compute.amazonaws.com\t\tN. California\n\nec2-35-161-203-105.us-west-2.compute.amazonaws.com\tOregon\n\nec2-52-213-13-179.eu-west-1.compute.amazonaws.com\tIreland\n\nec2-52-196-161-198.ap-northeast-1.compute.amazonaws.com\tTokyo\n\nec2-54-255-148-115.ap-southeast-1.compute.amazonaws.com\tSingapore\n\nec2-13-54-30-86.ap-southeast-2.compute.amazonaws.com\tSydney\n\nec2-52-67-177-90.sa-east-1.compute.amazonaws.com\tSao Paolo\n\nec2-35-156-54-135.eu-central-1.compute.amazonaws.com Frankfurta\n\n\n------------------------------------------------------------------------------------\n\nI.\tHigh level approach\n\na.\tDNSSever:\n\nThe DNS Server calculates the distance between client and all the replica servers and gives back the IP address of the nearest replica server with the help of active measurements.\n\n1.\tDnsserver.py: It is the main entrance for the dnsserver, run the DNS server.\n\n2.\tconstructDNS.py: It is used to manage the income packet\n\n3.\tquestionDNS.py: It is used to define the DNS question format\n\n4.\tresponsePacket.py: It is used to deal with response packet\n\n5.\tunpackDNS.py: It is used to unpack the DNS server\n\nb.\tHTTPSever\n\nThe main function of this is to deliver the requested content to the client.\n\n1.\tHttpserver.py: It is the HTTP server which deal with all income request. It will search the information from the cache, if it is not in the cache, it will ask for the origin server and save the information in the cache.\n\nc.\tMapping\n\n1.\tMapping.py: We will compare all replicated servers with client based on their locations. We will use ipinfodb service get their locations through their IP address, then select the nearest replicate server and return its IP address to the client. \n\nII.\tRunning the program:\n\n1.\tRun the deployCDN script – The source code is deployed to the DNS server and HTTP Servers to all replica servers.\n\n2.\tRun the runCDn script – It will run DNS server and all HTTP servers on all replicated servers.\n\n3.\tThe dig command should be run on the client in order to get the IP address. Then we can use wget command to request information from the nearest replicated server which the DNS server replied.\n\n4.\tRun the stopCDN script – To kill all the processes on the DNS and HTTP servers this is used.\n\nIII.\tperformance enhancing techniques\n\n1.\tUse “scp -q” to copy the file into the server which avoid showing too much upload information.\n\n2.\tUse scamper command to watch the latency\n\nCHALLENGES FACED:\n\n1: The understanding of the basic requirements took us a long time especially the DNS part which involves packing and unpacking\n\n2: Choosing active or passive measurement was a tough task for us. The passive measurement were fast but active would give better results for servers that were located far hence we chose for active\n\n3: We faced lot of difficulties to execute the program as whole and to track the flow.\n\n4. Let all servers use the same public key make us confused initially, but we know about the private key and public key now.\n\n5. How to find out the best replicated server is the main challenge for us, we test manually and find the algorithm we used before cannot reply the best replicated server. Then we take a long time to improve our algorithm and now it is much more better than before.\n\n"
},
{
"alpha_fraction": 0.5284697413444519,
"alphanum_fraction": 0.5409252643585205,
"avg_line_length": 27.149999618530273,
"blob_id": "baf137f056237c972b6c534061f6ed4624c2bfb3",
"content_id": "cddcb37070a9a696306ef31281eb4ce552f4b585",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 562,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 20,
"path": "/constructDNS.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import struct,questionDNS\n\n#Manage the income packet\ndef MSG_DCODE_DNS(content):\n HDR_DNS = struct.Struct(\"!6H\")\n D_H=HDR_DNS.unpack_from(content)\n OST = HDR_DNS.size\n CNT_q=D_H[2]\n IDENT=D_H[0] \n sth = questionDNS.QUES_DNS_UPCK(content, OST, CNT_q)\n QUER=sth[0]\n OST=sth[1]\n NAM_D = QUER[0]['domain_name']\n NAM = \"\"\n for moreWord in NAM_D:\n if NAM_D.index(moreWord) == len(NAM_D) - 1:\n NAM = NAM + moreWord\n else:\n NAM = NAM + moreWord + \".\"\n return NAM,IDENT"
},
{
"alpha_fraction": 0.38327527046203613,
"alphanum_fraction": 0.407665491104126,
"avg_line_length": 37.33333206176758,
"blob_id": "73fdb07bf05341be909144f1dd988f74460a87f7",
"content_id": "d5b999530b65f11ebde11406f08db9d924b2ec91",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 574,
"license_type": "no_license",
"max_line_length": 73,
"num_lines": 15,
"path": "/unpackDNS.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import struct\n#Unpack DNS server\ndef UPCK_DNS (content, OST):\n L = []\n while True:\n LEN, = struct.unpack_from(\"!B\", content, OST)\n if (LEN & 192) == 192:\n PTR, = struct.unpack_from(\"!H\", content, OST)\n OST = OST + 2\n return L + UPCK_DNS(content, PTR & 16383), OST\n OST += 1\n if LEN == 0:\n return L, OST\n L.append(*struct.unpack_from(\"!%ds\" % LEN, content, OST))\n OST = OST + LEN"
},
{
"alpha_fraction": 0.4823097586631775,
"alphanum_fraction": 0.6084779500961304,
"avg_line_length": 46.47618865966797,
"blob_id": "ad330e1a4e087992ae7057cb6c39508ebac885e2",
"content_id": "894d1c73ed9cb184736da374e3f8efc77cf1fe8f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2996,
"license_type": "no_license",
"max_line_length": 365,
"num_lines": 63,
"path": "/mapping.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import urllib,math\n\nclass mapping: \n pass \n \n #The algorithm get the distance between two locations\n def getCompare(self,first, second): \n if not first or not second: \n return 0; \n first.longitude = self.eastToWest(first.longitude, -180, 180); \n first.latitude = self.leftToWest(first.latitude, -74, 74); \n second.longitude = self.eastToWest(second.longitude, -180, 180); \n second.latitude = self.leftToWest(second.latitude, -74, 74); \n return self.townDown(self.originInt(first.longitude), self.originInt(second.longitude), self.originInt(first.latitude), self.originInt(second.latitude)) \n \n def leftToWest(self,first, second, third): \n first = max(first,second) \n first = min(first,third) \n return first \n \n def eastToWest(self,first, second, third): \n \n while first > third: \n first -= third - second \n while first < second: \n first += third - second \n return first \n \n def originInt(self,first): \n return math.pi * first / 180 \n \n def townDown(self,first, second, third, forth): \n return 6371000 * math.acos(math.sin(third) * math.sin(forth) + math.cos(third) * math.cos(forth) * math.cos(second - first)) \n\n def returnIP(self,IP_CLNT):\n IP_REP = ['54.210.1.206', '54.67.25.76', '35.161.203.105','52.213.13.179', '52.196.161.198', '54.255.148.115','13.54.30.86', '52.67.177.90', '35-156-54-135']\n POS_REP =['39.043720245361', '-77.487487792969', '37.774929046631', '-122.41941833496', ' 47.585639953613', '-122.297996521', '53.343990325928', '-6.2671899795532', '35.689506530762', '139.69169616699', '1.2896699905396', '103.85006713867', '-33.867851257324', '151.20732116699', '-23.547500610352', '-46.636108398438', '51.606979370117', '13.312430381775']\n DET_REP = urllib.urlopen('http://api.ipinfodb.com/v3/ip-city/?key=6fbe2ea7db25753b423c2952ff787ed99bdccbf8042e244c7f5a7395f5be4120&ip='+IP_CLNT).read()\n SPLT_DET_REP = DET_REP.split(';')\n print SPLT_DET_REP\n localLocation=mapping()\n #Get the client location and every servers locations\n localLocation.latitude=float(SPLT_DET_REP[-3])\n localLocation.longitude=float(SPLT_DET_REP[-2])\n serverLocation=mapping()\n serverLocation.latitude=float(POS_REP[0])\n serverLocation.longitude=float(POS_REP[1])\n Dis=self.getCompare(localLocation, serverLocation)\n minDistanse = Dis\n minnumber=0;\n m=1\n #Compare each distance return the nearest server to the client\n while (m < 9):\n serverLocation.latitude=float(POS_REP[2*m])\n serverLocation.longitude=float(POS_REP[2*m+1])\n Dis=self.getCompare(localLocation, serverLocation)\n print Dis\n if Dis<minDistanse:\n minnumber=m\n minDistanse=Dis\n m += 1 \n print minnumber \n return IP_REP[minnumber] "
},
{
"alpha_fraction": 0.5359042286872864,
"alphanum_fraction": 0.563829779624939,
"avg_line_length": 52.78571319580078,
"blob_id": "a64126410cfe1ea2278ce9ef9db96d41e86ea583",
"content_id": "2b7b82eb837501306f502591e70bd5804f56c729",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 752,
"license_type": "no_license",
"max_line_length": 194,
"num_lines": 14,
"path": "/responsePacket.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import struct\n#Deal with the response packet\ndef PCKT_RES(NAM,IP_REP_FIN,IDENT):\n PCKT = struct.pack(\"!H\", IDENT)+struct.pack(\"!H\", 32768)+struct.pack(\"!H\", 1)+struct.pack(\"!H\", 1)+struct.pack(\"!H\", 0)+struct.pack(\"!H\", 0) \n NAM_SPLT = NAM.split(\".\")\n for m in NAM_SPLT:\n PCKT += struct.pack(\"!B\", len(m))\n for n in bytes(m):\n PCKT += struct.pack(\"!c\", n)\n PCKT += struct.pack(\"!B\", 0)+struct.pack(\"!H\", 1)+struct.pack(\"!H\", 1)+struct.pack(\"!H\",49164)+struct.pack(\"!H\", 1)+struct.pack(\"!H\", 1)+struct.pack(\"!I\", 0)+struct.pack(\"!H\", 4) \n split_final_replica_ip = IP_REP_FIN.split(\".\")\n for ip_piece in split_final_replica_ip:\n PCKT += struct.pack(\"!B\", int(ip_piece))\n return PCKT"
},
{
"alpha_fraction": 0.5798252820968628,
"alphanum_fraction": 0.6711676120758057,
"avg_line_length": 41.482757568359375,
"blob_id": "73f38467225849051707d65112a9aa8b6f5e0e1b",
"content_id": "3532732fefca43c78abac8ee3b653399f88d49dc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 1259,
"license_type": "no_license",
"max_line_length": 140,
"num_lines": 29,
"path": "/runCDN",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\r\nHOSTS=(ec2-54-210-1-206.compute-1.amazonaws.com \r\nec2-54-67-25-76.us-west-1.compute.amazonaws.com \r\nec2-35-161-203-105.us-west-2.compute.amazonaws.com \r\nec2-52-213-13-179.eu-west-1.compute.amazonaws.com \r\nec2-52-196-161-198.ap-northeast-1.compute.amazonaws.com \r\nec2-54-255-148-115.ap-southeast-1.compute.amazonaws.com \r\nec2-13-54-30-86.ap-southeast-2.compute.amazonaws.com \r\nec2-52-67-177-90.sa-east-1.compute.amazonaws.com \r\nec2-35-156-54-135.eu-central-1.compute.amazonaws.com \r\n)\r\n\r\n# The way to run the deployCDN is: ./deployCDN -p <port> -o <origin> -n <name> -u <username> -i <keyfile>\r\n# port is port number, origin is the origin server address or IP, name is domain name, username is student's ID, keyfile is private key file\r\nport=$2\r\norigin=$4\r\nname=$6\r\nusername=$8\r\nkeyfile=${10}\r\n\r\n#Begin the running \r\nssh -i ${keyfile} ${username}@cs5700cdnproject.ccs.neu.edu \"./dnsserver -p $port -n $name < /dev/null > ./logfile 2>&1 &\"\r\necho \"The DNS server is running successfully!\"\r\n# Run HTTP servers in all replicated servers.\r\nfor host in \"${HOSTS[@]}\"\r\ndo\r\n ssh -i ${keyfile} ${username}@${host} \"./httpserver -p $port -o $origin < /dev/null > ./logfile 2>&1 &\"\r\n echo \"HTTP server is running under $host server now!\"\r\ndone"
},
{
"alpha_fraction": 0.7538461685180664,
"alphanum_fraction": 0.763076901435852,
"avg_line_length": 19.375,
"blob_id": "14d6f52a483c553cd5719a2812c02a386adc4028",
"content_id": "fbd065c4b593ab4f075db46ab25d9f4f1dfbf3d0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 325,
"license_type": "no_license",
"max_line_length": 27,
"num_lines": 16,
"path": "/Makefile",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "all:\n\tchmod +x dnsserver\n\tchmod +x httpserver\n\tchmod +x deployCDN\n\tchmod +x runCDN\n\tchmod +x stopCDN\n\tchmod +x constructDNS.py\n\tchmod +x dnsserver.py\n\tchmod +x httpserver.py\n\tchmod +x mapping.py\n\tchmod +x questionDNS.py\n\tchmod +x responsePacket.py\n\tchmod +x unpackDNS.py\n\tdos2unix deployCDN\n\tdos2unix runCDN\n\tdos2unix stopCDN"
},
{
"alpha_fraction": 0.6115471124649048,
"alphanum_fraction": 0.6205157041549683,
"avg_line_length": 32.660377502441406,
"blob_id": "7a89557d590f1483eb33bd62e53d24665d366053",
"content_id": "12ae457e26ca1a31f7b28d32f15397318a069efe",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1784,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 53,
"path": "/httpserver.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import httplib2, BaseHTTPServer, sys\n\nglobal originServerName, localCache, postions\nclass HTTPServerHandler(BaseHTTPServer.BaseHTTPRequestHandler):\n #Save the content in the cache if it is not in the replicated server\n def saveInCache(self,info):\n if len(localCache) == 10:\n position = postions[0]\n localCache.pop(position)\n postions.remove(0)\n localCache[self.path] = info\n \n #Search the content in the Cache\n def searchInCache(self):\n self.do_HEAD()\n info = localCache[self.path]\n self.wfile.write(info)\n \n #If the content is not in the replicated server, get the content from the origin server\n def searchFromOrigin(self):\n self.do_HEAD()\n r=httplib2.Http()\n originPath=\"http://\"+originServerName+\":8080\"+self.path\n sth = r.request(originPath)\n info=sth[1]\n self.wfile.write(info)\n self.saveInCache(info)\n \n #Deal with the Header part of the packet\n def do_HEAD(self):\n self.send_response(200)\n self.send_header(\"Content-type\",\"text/html\")\n self.end_headers()\n \n #Deal with the Get Method of the packet\n def do_GET(self):\n if self.path not in localCache:\n postions.append(self.path)\n if self.path in localCache:\n self.searchInCache()\n else:\n self.searchFromOrigin()\n\nportno = int(sys.argv[2])\noriginServerName = sys.argv[4]\nlocalCache = {}\npostions = []\nlocalHost = BaseHTTPServer.HTTPServer(('', portno), HTTPServerHandler)\ntry:\n localHost.serve_forever()\nexcept KeyboardInterrupt:\n localHost.server_close()\n print \"Please do not type anything during the running!\"\n"
},
{
"alpha_fraction": 0.6424201130867004,
"alphanum_fraction": 0.719918429851532,
"avg_line_length": 51.57143020629883,
"blob_id": "1547ef17e7e55a807bf62c4c6f5c36e68999f28f",
"content_id": "76c3214d793cbaf23b713880e1e82f80f07528df",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 1471,
"license_type": "no_license",
"max_line_length": 140,
"num_lines": 28,
"path": "/deployCDN",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nHOSTS=(ec2-54-210-1-206.compute-1.amazonaws.com \nec2-54-67-25-76.us-west-1.compute.amazonaws.com \nec2-35-161-203-105.us-west-2.compute.amazonaws.com \nec2-52-213-13-179.eu-west-1.compute.amazonaws.com \nec2-52-196-161-198.ap-northeast-1.compute.amazonaws.com \nec2-54-255-148-115.ap-southeast-1.compute.amazonaws.com \nec2-13-54-30-86.ap-southeast-2.compute.amazonaws.com \nec2-52-67-177-90.sa-east-1.compute.amazonaws.com \nec2-35-156-54-135.eu-central-1.compute.amazonaws.com \n)\n# The way to run the deployCDN is: ./deployCDN -p <port> -o <origin> -n <name> -u <username> -i <keyfile>\n# port is port number, origin is the origin server address or IP, name is domain name, username is student's ID, keyfile is private key file\n\nusername=$8\nkeyfile=${10}\n\n# Deploy and copy dnsserver.py and related files into cs5700cdn server\nscp -q -i ${keyfile} dnsserver privatekey dnsserver.py constructDNS.py mapping.py questionDNS.py responsePacket.py unpackDNS.py ${username}@cs5700cdnproject.ccs.neu.edu:~\necho \"DNS server has been deployed successfully!\"\n# Deploy and copy httpserver.py and related files into all replicated servers\nfor host in \"${HOSTS[@]}\"\ndo\n #remove all existed python and scripts file in all servers\n ssh -i ${keyfile} ${username}@${host} \"rm *.py httpserver < /dev/null > ./logfile 2>&1 &\"\n scp -q -i ${keyfile} httpserver httpserver.py ${username}@${host}:~\n echo \"HTTP server has been deployed in $host server successfully!\"\ndone"
},
{
"alpha_fraction": 0.601844072341919,
"alphanum_fraction": 0.6957250833511353,
"avg_line_length": 41.64285659790039,
"blob_id": "e7a770a3e1f81101026eb25206b2586f888e605c",
"content_id": "e2d97978c9cde8bbe870f7b8eb05433796696880",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 1193,
"license_type": "no_license",
"max_line_length": 140,
"num_lines": 28,
"path": "/stopCDN",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nHOSTS=(ec2-54-210-1-206.compute-1.amazonaws.com \nec2-54-67-25-76.us-west-1.compute.amazonaws.com \nec2-35-161-203-105.us-west-2.compute.amazonaws.com \nec2-52-213-13-179.eu-west-1.compute.amazonaws.com \nec2-52-196-161-198.ap-northeast-1.compute.amazonaws.com \nec2-54-255-148-115.ap-southeast-1.compute.amazonaws.com \nec2-13-54-30-86.ap-southeast-2.compute.amazonaws.com \nec2-52-67-177-90.sa-east-1.compute.amazonaws.com \nec2-35-156-54-135.eu-central-1.compute.amazonaws.com \n)\n\n# The way to run the deployCDN is: ./deployCDN -p <port> -o <origin> -n <name> -u <username> -i <keyfile>\n# port is port number, origin is the origin server address or IP, name is domain name, username is student's ID, keyfile is private key file\nusername=$8\nkeyfile=${10}\n\n\n# Try to stop DNS server\nssh -i ${keyfile} ${username}@cs5700cdnproject.ccs.neu.edu \"killall python < /dev/null > ./logfile 2>&1 &\"\necho \"DNS server has stopped already!\"\n\n#Stop all HTTP server running on all replicated servers\nfor host in \"${HOSTS[@]}\"\ndo\n ssh -i ${keyfile} ${username}@${host} \"killall python < /dev/null > ./logfile 2>&1 &\"\n echo \"The HTTP server under $host has been stopped successfully!\"\n done"
},
{
"alpha_fraction": 0.6124301552772522,
"alphanum_fraction": 0.623603343963623,
"avg_line_length": 30.844444274902344,
"blob_id": "3f0fce3d19ce231998214b15f6cb9acef3f60cda",
"content_id": "0659bce168b7c703434bde5f33704cb6964164f4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1432,
"license_type": "no_license",
"max_line_length": 80,
"num_lines": 45,
"path": "/dnsserver.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import socket, sys, constructDNS, responsePacket\nfrom mapping import mapping\n\n# Get the Source IP from the address which is input\ndef getSourceIP():\n soc = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)\n soc.connect((\"google.com\",80))\n return soc.getsockname()[0]\n\n#Receive data from clients \ndef receiveData():\n while True:\n global content, Clint_IP, port_Client, Nam, Ident\n sth = Reciev_Sock.recvfrom(65565)\n content=sth[0].strip()\n IP_ADD=sth[1]\n Clint_IP = IP_ADD[0]\n port_Client = IP_ADD[1]\n if content :\n Nam,Ident = constructDNS.MSG_DCODE_DNS(content)\n break\n\n#Check the validation of the input\nif (len(sys.argv) == 5): \n Prt_Host = int(sys.argv[2])\n DMN_C = sys.argv[4]\nelse:\n print 'Please write the right arguments!'\n sys.exit()\nhost_ip = getSourceIP() \n#Listen packets from clients\nwhile True: \n Reciev_Sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) \n Reciev_Sock.bind((host_ip ,Prt_Host))\n receiveData()\n m=mapping()\n REP_IP_FIN=m.returnIP(Clint_IP)\n if (Nam == DMN_C):\n RES_DNS_PCKT = responsePacket.PCKT_RES(Nam,REP_IP_FIN,Ident)\n print 'Response the packet successfully!'\n soc = Reciev_Sock.sendto(bytes(RES_DNS_PCKT), 0, (Clint_IP,port_Client))\n else:\n print 'Receive the wrong domain'\n exit()\n Reciev_Sock.close()"
},
{
"alpha_fraction": 0.5428571701049805,
"alphanum_fraction": 0.561344563961029,
"avg_line_length": 32.11111068725586,
"blob_id": "f71f949b6eecf0c62ec1eb510c63888cfd91a24e",
"content_id": "d94280ba740cf17b366c5906dc909334a4db5ab8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 595,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 18,
"path": "/questionDNS.py",
"repo_name": "yifengyan/CDN",
"src_encoding": "UTF-8",
"text": "import struct,unpackDNS\n#Define the DNS question format\ndef QUES_DNS_UPCK(content, OST, COUNT_QUES):\n QUERY = []\n FORMT_QUER_DNS = struct.Struct(\"!2H\")\n for i in range(COUNT_QUES):\n sth1 = unpackDNS.UPCK_DNS(content, OST)\n NAM_QUE=sth1[0]\n OST=sth1[1]\n sth2 = FORMT_QUER_DNS.unpack_from(content, OST)\n TYP_Q=sth2[0]\n CLS_Q=sth2[1]\n OST = OST + FORMT_QUER_DNS.size\n QUEST = {\"domain_name\": NAM_QUE,\n \"query_type\": TYP_Q,\n \"query_class\": CLS_Q}\n QUERY.append(QUEST)\n return QUERY, OST"
}
] | 12
|
virtuald/pygephi_graphstreaming
|
https://github.com/virtuald/pygephi_graphstreaming
|
294f4d6e08e5fd9bde04cb41c2c00c780c8b2de7
|
4c3c51b92a84121ba7657eaaa2d1a42250e94a30
|
a851d16588737e0296e1ed16bed71145c2bf717c
|
refs/heads/master
| 2020-12-28T23:05:42.469248
| 2014-04-25T14:55:09
| 2014-04-25T14:55:09
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.622474730014801,
"alphanum_fraction": 0.6287878751754761,
"avg_line_length": 29.461538314819336,
"blob_id": "8738fb85e0fca13a7b5a9dc759feeb1e4b0af4c9",
"content_id": "072da6509c94d101c4a47ec201448ec2b715563f",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 792,
"license_type": "permissive",
"max_line_length": 76,
"num_lines": 26,
"path": "/setup.py",
"repo_name": "virtuald/pygephi_graphstreaming",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nfrom os.path import join, dirname\nfrom distutils.core import setup\n\npackages = [\n 'pygephi'\n]\n\nsetup(name='pygephi',\n version=\"1.0\",\n description='Python scripts that can be used to stream data to gephi',\n long_description=open(join(dirname(__file__), 'README'), 'r').read(),\n author='Andre Panisson',\n author_email='panisson@gmail.com',\n license='Apache 2.0',\n url='https://github.com/panisson/pygephi_graphstreaming',\n packages=packages,\n classifiers=[\n 'Development Status :: 6 - Mature',\n 'Intended Audience :: Developers',\n 'License :: OSI Approved :: Apache Software License',\n 'Topic :: Scientific/Engineering :: Information Analysis',\n 'Topic :: Scientific/Engineering :: Visualization'\n ]\n)\n"
}
] | 1
|
AeroNotix/nesxpp
|
https://github.com/AeroNotix/nesxpp
|
6239ab2ff2d3d55458e701dad320f808bcc34424
|
bb2b1e9057b9269184b1ed8e02b12e322a595564
|
6bb973768fe01c1ad56895ef39e187722bb98b98
|
refs/heads/master
| 2020-04-16T20:08:28.085046
| 2019-01-16T01:22:18
| 2019-01-16T01:22:18
| 165,888,001
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.44629791378974915,
"alphanum_fraction": 0.5238513350486755,
"avg_line_length": 28.973684310913086,
"blob_id": "17958084856db3a67513aa1930bd54b1b279411c",
"content_id": "afb8d936754c6e2b5e650eb8e35c3928621dc66a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3417,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 114,
"path": "/encoder.py",
"repo_name": "AeroNotix/nesxpp",
"src_encoding": "UTF-8",
"text": "# Implementation of https://wiki.nesdev.com/w/index.php/PPU_pattern_tables\n\nimport png\nimport operator\nimport os\n\n# Need to turn the encoded form of:\n\n# [[3, 3, 3, 3, 3, 3, 3, 3],\n# [3, 1, 3, 3, 3, 1, 3, 3],\n# [3, 3, 1, 3, 1, 3, 3, 3],\n# [3, 3, 3, 1, 3, 3, 3, 3],\n# [3, 3, 1, 3, 1, 3, 3, 3],\n# [3, 1, 3, 3, 3, 1, 3, 3],\n# [3, 3, 3, 3, 3, 3, 3, 3],\n# [3, 3, 3, 3, 3, 3, 3, 3]]\n\n# Into:\n\n# [([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 0, 1, 1, 1, 0, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 0, 1, 0, 1, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 1, 1, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 0, 1, 0, 1, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 0, 1, 1, 1, 0, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1]),\n# ([1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1])]\n#\n# And vice versa\n#\n# Where a pixel value of 0 is the background and the remaining\n# numbers are colours in the current palette. Both bitplanes are\n# combined to create the encoded form. We need to separate them back\n# out to create the raw CHR file.\n#\n# The format for both bit planes:\n# Encoded BP0 BP1\n# 0 0 0\n# 1 1 0\n# 2 0 1\n# 3 1 1\n\nNES_BITMAP_DIMENSION = 8\nCHR_BANK_SIZE = 4096\nSPRITES_IN_CHR_BANK = 256\nSINGLE_SPRITE_SIZE = 16\nPNG_SPRITE_WIDTH = 32\nPNG_SPRITE_HEIGHT = 8\n\nclass IncorrectBitmapSize(Exception):\n pass\n\n\nclass IncorrectCHRBankSize(Exception):\n pass\n\n\ndef encode(bitmap):\n if len(bitmap) != SPRITES_IN_CHR_BANK and all(map(lambda row: len(row) == NES_BITMAP_DIMENSION, bitmap)):\n raise IncorrectBitmapSize()\n\n out = []\n\n for row in bitmap:\n bitplane0 = [0] * NES_BITMAP_DIMENSION\n bitplane1 = [0] * NES_BITMAP_DIMENSION\n for idx, colour in enumerate(row):\n if colour == 1:\n bitplane0[idx] = 1\n if colour == 2:\n bitplane1[idx] = 1\n if colour == 3:\n bitplane0[idx] = 1\n bitplane1[idx] = 1\n out.append((bitplane0, bitplane1))\n return out\n\n\ndef encode_to_png(bitmap):\n sprite_rows = [bitmap[x:x+16] for x in xrange(0, len(bitmap), 16)]\n pixels = []\n for sprite_row in sprite_rows:\n for x in range(8):\n row = []\n for sprite in sprite_row:\n row.extend(sprite[x])\n pixels.append(row)\n\n # todo: allow override\n f = open('png.png', 'wb')\n w = png.Writer(len(pixels[0]), len(pixels), greyscale=True, bitdepth=2)\n w.write(f, pixels)\n f.close()\n\n\ndef decode(filepath):\n '''Somewhat facerolled'''\n if os.stat(filepath).st_size != CHR_BANK_SIZE:\n raise IncorrectCHRBankSize()\n out = []\n with open(filepath, 'r') as chr_file:\n for x in range(SPRITES_IN_CHR_BANK):\n encoded_sprite = []\n sprite = chr_file.read(SINGLE_SPRITE_SIZE)\n bitplane0 = sprite[0:8]\n bitplane1 = sprite[8:]\n for idx in range(8):\n bp0 = map(int, list('{0:08b}'.format(ord(bitplane0[idx]))))\n # int(x)*2 so we can simply add the two bitplanes\n # together to get the PPU pattern table version\n bp1 = map(lambda x: int(x)*2, list('{0:08b}'.format(ord(bitplane1[idx]))))\n encoded_sprite.append(map(operator.add, bp0, bp1))\n out.append(encoded_sprite)\n return out\n"
}
] | 1
|
Phylliade/gym-extra
|
https://github.com/Phylliade/gym-extra
|
213f3a8f304511e4aa99d62b301b40131ee06451
|
153f4b72f16c6d93d3991e7bb5a96dfc01007d7e
|
4886b15bd006b855d1ad2ca15ec491d9e1da7283
|
refs/heads/master
| 2021-01-15T10:42:00.282178
| 2017-09-29T12:40:17
| 2017-09-29T12:40:17
| 99,592,594
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7260273694992065,
"alphanum_fraction": 0.7579908967018127,
"avg_line_length": 26.375,
"blob_id": "1f3b9f604eb5accdcaa29ebc5434023c551bee73",
"content_id": "55cc695bbcfa37453a9c02b777b6412bb738d518",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 219,
"license_type": "no_license",
"max_line_length": 74,
"num_lines": 8,
"path": "/gym_extra/__init__.py",
"repo_name": "Phylliade/gym-extra",
"src_encoding": "UTF-8",
"text": "from gym.envs.registration import register\n\nregister(\n id='MountainCarContinuous-v1',\n entry_point='gym_extra.envs.classic_control:ContinuousMountainCarEnv',\n max_episode_steps=999,\n reward_threshold=90.0\n)\n"
},
{
"alpha_fraction": 0.8804348111152649,
"alphanum_fraction": 0.8804348111152649,
"avg_line_length": 91,
"blob_id": "29f9f25a94275c1f2f10d64efb569f447471e29e",
"content_id": "31409eac0fc21659fa87e42ccfa47809315e0bd5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 92,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 1,
"path": "/gym_extra/envs/classic_control/__init__.py",
"repo_name": "Phylliade/gym-extra",
"src_encoding": "UTF-8",
"text": "from gym_extra.envs.classic_control.continuous_mountain_car import ContinuousMountainCarEnv\n"
},
{
"alpha_fraction": 0.7151898741722107,
"alphanum_fraction": 0.7151898741722107,
"avg_line_length": 18.75,
"blob_id": "99ec40bc5fd77e22a4bc800259186b470384633e",
"content_id": "e46c3bb3956800360f19a85c46a642be553ac46e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 158,
"license_type": "no_license",
"max_line_length": 60,
"num_lines": 8,
"path": "/README.md",
"repo_name": "Phylliade/gym-extra",
"src_encoding": "UTF-8",
"text": "# Gymextra\n\nExtra environment for [OpenAI gym](https://gym.openai.com/).\n\n# Installation\n```\npip install git+ssh://git@github.com/Phylliade/gym-extra.git\n```\n"
},
{
"alpha_fraction": 0.717391312122345,
"alphanum_fraction": 0.739130437374115,
"avg_line_length": 45,
"blob_id": "7ad8130f3b8f5c628e2a4af10e407d7610a792b8",
"content_id": "dc4a3fb1d70074fb1797e301c73cccada4884c2d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 138,
"license_type": "no_license",
"max_line_length": 92,
"num_lines": 3,
"path": "/setup.py",
"repo_name": "Phylliade/gym-extra",
"src_encoding": "UTF-8",
"text": "from setuptools import setup, find_packages\n\nsetup(name='gym_extra', version='0.0.1', install_requires=['gym'], packages=find_packages())\n"
}
] | 4
|
medani123/world-map
|
https://github.com/medani123/world-map
|
dd2b709980343c9695d5a61d052a84e4648077cd
|
4e9a0e2d0ad2239a43723c36d77da99ad8e6f50e
|
a81e35c679501f76feddf995d3d5e81e3ef50236
|
refs/heads/master
| 2020-08-10T12:57:27.400841
| 2019-10-11T05:02:35
| 2019-10-11T05:02:35
| 214,347,308
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5986460447311401,
"alphanum_fraction": 0.6528046131134033,
"avg_line_length": 30.3125,
"blob_id": "222459e8f6891e00a4714a0c9399ddfa82e5a936",
"content_id": "84ffbb732bc352d8b9b287bdad815e756ca2d1e7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1034,
"license_type": "no_license",
"max_line_length": 146,
"num_lines": 32,
"path": "/map1.py",
"repo_name": "medani123/world-map",
"src_encoding": "UTF-8",
"text": "import folium\r\nimport pandas\r\n\r\ndata = pandas.read_csv(\"Volcanoes_USA.txt\")\r\nlat = list(data[\"LAT\"])\r\nlon = list(data[\"LON\"])\r\nelev = list(data[\"ELEV\"])\r\n\r\ndef color_change(elevation):\r\n if elevation < 1000:\r\n return \"green\"\r\n elif 1000<= elevation <3000:\r\n return \"orange\"\r\n else:\r\n return \"red\"\r\nmap = folium.Map(location=[38.58, -99.09], zoom_start=6)\r\n\r\nfgv = folium.FeatureGroup(name=\"volcanoes\")\r\n\r\nfor lt ,ln, el in zip(lat, lon, elev):\r\n fgv.add_child(folium.CircleMarker(location=[lt, ln], radius=5, popup=str(el)+\" m\", fill_color=color_change(el), color=\"grey\", fill_opacity=1))\r\n\r\nfgp = folium.FeatureGroup(name=\"population\")\r\n\r\nfgp.add_child(folium.GeoJson(data=open('world.json', 'r', encoding='utf-8-sig').read(),\r\nstyle_function=lambda x: {'fillColor':'green' if x['properties']['POP2005'] < 10000000\r\nelse 'orange' if 10000000 <= x['properties']['POP2005'] < 20000000 else 'red'}))\r\n\r\nmap.add_child(fgv)\r\nmap.add_child(fgp)\r\nmap.add_child(folium.LayerControl())\r\nmap.save(\"map.html\")\r\n"
}
] | 1
|
lipatovdm/askravvin
|
https://github.com/lipatovdm/askravvin
|
61e87ddc9a2d6fe31f30adbcb9607c58a39b625f
|
83a50b3b855085e1dd44e275de77422a7d368257
|
aa6a16bd4a2cbc42feaffe60ea3a8819da950bc3
|
refs/heads/master
| 2022-12-09T08:28:07.176576
| 2017-07-14T05:45:01
| 2017-07-14T05:45:01
| 96,500,448
| 0
| 0
| null | 2017-07-07T04:55:39
| 2017-07-07T05:57:53
| 2022-12-07T23:57:47
|
Python
|
[
{
"alpha_fraction": 0.4986225962638855,
"alphanum_fraction": 0.71074378490448,
"avg_line_length": 15.5,
"blob_id": "ab9718fe91fcabcee64be41973df0fab53d3a0c4",
"content_id": "3a5957ee3b50142c2f4304a4022371530a774851",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 363,
"license_type": "no_license",
"max_line_length": 25,
"num_lines": 22,
"path": "/requirements.txt",
"repo_name": "lipatovdm/askravvin",
"src_encoding": "UTF-8",
"text": "Babel==2.4.0\nbeautifulsoup4==4.6.0\nblinker==1.4\ncertifi==2017.4.17\nchardet==3.0.4\nclick==6.7\ncoverage==4.4.1\nFlask==0.12.2\nFlask-Babel==0.11.2\nFlask-SQLAlchemy==2.2\nFlask-WhooshAlchemy==0.56\ngunicorn==19.7.1\nidna==2.5\nitsdangerous==0.24\nJinja2==2.9.6\nMarkupSafe==1.0\npytz==2017.2\nrequests==2.18.1\nSQLAlchemy==1.1.11\nurllib3==1.21.1\nWerkzeug==0.12.2\nWhoosh==2.7.4\n"
},
{
"alpha_fraction": 0.800000011920929,
"alphanum_fraction": 0.800000011920929,
"avg_line_length": 41.5,
"blob_id": "21a6bf3e3bf11ba92ba703a59d012344305b2c88",
"content_id": "044dd54eeaedc24951ac8febd14b422b4d637e92",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 85,
"license_type": "no_license",
"max_line_length": 73,
"num_lines": 2,
"path": "/README.md",
"repo_name": "lipatovdm/askravvin",
"src_encoding": "UTF-8",
"text": "# askravin\nCompare prices of video-games from official stores, with your own prices.\n"
},
{
"alpha_fraction": 0.6571571826934814,
"alphanum_fraction": 0.6646646857261658,
"avg_line_length": 35,
"blob_id": "ac0fef85fc732b9e0fcdb385711e3da0879cdac3",
"content_id": "a63cfe68d966cfb8023e4df2c2a73b7d074e9371",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3996,
"license_type": "no_license",
"max_line_length": 166,
"num_lines": 111,
"path": "/app/views.py",
"repo_name": "lipatovdm/askravvin",
"src_encoding": "UTF-8",
"text": "from app import app\nimport requests\nfrom flask import request\nfrom bs4 import BeautifulSoup as bs\nimport json\nimport logging\nfrom flask import render_template\n\nlogger = logging.getLogger(__name__)\n\n@app.route('/')\n@app.route('/index')\ndef index():\n\tjson = {\"msg\": \"hello world\"}\n\treturn render_template('index.html', json=json)\n\n@app.route('/api/fetch')\ndef fetch_game():\n\tregion = request.args.get('region')\n\tcurrency = request.args.get('currency')\n\tplatform = request.args.get('platform').upper()\n\tquery = request.args.get('q')\n\tuser_price = float(request.args.get('price'))\n\n\ts = requests.Session()\n\ts.headers.update({\n\t'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.9; rv:45.0) Gecko/20100101 Firefox/45.0'\n\t})\n\n\tuser_input = 'Need For Speed'\n\turl = 'https://psprices.com/region-{region}/search/?q={query}&platform={platform}'.format(region=region,query=query, platform=platform)\n\n\tdef get_currency_rate(val_from, val_to, amount):\n\t\tcurr_url = 'http://www.xe.com/currencyconverter/convert/?Amount=%s&From=%s&To=%s' % (amount, val_from, val_to)\n\t\tr = requests.get(curr_url)\n\t\tdata = r.text\n\t\tsoup = bs(data)\n\t\treturn float(soup.find('span', class_='uccResultAmount').text.replace(',', ''))\n\n\tdef load_data(url, session):\n\t\tconn = True\n\t\twhile conn:\n\t\t\ttry:\n\t\t\t\tr = session.get(url, timeout=5)\n\t\t\t\tconn = False\n\t\t\texcept requests.exceptions.ReadTimeout:\n\t\t\t\tprint('FUCK')\n\t\treturn r.text\n\n\tdef check_discount(item):\n\t\treturn item.find('span', class_='old') != None\n\n\n\tqueryset_text = load_data(url, s)\n\n\tdata = bs(queryset_text)\n\n\tdef fetch_search_results(data):\n\t\tresults = []\n\t\tfor game_card in data.find_all('div', class_=\"content__game_card\", limit=5):\n\t\t\titem_currency = 'RUB'\n\t\t\tnew_currency = currency.upper()\n\t\t\tdiscount = check_discount(game_card)\n\t\t\tgame_item = {}\n\t\t\tgame_item['metadata'] = {}\n\t\t\tgame_item['price'] = {}\n\t\t\tgame_item['price']['current_price'] = {}\n\t\t\tgame_item['price']['discount_price'] = {}\n\t\t\tgame_item['price']['discount_converted_price'] = {}\n\t\t\tgame_item['price']['converted_price'] = {}\n\t\t\tgame_item['price']['profit_price'] = {}\n\t\t\t\n\t\t\tgame_item_img = game_card.find('img').get('data-original')\n\t\t\tgame_item_title = game_card.find('span', class_='content__game_card__title').text\n\t\t\t# META DATA OF GAME\n\t\t\tgame_item['metadata']['title'] = game_item_title\n\t\t\tgame_item['metadata']['platform'] = platform\n\t\t\tgame_item['metadata']['id'] = game_item_img.split('/')[5]\n\t\t\tgame_item['metadata']['img'] = game_item_img\n\t\t\tgame_item['metadata']['discount'] = discount\n\t\t\t# META END\n\t\t\t\n\t\t\t#PRICE DATA OF GAME\n\t\t\t#CURRENT PRICE\n\t\t\tgame_item['price']['current_price']['amount'] = float(game_card.find('span', class_='content__game_card__price').get('content').split(',')[0])\n\t\t\tgame_item['price']['current_price']['currency'] = item_currency\n\n\t\t\t#CONVERTED PRICE\n\t\t\tgame_item['price']['converted_price']['amount'] = round(get_currency_rate(item_currency, new_currency, game_item['price']['current_price']['amount']),0)\n\t\t\tgame_item['price']['converted_price']['currency'] = new_currency\n\n\t\t\t#PROFIT PRICE\n\t\t\tgame_item['price']['profit_price']['amount'] = round(game_item['price']['converted_price']['amount'] - user_price,0)\n\t\t\tgame_item['price']['profit_price']['currency'] = new_currency\n\n\t\t\t#DISCOUNT\n\t\t\tif discount:\n\t\t\t\tgame_item['price']['discount_price']['amount'] = round(float(game_card.find('span', class_='old').text.split(' ')[0]),2)\n\t\t\t\tgame_item['price']['discount_price']['currency'] = item_currency\n\n\t\t\t\tgame_item['price']['discount_converted_price']['amount'] = round(get_currency_rate(item_currency, new_currency, game_item['price']['discount_price']['amount']),0)\n\t\t\t\tgame_item['price']['discount_converted_price']['currency'] = new_currency\n\t\t\t\n #PRICE END\n\t\t\tresults.append(game_item)\n\t\treturn results\n\n\tdef convert_price(price_input, out_currency, rate_list, src_currency=None,):\n\t\treturn price_input * rate_list[out_currency]\n\t# print(data)\n\treturn(json.dumps(fetch_search_results(data), ensure_ascii=False).encode('utf-8'))\n"
}
] | 3
|
carleton-cs257-fall-2018/assignments-2018obarnett
|
https://github.com/carleton-cs257-fall-2018/assignments-2018obarnett
|
347cf69b0bf4a780c3e42247891fc88ba84d1c50
|
423f254df0582070d7971f204980cf5eff4d38e8
|
f45c64df2def50a9487eeb9cb4e0da6d29a086b6
|
refs/heads/master
| 2020-03-28T14:38:00.046972
| 2018-10-01T16:47:55
| 2018-10-01T16:47:55
| 148,506,163
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5820244550704956,
"alphanum_fraction": 0.5837696194648743,
"avg_line_length": 34.24615478515625,
"blob_id": "5369fbbe4570a623c9700958ab2bca1d2a470535",
"content_id": "38816003cf9329e01a5d4c99056fba126b0441b8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2292,
"license_type": "no_license",
"max_line_length": 143,
"num_lines": 65,
"path": "/using-apis/api-test.py",
"repo_name": "carleton-cs257-fall-2018/assignments-2018obarnett",
"src_encoding": "UTF-8",
"text": "'''\nAuthor: Owen Barnett\nGets the movies from the specifed year, if a title is not provided it prints all the movies from that year\nIf a title is provided it will print the details of the specified movie\n'''\n\nimport requests\nimport argparse\n\nclass movie_dataset:\n\n def __init__(self,year):\n '''\n Downloads all the movie data from the hydra movie api and puts it in a dictionary called data\n There are too many movies in the whole database so only movies from the specified year are taken\n '''\n\n url = \"https://hydramovies.com/api-v2/?source=http://hydramovies.com/api-v2/current-Movie-Data.csv&movie_year={year}\".format(year=year)\n raw_data = requests.get(url)\n self.data = raw_data.json()\n\n def print_titles(self):\n for moive_number in self.data:\n movie = self.data[moive_number]\n print(movie[\"Title\"])\n\n def get_moive_by_name(self, movie_name):\n movie_name = movie_name.strip().lower()\n for movie_number in self.data:\n movie = self.data[movie_number]\n if movie[\"Title\"].strip().lower().replace(\" \",\"\") == movie_name:\n return movie\n\n return -1\n\n\ndef main(args):\n movies = movie_dataset(args.year)\n if args.title is None:\n movies.print_titles()\n else:\n valid_movie = movies.get_moive_by_name(args.title)\n if valid_movie == -1:\n print(\"Movie not found\")\n else:\n for attribute in valid_movie:\n print(str(attribute) + \": \" + str(valid_movie[attribute]))\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description='Gets the movies made in specifed year hydra movie api, '\n 'if a title is provided finds the movie and prints details')\n\n parser.add_argument('year',\n metavar='year',\n help='Which year the movies will be looked at',\n type = int)\n\n parser.add_argument('--title',\n metavar='title',\n help='Search for a specific movie, remove spaces from movie title (Default: print all movie titles from the year)',\n type = str)\n\n\n args = parser.parse_args()\n main(args)\n\n"
},
{
"alpha_fraction": 0.5743609666824341,
"alphanum_fraction": 0.586367130279541,
"avg_line_length": 28.352272033691406,
"blob_id": "8c303d9626c3f28373c5dfca0f7f21170b941392",
"content_id": "af11126ad76af39f99b5046224ea89e7f11868db",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2582,
"license_type": "no_license",
"max_line_length": 103,
"num_lines": 88,
"path": "/books/books1.py",
"repo_name": "carleton-cs257-fall-2018/assignments-2018obarnett",
"src_encoding": "UTF-8",
"text": "#Author: Owen Barnett\n\nimport sys\nimport csv\nimport os\n\ndef get_books(file):\n '''\n takes a file and return a list of the book names\n assumes that file is a valid path to a csv file\n '''\n books = set()\n reader = csv.reader(open(file, newline=''))\n for row in reader:\n books.add(row[0])\n\n return list(books)\n\ndef get_authors(file):\n '''\n takes a file and return a list of the author names\n assumes that file is a valid path to a csv file\n '''\n cut = \"1234567890()-\"\n authors = set()\n reader = csv.reader(open(file, newline=''))\n for row in reader:\n temp = \"\".join(i for i in row[2] if not i in cut).strip()\n loc = temp.find(\" and \")\n if loc != -1:\n authors.add(temp[0:loc].strip())\n authors.add(temp[loc+4:].strip())\n else:\n authors.add(temp)\n return list(authors)\n\n\ndef sort_authors(authors, dir):\n '''\n returns a sorted list of authors\n assumes that authors is a list of names\n direction is either True or False, True sorts in lexicon order false sorts in reverse lexicon order\n '''\n authors.sort(key = lambda x: x.split(\" \")[-1]+x.split(\" \")[0], reverse = dir)\n return authors\n\ndef sort_books(books, dir):\n '''\n returns a sorted list of book names\n assumes that books is a lsit of book names\n direction is either True or False, True sorts in lexicon order false sorts in reverse lexicon order\n '''\n books.sort(reverse = dir)\n return books\n\ndef valid_input():\n '''\n checks if the command line inputs follow the pattern: input-file action [sort-directoin]\n returns true if the inputs are good\n returns false if the inputs are bad\n '''\n if len(sys.argv) > 1 and \".csv\" in sys.argv[1] and os.path.exists(sys.argv[1]):\n if len(sys.argv)>2:\n if sys.argv[2] == \"authors\" or sys.argv[2] == \"books\":\n if len(sys.argv) == 3:\n return True\n if (len(sys.argv) == 4) and (sys.argv[3] == \"reverse\" or sys.argv[3]==\"forward\"):\n return True\n\n return False\n\ndef main():\n if not valid_input():\n print('Usage: input-file action [sort-direction]', file=sys.stderr)\n quit()\n direction = sys.argv[len(sys.argv)-1] == \"reverse\"\n list = []\n if sys.argv[2] == \"authors\":\n list = get_authors(sys.argv[1])\n list = sort_authors(list,direction)\n else:\n list = get_books(sys.argv[1])\n list = sort_books(list, direction)\n for k in list:\n print(k)\n\nif __name__== \"__main__\":\n main()"
}
] | 2
|
samuellin01/CS50-Final-Project
|
https://github.com/samuellin01/CS50-Final-Project
|
bd367176bf68ef96b0ccd2f5c71ae9f3541b568e
|
c92e716ed16cf223db27ef4ed8eb1c71d54386a5
|
399eb54542b1195a354f0ac1a492a42d9bb2b6bc
|
refs/heads/main
| 2023-01-24T09:04:49.697965
| 2020-12-10T01:42:34
| 2020-12-10T01:42:34
| 316,669,758
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.752136766910553,
"alphanum_fraction": 0.7863247990608215,
"avg_line_length": 7.153846263885498,
"blob_id": "79922d8cfed6da237a022d8b7eff9e4582aeae54",
"content_id": "f5b6b2b4fe9a4075c33efcd362cfbd373840a27b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 117,
"license_type": "no_license",
"max_line_length": 13,
"num_lines": 13,
"path": "/requirements.txt",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "Flask\r\nFlask-Session\r\nrequests\r\niso3166\r\ngeopy\r\nnumpy\r\nmatplotlib\r\nastropy\r\nephem\r\npyorbital\r\ngeopy\r\nskyfield\r\npandas"
},
{
"alpha_fraction": 0.45234376192092896,
"alphanum_fraction": 0.45625001192092896,
"avg_line_length": 29.268293380737305,
"blob_id": "ab94ee2307b49b4445fb0c85ad4681104a583694",
"content_id": "3b9e3eca9750e11e929561345d2d3f0b8ecf7623",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 1282,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 41,
"path": "/templates/weather.html",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "{% extends \"layout.html\" %}\r\n\r\n{% block title %}\r\n Weather\r\n{% endblock %}\r\n\r\n\r\n{% block main %}\r\n\r\n<form>\r\n <h1>Weather in current local time (for locations in search history)</h1>\r\n <table class=\"table table-bordered table-hover table-striped table-dark\">\r\n <thead class=\"thead-light\">\r\n <tr>\r\n <th scope=\"col\">Location Name</th>\r\n <th scope=\"col\">Zipcode</th>\r\n <th scope=\"col\">Country</th>\r\n <th scope=\"col\">Weather</th>\r\n <th scope=\"col\">Temperature</th>\r\n <th scope=\"col\">Feels Like</th>\r\n <th scope=\"col\">Wind Speed</th>\r\n </tr>\r\n </thead>\r\n <tbody>\r\n {% for i in range(length) %}\r\n <tr>\r\n <td>{{ weather[i][\"name\"]}}</td>\r\n <td>{{ search_history[i][0] }}</td>\r\n <td>{{ search_history[i][1] }}</td>\r\n <td>{{ weather[i][\"weather\"][0][\"description\"] }}</td>\r\n <td>{{ weather[i][\"main\"][\"temp\"] }} °F</td>\r\n <td>{{ weather[i][\"main\"][\"feels_like\"] }} °F</td>\r\n <td>{{ weather[i][\"wind\"][\"speed\"] }} mph</td>\r\n </tr>\r\n {% endfor %}\r\n </tbody>\r\n </table>\r\n <p>Current local time: {{ current_time }}</p>\r\n</form>\r\n\r\n{% endblock %}"
},
{
"alpha_fraction": 0.6962962746620178,
"alphanum_fraction": 0.7037037014961243,
"avg_line_length": 30.5,
"blob_id": "e3b7bb0331917bcf9a399bc9fb70c1f5014e1cd5",
"content_id": "fd322db2ab24b6d3f3345106cf508c1a41f99ff9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 945,
"license_type": "no_license",
"max_line_length": 105,
"num_lines": 30,
"path": "/helpers.py",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "import os\nimport urllib.parse\n\nfrom flask import redirect, render_template, request, session\nfrom functools import wraps\nfrom geopy.geocoders import Nominatim\nfrom iso3166 import countries\n\ndef login_required(f):\n \"\"\"\n Decorate routes to require login.\n\n https://flask.palletsprojects.com/en/1.1.x/patterns/viewdecorators/\n \"\"\"\n @wraps(f)\n def decorated_function(*args, **kwargs):\n if session.get(\"user_id\") is None:\n return redirect(\"/login\")\n return f(*args, **kwargs)\n return decorated_function\n\n# locator() takes in zipcode & country, outputs a dict with location data or None if nonexistent location\ndef locator(zipcode, country):\n geolocator = Nominatim(user_agent=\"skymap\")\n country_symbol = countries[country].alpha2.lower()\n location = geolocator.geocode(zipcode, country_codes=country_symbol)\n if location == None:\n return location\n else:\n return location.raw\n"
},
{
"alpha_fraction": 0.6469134092330933,
"alphanum_fraction": 0.6619845628738403,
"avg_line_length": 44.20163345336914,
"blob_id": "9d28fb159055f87c8215ac0c70dbc6f80b429b36",
"content_id": "cef1f49b8a08efaafb916ae9e03468c9ff7a930c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 16588,
"license_type": "no_license",
"max_line_length": 373,
"num_lines": 367,
"path": "/application.py",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "import matplotlib\n# Specify 'Agg' as backend at the very beginning of the program before imports\nmatplotlib.use('Agg')\n\nimport matplotlib.pyplot\nimport os\nimport io\nimport calendar\nimport datetime\nimport astropy.time\nimport astropy.units as units\nimport sqlite3\nimport requests, json\nimport numpy\nimport logging\n\nfrom flask import Flask, flash, redirect, render_template, request, session, Response, url_for\nfrom flask_session import Session\nfrom tempfile import mkdtemp\nfrom werkzeug.exceptions import default_exceptions, HTTPException, InternalServerError\nfrom werkzeug.security import check_password_hash, generate_password_hash\nfrom time import strptime\nfrom iso3166 import countries\nfrom astropy.coordinates import EarthLocation\nfrom math import modf\nfrom matplotlib.backends.backend_agg import FigureCanvasAgg\nfrom matplotlib.figure import Figure\nfrom astropy.coordinates import SkyCoord, get_moon\n\nfrom helpers import login_required, locator\n\n\n# Configure application\napp = Flask(__name__)\n\n# Ensure templates are auto-reloaded\napp.config[\"TEMPLATES_AUTO_RELOAD\"] = True\n\n# Ensure responses aren't cached\n@app.after_request\ndef after_request(response):\n response.headers[\"Cache-Control\"] = \"no-cache, no-store, must-revalidate\"\n response.headers[\"Expires\"] = 0\n response.headers[\"Pragma\"] = \"no-cache\"\n return response\n\n# Configure session to use filesystem (instead of signed cookies)\napp.config[\"SESSION_FILE_DIR\"] = mkdtemp()\napp.config[\"SESSION_PERMANENT\"] = False\napp.config[\"SESSION_TYPE\"] = \"filesystem\"\nSession(app)\n\n# Turn off matplotlib debug log messages\nlogging.basicConfig()\nmpl_logger = logging.getLogger('matplotlib')\nmpl_logger.setLevel(logging.WARNING)\n\n# Configure sqlite3 to use SQL\nuserdata_db = sqlite3.connect(\"userdata.db\", check_same_thread=False)\ncur1 = userdata_db.cursor()\n\n# Initialize stars and constellations SQL databases\nstars_db = sqlite3.connect(\"stars.db\", check_same_thread=False)\nconstellations_db = sqlite3.connect(\"constellations.db\", check_same_thread=False)\ns = stars_db.cursor()\nc = constellations_db.cursor()\n\n@app.route(\"/\")\n@login_required\ndef index():\n cur1.execute(\"SELECT * FROM timeplaces WHERE username = ? ORDER BY timestamp\", (session[\"username\"],))\n search_history = cur1.fetchall()\n return render_template(\"index.html\", search_history=search_history)\n\n@app.route(\"/login\", methods=[\"GET\", \"POST\"])\ndef login():\n \"\"\"Log user in\"\"\"\n\n # Forget any user_id\n session.clear()\n message = \"\"\n # User reached route via POST (as by submitting a form via POST)\n if request.method == \"POST\":\n # Ensure username was submitted\n if not request.form.get(\"username\"):\n message = \"Missing username\"\n return render_template(\"login.html\", message=message)\n \n # Ensure password was submitted\n elif not request.form.get(\"password\"):\n message = \"Missing password\"\n return render_template(\"login.html\", message=message)\n\n # Query database for username\n cur1.execute(\"SELECT * FROM users WHERE username = ?\", (request.form.get(\"username\"),))\n matches = cur1.fetchall()\n # Ensure username exists and password is correct\n if len(matches) != 1 or not check_password_hash(matches[0][2], request.form.get(\"password\")):\n message = \"Invalid username and/or password\"\n return render_template(\"login.html\", message=message)\n \n # Remember which user has logged in\n session[\"user_id\"] = matches[0][0]\n session[\"username\"] = matches[0][1]\n # Redirect user to home page\n # return redirect(\"/\")\n return redirect(\"/\")\n\n # User reached route via GET (as by clicking a link or via redirect)\n else:\n return render_template(\"login.html\", message=message)\n\n\n@app.route(\"/logout\")\ndef logout():\n \"\"\"Log user out\"\"\"\n\n # Forget any user_id\n session.clear()\n\n # Redirect user to login form\n # return redirect(\"/\")\n return render_template(\"login.html\", message=\"\")\n\n@app.route(\"/register\", methods=[\"GET\", \"POST\"])\ndef register():\n \"\"\"Register user\"\"\"\n # Forget any user_id\n session.clear()\n message = \"\"\n # User reached route via POST (as by submitting a form via POST)\n if request.method == \"POST\":\n\n # Ensure username was submitted\n if not request.form.get(\"username\"):\n message = \"Must provide username\"\n return render_template(\"register.html\", message=message)\n\n # Ensure password was submitted\n elif not request.form.get(\"password\"):\n message = \"Must provide password\"\n return render_template(\"register.html\", message=message)\n\n # Ensures both passwords match\n elif request.form.get(\"password\") != request.form.get(\"confirmation\"):\n message = \"Passwords don't match\"\n return render_template(\"register.html\", message=message)\n\n # Query database for username\n cur1.execute(\"SELECT * FROM users WHERE username = ?\", (request.form.get(\"username\"),))\n\n # Checks to see if the username exists\n if len(cur1.fetchall()) == 1:\n message = \"Username already exists\"\n return render_template(\"register.html\", message=message)\n\n # Generates a hashed password\n hash_password = generate_password_hash(request.form.get(\"password\"))\n cur1.execute(\"SELECT * FROM users\")\n total_users = len(cur1.fetchall())\n # Inserts new user into users\n cur1.execute(\"INSERT INTO users (id, username, hash) VALUES(?, ?, ?)\", (total_users+1, request.form.get(\"username\"), hash_password))\n userdata_db.commit()\n session[\"user_id\"] = total_users + 1\n session[\"username\"] = request.form.get(\"username\")\n return render_template(\"index.html\")\n\n # User reached route via GET (as by clicking a link or via redirect)\n else:\n return render_template(\"register.html\", message=\"\")\n\n# Uses OpenWeatherMap to provide current weather for locations in search history\n# Learned to write this function from documentation in https://openweathermap.org/current\n@app.route(\"/weather\")\n@login_required\ndef weather():\n API_endpoint = \"http://api.openweathermap.org/data/2.5/weather?\"\n join_1 = \"&appid=\"\n API_key = \"f85761c7a2fc0e62714200e820d3f3d6\"\n cur1.execute(\"SELECT DISTINCT zipcode, country FROM timeplaces WHERE username = ? ORDER BY timestamp\", (session[\"username\"],))\n search_history = cur1.fetchall()\n weather = []\n current_time = datetime.datetime.now()\n for location in search_history:\n # Retrieve JSON data by generating API url based on lat/lon\n lat = float(locator(location[0], location[1])[\"lat\"])\n lon = float(locator(location[0], location[1])[\"lon\"])\n current_weather_lat_lon = \"lat=\" + str(round(lat,2)) + \"&lon=\" + str(round(lon,2))\n units = \"&units=imperial\"\n current_coord_weather_url = API_endpoint + current_weather_lat_lon + join_1 + API_key + units\n # Convert JSON data into Python dict type, and store it in weather[] list\n json_data = requests.get(current_coord_weather_url).json()\n weather_data = json.loads(json.dumps(json_data))\n weather.append(weather_data)\n return render_template(\"weather.html\", length=len(search_history), search_history=search_history, weather=weather, current_time=current_time)\n\n@app.route(\"/timeplace\", methods=[\"GET\", \"POST\"])\n@login_required\ndef timeplace():\n months = []\n nations = []\n message = \"\"\n # Generate list of months\n for i in range(1, 13):\n months.append(datetime.date(2020, i, 1).strftime('%B'))\n # Generate list of countries from iso1366 API\n for c in countries:\n nations.append(c.name)\n # GET: Loads form requesting a place and time, the latter is defaulted to current local time\n if request.method == \"GET\":\n return render_template(\"timeplace.html\", message=message, months=months, nations=nations, present_month=datetime.datetime.now().strftime('%B'), present_day=int(datetime.datetime.now().strftime('%d')), present_year=datetime.datetime.now().strftime('%Y'), present_hour=datetime.datetime.now().strftime('%H'), present_minute=datetime.datetime.now().strftime('%M'))\n # POST: Retrives timeplace form's data, validates and stores the data, and redirects to skymap\n else:\n zipcode = request.form.get(\"zipcode\")\n nation = request.form.get(\"country\")\n month = strptime(request.form.get(\"month\")[0:3], '%b').tm_mon\n day = int(request.form.get(\"day\"))\n year = int(request.form.get(\"year\"))\n hour = int(request.form.get(\"hour\"))\n minute = int(request.form.get(\"minute\"))\n try:\n date = datetime.date(year=year, month=month, day=day)\n except ValueError:\n message = \"Invalid Date\"\n if locator(zipcode, nation) == None:\n message = \"Invalid/Missing Location\"\n elif year < 2000:\n message = \"Date must be after January 1, 2000\"\n elif year > 2040:\n message = \"Date must be before December 31st, 2039\"\n if message == \"\":\n # Store both the time to be used on sky map and time request is made\n requesttime = datetime.datetime(year, month, day, hour, minute)\n timestamp = datetime.datetime.now()\n cur1.execute(\"INSERT INTO timeplaces (username, zipcode, country, requesttime, timestamp) VALUES (?, ?, ?, ?, ?)\", (session[\"username\"], zipcode, nation, requesttime, timestamp))\n userdata_db.commit()\n return redirect(url_for('skymap'))\n else:\n return render_template(\"timeplace.html\", message=message, months=months, nations=nations, present_month=datetime.datetime.now().strftime('%B'), present_day=int(datetime.datetime.now().strftime('%d')), present_year=datetime.datetime.now().strftime('%Y'), present_hour=datetime.datetime.now().strftime('%H'), present_minute=datetime.datetime.now().strftime('%M'))\n\n# Called only from /skymap route to generate skymap image using matplotlib\n# Found useful information on https://stackoverflow.com/questions/50728328/python-how-to-show-matplotlib-in-flask\n@app.route(\"/skymap.png\")\ndef skymap_png():\n # Find latest timeplace request from user\n for item in cur1.execute(\"SELECT * FROM timeplaces ORDER BY timestamp DESC LIMIT 1\"):\n # Convert time to Coordinated Universal Time\n utc_difference = datetime.datetime.now()-datetime.datetime.utcnow()\n date_time_obj = datetime.datetime.strptime(item[3], '%Y-%m-%d %H:%M:%S')\n input_time = astropy.time.Time(date_time_obj - utc_difference)\n input_loc = EarthLocation(lat=float(locator(item[1], item[2])[\"lat\"])*units.deg, lon=float(locator(item[1], item[2])[\"lon\"])*units.deg)\n # Plot skymap and return a PNG\n matplotlib.pyplot.style.use('dark_background')\n fig, ax = draw_template()\n draw_constellations(ax)\n draw_vision(ax, input_time, input_loc)\n draw_moon(ax, input_time, input_loc)\n output = io.BytesIO()\n FigureCanvasAgg(fig).print_png(output)\n return Response(output.getvalue(), mimetype=\"image/png\")\n\n@app.route(\"/skymap\")\n@login_required\ndef skymap():\n # Renders skymap labeled with location and time\n for item in cur1.execute(\"SELECT * FROM timeplaces ORDER BY timestamp DESC LIMIT 1\"):\n lat = round(float(locator(item[1], item[2])[\"lat\"]), 3)\n lon = round(float(locator(item[1], item[2])[\"lon\"]), 3)\n zipcode = item[1]\n country = item[2]\n time = item[3][0:-3]\n return render_template(\"skymap.html\", lat=lat, lon=lon, zipcode=zipcode, country=country, time=time)\n\n\n# The following three functions were originally intended to be in helpers.py, but they were ultimately placed\n# in application.py to avoid the error: mathplotlib GUI is not in main thread\n\n\n# Draw polar graph to produce template for sky map\ndef draw_template():\n # Basic configurations\n fig = matplotlib.pyplot.figure(dpi=500)\n ax = fig.add_axes([0, 0, 1, 1], polar=True)\n ax.set_theta_direction(-1) \n ax.set_theta_zero_location('N')\n\n # Hide unnecessary tick labels\n for xlabel in ax.get_xticklabels():\n xlabel.set_visible(False)\n for ylabel in ax.get_yticklabels():\n ylabel.set_visible(False)\n \n # Draw inner gridlines\n ax.grid(True)\n gridlines = ax.get_xgridlines() + ax.get_ygridlines()\n for line in gridlines:\n line.set_linewidth(0.2)\n line.set_linestyle('-')\n \n return fig,ax\n\n\n# Draw constellations onto skymap using data from stars.db and constellations.db\ndef draw_constellations(ax):\n # Generate list of all constellations\n constellations = []\n for item in c.execute(\"SELECT DISTINCT(constellation) FROM constellations\"):\n constellations.append(item[0])\n # Draw each constellation by pairs of stars, using their right ascensions and declinations as coordinates\n for constellation in constellations:\n constellation_path = []\n for item in c.execute(\"SELECT * FROM constellations WHERE constellation=? ORDER BY ord\", (constellation,)):\n constellation_path.append(item[1])\n for i in range(len(constellation_path) - 1):\n stars = []\n ras = []\n decs = []\n for j in [i, i+1]:\n stars.append(constellation_path[j])\n for item in s.execute(\"SELECT ra FROM stars WHERE constellation = ? AND star = ?\", (constellation, stars[j-i])):\n ras.append(item[0])\n for item in s.execute(\"SELECT dec FROM stars WHERE constellation = ? AND star = ?\", (constellation, stars[j-i])):\n decs.append(item[0])\n ax.plot(numpy.radians([ras[0], ras[1]]), [-1 * decs[0]+45, -1 * decs[1] + 45], linewidth=1.0, color='skyblue')\n # Add label with constellation name next to first star \n if i == 0:\n ax.text(numpy.radians(ras[0]), -1 * decs[0]+45, str(format(constellation)), fontsize=4, weight='bold')\n\n# Draw area of skymap that observer can see\n# Found useful documentation on https://matplotlib.org/3.3.3/users/whats_new.html#what-s-new-in-matplotlib-3-3-0 \ndef draw_vision(ax, input_time, input_loc):\n # Convert coordinates to altitude-azimuth coordinates and to right-ascension/declination coordinates\n azimuth = numpy.arange(0, 360.1, 1)\n altitude = numpy.zeros(len(azimuth))\n vision = SkyCoord(azimuth, altitude, frame='altaz', unit='deg', obstime=input_time, location=input_loc).transform_to('icrs')\n \n # Plot RA and DEC coordinates\n ax.plot(vision.ra.radian, -vision.dec.value+45, '-', linewidth=0.3, color='darkblue')\n \n # Fill in outside circle\n ax.fill_between(vision.ra.radian, -vision.dec.value+45, len(-vision.dec.value+45) * [90], where=len(-vision.dec.value+45) * [90]>=-vision.dec.value+45, facecolor='skyblue', alpha=0.8 )\n\n # Draw curved axis\n curved_alt = [num for num in numpy.arange(0, 90.1, 1)]\n curved_az = len(curved_alt)*[90] + (len(curved_alt)-1)*[270]\n curved_alt = curved_alt + curved_alt[:-1][::-1]\n curved_ax = SkyCoord(curved_az, curved_alt, frame='altaz', unit='deg', obstime=input_time, location=input_loc).transform_to('icrs')\n ax.plot(curved_ax.ra.radian, -curved_ax.dec.value+45, '-', linewidth=0.5, color='turquoise')\n\n # Draw straight axis\n straight_ax = SkyCoord([0, 180], [0, 0], unit='deg', frame='altaz', obstime=input_time, location=input_loc).transform_to('icrs')\n ax.plot(straight_ax.ra.radian, -straight_ax.dec.value+45, '-', linewidth=0.5, color='turquoise')\n\n # Label North, South, East, West\n directions = ['N', 'E', 'S', 'W']\n counter = 0\n vision_circle_deg = SkyCoord(numpy.arange(0, 345.1, 15), numpy.zeros(len(numpy.arange(0, 345.1, 15))), frame='altaz', unit='deg', obstime=input_time, location=input_loc).transform_to('icrs')\n for (coordinate, label) in zip(vision_circle_deg, numpy.arange(0, 345.1, 15)):\n if int(label) % 90 == 0:\n ax.text(coordinate.ra.radian, -coordinate.dec.value+45, directions[counter], fontname=\"serif\", fontsize=10, fontweight='bold' )\n counter += 1\n\n# Draw location of moon at input time\ndef draw_moon(ax, input_time, input_loc):\n moon = get_moon(time=input_time, location=input_loc)\n moon = SkyCoord(moon.ra, moon.dec, frame='gcrs').transform_to('icrs')\n ax.plot([moon.ra.radian], [-moon.dec.value+45], color='yellow', linestyle='', marker='o')"
},
{
"alpha_fraction": 0.76953125,
"alphanum_fraction": 0.7752603888511658,
"avg_line_length": 74.77999877929688,
"blob_id": "8007e2912c5133d363f29dbabd3af8136a80824d",
"content_id": "545aa27922a8c210b29ee4e2eb1bfd6da7625cb7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 3860,
"license_type": "no_license",
"max_line_length": 623,
"num_lines": 50,
"path": "/README.md",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "Link to Youtube video: https://youtu.be/2tBjOh42LVc \r\n\r\nFile Organization:\r\n\r\nOur final project is a Flask application. Its components include various Python, HTML, CSS, and SQL files, organized such that the HTML files are located in a templates folder with the index.html as the homepage with the search history and the rest of the HTML corresponding to their function. We also have a static folder containing the CSS file and an image for our favicon.\r\n\r\nBefore running the Flask application:\r\n\r\nFirst, download and unzip the folder titled CS50-Final-Project-main. Our flask application can be executed either in a computer’s terminal, or in CS50 IDE. Regardless of which method is used, a user must have already navigated to the location of CS50-Final-Project-main on their computer’s directory. Once this is done, run the following command:\r\n`> pip install -r requirements`\r\nIf this command returns an error, it is probably because the computer has a different version of pip installed. Run the following command instead:\r\n`> pip3 install -r requirements`\r\nThis should install all of the necessary modules needed to run the program. It is best to do this with an Internet connection.\r\n\r\n\r\nRunning the Flask application:\r\n\r\nTo run the Flask application on Unix Bash (Linux, Mac, etc.), type the following commands:\r\n`$ export FLASK_APP=application`\r\n`$ flask run`\r\nTo run the Flask application on Windows CMD, type the following commands:\r\n`> set FLASK_APP=application`\r\n`> flask run`\r\nTo run the Flask application on Windows Powershell, type the following commands:\r\n`> $env:FLASK_APP = \"application\"`\r\n`> flask run`\r\nTo run the Flask application on CS50 IDE, type the following command:\r\n`> flask run`\r\nThe flask application should run properly at this point. Something similar to this should appear:\r\n`$ flask run`\r\n `* Serving Flask app \"application\"`\r\n `* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)`\r\nThe flask application can then be run on any browser (although Google Chrome works most reliably) by typing in the above address into the browser’s address bar. \r\n\r\n\r\n\r\n\r\nA Note about Incognito Mode:\r\n\r\nThis usually does not happen, but sometimes, a browser will store cache for the Flask website. This is usually only a problem on the developer’s side, but if changes in session are not reflected properly, then stop the flask application and rerun it in Incognito Mode.\r\n\r\nNavigating our Flask Website:\r\n\r\nOnce you have our skymap site open, you should see the interactive sky map sign in page with the title at the top and nav bar on the left hand side. If you are a first time user, you should click the register button in the nav bar to register. \r\n\r\nOnce your username and password have been accepted, then you’ll be at the home screen with the search history. If you are a first time user, this shouldn’t have any information just yet. Hop on over to the sky map section in the nav bar where you’ll see several pieces of information to fill out regarding your location and time. The main location info will be the zip code and for ease of use, we have defaulted the time to the user’s current time. After submitting this info, a sky map will load that is calibrated to what you will see in the night sky from your location and time. This may take several seconds to load. \r\n\r\nNext, we also have our weather section which will display the weather in local time for the locations entered in the sky map which appear in the search history. This will provide the user with the necessary information to determine if conditions are right for stargazing. We hope you enjoy our website and grow your interest in astronomy!\r\n\r\nNow, when you’re done viewing the website you can sign out by simply clicking the sign out button. Make sure you do this after you’re done as this will keep your location information safe. \r\n"
},
{
"alpha_fraction": 0.7986577153205872,
"alphanum_fraction": 0.8004881143569946,
"avg_line_length": 167.51724243164062,
"blob_id": "4e1ae9ff6053718703d427b74fa7576a6c0df4df",
"content_id": "9e6a79476d541ef968ebc4996773bfcc96e77bbb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 4931,
"license_type": "no_license",
"max_line_length": 807,
"num_lines": 29,
"path": "/DESIGN.md",
"repo_name": "samuellin01/CS50-Final-Project",
"src_encoding": "UTF-8",
"text": "Layout\r\n\r\nWe decided to implement Bootstrap’s functionality for our left navbar and overall design. Instead of the horizontal navbar that we commonly saw used, we opted for a vertical one that would provide a cleaner look and provide more space for our features. Colors were used that matched the theme of our project which was to implement a working night sky for each user. Another key note is that we created an HTML template with the intention of using Jinja, so that we wouldn’t have to copy and paste the same html for each page. \r\n\r\nRegister\r\n\r\nTo personalize the experience of our website for each unique visitor, we stored each user and password in a SQLite database. We used similar code from the finance pset such as the HTML/Python to simulate this functionality. On the front end of the website, the user had to input a username and password and reconfirm the password. On the back end of the website, we checked against restraints: for example, the username had to be unique so that we could track each user, and the passwords had to match. We had to additionally place links to these routes in the HTML navbar so that users can navigate to these pages. \r\n\r\nSignin / Signout\r\n\r\nThis was important so that not just anyone could access our website without providing information. We also kept track of the session_id so that each user can see their own search history and not have their location be broadcast to all users. It was important to us that location privacy was maintained in our website. More evidence of our personalization was that we added another feature that showed on the left navbar which person was signed in. \r\n\r\nSkymap\r\n\r\nOur original intention for this final project was to produce an interactive sky map for a user based on a specific location and time. To implement this, we created an HTML form to retrieve the location and time, two pieces of data that had to be processed on the back end of the website. To process location, we used Geopy API to convert zipcode and country into latitude and longitude coordinates. To process time, we used python’s datetime module. We found many APIs online that could produce the coordinates of celestial objects (in right-ascension/declination coordinates) given a user’s location and time, but we struggled to find an API that could produce an interactive graphic that had our desired results. \r\n\r\nInstead, we decided to use matplotlib API to draw out the constellations based on these coordinates. To do this, we pulled data from SIMBAD, a public astronomy database, converting their CSV databases into SQLite databases first. With the right-ascension/declination coordinates for individual stars in constellations, we could then plot them onto a polar graph in pairs. Finally, we used Astropy API to identify the portion of the sky observable by a user, and plotted this area on the same graph in a different color. We used North/South/East/West markers so that users could apply our graphic to real life. FInally, we rendered this graphic into a PNG file attached to one of our HTML pages.\r\n\r\nSearch History\r\n\r\nAgain, similar to finance, we have a search history of the user which is nice to have as you can look back on which locations you looked at and at what times to look up those skymaps from the past so that you can compare with the future. We had a table in the HTML and also used Jinja to pull data from our database containing this information. This was relatively easy to implement because every search made by a user was recorded in a SQLite database.\r\n\r\nWeather \r\n\r\nOur original intention was to provide a weather forecast widget alongside the sky map, both of which were to be based on the same location and time inputs. We encountered a design obstacle upon trying to implement this: most free weather APIs on the Internet can only provide forecasts up to three days prior and after the current time. This was a problem because we had designed our sky map to work for dates in a 40 year time span, and in fact, it would be a huge downgrade for us to limit users to a mere 6 day time span. Instead, we decided to work around this by providing only the current weather forecast for locations in a user’s search history. This worked out, and our current implementation provides current temperature, apparent temperature, wind speed, and a description of the current weather.\r\n\r\nAdditional Notes\r\n\r\nWe structured our Flask code into an application.py file and a helpers.py file, with most functions located in application.py. We had originally intended to place all functions without route decorators in helpers.py to avoid clutter, but this did not work out because matplotlib would occasionally stop working, saying that the matplotlib GUI must be in the main thread. Furthermore, we used Python’s sqlite3 module instead of CS50’s SQL library because we found that sqlite3 could execute reliably more often than CS50 SQL. \r\n"
}
] | 6
|
Sondro/iree
|
https://github.com/Sondro/iree
|
74874216471b075260c52e752a68f62963b3dee8
|
fb73b423ad8d865aab6b3901cadb444f5552cb91
|
273d32b2380988187c2142b066f83986c76a184b
|
refs/heads/master
| 2023-04-08T12:57:58.352794
| 2019-10-18T22:11:12
| 2019-10-18T22:11:48
| 216,159,884
| 0
| 0
|
Apache-2.0
| 2019-10-19T06:26:11
| 2019-10-19T06:26:12
| 2023-03-24T20:20:03
| null |
[
{
"alpha_fraction": 0.6692708134651184,
"alphanum_fraction": 0.7005208134651184,
"avg_line_length": 31.91428565979004,
"blob_id": "196b4cee54566bebeca50a9544588585cb2d0350",
"content_id": "a164d12ae1f2a989f3fc8f981de852d118edd1cc",
"detected_licenses": [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1152,
"license_type": "permissive",
"max_line_length": 107,
"num_lines": 35,
"path": "/iree/bindings/python/pyiree/compiler_test.py",
"repo_name": "Sondro/iree",
"src_encoding": "UTF-8",
"text": "# Copyright 2019 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom absl.testing import absltest\n\nfrom pyiree import binding as binding\n\n\nclass CompilerTest(absltest.TestCase):\n\n def testModuleCompileAndIntrospectFromAsm(self):\n\n m = binding.compiler.compile_module_from_asm(\"\"\"\n func @simple_mul(%arg0: tensor<4xf32>, %arg1: tensor<4xf32>) -> tensor<4xf32>\n attributes { iree.module.export } {\n %0 = \"xla_hlo.mul\"(%arg0, %arg1) {name = \"mul.1\"} : (tensor<4xf32>, tensor<4xf32>) -> tensor<4xf32>\n return %0 : tensor<4xf32>\n }\n \"\"\")\n self.assertTrue(m)\n\n\nif __name__ == '__main__':\n absltest.main()\n"
},
{
"alpha_fraction": 0.729187548160553,
"alphanum_fraction": 0.7331995964050293,
"avg_line_length": 32.233333587646484,
"blob_id": "f21d8aa766535568266caea172aabc0c756ab424",
"content_id": "5dc1479fe05cb74486aa98e1510ab103e08576e1",
"detected_licenses": [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 2991,
"license_type": "permissive",
"max_line_length": 80,
"num_lines": 90,
"path": "/iree/bindings/python/pyiree/compiler.cc",
"repo_name": "Sondro/iree",
"src_encoding": "UTF-8",
"text": "// Copyright 2019 Google LLC\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// https://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#include \"iree/bindings/python/pyiree/compiler.h\"\n\n#include <stdexcept>\n\n#include \"iree/bindings/python/pyiree/binding.h\"\n#include \"iree/bindings/python/pyiree/status_utils.h\"\n#include \"iree/compiler/Translation/Sequencer/SequencerModuleTranslation.h\"\n#include \"iree/schemas/module_def_generated.h\"\n#include \"llvm/Support/SourceMgr.h\"\n#include \"llvm/Support/raw_ostream.h\"\n#include \"mlir/IR/MLIRContext.h\"\n#include \"mlir/IR/Module.h\"\n#include \"mlir/Parser.h\"\n\nnamespace py = pybind11;\n\nusing namespace mlir;\nusing namespace mlir::iree_compiler;\n\nusing llvm::MemoryBuffer;\nusing llvm::MemoryBufferRef;\nusing llvm::StringRef;\n\nnamespace iree {\nnamespace python {\n\nnamespace {\n\nOwningModuleRef parseMLIRModuleFromString(StringRef contents,\n MLIRContext* context) {\n std::unique_ptr<MemoryBuffer> contents_buffer;\n if (contents.back() == 0) {\n // If it has a nul terminator, just use as-is.\n contents_buffer = MemoryBuffer::getMemBuffer(contents.drop_back());\n } else {\n // Otherwise, make a copy.\n contents_buffer = MemoryBuffer::getMemBufferCopy(contents, \"EMBED\");\n }\n\n llvm::SourceMgr source_mgr;\n source_mgr.AddNewSourceBuffer(std::move(contents_buffer), llvm::SMLoc());\n OwningModuleRef mlir_module = parseSourceFile(source_mgr, context);\n return mlir_module;\n}\n\n} // namespace\n\nstd::shared_ptr<MemoryModuleFile> CompileModuleFromAsm(\n const std::string& moduleAsm) {\n MLIRContext context;\n\n // Arrange to get a view that includes a terminating null to avoid additional\n // copy.\n const char* moduleAsmChars = moduleAsm.c_str();\n StringRef moduleAsmSr(moduleAsmChars, moduleAsm.size() + 1);\n\n // TODO(laurenzo): This error handling is super hoaky. Hook into the MLIR\n // error reporter and plumb through properly.\n OwningModuleRef mlirModule = parseMLIRModuleFromString(moduleAsmSr, &context);\n if (!mlirModule) {\n throw std::runtime_error(\"Failed to parse MLIR asm\");\n }\n\n auto moduleBlob =\n mlir::iree_compiler::translateMlirToIreeSequencerModule(mlirModule.get());\n if (moduleBlob.empty()) {\n throw std::runtime_error(\"Failed to translate MLIR module\");\n }\n\n auto moduleFile = PyConsumeStatusOr(FlatBufferFile<ModuleDef>::FromContainer(\n ModuleDefIdentifier(), std::move(moduleBlob)));\n return std::make_shared<MemoryModuleFile>(std::move(moduleFile));\n}\n\n} // namespace python\n} // namespace iree\n"
},
{
"alpha_fraction": 0.7140052318572998,
"alphanum_fraction": 0.7244764566421509,
"avg_line_length": 30.183673858642578,
"blob_id": "c9d75db2d2b91bd17434d2fe6645eabb3b4177e7",
"content_id": "f063b4bf5fd5fa9f210211eb4a8de7b76d99ab22",
"detected_licenses": [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1528,
"license_type": "permissive",
"max_line_length": 75,
"num_lines": 49,
"path": "/iree/bindings/python/pyiree/status_utils.h",
"repo_name": "Sondro/iree",
"src_encoding": "UTF-8",
"text": "// Copyright 2019 Google LLC\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// https://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#ifndef IREE_BINDINGS_PYTHON_PYIREE_STATUS_UTILS_H_\n#define IREE_BINDINGS_PYTHON_PYIREE_STATUS_UTILS_H_\n\n#include \"iree/base/status.h\"\n#include \"pybind11/pytypes.h\"\n\nnamespace iree {\nnamespace python {\n\n// Converts a failing status to a throwable exception, setting Python\n// error information.\n// Correct usage is something like:\n// if (!status.ok()) {\n// throw StatusToPyExc(status);\n// }\npybind11::error_already_set StatusToPyExc(const Status& status);\n\n// Consumes a StatusOr<T>, returning an rvalue reference to the T if the\n// status is ok(). Otherwise, throws an exception.\ntemplate <typename T>\nT&& PyConsumeStatusOr(iree::StatusOr<T>&& sor) {\n if (sor.ok()) {\n return std::move(*sor);\n }\n throw StatusToPyExc(sor.status());\n}\n\n} // namespace python\n} // namespace iree\n\nnamespace pybind11 {\nnamespace detail {} // namespace detail\n} // namespace pybind11\n\n#endif // IREE_BINDINGS_PYTHON_PYIREE_STATUS_UTILS_H_\n"
},
{
"alpha_fraction": 0.7210884094238281,
"alphanum_fraction": 0.7295918464660645,
"avg_line_length": 33.588233947753906,
"blob_id": "6689b7db635b6ee913f6b783e95a0c542aec4580",
"content_id": "b3b435fdeac2874e6222c711e40b5b27eeea658b",
"detected_licenses": [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1176,
"license_type": "permissive",
"max_line_length": 75,
"num_lines": 34,
"path": "/iree/bindings/python/pyiree/binding.cc",
"repo_name": "Sondro/iree",
"src_encoding": "UTF-8",
"text": "// Copyright 2019 Google LLC\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// https://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#include \"iree/bindings/python/pyiree/binding.h\"\n\n#include \"iree/bindings/python/pyiree/compiler.h\"\n#include \"iree/bindings/python/pyiree/status_utils.h\"\n\nnamespace iree {\nnamespace python {\n\nPYBIND11_MODULE(binding, m) {\n m.doc() = \"IREE Binding Backend Helpers\";\n\n auto compiler_m = m.def_submodule(\"compiler\", \"IREE compiler support\");\n py::class_<MemoryModuleFile, std::shared_ptr<MemoryModuleFile>>(\n compiler_m, \"MemoryModuleFile\")\n .def(py::init<>());\n compiler_m.def(\"compile_module_from_asm\", CompileModuleFromAsm);\n}\n\n} // namespace python\n} // namespace iree\n"
},
{
"alpha_fraction": 0.7369491457939148,
"alphanum_fraction": 0.7423728704452515,
"avg_line_length": 31.065217971801758,
"blob_id": "8c8cb61189c4f189fbfcdce4b9bb19255d82624d",
"content_id": "c947d14f081d6018e8771d00b80018f5962841fe",
"detected_licenses": [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1475,
"license_type": "permissive",
"max_line_length": 80,
"num_lines": 46,
"path": "/iree/bindings/python/pyiree/compiler.h",
"repo_name": "Sondro/iree",
"src_encoding": "UTF-8",
"text": "// Copyright 2019 Google LLC\n//\n// Licensed under the Apache License, Version 2.0 (the \"License\");\n// you may not use this file except in compliance with the License.\n// You may obtain a copy of the License at\n//\n// https://www.apache.org/licenses/LICENSE-2.0\n//\n// Unless required by applicable law or agreed to in writing, software\n// distributed under the License is distributed on an \"AS IS\" BASIS,\n// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n// See the License for the specific language governing permissions and\n// limitations under the License.\n\n#ifndef IREE_BINDINGS_PYTHON_PYIREE_COMPILER_H_\n#define IREE_BINDINGS_PYTHON_PYIREE_COMPILER_H_\n\n#include <string>\n\n#include \"iree/base/flatbuffer_util.h\"\n#include \"iree/bindings/python/pyiree/binding.h\"\n#include \"iree/schemas/module_def_generated.h\"\n\nnamespace iree {\nnamespace python {\n\nclass MemoryModuleFile : public std::enable_shared_from_this<MemoryModuleFile> {\n public:\n MemoryModuleFile() = default;\n explicit MemoryModuleFile(std::unique_ptr<FlatBufferFile<ModuleDef>> file)\n : file_(std::move(file)) {}\n virtual ~MemoryModuleFile() = default;\n\n FlatBufferFile<ModuleDef>* file() const { return file_.get(); }\n\n private:\n std::unique_ptr<FlatBufferFile<ModuleDef>> file_;\n};\n\nstd::shared_ptr<MemoryModuleFile> CompileModuleFromAsm(\n const std::string& moduleAsm);\n\n} // namespace python\n} // namespace iree\n\n#endif // IREE_BINDINGS_PYTHON_PYIREE_COMPILER_H_\n"
}
] | 5
|
udaybansal19/Rando
|
https://github.com/udaybansal19/Rando
|
7e7f21176811c81d396176af8fe47dd26565b202
|
0ab7f6b4f12ed0e9e063fbe563fa86354d8566d8
|
393d5e3006e993d555a9e465e3974417bcaf4d9f
|
refs/heads/master
| 2021-02-18T08:53:59.343644
| 2020-06-08T20:45:54
| 2020-06-08T20:45:54
| 245,179,643
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5315712094306946,
"alphanum_fraction": 0.5646108388900757,
"avg_line_length": 16.4743595123291,
"blob_id": "2f24d84ca379080bb89804617ae3b886bad686f4",
"content_id": "8eabaffb32884cdf5d673e43ee6d5b35d83cbc95",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1362,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 78,
"path": "/chaos-game.py",
"repo_name": "udaybansal19/Rando",
"src_encoding": "UTF-8",
"text": "import matplotlib.pyplot as plt \nimport array as arr\nimport random\nimport numpy as np\nimport random\n\nnumberOfPoints = 100000\n\n# Prime numbers didn't work\n# Rando works!!!\n# Gives somewhat shape for r=3 as well\n#\n# Value above bifurcation r=3.6 to r=4 gives perfect fractal\n# with disintegration below it\n# Digits of pi and other irrational numbers\n# Digits of pi work!!\n# Digits of all irrational numbers work\n# Iterate different functinos with different growth rate\n\nx_coor = arr.array('d')\ny_coor = arr.array('d')\n\nx = 1\ny = 2\nc = 0\n\n\ndef rand_func():\n eff = 100\n global c\n for i in range(3.6*eff,4*eff):\n rando(x,i/eff)\n c = c+1\n return randNum[c]*1000\n\ndef next_point(z):\n\n global x\n global y\n\n x_coor.append(x)\n y_coor.append(y)\n \n int(z)\n\n if(z%3==0):\n x = (0 + x)/2\n y = (0 + y)/2\n elif(z%3==1):\n x = (2 + x)/2\n y = (3 + y)/2\n elif(z%3==2):\n x = (4 + x)/2\n y = (0 + y)/2\n\n\ndef chaos_game(x,y):\n\n f = open(\"irrational_numbers/root2.txt\", \"r\")\n for i in range(1,numberOfPoints):\n a = f.read(1)\n if((a != ' ') and (a != '')):\n next_point(int(a))\n\n\n\ndef plotIT():\n\t\n\tplt.plot(x_coor,y_coor,'.',color='blue') \n \n\t# plt.ylabel('Random number') \n\t# plt.xlabel('Seed') \n\tplt.title('') \n \n\tplt.show()\n\nchaos_game(x,y)\nplotIT()"
},
{
"alpha_fraction": 0.7622950673103333,
"alphanum_fraction": 0.7650273442268372,
"avg_line_length": 25.214284896850586,
"blob_id": "8728ed144c65f72d7c4eb77d8028a7879ee4600e",
"content_id": "69857915884331f1330d84d856b6261108182697",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 366,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 14,
"path": "/README.md",
"repo_name": "udaybansal19/Rando",
"src_encoding": "UTF-8",
"text": "# Rando\nRepository to experiment with different pseudo random generating algorithms.\n\n## Rando\nImplementation of Logistics map in python and c++\n\n\n\n\n\n## Chaos Game\nMethod to check if a sequence of numbers is random or not.\n\n"
},
{
"alpha_fraction": 0.6049469709396362,
"alphanum_fraction": 0.6402826905250549,
"avg_line_length": 17.389610290527344,
"blob_id": "3ef823ca432238bec8d38bbd1748ee8e30dfd8df",
"content_id": "05eb638306a9da339aaf6481deb0f9ba1ddcddd5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1415,
"license_type": "no_license",
"max_line_length": 64,
"num_lines": 77,
"path": "/rando.py",
"repo_name": "udaybansal19/Rando",
"src_encoding": "UTF-8",
"text": "import matplotlib.pyplot as plt \nimport array as arr\nimport random\nimport numpy as np\nimport math\n\nitr = 10\n\nrandNum = arr.array('d')\ngrowthRate = arr.array('d')\n\n# TODO: Calculate Figenbaum's constant\n\ndef func(x,r):\n return r*(x*x-1)\n\ndef rando(ini,r):\n\n\tx = ini\n\tfor i in range(0,itr):\n\t\tx = func(x,r)\n\n\tfor i in range(0,100):\n\t\tx = func(x,r)\n\t\trandNum.append(x)\n\t\tgrowthRate.append(r)\ndef func1(x,r):\n return r*(100-x*x)\n\ndef rando1(ini,r):\n\n\tx = ini\n\tfor i in range(0,itr):\n\t\tx = func1(x,r)\n\n\tfor i in range(0,100):\n\t\tx = func1(x,r)\n\t\trandNum.append(x)\n\t\tgrowthRate.append(r)\ndef plotFunc(r):\n\tx = np.linspace(-3,3,100)\n\ty = func(x,r)\n\n\tfig = plt.figure()\n\tax = fig.add_subplot(1, 1, 1)\n\tax.spines['left'].set_position('center')\n\tax.spines['bottom'].set_position('zero')\n\tax.spines['right'].set_color('none')\n\tax.spines['top'].set_color('none')\n\tax.xaxis.set_ticks_position('bottom')\n\tax.yaxis.set_ticks_position('left')\n\n\tplt.plot(x, y,'r')\n\tplt.plot(x,func(func(x,r),r))\n\tplt.plot(x,func(func(func(x,r),r),r))\n\tplt.show() \t\n\ndef plotRando(x):\n\t\n\teff = 1000\n\tfor i in range(-10*eff,10*eff):\n\t\trando(x,i/eff)\n\t# for i in range(-10*eff,10*eff):\n\t# \trando1(x,i/eff)\n\tplt.plot(growthRate,randNum,',k', alpha=.25) \n \n\tplt.ylabel('Ouput Value from function after many iterations') \n\tplt.xlabel('Growth Rate (r)') \n\tplt.title('Logistic Map') \n \n\tplt.show() \t\n\nitr = 1000\nx = 0.1\nr = 1\nplotRando(x)\n#plotFunc(r)"
},
{
"alpha_fraction": 0.5271210074424744,
"alphanum_fraction": 0.5479832887649536,
"avg_line_length": 16.14285659790039,
"blob_id": "1218855ee5a404798917da36592c39b598ad78d5",
"content_id": "f2d4dde5779baacfd4efa2a4a7ebaca76eccef47",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 719,
"license_type": "no_license",
"max_line_length": 60,
"num_lines": 42,
"path": "/main.cpp",
"repo_name": "udaybansal19/Rando",
"src_encoding": "UTF-8",
"text": "#include <bits/stdc++.h>\n\nusing namespace std;\n\nlong long int itr=0;\n\nlong double func(long double x,long double r) {\n\n return r*x*(1-x);\n\n}\n\nlong double rando(long double ini,long double r,int view ) {\n\n long double x = ini;\n\n for(long long int i=0;i<itr;i++){\n x = func(x,r);\n }\n\n for(int i=0;i<view;i++){\n x = func(x,r);\n cout<<x<<endl;\n }\n\n return x;\n}\n\nint main() {\n\n itr = 1000;\n long double x = 0.2;\n long double r = 4;\n int display = 18;\n cout<<\"Using logistics equation\\n\";\n cout<<\"Initial Values: r: \"<<r<<\" x: \"<<x<<endl;\n cout<<\"Number of iterations: \"<<itr<<endl;\n cout << fixed << setprecision(6);\n rando(x,r,display);\n\n return 0;\n}"
}
] | 4
|
shanmeiliu/validating_postal_code
|
https://github.com/shanmeiliu/validating_postal_code
|
61b978299806172ab06b8482ddedf0834d0340a8
|
1f5278f4cfe38d2fe3411f573c7022d612a9c3cd
|
5bce30cc7bf38c261d404f7c5c9327864f9d0199
|
refs/heads/master
| 2020-09-16T18:59:56.545328
| 2019-11-25T16:01:59
| 2019-11-25T16:01:59
| 223,860,706
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5318351984024048,
"alphanum_fraction": 0.7490636706352234,
"avg_line_length": 6.388888835906982,
"blob_id": "027fd0403ec82f6d3a7dab4d6ec3ae0dd8989e90",
"content_id": "69de1b3b647c286e9f717ca1f523c5b8c256b6b4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 267,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 36,
"path": "/README.md",
"repo_name": "shanmeiliu/validating_postal_code",
"src_encoding": "UTF-8",
"text": "# validating_postal_code\nusing \"python without_if.py\" \n## some testing results for without_if.py in Python 3.7 \n\n3456789\nFalse\n\n123456\nTrue\n \n131245\nTrue\n \n121343\nFalse\n \n121314\nFalse\n \n00022\nFalse\n\n110000\nFalse\n\n552523\nFalse\n\n123\nFalse\n \n3f3456\nFalse\n\nasdfgh\nFalse\n\n"
},
{
"alpha_fraction": 0.625,
"alphanum_fraction": 0.6854838728904724,
"avg_line_length": 28.799999237060547,
"blob_id": "317a1efd3a3c0ec01e30f290edd1c03505bf36d4",
"content_id": "b5b402a6ddff42142cd94bd92597365aed0a0616",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 744,
"license_type": "no_license",
"max_line_length": 156,
"num_lines": 25,
"path": "/without_if.py",
"repo_name": "shanmeiliu/validating_postal_code",
"src_encoding": "UTF-8",
"text": "\"\"\"\nAuthor: Charmaine Liu\nNov 24, 2019\n\"\"\"\n\nregex_integer_in_range = r\"[1-9][0-9][0-9][0-9][0-9][0-9]\"\t# using regular expression to match 100000 to 999999\n\nregex_alternating_repetitive_digit_pair = r\"(\\d)(?=\\d\\1)\"\t# REF https://stackoverflow.com/questions/49325509/how-to-find-alternating-repetitive-digit-pair\n'''\nExplanation:\n\n (\\d): Match and capture a digit in group #1\n (?=: Start lookahead\n \\d: Match any digit\n \\1: Back-reference to captured group #1\n ): End lookahead\n\n'''\nimport re\nprint (\"Please enter the postal code you want to validate\")\nP=input()\n\n# using bool to validate 3 conditions\nprint (bool(re.match(regex_integer_in_range, P)) and len(P)==6 \\\nand len(re.findall(regex_alternating_repetitive_digit_pair, P)) < 2)"
},
{
"alpha_fraction": 0.48176583647727966,
"alphanum_fraction": 0.5278310775756836,
"avg_line_length": 19.076923370361328,
"blob_id": "3ca03881aa7354232ae5418e6c109ae3d0092b14",
"content_id": "951329bd8ea66cf6fa9f9c8d094f09030e9d54dc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 521,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 26,
"path": "/with_if.py",
"repo_name": "shanmeiliu/validating_postal_code",
"src_encoding": "UTF-8",
"text": "\"\"\"\nAuthor: Charmaine Liu\nNov 25, 2019\n\"\"\"\ndef validatingPostalCode(P):\n try:\n if int(P) > 999999 or int(P) < 100000:\n return False\n except Exception as e:\n print (e)\n return False\n count=0\n for i in range(0,4):\n if P[i] == P[i+2]:\n count+=1\n # print (count)\n if count>1:\n return False\n return True\n\n\n \nif __name__=='__main__':\n print(\"please enter the postal code you want to validate\")\n P=input()\n print (validatingPostalCode(P))"
}
] | 3
|
edawson/COSMIC2VCF
|
https://github.com/edawson/COSMIC2VCF
|
92442114e3cf907ad32b4f8cb3e0b89f6900c1eb
|
1766030f2521dfc28c0870c15dfebefbd6530d0d
|
d0a74566fde6250d25bd07abd25e30c89fdecabf
|
refs/heads/master
| 2020-06-02T18:52:31.476420
| 2019-09-10T20:43:34
| 2019-09-10T20:43:34
| 191,273,128
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7665677666664124,
"alphanum_fraction": 0.7754698395729065,
"avg_line_length": 35.10714340209961,
"blob_id": "f4695624922fabdd63f42aeab8f61a6c6f35bc40",
"content_id": "376c84d9f61c7bd240a659e45ad9f95fc06d036f",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1011,
"license_type": "permissive",
"max_line_length": 82,
"num_lines": 28,
"path": "/README.md",
"repo_name": "edawson/COSMIC2VCF",
"src_encoding": "UTF-8",
"text": "cosmic2vcf\n--------------\nConvert COSMIC structural variant TSV files to VCF format \nEric T Dawson \nJune 2019\n\n### Intro\nThe Catalog of Somatic Mutations in Cancer contains a publicly-available\nset of variant calls seen across many tumors. Some of these files (specifically\ncoding and non-coding small variants) are in the standard VCF format while others,\nmost notably the structural variant calls, are in a non-standard TSV format. This\nfrustrates their usage as inputs to other programs.\n\nThis repo contains a python script to convert the CosmicStructExport.tsv file\nto a standard VCF4.3 file that has the required SV info field tags such as \nSVLEN, SVTYPE, END, SPAN, etc. This VCF file can then be sorted/bgzipped/indexed\nand used in downstream analyses.\n\n### Usage\n```\npython cosmic_structexport_to_vcf.py -i CosmicStructExport.tsv > csv.vcf\n```\n\nCurrently, this script handles roughly 3/4 of the variants in COSMIC. It does no\nspecial handling of fold-back inversions or any other variants.\n\n### License\nMIT\n"
},
{
"alpha_fraction": 0.47240492701530457,
"alphanum_fraction": 0.47941091656684875,
"avg_line_length": 37.010868072509766,
"blob_id": "1746056b40b4dceb32c4929f1eeae59bd1d2e962",
"content_id": "c1f5efeae5fba3bf0ffd6c75b60ad2a52755e663",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6994,
"license_type": "permissive",
"max_line_length": 115,
"num_lines": 184,
"path": "/cosmic_structexport_to_vcf.py",
"repo_name": "edawson/COSMIC2VCF",
"src_encoding": "UTF-8",
"text": "from __future__ import print_function\nimport argparse\nimport sys\nimport re\nfrom statistics import mean\nfrom collections import defaultdict\nfrom math import floor\n\ndef parse_args():\n parser = argparse.ArgumentParser()\n parser.add_argument(\"-i\", \"--infile\", help=\"A CosmicStructExport.tsv file\", required=True, dest=\"infile\")\n\n return parser.parse_args()\n\ndef make_dummy_header():\n h = '##fileformat=VCFv4.3\\n'\n h += '##source=cosmic_structexport_to_vcf.py\\n'\n h += '##INFO=<ID=SVTYPE,Number=1,Type=String,Description=\"SV Type\">\\n'\n h += '##INFO=<ID=SVLEN,Number=1,Type=String,Description=\"SV length\">\\n'\n h += '##INFO=<ID=END,Number=1,Type=String,Description=\"END position of SV\">\\n'\n h += '##INFO=<ID=SPAN,Number=1,Type=String,Description=\"SPAN of SV\">\\n'\n h += '##INFO=<ID=CHR1_BP,Number=1,Type=String,Description=\"Breakpoint of SV on first CHROM\">\\n'\n h += '##INFO=<ID=CHR2_BP,Number=1,Type=String,Description=\"Breakpoint of SV on second CHROM\">\\n'\n h += '##INFO=<ID=CHR1,Number=1,Type=String,Description=\"First chromosome of SV\">\\n'\n h += '##INFO=<ID=CHR2,Number=1,Type=String,Description=\"Second chromosome of SV\">\\n'\n h += '##INFO=<ID=REF,Number=1,Type=String,Description=\"Reference genome of SV\">\\n'\n h += \"#CHROM\\tPOS\\tID\\tREF\\tALT\\tQUAL\\tFILTER\\tINFO\"\n\n return h\n\ndef make_header_dict(line):\n h = defaultdict(int)\n r = defaultdict(str)\n index = 0\n for i in line.strip().split(\"\\t\"):\n h[i] = index\n r[index] = i\n index += 1\n\n return h, r\n\ndef info_to_string(info):\n s = []\n for i in info:\n if info[i] is not None and info[i] != \"\":\n s.append(\"=\".join([i, str(info[i])]))\n\n return \";\".join(s)\n\nif __name__ == \"__main__\":\n\n args = parse_args()\n\n header_d = None\n reverse_d = None\n with open(args.infile, \"r\") as ifi:\n for line in ifi:\n if header_d is not None:\n tokens = line.strip().split(\"\\t\")\n mut_type = tokens[header_d[\"Mutation Type\"]]\n \n svtype = None\n svtag = None\n svlen = None\n span = None\n chrom = None\n chrom2 = None\n pos = None\n pos2 = None\n end = None\n ref = None\n alt = None\n id_field = None\n qual = \"99\"\n filter_field = \"\"\n info = defaultdict(str)\n\n location_info = tokens[header_d[\"description\"]]\n\n chrom = location_info.split(\":\")[0]\n\n location_info = \":\".join(location_info.split(\":\")[1:])\n if mut_type == \"intrachromosomal with non-inverted orientation\" or \\\n mut_type == \"intrachromosomal with inverted orientation\":\n location_info = re.sub(\"_chr[0-9XYMT]*:\", \"_\", location_info)\n if \"_chr\" in location_info:\n chrom2 = re.findall(\"_chr[0-9XYMT]*:\", location_info)[0].strip(\"_:\")\n if chrom2 is not None:\n location_info = re.sub(\"chr[A-Z0-9]{0,2}:[o]*\", \"\", location_info)\n\n\n\n location_info = location_info.strip(\"g.o\")\n stripped_location_info = location_info.strip(\"delinsinvdupbrkpttra\")\n intervals = re.findall(\"\\([0-9]*_[0-9XYMT]*\\)\", stripped_location_info)\n if len(intervals) == 0:\n splits = stripped_location_info.split(\"_\")\n pos = splits[0]\n end = splits[1]\n elif len(intervals) == 2:\n split_intervals = [i.strip(\"()\").split(\"_\") for i in intervals]\n mean_intervals = [floor(mean([int(j) for j in i])) for i in split_intervals]\n pos = mean_intervals[0]\n end = mean_intervals[1]\n\n else:\n sys.stderr.write(\"Nonstandard start/length intervals: \" + line + \"\\n\")\n continue\n \n if pos is not None:\n pos = str(pos).strip(\"o\")\n if end is not None:\n end = str(end).strip(\"o\")\n\n if not str(pos).isdigit() or not str(end).isdigit():\n sys.stderr.write(\"Not a digit \" + mut_type + \" \" + str(pos) + \" \" + str(end) + \"\\n\")\n continue\n \n pos = int(pos)\n end = int(end)\n\n\n\n\n ## Requires special handling because for some reason this seemed\n ## a reasonable format...\n if mut_type == \"intrachromosomal with inverted orientation\" or \\\n mut_type == \"intrachromosomal inversion\" or \\\n \"inv\" in location_info:\n svtype = \"INV\"\n svtag = \"<INV>\"\n elif mut_type == \"intrachromosomal deletion\" or \\\n mut_type == \"intrachromosomal with non-inverted orientation\" or \\\n mut_type == \"Intrachromosomal unknown type\" and \"bkpt\" in location_info or \\\n \"del\" in location_info:\n svtype = \"DEL\"\n svtag = \"<DEL>\"\n elif mut_type == \"Interchromosomal unknown type\" or \\\n mut_type == \"interchromosomal reciprocal translocation\" or \"TRA\" in location_info:\n svtype = \"TRA\"\n svtag = \"<TRA>\"\n elif mut_type == \"intrachromosomal tandem duplication\" or \"dup\" in location_info:\n svtype = \"DUP\"\n svtag = \"<DUP>\"\n\n elif \"ins\" in location_info:\n svtype = \"INS\"\n svtag = \"<INS>\"\n continue\n\n else:\n sys.stderr.write(\"Invalid SV type: \" + location_info + \" \" + mut_type + \"\\n\")\n continue\n\n if chrom == chrom2 and pos > end:\n tmp = pos\n pos = end\n end = tmp\n svlen = end - pos\n span = svlen\n if svtype == \"DEL\":\n svlen = -1 * svlen\n\n info[\"SVLEN\"] = svlen\n info[\"SVTYPE\"] = svtype\n info[\"END\"] = end\n info[\"SPAN\"] = span\n if chrom2 is not None:\n info[\"CHR2\"] = chrom2\n info[\"MUTTYPE\"] = str('\"' + mut_type.replace(\" \", \"_\") + '\"')\n\n id_field = \".\"\n filter_field = \"PASS\"\n ref = \"<N>\"\n alt = svtag\n\n \n infos = info_to_string(info)\n if svtype is not None:\n print(\"\\t\".join([str(i) for i in [chrom, pos, id_field, ref, alt, qual, filter_field, infos]]))\n\n else:\n header_d, reverse_d = make_header_dict(line)\n print(make_dummy_header())\n"
}
] | 2
|
P4G117/ProtocoloMESI
|
https://github.com/P4G117/ProtocoloMESI
|
ea92a7a9e9d67bceff658f3f778b661529ee00a9
|
f5049700ff2cf72b1fad323ef96000a29a122ce1
|
6cb9ef41cb5e73753afcdab14f13e5c47079c881
|
refs/heads/main
| 2023-08-03T02:52:48.587016
| 2021-09-27T04:54:06
| 2021-09-27T04:54:06
| 410,745,669
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5803213119506836,
"alphanum_fraction": 0.6041945815086365,
"avg_line_length": 33.152671813964844,
"blob_id": "110b2ea11867d1b6254162db4c690d27934a3c62",
"content_id": "26e5bb3a7e8dd47ed2e3aef7ea949a730510abd2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4483,
"license_type": "no_license",
"max_line_length": 122,
"num_lines": 131,
"path": "/procesadores.py",
"repo_name": "P4G117/ProtocoloMESI",
"src_encoding": "UTF-8",
"text": "#Creacion de la Clase Procesador \nimport scipy.stats\nfrom scipy.stats import poisson\nfrom random import getrandbits, randrange\nfrom random import randint\nfrom random import randrange\nimport random \nimport bloqueCache\nimport protocolo\nimport time\n\n#Variables para Probabilidad de Poisson\n#mu = 0.5\nk = randrange(11)\n\n#Generacion de la Direccion para la Instruccion: Caso Read y Write\ndef direccion():\n return random.randint(0,7)\n\n#Generacion del Dato de la Instruccion: Caso del Write \ndef dato():\n rand_hex_str = hex(randint(16, 65535))\n return rand_hex_str.replace(\"0x\",\"\") \n\n#Funcion para juntar en un String la Inst\ndef instFinal(ar):\n if(ar[1]==0):\n store = \"P\" + str(ar[0]) + \":\" + \" \" + \"calc\"\n elif(ar[1]== 1):\n store = \"P\" + str(ar[0]) + \":\" + \" \" + \"read\" + \",\" + \" \" + str(bin(ar[2])[2:].zfill(3)) \n else:\n store = \"P\" + str(ar[0]) + \":\" + \" \" + \"write\" + \",\" + \" \" + str(bin(ar[2])[2:].zfill(3)) + \",\" + \" \" + str(ar[3])\n return store\n\n#Creacion de Cache \n#Clase del Procesador\nclass Procesador:\n #Inicializamos el Procesador \n def __init__(self, numeroProce, memoria, busControl, mutex,instImprime):\n self.numProce = numeroProce\n self.memoria = memoria\n self.bus = busControl\n self.mutex = mutex\n self.cache = bloqueCache.cacheProcesador()\n self.hola = instImprime\n \n\n #Creacion de las Instrucciones \n def crearInstr(self, numProce):\n #Instrucciones Posibles\n mu = random.randint(0,10)\n #Calc = 0, Read = 1, Write = 2\n inst = poisson.rvs(mu,loc=k,size=1,random_state=None)\n var = [] #NumProce, Inst, Direccion y Dato\n if(0 <= inst <=3): \n var = [numProce, 0,0,0]\n return var\n elif(4 <= inst <=7):\n var = [numProce, 1,direccion(),0]\n return var\n else:\n var = [numProce, 2,direccion(),dato()]\n return var\n #Actualizar los Bloques de la Cache\n def actualizar(self, numProce):\n cacheActual = []\n for i in range(4):\n cacheActual.append(self.bus[numProce*4+i])\n\n self.cache.bloque0.setEstado(cacheActual[0][2])\n self.cache.bloque0.setDato(cacheActual[0][1])\n self.cache.bloque0.setDireccion(cacheActual[0][0])\n\n self.cache.bloque1.setEstado(cacheActual[1][2])\n self.cache.bloque1.setDato(cacheActual[1][1])\n self.cache.bloque1.setDireccion(cacheActual[1][0])\n\n self.cache.bloque2.setEstado(cacheActual[2][2])\n self.cache.bloque2.setDato(cacheActual[2][1])\n self.cache.bloque2.setDireccion(cacheActual[2][0])\n\n self.cache.bloque3.setEstado(cacheActual[3][2])\n self.cache.bloque3.setDato(cacheActual[3][1])\n self.cache.bloque3.setDireccion(cacheActual[3][0])\n \n #Imprimir los valores de los bloques de Cache\n def imprimirCache(self):\n \n print(self.cache.bloque0.getEstado())\n print(self.cache.bloque0.getDato())\n print(self.cache.bloque0.getDireccion())\n\n print(self.cache.bloque1.getEstado())\n print(self.cache.bloque1.getDato())\n print(self.cache.bloque1.getDireccion())\n\n print(self.cache.bloque2.getEstado())\n print(self.cache.bloque2.getDato())\n print(self.cache.bloque2.getDireccion())\n\n print(self.cache.bloque3.getEstado())\n print(self.cache.bloque3.getDato())\n print(self.cache.bloque3.getDireccion())\n\n #Funcion de Prueba\n def cambiaCache(self,pos):\n self.bus[pos][0] = random.getrandbits(10)\n self.bus[pos][1] = random.getrandbits(10)\n self.bus[pos][2] = \"Haloooo\"\n \n #Funcion para imprimir el Bus de Control\n def imprimirBus(self):\n for i in range(16):\n print(self.bus[i])\n print(\"\\n\")\n\n #Funcion para llamar al Protocolo \n def llamarProtocolo(self,numProce):\n time.sleep(2) \n timewait = randint(1,5)\n self.actualizar(numProce)\n inst = self.crearInstr(numProce)\n print(\" ------------------ Procesador en Ejecución:\", numProce, \"----------------------\")\n store = instFinal(inst)\n self.hola.append(store)\n print(\"La Instruccion es\", store)\n print(\"---------------- Comenzamos el Protocolo MESI ---------------\")\n self.mutex.acquire()\n protocolo.protoMesi(self,inst,numProce,self.memoria,self.bus,self.cache)\n self.mutex.release()\n time.sleep(timewait)\n "
},
{
"alpha_fraction": 0.8607594966888428,
"alphanum_fraction": 0.8607594966888428,
"avg_line_length": 38.5,
"blob_id": "d6f1fbbbde3229419c978b53aa89f12f3fcb988b",
"content_id": "3c90da7dc9a5f3f939853b5d3b6abfa47ae13d4e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 79,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 2,
"path": "/README.md",
"repo_name": "P4G117/ProtocoloMESI",
"src_encoding": "UTF-8",
"text": "# ProtocoloMESI\nProtocolo para coherencia de cache en sistemas multiprocesador\n"
},
{
"alpha_fraction": 0.6510313749313354,
"alphanum_fraction": 0.7159532904624939,
"avg_line_length": 51.8478889465332,
"blob_id": "1f915b8c13a7bddd12f93a926f596fb0fd77308f",
"content_id": "59200c3af3c4c044094ed5b49b1488d860b7a71d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 18766,
"license_type": "no_license",
"max_line_length": 108,
"num_lines": 355,
"path": "/main.py",
"repo_name": "P4G117/ProtocoloMESI",
"src_encoding": "UTF-8",
"text": "from random import randint\nimport random\nfrom procesadores import Procesador\nfrom threading import Thread, Lock\nimport threading\nimport time\nimport interfaz\nimport interfaz \nimport tkinter as tk\nimport tkinter as tk\nfrom tkinter import ttk\nfrom tkinter import *\n\n#Variable Global para Iniciar/Detener Flujo\nglobal Inicia\nInicia = False\n\nglobal instImprime \ninstImprime = []\n#Listas para los Datos\nvisualizarDatosMem = []\nvisualizarDatosBus = []\nvisualizarInsActual = []\nvisualizarInsAnteriores = []\nglobal instAnteriores\ninstAnteriores = [\" \",\" \",\" \",\" \"]\n\n#Iniciamos Flujo\ndef iniciaFlujo():\n global Inicia\n Inicia = True\n print(\"Comienzo Flujo\")\n\n#Detenemos Flujo\ndef detieneFlujo():\n global Inicia\n Inicia = False\n print(\"Detiene el Flujo\")\n\n#Funcion para la INterfaz\ndef creacionVenPrincipal(memoria, busControl):\n #Ventana Principal\n principal = tk.Tk()\n principal.title(\"Proyecto 1 - Protocolo Coherencia\")\n principal.geometry('640x760')\n principal.configure(background='pink')\n #Creacion de los Canvas\n #Canvas Principal\n canvas = Canvas(principal,bg=\"green\", width=640, height=760)\n canvas.pack()\n #Canvas para los Procesadores \n #Procesador 1\n canvas.create_rectangle(10,30,320,160,fill=\"white\")\n canvas.create_text(50,20,text=\"Procesador 1\",fill=\"yellow\")\n canvas.create_text(40,60,text=\"Bloque 0\",fill=\"blue\")\n canvas.create_text(40,80,text=\"Bloque 1\",fill=\"blue\")\n canvas.create_text(40,100,text=\"Bloque 2\",fill=\"blue\")\n canvas.create_text(40,120,text=\"Bloque 3\",fill=\"blue\")\n canvas.create_text(120,40,text=\"Dirección\",fill=\"blue\")\n #Direciones Bus Proce 1\n visualizarDatosBus.append(canvas.create_text(120,60,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,80,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,100,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,120,text=0,fill=\"black\"))\n canvas.create_text(200,40,text=\"Dato\",fill=\"blue\")\n #Datos Bus Proce 1\n visualizarDatosBus.append(canvas.create_text(200,60,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,80,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,100,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,120,text=0,fill=\"black\"))\n canvas.create_text(270,40,text=\"Estado\",fill=\"blue\")\n #Estados Bus Proce 1\n visualizarDatosBus.append(canvas.create_text(270,60,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,80,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,100,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,120,text=\"I\",fill=\"black\"))\n \n #Procesador 2\n canvas.create_rectangle(10,210,320,340,fill=\"white\")\n canvas.create_text(50,200,text=\"Procesador 2\",fill=\"yellow\")\n canvas.create_text(40,240,text=\"Bloque 0\",fill=\"blue\")\n canvas.create_text(40,260,text=\"Bloque 1\",fill=\"blue\")\n canvas.create_text(40,280,text=\"Bloque 2\",fill=\"blue\")\n canvas.create_text(40,300,text=\"Bloque 3\",fill=\"blue\")\n canvas.create_text(120,220,text=\"Dirección\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(120,240,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,260,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,280,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,300,text=0,fill=\"black\"))\n canvas.create_text(200,220,text=\"Dato\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(200,240,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,260,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,280,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,300,text=0,fill=\"black\"))\n canvas.create_text(270,220,text=\"Estado\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(270,240,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,260,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,280,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,300,text=\"I\",fill=\"black\"))\n #Procesador 3\n canvas.create_rectangle(10,390,320,520,fill=\"white\")\n canvas.create_text(50,380,text=\"Procesador 3\",fill=\"yellow\")\n canvas.create_text(40,420,text=\"Bloque 0\",fill=\"blue\")\n canvas.create_text(40,440,text=\"Bloque 1\",fill=\"blue\")\n canvas.create_text(40,460,text=\"Bloque 2\",fill=\"blue\")\n canvas.create_text(40,480,text=\"Bloque 3\",fill=\"blue\")\n canvas.create_text(120,400,text=\"Dirección\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(120,420,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,440,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,460,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,480,text=0,fill=\"black\"))\n canvas.create_text(200,400,text=\"Dato\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(200,420,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,440,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,460,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,480,text=0,fill=\"black\"))\n canvas.create_text(270,400,text=\"Estado\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(270,420,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,440,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,460,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,480,text=\"I\",fill=\"black\"))\n #Procesador 4\n canvas.create_rectangle(10,570,320,690,fill=\"white\")\n canvas.create_text(50,560,text=\"Procesador 4\",fill=\"yellow\")\n canvas.create_text(40,600,text=\"Bloque 0\",fill=\"blue\")\n canvas.create_text(40,620,text=\"Bloque 1\",fill=\"blue\")\n canvas.create_text(40,640,text=\"Bloque 2\",fill=\"blue\")\n canvas.create_text(40,660,text=\"Bloque 3\",fill=\"blue\")\n canvas.create_text(120,580,text=\"Dirección\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(120,600,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,620,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,640,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(120,660,text=0,fill=\"black\"))\n canvas.create_text(200,580,text=\"Dato\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(200,600,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,620,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,640,text=0,fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(200,660,text=0,fill=\"black\"))\n canvas.create_text(270,580,text=\"Estado\",fill=\"blue\")\n visualizarDatosBus.append(canvas.create_text(270,600,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,620,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,640,text=\"I\",fill=\"black\"))\n visualizarDatosBus.append(canvas.create_text(270,660,text=\"I\",fill=\"black\"))\n\n #Para Memoria \n canvas.create_rectangle(380,210,560,400,fill=\"white\")\n canvas.create_text(420,180,text=\"Memoria\",font=('family=Times,weight=bold,size=14'))\n canvas.create_text(430,220,text=\"Dirección\",fill=\"blue\")\n canvas.create_text(430,240,text=\"000\",fill=\"blue\")\n canvas.create_text(430,260,text=\"001\",fill=\"blue\")\n canvas.create_text(430,280,text=\"010\",fill=\"blue\")\n canvas.create_text(430,300,text=\"011\",fill=\"blue\")\n canvas.create_text(430,320,text=\"100\",fill=\"blue\")\n canvas.create_text(430,340,text=\"101\",fill=\"blue\")\n canvas.create_text(430,360,text=\"110\",fill=\"blue\")\n canvas.create_text(430,380,text=\"111\",fill=\"blue\")\n canvas.create_text(500,220,text=\"Dato\",fill=\"blue\")\n visualizarDatosMem.append(canvas.create_text(500,240,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,260,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,280,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,300,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,320,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,340,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,360,text=0,fill=\"black\"))\n visualizarDatosMem.append(canvas.create_text(500,380,text=0,fill=\"black\"))\n #Instrucciones de los Procesadores\n #Procesador 1\n canvas.create_text(420,420,text=\"Procesador 1\",font=('family=Times,weight=bold,size=14'))\n canvas.create_text(400,440,text=\"Inst Actual\",fill=\"blue\")\n visualizarInsActual.append(canvas.create_text(520,440,text=\" \",fill=\"black\"))\n canvas.create_text(405,460,text=\"Inst Anterior\",fill=\"blue\")\n visualizarInsAnteriores.append(canvas.create_text(520,460,text=\" \",fill=\"black\"))\n #Procesador 2\n canvas.create_text(420,480,text=\"Procesador 2\",font=('family=Times,weight=bold,size=14'))\n canvas.create_text(400,500,text=\"Inst Actual\",fill=\"blue\")\n visualizarInsActual.append(canvas.create_text(520,500,text=\" \",fill=\"black\"))\n canvas.create_text(405,520,text=\"Inst Anterior\",fill=\"blue\")\n visualizarInsAnteriores.append(canvas.create_text(520,520,text=\" \",fill=\"black\"))\n #Procesador 3\n canvas.create_text(420,540,text=\"Procesador 3\",font=('family=Times,weight=bold,size=14'))\n canvas.create_text(400,560,text=\"Inst Actual\",fill=\"blue\")\n visualizarInsActual.append(canvas.create_text(520,560,text=\" \",fill=\"black\"))\n canvas.create_text(405,580,text=\"Inst Anterior\",fill=\"blue\")\n visualizarInsAnteriores.append(canvas.create_text(520,580,text=\" \",fill=\"black\"))\n #Procesador 4\n canvas.create_text(420,600,text=\"Procesador 4\",font=('family=Times,weight=bold,size=14'))\n canvas.create_text(400,620,text=\"Inst Actual\",fill=\"blue\")\n visualizarInsActual.append(canvas.create_text(520,620,text=\" \",fill=\"black\"))\n canvas.create_text(405,640,text=\"Inst Anterior\",fill=\"blue\")\n visualizarInsAnteriores.append(canvas.create_text(520,640,text=\" \",fill=\"black\"))\n #Creamos los Botones para Comenzar y Pausar\n btn = Button(canvas, text='Comenzar', width=5,\n height=1, bd='1' ,command=iniciaFlujo)\n btn.place(x=400, y=10)\n\n btn2 = Button(canvas, text='Pausar', width=10,\n height=1, bd='1',command=detieneFlujo)\n btn2.place(x=480, y=10)\n \n return principal, canvas\n\n#Actualizamos los Datos del Bus \ndef updateDatosBus(canvas,busControl):\n #Datos del Procesador 1\n canvas.itemconfigure(visualizarDatosBus[0],text = bin(busControl[0][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[1],text = bin(busControl[1][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[2],text = bin(busControl[2][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[3],text = bin(busControl[3][0])[2:].zfill(3))\n\n canvas.itemconfigure(visualizarDatosBus[4],text = busControl[0][1])\n canvas.itemconfigure(visualizarDatosBus[5],text = busControl[1][1])\n canvas.itemconfigure(visualizarDatosBus[6],text = busControl[2][1])\n canvas.itemconfigure(visualizarDatosBus[7],text = busControl[3][1])\n\n canvas.itemconfigure(visualizarDatosBus[8],text = busControl[0][2])\n canvas.itemconfigure(visualizarDatosBus[9],text = busControl[1][2])\n canvas.itemconfigure(visualizarDatosBus[10],text = busControl[2][2])\n canvas.itemconfigure(visualizarDatosBus[11],text = busControl[3][2])\n #Datos del Procesador 2\n canvas.itemconfigure(visualizarDatosBus[12],text = bin(busControl[4][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[13],text = bin(busControl[5][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[14],text = bin(busControl[6][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[15],text = bin(busControl[7][0])[2:].zfill(3))\n\n canvas.itemconfigure(visualizarDatosBus[16],text = busControl[4][1])\n canvas.itemconfigure(visualizarDatosBus[17],text = busControl[5][1])\n canvas.itemconfigure(visualizarDatosBus[18],text = busControl[6][1])\n canvas.itemconfigure(visualizarDatosBus[19],text = busControl[7][1])\n\n canvas.itemconfigure(visualizarDatosBus[20],text = busControl[4][2])\n canvas.itemconfigure(visualizarDatosBus[21],text = busControl[5][2])\n canvas.itemconfigure(visualizarDatosBus[22],text = busControl[6][2])\n canvas.itemconfigure(visualizarDatosBus[23],text = busControl[7][2])\n #Datos del Procesador 3\n canvas.itemconfigure(visualizarDatosBus[24],text = bin(busControl[8][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[25],text = bin(busControl[9][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[26],text = bin(busControl[10][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[27],text = bin(busControl[11][0])[2:].zfill(3))\n\n canvas.itemconfigure(visualizarDatosBus[28],text = busControl[8][1])\n canvas.itemconfigure(visualizarDatosBus[29],text = busControl[9][1])\n canvas.itemconfigure(visualizarDatosBus[30],text = busControl[10][1])\n canvas.itemconfigure(visualizarDatosBus[31],text = busControl[11][1])\n\n canvas.itemconfigure(visualizarDatosBus[32],text = busControl[8][2])\n canvas.itemconfigure(visualizarDatosBus[33],text = busControl[9][2])\n canvas.itemconfigure(visualizarDatosBus[34],text = busControl[10][2])\n canvas.itemconfigure(visualizarDatosBus[35],text = busControl[11][2])\n #Datos del Procesador 4\n canvas.itemconfigure(visualizarDatosBus[36],text = bin(busControl[12][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[37],text = bin(busControl[13][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[38],text = bin(busControl[14][0])[2:].zfill(3))\n canvas.itemconfigure(visualizarDatosBus[39],text = bin(busControl[15][0])[2:].zfill(3))\n\n canvas.itemconfigure(visualizarDatosBus[40],text = busControl[11][1])\n canvas.itemconfigure(visualizarDatosBus[41],text = busControl[12][1])\n canvas.itemconfigure(visualizarDatosBus[42],text = busControl[14][1])\n canvas.itemconfigure(visualizarDatosBus[43],text = busControl[15][1])\n\n canvas.itemconfigure(visualizarDatosBus[44],text = busControl[12][2])\n canvas.itemconfigure(visualizarDatosBus[45],text = busControl[13][2])\n canvas.itemconfigure(visualizarDatosBus[46],text = busControl[14][2])\n canvas.itemconfigure(visualizarDatosBus[47],text = busControl[15][2])\n\n#Actualizamos los Datos de la Memoria \ndef updateDatosMem(canvas, memoria):\n canvas.itemconfigure(visualizarDatosMem[0],text = memoria[0])\n canvas.itemconfigure(visualizarDatosMem[1],text = memoria[1])\n canvas.itemconfigure(visualizarDatosMem[2],text = memoria[2])\n canvas.itemconfigure(visualizarDatosMem[3],text = memoria[3])\n canvas.itemconfigure(visualizarDatosMem[4],text = memoria[4])\n canvas.itemconfigure(visualizarDatosMem[5],text = memoria[5])\n canvas.itemconfigure(visualizarDatosMem[6],text = memoria[6])\n canvas.itemconfigure(visualizarDatosMem[7],text = memoria[7])\n\n#Actualizamos las Instrucciones Actuales\ndef updateInsActual(canvas, memoria):\n canvas.itemconfigure(visualizarInsActual[0],text = instImprime[0])\n canvas.itemconfigure(visualizarInsActual[1],text = instImprime[1])\n canvas.itemconfigure(visualizarInsActual[2],text = instImprime[2])\n canvas.itemconfigure(visualizarInsActual[3],text = instImprime[3])\n\n#Actualizamos las Instrucciones Anteriores\ndef updateInsAnterior(canvas, lista):\n canvas.itemconfigure(visualizarInsAnteriores[0],text = instAnteriores[0])\n canvas.itemconfigure(visualizarInsAnteriores[1],text = instAnteriores[1])\n canvas.itemconfigure(visualizarInsAnteriores[2],text = instAnteriores[2])\n canvas.itemconfigure(visualizarInsAnteriores[3],text = instAnteriores[3])\n \n#Funcion para Imprimir la Memoria\ndef imprimirMem(memoria):\n for i in range(8):\n print(memoria[i])\n\n#Creamos un Procesador\ndef crearProces(numProce, memoria, busControl, mutex,instImprime):\n procesador = Procesador(numProce,memoria,busControl,mutex,instImprime)\n procesador.llamarProtocolo(numProce)\n time.sleep(5)\n\n#Creamos el Hilo para cada Procesador Creado\ndef crearHilosProce(memoria, busControl, mutex,instImprime):\n threading.Thread(target=crearProces,args=(0, memoria,busControl,mutex,instImprime),daemon=True).start()\n time.sleep(5)\n threading.Thread(target=crearProces,args=(1, memoria,busControl,mutex,instImprime),daemon=True).start()\n time.sleep(5)\n threading.Thread(target=crearProces,args=(2, memoria,busControl,mutex,instImprime),daemon=True).start()\n time.sleep(5)\n threading.Thread(target=crearProces,args=(3, memoria,busControl,mutex,instImprime),daemon=True).start()\n time.sleep(5)\n\n#Funcion Principal \ndef main(): \n mutex = Lock()\n #Por cada Proce tengo: Dir, Dato y Estado\n #Para P1: del 0-3, bloques de la Cache \n #Para P2: del 4-7, bloques de la Cache \n #Para P3: del 8-11, bloques de la Cache \n #Para P4: del 12-15, bloques de la Cache \n busControl = [[0,0,\"M\"],[0,0,\"I\"],[6,\"aabb\",\"E\"],[0,0,\"I\"],[6,\"xyz1\",\"I\"],[0,0,\"I\"],[0,0,\"I\"],[0,0,\"I\"],\n [0,0,\"I\"],[4,0,\"S\"],[0,0,\"I\"],[0,0,\"I\"],[0,0,\"I\"],[0,0,\"I\"],[4,0,\"S\"],[0,0,\"I\"]]\n\n #Memoria Principal \n memoria = []\n #Iniciamos/Llenamos la Memoria con Valores en Hexadecimal\n for i in range(8):\n rand_hex_str = hex(randint(15, 65535))\n memoria.append(rand_hex_str.replace(\"0x\",\"\"))\n\n #Creamos la Ventana del Programa\n window = creacionVenPrincipal(memoria, busControl)\n\n #Comenzamos la Ejecucion\n while(True):\n window[0].update()\n if(Inicia): \n #Creamos lo Hilos\n crearHilosProce(memoria,busControl,mutex,instImprime)\n #Actualizamos los Datos de la MEM en la Interfaz \n updateDatosMem(window[1],memoria)\n #Actualizamos los Datos de los Bloques en la Interfaz\n updateDatosBus(window[1],busControl)\n #Actualizamos Inst Actuales en la Interfaz\n updateInsActual(window[1],instImprime)\n #Actualizamos Insen la Interfaz\n updateInsAnterior(window[1],instAnteriores)\n #Pasamos las Inst Anteriores\n for i in range(4):\n instAnteriores[i] = instImprime[i]\n #Seteamos para las nuevas Inst\n for i in range(len(instImprime)):\n instImprime.pop(0)\n \n#Iniciamos con el Protocolo y la Interfaz\nmain()\n"
},
{
"alpha_fraction": 0.5440714955329895,
"alphanum_fraction": 0.5653567910194397,
"avg_line_length": 39.136985778808594,
"blob_id": "d0cac6e52754fd3425549ae95e061b2752399fcf",
"content_id": "8081ea957102c2b2059b1a492a09f800f22376e0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14660,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 365,
"path": "/protocolo.py",
"repo_name": "P4G117/ProtocoloMESI",
"src_encoding": "UTF-8",
"text": "#Protocolo MESI\nimport bloqueCache\nimport time \nimport random \n\n#Funcion Principal del Protocolo de Coherencia MESI\ndef protoMesi(self, inst, numProce, memoria, bus, cache):\n print(\"Iniciamos Protcolo\")\n #Caso de que la Inst es el Calc \n if(inst[1] == 0):\n #time.sleep(1)\n print(\"La Instruccion fue un Calc\")\n time.sleep(2)\n\n #Caso de que la Inst es Read\n elif(inst[1]==1):\n print(\"La Instruccion fue un Read\")\n #Primer Caso: Read Hit\n dir = inst[2]\n #Lo encontre en mi Cache\n if((buscarCache(self,dir,cache) == True) and (diffInvalido(self,dir,cache)==True)):\n print(\"Caso 1: Hubo un Read Hit\")\n #No lo Encontre en mi cache: Read Miss\n #Lo voy a buscar a las Otras Caches\n #Aqui buscaría en el Bus \n #Caso 1: Read Miss - Read Hit\n else:\n print(\"Caso 2: Hubo un Read Miss\")\n if(buscarBus(self,dir,bus)==True):\n #Lo encontre en Otra Cache\n print(\"Read Miss -> Read Hit en Otra Cache\")\n otraCache(self,dir,bus,self.numProce)\n else:\n print(\"Caso 3: Hubo un Read Miss Miss\")\n print(\"Caso 3: Leo directo de Memoria\")\n #Caso 2: Read Miss - Read Miss\n #No lo encontre en ninguna Otra Cache\n #Tengo que ir hasta Memoria \n nuevoDato = memoria[dir]\n setNuevoDatoCache(self,numProce,bus,dir,nuevoDato)\n else:\n print(\"La Instruccion fue un Write\")\n dir = inst[2]\n #Caso 1: Write Hit en mi Cache\n #Escribo el nuevo dato en Memoria - Write Back desde mi Cache\n #Paso de E a M / Si estoy en M me quedo en M\n #Si estoy en S busco en las Otras Caches y las paso I \n if((buscarCache(self,dir,cache) == True)):\n print(\"Caso 1: Write Hit\")\n aux = verficaEstado(self,bus,dir)\n if(aux[0] == 1 or aux[0] == 2):\n print(\"Caso 1.1: Estado del Bloque es E O M\")\n dato = estadoM(self,dir,cache)\n #Hariamos Write Back\n memoria[dir]= dato[0]\n #Escribimos Datos en nuestra Cache\n setNuevoDatoCache2(self, numProce,bus,dir,inst[3],dato[1])\n elif(aux[0]==3):\n print(\"Caso 1.2: Estado del Bloque es S\")\n dato = cambioEstadoSE(self,dir,cache)\n #Hariamos Write Back\n memoria[dir] = dato[0]\n #Invalidamos a Todos los que tengan esa Direccion en S\n pasarInvalido(self,dir,bus)\n #Escribimos Datos en nuestra Cache\n setNuevoDatoCache3(self, numProce,bus,dir,inst[3],dato[1]) \n else:\n print(\"Caso 1.3: Estado del Bloque es I\")\n dato = estadoI(self,dir,cache)\n invalidarME(self,bus,dir,memoria)\n setNuevoDatoCache3(self, numProce,bus,dir,inst[3],dato[0])\n \n #Caso 2: Write Miss de mi Cache y Write Hit en las Otras Caches\n #Escribo el nuevo dato en Memoria - Write Back desde la Otra Cache\n #Paso de E/M a I en la Otra Cache\n #Si esta en S busco en las Otras Caches y las paso I \n elif((buscarCache(self,dir,cache) == False ) and (buscarBus(self,dir,bus)==True)):\n aux = verficaEstado(self,bus,dir)\n print(\"Caso 2: Write Miss\")\n if(aux[0] == 1 or aux[0] == 2):\n print(\"Caso 2.1: Estado del Bloque E o M en la Cache donde hubo Hit\")\n self.bus[aux[1]][2]=\"I\"\n #Hariamos Write Back\n memoria[dir]=self.bus[aux[1]][1]\n #Escribimos Datos en nuestra Cache\n setNuevoDatoCache(self, numProce,bus,dir,inst[3])\n elif(aux[0]==3):\n print(\"Caso 2.2: Estado del Bloque S en la Cache donde hubo Hit\")\n self.bus[aux[1]][2]=\"I\"\n #Hariamos Write Back\n memoria[dir]=self.bus[aux[1]][1]\n #Invalidamos a Todos los que tengan esa Direccion en S\n pasarInvalido(self,dir,bus)\n #Escribimos Datos en nuestra Cache\n setNuevoDatoCache(self, numProce,bus,dir,inst[3])\n \n elif(aux[0]==4):\n print(\"Caso 2.3: Estado del Bloque I en la Cache donde hubo Hit\")\n memoria[dir]=inst[3]\n setNuevoDatoCache(self, numProce,bus,dir,inst[3])\n #Caso 3: Write Miss de mi Cache y Write Miss de las Otras Caches\n #Escribo el nuevo dato en Memoria \n #Modifico Dir, Dato y Estado(pasa a E)\n \n elif((buscarCache(self,dir,cache) == False )and (buscarBus(self,dir,bus)==False)):\n print(\"Caso 3: Write Miss - Miss\")\n print(\"Vamos directo a Memoria\")\n memoria[dir]=inst[3]\n setNuevoDatoCache(self, numProce,bus,dir,memoria[dir])\n\n#Write Hit - Estado de mi Cache = I\n#Tengo que Invalidar en las Otras Caches si estan en E/M para esa Direccion\ndef invalidarME(self,bus,dir,memoria):\n for i in range(16):\n if(self.bus[i][0]==dir and self.bus[i][2] != \"M\"):\n self.bus[i][2] = \"I\"\n memoria[dir] = self.bus[i][1]\n if(self.bus[i][0]==dir and self.bus[i][2] != \"E\"):\n self.bus[i][2] = \"I\"\n memoria[dir] = self.bus[i][1]\n \n#Write Hit - Cambio Estado de E a M \ndef cambioEstadoEM(self, direccion, cache):\n dato = []\n if(direccion == self.cache.bloque0.getDireccion()):\n if(self.cache.bloque0.getEstado() == \"E\"):\n self.cache.bloque0.setEstado(\"M\") \n dato.append(self.cache.bloque0.getDato())\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque1.getDireccion()):\n if(self.cache.bloque1.getEstado() == \"E\"):\n self.cache.bloque1.setEstado(\"M\") \n dato.append(self.cache.bloque1.getDato())\n dato.append(1)\n return dato\n if(direccion == self.cache.bloque2.getDireccion()):\n if(self.cache.bloque2.getEstado() == \"E\"):\n self.cache.bloque2.setEstado(\"M\") \n print(self.cache.bloque2.getEstado())\n dato.append(self.cache.bloque2.getDato())\n dato.append(2)\n return dato\n if(direccion == self.cache.bloque3.getDireccion()):\n if(self.cache.bloque3.getEstado() == \"E\"):\n self.cache.bloque3.setEstado(\"M\") \n dato.append(self.cache.bloque3.getDato())\n dato.append(3)\n return dato\n return dato\n\n#Verifica si el Estado del Bloque es M\ndef estadoM(self, direccion, cache):\n dato = []\n if(direccion == self.cache.bloque0.getDireccion()):\n dato.append(self.cache.bloque0.getDato())\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque1.getDireccion()):\n dato.append(self.cache.bloque1.getDato())\n dato.append(1)\n return dato\n if(direccion == self.cache.bloque2.getDireccion()):\n dato.append(self.cache.bloque2.getDato())\n dato.append(2)\n return dato\n if(direccion == self.cache.bloque3.getDireccion()):\n dato.append(self.cache.bloque3.getDato())\n dato.append(3)\n return dato\n\n#Verifica si el Estado del Bloque es I\ndef estadoI(self, direccion, cache):\n dato = []\n if(direccion == self.cache.bloque0.getDireccion()):\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque1.getDireccion()):\n dato.append(1)\n return dato\n if(direccion == self.cache.bloque2.getDireccion()):\n dato.append(2)\n return dato\n if(direccion == self.cache.bloque3.getDireccion()):\n dato.append(3)\n return dato\n\n#Write Hit - Cambio el Estado del Bloque de S a E \ndef cambioEstadoSE(self, direccion, cache):\n dato = []\n if(direccion == self.cache.bloque0.getDireccion()):\n if(self.cache.bloque0.getEstado() == \"S\"):\n self.cache.bloque0.setEstado(\"E\") \n dato.append(self.cache.bloque0.getDato())\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque1.getDireccion()):\n if(self.cache.bloque1.getEstado() == \"S\"):\n self.cache.bloque1.setEstado(\"E\") \n dato.append(self.cache.bloque1.getDato())\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque2.getDireccion()):\n if(self.cache.bloque2.getEstado() == \"S\"):\n self.cache.bloque2.setEstado(\"E\")\n dato.append(self.cache.bloque2.getDato())\n dato.append(0)\n return dato\n if(direccion == self.cache.bloque3.getDireccion()):\n if(self.cache.bloque3.getEstado() == \"S\"):\n self.cache.bloque3.setEstado(\"E\") \n dato.append(self.cache.bloque3.getDato())\n dato.append(0)\n return dato\n\n#Para Buscar en la Cache Propia a ver si hay un Hit\ndef buscarCache(self, direccion, cache):\n if(direccion == self.cache.bloque0.getDireccion()):\n if(self.cache.bloque0.getEstado() != \"I\"):\n return True\n if(direccion == self.cache.bloque1.getDireccion()):\n if(self.cache.bloque1.getEstado() != \"I\"):\n return True\n if(direccion == self.cache.bloque2.getDireccion()):\n if(self.cache.bloque2.getEstado() != \"I\"):\n return True\n if(direccion == self.cache.bloque3.getDireccion()):\n if(self.cache.bloque3.getEstado() != \"I\"):\n return True\n return False\n\n#Para saber si el Estado del Bloque es diferente a Invalido\ndef diffInvalido(self, direccion, cache):\n if(direccion == self.cache.bloque0.getDireccion()):\n return True\n if(direccion == self.cache.bloque1.getDireccion()):\n return True\n if(direccion == self.cache.bloque2.getDireccion()):\n return True\n if(direccion == self.cache.bloque3.getDireccion()):\n return True\n return False\n\n#Cambiamos Estado de la Otra Cache donde Encontramos el Dato para Read Miss -> Read Hit\ndef cambiarEstOtrCacheRM(self, bloque, bus):\n if(self.bus[bloque][2] == \"M\"):\n self.bus[bloque][2] = \"S\"\n if(self.bus[bloque][2] == \"E\"):\n self.bus[bloque][2] = \"S\"\n if(self.bus[bloque][2] == \"S\"):\n self.bus[bloque][2] = \"S\"\n\n#Cambio Estado de la Cache desde donde Intente hacer la Instruccion \ndef cambiarEstCachePropiaRM(self, numProce,bus,dir):\n #Primer Caso. Primer Bloque del Procesador\n if(self.bus[numProce*4][0]==dir):\n if(self.bus[numProce*4][2] == \"S\"):\n self.bus[numProce*4][2] = \"S\"\n if(self.bus[numProce*4][2] == \"I\"):\n self.bus[numProce*4][2] = \"S\"\n if(self.bus[numProce*4][2] == \"E\"):\n self.bus[numProce*4][2] = \"S\"\n if(self.bus[numProce*4][2] == \"M\"):\n self.bus[numProce*4][2] = \"S\"\n #Segundo Caso. Segundo Bloque del Procesador\n if(self.bus[numProce*4+1][0]==dir):\n if(self.bus[numProce*4+1][2] == \"S\"):\n self.bus[numProce*4+1][2] = \"S\"\n if(self.bus[numProce*4+1][2] == \"I\"):\n self.bus[numProce*4+1][2] = \"S\"\n if(self.bus[numProce*4+1][2] == \"E\"):\n self.bus[numProce*4+1][2] = \"S\"\n if(self.bus[numProce*4+1][2] == \"M\"):\n self.bus[numProce*4+1][2] = \"S\"\n #Tercer Caso. Tercer Bloque del Procesador\n if(self.bus[numProce*4+2][0]==dir):\n if(self.bus[numProce*4+2][2] == \"S\"):\n self.bus[numProce*4+2][2] = \"S\"\n if(self.bus[numProce*4+2][2] == \"I\"):\n self.bus[numProce*4+2][2] = \"S\"\n if(self.bus[numProce*4+2][2] == \"E\"):\n self.bus[numProce*4+2][2] = \"S\"\n if(self.bus[numProce*4+2][2] == \"M\"):\n self.bus[numProce*4+2][2] = \"S\"\n #Tercer Caso. Tercer Bloque del Procesador\n if(self.bus[numProce*4+3][0]==dir):\n if(self.bus[numProce*4+3][2] == \"S\"):\n self.bus[numProce*4+3][2] = \"S\"\n if(self.bus[numProce*4+3][2] == \"I\"):\n self.bus[numProce*4+3][2] = \"S\"\n if(self.bus[numProce*4+3][2] == \"E\"):\n self.bus[numProce*4+3][2] = \"S\"\n if(self.bus[numProce*4+3][2] == \"M\"):\n self.bus[numProce*4+3][2] = \"S\"\n\n#Buscar si la Direccion esta en Otra Cache\ndef buscarBus(self,dir,bus):\n for i in range(16):\n if(self.bus[i][0]==dir):\n return True\n return False\n\n#Obtener Bloque de la Cache del Bus donde se encontro la Dirección \ndef otraCache(self, dir,bus,numProce):\n for i in range(16):\n if(self.bus[i][0]==dir and self.bus[i][2] != \"I\"):\n self.bus[i][2] = \"S\"\n setNuevoDatoCacheMH(self, numProce,bus,dir,self.bus[i][1])\n\n#Pasamos el Estado de un Bloque de S a I\ndef pasarInvalido(self, dir,bus):\n for i in range(16):\n if(self.bus[i][0]==dir and self.bus[i][2] == \"S\"):\n self.bus[i][2] = \"I\"\n\n#Verifica el Estado del Bloque para saber si es E, M, S o I\ndef verficaEstado(self,bus,dir):\n aux = []\n for i in range(16):\n if(self.bus[i][0]==dir):\n if(self.bus[i][2] == \"M\"):\n aux.append(1)\n aux.append(i)\n return aux\n if(self.bus[i][2] == \"E\"):\n aux.append(2)\n aux.append(i)\n return aux\n if(self.bus[i][2] == \"S\"):\n aux.append(3)\n aux.append(i)\n return aux\n else:\n aux.append(4)\n return aux\n\n#Setear Nuevo Estado a la Cache desde donde Busque \n#Traemos el dato desde Memoria\ndef setNuevoDatoCache(self, numProce,bus,dir,dato):\n #Estariamos haciendo el Set siempre en el bloque \n pos = random.randint(0,3)\n self.bus[numProce*4 + pos][0] = dir\n self.bus[numProce*4 + pos][1] = dato\n self.bus[numProce*4 + pos][2] = \"E\"\n\ndef setNuevoDatoCache2(self, numProce,bus,dir,dato,posBloque):\n #Estariamos haciendo el Set siempre en el bloque \n pos = posBloque\n self.bus[numProce*4 + pos][0] = dir\n self.bus[numProce*4 + pos][1] = dato\n self.bus[numProce*4 + pos][2] = \"M\"\n\ndef setNuevoDatoCache3(self, numProce,bus,dir,dato,posBloque):\n #Estariamos haciendo el Set siempre en el bloque \n pos = posBloque\n self.bus[numProce*4 + pos][0] = dir\n self.bus[numProce*4 + pos][1] = dato \n self.bus[numProce*4 + pos][2] = \"E\"\n\ndef setNuevoDatoCacheMH(self, numProce,bus,dir,dato):\n #Estariamos haciendo el Set siempre en el bloque \n pos = random.randint(0,3)\n self.bus[numProce*4 + pos][0] = dir\n self.bus[numProce*4 + pos][1] = dato\n self.bus[numProce*4 + pos][2] = \"S\" "
},
{
"alpha_fraction": 0.624365508556366,
"alphanum_fraction": 0.6359680891036987,
"avg_line_length": 28.95652198791504,
"blob_id": "aab741533eb92765205762ffec21914603c0560b",
"content_id": "497302a20c3d08495e044afb8a61ef909ba7a4a3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1388,
"license_type": "no_license",
"max_line_length": 59,
"num_lines": 46,
"path": "/bloqueCache.py",
"repo_name": "P4G117/ProtocoloMESI",
"src_encoding": "UTF-8",
"text": "#Clase para los bloques de cache \n\nclass bloqueCache:\n #Inicializacion de la clase\n #Número del Bloque: numbloque\n #Estado del Bloque: estado\n #Dirección Memoria: direccion\n #Dato del Bloque: dato\n def __init__(self, numbloque, estado, direccion, dato):\n self.numbloque = numbloque\n self.estado = estado\n self.direccion = direccion\n self.dato = dato\n\n #Funciones Get\n #Para el número de Bloque \n def getnumBloque(self):\n return self.numbloque\n #Para el número de Bloque \n def getEstado(self):\n return self.estado\n #Para el número de Bloque \n def getDireccion(self):\n return self.direccion\n #Para el número de Bloque \n def getDato(self):\n return self.dato\n\n #Funciones Set\n #Para el número de Bloque \n def setEstado(self, nuevo_estado):\n self.estado = nuevo_estado\n #Para el número de Bloque \n def setDireccion(self, nueva_dir):\n self.direccion = nueva_dir\n #Para el número de Bloque \n def setDato(self, nuevo_dato):\n self.dato = nuevo_dato\n\n#Inicializacion de las Caches para cada Procesador\nclass cacheProcesador:\n def __init__(self):\n self.bloque0 = bloqueCache(0, \"I\", 0, 0)\n self.bloque1 = bloqueCache(1, \"I\", 0, 0)\n self.bloque2 = bloqueCache(2, \"I\", 0, 0)\n self.bloque3 = bloqueCache(3, \"I\", 0, 0)\n\n"
}
] | 5
|
JoshOffCenter/Page-Pass
|
https://github.com/JoshOffCenter/Page-Pass
|
a7668bd49c0bb165f453cb1b5d5500dfc1b94df6
|
21252831d611913d4a78357dfc52bf5a463db55e
|
94544bd5f88feba8b88ef9be8ca2dc10a920fdea
|
refs/heads/master
| 2016-05-30T03:26:26.093003
| 2015-08-19T07:08:34
| 2015-08-19T07:08:34
| 41,014,836
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7297921180725098,
"alphanum_fraction": 0.7505773901939392,
"avg_line_length": 35.08333206176758,
"blob_id": "c954a01b0949c7ea7b1867f362b68685d3305319",
"content_id": "cef8f69ddfed5910a78806c50853536fd43c69ba",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 433,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 12,
"path": "/cloud/cloud_tests/deleteTextBook.py",
"repo_name": "JoshOffCenter/Page-Pass",
"src_encoding": "UTF-8",
"text": "# coding: utf-8\rimport json,httplib,urllib\rconnection = httplib.HTTPSConnection('api.parse.com', 443)\rconnection.connect()\rconnection.request('POST', '/1/functions/deleteTextBook', json.dumps({\r\"textBookId\": \"gVTuOjOrAh\"\r}), {\r\"X-Parse-Application-Id\": \"LjoUUKvQvdsKjUTyCbA6DW7fk5O6ZudQzbdFVPIl\",\r\"X-Parse-REST-API-Key\": \"CFoLiuh3STrjtCwugXYNLh06pS8JIg3gVjNrPJZS\",\r\"Content-Type\": \"application/json\"})\rresult = json.loads(connection.getresponse().read())\rprint result\r"
},
{
"alpha_fraction": 0.5989847779273987,
"alphanum_fraction": 0.6125211715698242,
"avg_line_length": 20.88888931274414,
"blob_id": "de7e891f050f7316496c5c53703ba1f8702fc7cf",
"content_id": "efc6c2d7f1d0339198391cd24c5e78bc23ae3e9a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Swift",
"length_bytes": 591,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 27,
"path": "/PagePass.xcodeproj/TextBook.swift",
"repo_name": "JoshOffCenter/Page-Pass",
"src_encoding": "UTF-8",
"text": "//\n// TextBook.swift\n// PagePass\n//\n// Created by Josh Carter on 7/7/15.\n// Copyright (c) 2015 Josh Carter. All rights reserved.\n//\n\nimport UIKit\nimport Parse\n\nclass TextBook {\n \n let title, author, isbn, condition,price, id: String!\n let coverFile: PFFile!\n\n init(title:String, author:String, isbn:String, condition:String, price:String, coverFile:PFFile, id:String) {\n \n self.title = title\n self.author = author\n self.isbn = isbn\n self.condition = condition\n self.price = price\n self.coverFile = coverFile\n self.id = id\n }\n}\n"
},
{
"alpha_fraction": 0.6821983456611633,
"alphanum_fraction": 0.6869773268699646,
"avg_line_length": 28.85714340209961,
"blob_id": "7313398b8ff7d23cae6c891b64ef44fc5599fb80",
"content_id": "824733ea6741a63e297341ccc5003c9ea5795e3d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 837,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 28,
"path": "/cloud/cloud/main.js",
"repo_name": "JoshOffCenter/Page-Pass",
"src_encoding": "UTF-8",
"text": "\n// Use Parse.Cloud.define to define as many cloud functions as you want.\n// For example:\nParse.Cloud.define(\"hello\", function(request, response) {\n response.success(\"Hello world!\");\n});\nfunction arrayAdd(array) {\n var counter = 0;\n for(var i = 0; i < array.length; i++) {\n counter += array[i];\n }\n return counter;\n}\n\nParse.Cloud.define(\"deleteTextBook\", function(request, response){\n var textBookId = request.params.textBookId\n var textBookQuery = new Parse.Query(\"TextBook\")\n textBookQuery.equalTo(\"objectId\", textBookId)\n textBookQuery.find().then(function(textBook_list){\n if (textBook_list.length > 0) {\n var textBook = textBook_list[0]\n return textBook.destroy()\n }\n }).then(function(destroyed_textBook){\n response.success(\"Textbook Deleted\")\n }, function(error){\n response.error(error)\n })\n})\n"
}
] | 3
|
StatML/speaker_recognition
|
https://github.com/StatML/speaker_recognition
|
90660ca00ac4b8f22914829a702ee34bb5f93f71
|
d9f510a0b3967cc86d2c910a54a54ff50a6b578e
|
428fdb329e14c211740948606d96d9087b51b777
|
refs/heads/master
| 2021-01-25T04:58:28.692462
| 2017-03-07T11:48:21
| 2017-03-07T11:48:21
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.674746572971344,
"alphanum_fraction": 0.6800352334976196,
"avg_line_length": 31.41428565979004,
"blob_id": "83ac5c1f3b19008efc1ce35cd9e08836e246acfd",
"content_id": "bb7ad60aa24df8af1204a277408ff6417225c69e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2269,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 70,
"path": "/demo.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import os\nfrom speaker_verifier import SpeakerVerifier\nfrom codecs import open\nimport time\nfrom flask import Flask, render_template, request\nimport re\napp = Flask(__name__)\n\nprint \"Preparing speaker verifier\"\nstart_time = time.time()\nverifier = SpeakerVerifier()\nprint \"The model is ready\"\nprint time.time() - start_time, \"seconds\"\ntest_file_name = 'tmp_test.wav' # PATH for saving wav files that are passed during verification stage\ntrain_folder_name = verifier.get_train_path()\n\n\ndef is_int(x):\n\tmatch = re.search(\"\\D\", x)\n\tif not match:\n\t\treturn True\n\telse:\n\t\treturn False\n\n@app.route(\"/speaker-verifier-demo\", methods=[\"POST\", \"GET\"])\ndef index_page(prediction=\"\", users=\"\"):\n\tusers = verifier.get_users()\n\tresult = ''\n\tif request.method == \"POST\":\n\t\tif request.form['bsubmit'] == 'Reset': \n\t\t\tusers = verifier.reset_classifier()\n\n\t\telif request.form['bsubmit'] == 'Upload': # DO TESTING\t\t\t\n\t\t\tf = request.files['file_for_test']\n\t\t\tif f.filename == '':\n\t\t\t\tprint('No selected file')\n\t\t\tif f.filename.find('wav')==-1 and f.filename.find('flac')==-1:\n\t\t\t\tprint('Selected file is not in audio format (WAV or FLAC)!')\n\t\t\tf.save(test_file_name)\n\t\t\tresult = verifier.verify(test_file_name)\n\n\t\telif request.form['bsubmit'] == 'Upload files': # DO TRAINING\n\t\t\tuploaded_files = request.files.getlist(\"files_for_training\")\n\t\t\tuserid = request.form[\"userid\"]\n\n\t\t\tfilenames = []\n\t\t\tfor file in uploaded_files:\n\t\t\t\t# Check if the file is one of the allowed types/extensions\n\t\t\t\tif file and (file.filename.find('wav')>0 or file.filename.find('flac')>0):\n\t\t\t\t\tfilename = file.filename\n\t\t\t\t\t# Move the file form the temporal folder to the upload folder \n\t\t\t\t\tfull_path = os.path.join(train_folder_name, filename)\n\t\t\t\t\tfile.save(full_path)\n\t\t\t\t\t# Save the filename into a list, we'll use it later\n\t\t\t\t\tfilenames.append(full_path)\t\t\t\t\t\n\t\t\t\telse:\n\t\t\t\t\tprint('Selected file \"%s\" is not in WAV or FLAC format!' % file.filename)\n\n\t\t\tif (is_int(userid)) and (int(userid) in users.keys()):\n\t\t\t\tverifier.train_existing_user(filenames, int(userid))\n\t\t\telse:\n\t\t\t\tverifier.train_new_user(filenames, userid)\n\t\t\t\tusers = verifier.get_users()\n\t\t\t\n\n\treturn render_template('hello.html', prediction=result, users=users)\n\n\nif __name__ == \"__main__\":\n\tapp.run(host='0.0.0.0', port=6006, debug=False)\n"
},
{
"alpha_fraction": 0.634482741355896,
"alphanum_fraction": 0.634482741355896,
"avg_line_length": 19.714284896850586,
"blob_id": "fb9c6b311d06dbe354a01a61496918faf43e70d9",
"content_id": "d831423064b0ea27991354719dcfb6357e29563e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 290,
"license_type": "no_license",
"max_line_length": 40,
"num_lines": 14,
"path": "/frontend/src/verifier/containers/LayoutView.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React from 'react';\nimport {connect} from 'react-redux';\nimport View from '../components/Layout';\n\nexport default connect((state) => ({\n users: state.users,\n}))((props) => (\n <View\n isSend={props.users.isSend}\n users={props.users.data}\n >\n {props.children}\n </View>\n));"
},
{
"alpha_fraction": 0.4503735303878784,
"alphanum_fraction": 0.45517608523368835,
"avg_line_length": 22.13580322265625,
"blob_id": "39dbd9a90636805866f113845c4ce1f3d43d160a",
"content_id": "6b15a36b70cf50507aab5b7e7b98471eaff9c355",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1874,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 81,
"path": "/frontend/src/verifier/components/Train.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React, { Component, PropTypes } from 'react';\nimport Timer from './Timer';\nimport '../resources/button.css';\n\nexport default class Train extends Component {\n\n static propTypes = {\n onClick: PropTypes.func.isRequired,\n isSend: PropTypes.bool.isRequired\n };\n\n state = {\n userId: null,\n files: []\n };\n\n _onClick = () => {\n this.props.onClick(\n this.state.userId,\n this.state.files\n );\n };\n\n _onChangeUserId = (value) => {\n this.setState({userId: value});\n };\n\n render() {\n return (\n \t<div>\n <p>\n Upload multiple files for trainig (new or existing user):<br/>\n Input user id for training (from the list above).<br/>\n Or just input a name for new user!\n </p>\n <input\n type=\"number\"\n value={this.state.user_id}\n name=\"userid\"\n min=\"1\"\n step=\"1\"\n onChange={(e) => {\n this._onChangeUserId(parseInt(e.target.value, 0));\n }}\n />\n <Timer\n max={10}\n long={5}\n onAdd={(filename, blob) => {\n this.setState({\n files: this.state.files.concat([{\n key: filename,\n data: blob\n }])\n });\n }}\n onDelete={(id) => {\n this.setState({\n files: this.state.files.filter(_ => _.key !== id),\n });\n }}\n />\n <p> Send user: </p>\n <p style={\n {\n display: (this.state.files.length > 1 && parseInt(this.state.userId, 0) > 0) ? 'initial' : 'none'\n }\n }>\n <input\n type=\"button\"\n value=\"Upload files\"\n className=\"button\"\n disabled={this.props.isSend}\n onClick={() => this._onClick()}\n />\n </p>\n\t </div>\n );\n }\n\n}"
},
{
"alpha_fraction": 0.5655608177185059,
"alphanum_fraction": 0.5655608177185059,
"avg_line_length": 22.44444465637207,
"blob_id": "90746d32c15595cf4a7248d5f01d4b1dc6dafebd",
"content_id": "111389b6109df10498707081ca8e2ca95ea9ea94",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 633,
"license_type": "no_license",
"max_line_length": 50,
"num_lines": 27,
"path": "/frontend/src/verifier/containers/ResetView.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React from 'react';\nimport View from '../components/ResetClassifier';\nimport { connect } from 'react-redux';\nimport { reset } from '../api/verifier';\nimport { send, complete } from '../actions/reset';\nimport { clear } from '../actions/users';\n\nexport default connect((state) => ({\n isSend: state.reset.send\n}), (dispatch) => ({\n onReset() {\n dispatch(send());\n reset()\n .then(\n data => dispatch(complete()),\n err => dispatch(complete(err))\n )\n .then(\n () => dispatch(clear())\n );\n }\n}))((props) =>\n <View\n isSend={props.isSend}\n onClick={() => props.onReset()}\n />\n);"
},
{
"alpha_fraction": 0.6819262504577637,
"alphanum_fraction": 0.6819262504577637,
"avg_line_length": 35.565216064453125,
"blob_id": "90af933947f4d49901a6abee4791941148be7bc9",
"content_id": "3cad36acaecb71a6c6f2bc800b256b0d792714b7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1682,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 46,
"path": "/frontend/src/index.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import React from 'react';\nimport ReactDOM from 'react-dom';\nimport App from './layout/components/App';\nimport PageNotFound from './layout/components/PageNotFound';\nimport './index.css';\nimport { Router, Route, browserHistory, IndexRedirect } from 'react-router';\nimport reducers from './verifier/reducers/index';\nimport LayoutView from './verifier/containers/LayoutView';\nimport ResetView from './verifier/containers/ResetView';\nimport TrainView from './verifier/containers/TrainView';\nimport VerifyView from './verifier/containers/VerifyView';\nimport { getUsers } from './verifier/api/verifier';\nimport { send, complete } from './verifier/actions/users';\nimport { createStore, combineReducers } from 'redux'\nimport { Provider } from 'react-redux'\nimport { syncHistoryWithStore, routerReducer } from 'react-router-redux'\n\nconst store = createStore(\n combineReducers({\n ...reducers,\n routing: routerReducer\n })\n);\n\nconst history = syncHistoryWithStore(browserHistory, store);\n\nstore.dispatch(send());\ngetUsers()\n .then(data => store.dispatch(complete(null, data)))\n .then(() => ReactDOM.render(\n <Provider store={store}>\n <Router history={history}>\n <Route path=\"/\" component={App}>\n <IndexRedirect to=\"/train\" />\n <Route path=\"/\" component={LayoutView}>\n <Route path=\"reset\" component={ResetView}/>\n <Route path=\"train\" component={TrainView}/>\n <Route path=\"verify\" component={VerifyView}/>\n <Route path='*' component={PageNotFound} />\n </Route>\n </Route>\n </Router>\n </Provider>,\n document.getElementById('root')\n ))\n .catch(err => store.dispatch(complete(err)));\n"
},
{
"alpha_fraction": 0.5898801684379578,
"alphanum_fraction": 0.5898801684379578,
"avg_line_length": 22.5,
"blob_id": "b1ef5efa03e34c931d00e4155606c008f11027a8",
"content_id": "5aaaf175aed866da1573c4b936ebf24e4cc23173",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 751,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 32,
"path": "/frontend/src/verifier/api/verifier.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import 'whatwg-fetch';\n\nexport function train(userId, files) {\n const formData = new FormData();\n files.map(_ => formData.append('files_for_training[]', _.data, `${_.key}.wav`));\n formData.append('userid', userId);\n\n return fetch('/api/train', {\n method: 'POST',\n body: formData\n })\n .then(res => res.json());\n}\n\nexport const verify = (file) => {\n const formData = new FormData();\n formData.append('file_for_test', file.data, `${file.key}.wav`);\n\n return fetch('/api/verify',{\n method: 'POST',\n body: formData\n })\n .then(res => res.json());\n};\n\nexport const reset = () => fetch('/api/reset', {\n method: 'POST'\n })\n .then(res => res.json());\n\nexport const getUsers = () => fetch('/api/users')\n .then(res => res.json());"
},
{
"alpha_fraction": 0.5661016702651978,
"alphanum_fraction": 0.5661016702651978,
"avg_line_length": 20.10714340209961,
"blob_id": "18a0a10b2cc38fb4a85628f71a2c855f7f9aaf67",
"content_id": "0313e3afd2965ec10edc5fdf35a98a045365c859",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 590,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 28,
"path": "/frontend/src/verifier/components/ResetClassifier.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import React, { Component, PropTypes } from 'react';\nimport '../resources/button.css';\n\nexport default class ResetClassifier extends Component {\n\n static propTypes = {\n onClick: PropTypes.func.isRequired,\n isSend: PropTypes.bool.isRequired\n };\n\n _onClick = () => this.props.onClick();\n\n render() {\n return (\n <div>\n <p> Remove previously saved data: </p>\n <input\n disabled={this.props.isSend}\n className=\"button\"\n type=\"button\"\n value=\"Reset\"\n onClick={() => this._onClick()}\n />\n </div>\n );\n }\n\n}"
},
{
"alpha_fraction": 0.5958378911018372,
"alphanum_fraction": 0.6297919154167175,
"avg_line_length": 35.046051025390625,
"blob_id": "5504cdd73c68aca6914b4b3abb9f283cd5b64cd7",
"content_id": "3cc1960828f86632d2479db5a908470c2a15f800",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5478,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 152,
"path": "/speaker_libri_vgg_finetuning.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import tensorflow as tf\nimport tflearn\nfrom tflearn.data_preprocessing import ImagePreprocessing\nimport os\n\nfrom tflearn.data_utils import build_hdf5_image_dataset\nimport h5py\n\nfrom random import shuffle\n\nimport numpy\n\n\ndef vgg16(input, num_class):\n\n x = tflearn.conv_2d(input, 64, 3, activation='relu', scope='conv1_1')\n x = tflearn.conv_2d(x, 64, 3, activation='relu', scope='conv1_2')\n x = tflearn.max_pool_2d(x, 2, strides=2, name='maxpool1')\n\n x = tflearn.conv_2d(x, 128, 3, activation='relu', scope='conv2_1')\n x = tflearn.conv_2d(x, 128, 3, activation='relu', scope='conv2_2')\n x = tflearn.max_pool_2d(x, 2, strides=2, name='maxpool2')\n\n x = tflearn.conv_2d(x, 256, 3, activation='relu', scope='conv3_1')\n x = tflearn.conv_2d(x, 256, 3, activation='relu', scope='conv3_2')\n x = tflearn.conv_2d(x, 256, 3, activation='relu', scope='conv3_3')\n x = tflearn.max_pool_2d(x, 2, strides=2, name='maxpool3')\n\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv4_1')\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv4_2')\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv4_3')\n x = tflearn.max_pool_2d(x, 2, strides=2, name='maxpool4')\n\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv5_1')\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv5_2')\n x = tflearn.conv_2d(x, 512, 3, activation='relu', scope='conv5_3')\n x = tflearn.max_pool_2d(x, 2, strides=2, name='maxpool5')\n\n x = tflearn.fully_connected(x, 4096, activation='relu', scope='fc6')\n x = tflearn.dropout(x, 0.5, name='dropout1')\n\n x = tflearn.fully_connected(x, 4096, activation='relu', scope='fc7')\n x = tflearn.dropout(x, 0.5, name='dropout2')\n\n x = tflearn.fully_connected(x, num_class, activation='softmax', scope='fc8',\n restore=False)\n\n return x\n\n\nTRAIN_DATA_PATH = \"data/LibriSpeech/test-clean\"\nDATASET_FILE = \"data/LibriSpeech/test-clean-spectro_vgg.txt\"\n\ndef get_libri_data(path): \n def ispng(name):\n return \"png\"==name.split(\".\")[-1]\n\n labels=[]\n data=[]\n speakers = [d for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]\n for speaker in speakers:\n speaker_dir = os.path.join(path,speaker)\n subdirs = [os.path.join(speaker_dir,d) for d in os.listdir(speaker_dir) if os.path.isdir(os.path.join(speaker_dir,d))]\n for subdir in subdirs:\n # now get flac files and process them\n files = [os.path.join(subdir,f) for f in os.listdir(subdir) if ispng(os.path.join(subdir,f))]\n for file in files: \n labels.append(speaker)\n data.append(file)\n #print(\"Got %s images\" % len(labels)) \n return data, labels\n\ndef create_dataset_file():\n files, speakers= get_libri_data(TRAIN_DATA_PATH)\n sp_set = set(speakers)\n num_classes=len(sp_set)\n sp_list = list(sp_set)\n speakers_map = {}\n labels=[]\n for i in range(num_classes):\n speakers_map[sp_list[i]]=i\n \n f = open(DATASET_FILE, 'w')\n lines = []\n for fname, speaker in zip(files,speakers):\n label = speakers_map[speaker] \n lines.append(\"%s %s\\n\" % (os.path.abspath(fname),label))\n shuffle(lines)\n f.writelines(lines)\n f.close()\n \n f = open(\"test_speakers_map_vgg.txt\", 'w')\n lines=[]\n lines.append(\"index speaker_id\\n\")\n for k in speakers_map:\n lines.append(\"%d %d\\n\" % (speakers_map[k], int(k)))\n f.writelines(lines)\n f.close()\n \n return len(files), num_classes, speakers_map\n\nnum_files, num_classes, sp_map = create_dataset_file()\nprint \"Got %d files of %d speakers\" % (num_files, num_classes)\n\n\nmodel_path = \"models/\"\ninput_width = 224\n\ndef create_hdf5_dataset(dataset_file, output_name):\n print('Building HDF5 dataset to %s ...' % output_name)\n build_hdf5_image_dataset(dataset_file, image_shape=(input_width, input_width), mode='file', \n output_path=output_name, categorical_labels=True, normalize=False)\n\ndef get_data_hdf5(dataset_file): \n h5f = h5py.File(dataset_file, 'r')\n X = h5f['X']\n Y = h5f['Y']\n return X, Y\n\nh5_filename = 'data/LibriSpeech/testdata_vgg.h5'\nif not os.path.isfile(h5_filename):\n create_hdf5_dataset(DATASET_FILE, h5_filename)\nX, Y = get_data_hdf5(h5_filename)\n\n\ntf.reset_default_graph()\ntflearn.init_graph(num_cores=2, gpu_memory_fraction=0.7)\n\n# VGG preprocessing\nimg_prep = ImagePreprocessing()\nimg_prep.add_featurewise_zero_center(mean=[123.68, 116.779, 103.939],\n per_channel=True)\n# VGG Network\nx = tflearn.input_data(shape=[None, input_width, input_width, 3], name='input',\n data_preprocessing=img_prep)\nsoftmax = vgg16(x, num_classes)\nregression = tflearn.regression(softmax, optimizer='adam',\n loss='categorical_crossentropy',\n learning_rate=0.001, restore=False)\n\nmodel = tflearn.DNN(regression, checkpoint_path='checkpoints/model_vgg_finetuning',\n max_checkpoints=1, tensorboard_verbose=2)\n\nmodel_file = os.path.join(model_path, \"vgg16.tflearn\")\nmodel.load(model_file, weights_only=True)\n\n# Start finetuning\nmodel.fit(X, Y, n_epoch=10, validation_set=0.1, shuffle=True,\n show_metric=True, batch_size=16, snapshot_epoch=True,\n run_id='vgg-finetuning')\n\nmodel.save('speakers_testset_retrained_vgg.tflearn')"
},
{
"alpha_fraction": 0.6697235107421875,
"alphanum_fraction": 0.6795887351036072,
"avg_line_length": 25.441177368164062,
"blob_id": "ac01e5d1b21d8ea17d4fba2250d769d53bc44289",
"content_id": "c270cd620559c391a5e0225bc858503cda9e2d9e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7197,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 272,
"path": "/speaker_verifier.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import os\nimport sys\nimport soundfile as sf\n\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nfrom sklearn import neighbors\nfrom sklearn.externals import joblib\n\nfrom scipy.misc import imread, imresize\nimport numpy as np\n\nimport tensorflow as tf\nimport tflearn\n\nfrom googlenet import googlenet_core as feature_layer\nfrom googlenet import googlenet\n\n#To make GPU invisible:\n#export CUDA_VISIBLE_DEVICES=\"\"\n\n#To return to normal:\n#unset CUDA_VISIBLE_DEVICES\n\nclass SpeakerVerifier(object):\n\n\tdef __init__(self):\t\t\n\t\tself.TRAINDATA_PATH = 'recordings_train/'\n\t\tself.EVAL_PATH = 'recordings_eval/'\n\t\tself.DICT_NAME = 'users'\n\t\tself.dict_path = self.TRAINDATA_PATH+self.DICT_NAME+'.txt'\n\t\tself.sep = '\\t'\n\n\t\tself.FEATURES_PATH = self.TRAINDATA_PATH + 'features.txt'\n\t\tself.clf_path = self.TRAINDATA_PATH + 'knn.pkl'\n\t\tself.test_img_path = 'temp.png'\n\n\t\t# kNN model params\n\t\tself.n_neighbors = 5\n\t\tself.weights = 'distance' #'uniform'\n\n\n\t\tself.MODEL_PATH = 'checkpoints/model_googlenet-12000'\n\t\tself.input_width = 227\n\t\tself.num_classes = 40\n\n\t\tself.users = self.read_dict()\n\t\tself.model = self.load_model()\n\t\tself.classifier = self.load_clf()\n\n\tdef get_train_path(self):\n\t\treturn self.TRAINDATA_PATH\n\n\tdef load_model(self):\n\t\ttf.reset_default_graph()\n\t\ttflearn.init_graph(num_cores=2, gpu_memory_fraction=0.5)\n\n\t\tfeatures = feature_layer(self.input_width)\n\t\tloss = tflearn.layers.core.fully_connected(features, self.num_classes, activation='softmax')\n\t\tnetwork = tflearn.regression(loss, optimizer='momentum',\n\t\t\t\t\tloss='categorical_crossentropy',\n\t\t\t\t\tlearning_rate=0.001)\n\t\tmodel = tflearn.DNN(network, checkpoint_path='checkpoints/model_googlenet',\n\t\t\t\t\tmax_checkpoints=1, tensorboard_verbose=2)\n\n\n\t\tmodel.load(self.MODEL_PATH, weights_only=True)\n\t\tm = tflearn.DNN(features, session=model.session)\n\n\t\treturn m\n\n\tdef load_clf(self):\n\t\tif os.path.isfile(self.clf_path):\n\t\t\treturn joblib.load(self.clf_path)\n\t\telse:\n\t\t\treturn neighbors.KNeighborsClassifier(self.n_neighbors, weights=self.weights)\n\n\tdef read_dict(self):\n\t\t\tif os.path.isfile(self.dict_path):\n\t\t\t\twith open(self.dict_path, \"r\") as f:\n\t\t\t\t\tdict = {}\n\t\t\t\t\tfor line in f:\n\t\t\t\t\t\tvalues = line.split(self.sep)\n\t\t\t\t\t\tdict[int(values[0])] = values[1].strip()\n\t\t\t\t\treturn(dict)\n\t\t\telse:\n\t\t\t\t# return empty dictionary\n\t\t\t\treturn {}\n\n\tdef write_dict(self, dict, filename, sep):\n\t\twith open(filename, \"w\") as f:\n\t\t\tfor i in dict.keys(): \n\t\t\t\tf.write(str(i) + sep + dict[i] + \"\\n\")\n\t\n\n\tdef get_users(self):\n\t\treturn self.users\n\n\tdef reset_classifier(self):\n\t\tself.users = {}\n\t\tself.classifier = neighbors.KNeighborsClassifier(self.n_neighbors, weights=self.weights)\n\t\tif os.path.isfile(self.FEATURES_PATH):\n\t\t\tos.remove(self.FEATURES_PATH)\n\t\treturn self.users\n\n\n\tdef wav_to_flac(self, filename):\n\t\tif filename[-5:]=='.flac':\n\t\t\treturn filename\n\t\twavdata, samplerate = sf.read(filename)\n\t\tsf.write(filename + '.flac', wavdata, samplerate)\n\t\n\t\treturn filename + '.flac'\n\n\t\n\tdef get_audio_info(self, audio_file):\n\t\t\"\"\" Reads flac files\n\t\t\"\"\"\n\t\tsamples, samplerate = sf.read(audio_file)\n\t\treturn samples, samplerate\n\n\n\tdef graph_spectrogram(self, audio_file):\n\t\tsound_info, frame_rate = self.get_audio_info(audio_file)\n\t\tplt.figure(num=None, figsize=(19, 12), frameon=False)\n\t\n\t\tfig,ax = plt.subplots(1)\n\t\t# Set whitespace to 0\n\t\tfig.subplots_adjust(left=0,right=1,bottom=0,top=1)\n\t\n\t\n\t\tplt.specgram(sound_info, Fs=frame_rate)\n\t\n\t\tplt.axis('tight')\n\t\tplt.axis('off')\n\t\n\t\tplt.savefig(self.test_img_path) #bbox_inches='tight', pad_inches=0) \n\t\tplt.clf()\n\t\tplt.close()\n\t\treturn self.test_img_path\n\n\t\n\tdef get_features(self, input_path):\n\t\t\"\"\" Calculates activations of hidden layer of trained NN\"\"\"\n\n\t\timg= imread(input_path, mode='RGB')\n\t\timg = imresize(img, (self.input_width, self.input_width))\n\n\n\t\tres = np.array(self.model.predict([img]))\n\t\treturn res.flatten()\n\n\n\tdef extract_feaures_for_dir(dirname, label=None):\n\t\n\t\tdef ispng(name):\n\t\t\treturn \"png\"==name.split(\".\")[-1]\n\t\t\n\t\tfiles = [os.path.join(dirname,f) for f in os.listdir(dirname) if ispng(os.path.join(dirname,f))]\n\t\tall_features = []\n\n\t\tfor file in files:\n\t\t\t#print('extracting features from ' + file + ' ...')\n\t\t\tf = get_features(file)\t\t\n\t\t\tif label is not None:\n\t\t\t\tf = np.concatenate([[label], f])\n\t\t\tall_features.append(f)\n\n\t\treturn np.array(all_features, dtype=np.float32)\n\n\tdef extract_feaures_for_files(self, files, label=None):\n\t\n\t\tall_features = []\n\n\t\tfor file in files:\n\t\t\tflac_fname = self.wav_to_flac(file)\n\t\t\timg_fname = self.graph_spectrogram(flac_fname)\t\t\n\t\t\tf = self.get_features(img_fname)\t\t\n\t\t\tif label is not None:\n\t\t\t\tf = np.concatenate([[label], f])\n\t\t\tall_features.append(f)\n\n\t\treturn np.array(all_features, dtype=np.float32)\n\n\n\tdef get_xy_pairs(self, features):\n\t\ty = features[:,0]\n\t\tX = features[:,1:]\n\t\treturn X, y\n\n\n\tdef training_routine(self, files, label):\n\t\t# calculate feature vectors\n\t\tfeature_set = self.extract_feaures_for_files(files, label)\n\n\t\t\n\t\t# append to existing features\n\t\tif os.path.isfile(self.FEATURES_PATH):\n\t\t\tdata = np.loadtxt(self.FEATURES_PATH, dtype=np.float32)\n\t\t\tfeature_set = np.concatenate([data, feature_set], axis=0)\t\t\n\n\t\t\n\t\t# FIT kNN MODEL\n\t\tclf = neighbors.KNeighborsClassifier(self.n_neighbors, weights=self.weights)\n\t\t#clf = neighbors.RadiusNeighborsClassifier(radius = 1.0, weights=weights)\n\t\tX, y = self.get_xy_pairs(feature_set)\n\t\tclf.fit(X, y)\n\t\tjoblib.dump(clf, self.clf_path) \n\t\tself.classifier = clf\n\n\t\t# saving features\n\t\twith open(self.FEATURES_PATH,'w') as f:\n\t\t\tnp.savetxt(f, feature_set, fmt='%.10f')\n\t\n\n\tdef train_existing_user(self, files, user_id):\n\t\tif len(self.users)==0:\n\t\t\treturn \"List of Users is empty!\"\n\n\t\tkeys = [int(k) for k in self.users.keys()]\n\t\tif not int(user_id) in keys:\n\t\t\treturn \"Invalid user ID: \" % str(user_id)\n\t\t\t\n\t\tself.training_routine(files, user_id)\n\t\t\n\n\tdef train_new_user(self, files, user_name):\t\t\n\t\tlabel = 1\n\t\tif len(self.users)>0:\n\t\t\tkeys = [int(k) for k in self.users.keys()]\n\t\t\tkey = np.max(keys)+1\n\t\t\tglobal label\n\t\t\tlabel = key\n\t\t\tself.users[label]=user_name.strip()\n\t\telse:\n\t\t\tself.users = {1: user_name.strip()}\n\n\n\t\tself.training_routine(files, label)\n\n\t\t# save dictionary \n\t\tself.write_dict(self.users, self.dict_path, self.sep)\n\n\n\tdef verify(self, file):\n\t\tflac_fname = self.wav_to_flac(file)\n\t\timg_fname = self.graph_spectrogram(flac_fname)\n\t\tfeatures = self.get_features(img_fname)\n\t\tanswer = int(self.classifier.predict(features.reshape(1,-1))[0])\n\t\tdist, ind = self.classifier.kneighbors(features.reshape(1,-1))\n\t\tif np.min(dist)<900.0:\n\t\t\tprint('Prediction is: %s (%s)' % (answer, self.users[answer]))\n\t\t\treturn '%s (%s)' % (answer, self.users[answer])\n\t\telse:\n\t\t\tprint('Speaker is unknown!')\n\t\t\treturn 'Speaker is unknown!'\n\n\n\"\"\"\tdef verification(self, files):\n\t\tfeatures = extract_feaures_for_dir(self.EVAL_PATH, None)\n\t\tclf = self.classifier\n\t\tfor i in range(len(features)):\n\t\t\tanswer = int(clf.predict(features[i].reshape(1,-1))[0])\n\t\t\tdist, ind = clf.kneighbors(features[i].reshape(1,-1))\n\t\t\tif np.min(dist)<900.0:\n\t\t\t\t#print('Prediction is: %s (%s)' % (answer, users[answer]))\n\t\t\t\treturn 'Prediction is: %s (%s)' % (answer, self.users[answer])\n\t\t\telse:\n\t\t\t\t#print('Sample is unknown!')\n\t\t\t\treturn 'Sample is unknown!' \"\"\"\n\n\n\t\n\n"
},
{
"alpha_fraction": 0.4417670667171478,
"alphanum_fraction": 0.4417670667171478,
"avg_line_length": 18.52941131591797,
"blob_id": "637bbacec3b8666043c45cfe970c1cae0cbd226f",
"content_id": "19013aa6039fa2275e80ad495fb8ce0004532360",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 996,
"license_type": "no_license",
"max_line_length": 58,
"num_lines": 51,
"path": "/frontend/src/verifier/reducers/users.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nconst INITIAL_STATE = {\n send: false,\n error: null,\n data: []\n};\n\nexport default (state = INITIAL_STATE, action) => {\n switch(action.type) {\n case 'SEND_USERS':\n return {\n ...state,\n error: null,\n send: true\n };\n case 'COMPLETE_USERS':\n return {\n ...state,\n send: false,\n error: action.error,\n data: action.data\n };\n case 'CLEAR_USERS':\n return {\n ...state,\n data: []\n };\n case 'ADD_USER':\n return {\n ...state,\n data: state.data.concat([{\n key: action.key,\n value: action.value\n }])\n };\n case 'UPDATE_USER':\n return {\n ...state,\n data: state.data.map(_ => (_.key === action.key)\n ? {..._, value: action.value}\n : _\n )\n };\n case 'REMOVE_USER':\n return {\n ...state,\n data: state.data.filter(_ => _.key !== action.key)\n };\n default:\n return state;\n }\n}"
},
{
"alpha_fraction": 0.5147783160209656,
"alphanum_fraction": 0.5147783160209656,
"avg_line_length": 16.65217399597168,
"blob_id": "5b0d598a486b4c2e6f413c206111b0a0e9e9817a",
"content_id": "ab7347bee5d777f0cfdb1bb927f57947665c2fe5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 406,
"license_type": "no_license",
"max_line_length": 51,
"num_lines": 23,
"path": "/frontend/src/verifier/reducers/verify.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nconst INITIAL_STATE = {\n send: false,\n speaker: null\n};\n\nexport default (state = INITIAL_STATE, action) => {\n switch (action.type) {\n case 'SEND_VERIFY':\n return {\n ...state,\n send: true,\n speaker: null\n };\n case 'COMPLETE_VERIFY':\n return {\n ...state,\n send: false,\n speaker: action.speaker\n };\n default:\n return state;\n }\n}"
},
{
"alpha_fraction": 0.6468531489372253,
"alphanum_fraction": 0.6630474925041199,
"avg_line_length": 31.3511905670166,
"blob_id": "2ed2c744d3547a7cf67df5bac85fd3125b2661dc",
"content_id": "a28ec86dfede85b8d8101562034ced8d71abbdd2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5434,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 168,
"path": "/speaker_libri.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "#!/usr/local/bin/python\n#!/usr/bin/env PYTHONIOENCODING=\"utf-8\" python\nimport os\nimport wave\n\nimport tflearn\nfrom tflearn.data_utils import image_preloader\nfrom tflearn.data_utils import build_hdf5_image_dataset\nimport h5py\n\nfrom random import shuffle\n\nimport numpy\n\nfrom googlenet import googlenet\nfrom tflearn.layers.estimator import regression\n\nimport tensorflow as tf\nprint(\"You are using tensorflow version \"+ tf.__version__) #+\" tflearn version \"+ tflearn.version)\nif tf.__version__ >= '0.12' and os.name == 'nt':\n\tprint(\"sorry, tflearn is not ported to tensorflow 0.12 on windows yet!(?)\")\n\tquit() # why? works on Mac?\n\n\n\ndef dense_to_one_hot(batch, batch_size, num_labels):\n\tsparse_labels = tf.reshape(batch, [batch_size, 1])\n\tindices = tf.reshape(tf.range(0, batch_size, 1), [batch_size, 1])\n\tconcatenated = tf.concat(1, [indices, sparse_labels])\n\tconcat = tf.concat(0, [[batch_size], [num_labels]])\n\toutput_shape = tf.reshape(concat, [2])\n\tsparse_to_dense = tf.sparse_to_dense(concatenated, output_shape, 1.0, 0.0)\n\treturn tf.reshape(sparse_to_dense, [batch_size, num_labels])\n\ndef dense_to_one_hot(labels_dense, num_classes=10):\n\t\"\"\"Convert class labels from scalars to one-hot vectors.\"\"\"\n\treturn numpy.eye(num_classes)[labels_dense]\n\ndef load_wav_file(name):\n\tf = wave.open(name, \"rb\")\n\t# print(\"loading %s\"%name)\n\tchunk = []\n\tdata0 = f.readframes(CHUNK)\n\twhile data0: # f.getnframes()\n\t\t# data=numpy.fromstring(data0, dtype='float32')\n\t\t# data = numpy.fromstring(data0, dtype='uint16')\n\t\tdata = numpy.fromstring(data0, dtype='uint8')\n\t\tdata = (data + 128) / 255. # 0-1 for Better convergence\n\t\t# chunks.append(data)\n\t\tchunk.extend(data)\n\t\tdata0 = f.readframes(CHUNK)\n\t# finally trim:\n\tchunk = chunk[0:CHUNK * 2] # should be enough for now -> cut\n\tchunk.extend(numpy.zeros(CHUNK * 2 - len(chunk))) # fill with padding 0's\n\t# print(\"%s loaded\"%name)\n\treturn chunk\n\n\ndef get_libri_data(path): \n def ispng(name):\n return \"png\"==name.split(\".\")[-1]\n\n labels=[]\n data=[]\n speakers = [d for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]\n for speaker in speakers:\n speaker_dir = os.path.join(path,speaker)\n subdirs = [os.path.join(speaker_dir,d) for d in os.listdir(speaker_dir) if os.path.isdir(os.path.join(speaker_dir,d))]\n for subdir in subdirs:\n # now get flac files and process them\n files = [os.path.join(subdir,f) for f in os.listdir(subdir) if ispng(os.path.join(subdir,f))]\n for file in files: \n labels.append(speaker)\n data.append(file)\n #print(\"Got %s images\" % len(labels)) \n return data, labels\n\nTRAIN_DATA_PATH = \"data/LibriSpeech/test-clean\"\nDATASET_FILE = \"data/LibriSpeech/test-clean-spectro.txt\"\n\ndef create_dataset_file():\n files, speakers= get_libri_data(TRAIN_DATA_PATH)\n sp_set = set(speakers)\n num_classes=len(sp_set)\n sp_list = list(sp_set)\n speakers_map = {}\n labels=[]\n for i in range(num_classes):\n speakers_map[sp_list[i]]=i\n \n f = open(DATASET_FILE, 'w')\n lines = []\n for fname, speaker in zip(files,speakers):\n label = speakers_map[speaker] \n lines.append(\"%s %s\\n\" % (os.path.abspath(fname),label))\n shuffle(lines)\n f.writelines(lines)\n f.close()\n \n f = open(\"test_speakers_map.txt\", 'w')\n lines=[]\n lines.append(\"index speaker_id\\n\")\n for k in speakers_map:\n lines.append(\"%d %d\\n\" % (speakers_map[k], int(k)))\n f.writelines(lines)\n f.close()\n \n return len(files), num_classes, speakers_map\n\n\n#if not os.path.isfile(DATASET_FILE):\n#\tcreate_dataset_file()\nnum_files, num_classes, sp_map = create_dataset_file()\nprint \"Got %d files of %d speakers\" % (num_files, num_classes)\n\ninput_width = 227\n\ndef create_hdf5_dataset(dataset_file, output_name):\n\tprint('Building HDF5 dataset to %s ...' % output_name)\n\tbuild_hdf5_image_dataset(dataset_file, image_shape=(input_width, input_width), mode='file', \n\t\toutput_path=output_name, categorical_labels=True, normalize=True)\n\n\ndef get_data_hdf5(dataset_file):\t\n\th5f = h5py.File(dataset_file, 'r')\n\tX = h5f['X']\n\tY = h5f['Y']\n\treturn X, Y\n\ndef get_data_preloader():\n\tX, Y = image_preloader(DATASET_FILE, image_shape=(input_width, input_width), mode='file', \n categorical_labels=True, normalize=True, grayscale=False)\n\treturn X, Y\n\nh5_filename = 'data/LibriSpeech/testdata.h5'\nif not os.path.isfile(h5_filename):\n\tcreate_hdf5_dataset(DATASET_FILE, h5_filename)\nX, Y = get_data_hdf5(h5_filename)\n\n\n'''\nTo make GPU invisible:\nexport CUDA_VISIBLE_DEVICES=\"\"\n\nTo return to normal:\nunset CUDA_VISIBLE_DEVICES\n'''\n\nBATCH_SIZE = 32\n\ntf.reset_default_graph()\ntflearn.init_graph(num_cores=2, gpu_memory_fraction=0.5)\n\nloss = googlenet(input_width, num_classes)\nnetwork = tflearn.regression(loss, optimizer='momentum',\n loss='categorical_crossentropy',\n learning_rate=0.001)\nmodel = tflearn.DNN(network, checkpoint_path='checkpoints/model_googlenet',\n max_checkpoints=1, tensorboard_verbose=2)\n\n\nmodel.load('checkpoints/model_googlenet-10350')\n\nmodel.fit(X, Y, n_epoch=200, validation_set=0.1, shuffle=True,\n show_metric=True, batch_size=BATCH_SIZE, snapshot_step=150,\n snapshot_epoch=False, run_id='speakers_googlenet_ontestset')\n\nmodel.save('speakers_googlenet_on_testset.tflearn')"
},
{
"alpha_fraction": 0.6414885520935059,
"alphanum_fraction": 0.6543846726417542,
"avg_line_length": 23.345291137695312,
"blob_id": "6ec49be5b15b724712dd8ea4bb1c98954f3cea78",
"content_id": "be58abefd435e015f974cc1962faa916c790fa09",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5428,
"license_type": "no_license",
"max_line_length": 97,
"num_lines": 223,
"path": "/speaker_recognition.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "from scipy.misc import imread, imresize\nimport tflearn\nimport numpy as np\n\nfrom sklearn import neighbors\nfrom sklearn.externals import joblib\n\nimport os\nimport sys\n\nfrom googlenet import googlenet_core as feature_layer\nfrom googlenet import googlenet\n\nimport tensorflow as tf\n\nMODEL_PATH = 'checkpoints/model_googlenet-12000'\ninput_width = 227\nnum_classes = 40\n\ndef load_model():\n tf.reset_default_graph()\n tflearn.init_graph(num_cores=2, gpu_memory_fraction=0.5)\n\n features = feature_layer(input_width)\n loss = tflearn.layers.core.fully_connected(features, num_classes, activation='softmax')\n network = tflearn.regression(loss, optimizer='momentum',\n loss='categorical_crossentropy',\n learning_rate=0.001)\n model = tflearn.DNN(network, checkpoint_path='checkpoints/model_googlenet',\n max_checkpoints=1, tensorboard_verbose=2)\n\n\n model.load(MODEL_PATH, weights_only=True)\n \n \n m = tflearn.DNN(features, session=model.session)\n \n return m\n\n\n\ndef get_features(model, input_path):\n \"\"\" Calculates activations of hidden layer of trained NN\n \"\"\"\n \n img= imread(input_path, mode='RGB')\n img = imresize(img, (input_width, input_width))\n\n\n res = np.array(model.predict([img]))\n return res.flatten()\n\n\ndef extract_feaures_for_dir(dirname, label=None):\n\t\n\tdef ispng(name):\n\t\treturn \"png\"==name.split(\".\")[-1]\n\n\tmodel = load_model()\n\tfiles = [os.path.join(dirname,f) for f in os.listdir(dirname) if ispng(os.path.join(dirname,f))]\n\tall_features = []\n\n\tfor file in files:\n\t\tprint('extracting features from ' + file + ' ...')\n\t\tf = get_features(model, file)\t\t\n\t\tif label is not None:\n\t\t\tf = np.concatenate([[label], f])\n\t\tall_features.append(f)\n\n\treturn np.array(all_features, dtype=np.float32)\n\n\n\ndef write_dict(dict, filename, sep):\n with open(filename, \"w\") as f:\n for i in dict.keys(): \n f.write(str(i) + sep + dict[i] + \"\\n\")\n\ndef read_dict(filename, sep):\n with open(filename, \"r\") as f:\n dict = {}\n for line in f:\n values = line.split(sep)\n dict[int(values[0])] = values[1].strip()\n return(dict)\n\n\nTRAINDATA_PATH = 'recordings_train/'\nEVAL_PATH = 'recordings_eval/'\nDICT_NAME = 'users'\ndict_path = TRAINDATA_PATH+DICT_NAME+'.txt'\nsep = '\\t'\n\nFEATURES_PATH = TRAINDATA_PATH + 'features.txt'\nclf_path = TRAINDATA_PATH + 'knn.pkl'\n\n# kNN model params\nn_neighbors = 5\nweights = 'distance' #'uniform'\n\ndef get_xy_pairs(features):\n\ty = features[:,0]\n\tX = features[:,1:]\n\treturn X, y\n\ndef run_training():\t\t\n\t# read dictionary and print existing users\n\tusers = {}\n\tcount = 0\n\t\n\tlabel=0\n\tif os.path.isfile(dict_path):\t\t\n\t\tusers = read_dict(dict_path, sep)\t\t\n\t\tkeys = [int(k) for k in users.keys()]\n\t\tcount = len(keys)\n\n\t\tprint 'Select existing user or add a new one:'\n\t\tfor k in users:\n\t\t\tprint '%s:\\t%s' % (str(k), users[k])\n\t\tprint '0:\\tADD NEW USER'\t\t\n\t\tchoice = int(raw_input('\\nType in selected index: ').strip())\n\t\tif choice==0:\n\t\t\tname = raw_input(\"Type new user's name: \").strip()\n\t\t\tkey = np.max(keys)+1\n\t\t\tusers[key]=name\n\t\t\tlabel=key\n\t\telse: \n\t\t\tlabel = choice\n\telse:\n\t\t# add label (user name) to empty dictionary\t\n\t\tname = raw_input(\"Type new user's name: \")\n\t\tusers = {1: name.strip()}\n\t\tlabel = 1\n\n\n\t# calculate feature vectors \n\tfeature_set = extract_feaures_for_dir(TRAINDATA_PATH, label)\n\n\t# save dictionary and features\n\tif len(users.keys())>count:\n\t\twrite_dict(users, dict_path, sep)\n\t\n\t# append to existing features\n\tif os.path.isfile(FEATURES_PATH):\n\t\tdata = np.loadtxt(FEATURES_PATH, dtype=np.float32)\n\t\tfeature_set = np.concatenate([data, feature_set], axis=0)\t\t\n\n\tprint('fitting kNN model...')\n\tclf = neighbors.KNeighborsClassifier(n_neighbors, weights=weights)\n\t#clf = neighbors.RadiusNeighborsClassifier(radius = 1.0, weights=weights)\n\tX, y = get_xy_pairs(feature_set)\n\tclf.fit(X, y)\n\tjoblib.dump(clf, clf_path) \n\n\n\tprint('saving features...')\n\twith open(FEATURES_PATH,'w') as f:\n\t\tnp.savetxt(f, feature_set, fmt='%.10f')\n\t\n\tprint('Done training!')\n\n\ndef run_eval():\n\tusers = read_dict(dict_path, sep)\n\tprint(users)\n\tfeatures = extract_feaures_for_dir(EVAL_PATH, None)\n\tclf = joblib.load(clf_path)\n\tfor i in range(len(features)):\n\t\tanswer = int(clf.predict(features[i].reshape(1,-1))[0])\n\t\tdist, ind = clf.kneighbors(features[i].reshape(1,-1))\n\t\tif np.min(dist)<900.0:\n\t\t\tprint('Prediction is: %s (%s)' % (answer, users[answer]))\n\t\telse:\n\t\t\tprint('Sample is unknown!')\n\t\t#print (\"Distances: \")\n\t\t#print dist\n\t\t#print (\"Indicies: \")\n\t\t#print ind\n\n\ndef dialog():\n\tchoice = raw_input('''Available modes:\n\t\t1: training\n\t\t2: evaluation\n\t\tYour choice: ''')\n\tchoice = int(choice)\n\tif choice==1:\n\t\trun_training()\n\telse:\n\t\trun_eval()\n\ndef init_paths():\n\tDICT_NAME = 'users'\n\tdict_path = TRAINDATA_PATH+DICT_NAME+'.txt'\n\tsep = '\\t'\n\n\tFEATURES_PATH = TRAINDATA_PATH + 'features.txt'\n\tclf_path = TRAINDATA_PATH + 'knn.pkl'\n\n\n#res = np.array(get_features('recordings_train/84-121550-0003.png'))\nif(__name__ == '__main__'):\n\t\n\tif len(sys.argv)==2:\n\t\targ = sys.argv[1]\n\t\tEVAL_PATH = arg\n\telif len(sys.argv)==3:\n\t\tTRAINDATA_PATH = sys.argv[1]\n\t\tEVAL_PATH = sys.argv[2]\n\t\tdict_path = TRAINDATA_PATH+DICT_NAME+'.txt'\n\t\tsep = '\\t'\n\n\t\tFEATURES_PATH = TRAINDATA_PATH + 'features.txt'\n\t\tclf_path = TRAINDATA_PATH + 'knn.pkl'\n\t\n\tinit_paths()\n\tprint TRAINDATA_PATH\n\tprint EVAL_PATH\n\tprint dict_path\n\tprint clf_path\n\tprint FEATURES_PATH\n\n\tdialog()"
},
{
"alpha_fraction": 0.5749655961990356,
"alphanum_fraction": 0.5749655961990356,
"avg_line_length": 24.068965911865234,
"blob_id": "3f67550847134e47d31b77fcfe2961a3fc9364ba",
"content_id": "170cc295f058e35df5e1cf9071607070793afdea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 727,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 29,
"path": "/frontend/src/verifier/containers/TrainView.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React from 'react';\nimport View from '../components/Train';\nimport { connect } from 'react-redux';\nimport { train } from '../api/verifier';\nimport {send, complete as trains} from '../actions/train';\nimport { complete as users } from '../actions/users';\n\nexport default connect((state) => ({\n isSend: state.train.send\n}), (dispatch) => ({\n onTrain(userId, files) {\n dispatch(send());\n train(userId, files)\n .then(\n data => {\n dispatch(users(null, data))\n }\n )\n .then(\n data => dispatch(trains()),\n err => dispatch(trains(err))\n )\n }\n}))((props) => (\n <View\n isSend={props.isSend}\n onClick={(userId, files) => props.onTrain(userId, files)}\n />\n));"
},
{
"alpha_fraction": 0.5920000076293945,
"alphanum_fraction": 0.5920000076293945,
"avg_line_length": 40.66666793823242,
"blob_id": "85060131bad57e983f4b6abedc1ff2d403e70d1e",
"content_id": "de59cd86c6ff029b73ab2749ff71a38564ad4f39",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 125,
"license_type": "no_license",
"max_line_length": 71,
"num_lines": 3,
"path": "/frontend/src/verifier/actions/reset.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nexport const complete = (error) => ({ type: 'COMPLETE_RESET', error });\n\nexport const send = () => ({ type: 'SEND_RESET' });"
},
{
"alpha_fraction": 0.5715462565422058,
"alphanum_fraction": 0.5913156270980835,
"avg_line_length": 34.85232162475586,
"blob_id": "c57a58d9f866243240d8798d88f5f95f24e7ed2a",
"content_id": "d1ed66e80ebbf808ababf3b017599a60a6735e93",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 8498,
"license_type": "no_license",
"max_line_length": 136,
"num_lines": 237,
"path": "/create_spectrograms.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport soundfile as sf\n\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nfrom numpy.lib import stride_tricks\nimport PIL.Image as Image\nimport os\n\n\ndef get_wav_info(wav_file):\n wav = wave.open(wav_file, 'r')\n frames = wav.readframes(-1)\n sound_info = pylab.fromstring(frames, 'Int16')\n frame_rate = wav.getframerate()\n wav.close()\n return sound_info, frame_rate\n\n# for flac files:\ndef get_audio_info(audio_file):\n samples, samplerate = sf.read(audio_file)\n return samples, samplerate\n\ndef graph_spectrogram(audio_file, img_path):\n sound_info, frame_rate = get_audio_info(audio_file)\n plt.figure(num=None, figsize=(19, 12), frameon=False)\n \n fig,ax = plt.subplots(1)\n # Set whitespace to 0\n fig.subplots_adjust(left=0,right=1,bottom=0,top=1)\n \n \n plt.specgram(sound_info, Fs=frame_rate)\n \n plt.axis('tight')\n plt.axis('off')\n \n plt.savefig(img_path) #bbox_inches='tight', pad_inches=0) \n plt.clf()\n plt.close()\n\n\n\"\"\" short time fourier transform of audio signal \"\"\"\ndef stft(sig, frameSize, overlapFac=0.5, window=np.hanning):\n win = window(frameSize)\n hopSize = int(frameSize - np.floor(overlapFac * frameSize))\n \n # zeros at beginning (thus center of 1st window should be for sample nr. 0)\n samples = np.append(np.zeros(np.floor(frameSize/2.0)), sig) \n # cols for windowing\n cols = np.ceil( (len(samples) - frameSize) / float(hopSize)) + 1\n # zeros at end (thus samples can be fully covered by frames)\n samples = np.append(samples, np.zeros(frameSize))\n \n frames = stride_tricks.as_strided(samples, shape=(cols, frameSize), strides=(samples.strides[0]*hopSize, samples.strides[0])).copy()\n frames *= win\n \n return np.fft.rfft(frames) \n \n\"\"\" scale frequency axis logarithmically \"\"\" \ndef logscale_spec(spec, sr=44100, factor=20., alpha=1.0, f0=0.9, fmax=1):\n spec = spec[:, 0:256]\n timebins, freqbins = np.shape(spec)\n scale = np.linspace(0, 1, freqbins) #** factor\n \n # http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=650310&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel4%2F89%2F14168%2F00650310\n scale = np.array(map(lambda x: x * alpha if x <= f0 else (fmax-alpha*f0)/(fmax-f0)*(x-f0)+alpha*f0, scale))\n scale *= (freqbins-1)/max(scale)\n\n newspec = np.complex128(np.zeros([timebins, freqbins]))\n allfreqs = np.abs(np.fft.fftfreq(freqbins*2, 1./sr)[:freqbins+1])\n freqs = [0.0 for i in range(freqbins)]\n totw = [0.0 for i in range(freqbins)]\n for i in range(0, freqbins):\n if (i < 1 or i + 1 >= freqbins):\n newspec[:, i] += spec[:, i]\n freqs[i] += allfreqs[i]\n totw[i] += 1.0\n continue\n else:\n # scale[15] = 17.2\n w_up = scale[i] - np.floor(scale[i])\n w_down = 1 - w_up\n j = int(np.floor(scale[i]))\n \n newspec[:, j] += w_down * spec[:, i]\n freqs[j] += w_down * allfreqs[i]\n totw[j] += w_down\n \n newspec[:, j + 1] += w_up * spec[:, i]\n freqs[j + 1] += w_up * allfreqs[i]\n totw[j + 1] += w_up\n \n for i in range(len(freqs)):\n if (totw[i] > 1e-6):\n freqs[i] /= totw[i]\n \n return newspec, freqs\n\n### Block Processing\n### Sound files can also be read in short, optionally overlapping blocks with \n### soundfile.blocks(). For example, this calculates the signal level for each \n### block of a long file:\n# rms = [np.sqrt(np.mean(block**2)) for block in\n# sf.blocks('myfile.wav', blocksize=1024, overlap=512)]\n\n\"\"\" plot spectrogram\"\"\"\ndef plotstft(audiopath, binsize=2**10, plotpath=None, colormap=\"gray\", channel=0, name='tmp.png', alpha=1, offset=0):\n samples, samplerate = sf.read(audiopath)\n #samples = samples[:, channel]\n s = stft(samples, binsize)\n\n sshow, freq = logscale_spec(s, factor=1, sr=samplerate, alpha=alpha)\n sshow = sshow[2:, :]\n ims = 20.*np.log10(np.abs(sshow)/10e-6) # amplitude to decibel\n timebins, freqbins = np.shape(ims)\n \n ims = np.transpose(ims)\n # ims = ims[0:256, offset:offset+768] # 0-11khz, ~9s interval\n ims = ims[0:256, :] # 0-11khz, ~10s interval\n #print \"ims.shape\", ims.shape\n \n image = Image.fromarray(ims) \n image = image.convert('L')\n image.save(name)\n\n\ndata_path = \"data/LibriSpeech/\"\ndef calculate_spectrograms(path):\n dirs = [os.path.join(path,d) for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]\n \n def isflac(name):\n return \"flac\"==name.split(\".\")[-1]\n\n print(\"Started parsing folders...\")\n for dir in dirs:\n speakers = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir,d))]\n for speaker in speakers:\n speaker_dir = os.path.join(dir,speaker)\n subdirs = [os.path.join(speaker_dir,d) for d in os.listdir(speaker_dir) if os.path.isdir(os.path.join(speaker_dir,d))]\n for subdir in subdirs:\n # now get flac files and process them\n files = [os.path.join(subdir,f) for f in os.listdir(subdir) if isflac(os.path.join(subdir,f))]\n for file in files:\n print(\"Processing file: %s\" % file)\n #plotstft(file, name=\".\".join((file.split(\".\")[0],\"png\")))\n img_name=\".\".join((file.split(\".\")[0],\"png\"))\n graph_spectrogram(file, img_name)\n\n\n print(\"Finished spectrograms!\")\n\ndef calculate_spectrograms_flat(path):\n def isflac(name):\n return \"flac\"==name.split(\".\")[-1]\n\n print(\"Started parsing folder '\" + path + \"'...\")\n # now get flac files and process them\n files = [os.path.join(path,f) for f in os.listdir(path) if isflac(os.path.join(path,f))]\n for file in files:\n print(\"Processing file: %s\" % file)\n img_name=\".\".join((file.split(\".\")[0],\"png\"))\n graph_spectrogram(file, img_name)\n\n print(\"Finished spectrograms for folder '\" + path + \"'!\")\n\n \ndef get_labels(path):\n dirs = [os.path.join(path,d) for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]\n \n def ispng(name):\n return \"png\"==name.split(\".\")[-1]\n\n labels=[]\n data=[]\n print(\"Started parsing folders...\")\n for dir in dirs:\n speakers = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir,d))]\n for speaker in speakers:\n speaker_dir = os.path.join(dir,speaker)\n subdirs = [os.path.join(speaker_dir,d) for d in os.listdir(speaker_dir) if os.path.isdir(os.path.join(speaker_dir,d))]\n for subdir in subdirs:\n # now get flac files and process them\n files = [os.path.join(subdir,f) for f in os.listdir(subdir) if ispng(os.path.join(subdir,f))]\n for file in files:\n print(\"Processing file: \", file)\n labels.append(speaker)\n data.append(file)\n \n print(\"Finished!\") \n return data, labels\n\ndef convert_rgba2rgb(img_name):\n img = Image.open(img_name)\n x = np.array(img)\n r, g, b, a = np.rollaxis(x, axis=-1)\n r[a == 0] = 255\n g[a == 0] = 255\n b[a == 0] = 255 \n x = np.dstack([r, g, b])\n res = Image.fromarray(x, 'RGB')\n res.save(img_name)\n\n\ndef convert_allfiles_to_rgb(path):\n dirs = [os.path.join(path,d) for d in os.listdir(path) if os.path.isdir(os.path.join(path,d))]\n \n def ispng(name):\n return \"png\"==name.split(\".\")[-1]\n\n labels=[]\n data=[]\n print(\"Started parsing folders...\")\n for dir in dirs:\n speakers = [d for d in os.listdir(dir) if os.path.isdir(os.path.join(dir,d))]\n for speaker in speakers:\n speaker_dir = os.path.join(dir,speaker)\n subdirs = [os.path.join(speaker_dir,d) for d in os.listdir(speaker_dir) if os.path.isdir(os.path.join(speaker_dir,d))]\n for subdir in subdirs:\n files = [os.path.join(subdir,f) for f in os.listdir(subdir) if ispng(os.path.join(subdir,f))]\n for file in files:\n print(\"Processing file: \", file)\n convert_rgba2rgb(file)\n \n print(\"Finished!\") \n\n#convert_allfiles_to_rgb(data_path)\n\n'''files, labels = get_labels(data_path)\nthefile = open('%sLibriData.txt' % data_path , 'w')\nfor i in range(len(files)):\n thefile.write(\"%s\\t%s\\n\" % (files[i], labels[i]))\nthefile.close()'''\n\n#calculate_spectrograms(data_path)\n\n"
},
{
"alpha_fraction": 0.5131876468658447,
"alphanum_fraction": 0.5131876468658447,
"avg_line_length": 25.019607543945312,
"blob_id": "02eb31ad8581146949216050892c0bfadebae7c6",
"content_id": "9ee4611c81dacf51c88e4f451c7c28546b510509",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1327,
"license_type": "no_license",
"max_line_length": 93,
"num_lines": 51,
"path": "/frontend/src/verifier/components/Layout.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React, { Component, PropTypes } from 'react';\nimport { Link } from 'react-router';\nimport ListUsers from '../components/ListUsers';\nimport '../resources/layout.css';\n\nexport default class Layout extends Component {\n\n static propTypes = {\n users: PropTypes.array.isRequired,\n isSend: PropTypes.bool.isRequired\n };\n\n static defaultProps = {\n users: [],\n isSend: false\n };\n\n render() {\n return (\n <div>\n <ul className=\"menu\">\n <li className=\"menu__item\" key=\"reset\">\n <Link to={'/reset'} className=\"menu__link\" activeClassName=\"menu__link--active\">\n Reset\n </Link>\n </li>\n <li className=\"menu__item\" key=\"train\">\n <Link to={'/train'} className=\"menu__link\" activeClassName=\"menu__link--active\">\n Train\n </Link>\n </li>\n <li className=\"menu__item\" key=\"verify\">\n <Link to={'/verify'} className=\"menu__link\" activeClassName=\"menu__link--active\">\n Verify\n </Link>\n </li>\n </ul>\n <br />\n List of Users:\n <br/>\n { (!this.props.isSend)\n ? (<ListUsers users={this.props.users} />)\n : (<p> Loading... </p>)\n }\n <br/>\n {this.props.children}\n </div>\n );\n }\n\n}"
},
{
"alpha_fraction": 0.6946107745170593,
"alphanum_fraction": 0.6946107745170593,
"avg_line_length": 26.83333396911621,
"blob_id": "df008b3c2f4316b6b3f31d51b176aa78512bf8ef",
"content_id": "d545d1ad648d24f7accfad0cadd57b36467aec9e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 167,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 6,
"path": "/frontend/src/verifier/reducers/index.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport reset from './reset';\nimport train from './train';\nimport verify from './verify';\nimport users from './users';\n\nexport default { reset, train, verify, users };"
},
{
"alpha_fraction": 0.5940931439399719,
"alphanum_fraction": 0.6020447015762329,
"avg_line_length": 29.70930290222168,
"blob_id": "9e95f6eae15941867370762c0472bacc2e00c964",
"content_id": "9ae90a2d75ddfed192344e853a4438a296c9ba52",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2641,
"license_type": "no_license",
"max_line_length": 106,
"num_lines": 86,
"path": "/server.py",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "import os\nfrom flask import Flask, render_template, request\nfrom flask_restful import Resource, Api, abort, reqparse\nfrom speaker_verifier import SpeakerVerifier\nimport re\nimport random\n\napp = Flask(__name__)\napi = Api(app)\n\nverifier = SpeakerVerifier()\nfull_path = os.path.realpath(__file__)\ntest_file_name = 'tmp_test.wav'\ntrain_folder_name = verifier.get_train_path()\n\n\nclass UsersResource(Resource):\n def get(self):\n users = verifier.get_users()\n return [{\n 'key': key,\n 'value': value\n } for key, value in users.items()]\n\n\nclass ResetResource(Resource):\n def post(self):\n verifier.reset_classifier()\n return {}\n\n\nclass VerifyResource(Resource):\n def post(self):\n f = request.files['file_for_test']\n if f.filename == '':\n abort(400, message='No selected file')\n if f.filename.find('wav') == -1 and f.filename.find('flac') == -1:\n abort(400, message='Selected file is not in audio format (WAV or FLAC)!')\n f.save(test_file_name)\n result = verifier.verify(test_file_name)\n return {'verify': result}\n\n\nclass TrainResource(Resource):\n def post(self):\n parser = reqparse.RequestParser()\n parser.add_argument('userid', type=int)\n args = parser.parse_args(strict=True)\n userid = args[\"userid\"]\n uploaded_files = request.files.getlist(\"files_for_training\")\n filenames = []\n for file in uploaded_files:\n if file and (file.filename.find('wav') > 0 or file.filename.find('flac') > 0):\n filename = file.filename\n full_path = os.path.join(train_folder_name, filename)\n file.save(full_path)\n filenames.append(full_path)\n else:\n abort(400, message=\"Selected file {} is not in WAV or FLAC format!\".format(file.filename))\n users = verifier.get_users()\n if (userid) and (userid in users.keys()):\n verifier.train_existing_user(filenames, userid)\n else:\n verifier.train_new_user(filenames, userid)\n users = verifier.get_users()\n return [{\n 'key': key,\n 'value': value\n } for key, value in users.items()]\n\n\napi.add_resource(ResetResource, '/api/reset')\napi.add_resource(VerifyResource, '/api/verify')\napi.add_resource(TrainResource, '/api/train')\napi.add_resource(UsersResource, '/api/users')\n\n\ndef is_int(x):\n match = re.search(\"\\D\", x)\n if not match:\n return True\n else:\n return False\n\nif __name__ == \"__main__\":\n app.run(host='0.0.0.0', port=6006, debug=True)\n"
},
{
"alpha_fraction": 0.5089605450630188,
"alphanum_fraction": 0.5149971842765808,
"avg_line_length": 25.63819122314453,
"blob_id": "f03706c65b957d237cb37f0d6db4428b715a28a4",
"content_id": "146966ddac07d01c1a6db38e3207af4611a26dfe",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 5301,
"license_type": "no_license",
"max_line_length": 117,
"num_lines": 199,
"path": "/frontend/src/verifier/components/Timer.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nimport React, { Component, PropTypes } from 'react';\nimport Recorder from '../api/recoder';\nimport '../resources/button.css';\n\nexport default class Timer extends Component {\n\n static propTypes = {\n long: PropTypes.number.isRequired,\n max: PropTypes.number.isRequired,\n onAdd: PropTypes.func.isRequired,\n onDelete: PropTypes.func.isRequired\n };\n\n state = {\n files: [],\n\n recording: false,\n playing: false,\n timer: '00',\n };\n\n constructor(props) {\n super(props);\n this.audioContext = null;\n this.recorder = null;\n this.snd = null;\n }\n\n componentDidMount() {\n\n try {\n window.AudioContext = window.AudioContext || window.webkitAudioContext;\n navigator.getUserMedia = navigator.getUserMedia || navigator.webkitGetUserMedia;\n window.URL = window.URL || window.webkitURL;\n\n this.audioContext = new AudioContext();\n console.log('Audio context set up.');\n console.log('navigator.getUserMedia ' + (navigator.getUserMedia ? 'available.' : 'not present!'));\n } catch (e) {\n console.error('No web audio support in this browser!', e);\n }\n\n navigator.getUserMedia({audio: true}, (stream) => {\n const input = this.audioContext.createMediaStreamSource(stream);\n console.log('Media stream created.');\n\n this.recorder = new Recorder(input, {\n bufferLen: 1024,\n numChannels: 1\n });\n console.log('Recorder initialised.');\n }, (e) => {\n console.error('No live audio input: ' + e);\n });\n }\n\n componentWillUnmount() {\n this.recorder && this.recorder.clear();\n this.audioContext = null;\n this.recorder = null;\n this.interval && clearInterval(this.interval);\n this.interval = null;\n }\n\n _onStart = () => {\n this.recorder && this.recorder.record();\n const time = Date.now();\n setTimeout(() => {\n if (this.state.recording === time) {\n this._onStop();\n }\n }, 10 * 1000);\n this.interval = setInterval(() => {\n const timer = parseInt((Date.now() - this.state.recording) / 1000, 0);\n this.setState({\n recording: time,\n timer: (timer > 9) ? timer.toString() : `0${timer}`\n });\n }, 500);\n console.log('Recording...');\n this.setState({\n recording: time,\n timer: '00'\n });\n };\n\n _onStop = () => {\n if (this.recorder) {\n this.recorder.stop();\n console.log('Stopped recording.');\n if (parseInt(this.state.timer, 0) >= this.props.long) {\n try {\n this.recorder.exportWAV((blob) => {\n const filename = new Date().toISOString();\n this.setState({\n files: this.state.files.concat([{\n key: filename,\n data: blob\n }])\n });\n this.props.onAdd(filename, blob);\n });\n } catch (e) {\n console.error(e);\n }\n }\n this.recorder.clear();\n }\n this.interval && clearInterval(this.interval);\n this.interval = null;\n this.setState({\n recording: null,\n timer: '00'\n });\n };\n\n _onPlay = (blob) => {\n this.snd && this.snd.pause();\n this.snd = new Audio(URL.createObjectURL(blob));\n this.snd.play();\n this.snd.addEventListener(\"ended\", () => {\n this.snd.currentTime = 0;\n this.setState({\n playing: false\n });\n });\n this.setState({\n playing: true\n });\n };\n\n _onPause = () => {\n this.snd && this.snd.pause();\n this.setState({\n playing: false\n });\n };\n\n _onDelete = (id) => {\n this.snd && this.snd.pause();\n this.setState({\n files: this.state.files.filter(_ => _.key !== id),\n playing: false\n });\n this.props.onDelete(id);\n };\n\n render() {\n return (\n <div>\n <p> Input files: </p>\n <ul>\n {this.state.files.map(file => (\n <li key={file.key}>\n <p>\n {file.key}\n </p>\n <p style={{display: (!this.state.recording) ? 'initial' : 'none'}}>\n <input type=\"button\" value=\"Play Record\" onClick={(e) => this._onPlay(file.data)} /> \n <input type=\"button\" value=\"Stop Record\" onClick={(e) => this._onPause()} /> \n <input type=\"button\" value=\"Delete Record\" onClick={(e) => this._onDelete(file.key)} />\n </p>\n </li>\n ))}\n </ul>\n <br />\n <p style={{display: (!this.state.playing && this.state.files.length < this.props.max) ? 'initial' : 'none'}}>\n <input\n type=\"button\"\n value=\"Start\"\n className=\"btn-controll\"\n disabled={this.state.recording}\n onClick={() => this._onStart()}\n />\n \n <span style={{\n color: (parseInt(this.state.timer, 0) >= this.props.long)\n ? 'green'\n : (\n (parseInt(this.state.timer, 0) === 0)\n ? 'black' : 'red'\n )\n }}>\n {this.state.timer}\n </span>\n \n <input\n type=\"button\"\n value=\"Stop\"\n className=\"btn-controll\"\n disabled={!this.state.recording}\n onClick={() => this._onStop()}\n />\n </p>\n </div>\n );\n }\n\n}"
},
{
"alpha_fraction": 0.5873016119003296,
"alphanum_fraction": 0.5873016119003296,
"avg_line_length": 40.66666793823242,
"blob_id": "887b6e8d002596a43e1ce745f4a7f0cdb0bf4660",
"content_id": "4a2bc64879cb50bdca94297d3807fa5422949b7d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 126,
"license_type": "no_license",
"max_line_length": 71,
"num_lines": 3,
"path": "/frontend/src/verifier/actions/train.js",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "\nexport const send = () => ({ type: 'SEND_TRAIN' });\n\nexport const complete = (error) => ({ type: 'COMPLETE_TRAIN', error });\n"
},
{
"alpha_fraction": 0.5294457077980042,
"alphanum_fraction": 0.7165126800537109,
"avg_line_length": 17.231578826904297,
"blob_id": "e1f406edba1d3fddae5e4f959f244f46b288927e",
"content_id": "25927142ce2dad4578071e12ba855f2f297183c2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 1732,
"license_type": "no_license",
"max_line_length": 41,
"num_lines": 95,
"path": "/requirements.txt",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "backports-abc==0.5\nbackports.shutil-get-terminal-size==1.0.0\nbackports.ssl-match-hostname==3.5.0.1\nbleach==1.5.0\ncertifi==2016.9.26\ncffi==1.9.1\nclick==6.7\nconfigparser==3.5.0\ncycler==0.10.0\ndask==0.12.0\ndecorator==4.0.10\nDjango==1.6.11\ndjango-angular==0.8.4\ndjango-bootstrap-pagination==1.6.2\ndjango-bootstrap3==8.1.0\ndjango-bower==5.2.0\ndjango-celery==3.1.17\ndjango-environ==0.4.1\ndjango-extensions==1.7.5\ndjangorestframework==2.4.8\nentrypoints==0.2.2\nenum34==1.1.6\nFlask==0.12\nfuncsigs==1.0.2\nfunctools32==3.2.3.post2\nh5py==2.6.0\nhtml5lib==0.9999999\nipykernel==4.5.2\nipython==5.1.0\nipython-genutils==0.1.0\nipywidgets==5.2.2\nitsdangerous==0.24\nJinja2==2.8\njsonschema==2.5.1\njupyter==1.0.0\njupyter-client==4.4.0\njupyter-console==5.0.0\njupyter-core==4.2.1\nMarkupSafe==0.23\nmatplotlib==1.5.3\nmistune==0.7.3\nmock==2.0.0\nmutagen==1.36\nnbconvert==5.0.0\nnbformat==4.2.0\nnetworkx==1.11\nnotebook==4.3.0\nnumpy==1.11.3\npandocfilters==1.4.1\npathlib2==2.1.0\npbr==1.10.0\npexpect==4.2.1\npickleshare==0.7.4\nPillow==3.4.2\nprompt-toolkit==1.0.9\nprotobuf==3.1.0\nptyprocess==0.5.1\npy-sonicvisualiser===0.2-9-gebe83bd\nPyAudio==0.2.7\npycparser==2.17\nPygments==2.1.3\npympi-ling==1.69\npyparsing==2.1.10\nPySoundFile==0.8.1\npython-dateutil==2.6.0\npytz==2016.10\nPyYAML==3.10\npyzmq==16.0.2\nqtconsole==4.2.1\nscikit-image==0.12.3\nscikit-learn==0.18.1\nscipy==0.18.1\nsimplegeneric==0.8.1\nsingledispatch==3.4.0.3\nsix==1.10.0\nsklearn==0.0\nSouth==1.0.2\nstevedore==1.19.1\ntensorflow==0.12.0\nterminado==0.6\ntestpath==0.3\ntflearn==0.2.2\nTimeSide==0.8.1\ntoolz==0.8.2\ntornado==4.4.2\ntraitlets==4.3.1\ntraits==4.6.0\nuWSGI==2.0.14\nvirtualenv==15.1.0\nvirtualenv-clone==0.2.6\nvirtualenvwrapper==4.7.2\nwatchdog==0.8.3\nwcwidth==0.1.7\nWerkzeug==0.11.15\nwidgetsnbextension==1.2.6\n"
},
{
"alpha_fraction": 0.8607594966888428,
"alphanum_fraction": 0.8607594966888428,
"avg_line_length": 78,
"blob_id": "d8d717994c23220715bab8488c63913d543e023a",
"content_id": "84a70c50110b571675d089bf8d28bac1b70a3c96",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 79,
"license_type": "no_license",
"max_line_length": 78,
"num_lines": 1,
"path": "/README.md",
"repo_name": "StatML/speaker_recognition",
"src_encoding": "UTF-8",
"text": "Speaker recognition and verification from arbitrary audio using deep learning.\n"
}
] | 23
|
danielpops/slack-starterbot
|
https://github.com/danielpops/slack-starterbot
|
f92c987db9e2851e60bc76e7a77bcc409758ed19
|
fb91647603f329d3321b3ff71d867944359d7fc9
|
cbe54761ea37d62d2f811254c643abbbb238f223
|
refs/heads/master
| 2020-06-28T07:31:18.668378
| 2019-08-02T06:51:02
| 2019-08-02T06:51:02
| 200,176,757
| 0
| 0
|
MIT
| 2019-08-02T06:17:12
| 2019-07-30T03:13:40
| 2019-01-07T18:13:20
| null |
[
{
"alpha_fraction": 0.5797803401947021,
"alphanum_fraction": 0.5810723304748535,
"avg_line_length": 31.25,
"blob_id": "bbb25813cb5993f13b31b859936d2929994710f2",
"content_id": "e10ca88d74ebad12038cc301fc5ba50bec1b8bea",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3096,
"license_type": "permissive",
"max_line_length": 96,
"num_lines": 96,
"path": "/starterbot.py",
"repo_name": "danielpops/slack-starterbot",
"src_encoding": "UTF-8",
"text": "import os\nimport time\nimport re\nfrom slackclient import SlackClient\n\n\n# instantiate Slack client\nslack_client = SlackClient(os.environ.get('SLACK_BOT_TOKEN'))\n# starterbot's user ID in Slack: value is assigned after the bot starts up\nstarterbot_id = None\n\n# constants\nRTM_READ_DELAY = 1 # 1 second delay between reading from RTM\nEXAMPLE_COMMAND = \"do\"\nMENTION_REGEX = \"^<@(|[WU].+?)>(.*)\"\n\ndef parse_event(slack_event):\n \"\"\"\n Parses a list of events coming from the Slack RTM API\n \"\"\"\n if event[\"type\"] == \"message\" and not \"subtype\" in event and not \"bot_id\" in event:\n user_id, message = parse_direct_mention(event[\"text\"])\n event[\"is_direct\"] = False\n event[\"mentioned_user\"] = None\n if user_id == starterbot_id:\n event[\"is_direct\"] = True\n event[\"mentioned_user\"] = user_id\n event[\"text\"] = message\n\n print event\n return event\n elif event[\"type\"] == \"reaction_added\":\n pass\n elif event[\"type\"] == \"reaction_removed\":\n pass\n\n return None\n\ndef parse_direct_mention(message_text):\n \"\"\"\n Finds a direct mention (a mention that is at the beginning) in message text\n and returns the user ID which was mentioned. If there is no direct mention, returns None\n \"\"\"\n matches = re.search(MENTION_REGEX, message_text)\n # the first group contains the username, the second group contains the remaining message\n return (matches.group(1), matches.group(2).strip()) if matches else (None, None)\n\ndef handle_event(event):\n \"\"\"\n Executes bot command if the command is known\n \"\"\"\n # Default to no response\n response = None\n \n if event[\"is_direct\"]:\n if event[\"text\"].startswith(\"hi\"):\n response = \"hi :wave:\"\n slack_client.api_call(\n \"reactions.add\",\n channel=event[\"channel\"],\n name=\"wave\",\n timestamp=event[\"event_ts\"],\n )\n else:\n # Do something else\n if \"love\" in event[\"text\"]:\n slack_client.api_call(\n \"reactions.add\",\n channel=event[\"channel\"],\n name=\"heart\",\n timestamp=event[\"event_ts\"],\n )\n\n if response:\n # Sends the response back to the channel\n slack_client.api_call(\n \"chat.postMessage\",\n as_user=True,\n channel=event[\"channel\"],\n text=response\n )\n\nif __name__ == \"__main__\":\n if slack_client.rtm_connect(with_team_state=False):\n print(\"Starter Bot connected and running!\")\n # Read bot's user ID by calling Web API method `auth.test`\n starterbot_id = slack_client.api_call(\"auth.test\")[\"user_id\"]\n while True:\n parsed_event = None\n for event in slack_client.rtm_read():\n parsed_event = parse_event(event)\n if parsed_event:\n handle_event(parsed_event)\n time.sleep(RTM_READ_DELAY)\n else:\n print(\"Connection failed. Exception traceback printed above.\")\n"
}
] | 1
|
Yadub/the_python_challenge
|
https://github.com/Yadub/the_python_challenge
|
f4f1d7625fb0c2ccba629b75cccb83ac269f8b03
|
f752ff2d6242e8f9c06b13cf703f0fac189c9342
|
8a005d0cd01e313ce26120dd34b5b9249f36fe0d
|
refs/heads/master
| 2021-01-15T11:38:04.961238
| 2017-08-25T23:05:48
| 2017-08-25T23:05:48
| 99,625,136
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5597484111785889,
"alphanum_fraction": 0.650943398475647,
"avg_line_length": 36.411766052246094,
"blob_id": "48efbd21591322407ccae7d85e8bf7e2eb46efa6",
"content_id": "d6fe996c96437edc846021e1a293c4742d4fb853",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 636,
"license_type": "no_license",
"max_line_length": 89,
"num_lines": 17,
"path": "/7.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "from PIL import Image\n\nim = Image.open('oxygen.png') # Load Image\npixels = list(im.getdata()) # Get Pixel Data\nwidth, height = im.size\n\nmiddle_pixels = pixels[ width * (height / 2): (width) * (1 + height / 2)]\nunique_RGB = [r for r, g, b, a in middle_pixels[::7] if r == g == b]\nsolution = \"\".join(map(chr, map(int, unique_RGB)))\nprint solution\n\n# Solution states:\n# smart guy, you made it. the next level is [105, 110, 116, 101, 103, 114, 105, 116, 121]\nnext_level = [105, 110, 116, 101, 103, 114, 105, 116, 121]\nnew_letters = [chr(i) for i in next_level]\nfinal_solution = \"\".join(map(chr, map(int, next_level)))\nprint final_solution\n"
},
{
"alpha_fraction": 0.6134454011917114,
"alphanum_fraction": 0.6302521228790283,
"avg_line_length": 21.3125,
"blob_id": "f4bad05f3d9d6a44871588f32b340203dfea67ca",
"content_id": "537391e080450c933c3fd589b7c76d915f0716e3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 357,
"license_type": "no_license",
"max_line_length": 59,
"num_lines": 16,
"path": "/6.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import zipfile\n\nzip_data = zipfile.ZipFile('channel.zip', 'r')\n\nnothing = [90052]\norder = []\n\nwhile nothing != []:\n file_name = str(nothing[0]) + '.txt'\n data = zip_data.read(file_name)\n print data\n\n order.append(file_name)\n nothing = [int(s) for s in data.split() if s.isdigit()]\n\nprint ''.join([zip_data.getinfo(n).comment for n in order])\n"
},
{
"alpha_fraction": 0.584782600402832,
"alphanum_fraction": 0.606521725654602,
"avg_line_length": 24.55555534362793,
"blob_id": "864806cf4043d5e601476cd9baead3e62087b168",
"content_id": "e7a1bf116b1806285710b920ec0d131dc782c4f9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 460,
"license_type": "no_license",
"max_line_length": 214,
"num_lines": 18,
"path": "/1.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "text1 = \"g fmnc wms bgblr rpylqjyrc gr zw fylb. rfyrq ufyr amknsrcpq ypc dmp. bmgle gr gl zw fylb gq glcddgagclr ylb rfyr\\'q ufw rfgq rcvr gq qm jmle. sqgle qrpgle.kyicrpylq() gq pcamkkclbcb. lmu ynnjw ml rfc spj.\"\ntext2 = \"map\"\n\ndef decode(text):\n\n txt = list(text)\n\n for i in range(len(txt)):\n val = ord(txt[i])+2\n if val > 97+25:\n val = val - 26\n txt[i] = chr(val)\n\n sol = \"\".join(txt)\n\n print sol\n\ndecode(text2)\n"
},
{
"alpha_fraction": 0.4258333444595337,
"alphanum_fraction": 0.4566666781902313,
"avg_line_length": 20.428571701049805,
"blob_id": "ed050c1a2cf3b2290cf48f4d95502609ff275387",
"content_id": "3ed0b093f5def7e9c0ac61664037026fe776dc3f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1200,
"license_type": "no_license",
"max_line_length": 59,
"num_lines": 56,
"path": "/3.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import urllib2\nurl = \"http://www.pythonchallenge.com/pc/def/equality.html\"\npage = urllib2.urlopen(url)\ndata = page.read()\n\nstart_data = data.find(\"<!--\")\nmy_data = data[start_data+4:-4]\n\ndata_list = list(my_data)\nu_max = 90\nu_min = 65\nl_max = 122\nl_min = 97\n\nl = len(data_list)\n\ndef check_uppercase(character):\n if 65 <= ord(character) <= 90:\n return True\n else:\n return False\n\nsol = []\n\nfor n in range(len(data_list)):\n big = True\n char = data_list[n]\n\n if l_min <= ord(char) <= l_max:\n\n c = data_list\n\n if n % 81 > 3 and n % 81 < 78:\n cs = data_list[n-3:n+4]\n for i in range(7):\n if i != 3:\n if not check_uppercase(cs[i]):\n big = False\n else:\n big = False\n\n if big:\n lv = uv = \"a\"\n if n % 81 > 4:\n lv = data_list[n-4]\n if n % 81 < 77:\n uv = data_list[n+4]\n if check_uppercase(uv):\n big = False\n if check_uppercase(lv):\n big = False\n if big:\n # print n, char, \":\", cs\n sol = sol + [char]\n\nprint \"\".join(sol)\n"
},
{
"alpha_fraction": 0.596875011920929,
"alphanum_fraction": 0.625,
"avg_line_length": 20.33333396911621,
"blob_id": "00c51f3dd157732da65f690d8a91b118d14e9916",
"content_id": "54193cd94a21d0daa1dbdfdda6abc742b8a53d43",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 320,
"license_type": "no_license",
"max_line_length": 73,
"num_lines": 15,
"path": "/4.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import urllib2\n\nnothing = [25357]\nwhile nothing != []:\n\n url = \"http://www.pythonchallenge.com/pc/def/linkedlist.php?nothing=\"\n url = url + str(nothing[0])\n page = urllib2.urlopen(url)\n data = page.read()\n\n current = nothing[0]\n\n print data\n\n nothing = [int(s) for s in data.split() if s.isdigit()]\n"
},
{
"alpha_fraction": 0.6524590253829956,
"alphanum_fraction": 0.6737704873085022,
"avg_line_length": 29.5,
"blob_id": "d22f3b06a794586f05cdd819677452b182576555",
"content_id": "0e2ac0d9d6d5b5707193072d9f0308023e396e01",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 610,
"license_type": "no_license",
"max_line_length": 90,
"num_lines": 20,
"path": "/12.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "# The webpage details\nurl = \"http://www.pythonchallenge.com/pc/return/evil.html\"\nusername = \"huge\"\npassword = \"file\"\n\n# Source code says image is called evil1.jpg. Check for evil2.jpg\nurl2 = \"http://www.pythonchallenge.com/pc/return/evil2.jpg\"\n\n# Leads to downloading the file evil2.gfx. A file of characters. Normally multiple images?\ndata = open('evil2.gfx').read()\nprint len(data)\n\n# The size of the file is divisible by 5. Multiple of 5 images?\nimg = {}\nfor i in range(5):\n img[i] = open(\"12.\" + str(i+1) + \".jpg\", \"w\" )\n\nfor i in range(len(data)):\n i_img = i % 5\n img[i_img].write(data[i])\n"
},
{
"alpha_fraction": 0.5882353186607361,
"alphanum_fraction": 0.6155462265014648,
"avg_line_length": 24.052631378173828,
"blob_id": "542fbfa9fd5cf4dfbc954ba5b4e33d571ea12848",
"content_id": "d363b3d4d4af3d784de7ba4658b0193a3b5f2b48",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 476,
"license_type": "no_license",
"max_line_length": 54,
"num_lines": 19,
"path": "/2.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import urllib2\nurl = \"http://www.pythonchallenge.com/pc/def/ocr.html\"\npage = urllib2.urlopen(url)\ndata = page.read()\n\nstart_data = data.find(\"<!--\")\nmy_data = data[start_data:]\n\nchars = list(my_data)\ncount = [None] * 128\nfor n in range(128):\n count[n] = my_data.count(chr(n))\n if count[n] > 100: count[n] = 0\n if count[n] == 0:\n while chr(n) in chars: chars.remove(chr(n))\n # #To see progress of code\n # print n\nsol = \"\".join(chars)\nprint \"\".join(chars)\n"
},
{
"alpha_fraction": 0.5789473652839661,
"alphanum_fraction": 0.699999988079071,
"avg_line_length": 29,
"blob_id": "f373466befcd5f65088940b62ada5a485c642335",
"content_id": "568118feb8448c4c7cda0d3611e913e6678f2e78",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 570,
"license_type": "no_license",
"max_line_length": 110,
"num_lines": 19,
"path": "/8.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import urllib2\nimport bz2\n\nurl = \"http://www.pythonchallenge.com/pc/def/integrity.html\"\npage = urllib2.urlopen(url)\ndata = page.read()\n\nstart_data = data.find(\"<!--\")\nend_data = data.find(\"-->\")\nmy_data = data[start_data+4:end_data]\n\nprint my_data\n\n# Found from the source code of the page\nun = 'BZh91AY&SYA\\xaf\\x82\\r\\x00\\x00\\x01\\x01\\x80\\x02\\xc0\\x02\\x00 \\x00!\\x9ah3M\\x07<]\\xc9\\x14\\xe1BA\\x06\\xbe\\x084'\npw = 'BZh91AY&SY\\x94$|\\x0e\\x00\\x00\\x00\\x81\\x00\\x03$ \\x00!\\x9ah3M\\x13<]\\xc9\\x14\\xe1BBP\\x91\\xf08'\n\nprint \"Username:\", bz2.decompress(un)\nprint \"Password:\", bz2.decompress(pw)\n"
},
{
"alpha_fraction": 0.6047903895378113,
"alphanum_fraction": 0.6227545142173767,
"avg_line_length": 19.875,
"blob_id": "c4d43baf860fd0a776b4a439b4305831c4cc1ed3",
"content_id": "20378b5dc481cf296ae50a7464d4c5513a2d72d7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 334,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 16,
"path": "/5.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "import urllib2\nimport pickle\n\nurl = \"http://www.pythonchallenge.com/pc/def/banner.p\"\npage = urllib2.urlopen(url)\ndata = page.read()\n\nmy_data = pickle.loads(data)\n\nprint my_data[1][1]\n\nfor i in range(len(my_data)):\n txt = \"\"\n for j in range(len(my_data[i])):\n txt = txt + my_data[i][j][0] * my_data[i][j][1]\n print txt\n"
},
{
"alpha_fraction": 0.41327300667762756,
"alphanum_fraction": 0.46304675936698914,
"avg_line_length": 22.678571701049805,
"blob_id": "7df902443a55b1de2013b408c3b6212f85534951",
"content_id": "64432c5ebf954861452a57fbc94eb1c86a7554f0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 663,
"license_type": "no_license",
"max_line_length": 75,
"num_lines": 28,
"path": "/10.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "# The webpage details\nurl = \"http://www.pythonchallenge.com/pc/return/bull.html\"\nusername = \"huge\"\npassword = \"file\"\n\n# Clicking on the bull gives:\n# a = [1, 11, 21, 1211, 111221,\n# Need to find a[30].\n# 1 = \"one ones\" -> 11 = \"two ones\" -> 21 = \"one twos, one ones\" -> 1211...\n\na = \"1\"\nfor x in range(30):\n anew = \"\"\n i = 0\n while i < len(a):\n count = 1\n for d in range(i+1,len(a)):\n if a[i] != a[d]:\n anew += str(count) + str(a[i])\n i = d\n break\n count += 1\n else:\n anew += str(count) + str(a[i])\n i = len(a)\n a = anew\n\nprint len(a)\n"
},
{
"alpha_fraction": 0.6012345552444458,
"alphanum_fraction": 0.6185185313224792,
"avg_line_length": 30.153846740722656,
"blob_id": "6060e210c1e3f9037baffd5ce00faf2bc8f20756",
"content_id": "daa7c916049c4069d25eb0703bdd60726687c81f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 810,
"license_type": "no_license",
"max_line_length": 79,
"num_lines": 26,
"path": "/11.py",
"repo_name": "Yadub/the_python_challenge",
"src_encoding": "UTF-8",
"text": "from PIL import Image, ImageDraw\n\n# The webpage details\nurl = \"http://www.pythonchallenge.com/pc/return/5808.html\"\nusername = \"huge\"\npassword = \"file\"\n\n# Title is called odd even. Can the image be segregated by odd and even pixels?\n\n# # Open image and get its data\nim = Image.open('cave.jpg')\npixels = list(im.getdata()) # Get Pixel Data\nwidth, height = im.size\n# Initialize odd and even images\nodd = Image.new(\"RGB\", (width // 2, height // 2))\neven = Image.new(\"RGB\", (width // 2, height // 2))\n# Put appropriate pixels in place\nfor w in range(width):\n for h in range(height):\n if (w + h) % 2 == 0:\n even.putpixel( (w // 2, h // 2), pixels[ h * width + w] )\n else:\n odd.putpixel( (w // 2, h // 2), pixels[ h * width + w] )\n# Show the images\nodd.show()\neven.show()\n"
}
] | 11
|
marcoswca/algorithms
|
https://github.com/marcoswca/algorithms
|
43fdf435abae01df2d3f2e1225a63902691b344e
|
4d9994e95d294594444a914bf1e0ac74e134925c
|
c50a709fa63d35b02ce1fbc3ce3bcd87325d1cb5
|
refs/heads/master
| 2020-12-04T14:57:27.721357
| 2020-10-23T02:30:59
| 2020-10-23T02:30:59
| 231,808,236
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.3914373219013214,
"alphanum_fraction": 0.4678899049758911,
"avg_line_length": 19.5,
"blob_id": "b04a4d450e7453a088ac9cb79e752782fbd32f1e",
"content_id": "77683f85ae725e1af3216c470c3963199a349864",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 327,
"license_type": "no_license",
"max_line_length": 41,
"num_lines": 16,
"path": "/coins.js",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "function solution(A) {\n A = A * 100;\n let coins = [100, 50, 25, 10, 5, 1];\n let moneyChange = [0, 0, 0, 0, 0, 0];\n\n coins.forEach((coin, index) => {\n while (A - coin >= 0) {\n A -= coin;\n moneyChange[index] += 1;\n }\n });\n\n return moneyChange;\n}\n\nconsole.log(solution(4.45));"
},
{
"alpha_fraction": 0.6197183132171631,
"alphanum_fraction": 0.6338028311729431,
"avg_line_length": 21.1875,
"blob_id": "c74cf882448a2c0853fc72870e8302f9bc042517",
"content_id": "206c1824e46432af737e384dce56189ceac2faeb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 355,
"license_type": "no_license",
"max_line_length": 59,
"num_lines": 16,
"path": "/REMOVEDUP.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "n = int(input())\noriginalArray = []\nwhile(n>0):\n element = int(input())\n if(originalArray.count(element) == 0):\n originalArray.append(element)\n n-=1\n\norder = ''\nreverse = ''\nfor i in range(0, len(originalArray)):\n order+=str(originalArray[i])+' '\n reverse+=str(originalArray[len(originalArray)-i-1])+' '\n\nprint(order)\nprint(reverse)\n"
},
{
"alpha_fraction": 0.5310077667236328,
"alphanum_fraction": 0.5341085195541382,
"avg_line_length": 27.688888549804688,
"blob_id": "b0c6e38c7e3ea7d70e65b726015d3bcc954ceb3f",
"content_id": "024c6383faf5477b12f1e0bfdfa5a535bc800135",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1290,
"license_type": "no_license",
"max_line_length": 64,
"num_lines": 45,
"path": "/SQF.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "class Categorie:\n def __init__(self, name, total_keys, limit):\n self.name = name\n self.total_keys = int(total_keys)\n self.limit = int(limit)\n self.keys = []\n \n def belengosTo(self, text):\n counter = 0\n words = text.split()\n for key in self.keys:\n counter += words.count(key)\n if(counter >= self.limit):\n return True\n else: \n return False\n \ndef main():\n test_case = input()\n categories = []\n for case_index in xrange(0, test_case):\n categories_number = input()\n for cat_index in xrange(0, categories_number):\n categorie_data = raw_input().split()\n categorie_instance = Categorie(*categorie_data)\n for key in xrange(0, categorie_instance.total_keys):\n categorie_instance.keys.append(raw_input())\n categories.append(categorie_instance)\n \n text = ''\n \n text = '\\n'.join(iter(raw_input, text))\n\n belongs_to = \"\"\n for categorie in categories:\n if(categorie.belengosTo(text)):\n belongs_to += categorie.name + \" \"\n \n if(belongs_to == \"\"):\n print(\"SQF Problem\")\n else:\n print(belongs_to.strip())\n \nif __name__ == \"__main__\":\n main()"
},
{
"alpha_fraction": 0.45588234066963196,
"alphanum_fraction": 0.5,
"avg_line_length": 33.5,
"blob_id": "7914bfef114fccda6ced6b65e46c65f913ad0e16",
"content_id": "bd864cd170c11f369a271aed0891b5ed8f1d8185",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 68,
"license_type": "no_license",
"max_line_length": 38,
"num_lines": 2,
"path": "/TAPETAO.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "[l,n] = map(int , raw_input().split())\nprint (l-(n-1))*(l-(n-1))+n-1"
},
{
"alpha_fraction": 0.4395161271095276,
"alphanum_fraction": 0.4677419364452362,
"avg_line_length": 23.399999618530273,
"blob_id": "e7bdb46812479e47b73ff45d852def6602ebf983",
"content_id": "177f153de49c64bd0dc331fb26e1bcd94e00fb25",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 248,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 10,
"path": "/QUERM.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "n = input()\ntestcase = 0\nwhile (n != 0):\n testcase+=1\n case = raw_input().split()\n for c in range(0, n):\n if(int(case[c]) == c+1):\n print(\"Teste {0} \\n{1}\".format(testcase, case[c]))\n break\n n = input()\n "
},
{
"alpha_fraction": 0.5163297057151794,
"alphanum_fraction": 0.5800933241844177,
"avg_line_length": 17.91176414489746,
"blob_id": "759c60946b80caf95a7f0246ceaa2452e129fc19",
"content_id": "cde3a3135d32b7885b9814f3e411bf069cda1cf8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Java",
"length_bytes": 643,
"license_type": "no_license",
"max_line_length": 64,
"num_lines": 34,
"path": "/Prime.java",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "package algorithms;\n\n/*\n * The prime factors of 13195 are 5, 7, 13 and 29.\n * What is the largest prime factor of the number 600851475143 ?\n */\npublic class Prime {\n\tpublic static void main(String[] args) {\n\t\tSystem.out.println(solution());\n\t}\n\n\tprivate static long solution() {\n\t\tlong num = 600851475143L;\n\t\tfor (long i = 1; i < num; i++) {\n\t\t\tif (num % i == 0) {\n\t\t\t\tlong factor = num / i;\n\t\t\t\tif (isPrime(factor)) {\n\t\t\t\t\treturn factor;\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t\treturn 0;\n\t}\n\n\tprivate static boolean isPrime(long num) {\n\t\tlong half = num / 2;\n\t\tfor (int i = 2; i <= half; i++) {\n\t\t\tif (num % i == 0) {\n\t\t\t\treturn false;\n\t\t\t}\n\t\t}\n\t\treturn true;\n\t}\n}\n"
},
{
"alpha_fraction": 0.3891891837120056,
"alphanum_fraction": 0.4216216206550598,
"avg_line_length": 17.600000381469727,
"blob_id": "7f5e6af9323cb1b716378bc45dc1a1eb408a5f12",
"content_id": "ffd87ee0367710f4a90740f41ad0cff8b4145d1c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 185,
"license_type": "no_license",
"max_line_length": 69,
"num_lines": 10,
"path": "/HANOI.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "n = input()\ni = 1\nsaida = ''\nwhile(n != 0):\n saida = saida + 'Teste ' + str(i) + '\\n' + str(pow(2,n)-1) + '\\n'\n i+=1\n n = input()\n if(n!=0):\n saida+='\\n'\nprint(saida)"
},
{
"alpha_fraction": 0.48481881618499756,
"alphanum_fraction": 0.5014691352844238,
"avg_line_length": 23.90243911743164,
"blob_id": "ead35dea11caff8e4872b53c617c3fd7bb602f37",
"content_id": "7837df7ec1c0109693336e4ec422ee02c82d0409",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1021,
"license_type": "no_license",
"max_line_length": 58,
"num_lines": 41,
"path": "/SALDO.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "from sys import maxint \ntotal_inputs = input()\nresult = ''\ncount_test = 1\nwhile(total_inputs != 0):\n response = []\n max_end_here = 0\n max_so_far = -maxint - 1\n for i in xrange (0, total_inputs):\n case = map(int, raw_input().strip().split())\n\n max_end_here = max_end_here + case[0] - case[1]\n\n if(max_so_far <= max_end_here):\n max_so_far = max_end_here\n response.append(1)\n else:\n \n initial = None\n last = None\n\n for i in xrange (0, len(response)):\n if(response[i] == 1 and initial == None):\n initial = i + 1\n elif(response[i] == 0):\n initial = None\n \n for j in reversed(xrange(0, len(response))):\n if(response[j] == 1 and last == None):\n last = j + 1\n elif(response[j] == 0):\n last = None\n \n result += 'Teste ' + str(count_test)\n result += '\\n' + str(initial) + ' ' + str(last) + '\\n'\n \n count_test += 1\n\n total_inputs = input()\n\nprint result\n"
},
{
"alpha_fraction": 0.582812488079071,
"alphanum_fraction": 0.621874988079071,
"avg_line_length": 25.14285659790039,
"blob_id": "cd1f20b7ccafc4f0ee813596f84b37c96aa215a4",
"content_id": "68fbe19011f1ea919f2b33fa8dd4af8c19df4748",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1280,
"license_type": "no_license",
"max_line_length": 309,
"num_lines": 49,
"path": "/ALBUM12.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "try:\n def isPossible(lista, album):\n acum = 0\n\n for photo in lista:\n if(photo[1] > album[1]):\n return False\n\n acum += photo[0]\n\n if(acum > album[0]):\n return False\n\n return True\n\n album = map(int,raw_input().split())\n album_v = [album[1], album[0]]\n\n listaDeFotos = []\n possibilidade1 = []\n possibilidade2 = []\n possibilidade3 = []\n possibilidade4 = []\n\n photo1 = map(int , raw_input().split())\n photo2 = map(int , raw_input().split())\n\n possibilidade1.append(photo1)\n possibilidade1.append(photo2)\n\n possibilidade2.append([photo1[1], photo1[0]])\n possibilidade2.append(photo2)\n\n possibilidade3.append(photo1)\n possibilidade3.append([photo2[1], photo2[0]])\n\n\n possibilidade4.append([photo1[1], photo1[0]])\n possibilidade4.append([photo2[1], photo2[0]])\n\n p = isPossible(possibilidade1, album_v) or isPossible(possibilidade2, album_v) or isPossible(possibilidade3, album_v) or isPossible(possibilidade4, album_v) or isPossible(possibilidade1, album) or isPossible(possibilidade2, album) or isPossible(possibilidade3, album) or isPossible(possibilidade4, album) \n\n if(p):\n print 'S'\n else:\n print 'N'\n\nexcept:\n print 0"
},
{
"alpha_fraction": 0.5655577182769775,
"alphanum_fraction": 0.6301369667053223,
"avg_line_length": 22.227272033691406,
"blob_id": "a265f4102a8fa1f681578458c481e363a18e9d4f",
"content_id": "bd62807ea756d8e1fdd2bc9cc30b95b119bc0134",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Java",
"length_bytes": 511,
"license_type": "no_license",
"max_line_length": 133,
"num_lines": 22,
"path": "/Multiple3and5.java",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "package algorithms;\n\n/*\n * If we list all the natural numbers below 10 that are multiples of 3 or 5, we get 3, 5, 6 and 9. The sum of these multiples is 23. \n * Find the sum of all the multiples of 3 or 5 below 1000.\n */\npublic class Multiple3and5 {\n\t\n\tpublic static void main(String[] args) {\n\t\tSystem.out.println(solution(100000000));\n\t}\n\n\tprivate static int solution(int value) {\n\t\tint count = 0;\n\t\tfor (int i = 1; i < value; i++) {\n\t\t\tif (i % 3 == 0 || i % 5 == 0)\n\t\t\t\tcount += i;\n\t\t}\n\n\t\treturn count;\n\t}\n}\n"
},
{
"alpha_fraction": 0.5246020555496216,
"alphanum_fraction": 0.5448625087738037,
"avg_line_length": 35.3684196472168,
"blob_id": "08157e044fd84471f1c3d2cb739f294cfc178c69",
"content_id": "78be5b051d098fc13b6cb9e917060345c0068d04",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Java",
"length_bytes": 1382,
"license_type": "no_license",
"max_line_length": 116,
"num_lines": 38,
"path": "/LeetCodeTwoSum.java",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "import java.util.ArrayList;\nimport java.util.Arrays;\nimport java.util.HashMap;\nimport java.util.List;\nimport java.util.Map;\n\npublic class LeetCodeTwoSum {\n public static int[] twoSum(int[] nums, int target) {\n int[] response = new int[2];\n Map<Integer, List<Integer>> map = new HashMap<>();\n\n for (int i = 0; i < nums.length; i++) {\n int number = nums[i];\n if (map.containsKey(number)) {\n map.get(number).add(i);\n } else {\n map.put(number, new ArrayList<>(Arrays.asList(i)));\n }\n }\n\n for (int i = 0; i < nums.length; i++) {\n int numberToFind = target - nums[i];\n if (map.containsKey(numberToFind) && map.get(numberToFind).get(map.get(numberToFind).size() - 1) != i) {\n response[0] = i;\n response[1] = map.get(numberToFind).get(map.get(numberToFind).size() - 1);\n return response;\n }\n }\n return new int[]{};\n }\n\n public static void main(String[] args) {\n System.out.println(Arrays.toString(twoSum(new int[]{7, 2, 11, 15}, 9)));\n System.out.println(Arrays.toString(twoSum(new int[]{2, 7, 11, 15}, 9)));\n System.out.println(Arrays.toString(twoSum(new int[]{3, 2, 4}, 6)));\n System.out.println(Arrays.toString(twoSum(new int[]{3, 3}, 6)));\n }\n}\n"
},
{
"alpha_fraction": 0.480211079120636,
"alphanum_fraction": 0.5,
"avg_line_length": 26.10714340209961,
"blob_id": "1e9b8846bf5a19db0cb0d00e09315310c45043fb",
"content_id": "a967b3fd229c96c18ced371088da24c50f19435e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 758,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 28,
"path": "/RUMO9S.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "def isMultipleOf9(number, level):\n if(len(str(number)) == 1 and number != 9):\n return False, level\n elif (number == 9):\n if(level == 0):\n return True, 1\n else:\n return True, level\n else:\n new_number = 0\n for n in str(number):\n new_number += int(n)\n return isMultipleOf9(new_number, level + 1)\n\ndef main():\n number = input()\n while number != 0:\n isMultiple, level = isMultipleOf9(number, 0)\n \n if(isMultiple):\n print(str(number) + ' is a multiple of 9 and has 9-degree ' + str(level) + '.')\n else:\n print(str(number) + ' is not a multiple of 9.')\n \n number = input()\n\nif __name__ == \"__main__\":\n main()"
},
{
"alpha_fraction": 0.4015544056892395,
"alphanum_fraction": 0.5129533410072327,
"avg_line_length": 20.44444465637207,
"blob_id": "26b23521dc878fa3a0342ffa76253bb3cb5f4882",
"content_id": "ae8d27c2ecd4864261cf9d7fbec5926b1a465914",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 386,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 18,
"path": "/coins2.js",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "function solution(A) {\n let change = Math.round(A * 100);\n const coins = [100, 50, 25, 10, 5, 1];\n let result = { 1: 0, 0.5: 0, 0.25: 0, 0.1: 0, 0.05: 0, 0.01: 0 };\n\n for (let i = 0; i < coins.length; i++) {\n const coin = coins[i];\n while (change - coin >= 0) {\n change -= coin;\n result[coin / 100] += 1;\n }\n }\n\n\n return result;\n}\n\nconsole.log(solution(4.26));\n"
},
{
"alpha_fraction": 0.572429895401001,
"alphanum_fraction": 0.586448609828949,
"avg_line_length": 21.526315689086914,
"blob_id": "95c4f61839c28d7014cff2ab3bd742e5756c23df",
"content_id": "c3e22db4ffdc1b6b7f291eb51e2409cbb95e476c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 428,
"license_type": "no_license",
"max_line_length": 64,
"num_lines": 19,
"path": "/NUMPALIN.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "n = int(input())\n\ndef isPalindrome(number):\n for d in range (0, int(len(str(number))/2)):\n if(str(number)[d] != str(number)[len(str(number))-d-1]):\n return 'NO'\n return 'YES'\n\ndef sumDigits(number):\n newNumber = 0\n for d in str(number):\n newNumber+=int(d)\n return newNumber\n\nwhile (n!=0):\n n-=1\n number = input()\n newNumber = sumDigits(number)\n print(isPalindrome(newNumber))\n"
},
{
"alpha_fraction": 0.6000000238418579,
"alphanum_fraction": 0.6000000238418579,
"avg_line_length": 9.090909004211426,
"blob_id": "6071ae6af057b638081acc5fb4723516c3585145",
"content_id": "1d316349657e5cd9fdb355e4b515b2a94173baad",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Java",
"length_bytes": 110,
"license_type": "no_license",
"max_line_length": 45,
"num_lines": 11,
"path": "/SQF.java",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "import java.util.*;\nimport java.lang.*;\n\nclass SQF {\n\n\n\n public static void main(String[] args ) {\n\n }\n}"
},
{
"alpha_fraction": 0.42307692766189575,
"alphanum_fraction": 0.470279723405838,
"avg_line_length": 21.8799991607666,
"blob_id": "92eea2bf7ae010fc8d2dd1bb144516328eacaddc",
"content_id": "ccdb14899b5949062db57f639076760de15d41ff",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 572,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 25,
"path": "/coins4.js",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "function solution(change) {\n const coins = [1, 2, 5];\n let table = [];\n for (let j = 0; j < coins.length + 1; j++) {\n table.push(new Array(change + 1).fill(0));\n }\n\n for (let i = 0; i < coins.length + 1; i++) {\n table[i][0] = 1;\n }\n\n for (let c = 1; c < coins.length + 1; c++) {\n for (let i = 1; i < change + 1; i++) {\n if (i >= coins[c-1]) {\n table[c][i] = table[c - 1][i] + table[c][i - coins[c - 1]];\n } else {\n table[c][i] = table[c - 1][i];\n }\n }\n }\n\n console.log(table[coins.length][change]);\n}\n\nsolution(10000000);\n"
},
{
"alpha_fraction": 0.4975247383117676,
"alphanum_fraction": 0.6064356565475464,
"avg_line_length": 22.764705657958984,
"blob_id": "8f4d7f775454cf64fc39b08b1951de511fab485d",
"content_id": "3183a482f74197353ad5618b7758d0312042af65",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 404,
"license_type": "no_license",
"max_line_length": 41,
"num_lines": 17,
"path": "/CONTA1.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "consumo = input()\nfaixa1 = 7\nfaixa4 = 0\nfaixa3 = 0\nfaixa2 = 0\n\nif(consumo>=101):\n faixa4 = int(consumo - 100) *5\n consumo -= (consumo - 100)\nif(consumo >= 31 and consumo <= 100):\n faixa3 = int(consumo - 30) *2\n consumo -= (consumo - 30)\nif(consumo >= 11 and consumo <= 30):\n faixa2 = int(consumo - 10) *1\n consumo -= (consumo - 10)\ntotal = faixa4 + faixa3 + faixa2 + faixa1\nprint total\n"
},
{
"alpha_fraction": 0.5083267092704773,
"alphanum_fraction": 0.5226011276245117,
"avg_line_length": 26.413043975830078,
"blob_id": "3ef5ad8d5040ed97ae3ea85ff0961b1da5f4c3e2",
"content_id": "0b0d0f3e7b0f999fe27ef96638e438f84a7d0507",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1261,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 46,
"path": "/SubArraySumK.py",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "\ndef firstOnePosition(position):\n for i in range(len(position)):\n if(position[i]==1):\n return i\n return len(position)\n\ndef firstIndexOne(position):\n for i in range(len(position)):\n if(position[i]==1):\n return i+1\n\ndef lastIndexOne(position):\n for i in reversed(range(len(position))):\n if(position[i]==1):\n return i+1\n\ndef printResult(position):\n print('{0} {1}'.format(firstIndexOne(position), lastIndexOne(position)))\n\ntest_case = int(input())\n\nwhile (test_case != 0):\n [n_elements, k] = map(int, raw_input().split())\n myArray = map(int, raw_input().split())\n currentSum = 0\n position = [0] * len(myArray)\n i = 0\n while (i<n_elements):\n if(currentSum == k):\n printResult(position)\n break\n elif(currentSum > k):\n firstIndex = firstOnePosition(position)\n if(firstIndex>=len(position)):\n print('-1')\n break\n currentSum-=myArray[firstIndex]\n position[firstIndex] = 0\n i = i - 1\n else:\n if(i+1==n_elements):\n print('-1')\n break\n currentSum += myArray[i]\n position[i] = 1\n i+=1"
},
{
"alpha_fraction": 0.6801195740699768,
"alphanum_fraction": 0.681614339351654,
"avg_line_length": 22.89285659790039,
"blob_id": "62f51ab6ddb129666fca4b5ac2834fdf303d1dfb",
"content_id": "4b4434dcf09c28ece839ffd605f1e86c35445dfa",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Java",
"length_bytes": 676,
"license_type": "no_license",
"max_line_length": 80,
"num_lines": 28,
"path": "/Circulo.java",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "package algorithms;\n\nimport java.io.IOException;\nimport java.util.Scanner;\nimport java.lang.Math;\n\n/**\n * IMPORTANT: O nome da classe deve ser \"Main\" para que a sua solução execute\n * Class name must be \"Main\" for your solution to execute El nombre de la clase\n * debe ser \"Main\" para que su solución ejecutar\n */\npublic class Circulo {\n\n\tpublic static void main(String[] args) throws IOException {\n\n\t\t/**\n\t\t * Escreva a sua solução aqui Code your solution here Escriba su solución aquí\n\t\t */\n\n\t\ttry (Scanner in = new Scanner(System.in)) {\n\t\t\twhile (in.hasNext()) {\n\t\t\t\tDouble rad = in.nextDouble();\n\t\t\t\tSystem.out.printf(\"%.4f\\n\", Math.PI * rad * rad);\n\t\t\t}\n\t\t}\n\t}\n\n}\n"
},
{
"alpha_fraction": 0.3167622685432434,
"alphanum_fraction": 0.3581899404525757,
"avg_line_length": 18.14634132385254,
"blob_id": "8874b2f4d3d726f11227d2f0c45ae8f27c457f24",
"content_id": "6b55d409a150aaef5d8fcef44d9b9d0eb7d94d4a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 1569,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 82,
"path": "/deck.js",
"repo_name": "marcoswca/algorithms",
"src_encoding": "UTF-8",
"text": "function solution(A) {\n let one = ['ac', 'ad', 'ah', 'as'];\n let two = ['2c', '2d', '2h', '2s'];\n let three = ['3c', '3d', '3h', '3s'];\n let four = ['4c', '4d', '4h', '4s'];\n let five = ['5c', '5d', '5h', '5s'];\n let six = ['6c', '6d', '6h', '6s'];\n let seven = ['7c', '7d', '7h', '7s'];\n let eight = ['8c', '8d', '8h', '8s'];\n let nine = ['9c', '9d', '9h', '9s'];\n let jack = ['jc', 'jd', 'jh', 'js'];\n let queen = ['qc', 'qd', 'qh', 'qs'];\n let king = ['kc', 'kd', 'kh', 'ks'];\n let deck = [...one, ...two, ...three, ...four, ...five, ...six, ...seven, ...eight, ...nine, ...jack, ...queen, ...king];\n console.log(deck);\n if (deck.length !== A.length) {\n return false;\n }\n\n A = [...one, ...two, ...three, ...four, ...five, ...six, ...seven, ...eight, ...nine, ...jack, ...queen, ...king];\n\n A = A.sort();\n deck = deck.sort();\n\n for (let i = 0; i < deck.length; i++) {\n let card = deck[i];\n let cardInput = A[i];\n if (card !== cardInput) return false;\n }\n\n return true;\n}\n\nconsole.log(solution(['ac',\n 'ad',\n 'ah',\n 'as',\n '2c',\n '2d',\n '2h',\n '2s',\n '3c',\n '3d',\n '3h',\n '3s',\n '4c',\n '4d',\n '4h',\n '4s',\n '5c',\n '5d',\n '5h',\n '5s',\n '6c',\n '6d',\n '6h',\n '6s',\n '7c',\n '7d',\n '7h',\n '7s',\n '8c',\n '8d',\n '8h',\n '8s',\n '9c',\n '9d',\n '9h',\n '9s',\n 'jc',\n 'jd',\n 'jh',\n 'js',\n 'qc',\n 'qd',\n 'qh',\n 'qs',\n 'kc',\n 'kd',\n 'kh',\n 'ks']\n));"
}
] | 20
|
joseph8th/devdial
|
https://github.com/joseph8th/devdial
|
5fa7d9729e787b0e7667d50b1d8fb37b287813d8
|
65a9463beb36f97a7dffc5a4652cbf98b895da5a
|
ab57498493ad3cc0a2fdc32784d33433fd68a424
|
refs/heads/master
| 2021-01-10T09:21:41.960454
| 2017-07-10T21:37:50
| 2017-07-10T21:37:50
| 51,599,851
| 2
| 1
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4421052634716034,
"alphanum_fraction": 0.5473684072494507,
"avg_line_length": 16.272727966308594,
"blob_id": "7f45209c04e75b38c33be14310250026325243f1",
"content_id": "4ca069c2f0dd92bbeb9a715a4ab9479f980203f5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 380,
"license_type": "no_license",
"max_line_length": 63,
"num_lines": 22,
"path": "/settings.py",
"repo_name": "joseph8th/devdial",
"src_encoding": "UTF-8",
"text": "\"\"\"\nMap channels numbers to arbitrary names for easier remembering.\n\"\"\"\n\nAUTH_CREDS = {\n 'address': '',\n 'port': 0,\n 'username': '',\n 'secret': '',\n}\n\nCHANNEL_MAP = {\n 'pushit': 999,\n 'babywheel': 1000,\n 'blister': 1001,\n 'goldfinger': 1002,\n 'blondie': 1003,\n '2001space': 1004,\n 'coldasice': 1005,\n 'darthvader': 1006,\n 'whatsup': 1007,\n}\n"
},
{
"alpha_fraction": 0.6083611845970154,
"alphanum_fraction": 0.6193979978561401,
"avg_line_length": 31.85714340209961,
"blob_id": "a4ffce00a1660f7187137719441d15711316a744",
"content_id": "13ea2316681d3413a78e87f3266e558866bd4eae",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2990,
"license_type": "no_license",
"max_line_length": 105,
"num_lines": 91,
"path": "/devdial.py",
"repo_name": "joseph8th/devdial",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python3\n\n\"\"\"\nRing phones in paging group 999 and play Salt'n Peppa OR Baby Fuckin' Wheel.\nAUTHORS: Mark Warren, Joseph Edwards\n\"\"\"\n\nimport os, sys\nimport argparse\nfrom asterisk.ami import AMIClient\nfrom asterisk.ami.action import SimpleAction\n\nVERBOSE=False\n\n\ndef dev_dial(action):\n \"\"\"Function that actually makes the asterisk call.\"\"\"\n\n try:\n client = AMIClient(address=AUTH_CREDS['address'], port=AUTH_CREDS['port'])\n client.login(username=AUTH_CREDS['username'], secret=AUTH_CREDS['secret'])\n\n future = client.send_action(action)\n if VERBOSE:\n print(future.response or \"None\")\n\n client.logoff()\n\n except Exception as e:\n print(\"Error: %s\" % e.strerror)\n sys.exit(1)\n\n\nif __name__==\"__main__\":\n # Follow symbolic link\n realfile = os.path.realpath(__file__)\n\n # If we have a channel map then use those as choices instead of any numeric\n CHANNEL_MAP = None\n if not os.path.exists(os.path.join(os.path.dirname(realfile), 'settings.py')):\n sys.exit(\"Settings file settings.py not found!\")\n\n from settings import CHANNEL_MAP, AUTH_CREDS\n description = \"Channel choices: {\"+', '.join(CHANNEL_MAP.keys())+\"}\" if CHANNEL_MAP else None\n\n parser = argparse.ArgumentParser(description=description)\n parser.add_argument(\"channel\", nargs=\"?\", default='999', help=\"the channel to play\")\n parser.add_argument(\"-v\", \"--verbose\", action=\"store_true\", help=\"output asterisk responses\")\n parser.add_argument(\"-o\", \"--outbound\", help=\"outbound number to dial\")\n parser.add_argument(\"-e\", \"--exten\", help=\"extension to dial\")\n parser.add_argument(\n \"-c\", \"--caller_id\", default=\"CES <3052328182>\", help=\"CallerID string, i.e., 'CES <3052328182>'\"\n )\n args = parser.parse_args()\n\n # If we used the channel map, then get the correct channel for the choice\n if not args.channel.isnumeric():\n if not CHANNEL_MAP:\n sys.exit(\"Unrecognized channel slug '{0}'\".format(args.channel))\n else:\n args.channel = CHANNEL_MAP[args.channel]\n\n # Config args for asterisk action\n if args.outbound:\n cdict = {\n \"Channel\": \"SIP/vitelity-outbound/{outbound}\".format(outbound=args.outbound),\n \"Context\": \"app-miscapps\",\n \"Exten\": \"*{channel}\".format(channel=args.channel),\n }\n elif args.exten:\n cdict = {\n \"Channel\": \"SIP/{exten}\".format(exten=args.exten),\n \"Context\": \"app-miscapps\",\n \"Exten\": \"*{channel}\".format(channel=args.channel),\n }\n else:\n cdict = {\n \"Channel\": \"Local/*{channel}@app-miscapps\".format(channel=args.channel),\n \"Context\": \"ext-paging\",\n \"Exten\": \"999\"\n }\n\n cdict.update({\"CallerID\": args.caller_id, \"Priority\": 1,})\n\n VERBOSE = args.verbose\n if VERBOSE:\n print(cdict)\n\n # Create action and dial\n action = SimpleAction(\"Originate\", **cdict)\n dev_dial(action)\n"
}
] | 2
|
vankhoa011/email_parser_demo
|
https://github.com/vankhoa011/email_parser_demo
|
29eaf5cc49fd211ce8637ac4aec6630a9bfe6738
|
a1e81c4e87b63906d9c47b63395a69666f974c0e
|
1ae103040e488419f17ad96f2e5fbfa157d211b6
|
refs/heads/master
| 2020-03-22T21:07:11.538712
| 2019-01-24T03:55:11
| 2019-01-24T03:55:11
| 140,658,195
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7020348906517029,
"alphanum_fraction": 0.7383720874786377,
"avg_line_length": 21.899999618530273,
"blob_id": "d3a7a1c1317124832bc76d22f748e7fbadc82b3b",
"content_id": "7ff2dcc240cf20c9047d64df98efab0c1ee08529",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 688,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 30,
"path": "/README.md",
"repo_name": "vankhoa011/email_parser_demo",
"src_encoding": "UTF-8",
"text": "# This is demo project how to deploy a lambda function by Terraform\n\n## Blog\n\nhttps://medium.com/@vankhoa011/parsing-log-by-aws-lambda-deploying-code-by-terraform-and-analyzing-data-by-aws-athena-92430e01680e\n\n### How to pakage this application.\n\n1. You should create a virtualenv for Python. I'm using Python 3.6\n2. Build the source code to create a zip file. \n```\n./build.sh\n```\n\n### How to deploy application to Lambda.\n\n1. Install Terraform.\n2. Configure AWS creadential. \n3. Run Terraform command to deploy\n\n```\nterraform init\nterraform apply\n```\n\n### How to verify the application.\n\n1. Upload the text file to S3.\n2. Check the S3 output bucket.\n3. Access Athena to query the data.\n\n"
},
{
"alpha_fraction": 0.6666666865348816,
"alphanum_fraction": 0.6800000071525574,
"avg_line_length": 14.8421049118042,
"blob_id": "3438068b762b1dbdb3f03dcd68f4839d3c195e07",
"content_id": "4c2ea380cbb9a59aec3c46bffb0bed9c332b8ab7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 300,
"license_type": "no_license",
"max_line_length": 51,
"num_lines": 19,
"path": "/build.sh",
"repo_name": "vankhoa011/email_parser_demo",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\n\nset -x\nset -e\n\nVENV=$VIRTUAL_ENV\nPROJ_DIR=`pwd -P`\nDELIVRABLE=./app.zip\n\n# Clean old one\nrm -f ${DELIVRABLE}\n\n# Add the whole virtual environment to the ZIP file\ncd ${VENV}/lib/python3.6/site-packages\nzip -r9 ${DELIVRABLE} ./*\n\n# Add our scripts\ncd ${PROJ_DIR}\nzip -r9 ${DELIVRABLE} *.py"
},
{
"alpha_fraction": 0.5534456372261047,
"alphanum_fraction": 0.5635528564453125,
"avg_line_length": 35.266666412353516,
"blob_id": "88d75750776ecc3ecacb0405312165ac8bbe2ca4",
"content_id": "798562de75e165eea5682e04cf31626dca66e9f6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3265,
"license_type": "no_license",
"max_line_length": 153,
"num_lines": 90,
"path": "/lambda_function.py",
"repo_name": "vankhoa011/email_parser_demo",
"src_encoding": "UTF-8",
"text": "import boto3\nfrom datetime import datetime \nimport os\nimport time\nimport json\nimport urllib.parse\n\nclient_athena = boto3.client('athena')\ns3 = boto3.client('s3')\n\ndatabase_name = \"email\"\ntable_name = \"email_info\"\n# NEED TO CHANGE - S3 bucket to output query result of Athena\ns3_result_path = \"s3://athena-email-result-output\"\n\n# NEED TO CHANGE - Data Path \ns3_data_path = \"s3://email-log-file-json/\"\ns3_folder = \"email-log-file-json\"\n\n\ndef lambda_handler(event, context):\n\n bucket = event['Records'][0]['s3']['bucket']['name']\n key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8')\n\n try:\n response = s3.get_object(Bucket=bucket, Key=key)\n email_content = response['Body'].read().decode('utf-8')\n email_lines = email_content.splitlines()\n file_name = key + \".json\"\n file_path = \"/tmp/\" + file_name\n for line in range(len(email_lines)):\n email_info = {}\n if \"Date\" in email_lines[line]:\n email_info['Date'] = email_lines[line][6:]\n email_info['Subject'] = email_lines[line+3][9:]\n email_info['From'] = email_lines[line+4][6:]\n email_info['To'] = email_lines[line+5][4:]\n with open(file_path, 'w') as outfile:\n json.dump(email_info, outfile)\n # Upload to S3.\n s3.upload_file(file_path, s3_folder, file_name)\n print(\"Upload Successful\")\n break\n print(\"Parsing Successful\")\n except Exception as e:\n print(e)\n print('Error getting object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket))\n raise e\n # We can separate create Athena table, but for saving time . I added them in this script.\n sql_query = \"\"\"\n CREATE DATABASE IF NOT EXISTS \n \"\"\" + database_name\n response = client_athena.start_query_execution(\n QueryString=sql_query,\n ResultConfiguration={\n 'OutputLocation': s3_result_path\n }\n )\n # Create table\n sql_query = \"\"\"\n CREATE EXTERNAL TABLE IF NOT EXISTS \"\"\" + database_name + \".\" + table_name + \"\"\" (\n `From` STRING,\n `Date` STRING,\n `Subject` STRING,\n `To` STRING\n )\n ROW FORMAT SERDE 'org.openx.data.jsonserde.JsonSerDe'\n WITH SERDEPROPERTIES (\n 'serialization.format' = '1'\n )\n LOCATION '\"\"\" + s3_data_path + \"\"\"';\n \"\"\"\n\n response = client_athena.start_query_execution(\n QueryString=sql_query,\n ResultConfiguration={\n 'OutputLocation': s3_result_path\n }\n )\n # Wait for query execution finish.\n time.sleep(3)\n # Get query result\n query_result = client_athena.get_query_execution(\n QueryExecutionId=response['QueryExecutionId']\n )\n if query_result['QueryExecution']['Status']['State'] == 'FAILED':\n raise Exception(query_result['QueryExecution']['Status']['StateChangeReason'])\n else:\n print(\"Create Athena DB Succesfully\")\n\n"
}
] | 3
|
TheEpicMinion/Ethereum-API
|
https://github.com/TheEpicMinion/Ethereum-API
|
9d542e0247cb3c5e401e81c0f4813fa262d2dc4c
|
2655f586d5e55bd44fcabbdb773041c8f32f4c1f
|
daa1b8c453b7d386ca87d690391e7f7ef7a44198
|
refs/heads/main
| 2023-05-09T03:44:03.009058
| 2021-05-26T11:56:55
| 2021-05-26T11:56:55
| 364,531,752
| 2
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.622458279132843,
"alphanum_fraction": 0.6455235481262207,
"avg_line_length": 31.623762130737305,
"blob_id": "a6dbfd1c9d5800ee46b96be7955006a3804944d4",
"content_id": "ea0a0a7c91d15aff7bd3ff256271a1f71a85ab28",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3295,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 101,
"path": "/EthereumWorth.py",
"repo_name": "TheEpicMinion/Ethereum-API",
"src_encoding": "UTF-8",
"text": "import urllib.request\nimport json\nimport requests\nfrom datetime import datetime\nimport time as t\nimport pylint\n\n# This is a script written for current price of the Ethereum cryptocurrency\n# All you need to do is fill in your Discord Webhooklink on line 22, your Etherscan API on line 25,\n# And the time of interval in seconds on line 28\n\n# The Etherscan API key isn't necessarry if you don't set the time under 5 sec\n\n# Now just run the program and everything should be ready to go.\n# Bugs can be reported to 'Epic Minion#5253'\n\n# Consider buying me a coffee\n# Ethereum: 0xECB542Cf182Eb4B0A1a7B81Fb2113E833FeEb017\n# Bitcoin: bc1qtmmlhlmdezre2ur3xvqlnv9kdcjw8ejfmsk3jc\n\n# Insert Discord Webhook here\ndiscordWebhookURL = \"\"\n\n# Insert etherscan.io API key here, you can get one here https://etherscan.io/myapikey/\napikey = \"\"\n\n# Insert time in seconds to wait between messages\ndelay = 3600\n\ndef discordWebhook():\n url = discordWebhookURL\n payload = {\n \"embeds\": [\n {\n \"author\": {\n \"name\": titleStr + \" | \" + str(worthUSD) + \"$\",\n \"url\": \"https://etherscan.io\",\n \"icon_url\": \"https://cryptologos.cc/logos/ethereum-eth-logo.png\",\n },\n \"description\": \"Proposed gas: **\" + gasPricePropose + \"**gwei | Fast gas: **\" + gasPriceFast + \"**gwei\",\n \"color\": color\n }\n ]\n }\n headers = {\"Content-Type\": \"application/json\"}\n response = requests.request(\"POST\", url, json=payload, headers=headers)\n\nworthUSDPrev = 1\n\nwhile(True):\n # Etherium price API\n url_price = \"https://api.etherscan.io/api?module=stats&action=ethprice&apikey=\" + apikey\n response = urllib.request.urlopen(url_price)\n data = json.loads(response.read())\n\n # Etherium gas API\n gas_url = \"https://api.etherscan.io/api?module=gastracker&action=gasoracle&apikey=\" + apikey\n gas_response = urllib.request.urlopen(gas_url)\n gas = json.loads(gas_response.read())\n\n # Get the worth in USD from JSON\n worthUSD = float(data[\"result\"][\"ethusd\"])\n\n # Check what embed color it gets\n if worthUSD <= worthUSDPrev : \n color = 16711680 # Price went down\n else : \n color = 65280 # Price went up\n\n # Get the timestamp from JSON\n timestamp = int(data[\"result\"][\"ethusd_timestamp\"])\n time = datetime.fromtimestamp(timestamp)\n\n # Calculating the percantage\n if worthUSD < worthUSDPrev : \n # Price went down\n percentage = (worthUSD / worthUSDPrev) * 100\n percentage = round(100 - percentage, 2) * -1\n\n titleStr = \"PRICE DROPPED: \" + str(percentage) + \"%\"\n\n else : \n # Price went up\n percentage = worthUSD / worthUSDPrev * 100\n percentage = round(percentage - 100, 2)\n\n titleStr = \"PRICE ROSE: \" + str(percentage) + \"%\"\n\n # Get the average gas price from JSON\n gasPricePropose = gas[\"result\"][\"ProposeGasPrice\"]\n gasPriceFast = gas[\"result\"][\"FastGasPrice\"]\n\n # Only send if there is a change and when the program isn't running for the first time\n if percentage != 0.0 and worthUSDPrev != 1:\n # Send the discord Webhook\n discordWebhook()\n\n # Set the new price as the old one for next time\n worthUSDPrev = worthUSD\n\n t.sleep(delay)\n"
},
{
"alpha_fraction": 0.5645445585250854,
"alphanum_fraction": 0.5853084921836853,
"avg_line_length": 33.040000915527344,
"blob_id": "0e1be08a65cea9ee983882cd320b5e4763293f96",
"content_id": "06365d85ee24e369cae4a77d72952f129d4e0ece",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5105,
"license_type": "no_license",
"max_line_length": 138,
"num_lines": 150,
"path": "/ethermine-api.py",
"repo_name": "TheEpicMinion/Ethereum-API",
"src_encoding": "UTF-8",
"text": "import urllib.request\nimport json\nimport requests\nimport time\n\n# This is a script written for the Ethereum cryptocurrency on the 2miners pool\n# All you need to do is fill in your Discord Webhooklink on line 18, your ethereumAdress on line 21,\n# And the time of interval in seconds on line 24.\n\n# Now just run the program and everything should be ready to go.\n# Bugs can be reported to 'Epic Minion#5253'\n\n# Consider buying me a coffee\n# Ethereum: 0xECB542Cf182Eb4B0A1a7B81Fb2113E833FeEb017\n# Bitcoin: bc1qtmmlhlmdezre2ur3xvqlnv9kdcjw8ejfmsk3jc\n\n# Insert Discord Webhook here\ndiscordWebhookURL = \"\"\n\n# Insert Ethereum adress here\n\nethereumAdress = \"\"\n\n# Insert time in seconds to wait between messages\ndelay = 1800\n\ndef spacer(message, char):\n posistion = len(message) - 2\n message = message[:posistion] + char + message[posistion:]\n return message\n\ndef discordWebhook():\n url = discordWebhookURL\n payload = {\n \"embeds\": [\n {\n \"author\": {\n \"name\": ethereumAdress,\n \"url\": \"https://ethermine.org/miners/\" + ethereumAdress,\n \"icon_url\": \"https://static.netify.ai/logos/e/t/h/rgurezvar/icon.png?v=1\",\n },\n \"description\": \"**Current Hashrate: **\" + hashrateCurrent + \" MH/s\\n**Reported Hashrate: **\" + hashrateReported + \" MH/s\",\n \"fields\": [\n {\n \"name\": \"Workers\",\n \"value\": \"Online: **\" + workerAmount + \"**\\n\" + workerStr,\n \"inline\": True\n },\n {\n \"name\": \"Shares\",\n \"value\": \"Valid: **\" + sharesValid + \"**\\nInvalid: **\" + sharesInvalid + \"**\\nStale: **\" + sharesStale + \"**\",\n \"inline\": True\n }, \n {\n \"name\": \"Balance\",\n \"value\": \"Unpaid: **\" + balanceUnpaid + \"** ETH\",\n \"inline\": True\n }\n ],\n }\n ]\n }\n headers = {\"Content-Type\": \"application/json\"}\n response = requests.request(\"POST\", url, json=payload, headers=headers)\n\nwhile(True):\n workerStr = \"\"\n\n url = \"https://api.ethermine.org/miner/\" + ethereumAdress + \"/dashboard\"\n headers = {\n\t \"cookie\": \"pmuser_country=be\",\n\t \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:87.0) Gecko/20100101 Firefox/87.0\"\n\t}\n response = requests.request(\"GET\", url, headers=headers).json()\n\n # Retrieve unpaid value from DICT\n unpaid = response[\"data\"][\"currentStatistics\"][\"unpaid\"]\n\n # Clear last 12 char and add DICT\n unpaid = str(unpaid)[:-12] + \"\\xb5 ETH\"\n\n # Retrieve hashrates from DICT\n hashrateCurrent = str(int((response[\"data\"][\"currentStatistics\"][\"currentHashrate\"])))\n hashrateReported = str(int((response[\"data\"][\"currentStatistics\"][\"reportedHashrate\"])))\n\n # Clear last chars\n hashrateCurrent = hashrateCurrent[:-4]\n hashrateCurrent = spacer(hashrateCurrent, \".\")\n\n hashrateReported = hashrateReported[:-4]\n hashrateReported = spacer(hashrateReported, \".\")\n\n # Retrieve worker value from DICT\n workerAmount = response[\"data\"][\"currentStatistics\"][\"activeWorkers\"]\n\n # initialize/reset the counter\n i = 0\n j = 0\n\n # Add Variables\n start = 0\n end = workerAmount\n step = 1\n\n # Loop throug every worker name\n for item in range(start,end,step):\n if i <= 30:\n # name of the worker\n workerName = response[\"data\"][\"workers\"][i][\"worker\"]\n workerReported = str(int(response[\"data\"][\"workers\"][i][\"reportedHashrate\"]))\n workerAverage = str(int(response[\"data\"][\"workers\"][i][\"currentHashrate\"]))\n\n # Clear last chars\n workerAverage = workerAverage[:-4]\n workerAverage = spacer(workerAverage, \".\")\n\n workerReported = workerReported[:-4]\n workerReported = spacer(workerReported, \".\")\n\n\n workerStr = str(workerStr + (\"*\" + workerName + \":* \" + str(workerAverage) + \" MH | \" + str(workerReported) + \" MH\\n\"))\n\n # Up one the counter\n i = i + 1\n\n # Chaning int to string\n workerAmount = str(workerAmount)\n\n # Retrieve amount of shares from DICT\n sharesValid = str(response[\"data\"][\"currentStatistics\"][\"validShares\"])\n sharesInvalid = str(response[\"data\"][\"currentStatistics\"][\"invalidShares\"])\n sharesStale = str(response[\"data\"][\"currentStatistics\"][\"staleShares\"])\n\n # Retrieve unpaid balance from JSON\n balanceUnpaid = str(response[\"data\"][\"currentStatistics\"][\"unpaid\"])\n balanceUnpaid = balanceUnpaid[:-14]\n\n if int(balanceUnpaid) < 100:\n balanceUnpaid = \"0.00\" + balanceUnpaid\n elif int(balanceUnpaid) < 1000:\n balanceUnpaid = \"0.0\" + balanceUnpaid\n elif int(balanceUnpaid) < 10000:\n balanceUnpaid = \"0.\" + balanceUnpaid\n else:\n balanceUnpaid = \"0.\" + balanceUnpaid\n\n # Send the discord Webhook\n discordWebhook()\n\n time.sleep(delay)"
},
{
"alpha_fraction": 0.7267355918884277,
"alphanum_fraction": 0.7754800319671631,
"avg_line_length": 28.434782028198242,
"blob_id": "847b831876758b68e320c557804bae8578ebeadc",
"content_id": "2f3c80bb8007748249370f3ccbf34e02af8c79ca",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 677,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 23,
"path": "/README.md",
"repo_name": "TheEpicMinion/Ethereum-API",
"src_encoding": "UTF-8",
"text": "# Ethereum-API\n\n This is a repository written for the Ethereum cryptocurrency\n All you need to do is download the files, fill in the requested info filled \n at the top of the file and run the script.\n\n\n\n This is a small community repository, requests can be made. This means if\n your request something it doesn't HAVE to be made. The auther chooses self\n if he makes it. All changes will be uploaded on the repository together with\n new projects.\n\n\n\n Bugs/reports/request can be reported to '*Epic Minion#5253*' on Discord\n\n\n\n **Consider buying me a coffee:**\n \n Ethereum: ``0xECB542Cf182Eb4B0A1a7B81Fb2113E833FeEb017``\n Bitcoin: ``bc1qtmmlhlmdezre2ur3xvqlnv9kdcjw8ejfmsk3jc``\n"
},
{
"alpha_fraction": 0.5294321775436401,
"alphanum_fraction": 0.561555802822113,
"avg_line_length": 32.68421173095703,
"blob_id": "2bdae3b9bd83460d95e31ee61ea9bccf30b11c71",
"content_id": "f7cd93bb301f0380f956f6c028fecfe51ffe04cb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5759,
"license_type": "no_license",
"max_line_length": 175,
"num_lines": 171,
"path": "/2miners-api.py",
"repo_name": "TheEpicMinion/Ethereum-API",
"src_encoding": "UTF-8",
"text": "import urllib.request\nimport json\nimport requests\nimport time\n\n# This is a script written for the Ethereum cryptocurrency on the 2miners pool\n# All you need to do is fill in your Discord Webhooklink on line 18, your ethereumAdress on line 21,\n# And the time of interval in seconds on line 24.\n\n# Now just run the program and everything should be ready to go.\n# Bugs can be reported to 'Epic Minion#5253'\n\n# Consider buying me a coffee\n# Ethereum: 0xECB542Cf182Eb4B0A1a7B81Fb2113E833FeEb017\n# Bitcoin: bc1qtmmlhlmdezre2ur3xvqlnv9kdcjw8ejfmsk3jc\n\n# Insert Discord Webhook here\ndiscordWebhookURL = \"\"\n\n# Insert Ethereum adress here\nethereumAdress = \"\"\n\n# Insert time in seconds to wait between messages\ndelay = 1800\n\ndef spacer(message, char):\n posistion = len(message) - 2\n message = message[:posistion] + char + message[posistion:]\n return message\n\ndef discordWebhook():\n url = discordWebhookURL\n payload = {\n \"embeds\": [\n {\n \"author\": {\n \"name\": ethereumAdress,\n \"url\": \"https://eth.2miners.com/account/\" + ethereumAdress,\n \"icon_url\": \"https://2miners.com/i/about-page/2m_logotype_ver.png\",\n },\n \"description\": \"**Current Hashrate: **\" + hashrateCurrent + \" MH/s\\n**Average Hashrate: **\" + hashrateAverage + \" MH/s\",\n \"fields\": [\n {\n \"name\": \"Workers\",\n \"value\": \"Online: **\" + workerOnline + \"** Offline: **\" + workerOffline + \"** Total: **\" + workerTotal + \"**\\n\" + workerStr,\n \"inline\": True\n },\n {\n \"name\": \"Rewards\",\n \"value\": sumReward0 + \"\\n\" + sumReward1 + \"\\n\" + sumReward2,\n \"inline\": True\n }, \n {\n \"name\": \"Payouts\",\n \"value\": \"Paid: **\" + balancePaid + \"**\\nUnpaid: **\" + balanceUnpaid + \"**\\n Progress: **\" + progress + \"**%\\n24H Change: **\" + procentChange + \"**%\",\n \"inline\": True\n }\n ],\n }\n ]\n }\n headers = {\"Content-Type\": \"application/json\"}\n response = requests.request(\"POST\", url, json=payload, headers=headers)\n\nwhile(True):\n workerStr = \"\"\n\n url = \"https://eth.2miners.com/api/accounts/\" + ethereumAdress\n\n response = urllib.request.urlopen(url)\n\n data = json.loads(response.read())\n\n # Retrieve reward value from JSON\n sumReward0 = data[\"sumrewards\"][0][\"reward\"]\n sumReward1 = data[\"sumrewards\"][1][\"reward\"]\n sumReward2 = data[\"sumrewards\"][2][\"reward\"]\n\n # Clear last 3 char and add string\n sumReward0 = \"**01h: **\" + str(sumReward0)[:-3] + \"\\xb5 ETH\"\n sumReward1 = \"**12h: **\" + str(sumReward1)[:-3] + \"\\xb5 ETH\"\n sumReward2 = \"**24h: **\" + str(sumReward2)[:-3] + \"\\xb5 ETH\"\n\n # Retrieve worker value from JSON\n workerAmount = data[\"workers\"]\n\n # initialize/reset the counter\n i = 0\n\n # Loop throug every worker name\n for key in json.loads(json.dumps(workerAmount)):\n if i < 30: \n # Save the status of the worker\n workerStatus = (data[\"workers\"][key][\"offline\"])\n\n # Check the status emoji\n if workerStatus == False:\n workerEmoji = \":white_check_mark:\"\n else:\n workerEmoji = \":x:\"\n \n # Add the worker to the list\n workerStr = str(workerStr + (\"*\" + key + \"*: \" + workerEmoji + \"\\n\"))\n # Up one the counter\n i = i + 1\n\n # Retrieve hashrates from JSON\n hashrateCurrent = str(data[\"currentHashrate\"])\n hashrateAverage = str(data[\"hashrate\"])\n\n # Clear last chars\n hashrateCurrent = hashrateCurrent[:-4]\n hashrateCurrent = spacer(hashrateCurrent, \".\")\n\n hashrateAverage = hashrateAverage[:-4]\n hashrateAverage = spacer(hashrateAverage, \".\")\n\n # Retrieve amount of workers from JSON\n workerOffline = str(data[\"workersOffline\"])\n workerOnline = str(data[\"workersOnline\"])\n workerTotal = str(data[\"workersTotal\"])\n\n # Retrieve unpaid balance from JSON\n balanceUnpaid = str(data[\"stats\"][\"balance\"])[:-5]\n\n if int(balanceUnpaid) < 10:\n balanceUnpaid = \"0.000\" + balanceUnpaid\n elif int(balanceUnpaid) < 100:\n balanceUnpaid = \"0.00\" + balanceUnpaid\n elif int(balanceUnpaid) < 1000:\n balanceUnpaid = \"0.0\" + balanceUnpaid\n else:\n balanceUnpaid = \"0.\" + balanceUnpaid\n\n # Retrieve paid balance from JSON\n balancePaid = str(data[\"stats\"][\"paid\"])[:-6]\n\n if int(balancePaid) < 100:\n balancePaid = \"0.0\" + str(balancePaid)\n elif int(balancePaid) < 1000 :\n balancePaid = \"0.\" + str(balancePaid)\n else:\n balancePaid = str(balancePaid)[:-3] + \".\" + str(balancePaid)[(len(str(balancePaid))-3):]\n\n # Calculate progress amount\n progress = str(round((float(balanceUnpaid) / 0.05 * 100), 3))\n\n # Clear the sumReward of extra char's\n change = sumReward2[-9:-5]\n\n # Add chars in front\n if int(change) < 10:\n change = \"0.00000\" + change\n elif int(change) < 100:\n change = \"0.0000\" + change\n elif int(change) < 1000:\n change = \"0.000\" + change\n elif int(change) < 10000:\n change = \"0.00\" + change\n elif int(change) < 100000:\n change = \"0.0\" + change\n elif int(change) < 1000000:\n change = \"0.\" + change\n\n # Calculate the 24h progress in procent\n procentChange = str(round((float(change) / 0.05 * 100), 2))\n\n # Send the discord Webhook\n discordWebhook()\n\n time.sleep(delay)"
}
] | 4
|
naty55/telegram_engprep_bot
|
https://github.com/naty55/telegram_engprep_bot
|
7f985cc39d47ada0271d849627b6961d2365c956
|
9b77d7bb30686e27f181872f1f0ab8b160027757
|
4d84c8d2c13b571f468f5323dce6a97ac26370da
|
refs/heads/main
| 2023-08-16T00:29:08.064324
| 2021-10-18T13:59:08
| 2021-10-18T13:59:08
| 335,922,428
| 4
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.608095109462738,
"alphanum_fraction": 0.6087375283241272,
"avg_line_length": 34.78160858154297,
"blob_id": "9ce1fd22a559b17a77237309c133b90f9411e806",
"content_id": "104ab3bf45e0d00fb2eadfb7bb1d938bc341582a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3113,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 87,
"path": "/bot_decorators.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from functools import wraps\nfrom inspect import signature\nfrom telegram import ChatAction\nfrom apis import bot_logger, sessions, updater\nfrom Person import Person\n\n# Should be refactored to remove repetition\n\ndefault_not_known_message = \"You are not registered please use /register to register first\"\n\n\ndef basic_handler(handler, command=None, regex_filter=None):\n \"\"\"\n\n :param handler: handler type\n :param command: command string\n :param regex_filter: string\n :return: function\n \"\"\"\n def decorator(func):\n arguments_count = len(signature(func).parameters.keys())\n\n def handler_func(update, context):\n person = _start_session(update.effective_user.id, update.effective_user.name)\n context.bot.send_chat_action(chat_id=person.id, action=ChatAction.TYPING)\n if arguments_count == 2:\n func(person, context)\n else:\n func(person, update, context)\n\n handler_name = handler.__name__\n if handler_name == 'CommandHandler':\n updater.dispatcher.add_handler(handler(command, handler_func))\n elif handler_name == 'CallbackQueryHandler':\n updater.dispatcher.add_handler(handler(handler_func))\n elif handler_name == 'PollAnswerHandler':\n updater.dispatcher.add_handler(handler(handler_func, pass_user_data=True, pass_chat_data=True))\n elif handler_name == 'MessageHandler':\n updater.dispatcher.add_handler(handler(regex_filter, handler_func))\n return func\n return decorator\n\n\ndef registered_only(not_known_message=default_not_known_message, send_message=True):\n def decorator(func):\n arguments_count = len(signature(func).parameters.keys())\n if arguments_count == 2:\n\n @wraps(func)\n def wrapper(person, context):\n if person.is_known:\n func(person, context)\n elif send_message:\n try:\n context.bot.send_message(chat_id=person.id, text=not_known_message)\n except:\n print(f\"couldn't send message to {person.id} - {person.name}\")\n\n return wrapper\n\n @wraps(func)\n def wrapper(person, update, context):\n if person.is_known:\n func(person, update, context)\n elif send_message:\n try:\n context.bot.send_message(chat_id=person.id, text=not_known_message)\n except Exception as e:\n print(f\"couldn't send message to {person.id} - {person.name} Error: {e}\")\n return wrapper\n return decorator\n\n\ndef _start_session(_id, _name):\n \"\"\"\n check if session already exist; if not create new session\n :param _id: person's id\n :param _name: person's name\n :return: Person\n \"\"\"\n person = sessions.get(_id)\n if not person:\n person = Person(_id, _name)\n sessions[person.id] = person\n bot_logger.info(\"%s started session with the bot id: %s\", person.name, person.id)\n\n return person\n"
},
{
"alpha_fraction": 0.5635945796966553,
"alphanum_fraction": 0.5673270225524902,
"avg_line_length": 28.024999618530273,
"blob_id": "1d5775d3ca023fea5d1a541c2f909a8ef8b77d76",
"content_id": "ae138d5d1d0ddcb15226d2d0195f7f72ec249eaa",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3483,
"license_type": "no_license",
"max_line_length": 131,
"num_lines": 120,
"path": "/Person.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from apis import db_api\nimport time\n\n\nclass Person:\n \"\"\"\n Represent live session with the bot\n \"\"\"\n\n def __init__(self, telegram_chat_id, current_name):\n \"\"\"\n :param telegram_chat_id:\n :param current_name:\n \"\"\"\n self.id = telegram_chat_id\n self.current_name = current_name\n self.name = current_name\n self.is_known = False\n self.interval_to_get_age_is_open = False # This variable will determine if the bot will get text messages from this person\n self._initialize()\n\n def _initialize(self):\n \"\"\"\n Initialize person settings\n :return:\n \"\"\"\n person_data = db_api.get_person_data(self.id)\n if person_data:\n self.is_known = True\n self.name = person_data['name']\n self.gender = person_data['gender']\n self.init_quiz()\n self.init_competition()\n # time\n self.time = time.time()\n\n def init_quiz(self):\n \"\"\"\n Init quiz settings and state\n :return: None\n \"\"\"\n self.is_on_quiz = False\n self.left_questions = 0\n self.quiz_on_heb_words = False\n\n def init_competition(self):\n \"\"\"\n Init competition settings and state\n :return: None\n \"\"\"\n self.init_quiz()\n self.is_on_competition = False\n self.against = None # The opponent person\n\n def start_quiz(self, on_heb_words):\n \"\"\"\n start quiz - adjust settings for the quiz\n :param on_heb_words: boolean flag to determine if the quiz is on hebrew or english words\n :return:\n \"\"\"\n self.is_on_quiz = True\n self.left_questions = 15\n self.failed = 15\n self.quiz_on_heb_words = on_heb_words\n\n def start_competition(self, other):\n self.start_quiz(False)\n self.is_on_competition = True\n self.finished_competition = False\n self.against = other\n\n def save_person_data(self):\n \"\"\"\n Save person data in db\n :return:\n \"\"\"\n # This method might be edited in future in order to\n # also let users to update their details\n db_api.add_new_person(self.name, self.id, self.gender, self.age)\n self.is_known = True\n\n def read_person_data(self):\n \"\"\"\n Not Implemented yet; should deal with more complex data if needed in the future\n :return:\n \"\"\"\n pass\n\n def touch(self):\n \"\"\"\n Update last time this person was in touch with the bot\n (used to make sure the bot won't be overflooded by persons that are out of session)\n :return: None\n \"\"\"\n self.time = time.time()\n\n def is_busy(self):\n \"\"\"\n Check if person is on a quiz or competition\n :return: True if person is on quiz or competition; False otherwise\n \"\"\"\n return self.is_on_quiz or self.is_on_competition\n\n def get_score(self):\n \"\"\"\n Return the score of person in the quiz, only if the person didn't finish the quiz already\n :return:\n \"\"\"\n if self.is_on_quiz:\n return round(((15 - self.failed) / 15) * 100, 2)\n\n def finish_competition(self):\n if self.is_on_competition:\n self.finished_competition = True\n\n def close(self):\n db_api.update_last_seen(self.id, self.time)\n\n def __repr__(self):\n return f\"Person name: {self.name}, id: {self.id}, last seen: {self.time}\"\n"
},
{
"alpha_fraction": 0.6051955819129944,
"alphanum_fraction": 0.6087449193000793,
"avg_line_length": 39.243160247802734,
"blob_id": "055b1f39f7d8cc31beeb335e5381c3bc78c35071",
"content_id": "b6ab00b7f738320b040e7ecb42a87c74c035a716",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13248,
"license_type": "no_license",
"max_line_length": 137,
"num_lines": 329,
"path": "/bot_handlers.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from telegram import Update, Poll\nfrom telegram.error import BadRequest\nfrom telegram.ext import (CommandHandler,\n CallbackQueryHandler,\n PollAnswerHandler,\n MessageHandler,\n Filters,\n CallbackContext,\n )\nfrom telegram_objects import choose_lang_button_markup, next_button_markup, gender_markup, compete_markup_factory, rematch_markup_factory\nfrom apis import dict_api, bot_logger, sessions, message_logger, config\nfrom bot_functions import send_message, count_down\nfrom Person import Person\nfrom bot_decorators import basic_handler, registered_only\nfrom time import time\nfrom threading import Thread\n\n\n@basic_handler(CommandHandler, command='start')\ndef start_handler(person: Person, context: CallbackContext) -> None:\n \"\"\"\n Start Handler - Greet the user and instruct the user how to use the bot\n :param person: person\n :param context: callback context\n :return: None\n \"\"\"\n if not person.is_known:\n context.bot.send_message(chat_id=person.id,\n text=f\"Welcome {person.name}\\n\"\n \"Use /register command to register\\n\"\n \"Use /menu to get all options of this bot\")\n else:\n context.bot.send_message(chat_id=person.id,\n text=f\"Welcome back {person.name}\\n\"\n \"Use /menu to get all options \"\n \"of this bot\")\n\n\n@basic_handler(CommandHandler, command='bot_status')\ndef status_handler(person: Person, context: CallbackContext) -> None:\n \"\"\"\n Status Handler - send bot status to the user, this is an admins' only command\n :param person: person\n :param context: callbackContext\n :return: None\n \"\"\"\n if person.id in config['admins']:\n text = (\"Bot is Up\\n\\n\"\n \"Open sessions:\\n\"\n ) + \"\\n\".join((person.name for person in sessions.values()))\n context.bot.send_message(chat_id=person.id, text=text)\n\n\n@basic_handler(CommandHandler, command='menu')\ndef menu_handler(person: Person, context: CallbackContext) -> None:\n \"\"\"\n Menu Handler - send the menu to the user\n :param person: person\n :param context: callbackContext\n :return: None\n \"\"\"\n text = (\"/start start conversion with the bot\\n\"\n \"/menu get all options of this bot\\n\"\n \"/register register in order to use the bot\\n\"\n \"/quiz_me quiz yourself (15 questions)\\n\"\n \"/quiz_me_en quiz yourself on English words\\n\"\n \"/quiz_me_he quiz yourself on Hebrew words\\n\"\n \"/contact send message to the developer\\n\"\n \"/compete compete against friend\")\n context.bot.send_message(chat_id=person.id, text=text)\n\n\n@basic_handler(CommandHandler, command='register')\ndef register_handler(person: Person, context: CallbackContext) -> None:\n \"\"\"\n Register Handler - let the user start registration process\n :param person: person\n :param context: callbackContext\n :return: None\n \"\"\"\n if person.is_known:\n context.bot.send_message(text=\"you are already registered\", chat_id=person.id)\n else:\n context.bot.send_message(reply_markup=gender_markup, chat_id=person.id, text=\"What's your gender\")\n\n\n@basic_handler(CommandHandler, 'contact')\n@registered_only()\ndef contact_handler(person: Person, update: Update, context: CallbackContext) -> None:\n \"\"\"\n Contact Handler - let the user contact and send feedback to the developer\n :param person: perosn\n :param update: Update\n :param context: callbackContext\n :return: None\n \"\"\"\n message = update.message.text[8:].strip()\n if message:\n message_logger.info(\"message form %s id: %d : %s\", person.name, person.id, message)\n context.bot.send_message(chat_id=person.id, text=\"Thanks for your message\")\n else:\n context.bot.send_message(chat_id=person.id, text=\"Use /contact <your message>\")\n\n\n@basic_handler(CallbackQueryHandler)\ndef button_map_handler(person: Person, update: Update, context: CallbackContext) -> None:\n \"\"\"\n Button Handler - This handler handle every type of button pressing event\n :param person: person\n :param update: Update\n :param context: callbackContext\n :return:\n \"\"\"\n update.callback_query.answer()\n query = update.callback_query\n answer = query.data\n try:\n query.delete_message()\n except BadRequest:\n pass # Ignore case; message couldn't be deleted\n\n data = answer.split('_')\n req_type = data[0]\n if req_type == 'gender':\n person.gender = data[1]\n person.interval_to_get_age_is_open = True\n context.bot.send_message(text=\"How old are you ? \", chat_id=person.id)\n\n elif req_type == 'quiz':\n try:\n context.bot_data.pop(update.callback_query.message.poll.id)\n except KeyError:\n pass # Ignore\n finally:\n if answer.endswith('next'):\n quiz_person(person, context)\n else:\n finish_quiz(person, context)\n elif req_type == 'lang' and person.is_known:\n # Making sure person is known - not required but on the safe side\n on_heb_words = True if 'he' in data else False\n start_quiz(person, context, on_heb_words)\n\n elif req_type == 'compete' and person.is_known:\n _, accepted, offering_person_id, offer_time = data\n if time() - float(offer_time) > 620:\n print(\"Offer expired\")\n return\n if accepted == \"accept\" and not person.is_busy():\n person1 = sessions.get(int(offering_person_id))\n start_competition(person, person1, context)\n\n elif req_type == 'rematch':\n another_user_id = data[1]\n compete_person(person, context, another_user_id)\n\n\n@basic_handler(CommandHandler, command='quiz_me')\n@registered_only()\ndef quiz_me_handler(person: Person, context: CallbackContext):\n context.bot.send_message(chat_id=person.id, reply_markup=choose_lang_button_markup, text=\"Choose an option: \")\n\n\n@basic_handler(CommandHandler, command='quiz_me_en')\n@registered_only(send_message=False)\ndef quiz_me_en_handler(person: Person, context: CallbackContext):\n start_quiz(person, context, False)\n\n\n@basic_handler(CommandHandler, command='quiz_me_he')\n@registered_only(send_message=False)\ndef quiz_me_he_handler(person: Person, context: CallbackContext):\n start_quiz(person, context, True)\n\n\n@basic_handler(PollAnswerHandler)\n@registered_only(send_message=False)\ndef quiz_handler(person: Person, update: Update, context: CallbackContext):\n user_answer = update.poll_answer.option_ids[0]\n try:\n poll_correct_answer = context.bot_data.pop(update.poll_answer.poll_id)\n except KeyError:\n pass # Ignore case he poll is not registered\n else:\n if poll_correct_answer == user_answer:\n person.failed -= 1\n else:\n pass\n\n\n@basic_handler(MessageHandler, regex_filter=Filters.regex(\"^[1-9][0 -9]*$\"))\ndef age_handler(person: Person, update: Update, context: CallbackContext):\n if person.interval_to_get_age_is_open:\n person.age = int(update.message.text)\n person.interval_to_get_age_is_open = False # Close Interval the bot now will no longer get text messages\n person.save_person_data() # DONE\n context.bot.send_message(text=\"Registration Completed\\nUse /menu to see what this bot can do\",\n chat_id=person.id)\n\n bot_logger.info(\"%s registered id: %s\", person.name, person.id)\n\n\n@basic_handler(CommandHandler, 'compete')\n@registered_only()\ndef compete_handler(person: Person, update: Update, context: CallbackContext):\n try:\n another_person_id = update.message.text[8:].strip()\n except AttributeError:\n pass\n else:\n if another_person_id.isalnum():\n compete_person(person, context, another_person_id)\n\n\ndef compete_person(person: Person, context: CallbackContext, another_person_id):\n if person.is_busy() or str(person.id) == str(another_person_id):\n return\n try:\n another_person = sessions.get(int(another_person_id))\n if another_person:\n if another_person.is_busy():\n context.bot.send_message(chat_id=person.id,\n text=f\"The person {another_person_id} is busy right now \"\n \"Try in 10 minutes again\")\n\n context.bot.send_message(chat_id=another_person_id,\n reply_markup=compete_markup_factory(person.id, person.time),\n text=f\"You are invited to a competition with {person.name}\")\n except BadRequest:\n context.bot.send_message(chat_id=person.id,\n text=\"Couldn't find your friend,\"\n \"ask him to start conversation with the bot \"\n \"{@english_prep_bot}\"\n \"or check his id again\")\n else:\n context.bot.send_message(chat_id=person.id,\n text=f\"Invitation sent to {another_person_id}, \"\n \"and it will expire in 10 minutes from now\")\n\n\ndef quiz_person(person: Person, context: CallbackContext):\n open_period = None\n if person.is_on_competition:\n open_period = 8\n if person.left_questions > 0:\n question = dict_api.get_question(on_heb_words=person.quiz_on_heb_words)\n word, word_id, answer, options = question['word'], question['word_id'], question['answer'], question['options']\n q = f\"What is the translation of the word '{word}'\"\n poll_message = context.bot.send_poll(chat_id=person.id,\n question=q,\n options=options,\n type=Poll.QUIZ,\n correct_option_id=answer,\n is_anonymous=False,\n reply_markup=next_button_markup,\n open_period=open_period\n )\n context.bot_data[poll_message.poll.id] = poll_message.poll.correct_option_id\n person.left_questions -= 1\n else:\n finish_quiz(person, context)\n\n\ndef finish_quiz(person: Person, context: CallbackContext):\n if person.is_on_competition:\n return finish_competition(person, context)\n send_message(f\"Your score is {person.get_score()}\", context.bot, person, animate=True)\n bot_logger.info(\"%s finished quiz with score %s id: %s\", person.name, person.get_score(), person.id)\n person.init_quiz()\n\n\ndef start_quiz(person: Person, context: CallbackContext, on_heb=False, mode='quiz', against=None):\n \"\"\"\n This function assumes that person is registered - therefore this method should be called from\n handlers decorated with @registered_only\n :param against:\n :param mode:\n :param person:\n :param context:\n :param on_heb:\n :return:\n \"\"\"\n if against is None and mode == 'compete':\n raise Exception(\"got 'compete' mode but didn't got the opponent person\")\n\n if person.is_busy():\n return\n if mode == 'quiz':\n person.start_quiz(on_heb)\n bot_logger.info(\"%s started quiz id: %s\", person.name, person.id)\n elif mode == 'compete':\n person.start_competition(against)\n\n quiz_person(person, context)\n\n\ndef start_competition(person1, person2, context):\n t1 = Thread(target=count_down, args=(person1, context.bot, \"Starting in\"))\n t2 = Thread(target=count_down, args=(person2, context.bot, \"Starting in\"))\n t1.start()\n t2.start()\n t1.join()\n t2.join()\n start_quiz(person1, context, mode='compete', against=person2)\n start_quiz(person2, context, mode='compete', against=person1)\n\n\ndef finish_competition(person: Person, context: CallbackContext):\n if not person.against.finished_competition:\n send_message(\"Waiting for opponent to finish...\", context.bot, person, animate=True)\n person.finish_competition()\n else:\n score = person.get_score()\n score1 = person.against.get_score()\n person_message = \"Congrats, You won 🥳\"\n person1_message = \"Maybe next time, You lost 😔\"\n if score1 > score:\n person1_message, person_message = person_message, person1_message\n elif score == score1:\n person1_message = person_message = \"it's a draw\"\n\n context.bot.send_message(chat_id=person.id,\n text=person_message,\n reply_markup=rematch_markup_factory(person.against.id))\n context.bot.send_message(chat_id=person.against.id,\n text=person1_message,\n reply_markup=rematch_markup_factory(person.id))\n person.against.init_competition()\n person.init_competition()\n\n\n"
},
{
"alpha_fraction": 0.7200000286102295,
"alphanum_fraction": 0.7239999771118164,
"avg_line_length": 32.266666412353516,
"blob_id": "6200b774fd5a25168d809a5208bc1e9c8280d411",
"content_id": "f85297cad552a7930a88db0da588a4b0958e85e2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 500,
"license_type": "no_license",
"max_line_length": 154,
"num_lines": 15,
"path": "/main.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "import sys\nfrom threading import Thread\nfrom apis import updater\nfrom util import clean_old_sessions\nfrom bot_functions import notify_all_users\nimport bot_handlers # This is not importing for nothing, if you don't import the handlers won't be registered in the dispatcher; should be fixed in future\n\n\nif __name__ == '__main__':\n if len(sys.argv) > 1:\n notify_all_users(sys.argv[1], updater.bot)\n\n Thread(target=clean_old_sessions).start()\n updater.start_polling()\n updater.idle()\n\n"
},
{
"alpha_fraction": 0.6077170372009277,
"alphanum_fraction": 0.6162915229797363,
"avg_line_length": 31.172412872314453,
"blob_id": "f248a04187a04b3b925437f552db9cd77d6ac6df",
"content_id": "092a60e7fe68a46d68dae5828ed5f2b9a287e486",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 933,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 29,
"path": "/util.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from time import sleep, time\nfrom apis import sessions, bot_logger\nimport json\nimport urllib.request\nimport os\nimport random\n\n\ndef clean_old_sessions():\n interval = 30 * 60 # 30 minutes\n while True:\n sleep(interval)\n for i in list(sessions.keys()):\n if time() - sessions[i].time > interval:\n person = sessions.pop(i)\n person.close()\n bot_logger.info(\"%s session expired id: %s\", person.name, person.id)\n\n\ndef get_ram_mem(_id=None):\n os.environ['no_proxy'] = \"https://rickandmortyapi.com\"\n base_url = \"https://rickandmortyapi.com/api/character/\"\n count = json.load(urllib.request.urlopen(base_url))['info']['count']\n if not _id:\n _id = random.randint(0, count + 1)\n res = json.load(urllib.request.urlopen(base_url + \"/\" + str(_id)))\n image = urllib.request.urlopen(res['image']).read()\n name = res['name']\n return name, image\n"
},
{
"alpha_fraction": 0.6385542154312134,
"alphanum_fraction": 0.6385542154312134,
"avg_line_length": 24.538461685180664,
"blob_id": "deb7c86365a80814df116f143c29e193049a8d83",
"content_id": "eb4969ff726b88d41b834cbd561adb7a131f0f06",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 332,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 13,
"path": "/SessionsDict.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from collections import defaultdict\n\n\nclass SessionsDict(defaultdict):\n \"\"\"\n dictionary for sessions\n every time a person is being pulled out it will update its time\n \"\"\"\n def get(self, key):\n person = super(SessionsDict, self).get(int(key))\n if person:\n person.touch()\n return person\n"
},
{
"alpha_fraction": 0.5534173846244812,
"alphanum_fraction": 0.5613802075386047,
"avg_line_length": 31.717391967773438,
"blob_id": "a5437b891046a2a606eb3307279c3769d073add2",
"content_id": "fbd81fb65d4982dee478ad634c39d1fdc2c7717a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1507,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 46,
"path": "/DictAPI.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "import csv\nimport random\n\n\nclass DictAPI:\n \"\"\"\n DictApi lets you control the dictionary (csv file) with more ease\n \"\"\"\n\n def __init__(self, dictfile):\n self.csvfile = open(dictfile, 'r', encoding='utf-8', newline='')\n self.reader = csv.reader(self.csvfile, delimiter=',')\n self.rows = list(self.reader)\n\n def get_words(self, start_index, amount):\n return self.rows[start_index:start_index + amount]\n\n def close(self):\n self.csvfile.close()\n\n def get_question(self, range_=(0, -1), number_of_options=4, on_heb_words=False):\n a = range_[0]\n b = range_[1]\n if b < 0:\n b = len(self.rows) + b\n word_lang_idx = 1\n answer_lang_idx = 2\n if on_heb_words:\n word_lang_idx, answer_lang_idx = answer_lang_idx, word_lang_idx\n answer_index = random.randint(a, b)\n word_id = self.rows[answer_index][0]\n word = self.rows[answer_index][word_lang_idx]\n answer = self.rows[answer_index][answer_lang_idx]\n\n options = [answer]\n while len(options) < number_of_options:\n index = random.randint(0, len(self.rows) - 1)\n option = self.rows[index][answer_lang_idx]\n if option not in options:\n options.append(option)\n random.shuffle(options)\n answer = options.index(answer)\n return {'word': word,\n 'word_id': word_id,\n 'answer': answer,\n 'options': options}\n\n\n"
},
{
"alpha_fraction": 0.7555031180381775,
"alphanum_fraction": 0.7555031180381775,
"avg_line_length": 27.886363983154297,
"blob_id": "1a19a18ded29a3564e45d71c60bc3ef73f734af1",
"content_id": "7a20f01530349871d6227c891b153fde6f513431",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1272,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 44,
"path": "/apis.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from DatabaseAPI import DataBase\nfrom DictAPI import DictAPI\nfrom SessionsDict import SessionsDict\nfrom telegram.ext import Updater\nimport logging\nimport json\n\n######\n# This file is for any object that should be\n# accessible from all parts of the program.\n# Here will be the factory for all of those objects\n######\n\n# API's\ndb_api = DataBase('test.db')\ndict_api = DictAPI('new_dict.csv')\n\n# Logging shit goes here\n# --- This is not well written - to be fixed in the future ---\nformat_string = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'\nformatter = logging.Formatter(format_string)\nlogging.basicConfig(format=format_string, level=logging.INFO)\nbot_logger = logging.getLogger('bot_logger')\nbot_file_handler = logging.FileHandler('bot_log.log')\nbot_file_handler.setFormatter(formatter)\nbot_logger.addHandler(bot_file_handler)\n\n# Sessions object\nsessions = SessionsDict(lambda: False)\n\n# Message Logger\nmessage_logger = logging.getLogger(\"MessageLogger\")\nmessage_logger.propagate = False\nmessage_file_handler = logging.FileHandler('messages.log')\nmessage_file_handler.setFormatter(formatter)\nmessage_logger.addHandler(message_file_handler)\n\n\n# Configuration\nwith open('config.json', 'r') as c:\n config = json.load(c)\n\n\nupdater = Updater(token=config['token'])\n\n"
},
{
"alpha_fraction": 0.7169058918952942,
"alphanum_fraction": 0.7169058918952942,
"avg_line_length": 51.25,
"blob_id": "51ce8cb02beaa3f77a1902ebe129579597474e08",
"content_id": "10d106244cd5134896be0df7b7d97adc6e7ae731",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1254,
"license_type": "no_license",
"max_line_length": 106,
"num_lines": 24,
"path": "/telegram_objects.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from telegram import InlineKeyboardButton, InlineKeyboardMarkup\n\ngender_kb = ([InlineKeyboardButton('Male', callback_data='gender_male')],\n [InlineKeyboardButton('Female', callback_data='gender_female')],\n [InlineKeyboardButton('Other', callback_data='gender_other')])\nnext_kb = ((InlineKeyboardButton('Finish Quiz', callback_data='quiz_finish'),\n InlineKeyboardButton('Next', callback_data='quiz_next')),)\nlang_kb = ((InlineKeyboardButton('Quiz on English words', callback_data='lang_en'),),\n (InlineKeyboardButton('Quiz on Hebrew words', callback_data='lang_he'),))\n\nnext_button_markup = InlineKeyboardMarkup(next_kb)\ngender_markup = InlineKeyboardMarkup(gender_kb)\nchoose_lang_button_markup = InlineKeyboardMarkup(lang_kb)\n\n\ndef compete_markup_factory(person_id, time):\n compete_kb = ((InlineKeyboardButton('Decline', callback_data=f'compete_decline_{person_id}_{time}'),),\n (InlineKeyboardButton('Accept', callback_data=f'compete_accept_{person_id}_{time}'),))\n return InlineKeyboardMarkup(compete_kb)\n\n\ndef rematch_markup_factory(person_id):\n offer_kb = ((InlineKeyboardButton('Offer rematch', callback_data=f'rematch_{person_id}'),),)\n return InlineKeyboardMarkup(offer_kb)\n"
},
{
"alpha_fraction": 0.7599999904632568,
"alphanum_fraction": 0.7599999904632568,
"avg_line_length": 27.285715103149414,
"blob_id": "132a04a3012f73fdfbf5cfae4183a995f9deb3a4",
"content_id": "c2f0733f3a0b1bf99787a69536081f2fcb1d269a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 200,
"license_type": "no_license",
"max_line_length": 54,
"num_lines": 7,
"path": "/start_bot.sh",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "#!bin/bash\necho \"[INFO] change directory to telegram_engprep_bot\"\ncd telegram_engprep_bot\necho \"[INFO] pulling latest updates from github.com\"\ngit pull\necho \"[INFO] starting the bot\"\npython main.py\n\n\n"
},
{
"alpha_fraction": 0.5848416090011597,
"alphanum_fraction": 0.5961538553237915,
"avg_line_length": 30.571428298950195,
"blob_id": "bcd54f82f8899e8b7f7ffd31a110749856044a8a",
"content_id": "a22c09cfbbdaf9f786c83bb8fc0db60f40d72643",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1768,
"license_type": "no_license",
"max_line_length": 112,
"num_lines": 56,
"path": "/bot_functions.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "from time import sleep\nfrom apis import db_api\nfrom telegram import Bot, Message\nfrom Person import Person\nfrom util import get_ram_mem\n\n\ndef notify_all_users(message: str, bot: Bot) -> None:\n \"\"\"\n Send Notification to all registered users;\n There is a telegram API limitation that only allow sending 30 messages\n in a minute so the function will take care of that too.\n :param message: message to send\n :param bot: The bot\n :return: None\n \"\"\"\n\n name, image = get_ram_mem()\n message += \"\\n\\n\\n\" + \"Character-name: \" + name\n\n counter = 0\n for _id in db_api.get_all_persons_id():\n try:\n counter += 1\n bot.send_photo(_id, photo=image, caption=message)\n if counter >= 28:\n sleep(60)\n except Exception as e:\n print(f\"Couldn't send message for user {db_api.get_person_data(_id).get('name')}\")\n print(e)\n\n\ndef send_message(text: str, bot: Bot, person: Person, interval: float = 0.01, animate: bool = False) -> Message:\n text = text.strip()\n if animate:\n str_to_send = text[0]\n message = bot.send_message(chat_id=person.id, text=str_to_send)\n for letter in text[1:]:\n str_to_send += letter\n if letter.isspace():\n continue\n message.edit_text(str_to_send)\n sleep(interval)\n return message\n\n return bot.send_message(chat_id=person, text=text)\n\n\ndef count_down(person: Person, bot: Bot, prefix: str = \"\", interval: float = 0.5) -> None:\n prefix += \" \"\n message = bot.send_message(chat_id=person.id, text=prefix + \"10\")\n for i in range(9, -1, -1):\n sleep(interval)\n text = prefix + str(i)\n message.edit_text(text)\n message.delete()\n"
},
{
"alpha_fraction": 0.6279069781303406,
"alphanum_fraction": 0.6372092962265015,
"avg_line_length": 29.714284896850586,
"blob_id": "a8646e960a1121de49be2aa1f7759722fa619e67",
"content_id": "125a8fa446ce20f4b7229d5121c709309deb12a2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 215,
"license_type": "no_license",
"max_line_length": 69,
"num_lines": 7,
"path": "/scripts/inspect_db.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "import pandas as pd\nimport sqlite3\n\nconn = sqlite3.connect(\"../test.db\")\nwhile (table_name := input(\"Select table name to show\\n>>>\")) != 'q':\n df = pd.read_sql(f'select * from {table_name}', conn)\n print(df)\n"
},
{
"alpha_fraction": 0.5201308727264404,
"alphanum_fraction": 0.5251102447509766,
"avg_line_length": 36.19047546386719,
"blob_id": "66fbf52ba044448880c0295e083d44fb188ed973",
"content_id": "0e22cdba26667ed4870ccf207087a919b6978b52",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7029,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 189,
"path": "/DatabaseAPI.py",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "import sqlite3\nfrom sqlite3 import Error\nfrom time import time\nimport logging\n\nlogging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO)\ndb_logger = logging.getLogger('db_logger')\n\n\nclass DataBase:\n \"\"\"\n API to represent the Database.\n \"\"\"\n\n def __init__(self, filename):\n \"\"\"\n Initialize the connection to DB\n :param: database filename\n \"\"\"\n self.connection = None\n self.create_connection(filename)\n self.initialize_tables()\n\n def create_connection(self, filename):\n \"\"\"\n Connect to DB\n :param filename:\n :return: None\n \"\"\"\n conn = None\n try:\n conn = sqlite3.connect(filename, check_same_thread=False) # for now\n\n except Error as e:\n db_logger.error(\"Couldn't Connect to DB\")\n else:\n db_logger.info(\"Connection to DB successful\")\n self.connection = conn\n\n def initialize_tables(self):\n \"\"\"\n Initialize tables in db.\n :return: None\n \"\"\"\n\n persons_table = (\"CREATE TABLE IF NOT EXISTS persons (\"\n \"id INTEGER PRIMARY KEY AUTOINCREMENT,\"\n \"name TEXT NOT NULL,\"\n \"telegram_id INTEGER NOT NULL,\"\n \"age INTEGER NOT NULL, \"\n \"gender INTEGER NOT NULL,\"\n \"last_seen STRING ,\"\n \"signup_date STRING);\")\n\n scores_table = (\"CREATE TABLE IF NOT EXISTS scores (\"\n \"word_id INTEGER NOT NULL,\"\n \"person_id INTEGER NOT NULL,\"\n \"duration INTEGER NOT NULL,\"\n \"failures INTEGER NOT NULL, \"\n \"total INTEGER NOT NULL, \"\n \"FOREIGN KEY (person_id) REFERENCES persons(id) );\")\n\n success = self.exec_query(persons_table, ()) + self.exec_query(scores_table, ())\n if success == 0:\n db_logger.info('Tables are all set')\n\n def exec_query(self, query: str, params: tuple) -> int:\n \"\"\"\n Generic function to execute read query on db\n :param params: params\n :param query: query to exe\n\n cute\n :return: 0 for success; 1 otherwise\n \"\"\"\n cursor = self.connection.cursor()\n try:\n cursor.execute(query, params)\n self.connection.commit()\n return 0\n except Error as e:\n db_logger.error(f'The error {e} occurred')\n print(e.with_traceback())\n return 1\n\n def exec_read_query(self, query: str, params: tuple):\n \"\"\"\n Generic function to execute read query on db\n :param query: query to execute\n :param params: tuple of params\n :return: list with the results; or empty list if there was no result\n \"\"\"\n cursor = self.connection.cursor()\n try:\n cursor.execute(query, params)\n return cursor.fetchall()\n except Error as e:\n db_logger.error(f'The error {e} occurred')\n return []\n\n def check_for_person(self, conditions: dict) -> bool:\n \"\"\"\n Check for person with given set of conditions\n :param conditions: dictionary\n :raise Exception if conditions are empty\n :return: True if person with give conditions exist; False otherwise\n \"\"\"\n if not len(conditions.items()):\n raise Exception(\"No conditions to work with\")\n keys = conditions.keys()\n conditions_str = \" AND \".join([f\"{str(key)}=?\" for key in keys])\n query = f\"SELECT * FROM persons WHERE ({conditions_str})\"\n result = self.exec_read_query(query, [conditions.get(key) for key in keys])\n return len(result) != 0\n\n def add_new_person(self, name: str, telegram_id: int, gender: str, age: int):\n \"\"\"\n Add new person to Database.\n set the new person's dict_index to 0\n :param name: name of the person\n :param telegram_id: telegram id of the telegram account\n :param gender: gender of person\n :param age: age of person\n :return: None\n \"\"\"\n if self.check_for_person({'telegram_id': telegram_id}):\n return\n query = f\"\"\"INSERT INTO persons\n (name, telegram_id, gender, age, signup_date)\n VALUES\n (?, ?, ?, ?, ?); \n \"\"\"\n result = self.exec_query(query, (name, telegram_id, gender, age, time()))\n if result == 0:\n db_logger.info(f\"new person updated name : {name}, telegram_id : {telegram_id}\")\n\n def update_last_seen(self, person_id, last_seen_time):\n query = (\"UPDATE persons \" \n \"SET last_seen=? \" \n \"WHERE telegram_id=?\")\n self.exec_query(query, (str(last_seen_time), person_id))\n\n def update_score(self, person_id, word_id, duration, failure):\n if not self.check_for_person({'id': person_id}):\n raise Exception(f\"No person with id={person_id}\")\n check_query = f\"SELECT * FROM scores WHERE (person_id=? AND word_id =?)\"\n result = self.exec_read_query(check_query, (person_id, word_id))\n params = (word_id, person_id, duration, 1 if failure else 0, 1)\n if result:\n failures = result[0][3] + (1 if failure else 0)\n total = result[0][4] + 1\n duration = (result[0][2] * (total - 1) + duration) / total\n query = \"\"\"UPDATE scores\n SET failures=?, total=?, duration=?\n WHERE (word_id =? AND person_id = ?)\"\"\"\n params = (failures, total, duration, word_id, person_id)\n else:\n total = 1\n query = (\"INSERT INTO scores\"\n \"(word_id, person_id, duration, failures, total)\"\n \"VALUES \"\n \"(?, ?, ?, ?, ?);\")\n success = self.exec_query(query, params)\n if success == 0:\n db_logger.info(f\"[INFO] score successfully updated person_id: {person_id}, word_id : {word_id}, \"\n f\"duration : {duration}, failure : {failure}, total : {total}\")\n\n def get_person_data(self, telegram_id):\n if self.check_for_person({'telegram_id': telegram_id}):\n query = f\"SELECT * FROM persons WHERE telegram_id=?\"\n row = self.exec_read_query(query, (telegram_id,))[0]\n data = {\n 'id': row[0],\n 'name': row[1],\n 'telegram_id': row[2],\n 'age': row[3],\n 'gender': row[4],\n 'last_seen': row[5],\n 'sing_up': row[6]\n }\n return data\n else:\n return None\n\n def get_all_persons_id(self):\n return [_[0] for _ in self.exec_read_query(f\"SELECT telegram_id FROM persons\", ())]\n\n def close(self):\n self.connection.close()\n"
},
{
"alpha_fraction": 0.7178899049758911,
"alphanum_fraction": 0.7262997031211853,
"avg_line_length": 53.5,
"blob_id": "129fa5abe7e879393d524796d671773d93b557fb",
"content_id": "6766ddfe9d21fd3bab452b29138360615c5bde33",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1308,
"license_type": "no_license",
"max_line_length": 174,
"num_lines": 24,
"path": "/README.md",
"repo_name": "naty55/telegram_engprep_bot",
"src_encoding": "UTF-8",
"text": "# telegram_engprep_bot\nTelegram Bot for learning English\n\n# What can this bot do ?\nAre you preparing for an exam in English and looking for a way to test and enrich your vocabulary ? \nThis bot was developed with you in mind! \nThis Bot let you:\n1. Quiz yourself on English or Hebrew words, With simple command `/quiz_me` you get 15 questions on English or Hebrew words (you can choose) .\n2. Compete against other users (for now you will need their telegram id)\n3. Get your scores and word-list that you need to improve [In-The-Future]\n4. Give feedback to the developer via `/contact` command \n5. Enjoy\n\n# I want to use the bot, how ?\nGreat, hopefully you already have your telegram account (if not go to https://telegram.org/ and create one). \nYou have 2 options:\n1. The easier one, go to https://t.me/english_prep_bot, command `/start` and from there follow the bot's instructions, but notice that the bot might be down from time to time\n2. a. Clone the project to your PC \n b. Get a token from FatherBot (Here you can see how https://core.telegram.org/bots#3-how-do-i-create-a-bot) \n c. Create `config.json` file and put `{'token': <your-token>, 'admins' : [] }` \n d. you are all set run the program and go enjoy the bot you have just created. \n\n# Note \nThis bot is under development\n"
}
] | 14
|
OregonCS325-2015/Project4
|
https://github.com/OregonCS325-2015/Project4
|
b34078c017f9e6dae241ccfa52d5b8d144242f4c
|
169e8c288da1a7791adb4743099952ed1c7e8aca
|
578e2ca97c41970338f7349425cbc9cf66b86efa
|
refs/heads/master
| 2016-08-12T15:32:02.220451
| 2015-12-06T05:36:25
| 2015-12-06T05:36:25
| 47,242,031
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.49348822236061096,
"alphanum_fraction": 0.5131995677947998,
"avg_line_length": 27.52409553527832,
"blob_id": "4e62e847dc9afe4d639ed3c242bf1d31272673bd",
"content_id": "3f2666310098680d2bb9555117d4dce8b1a85e72",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14205,
"license_type": "no_license",
"max_line_length": 141,
"num_lines": 498,
"path": "/tsp-rob.py",
"repo_name": "OregonCS325-2015/Project4",
"src_encoding": "UTF-8",
"text": "__author__ = 'Martha, Michael, and Robert'\n\nimport math\nimport heapq\nimport sys\nimport time\nimport random\n\n\n# Reads the files\n# @param a text file of space spearated numbers including an index\n# @return three arrays one of x coordinates one of y, and one multi\n# 0(n)\ndef read_file(name):\n x = [] # the values\n y = []\n z = []\n f = open(name, 'r')\n\n for i in f:\n index, a, b = i.split()\n #x.append(int(a))\n #y.append(int(b))\n z.append((int(a), int(b), int(index)))\n\n return z\n\n\n# takes two lists one of x coordinates one of y, calculates distances between each point\n# 0(n^2)\n# @param a text file of space spearated numbers including an index\n# @return one 2d array of distances\ndef calc_distance_matrix(x, y):\n matrix = [[0 for m in range(len(x))] for n in range(len(y))]\n\n for i in range(0, len(x)):\n\n for j in range(0, len(y)):\n # abs value because we don't want negative distances\n xdis = abs(x[i] - x[j])\n ydis = abs(y[i] - y[j])\n\n # dat hypotenuse - 3 figures\n dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n matrix[i][j] = dis\n\n return matrix\n\n\n# takes two coordinates, calculates distances between the point\n# C\n# @param crd = a coordinate list\n# @param i or j = a coordinate index i.e. [(438, 75), (381, 53)] (438, 75) = 0\n# @return one distance to three decimals\ndef calc_distance_point(crd, i, j):\n check1 = crd[i][0]\n check2 = crd[j][0]\n # abs value because we don't want negative distances\n xdis = abs(crd[i][0] - crd[j][0])\n ydis = abs(crd[i][1] - crd[j][1])\n\n # dat hypotenuse - 3 figures\n dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n return dis\n\n\n# takes two coordinates, calculates distances between the point\n# C\n# @param p1 p2 two points = with an x and y coordt\n# @return one distance to three decimals\ndef calc_distance(p1, p2):\n # \"\"\"\n # :rtype : float\n # \"\"\"\n # abs value because we don't want negative distances\n xdis = abs(p1[0] - p2[0])\n ydis = abs(p1[1] - p2[1])\n\n # dat hypotenuse - 3 figures\n #dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n dis = int( math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2)))\n\n return dis\n\n\n# sorts a tuple\n# @param crd = a coordinate list\n# @param a tuple\n# @param v position 0 or 1 in the tuple (x or y)\n# @return sorted tuple\ndef sort_coordinates(a, v):\n # set to look at opposite position for swapping\n # depending if we're sorting x's or y's\n if v == 0:\n l = 1\n else:\n l = 0\n\n a = sorted(a, key=lambda x: x[v])\n\n # bubble sorts the small sections where the sorted coordinate is the same\n for i in range(0, len(a)):\n # looks over the list swapping if the ys are larger\n for i in range(1, len(a)):\n if (a[i - 1][v] == a[i][v]) & (a[i - 1][l] > a[i][l]):\n # swap\n f, g = a[i - 1], a[i]\n a[i - 1], a[i] = g, f\n\n return a\n\n# #path[len(path)-1], points\n# def calc_minDistance(list, startP):\n# minDist = 100000\n# pointIndex = 0 # initilaize\n#\n# if startP > 0:\n#\n# for i in range(0, startP - 1):\n# prevMinDist = minDist\n# # calculate the minimum distance\n# minDist = min(minDist, calc_distance(list[startP], list[i + 1]))\n# if minDist < prevMinDist:\n# pointIndex = i + 1\n#\n# # check from stp to end\n# for i in range(startP, len(list) - startP - 1):\n# prevMinDist = minDist\n# minDist = min(minDist, calc_distance(list[startP], list[i + 1]))\n# if minDist <= prevMinDist:\n# pointIndex = i + 1\n#\n# savedPoint = list[pointIndex]\n# list.pop(pointIndex)\n#\n# return savedPoint\n\n#path[len(path)-1], points\ndef calc_minDistance(startP, L):\n minDist = 100000\n pointIndex = 0 # initilaize\n\n\n # check from stp to end\n for i in range(0, len(L)):\n prevMinDist = minDist\n minDist = min(minDist, calc_distance(startP, L[i]))\n if minDist < prevMinDist:\n pointIndex = i\n savedPoint = L[pointIndex]\n #L.pop(pointIndex)\n\n return savedPoint\n\n\n\n#\n# def genStartPoint(sortedList):\n#\n# pointofreturn = ()\n# smallD = 99999999\n# for i in range(0, 10):\n#\n# start_index = random.randrange (0, len(sortedList))\n# prevmin = smallD\n# mini, point = calc_minDistance(sortedList, start_index)\n# smallD = min (smallD, mini)\n# #store this point!\n# if smallD < prevmin:\n# pointofreturn = [mini, point, start_index]\n#\n#\n# return pointofreturn\n\n#print(px)\n#print(py)\n\n# ok here goes\n# This path veriable is absolutly necessary\npath = []\n# i dont want it to be a global but it is for now\n# The function, was built in a very liner fashion, thus there is repeated code but in the interest of time amd the complication nature of the\n# function, I'm not going to change it to make use of repeated structures at this point.\n# @ required is a sorted list\n\n\ndef spiralTSP(px, py):\n tolerance = 100\n ###LEFT CYCLE\n if(len(px) != 0 and px != ''):\n #path.append(px[0]) #add to path\n #py.remove(px[0]) #remove same from y\n #px.pop(0) #remove it\n\n\n #reset\n hix = px[len(px)-1]\n hiy = py[len(py)-1]\n lowx = px[0]\n lowy = py[0]\n\n #setdump Left\n temp = []\n # add the end of path\n #temp.append(path[len(path)-1])\n\n for i in range(0,len(px)):\n # if (px[i][0] >= py[len(py)-1][0]+tolerance):\n # break\n # for j in range(0,i):\n # temp.append(px[j])\n\n if ((px[i][0] <= py[len(py)-1][0]+tolerance) & (px[i][1] >= px[0][1])-tolerance):\n temp.append(px[i])\n # #px.remove(px[i])\n\n #ELSE sort the temp on the y\n temp = sort_coordinates(temp, 0)\n\n #dump it in the th path in order of increasing y\n for i in range(0,len(temp)):\n path.append(temp[i])\n px.pop(0)\n py.remove(temp[i])\n\n #TOPCYCLE\n #now add hiy\n if(len(px) != 0 and px != ''):\n # path.append(py[len(py)-1]) #add to path\n # px.remove(py[len(py)-1])\n # py.pop(len(py)-1) #remove from end of y\n\n\n #setdump Top\n temp = []\n # add the end of path\n #temp.append(path[len(path)-1])\n #path.pop(len(path)-1)\n\n # for i in range(0,len(px)):\n # if (px[i][1] >= px[len(py)-1][1]-tolerance):\n # break\n # for j in range(0,i):\n # temp.append(py[j])\n for i in range(0,len(px)):\n if (px[i][0] <= px[len(px)-1][0])& (px[i][1] >= px[len(px)-1][1]-tolerance):\n temp.append(px[i])\n\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 0)\n #path.append(temp[0])\n #dump it in the th path in order of increasing x\n for i in range(1,len(temp)):\n path.append(temp[i])\n px.remove(temp[i])\n py.remove(temp[i])\n\n ###RIGHT CYCLE\n if(len(px) != 0 and px != ''):\n # path.append(px[len(px)-1]) #add to path\n # py.remove(px[len(px)-1]) #remove\n # px.pop(len(px)-1) #remove from end of x\n #add end of path back on incase we shuffel\n temp = []\n # temp.append(path[len(path)-1])\n # path.pop(len(path)-1)\n\n for i in range(0,len(px)):\n if (px[i][0] >= py[0][0]-tolerance):\n break\n for j in range(0,i):\n temp.append(px[j])\n # #setdump RIGHT\n # temp = []\n # for i in range(0,len(px)):\n # if (px[i][0] >= py[0][0]) & (px[i][1] <= px[len(px)-1][1] ):\n # temp.append(px[i])\n # py.remove(px[i])\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 0)\n #path.append(temp[0])\n #dump it in the th path in order of decreasing y\n for i in range(len(temp)-1, -1, -1):\n path.append(temp[i])\n px.remove(temp[i])\n py.remove(temp[i])\n\n\n\n\n\n # ##adding the low y point\n # if(len(px) != 0 and px != ''):\n # prevlow = py[0]\n # path.append(py[0]) #add to path\n # px.remove(py[0]) #remove\n # py.pop(0) #remove from end of x\n\n # #RightInside----------------------------------------------------\n # if(len(px) != 0 and px != ''):\n # #setdump RIGHT\n # temp = []\n # for i in range(0,len(px)):\n # if (px[i][0] >= py[0][0]) & (px[i][1] <= py[len(px)-1][1] ):\n # temp.append(px[i])\n # px.remove(px[i])\n #\n # #ELSE sort the temp on the x\n # temp = sort_coordinates(temp, 1)\n #\n # #dump it in the th path in order of inccreasing y\n # for i in range(0, len(temp)-1):\n # path.append(temp[i])\n # py.remove(temp[i])\n #\n # prevx = px[len(px)-1] #needed for next point\n # path.append(px[len(px)-1]) #add next high x to path\n # py.remove(px[len(px)-1]) #remove\n # px.pop(len(px)-1) #remove from end of x\n #\n # #-----------------------------------------------------------------\n #\n # #TOPInside----------------------------------------------------\n # if(len(px) != 0 and px != ''):\n # #setdump RIGHT\n # temp = []\n # for i in range(0,len(px)):\n # if (px[i][0] >= py[len(py)-1][0]) & (px[i][1] >= prevx[1] ):\n # temp.append(px[i])\n # px.remove(px[i])\n #\n # #ELSE sort the temp on the x\n # temp = sort_coordinates(temp, 0)\n #\n # #dump it in the th path in order of inccreasing y\n # for i in range(len(temp)-1, -1, -1):\n # path.append(temp[i])\n # py.remove(temp[i])\n #\n # path.append(py[len(px)-1]) #add next high y to path\n # px.remove(py[len(px)-1]) #remove from x\n # py.pop(len(px)-1) #remove from end of y\n #\n # #-----------------------------------------------------------------\n #\n # #LEFTInside----------------------------------------------------\n # if(len(px) != 0 and px != ''):\n # #setdump RIGHT\n # temp = []\n # for i in range(0,len(px)):\n # if (px[i][0] >= py[len(py)-1][0]) & (px[i][1] >= prevx[1] ):\n # temp.append(px[i])\n # px.remove(px[i])\n #\n # #ELSE sort the temp on the x\n # temp = sort_coordinates(temp, 0)\n #\n # #dump it in the th path in order of inccreasing y\n # for i in range(len(temp)-1, -1, -1):\n # path.append(temp[i])\n # py.remove(temp[i])\n #\n # path.append(py[len(px)-1]) #add next high y to path\n # px.remove(py[len(px)-1]) #remove from x\n # py.pop(len(px)-1) #remove from end of y\n\n #-----------------------------------------------------------------\n\n #BOTTOM CYCLE\n #now add py[0]\n if(len(px) != 0 and px != ''):\n # path.append(py[0]) #add to path\n # px.remove(py[0]) #remove\n # py.pop(0) #remove from end of x\n\n #setdump Bottom\n temp = []\n for i in range(0,len(px)):\n if (px[i][0] <= py[0][0] ) & (px[i][1] <= px[0][1] ):\n temp.append(px[i])\n\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 0)\n\n #dump it in the th path in order of decreasing x\n for i in range(len(temp)-1, -1, -1):\n path.append(temp[i])\n px.remove(temp[i])\n py.remove(temp[i])\n\n if(len(px) > 1 ):\n #spiralTSP(px, py)\n print(px)\n #elif(len(px) == 1) :\n\n # path.append(px[0])\n # dont think this is necessary but we'll see\n # if(len(py)>0):\n # for i in range(0,len(py)):\n # path.append(py[i])\n\n else:\n print('have a nice day')\n#now call dat...\n# start = time.time()\n# spiralTSP(xsorted, ysorted)\n# stop = time.time()\n# duration = stop-start\n#print ('It took this long to calculate points: %d ')% duration #something wrong with this stupid line\n#print ('It took this long to calculate %d ')% duration #something wrong with this stupid line\n\n\ndef bs():\n factor = int(len(xsorted)/4) # for dividing up the grid\n\n xslice = xsorted[0:factor]\n yslice = ysorted[0:factor]\n\n xset = set(xslice)\n yset = set(yslice)\n\n #get the matching points and resort\n points = sort_coordinates(list(xset & yset), 1)\n print (points)\n\n #put lowest in a list\n path = []\n path.append(points[0])\n points.pop(0)\n\n for i in range(0, len(points)):\n path.append(calc_minDistance(path[len(path)-1], points)) # start at the end of the path calc to al other points\n points.remove(path[len(path)-1])\n print (points)\n print(path)\n\n pathset = set(path)\n\n\nzlist = read_file('tsp_test_cases/tsp_example_1.txt')\ntest = [(0, 50, 0), (0, 40, 1), (0, 10, 2)]\nysorted = sort_coordinates(zlist, 1)\nxsorted = sort_coordinates(zlist, 0)\n\nbs()\n\nprint(path)\n# update xsotred and y sorted\n# new = list( set(xsorted)&set(ysorted) )\n# ysorted = sort_coordinates(new, 1)\n# xsorted = sort_coordinates(new, 0)\n#\n# print(new)\n# print(len(new))\n\n#union = list(xset.intersection(yset))\n\n#print(union)\n#\n#\n# for i in range(0, factor-1): #n/5 elements\n# xset.add(xsorted[i])\n# yset.add(ysorted[i])\n\n\n#print(xset)\n#print(yset)\n\n#\n# union = list(xset.intersection(yset))\n# union2 = xset.symmetric_difference(yset)\n#\n# print(union)\n\n#\n# print('duration:')\n# print(duration)\n\n\n# print path\n# and time it took\n# print(path)\n# distance = 0\n# for i in range(0,len(path)-1):\n# distance += calc_distance(path[i],path[i+1])\n#\n# print(distance)\n#\n# #checking lists for duplicates because list 3 is not working and I cannot explain it\n# dupCheck = set()\n# for i in range (0, len(xsorted)):\n# dupCheck.add(xsorted[i])\n#\n# if len(dupCheck) == len(xsorted):\n# print ('they are equal')\n"
},
{
"alpha_fraction": 0.7085427045822144,
"alphanum_fraction": 0.7462311387062073,
"avg_line_length": 43.16666793823242,
"blob_id": "799efbbf2af9881783fd6d101ce9b7ea51ec3985",
"content_id": "e3ceecb758072b8697ceff519b6aedb4efbb2b1e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 796,
"license_type": "no_license",
"max_line_length": 118,
"num_lines": 18,
"path": "/README.txt",
"repo_name": "OregonCS325-2015/Project4",
"src_encoding": "UTF-8",
"text": "Martha Gebremariam\nMichael Hoppes\nRobert Jackson\nGroup Number - 11\nPROJECT 4\nCS 325 - Fall 2015\n\nhttps://github.com/OregonCS325-2015/Project4\n\nTo use this file type p4-tsp.py -i <your test file name> -o <your output file name>\n\nProgram automatically outputs yourfilename.txt with the results\n\nIf you put all files with the names as supplied in the assignment i.e('tsp_example_1.txt', 'tsp_example_2.txt',\n'test-input-1.txt', 'test-input-2.txt','test-input-3.txt', 'test-input-4.txt', 'test-input-5.txt', 'test-input-6.txt',\n'test-input-7.txt','tsp_example_3.txt') in a directory named tsp_test_results,\nAND make a results directory named tsp_results, it will cycle through all the files, and generate results when you do\nnot use any command line parameters. WARNING, that will take around 1 hour for all files to complete.\n"
},
{
"alpha_fraction": 0.5108327269554138,
"alphanum_fraction": 0.5423963665962219,
"avg_line_length": 27.723657608032227,
"blob_id": "2dd3ed772cd6e0161545e7a6eeede52a9473e1d7",
"content_id": "f4f21c7e3d861daab04e5c2df05e47580dc89d40",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14447,
"license_type": "no_license",
"max_line_length": 219,
"num_lines": 503,
"path": "/tsp.py",
"repo_name": "OregonCS325-2015/Project4",
"src_encoding": "UTF-8",
"text": "__author__ = 'Martha, Michael, and Robert'\n\nimport math\nimport heapq\nimport sys\nimport time\nimport random\n\n\n# Reads the files\n# @param a text file of space spearated numbers including an index\n# @return three arrays one of x coordinates one of y, and one multi\n# 0(n)\ndef read_file(name):\n x = [] # the values\n y = []\n z = []\n f = open(name, 'r')\n\n for i in f:\n index, a, b = i.split()\n #x.append(int(a))\n #y.append(int(b))\n z.append((int(a), int(b), int(index)))\n\n return z\n\n\n# takes two lists one of x coordinates one of y, calculates distances between each point\n# 0(n^2)\n# @param a text file of space spearated numbers including an index\n# @return one 2d array of distances\ndef calc_distance_matrix(x, y):\n matrix = [[0 for m in range(len(x))] for n in range(len(y))]\n\n for i in range(0, len(x)):\n\n for j in range(0, len(y)):\n # abs value because we don't want negative distances\n xdis = abs(x[i] - x[j])\n ydis = abs(y[i] - y[j])\n\n # dat hypotenuse - 3 figures\n dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n matrix[i][j] = dis\n\n return matrix\n\n\n# takes two coordinates, calculates distances between the point\n# C\n# @param crd = a coordinate list\n# @param i or j = a coordinate index i.e. [(438, 75), (381, 53)] (438, 75) = 0\n# @return one distance to three decimals\ndef calc_distance_point(crd, i, j):\n check1 = crd[i][0]\n check2 = crd[j][0]\n # abs value because we don't want negative distances\n xdis = abs(crd[i][0] - crd[j][0])\n ydis = abs(crd[i][1] - crd[j][1])\n\n # dat hypotenuse - 3 figures\n dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n return dis\n\n\n# takes two coordinates, calculates distances between the point\n# C\n# @param p1 p2 two points = with an x and y coordt\n# @return one distance to three decimals\ndef calc_distance(p1, p2):\n # \"\"\"\n # :rtype : float\n # \"\"\"\n # abs value because we don't want negative distances\n xdis = abs(p1[0] - p2[0])\n ydis = abs(p1[1] - p2[1])\n\n # dat hypotenuse - 3 figures\n #dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n dis = int( math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2)))\n\n return dis\n\n\ndef heapsort(iterable):\n h = []\n for value in iterable:\n heapq.heappush(h, value)\n return [heapq.heappop(h) for i in range(len(h))]\n\n\n# sorts a tuple\n# @param crd = a coordinate list\n# @param a tuple\n# @param v position 0 or 1 in the tuple (x or y)\n# @return sorted tuple\ndef sort_coordinates(a, v):\n # set to look at opposite position for swapping\n # depending if we're sorting x's or y's\n if v == 0:\n l = 1\n else:\n l = 0\n\n a = sorted(a, key=lambda x: x[v])\n\n # bubble sorts the small sections where the sorted coordinate is the same\n for i in range(0, len(a)):\n # looks over the list swapping if the ys are larger\n for i in range(1, len(a)):\n if (a[i - 1][v] == a[i][v]) & (a[i - 1][l] > a[i][l]):\n # swap\n f, g = a[i - 1], a[i]\n a[i - 1], a[i] = g, f\n\n return a\n\n# #Create outer cycle\n# #create edge list tuple\n# #create vertex tracking list\n# #create path tracking list\ndef algorithm(l):\n\n size = len(l)\n\n list1 = sort_coordinates(l, 0)\n list2 = sort_coordinates(l, 1)\n xTop = 0\n xBottom = size - 1\n yTop = 0\n yBottom = size - 1\n\n vertexList = [0] * size\n path = [0] * size\n pathIndex = 0\n smallXsmallY = list1[xTop]\n E = []\n\n while (list1[xTop][0] == list1[xTop + 1][0]):\n E.append((int(list1[xTop][0]), int(list1[xTop][1]), int(list1[xTop][2])))\n E.append((int(list1[xTop + 1][0]), int(list1[xTop + 1][1]), int(list1[xTop + 1][2])))\n path[pathIndex] = list1[xTop][2]\n pathIndex = pathIndex + 1\n path[pathIndex] = list1[xTop + 1][2]\n if (vertexList[list1[xTop][2] - 1] == 0):\n vertexList[list1[xTop][2] - 1] = 1\n if (vertexList[list1[xTop + 1][2] - 1] == 0):\n vertexList[list1[xTop + 1][2] - 1] = 1\n xTop = xTop + 1\n\n smallXlargeY = list1[xTop]\n if (vertexList[list1[xTop][2] - 1] == 0):\n vertexList[list1[xTop][2] - 1] = 1\n\n largeYlargeX = list2[yBottom]\n while (list2[yBottom][1] == list2[yBottom - 1][1]):\n E.append((int(list2[yBottom][0]), int(list2[yBottom][1]), int(list2[yBottom][2])))\n E.append((int(list2[yBottom - 1][0]), int(list2[yBottom - 1][1]), int(list2[yBottom - 1][2])))\n if (vertexList[list2[yBottom][2] - 1] == 0):\n vertexList[list2[yBottom][2] - 1] = 1\n if (vertexList[list2[yBottom - 1][2] - 1] == 0):\n vertexList[list2[yBottom - 1][2] - 1] = 1\n yBottom = yBottom - 1\n largeYsmallX = list2[yBottom + 1]\n\n if (smallXlargeY != largeYsmallX):\n E.append((int(list1[xTop][0]), int(list1[xTop][1]), int(list1[xTop][2])))\n\n E.append((int(list2[yBottom][0]), int(list2[yBottom][1]), int(list2[yBottom][2])))\n yBot = yBottom\n pathIndex = pathIndex + 1\n while (yBot < size):\n path[pathIndex] = list2[yBot][2]\n pathIndex = pathIndex + 1\n yBot = yBot + 1\n\n largeXlargeY = list1[xBottom]\n while (list1[xBottom][0] == list1[xBottom - 1][0]):\n E.append((int(list1[xBottom][0]), int(list1[xBottom][1]), int(list1[xBottom][2])))\n E.append((int(list1[xBottom - 1][0]), int(list1[xBottom - 1][1]), int(list1[xBottom - 1][2])))\n if (vertexList[list1[xBottom][2] - 1] == 0):\n vertexList[list1[xBottom][2] - 1] = 1\n if (vertexList[list1[xBottom - 1][2] - 1] == 0):\n vertexList[list1[xBottom - 1][2] - 1] = 1\n\n path[pathIndex] = list1[xBottom][2]\n pathIndex = pathIndex + 1\n path[pathIndex] = list1[xBottom - 1][2]\n xBottom = xBottom - 1\n\n largeXsmallY = list1[xBottom]\n\n if (largeXlargeY != largeYlargeX):\n E.append((largeYlargeX))\n\n E.append((largeXlargeY))\n\n smallYsmallX = list2[yTop]\n\n while (list2[yTop][1] == list2[yTop + 1][1]):\n E.append((int(list2[yTop][0]), int(list2[yTop][1]), int(list2[yTop][2])))\n E.append((int(list2[yTop + 1][0]), int(list2[yTop + 1][1]), int(list2[yTop + 1][2])))\n\n if (vertexList[list2[yTop][2] - 1] == 0):\n vertexList[list2[yTop][2] - 1] = 1\n if (vertexList[list2[yTop + 1][2] - 1] == 0):\n vertexList[list2[yTop + 1][2] - 1] = 1\n yTop = yTop + 1\n\n smallYlargeX = list2[yTop]\n if (vertexList[list2[yTop][2] - 1] == 0):\n vertexList[list2[yTop][2] - 1] = 1\n\n if (largeXsmallY != smallYlargeX):\n E.append((largeXsmallY))\n\n E.append((smallYlargeX))\n\n if (smallYsmallX != smallXsmallY):\n E.append((smallYsmallX))\n\n E.append((smallXsmallY))\n\n yTo = yTop\n pathIndex = pathIndex + 1\n while (yTo >= 0):\n path[pathIndex] = list2[yTo][2]\n pathIndex = pathIndex + 1\n yTo = yTo - 1\n\n print\n E[0:len(E)]\n print\n vertexList[0:len(vertexList)]\n print\n path[0:len(path)]\n\n\n\n\n\n\n\n# there will be four variables namely: xTop, xBottom, yTop, and yBottom that will be used to track current index from top and bottom in the two sorted lists\n# There will be a list E that holds current connected edge list in contiguous order\n# There will be a list v that is used to identify if specific vertex is already considered or not (0 for no or 1 for yes)\n# @param tpos bpos = xTop or Xbottom or whaever, sorted list is which list you're working from\n# @param E = visited edge lists\n# @param V = verifier list\n# @param sortedList = the x or y sorted list\ndef add_remaining(E, V, sortedList, tpos, bpos):\n # FOR EACH UNCONNECTED VERTEX, DETERMINE CONNECTION WITH LEAST ADDED COST (DISTANCE) AND CONNECT\n\n while tpos <= bpos:\n addition = sys.maxsize\n\n if V[tpos] == 0:\n\n # setup\n\n V[tpos] = 1\n vp = sortedList[tpos] # coordinate pair of Xtop\n s = len(E)\n idx = 0\n v1 = 0\n v2 = 0\n\n # loop\n for i in range(0, s - 1):\n # calc edges between all 3 points\n d1 = calc_distance(vp[0], E[i])\n d2 = calc_distance(vp[0], E[i + 1])\n lofEdge = calc_distance(E[i], E[i + 1])\n newAddition = (d1 + d2 - lofEdge)\n\n # if the new edge is awesome we do something with it\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n idx = i + 1 # not sure what for\n\n # Connect vprime with v1 and v2 to create edges vprimev1 and vprimev2 and disconnect v1 from v2\n # IS THIS THE EQUIVALENT OF PUTTING vp between E[i] and E[i+1] then... but this is happening outside of your for loop in the doc and now I'm befuddeled.\n # IF it is the case the we only insert when the if statement is true then this can go above. in addition it can be done then without setting the vars in the if stment. I followed the pseudo code and got lost\n\n E.insert(idx,\n vp) # CHECK THIS: it inserts before the point BUT IDEX IS NOT BEING SET OUT SIDE THE IF STMT\n\n tpos += 1 # increase the check position by 1\n\n\ndef calc_minDistance(list, startP):\n minDist = 100000\n pointIndex = 0 # initilaize\n\n if startP > 0:\n\n for i in range(0, startP - 1):\n prevMinDist = minDist\n # calculate the minimum distance\n minDist = min(minDist, calc_distance(list[startP], list[i + 1]))\n if minDist < prevMinDist:\n pointIndex = i + 1\n\n # check from stp to end\n for i in range(startP, len(list) - startP - 1):\n prevMinDist = minDist\n minDist = min(minDist, calc_distance(list[startP], list[i + 1]))\n if minDist < prevMinDist:\n pointIndex = i + 1\n\n return minDist, pointIndex\n\n\ndef genStartPoint(sortedList):\n\n pointofreturn = ()\n smallD = 99999999\n for i in range(0, 10):\n\n start_index = random.randrange (0, len(sortedList))\n prevmin = smallD\n mini, point = calc_minDistance(sortedList, start_index)\n smallD = min (smallD, mini)\n #store this point!\n if smallD < prevmin:\n pointofreturn = [mini, point, start_index]\n\n\n return pointofreturn\n\nzlist = read_file('tsp_test_cases/test-input-robtest.txt')\n\ntest = [(0, 50, 0), (0, 40, 1), (0, 10, 2)]\npy = sort_coordinates(zlist, 1)\npx = sort_coordinates(zlist, 0)\n\nprint(px)\nprint(py)\npath = []\ndef shit():\n\n ###LEFT CYCLE\n if(len(px) != 0 or px != ''):\n path.append(px[0]) #add to path\n py.remove(px[0]) #remove same from y\n px.pop(0) #remove it\n\n\n #reset\n hix = px[len(px)-1]\n hiy = py[len(py)-1]\n lowx = px[0]\n lowy = py[0]\n\n #setdump Left\n temp = []\n for i in range(0,len(px)):\n if (px[i][0] < hiy[0]) & (px[i][1] > lowx[1]):\n temp.append(px[i])\n py.remove(px[i])\n\n #ELSE sort the temp on the y\n temp = sort_coordinates(temp, 1)\n\n #dump it in the th path in order of increasing y\n for i in range(0,len(temp)):\n path.append(temp[i])\n px.remove(temp[i])\n\n #TOPCYCLE\n #now add hiy\n if(len(px) != 0 or px != ''):\n path.append(hiy) #add to path\n py.pop(len(py)-1) #remove from end of y\n px.remove(hiy)\n\n\n # #reset\n # hix = px[len(px)-1]\n # hiy = py[len(py)-1]\n # lowx = px[0]\n # lowy = py[0]\n\n #setdump Top\n temp = []\n for i in range(0,len(px)):\n if (px[i][0] > hiy[0]) & (px[i][1] > hix[1]):\n temp.append(px[i])\n py.remove(px[i])\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 0)\n\n #dump it in the th path in order of increasing y\n for i in range(0,len(temp)):\n path.append(temp[i])\n px.remove(temp[i])\n\n\n ###RIGHT CYCLE\n #now add hix\n if(len(px) != 0 or px != ''):\n path.append(hix) #add to path\n py.remove(hix) #remove\n px.pop(len(px)-1) #remove from end of x\n\n\n # #reset\n # hix = px[len(px)-1]\n # hiy = py[len(py)-1]\n # lowx = px[0]\n # lowy = py[0]\n\n #setdump RIGHT\n temp = []\n for i in range(0,len(px)):\n if (px[i][0] > lowy[0]) & (px[i][1] < hix[1]):\n temp.append(px[i])\n py.remove(px[i])\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 1)\n\n #dump it in the th path in order of decreasing y\n for i in range(len(temp)-1, -1, -1):\n path.append(temp[i])\n px.remove(temp[i])\n\n #BOTTOM CYCLE\n #now add lowy\n if(len(px) != 0 or px != ''):\n path.append(lowy) #add to path\n py.pop(0) #remove from end of x\n px.remove(lowy) #remove\n\n # hix = px[len(px)-1]\n # hiy = py[len(py)-1]\n # lowx = px[0]\n # lowy = py[0]\n\n #setdump Bottom\n temp = []\n for i in range(0,len(px)):\n if (px[i][0] < lowy[0]) & (px[i][1] < lowx[1]):\n temp.append(px[i])\n py.remove(px[i])\n\n #ELSE sort the temp on the x\n temp = sort_coordinates(temp, 0)\n\n #dump it in the th path in order of decreasing x\n for i in range(len(temp)-1, -1, -1):\n path.append(temp[i])\n px.remove(temp[i])\n\n\n print(temp)\n print(px)\n print(py)\n print(path)\n\n if(len(px) >0 or px != ''):\n shit()\n else:\n if(len(py)>0):\n for i in range(0,len(py)):\n path.append(py[i])\n print('have a nice day')\n\nshit()\n\n\n#HELD -KARP\n##print(calc_distance(zlist[0], zlist[1]))\n# #print (calc_minDistance(pyx, 0))\n# path = set()\n# dist = []\n# for i in range(0, 20):\n# a = genStartPoint(zlist)\n#\n# tup = (a[1], a[2])\n# zlist.pop(a[2])\n# zlist.pop(a[1])\n# path.add(tup)\n# dist.append(a[0])\n#\n# #path.add(a)\n# #b = genStartPoint(zlist)\n#\n# print(a)\n#\n# print(path)\n# print(dist)\n#\n# print(len(zlist))\n# print(zlist[1366])\n# print(zlist[1258])\n#\n# a = calc_minDistance(zlist, 1258)\n# print (a)"
},
{
"alpha_fraction": 0.38314250111579895,
"alphanum_fraction": 0.4112224876880646,
"avg_line_length": 30.602102279663086,
"blob_id": "03fecd2d86a7b8da7b467f5ec6c46dc1423aa66f",
"content_id": "dc76ffc45f3ac0c1bcd4873fbd2a1181ab78d647",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 21047,
"license_type": "no_license",
"max_line_length": 132,
"num_lines": 666,
"path": "/p4-tsp.py",
"repo_name": "OregonCS325-2015/Project4",
"src_encoding": "UTF-8",
"text": "import sys\nimport math\nimport time\nimport getopt\n\n#adapted from http://www.tutorialspoint.com/python/python_command_line_arguments.htm\ndef cmd_line_io(argv):\n\tinputfile = ''\n\toutputfile = ''\n\ttry:\n\t\topts, args = getopt.getopt(argv,\"hi:o:\",[\"ifile=\", \"ofile=\"])\n\texcept getopt.GetoptError:\n\t\tprint ('p4.py -i <inputfile> -o <outputfile>')\n\t\tsys.exit(2)\n\tfor opt, arg in opts:\n\t\t#help\n\t\tif opt == '-h':\n\t\t\tprint ('p4.py -i <inputfile> ')\n\t\t\tsys.exit()\n\n\t\t#input file\n\t\telif opt in (\"-i\", \"--ifile\"):\n\t\t\tinputfile = arg\n\t\telif opt in (\"-o\", \"--ofile\"):\n\t\t\toutputfile = arg\n\n\treturn inputfile, outputfile\n\n\tprint ('Input file is \"', inputfile)\n\tprint ('Output file is \"', outputfile)\n\n\ndef read_file(name):\n\n z = []\n f = open(name, 'r')\n\n for i in f:\n index, a, b = i.split()\n z.append((int(a), int(b), int(index)))\n\n return z\n\n\ndef calc_distance(p1, p2):\n xdis = abs(p1[0] - p2[0])\n ydis = abs(p1[1] - p2[1])\n\n # dat hypotenuse - 3 figures\n\t# dis = \"%.3f\" % math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2))\n dis = float(math.sqrt(math.pow(xdis, 2) + math.pow(ydis, 2)))\n\n return dis\n\n\ndef sort_coordinates(a, v):\n # set to look at opposite position for swapping\n # depending if we're sorting x's or y's\n if v == 0:\n l = 1\n else:\n l = 0\n\n a = sorted(z, key=lambda x: x[v])\n # print a[0:len(a)]\n for i in range(0, len(a)):\n # looks over the list swapping if the ys are larger\n for i in range(1, len(a)):\n if (a[i - 1][v] == a[i][v]) & (a[i - 1][l] > a[i][l]):\n # swap\n f, g = a[i - 1], a[i]\n a[i - 1], a[i] = g, f\n\n return a\n\n\ndef algorithm(l):\n size = len(l)\n list1 = sort_coordinates(l, 0)\n list2 = sort_coordinates(l, 1)\n xTop = 0\n xBottom = size - 1\n yTop = 0\n yBottom = size - 1\n\n vertexList = [0] * size\n\n # find the left most vertex(vertices). Connect if more than one\n smallXsmallY = list1[xTop]\n if (vertexList[list1[xTop][2]] == 0):\n vertexList[list1[xTop][2]] = 1\n\n E = []\n\n while (list1[xTop][0] == list1[xTop + 1][0]):\n E.append((int(list1[xTop][0]), int(list1[xTop][1]), int(list1[xTop][2])))\n E.append((int(list1[xTop + 1][0]), int(list1[xTop + 1][1]), int(list1[xTop + 1][2])))\n if (vertexList[list1[xTop][2]] == 0):\n vertexList[list1[xTop][2]] = 1\n if (vertexList[list1[xTop + 1][2]] == 0):\n vertexList[list1[xTop + 1][2]] = 1\n xTop = xTop + 1\n\n smallXlargeY = list1[xTop]\n if (vertexList[list1[xTop][2]] == 0):\n vertexList[list1[xTop][2]] = 1\n\n # find the top most vertex(ices). Connect if more than one\n largeYlargeX = list2[yBottom]\n if (vertexList[list2[yBottom][2]] == 0):\n vertexList[list2[yBottom][2]] = 1\n\n while (list2[yBottom][1] == list2[yBottom - 1][1]):\n E.append((int(list2[yBottom][0]), int(list2[yBottom][1]), int(list2[yBottom][2])))\n E.append((int(list2[yBottom - 1][0]), int(list2[yBottom - 1][1]), int(list2[yBottom - 1][2])))\n if (vertexList[list2[yBottom][2]] == 0):\n vertexList[list2[yBottom][2]] = 1\n if (vertexList[list2[yBottom - 1][2]] == 0):\n vertexList[list2[yBottom - 1][2]] = 1\n yBottom = yBottom - 1\n\n # if (yBottom==size-1):\n #\tyBottom=yBottom-1\n # yBottom=yBottom+1\n largeYsmallX = list2[yBottom]\n # largeYsmallX=list2[yBottom+1]\n\n if (vertexList[list2[yBottom][2]] == 0):\n vertexList[list2[yBottom][2]] = 1\n\n # yBottom=yBottom+1\n\n # connect left most vertex (if more than one,\n # top vertex of left most vertices) WITH top more vertex\n # (if more than one, left vertex of top most vertices)\n # unless it turns out to be the same vertex\n if (smallXlargeY != largeYsmallX):\n E.append((smallXlargeY))\n E.append((largeYsmallX))\n\n largeXlargeY = list1[xBottom]\n if (vertexList[list1[xBottom][2]] == 0):\n vertexList[list1[xBottom][2]] = 1\n\n while (list1[xBottom][0] == list1[xBottom - 1][0]):\n E.append((int(list1[xBottom][0]), int(list1[xBottom][1]), int(list1[xBottom][2])))\n E.append((int(list1[xBottom - 1][0]), int(list1[xBottom - 1][1]), int(list1[xBottom - 1][2])))\n if (vertexList[list1[xBottom][2]] == 0):\n vertexList[list1[xBottom][2]] = 1\n if (vertexList[list1[xBottom - 1][2]] == 0):\n vertexList[list1[xBottom - 1][2]] = 1\n\n xBottom = xBottom - 1\n\n largeXsmallY = list1[xBottom]\n\n if (largeXlargeY != largeYlargeX):\n E.append((largeYlargeX))\n\n E.append((largeXlargeY))\n\n smallYsmallX = list2[yTop]\n\n while (list2[yTop][1] == list2[yTop + 1][1]):\n E.append((int(list2[yTop][0]), int(list2[yTop][1]), int(list2[yTop][2])))\n E.append((int(list2[yTop + 1][0]), int(list2[yTop + 1][1]), int(list2[yTop + 1][2])))\n\n if (vertexList[list2[yTop][2]] == 0):\n vertexList[list2[yTop][2]] = 1\n if (vertexList[list2[yTop + 1][2]] == 0):\n vertexList[list2[yTop + 1][2]] = 1\n yTop = yTop + 1\n\n smallYlargeX = list2[yTop]\n if (vertexList[list2[yTop][2]] == 0):\n vertexList[list2[yTop][2]] = 1\n\n if (largeXsmallY != smallYlargeX):\n E.append((largeXsmallY))\n\n E.append((smallYlargeX))\n\n if (smallYsmallX != smallXsmallY):\n E.append((smallYsmallX))\n E.append((smallXsmallY))\n cost = 0\n i = 0\n while i < (len(E) - 1):\n length = calc_distance(E[i], E[i + 1])\n # \tprint E[i][2]\n # \tprint E[i+1][2]\n cost = float(cost + length)\n #\tprint (\"cost: %d\" %cost)\n i = i + 2\n\n # print E[0:len(E)]\n xTop = xTop + 1\n xBottom = xBottom - 1\n yTop = yTop + 1\n yBottom = yBottom - 1\n\n # for i in range (0, size):\n while xTop <= xBottom:\n addition = sys.maxsize\n if xTop <= xBottom:\n # print vertexList[list1[xTop][2]-1]\n if vertexList[list1[xTop][2]] == 0:\n vertexList[list1[xTop][2]] = 1\n newV = list1[xTop]\n # print list1[xTop][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n idx = i + 1\n i = i + 2\n # print \"\\n\"\n #\t\tprint\"ONE\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n xTop = xTop + 1\n # print E[0:len(E)]\n\n\n addition = sys.maxsize\n while list1[xTop][0] == list1[xTop - 1][0]:\n if xTop <= xBottom:\n # print vertexList[list1[xTop][2]-1]\n if vertexList[list1[xTop][2]] == 0:\n vertexList[list1[xTop][2]] = 1\n newV = list1[xTop]\n # print list1[xTop][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n # print \"\\n\"\n #\t\tprint \"TWO\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n xTop = xTop + 1\n # print E[0:len(E)]\n\n addition = sys.maxsize\n # m=list1[xBottom][0]\n # n=list1[xBottom-1][0]\n # while list1[xBottom][0]==list1[xBottom-1][0]:\n if xBottom >= xTop:\n # print xBottom\n # print xTop\n # print vertexList[list1[xBottom][2]-1]\n if vertexList[list1[xBottom][2]] == 0:\n vertexList[list1[xBottom][2]] = 1\n newV = list1[xBottom]\n # print list1[xBottom][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n\n # print \"\\n\"\n #\t\tprint \"THREE\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n xBottom = xBottom - 1\n # print E[idx-1]\n #\t print E[idx]\n #\t print (\"idxThree: %d\" %idx)\n #\t print E[0:len(E)]\n\n\n\n\n while list1[xBottom][0] == list1[xBottom + 1][0]:\n if xBottom >= xTop:\n if vertexList[list1[xBottom][2]] == 0:\n vertexList[list1[xBottom][2]] = 1\n newV = list1[xBottom]\n # print list1[xBottom][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n\n # print \"\\n\"\n #\t\tprint \"FOUR\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n #\t\tprint E[0:len(E)]\n #\t\tprint E[idx]\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n #\t\tprint (\"idxFour: %d\" %idx)\n cost = float(cost + addition)\n xBottom = xBottom - 1\n #\t print E[0:len(E)]\n\n addition = sys.maxsize\n # while list1[yTop][1]==list1[yTop+1][1]:\n if yTop <= yBottom:\n # print vertexList[list1[yTop][2]-1]\n if vertexList[list2[yTop][2]] == 0:\n vertexList[list2[yTop][2]] = 1\n newV = list2[yTop]\n # print list1[yTop][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n\n # print \"\\n\"\n #\t\tprint \"FIVE\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n yTop = yTop + 1\n # print E[0:len(E)]\n\n\n addition = sys.maxsize\n while list2[yTop][1] == list2[yTop - 1][1]:\n if yTop <= yBottom:\n # print vertexList[list1[yTop][2]-1]\n if vertexList[list2[yTop][2]] == 0:\n vertexList[list2[yTop][2]] = 1\n newV = list2[yTop]\n # print list1[yTop][2]\n s = len(E)\n i = 0\n while (i <= s - 1):\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n\n # print \"\\n\"\n #\t\tprint \"SIX\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n yTop = yTop + 1\n # print E[0:len(E)]\n\n addition = sys.maxsize\n # while list1[yBottom][1]==list1[yBottom-1][1]:\n if yBottom >= yTop:\n # print vertexList[list1[yBottom][2]-1]\n if vertexList[list2[yBottom][2]] == 0:\n vertexList[list2[yBottom][2]] = 1\n newV = list2[yBottom]\n # print list1[yBottom][2]\n s = len(E)\n i = 0\n while i <= s - 1:\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n #\t\t print (\"newAddition4: %d\" %newAddition)\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n #\n #\t\tprint \"\\n\"\n #\t\tprint \"SEVEN\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n yBottom = yBottom - 1\n # print E[0:len(E)]\n\n\n addition = sys.maxsize\n while list2[yBottom][1] == list2[yBottom + 1][1]:\n if yBottom >= yTop:\n # print vertexList[list1[yBottom][2]-1]\n if vertexList[list2[yBottom][2]] == 0:\n vertexList[list2[yBottom][2]] = 1\n newV = list2[yBottom]\n # print list1[yBottom][2]\n s = len(E)\n i = 0\n while i <= s - 1:\n d1 = calc_distance(newV, E[i])\n d2 = calc_distance(newV, E[i + 1])\n lenEdge = calc_distance(E[i], E[i + 1])\n newAddition = d1 + d2 - lenEdge\n if newAddition < addition:\n addition = newAddition\n v1 = E[i]\n v2 = E[i + 1]\n #\t\t\tprint (\"additon: %d\" %addition)\n #\t\t\tprint \"\\n\"\n #\t\t\tprint newV\n #\t\t\tprint v1\n #\t\t\tprint v2\n\n idx = i + 1\n i = i + 2\n # print \"\\n\"\n #\t\tprint \"EIGHT\"\n #\t\tprint newV\n #\t\tprint v1\n #\t\tprint v2\n\n\n E.append((E[idx]))\n E[idx] = newV\n E.append((newV))\n cost = float(cost + addition)\n yBottom = yBottom - 1\n # print E[0:len(E)]\n # return cost\n\n m = [[0] * (2) for x in range(size)]\n i = 0\n while i < (len(E) - 1):\n if m[E[i][2]][0] == 0:\n m[E[i][2]][0] = E[i + 1][2]\n else:\n m[E[i][2]][1] = E[i + 1][2]\n if m[E[i + 1][2]][0] == 0:\n m[E[i + 1][2]][0] = E[i][2]\n else:\n m[E[i + 1][2]][1] = E[i][2]\n i = i + 2\n\n i = m[0][0]\n q = 0\n path = []\n k = 1\n # while (k!=m[0][1]):\n while k != 0:\n if (m[i][0] == q):\n q = i\n i = m[i][1]\n path.append(q)\n # return q\n else:\n q = i\n i = m[i][0]\n path.append(q)\n # return q\n k = q\n return cost, path\n\n\n# print len(m)\n# print (\"\\n\")\n# print E[0:len(E)]\n# print (\"Length of E: %d\" %len(E))\n# print (\"\\n\")\n# print m[0:len(m)]\n\ndef writeFile(name, contents, method='a'):\n try:\n f = open(name, method)\n except:\n print(\"The file could not be opened: \", sys.exc_info()[0])\n\n f.write(contents)\n f.write('\\n')\n f.close()\n\n\nif __name__ == \"__main__\":\n\t(ifile, ofile) = cmd_line_io(sys.argv[1:])\n\n\tif (ifile != '') & (ofile != ''):\n\t\tprint ('Running...')\n\n\t\tz = read_file(ifile)\n\n\t\tstart = time.time()\n\t\tdistance, path = algorithm(z)\n\t\tstop = time.time()\n\t\tduration = stop - start\n\n\t\tpathstring = ''\n\t\tcount = 0\n\t\tfor i in range(0,len(path)):\n\t\t\tpathstring += str(path[i]) +'\\n'\n\t\t\tcount= count+1\n\n\t\tresultsummary = 'FILE: %s had points %i; Distance: %d; Time: %d \\n'%(ifile, count, distance, duration)\n\n\t\twriteFile(ofile, str(distance), method='a')\n\t\twriteFile(ofile, str(pathstring), method='a')\n\t\twriteFile('resultsumary.txt', resultsummary, method='a')\n\n\n\n\telif(ifile == '') & (ofile == ''):\n\t\tprint ('This will now cycle though all files we have')\n\n\t\tfilenames = ['tsp_example_1.txt', 'tsp_example_2.txt','test-input-1.txt', 'test-input-2.txt',\n 'test-input-3.txt', 'test-input-4.txt', 'test-input-5.txt', 'test-input-6.txt', 'test-input-7.txt','tsp_example_3.txt']\n\n\t\t#for i in range(0, len(filenames)):\n\t\tfor i in range(0, len(filenames)):\n\t\t\tcurFile = filenames[i]\n\t\t\tinput = 'tsp_test_cases/' + curFile\n\t\t\toutput = 'tsp_results/' + curFile\n\n\t\t\tz = read_file(input)\n\t\t\tresult = []\n\n\t\t\tstart = time.time()\n\t\t\tdistance, path = algorithm(z)\n\t\t\tstop = time.time()\n\t\t\tduration = stop - start\n\n\t\t\tpathstring = ''\n\t\t\tcount = 0\n\t\t\tfor i in range(0,len(path)):\n\t\t\t\tpathstring += str(path[i]) +'\\n'\n\t\t\t\tcount= count+1\n\n\t\t\tresultsummary = 'FILE: %s had points %i; Distance: %d; Time: %f \\n'%(curFile, count, distance, duration)\n\n\t\t\twriteFile(output, str(distance), method='a')\n\t\t\twriteFile(output, str(pathstring), method='a')\n\t\t\twriteFile('tsp_results/resultsumary.txt', resultsummary, method='a')\n\n\telse:\n\t\tprint ('Incorrect parameters provided try p4 -h')\n"
}
] | 4
|
luish/maquina-mealy
|
https://github.com/luish/maquina-mealy
|
ff6bb709374697206db486a23278eeb54142834f
|
69fe070ecd46c4bb0babc9f79acef52764c26dcb
|
31e5255a5c4035898b15a2d2c71751c3ad0fa286
|
refs/heads/master
| 2020-05-20T07:25:59.011646
| 2011-05-12T10:47:01
| 2011-05-12T10:47:01
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4969135820865631,
"alphanum_fraction": 0.5277777910232544,
"avg_line_length": 19.1875,
"blob_id": "209ac12e800c58a62a39ff631ce50276c06e0b40",
"content_id": "74ec790d9a9f2d3cf7fce87d256790836953c54d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "INI",
"length_bytes": 326,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 16,
"path": "/maquinas/mealy4.ini",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "[dados_gerais]\ntipo = mealy\nnome = Maquina de Mealy\ninformacoes = Esta é uma máquina de mealy para testes\n\n[dados_maquina]\nqte_estados = 1\nalfabeto_entrada = ['0','1']\nalfabeto_saida = ['a', 'b']\nestados_finais = []\nestado_inicial = 0\n\ntransicoes : [\n [0, '0', 0, 'a'],\n [0, '1', 0, 'b']\n ]\n\n"
},
{
"alpha_fraction": 0.37154990434646606,
"alphanum_fraction": 0.42038217186927795,
"avg_line_length": 22.5,
"blob_id": "094875b10dce31939c2d75dd6e4f894e62875601",
"content_id": "fe1363454d3348695b58bbd20c5a9f5ae391bc71",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "INI",
"length_bytes": 473,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 20,
"path": "/maquinas/mealy3.ini",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "[dados_gerais]\ntipo = mealy\nnome = Maquina de Mealy\ninformacoes = Esta é uma máquina de mealy para testes\n\n[dados_maquina]\nqte_estados = 3\nalfabeto_entrada = ['0','1']\nalfabeto_saida = ['a', 'b']\nestados_finais = [2]\nestado_inicial = 0\n\ntransicoes : [\n [0, '0', 1, 'aa'],\n [0, '1', 2, 'ab'],\n [1, '0', 2, 'aab'],\n [1, '1', 1, 'abb'],\n [2, '0', 0, 'bba'],\n [2, '1', 2, 'bbb']\n ]\n\n"
},
{
"alpha_fraction": 0.4496487081050873,
"alphanum_fraction": 0.48946136236190796,
"avg_line_length": 20.350000381469727,
"blob_id": "58d248cab7218d917dbb77523accf720e5b2eb29",
"content_id": "adca6a9cb85a721efc20865186ea8898aa4deafd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "INI",
"length_bytes": 429,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 20,
"path": "/maquinas/mealy2.ini",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "[dados_gerais]\ntipo = mealy\nnome = Maquina de Mealy 1\ninformacoes = Esta é uma máquina de mealy para testes\n\n[dados_maquina]\nqte_estados = 2\nalfabeto_entrada = ['0','1']\nalfabeto_saida = ['a', 'b']\nestados_finais = [1]\nestado_inicial = 0\n\n# Qantes, Input, Qdepois, Output\n\ntransicoes : [\n [0, '0', 0, 'aabb'],\n [0, '1', 1, 'bab'],\n [1, '0', 0, 'b'],\n [1, '1', 1, 'a']\n ]\n"
},
{
"alpha_fraction": 0.5158621668815613,
"alphanum_fraction": 0.5202794671058655,
"avg_line_length": 32.066490173339844,
"blob_id": "d5d77d79e766b38c7823f5defe9a6e4ba85782e0",
"content_id": "4fc2ff491f554c5db5a3ab9fdf1456ac230b4689",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 12560,
"license_type": "no_license",
"max_line_length": 117,
"num_lines": 376,
"path": "/maq_mealy.py",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\n# ##############################################################################\n# Trabalho de Teoria da Computação\n# Simulador de Máquina de Mealy\n# Copyright, 2010 por Luis Henrique B. Sousa, Lucas L. Garcia\n#\n# Arquivo maq_mealy.py\n# -> Implementação do core da Máquina de Mealy (funções e classe)\n#\n# Código licenciado sob a GNU GPL versão 2.0 ou superior\n#\n# Versão: 1.0 novembro de 2010\n# ###############################################################################\n\nimport ConfigParser\nimport os.path\n\nclass maq_mealy:\n \n \"\"\"\n Esta classe implementa uma máquina de Mealy. \n Retorna uma saída (output) que é feita em cada transição (e não nos estados,\n como nas Máquinas de Moore)\n \n @param o arquivo de configuração\n @param dicionário de configuração\n \"\"\"\n \n def __init__(self, file=None, config={}):\n \n \"\"\"\n Método construtor da classe. É um tipo de construtor múltiplo,\n pois pode receber um arquivo de configuração ou um dicionário.\n \"\"\"\n \n # se a instancia passou um arquivo como parametro\n \n if file:\n if os.path.isfile(file):\n self.__le_arquivo(file)\n else:\n return\n \n # senão, a instancia passou um dicionário de configuração\n \n elif len(config) > 0:\n self.nome = config['nome']\n self.tipo = config['tipo']\n self.informacoes = config['informacoes']\n self.qte_estados = config['num_estados']\n self.alfabeto_entrada = config['alfabeto_entrada']\n self.alfabeto_saida = config['alfabeto_saida']\n self.estados_finais = config['estados_finais']\n self.estado_inicial = config['estado_inicial']\n self.transicoes = config['transicoes']\n \n # não passou nenhum dos dois\n \n else:\n return\n \n # inicializa atributos\n \n self.erro = None\n self.est_atual = 0\n self.cabeca = 0\n self.posicao = 0\n self.estados = []\n self.entrada = \"\"\n self.output = \"\"\n self.pap = \"\"\n\n\n def __le_arquivo(self, conf):\n \n \"\"\"\n Recupera informações do arquivo de configuração da máquina de Mealy.\n Diferente da MT padrão, as máquinas de Mealy não tem estado(s) final(is). \n \"\"\"\n \n config = ConfigParser.RawConfigParser()\n config.read(conf)\n\n self.tipo = config.get('dados_gerais', 'tipo')\n self.nome = config.get('dados_gerais', 'nome')\n self.informacoes = config.get('dados_gerais', 'informacoes')\n \n self.qte_estados = int(config.get('dados_maquina', 'qte_estados'))\n \n self.alfabeto_entrada = eval(config.get('dados_maquina', 'alfabeto_entrada'))\n self.alfabeto_saida = eval(config.get('dados_maquina', 'alfabeto_saida'))\n self.estados_finais = eval(config.get('dados_maquina', 'estados_finais'))\n self.estado_inicial = eval(config.get('dados_maquina', 'estado_inicial'))\n \n self.transicoes = eval(config.get('dados_maquina','transicoes'))\n\n\n def gravar_arquivo(self, arquivo):\n \n \"\"\"\n Salva a máquina de mealy em um arquivo de configurações.\n \"\"\"\n \n config = ConfigParser.RawConfigParser()\n config.add_section('dados_gerais')\n config.add_section('dados_maquina')\n \n config.set('dados_gerais', 'tipo', self.tipo)\n config.set('dados_gerais', 'nome', self.nome)\n config.set('dados_gerais', 'informacoes', self.informacoes)\n \n config.set('dados_maquina', 'qte_estados', self.qte_estados)\n config.set('dados_maquina', 'alfabeto_entrada', self.alfabeto_entrada)\n config.set('dados_maquina', 'alfabeto_saida', self.alfabeto_saida)\n config.set('dados_maquina', 'estados_finais', self.estados_finais)\n config.set('dados_maquina', 'estado_inicial', self.estado_inicial)\n config.set('dados_maquina', 'transicoes', self.transicoes)\n \n with open(arquivo, 'wb') as configfile:\n config.write(configfile)\n\n\n def validar_maquina(self):\n \n \"\"\"\n Uma máquina de mealy é válida se não tem não-determinismo e se os caracteres de entrada\n e saída condizem, respectivamente, com os alfabetos de entrada e saída.\n \"\"\"\n \n valida = True\n \n if not self.__confere_num_transicoes():\n valida = False\n\n elif not self.__confere_alfabeto_entrada(self.entrada, self.alfabeto_entrada):\n valida = False\n \n elif not self.__confere_alfabeto_saida(self.entrada, self.alfabeto_saida):\n valida = False\n \n elif not self.__confere_num_estados(self.qte_estados):\n valida = False\n \n elif not self.confere_nao_determinismo():\n valida = False \n \n return valida\n \n \n def __confere_num_transicoes(self):\n \n \"\"\"\n Método para conferir se o número de transições está correto. Está incorreto quando\n há o número de transições é maior do que o produto dos estados e da quantidade de\n caracteres do alfabeto de entrada.\n \"\"\"\n \n if len(self.transicoes) > self.qte_estados * len(self.alfabeto_entrada):\n self.erro = \"ERRO: O número de transições está incorreto.\"\n return False\n\n else:\n return True\n\n\n def __confere_alfabeto_entrada(self, fita, alfabeto):\n \n \"\"\"\n Método para conferir se todos os caracteres na string de entrada pertencem\n ao alfabeto definido. Se algum caractere não faça parte do alfabeto, uma\n mensagem de erro é definida nos atributos de passo a passo e final, e false\n é retornado. Caso contrário, a conferência obteve sucesso e retorna true.\n \"\"\"\n \n for c in fita:\n if not c in alfabeto:\n self.erro = \"ERRO: O caractere %s não faz parte do alfabeto de entrada.\" % c\n \n for t in self.transicoes:\n entrada = t[1]\n if not entrada in alfabeto:\n self.erro = \"ERRO: O caractere %s não faz parte do alfabeto de entrada.\" % entrada\n\n if self.erro:\n return False\n \n return True\n \n \n def __confere_alfabeto_saida(self, fita, alfabeto):\n \n \"\"\"\n Método para conferir se todos os caracteres na string de saida pertencem\n ao alfabeto definido. Se algum caractere não faça parte do alfabeto, uma\n mensagem de erro é definida nos atributos de passo a passo e final, e false\n é retornado. Caso contrário, a conferência obteve sucesso e retorna true.\n \"\"\"\n \n for t in self.transicoes:\n saida = t[3]\n for c in saida:\n if not c in alfabeto:\n self.erro = \"ERRO: O caractere %s não faz parte do alfabeto de saída.\" % saida\n\n if self.erro:\n return False\n \n return True \n \n \n def __confere_num_estados(self, qtd_estados):\n \n \"\"\"\n Método para conferir se o número de estados é consistente com os estados colocados\n nas transições.\n \"\"\"\n \n for t in self.transicoes:\n if t[0] not in self.estados:\n self.estados.append(t[0])\n \n if len(self.estados) <= qtd_estados:\n return True\n \n else:\n self.erro = \"O número de estados está incorreto.\" \n return False\n\n\n def confere_nao_determinismo(self):\n \n \"\"\"\n Checa se um estado tem mais de uma transição possível quando lê um entrada.\n \"\"\"\n \n k = 0\n cont = 0\n \n while k < len(self.transicoes) and cont < 2 and not self.erro:\n estado = self.transicoes[k][0]\n leitura = self.transicoes[k][1]\n \n for transicao in self.transicoes:\n if transicao[0] == estado and transicao[1] == leitura:\n cont += 1\n \n if cont > 1:\n self.erro = \"ERRO: Uma Máquina de Mealy não pode ter não-determinismo.\"\n\n cont = 0\n k += 1\n \n return self.erro == None\n\n\n def executa(self, fita, *args):\n \n \"\"\"\n Método principal da máquina, pois processa a string na máquina de Mealy e produz uma saída (output).\n \"\"\"\n\n self.entrada = fita\n \n if len(args) == 0: \n \n if not self.validar_maquina():\n return\n\n self.est_atual = 0\n \n # variavel de controle sobre as transicoes\n \n t = 0\n \n for caractere in self.entrada:\n \n continua = True\n \n while continua and (t < len(self.transicoes)):\n \n self.cabeca = caractere \n\n estado = self.transicoes[t][0]\n leitura = self.transicoes[t][1]\n proximo = self.transicoes[t][2]\n escrita = self.transicoes[t][3]\n \n if self.cabeca == leitura and self.est_atual == estado:\n self.output = self.output.replace('_', '') + \"_\" + escrita\n self.pap += \"(q%d: %3s / %5s) => output: %s\\n\" % (estado, self.cabeca, escrita, self.output)\n self.est_atual = proximo\n continua = False\n self.posicao += 1\n \n if t <= len(self.transicoes):\n t = 0\n \n else:\n t += 1\n \n return self.output\n \n def aceita(self):\n if (self.est_atual in self.estados_finais) and (self.posicao >= len(self.entrada)):\n return True\n else:\n return False\n \n def get_output(self):\n return self.output.replace('_', '')\n \n def get_entrada(self):\n return self.entrada \n \n def get_pap(self):\n return self.pap\n \n def sucesso(self):\n return self.erro == None\n \n def get_erro(self):\n return self.erro\n \n def get_info(self):\n return { 'tipo': self.tipo, 'nome': self.nome, 'info': self.informacoes }\n\n def get_estado_atual(self):\n return self.est_atual\n\n def get_posicao(self):\n return self.posicao\n \n def gerar_imagem(self):\n \n \"\"\"\n Utilizando o aplicativo graphviz.org, geramos um arquivo com informações da máquina de mealy.\n A imagem é gerada usando o comando: $ dot -T png -o maq_mealy.png maq_mealy.dot\n \"\"\"\n \n states = self.estados\n states.sort()\n \n qfs = \" \".join(map(str, self.estados_finais))\n\n dot_graph = 'digraph mealy_machine {\\n'\n dot_graph += ' rankdir=LR;\\n'\n dot_graph += ' edge [fontname=arial,fontsize=11]\\n'\n dot_graph += ' node [shape=circle,size=8]\\n'\n dot_graph += ' start [shape=point]\\n'\n dot_graph += ' start -> %s\\n' % self.estado_inicial\n dot_graph += ' node [fontname=arial,fontsize=11,shape=doublecircle]\\n'\n dot_graph += ' ' + qfs\n dot_graph += ';\\n'\n dot_graph += ' node [shape=circle,size=8]\\n'\n\n for state in range(len(self.transicoes)):\n values = self.transicoes[state]\n dot_graph += ' %s -> %s [label=\"%s/%s\"]\\n' % (values[0], values[2], values[1], values[3])\n\n dot_graph += '}\\n'\n\n return dot_graph \n \n def gravar_imagem(self, nome_arquivo=\"imagens/maq_mealy.png\"):\n \n \"\"\"\n Cria código de um arquivo do aplicativo graphviz.org para depois gerar uma imagem da máquina.\n \"\"\"\n \n try:\n dotfile = file(nome_arquivo + \".dot\", \"wb\")\n dotfile.write(self.gerar_imagem())\n except IOError:\n pass\n \n \n"
},
{
"alpha_fraction": 0.3920792043209076,
"alphanum_fraction": 0.4396039545536041,
"avg_line_length": 21.954545974731445,
"blob_id": "ac6dc8041c8bf66088f9d077b70414a605becd3c",
"content_id": "e438e10cbb2cf02b588400765ccea0949b3b7554",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "INI",
"length_bytes": 507,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 22,
"path": "/maquinas/mealy1.ini",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "[dados_gerais]\ntipo = mealy\nnome = Maquina de Mealy 1\ninformacoes = Esta é uma máquina de mealy para testes\n\n[dados_maquina]\nqte_estados = 3\nalfabeto_entrada = ['0', '1']\nalfabeto_saida = ['a', 'b', 'c']\nestados_finais = [1, 2]\nestado_inicial = 0\n\n# Qantes, Input, Qdepois, Output\n\ntransicoes : [\n [0, '0', 0, 'abc'],\n [0, '1', 1, 'bb'],\n [1, '0', 2, 'ca'],\n [1, '1', 1, 'bc'],\n [2, '0', 0, 'aa'],\n [2, '1', 2, 'aaa']\n ]\n"
},
{
"alpha_fraction": 0.6310642957687378,
"alphanum_fraction": 0.6338849067687988,
"avg_line_length": 38.97744369506836,
"blob_id": "ff1630e1bca9ed78582b2fdb3c373f9264add413",
"content_id": "f49ba7dfa2c1ce677aef607fdea2f6497c4abbe8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5346,
"license_type": "no_license",
"max_line_length": 167,
"num_lines": 133,
"path": "/executa_maq_mealy.py",
"repo_name": "luish/maquina-mealy",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\nfrom maq_mealy import maq_mealy\nimport os.path\n\ndiretorio_maquinas = \"maquinas/\"\ndiretorio_imagens = \"imagens/\"\n\nopcao_sim = ['s', 'S', 'sim', 'y', 'yes']\n \nprint \"\"\"\nMáquina de Mealy\n\nDigite 0 (zero) para que os dados sejam lidos do arquivo ou \n1 (um) para que sejam adicionados via teclado.\"\"\"\n\nopcao = int(raw_input(\"0 ou 1? \"))\nwhile opcao not in [0, 1]:\n print \"Opcao invalida, digite novamente. \"\n opcao = int(raw_input(\"0 ou 1? \"))\n\nif opcao == 0:\n nome_arquivo = raw_input(\"Digite o nome do arquivo: maquinas/\")\n \n # checando se o arquivo de configuracao passado existe\n while not os.path.isfile(diretorio_maquinas + nome_arquivo):\n print \"O arquivo \\\"%s\\\" não existe! Digite novamente.\" % (nome_arquivo)\n nome_arquivo = raw_input(\"Digite o nome do arquivo: \" + diretorio_maquinas)\n \n # instancia a maquina de mealy passando um dicionario como parametro pro construtor da classe\n m = maq_mealy(file=diretorio_maquinas + nome_arquivo)\n\nelif opcao == 1:\n config = {}\n config['nome'] = raw_input(\"Nome da Máquina de Mealy: \")\n config['tipo'] = 'mealy'\n config['informacoes'] = \"Máquina de Mealy de testes\"\n config['num_estados'] = int(raw_input(\"Número de estados: \"))\n config['alfabeto_entrada'] = []\n config['alfabeto_saida'] = []\n config['estados_finais'] = [] \n config['transicoes'] = []\n \n num_alfabeto_entrada = int(raw_input(\"Quantidade de caracteres do alfabeto de entrada: \"))\n num_alfabeto_saida = int(raw_input(\"Quantidade de caracteres do alfabeto de saida: \"))\n num_estados_finais = int(raw_input(\"Quantidade de estados finais: \"))\n num_transicoes = num_alfabeto_entrada * config['num_estados']\n \n for i in range(num_alfabeto_entrada):\n config['alfabeto_entrada'].append(raw_input(\"Caractere de entrada %s: \" % str(i + 1)))\n\n for i in range(num_alfabeto_saida):\n config['alfabeto_saida'].append(raw_input(\"Caractere de saida %s: \" % str(i + 1)))\n\n for i in range(num_estados_finais):\n config['estados_finais'].append(raw_input(\"Estado finais (maximo %d): \" % int(config['num_estados']-1)))\n \n config['estado_inicial'] = int(raw_input(\"Estado inicial: \"))\n \n print \"Transições:\"\n for i in range(num_transicoes):\n print \"\\n=> Transição %d\" % i\n estado = int(raw_input(\"Número do estado: \"))\n leitura = raw_input(\"Quando lê: \")\n proximo = int(raw_input(\"Vai para o estado: \"))\n saida = raw_input(\"E escreve: \")\n \n # adiciona a transicao na matriz de transicoes\n config['transicoes'].append( [estado, leitura, proximo, saida] )\n \n # instancia a maquina de mealy passando um dicionario como parametro pro construtor da classe \n m = maq_mealy(config=config)\n\n# fim da entrada de dados\n\n# imprime informacoes na maquina de mealy \ninfo = m.get_info()\nprint '\\nNome: %s' % (info['nome'])\nprint 'Descrição: %s' % (info['info'])\n\n# recebe uma string que sera a entrada da maquina de mealy e a executa\nw = raw_input(\"\\nString de entrada: \")\nm.executa(w)\n\n# se a validacao da maquina de turing obteve sucesso, mostra passo a passo e outras opções\n\nif m.sucesso():\n print \"\\nPasso a passo:\"\n print m.get_pap()\n\n print \"Entrada : %s\" % m.get_entrada()\n print \"Output : %s\" % m.get_output()\n\n if m.aceita():\n print \"\\n => A string foi aceita. A máquina parou no estado final q%d e percorreu toda a entrada.\\n\" % m.get_estado_atual()\n else:\n print \"\\n => A string foi rejeitada. Parou no estado q%d e na posição %d (de %d) da entrada.\\n\" % (m.get_estado_atual(), m.get_posicao(), len(m.get_entrada()))\n\n #\n # opcoes de gravar em arquivo e salvar imagem PNG da maquina (utilizando graphviz)\n #\n \n opcao_gravar = raw_input(\"Deseja salvar a máquina de mealy em um arquivo? (s/n) \")\n if opcao_gravar in opcao_sim:\n arquivo_out = raw_input(\"Nome do arquivo de saída: \" + diretorio_maquinas)\n \n if os.path.isfile(diretorio_maquinas + arquivo_out):\n confirma = raw_input(\"O arquivo já existe, deseja sobrescreve-lo? (s/n) \")\n if confirma in opcao_sim:\n m.gravar_arquivo(diretorio_maquinas + arquivo_out)\n else:\n m.gravar_arquivo(diretorio_maquinas + arquivo_out)\n\n opcao_gravar = raw_input(\"Deseja salvar uma representação (PNG) da máquina de mealy? (s/n) \")\n if opcao_gravar in opcao_sim:\n arquivo_out = raw_input(\"Nome do arquivo de saída (ex: mealy): \" + diretorio_imagens )\n \n if os.path.isfile(diretorio_imagens + arquivo_out):\n confirma = raw_input(\"O arquivo já existe, deseja sobrescreve-lo? (s/n) \")\n if confirma in opcao_sim:\n m.gravar_imagem(diretorio_imagens + arquivo_out)\n else:\n m.gravar_imagem(diretorio_imagens + arquivo_out)\n\n print \"\\nExecute o comando abaixo para gerar a imagem da máquina de mealy (na pasta de imagens):\"\n print \"$ dot -T png -o %s.png %s.dot && rm %s.dot\" % (diretorio_imagens + arquivo_out, diretorio_imagens + arquivo_out, diretorio_imagens + arquivo_out)\n \n \n# se a validacao da maquina de mealy não obteve sucesso, mostra o erro\n \nelse:\n print m.get_erro()\n\n"
}
] | 6
|
barkmadley/hivery-backend-challenge
|
https://github.com/barkmadley/hivery-backend-challenge
|
6cd079d34e0a9af7a7cf673a981675cb77853315
|
f1a964367db8300816d8ebbdb08f6f508fa54b06
|
88ea5ad6a6d7a085ff20a07e82e4401f6841ba04
|
refs/heads/master
| 2020-06-21T23:00:45.275178
| 2019-07-24T12:48:34
| 2019-07-24T12:51:08
| 197,572,682
| 0
| 0
| null | 2019-07-18T11:19:12
| 2019-05-28T04:53:58
| 2019-02-19T12:37:43
| null |
[
{
"alpha_fraction": 0.6022904515266418,
"alphanum_fraction": 0.6043727397918701,
"avg_line_length": 38.20408248901367,
"blob_id": "21a61e6970275bd735b16222783f3d4670ec0d81",
"content_id": "50d7c326f260836c923bdb58175b5229da144663",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1921,
"license_type": "no_license",
"max_line_length": 86,
"num_lines": 49,
"path": "/mongo_db.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from typing import List\n\nfrom paranuara.company import Company, company_from_json, json_from_company\nfrom paranuara.db import CompanyNotFound, ParanuaraDB, PersonNotFound\nfrom paranuara.person import Person, json_from_person, person_from_json\n\n\nclass MongoDB(ParanuaraDB):\n def __init__(self, companies: List[Company], people: List[Person], mongo) -> None:\n self.mongo = mongo\n for company in companies:\n company_dict = json_from_company(company)\n self.mongo.db.company.replace_one(\n {\"index\": company_dict[\"index\"]}, company_dict, upsert=True\n )\n for person in people:\n person_dict = json_from_person(person)\n self.mongo.db.person.replace_one(\n {\"_id\": person_dict[\"_id\"]}, person_dict, upsert=True\n )\n # TODO: setup index: company.index\n # TODO: setup index: person.index\n # TODO: setup index: person.company_id\n\n def fetch_company_by_id(self, company_id: int) -> Company:\n results = list(self.mongo.db.company.find({\"index\": company_id}))\n if len(results) == 0:\n raise CompanyNotFound\n else:\n return company_from_json(results[0])\n\n def fetch_people_by_company_id(self, company_id: int) -> List[Person]:\n return [\n person_from_json(result)\n for result in self.mongo.db.person.find({\"company_id\": company_id})\n ]\n\n def fetch_person_by_id(self, person_id: int) -> Person:\n results = list(self.mongo.db.person.find({\"index\": person_id}))\n if len(results) == 0:\n raise PersonNotFound\n else:\n return person_from_json(results[0])\n\n def fetch_people_by_ids(self, person_ids: List[int]) -> List[Person]:\n return [\n person_from_json(result)\n for result in self.mongo.db.person.find({\"index\": {\"$in\": person_ids}})\n ]\n"
},
{
"alpha_fraction": 0.6683168411254883,
"alphanum_fraction": 0.6683168411254883,
"avg_line_length": 33.82758712768555,
"blob_id": "4b8c4fad6f31721234d45b77293a895103ae74a8",
"content_id": "c47600c302e9962e282db08a324a11e74e5348c4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1010,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 29,
"path": "/in_memory_db.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from typing import List\n\nfrom paranuara.company import Company\nfrom paranuara.db import CompanyNotFound, ParanuaraDB, PersonNotFound\nfrom paranuara.person import Person\n\n\nclass InMemoryDB(ParanuaraDB):\n def __init__(self, companies: List[Company], people: List[Person]) -> None:\n self.companies = companies\n self.people = people\n\n def fetch_company_by_id(self, company_id: int) -> Company:\n try:\n return self.companies[company_id]\n except IndexError:\n raise CompanyNotFound\n\n def fetch_people_by_company_id(self, company_id: int) -> List[Person]:\n return [person for person in self.people if person.company_id == company_id]\n\n def fetch_person_by_id(self, person_id: int) -> Person:\n try:\n return self.people[person_id]\n except IndexError:\n raise PersonNotFound\n\n def fetch_people_by_ids(self, person_ids: List[int]) -> List[Person]:\n return [self.people[person_id] for person_id in person_ids]\n"
},
{
"alpha_fraction": 0.6525198817253113,
"alphanum_fraction": 0.6525198817253113,
"avg_line_length": 24.133333206176758,
"blob_id": "0998c4713b0eb6e12515d17356de26ee604a47d0",
"content_id": "1b3e4ce728e5fd1d6b57ed4434d5f9b928c66058",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 377,
"license_type": "no_license",
"max_line_length": 85,
"num_lines": 15,
"path": "/cli_util.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "import os\n\ndef open_file(path):\n path = os.path.realpath(path)\n return open(path)\n\ndef add_companies_arg(parser):\n parser.add_argument(\n \"--companies\", metavar=\"file\", type=open_file, help=\"companies.json filename\"\n )\n\ndef add_people_arg(parser):\n parser.add_argument(\n \"--people\", metavar=\"file\", type=open_file, help=\"people.json filename\"\n )\n"
},
{
"alpha_fraction": 0.48838695883750916,
"alphanum_fraction": 0.5071383118629456,
"avg_line_length": 25.664772033691406,
"blob_id": "d1de68a7ba2eaab60020fecc4254c6736760dd0f",
"content_id": "bb5af4929bd6d0e7f5a9382ad313a5615eb6cbfa",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4693,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 176,
"path": "/paranuara/person.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from datetime import datetime\nfrom decimal import Decimal\nfrom typing import Any, Dict, List, NamedTuple, Optional\n\nPerson = NamedTuple(\n \"Person\",\n [\n (\"id\", int),\n (\"mongo_id\", str),\n (\"guid\", str),\n (\"has_died\", bool),\n (\"balance\", Decimal),\n (\"picture\", str),\n (\"age\", int),\n (\"eye_color\", str),\n (\"name\", str),\n (\"gender\", str),\n (\"company_id\", Optional[int]),\n (\"email\", str),\n (\"phone\", str),\n (\"address\", str),\n (\"about\", str),\n (\"registered\", datetime),\n (\"tags\", List[str]),\n (\"friends\", List[int]),\n (\"greeting\", str),\n (\"favourite_food\", List[str]),\n ],\n)\n\n\ndef json_from_datetime(datetime: datetime) -> str:\n return str(datetime)\n\n\ndef datetime_from_json(str: str) -> datetime:\n return datetime.fromisoformat(str)\n\n\ndef decimal_from_json(str: str) -> Decimal:\n return Decimal(str.replace(\"$\", \"\").replace(\",\", \"\"))\n\n\ndef json_from_decimal(dec: Decimal) -> str:\n return str(dec)\n\n\ndef friend_index_from_json(dict) -> int:\n return dict[\"index\"]\n\n\ndef json_from_friend_index(index: int) -> Dict[str, int]:\n return {\"index\": index}\n\n\ndef friends_list_from_json(array) -> List[int]:\n return [friend_index_from_json(dict) for dict in array]\n\n\ndef json_from_friends_list(array: List[int]) -> List[Dict[str, int]]:\n return [json_from_friend_index(index) for index in array]\n\n\n# All foods seen in the given people.json\nALL_FOODS = {\n \"banana\",\n \"orange\",\n \"celery\",\n \"strawberry\",\n \"cucumber\",\n \"beetroot\",\n \"apple\",\n \"carrot\",\n}\n\n# All known vegetables + lettuce which was in the README.md file\nVEGETABLES = {\"celery\", \"beetroot\", \"cucumber\", \"carrot\", \"lettuce\"}\n\nFRUITS = {\"banana\", \"orange\", \"strawberry\", \"apple\"}\n\n\ndef vegetables_from_foods(foods):\n return [food for food in foods if food in VEGETABLES]\n\n\ndef fruits_from_foods(foods):\n return [food for food in foods if food in FRUITS]\n\n\ndef person_from_json(dict) -> Person:\n \"\"\"\n Example person json:\n {\n \"_id\": \"595eeb9b96d80a5bc7afb106\",\n \"index\": 0,\n \"guid\": \"5e71dc5d-61c0-4f3b-8b92-d77310c7fa43\",\n \"has_died\": true,\n \"balance\": \"$2,418.59\",\n \"picture\": \"http://placehold.it/32x32\",\n \"age\": 61,\n \"eyeColor\": \"blue\",\n \"name\": \"Carmella Lambert\",\n \"gender\": \"female\",\n \"company_id\": 58,\n \"email\": \"carmellalambert@earthmark.com\",\n \"phone\": \"+1 (910) 567-3630\",\n \"address\": \"628 Sumner Place, Sperryville, American Samoa, 9819\",\n \"about\": \"...\",\n \"registered\": \"2016-07-13T12:29:07 -10:00\",\n \"tags\": [\n \"id\",\n \"quis\",\n \"ullamco\",\n \"consequat\",\n \"laborum\",\n \"sint\",\n \"velit\"\n ],\n \"friends\": [\n {\n \"index\": 0\n },\n {\n \"index\": 1\n },\n {\n \"index\": 2\n }\n ],\n \"greeting\": \"Hello, Carmella Lambert! You have 6 unread messages.\",\n \"favouriteFood\": [\n \"orange\",\n \"apple\",\n \"banana\",\n \"strawberry\"\n ]\n }\n \"\"\"\n return Person(\n id=dict[\"index\"],\n mongo_id=dict[\"_id\"],\n guid=dict[\"guid\"],\n has_died=dict[\"has_died\"],\n balance=decimal_from_json(dict[\"balance\"]),\n picture=dict[\"picture\"],\n age=dict[\"age\"],\n eye_color=dict[\"eyeColor\"],\n name=dict[\"name\"],\n gender=dict[\"gender\"],\n company_id=dict.get(\"company_id\"),\n email=dict[\"email\"],\n phone=dict[\"phone\"],\n address=dict[\"address\"],\n about=dict[\"about\"],\n registered=datetime_from_json(dict[\"registered\"]),\n tags=dict[\"tags\"],\n friends=friends_list_from_json(dict[\"friends\"]),\n greeting=dict[\"greeting\"],\n favourite_food=dict[\"favouriteFood\"],\n )\n\n\ndef json_from_person(person: Person) -> Dict[str, Any]:\n dict = person._asdict()\n dict[\"_id\"] = dict[\"mongo_id\"]\n del dict[\"mongo_id\"]\n dict[\"index\"] = dict[\"id\"]\n del dict[\"id\"]\n dict[\"eyeColor\"] = dict[\"eye_color\"]\n del dict[\"eye_color\"]\n dict[\"favouriteFood\"] = dict[\"favourite_food\"]\n del dict[\"favourite_food\"]\n dict[\"balance\"] = json_from_decimal(dict[\"balance\"])\n dict[\"friends\"] = json_from_friends_list(dict[\"friends\"])\n dict[\"registered\"] = json_from_datetime(dict[\"registered\"])\n return dict\n"
},
{
"alpha_fraction": 0.658823549747467,
"alphanum_fraction": 0.6784313917160034,
"avg_line_length": 27.22222137451172,
"blob_id": "63d0e8baf27ee3759160503933e04e8f7b535661",
"content_id": "d87c8712a585a0c6d600181f0f092f2bc498b9e5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 255,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 9,
"path": "/config.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "class BaseConfig:\n COMPANIES_FILE = \"resources/companies.json\"\n PEOPLE_FILE = \"resources/people.json\"\n DB = \"inmemory\"\n\nclass DevConfig(BaseConfig):\n DEVELOPMENT = True\n # DB = \"mongo\"\n MONGO_URI = \"mongodb://localhost:27017/paranuara\"\n\n"
},
{
"alpha_fraction": 0.6551437973976135,
"alphanum_fraction": 0.6603982448577881,
"avg_line_length": 30.172412872314453,
"blob_id": "dea84d02f50783abf610e831a2bcce04b7cb5eca",
"content_id": "86d8356366699ef10d89c6d2319a2476f12a2948",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3616,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 116,
"path": "/flaskr.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "import json\nimport os\nfrom typing import Any, Dict, List\n\nfrom flanker.addresslib import address\nfrom flask import Flask, abort, jsonify\nfrom flask_pymongo import PyMongo\n\nfrom in_memory_db import InMemoryDB\nfrom mongo_db import MongoDB\nfrom paranuara.company import Company, company_from_json\nfrom paranuara.db import CompanyNotFound, PersonNotFound\nfrom paranuara.person import (\n Person,\n fruits_from_foods,\n json_from_person,\n person_from_json,\n vegetables_from_foods,\n)\nfrom paranuara.query import JoinPeopleResponse, ParanuaraQuery\n\n\ndef json_from_join_people_response(\n join_people_response: JoinPeopleResponse\n) -> Dict[str, Any]:\n return {\n \"person1\": json_from_person(join_people_response.person1),\n \"person2\": json_from_person(join_people_response.person2),\n \"friends_in_common\": [\n json_from_person(person)\n for person in join_people_response.friends_in_common\n ],\n }\n\n\ndef person_to_simple_json(person: Person) -> Dict[str, Any]:\n email = address.parse(person.email)\n username = None\n if email:\n username = email.mailbox\n return {\n \"username\": username,\n \"age\": str(person.age),\n \"fruits\": fruits_from_foods(person.favourite_food),\n \"vegetables\": vegetables_from_foods(person.favourite_food),\n }\n\n\nclass DBNotConfigured(Exception):\n pass\n\n\ndef init_db(companies: List[Company], people: List[Person], app):\n if app.config[\"DB\"] == \"inmemory\":\n return InMemoryDB(companies, people)\n elif app.config[\"DB\"] == \"mongo\":\n assert app.config[\"MONGO_URI\"]\n return MongoDB(companies, people, PyMongo(app))\n raise DBNotConfigured()\n\n\ndef create_app(test_config=None):\n # create and configure the app\n app = Flask(__name__, instance_relative_config=True)\n app.config.from_mapping(\n SECRET_KEY=\"dev\", DATABASE=os.path.join(app.instance_path, \"flaskr.sqlite\")\n )\n\n if test_config is None:\n # load the instance config, if it exists, when not testing\n app.config.from_object(\"config.DevConfig\")\n else:\n # load the test config if passed in\n app.config.from_mapping(test_config)\n\n # ensure the instance folder exists\n try:\n os.makedirs(app.instance_path)\n except OSError:\n pass\n\n companies_json = json.load(open(app.config[\"COMPANIES_FILE\"]))\n companies = [company_from_json(company_dict) for company_dict in companies_json]\n\n people_json = json.load(open(app.config[\"PEOPLE_FILE\"]))\n people = [person_from_json(person_dict) for person_dict in people_json]\n\n db = init_db(companies, people, app)\n query = ParanuaraQuery(db=db)\n\n @app.route(\"/company/<int:company_id>/employees\")\n def company_employees(company_id):\n try:\n people = query.query_company_employees(company_id)\n json = [json_from_person(person) for person in people]\n return jsonify(json)\n except CompanyNotFound:\n return abort(404)\n\n @app.route(\"/person/<int:person_id>\")\n def person(person_id):\n try:\n result = query.query_person(person_id)\n return jsonify(person_to_simple_json(result))\n except PersonNotFound:\n return abort(404)\n\n @app.route(\"/person/<int:person1_id>/friends_join/<int:person2_id>\")\n def friends_join(person1_id, person2_id):\n try:\n query_result = query.query_join_friends(person1_id, person2_id)\n return jsonify(json_from_join_people_response(query_result))\n except PersonNotFound:\n raise abort(404)\n\n return app\n"
},
{
"alpha_fraction": 0.665764570236206,
"alphanum_fraction": 0.665764570236206,
"avg_line_length": 27.423076629638672,
"blob_id": "6b7d2866d0a6f2b9e9c2f0c137fef3e4a285b8ec",
"content_id": "58a371fe84c30e170585c0314368846980d87c10",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 739,
"license_type": "no_license",
"max_line_length": 68,
"num_lines": 26,
"path": "/paranuara/db.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from typing import Callable, List\n\nfrom paranuara.company import Company\nfrom paranuara.person import Person\n\n\nclass CompanyNotFound(Exception):\n pass\n\n\nclass PersonNotFound(Exception):\n pass\n\n\nclass ParanuaraDB:\n def __init__(\n self,\n fetch_company_by_id: Callable[[int], Company],\n fetch_people_by_company_id: Callable[[int], List[Person]],\n fetch_person_by_id: Callable[[int], Person],\n fetch_people_by_ids: Callable[[List[int]], List[Person]],\n ) -> None:\n self.fetch_company_by_id = fetch_company_by_id\n self.fetch_people_by_company_id = fetch_people_by_company_id\n self.fetch_person_by_id = fetch_person_by_id\n self.fetch_people_by_ids = fetch_people_by_ids\n"
},
{
"alpha_fraction": 0.5415636897087097,
"alphanum_fraction": 0.5567288398742676,
"avg_line_length": 32.09293746948242,
"blob_id": "e68fef2707f7e9277e93bc6da84ce7df6565a62c",
"content_id": "1c4998034e0560439efb140e6748cfe6abe75fde",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 8902,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 269,
"path": "/paranuara/query_test.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from datetime import datetime\nfrom decimal import Decimal\nfrom unittest import TestCase\n\nfrom paranuara.company import Company\nfrom paranuara.db import CompanyNotFound, ParanuaraDB, PersonNotFound\nfrom paranuara.person import Person\nfrom paranuara.query import JoinPeopleResponse, ParanuaraQuery\n\n\ndef generate_person(id=None, eye_color=\"red\", has_died=False, friends=[]):\n return Person(\n id=id,\n mongo_id=\"mongo_id\",\n guid=\"guid\",\n has_died=has_died,\n balance=Decimal(),\n picture=\"picture\",\n age=10,\n eye_color=eye_color,\n name=\"name\",\n gender=\"gender\",\n company_id=None,\n email=\"email\",\n phone=\"phone\",\n address=\"address\",\n about=\"about\",\n registered=datetime.now(),\n tags=[\"tags\"],\n friends=friends,\n greeting=\"greeting\",\n favourite_food=[\"favouriteFoods\"],\n )\n\n\nclass ParanuaraQueryTest_query_company_employees(TestCase):\n def test_has_employees(self):\n person1 = generate_person(id=1)\n company = Company(id=0, name=\"test\")\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=lambda id: company,\n fetch_people_by_company_id=lambda id: [person1],\n fetch_people_by_ids=None,\n fetch_person_by_id=None,\n )\n )\n\n result = query.query_company_employees(company_id=0)\n\n self.assertEqual(result, [person1])\n\n def test_no_employees(self):\n company = Company(id=0, name=\"test\")\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=lambda id: company,\n fetch_people_by_company_id=lambda id: [],\n fetch_people_by_ids=None,\n fetch_person_by_id=None,\n )\n )\n\n result = query.query_company_employees(company_id=0)\n\n self.assertEqual(result, [])\n\n def test_no_company(self):\n def fetch_company_by_id(id):\n raise CompanyNotFound()\n\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=fetch_company_by_id,\n fetch_people_by_company_id=lambda id: [],\n fetch_people_by_ids=None,\n fetch_person_by_id=None,\n )\n )\n\n with self.assertRaises(CompanyNotFound):\n query.query_company_employees(company_id=0)\n\n\nclass ParanuaraQueryTest_query_person(TestCase):\n def test_not_found(self):\n def fetch_person_by_id(id):\n raise PersonNotFound()\n\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=None,\n fetch_person_by_id=fetch_person_by_id,\n )\n )\n\n with self.assertRaises(PersonNotFound):\n query.query_person(person_id=0)\n\n def test_found(self):\n person = generate_person(0)\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=None,\n fetch_person_by_id=lambda id: person,\n )\n )\n\n result = query.query_person(person_id=0)\n\n self.assertEqual(result, person)\n\n\nclass ParanuaraQueryTest_query_join_friends(TestCase):\n def test_person1_not_found(self):\n def fetch_person_by_id(id):\n if id == 1:\n raise PersonNotFound()\n else:\n return generate_person(2)\n\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=None,\n fetch_person_by_id=fetch_person_by_id,\n )\n )\n\n with self.assertRaises(PersonNotFound):\n query.query_join_friends(person1_id=1, person2_id=2)\n\n def test_person2_not_found(self):\n def fetch_person_by_id(id):\n if id == 2:\n raise PersonNotFound()\n return generate_person(1)\n\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=None,\n fetch_person_by_id=fetch_person_by_id,\n )\n )\n with self.assertRaises(PersonNotFound):\n query.query_join_friends(person1_id=1, person2_id=2)\n\n def test_no_friends(self):\n person1 = generate_person(1)\n person2 = generate_person(2)\n people = {1: person1, 2: person2}\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=lambda ids: [people.get(id) for id in ids],\n fetch_person_by_id=lambda id: people.get(id),\n )\n )\n\n result = query.query_join_friends(person1_id=1, person2_id=2)\n\n self.assertEqual(\n result,\n JoinPeopleResponse(person1=person1, person2=person2, friends_in_common=[]),\n )\n\n def test_1_friend_in_common(self):\n person1 = generate_person(1, friends=[3])\n person2 = generate_person(2, friends=[3])\n friend_in_common = generate_person(3, eye_color=\"brown\", has_died=False)\n people = {1: person1, 2: person2, 3: friend_in_common}\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=lambda ids: [people.get(id) for id in ids],\n fetch_person_by_id=lambda id: people.get(id),\n )\n )\n\n result = query.query_join_friends(person1_id=1, person2_id=2)\n\n self.assertEqual(\n result,\n JoinPeopleResponse(\n person1=person1, person2=person2, friends_in_common=[friend_in_common]\n ),\n )\n\n def test_intersection(self):\n person1 = generate_person(1, friends=[3, 4])\n person2 = generate_person(2, friends=[3, 5])\n friend_in_common = generate_person(3, eye_color=\"brown\", has_died=False)\n friend_of_person1 = generate_person(4, eye_color=\"brown\", has_died=False)\n friend_of_person2 = generate_person(5, eye_color=\"brown\", has_died=False)\n people = {\n 1: person1,\n 2: person2,\n 3: friend_in_common,\n 4: friend_of_person1,\n 5: friend_of_person2,\n }\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=lambda ids: [people.get(id) for id in ids],\n fetch_person_by_id=lambda id: people.get(id),\n )\n )\n\n result = query.query_join_friends(person1_id=1, person2_id=2)\n\n self.assertEqual(\n result,\n JoinPeopleResponse(\n person1=person1, person2=person2, friends_in_common=[friend_in_common]\n ),\n )\n\n def test_eye_color_filter(self):\n person1 = generate_person(1, friends=[3])\n person2 = generate_person(2, friends=[3])\n friend_in_common = generate_person(3, eye_color=\"black\", has_died=False)\n people = {1: person1, 2: person2, 3: friend_in_common}\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=lambda ids: [people.get(id) for id in ids],\n fetch_person_by_id=lambda id: people.get(id),\n )\n )\n\n result = query.query_join_friends(person1_id=1, person2_id=2)\n\n self.assertEqual(\n result,\n JoinPeopleResponse(person1=person1, person2=person2, friends_in_common=[]),\n )\n\n def test_has_died_filter(self):\n person1 = generate_person(1, friends=[3])\n person2 = generate_person(2, friends=[3])\n friend_in_common = generate_person(3, eye_color=\"brown\", has_died=True)\n people = {1: person1, 2: person2, 3: friend_in_common}\n query = ParanuaraQuery(\n db=ParanuaraDB(\n fetch_company_by_id=None,\n fetch_people_by_company_id=None,\n fetch_people_by_ids=lambda ids: [people.get(id) for id in ids],\n fetch_person_by_id=lambda id: people.get(id),\n )\n )\n\n result = query.query_join_friends(person1_id=1, person2_id=2)\n\n self.assertEqual(\n result,\n JoinPeopleResponse(person1=person1, person2=person2, friends_in_common=[]),\n )\n"
},
{
"alpha_fraction": 0.7039337754249573,
"alphanum_fraction": 0.7039337754249573,
"avg_line_length": 23.149999618530273,
"blob_id": "2f0342966c438d9f7bf974ea79ea70a498e25a1b",
"content_id": "705827f9088a431ddec78078d5bdd1091aa87a37",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 483,
"license_type": "no_license",
"max_line_length": 71,
"num_lines": 20,
"path": "/process_companies_json.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "import json\nimport os\nfrom argparse import ArgumentParser\n\nfrom paranuara.company import company_from_json\nfrom cli_util import add_companies_arg\n\n\ndef main():\n parser = ArgumentParser(description=\"Process companies.json files\")\n add_companies_arg(parser)\n args = parser.parse_args()\n companies = json.load(args.companies)\n for company_dict in companies:\n company = company_from_json(company_dict)\n print(company)\n\n\nif __name__ == \"__main__\":\n main()\n"
},
{
"alpha_fraction": 0.5326315760612488,
"alphanum_fraction": 0.5347368717193604,
"avg_line_length": 21.619047164916992,
"blob_id": "fbd251073ad757b8e6bf77c10e2ec61e6f1ea554",
"content_id": "a1bcf7d6f70092a62e1d9f1f4906d642d603f04c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 475,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 21,
"path": "/paranuara/company.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from typing import Any, Dict, NamedTuple\n\nCompany = NamedTuple(\"Company\", [(\"id\", int), (\"name\", str)])\n\n\ndef company_from_json(dict):\n \"\"\"\n Example company json:\n {\n \"index\": 0, ==> id\n \"company\": \"NETBOOK\" ==> name\n }\n \"\"\"\n return Company(id=dict[\"index\"], name=dict[\"company\"])\n\n\ndef json_from_company(company: Company) -> Dict[str, Any]:\n return {\n \"index\": company.id,\n \"company\": company.name,\n }\n"
},
{
"alpha_fraction": 0.6635622978210449,
"alphanum_fraction": 0.6635622978210449,
"avg_line_length": 25.84375,
"blob_id": "6f09f94e05add75bb8c131dbe35e3c55b37a5582",
"content_id": "0e46801e6b7d0d69a83d75bfd45531478fae524e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 859,
"license_type": "no_license",
"max_line_length": 68,
"num_lines": 32,
"path": "/process_persons_json.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "import json\nimport os\nfrom argparse import ArgumentParser\n\nfrom flanker.addresslib import address\n\nfrom paranuara.person import person_from_json\nfrom cli_util import add_people_arg\n\n\ndef main():\n parser = ArgumentParser(description=\"Process people.json files\")\n add_people_arg(parser)\n args = parser.parse_args()\n people = json.load(args.people)\n foods = set()\n email_domains = set()\n email_usernames = set()\n for person_dict in people:\n person = person_from_json(person_dict)\n foods |= set(person.favourite_food)\n email_parsed = address.parse(person.email)\n if email_parsed:\n email_usernames |= set([email_parsed.mailbox])\n email_domains |= set([email_parsed.hostname])\n print(foods)\n print(email_domains)\n print(len(email_usernames))\n\n\nif __name__ == \"__main__\":\n main()\n"
},
{
"alpha_fraction": 0.7340946197509766,
"alphanum_fraction": 0.7373572587966919,
"avg_line_length": 19.433332443237305,
"blob_id": "233bb5799007cd2623cf92a93da206ee47c8c556",
"content_id": "952852db89704378a737410bb92b3acce6a4af66",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 613,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 30,
"path": "/Makefile",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": ".PHONY: setup\nsetup:\n\t# Requires python 3\n\tvirtualenv .venv -p `which python3`\n\t@echo \"Please run 'source .venv/bin/activate' to enter virtualenv for subsequent commands\"\n\n.PHONY: find-dep\nfind-deps:\n\tpip install pip-tools\n\tpip-compile\n\n.PHONY: dep\ndep:\n\tpip install -r requirements.txt\n\n.PHONY: test\ntest:\n\tPYTHONPATH=${PYTHONPATH}:. python -m unittest discover -p \"*_test.py\"\n\n.PHONY: typecheck\ntypecheck:\n\tPYTHONPATH=${PYTHONPATH}:. mypy . --ignore-missing-imports\n\n.PHONY: lint\nlint:\n\tPYTHONPATH=${PYTHONPATH}:. pyflakes paranuara\n\n.PHONY: run\nrun:\n\tPYTHONPATH=${PYTHONPATH}:. FLASK_ENV=development flask run\n"
},
{
"alpha_fraction": 0.6343449354171753,
"alphanum_fraction": 0.6447076201438904,
"avg_line_length": 32.775001525878906,
"blob_id": "8f455b3f80e7efb5aedc5bb32f45e109e84f0c28",
"content_id": "fd430b79efdf572acb84cd92f22d6e6d0d3fc8ed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1351,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 40,
"path": "/paranuara/query.py",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "from typing import List, NamedTuple\n\nfrom paranuara.db import ParanuaraDB\nfrom paranuara.person import Person\n\nJoinPeopleResponse = NamedTuple(\n \"JoinPeopleResponse\",\n [(\"person1\", Person), (\"person2\", Person), (\"friends_in_common\", List[Person])],\n)\n\n\nclass ParanuaraQuery:\n def __init__(self, db: ParanuaraDB) -> None:\n self.db = db\n\n def query_company_employees(self, company_id: int) -> List[Person]:\n company = self.db.fetch_company_by_id(company_id)\n return self.db.fetch_people_by_company_id(company.id)\n\n def query_join_friends(\n self, person1_id: int, person2_id: int\n ) -> JoinPeopleResponse:\n person1 = self.db.fetch_person_by_id(person1_id)\n person2 = self.db.fetch_person_by_id(person2_id)\n friend_ids_in_common = set(person1.friends) & set(person2.friends)\n friends_in_common_full = self.db.fetch_people_by_ids(list(friend_ids_in_common))\n\n friends_in_common = [\n friend\n for friend in friends_in_common_full\n if friend.eye_color == \"brown\"\n and not friend.has_died\n ]\n\n return JoinPeopleResponse(\n person1=person1, person2=person2, friends_in_common=friends_in_common\n )\n\n def query_person(self, person_id: int) -> Person:\n return self.db.fetch_person_by_id(person_id)\n"
},
{
"alpha_fraction": 0.6962763667106628,
"alphanum_fraction": 0.7198294997215271,
"avg_line_length": 27.94805145263672,
"blob_id": "2604aedc7c44256265de9647816723a7f1df907a",
"content_id": "8a6a4bc7b72551ba67fe9866773c95170cc49f79",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 4458,
"license_type": "no_license",
"max_line_length": 513,
"num_lines": 154,
"path": "/README.md",
"repo_name": "barkmadley/hivery-backend-challenge",
"src_encoding": "UTF-8",
"text": "# Setup Instructions:\n\n### 0. First time setup\n\nThis python application depends on python3.\n\n```\n$ make setup\nPlease run 'source .venv/bin/activate' to enter virtualenv for subsequent commands\n```\n\n### Install python dependencies\n\n```\n(.venv) $ make dep\n...\nSuccessfully intalled appdirs-1.4.3 ... werkzeug-0.15.5\n```\n\n### Testing\n\n```\n(.venv) $ make typecheck lint test\n```\n\n### Running the server\n\n```\n(.venv) $ make run\n```\n\n# Configuration options\n\n## Configuring the location of the companies/people JSON files\n\nModify the lines in `config.py` that set the constants `COMPANIES_FILE` and `PEOPLE_FILE`\n\n## Configuring the database\n\nModify the lines in `config.py` that set `DB` and `MONGO_URI`.\n\nSetting `DB` to `\"mongo\"` will load the json blobs into the mongo specified by\n`MONGO_URI` and then serve the requests from that DB.\n\nOnly a little bit of time has been spent optmising the mongo backend.\n\nSetting `DB` to `\"inmemory\"` will load the json blobs into memory and just do\nindex based lookups\n\n# Manual Testing\n\n```\n$ curl http://localhost:5000/company/1/employees | jq length\n7\n```\n\n```\n$ curl http://localhost:5000/person/1\n{\n \"age\": \"60\",\n \"fruits\": [],\n \"username\": \"deckermckenzie\",\n \"vegetables\": [\n \"cucumber\",\n \"beetroot\",\n \"carrot\",\n \"celery\"\n ]\n}\n```\n\n```\n$ curl http://localhost:5000/person/1/friends_join/10\n{\n \"friends_in_common\": [\n {\n ...\n \"email\": \"deckermckenzie@earthmark.com\",\n ...\n }\n ]\n \"person1\": {\n ...\n \"email\": \"deckermckenzie@earthmark.com\",\n ...\n }\n \"person2\": {\n ...\n \"email\": \"kathleenclarke@earthmark.com\",\n ...\n }\n}\n```\n\n```\n$ curl http://localhost:5000/company/arbitrary/employees\n404\n```\n\n```\n$ curl http://localhost:5000/company/100000/employees\n404\n```\n\n```\n$ curl http://localhost:5000/person/100000\n404\n```\n\n```\n$ curl http://localhost:5000/person/arbitrary\n404\n```\n\n```\n$ curl http://localhost:5000/person/10000/friends_join/10\n404\n```\n\n```\n$ curl http://localhost:5000/person/1/friends_join/100000\n404\n```\n\n# Paranuara Challenge\n\nParanuara is a class-m planet. Those types of planets can support human life, for that reason the president of the Checktoporov decides to send some people to colonise this new planet and\nreduce the number of people in their own country. After 10 years, the new president wants to know how the new colony is growing, and wants some information about his citizens. Hence he hired you to build a rest API to provide the desired information.\n\nThe government from Paranuara will provide you two json files (located at resource folder) which will provide information about all the citizens in Paranuara (name, age, friends list, fruits and vegetables they like to eat...) and all founded companies on that planet.\nUnfortunately, the systems are not that evolved yet, thus you need to clean and organise the data before use.\nFor example, instead of providing a list of fruits and vegetables their citizens like, they are providing a list of favourite food, and you will need to split that list (please, check below the options for fruits and vegetables).\n\n## New Features\n\nYour API must provides these end points:\n\n- Given a company, the API needs to return all their employees. Provide the appropriate solution if the company does not have any employees.\n- Given 2 people, provide their information (Name, Age, Address, phone) and the list of their friends in common which have brown eyes and are still alive.\n- Given 1 people, provide a list of fruits and vegetables they like. This endpoint must respect this interface for the output: `{\"username\": \"Ahi\", \"age\": \"30\", \"fruits\": [\"banana\", \"apple\"], \"vegetables\": [\"beetroot\", \"lettuce\"]}`\n\n## Delivery\n\nTo deliver your system, you need to send the link on GitHub. Your solution must provide tasks to install dependencies, build the system and run. Solutions that does not fit this criteria **will not be accepted** as a solution. Assume that we have already installed in our environment Java, Ruby, Node.js, Python, MySQL, MongoDB and Redis; any other technologies required must be installed in the install dependencies task. Moreover well tested and designed systems are one of the main criteria of this assessement\n\n## Evaluation criteria\n\n- Solutions written in Python would be preferred.\n- Installation instructions that work.\n- During installation, we may use different companies.json or people.json files.\n- The API must work.\n- Tests\n\nFeel free to reach to your point of contact for clarification if you have any questions.\n"
}
] | 14
|
mtham8/spacy
|
https://github.com/mtham8/spacy
|
54fcbb40fc047a10b94e33204cbc7491c28ad7b9
|
d315ad9a624bd82ee9e9e97b606e3be4cc71750c
|
0e5831a07ddf9fae704a983dc0e7b9b4de8782a4
|
refs/heads/master
| 2022-12-12T21:32:27.552676
| 2019-07-24T17:45:54
| 2019-07-24T17:45:54
| 198,682,295
| 0
| 0
| null | 2019-07-24T17:37:01
| 2019-07-24T17:46:23
| 2022-12-08T05:56:01
|
Python
|
[
{
"alpha_fraction": 0.782608687877655,
"alphanum_fraction": 0.782608687877655,
"avg_line_length": 10.5,
"blob_id": "283247fe16765fccd2ccfef3921a9040f25d3402",
"content_id": "dd713144a68de06eccc16c9df341a5ede484c79a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 23,
"license_type": "no_license",
"max_line_length": 14,
"num_lines": 2,
"path": "/README.md",
"repo_name": "mtham8/spacy",
"src_encoding": "UTF-8",
"text": "# spacy\nnlp playground\n"
},
{
"alpha_fraction": 0.624772310256958,
"alphanum_fraction": 0.6393442749977112,
"avg_line_length": 22.869565963745117,
"blob_id": "57622a8e7d37159e324a1990cb8199427ed9b604",
"content_id": "7b4a16612741f5a42f716e7cc8e9c7a8b2cbcc34",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 549,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 23,
"path": "/example.py",
"repo_name": "mtham8/spacy",
"src_encoding": "UTF-8",
"text": "import spacy\nfrom spacy.lang.en import English\n\nnlp = English()\n\n# find percentages in text\ndoc = nlp(\n \"In 1990, more than 60% of people in East Asia were in extreme poverty. \"\n \"Now less than 4% are.\")\n\nfor token in doc:\n if token.like_num:\n next_token = doc[token.i + 1]\n if next_token.text == \"%\":\n print(\"Percentage found:\", token.text)\n\n# lang model\nen_nlp = spacy.load('en_core_web_sm')\n\npizza = en_nlp('She ate the pizza')\n\nfor token in pizza:\n print(token.text, token.pos_, token.dep_, token.head.text)\n"
}
] | 2
|
shreya-prabhu/Lexical-Text-Simplification
|
https://github.com/shreya-prabhu/Lexical-Text-Simplification
|
0eb734042adf4435602b7a632dfb40a500c34d5e
|
9558a87444e87786765a5978aa1670b31ef6f30a
|
efbc150d3d0634f87ac5036de07c6cbe3ac2a678
|
refs/heads/main
| 2023-04-15T16:55:57.952571
| 2021-04-28T03:46:28
| 2021-04-28T03:46:28
| 339,754,895
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8620689511299133,
"alphanum_fraction": 0.8620689511299133,
"avg_line_length": 29,
"blob_id": "23a624c7b41d37bc9758dd9ab8537d18bb1317fd",
"content_id": "d111074d96a333540323a4181aad02ee1deabb0c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 29,
"license_type": "no_license",
"max_line_length": 29,
"num_lines": 1,
"path": "/README.md",
"repo_name": "shreya-prabhu/Lexical-Text-Simplification",
"src_encoding": "UTF-8",
"text": "# Lexical-Text-Simplification"
},
{
"alpha_fraction": 0.6200156211853027,
"alphanum_fraction": 0.6262705326080322,
"avg_line_length": 34.55555725097656,
"blob_id": "659f5dc1b152b5e47eaa19e05e36d22be862e980",
"content_id": "04e00276cfcf9ab0f8e6dff76ce7efaef1226686",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1279,
"license_type": "no_license",
"max_line_length": 68,
"num_lines": 36,
"path": "/LexicalTextSimplification-test/evaluate.py",
"repo_name": "shreya-prabhu/Lexical-Text-Simplification",
"src_encoding": "UTF-8",
"text": "import textstat\nimport nltk\nimport readability\nfrom readability import Readability\n\nwith open('./data/input3.txt','r',encoding='utf-8') as file:\n test_data = file.read()\n x = Readability(test_data)\n fk = x.flesch_kincaid()\n print('score',fk.score)\n print('grade level',fk.grade_level)\n print('difficult words',textstat.difficult_words(test_data))\n\nwith open('./evaluation/output10.txt','r') as file:\n test_data = file.read()\n x = Readability(test_data)\n fk = x.flesch_kincaid()\n print('score',fk.score)\n print('grade level',fk.grade_level)\n print('difficult words',textstat.difficult_words(test_data))\n\nwith open('./evaluation/output11.txt','r') as file:\n test_data = file.read()\n x = Readability(test_data)\n fk = x.flesch_kincaid()\n print('score',fk.score)\n print('grade level',fk.grade_level)\n print('difficult words',textstat.difficult_words(test_data))\n\nwith open('./evaluation/output12.txt','r') as file:\n test_data = file.read()\n x = Readability(test_data)\n fk = x.flesch_kincaid()\n print('score',fk.score)\n print('grade level',fk.grade_level)\n print('difficult words',textstat.difficult_words(test_data))"
},
{
"alpha_fraction": 0.6028119325637817,
"alphanum_fraction": 0.6285881400108337,
"avg_line_length": 36.55555725097656,
"blob_id": "fcc418e60a6fb721ed7a70fe45fc81ca6893dc6a",
"content_id": "a5b5232d877e892bdb19e81315a5f6770e7b86df",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1707,
"license_type": "no_license",
"max_line_length": 150,
"num_lines": 45,
"path": "/LexicalTextSimplification-test/script.py",
"repo_name": "shreya-prabhu/Lexical-Text-Simplification",
"src_encoding": "UTF-8",
"text": "import re\nimport pandas as pd\nimport ujson\nimport _pickle as pickle\nfrom nltk import sent_tokenize, word_tokenize, pos_tag\nimport pandas as pd\nimport gensim\n\nfrom nltk.corpus import brown\nfrom nltk.probability import *\nfrom nltk.corpus import wordnet\nfrom nltk import sent_tokenize, word_tokenize, pos_tag\nimport text_simplification\nfrom conjugation import convert\n\n\ndef generate_freq_dict():\n \"\"\" Create frequency dictionary based on BROWN corpora. \"\"\"\n freq_dict = FreqDist()\n for sentence in brown.sents():\n for word in sentence:\n freq_dict[word] += 1\n return freq_dict\n\n\nif __name__ == '__main__':\n\n simplifier1 = text_simplification.Simplifier()\n with open('./data/input.txt',encoding='utf-8') as f:\n with open('./evaluation/output10.txt', 'w') as s0, open('./evaluation/output11.txt', 'w') as s1, open('./evaluation/output12.txt', 'w') as s2:\n for input in f:\n simplified0, simplified1, simplified2 = simplifier1.simplify(input)\n s0.writelines(simplified0 + \"\\n\")\n s1.writelines(simplified1 + \"\\n\")\n s2.writelines(simplified2 + \"\\n\")\n \n \n simplifier2 = text_simplification.Simplifier()\n with open('./data/input2.txt',encoding='utf-8') as f:\n with open('./evaluation/output21.txt', 'w') as s0, open('./evaluation/output22.txt', 'w') as s1, open('./evaluation/output23.txt', 'w') as s2:\n for input in f:\n simplified0, simplified1, simplified2 = simplifier2.simplify(input)\n s0.writelines(simplified0 + \"\\n\")\n s1.writelines(simplified1 + \"\\n\")\n s2.writelines(simplified2 + \"\\n\")\n \n"
},
{
"alpha_fraction": 0.5479212999343872,
"alphanum_fraction": 0.556449294090271,
"avg_line_length": 47.650943756103516,
"blob_id": "dc857271ae22b65c6bdb44588837cdc06de87894",
"content_id": "001e254b91aa7a8952b99dd7177fc35d5356b1e5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 10319,
"license_type": "no_license",
"max_line_length": 201,
"num_lines": 212,
"path": "/LexicalTextSimplification-test/text_simplification.py",
"repo_name": "shreya-prabhu/Lexical-Text-Simplification",
"src_encoding": "UTF-8",
"text": "\"\"\" Simple text simplification approach based on frequency.\nChoose 50% top low frequent words in the sentence,\nreplace them with the most frequent candidate from wordnet \"\"\"\n\nimport pandas as pd\nimport gensim\nfrom nltk.corpus import brown,wordnet\nfrom nltk.probability import FreqDist\nfrom nltk import sent_tokenize, word_tokenize, pos_tag\nfrom conjugation import convert\nfrom statistics import mode\n\n\ndef generate_brown_frequency_dictionary():\n \"\"\" Create frequency distribution of BROWN corpora. \"\"\"\n brown_frequency_dictionary = FreqDist()\n for sentence in brown.sents():\n for word in sentence:\n brown_frequency_dictionary[word] += 1\n\n corpus_frequency_distribution = pd.DataFrame(list(brown_frequency_dictionary.items()), columns = [\"Word\",\"Frequency\"])\n corpus_frequency_distribution.sort_values(\"Frequency\")\n corpus_frequency_distribution.to_csv('corpus_frequency.csv')\n return brown_frequency_dictionary\n\n\nclass Simplifier:\n def __init__(self):\n ''' The ngram frequency dictionary is annotated as\n frequency, word1...wordn, pos1...posn'''\n ngrams = pd.read_csv('./results/ngrams.csv')\n ngrams = ngrams.drop_duplicates(subset='bigram', keep='first')\n self.bigrams_brown_frequency_dictionary = dict(zip(ngrams.bigram, ngrams.freq))\n bigrams_distribution = pd.DataFrame(list(self.bigrams_brown_frequency_dictionary.items()), columns = [\"Bigram\",\"Frequency\"])\n bigrams_distribution.to_csv('bigrams_frequency.csv')\n self.brown_frequency_dictionary = generate_brown_frequency_dictionary()\n self.steps = open('steps.txt', 'w')\n\n def check_if_word_fits_the_context(self, context, token, replacement):\n \"\"\" Check if bigram with the replacement exists.\n Check for word preceeding and succeeding the replacement in the bigram dictionary. \"\"\"\n \n if len(context) == 3:\n if (context[0] + ' ' + replacement).lower() in self.bigrams_brown_frequency_dictionary.keys() or (replacement + ' ' + context[2]).lower() in self.bigrams_brown_frequency_dictionary.keys() :\n return True\n else:\n return False\n else:\n return False\n\n def return_bigram_score(self, context, token, replacement):\n \"\"\" Return the averaged frequency of left- and right-context bigram. \"\"\"\n score = 0\n if (context[0] + ' ' + replacement).lower() in self.bigrams_brown_frequency_dictionary.keys():\n score += self.bigrams_brown_frequency_dictionary[(context[0] + ' ' + replacement).lower()]\n if (replacement + ' ' + context[2]).lower() in self.bigrams_brown_frequency_dictionary.keys():\n score += self.bigrams_brown_frequency_dictionary[(replacement + ' ' + context[2]).lower()]\n return score / 2\n\n def check_if_replacable(self, word):\n \"\"\" Check POS, we only want to replace nouns, adjectives and verbs. \"\"\"\n word_tag = pos_tag([word])\n if 'NN' in word_tag[0][1] or 'JJ' in word_tag[0][1] or 'VB' in word_tag[0][1]:\n return True\n else:\n return False\n\n def generate_wordnet_candidates(self, word):\n \"\"\" Generate wordnet candidates for each word in input. \"\"\"\n candidates = set()\n if self.check_if_replacable(word):\n for synset in wordnet.synsets(word):\n for lemma in synset.lemmas():\n converted = convert(lemma.name().lower(), word)\n if converted != word and converted != None:\n try:\n w1 = wordnet.synsets(word)[0]\n w2 = wordnet.synsets(converted)[0]\n similarity = w1.wup_similarity(w2)\n if isinstance(similarity,float) and w1.wup_similarity(w2) >0.6 :\n candidates.add(converted)\n except:\n pass\n # print(\"candidate\",word,candidates)\n return candidates\n\n def check_pos_tags(self, sent, token_id, replacement):\n old_tag = pos_tag(sent)[token_id][1]\n sent[token_id] = replacement\n new_tag = pos_tag(sent)[0][1]\n if new_tag == old_tag:\n return True\n else:\n return False\n\n\n \n def simplify(self, input):\n simplified0 = ''\n simplified1 = ''\n simplified2 = ''\n\n sents = sent_tokenize(input) # Split by sentences\n\n '''Top 40 % least frequency score (rarer) words of the input corpus are taken as difficult words'''\n\n top_n = int(40/100*(len(input)))\n freq_top_n = sorted(self.brown_frequency_dictionary.values(), reverse=True)[top_n - 1]\n for sent in sents:\n self.steps.write(sent + '\\n')\n tokens = word_tokenize(sent) # Split a sentence by words\n\n #Store all difficult words\n difficultWords = [t for t in tokens if self.brown_frequency_dictionary[t] < freq_top_n]\n self.steps.write('difficultWords:' + str(difficultWords) + '\\n')\n\n all_options = {}\n for difficultWord in difficultWords:\n replacement_candidate = {}\n\n '''Collect WordNet synonyms for each difficult word, \n along with their brown corpus frequency.'''\n\n for option in self.generate_wordnet_candidates(difficultWord):\n replacement_candidate[option] = self.brown_frequency_dictionary.freq(option)\n\n '''store all these candidates in all_options '''\n\n all_options[difficultWord] = replacement_candidate\n all_options_list = [(k, v) for k, v in all_options.items()]\n self.steps.write('all_options:')\n self.steps.write(str(all_options_list) + '\\n')\n\n ''' Populate best candidates dictionary if it is a bigram, and add bigram score '''\n best_candidates = {}\n for token_id in range(len(tokens)):\n token = tokens[token_id]\n\n best_candidates[token] = {}\n if token in all_options:\n for opt in all_options[token]:\n if token_id != 0 and token_id != len(tokens): # if not the first or the last word in the sentence\n if self.check_if_word_fits_the_context(tokens[token_id - 1:token_id + 2], token, opt):\n \n best_candidates[token][opt] = self.return_bigram_score(tokens[token_id - 1:token_id + 2], token, opt)\n # self.steps.write('best_candidates:' + str(best_candidates) + '\\n')\n best_candidates_list = [(k, v) for k, v in best_candidates.items()]\n self.steps.write('best_candidates:')\n self.steps.write(str(best_candidates_list) + '\\n')\n\n '''Generate steps0 - take the word with the highest bigram score'''\n output = []\n for token in tokens:\n if token in best_candidates:\n if token.istitle() is False and best_candidates[token] != {}:\n # Choose the one with the highest bigram score\n best = max(best_candidates[token], key=lambda i: best_candidates[token][i])\n self.steps.write('best v1:' + str(token) + ' -> ' + str(best) + '\\n')\n output.append(best)\n else:\n output.append(token)\n else:\n output.append(token)\n simplified0 += ' '.join(output)\n\n '''Generate steps1 - take the word with the highest frequency + check the context'''\n output = []\n for token_id in range(len(tokens)):\n token = tokens[token_id]\n if token in all_options and len(all_options[token]) > 0 and token in difficultWords and token.istitle() is False:\n if token_id != 0 and token_id != len(tokens):\n # Choose most frequent and check if fits the context\n best_filtered = {word: all_options[token][word] for word in all_options[token] if\n self.check_if_word_fits_the_context(tokens[token_id - 1:token_id + 2], token, word)\n and self.check_pos_tags(tokens, token_id, word)}\n if best_filtered != {}: # if not empty\n best = max(best_filtered, key=lambda i: best_filtered[i])\n self.steps.write('best v2:' + str(token) + ' -> ' + str(best) + '\\n')\n output.append(best)\n else:\n output.append(token)\n else:\n output.append(token)\n else:\n output.append(token)\n simplified1 += ' '.join(output)\n\n '''Generate steps2 - take the synonym with the highest frequency'''\n output = []\n for token in tokens:\n # Replace word if in is difficult and a candidate was found\n if token in all_options and len(all_options[token]) > 0 and token in difficultWords and token.istitle() is False:\n best = max(all_options[token], key=lambda i: all_options[token][i])\n self.steps.write('best v3:' + str(token) + ' -> ' + str(best) + '\\n')\n output.append(best)\n else:\n output.append(token)\n simplified2 += ' '.join(output)\n\n return simplified0, simplified1, simplified2\n\n\n# if __name__ == '__main__':\n\n# simplifier1 = Simplifier()\n# with open('./data/input3.txt',encoding='utf8') as f:\n# with open('./evaluation/output10.txt', 'w') as s0, open('./evaluation/output11.txt', 'w') as s1, open('./evaluation/output12.txt', 'w') as s2:\n# for input in f:\n# simplified0, simplified1, simplified2 = simplifier1.simplify(input)\n# s0.writelines(simplified0 +'\\n')\n# s1.writelines(simplified1 +'\\n')\n# s2.writelines(simplified2 +'\\n')\n \n\n\n"
}
] | 4
|
saltyscript/Algo-DataStructures
|
https://github.com/saltyscript/Algo-DataStructures
|
b12b427c421858e0b56467c771a0bfbd7aebfe75
|
777c5109cd588c43859f7fac9dcba84d484a0650
|
9932e57f80b3329a47a27f5c2f7b16529e84521d
|
refs/heads/master
| 2021-01-10T03:56:11.927639
| 2016-04-07T05:40:51
| 2016-04-07T05:40:51
| 55,659,295
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6909090876579285,
"alphanum_fraction": 0.7863636612892151,
"avg_line_length": 43,
"blob_id": "e09a04d1de868bacb910c872677e0974f705e007",
"content_id": "517ee469b0610344d82304fd610533e724d73d45",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 220,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 5,
"path": "/README.md",
"repo_name": "saltyscript/Algo-DataStructures",
"src_encoding": "UTF-8",
"text": "# Algo-DataStructures\n\n4/16/2016 - LinkedList implementation using Python\n4/16/2016 - Queue implementation using LinkedList\n4/16/2016 - LinkedList feature addition ( Finding the second to last node - second_last_node())\n"
},
{
"alpha_fraction": 0.49708738923072815,
"alphanum_fraction": 0.5058252215385437,
"avg_line_length": 21.822221755981445,
"blob_id": "69874aeff6cf4d37aa30222334c8f3ae972d3adb",
"content_id": "ee74068f95f578ed053e089d044fe5daf99eda45",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1030,
"license_type": "no_license",
"max_line_length": 65,
"num_lines": 45,
"path": "/LinkedList.py",
"repo_name": "saltyscript/Algo-DataStructures",
"src_encoding": "UTF-8",
"text": "class LinkedNode:\n def __init__(self, value, tail = None):\n self.value = value\n self.next = tail\n\n\nclass LinkedList:\n def __init__(self):\n self.head = None\n\n def prepend (self, value):\n new_node = LinkedNode(value , self.head)\n self.head = new_node\n\n def pop(self):\n if self.head is not None:\n node = self.head\n self.head = node.next\n print (node.value)\n else:\n raise Exception (\"LinkedList is empty\")\n\n def second_last_node(self):\n n = self.head\n while n.next.next is not None:\n n = n.next\n print (n.value)\n\n def __iter__(self):\n n = self.head\n while n is not None:\n yield n.value\n n = n.next\n\n def __repr__(self):\n return \" LinkedList = [\" + \",\" .join(map(str,self)) + \"]\"\n\nif __name__ == '__main__':\n a=LinkedList()\n a.prepend(5)\n a.prepend(13)\n a. prepend(10)\n a.prepend(20)\n a.prepend(15)\n a.second_last_node()\n\n\n\n"
},
{
"alpha_fraction": 0.5065326690673828,
"alphanum_fraction": 0.5115578174591064,
"avg_line_length": 22.13953399658203,
"blob_id": "d4cad9670d13e5416d27be5a4f092a4442924beb",
"content_id": "f9d47d2ffecdacda4e0986e525a7aaff01ef89e7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 995,
"license_type": "no_license",
"max_line_length": 58,
"num_lines": 43,
"path": "/QueueLinkedList.py",
"repo_name": "saltyscript/Algo-DataStructures",
"src_encoding": "UTF-8",
"text": "from LinkedList import LinkedNode\n\n\nclass QueueLinkedList():\n def __init__(self):\n self.head = None\n self.tail = None\n\n def append(self,value):\n new_node = LinkedNode(value, None)\n\n if self.head is None:\n self.head = self.tail = new_node\n else:\n self.tail.next = new_node\n self.tail = new_node\n def pop(self):\n if self.head is not None:\n pop_node = self.head\n self.head = pop_node.next\n print (pop_node.value)\n else:\n raise Exception (\"Queue is empty\")\n\n def is_empty(self):\n return print(self.head is None)\n\n def __iter__(self):\n n = self.head\n while n is not None:\n yield n.value\n n = n.next\n\n def __repr__(self):\n return \"Queue :[\" + \",\" .join(map(str,self)) + \"]\"\n\nif __name__=='__main__':\n q = QueueLinkedList()\n q.is_empty()\n q.append(5)\n q.append(10)\n q.append(15)\n print (q)\n"
}
] | 3
|
jaagrit10/sort_n_search
|
https://github.com/jaagrit10/sort_n_search
|
2a1680a86cb82ec9b3b9c91a1040f15704e3a762
|
ea7617b5ccca5da26d2d05cc5e95175602275759
|
1fb3df340db084cb1560bb450538043a44e1935c
|
refs/heads/master
| 2023-06-21T16:40:36.910376
| 2021-07-27T18:09:47
| 2021-07-27T18:09:47
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7075812220573425,
"alphanum_fraction": 0.7310469150543213,
"avg_line_length": 35.93333435058594,
"blob_id": "6d1d5e8637985ecfd0f19b75076b43c94f9846c9",
"content_id": "820dac57d36f3f792be2404e74c4f46ba4e5f22d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1108,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 30,
"path": "/Intro to DSA in python/Trees/Tree Question.md",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#### Data structures exercise: General Tree\n\n1. Below is the management hierarchy of a company.\n\n \n\nExtend print_tree function such that it can print either name tree, designation tree or name and designation tree. As shown below,\n\n \n\nHere is how your main function should will look like,\n```\nif __name__ == '__main__':\n root_node = build_management_tree()\n root_node.print_tree(\"name\") # prints only name hierarchy\n root_node.print_tree(\"designation\") # prints only designation hierarchy\n root_node.print_tree(\"both\") # prints both (name and designation) hierarchy\n```\n\n[Solution](https://github.com/Divine275/sort_n_search/blob/master/Intro%20to%20DSA%20in%20python/General_Tree_ex1.py)\n\n2. Build below location tree using **TreeNode** class\n\n \n\nNow modify print_tree method to take tree level as input. And that should print tree only upto that level as shown below,\n\n \n\n[Solution](https://github.com/Divine275/sort_n_search/blob/master/Intro%20to%20DSA%20in%20python/General_tree_ex2.py)\n"
},
{
"alpha_fraction": 0.5467625856399536,
"alphanum_fraction": 0.5503597259521484,
"avg_line_length": 14.5,
"blob_id": "fb019355cc88727a20ab246e5b4fc0dfef00cd99",
"content_id": "d92e77d16538e43cfa7b362f01207ee47534783d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 278,
"license_type": "no_license",
"max_line_length": 93,
"num_lines": 18,
"path": "/Additional_C++/L3_const.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n\nclass Tes {\npublic:\n int x;\n int getX() const{ // -> when function is const, u can't change the value of data members.\n return x;\n }\n\n void setX(int x) {\n this->x = x;\n }\n};\n\nint main() {\n return 0;\n}"
},
{
"alpha_fraction": 0.663095235824585,
"alphanum_fraction": 0.6738095283508301,
"avg_line_length": 29.035715103149414,
"blob_id": "9a8d689f2899a7fb609a226ae58b1727376bb035",
"content_id": "d069b45b14f09e2682447c70355507907a48d0bc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 840,
"license_type": "no_license",
"max_line_length": 117,
"num_lines": 28,
"path": "/Intro to DSA in python/Queue/Queue_Implementation.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "from collections import deque #pronounced as deck not d-q-q\n\n# We can implement this using list and linked list. \n\nclass Queue:\n def __init__(self):\n self.buffer = deque() #buffer stores our data\n \n def enqueue(self, val): #adding data at beginning \n self.buffer.appendleft(val)\n\n def dequeue(self):\n \"\"\"return last element (see enqueue carefully and convince yourself that dequeue follows FI\"FO\" principle)\"\"\"\n return self.buffer.pop()\n \n def size(self):\n return len(self.buffer)\n\n def is_empty(self):\n return (len(self.buffer) == 0)\n\nmy_queue = Queue()\nmy_queue.enqueue(3)\nmy_queue.enqueue(9)\nmy_queue.enqueue(4)\nmy_queue.enqueue(8)\nprint(my_queue.dequeue()) # 3 was inserted first so output should be 3\nprint(my_queue.dequeue()) # 9 was inserted second to output should be 9"
},
{
"alpha_fraction": 0.4536195993423462,
"alphanum_fraction": 0.46875861287117004,
"avg_line_length": 19.415729522705078,
"blob_id": "0088163b25a51b6dca703e08f0f8584e29374990",
"content_id": "8ddd97da235e2aaf6357067f6c9247603d71b1b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 3633,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 178,
"path": "/Intro to DSA in C++/L13_Mixed_Problems.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n#define vi vector<int>\n#define vpi vector<pair<int, int>>\n#define pii pair<int, int>\n#define f first\n#define s second\n#define int long long int\n#define endl \"\\n\"\n\n\n// given an array consisting of unique values, Find the total sum of maximum value of all sub arrays.\nvi get_pge(vi arr, int n) {\n vi ans(n);\n stack<int> s;\n\n for(int i=0; i<n; i++) {\n while(s.size() and arr[s.top()] <= arr[i])\n s.pop();\n ans[i]=s.empty() ? -1 : s.top();\n s.push(i);\n }\n return ans;\n}\n\nvi get_nge(vi arr, int n) {\n vi ans(n);\n stack<int> s;\n\n for(int i=n-1; i>=0; i--) {\n while(s.size() and arr[s.top()] <= arr[i])\n s.pop();\n ans[i]=s.empty() ? n : s.top();\n s.push(i);\n }\n return ans;\n}\n\nvoid solve1() {\n int n; cin>>n;\n vi arr(n);\n\n for(int &i : arr) cin>>i;\n\n vi nge = get_nge(arr, n);\n vi pge = get_pge(arr, n);\n\n int ans=0;\n\n for(int i=0; i<n; i++) {\n ans+=(i-pge[i])*(nge[i]-i);\n }\n\n cout<<ans<<endl;\n}\n\n\n// given two arrays X and P (X is sorted).\n// Find a pair of distinct integers i, j such that abs(x[j]-x[i]) + P[i] + P[j] is maximum\n\npii getAns(vi x, vi p, int n) {\n int max_diff = p[0]-x[0], max_id=0, max_ans = INT_MIN;\n pii ans = {-1, -1};\n\n for(int j=1; j<n; j++) {\n int cur_sum = p[j]+x[j];\n\n if(cur_sum + max_diff > max_ans)\n max_ans = cur_sum + max_diff, ans = {max_id, j};\n\n if(p[j]-x[j] > max_diff) \n max_diff = p[j] - x[j], max_id = j;\n }\n return ans;\n}\n\nvoid solve2() {\n int n; cin>>n;\n vi x(n), p(n);\n\n for(int &i : x) cin>>i;\n\n for(int &j : p) cin>>j;\n\n pii ans = getAns(x, p, n);\n cout<<ans.f<<\" \"<<ans.s<<endl;\n}\n\n\n// condition:\n// that abs(x[j] - x[i]) <= k (given)\n\n// for any j\n // max(p[i] - p[j]) where i<j and x[j] - x[i] <=k\n\npii getAns2(vi x, vi p, int n, int k) {\n pii ans = {-1, -1};\n deque<int> q;\n int max_ans = INT_MIN;\n\n for(int j=0; j<n; j++) {\n while(q.size() and x[j] - x[q.front()] > k) \n q.pop_front();\n\n if(q.size()) {\n int id = q.front();\n int cur_sum = p[j]+x[j];\n\n if(cur_sum + p[id] - x[id] > max_ans) \n max_ans = cur_sum+p[id]+x[id], ans={id, j};\n }\n\n while(q.size() and p[q.back()] - x[q.back()] <= p[j]-x[j]) \n q.pop_back();\n \n q.push_back(j);\n }\n return ans;\n}\n\nvoid solve3() {\n int n; cin>>n;\n int k; cin>>k;\n vi x(n), p(n);\n\n for(int &i : x) cin>>i;\n\n for(int &j : p) cin>>j;\n\n pii ans = getAns2(x, p, n, k);\n cout<<ans.f<<\" \"<<ans.s<<endl;\n}\n\n\n// x[i] is angle in degrees\n// d=abs(x[i]-x[j])\n// maximize(min(d, 360-d) + p[i] + p[j])\npii getAns3(vi x, vi p, int n) {\n pii ans1 = getAns2(x, p, n, 180);\n\n pii ans2 = {1, 1};\n\n int max_sum = 0, max_id=-1, i=-1, max_ans = INT_MIN;\n\n for(int j=1; j<n; j++) {\n while(i+1<j and x[j] - x[i+1] > 180) {\n if(x[i+1] + p[i+1] > max_sum) {\n max_sum = x[i+1] + p[i+1], max_id = i;\n }\n i++;\n } \n\n int cur_diff = p[j] - x[j];\n\n if(max_id !=-1 and cur_diff + max_sum > max_ans) \n max_ans = cur_diff + max_sum, ans2 = {max_id, j};\n } \n\n int i= ans1.first, j=ans1.second;\n\n\n if(i==1 and max_ans > abs(x[i]-x[j])+p[i]+p[j])\n return ans2;\n\n return ans1;\n}\n\n\n\n// many buildings in a row, bahut door door\n// how many building can he see on right\n\n// calculate nge of all elements\n// my ans = nge of my nge+ so on\n\nint32_t main() {\n return 0;\n}"
},
{
"alpha_fraction": 0.5120643377304077,
"alphanum_fraction": 0.5227882266044617,
"avg_line_length": 15.260869979858398,
"blob_id": "c7f0b6fbe2d09cc83a1743305d57fff5a1ae3273",
"content_id": "f8f37c878a0d892b4860e323684e3c6c59fa8abd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 373,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 23,
"path": "/Additional_C++/L3_Constructor.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n\nclass ComplexNumber {\n int real, img;\n\n // ComplexNumber() {} //-> random value int\n\n // ComplexNumber() {\n // this->real=0;\n // this->img=0;\n // }\n\n ComplexNumber() : real(0), img(0){}\n ComplexNumber(int real, int img) {\n this->real=real;\n this->img=img;\n }\n};\n\nint main() {\n\n}"
},
{
"alpha_fraction": 0.46735668182373047,
"alphanum_fraction": 0.4721337556838989,
"avg_line_length": 24.80821990966797,
"blob_id": "603f87b8bf809ee1fa49d2fe649b06a8eb73f57a",
"content_id": "3a5ee567fcefc1b34c1462972d91e01a3c762533",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3768,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 146,
"path": "/Intro to DSA in python/1_Arrays/Doubly_LL_implementation.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "class Node:\n def __init__(self, data = None, next = None, prev = None):\n self.data = data\n self.next = next\n self.prev = prev\n \nclass doublyLinkedList:\n def __init__(self):\n self.head = None\n \n def insert_at_beginning(self, data):\n if self.head == None:\n node = Node(data, None, None)\n self.head = node\n else:\n node = Node(data, self.head, None)\n self.head.prev = node\n self.head = node\n \n def print_forward(self):\n if self.head is None:\n print(\"Linked List is empty\")\n return\n llstr = \"\"\n itr = self.head\n while itr:\n llstr += str(itr.data) + \"--->\"\n itr = itr.next\n print(llstr)\n\n def get_last(self):\n itr = self.head\n while itr.next is not None:\n itr = itr.next\n return itr\n\n def print_backward(self):\n last_node = self.get_last()\n if self.head is None:\n print(\"Linked list is empty\")\n return\n \n itr = last_node\n llstr = \"\"\n\n while itr is not None:\n llstr += str(itr.data) + \"--->\"\n itr = itr.prev\n print(llstr)\n\n def insert_at_end(self, data):\n if self.head is None:\n node = Node(data, None, None)\n self.head = node\n return\n \n last_node = self.get_last()\n node = Node(data, None, last_node)\n last_node.next = node\n\n def insert_values(self, data_list):\n self.head = None\n for data in data_list:\n self.insert_at_end(data)\n\n def length(self):\n count = 0\n itr = self.head\n while itr:\n itr = itr.next\n count += 1\n\n return count\n\n def remove_at(self, index):\n if (index < 0 or index > self.length()):\n raise Exception(\"Inavlid Index\")\n\n if index == 0:\n self.head = self.head.next\n return \n\n itr = self.head; count = 0\n while itr:\n if count == index - 1:\n itr.next = itr.next.next\n break\n itr = itr.next\n count += 1\n\n def insert_at(self, index, data):\n if (index < 0 or index >= self.length()):\n raise Exception(\"Inavlid Index\")\n\n if index == 0:\n self.insert_at_beg\n inning(data)\n return\n \n itr = self.head; count = 0\n while itr:\n if count == index - 1:\n node = Node(data, itr.next, itr)\n itr.next.prev = node \n itr.next = node\n break\n itr = itr.next\n count += 1\n\n def insert_after_value(self, data_after, data_to_insert):\n if self.head is None:\n node = Node(data_to_insert, None, None)\n self.head = node\n return\n\n itr = self.head\n while itr is not None:\n if itr.data == data_after:\n node = Node(data_to_insert, itr.next, itr)\n itr.next.prev = node\n itr.next = node\n break \n itr = itr.next\n\n def remove_by_value(self, data_to_remove):\n if self.head is None:\n return\n \n if self.head.data == data_to_remove:\n self.head = self.head.next\n return\n \n itr = self.head.next \n while itr is not None:\n if itr.data == data_to_remove:\n itr.prev.next = itr.next\n break\n itr = itr.next\n\n\ndll = doublyLinkedList()\nnums = [1,2,3,4,5]\ndll.insert_values(nums)\ndll.print_forward()\ndll.remove_by_value(3)\ndll.print_forward()\n"
},
{
"alpha_fraction": 0.5610021948814392,
"alphanum_fraction": 0.5648148059844971,
"avg_line_length": 28.063491821289062,
"blob_id": "c8d37e0e41a8ebc68eb8334383aed41a0d7686e2",
"content_id": "ebb1f695138fe75c3e66461b4b0a3854e75d3fea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1836,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 63,
"path": "/Intro to DSA in python/Trees/General_Tree_ex1.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "class TreeNode: \n # This class doesn't represent a tree but one node of tree \n def __init__(self, name, designation): \n data = (name, designation)\n self.data = data\n self.children = []\n self.parent = None\n\n def add_child(self, child): #child is TreeNode\n child.parent = self # parent of this child is self \n self.children.append(child) # adding child(a tuple) to self object\n\n def get_level(self):\n level = 0\n p = self.parent\n while p is not None:\n level += 1\n p = p.parent\n\n return level\n\n def print_tree(self, get = \"both\"):\n prefix = \" \"*self.get_level() + \"|__\" if self.parent is not None else \"\"\n if get == \"name\":\n val = self.data[0]\n elif get == \"designation\":\n val = self.data[1]\n else:\n val = f\"{self.data[0]} ({self.data[1]})\"\n\n print(prefix + val)\n\n if len(self.children) > 0:\n for child in self.children:\n child.print_tree(get)\n\n\ndef build_product_tree():\n #CTO hierarchy\n infra_head = TreeNode(\"Vishwa\", \"Infrastructure Head\") \n infra_head.add_child(TreeNode(\"Dhaval\", \"Cloud Manager\"))\n infra_head.add_child(TreeNode(\"Abhijit\", \"App Manager\"))\n\n app_head = TreeNode(\"Aamir\", \"Application Head\")\n\n cto = TreeNode(\"Chinmay\", \"CTO\")\n cto.add_child(infra_head)\n cto.add_child(app_head)\n \n # HR Head Hierarchy\n hr_head = TreeNode(\"Gels\", \"HR Head\")\n hr_head.add_child(TreeNode(\"Peter\", \"Recruitment Manager\"))\n hr_head.add_child(TreeNode(\"Waqas\", \"Policy Manager\"))\n\n root = TreeNode(\"Niupul\", \"CEO\")\n root.add_child(cto)\n root.add_child(hr_head)\n\n return root\n\nif __name__ == \"__main__\":\n root = build_product_tree()\n root.print_tree(\"bth\")\n \n"
},
{
"alpha_fraction": 0.6511628031730652,
"alphanum_fraction": 0.6763566136360168,
"avg_line_length": 15.677419662475586,
"blob_id": "6b41d5ebc1dfcc87d6a1564f457e2b27df7c662c",
"content_id": "8449a64d7e696fa99e66b3e2d0935c6c64c3d616",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 516,
"license_type": "no_license",
"max_line_length": 58,
"num_lines": 31,
"path": "/Intro to DSA in C++/L11_Doubt_Clearing.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n\n// prev smaller element -- L9\n\n// Expression evalutaion -- L9\n\n// string to int\nstring s = \"1233\";\nint x = stoi(s);\nint lld = stoll(s);\n\n// https://leetcode.com/problems/asteroid-collision/\nvector<int> asteroidCollision(vector<int>& asteroids) {\n \n}\n\n\n// https://leetcode.com/problems/maximum-product-subarray/\nint maxProduct(vector<int>& nums) {\n \n}\n\n// https://codeforces.com/problemset/problem/1481/C\nvoid fence_painting() {\n\n}\n\nint32_t main() {\n return 0;\n}"
},
{
"alpha_fraction": 0.5624024868011475,
"alphanum_fraction": 0.5676026940345764,
"avg_line_length": 29.484127044677734,
"blob_id": "eee01e2502e9b38d1faec31b855215049330d994",
"content_id": "a661c72d0052d53ffc7a4624ef32121e1f0f3f54",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3846,
"license_type": "no_license",
"max_line_length": 124,
"num_lines": 126,
"path": "/Intro to DSA in python/Binary_Search_Tree/BST_Implementation.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "# BST - \n# In our BST all element in left node will be smaller than Base/Root Node and those at right will be greater than root-node \n\nclass BinarySearchTreeNode:\n def __init__(self, data):\n self.data = data\n self.left = None\n self.right = None\n \n def add_child(self, data):\n if (data == self.data):\n return # since BST don't have any duplicate element \n \n if (data < self.data):\n if self.left is not None:\n # we are not in leaf node so move forward\n self.left.add_child(data) # this will add data only when we reach root node\n else:\n self.left = BinarySearchTreeNode(data)\n \n else:\n if self.right is not None:\n # we are not in leaf node so move forward\n self.right.add_child(data)\n else:\n self.right = BinarySearchTreeNode(data)\n\n def in_order_traversal(self): \n #return element [left subtree -> node -> right subtree] in this order (recursively)\n #in our case (see Line-2) it is same as ascending order\n\n elements = []\n\n #visiting left subtree first\n if self.left:\n elements += self.left.in_order_traversal()\n\n #visit the Base/Root node\n elements.append(self.data)\n\n #visit right subtree\n if self.right:\n elements += self.right.in_order_traversal()\n\n return elements\n\n def post_order_traversal(self):\n # return element [left -> right -> node] in this order (recursively)\n elements = [] \n\n # visit left subtree\n if self.left is not None:\n elements += self.left.post_order_traversal()\n \n #visit right subtree\n if self.right is not None:\n elements += self.right.post_order_traversal()\n \n #visit base/root node\n elements.append(self.data)\n\n return elements\n\n def pre_order_traversal(self):\n # return elements [node -> left subtree -> right subtree] in this order (recursively)\n elements = []\n\n #visit node\n elements.append(self.data)\n\n #visit left subtree\n if self.left:\n elements += self.left.pre_order_traversal()\n\n #visiting right subtree\n if self.right:\n elements += self.right.pre_order_traversal()\n\n return elements\n\n def search(self, val):\n if self.data == val:\n return True\n\n if (val < self.data): # it might be in left subtree\n if self.left is not None: \n return self.left.search(val)\n else:\n return False\n \n if (val > self.data): # it might be in right subtree\n if self.left is not None:\n return self.right.search(val)\n else:\n return False\n\n def find_min(self):\n if self.left is None:\n return self.data\n return self.left.find_min()\n\n def find_max(self):\n if self.right is None:\n return self.data\n return self.right.find_max() \n\n def calc_sum(self):\n left_sum = self.left.calc_sum() if self.left is not None else 0 \n right_sum = self.right.calc_sum() if self.right else 0\n return left_sum + right_sum + self.data\n\n# Helper method to help us build a tree\ndef build_tree(elements):\n root = BinarySearchTreeNode(elements[0])\n\n for i in range(1, len(elements)):\n root.add_child(elements[i])\n\n return root\n\nif __name__ == \"__main__\":\n numbers = [15, 12, 27, 7, 14, 20, 88, 23] # first element is considered node\n number_tree = build_tree(numbers) \n print(number_tree.in_order_traversal())\n print(number_tree.post_order_traversal())\n print(number_tree.pre_order_traversal())\n \n"
},
{
"alpha_fraction": 0.5945663452148438,
"alphanum_fraction": 0.6029258370399475,
"avg_line_length": 23.947368621826172,
"blob_id": "401154b25e3cb0e25c39cb0d7ab4d7b4300f4290",
"content_id": "e94523bed63782d0e55690de7e0895a9db3d5303",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 957,
"license_type": "no_license",
"max_line_length": 117,
"num_lines": 38,
"path": "/Intro to DSA in python/Queue/Binary_seq_usingQueue.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "# print Binary number for decimal number (1 to n)\n\nfrom collections import deque #pronounced as deck not d-q-q\n\nclass Queue:\n def __init__(self):\n self.buffer = deque() #buffer stores our data\n \n def enqueue(self, val): #adding data at beginning \n self.buffer.appendleft(val)\n\n def dequeue(self):\n \"\"\"return last element (see enqueue carefully and convince yourself that dequeue follows FI\"FO\" principle)\"\"\"\n return self.buffer.pop()\n \n def size(self):\n return len(self.buffer)\n\n def is_empty(self):\n return (len(self.buffer) == 0)\n\n def front(self):\n return self.buffer[~0]\n\n\ndef generate_binary(n):\n queue = Queue()\n queue.enqueue(\"1\")\n\n for i in range(n):\n front_num = queue.front()\n print(front_num)\n queue.enqueue(front_num + \"0\")\n queue.enqueue(front_num + \"1\")\n # print(queue)\n queue.dequeue()\n\n# generate_binary(10)\n\n "
},
{
"alpha_fraction": 0.4292929172515869,
"alphanum_fraction": 0.4396745264530182,
"avg_line_length": 16.095922470092773,
"blob_id": "9aa2e16761dc627896a86e85547a5931db0f36ad",
"content_id": "8912eb55d1fc82d3d45babce1fb1cb1043dadefe",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 7128,
"license_type": "no_license",
"max_line_length": 100,
"num_lines": 417,
"path": "/Intro to DSA in C++/L10_Queues_intuition_and_implementation.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n\n// Queue using a LL\n// push = add node at back\n// pop = remove node from front\n\n// Queue using array\n// circular queue to manage space\n\nclass Node {\n public:\n int data;\n Node *next;\n Node *prev;\n\n Node(int d) {\n data=d;\n next=NULL;\n prev=NULL;\n }\n};\n\nclass custom_queue_LL {\n Node *head, *tail;\n int sz;\n\npublic:\n custom_queue_LL() : head(NULL), sz(0), tail(NULL){}\n\n void push(int num) {\n Node *new_node = new Node(num);\n if(!sz) \n head = tail = new_node;\n else\n tail->next = new_node, tail=new_node;\n sz++;\n }\n\n int front() {\n if(!sz) {\n cout<<\" Queue empty\\n\";\n return -1;\n } \n return head->data;\n }\n\n void pop() {\n if(!sz) {\n cout<<\"Queue Empty\\n\";\n return;\n }\n\n if(sz==1) tail=NULL;\n\n Node *new_node = head->next;\n delete head;\n head=new_node;\n sz--;\n }\n\n int size() {\n return sz;\n }\n\n bool empty() {\n return (sz==0);\n }\n\n void clear() {\n while(sz) {\n pop();\n }\n }\n};\n\nclass circular_queue_using_arr {\n int *arr, st, en, sz, cap;\n\npublic: \n circular_queue_using_arr(int cap) {\n arr = new int[cap];\n st=0; en=-1; sz=0, this->cap=cap;\n }\n\n void push(int num) {\n if(sz==cap) {\n cout<<\"Queue full, kl ana\"<<endl;\n return;\n }\n\n en=(en+1)%cap;\n arr[en]=num;\n sz++;\n }\n\n int front() {\n if(sz) \n return arr[st];\n cout<<\"Queue empty\"<<endl;\n return -1;\n }\n\n int back() {\n if(sz) \n return arr[en];\n cout<<\"Queue Empty\"<<endl;\n return -1;\n }\n\n void pop() {\n if(!sz) {\n cout<<\"Queue khali!\"<<endl;\n return;\n }\n\n st=(st+1)%cap;\n sz--;\n }\n\n int size() {return sz;}\n\n bool empty() {return (sz==0);}\n\n void clear() {\n while(sz)\n pop();\n }\n};\n\nclass custom_deque_LL {\n Node *head, *tail;\n int sz;\n\npublic:\n custom_deque_LL() : head(NULL), sz(0), tail(NULL){}\n\n void push_back(int num) {\n Node *new_node = new Node(num);\n if(!sz) \n head=tail=new_node;\n else{\n tail->next=new_node;\n new_node->prev = tail;\n tail=new_node;\n }\n sz++;\n }\n\n void pop_back() {\n if(!sz) {\n cout<<\"Deque Empty\\n\";\n return;\n }\n if(sz==1) tail=NULL, head=NULL;\n\n Node *new_node = tail->prev;\n delete tail;\n tail=new_node;\n sz--;\n }\n\n void push_front(int num) {\n Node *new_node = new Node(num);\n new_node->next = head;\n head=new_node;\n sz++;\n }\n\n void pop_front() {\n if(!sz) {\n cout<<\"Deque Empty\\n\";\n return;\n }\n Node *new_node = head->next;\n delete head;\n head=new_node;\n sz--;\n }\n\n int size() {\n return sz;\n }\n\n bool empty() {\n return (sz==0);\n }\n\n void clear() {\n while(sz) pop_back();\n }\n \n int front() {\n if(!sz) {\n cout<<\"Deque empty\\n\";\n return -1;\n }\n return head->data;\n }\n\n int back() {\n if(!sz) {\n cout<<\"Deque empty\\n\";\n return -1;\n }\n return tail->data;\n }\n};\n\nclass circular_deque_using_arr {\n int *arr, st, en, sz, cap;\n\npublic: \n circular_deque_using_arr(int cap) {\n arr = new int[cap];\n st=0; en=-1; sz=0, this->cap=cap;\n }\n\n void push_back(int num) {\n if(sz==cap) {\n cout<<\"Queue full, kl ana\"<<endl;\n return;\n }\n\n if(sz==0) {\n st=en=0;\n sz=1;\n arr[st]=num;\n return;\n }\n\n en=(en+1)%cap;\n arr[en]=num;\n sz++;\n }\n\n void push_front(int num) {\n if(sz==cap) {\n cout<<\"Queue full, kl ana\"<<endl;\n return;\n }\n\n if(sz==0) {\n st=en=0;\n sz=1;\n arr[st]=num;\n return;\n }\n\n st=(st-1 + cap)%cap; // to make sure the number is positive\n arr[st]=num;\n sz++;\n }\n\n void pop_front() {\n if(!sz) {\n cout<<\"Deque khali!\"<<endl;\n return;\n }\n\n st=(st+1)%cap;\n sz--;\n }\n\n void pop_back() {\n if(!sz) {\n cout<<\"Deque Khali!\\n\";\n return;\n }\n\n en=(en-1+cap)%cap;\n sz--;\n }\n\n int front() {\n if(sz) \n return arr[st];\n cout<<\"Queue empty\"<<endl;\n return -1;\n }\n\n int back() {\n if(sz) \n return arr[en];\n cout<<\"Queue Empty\"<<endl;\n return -1;\n }\n\n int size() {return sz;}\n\n bool empty() {return (sz==0);}\n\n void clear() {\n while(sz)\n pop_back();\n }\n};\n\n// implement a stack using only queue.\n// ans - > \n\n// use 2 queues \n\n// method 1\n// push O(n), pop O(1)\n// main and auxilliary\n// main: \n// auxilliary: \n// push - transfer all from main to aux, push to main, transfer back from aux to main.\n// pop - pop the front.\n\n// method 2\n// push in O(1)\n// pop in O(n) \n// - transfer all except the last from main to aux, then pop out the element, transfer back to main.\n\n\n// using 1 queue\n// push - simple q.push() O(1)\n// pop - O(n)\n/*\nint n=q.size();\nn--;\nwhile(n--) {\n q.push(q.front());\n q.pop();\n}\nq.pop();\n*/ \n\n\n// Queue using stack(s)\n\n// 2 stacks i lgenege...............\n// O(N) pop, O(1) push\n// O(1) pop, O(N) push\n// similar to stack using queue\n\n\n// O(1) both\n\n// push = push in stack 1 \n/*\nq.push(num) => in.push(num)\n*/\n// pop\n// check the stack 2 to be empty..\n// move all elements to 2\n// pop the top element\n// repeat\n/*\nq.pop() =>\n\nif(out.empty()) {\n while(in.size()) {\n out.push(in.top()), in.pop();\n }\n}\n\nif(out.size()) {\n out.pop();\n} else {\n cout<<\"khali\"<<endl;\n}\n*/\n\n\n// negative modulo problem\n// a%m = ((a%m)+m)%m;\n\n// given two numbers l and r\n// 1 <= l <= r <= 10**12\n// print all number form l to r, which have only 2, 3 or 5 as their digits\nvoid digitProblem(int l, int r) {\n queue<int> q;\n vector<int> ans;\n\n q.push(2);\n q.push(3);\n q.push(5);\n\n while(q.front()<=r) {\n int n=q.front();\n q.pop();\n if(n>=l) {\n ans.push_back(n);\n }\n q.push(10*n+2), q.push(10*n+3), q.push(10*n+5);\n }\n}\n\n\nint32_t main() {\n circular_queue_using_arr q(5);\n // custom_queue_LL q;\n int n=5;\n for(int i=0; i<n; i++) {\n q.push(i);\n }\n cout<<q.size()<<endl;\n cout<<q.front()<<endl;\n q.pop();\n cout<<q.size()<<endl;\n q.clear();\n cout<<q.size()<<endl;\n\n custom_deque_LL d;\n for(int i=0; i<n; i++) d.push_back(i);\n\n cout<<d.front()<<endl;\n d.pop_front();\n cout<<d.size()<<endl;\n d.pop_back();\n cout<<d.size()<<endl;\n cout<<d.back()<<endl;\n return 0;\n}"
},
{
"alpha_fraction": 0.5635474920272827,
"alphanum_fraction": 0.5656424760818481,
"avg_line_length": 23.620689392089844,
"blob_id": "8361afd4516c2530aaead125b336a1907694884d",
"content_id": "967769c2aa50833316f805a590bbe5d26db08972",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1432,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 58,
"path": "/Intro to DSA in python/Trees/General_tree_ex2.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "class TreeNode:\n def __init__(self, data):\n self.data = data\n self.children = []\n self.parent = None\n \n def add_child(self, child):\n child.parent = self\n self.children.append(child)\n\n def get_level(self):\n level = 0\n p = self.parent\n\n while p is not None:\n level += 1\n p = p.parent\n \n return level\n\n def print_tree(self, level):\n prefix = \" \"*self.get_level() + \"|__\" if self.parent is not None else \"\"\n val = self.data\n\n if self.get_level() <= level:\n print(prefix + val)\n\n if len(self.children) > 0:\n for child in self.children:\n child.print_tree(level)\n\ndef build_product_tree():\n root = TreeNode(\"Electronics\")\n\n laptop = TreeNode(\"Laptop\")\n laptop.add_child(TreeNode(\"Macbook\"))\n laptop.add_child(TreeNode(\"HP\"))\n laptop.add_child(TreeNode(\"Surface\"))\n\n cellphone = TreeNode(\"Cell Phone\")\n cellphone.add_child(TreeNode(\"iPhone\"))\n cellphone.add_child(TreeNode(\"Google Pixel\"))\n cellphone.add_child(TreeNode(\"Vivo\"))\n\n tv = TreeNode(\"TV\")\n tv.add_child(TreeNode(\"Samsung\"))\n tv.add_child(TreeNode(\"LG\"))\n\n root.add_child(laptop)\n root.add_child(cellphone)\n root.add_child(tv)\n\n return root\n\nif __name__ == \"__main__\":\n root = build_product_tree()\n level = int(input())\n root.print_tree(level)\n "
},
{
"alpha_fraction": 0.4910714328289032,
"alphanum_fraction": 0.5172619223594666,
"avg_line_length": 27.491525650024414,
"blob_id": "4bf85b497dd7c15a297b35ee77fee52d7650ad33",
"content_id": "f46e9cb6b40858a689cd7af2fafe1e64a127a6e8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1680,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 59,
"path": "/Intro to DSA in python/Hash_Map/HashMap_implementation.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "# def get_hash(key):\n# h = 0\n# for char in key:\n# h += ord(char)\n# return (h % 10)\n\n# print(get_hash('march 2'))\n# # two key got same has map this means our array size was not sufficient so we have to make a bigger array (worst case)\n# print(get_hash('march 10'))\n# print(get_hash('march 9'))\n\nclass HashTable:\n def __init__(self):\n self.MAX = 10\n self.arr = [[] for i in range(self.MAX)]\n\n def get_hash(self, key):\n h = 0\n for char in key:\n h += ord(char)\n return (h % self.MAX)\n\n # def __setitem__(self, key, pair): # t['match 6'] = 130\n # def __getitem__(self, key): #t['match 6'] returns 130 \n\n def __setitem__(self, key, value):\n h = self.get_hash(key)\n found = False\n for idx, element in enumerate(self.arr):\n if len(element) == 2 and element[0] == key:\n self.arr[h][idx] = (key, value)\n found = True\n break\n if not found:\n self.arr[h].append((key, value))\n\n def __getitem__(self, key):\n h = self.get_hash(key)\n for element in self.arr[h]:\n if element[0] == key:\n return element[1]\n\n return None\n\n def __delitem__(self, key):\n h = self.get_hash(key)\n for index, element in enumerate(self.arr[h]):\n if element[0] == key:\n del self.arr[h][index]\n return\nt = HashTable()\n# t[\"hi\"] = 34 will override march-6 as (ascii sum % 100) matches for both of them\nt[\"march 17\"] = 23\nt[\"march 6\"] = 345\nprint(t[\"march 17\"])\ndel t[\"march 17\"]\nprint(t[\"march 17\"])\nprint(t.arr)\ndel t[\"march 6\"]"
},
{
"alpha_fraction": 0.6800750494003296,
"alphanum_fraction": 0.6838265657424927,
"avg_line_length": 27.064327239990234,
"blob_id": "8a4772ad91ffc8fe5636b323e0d74e40edb432d3",
"content_id": "bf3823da6038e0241ede7b22a232bea2b431347f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 4798,
"license_type": "no_license",
"max_line_length": 167,
"num_lines": 171,
"path": "/Additional_C++/README.md",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "# Additional Concepts in C++\n\n## Memory Management\n### Pointers\n+ Variable that stores address.\n+ When a variable in initialized, it is stored in a stack frame.\n+ ```int* ptr = &x;```\n+ If we want to access the variable even after removing the stack frame: \n + in C, malloc is used\n + We use heap to solve this problem.\n + A bucket is made in heap part of memory, and pointer to it is used in stack frame.\n\n### new and delete\n+ __new__ : replacement of malloc, calloc\n + It initialise a bucket in heap, and return its pointer to the function.\n + Syntax: \n + ```<data-type>* <variable-name> = new <data-type>(value);```\n+ __delete__: replacement of free in C++\n\n### Function Pointers\n+ Address which stores the function\n+ Syntax:\n + ```<return_type>(*<variable_name>)(<argument_type>) = <function_name>```\n + ```auto <variable_name> = <function_name>```\n+ Used to pass a function are a parameter to other function.\n\n### Lambda's in C++\n+ Similar to lambda in python\n+ [] -> use external variables in lambda\n+ Used to declare and use a function in same line.\n+ Syntax(example):\n + ```[](int v) {cout<<\"value is: \"<<v<<endl;}```\n\n### Smart pointers\n+ Only way to store values in heap, pointers must be used. And they need to be removed manually.\n+ __*Smart Pointers*__ is a solution to this problem, deleting up the memory space will be automatically managed by them.\n\n### Three types of smart pointers\n+ Unique\n+ Shared\n+ Weak\n\n__Unique Pointer__: If we have created an object using unique pointer, no other pointer can point to this object.\n\n__Shared Pointer__: It gives you access to share object.\n\n__Weak Pointer__: It does not keep a refernce count. It does not give access to use the object. It is just for inspection purpose. Solve the prob of dangling pointer.\nIt can help in checking whether the pointer is deleted, using `expired()` method.\n\nSmart pointer keep a *reference count*. This helps in the implementation of diff smart pointer. \n\n\n### Destructure\nFunction executed just before a struct gets removed from memory.\n\n\n## Object Oriented Programming(OOPs)\n### Objects\nReal life enities, also called instances.\n### Class\nBlue print of a real life object.\n\nIncrease readability of the code.\nGiven a huge upper hand in using business logic.\n\n### Object\n+ Each object has data members and functionalities.\n\n### Constructor\nIt creates a new instance(object) of a class.\n\n### Visibility\n+ __*Private*__ : Default. Not visible anywhere outside the class.\n+ __*Public*__ : Accessible everywhere.\n+ __*Protected*__\n\n### What happend when we create an object?\nFirst it will store the data members.\n\n### \"this\" pointer\nThis store the address of the object in memory.\n\n### -> and . notation\n+ If accessing via a _pointer_, use ->\n+ If accessing via an _object_, use .\n\n### Structs and Classes\nOnly difference between struct and class in C++ is that, everything in struct in public by default but we can have custom visibility modifier in classes.\n\nStructs also support private and protected.\n__Class__ is widely used in industry.\n\n### const keyword\nThe variable which cant be reassigned.\n> Promises are made to be broken -- Sanket Singh, 2021\n```cpp\nconst int x = 24;\nx = 26; // -> not allowed\n\nint *ptr = &x; // -> give error\nconst int *ptr = &x; // -> we cant change value\n\nconst int *p = &x;\n\nint *ptr = new int;\n*ptr = 2;\nptr = (int) &x;\n// p and ptr have same value\n\ncout<<x<<\" \"<<*ptr<<endl; // -> x not changes, *ptr shows changed result.\n// -> very wierd.\n```\n\n+ const int*\n+ int const*\n + We cant change the value, but cant change the value.\n\nAbove two are same\n+ int* const\n + Change the value, no reassignment\n\n```cpp\nconst int *a = new int; // -> never change value\nc = (int*) &x;\n\nint* const a = new int; // -> no reassignment, but change of value permitted\n\n\nconst int *p const z = 420; // -> compeletely blocked pointer.\n```\nIf a fucntion has const parameters, then any non-const function can't be used inside that fucntion.\n\n+ Use `mutable` keyword to bypass const\n```cpp\nmutable int x = 45; // this can be changed in const functions.\n```\n\n### Costructors\n+ If we write no costructor, compiler uses the deafult.\n+ Otherwise it will not use default.\n\n+ There are many ways to \"construct\" an object\n```cpp\nclass ComplexNumber {\n int real, img;\n\n ComplexNumber() {} //-> random value int\n\n ComplexNumber() {\n this->real=0;\n this->img=0;\n }\n\n ComplexNumber() : real(0), img(0){}\n ComplexNumber(int real, int img) {\n this->real=real;\n this->img=img;\n }\n};\n```\n\n__Constructor overloading__ : \n+ Solved in compile time.\n\n### Polymorphism\nPoly -> Many, morphism -> form\nTwo types\n+ Compile time (early binding, static binding)\n+ Run time \n### Overloading and Overriding\n### Operator and Function Overloading"
},
{
"alpha_fraction": 0.4758317768573761,
"alphanum_fraction": 0.4965474009513855,
"avg_line_length": 25.032787322998047,
"blob_id": "d16e5870f26e1ea2688d61b277086026ed788782",
"content_id": "733dd879dd1e115f991bf0bb27d2f14d645cc7f6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1593,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 61,
"path": "/Intro to DSA in python/Hash_Map/Collison_handling_LinearProb.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "class HashTable:\n def __init__(self):\n self.MAX = 5\n self.arr = [None for i in range(self.MAX)]\n\n def get_hash(self, key):\n h = 0\n for char in key:\n h += ord(char)\n return (h % self.MAX)\n\n def get_prob_range(self, index):\n return [*range(index, len(self.arr))] + [*range(0, index)]\n\n def __getitem__(self, key):\n h = self.get_hash(key)\n if self.arr[h] is None:\n return\n prob_range = self.get_prob_range(h)\n for prob_index in prob_range:\n element = self.arr[prob_index]\n if element is None:\n return None\n if element[0] == key:\n return element[1]\n\n def __setitem__(self, key, value):\n h = self. get_hash(key)\n prob_range = self.get_prob_range(h)\n for prob_index in prob_range:\n if self.arr[prob_index] is None:\n self.arr[prob_index] = (key, value)\n return\n\n if self.arr[prob_index][0] == key:\n self.arr[prob_index] = (key, value)\n return\n \n raise Exception(\"Hash Map Full\")\n \n def __delitem__(self, key):\n h = self.get_hash(key)\n prob_range = self.get_prob_range(h)\n\n for prob_index in prob_range:\n if self.arr[prob_index][0] == key:\n self.arr[prob_index] = None\n return None\n\n return \n\n \nd = HashTable()\n# d[\"march 9\"] = 310\nd[\"march 7\"] = 320\nd[\"march 8\"] = 330\nd[\"march 10\"] = 340\nd[\"march 13\"] = 56\nd[\"march 11\"] = 260\n\nprint(d.arr)\n\n "
},
{
"alpha_fraction": 0.4674418568611145,
"alphanum_fraction": 0.4715116322040558,
"avg_line_length": 19.722890853881836,
"blob_id": "be922acca4cf26d8460bb43bb3b6a6209bea62a4",
"content_id": "82ddca0cf8ddcffcf16789c66c1dd63ff459949c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1720,
"license_type": "no_license",
"max_line_length": 104,
"num_lines": 83,
"path": "/Intro to DSA in C++/L12_Queue_Classical _Problems.cpp",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "#include<bits/stdc++.h>\nusing namespace std;\n#define vi vector<int>\n#define mii map<int, int>\n#define pi pair<int, int>\n\n// given an array of integers and a number k, Find the max of each sub array of size k.\n\n// map method O(nlogn)\n\n\n// queue method O(n)\nvoid max_sub_array(vi v, int k) {\n \n int n=v.size();\n deque<int> q;\n for(int i=0; i<k; i++) {\n while(q.size() and v[q.back()]<=v[i]) {\n q.pop_back();\n }\n q.push_back(i);\n }\n\n cout<<v[q.front()]<<' ';\n\n for(int i=k; i<n; i++) {\n if(q.front()==i-k) {\n q.pop_front();\n }\n while(q.size() and v[q.back()]<=v[i]) {\n q.pop_back();\n }\n q.push_back(i);\n\n cout<<v[q.front()]<<' ';\n }\n}\n\n\n// N people, given a list of pairs of friends.\n// We're hosting a party and a person can come to the party only if atleast k of his friends have come. \n// Tell the maximum no. of people that we can expect in the party.\n\n// create an adjacency list\nvoid party() {\n int n, m, k;\n cin>>n>>m>>k;\n vector<vi> adj(n+1);\n vi num(n+1);\n vector<bool> coming(n+1, true);\n\n\n while(m--) {\n int i, j;\n cin>>i>>j;\n adj[i].push_back(j);\n adj[j].push_back(i);\n\n num[i]++, num[j]++;\n }\n\n queue<int> q;\n for(int i=1; i<=n; i++) \n if(num[i]<k) \n coming[i]=false, q.push(i);\n\n while(!q.empty()) {\n int i=q.front();\n q.pop();\n\n for(int j : adj[i]) {\n num[j]--;\n\n if(coming[i] == true and num[j] == k-1) \n coming[j]=false, q.push(j);\n }\n }\n\n for(int i=1; i<=n; i++)\n if(coming[i])\n cout<< i <<\" \";\n cout<<endl;\n}\n"
},
{
"alpha_fraction": 0.5296229720115662,
"alphanum_fraction": 0.539198100566864,
"avg_line_length": 26.393442153930664,
"blob_id": "7410a0ba14cee28337df788c558a68d8a24eb196",
"content_id": "c7207dadba237bc827829b4998564eea14a48288",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1671,
"license_type": "no_license",
"max_line_length": 116,
"num_lines": 61,
"path": "/Intro to DSA in python/7-8_Stack/L7-Stack-Implementation.py",
"repo_name": "jaagrit10/sort_n_search",
"src_encoding": "UTF-8",
"text": "\"\"\"\nLine 7 - 28 Stack Implementaion\nLine 30 - 37Reversing a string using stack \nLine 39 - 55 Checking wheather different types of paranthesis are balanced or not (Refer Line 57 onward for clarity)\n\"\"\"\n\nfrom collections import deque # deque is Double Ended QUEue (pronounced as deck)\n\nclass Stack:\n def __init__(self):\n self.container = deque()\n\n def push(self, val):\n self.container.append(val)\n\n def pop(self):\n if not self.isEmpty():\n return self.container.pop()\n return None\n\n def peek(self): \n return self.container[-1]\n\n def isEmpty(self):\n return (len(self.container) == 0)\n\n def size(self):\n return len(self.container)\n\ndef reverse_string(string):\n stack = Stack()\n rev_string = \"\"\n for i in range(len(string)):\n stack.push(string[i])\n for i in range(len(string)):\n rev_string += stack.pop()\n return rev_string\n\ndef is_balanced(exp) -> bool:\n stack = Stack()\n ans = True\n map = {\"}\" : \"{\", \"]\" : \"[\", \")\" : \"(\"}\n closed_brackets = {\")\", \"}\", \"]\"}; open_brackets = {\"(\", \"{\", \"[\"}\n brackets = {\"{\", \"[\", \"(\", \"}\", \")\", \"]\"}\n for i in exp:\n if i in open_brackets:\n stack.push(i)\n continue\n if i in closed_brackets:\n if stack.isEmpty():\n return False\n if not (map[i] == stack.pop()):\n return False\n \n return (stack.isEmpty())\n \n# print(is_balanced(\"({a+b})\")) #True\n# print(is_balanced(\"))((a+b}{\")) #False \n# print(is_balanced(\"((a+b))\")) # True\n# print(is_balanced(\"[a+b]*(x+2y)*{gg+kk}\")) #True\n# print(is_balanced(\"(\")) #False\n"
}
] | 17
|
tueseed/stock
|
https://github.com/tueseed/stock
|
8619f61fb37b80752bd5e9c63a1cdf71a822ade9
|
6475d67d5150226065a87dbda565f283cd4afe70
|
661737ca471e66f551ce328adea6f370098ad3e2
|
refs/heads/main
| 2023-04-30T23:14:56.027149
| 2021-05-10T08:08:44
| 2021-05-10T08:08:44
| 365,635,870
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.542983889579773,
"alphanum_fraction": 0.5571269989013672,
"avg_line_length": 34.71287155151367,
"blob_id": "94e2832e8df14c78360c1df20bfe235f6c96c681",
"content_id": "ba63c59f6e3a9d9d8411c6a2edf5d591e6cb70d7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4216,
"license_type": "no_license",
"max_line_length": 111,
"num_lines": 101,
"path": "/app.py",
"repo_name": "tueseed/stock",
"src_encoding": "UTF-8",
"text": "from flask import Flask,request\nimport json\nfrom bs4 import BeautifulSoup\nimport requests\nfrom makemsg import makecarousel\n\n# ตรง YOURSECRETKEY ต้องนำมาใส่เองครับจะกล่าวถึงในขั้นตอนต่อๆ ไป\nglobal LINE_API_KEY\nLINE_API_KEY = 'Bearer 5eXKUJTmf55Pnd1zCZS2+1Ot01rzUPkOmAdzCisnOY3W2wjrMDT1hlbMKAiRnBw8QKDBy32lm5HDu7TmyYEreQsd5+B24zLLSJFb33o4er2wigrL8P/ZzXxfO/j+hC8Etc0eHTct5r1wmq0WrwCjCQdB04t89/1O/w1cDnyilFU='\n\n############################################################\napp = Flask(__name__)\n###########################หน้าแรก################################\n@app.route('/')\ndef index():\n return \"Hi Welcome to python page\"\n#################################หน้าราคาหุ้น###############################\n@app.route('/getquote', methods=['GET'])\ndef getquote(symbol):\n # symbol_param = request.args.get(\"symbol\")\n url = \"https://www.settrade.com/C04_01_stock_quote_p1.jsp?txtSymbol=\"+symbol+\"&ssoPageId=9&selectPage=1\"\n res = requests.get(url)\n res.encoding = \"tis-620\"\n soup = BeautifulSoup(res.text, 'html.parser')\n #####หาชื่อหุ้นและเวลาอัพเดท#######\n data_span = soup.find_all('span')\n span_list = []\n for data_spans in data_span:\n obj_span = data_spans.string\n span_list.append(obj_span)\n last_update = span_list[22]\n symbol = span_list[24]\n ######หาราคาล่าสุดและการเปลี่ยนแปลง#####\n data_h1 = soup.find_all('h1')\n h1_list = []\n for data_h1s in data_h1:\n obj_h1 = data_h1s.text\n h1_list.append(obj_h1)\n last_price = h1_list[1].strip()\n price_chg = h1_list[2].strip()\n percent_chg = h1_list[3].strip()\n\n ########หารานละเอียด###############\n data_td = soup.find_all('td')\n td_list = []\n for data_tds in data_td:\n obj_td = data_tds.text\n td_list.append(obj_td)\n\n stock_return = {\n \"symbol\": symbol, \"lastupdate\": last_update, \"lastprice\": last_price,\n \"pricechange\": price_chg,\"percentchange\": percent_chg, \"p_close\": td_list[1].strip(),\n \"open\": td_list[3].strip(),\"high\": td_list[5].strip(),\"low\": td_list[7].strip(),\n \"average\": td_list[9].strip(),\"volumn\": td_list[11].strip(),\"vol(k)\": td_list[13].strip(),\n \"ceiling\": td_list[17].strip(),\"floor\": td_list[19].strip(),\"bid/vol\": td_list[21].strip(),\n \"offer/vol\": td_list[23].strip()\n }\n # return json.dumps(stock_return)\n return stock_return\n\n@app.route('/bot', methods=['POST'])\ndef bot():\n # ข้อความที่ต้องการส่งกลับ\n # replyStack = list()\n if request.method == 'POST':\n # ข้อความที่ได้รับมา\n msg_in_json = request.get_json()\n # msg_in_string = json.dumps(msg_in_json)\n\n # Token สำหรับตอบกลับ (จำเป็นต้องใช้ในการตอบกลับ)\n replyToken = msg_in_json[\"events\"][0]['replyToken']\n symbol_from_line = msg_in_json[\"events\"][0]['message']\n txtre = symbol_from_line['text']\n databack = getquote(txtre)\n makemessage = makecarousel(databack)\n # ทดลอง Echo ข้อความกลับไปในรูปแบบที่ส่งไป-มา (แบบ json)\n # replyStack.append(msg_in_string)\n reply(replyToken, makemessage)\n\n return 'OK'\n\ndef reply(replyToken, msg):\n # Method สำหรับตอบกลับข้อความประเภท text กลับครับ เขียนแบบนี้เลยก็ได้ครับ\n LINE_API = 'https://api.line.me/v2/bot/message/reply'\n headers = {'Content-Type': 'application/json; charset=UTF-8','Authorization': LINE_API_KEY}\n # msgs = [{\"type\":\"text\",\"text\":str(textList)}]\n\n flexMsg =[{\n \"type\":\"flex\",\n \"altText\":\"test\",\n \"contents\":msg\n }]\n data = json.dumps({\"replyToken\":replyToken,\"messages\":flexMsg})\n requests.post(LINE_API, headers=headers, data=data)\n return\n\n\n\n\nif __name__ == '__main__':\n app.run()"
}
] | 1
|
twolfe21/sideprojects
|
https://github.com/twolfe21/sideprojects
|
c04d0d6e9044e381bef10f5d11d38660aaa9eac9
|
e4292b962ef234bc1069c2d77e763a0ab9389232
|
a8272c36b77d9988c6c85b6b8922bf9ed59e2b52
|
refs/heads/master
| 2019-06-17T10:52:54.839932
| 2019-03-15T01:48:33
| 2019-03-15T01:48:33
| 99,933,703
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5827338099479675,
"alphanum_fraction": 0.5953237414360046,
"avg_line_length": 14.800000190734863,
"blob_id": "eddc977de4e3fe43456d4cb10ad0a6c623521c9e",
"content_id": "c816891cb97bc23b27e956fd10acc30709f0ebcc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 556,
"license_type": "no_license",
"max_line_length": 52,
"num_lines": 35,
"path": "/c/reverse/reverse.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n#include <stdlib.h>\n#include <string.h>\n\nchar* reverse(char*, int);\n\nint main()\n{\t\n\tconst int MAX_SIZE = 100;\n\tint size;\n\tchar* input = (char*)malloc(MAX_SIZE*sizeof(char));\n\t\n\tprintf(\"Enter text: \");\n\tfgets(input, MAX_SIZE, stdin);\n\tsize = strlen(input);\n\t\n\tinput = reverse(input, size);\n\tprintf(\"Your input reversed: %s\\n\", input);\n\treturn 0;\t\n}\n\n\t\nchar* reverse(char* s, int size)\n{\n\tint i;\n\tint j = 0;\n\tchar* temp = (char*)malloc(size*sizeof(char));\n\tfor(i = size; i > 0; i--)\n\t{\n\t\ttemp[j] = s[i-1];\n\t\tj++;\t\n\t}\n\n\treturn temp;\t \n}\n\n\t\n"
},
{
"alpha_fraction": 0.5717566013336182,
"alphanum_fraction": 0.5763490200042725,
"avg_line_length": 21.28205108642578,
"blob_id": "4f833475154750ceb2e9cf26a53578b206efbcf9",
"content_id": "39e9a077315b4fbd716e47bc5a92b5d2201d7603",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 871,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 39,
"path": "/python/modules/garage.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import car\nimport sys\n\ngarage = []\ncount = 1\nwhile True:\n\tprint(\"FOR CAR #\" + str(count) + \"\\n--------------------\\n\")\n\tmake = input(\"Make: \")\n\tmodel = input(\"Model: \")\n\tyear = input(\"Year: \")\n\tcolor = input(\"Color: \")\n\tkind = input(\"Type of Car: \")\n\t\n\tnewCar = car.Car(make, model, year, color, kind)\n\tgarage.append(newCar)\n\n\tdoneWithInput = input(\"\\nWould you like to add another car to your Garage? (y/n)\\n\")\n\n\tif doneWithInput == \"y\":\n\t\tcount += 1\n\t\tcontinue\n\telif doneWithInput != \"n\":\n\t\tprint(\"Invalid input.\")\n\t\tsys.exit()\n\telse:\n\t\tbreak\n\n\n\n\ntotalAge = 0\nprint(\"MY GARAGE\\n==================\\n\")\t\t\nfor i in range(0, len(garage)):\n\tcar = garage[i]\n\tprint(car.color + \" \" + str(car.year) + \" \" + car.make + \" \" + car.model + \" \" + car.kind + \"\\n\")\n\ttotalAge += car.age()\n\n\nprint(\"The average age of cars in your garage is: \" + str((totalAge/len(garage))) + \"\\n\")\t\t\n"
},
{
"alpha_fraction": 0.5378274917602539,
"alphanum_fraction": 0.5410656332969666,
"avg_line_length": 18.865497589111328,
"blob_id": "15fcbc7f427660ed7eff6a652ebbfefb07cc5dc4",
"content_id": "5f772b1406890600c9d785d7ec0dc14bf2cb8a83",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 3397,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 171,
"path": "/c/dll/src/dll.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdlib.h>\n#include \"dll.h\"\n\nstatic struct dll_node* get_node_at_index(struct dll* list, int index)\n{\n int i;\n struct dll_node* current_node = list->head;\n\n if(index >= count(list) || index < 0)\n {\n return NULL;\n }\n\n for(i = 0; i < index; i++)\n {\n current_node = current_node->next;\n }\n\n return current_node;\n}\n\nvoid insert_at_index(struct dll* list, void* data, int index)\n{\n struct dll_node* new_node;\n struct dll_node* node_at_index;\n struct dll_node* next;\n\n if(index < 0 || index >= count(list))\n return;\n\n if(index == 0) \n {\n prepend(list, data);\n }\n else if(index == count(list))\n {\n append(list, data);\n }\n else\n {\n new_node = (struct dll_node*)malloc(sizeof(struct dll_node));\n node_at_index = get_node_at_index(list, index - 1);\n next = node_at_index->next;\n\n node_at_index->next = new_node;\n new_node->prev = node_at_index;\n\n new_node->next = next;\n next->prev = new_node;\n list->count++;\n }\n}\n\nvoid prepend(struct dll* list,void* data)\n{\n struct dll_node* new_node = (struct dll_node*)malloc(sizeof(struct dll_node));\n\n new_node->data = data;\n new_node->prev = NULL;\n new_node->next = list->head;\n list->head->prev = new_node;\n list->head = new_node;\n list->count++;\n}\n\nvoid append(struct dll* list, void* data)\n{\n struct dll_node* new_node = (struct dll_node*)malloc(sizeof(struct dll_node));\n new_node->data = data;\n new_node->prev = list->tail;\n\n if(list->tail != NULL) {\n list->tail->next = new_node;\n }\n\n new_node->next = NULL;\n list->tail = new_node;\n if(list->count == 0) {\n list->head = new_node;\n }\n list->count++;\n}\n\nvoid* remove_front(struct dll* list)\n{\n void* data;\n struct dll_node* head_node = list->head;\n\n if(list->count == 1) {\n list->head = NULL;\n list->tail = NULL;\n }\n else {\n list->head->next->prev = NULL;\n list->head = head_node->next;\n }\n\n list->count--;\n\n data = head_node->data;\n free(head_node);\n\n return data;\n}\n\nvoid* remove_end(struct dll* list)\n{\n void* data;\n struct dll_node* tail_node = list->tail;\n\n if(list->count == 1) {\n list->head = NULL;\n list->tail = NULL;\n }\n else {\n list->tail->prev->next = NULL;\n list->tail = tail_node->prev;\n }\n\n list->count--;\n\n data = tail_node->data;\n free(tail_node);\n\n return data;\n}\n\nvoid* remove_at_index(struct dll* list, int index)\n{\n struct dll_node* prev_node;\n struct dll_node* next_node;\n struct dll_node* node_to_remove;\n void* data;\n\n if(index >= count(list) || index < 0)\n {\n return NULL;\n }\n\n if(index == 0) \n {\n return remove_front(list);\n }\n else if(index == list->count - 1) \n {\n return remove_end(list);\n }\n else\n {\n node_to_remove = get_node_at_index(list, index);\n prev_node = node_to_remove->prev;\n next_node = node_to_remove->next;\n\n node_to_remove->next = NULL;\n node_to_remove->prev = NULL;\n\n prev_node->next = next_node;\n next_node->prev = prev_node;\n\n data = node_to_remove->data;\n free(node_to_remove); \n list->count--;\n\n return data;\n }\n}\n\nint count(struct dll* list)\n{\n return list->count;\n}\n"
},
{
"alpha_fraction": 0.6818181872367859,
"alphanum_fraction": 0.7121211886405945,
"avg_line_length": 12,
"blob_id": "ffc07df9a1f1f8d8224ffc48f060b615ce549f4e",
"content_id": "c94bfc3ca262f85f4aa513960621c7d69b865865",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 66,
"license_type": "no_license",
"max_line_length": 28,
"num_lines": 5,
"path": "/python/hello.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import random\nimport sys\nimport os\n\nprint(\"Hello World!\\n\" * 10)\n\n"
},
{
"alpha_fraction": 0.5895061492919922,
"alphanum_fraction": 0.5987654328346252,
"avg_line_length": 14.380952835083008,
"blob_id": "2489bb77f69fea19091c621c57cd4a3fe1e6072a",
"content_id": "d29f82e33f4128366d8bc99934eb58884a76955c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 324,
"license_type": "no_license",
"max_line_length": 45,
"num_lines": 21,
"path": "/c/factorial/factorial.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n\nunsigned long long fact(unsigned long long);\n\nint main()\n{\n unsigned long long input;\n printf(\"Input number: \");\n scanf(\"%llu\", &input);\n\n printf(\"%llu\\n\", fact(input));\n return 0; \n}\n\nunsigned long long fact(unsigned long long n)\n{\n if(n == 1)\n return n;\n\n return n * fact(n - 1);\n}\n\n"
},
{
"alpha_fraction": 0.5809524059295654,
"alphanum_fraction": 0.5809524059295654,
"avg_line_length": 8.363636016845703,
"blob_id": "91a425d691158e2a4e5262e44679036f2a46d63c",
"content_id": "17d71ac4e1180bbcffad92dda6f33c517b6d56f5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 105,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 11,
"path": "/c/fib/Makefile",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "\nCC=gcc\nCFLAGS=-Wall\nPROGS=fib.c\nEXE=fib\n\nall:\n\t$(CC) $(CFLAGS) $(PROGS) -o $(EXE)\n\nclean: \n\n\trm -f fib \n"
},
{
"alpha_fraction": 0.6561163663864136,
"alphanum_fraction": 0.6561163663864136,
"avg_line_length": 24.413043975830078,
"blob_id": "d2c4227f7f2d4afb21c35d2e4146c8272fca6895",
"content_id": "36675a5baccf86a408b32c4ddc6d012ac325b4ad",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 1169,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 46,
"path": "/c/dll/include/dll.h",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#ifndef _DLL_H\n#define _DLL_H\n\nstruct dll_node {\n void* data; /* pointer to data */\n struct dll_node* next; /* pointer to next node in list */\n struct dll_node* prev; /* pointer to prev node in list */\n};\n\nstruct dll {\n struct dll_node* head; /* pointer to head node */\n struct dll_node* tail; /* pointer to tail node */\n int count; /* number of nodes in the list */\n};\n\n/* insert new node with void* data at an index */\nvoid insert_at_index(struct dll*, void*, int);\n\n/* append to the end of the list */\nvoid append(struct dll*, void*);\n\n/* prepend to the front of the list */\nvoid prepend(struct dll*, void*);\n\n/* remove data at specified index */\nvoid* remove_at_index(struct dll*, int);\n\n/* remove specified data from list */\nvoid* remove_data(struct dll*, void*);\n\n/* remove data from front of list */\nvoid* remove_front(struct dll*);\n\n/* remove data from end of list */\nvoid* remove_end(struct dll*);\n\n/* get data at the specified index from the list */\nvoid* get_data_at_index(struct dll*, int);\n\n/* get specified data from list */\nvoid* get_data(struct dll*, void*);\n\n/* number of items in list */\nint count(struct dll*);\n\n#endif /* _DLL_H */\n"
},
{
"alpha_fraction": 0.4485049843788147,
"alphanum_fraction": 0.47508305311203003,
"avg_line_length": 17.24242401123047,
"blob_id": "9412c0f0237c3d6ff65f0ce58d8c69899c2319b0",
"content_id": "8ebaa4b2712c5a9c5e292cab2c2b349edf767c72",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 602,
"license_type": "no_license",
"max_line_length": 65,
"num_lines": 33,
"path": "/c/dll/src/main.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n#include <stdlib.h>\n#include \"dll.h\"\n\n\nint main(int argc, char** argv)\n{\n int i;\n int* data;\n struct dll* list = (struct dll*)malloc(sizeof(struct dll)); \n\n for(i = 0; i < 1000; i++) {\n data = malloc(sizeof(int));\n *data = i;\n append(list, (void*)data);\n }\n\n for(i = 0; i < 1000; i++) {\n data = malloc(sizeof(int));\n *data = i;\n prepend(list, (void*)data);\n }\n\n for(i = 0; i < 2000; i++) {\n data = remove_front(list);\n printf(\"%d\\n\", *data);\n free(data);\n }\n\n free(list);\n\n return 0;\n}\n"
},
{
"alpha_fraction": 0.5532544255256653,
"alphanum_fraction": 0.5591716170310974,
"avg_line_length": 16.789474487304688,
"blob_id": "62792a57396c01c22d6f5cb228cdb1d5b7ae1995",
"content_id": "09a8722edbdbcbd400ac78cc026734667bf4a751",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 338,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 19,
"path": "/c/dll/makefile",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "CC=gcc\nCFLAGS=-Wall -pedantic\nC_STD=-std=c89\nINC=include\nSRC=src\nOBJ=obj\nBIN=bin\nEXE=dll\n\nall:\n\t$(CC) $(CFLAGS) $(C_STD) -I $(INC) $(SRC)/dll.c $(SRC)/main.c -o $(BIN)/$(EXE)\n\ndebug:\n\t$(CC) $(CFLAGS) $(C_STD) -I $(INC) $(SRC)/dll.c $(SRC)/main.c -g -o $(BIN)/$(EXE)_debug\n\tgdb --tui $(BIN)/$(EXE)_debug\n\n\nclean:\n\trm -rf $(BIN)/* $(OBJ)/*\n"
},
{
"alpha_fraction": 0.5965909361839294,
"alphanum_fraction": 0.6008522510528564,
"avg_line_length": 22.081966400146484,
"blob_id": "dde8cdc56512e0971db0739a836ca541c9b3a8a9",
"content_id": "5bb58bca71b06b09db5be4f7964596dfe492b97c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 1408,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 61,
"path": "/c/pressF.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n#include <stdlib.h>\n#include <string.h>\n\n#define MAX_STR_LEN 256\n#define FILE_NAME \"/.respeccs\"\n#define READ \"r\"\n#define WRITE \"w+\"\n\n/* handle reading of the file, or creation if needed */\nint read_num_respeccs(FILE* fp, char* const path) {\n\n int num_respeccs = -1;\n char respeccs_str[MAX_STR_LEN];\n\n if(fp != NULL) {\n /* we're good, so read from the file and convert to int. */\n fgets(respeccs_str, MAX_STR_LEN, fp);\n num_respeccs = atoi(respeccs_str);\n fclose(fp);\n }\n else {\n /* fp is NULL, so it likely doesn't exist. create it. */\n char cmd[MAX_STR_LEN];\n strncpy(cmd, \"touch \", MAX_STR_LEN);\n strncat(cmd, path, MAX_STR_LEN);\n num_respeccs = 0;\n system(cmd);\n }\n\n\n return num_respeccs;\n}\n\n\nvoid write_num_respeccs(FILE* fp, int num_respeccs) {\n\n if(fp != NULL) {\n fprintf(fp, \"%d\\n\", num_respeccs);\n }\n\n}\n\nint main(int argc, char** argv) {\n\n int num_respeccs;\n char path[MAX_STR_LEN];\n FILE* respecc_filep;\n\n strncpy(path, getenv(\"HOME\"), MAX_STR_LEN);\n strncat(path, FILE_NAME, MAX_STR_LEN);\n respecc_filep = fopen(path, READ);\n\n num_respeccs = read_num_respeccs(respecc_filep, path);\n respecc_filep = fopen(path, WRITE);\n write_num_respeccs(respecc_filep, ++num_respeccs);\n\n printf(\"Number of respects paid: %d\\n\", num_respeccs);\n\n return 0;\n}\n"
},
{
"alpha_fraction": 0.5447761416435242,
"alphanum_fraction": 0.6268656849861145,
"avg_line_length": 15.75,
"blob_id": "f1c14ec7a96fd26c1647a77b95835fe77568a753",
"content_id": "da6fb062f188ca24fac955d20792a59208af5e5f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 134,
"license_type": "no_license",
"max_line_length": 41,
"num_lines": 8,
"path": "/python/list.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import random\nimport sys\nimport os\n\nintegers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 0]\n\nfor i in range (0, len(integers)):\n\tprint(integers[i])\n"
},
{
"alpha_fraction": 0.5502008199691772,
"alphanum_fraction": 0.5783132314682007,
"avg_line_length": 11.300000190734863,
"blob_id": "e20406b7f62575e66b5cef6d4eddfeb5814def85",
"content_id": "2ee1d085dce832ec88a9455600f65b0a54565700",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 249,
"license_type": "no_license",
"max_line_length": 48,
"num_lines": 20,
"path": "/python/fib.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import sys\nimport os\n\ndef fib(n):\n\tif(n < 0):\n\t\tprint(\"Invalid input.\")\n\t\tsys.exit()\n\tif n == 1:\n\t\treturn 0\n\telif n == 2:\n\t\treturn 1\n\telse:\n\t\treturn fib(n - 2) + fib(n - 1)\n\n\n\n\nnumber = int(input(\"Enter an integer number: \"))\n\nprint(fib(number))\n\n \n"
},
{
"alpha_fraction": 0.6047008633613586,
"alphanum_fraction": 0.632478654384613,
"avg_line_length": 17.639999389648438,
"blob_id": "acdb956c8f70e61883a0911e03e1bd0cf8cbc608",
"content_id": "f5049e0922c728023dde3c9256a0d3f3816bad61",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 468,
"license_type": "no_license",
"max_line_length": 52,
"num_lines": 25,
"path": "/python/age.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import os\nimport sys\n\ndef getAge():\n\tage = int(input(\"How old are you?\\n\"))\n\tif age < 0:\n\t\tprint(\"Error! You can't be \" + age + \"years old!\")\n\t\tgetAge()\n\treturn age\n\n\nmyAge = getAge()\n\n\nif myAge < 16:\n\tprint(\"You're not old enough to do anything!\")\n\nif myAge >= 16 and myAge < 18:\n\tprint(\"You can drive, but that's about it!\")\n\nif myAge >= 18 and myAge < 21:\n\tprint(\"You can vote and buy tobacco products!\")\n\nif myAge >= 21: \n\tprint(\"There's nothing you can't do!\")\n\n\n"
},
{
"alpha_fraction": 0.6703910827636719,
"alphanum_fraction": 0.6849161982536316,
"avg_line_length": 17.244897842407227,
"blob_id": "5b1f2da7e95405343299673af10100e83fe5aeae",
"content_id": "1f0084342aa090ac620b202cf05cb0bbbbfba755",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 895,
"license_type": "no_license",
"max_line_length": 64,
"num_lines": 49,
"path": "/c/digit_isolator/isolator.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n\ndouble voltageRes;\nint adcCount;\ndouble voltageADC;\n\nint onesPlace(double voltsADC);\n\nint tenthsPlace(double voltsADC);\n\nint hundredthsPlace(double voltsADC);\n\nint main()\n{\n\tprintf(\"Input V_res: \\n\");\n\tscanf(\"%lf\", &voltageRes);\n\tprintf(\"\\nInput ADC Count: \\n\");\n\tscanf(\"%d\", &adcCount);\n\n\tvoltageADC = voltageRes * adcCount;\n\n\tprintf(\"\\n%f\", voltageADC);\n\n\tprintf(\"\\nOne's place: %d\\n\", onesPlace(voltageADC));\n\tprintf(\"Tenth's place: %d\\n\", tenthsPlace(voltageADC));\n\tprintf(\"Hundredth's place: %d\\n\", hundredthsPlace(voltageADC));\n\t\n\treturn 0;\n}\n\nint onesPlace(double voltsADC)\n{\n\tint ones = (int)voltsADC / 1;\n\treturn ones;\n}\n\nint tenthsPlace(double voltsADC)\n{\n\tvoltsADC = voltsADC * 10;\n\tint tenths = ((int)voltsADC % 10) / 1; \n\treturn tenths;\n}\n\nint hundredthsPlace(double voltsADC)\n{\n\tvoltsADC = voltsADC * 100;\n\tint hund = ((int)voltsADC % 10) / 1;\n\treturn hund;\n}\n\n"
},
{
"alpha_fraction": 0.4865470826625824,
"alphanum_fraction": 0.49551570415496826,
"avg_line_length": 20.934425354003906,
"blob_id": "1a6869231e06423467703b56d69a56585bdbaea8",
"content_id": "51f7a9e9a8b95dfc1751ba438aef243a02b70b7e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1338,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 61,
"path": "/python/sll/SLLNode.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "class SLLNode:\n\n def __init__(self, data=None, nxt=None):\n self.data = data\n self.nxt = nxt\n\n def getData(self):\n return self.data\n\n def setData(self, data):\n self.data = data\n\n def getNext(self):\n return self.nxt\n\n def setNext(self, nxt):\n self.nxt = nxt\n\n def __str__(self):\n return slf.data\n\n\nclass SingleLinkedList:\n\n def __init__(self):\n self.head = None\n self.tail = None\n self.size = 0\n\n def append(self, data):\n newNode = SLLNode(data, None)\n\n if self.size == 0:\n self.head = newNode\n self.tail = newNode\n self.size += 1\n\n elif self.size == 1:\n self.tail = newNode\n self.head.setNext(self.tail)\n self.size += 1\n else:\n self.tail.setNext(newNode)\n self.tail = newNode\n self.size += 1\n\n def get(self, index):\n if index > self.size or index < 0:\n print(\"Invalid index!\")\n return\n if index == 0 and self.size == 0:\n print(\"There is nothing in the list to get\")\n return\n\n i = 0\n current = self.head\n while i < self.size - 1 and i < index:\n current = current.getNext()\n i += 1\n\n return current.getData()\n"
},
{
"alpha_fraction": 0.7259259223937988,
"alphanum_fraction": 0.7481481432914734,
"avg_line_length": 10.25,
"blob_id": "8fcae9e91506d76d34a9dd4ddf99e5dbc9b64723",
"content_id": "7e29c29a1e701b1d593e321d7f754c4e3ea01d3f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 135,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 12,
"path": "/python/sll/ListTest.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import os\nimport SLLNode\n\n\nsllist = SLLNode.SingleLinkedList()\n\nsllist.append(1)\nsllist.append(2)\n\nmyVar = sllist.get(1)\n\nprint(myVar)\n"
},
{
"alpha_fraction": 0.5154929757118225,
"alphanum_fraction": 0.5408450961112976,
"avg_line_length": 10.09375,
"blob_id": "a2515ac3a734cc318e5d1f5c8727a3ed3dd7351e",
"content_id": "919497dd594522703b80a681b34fbbc533826135",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C",
"length_bytes": 355,
"license_type": "no_license",
"max_line_length": 36,
"num_lines": 32,
"path": "/c/fib/fib.c",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "#include <stdio.h>\n#include <stdlib.h>\n\nint fib(int);\n\nint main()\n{\n\tint input;\n\n\tprintf(\"Enter a number: \");\n\tscanf(\"%d\", &input);\n\n\tprintf(\"%d\\n\", fib(input));\n\n\treturn 0;\n}\n\nint fib(int n)\n{\n\tif(n < 0)\n\t{\n\t\tprintf(\"\\nError. Invalid input.\");\n\t\texit(1);\n\t}\n\n\tif(n == 0)\n\t\treturn 0;\n\telse if(n == 1)\n\t\treturn 1;\n\telse\n\t\treturn fib(n - 2) + fib(n - 1);\n}\n"
},
{
"alpha_fraction": 0.6696969866752625,
"alphanum_fraction": 0.6696969866752625,
"avg_line_length": 18.235294342041016,
"blob_id": "1108c7587dde9c54fcccff4a3ba172c161a48c22",
"content_id": "1d57d03c0c4ed5fee4b9efd40be6d0cd369cacbe",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 330,
"license_type": "no_license",
"max_line_length": 52,
"num_lines": 17,
"path": "/python/modules/car.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import os\nimport datetime #used for determining age of vehicle\n\nclass Car:\n\n\tdef __init__(self, make, model, year, color, kind):\n\t\tself.make = make\n\t\tself.model = model\n\t\tself.year = int(year)\n\t\tself.color = color\n\t\tself.kind = kind\n\n\n\tdef age(self):\n\t\ttoday = datetime.date.today()\n\t\tage = today.year - self.year\n\t\treturn age\n\n\t\n"
},
{
"alpha_fraction": 0.800000011920929,
"alphanum_fraction": 0.800000011920929,
"avg_line_length": 20.5,
"blob_id": "88f4ad6d1635c2579bd4c19d8fc9d382455a08d9",
"content_id": "499ebe80a77edf901439ccc37fb37e0cb8cf1115",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 45,
"license_type": "no_license",
"max_line_length": 30,
"num_lines": 2,
"path": "/python/reddit_inbox/reddit_inbox.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "from twilio.rest import Client\nimport praw\n\n\n"
},
{
"alpha_fraction": 0.6350364685058594,
"alphanum_fraction": 0.6350364685058594,
"avg_line_length": 15.875,
"blob_id": "a8f62567c303557cadc05d3958267107d36b966e",
"content_id": "daa73ed6b0686851c23dbb4e01bf7f38337d51e5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 137,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 8,
"path": "/python/file/text.py",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "import os\nimport sys\n\ns = input(\"Enter some text to be written to file:\\n\")\n\nwith open('hello.txt', 'w+') as f:\n\tf.write(s)\n\tf.close()\n\n\n"
},
{
"alpha_fraction": 0.5692307949066162,
"alphanum_fraction": 0.5692307949066162,
"avg_line_length": 8.142857551574707,
"blob_id": "bf11b60d7843e6ea029be6410843aebea712daf4",
"content_id": "946edee17a6ba35d23ef6b5027696ee10676a5df",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 130,
"license_type": "no_license",
"max_line_length": 25,
"num_lines": 14,
"path": "/c/reverse/Makefile",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "\nCC = gcc\nPROGS = reverse.c\nEXE = reverse\n\nall: reverse.c\n\n\t$(CC) $(PROGS) -o $(EXE)\n\nrev: all\n\t./$(EXE)\n\nclean:\n\n\trm -f reverse\n\n"
},
{
"alpha_fraction": 0.6052631735801697,
"alphanum_fraction": 0.6052631735801697,
"avg_line_length": 9.181818008422852,
"blob_id": "112a41de595da6c650ece7dca609a45229ab0a1d",
"content_id": "6f8574dec7d634680e2b09036110072f00a0a8d7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Makefile",
"length_bytes": 114,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 11,
"path": "/c/factorial/Makefile",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "\nCC=gcc \nCFLAGS=-Wall \nPROGS=factorial.c\nEXE=fact\n\nall:\n\t$(CC) $(CFLAGS) $(PROGS) -o $(EXE)\n\nclean:\n\n\trm -f fact \n"
},
{
"alpha_fraction": 0.45945945382118225,
"alphanum_fraction": 0.5135135054588318,
"avg_line_length": 8.25,
"blob_id": "e9980d337b1324801c9430848111d90deb46b5a1",
"content_id": "bc639bdf4fe66ee698a3f9cb7f3095792af7877c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "PHP",
"length_bytes": 74,
"license_type": "no_license",
"max_line_length": 22,
"num_lines": 8,
"path": "/php/run.php",
"repo_name": "twolfe21/sideprojects",
"src_encoding": "UTF-8",
"text": "<?php\ninclude(\"point.php\");\n\n$p1 = new Point(1, 1);\n\nprint $p1 .\"\\n\";\n\n?>\n"
}
] | 23
|
flc/django-recurly
|
https://github.com/flc/django-recurly
|
70683a87794169b8b2fa129536c24422f3117554
|
4aa1e25c2108f481049db833ae2f30a899dddf01
|
a0c0914e5b1257d27718ebc0a2a1c4bda9b180e1
|
refs/heads/master
| 2021-01-17T03:15:52.637902
| 2014-07-14T18:46:24
| 2014-07-14T18:46:24
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6886447072029114,
"alphanum_fraction": 0.6886447072029114,
"avg_line_length": 21.75,
"blob_id": "261fcc11274c7149071e2ac3db3d3d2201964b5d",
"content_id": "e8ecaa089a0eab9aef337532b06ac40a80ff084e",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 273,
"license_type": "permissive",
"max_line_length": 50,
"num_lines": 12,
"path": "/django_recurly/admin.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "from django.contrib import admin\n\nfrom . import models\n\n\nclass AccountAdmin(admin.ModelAdmin):\n list_display = ('user', 'account_code',)\n search_fields = ('=user__id', '=account_code')\n raw_id_fields = ('user',)\n\n\nadmin.site.register(models.Account, AccountAdmin)\n"
},
{
"alpha_fraction": 0.7917159795761108,
"alphanum_fraction": 0.7917159795761108,
"avg_line_length": 45.94444274902344,
"blob_id": "f0cc77ddecc820ee60896f103ef174d41e7da329",
"content_id": "50832b7497e90c1a6be0747cc3d37ace84feb4cf",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 845,
"license_type": "permissive",
"max_line_length": 71,
"num_lines": 18,
"path": "/django_recurly/constants.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "# A subscription will belong to more than one state.\n\n# Subscriptions that are valid for the current time.\n# This includes subscriptions in a trial period\nSUBSCRIPTION_STATE_ACTIVE = \"active\"\n# Subscriptions that are valid for the current time but\n# will not renew because a cancelation was requested\nSUBSCRIPTION_STATE_CANCELED = \"canceled\"\n# Subscriptions that have expired and are no longer valid\nSUBSCRIPTION_STATE_EXPIRED = \"expired\"\n# Subscriptions that will start in the future, they are not active yet\nSUBSCRIPTION_STATE_FUTURE = \"future\"\n# Subscriptions that are active or canceled and are in a trial period\nSUBSCRIPTION_STATE_IN_TRIAL = \"in_trial\"\n# All subscriptions that are not expired\nSUBSCRIPTION_STATE_LIVE = \"live\"\n# Subscriptions that are active or canceled and have a past-due invoice\nSUBSCRIPTION_STATE_PAST_DUE = \"past_due\"\n"
},
{
"alpha_fraction": 0.6681151390075684,
"alphanum_fraction": 0.6681151390075684,
"avg_line_length": 28.22222137451172,
"blob_id": "37d2a84ad8586529e2d5824409ec194418c9131d",
"content_id": "7d836ae2d7dbcec66298202ed71c1b6e5f294722",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1841,
"license_type": "permissive",
"max_line_length": 78,
"num_lines": 63,
"path": "/django_recurly/models.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "import logging\nimport recurly\n\nfrom django.conf import settings\nfrom django.db import models\nfrom django.utils.translation import ugettext_lazy as _\n\nfrom shortuuidfield import ShortUUIDField\n\nfrom . import settings as app_settings\nfrom .utils import (\n get_hosted_account_management_url,\n get_hosted_payment_page_url,\n )\n\n\nrecurly.SUBDOMAIN = app_settings.RECURLY_SUBDOMAIN\nrecurly.API_KEY = app_settings.RECURLY_API_PRIVATE_KEY\nrecurly.DEFAULT_CURRENCY = app_settings.RECURLY_DEFAULT_CURRENCY\n\n\nlogger = logging.getLogger(__name__)\n\n\nclass Account(models.Model):\n user = models.ForeignKey(\n settings.AUTH_USER_MODEL,\n related_name=\"recurly_account\",\n null=True, blank=True,\n on_delete=models.SET_NULL,\n )\n account_code = ShortUUIDField(\n unique=True,\n db_index=True,\n )\n # store this for caching purposes\n hosted_login_token = models.TextField(blank=True)\n\n def get_hosted_account_management_url(self):\n if not self.hosted_login_token:\n return None\n return get_hosted_account_management_url(self.hosted_login_token)\n\n def get_hosted_payment_page_url_params(self):\n data = {\n 'first_name': self.user.first_name,\n 'last_name': self.user.last_name,\n 'email': self.user.email,\n 'username': getattr(self.user, \"username\", None),\n }\n return data\n\n def get_hosted_payment_page_url(self, plan_code):\n data = self.get_hosted_payment_page_url_params()\n return get_hosted_payment_page_url(plan_code, self.account_code, data)\n\n @classmethod\n def get_or_create_from_user(cls, user):\n obj, created = cls.objects.get_or_create(user=user)\n return obj, created\n\n def fetch_from_api(self):\n return recurly.Account.get(self.account_code)\n"
},
{
"alpha_fraction": 0.6013985872268677,
"alphanum_fraction": 0.6022727489471436,
"avg_line_length": 25.604650497436523,
"blob_id": "247a50d8929fde9999a938c018b919ddf8b228d2",
"content_id": "f0b7e956ae6e37ab084cdb61618d6f155d7aee3d",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1144,
"license_type": "permissive",
"max_line_length": 72,
"num_lines": 43,
"path": "/django_recurly/utils.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "import urllib\nimport urlparse\n\nfrom . import settings as app_settings\n\n\ndef get_hosted_account_management_url(hosted_login_token):\n return 'https://%s.recurly.com/account/%s' % (\n app_settings.RECURLY_SUBDOMAIN,\n hosted_login_token,\n )\n\n\ndef encode_dict(data):\n return dict([\n (key, val.encode('utf-8')) for key, val in data.items()\n if isinstance(val, basestring)\n ])\n\n\ndef get_hosted_payment_page_url(plan_code, account_code, data=None):\n if not data:\n data = {}\n\n # passing account_code and username as a query param would also work\n # data['account_code'] = account_code\n # url = 'https://%s.recurly.com/subscribe/%s/%s' % (\n # app_settings.RECURLY_SUBDOMAIN,\n # plan_code,\n # urllib.urlencode(encode_dict(data))\n # )\n url = 'https://%s.recurly.com/subscribe/%s/%s/' % (\n app_settings.RECURLY_SUBDOMAIN,\n plan_code,\n account_code,\n )\n username = data.pop(\"username\", None)\n if username:\n url = urlparse.urljoin(url, username)\n return '%s?%s' % (\n url,\n urllib.urlencode(encode_dict(data)),\n )\n"
},
{
"alpha_fraction": 0.7926663756370544,
"alphanum_fraction": 0.7926663756370544,
"avg_line_length": 48.64044952392578,
"blob_id": "0437a754a4ade938341be2d08cdceae311d08c48",
"content_id": "49998f10d9fb1facdc640e6dda69b3a8ab4e329b",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4418,
"license_type": "permissive",
"max_line_length": 102,
"num_lines": 89,
"path": "/django_recurly/signals.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "# https://docs.recurly.com/api/push-notifications\n# https://docs.recurly.com/push-notifications\n# IMPORTANT!\n# Webhooks are not actionable on their own and should not be used for critical functions\n# like provisioning accounts. Use the receipt of a webhook to trigger an API query to\n# validate the push notification details against the current API data.\n\nfrom django.dispatch import Signal\n\n\n# Account Notifications\n\n# New Account\n# Sent when a new account is created.\nnew_account_notification = Signal(providing_args=('data',))\n# Closed Account\n# Sent when an account is closed.\ncanceled_account_notification = Signal(providing_args=('data',))\n# Updated Billing Information\n# Sent when billing information is successfully created or updated on an account.\nbilling_info_updated_notification = Signal(providing_args=('data',))\n# Reactivated Account\n# Sent when an account subscription is reactivated after having been canceled.\nreactivated_account_notification = Signal(providing_args=('data',))\n\n\n# Invoices\n\n# New Invoice, New Invoice (Manual)\n# If a new invoice is generated, a new_invoice_notification is sent.\nnew_invoice_notification = Signal(providing_args=('data',))\n# Closed Invoice, Closed Invoice (Manual)\nclosed_invoice_notification = Signal(providing_args=('data',))\n# Past Due Invoice, Past Due Invoice (Manual)\npast_due_invoice_notification = Signal(providing_args=('data',))\n\n\n# Subscription Notifications\n\n# New Subscription\n# Sent when a new subscription is created.\nnew_subscription_notification = Signal(providing_args=('data',))\n# Updated Subscription\n# When a subscription is upgraded or downgraded, Recurly will send an\n# updated_subscription_notification. The notification is sent after the\n# modification is performed. If you modify a subscription and it takes place\n# immediately, the notification will also be sent immediately. If the\n# subscription change takes effect at renewal, then the notification will be\n# sent when the subscription renews. Therefore, if you receive an\n# updated_subscription_notification, it contains the latest subscription information.\nupdated_subscription_notification = Signal(providing_args=('data',))\n# Canceled Subscription\n# The canceled_subscription_notification is sent when a subscription is canceled.\n# This means the subscription will not renew. The subscription state is set to\n# canceled but the subscription is still valid until the expires_at date.\n# The next notification is sent when the subscription is completely terminated.\ncanceled_subscription_notification = Signal(providing_args=('data',))\n# Expired Subscription\n# The expired_subscription_notification is sent when a subscription is no longer valid.\n# This can happen if a canceled subscription expires or if an active subscription is refunded\n# (and terminated immediately). If you receive this message, the account no longer has a subscription.\nexpired_subscription_notification = Signal(providing_args=('data',))\n# Renewed Subscription\n# The renewed_subscription_notification is sent whenever a subscription renews.\n# This notification is sent regardless of a successful payment being applied to the\n# subscription-it indicates the previous term is over and the subscription is now in a new term.\n# If you are performing metered or usage-based billing, use this notification to reset your\n# usage stats for the current billing term.\nrenewed_subscription_notification = Signal(providing_args=('data',))\n\n\n# Payments\n\n# Successful Payment, Manual Payment\n# A successful_payment_notification is sent when a payment is successfully captured.\n# A successful_payment_notification is also sent when a manual offline payment is recorded.\nsuccessful_payment_notification = Signal(providing_args=('data',))\n# Failed Payment\n# A failed_payment_notification is sent when a payment attempt is declined\n# by the payment gateway.\nfailed_payment_notification = Signal(providing_args=('data',))\n# Successful Refund\n# If you refund an amount through the API or admin interface, a successful_refund_notification\n# is sent. Failed refund attempts do not generate a notification.\nsuccessful_refund_notification = Signal(providing_args=('data',))\n# Void Payment\n# If you void a successfully captured payment before it settles, a void_payment_notification\n# is sent. Payments can only be voided before the funds settle into your merchant account.\nvoid_payment_notification = Signal(providing_args=('data',))\n"
},
{
"alpha_fraction": 0.6192196607589722,
"alphanum_fraction": 0.6217485666275024,
"avg_line_length": 30.089887619018555,
"blob_id": "d7804437f5507439a028fc1ab539d5c1d4a48c32",
"content_id": "8c5a2e5d2e670242b8391e7f22a097216f0dce03",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2768,
"license_type": "permissive",
"max_line_length": 76,
"num_lines": 89,
"path": "/django_recurly/views.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "import logging\n\nimport recurly\n\nfrom django.conf import settings\nfrom django.http import HttpResponse, HttpResponseBadRequest\nfrom django.views.decorators.csrf import csrf_exempt\nfrom django.views.decorators.http import require_POST\n\nfrom .decorators import recurly_basic_authentication\nfrom . import signals\nfrom .models import Account\n\n\nlogger = logging.getLogger(__name__)\n\n\n@csrf_exempt\n@recurly_basic_authentication\n@require_POST\ndef push_notification(request):\n # big try catch because we don't want to send recurly any\n # technical error response with all our settings if we happen to\n # test the webhooks with DEBUG=True\n try:\n data = recurly.objects_for_push_notification(request.body)\n\n try:\n _type = data['type']\n logger.info(\"Recurly notification: %s\", _type)\n signal = getattr(signals, _type)\n except AttributeError:\n return HttpResponseBadRequest(\"Unrecognized notification type.\")\n\n signal.send(sender=request, data=data)\n except Exception as e:\n if settings.DEBUG:\n logger.exception(e)\n return HttpResponse(status=500)\n raise\n\n return HttpResponse()\n\n\nif 'rest_framework' in settings.INSTALLED_APPS:\n from rest_framework.views import APIView\n from rest_framework.response import Response\n from rest_framework import authentication, permissions\n from rest_framework import status\n\n\n class HostedPaymentPageData(APIView):\n allowed_methods = ['post']\n\n permission_classes = (permissions.IsAuthenticated, )\n\n def post(self, request, format=None):\n # we use POST because it's possible that there is no\n # associated Account object for the user yet and we\n # need to create it and generate a unique account_code\n # for it\n try:\n plan_code = request.DATA['plan_code']\n except KeyError:\n return Response(\n {'plan_code': 'Plan code is missing'},\n status=status.HTTP_400_BAD_REQUEST,\n )\n\n user = request.user\n account, created = Account.get_or_create_from_user(user)\n return Response({\n 'url': account.get_hosted_payment_page_url(plan_code)\n })\n\n\n class HostedAccountManagementPageData(APIView):\n\n def get(self, request, format=None):\n user = request.user\n try:\n account = Account.objects.filter(user=request.user)[0]\n except IndexError:\n url = None\n else:\n url = account.get_hosted_account_management_url()\n return Response({\n 'url': url\n })\n\n"
},
{
"alpha_fraction": 0.7623604536056519,
"alphanum_fraction": 0.7623604536056519,
"avg_line_length": 40.79999923706055,
"blob_id": "c87d815c0674a56bd34b80b1b9f5becbd627cc21",
"content_id": "8e3410b0e8babfe247e6088887cb97dd188e2b91",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 627,
"license_type": "permissive",
"max_line_length": 74,
"num_lines": 15,
"path": "/django_recurly/settings.py",
"repo_name": "flc/django-recurly",
"src_encoding": "UTF-8",
"text": "from django.conf import settings\n\n\nRECURLY_SUBDOMAIN = settings.RECURLY_SUBDOMAIN\nRECURLY_API_PRIVATE_KEY = settings.RECURLY_API_PRIVATE_KEY\nRECURLY_API_PUBLIC_KEY = getattr(settings, \"RECURLY_API_PUBLIC_KEY\", None)\nRECURLY_JS_PRIVATE_KEY = getattr(settings, \"RECURLY_JS_PRIVATE_KEY\", None)\nRECURLY_DEFAULT_CURRENCY = getattr(\n settings, \"RECURLY_DEFAULT_CURRENCY\",\n getattr(settings, \"SITE_CURRENCY\", \"USD\")\n )\n# The username & password used to authorise Recurly's\n# webhook. In the format \"username:password\"\nRECURLY_WEBHOOK_HTTP_AUTHENTICATION = \\\n getattr(settings, 'RECURLY_WEBHOOK_HTTP_AUTHENTICATION', None)\n"
}
] | 7
|
CarlosTechTalents/curso-python-tkinter-i
|
https://github.com/CarlosTechTalents/curso-python-tkinter-i
|
c8b42d606ba5911b918585116c45bd712d07e063
|
117bd834868793e952c86687c43136f727206885
|
3274912cf69c1b5393dad96bef625487dc88f8d2
|
refs/heads/main
| 2023-02-16T07:17:07.803887
| 2021-01-19T08:37:39
| 2021-01-19T08:37:39
| 330,913,694
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6450880169868469,
"alphanum_fraction": 0.6774559617042542,
"avg_line_length": 45.342105865478516,
"blob_id": "8593cfaca95427160b9c414db425ef9e8b515c29",
"content_id": "27efa4c868c39869cff345ebc432739c0f383d6c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1761,
"license_type": "no_license",
"max_line_length": 287,
"num_lines": 38,
"path": "/09-sierpinsky_triangle.py",
"repo_name": "CarlosTechTalents/curso-python-tkinter-i",
"src_encoding": "UTF-8",
"text": "from tkinter import *\nimport random\nimport math\n\n\ndef plotpoint(x, y):\n global canvas\n # point = canvas.create_line(x-1, y-1, x+1, y+1, fill = \"#000000\")\n point = canvas.create_oval(x, y, x, y, fill=\"#000000\", outline=\"#000000\")\n\n\nx = 0 # Initial coordinates\ny = 0\n# x and y will always be in the interval [0, 1]\nmod = int(input(\"What is the modulo of the Sierpinsky triangle that you want to generate? (try:3)\"))\npoints = int(input(\"How many points do you want the triangle to have? (try:100.0000\"))\ntkengine = Tk() # Window in which the triangle will be generated\nwindow = Frame(tkengine)\nwindow.pack()\n# The dimensions of the canvas make the triangle look equilateral\ncanvas = Canvas(window, height=700, width=808, bg=\"#FFFFFF\")\ncanvas.pack()\nfor t in range(points):\n # Procedure for placing the points\n while True:\n # First, randomly choose one of the mod(mod+1)/2 triangles of the first step. a and b are two vectors which point to the chosen triangle. a goes one triangle to the right and b one up-right. The algorithm gives the same probability to every triangle, although it's not efficient.\n a = random.randint(0, mod - 1)\n b = random.randint(0, mod - 1)\n if a + b < mod:\n break\n # The previous point is dilated towards the origin of coordinates so that the big triangle of step 0 becomes the small one at the bottom-left of step one (divide by modulus). Then the vectors are added in order to move the point to the same place in another triangle.\n x = x / mod + a / mod + b / 2 / mod\n y = y / mod + b / mod\n # Coordinates [0,1] converted to pixels, for plotting in the canvas.\n X = math.floor(x * 808)\n Y = math.floor((1 - y) * 700)\n plotpoint(X, Y)\ntkengine.mainloop()\n"
},
{
"alpha_fraction": 0.7599999904632568,
"alphanum_fraction": 0.7599999904632568,
"avg_line_length": 24,
"blob_id": "debdafc398208299aebec43df9fd73498a81c1e5",
"content_id": "1f6fe83be46849339d8eb42d353264bf4907b50e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 25,
"license_type": "no_license",
"max_line_length": 24,
"num_lines": 1,
"path": "/README.md",
"repo_name": "CarlosTechTalents/curso-python-tkinter-i",
"src_encoding": "UTF-8",
"text": "# curso-python-tkinter-i\n"
},
{
"alpha_fraction": 0.6302250623703003,
"alphanum_fraction": 0.68006432056427,
"avg_line_length": 28.619047164916992,
"blob_id": "c2e9cd27ff325cfedb3586b01e376dcca56ce5bb",
"content_id": "33016e701a7473e1f593d3282d0194fb8928bb84",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 627,
"license_type": "no_license",
"max_line_length": 75,
"num_lines": 21,
"path": "/main.py",
"repo_name": "CarlosTechTalents/curso-python-tkinter-i",
"src_encoding": "UTF-8",
"text": "import tkinter as tk\nfrom tkinter import ttk\n\nroot = tk.Tk()\n\nroot.geometry(\"600x400\")\n\nrectangle_1 = tk.Label(root, text=\"Rectágulo 1\", bg=\"green\", fg=\"white\")\nrectangle_1.pack(side=\"left\", ipadx=10, ipady=10, fill=\"both\", expand=True)\n\nrectangle_2 = tk.Label(root, text=\"Rectángulo 2\", bg=\"red\", fg=\"white\")\nrectangle_2.pack(side=\"top\", ipadx=10, ipady=10, fill=\"both\", expand=True)\n\nrectangle_3 = tk.Label(root, text=\"Rectángulo 3\", bg=\"blue\", fg=\"white\")\nrectangle_3.pack(side=\"left\", ipadx=10, ipady=10, fill=\"both\")\n\nttk.Label(root, text=\"¡Hola Mundo!\", padding=(30, 10)).pack()\n\nroot.mainloop()\n\nprint(\"¡Hola Mundo!\")\n"
},
{
"alpha_fraction": 0.6076352000236511,
"alphanum_fraction": 0.6267232298851013,
"avg_line_length": 18.64583396911621,
"blob_id": "02a44c0acaeb3d6200f4baccd3f102b9dc3e5ec3",
"content_id": "c54e16a33e2b626fb4496e2255566948144403eb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 943,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 48,
"path": "/04-images.py",
"repo_name": "CarlosTechTalents/curso-python-tkinter-i",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python3\n\n\"\"\"\nZetCode Tkinter tutorial\n\nIn this script, we draw an image\non the canvas.\n\nAuthor: Jan Bodnar\nWebsite: www.zetcode.com\n\nRequiere intalar PIP y Pillow\npython3 -m pip install --upgrade pip\npython3 -m pip install --upgrade Pillow\n\"\"\"\n\nfrom tkinter import Tk, Canvas, Frame, BOTH, NW\nfrom PIL import Image, ImageTk\n\n\nclass Example(Frame):\n def __init__(self):\n super().__init__()\n\n self.initUI()\n\n def initUI(self):\n\n self.master.title(\"High Tatras\")\n self.pack(fill=BOTH, expand=1)\n\n self.img = Image.open(\"imagen1.jpg\")\n self.imagen1 = ImageTk.PhotoImage(self.img)\n\n canvas = Canvas(self, width=self.img.size[0] + 20, height=self.img.size[1] + 20)\n canvas.create_image(10, 10, anchor=NW, image=self.imagen1)\n canvas.pack(fill=BOTH, expand=1)\n\n\ndef main():\n\n root = Tk()\n ex = Example()\n root.mainloop()\n\n\nif __name__ == '__main__':\n main()\n"
}
] | 4
|
caibird2020/ABSADatasets
|
https://github.com/caibird2020/ABSADatasets
|
c4c1ccc7e6415bfb7ce877f99db0184efb2f71a7
|
17022c2ef494af2f35de2e9966358b072289d5a9
|
a304c474c8e694b6a41bfd4046882340a10526f3
|
refs/heads/master
| 2023-08-27T11:18:16.747051
| 2021-10-06T10:13:44
| 2021-10-06T10:13:44
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7538461685180664,
"alphanum_fraction": 0.7743589878082275,
"avg_line_length": 77.19999694824219,
"blob_id": "c9a908ab61d57456bf35c24f76125dc91ba983f8",
"content_id": "05198d070a58e8ea5852b38cc9ebffbdd895f4b8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 390,
"license_type": "no_license",
"max_line_length": 128,
"num_lines": 5,
"path": "/datasets/apc_datasets/README.md",
"repo_name": "caibird2020/ABSADatasets",
"src_encoding": "UTF-8",
"text": "The Chinese datasets has binary polarity labeled as 0 (Negative), 1 (Positive)\nThe multilingual dataset is the sum of other datasets and convert the Chinese polarities from {0, 1} to {0, 2},\nin order to fit the triple sentiment categories of English datasets. \n\nHowever, when construct your custom dataset, you should label the sentiment polarities in [0, N-1] (i.e., N types of polarities)"
},
{
"alpha_fraction": 0.7241764664649963,
"alphanum_fraction": 0.7828028798103333,
"avg_line_length": 50.17142868041992,
"blob_id": "014c956150c2f6f3a8913f556ecc67c9b7db0ecf",
"content_id": "18f57a8bfa7932497f319866211500747a28ae54",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1791,
"license_type": "no_license",
"max_line_length": 294,
"num_lines": 35,
"path": "/README.MD",
"repo_name": "caibird2020/ABSADatasets",
"src_encoding": "UTF-8",
"text": "# ABSA datasets for [PyABSA](https://github.com/yangheng95/PyABSA)\n\n## Dataset contribution\n\nWe hope you can share your custom dataset or a available public dataset. If you want to, follow these steps:\n\n- Format your APC dataset according to our dataset format. (**Recommended. Once you finoshed this step, we can help you to finish other steps**)\n- Generate the inference dataset for APC / ATEPC task (**Optional**. The example is available [here](https://github.com/yangheng95/PyABSA/blob/release/demos/aspect_polarity_classification/generate_inference_set.py))\n- Convert the APC dataset to ATEPC dataset, and move the transformed ATEPC datasets from apc_dataset to corresponding atepc_datasets. (**Optional**. The example is available [here](https://github.com/yangheng95/PyABSA/blob/release/demos/aspect_term_extraction/convert_apc_set_to_atepc_set.py) )\n- Register your dataset in PyABSA. (**Optional**. Register [here](https://github.com/yangheng95/PyABSA/blob/3238f319f6ee4938d728ed6ae61eb98b4753311a/pyabsa/functional/dataset/dataset_manager.py#L32))\n\n\n## Notice\n\nAll datasets provided are for research only, we do not hold any Copyright of any datasets. These datasets follow their original licenses (if any).\n\n## Datasets source:\n\nMAMS https://github.com/siat-nlp/MAMS-for-ABSA\n\nSemEval 2014: https://alt.qcri.org/semeval2014/task4/index.php?id=data-and-tools\n\nSemEval 2015: https://alt.qcri.org/semeval2015/task12/index.php?id=data-and-tools\n\nSemEval 2016: https://alt.qcri.org/semeval2016/task5/index.php?id=data-and-tools\n\nChinese: https://www.sciencedirect.com/science/article/abs/pii/S0950705118300972?via%3Dihub\n\nShampoo: brightgems@github\n\nMOOC: jmc-123@github\n\nTwitter: https://dl.acm.org/doi/10.5555/2832415.2832437\n\nTelevision & TShirt: https://github.com/rajdeep345/ABSA-Reproducibility\n"
},
{
"alpha_fraction": 0.5024154782295227,
"alphanum_fraction": 0.6231883764266968,
"avg_line_length": 22,
"blob_id": "7b79b63e501f2ef096ac38ad13908cbae6407821",
"content_id": "09fc60bfb16f4160ff961167a97475befb8a04b4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 207,
"license_type": "no_license",
"max_line_length": 42,
"num_lines": 9,
"path": "/datasets/__init__.py",
"repo_name": "caibird2020/ABSADatasets",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\n# file: __init__.py\n# time: 2021/6/8 0008\n# author: yangheng <yangheng@m.scnu.edu.cn>\n# github: https://github.com/yangheng95\n# Copyright (C) 2021. All Rights Reserved.\n\n\n__version__ = '2021.09.29'\n"
}
] | 3
|
kungeng/Leetcode-Linked-List
|
https://github.com/kungeng/Leetcode-Linked-List
|
17f08ed273fcaa9c163f062df69f4d4c9abe5245
|
65039938ede94b42b58a29f5c280d244430bfa51
|
3848b4a68e1a9d97caaeac140a7c94af9ae6845f
|
refs/heads/master
| 2021-01-19T09:18:45.037339
| 2017-04-09T23:41:12
| 2017-04-09T23:41:12
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.44585365056991577,
"alphanum_fraction": 0.4565853774547577,
"avg_line_length": 32.16666793823242,
"blob_id": "5f3e43618522093371baa24fe5a647f5f41a0c82",
"content_id": "d452673900d32242f10690317bb6904beee844b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1025,
"license_type": "no_license",
"max_line_length": 128,
"num_lines": 30,
"path": "/234E_Palindrome_Linked_List.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "class Solution(object):\r\n def isPalindrome(self, head):\r\n \"\"\"\r\n :type head: ListNode\r\n :rtype: bool\r\n \"\"\"\r\n if head == None:\r\n return True\r\n elif head != None and head.next == None:\r\n return True\r\n else:\r\n fast = head\r\n slow = head\r\n stack = []\r\n while fast != None and fast.next != None:\r\n stack.append(slow.val)\r\n slow = slow.next\r\n fast = fast.next.next\r\n\r\n\r\n if fast != None: #namely fast.next = None, namely this Palindrome has even number of digits, e.g. \"1->2->3->3->2->1\"\r\n slow = slow.next\r\n # otherwise, the Palindrome should has odd number of digits, e.g. \"1->2->3->2->1\"\r\n while slow != None:\r\n if slow.val != stack.pop(): #compare right handside to left handside\r\n return False\r\n else:\r\n slow = slow.next\r\n\r\n return True\r\n"
},
{
"alpha_fraction": 0.5100806355476379,
"alphanum_fraction": 0.5100806355476379,
"avg_line_length": 37.68000030517578,
"blob_id": "3407cb428c2efb26fafc4cc048fa14bcac27cef1",
"content_id": "6cc83941209d31a7d3b53fb57324aeab18cf5d0b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 992,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 25,
"path": "/Remove_Duplicate_1.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution(object):\r\n def deleteDuplicates(self, head):\r\n \"\"\"\r\n :type head: ListNode\r\n :rtype: ListNode\r\n \"\"\"\r\n if head == None or head.next == None:\r\n return head\r\n else:\r\n present = head # present is a node\r\n next_nd = head.next # next_nd is a node, which is used for removing items\r\n while next_nd != None:\r\n if next_nd.val == present.val:\r\n present.next = next_nd.next # advance the node of present, remove/skip next_nd\r\n next_nd = next_nd.next # advance the node of next_nd\r\n else:\r\n present = next_nd #advance one step, present -> next_nd\r\n next_nd = next_nd.next #advance one step, next_nd -> next_nd.next\r\n return head\r\n"
},
{
"alpha_fraction": 0.5401310324668884,
"alphanum_fraction": 0.5589680671691895,
"avg_line_length": 47.836734771728516,
"blob_id": "e9be508df1e5333a0c14a8c81b6d7afacb9f5be0",
"content_id": "312fa9918dfeb52c0d6a6d855b1d10e4f56c8bf0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2446,
"license_type": "no_license",
"max_line_length": 89,
"num_lines": 49,
"path": "/Add_Two_Numbers_1.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "## I modify Add_Two_Numbers_1\r\n\r\n# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\nclass Solution(object):\r\n def addTwoNumbers(self, l1, l2):\r\n carry = 0 ## carry will take the \"进位\", i.e. 4+6=10, '1' will be added to 'carry'\r\n ## new_head is the dummy head. Initialize the current node to dummy head\r\n ## of the returning list by claiming it is ListNode(0).\r\n new_head = ListNode(0)\r\n ## 'present' represents the present/current node (only one node), i.e.\r\n ## the first node here\r\n present = new_head\r\n\r\n while l1 or l2 or carry:\r\n v1 = v2 = 0\r\n if l1:\r\n v1 = l1.val ## set v1 to be the value of the first node of l1\r\n l1 = l1.next ## advance one step further to next node\r\n if l2:\r\n v2 = l2.val\r\n l2 = l2.next\r\n\r\n ## divmod(): Take two (non complex) numbers as arguments and return a pair of\r\n ## numbers consisting of their quotient and remainder when using long\r\n ## division. With mixed operand types, the rules for binary arithmetic\r\n ## operators apply. For plain and long integers, the result is the\r\n ## same as (a // b, a % b). For floating point numbers the result is\r\n ## (q, a % b), where q is usually math.floor(a / b) but may be 1 less\r\n ## than that. In any case q * b + a % b is very close to a, if a % b\r\n ## is non-zero it has the same sign as b, and 0 <= abs(a % b) < abs(b).\r\n ## e.g. v1=4, v2=6, carry=0, then carry, val = divmod(4+6+0, 10) = 1, 0\r\n carry, val = divmod(v1+v2+carry, 10)\r\n\r\n ## Create a new node with the digit value of 'val', and set it to\r\n ## current node's next, then advance current node to next.\r\n new_node = ListNode(val) ## Claim a new node.\r\n ## set 'new_node' to the present node's next node\r\n present.next = new_node\r\n ## advance the present node to the new node 'new_node'\r\n present = present.next\r\n\r\n ## Return dummy head's next node.Note that we use a dummy head to simplify\r\n ## the code. Without a dummy head, you would have to write extra\r\n ## conditional statements to initialize the head's value.\r\n return new_head.next\r\n"
},
{
"alpha_fraction": 0.4442518651485443,
"alphanum_fraction": 0.44945117831230164,
"avg_line_length": 30.05555534362793,
"blob_id": "6bf859509dfeed82c9631e5b7e7c87fdc403ec0b",
"content_id": "eabe8cef96900450ceaa356fd2b77312631f99b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1731,
"license_type": "no_license",
"max_line_length": 127,
"num_lines": 54,
"path": "/160E_Intersection_of_Two_Linked_Lists_solution2.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution(object):\r\n def getIntersectionNode(self, headA, headB):\r\n \"\"\"\r\n :type head1, head1: ListNode\r\n :rtype: ListNode\r\n \"\"\"\r\n if headA == None and headB == None:\r\n return None\r\n elif headA == None and headB != None:\r\n return None\r\n elif headA != None and headB == None:\r\n return None\r\n else:\r\n len_a = 0\r\n len_b = 0\r\n\r\n current = headA\r\n while current != None:\r\n current = current.next\r\n len_a += 1\r\n\r\n current = headB\r\n while current != None:\r\n current = current.next\r\n len_b += 1\r\n\r\n diff = 0\r\n current = None\r\n if len_a > len_b:\r\n diff = len_a - len_b\r\n currentA = headA\r\n currentB = headB\r\n else:\r\n diff = len_b - len_a\r\n currentA = headB\r\n currentB = headA\r\n ## so that we ensure currentA is in the longer linked list than currentB\r\n\r\n count = 0\r\n while count < diff:\r\n currentA = currentA.next\r\n count += 1\r\n while currentA != None and currentB != None:\r\n if currentA == currentB:\r\n return currentA ##find when node currentA is the same as node currentB, and then it is the overlapping node\r\n else:\r\n currentA = currentA.next\r\n currentB = currentB.next\r\n"
},
{
"alpha_fraction": 0.5162180662155151,
"alphanum_fraction": 0.523809552192688,
"avg_line_length": 36.1315803527832,
"blob_id": "32c05db7a8d185c7c2d3f83f1de39352ddc9974d",
"content_id": "02b38d20f5ed001a5490921034b12226dc841a14",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1449,
"license_type": "no_license",
"max_line_length": 80,
"num_lines": 38,
"path": "/Remove_N.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution(object):\r\n def removeNthFromEnd(self, head, n):\r\n \"\"\"\r\n :type head: ListNode\r\n :type n: int\r\n :rtype: ListNode\r\n \"\"\"\r\n # this question is different from question \"2M_Add_Two_Numbers\" and\r\n # question \"21E_Merge_Two_Sorted_Lists\". This question has a head as\r\n # the first node, while other two questions need some dummy heads (since\r\n # the first node is also variable)\r\n if head == None or head.next == None:\r\n return None\r\n else:\r\n length = 1 # length is the number of nodes (include head)\r\n ## 'present' represents the present/current node (only one node)\r\n present = head\r\n while present.next != None:\r\n length += 1\r\n # advance to next node\r\n present = present.next\r\n\r\n target = length - n # number of nodes before target\r\n if target == 0: # remove the first node (after the head)\r\n head = head.next\r\n else:\r\n present = head\r\n for i in range(target-1): # [0, 1,...(target-2)]\r\n present = present.next\r\n\r\n present.next = present.next.next # skip the (target+1)th node\r\n return head\r\n"
},
{
"alpha_fraction": 0.505220890045166,
"alphanum_fraction": 0.5148594379425049,
"avg_line_length": 28.365854263305664,
"blob_id": "1960139d924611f75a56d854924f41a409582033",
"content_id": "dd4be0a028aa91a516862642f63d56cae714d52f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1245,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 41,
"path": "/92M_Reverse_Linked_List_II.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution(object):\r\n def reverseBetween(self, head, m, n):\r\n \"\"\"\r\n :type head: ListNode\r\n :type m: int\r\n :type n: int\r\n :rtype: ListNode\r\n \"\"\"\r\n if m == n:\r\n return head\r\n\r\n dummyNode = ListNode(0) #create a new node, remember to get rid of it\r\n dummyNode.next = head\r\n pre = dummyNode\r\n\r\n for i in range(m - 1):\r\n pre = pre.next #pre is the (m-1)th node\r\n\r\n # reverse the [m, n] nodes\r\n reverse = None\r\n cur = pre.next # cur is the mth node, which will be reversed with nth node\r\n for i in range(n - m + 1):\r\n #reverse cur and cur.next and advance cur urther iteratively\r\n # the result is, 4->7->8->9 becomes 9->8->7->4\r\n nex_temp = cur.next\r\n cur.next = reverse\r\n reverse = cur\r\n cur = nex_temp\r\n\r\n pre.next.next = cur\r\n pre.next = reverse\r\n # these order of these two lines cannot be reversed. The reason is unknown\r\n\r\n #return cur\r\n return dummyNode.next\r\n"
},
{
"alpha_fraction": 0.4725663661956787,
"alphanum_fraction": 0.4769911468029022,
"avg_line_length": 33.3125,
"blob_id": "537fab6f9cf852d8e2e937139aa3069e376e46a5",
"content_id": "b958794291e59aab297aaca69b8a823794f0a85c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1130,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 32,
"path": "/Linked_List_Cycle_II.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "class Solution:\r\n # @param head, a ListNode\r\n # @return a ListNode\r\n def detectCycle(self, head):\r\n if head == None:\r\n return head\r\n else:\r\n fast = head\r\n slow = head\r\n\r\n has_cycle = False\r\n while fast != None and fast.next != None:\r\n slow = slow.next\r\n fast = fast.next.next\r\n if fast == slow:\r\n has_cycle = True\r\n break\r\n\r\n if has_cycle == False:\r\n return None\r\n\r\n # return the node where the cycle begins\r\n # slow starts from head and has a speed of 1\r\n # fast starts from the crossing point of X fast (speed 2) and slow\r\n # (speed 1). But now fast also moves at a speed of 1\r\n # It can be shown, if two pointers start from head and X, respectively\r\n # (at same speed of 1), one first reaches E, the other also reaches E.\r\n slow = head\r\n while fast != slow:\r\n fast = fast.next\r\n slow = slow.next\r\n return slow\r\n"
},
{
"alpha_fraction": 0.7611940503120422,
"alphanum_fraction": 0.7611940503120422,
"avg_line_length": 32.5,
"blob_id": "f9c692d54e4ea66d4bb2d2d0af42dfe83150e10e",
"content_id": "742568e0091252de2b0735e1f270bf6597cdd6a7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 67,
"license_type": "no_license",
"max_line_length": 43,
"num_lines": 2,
"path": "/README.md",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "# Leetcode-Linked_List\nKun Geng's Leetcode (Algorithms, Linked List)\n"
},
{
"alpha_fraction": 0.47145605087280273,
"alphanum_fraction": 0.47658756375312805,
"avg_line_length": 29.18000030517578,
"blob_id": "a6d84320a18f8804c024967253b1b63d924aaf40",
"content_id": "bb8947e9e589843dacc61fa3caf2b15e96c01d58",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1559,
"license_type": "no_license",
"max_line_length": 97,
"num_lines": 50,
"path": "/Swap_Nodes_in_Pairs.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "#################################################################################################\r\n# recursive solution\r\n# Definition for singly-linked list.\r\n# class ListNode:\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution:\r\n # @param a ListNode\r\n # @return a ListNode\r\n def swapPairs(self, head):\r\n if head == None:\r\n return None\r\n if head.next == None:\r\n return head\r\n A = head\r\n B = head.next\r\n B.next = self.swapPairs(B.next)\r\n A.next = B.next #what was next to B is now next to A, namely, replace B by A\r\n B.next = A ## A is next to B, namely, B->A\r\n\r\n return B\r\n\r\n#################################################################################################\r\n# iterative solution\r\n# Definition for singly-linked list.\r\n# class ListNode:\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\n\r\nclass Solution:\r\n # @param a ListNode\r\n # @return a ListNode\r\n def swapPairs(self, head):\r\n start = ListNode(0) # create a new node, remember to get rid of it later\r\n start.next = head\r\n\r\n cur = start\r\n while cur.next != None and cur.next.next != None:\r\n cur.next = self.swap(cur.next, cur.next.next)\r\n cur = cur.next.next\r\n\r\n return start.next # don't return start, because start is self-added\r\n\r\n def swap(self, next1, next2):\r\n next1.next = next2.next\r\n next2.next = next1\r\n return next2\r\n"
},
{
"alpha_fraction": 0.48323795199394226,
"alphanum_fraction": 0.5057236552238464,
"avg_line_length": 42.47272872924805,
"blob_id": "58ec47ea5818b9a9db627b196a0c90874e7c4661",
"content_id": "54808f3ffc2a1b9ed3d21b2c5800bb7c035462d6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2446,
"license_type": "no_license",
"max_line_length": 121,
"num_lines": 55,
"path": "/Merge_Two_Sorted_Lists.py",
"repo_name": "kungeng/Leetcode-Linked-List",
"src_encoding": "UTF-8",
"text": "##e.g. l1: 3->5->14, l2: 4->6->8, merged list is 3->4->5->6->8->14\r\n\r\n# Definition for singly-linked list.\r\n# class ListNode(object):\r\n# def __init__(self, x):\r\n# self.val = x\r\n# self.next = None\r\nclass Solution(object):\r\n def mergeTwoLists(self, l1, l2):\r\n \"\"\"\r\n :type l1: ListNode\r\n :type l2: ListNode\r\n :rtype: ListNode\r\n \"\"\"\r\n if l1 == None:\r\n return l2\r\n elif l2 == None:\r\n return l1\r\n else:\r\n ## new_head is the dummy head. Initialize the current node to dummy head\r\n ## of the returning list by claiming it is ListNode(0).\r\n new_head = ListNode(0)\r\n ## 'present' represents the present/current node (only one node), i.e.\r\n ## the first node here\r\n present = new_head ## the 'new_head' is the only present result of the linked list\r\n\r\n while l1 != None and l2 != None:\r\n if l1.val <= l2.val:\r\n ## Create a new node with the digit value of 'l1.val', and\r\n ## set it to the current node's next, then advance current\r\n ## node to the next.\r\n new_node = ListNode(l1.val) ## claim a new node\r\n ## make 'new_node' the present node's next node\r\n present.next = new_node\r\n\r\n\r\n ## advance the present node to the next node 'new_node',\r\n present = present.next\r\n ##move node l1 to the next node\r\n l1 = l1.next\r\n else:\r\n new_node = ListNode(l2.val)\r\n present.next = new_node\r\n present = present.next\r\n l2 = l2.next\r\n if l1 != None: ##l2 is shorter than l1, we finish all l2 but still some l1 left\r\n present.next = l1\r\n else: ##l2 is shorter than l1, we finish all l2 but still some l1 left\r\n present.next = l2\r\n\r\n ## Return dummy head's next node.Note that we use a dummy head to simplify\r\n ## the code. Without a dummy head, you would have to write extra\r\n ## conditional statements to initialize the head's value.\r\n return new_head.next ##output is [1,2]\r\n #return new_head ## if we use 'new_head' instead, final result has a 0 in the front, namely output is [0,1,2]\r\n"
}
] | 10
|
amadousysada/BI
|
https://github.com/amadousysada/BI
|
e941f71aeafe6eedc05a21b0076c96f49e5276df
|
a2c97d38f047095db275894b217c10f835b15e0e
|
e3aee4a958c0fda09ec2d1b47072b11a859b720f
|
refs/heads/master
| 2021-10-22T23:03:27.129584
| 2019-03-13T11:39:11
| 2019-03-13T11:39:11
| 171,424,067
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7375447750091553,
"alphanum_fraction": 0.7434060573577881,
"avg_line_length": 31.67021369934082,
"blob_id": "307a0dad3224676ab7b70f950718e7544308c08e",
"content_id": "387d3c775a2a2ecaf09a739cccaa172501bbd191",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3071,
"license_type": "no_license",
"max_line_length": 127,
"num_lines": 94,
"path": "/tp2-2.1.py",
"repo_name": "amadousysada/BI",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\nfrom sklearn.dummy import DummyClassifier\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn import tree\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn import svm\nfrom sklearn.model_selection import cross_val_score\nfrom sklearn.model_selection import cross_val_predict\nfrom sklearn import metrics\nfrom scipy.io import arff\nfrom sklearn.impute import SimpleImputer\n\nfrom matplotlib import pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom sklearn import preprocessing\n\ndummycl = DummyClassifier(strategy=\"most_frequent\")\ngmb = GaussianNB()\ndectree = tree.DecisionTreeClassifier()\nlogreg = LogisticRegression(solver=\"liblinear\")\nsvc = svm.SVC(gamma='scale')\n\n<<<<<<< HEAD\ndata, meta = arff.loadarff(\"crx.arff\")\n\nimp_mean = SimpleImputer(missing_values=np.nan, strategy='mean')\nimp_mean.fit_transform(data)\n\nstandardscaler = preprocessing.StandardScaler()\n\nX_norm = standardscaler.fit_transform(data)\n\ndata, meta = arff.loadarff('crx.arff')\ndf = pd.DataFrame(data)\n\nplt.hist(data['class'], bins='auto')\nplt.savefig(\"distribution des classes positives et negatives\")\n\n\npercent=df.groupby(['class']).agg({'class':'count'})\npercent = percent.divide(len(df['class']))*100\n\n\n\nlst_classif = [dummycl, gmb, dectree, logreg, svc]\nlst_classif_names = ['Dummy', 'Naive Bayes', 'Decision tree', 'Logistic regression', 'SVM']\n\n\ndef accuracy_score(lst_classif,lst_classif_names,X,y):\n for clf,name_clf in zip(lst_classif,lst_classif_names):\n scores = cross_val_score(clf, X, y, cv=5)\n print(\"Accuracy of \"+name_clf+\" classifier on cross-validation: %0.2f (+/- %0.2f)\" % (scores.mean(), scores.std() * 2))\n\ndef confusion_matrix(lst_classif,lst_classif_names,X,y):\n for clf,name_clf in zip(lst_classif,lst_classif_names):\n predicted = cross_val_predict(clf, X, y, cv=5) \n print(\"Accuracy of \"+name_clf+\" classifier on cross-validation: %0.2f\" % metrics.accuracy_score(y, predicted))\n print(metrics.confusion_matrix(y, predicted))\n\n# Replace missing values by mean and scale numeric values\ndata_num = df.select_dtypes(include='float64')\nlabels = data_num.columns\n#Imputation des valeurs manquantes\nimp_mean = SimpleImputer(missing_values=np.nan, strategy='mean')\n\ndata_num = imp_mean.fit_transform(data_num)\n\n#Standardisation\nstandardscaler = preprocessing.StandardScaler()\n\nX = standardscaler.fit_transform(data_num)\n\ny= df['class']\n\naccuracy_score(lst_classif,lst_classif_names,X,y)\n\n# Replace missing values by mean and discretize categorical values\ndata_cat = df.select_dtypes(exclude='float64').drop('class',axis=1)\nimp_most_freq = SimpleImputer(missing_values='?', strategy='most_frequent')\ndata_cat = imp_most_freq.fit_transform(data_cat)\nX = pd.get_dummies(pd.DataFrame(data_cat))\nprint(\"\\n\\n Categorical classement\")\naccuracy_score(lst_classif,lst_classif_names,X,y)\n\ndf[labels] = standardscaler.fit_transform(df[labels])\nprint(\"\\n\\n Toute les donnees\")\nd=pd.concat(df[labels],X)\nprint type(df[labels])\nexit()\naccuracy_score(lst_classif,lst_classif_names,df,y)\n"
},
{
"alpha_fraction": 0.5960237979888916,
"alphanum_fraction": 0.6357859969139099,
"avg_line_length": 28.7560977935791,
"blob_id": "66e76134c8b0dd8b260ae9a359916a35c8fca25e",
"content_id": "b036e89ad1226a215582f194b79ea0dc47aae9ff",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4883,
"license_type": "no_license",
"max_line_length": 96,
"num_lines": 164,
"path": "/tp2-1.1.py",
"repo_name": "amadousysada/BI",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport pandas as pd\nfrom matplotlib import cm\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.decomposition import PCA\nfrom sklearn import preprocessing\nfrom sklearn. cluster import KMeans\nfrom sklearn.preprocessing import MinMaxScaler\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom R_square_clustering import r_square\nfrom scipy.cluster import hierarchy\n\ndata = pd.read_csv(\"eurostat/eurostat-2013.csv\")\n\n#diviser les valeurs de la colonne('tsc00004 (2012)') par la population\ndata['tsc00004 (2012)'] = data['tsc00004 (2012)'].divide(data['tps00001 (2013)'])\ndata['tet00002 (2013)'] = data['tet00002 (2013)'].divide(data['tps00001 (2013)'])\n\n#Supprimer les données correspondant à la population.\ndata =data.drop(['tps00001 (2013)'], axis=1)\n\nstandardscaler = preprocessing.StandardScaler()\n\nX = data.iloc[:,2:11]\n\nY= [\"axe1\",\"axe2\",\"axe3\",\"axe4\",\"axe5\",\"axe6\",\"axe7\",\"axe8\",\"axe9\"]\n\nX_norm = standardscaler.fit_transform(X)\n\npca = PCA()\n\nX_pca =pca.fit_transform(X_norm)\n\naxes = pd.DataFrame(data=X_pca, columns = Y)\n\n\ncmap = cm.get_cmap('gnuplot')\ndf = pd.concat([axes, data[['Code']]], axis = 1)\n\n'''\n l'affichage des instances étiquetées par le code du pays suivant les 2 facteurs\nprincipaux de l'ACP, puis suivant les facteurs 3 et 4 de l'ACP.\n'''\nfig = plt.figure(figsize = (8,8))\nax = fig.add_subplot(1,1,1) \nax.set_xlabel('axe1', fontsize = 15)\nax.set_ylabel('axe2', fontsize = 15)\nax.set_title('2 first components PCA', fontsize = 20)\ntargets = df['Code'].values\nfor target in targets:\n \n indicesToKeep = df['Code'] == target\n plt.annotate(target,\n xy=(\n df.loc[indicesToKeep, 'axe1'],\n df.loc[indicesToKeep, 'axe2']\n )\n )\n ax.scatter(df.loc[indicesToKeep, 'axe1']\n , df.loc[indicesToKeep, 'axe2']\n , cmap = cmap\n , s = 50)\nax.grid()\nplt.savefig(\"2 facteurs principaux de l'ACP\")\nplt.close()\n\n#teilm (M dec 2013) --> tec00118 (2013)\nfig1 = plt.figure(figsize = (8,8))\nax1 = fig1.add_subplot(1,1,1) \n\nax1.set_xlabel('axe3', fontsize = 15)\nax1.set_ylabel('axe4', fontsize = 15)\nax1.set_title('3th and 4th components PCA', fontsize = 20)\n\nfor target in targets:\n \n indicesToKeep = df['Code'] == target\n plt.annotate(target,\n xy=(\n df.loc[indicesToKeep, 'axe3'],\n df.loc[indicesToKeep, 'axe4']\n )\n )\n ax1.scatter(df.loc[indicesToKeep, 'axe3']\n , df.loc[indicesToKeep, 'axe4']\n , cmap = cmap\n , s = 50)\nax1.grid()\nplt.savefig(\"3iem et 4iem facteurs de l'ACP\")\nplt.close()\n\nn = np.size(X_norm, 0)\np = np.size(X_norm, 1)\neigval = float(n-1)/n*pca.explained_variance_\n\nsqrt_eigval = np.sqrt(eigval)\ncorvar = np.zeros((p,p))\nfor k in range(p):\n corvar [:, k] = pca.components_[k,:]*sqrt_eigval[k]\n \n \n#correlation_circle\ndef correlation_circle(df,nb_var,x_axis,y_axis):\n fig, axes = plt.subplots(figsize=(8,8))\n axes.set_xlim(-1,1)\n axes.set_ylim(-1,1)\n # label with variable names\n for j in range(nb_var):\n # ignore two first columns of df: Nom and Code^Z\n plt.annotate(df.columns[j+2],(corvar[j,x_axis],corvar[j,y_axis]))\n # axes\n plt.plot([-1,1],[0,0],color='silver',linestyle='-',linewidth=1)\n plt.plot([0,0],[-1,1],color='silver',linestyle='-',linewidth=1)\n # add a circle\n cercle = plt.Circle((0,0),1,color='blue',fill=False)\n axes.add_artist(cercle)\n plt.savefig('acp_correlation_circle_axes_'+str(x_axis)+'_'+str(y_axis))\n plt.close(fig)\n\ncorrelation_circle(data,9,2,3)\n\n#question 5\nlst_k=range(2,8)\nlst_rsq = []\nfor k in lst_k:\n est=KMeans(n_clusters=k)\n est.fit (X_norm)\n lst_rsq.append(r_square(X_norm, est.cluster_centers_,est.labels_,k))\nfig = plt. figure ()\nplt.plot(lst_k, lst_rsq, 'bx-')\nplt.xlabel('k')\nplt.ylabel('RSQ')\nplt.title ('The Elbow Method showing the optimal k')\nplt.savefig('r_square')\nplt.close(fig)\n\n\nest = KMeans(n_clusters=5)\n\nest.fit(X)\n\n# print centroids associated with several countries\nlst_countries=['EL','FR','DE','US']\n# centroid of the entire dataset\n# est: KMeans model fit to the dataset\ny=data['Code']\n\nprint (est.cluster_centers_)\nfor name in lst_countries:\n num_cluster = est.labels_[y.loc[y==name].index][0]\n print ('Num cluster for '+name+': '+str(num_cluster))\n print ('\\tlist of countries: '+', '.join(y.iloc[np.where(est.labels_==num_cluster)].values))\n print ('\\tcentroid: '+str(est.cluster_centers_[num_cluster]))\n\n\nZ = hierarchy.linkage(X,'ward')\nlst_labels = map(lambda pair: pair[0], zip( data['Code'].values, data.index))\nplt.figure()\ndn = hierarchy.dendrogram(Z,color_threshold=0,labels=lst_labels)\nplt.savefig ('dendogramme')\nplt.close( fig )"
},
{
"alpha_fraction": 0.7263922691345215,
"alphanum_fraction": 0.736884593963623,
"avg_line_length": 34.42856979370117,
"blob_id": "2e0b0b3fe230f47d5ee227cf727cd6951d5751c6",
"content_id": "98d1c0eced95fb633ebefbb2c7b66f21900d07c2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1239,
"license_type": "no_license",
"max_line_length": 100,
"num_lines": 35,
"path": "/tp2-1.2.py",
"repo_name": "amadousysada/BI",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom mlxtend.frequent_patterns import apriori\nfrom mlxtend.frequent_patterns import association_rules\n\nfrom scipy.io import arff\nimport pandas as pd\n\ndata, meta = arff.loadarff(\"vote.arff\")\n\nvote = pd.DataFrame(data)\n\n# convert categorical values into one-hot vectors and ignore ? values\n# corresponding to missing values\n# ex: handicapped-infants=y -> [1,0], handicapped-infants=n -> [0,1], handicapped-infants=? -> [0,0]\nvote_one_hot = pd.get_dummies(vote)\n\nvote_one_hot.drop(vote_one_hot.filter(regex='_\\?$',axis=1).columns,axis=1,inplace=True)\nfrequent_item_sets = apriori(vote_one_hot, min_support=0.4, use_colnames=True)\n\nrules = association_rules(frequent_item_sets, metric=\"confidence\", min_threshold=0.9)\n\n# check that there is no rule implying Republicans\nfilter(lambda x: \"Class_'republican'\" in x,rules['antecedents'])\nfilter(lambda x: \"Class_'republican'\" in x,rules['consequents'])\n\n#meilleur regle pour la metric lift\nmax_lift = rules[rules['lift']==max(rules['lift'])]\n\n#meilleur regle pour la metric leverage\nmax_lever = rules[rules['leverage']==max(rules['leverage'])]\n\n#meilleur regle pour la metric convition\nmax_conv = rules[rules['conviction']==max(rules['conviction'])]"
}
] | 3
|
jariberi/git_merge
|
https://github.com/jariberi/git_merge
|
224d90c7a2781e49b445d43546ffb79bfae6369f
|
d05bc264890e019452524e20e22729d1deea3d55
|
74e2c937318da6f10bbbc0be274a218cfbc8443e
|
refs/heads/master
| 2021-01-21T14:19:26.167237
| 2017-06-24T01:14:39
| 2017-06-24T01:14:39
| 95,267,406
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5458333492279053,
"alphanum_fraction": 0.5458333492279053,
"avg_line_length": 8.600000381469727,
"blob_id": "6bf84a41259cde4c1a1d28bbc3999a58db0ec9fe",
"content_id": "eb05c1668cf820e88823dd9fadbd45cab5db92d4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 240,
"license_type": "no_license",
"max_line_length": 25,
"num_lines": 25,
"path": "/main.py",
"repo_name": "jariberi/git_merge",
"src_encoding": "UTF-8",
"text": "import math\n\n\ndef suma(a, b):\n return a + b\n\n\ndef resta(a, b):\n return a - b\n\n\ndef multiplicacion(a, b):\n return a * b\n\n\ndef division(a, b):\n return a // b\n\n\ndef potencia(a, b):\n return a ** b\n\n\ndef raiz(a):\n math.sqrt(a)\n"
},
{
"alpha_fraction": 0.8611111044883728,
"alphanum_fraction": 0.8611111044883728,
"avg_line_length": 36,
"blob_id": "1ca9d550d073a49267b11a773f5735f34edf4f52",
"content_id": "f0f376f35f310bfa6e5368bf2f1204b6b7fe519d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 36,
"license_type": "no_license",
"max_line_length": 36,
"num_lines": 1,
"path": "/readme.md",
"repo_name": "jariberi/git_merge",
"src_encoding": "UTF-8",
"text": "Repositorio para prueba de git merge"
}
] | 2
|
adithshetty1995/Price-Prediction-of-Used-Cars
|
https://github.com/adithshetty1995/Price-Prediction-of-Used-Cars
|
25957c22ed30df83f8a4d6dacd9b2a1b8393ad7d
|
de7263ebcbc4cc4a54dd7e333804f193c5519724
|
e9985ac56e446c479153f589a6eb479205524cac
|
refs/heads/main
| 2023-08-03T18:29:39.847621
| 2021-09-15T21:34:37
| 2021-09-15T21:34:37
| 406,925,385
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8156779408454895,
"alphanum_fraction": 0.8220338821411133,
"avg_line_length": 93.4000015258789,
"blob_id": "1e81a1336802b848c13118b34e9ff3bb1ebdc63b",
"content_id": "22e56b9c2d5648a0fc815f0fee7c93be30d51c1c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 472,
"license_type": "no_license",
"max_line_length": 225,
"num_lines": 5,
"path": "/README.md",
"repo_name": "adithshetty1995/Price-Prediction-of-Used-Cars",
"src_encoding": "UTF-8",
"text": "# Price-Prediction-of-Used-Cars using Random Forest Classifier, K-Folds Cross Validation, and Python\n\n- Built a prediction model applying the Random Forest Regression Algorithm employing data preprocessing, feature normalization, label encoding, and data modeling with Scikit-learn pre-processing to estimate the price of a car\n- Evaluated the model employing K-Folds cross validation for testing the model accuracy\n- Showcased an overall prediction success rate of 91.3%\n"
},
{
"alpha_fraction": 0.6572875380516052,
"alphanum_fraction": 0.6857062578201294,
"avg_line_length": 13.669421195983887,
"blob_id": "741e7a325d13d1d1823d15f6990c8d65b73a28e9",
"content_id": "09096b976bcba9d31b47cc641572d5f32a96c9c1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3554,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 242,
"path": "/Final_ProjectCode.py",
"repo_name": "adithshetty1995/Price-Prediction-of-Used-Cars",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing\nimport matplotlib.pyplot as plt \nimport seaborn as sns\n#Read dataset\ndata = pd.read_csv('C:/Users/User/Desktop/Project/car_ad1.csv',encoding ='latin-1')\ndata.shape\n\n\n# In[2]:\n\n\ndata.info()\n\n\n# In[3]:\n\n\ndata.price[data.price ==0].count()\n\n\n# In[4]:\n\n\ndata=data.drop(data[data.price <= 0 ].index) #Drop records where price is zero\n\n\n# In[5]:\n\n\ndata.price[data.price ==0].count()\n\n\n# In[6]:\n\n\ndata.shape #Get the shape of dataframe\n\n\n# In[7]:\n\n\ndata.engV[data.engV >9].count()\n\n\n# In[9]:\n\n\ndata=data.drop(data[data.engV >9].index) #Drop records where engV is zero\n\n\n# In[10]:\n\n\ndata.engV[data.engV >9].count()\n\n\n# In[11]:\n\n\ndata.shape\n\n\n# In[12]:\n\n\ndata.isnull().sum() #Check null values in dataframe\n\n\n# In[15]:\n\n\ndata.head() #Display first few records of dataframe\n\n\n# In[16]:\n\n\ndata.mean() #Calculate Mean \n\n\n# In[18]:\n\n\ndata=data.fillna(data.mean()) #Replace missing values with Mean\n\n\n# In[20]:\n\n\ndata.isnull().sum()\n\n\n# In[21]:\n\n\ndata.head()\n\n\n# In[22]:\n\n\ndata.drive.mode() #Calculate Mode\n\n\n# In[23]:\n\n\ndata['drive'] = data['drive'].fillna(data['drive'].mode()[0]) #Replace missing values with Mode \n\n\n# In[24]:\n\n\ndata.isnull().sum()\n\n\n# In[25]:\n\n\ndata.head()\n\n\n# In[27]:\n\n\ndata.shape\n\n\n# In[28]:\n\n\ndata_copy=data.copy() #Copy dataframe contents to another datframe\ndata_copy.head()\n\n\n# In[29]:\n\n\ndata = pd.get_dummies(data) #One hot encode\n\n\n# In[30]:\n\n\ndata.shape\n\n\n# In[31]:\n\n\ndata.head() \n\n\n# In[32]:\n\n\nsns.regplot(x='year',y='price',data=data) #Scatterplot of two variables with Regression line\n\n\n# In[33]:\n\n\nsns.regplot(x='mileage',y='price',data=data)\n\n\n# In[34]:\n\n\nsns.regplot(x='engV',y='price',data=data)\n\n\n# In[36]:\n\n\ndata_copy=data.copy()\ndata_copy.head()\n\n\n# In[37]:\n\n\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import mean_absolute_error\nfrom sklearn.metrics import mean_squared_error\nfrom sklearn.metrics import r2_score\nX = data.drop(\"price\",axis=1)\ny = data[\"price\"]\n#Split data set into train and test data sets\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n\n\n# In[41]:\n\n\nmodel = RandomForestRegressor(n_estimators=100,random_state=42) #Create Random Forest Regression model\nmodel.fit(X_train, y_train) #Fit the model with train & test values\npred = model.predict(X_test) #Predict values\nprint (\"R2_Score value is\",model.score(X_test, y_test)*100) #Determine model accuracy\n\n\n# In[42]:\n\n\nfrom sklearn.ensemble import RandomForestRegressor\nfrom sklearn.model_selection import KFold # Import KFold\nfrom sklearn.model_selection import train_test_split\nX = data.drop(\"price\",axis=1)\ny = data[\"price\"]\nX = X.to_numpy() #Convert dataframe to NumPy array\ny = y.to_numpy() #Convert dataframe to NumPy array\nkf = KFold(n_splits=10,random_state=42) #Split into 10 folds \nfor train_index, test_index in kf.split(X):\n #print(train_index,test_index)\n X_train, X_test = X[train_index], X[test_index]\n y_train, y_test = y[train_index], y[test_index]\n\nmodel = RandomForestRegressor(n_estimators=100,random_state=42)\nmodel.fit(X_train, y_train)\npred = model.predict(X_test)\nprint (\"R2_Score value is\",model.score(X_test, y_test)*100)\n\n\n# In[43]:\n\n\nplt.figure(figsize= (6, 6))\nplt.title('Visualizing the Regression using Random Forest Regression algorithm')\nsns.regplot(pred, y_test, color = 'teal')\nplt.xlabel(\"New Predicted Price (Price)\")\nplt.ylabel(\"Old Price (Price)\")\nplt.show()\n\n\n# In[ ]:\n\n\n\n\n"
}
] | 2
|
rokaN8/eskomloadshedding
|
https://github.com/rokaN8/eskomloadshedding
|
0b0e705fd6d0604ec8e285cb620ed5c19ae5cd3b
|
f7576f99a9ed0e5908e240b1ceec1979fb824b4b
|
5bb1340c7f1ec44563ddb7038d64df45cf3e32c3
|
refs/heads/master
| 2020-04-15T04:54:18.749890
| 2019-01-07T08:36:22
| 2019-01-07T08:36:22
| 164,400,934
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6627634763717651,
"alphanum_fraction": 0.6674473285675049,
"avg_line_length": 29.571428298950195,
"blob_id": "18bf2e0b265d6bd294aba2772a19941bc72d60cc",
"content_id": "63b012956da337a4b6758acee0832c2f7368821c",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 427,
"license_type": "permissive",
"max_line_length": 80,
"num_lines": 14,
"path": "/classes/webscraper.py",
"repo_name": "rokaN8/eskomloadshedding",
"src_encoding": "UTF-8",
"text": "from urllib.request import urlopen\nimport datetime\nfrom bs4 import BeautifulSoup\n\nclass Webscraper():\n\n def get_loadshedding_status(self):\n page = urlopen(\"http://loadshedding.eskom.co.za/LoadShedding/getstatus\")\n soup = BeautifulSoup(page, \"html.parser\")\n print()\n status = int(str(soup)) - 1\n\n print(\"Current Status @\", datetime.datetime.now(), \"is Stage:\", status)\n return status"
},
{
"alpha_fraction": 0.7931034564971924,
"alphanum_fraction": 0.8007662892341614,
"avg_line_length": 28,
"blob_id": "eb507be77d62d9aa513fe6a65956d79e3493e373",
"content_id": "04f36dddae68c87d2fd688f88e1e24ecd45cbb91",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 261,
"license_type": "permissive",
"max_line_length": 97,
"num_lines": 9,
"path": "/README.md",
"repo_name": "rokaN8/eskomloadshedding",
"src_encoding": "UTF-8",
"text": "# Eskom Loadshedding\n\nWIP Pi2b loadshedding notification\n\n## Wiring Guide\nhttps://github.com/leon-anavi/raspberrypi-lcd/blob/master/raspberrypi-lcd.py\n\n## Results\n\n"
},
{
"alpha_fraction": 0.489790141582489,
"alphanum_fraction": 0.5087918043136597,
"avg_line_length": 31.348623275756836,
"blob_id": "c7bc72bfb64bed80eea19ca0b689beafe7710d8d",
"content_id": "4b98de0a8588ec8af68c1d9030c90c1f9871c329",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3526,
"license_type": "permissive",
"max_line_length": 132,
"num_lines": 109,
"path": "/main.py",
"repo_name": "rokaN8/eskomloadshedding",
"src_encoding": "UTF-8",
"text": "import time\nimport datetime\n\nfrom classes.lookup import Lookup\nfrom classes.webscraper import Webscraper\nfrom classes.lcddisplay import LCDDisplay\n\nlcd = LCDDisplay()\nlcd.lcd_display()\n\ndef blank_display(status, now):\n group = 2\n\n future_list = Lookup.stage_group_lookup(None, 2, group, 3)\n next_displayed = False\n\n lcd.write(\"No Remaining\", lcd.LCD_LINE_1)\n print(\"No Loadshedding Remaining Today\")\n display_status = \"Current Stage: \" + str(status)\n print(display_status)\n lcd.write(display_status, lcd.LCD_LINE_2)\n time.sleep(20)\n\n for future_item in future_list:\n if future_item[0] != now.day:\n if next_displayed == False:\n # next_displayed = True\n next = str(\n datetime.datetime(now.year, now.month, future_item[0], int(future_item[1].split(\":\")[0]), 0, 0))\n\n future_display = \"Next: \" + future_item[3]\n print(future_display)\n lcd.write(future_display, lcd.LCD_LINE_1)\n print(next)\n lcd.write(next, lcd.LCD_LINE_2)\n time.sleep(7)\n # print(datetime.datetime(now.year, now.month, future_item[0], int(future_item[1].split(\":\")[0]), 0, 0), future_item[3])\n\ndef checker():\n counter = 0\n status = 0 #\n\n while True:\n group = 2\n sleep_timer_multiplier = 1\n update_time = 10\n if (counter % update_time) == 0:\n status = Webscraper.get_loadshedding_status(None)\n counter = 0\n counter += 1\n list = Lookup.stage_group_lookup(None, status, group, 1)\n\n now = datetime.datetime.now()\n print(\"Current status\", status)\n if status == 0 or list.__len__() == 0:\n blank_display(status, now)\n return\n\n if list.__len__() > 0:\n for item in list:\n start_hour = int(item[1].split(\":\")[0])\n\n start = datetime.datetime(now.year, now.month, now.day, start_hour, 0, 0)\n\n tdelta = start - now\n tdelta = tdelta.total_seconds()\n diff = tdelta\n\n if status == 0 or diff < 0:\n blank_display(status, now)\n break\n else:\n display_status = \"Stage: \" + str(status)\n lcd.write(display_status, lcd.LCD_LINE_1)\n time.sleep(20)\n print(\"Time till next loadshedding (minutes):\", diff, \"at\", item[1])\n\n m, s = divmod(diff, 60)\n h, m = divmod(m, 60)\n hms = \"%d:%02d\" % (h, m)\n display_next = \"Next at: \" + str(start_hour) + \":00\"\n print(display_next)\n lcd.write(display_next, lcd.LCD_LINE_1)\n display_countdown = \"Countdown: \" + hms\n print(display_countdown)\n lcd.write(display_countdown, lcd.LCD_LINE_2)\n '''\n if diff < 10 and diff > 0:\n #winsound.MessageBeep(winsound.MB_OK)\n break\n '''\n break\n #time.sleep(60*sleep_timer_multiplier)\n\ndef main():\n print(\"Starting Eskom Loadshedding checker\")\n checker()\n print(\"End\")\n '''\n items = Lookup.stage_group_lookup(None, 2, 2, 5)\n for item in items:\n print(item)\n '''\n return\n #winsound.Beep(winsound.MB_OK.,100)\n\n\nif __name__ == \"__main__\":\n main()\n"
},
{
"alpha_fraction": 0.5246530771255493,
"alphanum_fraction": 0.5724830031394958,
"avg_line_length": 29.790908813476562,
"blob_id": "d8f8d3ee5eb9335d5f4da3407e2dd59e776f533b",
"content_id": "db392afe4bf3161f20769b37fc7bf04c81aa7cf6",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3387,
"license_type": "permissive",
"max_line_length": 91,
"num_lines": 110,
"path": "/classes/lcddisplay.py",
"repo_name": "rokaN8/eskomloadshedding",
"src_encoding": "UTF-8",
"text": "#import RPi.GPIO as GPIO\nimport time\n\nclass LCDDisplay():\n # Define GPIO to LCD mapping\n LCD_RS = 25\n LCD_E = 24\n LCD_D4 = 23\n LCD_D5 = 17\n LCD_D6 = 18\n LCD_D7 = 22\n\n # Define some device constants\n LCD_WIDTH = 16 # Maximum characters per line\n LCD_CHR = True\n LCD_CMD = False\n\n LCD_LINE_1 = 0x80 # LCD RAM address for the 1st line\n LCD_LINE_2 = 0xC0 # LCD RAM address for the 2nd line\n\n # Timing constants\n E_PULSE = 0.0005\n E_DELAY = 0.0005\n\n def write(self, write, line):\n self.lcd_string(write, line)\n\n def lcd_display(self):\n # Main program block\n GPIO.setwarnings(False)\n GPIO.setmode(GPIO.BCM) # Use BCM GPIO numbers\n GPIO.setup(self.LCD_E, GPIO.OUT) # E\n GPIO.setup(self.LCD_RS, GPIO.OUT) # RS\n GPIO.setup(self.LCD_D4, GPIO.OUT) # DB4\n GPIO.setup(self.LCD_D5, GPIO.OUT) # DB5\n GPIO.setup(self.LCD_D6, GPIO.OUT) # DB6\n GPIO.setup(self.LCD_D7, GPIO.OUT) # DB7\n\n # Initialise display\n self.lcd_init()\n\n def lcd_init(self):\n # Initialise display\n self.lcd_byte(0x33, self.LCD_CMD) # 110011 Initialise\n self.lcd_byte(0x32, self.LCD_CMD) # 110010 Initialise\n self.lcd_byte(0x06, self.LCD_CMD) # 000110 Cursor move direction\n self.lcd_byte(0x0C, self.LCD_CMD) # 001100 Display On,Cursor Off, Blink Off\n self.lcd_byte(0x28, self.LCD_CMD) # 101000 Data length, number of lines, font size\n self.lcd_byte(0x01, self.LCD_CMD) # 000001 Clear display\n time.sleep(self.E_DELAY)\n\n def lcd_byte(self, bits, mode):\n # Send byte to data pins\n # bits = data\n # mode = True for character\n # False for command\n\n GPIO.output(self.LCD_RS, mode) # RS\n\n # High bits\n GPIO.output(self.LCD_D4, False)\n GPIO.output(self.LCD_D5, False)\n GPIO.output(self.LCD_D6, False)\n GPIO.output(self.LCD_D7, False)\n if bits & 0x10 == 0x10:\n GPIO.output(self.LCD_D4, True)\n if bits & 0x20 == 0x20:\n GPIO.output(self.LCD_D5, True)\n if bits & 0x40 == 0x40:\n GPIO.output(self.LCD_D6, True)\n if bits & 0x80 == 0x80:\n GPIO.output(self.LCD_D7, True)\n\n # Toggle 'Enable' pin\n self.lcd_toggle_enable()\n\n # Low bits\n GPIO.output(self.LCD_D4, False)\n GPIO.output(self.LCD_D5, False)\n GPIO.output(self.LCD_D6, False)\n GPIO.output(self.LCD_D7, False)\n if bits & 0x01 == 0x01:\n GPIO.output(self.LCD_D4, True)\n if bits & 0x02 == 0x02:\n GPIO.output(self.LCD_D5, True)\n if bits & 0x04 == 0x04:\n GPIO.output(self.LCD_D6, True)\n if bits & 0x08 == 0x08:\n GPIO.output(self.LCD_D7, True)\n\n # Toggle 'Enable' pin\n self.lcd_toggle_enable()\n\n def lcd_toggle_enable(self):\n # Toggle enable\n time.sleep(self.E_DELAY)\n GPIO.output(self.LCD_E, True)\n time.sleep(self.E_PULSE)\n GPIO.output(self.LCD_E, False)\n time.sleep(self.E_DELAY)\n\n def lcd_string(self, message, line):\n # Send string to display\n\n message = message.ljust(self.LCD_WIDTH, \" \")\n\n self.lcd_byte(line, self.LCD_CMD)\n\n for i in range(self.LCD_WIDTH):\n self.lcd_byte(ord(message[i]), self.LCD_CHR)\n"
},
{
"alpha_fraction": 0.44024673104286194,
"alphanum_fraction": 0.45643794536590576,
"avg_line_length": 26.04166603088379,
"blob_id": "3d30f04109785ebd4f4933fe17586ffb04a3a926",
"content_id": "37371b572fd94ae6218f928c7dc7f829f52163da",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1297,
"license_type": "permissive",
"max_line_length": 91,
"num_lines": 48,
"path": "/classes/lookup.py",
"repo_name": "rokaN8/eskomloadshedding",
"src_encoding": "UTF-8",
"text": "import datetime\n\n\ndef sortFirst(val):\n return val[0]\n\nclass Lookup():\n\n def stage_group_lookup(self, stage, group, forecast = 5):\n\n f = open(\"tshwane.csv\")\n\n line = f.readline()\n\n time_now = datetime.datetime.now()\n #print(\"Time Now:\", time_now)\n list = []\n while line != None:\n line = line.replace(\"\\n\", \"\")\n entries = line.split(\",\")\n\n if \"From\" not in entries[0]:\n file_stage = int(entries[2].split(\" \")[1])\n\n if file_stage <= stage:\n day = time_now.day\n\n # forecast\n offset = 2\n for i in range(0 + offset + day, 0 + offset + day + forecast):\n\n if int(entries[i]) == group and int(entries[0].split(\":\")[0]) >= 9:\n #print(i - 3, entries)\n list.append([i - 3 + 1, entries[0], entries[1], entries[2]])\n\n\n line = f.readline()\n\n if line == \"\":\n break\n\n list = sorted(list, key=sortFirst)\n\n for item in list:\n affected_date = datetime.date(time_now.year, time_now.month, item[0])\n #print(affected_date, str(item[1] + \"-\" + item[2]), item[3])\n\n return list"
}
] | 5
|
AlecLjpg/PythonSetlist2
|
https://github.com/AlecLjpg/PythonSetlist2
|
9579907a6619ab5033037cec80ed7b406a3e38ef
|
785c4f306e538794afd9aa9e1d8c7df97338caf1
|
a0e30389c8bd2c7250b03d92e71003e42a8eba56
|
refs/heads/master
| 2020-07-29T02:57:02.802865
| 2019-09-19T20:26:01
| 2019-09-19T20:26:01
| 209,641,505
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6119999885559082,
"alphanum_fraction": 0.6600000262260437,
"avg_line_length": 23.200000762939453,
"blob_id": "20fb8dbaa610f5d072239825a71c104ac58bc77c",
"content_id": "5a41da43868afca59315982a21ff780aa9cdf786",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 250,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 10,
"path": "/Setlist2/Q26.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "import base64\r\nx = input(\"Enter a word to be encoded and decoded: \")\r\n\r\ny = base64.b64encode(x.encode('utf-8',errors='strict'))\r\n\r\nprint(\"Encoded String: \", y)\r\n\r\nz = base64.b64decode(y.decode('utf-8',errors='strict'))\r\n\r\nprint(\"Decoded string: \", z)"
},
{
"alpha_fraction": 0.5706214904785156,
"alphanum_fraction": 0.6355932354927063,
"avg_line_length": 31.619047164916992,
"blob_id": "ae8c8cb3dd38a8b05ad1225927d4bf73a4088c53",
"content_id": "9a0b8c3f2f6f38a66b1e059d69c92ad56490a4b4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 708,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 21,
"path": "/Setlist2/Q37.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "dict1 = {\"Animal Type\":\"Dog\", \"Color\":\"Brown\", \"Age\":4}\r\ndict2 = {\"Name\":\"Alec\",\"Eye Color\":\"Blue\",\"Age\":23}\r\ndict3 = {\"Make\":\"Nissan\",\"Model\":\"Frontier\",\"Year\":2016}\r\n\r\nif cmp(dict1,dict2) == 1 and (dict1,dict3) == 1:\r\n print(\"Dict1 is the greatest\")\r\nelif cmp(dict2,dict1) == 1 and cmp(dict2,dict1) == 1:\r\n print(\"Dict2 is the greatest\")\r\nelif cmp(dict3,dict1) == 1 and cmp(dict3,dict2) == 1:\r\n print(\"Dict3 is the greatest\")\r\n\r\nprint(\"Adding new elements to dict1 and dict2: \")\r\ndict1.update({\"Favorite Toy\":\"Squeaky Toy\"})\r\ndict2.update({\"Height\":\"5 11\"})\r\nprint(dict1)\r\nprint(dict2)\r\n\r\nprint(\"The lengths of dict1,dict2, and dict3:\")\r\nprint(len(dict1))\r\nprint(len(dict2))\r\nprint(len(dict3))\r\n\r\n"
},
{
"alpha_fraction": 0.6236559152603149,
"alphanum_fraction": 0.675268828868866,
"avg_line_length": 29,
"blob_id": "04ca1f8ad726d7b4e25584785e887bd74f3391f9",
"content_id": "b39a9ef335ddef44e0ccda189fc87d1022c75b36",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 465,
"license_type": "no_license",
"max_line_length": 54,
"num_lines": 15,
"path": "/Setlist2/Q24.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "print(\"Demonstration of escape characters in python:\")\r\n\r\nprint(\"Newline: \\n this is a new line\")\r\nprint(\"Backslash : \\\\\")\r\nprint(\"Single quote \\'\")\r\nprint(\"Double quote \\\"\")\r\nprint(\"ASCII Bell \\a\")\r\nprint(\"ASCII Backspace \\b!\")\r\nprint(\"ASCII \\f Formfeed\")\r\nprint(\"ASCII Linefeed\")\r\nprint(\"ASCII Carriage return \\r here\")\r\nprint(\"Horizontal \\t tab\")\r\nprint(\"Vertical \\v tab\")\r\nprint(\"Octal value \\110\\145\\154\\154\\157\\40\")\r\nprint(\"Hex value: \\x48\\x65\\x6c\\x6c\\x6f\")\r\n"
},
{
"alpha_fraction": 0.5655527114868164,
"alphanum_fraction": 0.5758354663848877,
"avg_line_length": 24.066667556762695,
"blob_id": "daabc136b5ced28f7f601ee41861f3432cce93f6",
"content_id": "5f8dacbd1684197e748e328ac40fd2006b71be23",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 389,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 15,
"path": "/Setlist2/Q33.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "list1 = ['Boston', 'New York', 'Burlington', 'Hartford', 'Albany']\r\nnewList = list1\r\n\r\ndef alterList(x):\r\n x.append(\"Detroit\")\r\n x.insert(4,\"Indianapolis\")\r\n x = sorted(x, key=len)\r\n print(\"Sorted list:\")\r\n for val in x:\r\n print(val)\r\n x = x[:len(x)-3]\r\n print(\"List with last three elements deleted:\")\r\n for val in x:\r\n print(val)\r\nalterList(newList)"
},
{
"alpha_fraction": 0.6116504669189453,
"alphanum_fraction": 0.6456310749053955,
"avg_line_length": 35.6363639831543,
"blob_id": "b24cb9a7fecd81d153083ffa1894cd9d205e6587",
"content_id": "851f5d110f95440385436a5c673519f8a02b2def",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 412,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 11,
"path": "/Setlist2/Q21.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "import math\r\nimport random\r\n\r\nx = float(input(\"Enter a float for it to be rounded: \"))\r\nprint(str(x) + \" rounded returns: \" + str(round(x)))\r\n\r\ny = float(input(\"Enter a number to find its square root: \"))\r\nprint(\"The square root of \" + str(y) + \" is: \" + str(math.sqrt(y)))\r\n\r\nprint(\"Random number between 0-1: \" + str(random.randint(0,1)))\r\nprint(\"Random number between 10-500: \" + str(random.uniform(10,500)) )"
},
{
"alpha_fraction": 0.6085192561149597,
"alphanum_fraction": 0.610547661781311,
"avg_line_length": 36.07692337036133,
"blob_id": "3a1af731d0685bcf4526faf2a73cf703a7bf05d8",
"content_id": "f5930180073784bc35f936fada47a05a816b5325",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 493,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 13,
"path": "/Setlist2/Q22.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "import math\r\n\r\nx = float(input(\"Enter x value for trig functions: \"))\r\ny = float(input(\"Enter y value for trig functions: \"))\r\n\r\nprint(\"Arc Cosine of x:\" + str(math.acos(x)))\r\nprint(\"Arc Sine of x: \" + str(math.asin(x)))\r\nprint(\"Arc Tan of x: \" + str(math.atan(x)))\r\nprint(\"Tan of y/x: \" + str(math.atan2(y,x)))\r\nprint(\"Cosinse of x: \" + str(math.cos(x)))\r\nprint(\"Euclidean norm of x,y: \" + str(math.hypot(x,y)))\r\nprint(\"Sine of x: \" + str(math.sin(x)))\r\nprint(\"Tan of x: \" + str(math.tan(x)))"
},
{
"alpha_fraction": 0.6428571343421936,
"alphanum_fraction": 0.6507936716079712,
"avg_line_length": 30,
"blob_id": "730a647e6a9e5e4b3fa1333c9b42886f2a8886c0",
"content_id": "a58da44fb2620e3ef717112ad984632e1bea768a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 126,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 4,
"path": "/Setlist2/Q23.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "import math\r\nrad = float(input(\"Enter the radius of the cirle to find the area: \"))\r\n\r\nprint(\"Area: \" + str(math.pi * rad**2))"
},
{
"alpha_fraction": 0.5981308221817017,
"alphanum_fraction": 0.672897219657898,
"avg_line_length": 26.53333282470703,
"blob_id": "b8b2bc0754f2fd5a03aa53df2622e7c3b61a9b54",
"content_id": "91b7ab8431ed9ffe7bb3ef2bd11cfe28164bbd45",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 428,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 15,
"path": "/Setlist2/Q38.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "dict1 = {'Name':'Ramakrishna','Age':25}\r\ndict2 = {'EmpId':1234,'Salary':5000}\r\ndict1.update(dict2)\r\ndict3 = dict(dict1)\r\nprint(\"New dictionary created from dict1 and dict2: \" + str(dict3))\r\n\r\n\r\ndict3.update({\"Salary\":5500})\r\ndict3.update({\"Age\":26})\r\ndict3.update({'Grade':'B1'})\r\nprint(\"Salary and age updated, grade added:\")\r\nprint(str(dict3))\r\ndict3.pop('Age',None)\r\nprint(\"Dictionary with Age removed:\")\r\nprint(str(dict3))\r\n"
},
{
"alpha_fraction": 0.5314353704452515,
"alphanum_fraction": 0.5658363103866577,
"avg_line_length": 27.10344886779785,
"blob_id": "02421d6db56c076bc7d5b054f0da28542a55c1c5",
"content_id": "84798fbc7c9e22c1f49dd3c4a97b68bcc6c811c2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1686,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 58,
"path": "/Setlist2/Q32.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "list1 = ['Boston', 'New York', 'Burlington', 'Hartford', 'Albany']\r\nlist2 = ['Atlanta', 'Charlotte', 'Birmingham','Nashville', 'Charleston']\r\nlist3 = ['Dallas', 'Houston','El Paso','Arlington','Fort Worth']\r\n\r\ndef printCityLength(x):\r\n for val in x:\r\n print(\"City:\" + val + \"\\t Length:\" + str(len(val)))\r\nprint(\"List 1\")\r\nprintCityLength(list1)\r\nprint(\"\\nList 2\")\r\nprintCityLength(list2)\r\nprint(\"\\nList 3\")\r\nprintCityLength(list3)\r\n\r\ndef maxMin(x):\r\n y = sorted(x,key=len)\r\n print(\"Max: \" + y[-1])\r\n print(\"Min: \" + y[0])\r\n\r\nprint(\"\\nList1\")\r\nmaxMin(list1)\r\nprint(\"\\nList2\")\r\nmaxMin(list2)\r\nprint(\"\\nList3\")\r\nmaxMin(list3)\r\n\r\ndef listCompare():\r\n x = sorted(list1,key=len)\r\n y = sorted(list2,key=len)\r\n z = sorted(list3,key=len)\r\n \r\n if x[-1] > y[-1]and [x-1] > z[-1]:\r\n print(\"The max of all three lists is: \" + x[-1])\r\n elif y[-1] > x[-1] and y[-1] > z[-1]:\r\n print(\"The max of all three lists is: \" + y[-1])\r\n elif z[-1] > x[-1] and z[-1] > y[-1]:\r\n print(\"The max of all three lists is: \" + z[-1])\r\n if x[0] < y[0] and x[0] < z[0]:\r\n print(\"The min of all three lists is: \" + x[0])\r\n elif y[0] < x[0] and y[0] < z[0]:\r\n print(\"The min of all three lists is: \" + y[0])\r\n elif z[0] < x[0] and z[0] < y[0]:\r\n print(\"The min of all three lists is: \" + z[0])\r\n\r\nlistCompare()\r\n\r\ndef deleteFirstLast(x):\r\n x.pop(0)\r\n x.pop(-1)\r\n\r\n for val in x:\r\n print(val)\r\nprint(\"List 1, first and last elements removed:\")\r\ndeleteFirstLast(list1)\r\nprint(\"List 2, first and last elements removed:\")\r\ndeleteFirstLast(list2)\r\nprint(\"List 3, first and last elements removed:\")\r\ndeleteFirstLast(list3)"
},
{
"alpha_fraction": 0.44980695843696594,
"alphanum_fraction": 0.46138995885849,
"avg_line_length": 24,
"blob_id": "43a36d6533a2323692f6303cef1bf03dddb1ebe5",
"content_id": "cbe278a5812d89d7a270173de921bad11f98b31c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 518,
"license_type": "no_license",
"max_line_length": 63,
"num_lines": 20,
"path": "/Setlist2/Q30.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "y = int(input(\"Enter the number of integers you will enter: \"))\r\nx = []\r\ndef enterNumber(y):\r\n for i in range(y):\r\n z = int(input(\"Enter a number: \"))\r\n x.append(z)\r\n\r\nenterNumber(y)\r\nplaceholder = 0\r\ndef sort(x):\r\n for val in x:\r\n for i in range(len(x)-1):\r\n if x[i] > x[i+1]:\r\n continue\r\n elif x[i]<x[i+1]:\r\n placeholder = x[i+1]\r\n x[i+1] = x[i]\r\n x[i] = placeholder\r\nsort(x)\r\nprint(\"Sorted list: \" + str(x))"
},
{
"alpha_fraction": 0.5866666436195374,
"alphanum_fraction": 0.653333306312561,
"avg_line_length": 28.68181800842285,
"blob_id": "713dec61b6da3f5d8e254d4b671630bd08d58986",
"content_id": "f38f5c6d7ac1adb84f8e4c64c8845d0938a1c44b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 675,
"license_type": "no_license",
"max_line_length": 118,
"num_lines": 22,
"path": "/Setlist2/Q35.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "tup1 = ('Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday')\r\ntup2 = ('January','February','March','April','May','June','July','August','September','October','November','December')\r\ntup3 = tup1 + tup2\r\nprint(tup3)\r\n\r\ntup1x = (1,3,4,5)\r\ntup2x = (1,5,9,7)\r\ntup3x = (3,6,7,4)\r\n\r\nif (tup1x>tup2x and tup1x>tup3x):\r\n print(\"Tuple 1 is the greatest\")\r\nelif(tup2x>tup1x and tup2x>tup3x):\r\n print(\"Tuple 2 is the greatest\")\r\nelif(tup3x>tup1x and tup3x>tup2x):\r\n print(\"Tuple 3 is the greatest\")\r\n\r\ntup1x = list(tup1x)\r\ntup1x.insert(8,7)\r\ntup1x = tuple(tup1x)\r\nprint(\"Tup1 with new elements added through typecasting:\")\r\nfor val in tup1x:\r\n print(val)\r\n"
},
{
"alpha_fraction": 0.5106382966041565,
"alphanum_fraction": 0.589486837387085,
"avg_line_length": 21.558822631835938,
"blob_id": "aa08f9dd4962948a62b31914f34864808f83c1f5",
"content_id": "4b4262e8e752d5ac0de12df78928f806c52161eb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 799,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 34,
"path": "/Setlist2/Q34.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "list1 = [1,4,5,6,8,21,57,97]\r\nlist2 = [5,65,34,12,87,89,5,9]\r\nlist3 = [4,2,6,8,6,5,44,32]\r\n\r\nmaxList = []\r\nminList = []\r\ndef createMaxMinList():\r\n list1.sort()\r\n list2.sort()\r\n list3.sort()\r\n maxList.extend(list1[len(list1)-(len(list1)+2):])\r\n maxList.extend(list2[len(list2)-(len(list2)+2):])\r\n maxList.extend(list3[len(list3)-(len(list3)+2):])\r\n\r\n minList.extend(list1[0:2])\r\n minList.extend(list2[0:2])\r\n minList.extend(list3[0:2])\r\n\r\ncreateMaxMinList()\r\nprint(\"MAX LIST:\")\r\nx = 0\r\nfor val in maxList:\r\n x += val\r\n print(val)\r\nx /= len(maxList)\r\nprint(\"The average value of the max list is: \" + str(x)+\"\\n\")\r\n\r\nprint(\"MIN LIST:\")\r\ny = 0\r\nfor val in minList:\r\n y += val\r\n print(val)\r\ny /= len(minList)\r\nprint(\"The average value of the minList is: \" + str(y))"
},
{
"alpha_fraction": 0.7292817831039429,
"alphanum_fraction": 0.7292817831039429,
"avg_line_length": 20.875,
"blob_id": "f1cd174a0011bc899067535c064faac705aa4885",
"content_id": "08db02e3665674e8a722be7030b7e88578476698",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 181,
"license_type": "no_license",
"max_line_length": 39,
"num_lines": 8,
"path": "/Setlist2/Q39.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "from datetime import datetime\r\n\r\ncurrentDT = datetime.now()\r\n\r\nprint(\"Current date/time: \", currentDT)\r\n\r\ncurrentMonth = datetime.now().month\r\nprint(\"Current month: \", currentMonth)"
},
{
"alpha_fraction": 0.541329026222229,
"alphanum_fraction": 0.5964343547821045,
"avg_line_length": 23.79166603088379,
"blob_id": "055fa2bce7497a16b8317bd5328ff4bd3f42a448",
"content_id": "65ceb5b20bf3ac6dc36e4dc19f923bab37f7b565",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 617,
"license_type": "no_license",
"max_line_length": 51,
"num_lines": 24,
"path": "/Setlist2/Q36.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "tup1 = (\"A\",\"B\",\"C\",\"D\")\r\ntup2 = (\"E\",\"F\",\"G\",\"H\")\r\n\r\nprint(\"Comparison of tup1 and tup2:\")\r\nif tup1 > tup2:\r\n print(\"Tup1 is greater than tup2\")\r\nelif tup2 > tup1:\r\n print(\"Tup2 is greater than tup1\")\r\n\r\nprint(\"Length of tup1:\" + str(len(tup1)))\r\nprint(\"Length of tup2: \" + str(len(tup2)))\r\n\r\nprint(\"Max of tup1: \" + max(tup1))\r\nprint(\"Max of tup2: \" + max(tup2))\r\n\r\nprint(\"Min of tup1: \" + min(tup1))\r\nprint(\"Min of tup2: \" + min(tup2))\r\n\r\nlist1 = list(tup1)\r\nlist2 = list(tup2)\r\n\r\nprint(\"Conversion of list1 and list2 into tuples:\")\r\nprint(\"List1: \" + str(tuple(list1)))\r\nprint(\"List2: \" + str(tuple(list2)))"
},
{
"alpha_fraction": 0.5709090828895569,
"alphanum_fraction": 0.6036363840103149,
"avg_line_length": 32.375,
"blob_id": "ce8ebdcd2e43295097868c0833ecb8142a0d12f1",
"content_id": "e2e55dcac58db798341cb3b150dbfac762f8ad6d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 275,
"license_type": "no_license",
"max_line_length": 73,
"num_lines": 8,
"path": "/Setlist2/Q25.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "name = \"Alec\"\r\nage = 23\r\npi = 3.14\r\ninterests = ['dogs', 'football', 'music']\r\n\r\nprint(\"Hello my name is %s and I am %d years old.\" % (name,age))\r\nprint(\"I like %s, %s, and %s\" % (interests[0],interests[1],interests[2]))\r\nprint(\"The first three digits of pi are %.2f\" % pi)\r\n"
},
{
"alpha_fraction": 0.47493404150009155,
"alphanum_fraction": 0.4960422217845917,
"avg_line_length": 20.84848403930664,
"blob_id": "bc104ed61fc8fc0daa7c80845df9c539123af2c2",
"content_id": "88cbf4a2e560f0f3a6d553c76f2252f6a56420cb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 758,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 33,
"path": "/Setlist2/Q28.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "x = input(\"Enter a string to check the number of vowels are included: \")\r\nxList = list(x)\r\naCount = 0\r\neCount = 0\r\niCount = 0\r\noCount = 0\r\nuCount = 0\r\ntotalCount = 0\r\n\r\n\r\nfor val in xList:\r\n if val == 'a' or val == 'A': \r\n aCount+=1\r\n totalCount+=1\r\n if val == 'e' or val =='E':\r\n eCount+=1\r\n totalCount+=1\r\n if val == 'i' or val == 'I':\r\n iCount+=1\r\n totalCount+=1\r\n if val == 'o' or val == 'O':\r\n iCount+=1\r\n totalCount+=1\r\n if val == 'u' or val == 'U':\r\n uCount+=1\r\n totalCount+=1\r\n\r\nprint(\"Total number:\" + str(totalCount))\r\nprint(\"A: \" + str(aCount))\r\nprint(\"E: \" + str(eCount))\r\nprint(\"I: \" + str(iCount))\r\nprint(\"O: \" + str(oCount))\r\nprint(\"U: \" + str(uCount))\r\n\r\n\r\n"
},
{
"alpha_fraction": 0.5810810923576355,
"alphanum_fraction": 0.5855855941772461,
"avg_line_length": 26,
"blob_id": "72683afa1e4a706c29088dfb11f425df26886ee6",
"content_id": "f902de23cd74001669e2a37067bee210549ade8a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 222,
"license_type": "no_license",
"max_line_length": 57,
"num_lines": 8,
"path": "/Setlist2/Q27.py",
"repo_name": "AlecLjpg/PythonSetlist2",
"src_encoding": "UTF-8",
"text": "x = input(\"Enter a string to see if it is a palindrom: \")\r\n\r\ndef palindromeCheck(x):\r\n if str(x) == str(x)[::-1]:\r\n print(x + \" is a palindrome\")\r\n else: print(x + \" is not a palindrome\")\r\n\r\npalindromeCheck(x)"
}
] | 17
|
ArjunBiradar/Melanoma-Cancer-Prediction
|
https://github.com/ArjunBiradar/Melanoma-Cancer-Prediction
|
1db07a354b898da6dde08db7e1aeb692a00a1830
|
84bdcf182ddda12167fa9ecf9fdadfc5e1de8baf
|
ab331f7de7cbb4384f178239e344924032c217b2
|
refs/heads/main
| 2023-04-30T20:43:22.992314
| 2021-05-24T16:32:11
| 2021-05-24T16:32:11
| 370,418,030
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7790697813034058,
"alphanum_fraction": 0.7790697813034058,
"avg_line_length": 41,
"blob_id": "00c59af2e4c701802340cc1ab5b085be016673ca",
"content_id": "32d07c9076c308bb16f92677cc043e48a6e6f8d3",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 86,
"license_type": "permissive",
"max_line_length": 58,
"num_lines": 2,
"path": "/README.md",
"repo_name": "ArjunBiradar/Melanoma-Cancer-Prediction",
"src_encoding": "UTF-8",
"text": "# Skin-Cancer-Prediction\r\nBuilt a web app to detect the deadly melanoma skin cancer.\r\n"
},
{
"alpha_fraction": 0.6585366129875183,
"alphanum_fraction": 0.7317073345184326,
"avg_line_length": 11.5,
"blob_id": "d261dbc5890038afd1d6d47176c79a713a6d76e3",
"content_id": "22436cfd6f68d2289e744f1970617d81de207372",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 82,
"license_type": "permissive",
"max_line_length": 16,
"num_lines": 6,
"path": "/requirements.txt",
"repo_name": "ArjunBiradar/Melanoma-Cancer-Prediction",
"src_encoding": "UTF-8",
"text": "albumentations\r\nflask\r\nflask_cors\r\npretrainedmodels\r\ntorch==1.5.0\r\nwtfml==0.0.3 \r\n"
},
{
"alpha_fraction": 0.5725504755973816,
"alphanum_fraction": 0.5998504161834717,
"avg_line_length": 26.094736099243164,
"blob_id": "486a121f654b7f9e9615c96208e69a5602ad7335",
"content_id": "4a39e0117c9866b8cb8a83a8e17dc2c33446ac1a",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2674,
"license_type": "permissive",
"max_line_length": 96,
"num_lines": 95,
"path": "/app.py",
"repo_name": "ArjunBiradar/Melanoma-Cancer-Prediction",
"src_encoding": "UTF-8",
"text": "from flask import Flask, request, render_template\r\n\r\nimport os\r\nimport torch\r\nfrom torch.utils import data \r\n\r\nimport albumentations\r\nimport pretrainedmodels\r\n\r\nimport numpy as np\r\nimport torch.nn as nn\r\n\r\nfrom torch.nn import functional as F\r\n\r\nfrom wtfml.data_loaders.image.classification import ClassificationDataset\r\nfrom wtfml.engine.engine import Engine\r\n\r\napp = Flask(__name__)\r\nUPLOAD_FOLDER = \"D:/pythonProject/melanoma/static\" \r\nDEVICE = \"cpu\"\r\nMODEL = None\r\n\r\n\r\nclass SEResNext50_32x4d(nn.Module):\r\n def __init__(self, pretrained=\"imagenet\"):\r\n super(SEResNext50_32x4d, self).__init__()\r\n self.base_model = pretrainedmodels.__dict__[\r\n \"se_resnext50_32x4d\"\r\n ](pretrained=pretrained)\r\n self.l0 = nn.Linear(2048, 1)\r\n\r\n def forward(self, image, targets):\r\n bs, _, _, _ = image.shape\r\n x = self.base_model.features(image)\r\n x = F.adaptive_avg_pool2d(x, 1)\r\n x = x.reshape(bs, -1)\r\n out = torch.sigmoid(self.l0(x))\r\n loss = 0\r\n return out, loss\r\n\r\n\r\ndef predict(image_path, model):\r\n mean = (0.485, 0.456, 0.406)\r\n std = (0.229, 0.224, 0.225)\r\n\r\n test_aug = albumentations.Compose(\r\n [\r\n albumentations.Normalize(mean, std, max_pixel_value=255.0, always_apply=True),\r\n ]\r\n )\r\n\r\n test_images = [image_path]\r\n test_targets = [0]\r\n\r\n test_dataset = ClassificationDataset(\r\n image_paths=test_images,\r\n targets=test_targets,\r\n resize=None,\r\n augmentations=test_aug\r\n )\r\n\r\n test_loader = data.DataLoader(\r\n test_dataset,\r\n batch_size=1,\r\n shuffle=False,\r\n num_workers=0\r\n )\r\n eng = Engine(model, device=DEVICE, optimizer=None)\r\n\r\n predictions = eng.predict(test_loader)\r\n\r\n return np.vstack((predictions)).ravel()\r\n\r\n\r\n@app.route(\"/\", methods=[\"GET\", \"POST\"])\r\ndef upload_predict():\r\n if request.method == \"POST\":\r\n image_file = request.files[\"image\"]\r\n if image_file:\r\n image_location = os.path.join(\r\n UPLOAD_FOLDER,\r\n image_file.filename\r\n )\r\n image_file.save(image_location)\r\n pred = predict(image_location, MODEL)[0]\r\n return render_template(\"index.html\", prediction=pred, image_loc=image_file.filename)\r\n return render_template(\"index.html\", prediction=0, image_loc=None)\r\n\r\n\r\nif __name__ == \"__main__\":\r\n MODEL = SEResNext50_32x4d(pretrained=None)\r\n MODEL.load_state_dict(torch.load(\"model.bin\", map_location=torch.device(DEVICE)))\r\n MODEL.to(DEVICE)\r\n # app.run(host=\"0.0.0.0\", port=12000, debug=True)\r\n app.run(debug=True) \r\n "
},
{
"alpha_fraction": 0.6753246784210205,
"alphanum_fraction": 0.698051929473877,
"avg_line_length": 18.46666717529297,
"blob_id": "b6a74bdff0b1737264b70dbec02dadb8e7c2cff3",
"content_id": "ab4dd05d2a808d87894902de55854b3c770975ee",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Dockerfile",
"length_bytes": 308,
"license_type": "permissive",
"max_line_length": 65,
"num_lines": 15,
"path": "/Dockerfile",
"repo_name": "ArjunBiradar/Melanoma-Cancer-Prediction",
"src_encoding": "UTF-8",
"text": "FROM ubuntu:18.04\r\n\r\nRUN apt-get update && apt-get install -y python3 python3-pip sudo\r\n\r\nRUN useradd -m aniket\r\n\r\nRUN chown -R aniket:aniket /home/aniket/\r\n\r\nCOPY --chown=aniket . /home/aniket/app/\r\n\r\nUSER aniket\r\n\r\nRUN cd /home/aniket/app/ && pip3 install -r requirements.txt\r\n\r\nWORKDIR /home/aniket/app \r\n"
}
] | 4
|
e-k-a/parserGosZakupki
|
https://github.com/e-k-a/parserGosZakupki
|
df36120d7af25af6e74823726a9b69d7ccb2d7b6
|
f08e9deb2c2b70d114cd0b8ab75e28162d6072c8
|
032efecb6f4e643226938894b7ee10618065c249
|
refs/heads/main
| 2023-06-17T02:53:01.275915
| 2021-07-09T18:42:10
| 2021-07-09T18:42:10
| 384,523,168
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5628800392150879,
"alphanum_fraction": 0.587479293346405,
"avg_line_length": 66.18868255615234,
"blob_id": "385eb9eb4184f4d3262b436e31694b28c9b2a43f",
"content_id": "a3a78864e54d3e63a41e0d91b4771a10be2a26e2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7492,
"license_type": "no_license",
"max_line_length": 893,
"num_lines": 106,
"path": "/goszakupki/goszakupki/spiders/kon.py",
"repo_name": "e-k-a/parserGosZakupki",
"src_encoding": "UTF-8",
"text": "import scrapy\r\n\r\nclass CatalogSpider(scrapy.Spider):\r\n name = 'kontrac'\r\n allowed_domains = ['zakupki.gov.ru']\r\n start_urls = ['https://zakupki.gov.ru/']\r\n pages_count = 5\r\n\r\n def start_requests(self):\r\n for page in range(1, 1 + self.pages_count):\r\n url = f'https://zakupki.gov.ru/epz/contract/search/results.html?searchString=&morphology=on&search-filter=%D0%94%D0%B0%D1%82%D0%B5+%D1%80%D0%B0%D0%B7%D0%BC%D0%B5%D1%89%D0%B5%D0%BD%D0%B8%D1%8F&savedSearchSettingsIdHidden=&fz44=on&contractStageList_0=on&contractStageList_1=on&contractStageList_2=on&contractStageList_3=on&contractStageList=0%2C1%2C2%2C3&contractInputNameDefenseOrderNumber=&contractInputNameContractNumber=&contractPriceFrom=&rightPriceRurFrom=&contractPriceTo=&rightPriceRurTo=&priceToUnitGWS=&contractCurrencyID=-1&nonBudgetCodesList=&budgetLevelsIdHidden=&budgetLevelsIdNameHidden=%7B%7D&budgetName=&customerPlace=&customerPlaceCodes=&contractDateFrom=&contractDateTo=&publishDateFrom=&publishDateTo=&updateDateFrom=&updateDateTo=&placingWayList=&selectedLaws=&sortBy=UPDATE_DATE&pageNumber={page}&sortDirection=false&recordsPerPage=_10&showLotsInfoHidden=false'\r\n yield scrapy.Request(url, callback=self.parse_pages)\r\n\r\n def parse_pages(self, response, **kwargs):\r\n for href in response.css('.registry-entry__header-mid__number ::attr(\"href\")').extract():\r\n url = response.urljoin(href)\r\n yield scrapy.Request(url, callback=self.parse)\r\n\r\n def parse(self, response, **kwargs):\r\n GenInf = {}\r\n for GI in response.xpath('/html/body/div[2]/div/div[2]/div[1]/div/div/div/section'):\r\n Value = GI.xpath('span[2]/text()').extract_first('').strip()\r\n if Value:\r\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span[2]/text()').extract_first('').strip()\r\n else:\r\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span/a/text()').extract_first('').strip()\r\n ChangeKontr = {}\r\n for CK in response.xpath('/html/body/div[2]/div/div[2]/div[2]/div/div/div/section'):\r\n ChangeKontr[CK.xpath('span[1]/text()').extract_first('').strip() ] = CK.xpath('span[2]/text()').extract_first('').strip() \r\n CustInf = {}\r\n for CI in response.xpath('/html/body/div[2]/div/div[2]/div[3]/div/div/div/section'):\r\n Value = CI.xpath('span[2]/text()').extract_first('').strip()\r\n if Value:\r\n CustInf[CI.xpath('span[1]/text()').extract_first('').strip() ] = CI.xpath('span[2]/text()').extract_first('').strip()\r\n else:\r\n CustInf[CI.xpath('span[1]/text()').extract_first('').strip() ] = CI.xpath('span/a/text()').extract_first('').strip() \r\n GenData = {}\r\n for GD in response.xpath('/html/body/div[2]/div/div[2]/div[3]/div/div/div/section'):\r\n GenData[GD.xpath('span[1]/text()').extract_first('').strip() ] = GD.xpath('span[2]/text()').extract_first('').strip() \r\n\r\n\r\n #urlTable = 'https://zakupki.gov.ru' + response.xpath('/html/body/div[2]/div/div[1]/div[3]/div/a[2]/@href').extract_first()\r\n urlHelp = response.urljoin(response.xpath('/html/body/div[2]/div/div[1]/div[3]/div/a[2]/@href').extract_first())\r\n #POK = scrapy.Request(urlHelp, callback=self.ParseTable)\r\n \r\n\r\n item = {}\r\n item['номер'] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[1]/div[1]/div/span[1]/a//text()\").extract_first('').strip()\r\n item['url'] = response.request.url,\r\n '''\r\n item['статус контракта'] = response.css('.cardMainInfo__state ::text').extract_first('').strip(),\r\n item['объект закупки' ] = response.xpath('/html/body/div[2]/div/div[1]/div[2]/div[2]/div[1]/div[2]/div[3]/div[2]/span/text()').extract_first(\"\").strip(),\r\n item['заказчик' ] = response.xpath(\"/html/body/div[2]/div/div[2]/div[2]/div/div/div/section[1]/span[2]/a/text()\").extract_first(' ').strip(),\r\n item['начальная цена' ] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[1]/span[2]/text()\").extract_first(' ').strip(),\r\n item['Заключение контракта'] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[1]/span[2]/text()\").extract_first(' ').strip(),\r\n item['Срок исполнения'] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[2]/span[2]/text()\").extract_first(' ').strip(),\r\n item['Размещен контракт в реестре контрактов'] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[3]/span[2]/text()\").extract_first(' ').strip(),\r\n item['Обновлен контракт в реестре контрактов'] = response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[4]/span[2]/text()\").extract_first(' ').strip(),\r\n item['Общая информация'] = GenInf,\r\n item['Информация о заказчике'] = CustInf,\r\n item['Общие данные'] = GenData,\r\n '''\r\n item['url 2-ой страницы'] = urlHelp,\r\n #'Последняя часть' : POK,\r\n\r\n\r\n \r\n\r\n \r\n yield scrapy.Request(urlHelp, callback=self.ParseTable, meta={'item': item})\r\n #yield item\r\n\r\n \r\n def ParseTable(self, response):\r\n item = response.meta['item']\r\n #item['Проверка'] = response.xpath('/html/body/div[2]/div/div[2]/div/div/div[1]/div[1]/div[1]/div/span/text()').extract_first(' ').strip()\r\n #head = []\r\n #for n in response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/thead/tr/th'):\r\n \r\n #head.append(n.xpath('/text()')).extract_first('').strip()\r\n # item['заголовки'] = n.xpath('/text()').extract_first('').strip()\r\n item['h'] = response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/tfoot/tr/td[1]/span/text()').extract_first('').strip()\r\n gg={}\r\n for GI in response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/tbody/tr/td[1]'):\r\n gg[response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/thead/tr/th[1]/text()').extract_first('').strip()] = 'шесть слонов'\r\n item['help'] = gg \r\n '''\r\n GenData = {}\r\n for GD in response.xpath(' //*[@id=\"contract_subjects\"]/tbody/tr[1]/td'):\r\n h = GD.xpath('/div[1]/text()').extract_first('').strip()\r\n if h:\r\n GenData['Help' ] = GD.xpath('/div[1]/text()').extract_first('').strip()\r\n print(\"Gd1\",GD.xpath('/div[1]/text()').extract())\r\n else:\r\n GenData['Help' ] = GD.xpath('/text()').extract_first('').strip()\r\n print(\"Gd2\",GD.xpath('/text()').extract())\r\n item['help'] = GenData\r\n print(\"Gendata\",GenData)\r\n '''\r\n '''\r\n OBJ = {}\r\n for ob in response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/tbody/tr'):\r\n OBJ[response.xpath('/html/body/div[2]/div/div[3]/div/div/div/div[1]/table/thead/tr/th[1]/text()').extract_first('').strip() ] = OBJ.xpath('/td[1]/div[1]/text()').extract_first('').strip() \r\n item['Объекты закупки'] = OBJ\r\n ''' \r\n yield item\r\n "
},
{
"alpha_fraction": 0.557055652141571,
"alphanum_fraction": 0.5884963870048523,
"avg_line_length": 77.20289611816406,
"blob_id": "29fc41bbf85cd42013515175a3e7fa68d0dcaed9",
"content_id": "e4d98eef7ef23229bb394906444d9d442e59a53f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5592,
"license_type": "no_license",
"max_line_length": 684,
"num_lines": 69,
"path": "/goszakupki/goszakupki/spiders/goszakupkik.py",
"repo_name": "e-k-a/parserGosZakupki",
"src_encoding": "UTF-8",
"text": "import scrapy\n\nclass CatalogSpider(scrapy.Spider):\n name = 'goszakupki'\n #allowed_domains = ['zakupki.gov.ru']\n start_urls = ['https://zakupki.gov.ru/']\n pages_count = 100\n\n def start_requests(self):\n for page in range(1, 1 + self.pages_count):\n url = f'https://zakupki.gov.ru/epz/order/extendedsearch/results.html?searchString=&morphology=on&search-filter=%D0%94%D0%B0%D1%82%D0%B5+%D1%80%D0%B0%D0%B7%D0%BC%D0%B5%D1%89%D0%B5%D0%BD%D0%B8%D1%8F&pageNumber={page}&sortDirection=false&recordsPerPage=_10&showLotsInfoHidden=false&savedSearchSettingsIdHidden=&sortBy=UPDATE_DATE&fz44=on&fz223=on&af=on&ca=on&pc=on&pa=on&placingWayList=&selectedLaws=&priceFromGeneral=&priceFromGWS=&priceFromUnitGWS=&priceToGeneral=&priceToGWS=&priceToUnitGWS=¤cyIdGeneral=-1&publishDateFrom=&publishDateTo=&applSubmissionCloseDateFrom=&applSubmissionCloseDateTo=&customerIdOrg=&customerFz94id=&customerTitle=&okpd2Ids=&okpd2IdsCodes='\n yield scrapy.Request(url, callback=self.parse_pages)\n\n def parse_pages(self, response, **kwargs):\n for href in response.css('.registry-entry__header-mid__number ::attr(\"href\")').extract():\n url = response.urljoin(href)\n yield scrapy.Request(url, callback=self.parse)\n\n def parse(self, response, **kwargs):\n \n CheckSite1 = response.css('.cardMainInfo__purchaseLink ::text').extract_first('').strip()\n CheckSite2 = response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[2]/td[2]/span/text()\").extract_first('').strip(),\n if (CheckSite1):\n GenInf = {}\n for GI in response.xpath('/html/body/div[2]/div/div[2]/div/div/section'):\n Value = GI.xpath('span[2]/text()').extract_first('').strip()\n if Value:\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span[2]/text()').extract_first('').strip()\n else:\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span/a/text()').extract_first('').strip()\n\n item = {\n 'номер' : response.css('.cardMainInfo__purchaseLink ::text').extract_first('').strip(),\n 'url': response.request.url,\n 'заказчик' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[1]/div[2]/div[2]/span[2]/a/text()\").extract_first(' ').strip(),\n 'объект' : response.css('.cardMainInfo__content ::text').extract_first(''),\n #'начальная цена' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[1]/span[2]/text()\").extract_first(' ').strip(),\n #'статус закупки' : response.css('.cardMainInfo__state ::text').extract_first(''),\n 'Размещено' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[1]/div[1]/span[2]/text()\").extract_first(' ').strip(),\n 'Обновлено' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[1]/div[2]/span[2]/text()\").extract_first(' ').strip(),\n 'Окончание подачи заявок' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[2]/span[2]/text()\").extract_first(' ').strip(),\n 'Общая информация' : GenInf,\n }\n\n elif (CheckSite2):\n GenInf = {}\n \n #GenInf[response.xpath('/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[1]/td[1]/text()').extract_first('').strip() ] = response.xpath('/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[2]/td[2]/span/text()').extract_first('').strip()\n for GI in response.xpath('/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr'):\n Value = GI.xpath('/td[1]/text()').extract_first('').strip()\n if Value:\n GenInf[GI.xpath('td[1]/span/text()').extract_first('').strip() ] = GI.xpath('td[2]/span/text()').extract_first('').strip()\n \n \n \n item = {\n 'номер' : response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[2]/td[2]/span//text()\").extract_first().strip(),\n 'url': response.request.url,\n 'заказчик' : response.xpath('/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[4]/table/tbody/tr[1]/td[2]/text()').extract_first('').strip(),\n 'объект' : response.xpath('/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[4]/td[2]/span//text()').extract_first().strip(),\n #'начальная цена' : response.xpath('//*[@id=\"lot\"]/tbody/tr/td[4]/text()').extract_first().strip(),\n 'Размещено' : response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[7]/td[2]/text()\").extract_first(' ').strip(),\n 'Обновлено' : response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[8]/td[2]/text()\").extract_first(' ').strip(),\n 'Окончание подачи заявок' : response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[6]/table/tbody/tr[3]/td[2]/span/text()\").extract_first(' ').strip(),\n 'Общая информация' : GenInf,\n\n }\n\n yield item\n \n\n\n"
},
{
"alpha_fraction": 0.7857142686843872,
"alphanum_fraction": 0.8492063283920288,
"avg_line_length": 41,
"blob_id": "fae341ef5bf621ad6e1b1119ab5b961fbf17994c",
"content_id": "e44868e263375a4efd7601352f6be0bb5e7bc208",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 202,
"license_type": "no_license",
"max_line_length": 93,
"num_lines": 3,
"path": "/README.md",
"repo_name": "e-k-a/parserGosZakupki",
"src_encoding": "UTF-8",
"text": "# parserGosZakupki\nPractic 2021\nДанная папка содержит файлы для паука, который создавался на вычислительной практике 2021 МАИ\n"
},
{
"alpha_fraction": 0.5958386063575745,
"alphanum_fraction": 0.6387137174606323,
"avg_line_length": 49.16128921508789,
"blob_id": "4a02dd905b4db0badd5787adc304c2864c259005",
"content_id": "ae61440aa3d38709c2020b6cf8434f11b8386656",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1610,
"license_type": "no_license",
"max_line_length": 527,
"num_lines": 31,
"path": "/goszakupki/goszakupki/spiders/dogovor.py",
"repo_name": "e-k-a/parserGosZakupki",
"src_encoding": "UTF-8",
"text": "import scrapy\r\n\r\nclass CatalogSpider(scrapy.Spider):\r\n name = 'dogovor'\r\n start_urls = ['https://zakupki.gov.ru/']\r\n pages_count = 5\r\n\r\n def start_requests(self):\r\n for page in range(1, 1 + self.pages_count):\r\n url = f'https://zakupki.gov.ru/epz/contractfz223/search/results.html?searchString=&morphology=on&search-filter=%D0%94%D0%B0%D1%82%D0%B5+%D1%80%D0%B0%D0%B7%D0%BC%D0%B5%D1%89%D0%B5%D0%BD%D0%B8%D1%8F&savedSearchSettingsIdHidden=&statuses_0=on&statuses_1=on&statuses_2=on&statuses_3=on&statuses=0%2C1%2C2%2C3&priceFrom=&priceTo=¤cyId=-1&contract223DateFrom=&contract223DateTo=&publishDateFrom=&publishDateTo=&sortBy=BY_UPDATE_DATE&pageNumber={page}&sortDirection=false&recordsPerPage=_10&showLotsInfoHidden=false'\r\n yield scrapy.Request(url, callback=self.parse_pages)\r\n\r\n def parse_pages(self, response, **kwargs):\r\n for href in response.css('.registry-entry__header-mid__number ::attr(\"href\")').extract():\r\n url = response.urljoin(href)\r\n yield scrapy.Request(url, callback=self.parse)\r\n\r\n def parse(self, response, **kwargs):\r\n item = {\r\n 'номер' : response.xpath(\"/html/body/div[3]/div/div/div[2]/div/div/div[2]/div[2]/div[1]/table/tbody/tr[1]/td[2]/text()\").extract_first().strip(),\r\n 'url': response.request.url,\r\n #'заказчик' : response.xpath(\"/html/body/div[2]/div/div[2]/div[2]/div/div/div/section[1]/span[2]/a/text()\").extract_first(' ').strip(),\r\n #'Общие данные' : GenData,\r\n\r\n\r\n\r\n }\r\n\r\n \r\n \r\n yield item\r\n"
},
{
"alpha_fraction": 0.5816901326179504,
"alphanum_fraction": 0.6106640100479126,
"avg_line_length": 72.14925384521484,
"blob_id": "78d8cca52ca23ef51b054dccc44e5e18d44b15e7",
"content_id": "af8bbce9c6f8c67383810d4570f619353449c294",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5171,
"license_type": "no_license",
"max_line_length": 893,
"num_lines": 67,
"path": "/goszakupki/goszakupki/spiders/kontract.py",
"repo_name": "e-k-a/parserGosZakupki",
"src_encoding": "UTF-8",
"text": "import scrapy\r\n\r\nclass CatalogSpider(scrapy.Spider):\r\n name = 'kontract'\r\n allowed_domains = ['zakupki.gov.ru']\r\n start_urls = ['https://zakupki.gov.ru/']\r\n pages_count = 100\r\n\r\n def start_requests(self):\r\n for page in range(1, 1 + self.pages_count):\r\n url = f'https://zakupki.gov.ru/epz/contract/search/results.html?searchString=&morphology=on&search-filter=%D0%94%D0%B0%D1%82%D0%B5+%D1%80%D0%B0%D0%B7%D0%BC%D0%B5%D1%89%D0%B5%D0%BD%D0%B8%D1%8F&savedSearchSettingsIdHidden=&fz44=on&contractStageList_0=on&contractStageList_1=on&contractStageList_2=on&contractStageList_3=on&contractStageList=0%2C1%2C2%2C3&contractInputNameDefenseOrderNumber=&contractInputNameContractNumber=&contractPriceFrom=&rightPriceRurFrom=&contractPriceTo=&rightPriceRurTo=&priceToUnitGWS=&contractCurrencyID=-1&nonBudgetCodesList=&budgetLevelsIdHidden=&budgetLevelsIdNameHidden=%7B%7D&budgetName=&customerPlace=&customerPlaceCodes=&contractDateFrom=&contractDateTo=&publishDateFrom=&publishDateTo=&updateDateFrom=&updateDateTo=&placingWayList=&selectedLaws=&sortBy=UPDATE_DATE&pageNumber={page}&sortDirection=false&recordsPerPage=_10&showLotsInfoHidden=false'\r\n yield scrapy.Request(url, callback=self.parse_pages)\r\n\r\n def parse_pages(self, response, **kwargs):\r\n for href in response.css('.registry-entry__header-mid__number ::attr(\"href\")').extract():\r\n url = response.urljoin(href)\r\n yield scrapy.Request(url, callback=self.parse)\r\n\r\n def parse(self, response, **kwargs):\r\n GenInf = {}\r\n for GI in response.xpath('/html/body/div[2]/div/div[2]/div[1]/div/div/div/section'):\r\n Value = GI.xpath('span[2]/text()').extract_first('').strip()\r\n if Value:\r\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span[2]/text()').extract_first('').strip()\r\n else:\r\n GenInf[GI.xpath('span[1]/text()').extract_first('').strip() ] = GI.xpath('span/a/text()').extract_first('').strip()\r\n ChangeKontr = {}\r\n for CK in response.xpath('/html/body/div[2]/div/div[2]/div[2]/div/div/div/section'):\r\n ChangeKontr[CK.xpath('span[1]/text()').extract_first('').strip() ] = CK.xpath('span[2]/text()').extract_first('').strip() \r\n CustInf = {}\r\n for CI in response.xpath('/html/body/div[2]/div/div[2]/div[3]/div/div/div/section'):\r\n Value = CI.xpath('span[2]/text()').extract_first('').strip()\r\n if Value:\r\n CustInf[CI.xpath('span[1]/text()').extract_first('').strip() ] = CI.xpath('span[2]/text()').extract_first('').strip()\r\n else:\r\n CustInf[CI.xpath('span[1]/text()').extract_first('').strip() ] = CI.xpath('span/a/text()').extract_first('').strip() \r\n GenData = {}\r\n for GD in response.xpath('/html/body/div[2]/div/div[2]/div[3]/div/div/div/section'):\r\n GenData[GD.xpath('span[1]/text()').extract_first('').strip() ] = GD.xpath('span[2]/text()').extract_first('').strip() \r\n\r\n\r\n #urlTable = 'https://zakupki.gov.ru' + response.xpath('/html/body/div[2]/div/div[1]/div[3]/div/a[2]/@href').extract_first()\r\n #urlHelp = response.urljoin(response.xpath('/html/body/div[2]/div/div[1]/div[3]/div/a[2]/@href').extract_first())\r\n \r\n \r\n\r\n item = {\r\n 'номер' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[1]/div[1]/div/span[1]/a//text()\").extract_first('').strip(),\r\n 'url': response.request.url,\r\n 'статус контракта' : response.css('.cardMainInfo__state ::text').extract_first('').strip(),\r\n 'объект закупки' : response.xpath('/html/body/div[2]/div/div[1]/div[2]/div[2]/div[1]/div[2]/div[3]/div[2]/span/text()').extract_first(\"\").strip(),\r\n 'заказчик' : response.xpath(\"/html/body/div[2]/div/div[2]/div[2]/div/div/div/section[1]/span[2]/a/text()\").extract_first(' ').strip(),\r\n 'начальная цена' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[1]/span[2]/text()\").extract_first(' ').strip(),\r\n 'Заключение контракта' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[1]/span[2]/text()\").extract_first(' ').strip(),\r\n 'Срок исполнения' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[2]/span[2]/text()\").extract_first(' ').strip(),\r\n 'Размещен контракт в реестре контрактов' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[3]/span[2]/text()\").extract_first(' ').strip(),\r\n 'Обновлен контракт в реестре контрактов' : response.xpath(\"/html/body/div[2]/div/div[1]/div[2]/div[2]/div[2]/div[2]/div[4]/span[2]/text()\").extract_first(' ').strip(),\r\n 'Общая информация' : GenInf,\r\n 'Информация о заказчике' : CustInf,\r\n 'Общие данные' : GenData,\r\n\r\n\r\n }\r\n\r\n \r\n \r\n yield item\r\n\r\n"
}
] | 5
|
utk1801/fsdse-python-assignment-15
|
https://github.com/utk1801/fsdse-python-assignment-15
|
4fbc382fd0664b66c5d823c10b2a224264fb2244
|
1ecfe92e11123ade726cd1834d6cfb298ee3d72e
|
18c30030a3999a6ff1e7431f753da271cd10b604
|
refs/heads/master
| 2021-01-25T10:50:30.614386
| 2017-06-13T17:41:12
| 2017-06-13T17:41:12
| 93,884,046
| 0
| 0
| null | 2017-06-09T17:58:06
| 2017-05-23T09:07:53
| 2017-06-05T10:08:34
| null |
[
{
"alpha_fraction": 0.4810126721858978,
"alphanum_fraction": 0.4873417615890503,
"avg_line_length": 18.75,
"blob_id": "898cd2d850c9446b53ff7cd3c319309271d5acc6",
"content_id": "de7e673442967bedfb30d019f938946031558694",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 158,
"license_type": "no_license",
"max_line_length": 37,
"num_lines": 8,
"path": "/build.py",
"repo_name": "utk1801/fsdse-python-assignment-15",
"src_encoding": "UTF-8",
"text": "def solution(list):\n r=list[::-1]\n print r\n if list==r:\n return True\n else:\n return False\nprint solution(['n','i','t','i','n'])\n"
}
] | 1
|
ShozenD/CNN-Nogizaka46
|
https://github.com/ShozenD/CNN-Nogizaka46
|
b561c383e72b59140be336fe0c3aed0fffc747b9
|
b762bf58c3fda2c15fd32a714719fb03b5986063
|
a5a8f28733f3a320c18ce2492700cb7b16e75ae8
|
refs/heads/master
| 2020-04-15T09:27:01.476815
| 2019-01-23T06:00:45
| 2019-01-23T06:00:45
| 164,550,374
| 2
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6084533333778381,
"alphanum_fraction": 0.6168137192726135,
"avg_line_length": 34.81666564941406,
"blob_id": "3e94261fdadc83da93b8f4e6454d1b0150e440c9",
"content_id": "64896cb1f0636d69bf810e982bf82adcf747f0cd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4350,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 120,
"path": "/PreprocessingNoRotate.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import glob, os, cv2, math, shutil\nfrom scipy import ndimage\n\n# Path to the directory that will hold the data\nbase_dir='./Input_Data_NoRotate'\nos.mkdir(base_dir)\n\n# The directories to house the training images, validation images, and test images\ntrain_dir = os.path.join(base_dir, 'train')\nos.mkdir(train_dir)\ntest_dir = os.path.join(base_dir, 'test')\nos.mkdir(test_dir)\n\n# Creating the directory to house the training images\ntrain_erika_dir = os.path.join(train_dir, 'erika')\nos.mkdir(train_erika_dir)\ntrain_asuka_dir = os.path.join(train_dir, 'asuka')\nos.mkdir(train_asuka_dir)\ntrain_mai_dir = os.path.join(train_dir, 'mai')\nos.mkdir(train_mai_dir)\ntrain_nanase_dir = os.path.join(train_dir, 'nanase')\nos.mkdir(train_nanase_dir)\ntrain_nanami_dir = os.path.join(train_dir, 'nanami')\nos.mkdir(train_nanami_dir)\n\n# The directory to house the testing images\ntest_erika_dir = os.path.join(test_dir, 'erika')\nos.mkdir(test_erika_dir)\ntest_asuka_dir = os.path.join(test_dir, 'asuka')\nos.mkdir(test_asuka_dir)\ntest_mai_dir = os.path.join(test_dir, 'mai')\nos.mkdir(test_mai_dir)\ntest_nanase_dir = os.path.join(test_dir, 'nanase')\nos.mkdir(test_nanase_dir)\ntest_nanami_dir = os.path.join(test_dir, 'nanami')\nos.mkdir(test_nanami_dir)\n\nfnames = glob.glob(\"./Aligned/生田絵梨花/*\") \ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_erika_dir, 'erika.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_erika_dir, 'erika.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/齋藤飛鳥/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_asuka_dir, 'asuka.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_asuka_dir, 'asuka.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/白石麻衣/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_mai_dir, 'mai.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_mai_dir, 'mai.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/橋本奈々未/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_nanase_dir, 'nanami.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_nanase_dir, 'nanami.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/西野七瀬/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_nanami_dir, 'nanase.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_nanami_dir, 'nanase.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\n# Augmenting the Data\nnames = [\"asuka\",\"mai\",\"erika\",\"nanami\",\"nanase\"]\nfor name in names:\n in_dir = \"./Input_Data_NoRotate/train/\"+name+\"/*\"\n out_dir = \"./Input_Data_NoRotate/train/\"+name\n in_jpg=glob.glob(in_dir)\n img_file_name_list=os.listdir(\"./Input_Data_NoRotate/train/\"+name+\"/\")\n for i in range(len(in_jpg)):\n img = cv2.imread(str(in_jpg[i]))\n # Rotate Images\n for ang in [0]:\n img_rot = ndimage.rotate(img,ang)\n img_rot = cv2.resize(img_rot,(150,150))\n fileName=os.path.join(out_dir,str(i)+\"_\"+str(ang)+\".jpg\")\n cv2.imwrite(str(fileName),img_rot)\n # Threshold\n img_thr = cv2.threshold(img_rot, 100, 255, cv2.THRESH_TOZERO)[1]\n fileName=os.path.join(out_dir,str(i)+\"_\"+str(ang)+\"thr.jpg\")\n cv2.imwrite(str(fileName),img_thr)\n # Filter Images\n img_filter = cv2.GaussianBlur(img_rot, (5, 5), 0)\n fileName=os.path.join(out_dir,str(i)+\"_\"+str(ang)+\"filter.jpg\")\n cv2.imwrite(str(fileName),img_filter)\n "
},
{
"alpha_fraction": 0.6303257942199707,
"alphanum_fraction": 0.63345867395401,
"avg_line_length": 32.61052703857422,
"blob_id": "dbf49f0b832b1bf7229a85d4f91af21c3c3a0916",
"content_id": "e0c902c58dbaeba714559cfcbeba2b2b67c90dce",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3236,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 95,
"path": "/PreprocessingNoChange.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import os, math, shutil, glob\n\n# Path to the directory that will hold the data\nbase_dir='./Input_Data_NoChange'\nos.mkdir(base_dir)\n\n# The directories to house the training images, validation images, and test images\ntrain_dir = os.path.join(base_dir, 'train')\nos.mkdir(train_dir)\ntest_dir = os.path.join(base_dir, 'test')\nos.mkdir(test_dir)\n\n# Creating the directory to house the training images\ntrain_erika_dir = os.path.join(train_dir, 'erika')\nos.mkdir(train_erika_dir)\ntrain_asuka_dir = os.path.join(train_dir, 'asuka')\nos.mkdir(train_asuka_dir)\ntrain_mai_dir = os.path.join(train_dir, 'mai')\nos.mkdir(train_mai_dir)\ntrain_nanase_dir = os.path.join(train_dir, 'nanase')\nos.mkdir(train_nanase_dir)\ntrain_nanami_dir = os.path.join(train_dir, 'nanami')\nos.mkdir(train_nanami_dir)\n\n# The directory to house the testing images\ntest_erika_dir = os.path.join(test_dir, 'erika')\nos.mkdir(test_erika_dir)\ntest_asuka_dir = os.path.join(test_dir, 'asuka')\nos.mkdir(test_asuka_dir)\ntest_mai_dir = os.path.join(test_dir, 'mai')\nos.mkdir(test_mai_dir)\ntest_nanase_dir = os.path.join(test_dir, 'nanase')\nos.mkdir(test_nanase_dir)\ntest_nanami_dir = os.path.join(test_dir, 'nanami')\nos.mkdir(test_nanami_dir)\n\nfnames = glob.glob(\"./Aligned/生田絵梨花/*\") \ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_erika_dir, 'erika.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_erika_dir, 'erika.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/齋藤飛鳥/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_asuka_dir, 'asuka.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_asuka_dir, 'asuka.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/白石麻衣/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_mai_dir, 'mai.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_mai_dir, 'mai.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/橋本奈々未/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_nanase_dir, 'nanami.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_nanase_dir, 'nanami.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n\nfnames = glob.glob(\"./Aligned/西野七瀬/*\")\ntrain_len = math.floor(len(fnames) * 0.7)\nfor i in range(len(fnames)):\n if i < train_len:\n src = fnames[i]\n dst = os.path.join(train_nanami_dir, 'nanase.{}.jpg'.format(i))\n shutil.copyfile(src, dst)\n else: \n src = fnames[i]\n dst = os.path.join(test_nanami_dir, 'nanase.{}.jpg'.format(i))\n shutil.copyfile(src, dst)"
},
{
"alpha_fraction": 0.6750285029411316,
"alphanum_fraction": 0.6830102801322937,
"avg_line_length": 34.099998474121094,
"blob_id": "4f97d7bdd837a0bf186343e50a5c37d3d8b270c3",
"content_id": "4548e1e1690e12720d8eaa6a9da7fa6f51e845bf",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1754,
"license_type": "no_license",
"max_line_length": 123,
"num_lines": 50,
"path": "/FaceAligner.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import dlib\nimport cv2\nimport os\nimport glob\n\nprint('Using dlib version: {}'.format(dlib.__version__))\nprint('Using cv2 version: {}'.format(cv2.__version__))\n\ndef FaceAligner(face_file_path, output_path, predictor_path='./shape_predictor_5_face_landmarks.dat'):\n # Load all the models we need: a detector to find the faces, a shape predictor\n # to find face landmarks so we can precisely localize the face\n detector = dlib.get_frontal_face_detector()\n sp = dlib.shape_predictor(predictor_path)\n \n img=cv2.imread(face_file_path)\n if img is None:\n return\n \n b,g,r = cv2.split(img)\n img = cv2.merge([r,g,b])\n \n # Ask the detector to find the bounding boxes of each face. The 1 in the\n # second argument indicates that we should upsample the image 1 time. This\n # will make everything bigger and allow us to detect more faces.\n dets = detector(img, 1)\n num_faces = len(dets)\n\n if num_faces == 0:\n return\n \n # Find the 5 face landmarks we need to do the alignment.\n faces = dlib.full_object_detections()\n for detection in dets:\n faces.append(sp(img, detection))\n\n # Save Image\n image = dlib.get_face_chip(img, faces[0])\n dlib.save_image(image, output_path)\n\nroot=\"./Images/*\" # The directory where the downloaded images are housed\ndst_dir=\"./Aligned\" # The directory to place the cropped and resized images\nos.mkdir(dst_dir)\nsrc_dir=glob.glob(root)\n\n# Will crop and resize the downloaded images using OpenCV and place the results in the destination directory declared above\nfor path in src_dir:\n dst = os.path.join(dst_dir, path.split('/')[2])\n os.mkdir(dst)\n for img in os.listdir(path):\n FaceAligner(os.path.join(path, img), os.path.join(dst, img))"
},
{
"alpha_fraction": 0.6238431930541992,
"alphanum_fraction": 0.63364177942276,
"avg_line_length": 37.29166793823242,
"blob_id": "023f50cd5258c0bc1339dae6c3208f76b2fb6fa7",
"content_id": "9b23855f2d17c127414af6483e73c31f1965f94b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1881,
"license_type": "no_license",
"max_line_length": 243,
"num_lines": 48,
"path": "/GetImage.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import httplib2\nimport json\nimport os \nimport urllib.request\nimport glob\nimport shutil\nfrom urllib.parse import quote\n\n# Basic Setup\nAPI_KEY='YOUR_API_KEY'\nCUSTOM_SEARCH_ENGINE='YOUR_CUSTOM_SEARCH_ENGINE'\nKEYWORDS=[\"生田絵梨花\",\"齋藤飛鳥\",\"白石麻衣\",\"西野七瀬\",\"橋本奈々未\"]\nNUM_OF_IMAGES=100 # Will Error if more than 100 \n\n# Function: Obtain Image Url via Google Custom Search API\ndef getImageUrl(search_item: list, total_num: int):\n img_list = []\n i = 0\n while i < total_num:\n query_img = \"https://www.googleapis.com/customsearch/v1?key=\" + API_KEY + \"&cx=\" + CUSTOM_SEARCH_ENGINE + \"&num=\" + str(10 if(total_num-i)>10 else (total_num-i)) + \"&start=\" + str(i+1) + \"&q=\" + quote(search_item) + \"&searchType=image\"\n res = urllib.request.urlopen(query_img)\n data = json.loads(res.read().decode('utf-8'))\n for j in range(len(data['items'])):\n img_list.append(data['items'][j]['link'])\n i=i+10\n return img_list\n\n# Function: Obtain Images \ndef getImage(search_item: list, img_list: list, base_dir_name='Images'):\n os.mkdir(base_dir_name) # create base dir\n item_dir = os.path.join(base_dir_name, search_item)\n os.mkdir(item_dir) # directory to house the images\n http = httplib2.Http(\".cache\") # Initiate http request object instance \n for i in range(len(img_list)):\n try:\n response, content = http.request(img_list[i])\n filename = os.path.join(item_dir, search_item + '.' + str(i) + '.jpg')\n with open(filename, 'wb') as f:\n f.write(content)\n except:\n print('Error: failed to download image')\n continue\n\n# Obtain Images\nfor j in range(len(KEYWORDS)):\n print('=== downloading images for {} ==='.format(KEYWORDS[j]))\n img_list=getImageUrl(KEYWORDS[j],NUM_OF_IMAGES)\n getImage(KEYWORDS[j], img_list)"
},
{
"alpha_fraction": 0.6163342595100403,
"alphanum_fraction": 0.6413422226905823,
"avg_line_length": 30.600000381469727,
"blob_id": "e90f41495d1e4d6c9a96a0cf331a542f31fd0fc1",
"content_id": "640b29957992fc0615f7e85b5329a7893b7781f7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3159,
"license_type": "no_license",
"max_line_length": 90,
"num_lines": 100,
"path": "/BasicCNN.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import os\nimport cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nname = [\"asuka\",\"mai\",\"erika\",\"nanami\",\"nanase\"]\n\n# Labeling the training data\ntrain_dir=\"./Input_Data/train/\"\nX_train = []\nY_train = []\nfor i in range(len(name)):\n img_file_name_list=os.listdir(train_dir+name[i])\n print('Found {} training images for {}'.format(len(img_file_name_list), name[i]))\n for j in range(0, len(img_file_name_list)-1):\n n=os.path.join(train_dir+name[i]+\"/\", img_file_name_list[j])\n img = cv2.imread(n)\n b,g,r = cv2.split(img)\n img = cv2.merge([r,g,b])\n # refactoring the image\n img = np.divide(img, 255)\n X_train.append(img)\n Y_train.append(i)\n\n# Labeling the validation data\nvalidation_dir=\"./input_data/test/\"\nX_test = []\nY_test = []\nfor i in range(len(name)):\n img_file_name_list=os.listdir(validation_dir+name[i])\n print('Found {} testing images for {}'.format(len(img_file_name_list), name[i]))\n for j in range(0, len(img_file_name_list)-1):\n n=os.path.join(validation_dir+name[i]+\"/\", img_file_name_list[j])\n img=cv2.imread(n)\n b,g,r = cv2.split(img)\n img = cv2.merge([r,g,b])\n # Refactoring the images\n img = np.divide(img, 255)\n X_test.append(img)\n Y_test.append(i)\nX_train=np.array(X_train)\nX_test=np.array(X_test)\n\nfrom keras.utils.np_utils import to_categorical\ny_train = to_categorical(Y_train)\ny_test = to_categorical(Y_test)\n\nfrom keras import layers, optimizers, models\n\nmodel = models.Sequential()\nmodel.add(layers.Conv2D(32, (2, 2), input_shape=(64,64,3), strides=(1,1), padding='same'))\nmodel.add(layers.MaxPooling2D((2,2)))\nmodel.add(layers.Conv2D(32, (2, 2), strides=(1,1), padding='same'))\nmodel.add(layers.MaxPooling2D((2,2)))\nmodel.add(layers.Conv2D(32, (2, 2), strides=(1,1), padding='same'))\nmodel.add(layers.MaxPooling2D((2,2)))\nmodel.add(layers.Conv2D(128, (2, 2), strides=(1,1), padding='same'))\nmodel.add(layers.MaxPooling2D((2,2)))\nmodel.add(layers.Flatten())\nmodel.add(layers.Dense(256, activation='sigmoid'))\nmodel.add(layers.Dense(128, activation='sigmoid'))\nmodel.add(layers.Dense(5, activation='softmax'))\n\nmodel.summary()\n\nmodel.compile(loss='categorical_crossentropy',\n optimizer='sgd',\n metrics=['accuracy'])\n\nhistory = model.fit(X_train, y_train, \n batch_size=32,\n epochs=100,\n validation_data=(X_test, y_test),\n verbose=1\n )\n\nmodel.save('BasicCNN.h5')\n\nacc = history.history['acc']\nval_acc = history.history['val_acc']\nloss = history.history['loss']\nval_loss = history.history['val_loss']\n\nepochs = range(1, len(acc) + 1)\n\n# Plot the accuracy\nplt.plot(epochs, acc, 'bo', label='Training acc')\nplt.plot(epochs, val_acc, 'b', label='Validation acc')\nplt.title('Training and Validation Accuracy')\nplt.legend()\nplt.savefig('BasicCNN_acc.png')\n\nplt.figure()\n\n# Plot the loss value\nplt.plot(epochs, loss, 'bo', label='Training loss')\nplt.plot(epochs, val_loss, 'b', label='Validation loss')\nplt.title('Training and Validation Loss')\nplt.legend()\nplt.savefig('BasicCNN_loss.png')"
},
{
"alpha_fraction": 0.6346760988235474,
"alphanum_fraction": 0.6439576745033264,
"avg_line_length": 30.319766998291016,
"blob_id": "3abee25691beab3446373d2dccc91f9b6cdd7831",
"content_id": "fcbe610b63174ef4fb156df37d759aed8daa2228",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5387,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 172,
"path": "/VGGFace.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "print(\"=== Importing Libraries ===\")\nimport os, argparse, glob, math, shutil, cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom keras.utils.np_utils import to_categorical\nfrom keras.engine import Model\nfrom keras.layers import Flatten, Dense, Input\nfrom keras_vggface.vggface import VGGFace\nfrom keras import optimizers\n\nparser = argparse.ArgumentParser(description='Train using VGGFace network with specified data')\nparser.add_argument('-i', dest='data', type=str, help='the path to the data', required=True)\nargs = parser.parse_args()\nprint('Will train network with {}'.format(args.data))\n\nprint('=== Preprocessing Data ===')\n\nNAME = [\"asuka\",\"mai\",\"erika\",\"nanami\",\"nanase\"]\nTRAIN_DIR = os.path.join(args.data, 'train')\nVALIDATION_DIR = os.path.join(args.data, 'test')\n\n# Creating tensors and labeling training and validation data\nX_train = []\nY_train = []\nfor i in range(len(NAME)):\n img_file_name_list=os.listdir(os.path.join(TRAIN_DIR, NAME[i]))\n print('Found {} training images for {}'.format(len(img_file_name_list), NAME[i]))\n for j in range(0, len(img_file_name_list)-1):\n n=os.path.join(TRAIN_DIR, NAME[i], img_file_name_list[j])\n img = cv2.imread(n)\n b,g,r = cv2.split(img)\n img = cv2.merge([r,g,b])\n # refactoring the image\n img = np.divide(img, 255)\n X_train.append(img)\n Y_train.append(i)\n\n\nX_test = []\nY_test = []\nfor i in range(len(NAME)):\n img_file_name_list=os.listdir(os.path.join(VALIDATION_DIR,NAME[i]))\n print('Found {} testing images for {}'.format(len(img_file_name_list), NAME[i]))\n for j in range(0, len(img_file_name_list)-1):\n n=os.path.join(VALIDATION_DIR, NAME[i], img_file_name_list[j])\n img=cv2.imread(n)\n b,g,r = cv2.split(img)\n img = cv2.merge([r,g,b])\n # Refactoring the images\n img = np.divide(img, 255)\n X_test.append(img)\n Y_test.append(i)\nX_train=np.array(X_train)\nX_test=np.array(X_test)\n\nprint(X_train.shape, X_test.shape)\n\ny_train = to_categorical(Y_train)\ny_test = to_categorical(Y_test)\n\nprint('=== Importing VGGFace Net ===')\nconv_base = VGGFace(include_top=False, input_shape=(150, 150, 3))\n\nprint('=== Creating Model ===')\n# custom parameters\nNB_CLASS = 5\nHIDDEN_DIM = 512\n\nlast_layer = conv_base.get_layer('pool5').output\nx = Flatten(name='flatten')(last_layer)\nx = Dense(HIDDEN_DIM, activation='relu', name='fc6')(x)\nx = Dense(HIDDEN_DIM, activation='relu', name='fc7')(x)\nout = Dense(NB_CLASS, activation='softmax', name='fc8')(x)\nmodel = Model(conv_base.input, out)\n\nmodel.summary()\n\nprint(\"=== Freezing the Convolutional Base ===\")\n# Freezing the Network\nprint('This is the number of trainable weights '\n 'before freezing the conv base:', len(model.trainable_weights))\n \nconv_base.trainable = False\nfor layer in conv_base.layers:\n layer.trainable = False\n\nprint('This is the number of trainable weights '\n 'after freezing the conv base:', len(model.trainable_weights))\n\nmodel.compile(loss='categorical_crossentropy',\n optimizer='sgd',\n metrics=['accuracy'])\n\nprint('=== Training the Model ===')\n# Using the batch generator to fit the model to the data\nhistory = model.fit(X_train, y_train, \n batch_size=29,\n epochs=50,\n validation_data=(X_test, y_test),\n verbose=1\n )\n \nacc = history.history['acc']\nval_acc = history.history['val_acc']\nloss = history.history['loss']\nval_loss = history.history['val_loss']\n\nepochs = range(1, len(acc) + 1)\n\nprint('=== Plotting Results ===')\n# Plot the accuracy\nplt.plot(epochs, acc, 'bo', label='Training acc')\nplt.plot(epochs, val_acc, 'b', label='Validation acc')\nplt.title('Training and Validation Accuracy')\nplt.legend()\nplt.savefig('./pret_acc.png')\n\nplt.figure()\n\n# Plot the loss value\nplt.plot(epochs, loss, 'bo', label='Training loss')\nplt.plot(epochs, val_loss, 'b', label='Validation loss')\nplt.title('Training and Validation Loss')\nplt.legend()\nplt.savefig('./pret_loss.png')\n\nprint('=== Unfreezing Network ===')\nconv_base.trainable = True\nset_trainable = False\nfor layer in conv_base.layers:\n if layer.name == 'conv4_1':\n set_trainable = True\n if set_trainable:\n layer.trainable = True\n else:\n layer.trainable = False\n\nprint('=== Fine Tuning ===')\nmodel.compile(loss='categorical_crossentropy', optimizer=optimizers.RMSprop(lr=1e-5), metrics=['acc'])\n\nhistory = model.fit(X_train, y_train, \n batch_size=29,\n epochs=50,\n validation_data=(X_test, y_test),\n verbose=1\n )\n\nprint('=== Plotting Results ===')\nacc = history.history['acc']\nval_acc = history.history['val_acc']\nloss = history.history['loss']\nval_loss = history.history['val_loss']\n\nepochs = range(1, len(acc) + 1)\n\n# Plot the accuracy\nplt.figure()\n\nplt.plot(epochs, acc, 'bo', label='Training acc')\nplt.plot(epochs, val_acc, 'b', label='Validation acc')\nplt.title('Training and Validation Accuracy')\nplt.legend()\nplt.savefig('./pret_acc_ft.png')\n\nplt.figure()\n\n# Plot the loss value\nplt.plot(epochs, loss, 'bo', label='Training loss')\nplt.plot(epochs, val_loss, 'b', label='Validation loss')\nplt.title('Training and Validation Loss')\nplt.legend()\nplt.savefig('./pret_loss_ft.png')\n"
},
{
"alpha_fraction": 0.6221453547477722,
"alphanum_fraction": 0.6429065465927124,
"avg_line_length": 42.818180084228516,
"blob_id": "f1405d24d6e305a482b99d85d61965dd11245b2f",
"content_id": "57ac1521a57f0a9c50b67c1aa197ee0eb55b17eb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1445,
"license_type": "no_license",
"max_line_length": 139,
"num_lines": 33,
"path": "/Cropper.py",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "import os\nimport glob\nimport cv2\n\n### Recognize, crop, and resize with OpenCV\nroot=\"./Images/*\" # The directory where the downloaded images are housed\ndst_dir=\"./Cropped\" # The directory to place the cropped and resized images\nos.mkdir(dst_dir)\nsrc_dir=glob.glob(root)\n\n# Will crop and resize the downloaded images using OpenCV and place the results in the destination directory declared above\nfor path in src_dir:\n dst = os.path.join(dst_dir, path.split('/')[2])\n os.mkdir(dst)\n for img in os.listdir(path):\n image = cv2.imread(os.path.join(path, img))\n if image is None:\n continue\n image_grey=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # Convert image to greyscale\n cascade=cv2.CascadeClassifier(\"/usr/local/opt/opencv/share/OpenCV/haarcascades/haarcascade_frontalface_alt.xml\") #Import Classifier\n face_list=face_list=cascade.detectMultiScale(image_grey, scaleFactor=1.1, minNeighbors=2,minSize=(64,64)) # Face recognition\n # If faces were detected\n if len(face_list) > 0: \n for rect in face_list:\n x,y,width,height=rect\n image=image[rect[1]:rect[1]+rect[3],rect[0]:rect[0]+rect[2]]\n if image.shape[0] < 64: \n continue\n image = cv2.resize(image,(64,64))\n fileName=os.path.join(dst, img)\n cv2.imwrite(fileName, image) # Save image\n else:\n continue"
},
{
"alpha_fraction": 0.738095223903656,
"alphanum_fraction": 0.7976190447807312,
"avg_line_length": 41,
"blob_id": "a9fc2ca98ac2a76856f4d15d67d57e1816577eac",
"content_id": "19c9e93e92df0990348f84fe85b8ee9f77aa0fc2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 84,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 2,
"path": "/README.md",
"repo_name": "ShozenD/CNN-Nogizaka46",
"src_encoding": "UTF-8",
"text": "# CNN-Nogizaka46\nA project using CNN to identify the faces of 5 Nogizaka 46 members\n"
}
] | 8
|
SunnyOneSoTrue/PythonQuiz
|
https://github.com/SunnyOneSoTrue/PythonQuiz
|
77c7123abb40528f0c66268c6033cf82bd59a29f
|
87fee5c041ea84af98728e909d70bc24f2fcaa4d
|
539f9905b6b0937d54e0a0a9df3e1d7a676de9d3
|
refs/heads/main
| 2023-05-30T23:52:40.291682
| 2021-06-24T22:06:51
| 2021-06-24T22:06:51
| 380,060,620
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6259542107582092,
"alphanum_fraction": 0.628216028213501,
"avg_line_length": 29.026315689086914,
"blob_id": "79a6e72d347003a35cc970ec45ec8120df6d722a",
"content_id": "22c4e0a4bfc6165be32df4cfa1a7ba977a66fee7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4701,
"license_type": "no_license",
"max_line_length": 114,
"num_lines": 114,
"path": "/main.py",
"repo_name": "SunnyOneSoTrue/PythonQuiz",
"src_encoding": "UTF-8",
"text": "from flask import Flask, redirect, url_for, render_template, request, session, flash\r\nfrom flask_sqlalchemy import SQLAlchemy\r\n\r\napp = Flask(__name__) # ფლასკ კლასის ობიექტი(აპლიკაცია). _name_ არის წინასწარ შექმნილი ცვლადი,\r\n# რომლის მნიშვნელობაა გამშვები ფაილის დასახელება.\r\n\r\napp.config['SECRET_KEY'] = 'Python'\r\napp.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///books.sqlite'\r\n# შემოვიღოთ sqlalchemy კლასის ობიექტი, რომლითაც შემდეგ ვიმუშავებთ ბაზასთან\r\ndb = SQLAlchemy(app)\r\n\r\n\r\n# კლასის შექმნა bazis\r\nclass Animes(db.Model):\r\n id = db.Column(db.Integer, primary_key=True)\r\n title = db.Column(db.String(40), nullable=False)\r\n rating = db.Column(db.Float, nullable=False)\r\n ranking = db.Column(db.Integer, nullable=False)\r\n\r\n def __str__(self):\r\n return f\"\"\"Anime title:{self.title}; Rating: {self.rating}; Ranking: {self.ranking}\"\"\"\r\n\r\n\r\n# b1 = Books.query.first() #erti selecti\r\n# print(b1)\r\n\r\n\r\n# yvelas select\r\n\r\n# all_books = Books.query.all()\r\n# print(all_books)\r\n# for each in all_books:\r\n# print(each)\r\n\r\n# gafiltruli select\r\n# all_books = Animes.query.filter_by(author='აკაკი წერეთელი').all()\r\n# print(all_books)\r\n# for each in all_books:\r\n# print(each)\r\n\r\n\r\n# db.create_all() # ეს ბრძანება გამოიყენება მაშინ, როცა ბაზა არ გვაქვს ჯერ. და შექმნის ამ ბაზას კლასის სტრუქტურით.\r\n# # ხოლო თუ გვაქვს, არ შეიქმნება.\r\n\r\n# insertebi\r\n# b1 = Books(title='ლექსები', author='ილია', price=15)\r\n# db.session.add(b1)\r\n# db.session.commit()\r\n\r\n# HOME PAGE\r\n@app.route('/')\r\ndef home():\r\n return render_template('index.html') # მთავარი გვერდის html-ის დარენდერებული ვერსიის დაბრუნება\r\n\r\n\r\n\r\n#davamato ro paroli rtuli unda iyosssss\r\n@app.route('/login', methods=['POST', 'GET'])\r\ndef login():\r\n if request.method == 'POST':\r\n username = request.form['username']\r\n password = request.form['password']\r\n if username == \"\" or password == \"\":\r\n flash(\"შეავსეთ ყველა ველი\")\r\n else:\r\n session['username'] = username\r\n return redirect(url_for('user'))\r\n # url for ფუნქცია ააგებს იუზერზე იუერელს და მოახდენს რედაირექთს მასზე.\r\n else:\r\n return render_template('login.html')\r\n\r\n return render_template('login.html')\r\n\r\n\r\n@app.route('/user')\r\ndef user():\r\n animes = ['Fullmetal Alchemist: Brotherhood', 'Death Note', 'Attack On Titan', 'Hunter X Hunter',\r\n 'Samurai Champloo', 'Naruto', 'Kuroko\\'s Basketball']\r\n return render_template('user.html', animes=animes) # იუზერის html-ის დარენდერება.\r\n\r\n\r\n# სახელისა და ასაკის რუთი\r\n@app.route('/<name>/<age>')\r\ndef userage(name, age):\r\n return f'Hello {name}, your age is {age}'\r\n\r\n\r\n@app.route('/logout')\r\ndef logout():\r\n session.pop('username', None)\r\n return render_template('index.html')\r\n\r\n\r\n@app.route('/books', methods=['GET', 'POST'])\r\ndef books():\r\n if request.method == 'POST':\r\n rk = request.form['ranking']\r\n t = request.form['title']\r\n r = request.form['rating']\r\n if rk == \"\" or t == \"\" or r == \"\":\r\n flash(\"შეავსეთ ყველა ველი\")\r\n elif not r.isnumeric():\r\n flash(\"ფასი უნდა იყოს რიცხვითი მონაცემი\")\r\n else:\r\n b = Animes(ranking=rk, title=t, rating=float(r))\r\n db.session.add(b)\r\n db.session.commit()\r\n flash('მონაცემები დამატებულია')\r\n return render_template('animes.html')\r\n\r\n\r\n# აპლიკაციის გაშვება run მეთოდით მოხდება მხოლოდ მაშინ, როცა ეს ფაილი იქნება მთავარი გამშვები ფაილი\r\nif __name__ == \"__main__\":\r\n app.run(debug=True)\r\n"
}
] | 1
|
kuldeepkhatke/django_multi_db
|
https://github.com/kuldeepkhatke/django_multi_db
|
67131194f18eafd3004e1c131411071fe6b464cf
|
b1a7f06502341a4fd2ce884b9ca0eaf9ca976595
|
ac68dd1c8ef57597fa857540bca3bb575f073453
|
refs/heads/master
| 2023-05-21T18:50:22.179036
| 2020-06-01T10:04:39
| 2020-06-01T10:04:39
| 267,903,998
| 0
| 0
| null | 2020-05-29T16:25:54
| 2020-06-01T10:05:47
| 2021-06-10T22:58:57
|
Python
|
[
{
"alpha_fraction": 0.5,
"alphanum_fraction": 0.7083333134651184,
"avg_line_length": 15,
"blob_id": "f60debc76acf0e81e4cbeeb984b7ad126c9a7221",
"content_id": "3cafebe08da73157d07350c27306218360ce13bd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 48,
"license_type": "no_license",
"max_line_length": 18,
"num_lines": 3,
"path": "/requirements.txt",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "Django==1.10\nmysqlclient==1.4.6\npsycopg2==2.8.5\n"
},
{
"alpha_fraction": 0.6593886613845825,
"alphanum_fraction": 0.6659388542175293,
"avg_line_length": 23.105262756347656,
"blob_id": "d04dc36ae6c397082b64c4c8149fe70140d25b23",
"content_id": "d8872e71d70cc75b7bbd8e6cb271e5c5fe6cda4d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 458,
"license_type": "no_license",
"max_line_length": 60,
"num_lines": 19,
"path": "/dashboard/models.py",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "from django.db import models\nfrom django.contrib.auth.models import User\n\nclass UserProfile(models.Model):\n user = models.ForeignKey(User, on_delete=models.CASCADE)\n db = models.TextField()\n\n def __str__(self):\n return self.user.username\n\nclass Product(models.Model):\n name = models.CharField(max_length=100)\n user = models.IntegerField()\n\n def __str__(self):\n return self.name\n \n class Meta:\n db_table=\"product\"\n"
},
{
"alpha_fraction": 0.6872037649154663,
"alphanum_fraction": 0.6872037649154663,
"avg_line_length": 37.3636360168457,
"blob_id": "9f76b201030a7b78e3b41a7134fb1979a5183a16",
"content_id": "499d50bd5de093534a42abafedcfb476ffcb84cc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 422,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 11,
"path": "/dashboard/urls.py",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "from django.conf.urls import url, include\nfrom django.contrib import admin\nfrom . import views\nfrom django.contrib.auth import views as auth_views\n\nurlpatterns = [\n url(r'^login/$', auth_views.login, name='login'),\n url(r'^logout/$', auth_views.logout, name='logout'),\n url(r'^accounts/profile/$', views.dashboard, name=\"dashboard\"),\n url(r'^delete/user/(?P<pk>\\d+)/$', views.delete_user, name=\"dashboard\"),\n]\n"
},
{
"alpha_fraction": 0.6301369667053223,
"alphanum_fraction": 0.6438356041908264,
"avg_line_length": 31.758621215820312,
"blob_id": "87f6e9397129120aeeb88b04146088aaa441b916",
"content_id": "1269ac3c3dc2ebd4dc7f43fb263a54b37453b12e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 949,
"license_type": "no_license",
"max_line_length": 74,
"num_lines": 29,
"path": "/dashboard/forms.py",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "from django import forms\nfrom django.contrib.auth.forms import UserCreationForm\nfrom django.contrib.auth.models import User\nfrom .models import UserProfile, Product\n\n\nDB_CHOICES =( \n (\"database1\", \"database1\"), \n (\"database2\", \"database2\"), \n (\"database3\", \"database3\"), \n (\"database4\", \"database4\"), \n (\"database5\", \"database5\"), \n) \n\nclass ProductForm(forms.Form):\n def __init__(self, userprofile, *args, **kwargs):\n super(ProductForm, self).__init__(*args, **kwargs)\n self.fields['db'] = forms.ChoiceField(\n choices=[(db,db) for db in userprofile.db.split(',')]\n )\n name = forms.CharField(label='Product name', max_length=100)\n # db = forms.ChoiceField(label='Database')\n\nclass CreateUserForm(UserCreationForm):\n db = forms.MultipleChoiceField(label='Database', choices = DB_CHOICES)\n\n class Meta:\n model = User\n fields = ('username', 'db', 'password1', 'password2', )"
},
{
"alpha_fraction": 0.5775281190872192,
"alphanum_fraction": 0.5775281190872192,
"avg_line_length": 44.159420013427734,
"blob_id": "27de844be2e638b837e4ea08d561462ee529759a",
"content_id": "9a4e93fdc92841782a50de0b7192cc6c55742b63",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3115,
"license_type": "no_license",
"max_line_length": 129,
"num_lines": 69,
"path": "/dashboard/views.py",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "from django.shortcuts import render, redirect\nfrom .forms import ProductForm, CreateUserForm\nfrom .models import Product, UserProfile\nfrom django.conf import settings\nfrom django.contrib.auth.models import User\n\ndef dashboard(request):\n if request.user.is_superuser:\n if request.method == 'POST':\n form = CreateUserForm(request.POST)\n if form.is_valid():\n user = User()\n user.username = form.cleaned_data['username']\n user.set_password(form.cleaned_data['password1'])\n user.save()\n userprofile = UserProfile()\n userprofile.user = user\n userprofile.db = ','.join(form.cleaned_data['db'])\n userprofile.save()\n\n data = []\n users = User.objects.all().exclude(id=request.user.id)\n for user in users:\n obj= {\"user\":user,\"database\":[]}\n for db in settings.DATABASES.keys():\n obj[\"database\"].append({\"name\":db, \"products\":Product.objects.using(db).filter(user=user.id)})\n data.append(obj)\n form = CreateUserForm()\n\n \n return render(request, 'admin/adminpanel.html', {'form': form,'data':data, 'users':users})\n else:\n data = []\n users = User.objects.all().exclude(id=request.user.id)\n for user in users:\n obj= {\"user\":user,\"database\":[]}\n for db in settings.DATABASES.keys():\n obj[\"database\"].append({\"name\":db, \"products\":Product.objects.using(db).filter(user=user.id)})\n data.append(obj)\n form = CreateUserForm()\n return render(request, 'admin/adminpanel.html', {'form': form,'data':data})\n\n if request.method == 'POST':\n userprofile = UserProfile.objects.get(user=request.user)\n form = ProductForm(userprofile,request.POST)\n \n if form.is_valid():\n Product.objects.using(str(form.cleaned_data['db'])).create(name=str(form.cleaned_data['name']), user=request.user.id)\n data = []\n for db in settings.DATABASES.keys():\n data.append({\"db\":db, \"products\":Product.objects.using(db).filter(user=request.user.id)})\n userprofile = UserProfile.objects.get(user=request.user)\n form = ProductForm(userprofile) \n return render(request, 'dashboard/dashboard.html', {'form': form,'data':data})\n else:\n data = []\n for db in settings.DATABASES.keys():\n data.append({\"db\":db, \"products\":Product.objects.using(db).filter(user=request.user.id)})\n \n userprofile = UserProfile.objects.get(user=request.user)\n form = ProductForm(userprofile) \n\n return render(request, 'dashboard/dashboard.html', {'form': form,'data':data})\n\ndef delete_user(request,pk):\n User.objects.get(id=pk).delete()\n for db in settings.DATABASES.keys():\n Product.objects.using(db).filter(user=pk).delete()\n return redirect('/accounts/profile/')"
},
{
"alpha_fraction": 0.7835433483123779,
"alphanum_fraction": 0.797627866268158,
"avg_line_length": 31.878047943115234,
"blob_id": "79fadff57096345aede6ad65740b59dc9471b559",
"content_id": "1acd717ef906700e1dad07a4e3c4fac6ed7afb3c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1349,
"license_type": "no_license",
"max_line_length": 89,
"num_lines": 41,
"path": "/README.md",
"repo_name": "kuldeepkhatke/django_multi_db",
"src_encoding": "UTF-8",
"text": "# django_multi_db\nDjango multi database application.\n\n\n# Create databases\n\n# Create postgres database\ncreate database database1;\ncreate database database2;\n\nGRANT ALL PRIVILEGES ON DATABASE \"database1\" to postgres_user;\nGRANT ALL PRIVILEGES ON DATABASE \"database2\" to postgres_user;\n\n# Create mysql database\ncreate database database3;\ncreate database database4;\ncreate database database5;\n\nGRANT ALL PRIVILEGES ON DATABASE \"database3\" to mysql_user;\nGRANT ALL PRIVILEGES ON DATABASE \"database4\" to mysql_user;\nGRANT ALL PRIVILEGES ON DATABASE \"database5\" to mysql_user;\n\n# Create an virtualenv & install all requirements present in requirements.txt\npip install -r requirements.txt \n\n# Update database access username & password in settings.py file\n\n# Run following commands\npython manage.py migrate\npython manage.py migrate dashboard --database='database1'\npython manage.py migrate dashboard --database='database2'\npython manage.py migrate dashboard --database='database3'\npython manage.py migrate dashboard --database='database4'\npython manage.py migrate dashboard --database='database5'\n\n# Create superuser & set username & password for ex. username=admin & password=admin@123\npython manage.py createsuperuser\n\n# Now do runserver \n# For Admin & User Login Use: localhost:8000/login\n# Here if you login you will be redirected to /account/profile \n"
}
] | 6
|
JuntaoXu/Tim-Hortons-Ordering-System
|
https://github.com/JuntaoXu/Tim-Hortons-Ordering-System
|
ae31ff49e4d31fdb8c36ef5af69a6d1e0e5bfde0
|
552163d1d8d0dc20c491e0a435795c9270ed075b
|
8c516c2f9279125daa29b529f45a762b680a639e
|
refs/heads/master
| 2020-04-28T02:01:55.805936
| 2019-03-10T21:20:06
| 2019-03-10T21:20:06
| 174,882,393
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8028455376625061,
"alphanum_fraction": 0.8028455376625061,
"avg_line_length": 163,
"blob_id": "dc15f9110b49839cd2b53729dbea0c5bbddf399f",
"content_id": "2e37067fd502e6a1db4a46a4241ca38ee255bdda",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 492,
"license_type": "no_license",
"max_line_length": 256,
"num_lines": 3,
"path": "/readme.md",
"repo_name": "JuntaoXu/Tim-Hortons-Ordering-System",
"src_encoding": "UTF-8",
"text": "[School Assignment] This Program simulates the Tim Hortons Ordering System.\nIt reads order from the website, decode the information and organize the order into a list format. (The list conatins instruction, id, order contents, price) \nThen the program runs accoridng to the isntructions given. th program has functions as followed: adding a order, canceling an order, calculating the sum value of orders, modify an order, check the next order, sleep the program for a certain period of time.\n"
},
{
"alpha_fraction": 0.634743869304657,
"alphanum_fraction": 0.639643669128418,
"avg_line_length": 22.144329071044922,
"blob_id": "961c97bdf51a7f15d9216f2f5aecc660143e1f11",
"content_id": "bc62c2d054b82fab09b5692891b4fc9d754a96f9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2245,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 97,
"path": "/queue_operations.py",
"repo_name": "JuntaoXu/Tim-Hortons-Ordering-System",
"src_encoding": "UTF-8",
"text": "# queue Module Juntao Xu Student: 20132432\n\n'''\nThis is the module that implements the functionality of a queue\n- add to the queue\n- delete from the queue\n- provide the size of the queue\n- indicate if the queue is empty\n- what's the next item in the queue\n'''\n\n# NO PRINT STATEMENTS IN THIS MODULE\n\n\ndef enqueue(queue, queue_append):\n '''\n add to the queue\n input: queue\n output: a new queue with an additional element\n '''\n queue.append(queue_append)\n return queue\n\n\ndef dequeue(queue, target_queue):\n '''\n delete from the queue\n input: queue\n output: a new queue with one one less element\n '''\n queue.pop(queue.index(target_queue))\n return queue\n\n\ndef size(queue):\n '''\n check the size of the queue\n input: queue\n output: the size opf the queue\n '''\n queue_size = len(queue)\n return queue_size\n\n\ndef is_empty(queue_size):\n '''\n check if the queue is empty\n input: queue\n outputL: True or False (whether the queue is empty)\n '''\n if len(queue_size) == 0:\n return True\n return False\n\n\ndef look(queue):\n '''\n check the next element in the queue\n input: queue\n output: the second element in the queue\n '''\n return queue[1]\n\n\nif __name__ == '__main__':\n print('The following are the testing materials')\n queue = [['a'],['b']]\n queue_append = ['c']\n target_queue = ['a']\n empty_list = []\n\n print()\n print('The following is the testing code part')\n\n # enqueue function\n print(enqueue(queue, queue_append))\n print('should return list containing abc')\n\n # dequeue function\n queue = [['a'], ['b']] # define the variable again since it has been changed in the previous function\n print(dequeue(queue, target_queue))\n print('should return a list of list containing b')\n\n # size function\n queue = [['a'], ['b']] # define the variable again since it has been changed in the previous function\n print(size(queue))\n print('should return 2')\n\n # is_empty function\n print(is_empty(queue))\n print('should return False')\n print(is_empty(empty_list))\n print('should return True')\n\n # look function\n print(look(queue, target_queue))\n print('should return a list containing b')\n"
},
{
"alpha_fraction": 0.6684695482254028,
"alphanum_fraction": 0.68718022108078,
"avg_line_length": 36.184783935546875,
"blob_id": "c01b420ab85c72ea96a224193611a4b2bbc06881",
"content_id": "b1bb6df7dd0f20497a7026c40c092383952e7497",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6841,
"license_type": "no_license",
"max_line_length": 156,
"num_lines": 184,
"path": "/command.py",
"repo_name": "JuntaoXu/Tim-Hortons-Ordering-System",
"src_encoding": "UTF-8",
"text": "# command Module Juntao Xu Student: 20132432\n\n'''\nthis module calls the functions in the queue module\nother functionality such as modifying orders and canceling orders will go into this function\neach data in the queue should store the order ID, a timestamp, the contents of the order, price of the order\nexample of a queue = [id, timestamp, order contents, price]\n'''\n\n# need to perform linear search\n# DO NOT duplicate the code in multiple functions\n# THERE ARE NO USER INPUT IN THIS PROGRAM\n\n'''\n- SUBMIT indicates the cashier has received an order and is passing it to the chef\n ex: submit 101 %grilled cheese, broccoli soup, medium decaf% 12.95\n keyword, content, price\n Add a time stamp to the order\n the % should not be stored\n figure out what python module can be used to add timestamp\n program should print(Adding order XXX(id) to the queue with timestamp YYY(time order submitted)\n\n- COMPLETE indicates that the next order has been completed\n should print(completed order XXX(id) in YYY(seconds))\n figure out the python module that finds out the current time\n\n- Queue Contents\n print the number of orders currently in the queue and the total value of the orders\n should print(total number of orders: XX total value: YY)\n MUST NOT STORE RUNNING TOTAL IN THE PROGRAM\n\n- Cancel\n remove an order from the program\n if job not on the queue, print(unable to cancel job XX, it has already been processed\n\n- Modify\n find the order and replace the old content with new ones, change the price as well\n if not exist, print(cannot modify order)\n elif modified print(modified order XXX)\n timestamp remain unchanged\n\n- Next Order\n print the next order\n should print(next order is XXX: YYY)\n if there are no orders in the queue print(no orders remaining)\n\n- Sleep\n you should have your program rest for the time XX(seconds) specified\n find a python module that does this\n print nothing on the screen when the program is asleep\n'''\n\n\nimport queue_operations\nfrom datetime import datetime\nimport time\n\n\ndef submit(raw_queue, all_orders):\n # add the timestamp\n start = datetime.now()\n # submit the new\n modified_queue = queue_operations.enqueue(raw_queue, start)\n # append the order with timestamp to all orders\n all_orders.append(modified_queue)\n return all_orders, raw_queue, start\n\n\ndef complete(all_orders):\n # figure out the current time\n end = datetime.now()\n element = all_orders[0]\n # delete the order from al orders\n all_orders.pop(0)\n # to find the same order in all orders\n element.append(end)\n time_spend = element[-1] - element[-2]\n return all_orders, element, time_spend\n\n\ndef queue_contents(all_orders):\n number_of_orders = queue_operations.size(all_orders)\n total_value = 0\n # loop for calculating the sum\n for order in all_orders:\n total_value = total_value + float(order[-2])\n return number_of_orders, total_value\n\n\ndef cancel(all_orders, target_orders):\n # try if we can cancel the order\n try:\n all_orders = queue_operations.dequeue(all_orders, target_orders)\n return all_orders\n except:\n return target_orders[0][-1]\n\n\ndef modify(all_orders, target_order, modified_order):\n # try if we can find the order\n try:\n position = all_orders.index(target_order)\n # if found modify the\n all_orders[position][1] = modified_order[0]\n all_orders[position][2] = modified_order[1]\n return all_orders, target_order[0][-1]\n except:\n return 1, 2\n\n\ndef next_order(all_orders):\n try:\n next_order = queue_operations.look(all_orders)\n return next_order\n except:\n return 1\n\n\ndef sleep(sleep_time):\n time.sleep(int(sleep_time))\n\n\nif __name__ == '__main__':\n # test for the sumbit function\n print()\n raw_queue = ['submit 1', 'turkey wrap large coffee', '8.25']\n all_orders = []\n print(submit(raw_queue, all_orders))\n print('should return submit 1 in a list of list, a raw queue with a timestamp and another timestamp')\n\n # test for the complete function\n print()\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25']]\n all_orders[0].append(datetime.now())\n print(complete(all_orders))\n print('should return the time spend for completing the order and return an empty list')\n\n # test for the queue_contents function\n print()\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp']]\n print(queue_contents(all_orders))\n print('should return 2 and the current order and the combined value of all orders')\n\n # test of the cancel function\n print()\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp']]\n target_order = ['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp']\n print(cancel(all_orders, target_order))\n print('should return the orders left in all orders after deleting target order')\n\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp']]\n target_order = ['submit 3', 'ham and swiss chocolate milk', '8.29', 'timestamp']\n print(cancel(all_orders, target_order))\n print('should return None')\n\n # test for the modify order function\n print()\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp 1'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp 1']]\n target_order = ['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp 1']\n modified_order = ['ham and swiss chocolate milk', '8.29']\n print(modify(all_orders, target_order, modified_order))\n print('should return orders containing submit 1 and timestamp 1')\n\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp 1'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp 1']]\n target_order = ['submit 3', 'ham and swiss chocolate milk', '8.29', 'timestamp 2']\n modified_order = ['turkey wrap large coffee', '8.25']\n modify(all_orders, target_order, modified_order)\n print('should print cannot modify order')\n\n # test for the next order function\n print()\n all_orders = [['submit 1', 'turkey wrap large coffee', '8.25', 'timestamp'], ['submit 2', 'mushroom soup chocolate dip donut', '7.59', 'timestamp']]\n next_order(all_orders)\n print('should return submit 2 order')\n\n all_orders = [['submit 3', 'ham and swiss chocolate milk', '8.29']]\n next_order(all_orders)\n print('should print no orders remaining')\n\n # test for the sleep function\n print()\n sleep_time = 5\n sleep(sleep_time)\n print('the function should print this after sleeping for 5 seconds')"
},
{
"alpha_fraction": 0.558650553226471,
"alphanum_fraction": 0.5680903792381287,
"avg_line_length": 38.88271713256836,
"blob_id": "00c80f2946487770213f730eda245bde68d3e9e2",
"content_id": "2de101ea96049e1f4eee062d74123c0069d88030",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6462,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 162,
"path": "/drive.py",
"repo_name": "JuntaoXu/Tim-Hortons-Ordering-System",
"src_encoding": "UTF-8",
"text": "# drive Module Juntao Xu Student: 20132432\n\n'''\nThis is the module that drive the program\nthe program should have open connection to any website\nread and process the commands one by one\n'''\n\n# the driver program should be a bunch of if statements\n# if functionality belonging tob each if statement exceed split it into more modules\n# all printing(output) should happen in this module\n\nimport urllib.request\nimport command\n\n\ndef organize_data(data):\n '''\n organize the data form the website\n input: information from the website\n output: organized queue which is format as a list of lists\n '''\n adjusted_content = ''\n adjusted_list = []\n\n # when me need to adjust the data commands\n if len(data) < 3:\n for element in data:\n adjusted_content = adjusted_content + element + ' '\n\n # change the flag to enter the second circumstance\n return adjusted_content[:-1]\n\n # when me need to adjust the data for order contents\n else:\n for element in data:\n # for the situation where we have %abc\n if element[0] == '%':\n # append the content stored and start a new content\n adjusted_list.append(adjusted_content[:-1])\n adjusted_content = ' '\n element = element[1:]\n adjusted_content = adjusted_content + element + ' '\n\n # for this situation we have abc%\n elif element[-1] == '%':\n element = element[:-1]\n adjusted_content = adjusted_content + element\n # append the content stored and start a new content\n adjusted_list.append(adjusted_content[1:])\n adjusted_content = ' '\n\n # for the situation where there isn't a % symbol in the element\n else:\n adjusted_content = adjusted_content + element + ' '\n\n # to append the price of the order to the list, otherwise it will fail to append\n adjusted_list.append(adjusted_content[1:-1])\n\n # change the flag to enter the first circumstance\n return adjusted_list\n\n\ndef readHtml():\n print('I\\'ve added command name before each operation runs to make it easier to check')\n print('for performing linear search, list.index() is also a sort of linear search')\n response = urllib.request.urlopen(\"http://research.cs.queensu.ca/home/cords2/timOrders.txt\")\n html = response.readline() # reads one line\n # add a loop here to check to see if the content length of html is 0. If not, continue\n all_orders = []\n while len(html) > 0:\n # splits this line into a list of \"tokens\" (print it to see what you get)\n data = html.decode('utf-8').split()\n # at this point you have a list representing this command\n adjusted_data = organize_data(data)\n\n if data[0] == 'submit':\n print('command submit')\n raw_order = organize_data(data)\n all_orders, raw_queue, start = command.submit(raw_order, all_orders)\n print('Adding order', raw_queue[0][-1], 'to the queue with timestamp', start)\n\n else:\n if data[0] == 'complete':\n print('command complete')\n all_orders, element, time_spend = command.complete(all_orders)\n print('completed order', element[0][-1], 'in', time_spend)\n\n elif data[0] == 'queue':\n print('command queue')\n number_of_orders, total_value = command.queue_contents(all_orders)\n print('There are currently', number_of_orders, 'orders')\n print('The total value of orders are', total_value)\n\n elif data[0] == 'cancel':\n print('command cancel')\n # to process the necessary variables for the function\n for order in all_orders:\n if order[0][-1] == data[1]:\n target_order = order\n command.cancel(all_orders, target_order)\n\n # store the return of the function temporarily\n memory = command.cancel(all_orders, target_order)\n\n # to differentiate the return value\n if len(memory) < 2:\n print(print('unable to cancel job', memory, 'it has already been processed'))\n else:\n all_orders = memory\n\n elif data[0] == 'modify':\n print('command modify')\n for order in all_orders:\n # to process the necessary variables for the function\n if order[0][-1] == data[1]:\n target_order = order\n modified_order = organize_data(data)\n command.modify(all_orders, target_order, modified_order[-2:])\n memory1, memory2 = command.modify(all_orders, target_order, modified_order[-2:])\n if memory1 == 1:\n print('cannot modify order')\n else:\n all_orders = memory1\n print('modified order', memory2)\n\n elif data[0] == 'next':\n print('command next')\n memory = command.next_order(all_orders)\n if memory == 1:\n print('there isn\\'t a next order')\n else:\n print('the next order is', memory)\n\n elif data[0] == 'sleep':\n print('command sleep')\n command.sleep(data[1])\n\n # note that the food order isn't quite what you want, write a function that will fix it.\n # now take action depending on what the command is, for example removeFromQueue(101)\n # read another line\n html = response.readline()\n\nreadHtml()\n\n\n# the flowing test code is for the organize data function, get rid of the quotations to activate it\n'''\nif __name__ == '__main__':\n # to check the organize_data function\n # while the function is reading the order instructions\n queue = ['queue', 'contents']\n a = organize_data(queue)\n print(a)\n print('should return queue contents')\n\n # while the function is reading the order detail\n queue = ['submit', '1', '%turkey', 'wrap', 'large', 'coffee%', '8.25']\n a = organize_data(queue)\n print(a)\n print('should print [\\'submit 1\\', \\'turkey wrap large coffee\\', \\'8.25\\']')\n'''\n\n"
}
] | 4
|
kennethZhangML/lungSegmentation
|
https://github.com/kennethZhangML/lungSegmentation
|
217a45a4ad57c3a31c822d7d3abf78082c573bb4
|
0ac51230389eee68f3c5e06279bcd36da2e5c011
|
00747a33a0325b2f929b5a6d1bd02896947c261f
|
refs/heads/main
| 2023-01-19T06:14:53.757063
| 2020-11-29T13:41:51
| 2020-11-29T13:41:51
| 316,840,911
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5909090638160706,
"alphanum_fraction": 0.6038960814476013,
"avg_line_length": 29.200000762939453,
"blob_id": "7d7c0e5b61b0ce19ceda648fdc37429a5fbcfc42",
"content_id": "13c13215e44e3b2cce38d66f6d9f89cb12bcabf7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 154,
"license_type": "no_license",
"max_line_length": 39,
"num_lines": 5,
"path": "/read_nii.py",
"repo_name": "kennethZhangML/lungSegmentation",
"src_encoding": "UTF-8",
"text": "def read_nii(file_path):\r\n ct_scan = nib.load(file_path)\r\n array = ct_scan.get_fdata()\r\n array = np.rot90(np.array(array))\r\n return(array)"
},
{
"alpha_fraction": 0.7836089134216309,
"alphanum_fraction": 0.7924754619598389,
"avg_line_length": 108.7631607055664,
"blob_id": "22d15a82ebc21193d327374e97496118678761b0",
"content_id": "a3bc15f7972e884138bb63676a44eefdfb7699b9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 4173,
"license_type": "no_license",
"max_line_length": 555,
"num_lines": 38,
"path": "/README.md",
"repo_name": "kennethZhangML/lungSegmentation",
"src_encoding": "UTF-8",
"text": "# Lung Segmentation and COVID-19 Infection Prediction\nKenneth's Lung Segmentation and COVID-19 Infection Prediction Program for HackTable2020\n\n## Inspiration\nSince the beginning of the COVID-19 pandemic, we have utilized traditional methods of COVID-19 diagnosis and detection. While utilizing trained professionals and experts in medicine to assess a patient is relatively effective, it is not efficient. By training a UNet, a neural network designed for biomedical imaging and segmentation, we can perhaps generate more precise, effective, and efficient methods of detection of COVID-19. \n\n## What it does\nThe following project uses a UNet, a neural network designed for biomedical imaging, classification, and segmentation, to detect and segment the specific parameters and perimeters of the lung in an NII/CT scan. It is able to recognize the precise locations of a lung in an image and is also able to segment and predict where the infection is. \n\n## How I built it\nThe UNet can be trained just like any other neural network in the plethora of neural network architectures available to us as Machine Learning engineers. In addition, the dataset provided was also preprocessed and organized so training would be more organized and accessible at once.\n\n1. Preprocessing + Reading the Lung Masks, Segmentation Masks and Infection Masks\nIn the first stages, we must read the masks in the correct manner. Since they were \".nii\" files, a file dedicated to neuroimaging, we must convert each image to a NumPy array in a certain fashion. Here is the following code:\n\n```python\ndef read_nii(file_path):\n ct_scan = nib.load(file_path)\n array = ct_scan.get_fdata()\n array = np.rot90(np.array(array))\n return(array)\n```\nAs you can see, the first line defines the function. The second line loads the \".nii\" file from the file path. The array variable is set and gets the NumPy array of the image while rotating it 90 degrees.\n\n2. Visualizing the Images (Masks + CT_Scans)\nWe then can visualize the masks and the CT scans together. By simply using MatPlotLib, we can plot each of the images and see the masks that will train the UNet to recognize the precise locations of the lungs. The infection masks will allow the UNet to be trained to recognize the probable locations of COVID-19 infections in the lung masks.\nThe lung and infection masks are of CT scans that have been confirmed to contain COVID-19 in them, and are able to plot them so that we can visualize where the probable locations of COVID-19 could be.\n\n3. Training the UNet \nWe must first define the UNet, either through loading pre-trained weights or by completely implementing it from the ground up. We can then fit the model to the masks and scans. The model will loop through the entire dataset around 10 times in order to maximize the performance and accuracy of the model. The model will then be validated on our provided validation set with the same image shapes. \n\n4. Visualizing the Training Results\nIt is important that all models are evaluated at the end of the process. We use the Matplotlib library to plot the Training and validation loss, as well as the training and validation accuracy of the model over the 10 epochs. I completed steps 1 - 4 around 5 times in order to visualize some consistency. The model was able to consistently maintain over a 99% accuracy using the same number of epochs. \n\n## Challenges I ran into\nWhile training the UNet was rather simple, loading the data in and converting the \".nii\" files into NumPy arrays was difficult. I was not previously equipped with an understanding of the format of the images in the dataset. The first attempt I made to convert the images to a NumPy array resulted in me disrupting and causing detrimental damage to the dataset, as I had accidentally manipulated some of the images. On my second attempt, I was able to successfully import and load the image and convert them into NumPy arrays via the read_nii.py function. \n\nnote: If you want the read_nii.py function to work, please import the function in the main.ipynb file. Make sure the read_nii.py file is in the same directory, or else it will not work. Happy Programming!\n\n\n"
}
] | 2
|
mudjaycker/GUI_binHex
|
https://github.com/mudjaycker/GUI_binHex
|
12fc6bc2b3ec311b9911b3fab82db57cfb80e97e
|
6414d2df45c0a28e6bbf49147567c39992c945ff
|
672f35d5328a1725c34114e93653d64372a8bfa8
|
refs/heads/master
| 2023-06-05T14:38:10.212021
| 2021-06-14T22:27:49
| 2021-06-14T22:27:49
| 372,483,622
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4877036213874817,
"alphanum_fraction": 0.5071861743927002,
"avg_line_length": 28.271028518676758,
"blob_id": "dcdd7ed4ccaa54890812c9a8c7a9470e32e3e46e",
"content_id": "f0823538d18f2dbe1abfb3e1cc7e3224b0e8a21b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3131,
"license_type": "no_license",
"max_line_length": 96,
"num_lines": 107,
"path": "/GUI_binHex.py",
"repo_name": "mudjaycker/GUI_binHex",
"src_encoding": "UTF-8",
"text": "############################# Convert to #################################\n############################## Binary ###################################\ndef varToBin(variable):\n \n tabBin = [int(ord(i)) for i in variable]\n binaire = [bin(i)[2:] for i in tabBin]\n binary = ' '.join(str(i) for i in binaire)\n \n return binary\n############################# Convert to #################################\n############################## Hexadecimal ###############################\ndef VarToHex(variable):\n tabHex = [int(ord(i)) for i in variable]\n hexadecimal = [format(i,'X') for i in tabHex]\n hexa = ' '.join(str(i) for i in hexadecimal)\n return hexa\n\n \n\n############################# GUI #################################\n\nfrom tkinter import *\n############################## Conversion functions ###################################\ndef hexBinUpdate(*args):\n toConvert = valueInput.get()\n\n binOutput.set(varToBin(toConvert))\n hexOutput.set(VarToHex(toConvert))\n if toConvert == \"\":\n binOutput.set(\"\")\n hexOutput.set(\"\")\n############################## onCenter function ###################################\ndef onCenter(root:str, W:int, H:int):\n screenX = root.winfo_screenwidth()\n scrennY = root.winfo_screenheight()\n\n positionX = (screenX//2) - W//2\n positionY = (scrennY//2) - H//2\n geo = (f'{W}x{H}+{positionX}+{positionY}')\n\n return root.geometry(geo)\n\n\n ############################## run function (main function) ###################################\ndef run():\n root = Tk()\n W= 760\n H = 365\n onCenter(root, W, H)\n root.resizable(False,False)\n\n\n\n valueInput = StringVar()\n valueInput.trace('w',hexBinUpdate)\n entry = Entry(root,width=80,textvariable=valueInput).place(y=80,x=50)\n\n labBinPos = W/3.415\n binOutput = StringVar()\n labelBin = Label(root,bg=\"#deb887\",width=80,textvariable=binOutput)\n labelBin.config(font=('Andika',11))\n labelBin.place(y=labBinPos,x=15)\n\n\n labHexPos = W/2.732\n\n hexOutput = StringVar()\n labelHex = Label(root,bg=\"#a9a9a9\",width=80,textvariable=hexOutput)\n labelHex.config(font=('Andika',11))\n labelHex.place(y=labHexPos,x=15)\n\n\n\n ################### Fonctions to copy ######################\n from tkinter import messagebox\n\n def copyBin():\n value = valueInput.get()\n root.clipboard_clear()\n root.clipboard_append(varToBin(value))\n messagebox.showinfo(\"Binary copied!\",\"{} copied\".format(varToBin(value)))\n\n def copyHex():\n value = valueInput.get()\n root.clipboard_clear()\n root.clipboard_append(VarToHex(value))\n messagebox.showinfo(\"Hexadecimal copied!\",\"{} copied\".format(VarToHex(value)))\n\n\n\n\n butY=int(H/(H/310))\n but = int(W/(W/20))\n butBin = Button(root,width=2,height=1,bg='#deb887',command=copyBin,\n text=\"copy\").place(y=butY,x=but)\n\n butX=int(W/(W/650))\n butHex = Button(root,width=2,height=1,bg='#a9a9a9',command=copyHex,\n text=\"copy\").place(y=butY, x=butX)\n root.mainloop()\n \n\n\n\n\nif __name__==\"__main__\":\n run()"
}
] | 1
|
vovok/sea-fight
|
https://github.com/vovok/sea-fight
|
f7ed6c1c1c58faac85946b50eee9b3bd65f1b6ae
|
8b9d49fd2dd4e9193ca7d65903919801d032df6e
|
36232f6ebf9c9a238c34f2f615b56a45abcc948b
|
refs/heads/master
| 2022-01-07T17:48:00.120443
| 2019-08-07T17:43:33
| 2019-08-07T17:43:33
| 29,233,760
| 4
| 3
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5553919076919556,
"alphanum_fraction": 0.5657830238342285,
"avg_line_length": 42.49466323852539,
"blob_id": "33ff2daa3c4a7e52a1b94519722b49a5a0d5a0e0",
"content_id": "54fbcfecb8474f597c0ddcd8eea62dcf904d7ac1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13084,
"license_type": "no_license",
"max_line_length": 257,
"num_lines": 281,
"path": "/main.py",
"repo_name": "vovok/sea-fight",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport service\nfrom random import choice, randint, shuffle\nfrom copy import copy, deepcopy\nfrom logging import basicConfig, INFO, info\n\nbasicConfig(format=u'[%(asctime)s] %(message)s', level=INFO)\n\n\nclass Game(object):\n def __init__(self, player1, player2):\n # info(u'Начало игры')\n self.player_list = [player1, player2]\n self.curr_player = None\n self.player_log_list()\n\n def player_log_list(self):\n # info(u'Игроки: %s', \", \".join([x.player_name for x in self.player_list]))\n pass\n\n def game(self):\n tour_stats.game_id += 1\n # Выбираем игрока для первого хода\n if self.curr_player is None:\n self.curr_player = choice(self.player_list)\n # Получаем координаты для хода\n crd_for_shoot = self.curr_player.strategy.get_crd_for_step()\n # Выделяем второго игрока из списка\n player2 = filter(lambda x: x != self.curr_player, self.player_list)[0]\n # Ходим и сохраняем результаты хода\n shoot_res = player2.shoot(crd_for_shoot)\n # Передаём результаты хода ходившему игроку\n # logging.info(u'Ходит: %s, координаты: %s, статус: %s', self.curr_player.player_name, crd_for_shoot, shoot_res)\n self.curr_player.strategy.return_shoot_state(shoot_res, crd_for_shoot, player2)\n self.curr_player.stat.step += 1\n if shoot_res in [u'Убил!', u'Попал!']:\n self.curr_player.stat.score += 1\n # Меняем счётчик текущего пользователя, если ходивший промазал\n if shoot_res == u'Мимо!':\n self.curr_player = player2\n # Конец игры и вывод статистики\n if shoot_res == u'Убил!':\n self.curr_player.stat.ships_defeat.append(1)\n if len(self.curr_player.stat.ships_defeat) == 10:\n # info(u'Выйграл: %s', self.curr_player.player_name)\n # info(u'%s', \", \".join([str(x.player_name) + u\" набрал очков: \" + str(x.scores) + u\", ходов: \" + str(x.steps) for x in self.player_list]))\n # Сбрасываем счётчики\n self.curr_player.stat.tur_scores += self.curr_player.stat.score\n tour_stats.get_stats(self.player_list)\n self.curr_player.reset_values()\n # info(u'------------------')\n return self.curr_player\n # Если игра продолжается, то перезапускаем функцию game()\n return self.game()\n\n\nclass Player(object):\n def __init__(self):\n self.player_name = service.rdn_usr_name()\n self.strategy = PlayerStrategy()\n self.stat = PlayerStatistic()\n self.ships = self.create_ships()\n\n def create_ships(self):\n self.ships = []\n buff_cord = []\n ships = [4, 3, 3, 2, 2, 2, 1, 1, 1, 1]\n for ship in ships:\n if self.strategy.combinations[ship]:\n cords = choice(self.strategy.combinations[ship])\n overlay = service.set_halo(cords)\n self.strategy.data_cleaner(cords, overlay)\n buff_cord.append([ship, cords, overlay])\n else:\n self.strategy.reload()\n return self.create_ships()\n for cords_for_unpack in buff_cord:\n ship, cords, overlay = cords_for_unpack\n self.ships.append(Ship(ship, cords, overlay))\n return self.ships\n\n def shoot(self, cords):\n \"\"\"Возвращает результат стрельбы по координатам\"\"\"\n for ship in self.ships:\n if cords in ship.cord:\n ship.shoots.append(cords)\n shoot_res = ship.get_state()\n return shoot_res\n else:\n return u'Мимо!'\n\n def reset_values(self):\n self.strategy.reset()\n self.stat.reset()\n self.ships = self.create_ships()\n\n\nclass Ship(object):\n def __init__(self, ship_type, cord, halo):\n self.ship_type = ship_type\n self.cord = cord\n self.halo = halo\n self.shoots = []\n self.state = u'Цел'\n\n def get_state(self):\n if len(self.shoots) == self.ship_type:\n self.state = u'Убил!'\n else:\n self.state = u'Попал!'\n return self.state\n\n\nclass PlayerStatistic(object):\n def __init__(self):\n self.score = 0\n self.step = 0\n self.ships_defeat = []\n self.tur_scores = 0\n\n def reset(self):\n self.score = 0\n self.step = 0\n self.ships_defeat = []\n\n\nclass TournaimentStatistic(object):\n def __init__(self):\n self.game_id = 0\n self.step_all = []\n self.step_winners = []\n self.scores_loosers = []\n self.step_loosers = []\n self.players_copy_list = []\n\n def get_stats(self, player_list):\n self.players_copy_list.extend([deepcopy(player) for player in player_list])\n\n def count_middles(self):\n self.step_all = [player.stat.step for player in self.players_copy_list]\n self.step_winners = [player.stat.step for player in self.players_copy_list if\n len(player.stat.ships_defeat) == 10]\n self.step_loosers = [player.stat.step for player in self.players_copy_list if\n len(player.stat.ships_defeat) != 10]\n self.scores_loosers = [player.stat.score for player in self.players_copy_list if\n len(player.stat.ships_defeat) != 10]\n return sum(self.step_all) / float(len(self.step_all)), sum(self.step_winners) / float(\n len(self.step_winners)), sum(self.step_loosers) / float(len(self.step_loosers)), sum(\n self.scores_loosers) / float(len(self.scores_loosers))\n\n def startegy_effect(self):\n report_strategy = {u\"Победители\": [], u\"Проигравшие\": []}\n for player in self.players_copy_list:\n pl_stat = \"\"\n if len(player.stat.ships_defeat) == 10:\n pl_stat = u\"Победители\"\n else:\n pl_stat = u\"Проигравшие\"\n report_strategy[pl_stat].append(\n [player.strategy.ships_strategy_collocation, player.strategy.steps_strategy])\n return report_strategy\n\n\nclass PlayerStrategy(object):\n def __init__(self):\n self.alien_cords = []\n self.recomendation_pool = []\n self.succ_shoots = []\n self.ships_strategy_collocation = STRATEGY_QUOTA.pop()\n self.combinations = deepcopy(service.gen_cord(self.ships_strategy_collocation))\n self.steps_strategy = choice(list(service.STEPS_STRATEGY.keys()))\n self.steps_cords = deepcopy(service.STEPS_STRATEGY[self.steps_strategy])\n\n def get_crd_for_step(self):\n \"\"\"Выбор координат для хода\"\"\"\n if self.recomendation_pool:\n crd = self.recomendation_pool.pop(0)\n elif self.steps_cords:\n shuffle(self.steps_cords)\n crd = self.steps_cords.pop(0)\n else:\n crd = choice(filter(lambda x: x not in self.alien_cords, service.CORD_10_10))\n if crd in self.recomendation_pool:\n self.recomendation_pool.remove(crd)\n elif crd in self.recomendation_pool:\n self.recomendation_pool.remove(crd)\n self.alien_cords.append(crd)\n return crd\n\n def return_shoot_state(self, state, crd, player2):\n \"\"\"Стратегия дальнейщих ходов в зависимости от результата текущего хода\"\"\"\n if state == u'Попал!':\n if not self.recomendation_pool:\n crd_rec = [[crd[0] - 1, crd[1]], [crd[0] + 1, crd[1]], [crd[0], crd[1] - 1], [crd[0], crd[1] + 1]]\n crd_rec = filter(lambda x: 0 <= x[0] <= 9 and 0 <= x[1] <= 9, crd_rec)\n self.succ_shoots.append(crd)\n self.recomendation_pool.extend([crd for crd in crd_rec if crd not in self.alien_cords])\n else:\n crd_s1 = self.recomendation_pool[0]\n crd_s2 = self.succ_shoots[0]\n for ind in range(2):\n if crd_s1[ind] != crd_s2[ind]:\n if crd_s1[ind] > crd_s2[ind]:\n crd_rec = [[crd_s1[ind] + 1, crd_s1[ind] + 2], [crd_s2[ind] - 1, crd_s2[ind] - 2]]\n else:\n crd_rec = [[crd_s1[ind] - 1, crd_s1[ind] - 2], [crd_s2[ind] + 1, crd_s2[ind] + 2]]\n crd_rec = filter(lambda x: 0 <= x[0] <= 9 and 0 <= x[1] <= 9, crd_rec)\n self.recomendation_pool.extend([crd for crd in crd_rec if crd not in self.alien_cords])\n elif state == u'Убил!':\n for ship in player2.ships:\n if crd in ship.cord:\n self.alien_cords.extend([crd for crd in ship.halo if crd not in self.alien_cords])\n self.steps_cords = filter(lambda x: x not in ship.halo and x not in self.alien_cords,\n self.steps_cords)\n self.recomendation_pool = []\n self.succ_shoots = []\n\n def data_cleaner(self, cords, overlay):\n \"\"\"Удаляет использованные комбинации из словаря комбинаций пользователя\n используется при создании кораблей\"\"\"\n del_index = {}\n for ship in self.combinations.keys():\n del_index[ship] = []\n for ind, crd_pack in enumerate(self.combinations[ship]):\n for crd in cords + overlay:\n if crd in crd_pack and ind not in del_index[ship]:\n del_index[ship].append(ind)\n for ship in del_index.keys():\n for ind_for_del in reversed(del_index[ship]):\n del self.combinations[ship][ind_for_del]\n\n def reload(self):\n self.combinations = deepcopy(service.gen_cord(self.ships_strategy_collocation))\n\n def reset(self):\n self.alien_cords = []\n self.recomendation_pool = []\n self.succ_shoots = []\n self.combinations = deepcopy(service.gen_cord(self.ships_strategy_collocation))\n self.steps_strategy = choice(service.STEPS_STRATEGY.keys())\n self.steps_cords = deepcopy(service.STEPS_STRATEGY[self.steps_strategy])\n\n\nif __name__ == '__main__':\n turnaiment_player_counter = 1024\n tour_stats = TournaimentStatistic()\n info(u'Начало турнира')\n STRATEGY_QUOTA = [y for y in [\"for_1_ship_left\",\n \"for_1_ship_right\",\n \"for_1_ship_top\",\n \"for_1_ship_bottom\",\n \"for_1_ship_center_horisontal\",\n \"for_1_ship_center_vertical\",\n \"for_1_ship_36\",\n \"random_12\"] for x in range(int(turnaiment_player_counter / 8))]\n shuffle(STRATEGY_QUOTA)\n tur_player_list = [Player() for player in range(turnaiment_player_counter)]\n # info(u'Список игроков: %s', \", \".join([x.player_name for x in tur_player_list]))\n tur_player_list_next_iter = []\n while len(tur_player_list) != 1:\n for player_ind in range(1, len(tur_player_list), 2):\n winner = Game(tur_player_list[player_ind - 1], tur_player_list[player_ind]).game()\n tur_player_list_next_iter.append(winner)\n tur_player_list = copy(tur_player_list_next_iter)\n tur_player_list_next_iter = []\n else:\n info(u'Турнир выйграл: %s, набрал очков: %s', tur_player_list[0].player_name,\n tur_player_list[0].stat.tur_scores)\n med_step_all, med_step_win, med_step_looser, med_score_looser = tour_stats.count_middles()\n info(\n u'Статистика: \\n\\t1. Среднее количесво ходов (всех игроков): %.2f,\\n\\t2. Среднее количество ходов выйгравших игроков: %.2f,\\n\\t3. Среднее количество ходов проигравших игроков: %.2f,\\n\\t4. Среднее количество очков, которое набрали проигравшие: %.2f',\n med_step_all, med_step_win, med_step_looser, med_score_looser)\n res_strat = tour_stats.startegy_effect()\n for pl_stat in res_strat.keys():\n info(u'%s:', pl_stat)\n bf = []\n for strategy_com in res_strat[pl_stat]:\n if strategy_com not in bf:\n bf.append(strategy_com)\n info(u'%s: %s', \", \".join(strategy_com), res_strat[pl_stat].count(strategy_com))\n"
},
{
"alpha_fraction": 0.5199084877967834,
"alphanum_fraction": 0.5704805254936218,
"avg_line_length": 41.019229888916016,
"blob_id": "dc2a29b4d37e0bbe69dd090395f3a77c43c415ed",
"content_id": "d89a303dd75587a987bf36e347ebc6c6ba4566b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4653,
"license_type": "no_license",
"max_line_length": 115,
"num_lines": 104,
"path": "/service.py",
"repo_name": "vovok/sea-fight",
"src_encoding": "UTF-8",
"text": "#!python\n# -*- coding: utf-8 -*-\nfrom random import randint, choice\nfrom itertools import permutations as comb\n\n\ndef rdn_usr_name():\n \"\"\"Генерирует случайное имя для робота на основе 5-ти суффиксов\"\"\"\n suffix_list = ['pa', 'li', 'ra', 'co', 'si']\n res = ''\n for cntr in range(3): res += suffix_list[randint(0, 4)]\n return res.capitalize() + str(randint(0, 999))\n\n\ndef adds(cord, delta):\n \"\"\"Функция суммирования значений двух списков\"\"\"\n sum_list = []\n for i in range(len(cord)):\n sum_list.append(cord[i] + delta[i])\n return sum_list\n\n\ndef set_halo(cords):\n \"\"\"Функция генерации ореола по координатам\"\"\"\n halo = []\n delta_comb = list(comb(range(-1, 2), 2))\n delta_comb += [(1, 1), (-1, -1)]\n for cord in cords:\n for delta in delta_comb:\n ads = adds(cord, delta)\n if ads != 0 and ads not in halo and ads not in cords:\n halo.append(ads)\n return filter(lambda x: 0 <= x[0] <= 9 and 0 <= x[1] <= 9, halo)\n\n\ndef gen_cord(strategy):\n \"\"\"Генератор всех возможных комбинаций координат + генерирует случайную стратегию из 12 координат\"\"\"\n all_comb, cords_for_1_ship = GLOBAL_DATA\n GLOBAL_DATA[1][\"random_12\"] = []\n while len(GLOBAL_DATA[1][\"random_12\"]) != 12:\n x_cord = randint(0, 9)\n y_cord = randint(0, 9)\n if [x_cord, y_cord] not in GLOBAL_DATA[1][\"random_12\"]:\n GLOBAL_DATA[1][\"random_12\"].append([x_cord, y_cord])\n for_1_ship = cords_for_1_ship[strategy]\n for_other_ship = filter(lambda x: x not in for_1_ship, all_comb)\n cord_comb = {1: [[x] for x in for_1_ship], 2: [], 3: [], 4: []}\n for ship in filter(lambda x: x != 1, cord_comb.keys()):\n for cord in for_other_ship:\n hor_direction = [cord] + [[cord[0] + x, cord[1]] for x in range(1, ship)]\n ver_direction = [cord] + [[cord[0], cord[1] + x] for x in range(1, ship)]\n for dir_d in [hor_direction, ver_direction]:\n for cord_d in dir_d:\n if cord_d not in for_other_ship:\n break\n else:\n cord_comb[ship].append(dir_d)\n return cord_comb\n\n\ndef get__cord_for_1_ship():\n \"\"\"Генерирует 7 кобинайций расстановки однопалубных и возвращает случайную комбинацию\"\"\"\n cord_for_1_ship = {\n \"for_1_ship_left\": filter(lambda x: x[0] in range(0, 6) and x[1] in range(0, 10), CORD_10_10),\n \"for_1_ship_right\": filter(lambda x: x[0] in range(4, 10) and x[1] in range(0, 10), CORD_10_10),\n \"for_1_ship_top\": filter(lambda x: x[0] in range(0, 10) and x[1] in range(0, 6), CORD_10_10),\n \"for_1_ship_bottom\": filter(lambda x: x[0] in range(0, 10) and x[1] in range(4, 10), CORD_10_10),\n \"for_1_ship_center_horisontal\": filter(lambda x: x[0] in range(2, 10) and x[1] in range(2, 8), CORD_10_10),\n \"for_1_ship_center_vertical\": filter(lambda x: x[0] in range(2, 8) and x[1] in range(0, 10), CORD_10_10),\n \"for_1_ship_36\": filter(lambda x: x[0] in range(2, 8) and x[1] in range(2, 8), CORD_10_10)}\n return CORD_10_10, cord_for_1_ship\n\n\ndef gen_cross_cord():\n cross_cord = []\n cross_cord.extend([[x, x] for x in range(10)])\n cross_cord.extend([[9 - x, x] for x in range(10)])\n cross_cord.extend([[x, y] for x in range(5, 6) for y in range(1, 10, 2)])\n cross_cord.extend([[x, y] for x in range(4, 5) for y in range(0, 10, 2)])\n cross_cord.extend([[x, y] for y in range(5, 6) for x in range(1, 10, 2)])\n cross_cord.extend([[x, y] for y in range(4, 5) for x in range(0, 10, 2)])\n del_cords = [[x, y] for x in range(4, 6) for y in range(4, 6)]\n for del_crd in del_cords:\n while 1:\n if del_crd in cross_cord:\n cross_cord.remove(del_crd)\n else:\n break\n return cross_cord\n\n\ndef gen_linear_cord_var_2():\n \"\"\"http://habrahabr.ru/post/180995/ вариант 2\"\"\"\n linear_cord = []\n linear_cord.extend([[3 - x, 0 + x] for x in range(4)])\n linear_cord.extend([[7 - x, 0 + x] for x in range(8)])\n linear_cord.extend([[2 + x, 9 - x] for x in range(8)])\n linear_cord.extend([[6 + x, 9 - x] for x in range(4)])\n return linear_cord\n\n\nCORD_10_10 = [[x / 10, x % 10] for x in range(100)]\nGLOBAL_DATA = get__cord_for_1_ship()\nSTEPS_STRATEGY = {\"cross\": gen_cross_cord(), \"linear\": gen_linear_cord_var_2(), \"random\": []}\n"
}
] | 2
|
ARONDALTON/DilutionSolution
|
https://github.com/ARONDALTON/DilutionSolution
|
fe2ce6e696036a665709202f2a4626381ba6ae80
|
e2b9393f2e17cd507f869d651905a7809850f08b
|
f57d1226db1d7e8db9bcc87cc25329790392e7fb
|
refs/heads/master
| 2021-05-27T04:51:45.506934
| 2013-01-09T19:41:22
| 2013-01-09T19:41:22
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6337341666221619,
"alphanum_fraction": 0.6802079677581787,
"avg_line_length": 37.474998474121094,
"blob_id": "0bf6aafb0ce650738bf44274bd10428334521dbb",
"content_id": "6199198c2c9d72774b96e8bc5d8ef08a0c9cc2c5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3077,
"license_type": "no_license",
"max_line_length": 128,
"num_lines": 80,
"path": "/dilutionSolution.py",
"repo_name": "ARONDALTON/DilutionSolution",
"src_encoding": "UTF-8",
"text": "#!python\n\n__author__ = 'estsauver'\n\nimport sys\n\nfrom PySide.QtGui import *\n\n\n\nfrom ui_dilutionSolution import Ui_Dialog\n\ndef stock_calc(self, desVol, desVolUnits, desConc, desConcunits, stockConc, stockConcUnits):\n assert isinstance(stockConcUnits, float)\n assert isinstance(desConc, float)\n assert isinstance(desConcunits,float)\n assert isinstance(desVol,float)\n assert isinstance(desVolUnits,float)\n assert isinstance(stockConc,float)\n assert isinstance(stockConcUnits,float)\n desConcinMolar = desConc*desConcunits\n print \"Deisred Concentration in Molar %s\" %desConcinMolar\n desVolinL = desVol*desVolUnits\n print \"Desired Volume in L: %s\" %desVolinL\n stockConcinMolar = stockConc*stockConcUnits\n print \"Stock Concentration in Molar %s\" %stockConcinMolar\n stockVolumeinL = (desConcinMolar*desVolinL)/stockConcinMolar\n print \"Stock Volume in Liters: %s\" %stockVolumeinL\n soluteVolumeinL = desVolinL-stockVolumeinL\n print \"Solute Volume in LIters: %s\" %soluteVolumeinL\n assert (stockVolumeinL+soluteVolumeinL==desVolinL)\n return (stockVolumeinL,soluteVolumeinL)\n\nclass MainWindow(QMainWindow, Ui_Dialog):\n def __init__(self, parent=None):\n super(MainWindow, self).__init__(parent)\n self.setupUi(self)\n\n\n def accept(self):\n unitConcDict = {\"Mol/L\":1.0,\"mMol/L\":0.001,\"mMol/mL\":1.0,\"mMol/uL\":1000,\"uMol/L\":0.000001, \"uMol/mL\":0.001,\n \"uMol/uL\":1.0,\"nMol/L\":0.000000001, \"nMol/mL\":0.000001, \"nMol/uL\":0.001, \"nMol/nL\":1.0,\"nMol/pL\":1000.0,\n \"pMol/L\":0.000000000001,\"pMol/mL\":0.000000001, \"pMol/uL\":0.000001, \"pMol/nL\":0.001, \"pMol/pL\":1}\n unitVolDict = {\"L\":1.0,\"mL\":0.001,\"uL\":0.000001,\"pL\":0.000000001}\n desConc = float(self.desConcValue.text())\n desConcUnitsString = self.desConcUnits.currentItem().text()\n desConcUnits = unitConcDict[desConcUnitsString]\n\n desVol = float(self.desVolValue.text())\n desVolUnitsString = self.desVolUnits.currentItem().text()\n desVolUnits = unitVolDict[desVolUnitsString]\n\n stockConc = float(self.stockConcValue.text())\n stockConcUnitsString = self.stockConcUnits.currentItem().text()\n stockConcUnits = unitConcDict[stockConcUnitsString]\n\n print (desVol, desVolUnits, desConc, desConcUnits, stockConc, stockConcUnits)\n (stockVolinL, soluteVolinL) = stock_calc(super, desVol, desVolUnits, desConc, desConcUnits, stockConc, stockConcUnits)\n\n self.label_3.setText(\"L: %s \" % unicode(stockVolinL))\n self.label_4.setText(\"mL: %s \" % unicode(stockVolinL*1000.0))\n self.label_5.setText(\"uL: %s \" % unicode(stockVolinL*1000000.0))\n self.label_6.setText(\"L: %s \" % unicode(soluteVolinL))\n self.label_7.setText(\"ml: %s \" %unicode(soluteVolinL*1000.0))\n self.label_8.setText(\"ul: %s \" %unicode(soluteVolinL*1000000.0))\n\n\n\n\n\n\n def reject(self):\n QApplication.instance().quit()\n\n\nif __name__==\"__main__\":\n app = QApplication(sys.argv)\n frame = MainWindow()\n frame.show()\n app.exec_()"
},
{
"alpha_fraction": 0.8024691343307495,
"alphanum_fraction": 0.8024691343307495,
"avg_line_length": 79,
"blob_id": "8fcd0ef7daffd4a6b8a31737861ffcae4578efdd",
"content_id": "83742d4da79c942cc598f08fe63ccbc9fb1b3ab3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 81,
"license_type": "no_license",
"max_line_length": 79,
"num_lines": 1,
"path": "/README.md",
"repo_name": "ARONDALTON/DilutionSolution",
"src_encoding": "UTF-8",
"text": "A simple dilution calculator. Needs all fields ot be selected to work properly. \n"
},
{
"alpha_fraction": 0.7125838398933411,
"alphanum_fraction": 0.7294947504997253,
"avg_line_length": 67.24766540527344,
"blob_id": "e4306eef8aef856dd0fd5fdd1d614f789b93021a",
"content_id": "7844b7dd6a59bd2a00913ce4c43413bad5010062",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14606,
"license_type": "no_license",
"max_line_length": 136,
"num_lines": 214,
"path": "/ui_dilutionSolution.py",
"repo_name": "ARONDALTON/DilutionSolution",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\n\n# Form implementation generated from reading ui file 'dilutionSolution.ui'\n#\n# Created: Wed Jan 9 11:37:18 2013\n# by: pyside-uic 0.2.13 running on PySide 1.1.0\n#\n# WARNING! All changes made in this file will be lost!\n\nfrom PySide import QtCore, QtGui\n\nclass Ui_Dialog(object):\n def setupUi(self, Dialog):\n Dialog.setObjectName(\"Dialog\")\n Dialog.resize(600, 600)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(Dialog.sizePolicy().hasHeightForWidth())\n Dialog.setSizePolicy(sizePolicy)\n self.verticalLayoutWidget = QtGui.QWidget(Dialog)\n self.verticalLayoutWidget.setGeometry(QtCore.QRect(20, 10, 211, 561))\n self.verticalLayoutWidget.setObjectName(\"verticalLayoutWidget\")\n self.verticalLayout = QtGui.QVBoxLayout(self.verticalLayoutWidget)\n self.verticalLayout.setContentsMargins(0, 0, 0, 0)\n self.verticalLayout.setObjectName(\"verticalLayout\")\n self.desConcLabel = QtGui.QLabel(self.verticalLayoutWidget)\n self.desConcLabel.setObjectName(\"desConcLabel\")\n self.verticalLayout.addWidget(self.desConcLabel)\n self.desConcValue = QtGui.QLineEdit(self.verticalLayoutWidget)\n self.desConcValue.setObjectName(\"desConcValue\")\n self.verticalLayout.addWidget(self.desConcValue)\n self.desConcUnits = QtGui.QListWidget(self.verticalLayoutWidget)\n self.desConcUnits.setObjectName(\"desConcUnits\")\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n QtGui.QListWidgetItem(self.desConcUnits)\n self.verticalLayout.addWidget(self.desConcUnits)\n spacerItem = QtGui.QSpacerItem(20, 40, QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Expanding)\n self.verticalLayout.addItem(spacerItem)\n self.desVolLabel = QtGui.QLabel(self.verticalLayoutWidget)\n self.desVolLabel.setObjectName(\"desVolLabel\")\n self.verticalLayout.addWidget(self.desVolLabel)\n self.desVolValue = QtGui.QLineEdit(self.verticalLayoutWidget)\n self.desVolValue.setObjectName(\"desVolValue\")\n self.verticalLayout.addWidget(self.desVolValue)\n self.desVolUnits = QtGui.QListWidget(self.verticalLayoutWidget)\n self.desVolUnits.setObjectName(\"desVolUnits\")\n QtGui.QListWidgetItem(self.desVolUnits)\n QtGui.QListWidgetItem(self.desVolUnits)\n QtGui.QListWidgetItem(self.desVolUnits)\n QtGui.QListWidgetItem(self.desVolUnits)\n self.verticalLayout.addWidget(self.desVolUnits)\n self.verticalLayoutWidget_2 = QtGui.QWidget(Dialog)\n self.verticalLayoutWidget_2.setGeometry(QtCore.QRect(280, 10, 291, 561))\n self.verticalLayoutWidget_2.setObjectName(\"verticalLayoutWidget_2\")\n self.verticalLayout_2 = QtGui.QVBoxLayout(self.verticalLayoutWidget_2)\n self.verticalLayout_2.setContentsMargins(0, 0, 0, 0)\n self.verticalLayout_2.setObjectName(\"verticalLayout_2\")\n self.stockConcLabel = QtGui.QLabel(self.verticalLayoutWidget_2)\n self.stockConcLabel.setObjectName(\"stockConcLabel\")\n self.verticalLayout_2.addWidget(self.stockConcLabel)\n self.stockConcValue = QtGui.QLineEdit(self.verticalLayoutWidget_2)\n self.stockConcValue.setObjectName(\"stockConcValue\")\n self.verticalLayout_2.addWidget(self.stockConcValue)\n self.stockConcUnits = QtGui.QListWidget(self.verticalLayoutWidget_2)\n self.stockConcUnits.setObjectName(\"stockConcUnits\")\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n QtGui.QListWidgetItem(self.stockConcUnits)\n self.verticalLayout_2.addWidget(self.stockConcUnits)\n self.label = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label.setFont(font)\n self.label.setObjectName(\"label\")\n self.verticalLayout_2.addWidget(self.label)\n self.label_3 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_3.setFont(font)\n self.label_3.setObjectName(\"label_3\")\n self.verticalLayout_2.addWidget(self.label_3)\n self.label_4 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_4.setFont(font)\n self.label_4.setObjectName(\"label_4\")\n self.verticalLayout_2.addWidget(self.label_4)\n self.label_5 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_5.setFont(font)\n self.label_5.setObjectName(\"label_5\")\n self.verticalLayout_2.addWidget(self.label_5)\n self.label_2 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_2.setFont(font)\n self.label_2.setObjectName(\"label_2\")\n self.verticalLayout_2.addWidget(self.label_2)\n self.label_6 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_6.setFont(font)\n self.label_6.setObjectName(\"label_6\")\n self.verticalLayout_2.addWidget(self.label_6)\n self.label_7 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_7.setFont(font)\n self.label_7.setObjectName(\"label_7\")\n self.verticalLayout_2.addWidget(self.label_7)\n self.label_8 = QtGui.QLabel(self.verticalLayoutWidget_2)\n font = QtGui.QFont()\n font.setPointSize(12)\n self.label_8.setFont(font)\n self.label_8.setObjectName(\"label_8\")\n self.verticalLayout_2.addWidget(self.label_8)\n self.buttonBox = QtGui.QDialogButtonBox(self.verticalLayoutWidget_2)\n self.buttonBox.setOrientation(QtCore.Qt.Horizontal)\n self.buttonBox.setStandardButtons(QtGui.QDialogButtonBox.Close|QtGui.QDialogButtonBox.Ok)\n self.buttonBox.setObjectName(\"buttonBox\")\n self.verticalLayout_2.addWidget(self.buttonBox)\n\n self.retranslateUi(Dialog)\n QtCore.QObject.connect(self.buttonBox, QtCore.SIGNAL(\"accepted()\"), Dialog.accept)\n QtCore.QObject.connect(self.buttonBox, QtCore.SIGNAL(\"rejected()\"), Dialog.reject)\n QtCore.QMetaObject.connectSlotsByName(Dialog)\n\n def retranslateUi(self, Dialog):\n Dialog.setWindowTitle(QtGui.QApplication.translate(\"Dialog\", \"Dilution Solution\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcLabel.setText(QtGui.QApplication.translate(\"Dialog\", \"Desired Concentration\", None, QtGui.QApplication.UnicodeUTF8))\n __sortingEnabled = self.desConcUnits.isSortingEnabled()\n self.desConcUnits.setSortingEnabled(False)\n self.desConcUnits.item(0).setText(QtGui.QApplication.translate(\"Dialog\", \"Mol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(1).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(2).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(3).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(4).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(5).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(6).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(7).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(8).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(9).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(10).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/pL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(11).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(12).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(13).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(14).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/nL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.item(15).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/pL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desConcUnits.setSortingEnabled(__sortingEnabled)\n self.desVolLabel.setText(QtGui.QApplication.translate(\"Dialog\", \"Desired Volume\", None, QtGui.QApplication.UnicodeUTF8))\n __sortingEnabled = self.desVolUnits.isSortingEnabled()\n self.desVolUnits.setSortingEnabled(False)\n self.desVolUnits.item(0).setText(QtGui.QApplication.translate(\"Dialog\", \"L\", None, QtGui.QApplication.UnicodeUTF8))\n self.desVolUnits.item(1).setText(QtGui.QApplication.translate(\"Dialog\", \"mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desVolUnits.item(2).setText(QtGui.QApplication.translate(\"Dialog\", \"uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desVolUnits.item(3).setText(QtGui.QApplication.translate(\"Dialog\", \"pL\", None, QtGui.QApplication.UnicodeUTF8))\n self.desVolUnits.setSortingEnabled(__sortingEnabled)\n self.stockConcLabel.setText(QtGui.QApplication.translate(\"Dialog\", \"Stock Concentration\", None, QtGui.QApplication.UnicodeUTF8))\n __sortingEnabled = self.stockConcUnits.isSortingEnabled()\n self.stockConcUnits.setSortingEnabled(False)\n self.stockConcUnits.item(0).setText(QtGui.QApplication.translate(\"Dialog\", \"Mol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(1).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(2).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(3).setText(QtGui.QApplication.translate(\"Dialog\", \"mMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(4).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(5).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(6).setText(QtGui.QApplication.translate(\"Dialog\", \"uMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(7).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(8).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(9).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(10).setText(QtGui.QApplication.translate(\"Dialog\", \"nMol/pL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(11).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/L\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(12).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/mL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(13).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/uL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(14).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/nL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.item(15).setText(QtGui.QApplication.translate(\"Dialog\", \"pMol/pL\", None, QtGui.QApplication.UnicodeUTF8))\n self.stockConcUnits.setSortingEnabled(__sortingEnabled)\n self.label.setText(QtGui.QApplication.translate(\"Dialog\", \"Volume Stock Solution:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_3.setText(QtGui.QApplication.translate(\"Dialog\", \"Liters:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_4.setText(QtGui.QApplication.translate(\"Dialog\", \"mL:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_5.setText(QtGui.QApplication.translate(\"Dialog\", \"uL:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_2.setText(QtGui.QApplication.translate(\"Dialog\", \"Volume Solution:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_6.setText(QtGui.QApplication.translate(\"Dialog\", \"Liters:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_7.setText(QtGui.QApplication.translate(\"Dialog\", \"mL:\", None, QtGui.QApplication.UnicodeUTF8))\n self.label_8.setText(QtGui.QApplication.translate(\"Dialog\", \"uL:\", None, QtGui.QApplication.UnicodeUTF8))\n\n"
}
] | 3
|
DavidMLink/JobListings
|
https://github.com/DavidMLink/JobListings
|
3bfa0fbf8cfe5d95bbfde0ec0ff849909899bb1f
|
3661a2cb4411641adf6dae1b537b3f311a6fe274
|
974c5a7cdd1c07172830413fd190e0f4a7a7180c
|
refs/heads/master
| 2020-04-02T22:47:22.337455
| 2018-10-26T16:59:30
| 2018-10-26T16:59:30
| 154,844,482
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6516666412353516,
"alphanum_fraction": 0.6549999713897705,
"avg_line_length": 33.28571319580078,
"blob_id": "4dc31409a2a14447dc6938d17450577b015a4922",
"content_id": "420f44114139e10683478899ad57c1399f118c64",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2400,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 70,
"path": "/jobboard/urls.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "\"\"\"jobboard URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/2.1/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: path('', views.home, name='home')\nClass-based views\n 1. Add an import: from other_app.views import Home\n 2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')\nIncluding another URLconf\n 1. Import the include() function: from django.urls import include, path\n 2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))\n\"\"\"\nfrom django.urls import path\nfrom jobboard_app import views\n\nurlpatterns = [\n \n # LOGIN AND REGISTRATION\n path('', views.index),\n path('registerProcess', views.register),\n path('loginProcess', views.login),\n path('homeTemplate', views.home),\n # END OF LOGIN AND REGISTRATION\n\n # RESET SESSIONS\n path('resetSessions', views.resetSessions),\n # END OF RESET SESSIONS\n\n #UNKNOWN PROCESSES\n path('DeleteProcess/<id>', views.remove),\n # END OF PROCESSES\n\n # DASHBOARD ROUTING\n path('dashboardTemplate', views.dashboard),\n # LEFT FILTER\n path('sortByProcess', views.sortByProcess),\n path('distanceProcess', views.distanceProcess),\n path('salaryProcess', views.salaryProcess),\n path('jobProcess', views.jobProcess),\n path('locationProcess', views.locationProcess),\n path('companyProcess', views.companyProcess),\n path('experienceProcess', views.experienceProcess),\n # END OF LEFT FILTER\n\n # ARTICLE\n path('allJobsProcess', views.allJobsProcess),\n path('newestJobsProcess', views.newestJobsProcess),\n path('saveJobProcess/<id>', views.saveJob),\n # END OF ARTICLE\n\n # RIGHT ASIDE\n\n # END OF RIGHT ASIDE\n\n # END OF DASHBOARD\n\n # SAVED JOBS\n path('removeFromSavedlistProcess/<id>', views.removeFromSavedListProcess),\n path('mySavedJobsTemplate', views.mySavedJobsTemplate),\n # END OF SAVED JOBS\n\n # ADMIN\n path('adminTemplate', views.adminTemplate),\n path('addJobProcess', views.addJobProcess),\n path('viewUsersTemplate', views.viewUsersTemplate),\n path('viewAdminsTemplate', views.viewAdminsTemplate),\n]\n"
},
{
"alpha_fraction": 0.610181987285614,
"alphanum_fraction": 0.6222331523895264,
"avg_line_length": 34.9822998046875,
"blob_id": "10fa4ff617b511e5f72bf31e962f837168b976c4",
"content_id": "a4acb1161ef61c9e766ebf534c3c6b39f7080710",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4066,
"license_type": "no_license",
"max_line_length": 94,
"num_lines": 113,
"path": "/jobboard_app/models.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "from __future__ import unicode_literals\nfrom django.db import models\nfrom datetime import datetime\nimport re\n\nnow = str(datetime.now())\nEMAILREGEX = re.compile(r'^[a-zA-Z0-9.+-]+@[a-zA-Z0-9_.+-]+.[a-zA-Z]+$')\n\nclass UserManager(models.Manager):\n\n def login_validator(self, postData):\n print(\" i am in login validator-------!!!!!!!\")\n print(\"POSTDATA is\", postData)\n errors = {}\n \n #Email Validation\n if len(postData[\"login_email\"]) < 1:\n print(\" I am in less than 1 letter of email\")\n errors[\"email\"] = \"email is required\"\n elif not EMAILREGEX.match(postData['login_email']):\n errors['email']= \"Email Address not valid\"\n elif not User.objects.filter(email = postData[\"login_email\"]):\n errors[\"email\"] = \"This email does not exist. Please register!\"\n\n #Password Validation\n if len(postData['login_password']) < 1:\n errors['password'] = \"password is required\"\n\n return errors\n\n# registration validator here\n def reg_validator(self, postData):\n print(\" i am in reg validator-------!!!!!!!\")\n print(\"POSTDATA is\", postData)\n errors = {}\n \n if len(postData[\"name\"]) < 1:\n errors[\"name\"] = \"name is required\"\n\n #Email Validation\n if len(postData[\"email\"]) < 1:\n print(\" I am in less than 1 letter of email\")\n errors[\"email\"] = \"email is required\"\n elif not EMAILREGEX.match(postData['email']):\n errors['email']= \"Email Address not valid\"\n elif User.objects.filter(email = postData[\"email\"]):\n errors[\"email\"] = \"This email is already registered. Please log in!\"\n elif postData['password'] != postData['confirm_password']:\n errors[\"password_no_match\"] = \"Passwords do not match\"\n\n #Password Validation\n if len(postData['password']) < 1:\n errors['password'] = \"password is required\"\n return errors\n\n\n# Create your models here.\nclass User(models.Model):\n first_name = models.CharField(max_length=255, default=\"\")\n last_name = models.CharField(max_length=255, default=\"\")\n email = models.CharField(max_length=255, default=\"\")\n password = models.CharField(max_length=255, default=\"\")\n admin = models.BooleanField(max_length=255, default=False)\n\n created_at = models.DateTimeField(auto_now_add = True)\n updated_at = models.DateTimeField(auto_now = True)\n \n\n objects = UserManager()\n\n\nclass JobManager(models.Manager):\n def basic_validator(self, postData):\n print(\"POSTDATA is: \", postData)\n errors = {}\n #destination validation\n # if len(postData[\"destination\"]) < 1:\n # errors[\"destination\"] = \"destination is required\"\n \n # #description validation\n # if len(postData[\"desc\"]) < 1:\n # errors[\"desc\"] = \"desc is required\"\n\n print(\"About to return from basic validator\")\n return errors\n\n\nclass Job(models.Model):\n company_name = models.CharField(max_length=255, default=\"\")\n company_location = models.CharField(max_length=255, default=\"\")\n job_description = models.CharField(max_length=255, default=\"\")\n job_technology = models.CharField(max_length=255, default=\"\")\n POC_name = models.CharField(max_length=255, default=\"\")\n POC_email = models.CharField(max_length=255, default=\"\")\n destination = models.CharField(max_length=255, default=\"\")\n\n created_at = models.DateTimeField(auto_now_add = True)\n updated_at = models.DateTimeField(auto_now = True)\n \n\n #ONE TO MANY RELATIONSHIP\n added_by = models.ForeignKey(User, related_name=\"jobs\", on_delete=models.CASCADE)\n\n objects = JobManager()\n\n #represent method\n def __repr__(self):\n return f\"Job: {self.id} {self.comp_name}\"\n\n#MANY TO MANY RELATIONSHIP\nclass Saved(models.Model):\n user = models.ForeignKey(User, related_name=\"user_saving_jobs\", on_delete=models.CASCADE)\n job = models.ForeignKey(Job, related_name=\"jobs_saved_by_users\", on_delete=models.CASCADE)\n"
},
{
"alpha_fraction": 0.520686149597168,
"alphanum_fraction": 0.5418769121170044,
"avg_line_length": 37.11538314819336,
"blob_id": "8467cb7ca91d44443a7f00917579e301f6fc4994",
"content_id": "b8b2342493eaa0078ee675f512d64ffe6934872b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1982,
"license_type": "no_license",
"max_line_length": 127,
"num_lines": 52,
"path": "/jobboard_app/migrations/0001_initial.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "# Generated by Django 2.1.2 on 2018-10-24 18:26\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n initial = True\n\n dependencies = [\n ]\n\n operations = [\n migrations.CreateModel(\n name='Job',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('comp_name', models.CharField(max_length=255)),\n ('comp_loc', models.CharField(max_length=255)),\n ('job_desc', models.CharField(max_length=255)),\n ('job_tech', models.CharField(max_length=255)),\n ('POC_name', models.CharField(max_length=255)),\n ('POC_email', models.CharField(max_length=255)),\n ],\n ),\n migrations.CreateModel(\n name='Joint',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('job', models.ForeignKey(on_delete='DO NOTHING', related_name='jobs_joined_by_users', to='jobboard_app.Job')),\n ],\n ),\n migrations.CreateModel(\n name='User',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('name', models.CharField(max_length=255)),\n ('email', models.CharField(max_length=255)),\n ('password', models.CharField(max_length=255)),\n ],\n ),\n migrations.AddField(\n model_name='joint',\n name='user',\n field=models.ForeignKey(on_delete='DO NOTHING', related_name='user_joining_jobs', to='jobboard_app.User'),\n ),\n migrations.AddField(\n model_name='job',\n name='added_by',\n field=models.ForeignKey(on_delete='DO NOTHING', related_name='jobs', to='jobboard_app.User'),\n ),\n ]\n"
},
{
"alpha_fraction": 0.3260954022407532,
"alphanum_fraction": 0.35707804560661316,
"avg_line_length": 37.002464294433594,
"blob_id": "f4887b25e413050ff2d5097e4a5b952200ca8798",
"content_id": "0d13da0735f636c08e207bf260fde08d6805e040",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 15428,
"license_type": "no_license",
"max_line_length": 248,
"num_lines": 406,
"path": "/jobboard_app/views.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "from django.shortcuts import render, redirect, HttpResponse\nfrom .models import *\nfrom django.contrib import messages\nimport bcrypt\n\n\"\"\"\n.##........#######...######...####.##....##..........##....########..########..######...####..######..########.########.########.\n.##.......##.....##.##....##...##..###...##.........##.....##.....##.##.......##....##...##..##....##....##....##.......##.....##\n.##.......##.....##.##.........##..####..##........##......##.....##.##.......##.........##..##..........##....##.......##.....##\n.##.......##.....##.##...####..##..##.##.##.......##.......########..######...##...####..##...######.....##....######...########.\n.##.......##.....##.##....##...##..##..####......##........##...##...##.......##....##...##........##....##....##.......##...##..\n.##.......##.....##.##....##...##..##...###.....##.........##....##..##.......##....##...##..##....##....##....##.......##....##.\n.########..#######...######...####.##....##....##..........##.....##.########..######...####..######.....##....########.##.....##\n\"\"\"\n\ndef index(request):\n\n # User.objects.all().delete()\n # Job.objects.all().delete()\n\n return redirect('/homeTemplate')\n\n# TEMPLATE\ndef home(request):\n\n return render(request, \"index.html\")\n\n\n# PROCESS\ndef resetSessions(request):\n print(\"i made it to reset\")\n request.session.clear()\n return redirect(\"/\")\n\n# PROCESS\ndef register(request):\n print(\" i am in register!! yay\")\n\n #<<--------VALIDATIONS-------->>\n errors = User.objects.reg_validator(request.POST)\n if len(errors):\n # if the errors object contains anything, loop through each key-value pair and make a flash message\n for key, value in errors.items():\n messages.error(request, value)\n \n print(errors)\n \n print(\"done with register if\")\n\n # redirect the user back to the form to fix the errors\n return redirect('/homeTemplate')\n else:\n hash_brown = bcrypt.hashpw(request.POST['password'].encode(), bcrypt.gensalt())\n # Check for any users, if not make the first user an admin\n print (\"Total users are:\", User.objects.count())\n if User.objects.count() == 0:\n user = User.objects.create(first_name = request.POST['name'], last_name = request.POST['name'], email = request.POST['email'], password = hash_brown.decode(\"utf-8\"), admin = True)\n print(\"New Admin Created!\")\n\n #store user id in session\n request.session['id'] = user.id\n request.session['first_name'] = user.first_name\n\n return redirect('/adminTemplate')\n else:\n user = User.objects.create(first_name = request.POST['name'], last_name = request.POST['name'], email = request.POST['email'], password = hash_brown.decode(\"utf-8\"))\n print(\"New User Created!\")\n\n #store user id in session\n request.session['id'] = user.id\n request.session['first_name'] = user.first_name\n\n return redirect('/dashboardTemplate')\n\n# PROCESS\ndef login(request):\n\n errors = User.objects.login_validator(request.POST)\n print(errors)\n\n if len(errors):\n # if the errors object contains anything, loop through each key-value pair and make a flash message\n for key, value in errors.items():\n messages.error(request, value)\n \n print(errors)\n # redirect the user back to the form to fix the errors\n return redirect('/homeTemplate')\n else:\n user = User.objects.get(email=request.POST['login_email'])\n if bcrypt.checkpw(request.POST['login_password'].encode(), user.password.encode()):\n print(\"password match\")\n # HAVE A CHECK FOR ADMIN OR USER\n request.session['id'] = user.id\n request.session['first_name']=user.first_name\n return redirect(\"/dashboardTemplate\")\n else:\n print(\"failed password\")\n messages.error(request, \"Wrong password\")\n\n return redirect('/homeTemplate')\n\n\n\"\"\"\n.########.##....##.########......#######..########....##........#######...######............##....########..########..######..\n.##.......###...##.##.....##....##.....##.##..........##.......##.....##.##....##..........##.....##.....##.##.......##....##.\n.##.......####..##.##.....##....##.....##.##..........##.......##.....##.##...............##......##.....##.##.......##.......\n.######...##.##.##.##.....##....##.....##.######......##.......##.....##.##...####.......##.......########..######...##...####\n.##.......##..####.##.....##....##.....##.##..........##.......##.....##.##....##.......##........##...##...##.......##....##.\n.##.......##...###.##.....##....##.....##.##..........##.......##.....##.##....##......##.........##....##..##.......##....##.\n.########.##....##.########......#######..##..........########..#######...######......##..........##.....##.########..######..\n\"\"\"\n\n\n\n\n\n\n\n\n\n\n\"\"\"\n.########.....###.....######..##.....##.########...#######.....###....########..########.\n.##.....##...##.##...##....##.##.....##.##.....##.##.....##...##.##...##.....##.##.....##\n.##.....##..##...##..##.......##.....##.##.....##.##.....##..##...##..##.....##.##.....##\n.##.....##.##.....##..######..#########.########..##.....##.##.....##.########..##.....##\n.##.....##.#########.......##.##.....##.##.....##.##.....##.#########.##...##...##.....##\n.##.....##.##.....##.##....##.##.....##.##.....##.##.....##.##.....##.##....##..##.....##\n.########..##.....##..######..##.....##.########...#######..##.....##.##.....##.########.\n\"\"\"\n\n# TEMPLATE\ndef dashboard(request):\n\n # my_jobs = Saved.objects.filter(user_id = request.session['id'])\n # my_jobs2 = Job.objects.filter(added_by_user= request.session['name'])\n\n # context = {\n # \"my_jobs\" : my_jobs, \"my_jobs2\":my_jobs2, \"jobs\" : Job.objects.exclude(added_by_user = request.session['name'])\n # }\n\n # Checks if signed in or not\n if \"id\" in request.session:\n\n context = {\n \"jobs\": Job.objects.all(),\n \"savedjobs\": Saved.objects.filter(user_id = request.session['id']),\n }\n\n return render(request,\"dashboard.html\", context=context)\n \n else:\n return HttpResponse(\"You are not signed in!! Your cookie was deleted!\")\n\n\n# what is this doing???????\n# PROCESS\ndef remove(request,id):\n print(\" i made it to delete!!!!!!!!\")\n print(\"this is my id: \", id)\n # b = Wish.objects.filter(id = int(id))\n\n # Wish.objects.raw(\"delete from wish_list_app_wish where id = \"+id) \n \n job_to_remove = Job.objects.filter(id=id)\n # print(job_to_remove.delete)\n \n job_to_remove.delete()\n print(\" -=-=-=-=-=--=-=-=-=-=--=-=-=-=-=--=-=-=-=-=-==\")\n \n return redirect(\"/dashboardTemplate\")\n\n\"\"\"\n88 888888 888888 888888 888888 88 88 888888 888888 88\"\"Yb\n88 88__ 88__ 88 88__ 88 88 88 88__ 88__dP\n88 .o 88\"\" 88\"\" 88 88\"\" 88 88 .o 88 88\"\" 88\"Yb\n88ood8 888888 88 88 88 88 88ood8 88 888888 88 Yb\n\"\"\"\n\ndef sortByProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef distanceProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef salaryProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef jobProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef locationProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef companyProcess(request):\n return redirect(\"/dashboardTemplate\")\n\ndef experienceProcess(request):\n return redirect(\"/dashboardTemplate\")\n\n\"\"\"\n888888 88b 88 8888b. dP\"Yb 888888 88 888888 888888 888888 888888 88 88 888888 888888 88\"\"Yb\n88__ 88Yb88 8I Yb dP Yb 88__ 88 88__ 88__ 88 88__ 88 88 88 88__ 88__dP\n88\"\" 88 Y88 8I dY Yb dP 88\"\" 88 .o 88\"\" 88\"\" 88 88\"\" 88 88 .o 88 88\"\" 88\"Yb\n888888 88 Y8 8888Y\" YbodP 88 88ood8 888888 88 88 88 88 88ood8 88 888888 88 Yb\n\"\"\"\n\n\n\n\n\n\"\"\"\n 88888 dP\"Yb 88\"\"Yb 88\"\"Yb dP\"Yb .dP\"Y8 888888 88 88b 88 dP\"\"b8 .dP\"Y8\n 88 dP Yb 88__dP 88__dP dP Yb `Ybo.\" 88 88 88Yb88 dP `\" `Ybo.\"\no. 88 Yb dP 88\"\"Yb 88-\"\" Yb dP o.`Y8b 88 88 88 Y88 Yb \"88 o.`Y8b\n\"bodP' YbodP 88oodP 88 YbodP 8bodP' 88 88 88 Y8 YboodP 8bodP'\n\"\"\"\n\n# PROCESS\ndef allJobsProcess(request):\n return redirect(\"/dashboardTemplate\") \n\n# PROCESS\ndef newestJobsProcess(request):\n return redirect(\"/dashboardTemplate\") \n\n\n# PROCESS\ndef saveJob(request,id):\n print(\"this is my real job_id: \", id)\n user = User.objects.get(id=request.session[\"id\"])\n print(\"this is my user: \", user.name)\n\n job = Job.objects.get(id=id)\n print(\"this is my job: \", job.id)\n\n new_job = Saved(job=job, user = user)\n new_job.save()\n print(\"this is my new job:\", new_job)\n\n return redirect('/dashboardTemplate')\n\n\n\"\"\"\n888888 88b 88 8888b. dP\"Yb 888888 88888 dP\"Yb 88\"\"Yb 88\"\"Yb dP\"Yb .dP\"Y8 888888 88 88b 88 dP\"\"b8 .dP\"Y8\n88__ 88Yb88 8I Yb dP Yb 88__ 88 dP Yb 88__dP 88__dP dP Yb `Ybo.\" 88 88 88Yb88 dP `\" `Ybo.\"\n88\"\" 88 Y88 8I dY Yb dP 88\"\" o. 88 Yb dP 88\"\"Yb 88-\"\" Yb dP o.`Y8b 88 88 88 Y88 Yb \"88 o.`Y8b\n888888 88 Y8 8888Y\" YbodP 88 \"bodP' YbodP 88oodP 88 YbodP 8bodP' 88 88 88 Y8 YboodP 8bodP'\n\"\"\"\n\n\n\n\n\"\"\"\n.########.##....##.########......#######..########....########.....###.....######..##.....##.########...#######.....###....########..########.\n.##.......###...##.##.....##....##.....##.##..........##.....##...##.##...##....##.##.....##.##.....##.##.....##...##.##...##.....##.##.....##\n.##.......####..##.##.....##....##.....##.##..........##.....##..##...##..##.......##.....##.##.....##.##.....##..##...##..##.....##.##.....##\n.######...##.##.##.##.....##....##.....##.######......##.....##.##.....##..######..#########.########..##.....##.##.....##.########..##.....##\n.##.......##..####.##.....##....##.....##.##..........##.....##.#########.......##.##.....##.##.....##.##.....##.#########.##...##...##.....##\n.##.......##...###.##.....##....##.....##.##..........##.....##.##.....##.##....##.##.....##.##.....##.##.....##.##.....##.##....##..##.....##\n.########.##....##.########......#######..##..........########..##.....##..######..##.....##.########...#######..##.....##.##.....##.########.\n\"\"\"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\"\"\"\n..######.....###....##.....##.########.########...........##..#######..########...######.\n.##....##...##.##...##.....##.##.......##.....##..........##.##.....##.##.....##.##....##\n.##........##...##..##.....##.##.......##.....##..........##.##.....##.##.....##.##......\n..######..##.....##.##.....##.######...##.....##..........##.##.....##.########...######.\n.......##.#########..##...##..##.......##.....##....##....##.##.....##.##.....##.......##\n.##....##.##.....##...##.##...##.......##.....##....##....##.##.....##.##.....##.##....##\n..######..##.....##....###....########.########......######...#######..########...######.\n\"\"\"\n\n# TEMPLATE\ndef mySavedJobsTemplate(request):\n\n context = {\n \"jobs\": Job.objects.all(),\n \"savedjobs\": Saved.objects.filter(user_id = request.session['id']),\n }\n\n return render(request,\"mysavedjobs.html\", context=context)\n\n# PROCESS\ndef removeFromSavedListProcess(request,id):\n print(\" i made it to RemoveFromSavedlist !!!!!!!!\")\n\n job_to_remove = Saved.objects.get(id=id)\n print(\"this is the id i'm trying to remove:\" ,id)\n job_to_remove.delete()\n print(\"it's done! it's gone-=-=-=--=-=-==--==--=-=-=--=-=-==--==---=-=-=--=-=-==--==-- koala -\")\n\n return redirect(\"/dashboardTemplate\")\n\n# what is this doing???????\n# TEMPLATE\ndef job(request, id):\n\n job_row = Job.objects.get(id = id)\n # job_row.added_by_id\n first_name_row = User.objects.get ( id = job_row.added_by_id)\n context = {\n \"my_job\": Job.objects.get(id = id),\n \"Other_Users_On_Job\": Saved.objects.filter(job_id= id),\n \"first_name_row\": first_name_row\n }\n\n return render(request, \"job.html\", context=context)\n\n\"\"\"\n.########.##....##.########......#######..########.....######.....###....##.....##.########.########...........##..#######..########...######.\n.##.......###...##.##.....##....##.....##.##..........##....##...##.##...##.....##.##.......##.....##..........##.##.....##.##.....##.##....##\n.##.......####..##.##.....##....##.....##.##..........##........##...##..##.....##.##.......##.....##..........##.##.....##.##.....##.##......\n.######...##.##.##.##.....##....##.....##.######.......######..##.....##.##.....##.######...##.....##..........##.##.....##.########...######.\n.##.......##..####.##.....##....##.....##.##................##.#########..##...##..##.......##.....##....##....##.##.....##.##.....##.......##\n.##.......##...###.##.....##....##.....##.##..........##....##.##.....##...##.##...##.......##.....##....##....##.##.....##.##.....##.##....##\n.########.##....##.########......#######..##...........######..##.....##....###....########.########......######...#######..########...######.\n\"\"\"\n\n\n\n\n\n\n\n\n\n\n\n\n\"\"\"\n....###....########..##.....##.####.##....##\n...##.##...##.....##.###...###..##..###...##\n..##...##..##.....##.####.####..##..####..##\n.##.....##.##.....##.##.###.##..##..##.##.##\n.#########.##.....##.##.....##..##..##..####\n.##.....##.##.....##.##.....##..##..##...###\n.##.....##.########..##.....##.####.##....##\n\"\"\"\n\n# TEMPLATE\ndef adminTemplate(request):\n return render(request, \"admin.html\")\n\n# TEMPLATE\ndef addJobTemplate(request):\n return render(request, \"Add_Job.html\")\n\n# TEMPLATE\ndef viewUsersTemplate(request):\n context = {\n \n }\n return render(request, \"viewusers.html\")\n\ndef viewAdminsTemplate(request):\n context = {\n\n }\n return render(request, \"viewusers.html\")\n\n# PROCESS\ndef addJobProcess(request):\n\n #<<--------VALIDATIONS-------->>\n errors = Job.objects.basic_validator(request.POST)\n\n if len(errors):\n for key, value in errors.items():\n messages.error(request, value)\n \n print(errors)\n # redirect the user back to the form to fix the errors\n return redirect('/addJobTemplate')\n \n else:\n new_job = Job(comp_name = request.POST[\"comp_name\"], comp_loc = request.POST[\"comp_loc\"], job_desc = request.POST[\"job_desc\"], job_tech = request.POST[\"job_tech\"], POC_name = request.POST[\"POC_name\"], POC_email = request.POST[\"POC_email\"], \n added_by = User.objects.get(id=request.session[\"id\"]) )\n \n new_job.save()\n\n print(\" i just created a new job!\")\n return redirect(\"/dashboardTemplate\")\n\n\"\"\"\n.########.##....##.########......#######..########.......###....########..##.....##.####.##....##\n.##.......###...##.##.....##....##.....##.##............##.##...##.....##.###...###..##..###...##\n.##.......####..##.##.....##....##.....##.##...........##...##..##.....##.####.####..##..####..##\n.######...##.##.##.##.....##....##.....##.######......##.....##.##.....##.##.###.##..##..##.##.##\n.##.......##..####.##.....##....##.....##.##..........#########.##.....##.##.....##..##..##..####\n.##.......##...###.##.....##....##.....##.##..........##.....##.##.....##.##.....##..##..##...###\n.########.##....##.########......#######..##..........##.....##.########..##.....##.####.##....##\n\"\"\""
},
{
"alpha_fraction": 0.7653061151504517,
"alphanum_fraction": 0.7653061151504517,
"avg_line_length": 18.600000381469727,
"blob_id": "55351e9808c22da4d71182fecfd3abd8d4be40de",
"content_id": "f1f6d9e6334c31283ebc4b7bc75970e87f2de924",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 98,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 5,
"path": "/jobboard_app/apps.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "from django.apps import AppConfig\n\n\nclass JobboardAppConfig(AppConfig):\n name = 'jobboard_app'\n"
},
{
"alpha_fraction": 0.5128384828567505,
"alphanum_fraction": 0.5284780859947205,
"avg_line_length": 31.454545974731445,
"blob_id": "86ece1be71145275e0822549aa60303ab538a2cd",
"content_id": "6cb912396ad2b843d04ac46ffc312845475a32cd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4284,
"license_type": "no_license",
"max_line_length": 140,
"num_lines": 132,
"path": "/jobboard_app/migrations/0003_auto_20181025_2333.py",
"repo_name": "DavidMLink/JobListings",
"src_encoding": "UTF-8",
"text": "# Generated by Django 2.1.2 on 2018-10-26 03:33\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\nimport django.utils.timezone\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('jobboard_app', '0002_auto_20181024_2346'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='job',\n name='comp_loc',\n ),\n migrations.RemoveField(\n model_name='job',\n name='comp_name',\n ),\n migrations.RemoveField(\n model_name='job',\n name='job_desc',\n ),\n migrations.RemoveField(\n model_name='job',\n name='job_tech',\n ),\n migrations.RemoveField(\n model_name='user',\n name='name',\n ),\n migrations.AddField(\n model_name='job',\n name='company_location',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='job',\n name='company_name',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='job',\n name='created_at',\n field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now),\n preserve_default=False,\n ),\n migrations.AddField(\n model_name='job',\n name='destination',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='job',\n name='job_description',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='job',\n name='job_technology',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='job',\n name='updated_at',\n field=models.DateTimeField(auto_now=True),\n ),\n migrations.AddField(\n model_name='user',\n name='admin',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='user',\n name='created_at',\n field=models.DateTimeField(auto_now_add=True, default=django.utils.timezone.now),\n preserve_default=False,\n ),\n migrations.AddField(\n model_name='user',\n name='first_name',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='user',\n name='last_name',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AddField(\n model_name='user',\n name='updated_at',\n field=models.DateTimeField(auto_now=True),\n ),\n migrations.AlterField(\n model_name='job',\n name='POC_email',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AlterField(\n model_name='job',\n name='POC_name',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AlterField(\n model_name='job',\n name='added_by',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='jobs', to='jobboard_app.User'),\n ),\n migrations.AlterField(\n model_name='saved',\n name='job',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='jobs_saved_by_users', to='jobboard_app.Job'),\n ),\n migrations.AlterField(\n model_name='saved',\n name='user',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='user_saving_jobs', to='jobboard_app.User'),\n ),\n migrations.AlterField(\n model_name='user',\n name='email',\n field=models.CharField(default='', max_length=255),\n ),\n migrations.AlterField(\n model_name='user',\n name='password',\n field=models.CharField(default='', max_length=255),\n ),\n ]\n"
}
] | 6
|
106-NCHU-MIS-Project/2017-Summer-Training
|
https://github.com/106-NCHU-MIS-Project/2017-Summer-Training
|
3456ac2d55a69642bef9e321621c5ff25385bfdc
|
55ed6d54fef8a05cae84f563915ba3cbb5de7ba4
|
8c6cab8c1bdf431e252d29c2398bea424ce67d6d
|
refs/heads/master
| 2020-12-03T00:08:28.354471
| 2017-07-30T13:22:03
| 2017-07-30T13:22:03
| 95,993,186
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8266423344612122,
"alphanum_fraction": 0.8412408828735352,
"avg_line_length": 19.076923370361328,
"blob_id": "6d4b5e186c6298b4fa2f84bd5ffcfa8242605c43",
"content_id": "78b248e7fab42fc6945652a20a0988798de8d2b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1114,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 26,
"path": "/David/README.md",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "# Webduino\r\nhttps://baboom3126.github.io/chattingRoom/sound.html\r\nwebduino網站上的教學都測試了一次\r\n拉出來打包成app的練習\r\n用蜂鳴器做一個很簡單的鋼琴\r\n了解javascript控制sensor的那些語法和步驟\r\n\r\n# Firebase\r\nhttps://baboom3126.github.io/chattingRoom/chatroom.html\r\n從頭自製匿名聊天室 打包成app 技術很簡單\r\n不過與到一個小問題\r\non()應該是要資料庫數據變化才會執行\r\n但是剛開網頁就會自己執行一次了\r\n比對googleMap之前的教學範例複製過來\r\n第一次開始也是直接執行了\r\n雖然可以用if控制第一次不執行 但想知道問題出在哪\r\n\r\n# 專題想法\r\n學長做的智慧門鎖之前就有想做類似的應用\r\n因為NFC越來越普及 相關應用很廣泛\r\n如果能把所有NFC的卡片ID都讀進手機\r\n手機再直接取代卡片 去做刷卡的動作\r\n概念類似電子錢包 一個手機有一堆卡的功能\r\n搜google只有看到有一個類似的程式做得到 (TagInfo)\r\n但是很粗糙 而且需要root才能做到\r\n簡單來說 手機取代所有NFC卡片不知道能否實現\r\n"
},
{
"alpha_fraction": 0.649350643157959,
"alphanum_fraction": 0.701298713684082,
"avg_line_length": 14.199999809265137,
"blob_id": "cbde903cb555ef71d771e4056157c4422c6dbae5",
"content_id": "33c77b0a7e96d84845ccbd198be4d32f7c0468dc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 151,
"license_type": "no_license",
"max_line_length": 51,
"num_lines": 5,
"path": "/jiu/README.md",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "# 7/3 - 7/9\n\n熟悉Ai操作. \n\n上網看了排版相關影片, 發現很多都有用到Dreamweaver, 再看看是不是有必要來學一下這個///\n\n"
},
{
"alpha_fraction": 0.633726179599762,
"alphanum_fraction": 0.6436989903450012,
"avg_line_length": 43.119998931884766,
"blob_id": "a48ee782a32a7b7d1e4805881d35bd30e53a7a65",
"content_id": "238db89c3fd0d181380e529948914541a058abed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1103,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 25,
"path": "/cabao/Crawler/apple/apple/spiders/crawler.py",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "import scrapy\nfrom bs4 import BeautifulSoup\nfrom apple.items import AppleItem\nfrom scrapy.spiders import CrawlSpider, Rule\nfrom scrapy.linkextractors import LinkExtractor\nclass AppleCrawler(CrawlSpider):\n name = 'apple'\n start_urls = ['http://www.appledaily.com.tw/realtimenews/section/new/']\n rules = [\n Rule(LinkExtractor(allow=('/realtimenews/section/new/[1-3]$')), callback='parse_list', follow=True)\n ]\n def parse_list(self, response):\n domain = 'http://www.appledaily.com.tw'\n res = BeautifulSoup(response.body)\n for news in res.select('.rtddt'):\n # print news.select('h1')[0].text\n # print domain + news.select('a')[0]['href']\n yield scrapy.Request(domain + news.select('a')[0]['href'], self.parse_detail)\n def parse_detail(self, response):\n res = BeautifulSoup(response.body)\n appleItem = AppleItem()\n appleItem['title'] = res.select('#h1')[0].text\n appleItem['content'] = res.select('.trans')[0].text\n appleItem['time'] = res.select('.gggs time')[0].text\n return appleItem\n"
},
{
"alpha_fraction": 0.6200274229049683,
"alphanum_fraction": 0.6625514626502991,
"avg_line_length": 29.375,
"blob_id": "68c83e5d77498018c5f5801d7c1439a6f00509f3",
"content_id": "8354bd5d79a0dcccefc7ec9d43d3c30ea1576735",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 857,
"license_type": "no_license",
"max_line_length": 124,
"num_lines": 24,
"path": "/cabao/README.md",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "# 7/3 - 7/9\n\n這週因為比較多事情，所以進度較少。\n主要以學習 Perl 為主，還有練習寫 Blog ( ? \n期望下週能完成到 regex 的部份 XD \n[Repo Link](https://github.com/Perl-learning)\n\n---\n\n## Perl\n\n|Title|Source code links|Blog links|\n|-----------|-------------------------------|------------------------------|\n|Introdution|https://github.com/Perl-learning/CH1-Introduction|http://camel-perl-trip.blogspot.tw/2017/07/introduction.html|\n|Scalar|https://github.com/Perl-learning/CH2-Scalar|http://camel-perl-trip.blogspot.tw/2017/07/scalar.html|\n|List&Array|https://github.com/Perl-learning/CH3-List-Array|http://camel-perl-trip.blogspot.tw/2017/07/list.html| \n\n---\n\n## Misc.\n\n翻書發現的Paper.js \nhttps://camel-summer-training.blogspot.tw/2017/07/paperjs.html \n不知道將來會不會用到，不過還是先收著 XD\n"
},
{
"alpha_fraction": 0.5525000095367432,
"alphanum_fraction": 0.6700000166893005,
"avg_line_length": 24,
"blob_id": "1a6a7b64d70d498a165871cecc7fe1f3d00a0e34",
"content_id": "86ad66720b0cae3555727e17e45a648f9b7532b0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 418,
"license_type": "no_license",
"max_line_length": 92,
"num_lines": 16,
"path": "/README.md",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "# 2017-Summer-Training\n\n|Name|Link|\n|------|------|\n|許達夫 (cabao)|https://github.com/106-NCHU-MIS-Project/2017-Summer-Training/tree/master/cabao|\n|吳品融 (jiu)|https://github.com/106-NCHU-MIS-Project/2017-Summer-Training/tree/master/jiu|\n|郝大為(David)|https://github.com/106-NCHU-MIS-Project/2017-Summer-Training/tree/master/David|\n|Name|Link|\n\n## 7/3 - 7/9\n\n## 7/10 - 7/16\n\n## 7/17 - 7/23\n\n## 7/24 - 7/30\n"
},
{
"alpha_fraction": 0.71856290102005,
"alphanum_fraction": 0.7245509028434753,
"avg_line_length": 17.55555534362793,
"blob_id": "7356b70ae4cc2d5f2462dee8b42fd8f613ec453d",
"content_id": "83162119b5859d23e53b9e9a0719453ed876f0ee",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 438,
"license_type": "no_license",
"max_line_length": 93,
"num_lines": 18,
"path": "/cabao/Crawler/README.md",
"repo_name": "106-NCHU-MIS-Project/2017-Summer-Training",
"src_encoding": "UTF-8",
"text": "# Scrapy - 以蘋果新聞為例\n[Scrapy Document](https://docs.scrapy.org/en/latest/)\n## Requirements\n* bs4\n`pip install bs4`\n\n## Installation\n```shell=\npip install scrapy\n```\n\n## Usage\n\n```shell=\ncd ./apple\nscrapy crawl apple -o apple.json -t json\n```\n最後會輸出一個 apple.json ，可以發現這個output 會依照我在 items.py 中定義的 Schema 儲存，而這個file會以unicode編碼，可以再進行後續的處理。\n"
}
] | 6
|
saketrule/Interpreter_Scala
|
https://github.com/saketrule/Interpreter_Scala
|
4d7d6892cc66af171c10ede9eae416cbd45efe49
|
42b3efa603b57dedbff226ac84825d6efcfc7e39
|
b3904c5dc542ddcf732b19519d477e93398104ca
|
refs/heads/master
| 2021-01-21T05:09:44.610449
| 2017-02-25T14:11:23
| 2017-02-25T14:11:23
| 83,135,930
| 3
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5958333611488342,
"alphanum_fraction": 0.5972222089767456,
"avg_line_length": 25.20754623413086,
"blob_id": "bdb85dbff01551434487acac63344d8be7806bba",
"content_id": "2e25669730bc42a5dc86992f55550dd052d445f4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1440,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 53,
"path": "/parsers.py",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "import sys\r\nfrom basic_parser_combinators import *\r\nfrom base_parsers import *\r\nfrom lexer_tokens import *\r\n\r\ndef expr():\r\n return inFixExpr()\r\n \r\ndef inFixExpr():\r\n ##add prefix expression\r\n ##add super postfix\r\n return litExp()\r\n \r\ndef litExp():\r\n return precedence(aexp_term(),\r\n aexp_precedence_levels,\r\n infix_num_op)\r\n \r\ndef aexp_term():\r\n return numLit() | aexp_group()\r\n \r\ndef numLit():\r\n return intLit() | floatLit()\r\n \r\ndef intLit():\r\n return Tag(INT) ^ (lambda i: IntLit(int(i)))\r\n \r\ndef floatLit():\r\n return Tag(FLOAT) ^ (lambda i: FloatLit(float(i)))\r\n\r\ndef aexp_group():\r\n return Reserved('(',PAREN) + Lazy(litExp) + Reserved(')',PAREN) ^ process_group\r\n\r\n\r\ndef precedence(value_parser, precedence_levels, combine):\r\n def op_parser(precedence_level):\r\n return any_operator_in_list(precedence_level) ^ combine\r\n parser = value_parser * op_parser(precedence_levels[0])\r\n for precedence_level in precedence_levels[1:]:\r\n parser = parser * op_parser(precedence_level)\r\n return parser\r\n \r\ndef any_operator_in_list(ops):\r\n op_parsers = [Reserved(op,OPCHAR) for op in ops]\r\n parser = reduce(lambda l, r: l | r, op_parsers)\r\n return parser\r\n \r\ndef process_group(parsed):\r\n ((_, p), _) = parsed\r\n return p\r\n \r\ndef infix_num_op(op):\r\n return (lambda l,r : InfixNumOp(l,op,r))"
},
{
"alpha_fraction": 0.32024598121643066,
"alphanum_fraction": 0.3240302801132202,
"avg_line_length": 35.122806549072266,
"blob_id": "a3a914a75976d19d9752a8adb9140c4f26229490",
"content_id": "8acaed7539cdbe78e789ecda1f57b4a77b2bb828",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2114,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 57,
"path": "/lexer_tokens.py",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "RESERVED = 'RESERVED'\r\nLITERAL = 'LITERAL'\r\nCHAR = 'CHAR'\r\nSTRING = 'STRING'\r\nBOOL = 'BOOL'\r\nINT = 'INT'\r\nFLOAT = 'FLOAT'\r\nSTRING = 'STRING'\r\nID = 'ID'\r\nDATATYPE = 'DATATYPE'\r\nSEMI = 'SEMI'\r\nPAREN = 'PAREN'\r\nCOMPARE = 'COMPARE'\r\nCOMMENT = 'COMMENT'\r\nOPCHAR = 'OPCHAR'\r\nQUALID = 'QUALID'\r\n\r\ntokens = [\r\n (r'and', RESERVED),\r\n (r'or', RESERVED),\r\n (r'not', RESERVED),\r\n (r'if', RESERVED),\r\n (r'else', RESERVED),\r\n (r'while ', RESERVED),\r\n (r'do', RESERVED), \r\n (r'val', RESERVED),\r\n (r'var', RESERVED),\r\n \r\n (r'String', DATATYPE), ## May remove once implement classes\r\n (r'Int', DATATYPE),\r\n (r'Float', DATATYPE),\r\n (r'Unit', DATATYPE),\r\n (r'Double', DATATYPE),\r\n \r\n (r'[\\(\\){}\\[\\]]', PAREN),\r\n (r'\\/\\/[^\\n]*\\n*', COMMENT),\r\n (r'/\\*[^(\\*/)]*?\\*/', COMMENT), ##Can't figure out how to match /,.. ## no nested comments :<\r\n \r\n (r'object ', RESERVED),\r\n (r'def ', RESERVED),\r\n (r'main', RESERVED),\r\n (r'import', RESERVED), \r\n (r'\\'.\\'', CHAR), ## Check what . matches\r\n (r'\\\".*?\\\"', STRING),\r\n (r'-?[0-9]+', INT),\r\n (r'[0-9]*\\.[0-9]+', FLOAT),\r\n (r'(true|false)', BOOL),\r\n (r'[A-Za-z][A-Za-z0-9_]*', ID),\r\n (r'<-', OPCHAR),\r\n (r'=>', OPCHAR), ##Not sure belongs to opchar, for anonymous functions\r\n (r'<=|<|==|>|>=|!=', COMPARE),\r\n (r'[\\+\\-\\*/^\\?=]', OPCHAR),\r\n (r'\\.', QUALID), ## hAVEN'T added ,\r\n (r';', SEMI ),\r\n (r'\\n+', SEMI ),\r\n (r'[ \\n\\t]+', None ),\r\n]"
},
{
"alpha_fraction": 0.5557894706726074,
"alphanum_fraction": 0.5642105340957642,
"avg_line_length": 18.7391300201416,
"blob_id": "ae5107bdd3efbb7b0e8a696f0d08205194b66f4f",
"content_id": "ec8427ffe71e7e7b398b4cad30d52fa5d820a191",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 475,
"license_type": "no_license",
"max_line_length": 60,
"num_lines": 23,
"path": "/main.py",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "## Driver program\r\n## Written by Saket\r\n\r\nimport sys\r\n\r\nfrom lexer import *\r\nfrom parsers import *\r\n\r\ndef usage():\r\n sys.stderr.write('Provide scala filename as argument\\n')\r\n sys.exit(1)\r\n\r\nif __name__ == '__main__':\r\n if len(sys.argv) != 2:\r\n usage()\r\n filename = sys.argv[1]\r\n text = open(filename).read()\r\n tokens = scala_lex(text)\r\n print(\"Tokens found: \\n\")\r\n for x in tokens:\r\n print(x)\r\n ast = expr()(tokens,0)\r\n print(ast)"
},
{
"alpha_fraction": 0.6283783912658691,
"alphanum_fraction": 0.6351351141929626,
"avg_line_length": 14.666666984558105,
"blob_id": "3ee817a44dec873b0205004ef6e94e027179cf44",
"content_id": "1ed96eb8e00a541153ddaeaec147eed592907090",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 148,
"license_type": "no_license",
"max_line_length": 29,
"num_lines": 9,
"path": "/parser.py",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "## Parser driver program\r\n\r\nfrom parsers import *\r\n\r\ndef parse(tokens):\r\n return parser()(tokens,0)\r\n \r\ndef parser():\r\n return Phrase(expr)"
},
{
"alpha_fraction": 0.482828289270401,
"alphanum_fraction": 0.482828289270401,
"avg_line_length": 25.03636360168457,
"blob_id": "547095adf10223b0fd4f7f5c16102ec1f534b295",
"content_id": "e2cda85981fe333934235f97daa5f6ee6b3dbd7b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1485,
"license_type": "no_license",
"max_line_length": 74,
"num_lines": 55,
"path": "/base_parsers.py",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "class Literal:\r\n def __init__(self,val):\r\n self.val = val\r\n \r\n def __eval__(self,env):\r\n return self.val\r\n \r\nclass IntLit(Literal): \r\n def __repr__(self):\r\n return 'IntLit(%d) ' % self.val\r\n \r\nclass BoolLit(Literal):\r\n def __repr__(self):\r\n return 'BoolLit(%d) ' % self.val\r\n \r\nclass CharLit(Literal):\r\n def __repr__(self):\r\n return 'CharLit(%d) ' % self.val\r\n \r\nclass StringLit(Literal):\r\n def __repr__(self):\r\n return 'StringLit(%d) ' % self.val\r\n \r\nclass FloatLit(Literal):\r\n def __repr__(self):\r\n return 'FloatLit(%d) ' % self.val\r\n \r\naexp_precedence_levels = [\r\n ['*', '/'],\r\n ['+', '-'],\r\n]\r\n\r\nclass InfixNumOp():\r\n def __init__(self, op, left, right):\r\n self.op = op\r\n self.left = left\r\n self.right = right\r\n\r\n def __repr__(self):\r\n return 'Infixnumop(%s, %s, %s)' % (self.op, self.left, self.right)\r\n\r\n def eval(self, env):\r\n left_value = self.left.eval(env)\r\n right_value = self.right.eval(env)\r\n if self.op == '+':\r\n value = left_value + right_value\r\n elif self.op == '-':\r\n value = left_value - right_value\r\n elif self.op == '*':\r\n value = left_value * right_value\r\n elif self.op == '/':\r\n value = left_value / right_value\r\n else:\r\n raise RuntimeError('unknown operator: ' + self.op)\r\n return value"
},
{
"alpha_fraction": 0.828125,
"alphanum_fraction": 0.828125,
"avg_line_length": 31,
"blob_id": "b097eab32638b5c6c9b6093c29ca9c61d21dad35",
"content_id": "010c8bf1c6ace31ae4b3c95724dfef7d9c1d23d7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 64,
"license_type": "no_license",
"max_line_length": 43,
"num_lines": 2,
"path": "/README.md",
"repo_name": "saketrule/Interpreter_Scala",
"src_encoding": "UTF-8",
"text": "# Interpreter_Scala\nInterpreter for some part of Scala language\n"
}
] | 6
|
WilsonKoder/PyBoxes
|
https://github.com/WilsonKoder/PyBoxes
|
88934acf1803130d68b63f48b8c24587640944f0
|
f60787b7e9232b010ccbadc44266e64a638ac7ae
|
9d61622b8092fd5ca7df65683170da71eaa412c0
|
refs/heads/master
| 2021-01-02T22:50:46.038523
| 2014-12-30T10:25:37
| 2014-12-30T10:25:37
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4916805922985077,
"alphanum_fraction": 0.5091913342475891,
"avg_line_length": 39.71893310546875,
"blob_id": "20f4979f200f4d0d7f65108825aade632871c8a8",
"content_id": "2b852e02fd0ba1b0ea78ba4a407b3f9fd8338dc0",
"detected_licenses": [
"WTFPL",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13763,
"license_type": "permissive",
"max_line_length": 139,
"num_lines": 338,
"path": "/mainGame.py",
"repo_name": "WilsonKoder/PyBoxes",
"src_encoding": "UTF-8",
"text": "__author__ = 'Wilson Koder'\n \n# Created by Wilson Koder on the 23rd of October 2014\n# Inspired by Boxes ;)\n# In real life I can't wink.\n\n# This now features an ingame python shell, its buggy at the moment and allows you to pretty much hack the game\n# this is because it uses the exec() function, which allows for any code to be executed (assuming it's valid python)\n\nimport pymunk\nimport pygame\nimport pygame.gfxdraw\nimport pymunk.pygame_util\nimport sys\nimport time\n \nwhite = 255, 255, 255\nblack = 0, 0, 0\nred = 146, 26, 0\ngreen = 0, 255, 0\nblue = 0, 0, 255\nyellow = 255, 255, 0\n\nallowedKeys = \"abcdefghijklmnopqrstuvwxyz=\\\"\\'12345678( )-\"\n\npygame.init()\nwindow_size = (800, 600)\nscreen = pygame.display.set_mode(window_size)\npygame.display.set_caption(\"PyBoxes v0.3\")\nclock = pygame.time.Clock()\nstart_time = time.time()\nplay_time = 0\n\nspace = pymunk.Space()\nspace.gravity = (0.0, -900.0) # negative 900 makes for a good simulation.\n\ncircle_count = 0\nrad = 14\nball_elasticity = 0.8\ngravity = -900\nwind = 0.0\nmouse_down = False\nhold_down_mouse = False\n \nrunning = True\ndebugging = False\npaused = False\n \nliquid_sim = False\nliquid_rad = 1\nliquid_particles = []\n\nfriction = 0.8\n\ncolor = red\n\ndef create_circle(position):\n mass = 1\n inertia = pymunk.moment_for_circle(mass, 0, rad)\n body = pymunk.Body(mass, inertia)\n body.position = position\n # body.position = position\n shape = pymunk.Circle(body, rad)\n shape.elasticity = ball_elasticity\n shape.friction = friction\n space.add(body, shape)\n return shape\n \n \ndef create_line(space_temp):\n body = pymunk.Body()\n body.position = (400, 600)\n line_shape = pymunk.Segment(body, (-400, -500), (400, -500), 15)\n line_shape.elasticity = 0.5\n space_temp.add(line_shape)\n return line_shape\n \nline = create_line(space)\nline.color = blue\ncircles = []\n\ninTextBox = False\ncommand = \"\"\nshiftKeyDown = False\n \narial = pygame.font.SysFont(\"Arial\", 24)\n \nwhile running:\n for event in pygame.event.get(): # go through every event that frame.\n if event.type == pygame.QUIT:\n running = False # if the user tries to quit the app, set running to false in order to exit the loop\n \n if event.type == pygame.KEYDOWN:\n # check for keyboard input\n shiftKeyDown = pygame.key.get_mods() & pygame.KMOD_SHIFT # returns true if user is pressing shift\n\n if inTextBox and event.key != pygame.K_RETURN:\n key = pygame.key.name(event.key)\n if key == \"backspace\":\n command = command[:-1]\n elif key not in allowedKeys:\n print(\"key not allowed\")\n else:\n command += pygame.key.name(event.key)\n\n if event.key == pygame.K_9:\n if shiftKeyDown:\n command += \"(\"\n else:\n command += \"9\"\n\n elif event.key == pygame.K_0:\n if shiftKeyDown:\n command += \")\"\n else:\n command += \"0\"\n else:\n if event.key == pygame.K_RETURN:\n if inTextBox:\n try: # catch any errors that the user has in their code.\n if command != \"clear\":\n exec(command)\n else:\n space.remove(circles)\n circles = []\n except NameError or ValueError or SyntaxError:\n print(\"Sorry, that's not a command or you entered an incorrect value. \")\n command = \"\"\n inTextBox = False\n\n if not inTextBox:\n\n if event.key == pygame.K_p:\n if not paused:\n print(\"pausing\")\n paused = True\n elif paused:\n paused = False\n if event.key == pygame.K_n:\n newRad = input(\"Please input a new radius (int): \")\n try:\n rad = int(newRad)\n except ValueError:\n print(str(newRad) + \" is not an int. Please input an integer next time.\")\n if event.key == pygame.K_g:\n newColor = input(\"Please choose a new color (green, red, blue, yellow): \")\n if newColor.lower() == \"green\":\n color = green\n elif newColor.lower() == \"yellow\":\n color = yellow\n elif newColor.lower() == \"red\":\n color = red\n elif newColor == \"blue\":\n color = blue\n else:\n print(newColor + \" is not a color from the list... Press g to choose again.\")\n if event.key == pygame.K_c: # clear the screen\n space.remove(circles)\n circles = []\n if event.key == pygame.K_x:\n space.remove(liquid_particles)\n liquid_particles = []\n if event.key == pygame.K_a:\n wind -= 100\n if event.key == pygame.K_q:\n wind += 100\n if event.key == pygame.K_w: # increase size of ball\n rad += 5\n if event.key == pygame.K_s: # decrease size of ball\n # must check if above 5 so it doesnt throw an error if you go below 0 :p\n if rad > 5:\n rad -= 5\n else:\n print(\"rad is too low to decrease even more.\")\n if event.key == pygame.K_e:\n gravity += 100\n if event.key == pygame.K_l:\n if liquid_sim is False:\n friction = 0.0\n liquid_sim = True\n rad = liquid_rad\n ball_elasticity = 0.5\n else:\n friction = 0.8\n liquid_sim = False\n rad = 4\n ball_elasticity = 0.8\n if event.key == pygame.K_d:\n gravity -= 100\n if event.key == pygame.K_UP:\n ball_elasticity += 0.25\n if event.key == pygame.K_DOWN:\n if ball_elasticity > 0.5:\n ball_elasticity -= 0.25\n else:\n print(\"e is to low to decrease even more.\")\n if event.key == pygame.K_r:\n if hold_down_mouse:\n hold_down_mouse = False\n else:\n hold_down_mouse = True\n\n if event.key == pygame.K_f:\n if debugging:\n debugging = False\n else:\n debugging = True\n\n if event.type == pygame.KEYUP:\n if event.key == pygame.KMOD_SHIFT:\n shiftKeyDown = False\n\n if event.type == pygame.MOUSEBUTTONDOWN: # check if the mouse is clicked\n pos = pygame.mouse.get_pos()\n if pos[0] > 600 and pos[1] < 50:\n print(\"clicked in textbox\")\n inTextBox = True\n else:\n if hold_down_mouse:\n mouse_down = True\n else:\n pos = pygame.mouse.get_pos()\n if pos[1] < 500:\n pos = pygame.mouse.get_pos() # get the mouse pos\n real_pos = pymunk.pygame_util.to_pygame(pos, screen)\n new_circle = create_circle(real_pos) # create a circle object\n if not liquid_sim:\n circles.append(new_circle) # add it to the list\n else:\n liquid_particles.append(new_circle)\n \n if event.type == pygame.MOUSEBUTTONUP:\n if hold_down_mouse:\n mouse_down = False\n \n if mouse_down:\n pos = pygame.mouse.get_pos()\n if pos[1] < 500:\n if liquid_sim:\n for i in range(0, 20):\n pos = pygame.mouse.get_pos() # get the mouse pos\n real_pos = pymunk.pygame_util.to_pygame(pos, screen)\n new_particle = create_circle(real_pos) # create a circle object\n liquid_particles.append(new_particle) # add it to the list\n else:\n pos = pygame.mouse.get_pos() # get the mouse pos\n real_pos = pymunk.pygame_util.to_pygame(pos, screen)\n new_circle = create_circle(real_pos) # create a circle object\n circles.append(new_circle) # add it to the list\n\n if rad != liquid_rad and liquid_sim is True:\n liquid_sim = False\n \n play_time = round(time.time() - start_time, 0)\n\n space.gravity = (wind, gravity)\n\n screen.fill(white) # clear the screen\n if not paused:\n space.step(1 / 60.0) # step\n \n pymunk.pygame_util.draw(screen, line) # draw the floor, couldn't get it working with normal pygame, so using util's\n \n for circle in circles:\n try:\n p_circle = int(circle.body.position.x), 600 - int(circle.body.position.y) # render each circle in the list\n # pygame.draw.circle(screen, red, p_circle, int(circle.radius), 0) # render each circle in the list\n\n pygame.gfxdraw.aacircle(screen, p_circle[0], p_circle[1], int(circle.radius), color)\n if p_circle[0] > (800 + circle.radius) or p_circle[0] < -circle.radius:\n space.remove(circle)\n circles.remove(circle)\n except OverflowError:\n print(\"ERROR! ERROR! OVERFLOW! Deleting all circles and liquid particles!\")\n space.remove(circles)\n circles = []\n space.remove(liquid_particles)\n liquid_particles = []\n if len(liquid_particles) != 0:\n for particle in liquid_particles:\n try:\n p_circle = int(particle.body.position.x), 600-int(particle.body.position.y) # render each circle in the list\n\n pygame.gfxdraw.aacircle(screen, p_circle[0], p_circle[1], int(particle.radius), color)\n if p_circle[0] > (800 + particle.radius) or p_circle[0] < -particle.radius:\n space.remove(particle)\n liquid_particles.remove(particle)\n except OverflowError:\n print(\"ERROR! ERROR! OVERFLOW! Deleting all circles and liquid particles!\")\n space.remove(circles)\n circles = []\n space.remove(liquid_particles)\n liquid_particles = []\n\n # pymunk.pygame_util.draw(screen, circles)\n # pymunk.pygame_util.draw(screen, liquid_particles)\n\n mousePos = pygame.mouse.get_pos()\n pygame.gfxdraw.aacircle(screen, mousePos[0], mousePos[1], rad, black)\n\n if inTextBox:\n commandText = arial.render(command, 1, black, None)\n screen.blit(commandText, (600, 30))\n\n # if you're in debug mode, set text then draw text.\n if debugging:\n debugTextWind = arial.render(\"Wind Power = \" + str(int(wind)), 1, black, None)\n debugTextCount = arial.render(\"Circle Count = \" + str(len(circles)), 1, black, None) # count of circles\n debugTextParticleCount = arial.render(\"Liquid Particle Count = \" + str(len(liquid_particles)), 1, black, None) # liquid particles\n debugTextColor = arial.render(\"Color = \" + str(color), 1, black, None) # color\n debugTextRad = arial.render(\"Radius = \" + str(rad), 1, black, None) # radius text\n debugTextElasticity = arial.render(\"Elasticity = \" + str(ball_elasticity), 1, black, None) # bounciness text\n debugTextMousePos = arial.render(\"Mouse Pos = \" + str(pygame.mouse.get_pos()), 1, black, None) # mouse pos text\n debugTextFPS = arial.render(\"FPS = \" + str(round(clock.get_fps(), 1)), 1, black, None) # fps text\n debugTextGravity = arial.render(\"Gravity = \" + str(gravity), 1, black, None) # gravity text to one d.p.\n debugTextTime = arial.render(\"Play Time = \" + str(int(play_time)) + \" Seconds\", 1, black, None)\n if liquid_sim:\n debugLiquidSim = arial.render(\"Liquid Simulation On\", 1, black, None)\n elif not liquid_sim:\n debugLiquidSim = arial.render(\"Liquid Simulation Off\", 1, black, None)\n else:\n debugLiquidSim = arial.render(\"WAAAAAHHHHHTTTT?!?!?\", 1, black, None)\n screen.blit(debugTextCount, (0, 0))\n screen.blit(debugTextRad, (0, 30))\n screen.blit(debugTextElasticity, (0, 60))\n screen.blit(debugTextMousePos, (0, 90))\n screen.blit(debugTextFPS, (0, 120))\n screen.blit(debugTextGravity, (0, 150))\n screen.blit(debugTextTime, (0, 180))\n screen.blit(debugLiquidSim, (0, 210))\n screen.blit(debugTextWind, (0, 240))\n screen.blit(debugTextParticleCount, (0, 270))\n\n pygame.display.flip() # draw everything\n clock.tick(60) # limit fps :)\n\nprint(\"Congrats! You just wasted \" + str(int(play_time)) + \" seconds of your life!\")\nsys.exit() # quit if the user is no longer running the application.\n"
},
{
"alpha_fraction": 0.7244400978088379,
"alphanum_fraction": 0.7312560677528381,
"avg_line_length": 15.564516067504883,
"blob_id": "dd0d97015f042c3fd09a8a5601c5c7364c48b84c",
"content_id": "1b20354580f0af481334dda0f87c5b604154aaf9",
"detected_licenses": [
"WTFPL",
"LicenseRef-scancode-unknown-license-reference"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 1027,
"license_type": "permissive",
"max_line_length": 145,
"num_lines": 62,
"path": "/README.md",
"repo_name": "WilsonKoder/PyBoxes",
"src_encoding": "UTF-8",
"text": "PyBoxes\n=======\n\nA small physics implementation\n\nMade at 1 AM on a thursday night\n\nInspired by Boxes\n\nCreated by Wilson Koder using:\n\nPymunk\n\nPygame\n\nPython 3.4\n\nPyCharm CE\n\nUsage\n=====\n\nIDE\n---\n\nTo run PyBoxes just open the .py file up in your preffered IDE, and click the run button. Make sure you have pymunk and pygame insstalled though.\n\nCLI\n---\n\nTo run PyBoxes from the command line, just type 'Python3 mainGame.py' and if you have pymunk and pygame installed properly a window\nwill pop-up and PyBoxes will be ready for some playin'!\n\nControls\n--------\n\nW - Increase circle radius\n\nS - Decrease circle radius\n\nUp arrow - Increase Bounciness\n\nDown arrow - Decrease bounciness\n\nE - Increase gravity\n\nD - Decrease gravity\n\nR - Turn on hold down mouse mode\n\nC - Clear screen\n\nF - Turn on debug info\n\nMouse Click - Instantiate circle\n\nLisence\n=======\n\nhttps://tldrlegal.com/license/do-wtf-you-want-to-public-license-v2-(wtfpl-2.0)\n\n... that doesn't apply to the modules though :) check pygame.org and pymunk.org for their licenses.\n"
}
] | 2
|
jevellangelo/fullstack-nanodegree-vm-2018
|
https://github.com/jevellangelo/fullstack-nanodegree-vm-2018
|
e808b32ad48538696998eb115f7c05f5e38cbb47
|
8a2d990386ce3968bcba32c0d23e68480c6945c9
|
fbe9aec66581f9c9523bf7cf64e06d18313b74a8
|
refs/heads/master
| 2021-06-28T07:29:14.820938
| 2019-04-15T08:48:54
| 2019-04-15T08:48:54
| 122,301,321
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6832579374313354,
"alphanum_fraction": 0.6877828240394592,
"avg_line_length": 26.54166603088379,
"blob_id": "a70e9c321abea4b9251b48c7088d9d222da1cefe",
"content_id": "2d60d94d9691d8de8275d7c46125b4649fa09b30",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 663,
"license_type": "no_license",
"max_line_length": 69,
"num_lines": 24,
"path": "/vagrant/forum/forumdb.py",
"repo_name": "jevellangelo/fullstack-nanodegree-vm-2018",
"src_encoding": "UTF-8",
"text": "# \"Database code\" for the DB Forum.\n\nimport datetime\nimport psycopg2, bleach\n\nPOSTS = [(\"This is the first post.\", datetime.datetime.now())]\n\nDBNAME = \"forum\"\n\ndef get_posts():\n \"\"\"Return all posts from the 'database', most recent first.\"\"\"\n conn = psycopg2.connect(database=DBNAME)\n c = conn.cursor()\n c.execute(\"select content, time from posts order by time desc\")\n return c.fetchall()\n conn.close()\n\ndef add_post(content):\n \"\"\"Add a post to the 'database' with the current timestamp.\"\"\"\n conn = psycopg2.connect(database=DBNAME)\n c = conn.cursor()\n c.execute(\"insert into posts values (%s)\", (bleach.clean(content,))\n conn.commit()\n conn.close()\n\n\n"
},
{
"alpha_fraction": 0.6483660340309143,
"alphanum_fraction": 0.6640523076057434,
"avg_line_length": 28.81818199157715,
"blob_id": "b74ad4ef09233ac72737d28ab36d4b2681bbbfaf",
"content_id": "ffa34556779c5817e948f15f357531dbc2fb58a4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2295,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 77,
"path": "/vagrant/logs_analysis_project.py",
"repo_name": "jevellangelo/fullstack-nanodegree-vm-2018",
"src_encoding": "UTF-8",
"text": "# Database code for the Logs Analysis Project\n\nimport psycopg2\nDB_NAME = \"news\"\n\n# Logs Analysis Questions\nquestion_1 = (\"What are the most popular three articles of all time?\")\nquestion_2 = (\"Who are the most popular article authors of all time?\")\nquestion_3 = (\"On which days did more than 1 percent of requests lead to errors?\")\n\n# Database queries\ntop_articles = \"\"\"select articles.title, count(*) as views\n\t\t\tfrom log join articles\n\t\t\ton substring(log.path,10) = articles.slug\n\t\t\twhere log.status = '200 OK'\n\t\t\tgroup by title\n\t\t\torder by views desc\n\t\t\tlimit 3;\"\"\"\n\ntop_authors = \"\"\"select authors.name, count(*) as views\n\t\t\tfrom articles\n\t\t\tjoin authors on articles.author = authors.id\n\t\t\tjoin log on substring(log.path,10) = articles.slug\n\t\t\tand log.status = '200 OK'\n\t\t\tgroup by authors.name\n\t\t\torder by views desc\n\t\t\tlimit 3;\"\"\"\n\nerror_requests = \"\"\"select * from (\n\t\t\tselect all_requests.day,\n\t\t\tround((100*failed_requests.requests / all_requests.requests),2)\n\t\t\tas percentage from (\n\t\t\t\t(select to_char(log.time, 'FMMonth DD, YYYY') as day,\n\t\t\t\tcount(*) as requests\n\t\t\t\tfrom log\n\t\t\t\tgroup by day) as all_requests\n\t\t\t\tjoin\n\t\t\t\t(select to_char(log.time, 'FMMonth DD, YYYY') as day,\n\t\t\t\tcount(*) as requests\n\t\t\t\tfrom log\n\t\t\t\twhere status = '404 NOT FOUND'\n\t\t\t\tgroup by day) as failed_requests\n\t\t\ton all_requests.day = failed_requests.day))\n\t\t\tas t where percentage > 1.0;\"\"\"\n\n# Database sql request\ndef query_db(sql_request):\n db = psycopg2.connect(database=DB_NAME)\n c = db.cursor()\n c.execute(sql_request)\n results = c.fetchall()\n db.close()\n return results\n\n# Question 1\ndef top_three_articles():\n top_three_articles = query_db(top_articles)\n print(\"\\n 1. \" + question_1 + \"\\n\")\n for title, views in top_three_articles:\n \tprint(\" \\\"{t}\\\" -- {v} views\". format(t=title,v=views))\ntop_three_articles()\n\n#Question 2\ndef top_three_authors():\n\ttop_three_authors = query_db(top_authors)\n\tprint(\"\\n 2. \" + question_2 + \"\\n\")\n\tfor name, views in top_three_authors:\n\t\tprint(\" {n} -- {v} views\". format(n=name,v=views))\ntop_three_authors()\n\n#Question #3\ndef more_errors():\n\tmore_errors = query_db(error_requests)\n\tprint(\"\\n 3. \" + question_3 + \"\\n\")\n\tfor day, percentage in more_errors:\n\t\tprint(\" {d} -- {p} views \\n\". format(d=day,p=percentage))\nmore_errors()"
},
{
"alpha_fraction": 0.5869051814079285,
"alphanum_fraction": 0.6010800004005432,
"avg_line_length": 30.860214233398438,
"blob_id": "5311c9909339ec4d2c95e9ace4eb4858305dd468",
"content_id": "71798ad45040a59670e80366966d7546fab18293",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2963,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 93,
"path": "/vagrant/report_tool.py",
"repo_name": "jevellangelo/fullstack-nanodegree-vm-2018",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Internal reporting tool using the DB-API Psycopg2\n\nimport psycopg2\nfrom unicodedata import *\n\nDBNAME = \"news\"\n\n# Database query for top_articles: \n# What are the three most popular articles of all time?\nrequest_articles = \"\"\"SELECT articles.title, COUNT(log.status) AS views\n FROM log, articles\n WHERE SUBSTRING(log.path, 10) = articles.slug\n AND log.status = '200 OK'\n GROUP BY articles.title\n ORDER BY views DESC\n LIMIT 3;\n \"\"\"\n\n# Database query for top_authors: \n# Who are the most popular article authors of all time?\nrequest_authors = \"\"\"SELECT authors.name, COUNT(articles.slug) AS views\n FROM articles, authors, log\n WHERE SUBSTRING(log.path, 10) = articles.slug\n AND authors.id = articles.author\n GROUP BY authors.name\n ORDER BY views DESC;\n \"\"\"\n\n# Database query for most_errors: \n# On which days did more than 1% of requests lead to errors?\nrequest_errors = \"\"\"SELECT to_char(date, 'FMMonth DD, YYYY'), percent\n FROM (\n SELECT errors.date,\n round((errors.errors::numeric/requests.all_requests::numeric)*100,2)\n AS percent\n FROM errors, requests\n WHERE errors.date = requests.date\n ) AS foo\n WHERE percent > 1.0;\n \"\"\"\n\n\n# Query data from database, open and close the connection\ndef sql_query(sql_request):\n try:\n\t\tconn = psycopg2.connect(database=DBNAME)\n\t\tc = conn.cursor()\n\t\t# Print PostgreSQL Connection properties for debugging\n\t\t# print(conn.get_dsn_parameters(),\"\\n\")\n\t\tc.execute(sql_request)\n\t\tresults = c.fetchall()\n except psycopg2.DatabaseError, e:\n print(\"Error connecting to {} database.\\nError: {}\".format(DBNAME, e))\n finally:\n \t\tif conn is not None:\n\t\t\tconn.close()\n\t\t\treturn results\n\n\ndef top_articles():\n \"\"\"Prints the top 3 articles in a sorted list\"\"\"\n top_3 = sql_query(request_articles)\n print('Most popular three articles of all time:')\n for row in top_3:\n print((' ' + u'\\u2022' + ' \"{}\" -- {} views').format(row[0],row[1]))\n # print(row)\n print('\\n')\n\n\ndef top_authors():\n \"\"\"Prints the top authors in a sorted list\"\"\"\n most_popular = sql_query(request_authors)\n print('Most popular article authors of all time:')\n for row in most_popular:\n print((' ' + u'\\u2022' + ' {} -- {} views').format(row[0],row[1]))\n print('\\n')\n\n\ndef most_errors():\n \"\"\"Prints which days did more than 1% of requests lead to errors\"\"\"\n most_errors = sql_query(request_errors)\n print('The days with more than one percent of requests lead to errors:')\n for row in most_errors:\n print((' ' + u'\\u2022' + ' {} -- {} views').format(row[0],row[1]))\n print('\\n')\n\n\nif __name__ == '__main__':\n top_articles()\n top_authors()\n most_errors()\n"
},
{
"alpha_fraction": 0.6898608207702637,
"alphanum_fraction": 0.6958250403404236,
"avg_line_length": 27,
"blob_id": "bfe8ece3ec616716d8a2c79e40a44c93f77d1e5d",
"content_id": "685d65ef10cf53c53ff2b1f00606e94e3954f6e8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "SQL",
"length_bytes": 503,
"license_type": "no_license",
"max_line_length": 81,
"num_lines": 18,
"path": "/vagrant/create_views.sql",
"repo_name": "jevellangelo/fullstack-nanodegree-vm-2018",
"src_encoding": "UTF-8",
"text": "-- Create views in news database for report_tool.py\n\nCREATE VIEW requests AS\n\t-- SELECT REGEXP_REPLACE(to_char(log.time, 'Month DD, YYYY'),'\\s+',' ') AS date,\n\tSELECT time::date AS date,\n\tCOUNT(log.status) AS all_requests\n\tFROM log\n\tGROUP BY date\n\tORDER BY date ASC;\n\nCREATE VIEW errors AS\n\t-- SELECT REGEXP_REPLACE(to_char(log.time, 'Month DD, YYYY'),'\\s+',' ') AS date,\n\tSELECT time::date AS date,\n\tCOUNT(log.status) AS errors\n\tFROM log\n\tWHERE log.status <> '200 OK'\n\tGROUP BY date\n\tORDER BY date ASC;"
}
] | 4
|
Ram-5508/Face-landmark-detection
|
https://github.com/Ram-5508/Face-landmark-detection
|
e8b6a97242df0f915d091db979e92c768ee2e993
|
b18ab1e2e7e3613da0c66e921c10e3146d590260
|
f478f3ca29ad435fab058a65aa2fb36c45b469cc
|
refs/heads/master
| 2020-09-06T09:09:39.260703
| 2019-11-08T03:59:12
| 2019-11-08T03:59:12
| 220,382,441
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8138527870178223,
"alphanum_fraction": 0.822510838508606,
"avg_line_length": 76,
"blob_id": "de7c6fe2a9da74f41f339d6252c92d67a8869a3b",
"content_id": "518e8b54a8f8df7f4bb5c9dbe463637adcd82ed9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 462,
"license_type": "no_license",
"max_line_length": 129,
"num_lines": 6,
"path": "/README.md",
"repo_name": "Ram-5508/Face-landmark-detection",
"src_encoding": "UTF-8",
"text": "# Face-landmark-detection\n\nFirst I have done face detection using dlib library. Dlib library for face detection is quite accurate when compared with OpenCV.\nThen in the detected face I have detected 68 landmark points using the readily available package for face landmark detection. \nThe package is available in github and I will add the link below\nhttps://github.com/AKSHAYUBHAT/TensorFace/blob/master/openface/models/dlib/shape_predictor_68_face_landmarks.dat\n"
},
{
"alpha_fraction": 0.5184381604194641,
"alphanum_fraction": 0.5770065188407898,
"avg_line_length": 22.972972869873047,
"blob_id": "c585338e1a58057432780a94d0fbdf8e4438cdd7",
"content_id": "d9d6dcbc7f1cc9305a1facaac0702db5088ba490",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 922,
"license_type": "no_license",
"max_line_length": 116,
"num_lines": 37,
"path": "/Face_landmark_detection.py",
"repo_name": "Ram-5508/Face-landmark-detection",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Nov 7 12:05:21 2019\r\n\r\n@author: Lenovo\r\n\"\"\"\r\n\r\nimport cv2\r\nimport dlib\r\n\r\ncap=cv2.VideoCapture(0)\r\ndetector=dlib.get_frontal_face_detector()\r\npredictor=dlib.shape_predictor('C:/Users/Lenovo/Desktop/Ram_Perceptrons/Dlib/shape_predictor_68_face_landmarks.dat')\r\n\r\nwhile 1:\r\n _,img=cap.read()\r\n gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\r\n faces=detector(gray)\r\n for face in faces:\r\n x1=face.left()\r\n y1=face.top()\r\n x2=face.right()\r\n y2=face.bottom()\r\n #cv2.rectangle(img,(x1,y1),(x2,y2),(255,0,0),2)\r\n landmark=predictor(gray,face)\r\n for i in range(0,68):\r\n x=landmark.part(i).x\r\n y=landmark.part(i).y\r\n cv2.circle(img,(x,y),3,(0,255,0),-1)\r\n \r\n cv2.imshow('Detect',img)\r\n k=cv2.waitKey(1)& 0xff\r\n if k==27:\r\n break\r\n \r\ncap.release()\r\ncv2.destroyAllWindows()"
}
] | 2
|
Leopard-C/MisakaSisters
|
https://github.com/Leopard-C/MisakaSisters
|
8600954e76d42d9143759686ad2a1f063411d25e
|
234f712915fc6a6f51b96097d745311f85793aa3
|
60efbb56f766fabee1ca88db0aaf5061a5d500b7
|
refs/heads/master
| 2021-01-16T16:32:38.346089
| 2020-12-10T05:35:55
| 2020-12-10T05:35:55
| 243,184,743
| 5
| 1
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6148591041564941,
"alphanum_fraction": 0.6319385170936584,
"avg_line_length": 22.87755012512207,
"blob_id": "34e829d3d3813bb9fae8ebe94e07e8542310d5a0",
"content_id": "abd381d92927f6bf990b940db75888a6ad037fd6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1171,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 49,
"path": "/src/Searcher.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#pragma once\n\n#include <set>\n#include <string>\n#include \"Client.h\"\n#include \"MysqlDB.h\"\n\nclass Searcher {\npublic:\n Searcher();\n\n int search(const std::string& keyword, int misakaId);\n int search(const std::string& keywordPattern, int start, int end);\n\n void fixError();\n\n void exportToFile(const char* filename);\n\n enum {\n Error = -1,\n NotExist = 0,\n Exist = 1,\n };\n\nprivate:\n int search_(const std::string& keyword, int misakaId);\n\n void writeError(const std::string& name, int misaka_id);\n void write(int64_t mid, const std::string& name, int gender,\n const std::string& face, const std::string& sign, int level,\n int misaka_id, int fans, int videos);\n\n // Remove record from database\n void remove(const std::string& keyword);\n\n // Read all records from database and cache them\n void readAll();\n\n // Get proper misaka_id\n // For example:\n // misaka156hahaha => 156\n // lv6_misaka20001 => -1 (two number in the name)\n int getProperMisakaId(const std::string& name);\n\nprivate:\n Client client;\n MysqlDB mysqlDB;\n std::set<int64_t> midsCache; // member id\n};\n\n"
},
{
"alpha_fraction": 0.49643704295158386,
"alphanum_fraction": 0.6508313417434692,
"avg_line_length": 14.592592239379883,
"blob_id": "940349f32c07f6a9d6753e4c1ea8bc6e9deb3bd7",
"content_id": "93b2bbcfea49eca162d70ec278e0238d8eaa9915",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 505,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 27,
"path": "/list/check/README.md",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "## Format of check.list\n\n+ Exact\n\nWith misaka_id: `misaka10032 10032`\n\nNo misaka_id: `御坂妹妹 -1` (`-1` is required)\n\n+ Scope\n\n`御坂%d号 100 1051` (check 御坂100号, 御坂101号, ... 御坂1050号)\n\n`御坂妹妹%d 0 20002` (check 御坂妹妹0, 御坂妹妹1, ... 御坂妹妹20001)\n\n\n## Notice !\n\nThe nickname will be expanded if it contains digit `0`. Replace `0` with `O`.\n\nFor example:\n\n`御坂10032` will be expanded to \n\n+ 御坂10032\n+ 御坂1O032\n+ 御坂10O32\n+ 御坂1OO32\n"
},
{
"alpha_fraction": 0.5502060651779175,
"alphanum_fraction": 0.5576995015144348,
"avg_line_length": 27.238094329833984,
"blob_id": "971b3397046cd57267cbd7ff6d2497a7dbae4cdd",
"content_id": "d8e417f8551d022e39853ea04e5fef3cf84e83fd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 5338,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 189,
"path": "/src/Validator.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"Validator.h\"\n#include \"Util.h\"\n#include \"jsoncpp/json/json.h\"\n#include <iostream>\n\nValidator::Validator() {\n if (!mysqlDB.connect(\"config/mysqldb.json\")) {\n util::LErrorN(\"Connect to db failed\");\n exit(1);\n }\n readAll();\n}\n\nint Validator::check(const std::string& name, int misaka_id, bool useCache) {\n if (name.find(\"0\") == std::string::npos) {\n return check_(name, misaka_id, useCache);\n }\n else {\n std::vector<std::string> namesAll = util::replace0toO(name);\n int count = 0;\n for (auto& nm : namesAll) {\n count = check_(nm, misaka_id, useCache);\n }\n return count;\n }\n}\n\nint Validator::check_(const std::string& name, int misaka_id, bool useCache) {\n util::LogF(\" [%2d] Checking: %s \", Client::CURRENT_PROXY_ID, name.c_str());\n\n if (useCache && nameExistCache.find(name) != nameExistCache.end()) {\n util::Log(\"[Exist]*\\n\");\n return Exist;\n }\n\n client.clearParam();\n std::string encodeName = name;\n client.encode(encodeName);\n client.emplaceParam(\"nickName\", encodeName);\n std::string url = \"http://passport.bilibili.com/web/generic/check/nickname?\";\n url += client.getMergedParam();\n client.setUrl(url);\n\n std::string response;\n Json::Reader reader;\n Json::Value root;\n int ct = 10;\n\n // try for 10 time at most\n // change different ip\n while (--ct) {\n if (!client.Get(response)) {\n util::LErrorN(\"GET Error\");\n continue;\n }\n if (!reader.parse(response, root, false)) {\n util::LErrorN(\"Parse JSON error]\");\n continue;\n }\n if (root[\"code\"].isNull()) {\n util::LErrorN(\"Error: code is not 0\");\n continue;\n }\n break;\n }\n\n if (ct == 0) {\n util::LErrorN(\"Error for 10 times\");\n writeError(name, misaka_id); \n return Error;\n }\n\n // Write to table: nicknames\n int code = root[\"code\"].asInt();\n if (code == 40014) {\n write(name, true, misaka_id);\n util::LogN(\"[Exist]\");\n return Exist;\n }\n else {\n write(name, false, misaka_id);\n util::LogN(\"[NOT Exist]\");\n return NotExist;\n }\n}\n\nvoid Validator::check(const std::string& pattern, int start, int end, bool useCache) {\n auto pos = pattern.find(\"%d\");\n if (pos == std::string::npos) {\n return;\n }\n\n std::string left = pattern.substr(0, pos);\n std::string right = pattern.substr(pos + 2);\n\n for (int i = start; i < end; ++i) {\n std::string name = left;\n name += std::to_string(i);\n name += right;\n check(name, i, useCache);\n }\n}\n\n\nvoid Validator::writeError(const std::string& name, int misaka_id) {\n char sql[128] = { 0 };\n sprintf(sql, \"INSERT INTO nicknames_error (nickname,misaka_id) VALUES('%s',%d)\"\n \"ON DUPLICATE KEY UPDATE misaka_id=%d\",\n name.c_str(), misaka_id, misaka_id);\n mysqlDB.exec(sql);\n}\n\n\nvoid Validator::write(const std::string& name, bool exist, int misaka_id) {\n char sql[256] = { 0 };\n sprintf(sql, \"INSERT INTO nicknames (nickname, exist, misaka_id) VALUES ('%s',%d,%d)\"\n \"ON DUPLICATE KEY UPDATE exist=%d,misaka_id=%d;\",\n util::normalize(name).c_str(), exist, misaka_id,\n exist, misaka_id);\n if (!mysqlDB.exec(sql)) {\n util::LErrorF(\"%s\\n\", sql);\n writeError(name, misaka_id);\n }\n}\n\nvoid Validator::readAll() {\n const char* sql = \"SELECT * FROM nicknames\";\n if (!mysqlDB.exec(sql)) {\n util::LErrorN(\"Read data from `nicknames` failed\");\n return;\n }\n\n auto* result = mysqlDB.getResult();\n if (!result) \n return;\n\n int numRows = mysql_num_rows(result);\n util::LInfoN(numRows);\n for (int i = 0; i < numRows; ++i) {\n MYSQL_ROW row = mysql_fetch_row(result);\n if (row < 0)\n break;\n nameExistCache.emplace(std::string(row[0]), util::convert<bool>(row[1]));\n }\n util::LInfoN(\"Read \", nameExistCache.size(), \" records from `nicknames`\");\n}\n\nvoid Validator::fixError(bool useCache) {\n const char* sql = \"SELECT * FROM nicknames_error\";\n if (!mysqlDB.exec(sql)) {\n util::LErrorN(\"Read data from `nicknames_error` failed\");\n return;\n }\n\n auto* result = mysqlDB.getResult();\n if (!result) \n return;\n\n std::vector<std::pair<std::string, int>> errorRecords;\n int numRows = mysql_num_rows(result);\n if (numRows == 0)\n return;\n util::LInfoF(\"Fixing %d errors\\n\", numRows);\n\n for (int i = 0; i < numRows; ++i) {\n MYSQL_ROW row = mysql_fetch_row(result);\n if (!row) {\n break;\n }\n std::string name = std::string(row[0]);\n int misaka_id = util::convert<int>(row[1]);\n errorRecords.emplace_back(name, misaka_id);\n }\n\n for (auto pair : errorRecords) {\n if (check_(pair.first, pair.second, useCache) != -1) {\n util::LInfoN(\"Removing record: name=\", pair.first);\n remove(pair.first);\n }\n }\n}\n\nvoid Validator::remove(const std::string& name) {\n char sql[64] = { 0 };\n sprintf(sql, \"DELETE FROM nicknames_error WHERE name='%s'\", util::normalize(name).c_str());\n if (!mysqlDB.exec(sql)) {\n util::LErrorF(\"%s\\n\", sql);\n }\n}\n\n"
},
{
"alpha_fraction": 0.5639097690582275,
"alphanum_fraction": 0.6616541147232056,
"avg_line_length": 13.666666984558105,
"blob_id": "77fe20255cdad1d1c092eb67241a32dc7c50dfff",
"content_id": "900689a7d860ff0fd2a1e3352bdab221b02d36a4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 133,
"license_type": "no_license",
"max_line_length": 40,
"num_lines": 9,
"path": "/python_Abandoned/README.md",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "## How many Misaka Sister's in Bilibili.\n\n\\>= 1911\n\n\n\n\n\n\n\n"
},
{
"alpha_fraction": 0.5056179761886597,
"alphanum_fraction": 0.6432584524154663,
"avg_line_length": 13.199999809265137,
"blob_id": "fe4fbccadbeea55b00f3a5c5879b1a465d4c1faf",
"content_id": "1ddac0503fa642de7e205f8dfa1dfb29e25aac14",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 404,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 25,
"path": "/list/search/README.md",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "## Format of search.list\n\n+ Exact\n\nWith misaka_id: `御坂10032 10032`\n\nNo misaka_id: `御坂 -1` (`-1` is required)\n\n+ Scope\n\n`御坂%d 0 20002` (search 御坂0, 御坂1, 御坂2, ... 御坂20001)\n\n\n## Notice !\n\nThe keyword will be expanded if it contains digit `0`. Replace `0` with `O`.\n\nFor example:\n\n`御坂10032` will be extented to \n\n+ 御坂10032\n+ 御坂1O032\n+ 御坂10O32\n+ 御坂1OO32\n\n"
},
{
"alpha_fraction": 0.5400956869125366,
"alphanum_fraction": 0.5469856262207031,
"avg_line_length": 29.823009490966797,
"blob_id": "c16e84bc12d9f01ee01f2f9190865a970f2718ef",
"content_id": "d23523e3342f529224a2ba482b9d9e9c1bd7b0fd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 10544,
"license_type": "no_license",
"max_line_length": 103,
"num_lines": 339,
"path": "/src/Client.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"Client.h\"\n#include \"Util.h\"\n#include <unistd.h>\n\n#include <random>\n#include <cstring>\n#include <sstream>\n#include <fstream>\n#include <iostream>\n#include <thread>\n#include <chrono>\n\nbool Client::shouldQuit = false;\nbool Client::isQuit = false;\nint Client::COUNT = 0;\nint Client::MAX_COUNT_TO_SLEEP = 300;\nint Client::SLEEP_TIME = 20;\nint Client::SLEEP_COUNT = 0;\nint Client::CURRENT_PROXY_ID = 0;\nstd::vector<Proxy> Client::proxies;\n\nClient::Client()\n{\n curl_ = curl_easy_init();\n}\n\nClient::~Client() {\n if (curl_)\n curl_easy_cleanup(curl_);\n}\n\n\nvoid Client::addProxy(int type, bool isNeedAuth, const std::string& addr, const std::string& userpwd) {\n proxies.emplace_back(type, isNeedAuth, addr, userpwd);\n}\n\n\n// 合并参数为字符串(key1=value1&key2=value2&key2=value3)\nstd::string Client::getMergedParam() {\n std::string mergedParam;\n for (auto it = params_.begin(); it != params_.end(); ++it) {\n if (it != params_.begin()) {\n mergedParam += \"&\";\n }\n mergedParam += it->first;\n mergedParam += \"=\";\n mergedParam += it->second;\n }\n return mergedParam;\n}\n\n// 发送Get请求\nbool Client::Get() {\n std::string response;\n CURLcode res = curlGet_(url_, response);\n return res == CURLE_OK;\n}\n\nbool Client::Get(std::string& response) {\n CURLcode res = curlGet_(url_, response);\n if (res == CURLE_OK) {\n std::string::size_type pos;\n int offset = 0;\n if (response.find('\\r') == std::string::npos) {\n pos = response.find(\"\\n\\n\");\n offset = 2;\n }\n else {\n pos = response.find(\"\\r\\n\\r\\n\");\n offset = 4;\n }\n if (pos != std::string::npos) {\n response = response.substr(pos + offset);\n return true;\n }\n else {\n return false;\n }\n }\n else {\n return false;\n }\n}\n\n\n// 发送Post请求\nbool Client::Post() {\n std::string response;\n CURLcode res = curlPost_(url_, getMergedParam(), response);\n return res == CURLE_OK;\n}\n\n// URL编码\nvoid Client::encode(std::string& str) {\n char* encodedStr = curl_easy_escape(curl_, str.c_str(), str.size());\n str = std::string(encodedStr);\n curl_free(encodedStr);\n}\n\n\n// curl辅助函数\nsize_t Client::reqReply_(void* ptr, size_t size, size_t nmemb, void* stream) {\n std::string *str = (std::string*)stream;\n //DEBUG(\"---->reply\");\n //DEBUG(*str);\n (*str).append((char*)ptr, size*nmemb);\n return size * nmemb;\n}\n\n// 发送Post请求(私有函数)\nCURLcode Client::curlPost_(const std::string& url, const std::string& param, std::string& response) {\n checkSleep_();\n addHeader_();\n setRandomProxy_();\n curl_easy_setopt(curl_, CURLOPT_URL, url.c_str()); // url\n curl_easy_setopt(curl_, CURLOPT_POSTFIELDSIZE, param.length());\n curl_easy_setopt(curl_, CURLOPT_POSTFIELDS, param.c_str());\n curl_easy_setopt(curl_, CURLOPT_SSL_VERIFYPEER, false); // \n curl_easy_setopt(curl_, CURLOPT_SSL_VERIFYHOST, false); // Not verify cert & host\n curl_easy_setopt(curl_, CURLOPT_POST, 1);\n curl_easy_setopt(curl_, CURLOPT_VERBOSE, 0);\n curl_easy_setopt(curl_, CURLOPT_READFUNCTION, NULL);\n curl_easy_setopt(curl_, CURLOPT_WRITEFUNCTION, reqReply_);\n curl_easy_setopt(curl_, CURLOPT_WRITEDATA, (void *)&response);\n curl_easy_setopt(curl_, CURLOPT_FOLLOWLOCATION, 1); \n curl_easy_setopt(curl_, CURLOPT_NOSIGNAL, 1);\n curl_easy_setopt(curl_, CURLOPT_HEADER, 1);\n curl_easy_setopt(curl_, CURLOPT_TIMEOUT, 2); // 超时\n\n CURLcode ret = curl_easy_perform(curl_);\n curl_easy_cleanup(curl_);\n curl_ = curl_easy_init();\n return ret;\n}\n\n\n// 发送get请求(私有函数)\nCURLcode Client::curlGet_(const std::string& url, std::string& response) {\n checkSleep_();\n addHeader_();\n setRandomProxy_();\n curl_easy_setopt(curl_, CURLOPT_URL, url.c_str());\n curl_easy_setopt(curl_, CURLOPT_SSL_VERIFYPEER, false);\n curl_easy_setopt(curl_, CURLOPT_SSL_VERIFYHOST, false);\n curl_easy_setopt(curl_, CURLOPT_VERBOSE, 0);\n curl_easy_setopt(curl_, CURLOPT_READFUNCTION, NULL);\n curl_easy_setopt(curl_, CURLOPT_WRITEFUNCTION, reqReply_);\n curl_easy_setopt(curl_, CURLOPT_WRITEDATA, (void *)&response);\n curl_easy_setopt(curl_, CURLOPT_NOSIGNAL, 1);\n curl_easy_setopt(curl_, CURLOPT_HEADER, 1);\n curl_easy_setopt(curl_, CURLOPT_TIMEOUT, 2); // 超时\n\n CURLcode ret = curl_easy_perform(curl_);\n curl_easy_cleanup(curl_);\n curl_ = curl_easy_init();\n return ret;\n}\n\nvoid Client::checkSleep_() {\n Client::COUNT++;\n if (Client::COUNT > Client::MAX_COUNT_TO_SLEEP) {\n Client::COUNT = 0;\n Client::SLEEP_COUNT++;\n util::LInfoN(\"\\nSleeping \", Client::SLEEP_TIME, \"s...\");\n std::this_thread::sleep_for(std::chrono::seconds(Client::SLEEP_TIME));\n }\n}\n\nvoid Client::setRandomProxy_() {\n if (proxies.empty())\n exit(1);\n int size = proxies.size();\n CURRENT_PROXY_ID = rand() % size;\n\n const Proxy& proxy = proxies[CURRENT_PROXY_ID];\n curl_easy_setopt(curl_, CURLOPT_PROXY, proxy.addr.c_str());\n curl_easy_setopt(curl_, CURLOPT_PROXYTYPE, proxy.type);\n if (proxy.isNeedAuth) {\n curl_easy_setopt(curl_, CURLOPT_PROXYUSERPWD, proxy.userpwd.c_str());\n }\n}\n\n\n// 添加请求头\nvoid Client::addHeader_() {\n if (headers_.empty())\n return;\n\n std::string header;\n struct curl_slist* chunk = nullptr;\n for (auto it = headers_.begin(); it != headers_.end(); ++it) {\n header = it->first;\n header += \":\";\n header += it->second;\n chunk = curl_slist_append(chunk, header.c_str());\n }\n //DEBUG(header);\n curl_easy_setopt(curl_, CURLOPT_HTTPHEADER, chunk);\n}\n\n\n// Background thread:\n// Check the response time of proxy ip address every 2 min\n//\n/*static*/ bool Client::LoadProxyIp(const std::string& filename) {\n if (!readProxyIpFromFile(filename)) {\n return false;\n }\n if (Client::proxies.empty()) {\n return false;\n }\n\n // Background thread\n // Check the response time of proxy server\n std::thread t([]{\n\n // pid file\n // \n char pidfile[64] = { 0 };\n sprintf(pidfile, \"%s/.misaka/%d\", getenv(\"HOME\"), getpid());\n\n auto& proxies = Client::proxies;\n std::vector<Proxy> unUsedProxies;\n std::string cmdBase = \"curl http://passport.bilibili.com/web/generic/check/\"\n \"nickname\\?nickName\\=TEMP123 -s -m 3 -x \";\n auto getResponseTime = [&cmdBase](const Proxy& proxy){\n std::string cmd = cmdBase;\n // test response-time for 3 times and get average time\n if (proxy.isNeedAuth) {\n std::string authOpt = proxy.userpwd;\n authOpt += \"@\";\n cmd += authOpt;\n }\n cmd += proxy.addr;\n char result[128];\n int count = 0;\n for (int i = 0; i < 3; ++i) {\n auto start = std::chrono::system_clock::now();\n memset(result, 0, 128);\n util::execShell(cmd.c_str(), result, 127);\n auto end = std::chrono::system_clock::now();\n auto dur = std::chrono::duration_cast<std::chrono::milliseconds>(end - start);\n count += dur.count();\n if (count > 3000)\n break;\n }\n return count;\n };\n\n while (true) {\n util::LInfoN(\"\\nChecking response time. Proxies Count: \", proxies.size());\n util::LogToFileF(pidfile, \"%d %d %d\\n\", time(NULL), proxies.size(),\n Client::SLEEP_COUNT * Client::MAX_COUNT_TO_SLEEP + Client::COUNT);\n\n std::vector<Proxy> tmpVec;\n for (auto iter = proxies.begin(); iter != proxies.end();/* ++iter*/) {\n if (shouldQuit) {\n util::LInfoN(\"Background thread quit\");\n isQuit = true;\n return;\n }\n auto responseTime = getResponseTime(*iter);\n if (responseTime > 3000) {\n tmpVec.emplace_back(*iter);\n iter = proxies.erase(iter);\n util::LErrorN(\"Remove proxy [\", iter->addr, \"] Proxies Count:\", proxies.size());\n }\n else {\n ++iter;\n }\n }\n\n for (auto iter = unUsedProxies.begin(); iter != unUsedProxies.end();/* ++iter*/) {\n if (shouldQuit) {\n util::LInfoN(\"Background thread quit\");\n isQuit = true;\n return;\n }\n auto responseTime = getResponseTime(*iter);\n if (responseTime > 2500) {\n ++iter;\n }\n else {\n proxies.emplace_back(*iter);\n iter = unUsedProxies.erase(iter);\n util::LInfoN(\"Add proxy [\", iter->addr, \"] Proxies Count:\", proxies.size());\n }\n }\n if (tmpVec.size() > 0) {\n unUsedProxies.insert(unUsedProxies.end(), tmpVec.begin(), tmpVec.end());\n }\n for (int i = 0; i < 240; ++i) {\n if (shouldQuit) {\n util::LInfoN(\"Background thread quit\");\n isQuit = true;\n return;\n }\n std::this_thread::sleep_for(std::chrono::milliseconds(500));\n }\n } // end while(true)\n }); // end thread t\n\n t.detach();\n return true;\n}\n\n/*static*/ bool Client::readProxyIpFromFile(const std::string& filename) {\n std::ifstream ifs(filename);\n if (!ifs.is_open())\n return false;\n\n while (!ifs.eof()) {\n std::string typeStr, addrStr, userpwdStr;\n ifs >> typeStr >> addrStr >> userpwdStr;\n if (ifs.fail())\n break;\n int type = CURLPROXY_HTTP;\n if (typeStr == \"HTTPS\") {\n //type == CURLPROXY_HTTPS; \n }\n if (userpwdStr == \"NULL\") {\n Client::proxies.emplace_back(type, false, addrStr, \"\");\n }\n else {\n Client::proxies.emplace_back(type, true, addrStr, userpwdStr);\n }\n }\n\n ifs.close();\n return true;\n}\n\n/*static*/ void Client::Quit() {\n shouldQuit = true;\n util::LInfoN(\"Waiting for background thread to quit...\");\n while (!isQuit) {\n std::this_thread::sleep_for(std::chrono::seconds(1));\n }\n}\n\n"
},
{
"alpha_fraction": 0.5206307768821716,
"alphanum_fraction": 0.5305681824684143,
"avg_line_length": 30.810997009277344,
"blob_id": "7d4f25de160773243588af0718fb13ce6a430074",
"content_id": "c20a7d32439ce001c8466e4248aa699e3f83e494",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 9258,
"license_type": "no_license",
"max_line_length": 111,
"num_lines": 291,
"path": "/src/Searcher.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"Searcher.h\"\n#include \"Util.h\"\n#include \"jsoncpp/json/json.h\"\n#include <cstdlib>\n\nSearcher::Searcher() {\n if (!mysqlDB.connect(\"config/mysqldb.json\")) {\n util::LErrorN(\"Connect mysql failed\");\n exit(1);\n }\n readAll();\n}\n\n\n// Search by keyword\nint Searcher::search(const std::string& keyword, int misaka_id) {\n if (keyword.find(\"0\") == std::string::npos) {\n return search_(keyword, misaka_id);\n }\n else {\n std::vector<std::string> keywordsAll = util::replace0toO(keyword);\n int count = 0;\n for (auto& kw : keywordsAll) {\n count = search_(kw, misaka_id);\n }\n return count;\n }\n}\n\n// Do real_searching \nint Searcher::search_(const std::string& keyword, int misakaId) {\n int count = 0;\n int i = 0;\n int pages = INT_MAX;\n while ((i++) < pages) {\n util::LogF(\"[%2d] keyword=\\\"%s\\\" page=%d\\n\", Client::CURRENT_PROXY_ID,\n keyword.c_str(), i);\n client.clearParam();\n client.emplaceParam(\"search_type\", \"bili_user\");\n std::string encodedKeyword = keyword;\n client.encode(encodedKeyword);\n client.emplaceParam(\"keyword\", encodedKeyword);\n client.emplaceParam(\"page\", std::to_string(i));\n std::string url = \"http://api.bilibili.com/x/web-interface/search/type?\";\n url += client.getMergedParam();\n client.setUrl(url);\n\n std::string response;\n Json::Reader reader;\n Json::Value root;\n int ct = 10;\n\n // try for 10 time at most\n while (--ct) {\n if (!client.Get(response)) {\n util::LErrorN(\"GET Error\");\n continue;\n }\n if (!reader.parse(response, root, false)) {\n util::LErrorN(\"Parse JSON Error\");\n continue;\n }\n if (root[\"code\"].asInt() != 0) {\n util::LErrorN(\"Ret code is not 0\");\n continue;\n }\n break;\n }\n\n if (ct == 0) {\n util::LErrorN(\"Error for 10 times\");\n writeError(keyword, misakaId);\n return -1;\n }\n\n Json::Value& data = root[\"data\"];\n pages = data[\"numPages\"].asInt();\n Json::Value& result = data[\"result\"];\n int pageSize = result.size();\n count += pageSize;\n\n // 20 items at most in one page\n for (int k = 0; k < pageSize; ++k) {\n Json::Value& user = result[k];\n int64_t mid = user[\"mid\"].asInt64();\n util::LogF(\" mid=%-11lld \", mid);\n // already added to database \n if (midsCache.find(mid) != midsCache.end()) {\n util::LogN(\"[Exist]*\");\n }\n else {\n util::LogN(\"[New]\");\n }\n midsCache.emplace(mid);\n std::string name = user[\"uname\"].asString();\n std::string sign = user[\"usign\"].asString();\n int gender = user[\"gender\"].asInt();\n std::string face = \"http:\";\n std::string face_ = user[\"upic\"].asString();\n face += face_;\n int level = user[\"level\"].asInt();\n int fans = user[\"fans\"].asInt();\n int videos = user[\"videos\"].asInt();\n write(mid, name, gender, face, sign, level, misakaId, fans, videos);\n }\n }\n\n return count;\n}\n\n\n// Search continuously\n// For example:\n// misaka100, misaka101, misaka102, ... misaka999\nint Searcher::search(const std::string& keywordPattern, int start, int end) {\n auto pos = keywordPattern.find(\"%d\");\n if (pos == std::string::npos) {\n return 0;\n }\n\n std::string left = keywordPattern.substr(0, pos);\n std::string right = keywordPattern.substr(pos + 2);\n int count = 0;\n\n for (int i = start; i < end; ++i) {\n std::string keyword = left;\n keyword += std::to_string(i);\n keyword += right;\n count += search(keyword, i);\n }\n\n return count;\n}\n\n\nvoid Searcher::fixError() {\n const char* sql = \"SELECT * FROM misaka_sisters_info_error\";\n if (!mysqlDB.exec(sql)) {\n util::LErrorN(\"Read data from `misaka_sisters_info_error` failed\");\n return;\n }\n\n auto* result = mysqlDB.getResult();\n if (!result) {\n util::LErrorN(\"Result is NULL\");\n return;\n }\n\n std::vector<std::pair<std::string, int>> errorRecords;\n int numRows = mysql_num_rows(result);\n if (numRows == 0)\n return;\n util::LInfoF(\"Fixing %d errors\\n\", numRows);\n\n for (int i = 0; i < numRows; ++i) {\n MYSQL_ROW row = mysql_fetch_row(result);\n if (!row) {\n break;\n }\n std::string keyword = std::string(row[0]);\n int misakaId = util::convert<int>(row[1]);\n errorRecords.emplace_back(keyword, misakaId);\n }\n\n for (auto& pair : errorRecords) {\n if (search_(pair.first, pair.second) != -1) {\n util::LInfoN(\"Removing record: keyword=\", pair.first);\n remove(pair.first); \n }\n }\n}\n\n\nvoid Searcher::writeError(const std::string& name, int misaka_id) {\n char sql[128];\n sprintf(sql, \"INSERT INTO misaka_sisters_info_error VALUES('%s', %d);\",\n name.c_str(), misaka_id);\n mysqlDB.exec(sql);\n}\n\nvoid Searcher::write(int64_t mid, const std::string& name, int gender,\n const std::string& face, const std::string& sign, int level,\n int misaka_id, int fans, int videos)\n{\n int exact = 1;\n if (misaka_id == -1) {\n // First: Get misaka_id from database\n char sql_query[128] = { 0 };\n sprintf(sql_query, \"SELECT `name`,misaka_id,exact FROM misaka_sisters_info WHERE mid=%lld\", mid);\n if (!mysqlDB.exec(sql_query)) {\n util::LogF(\"%s\\n\", sql_query);\n return;\n }\n auto* result = mysqlDB.getResult();\n if (!result) {\n util::LErrorN(\"result is NULL\");\n return;\n }\n int numRows = mysql_num_rows(result);\n // not found in database\n if (numRows == 0) {\n // Calculate proper misaka_id\n misaka_id = getProperMisakaId(name);\n if (misaka_id != -1)\n exact = 0; // misaka_id is not exact, need manually to verfiy \n }\n // found in database\n else if (numRows == 1) {\n MYSQL_ROW row = mysql_fetch_row(result);\n misaka_id = util::convert<int>(row[1]);\n exact = util::convert<int>(row[2]);\n //util::LInfoF(\"Found: misaka_id=%d\\n\", misaka_id);\n }\n // won't get down here\n else {\n return;\n }\n }\n\n // Insert into database\n // or\n // Update exist record\n char sql[2048] = { 0 };\n std::string n_name = util::normalize(name);\n std::string n_sign = util::normalize(sign);\n sprintf(sql, \"INSERT INTO misaka_sisters_info (mid,`name`,gender,face,`sign`,`level`,\"\n \"misaka_id,fans,videos,exact) VALUES(%lu,'%s',%d,'%s','%s',%d,%d,%d,%d,%d) \"\n \"ON DUPLICATE KEY UPDATE `name`='%s',gender=%d,face='%s',`sign`='%s',level=%d,\"\n \"misaka_id=%d,fans=%d,videos=%d,exact=%d;\", \n mid, n_name.c_str(), gender, face.c_str(), n_sign.c_str(), level, misaka_id, fans, videos, exact,\n n_name.c_str(), gender, face.c_str(), n_sign.c_str(), level, misaka_id, fans, videos, exact);\n if (!mysqlDB.exec(sql)) {\n util::LogF(\"%s\\n\", sql);\n }\n}\n\nvoid Searcher::remove(const std::string& keyword) {\n char sql[128] = { 0 };\n sprintf(sql, \"DELETE FROM misaka_sisters_info_error WHERE keyword='%s'\", util::normalize(keyword).c_str());\n if (!mysqlDB.exec(sql)) {\n util::LogF(\"%s\\n\", sql);\n }\n}\n\nvoid Searcher::readAll() {\n const char* sql = \"SELECT mid FROM misaka_sisters_info;\";\n if (!mysqlDB.exec(sql)) {\n util::LErrorN(\"Read data from mysql failed\");\n return;\n }\n\n auto* result = mysqlDB.getResult();\n if (!result) \n return;\n\n int numRows = mysql_num_rows(result);\n for (int i = 0; i < numRows; ++i) {\n MYSQL_ROW row = mysql_fetch_row(result);\n if (row < 0)\n break;\n int64_t mid = util::convert<int64_t>(row[0]);\n midsCache.emplace(mid);\n }\n util::LInfoF(\"Read %d records from `misaka_sisters_info`\\n\", midsCache.size());\n}\n\n\nint Searcher::getProperMisakaId(const std::string& name) {\n auto pos1 = name.find(\"O\");\n auto pos2 = name.find(\"O\");\n if (pos1 == std::string::npos && pos2 == std::string::npos) {\n std::vector<int> nums = util::getNumber(name);\n if (nums.size() == 1) {\n return nums[0];\n }\n }\n return -1;\n}\n\nvoid Searcher::exportToFile(const char* filename) {\n char sql[2048] = { 0 };\n sprintf(sql, \n \"SELECT * INTO OUTFILE '/var/lib/mysql-files/%s' \"\n \"FIELDS TERMINATED BY ';' LINES TERMINATED BY '\\n' FROM \"\n \"(SELECT 'mid','name','misaka_id','exact','level','sign','gender','face','fans','videos' union \"\n \"SELECT `mid`,`name`,`misaka_id`,`exact`,`level`,`sign`,`gender`,`face`,`fans`,`videos` \"\n \"FROM misaka_sisters_info) b;\", filename);\n if (!mysqlDB.exec(sql)) {\n util::LErrorN(\"Export to file failed!\");\n }\n}\n\n"
},
{
"alpha_fraction": 0.6376811861991882,
"alphanum_fraction": 0.6521739363670349,
"avg_line_length": 10.5,
"blob_id": "595b5a0c5bb2edbfe9a0a5c2eb60efdb7b42a873",
"content_id": "a76a2b9e2adbd9495067dcac321843d9b02a1058",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 138,
"license_type": "no_license",
"max_line_length": 48,
"num_lines": 12,
"path": "/src/User.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#pragma once\n\n#include \"Client.h\"\n\n\nclass User {\npublic:\n bool getInfo(int64_t mid, std::string& res);\n\nprivate:\n Client client;\n};\n"
},
{
"alpha_fraction": 0.5197740197181702,
"alphanum_fraction": 0.5225988626480103,
"avg_line_length": 21.112499237060547,
"blob_id": "3d5ef3d581eaa3c8ea9cddf74aeecf0b05d9835b",
"content_id": "ad2602c0b44457ddf12006d24b23ffbc3461d5ed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1770,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 80,
"path": "/src/App.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"App.h\"\n#include \"Util.h\"\n#include \"Validator.h\"\n#include \"Searcher.h\"\n#include \"User.h\"\n\n#include <iostream>\n#include <string>\n#include <fstream>\n\n\n// Check\n// Exist or not exist.\n// Can not get detailed information.\nvoid App::check(const char* checkListFile, bool useCache) {\n std::ifstream ifs(checkListFile);\n if (!ifs.is_open()) {\n util::LErrorF(\"Open file %s failed\\n\", checkListFile);\n return;\n }\n\n Validator validator;\n\n while (!ifs.eof()) {\n std::string name;\n ifs >> name;\n if (ifs.fail())\n break;\n auto pos = name.find(\"%d\");\n if (pos == std::string::npos) {\n int misakaId;\n ifs >> misakaId;\n validator.check(name, misakaId, useCache);\n }\n else {\n int start, end;\n ifs >> start >> end;\n validator.check(name, start, end, useCache);\n }\n }\n\n validator.fixError(useCache);\n\n ifs.close();\n}\n\n\n// Search\nvoid App::search(const char* keywordListFile) {\n std::ifstream ifs(keywordListFile);\n if (!ifs.is_open()) {\n util::LogColorF(255, 0, 0, \"Open file %s failed\\n\", keywordListFile);\n return;\n }\n\n Searcher searcher;\n\n while (!ifs.eof()) {\n std::string keyword;\n ifs >> keyword;\n if (ifs.fail())\n break;\n auto pos = keyword.find(\"%d\");\n if (pos == std::string::npos) {\n int misakaId;\n ifs >> misakaId;\n util::LDebugN(misakaId);\n searcher.search(keyword, misakaId);\n }\n else {\n int start, end;\n ifs >> start >> end;\n searcher.search(keyword, start, end);\n }\n }\n\n searcher.fixError();\n\n ifs.close();\n}\n\n"
},
{
"alpha_fraction": 0.6899224519729614,
"alphanum_fraction": 0.6899224519729614,
"avg_line_length": 17.428571701049805,
"blob_id": "671916fc1f6e0da9e0f055dfc9d7a8c864e35f32",
"content_id": "ccb47041bd1c25288e5af1963aacc01043bcc3f2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 129,
"license_type": "no_license",
"max_line_length": 52,
"num_lines": 7,
"path": "/src/App.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#pragma once\n\nclass App {\npublic:\n void check(const char* filename, bool useCache);\n void search(const char* filename);\n};\n"
},
{
"alpha_fraction": 0.6377748847007751,
"alphanum_fraction": 0.6416558623313904,
"avg_line_length": 20.44444465637207,
"blob_id": "afa0e34bfe1e0f93dd6655de4ad894de5dd27770",
"content_id": "b20fdc66d7746c22409871f176f8be29638cd561",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 773,
"license_type": "no_license",
"max_line_length": 78,
"num_lines": 36,
"path": "/src/Validator.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#pragma once\n\n#include <map>\n#include <string>\n#include \"Client.h\"\n#include \"MysqlDB.h\"\n\nclass Validator {\npublic:\n Validator();\n\n int check(const std::string& name, int misaka_id, bool useCache);\n void check(const std::string& pattern, int start, int end, bool useCache);\n\n void fixError(bool useCache);\n\n enum {\n Error = -1,\n NotExist = 0,\n Exist = 1,\n };\n\nprivate:\n int check_(const std::string& name, int misaka_id, bool useCache);\n\n void write(const std::string& name, bool exist, int misaka_id);\n void writeError(const std::string& name, int misaka_id);\n\n void remove(const std::string& name);\n void readAll();\n\nprivate:\n Client client;\n MysqlDB mysqlDB;\n std::map<std::string, bool> nameExistCache;\n};\n\n"
},
{
"alpha_fraction": 0.7028862237930298,
"alphanum_fraction": 0.7028862237930298,
"avg_line_length": 52.54545593261719,
"blob_id": "4f081f96d3c43c24aa8a95b13bcaf98f79662adb",
"content_id": "df8aae9ab96c8f8b3fa429c34d77d1af4e1627a8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "SQL",
"length_bytes": 589,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 11,
"path": "/sql/export.sql",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "SELECT * INTO OUTFILE '/var/lib/mysql-files/misaka_sisters_info.csv'\n FIELDS TERMINATED BY ';' LINES TERMINATED BY '\\n' FROM\n (SELECT 'mid','name','misaka_id','exact','level','sign','gender','face','fans','videos' union \n SELECT `mid`,`name`,`misaka_id`,`exact`,`level`,`sign`,`gender`,`face`,`fans`,`videos`\n FROM MisakaSisters.misaka_sisters_info) b;\n\nSELECT * INTO OUTFILE '/var/lib/mysql-files/nicknames.csv'\n FIELDS TERMINATED BY ';' LINES TERMINATED BY '\\n' FROM\n (SELECT 'nickname','exist','misaka_id' union \n SELECT `nickname`,`exist`,`misaka_id`\n FROM MisakaSisters.nicknames) b;\n"
},
{
"alpha_fraction": 0.6665188670158386,
"alphanum_fraction": 0.6731707453727722,
"avg_line_length": 29.472972869873047,
"blob_id": "4eb07d38c99986a1cd4ad50c9b8252a003c6e1fa",
"content_id": "52cbbf5f974297141ca8a0499283afb279c0f79b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 2259,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 74,
"path": "/src/Client.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#ifndef __CLIENT_H__\n#define __CLIENT_H__\n\n#include <map>\n#include <vector>\n#include <string>\n#include <curl/curl.h>\n#include <curl/easy.h>\n\nstruct Proxy {\n Proxy(int type, bool isNeedAuth, const std::string& addr, const std::string& userpwd) :\n type(type), isNeedAuth(isNeedAuth), addr(addr), userpwd(userpwd) {}\n int type;\n bool isNeedAuth;\n std::string addr;\n std::string userpwd;\n};\n\n\nclass Client {\npublic:\n Client();\n ~Client();\npublic:\n void setUrl(const std::string& url) { url_ = url; }\n\n void addProxy(int type, bool isNeedAuth, const std::string& addr, const std::string& userpwd);\n\n void emplaceParam(const std::string& key, const std::string& value) { params_.emplace(key, value); }\n void emplaceParam(const std::string& key, int value) { params_.emplace(key, std::to_string(value)); }\n void emplaceParam(const std::string& key, int64_t value) { params_.emplace(key, std::to_string(value)); }\n void emplaceHeader(const std::string& key, const std::string& value) { headers_.emplace(key, value); }\n std::string getMergedParam();\n void clearParam() { params_.erase(params_.begin(), params_.end()); }\n\n void encode(std::string& str); // URL编码\n bool Get(std::string& res);\n bool Get();\n bool Post();\n\nprivate:\n CURLcode curlPost_(const std::string& url, const std::string& param, std::string& response);\n CURLcode curlGet_(const std::string &url, std::string& response);\n static size_t reqReply_(void* ptr, size_t size, size_t nmemb, void* stream);\n void addHeader_();\n void setRandomProxy_();\n void checkSleep_();\n\npublic:\n static bool LoadProxyIp(const std::string& filename);\n static bool readProxyIpFromFile(const std::string& filename);\n static void Quit();\n\npublic:\n static bool shouldQuit;\n static bool isQuit;\n static int COUNT/* = 0*/;\n static int MAX_COUNT_TO_SLEEP/* = 1000*/; // If GET or POST 500 times, the COUNT will be set to -1.\n static int SLEEP_TIME/* = 20*/; // 20 seconds\n static int SLEEP_COUNT;\n static int CURRENT_PROXY_ID;\n\n static std::vector<Proxy> proxies; // ip proxy pool\n\nprivate:\n CURL* curl_;\n std::string url_;\n\n std::multimap<std::string, std::string> params_;\n std::multimap<std::string, std::string> headers_;\n};\n\n\n#endif // __CLIENT_H__\n"
},
{
"alpha_fraction": 0.5875869989395142,
"alphanum_fraction": 0.6906419396400452,
"avg_line_length": 23.603960037231445,
"blob_id": "ddc9b0d26ad8a72b63b23014bf7d923590ff779b",
"content_id": "62b1b5c0fa6bc7d1e87e9d322c457ae8f322c201",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 7396,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 202,
"path": "/README.md",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "> 更详细的统计，在这里：[Leopard-C/BiliUserSpider](https://github.com/Leopard-C/BiliUserSpider)\r\n\r\n> 网址：https://misaka.sisters.top\r\n\r\n## How many Misaka Sisters in bilibili ?\r\n\r\n2020-04-15\r\n\r\n~~使用Python开发~~ \r\n\r\n【使用C++开发】，依赖\r\n\r\n+ JsonCpp ：解析json数据\r\n+ libcurl：网络请求\r\n\r\n## 1. 功能\r\n\r\n+ 精确判断某用户名是否存在：`Validator::check(nickname, ...)`\r\n + 御坂1号\r\n + 御坂10032\r\n + 御坂20001号\r\n + misaka10032\r\n + ...\r\n+ 关键词搜索：`Searcher::search(keyword, ...)`\r\n + 御坂\r\n + 御坂妹妹\r\n + misaka\r\n + 御坂号\r\n + yuban\r\n + 御板（错别字）\r\n + みさか（日文“御坂”）\r\n + ...\r\n\r\n查找/搜索 的输入文件 在 `list/`目录下\r\n\r\n支持扩展符：如\r\n\r\n`御坂%d 0 20002` ： 程序运行时，将查找或匹配 `御坂0`， `御坂1`，`...` `御坂20001`\r\n\r\n`御坂%d号 0 20002` ： 程序运行时，将查找或匹配 `御坂0号`， `御坂1号`，`...` `御坂20001号`\r\n\r\n## 2. 使用\r\n\r\n### 2.1 精确匹配 (check)\r\n\r\n`./misaka_sisters check [check.list] [USE_CACHE / NO_CACHE] [proxy.list]`\r\n\r\n无论该用户是否存在都会写入(`MySQL数据库`)数据表`MisakaSisters.misaka_sisters_info`，通过`exist`字段表示。\r\n\r\n### 2.2 关键词搜索\r\n\r\n`./misaka_sisters search [search.list] [proxy.list]`\r\n\r\n搜索结果写入数据表`MisakaSisters.nicknames`\r\n\r\n## 3. 每周自动更新\r\n\r\n通过Linux的`crontab`，让`run.sh`每`周日`运行一次。\r\n\r\n`run.sh`：启动若干个后台程序，进行精确匹配或搜索。所有后台程序结束后，将导出数据库内容（分别导出为`.sql`格式和`.csv`格式），然后进行打包，发布到本仓库的`release`页面下。\r\n\r\n## 4. 结果【最后更新于2020-04-15】\r\n\r\n+ 精确匹配了`10万`余次，查找到存在的用户`8千`余个\r\n\r\n\r\n\r\n+ 另外，进行关键词搜索得到`4510`条记录\r\n\r\n\r\n\r\n下面是分析后的数据\r\n\r\n### 4.1 最`正统`的MisakaSister：[ 5314 个 ]\r\n\r\n注：后面出现的`%d`都代表一个数字\r\n\r\n+ 御坂%d号\r\n+ 御坂妹妹%d号\r\n\r\n\r\n\r\n```SQL\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂[0-9]+号$'\r\nUNION\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂妹妹[0-9]+号$'\r\nUNION\r\nSELECT nickname AS unique_name FROM MisakaSisters.nicknames WHERE exist = 1 and nickname REGEXP '^御坂[0-9]+号$'\r\nUNION\r\nSELECT nickname AS unique_name FROM MisakaSisters.nicknames WHERE exist = 1 and nickname REGEXP '^御坂妹妹[0-9]+号$';\r\n```\r\n\r\n另外，有23个用户将数字`0`替换成字母`O`进行注册，很遗憾，没有将你们算入正统。\r\n\r\n\r\n\r\n### 4.2 比较纯粹的MisakaSister [ 8824 个 ]\r\n\r\n昵称中只有`Misaka`、`御坂`、`御坂妹妹`、`号`以及数字编号的用户。\r\n\r\n+ Misaka%d\r\n+ 御坂%d\r\n+ 御坂%d号\r\n+ 御坂妹妹%d\r\n+ 御坂妹妹%d号\r\n\r\n\r\n\r\n```SQL\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^[mM][iI][sS][aA][kK][aA][O0-9]+$'\r\nUNION\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂[O0-9]+$'\r\nUNION\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂[O0-9]+号$'\r\nUNION\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂妹妹[O0-9]+$'\r\nUNION\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info where name REGEXP '^御坂妹妹[O0-9]+号$'\r\nUNION\r\nSELECT nickname AS unique_name FROM MisakaSisters.nicknames WHERE exist = 1;\r\n```\r\n\r\n### 4.3 较为全面(宽松)的统计 [ 9426 个 ]\r\n\r\n也就是b站有 `9426+ `个御坂妹妹。\r\n\r\n昵称中含有`Misaka`、`御坂`、`御坂妹妹`、`号`、数字以及其他字符的用户。\r\n\r\n<font color=\"red\">但是数字必须是有编号的意思，</font>如`我是御坂10032号`是符合要求的。而`御坂御坂LV6`就不符合要求。需要人工剔除（唉，我太难了）。\r\n\r\n\r\n\r\n```SQL\r\nSELECT name AS unique_name FROM MisakaSisters.misaka_sisters_info WHERE misaka_id <> -1\r\nUNION\r\nSELECT nickname AS unique_name FROM MisakaSisters.nicknames WHERE exist = 1;\r\n```\r\n\r\n### 4.4 编号不合法 [ 53 个 ]\r\n\r\n+ misaka_id > 20001\r\n\r\n\r\n\r\n```SQL\r\nSELECT * FROM MisakaSisters.misaka_sisters_info WHERE misaka_id > 20001;\r\n```\r\n\r\n### 4.5 最火的MisakaSister [ 10032 号 ]\r\n\r\n导出数据为`csv`，使用`Excel`进一步分析\r\n\r\n```SQL\r\nSELECT name AS unique_name, misaka_id FROM MisakaSisters.misaka_sisters_info WHERE misaka_id <> -1\r\nUNION\r\nSELECT nickname AS unique_name, misaka_id FROM MisakaSisters.nicknames WHERE exist = 1\r\nINTO OUTFILE '/var/lib/mysql-files/unique_name_misaka_id.csv' \r\nFIELDS TERMINATED BY ',' OPTIONALLY ENCLOSED BY '';\r\n```\r\n\r\n出现次数大于`5`次的`misaka_id`如下图所示。\r\n\r\n其中前五名分别为\r\n\r\n+ 10032\r\n+ 20001（最后之作）\r\n+ 10086 （很有中国特色！）\r\n+ 19090\r\n+ 9982\r\n\r\n\r\n\r\n## 5. 数据(表)说明\r\n\r\n+ `misaka_sisters_info`：基于关键词搜索得到的结果，信息较为详细，包括用户id(mid)，misaka_id，签名(sign)，头像URL(face)，粉丝数(fan)，视频数(video)，等级(level)等。\r\n + `misaka_id`：为`-1`说明该条记录和御坂妹妹无关。否则就代表御坂编号（经过人工筛选，99%+的可信率）\r\n + `exact`：为`0`表示前面的`misaka_id`是程序提取的，需要人工确认。为`1`表示较为精确(不排除极少数例外)。经过人工筛选，所有的`exact`均已经置为`1`。\r\n+ `nicknames`：精确匹配的结果。信息简略，只能判断该用户名是否存在。\r\n + `nickname`：昵称（用户名）\r\n + `exist`：是否存在。`1`表示存在，`0`表示不存在。该字段100%可信。\r\n\r\n数据每周日更新一次。最新的数据中，相比之前新增的数据需要人工确认。（我应该会选择性的确认部分数据）。\r\n\r\n## 6. Hahahaha\r\n\r\n+ `lever5`：单词拼错，还好无意间看到了（之前筛选过`level`，没想到后来又看到一个`lever`）\r\n\r\n+ 给呱太编号的：`御坂美琴的呱呱太1508`，想混进御坂网络，没门。\r\n+ 签名是一幅画\r\n\r\n\r\n\r\n+ “御坂32001倒写”，可想而知`10032`有多抢手\r\n+ “御坂野穹12138”，剔除。（在网上也没搜到“御坂野穹”是谁，暂且剔除吧）。\r\n+ “御坂10032的黑猫”。剔除。\r\n+ “爱御坂美琴的黑子1997”。你给黑子编啥号啊（也有可能是指1997年吧，出生年份，maybe）。\r\n+ “御板黑子001”。又一个。\r\n+ “L5の御坂”。呃呃，我查询了`Level`、`LV`，你竟然用`L5`，还好后来搜索`5`的时候找到了你，把你剔除。\r\n\r\n## END\r\n\r\n<leopard.c@outlook.com>\r\n"
},
{
"alpha_fraction": 0.686274528503418,
"alphanum_fraction": 0.686274528503418,
"avg_line_length": 10.333333015441895,
"blob_id": "3a14b46d5d04c66b74ad1b9943cbdf955ede3fbb",
"content_id": "2b1a4640c9385126f046f2729ba037c914e79406",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 102,
"license_type": "no_license",
"max_line_length": 28,
"num_lines": 9,
"path": "/list/proxy/README.md",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "## Format of proxy.list\n\n+ Require Auth\n\n`HTTP IP:PORT USER:PASSWORD`\n\n+ No Auth\n\n`HTTP IP:PORT NULL`\n"
},
{
"alpha_fraction": 0.6492753624916077,
"alphanum_fraction": 0.6550724506378174,
"avg_line_length": 27.75,
"blob_id": "7f8d480fb00e32b2fea248ee990c9f7cfc2ece55",
"content_id": "bdb42870fb8b50c8ee736e7506243c911db018d5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 345,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 12,
"path": "/src/User.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"User.h\"\n\nbool User::getInfo(int64_t mid, std::string& response) {\n client.clearParam();\n client.emplaceParam(\"mid\", mid);\n client.emplaceParam(\"jsonp\", \"jsonp\");\n std::string url = \"https://api.bilibili.com/x/space/acc/info?\";\n url += client.getMergedParam();\n client.setUrl(url);\n\n return client.Get(response);\n}\n"
},
{
"alpha_fraction": 0.6309523582458496,
"alphanum_fraction": 0.6309523582458496,
"avg_line_length": 18.090909957885742,
"blob_id": "33d199bd74c311636415b3e76dd33621eeaf93d6",
"content_id": "ca6e1cc4c3c963fea7fcb939b48b5816c964b868",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 420,
"license_type": "no_license",
"max_line_length": 71,
"num_lines": 22,
"path": "/src/MysqlDB.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#pragma once\n\n#include <mysql/mysql.h>\n\n\nclass MysqlDB {\npublic:\n MysqlDB();\n ~MysqlDB();\n\n bool connect(const char* host, unsigned int port, const char* user,\n const char* pwd, const char* db_name);\n bool connect(const char* dbInfoFile);\n bool exec(const char* sql);\n\n MYSQL_RES* getResult() const { return result; }\n\nprivate:\n MYSQL* mysql;\n MYSQL_RES* result;\n MYSQL_ROW row;\n};\n"
},
{
"alpha_fraction": 0.4457516372203827,
"alphanum_fraction": 0.4852578043937683,
"avg_line_length": 27.920167922973633,
"blob_id": "5e81ad6a8a3bb22f603a093f920b0aa6c3d6a941",
"content_id": "63c80ea686e331eff8abe8be297d864296b4fabd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7093,
"license_type": "no_license",
"max_line_length": 97,
"num_lines": 238,
"path": "/python_Abandoned/searchMisakaSisters.py",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/python3\n\nimport csv\nimport re\nimport requests\nimport time\nimport os\nimport sys\nimport codecs\nfrom lxml import etree\n\nuids = []\nflag1 = False\nflag2 = False\nflag3 = False\ntime_start = time.time()\n\nif not os.path.exists('./cache'):\n os.mkdir('./cache')\n\n# 记录已经读取的用户的唯一id\n# 防止重复\nuidsFile = open('./cache/uids', 'a+')\n\n\ndef searchYuBan(keyword):\n results = []\n\n global time_start\n global flag1\n global flag2\n global flag3\n global uids\n\n # Bilibili return 50 pages at most (20 records in one page)\n for i in range(1, 51): # page\n # 每隔30s暂停5s\n time_end = time.time()\n duration = time_end - time_start\n if duration > 300:\n print('Sleeping 30s')\n time.sleep(30)\n time_start = time_end\n flag1 = flag2 = flag3 = False\n elif duration > 210 and flag3 == False:\n print('Sleeping 30s')\n time.sleep(30)\n flag3 = True\n elif duration > 110 and flag2 == False:\n print('Sleeping 20s')\n time.sleep(20)\n flag2 = True\n elif duration > 60 and flag1 == False:\n print('Sleeping 10s')\n time.sleep(10)\n flag1 = True\n\n print(keyword, \" page=\", i)\n\n url = \"https://search.bilibili.com/upuser?keyword=\" + keyword + \"&page=\" + str(i)\n try:\n res = requests.get(url)\n except BaseException as e:\n print(e)\n sleep(60)\n res = requests.get(url)\n\n if res.text.find('没有相关数据') != -1:\n break\n if res.status_code != 200:\n res = requests.get(url)\n\n html = etree.HTML(res.text)\n uls = html.xpath('//*[@id=\"user-list\"]/div[1]/ul')\n\n if len(uls) == 0:\n continue\n\n for li in range(1, len(uls[0]) + 1):\n ahrefXPath = '//*[@id=\"user-list\"]/div[1]/ul/li[%d]/div[2]/div[1]/a[1]/@href' %(li)\n atitleXPath = '//*[@id=\"user-list\"]/div[1]/ul/li[%d]/div[2]/div[1]/a[1]/@title' %(li)\n ahrefs = html.xpath(ahrefXPath)\n atitles = html.xpath(atitleXPath)\n\n if len(ahrefs) == 0 or len(atitles) == 0:\n continue\n\n ahref = ahrefs[0]\n atitle = atitles[0]\n\n uname = atitle\n uid = ahref[ahref.find('com/')+4 : ahref.find('?')]\n\n # 是否重复\n if uid in uids:\n print(\"repeat: \", uid)\n continue\n else:\n uids.append(uid)\n\n uurl = 'https://space.bilibili.com/' + uid\n sisterId = re.findall('\\d+', uname);\n\n if sisterId:\n row = [uurl, uid, uname]\n for digit in sisterId:\n row.append(int(digit))\n print(row)\n results.append(row)\n\n # 本页用户数不为20，说明已到最后一页\n if len(uls[0]) != 20:\n print('break')\n break\n\n return results\n\n\ndef searchYuBanByIDs(startId, endId):\n results = []\n for i in range(startId, endId):\n keyword = '%E5%BE%A1%E5%9D%82%20' + str(i)\n resultTmp = searchYuBan(keyword)\n if resultTmp:\n results.extend(resultTmp)\n return results\n\n\ndef saveToFile(results, fileName):\n fileHeader = [\"UserSpaceUrl\", \"UserId\", \"UserFullName\", \"sisterID...\"]\n csvFile = open(fileName, \"w\")\n csvFile = codecs.open(fileName, 'w', encoding='utf-8')\n writer = csv.writer(csvFile)\n writer.writerow(fileHeader)\n for record in results:\n writer.writerow(record)\n csvFile.close()\n\n\ndef readUidsFile():\n global uidsFile\n uidsFile.seek(0)\n length = uidsFile.tell()\n lines = uidsFile.readlines()\n for i in range(0, len(lines)):\n uids.append(lines[i].rstrip('\\n'))\n uidsFile.close()\n uidsFile = open('./cache/uids', 'w')\n\n print(uids)\n\ndef mergeFiles():\n root_path = './cache'\n outputFileName = 'YubanSisters.csv'\n outputFile = codecs.open(outputFileName, 'w', encoding='utf-8')\n fileHeader = [\"UserSpaceUrl\", \"UserId\", \"UserFullName\", \"sisterID...\"]\n writer = csv.writer(outputFile)\n writer.writerow(fileHeader)\n for i in os.walk(root_path):\n for j in i[2]:\n path = os.path.join(i[0], j)\n csvFile = codecs.open(path, 'r', encoding='utf-8')\n reader = csv.reader(csvFile)\n for iRow,row in enumerate(reader):\n if iRow > 0 and len(row) > 2: # Read from line 2 and except file 'uids'\n writer.writerow(row)\n csvFile.close()\n outputFile.close()\n\n\nif __name__ == '__main__':\n try:\n time_start = time.time()\n\n readUidsFile()\n\n startId = 0\n endId = 300001\n step = 300\n\n # Input endId form command line\n # default value is 30001\n #\n if len(sys.argv) > 1:\n endId = int(sys.argv[1])\n\n # Search by id\n # '御坂 0' ~ '御坂 30000'\n #\n for i in range(startId, endId, step):\n start = i\n end = i + step\n if end > endId:\n end = endId\n results = searchYuBanByIDs(start, end)\n if results:\n fileName = './cache/' + str(start) + '-' + str(end)\n saveToFile(results, fileName)\n\n # Blur search (by keywords)\n keywords = [\n '%E5%BE%A1%E5%9D%82', # 御坂\n '%E5%BE%A1%E5%9D%82%E5%BE%A1%E5%9D%82', # 御坂御坂\n '%E5%BE%A1%E5%9D%82%20%E5%8F%B7', # 御坂 号\n '%E5%BE%A1%E5%9D%82%E5%A6%B9%E5%A6%B9', # 御坂妹妹\n '%E5%BE%A1%E5%9D%82%2000', # 御坂 00 (%20代表空格)\n '%E5%BE%A1%E5%9D%82%20000', # 御坂 000\n '%E5%BE%A1%E5%9D%82%200000', # 御坂 0000\n '%E5%BE%A1%E5%9D%82%2000000', # 御坂 00000\n '%E5%BE%A1%E5%9D%82%20o', # 御坂 o (用字母o代表数字0)\n '%E5%BE%A1%E5%9D%82%20oo', # 御坂 oo\n '%E5%BE%A1%E5%9D%82%20ooo', # 御坂 ooo\n '%E5%BE%A1%E5%9D%82%20oooo', # 御坂 oooo\n '%E5%BE%A1%E5%9D%82%20ooooo', # 御坂 ooooo\n '%E5%BE%A1%E6%9D%BF', # 御板 (错别字)\n 'yuban', # (拼音)\n 'みさか', # (日语)\n 'misaka'\n ]\n for i in range(0, len(keywords)):\n results = searchYuBan(keywords[i])\n if results:\n fileName = './cache/' + str(i)\n saveToFile(results, fileName)\n\n print(\"OK!\")\n\n except Exception as e:\n print(e)\n finally:\n for uid in uids:\n uidsFile.write(uid)\n uidsFile.write('\\n')\n uidsFile.close()\n\n mergeFiles()\n\n print(\"End\")\n\n\n"
},
{
"alpha_fraction": 0.5502512454986572,
"alphanum_fraction": 0.5678392052650452,
"avg_line_length": 17.904762268066406,
"blob_id": "d036298fd7e72fac815b8a430cefaa451bbcd893",
"content_id": "26e79ca31cbd1742970c981f7cf5cbe039676420",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Lua",
"length_bytes": 398,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 21,
"path": "/xmake.lua",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "\ntarget(\"misaka_sisters\")\n set_kind(\"binary\")\n\n -- std=c++14\n set_languages(\"c99\", \"cxx14\")\n\n -- jsoncpp\n add_includedirs(\"src/jsoncpp\")\n\n -- source files\n add_files(\"src/*.cpp\")\n add_files(\"src/jsoncpp/*.cpp\")\n\n -- link flags\n add_links(\"pthread\", \"curl\", \"mysqlclient\")\n\n -- build dir\n set_targetdir(\".\")\n set_objectdir(\"build/objs\")\n\n add_mflags(\"-O2\")\n"
},
{
"alpha_fraction": 0.5360721349716187,
"alphanum_fraction": 0.5561122298240662,
"avg_line_length": 27.913043975830078,
"blob_id": "95159afc63e32edc41839d49df81a492a4044a76",
"content_id": "0822a2eb8be4c516b7fd7c10c29ad6e1d1c588fd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1996,
"license_type": "no_license",
"max_line_length": 97,
"num_lines": 69,
"path": "/src/main.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"App.h\"\n#include \"Client.h\"\n#include \"Util.h\"\n#include <ctime>\n#include <cstring>\n#include <cstdlib>\n#include <chrono>\n#include <unistd.h>\n#include \"Searcher.h\"\n\nvoid printUsage() {\n util::LogN(\"Usage:\");\n util::LogN(\"\\t misaka_sisetrs [command] [param1] [para2] [param...] [proxy_list_file_name]\");\n util::LogN(\"For example:\");\n util::LogN(\"\\t1. misaka_sisetrs check check.list USE_CACHE proxy.list\");\n util::LogN(\"\\t2. misaka_sisetrs check check.list NO_CACHE proxy.list\");\n util::LogN(\"\\t3. misaka_sisetrs search keyword.list proxy.list\");\n}\n\nint main(int argc, char** argv) {\n if (argc < 4) {\n printUsage();\n return 1;\n }\n\n using namespace std::chrono;\n auto start = system_clock::now();\n srand(time(NULL));\n\n char pidfile[64] = { 0 };\n sprintf(pidfile, \"%s/.misaka/%d\", getenv(\"HOME\"), getpid());\n util::LogToFileF(pidfile, \"%s %s\\n\", argv[1], argv[2]);\n util::LogToFileF(pidfile, \"START\\n\");\n\n if (!Client::LoadProxyIp(argv[argc - 1])) {\n util::LErrorF(\"Load proxy ip failed\\n\");\n util::LogToFileF(pidfile, \"Load proxy ip failed\\n\");\n return 1;\n }\n\n App app;\n\n if (strcmp(argv[1], \"check\") == 0) {\n if (argc != 5) {\n printUsage();\n return 1;\n }\n if (strcmp(argv[3], \"USE_CACHE\") == 0 || strcmp(argv[3], \"1\") == 0) {\n app.check(argv[2], true);\n }\n else if (strcmp(argv[3], \"NO_CACHE\") == 0 || strcmp(argv[3], \"0\") == 0) {\n app.check(argv[2], false);\n }\n }\n else if (strcmp(argv[1], \"search\") == 0) {\n app.search(argv[2]);\n }\n else {\n util::LErrorF(\"Unknown command: %s\\n\", argv[1]);\n }\n\n Client::Quit();\n auto end = system_clock::now();\n auto duration = duration_cast<minutes>(end - start);\n util::LogN(\"Time consuming: \", duration.count(), \"min\");\n util::LogColorF(0, 255, 0, \"Quit successfully!\\n\");\n util::LogToFileF(pidfile, \"QUIT\\n\");\n return 0;\n}\n\n"
},
{
"alpha_fraction": 0.5421753525733948,
"alphanum_fraction": 0.5610432624816895,
"avg_line_length": 27.603174209594727,
"blob_id": "0d3d45cee6870ca6739d9acc2afaa7b3e30b9f9b",
"content_id": "4423673bd18421f5fa48abce1f8cbb6ec11ed341",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 3634,
"license_type": "no_license",
"max_line_length": 79,
"num_lines": 126,
"path": "/src/Util.h",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#ifndef __UTILS_H__\n#define __UTILS_H__\n\n#include <string>\n#include <vector>\n#include <sstream>\n#include <stdarg.h>\n#include <iostream>\n\n\nnamespace util {\n\n extern char g_now[];\n extern char g_cwd[];\n\n // 获取当前时间\n char* getTime(const char* fmt);\n\n // type convert\n template <typename output_type, typename input_type>\n output_type convert(const input_type &input) {\n std::stringstream ss;\n ss << input;\n output_type result;\n ss >> result;\n return result;\n }\n\n // add \"\\\" befor \"'\"\n std::string normalize(const std::string& str);\n\n // get number from string\n std::vector<int> getNumber(const std::string& str);\n\n // 执行shell命令并获取结果\n bool execShell(const char* cmd, char* result, int maxSize);\n\n // replace '0' to 'O'\n std::vector<std::string> replace0toO(const std::string& str);\n\n\n /************************** Print to console ****************************/\n\n // print (use std::cout) no color, no endline\n template<typename T>\n void Log(const T& arg) {\n std::cout << arg;\n }\n\n template<typename T, typename ... Types>\n void Log(const T& arg1, const Types& ... args) {\n std::cout << arg1;\n Log(args...);\n }\n\n // print (use std::cout) no color, with endline\n template<typename T>\n void LogN(const T& arg) {\n std::cout << arg << std::endl;\n }\n\n template<typename T, typename ... Types>\n void LogN(const T& arg1, const Types& ... args) {\n std::cout << arg1;\n LogN(args...);\n }\n\n template<typename T>\n static void LogColor_(const T& arg) {\n std::cout << arg;\n }\n\n template<typename T, typename ... Types>\n static void LogColor_(const T& arg1, const Types& ... args) {\n std::cout << arg1;\n Log(args...);\n }\n\n // print (use std::cout) with color, no endline\n template<typename T, typename ... Types>\n void LogColor(int r, int g, int b, const T& arg1, const Types& ... args) {\n printf(\"\\033[38;2;%d;%d;%dm\", r, g, b);\n LogColor_(arg1, args...);\n printf(\"\\033[0m\");\n }\n\n // print (use std::cout) with color, with endline\n template<typename T, typename ... Types>\n void LogColorN(int r, int g, int b, const T& arg1, const Types& ... args) {\n printf(\"\\033[38;2;%d;%d;%dm\", r, g, b);\n LogColor_(arg1, args...);\n printf(\"\\033[0m\\n\");\n }\n\n void LogF(const char* fmt, ...);\n void LogColorF(int r, int g, int b, const char* fmt, ...);\n\n // encapsulation functions\n template<typename T, typename ... Types>\n void LError(const T& arg1, const Types& ... args)\n { LogColor(255, 0, 0, arg1, args...); }\n template<typename T, typename ... Types>\n void LInfo(const T& arg1, const Types& ... args)\n { LogColor(255, 255, 0, arg1, args...); }\n template<typename T, typename ... Types>\n void LDebug(const T& arg1, const Types& ... args)\n { Log(arg1, args...); }\n\n template<typename T, typename ... Types>\n void LErrorN(const T& arg1, const Types& ... args)\n { LogColorN(255, 0, 0, arg1, args...); }\n template<typename T, typename ... Types>\n void LInfoN(const T& arg1, const Types& ... args)\n { LogColorN(255, 255, 0, arg1, args...); }\n template<typename T, typename ... Types>\n void LDebugN(const T& arg1, const Types& ... args)\n { LogN(arg1, args...); }\n\n void LErrorF(const char* fmt, ...);\n void LInfoF(const char* fmt, ...);\n void LDebugF(const char* fmt, ...);\n\n void LogToFileF(const char* filename, const char* fmt, ...);\n}\n\n#endif // __UTILS_H__\n"
},
{
"alpha_fraction": 0.5847176313400269,
"alphanum_fraction": 0.5863787531852722,
"avg_line_length": 25.159420013427734,
"blob_id": "a9ecc1db8b64872a5c12587caec750b8fe285b44",
"content_id": "09635e9d397a1a476e347e724dbe3310a247a2f8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 1806,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 69,
"path": "/src/MysqlDB.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"MysqlDB.h\"\n#include \"Util.h\"\n#include \"jsoncpp/json/json.h\"\n#include <fstream>\n\nMysqlDB::MysqlDB()\n : mysql(nullptr), result(nullptr)\n{\n mysql = mysql_init(mysql);\n if (!mysql) {\n util::LErrorN(\"Mysql Init error\");\n }\n}\n\nMysqlDB::~MysqlDB() {\n if (!mysql) {\n mysql_close(mysql);\n }\n}\n\nbool MysqlDB::connect(const char* host, unsigned int port, const char* user,\n const char* pwd, const char* db_name) {\n mysql = mysql_real_connect(mysql, host, user, pwd,\n db_name, port, NULL, 0); \n if (!mysql) {\n util::LErrorF(\"Connect db failed: %s\\n\", mysql_error(mysql));\n return false;\n }\n mysql_set_character_set(mysql,\"utf8\");\n return true;\n}\n\nbool MysqlDB::connect(const char* dbInfoFile) {\n std::ifstream ifs(dbInfoFile);\n if (!ifs.is_open()) {\n util::LErrorF(\"Read dbInfoFile failed: %s\\n\", dbInfoFile);\n return false;\n }\n\n Json::Reader reader;\n Json::Value root;\n if (!reader.parse(ifs, root, false)) {\n util::LErrorF(\"Parse dbInfoFile failed: %s\\n\", dbInfoFile);\n ifs.close();\n return false;\n }\n\n std::string host = root[\"host\"].asString();\n unsigned int port = root[\"port\"].asUInt();\n std::string user = root[\"user\"].asString();\n std::string pwd = root[\"password\"].asString();\n std::string dbname = root[\"dbname\"].asString();\n\n ifs.close();\n return connect(host.c_str(), port, user.c_str(), pwd.c_str(), dbname.c_str());\n}\n\nbool MysqlDB::exec(const char* sql) {\n if (result) {\n mysql_free_result(result);\n result = nullptr;\n }\n if (mysql_query(mysql, sql) != 0) {\n util::LErrorF(\"Exec sql error: %s\\n\", mysql_error(mysql));\n return false;\n }\n result = mysql_store_result(mysql);\n return true;\n}\n\n"
},
{
"alpha_fraction": 0.508385419845581,
"alphanum_fraction": 0.5221966505050659,
"avg_line_length": 22.55813980102539,
"blob_id": "7f0cb5dc9184b95038906c37227167e231e3f03f",
"content_id": "7c7428ea5bf15ff767adc3f200198d8cc034645c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 3041,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 129,
"path": "/run.sh",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\n\nPROJ_Dir=/root/doc/prog/cpp/MisakaSisters\nprogram=$PROJ_Dir/misaka_sisters\n\nList=$PROJ_Dir/list\nProxyList=$List/proxy/1.list\n\n# directory to save pid file\nif [ ! -d \"$HOME/.misaka\" ]; then\n mkdir $HOME/.misaka\nelse\n rm $HOME/.misaka/*\nfi\n\n\n# check\npid=`nohup $program check $List/check/1.list NO_CACHE $ProxyList > /dev/null & echo $!`\npids=($pid)\npidsRunning=(1)\npids[1]=`nohup $program check $List/check/2.list NO_CACHE $ProxyList > /dev/null & echo $!`\npidsRunning[1]=1\npids[2]=`nohup $program check $List/check/3.list NO_CACHE $ProxyList > /dev/null & echo $!`\npidsRunning[2]=1\n\n## search\npids[3]=`nohup $program search $List/search/1.list $ProxyList > /dev/null & echo $!`\npidsRunning[3]=1\n\n\n# Wait for all background program exit\nwhile [ 1 ]\ndo\n for((i=0;i<${#pids[@]};i++))\n do\n pid=${pids[i]}\n running=${pidsRunning[i]}\n if [ $running -eq 0 ]; then\n continue\n fi\n\n # check pid exist\n ps -ax | awk '{ print $1 }' | grep -e \"$pid\"\n if [ $? -ne 0 ]; then\n pidsRunning[i]=0\n continue\n fi\n\n continue\n\n # check pid file\n pidfile=\"~/.misaka/$pid\"\n if [ ! -e pidfile ]; then pidsRunning[i]=1; continue; fi\n arr=(`tail -n1 $pidfile`)\n if [ ${#arr[@]} -eq 0 ]; then\n # error\n # won't happen\n pidsRunning[i]=0\n else\n if [ ${arr[0]} = \"QUIT\" ]; then\n pidsRunning[i]=0\n elif echo ${arr[0]} | grep -q '[^0-9]'; then\n current=`date \"+%Y-%m-%d %H:%M:%S\"`\n timeStamp=`date -d \"$current\" +%s` \n timeSpan=`expr $timeStamp -${arr[0]}`\n if [ $timeSpan -gt 500 ]; then\n pidsRunning[i]=0\n fi\n fi\n fi\n done\n\n # all program quit\n count=0\n for((i=0;i<${#pidsRunning[@]};i++))\n do\n if [ ${pidsRunning[i]} -eq 0 ]; then\n ((count++))\n fi\n done\n echo \"count=$count\"\n if [ $count -eq ${#pidsRunning[@]} ]; then\n break\n fi\n\n sleep 60\ndone\n\n\n##################################\n# export data #\n##################################\n\n# date\nDataDir=$PROJ_Dir/data\nNOW=`date +%Y%m%d_%H%M%S`\nDataDirForThis=$DataDir/$NOW\nif [ ! -d \"$DataDirForThis\" ]; then\n mkdir -p $DataDirForThis\nfi\n\ntb_misaka_sisters_info=/var/lib/mysql-files/misaka_sisters_info.csv\ntb_nicknames=/var/lib/mysql-files/nicknames.csv\n\nif [ -e \"$tb_misaka_sisters_info\" ]; then\n rm $tb_misaka_sisters_info\nfi\nif [ -e \"$tb_nicknames\" ]; then\n rm $tb_nicknames\nfi\n\n#\n# need to create a file ~/.my.cnf\n# and write:\n# [client]\n# password=your_password\n# user=root \n#\n# 1. sql file\nmysqldump MisakaSisters > $DataDirForThis/db.sql\n# 2. csv file\nmysql -N < $PROJ_Dir/sql/export.sql\ncp $tb_misaka_sisters_info $DataDirForThis\ncp $tb_nicknames $DataDirForThis\n\n\n####################################\n# git tag and release #\n####################################\n\n\n"
},
{
"alpha_fraction": 0.47641921043395996,
"alphanum_fraction": 0.5021833777427673,
"avg_line_length": 22.126262664794922,
"blob_id": "5d2360ed31d902ebbcf38f2594fbeccdaa976df8",
"content_id": "796269957a07449d6b49aa8a31148381b3b7da6f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "C++",
"length_bytes": 4610,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 198,
"path": "/src/Util.cpp",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "#include \"Util.h\"\n\n#include <algorithm>\n#include <cstdlib>\n#include <cstring>\n#include <unistd.h>\n\nnamespace util {\n\nchar g_now[32] = { 0 };\nchar g_cwd[256] = { 0 };\n\nvoid LErrorF(const char* fmt, ...) {\n printf(\"\\033[38;2;255;0;0m\");\n va_list args;\n va_start(args, fmt);\n vprintf(fmt, args);\n va_end(args);\n printf(\"\\033[0m\");\n}\n\nvoid LInfoF(const char* fmt, ...) {\n printf(\"\\033[38;2;255;255;0m\");\n va_list args;\n va_start(args, fmt);\n vprintf(fmt, args);\n va_end(args);\n printf(\"\\033[0m\");\n}\n\nvoid LDebugF(const char* fmt, ...) {\n va_list args;\n va_start(args, fmt);\n vprintf(fmt, args);\n va_end(args);\n}\n\nvoid LogF(const char* fmt, ...) {\n va_list args;\n va_start(args, fmt);\n vprintf(fmt, args);\n va_end(args);\n}\n\nvoid LogColorF(int r, int g, int b, const char* fmt, ...) {\n printf(\"\\033[38;2;%d;%d;%dm\", r, g, b);\n va_list args;\n va_start(args, fmt);\n vprintf(fmt, args);\n va_end(args);\n printf(\"\\033[0m\");\n}\n\nvoid LogToFileF(const char* filename, const char* fmt, ...) {\n FILE* fp = fopen(filename, \"a+\");\n if (!fp)\n return;\n va_list args;\n va_start(args, fmt);\n vfprintf(fp, fmt, args);\n va_end(args);\n fclose(fp);\n}\n\n// 获取当前时间\nchar* getTime(const char* fmt) {\n time_t now = time(0);\n strftime(g_now, sizeof(g_now), fmt, localtime(&now));\n\n return g_now;\n}\n\nstatic void normalize_(const std::string& ch, std::string& str) {\n auto pos = str.find(ch);\n while (pos != std::string::npos) {\n str.insert(pos, \"\\\\\");\n pos = str.find(ch, pos + 2);\n }\n}\n\n// add \"\\\" befor \"'\"\nstd::string normalize(const std::string& str) {\n std::string ret = str;\n normalize_(\"\\\\\", ret);\n normalize_(\"'\", ret);\n normalize_(\"%\", ret);\n normalize_(\"<\", ret);\n normalize_(\">\", ret);\n return ret;\n}\n\nstatic int countStartedOne(char c) {\n int bit1 = 1;\n int count = 0;\n for (int i = sizeof(c) * 8 - 1; i >= 0; i--){\n unsigned int x = (((bit1 << i)&c) != 0);\n if (x == 1)\n count++;\n else\n return count;\n }\n}\n\n\n// get number from string\nstd::vector<int> getNumber(const std::string& str) {\n int len = str.length();\n std::vector<int> nums;\n bool isNumStarted = false;\n int start = 0, end = 0;\n for (int i = 0; i < len; /*++i*/) {\n char c = str[i];\n if (c >= '0' && c <= '9') {\n if (!isNumStarted) {\n isNumStarted = true;\n start = i;\n }\n i++;\n }\n else {\n if (isNumStarted) {\n isNumStarted = false;\n end = i;\n nums.push_back(util::convert<int>(str.substr(start, end - start)));\n }\n if (c < 0) {\n i += countStartedOne(str[i]);\n }\n else {\n i++;\n }\n }\n }\n\n if (isNumStarted) {\n isNumStarted = false;\n end = len;\n nums.push_back(util::convert<int>(str.substr(start, end - start)));\n }\n\n return nums;\n}\n\n\n// 执行shell命令并获取输出\nbool execShell(const char* cmd, char* result, int maxSize) {\n FILE* fp = popen(cmd, \"r\");\n if (!fp)\n return false;\n\n char buf[1024] = { 0 };\n while (fgets(buf, 1024, fp) != NULL) {\n if (strlen(result) + 1024 <= maxSize)\n strcat(result, buf);\n else\n strncat(result, buf, maxSize - strlen(result));\n memset(buf, 0, 1024);\n }\n pclose(fp);\n fp = NULL;\n\n return true;\n}\n\n// replace '0' to 'O'\n// for example:\n// input: str = \"misaka10032\"\n// output: misaka10032 misaka1O032 misaka10O32 misaka1OO32\nstd::vector<std::string> replace0toO(const std::string& str) {\n std::vector<std::string> ret;\n // find all '0'\n std::vector<int> positions;\n std::string::size_type pos = -1;\n // replace \"0\" to \" \"O\"\n while ((pos = str.find(\"0\", pos + 1)) != std::string::npos) {\n positions.push_back(pos);\n }\n int count = positions.size();\n // permutation\n for (int i = 0; i < count + 1; ++i) {\n std::vector<std::string> chars;\n for (int j = 0; j < i ; ++j)\n chars.push_back(\"0\");\n for (int j = i; j < count; ++j)\n chars.push_back(\"O\");\n do {\n std::string strNew = str;\n for (int k = 0; k < count; ++k) {\n strNew.replace(positions[k], 1, chars[k]);\n }\n ret.push_back(strNew);\n } while (next_permutation(chars.begin(), chars.end()));\n }\n\n return ret;\n}\n\n} // namespace util\n\n"
},
{
"alpha_fraction": 0.6045317053794861,
"alphanum_fraction": 0.6755287051200867,
"avg_line_length": 34.9782600402832,
"blob_id": "0a7a15e6c0b46e79c7e4e0d030483493bf953998",
"content_id": "c177297f7c01db71019677dcbd0b4fd1763a1678",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "SQL",
"length_bytes": 3310,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 92,
"path": "/sql/MisakaSisters_db.sql",
"repo_name": "Leopard-C/MisakaSisters",
"src_encoding": "UTF-8",
"text": "-- MySQL dump 10.13 Distrib 5.7.29, for Linux (x86_64)\n--\n-- Host: localhost Database: MisakaSisters\n-- ------------------------------------------------------\n-- Server version\t5.7.29-0ubuntu0.18.04.1\n\n/*!40101 SET @OLD_CHARACTER_SET_CLIENT=@@CHARACTER_SET_CLIENT */;\n/*!40101 SET @OLD_CHARACTER_SET_RESULTS=@@CHARACTER_SET_RESULTS */;\n/*!40101 SET @OLD_COLLATION_CONNECTION=@@COLLATION_CONNECTION */;\n/*!40101 SET NAMES utf8 */;\n/*!40103 SET @OLD_TIME_ZONE=@@TIME_ZONE */;\n/*!40103 SET TIME_ZONE='+00:00' */;\n/*!40014 SET @OLD_UNIQUE_CHECKS=@@UNIQUE_CHECKS, UNIQUE_CHECKS=0 */;\n/*!40014 SET @OLD_FOREIGN_KEY_CHECKS=@@FOREIGN_KEY_CHECKS, FOREIGN_KEY_CHECKS=0 */;\n/*!40101 SET @OLD_SQL_MODE=@@SQL_MODE, SQL_MODE='NO_AUTO_VALUE_ON_ZERO' */;\n/*!40111 SET @OLD_SQL_NOTES=@@SQL_NOTES, SQL_NOTES=0 */;\n\n--\n-- Table structure for table `misaka_sisters_info`\n--\n\nDROP TABLE IF EXISTS `misaka_sisters_info`;\n/*!40101 SET @saved_cs_client = @@character_set_client */;\n/*!40101 SET character_set_client = utf8 */;\nCREATE TABLE `misaka_sisters_info` (\n `mid` bigint(20) NOT NULL,\n `name` varchar(30) DEFAULT NULL,\n `misaka_id` int(11) DEFAULT NULL,\n `exact` tinyint(1) DEFAULT NULL,\n `level` tinyint(1) DEFAULT NULL,\n `sign` varchar(300) DEFAULT NULL,\n `gender` tinyint(1) DEFAULT NULL,\n `face` varchar(100) DEFAULT NULL,\n `fans` int(11) DEFAULT NULL,\n `videos` int(11) DEFAULT NULL,\n PRIMARY KEY (`mid`)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n/*!40101 SET character_set_client = @saved_cs_client */;\n\n--\n-- Table structure for table `misaka_sisters_info_error`\n--\n\nDROP TABLE IF EXISTS `misaka_sisters_info_error`;\n/*!40101 SET @saved_cs_client = @@character_set_client */;\n/*!40101 SET character_set_client = utf8 */;\nCREATE TABLE `misaka_sisters_info_error` (\n `keyword` varchar(20) NOT NULL,\n `misaka_id` int(11) DEFAULT NULL,\n PRIMARY KEY (`keyword`)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n/*!40101 SET character_set_client = @saved_cs_client */;\n\n--\n-- Table structure for table `nicknames`\n--\n\nDROP TABLE IF EXISTS `nicknames`;\n/*!40101 SET @saved_cs_client = @@character_set_client */;\n/*!40101 SET character_set_client = utf8 */;\nCREATE TABLE `nicknames` (\n `nickname` varchar(30) NOT NULL,\n `exist` tinyint(1) DEFAULT NULL,\n `misaka_id` int(11) DEFAULT NULL,\n PRIMARY KEY (`nickname`)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n/*!40101 SET character_set_client = @saved_cs_client */;\n\n--\n-- Table structure for table `nicknames_error`\n--\n\nDROP TABLE IF EXISTS `nicknames_error`;\n/*!40101 SET @saved_cs_client = @@character_set_client */;\n/*!40101 SET character_set_client = utf8 */;\nCREATE TABLE `nicknames_error` (\n `nickname` varchar(30) NOT NULL,\n `misaka_id` int(11) DEFAULT NULL,\n PRIMARY KEY (`nickname`)\n) ENGINE=InnoDB DEFAULT CHARSET=utf8;\n/*!40101 SET character_set_client = @saved_cs_client */;\n/*!40103 SET TIME_ZONE=@OLD_TIME_ZONE */;\n\n/*!40101 SET SQL_MODE=@OLD_SQL_MODE */;\n/*!40014 SET FOREIGN_KEY_CHECKS=@OLD_FOREIGN_KEY_CHECKS */;\n/*!40014 SET UNIQUE_CHECKS=@OLD_UNIQUE_CHECKS */;\n/*!40101 SET CHARACTER_SET_CLIENT=@OLD_CHARACTER_SET_CLIENT */;\n/*!40101 SET CHARACTER_SET_RESULTS=@OLD_CHARACTER_SET_RESULTS */;\n/*!40101 SET COLLATION_CONNECTION=@OLD_COLLATION_CONNECTION */;\n/*!40111 SET SQL_NOTES=@OLD_SQL_NOTES */;\n\n-- Dump completed on 2020-04-14 16:25:58\n"
}
] | 25
|
Huanhuan14704/Python-002
|
https://github.com/Huanhuan14704/Python-002
|
70d1ad32e5c058007932daacc9968980df0ff1b5
|
4d2299e0b1ebba57704f0d1eac92f49fe32cdc12
|
1d82ca32df018abbcbd630723378e6be3d8d8947
|
refs/heads/master
| 2022-11-23T19:06:47.482882
| 2020-07-26T12:12:55
| 2020-07-26T12:12:55
| 281,342,108
| 0
| 0
| null | 2020-07-21T08:35:51
| 2020-07-19T15:13:25
| 2020-07-15T06:43:24
| null |
[
{
"alpha_fraction": 0.6581892371177673,
"alphanum_fraction": 0.6948118209838867,
"avg_line_length": 24.789474487304688,
"blob_id": "fc340347882d24e3de7a2f8e015c266539175a5e",
"content_id": "3bcbaa6af1800461b001a2f4f42b8c6c0a6aa086",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1047,
"license_type": "no_license",
"max_line_length": 136,
"num_lines": 38,
"path": "/week01/homework01.py",
"repo_name": "Huanhuan14704/Python-002",
"src_encoding": "UTF-8",
"text": "import requests\nfrom bs4 import BeautifulSoup as bs\nimport time\n\n\nuser_agent = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'\n\nheader = {'user-agent':user_agent}\n\nmyurl = 'https://maoyan.com/films?showType=3'\n\nresponse = requests.get(myurl,headers=header)\n\nbs_info = bs(response.text, 'html.parser')\n\n# 获取页面上所有电影链接后缀列表\nurls_suffix = []\n\nfor dds in bs_info.find_all('dl', attrs={'class': 'movie-list'}):\n for atag in dds.find_all('a'):\n #print(atag.get('href'))\n urls_suffix.append(atag.get('href'))\n\n# 只取前n个电影\nfirst_n = 10 # <=30 len(urls_suffix)\nurls_suffix_first_n = urls_suffix[:first_n]\n\n# 获得所需前10个完整链接的tuple\nurls = tuple(f'https://maoyan.com{url_suffix}' for url_suffix in urls_suffix_first_n)\n\nprint (urls)\n\n# parse first film page\nurl_one_film = urls[0]\nprint(url_one_film)\n\nr_one_film = requests.get(url_one_film,headers=header)\nbs_one_film = bs(r_one_film.text, 'html.parser')\n\n\n\n"
}
] | 1
|
kodeutility/Square_real_estate_agency_project
|
https://github.com/kodeutility/Square_real_estate_agency_project
|
15a257508133760960710075d98fb73704643764
|
f534360f2b1749527c4e217a1e7c140339e98da1
|
15ea39d670107f5f5c033f52e8f52674eb7de5fb
|
refs/heads/master
| 2020-04-22T22:26:24.947710
| 2019-02-23T13:47:49
| 2019-02-23T13:47:49
| 170,708,168
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.736952006816864,
"alphanum_fraction": 0.7411273717880249,
"avg_line_length": 35.846153259277344,
"blob_id": "67dc32a471dc1500777eaa2d22663aac3e8a4022",
"content_id": "6524cf37426c77351b36bcef5f305c37f06ffee0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 479,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 13,
"path": "/square_re_agency/pages/views.py",
"repo_name": "kodeutility/Square_real_estate_agency_project",
"src_encoding": "UTF-8",
"text": "from django.shortcuts import render\nfrom listings.models import Listing\nfrom realtors.models import Realtor\n\n# Create your views here.\ndef index(request):\n listings = Listing.objects.order_by('-list_date').filter(is_published=True)[:3]\n return render(request,'pages/index.html',{'listings':listings})\n\ndef about(request):\n realtors = Realtor.objects.all()\n mvp_realtors = Realtor.objects.filter(is_mvp=True)[:1]\n return render(request,'pages/about.html',locals())\n"
},
{
"alpha_fraction": 0.8278688788414001,
"alphanum_fraction": 0.8278688788414001,
"avg_line_length": 59.5,
"blob_id": "c3c70cc5359e76dde08255aefa1e479928b18806",
"content_id": "0aabf56f8f7f24ef014fc5d2a5764029e73c2bcd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 122,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 2,
"path": "/README.md",
"repo_name": "kodeutility/Square_real_estate_agency_project",
"src_encoding": "UTF-8",
"text": "# Square_real_estate_agency_project\nA real estate web application for imaginary company called Square Real Estate Agency \n"
},
{
"alpha_fraction": 0.7341040372848511,
"alphanum_fraction": 0.7442196607589722,
"avg_line_length": 35.421051025390625,
"blob_id": "8eb73eb5fd9ad58713ef340a31858cf0cbe16a2c",
"content_id": "7a785ff2458323eb9ece4525be6b4e82e606a25c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 692,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 19,
"path": "/square_re_agency/listings/views.py",
"repo_name": "kodeutility/Square_real_estate_agency_project",
"src_encoding": "UTF-8",
"text": "from django.shortcuts import render,get_object_or_404\nfrom django.core.paginator import Paginator\nfrom listings.models import Listing\n\n# Create your views here.\ndef index(request):\n listings_list = Listing.objects.order_by('-list_date').filter(is_published=True)\n paginator = Paginator(listings_list, 2)\n\n page = request.GET.get('page')\n listings = paginator.get_page(page)\n return render(request,'listings/listings.html',{'listings':listings})\n\ndef listing(request,listing_id):\n listing = get_object_or_404(Listing,pk=listing_id)\n return render(request,'listings/listing.html',{'listing':listing})\n\ndef search(request):\n return render(request,'listings/search.html')\n"
}
] | 3
|
ycarissan/plot_spectra
|
https://github.com/ycarissan/plot_spectra
|
da53a88c1e2871abe296e70c57b5b966ac2daf22
|
7bc39906d5d12b346349cee8599abb9a440bfad2
|
ece67f0389289d1f978c083c1dfaec6bffaced65
|
refs/heads/main
| 2023-02-15T02:20:54.664348
| 2021-01-06T10:11:18
| 2021-01-06T10:11:18
| 327,265,068
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5750241875648499,
"alphanum_fraction": 0.6011616587638855,
"avg_line_length": 29.382352828979492,
"blob_id": "fe7d11fe3aded373b0ec35d8c18a4129956a8316",
"content_id": "06d28b19b042cc6987152f8641d47ae4346b63aa",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1033,
"license_type": "no_license",
"max_line_length": 104,
"num_lines": 34,
"path": "/plot_spectra.py",
"repo_name": "ycarissan/plot_spectra",
"src_encoding": "UTF-8",
"text": "import numpy\nimport matplotlib.pyplot as plt\n\ndir=\"/home/avaret/com_irreg_1_9_hexagons/done/classes\"\nfile=\"/home/avaret/com_irreg_1_9_hexagons/done/classes/38_carbons_18_hydrogens/9_hexagons1968_irreg.log\"\n\nfrequencies = []\nintensities = []\nlu = open(file, \"r\")\nfor l in lu.readlines():\n if \"Frequencies\" in l:\n a = l.split()\n frequencies.append(a[2])\n frequencies.append(a[3])\n frequencies.append(a[4])\n if \"IR Inten\" in l:\n a = l.split()\n intensities.append(a[2])\n intensities.append(a[3])\n intensities.append(a[4])\n\nlistlu = open(\"/home/avaret/com_irreg_1_9_hexagons/done/classes/list_dir\", \"r\")\nfor dir in listlu.readlines():\n x=[]\n y=[]\n file=\"/home/avaret/com_irreg_1_9_hexagons/done/classes/\"+dir.strip()+\"results.txt\"\n lu = open(file, \"r\")\n for l in lu.readlines()[12:]:\n l = l.replace(\"Result(\",\"\")\n l = l.replace(\") =\",\"\")\n x.append(float(l.split()[0]))\n y.append(float(l.split()[1]))\n plt.plot(x,y)\n plt.show()\n"
}
] | 1
|
Shubham8037/Rutgers-CS-352
|
https://github.com/Shubham8037/Rutgers-CS-352
|
d8c6f324a0aaa952c2d282b2ad7c28fc4c26d645
|
6377e5b7c17f0f7b5b3a4d7be1c90f5a677f9044
|
ff82c08b048f43f509bcfb28a935af576fd276a4
|
refs/heads/master
| 2023-07-25T03:22:32.897862
| 2021-09-05T10:55:32
| 2021-09-05T10:55:32
| 258,490,823
| 0
| 1
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7838616967201233,
"alphanum_fraction": 0.8126801252365112,
"avg_line_length": 42.375,
"blob_id": "9c7f10eb2b45ed28a797827765f5982917913745",
"content_id": "6ee483cbb62251d9edd0047348bfd0fe98c4e05b",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 347,
"license_type": "permissive",
"max_line_length": 250,
"num_lines": 8,
"path": "/README.md",
"repo_name": "Shubham8037/Rutgers-CS-352",
"src_encoding": "UTF-8",
"text": "# Rutgers CS 352\nCS 352 Internet Technology at Rutgers University\n\nProfessor Desheng Zhang\n\nFall 2019\n\nPlease follow both [Rutgers University's Principles of Academic Integrity](http://academicintegrity.rutgers.edu/) and the [Rutgers Department of Computer Science's Academic Integrity Policy](https://www.cs.rutgers.edu/academic-integrity/introduction)\n"
},
{
"alpha_fraction": 0.6063150763511658,
"alphanum_fraction": 0.6241182684898376,
"avg_line_length": 29.670103073120117,
"blob_id": "494256b57b144e001815f0ea8c422e69ec0cf2c0",
"content_id": "5bdd8c4bd35321195172f9cd1e93cb5b478f78bf",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2977,
"license_type": "permissive",
"max_line_length": 138,
"num_lines": 97,
"path": "/Project 2/client2-1.py",
"repo_name": "Shubham8037/Rutgers-CS-352",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/python\n\n# This is the CS 352 Spring 2017 Client for the 2nd programming\n# project\n\n# (c) 2017, R. P. Martin, under the GPL version 2. \n\nimport argparse\nimport time\nimport struct \nimport os \nimport sock352\n\ndef main():\n # parse all the arguments to the client \n parser = argparse.ArgumentParser(description='CS 352 Socket Client')\n parser.add_argument('-f','--filename', help='File to Send', required=False)\n parser.add_argument('-d','--destination', help='Destination IP Host', required=True)\n parser.add_argument('-p','--port', help='remote sock352 port', required=False)\n parser.add_argument('-u','--udpportRx', help='UDP port to use for receiving', required=True)\n parser.add_argument('-v','--udpportTx', help='UDP port to use for sending', required=False)\n\n\n # get the arguments into local variables \n args = vars(parser.parse_args())\n filename = args['filename']\n destination = args['destination']\n udpportRx = args['udpportRx']\n\n \n if (args['udpportTx']):\n udpportTx = args['udpportTx']\n else:\n udpportTx = ''\n \n # the port is not used in part 2 assignment, except as a placeholder\n if (args['port']): \n port = args['port']\n else:\n port = 5555 \n\n # open the file to send to the server for reading\n if (filename):\n try: \n filesize = os.path.getsize(filename)\n fd = open(filename, \"rb\")\n usefile = True\n except:\n print ( \"error opening file: %s\" % (filename))\n exit(-1)\n else:\n pass \n\n # This is where we set the transmit and receive\n # ports the client uses for the underlying UDP\n # sockets. If we are running the client and\n # server on the same machine, these ports\n # need to be different. If they are running on\n # different machines, we can re-use the same\n # ports. \n if (udpportTx):\n sock352.init(udpportTx,udpportRx)\n else:\n sock352.init(udpportRx,udpportRx)\n\n \n \n # create a socket and connect to the remote server\n s = sock352.socket()\n s.connect((destination,port))\n #mesure the start stamp\n start_stamp = time.clock() \n\t#load the whole file into memory\n whole_file = fd.read()\n #mesure its length\n filesize = len(whole_file)\n longPacker = struct.Struct(\"!L\")\n fileLenPacked = longPacker.pack(filesize);\n s.send(fileLenPacked)\n\t\n sent = s.send(whole_file)\n if (sent != filesize):\n raise RuntimeError(\"socket broken\")\n\n end_stamp = time.clock() \n lapsed_seconds = end_stamp - start_stamp\n \n if (lapsed_seconds > 0.0):\n print (\"client1: sent %d bytes in %0.6f seconds, %0.6f MB/s \" % (filesize, lapsed_seconds, (filesize/lapsed_seconds)/(1024*1024)))\n else:\n print (\"client1: sent %d bytes in %d seconds, inf MB/s \" % (filesize, lapsed_seconds)) \n\n fd.close()\n s.close()\n# this gives a main function in Python\nif __name__ == \"__main__\":\n main()\n\n\n"
},
{
"alpha_fraction": 0.5945619344711304,
"alphanum_fraction": 0.6169184446334839,
"avg_line_length": 28.03508758544922,
"blob_id": "744cc0ecb483b06084be8d21d4bf10d359d2a2ab",
"content_id": "7a5b6e844048997f522a1aae321cb41ca9a19ecf",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3310,
"license_type": "permissive",
"max_line_length": 140,
"num_lines": 114,
"path": "/Project 2/server2-1.py",
"repo_name": "Shubham8037/Rutgers-CS-352",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/python\n\n# This is the CS 352 Spring 2017 server for the 3rd programming\n# project\n\n# (c) 2017, R. P. Martin, under the GPL version 2. \n\nimport argparse\nimport time\nimport struct \nimport os \nimport sock352\nimport random\n\ndef main():\n \n # parse all the arguments to the client \n parser = argparse.ArgumentParser(description='CS 352 Socket Server')\n parser.add_argument('-f','--filename', help='Filename to Receiver', required=False)\n parser.add_argument('-p','--port', help='CS 352 Socket Port (optional for part 1)', required=False)\n parser.add_argument('-u','--udpportRx', help='UDP port to use for receiving', required=True)\n parser.add_argument('-v','--udpportTx', help='UDP port to use for sending', required=False)\n\n args = vars(parser.parse_args())\n\n # open the file for writing\n filename = args['filename']\n udpportRx = args['udpportRx']\n \n if (args['udpportTx']):\n udpportTx = args['udpportTx']\n else:\n udpportTx = ''\n \n # the port is not used in part 1 assignment, except as a placeholder\n if (args['port']): \n port = args['port']\n else:\n port = 1111 \n \n if (filename):\n try: \n fd = open(filename, \"wb\")\n usefile = True\n except:\n print ( \"error opening file: %s\" % (filename))\n exit(-1)\n else:\n pass \n\n # This is where we set the transmit and receive\n # ports the server uses for the underlying UDP\n # sockets. If we are running the client and\n # server on different machines, these ports\n # need to be different, otherwise we can\n # use the same ports\n if (udpportTx):\n sock352.init(udpportTx,udpportRx)\n else:\n sock352.init(udpportRx,udpportRx)\n\n s = sock352.socket()\n\n # set the maximum fragment size we will read on \n MAXFRAGMENTSIZE = 16384\n\n # binding the host to empty allows reception on\n # all network interfaces\n s.bind(('',port))\n s.listen(5)\n\n # when accept returns, the client is connected \n (s2,address) = s.accept() \n\n # this receives the size of the file\n # as a 4 byte integer in network byte order (big endian)\n longPacker = struct.Struct(\"!L\")\n long = s2.recv(4)\n fn = longPacker.unpack(long)\n filelen = fn[0]\n\n # the MD5 computes a unique hash for all the data \n\n bytes_to_receive = filelen\n start_stamp = time.clock()\n \n random.seed(a=352)\n # main loop to receive the data from the client \n while (bytes_to_receive > 0):\n size = random.randrange(1,MAXFRAGMENTSIZE)\n if (bytes_to_receive >= size):\n # pick a random size to receive\n fragment = s2.recv(size)\n else: \n fragment = s2.recv(bytes_to_receive)\n\n bytes_to_receive = bytes_to_receive - len(fragment)\n fd.write(fragment)\n\n end_stamp = time.clock() \n lapsed_seconds = end_stamp - start_stamp\n\n \n if (lapsed_seconds > 0.0):\n print (\"server1: received %d bytes in %0.6f seconds, %0.6f MB/s \" % (filelen, lapsed_seconds, (filelen/lapsed_seconds)/(1024*1024)))\n else:\n print (\"server1: received %d bytes in %d seconds, inf MB/s \" % (filelen, lapsed_seconds))\n fd.close()\n s2.close()\n \n\n# create a main function in Python\nif __name__ == \"__main__\":\n main()\n"
}
] | 3
|
Aleksandr2424/hello-world
|
https://github.com/Aleksandr2424/hello-world
|
0d0e1596fdcbaeff357bb0ffedfc78da64d432a9
|
87c49c682b4bb73909016e22a7593a2a1305dfbb
|
ef94ae364ac677d0f85a0ec640f2563983b3074b
|
refs/heads/master
| 2021-05-14T01:23:23.324049
| 2018-01-31T18:29:43
| 2018-01-31T18:29:43
| 116,564,109
| 0
| 0
| null | 2018-01-07T12:35:46
| 2018-01-07T12:35:46
| 2018-01-07T12:56:53
| null |
[
{
"alpha_fraction": 0.6187845468521118,
"alphanum_fraction": 0.6353591084480286,
"avg_line_length": 16.190475463867188,
"blob_id": "da27d520064b1543498a7b28b02173dac69e7316",
"content_id": "6c96f2e7251fa18d0b7db888deeb1a0b21447701",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 362,
"license_type": "no_license",
"max_line_length": 50,
"num_lines": 21,
"path": "/testGuess.py",
"repo_name": "Aleksandr2424/hello-world",
"src_encoding": "UTF-8",
"text": "from random import randint\n\nfigure = randint(1, 100)\ncounter = 1\nwhile True:\n\twhile True:\n\t\ttry:\n\t\t\tproba = int(input(\"Your choice: \"))\n\t\t\tbreak\n\t\texcept ValueError:\n\t\t\tprint(\"Please, try again\")\n\t\t\n\tif proba == figure:\n\t\tprint(\"You won! You made \", counter, \"attempts\")\n\t\tbreak\n\telse:\n\t\tcounter += 1\n\tif proba > figure:\n\t\tprint(\"Less\")\n\telse:\n\t\tprint(\"More\")\n\n"
}
] | 1
|
EugenBudanow/4_json
|
https://github.com/EugenBudanow/4_json
|
cec1b8905f8f85ec127ce8e792f25493aa732a32
|
3d433e9d42297c47debdcc1f58ca7b08a83012cf
|
b455300d065870688392744eb558f9f2cae0d568
|
refs/heads/master
| 2020-09-13T19:33:44.156694
| 2019-11-28T12:43:08
| 2019-11-28T12:43:08
| 222,883,384
| 0
| 0
| null | 2019-11-20T08:05:17
| 2016-09-04T07:23:11
| 2019-06-11T12:59:43
| null |
[
{
"alpha_fraction": 0.6091160178184509,
"alphanum_fraction": 0.6160221099853516,
"avg_line_length": 24.85714340209961,
"blob_id": "09b0a96e3587ed71dff0921cccbeb2f0ef253154",
"content_id": "34c2356135873423a72aa988f721abab3465041d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 724,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 28,
"path": "/pprint_json.py",
"repo_name": "EugenBudanow/4_json",
"src_encoding": "UTF-8",
"text": "import json\nimport sys\n\n\ndef load_data(filepath):\n try:\n with open(filepath, \"r\", encoding=\"utf-8\") as file:\n return json.load(file)\n except (IOError, json.decoder.JSONDecodeError) as errormsg:\n print(errormsg)\n return\n\n\ndef pretty_print_json(object_with_json):\n if object_with_json:\n readable_json = json.dumps(object_with_json, indent=4, sort_keys=4, ensure_ascii=False)\n return readable_json\n else:\n return \"Error while reading file\"\n\n\nif __name__ == '__main__':\n if len(sys.argv) != 2:\n print(\"Enter a file name\")\n else:\n filename = sys.argv[1]\n json_content = load_data(filename)\n print(pretty_print_json(json_content))\n"
},
{
"alpha_fraction": 0.477027028799057,
"alphanum_fraction": 0.5932432413101196,
"avg_line_length": 22.15625,
"blob_id": "82ef3a6a7efe9d6321c5e04d0c1a45baee008c96",
"content_id": "ed26b40d7e4d15d87e23cbe068083e240df76506",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 740,
"license_type": "no_license",
"max_line_length": 155,
"num_lines": 32,
"path": "/README.md",
"repo_name": "EugenBudanow/4_json",
"src_encoding": "UTF-8",
"text": "# Prettify JSON\n\nSimple JSON formatter\n\n# Example\n\nExample of script launch on Linux, Python 3.5:\n\n`data.json`\n```json data.json\n[{\"_id\":\"5dd64aa002fc1b9a6425d381\",\"index\":0,\"guid\":\"597fa9dc-46c8-4426-bfb1-4cbbb4b4053f\",\"isActive\":true,\"balance\":\"$2,299.91\",\"age\":25,\"name\":\"Jeanette Drake\"}]\n```\n```bash\n\n$ python pprint_json.py data.json\n>>>[\n>>> {\n>>> \"_id\": \"5dd64aa002fc1b9a6425d381\",\n>>> \"index\": 0,\n>>> \"guid\": \"597fa9dc-46c8-4426-bfb1-4cbbb4b4053f\",\n>>> \"isActive\": true,\n>>> \"balance\": \"$2,299.91\",\n>>> \"age\": 25,\n>>> \"name\": \"Jeanette Drake\"\n>>> }\n>>>]\n\n```\n\n# Project Goals\n\nThe code is written for educational purposes. Training course for web-developers - [DEVMAN.org](https://devman.org)"
}
] | 2
|
amolchanov86/quad_sim2multireal
|
https://github.com/amolchanov86/quad_sim2multireal
|
948170c05e3448b94ab881e2d5aede1ef43ba9e8
|
8bb11facfacb00ba19fcae7168c793de44491ed4
|
6f59114f26643e080ec497d8e5159e27869fd0c8
|
refs/heads/master
| 2020-08-31T08:25:55.956908
| 2019-11-16T01:36:50
| 2019-11-16T01:36:50
| 218,647,870
| 16
| 13
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5129205584526062,
"alphanum_fraction": 0.5537068247795105,
"avg_line_length": 38.71929931640625,
"blob_id": "775d97c2f91115c3c39a13aa75c1f92a90939c44",
"content_id": "058993af8491e71f7ae413f74b9e7f3d7100beb3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13583,
"license_type": "no_license",
"max_line_length": 136,
"num_lines": 342,
"path": "/quad_sim/quadrotor_visualization.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom numpy.linalg import norm\nimport copy\n\nimport quad_sim.rendering3d as r3d\nfrom quad_sim.quad_utils import *\n\n# for visualization.\n# a rough attempt at a reasonable third-person camera\n# that looks \"over the quadrotor's shoulder\" from behind\nclass ChaseCamera(object):\n def __init__(self, view_dist=4):\n self.view_dist = view_dist\n\n def reset(self, goal, pos, vel):\n self.goal = goal\n self.pos_smooth = pos\n self.vel_smooth = vel\n self.right_smooth, _ = normalize(cross(vel, npa(0, 0, 1)))\n\n def step(self, pos, vel):\n # lowpass filter\n ap = 0.6\n av = 0.999\n ar = 0.9\n self.pos_smooth = ap * self.pos_smooth + (1 - ap) * pos\n self.vel_smooth = av * self.vel_smooth + (1 - av) * vel\n\n veln, n = normalize(self.vel_smooth)\n up = npa(0, 0, 1)\n ideal_vel, _ = normalize(self.goal - self.pos_smooth)\n if True or np.abs(veln[2]) > 0.95 or n < 0.01 or np.dot(veln, ideal_vel) < 0.7:\n # look towards goal even though we are not heading there\n right, _ = normalize(cross(ideal_vel, up))\n else:\n right, _ = normalize(cross(veln, up))\n self.right_smooth = ar * self.right_smooth + (1 - ar) * right\n\n # return eye, center, up suitable for gluLookAt\n def look_at(self):\n up = npa(0, 0, 1)\n back, _ = normalize(cross(self.right_smooth, up))\n to_eye, _ = normalize(0.9 * back + 0.3 * self.right_smooth)\n eye = self.pos_smooth + self.view_dist * (to_eye + 0.3 * up)\n center = self.pos_smooth\n return eye, center, up\n\n\n# for visualization.\n# In case we have vertical control only we use a side view camera\nclass SideCamera(object):\n def __init__(self, view_dist):\n self.view_dist = view_dist\n\n def reset(self, goal, pos, vel):\n self.goal = goal\n self.pos_smooth = pos\n self.vel_smooth = vel\n self.right_smooth, _ = normalize(cross(vel, npa(0, 0, 1)))\n\n def step(self, pos, vel):\n # lowpass filter\n ap = 0.6\n av = 0.999\n ar = 0.9\n self.pos_smooth = ap * self.pos_smooth + (1 - ap) * pos\n self.vel_smooth = av * self.vel_smooth + (1 - av) * vel\n\n veln, n = normalize(self.vel_smooth)\n up = npa(0, 0, 1)\n ideal_vel, _ = normalize(self.goal - self.pos_smooth)\n if True or np.abs(veln[2]) > 0.95 or n < 0.01 or np.dot(veln, ideal_vel) < 0.7:\n # look towards goal even though we are not heading there\n right, _ = normalize(cross(ideal_vel, up))\n else:\n right, _ = normalize(cross(veln, up))\n self.right_smooth = ar * self.right_smooth + (1 - ar) * right\n\n # return eye, center, up suitable for gluLookAt\n def look_at(self):\n up = npa(0, 0, 1)\n back, _ = normalize(cross(self.right_smooth, up))\n to_eye, _ = normalize(0.9 * back + 0.3 * self.right_smooth)\n # eye = self.pos_smooth + self.view_dist * (to_eye + 0.3 * up)\n eye = self.pos_smooth + self.view_dist * np.array([0, 1, 0])\n center = self.pos_smooth\n return eye, center, up\n\n\n# using our rendering3d.py to draw the scene in 3D.\n# this class deals both with map and mapless cases.\nclass Quadrotor3DScene(object):\n def __init__(self, w, h,\n quad_arm=None, model=None, obstacles=True, visible=True, resizable=True, goal_diameter=None, viewpoint='chase', obs_hw=[64,64]):\n\n self.window_target = None\n self.window_w, self.window_h = w , h\n self.resizable = resizable\n self.viepoint = viewpoint\n self.obs_hw = copy.deepcopy(obs_hw)\n\n # self.world_box = 40.0\n self.quad_arm = quad_arm\n self.obstacles = obstacles\n self.model = model\n\n if goal_diameter:\n self.goal_forced_diameter = goal_diameter\n else:\n self.goal_forced_diameter = None\n self.update_goal_diameter()\n \n if self.viepoint == 'chase':\n self.chase_cam = ChaseCamera(view_dist=self.diameter * 15)\n elif self.viepoint == 'side':\n self.chase_cam = SideCamera(view_dist=self.diameter * 15)\n\n self.scene = None\n self.window_target = None\n self.obs_target = None\n self.video_target = None\n\n def update_goal_diameter(self):\n if self.quad_arm is not None:\n self.diameter = 2 * self.quad_arm\n else:\n self.diameter = 2 * np.linalg.norm(self.model.params[\"motor_pos\"][\"xyz\"][:2])\n \n if self.goal_forced_diameter:\n self.goal_diameter = self.goal_forced_diameter\n else:\n self.goal_diameter = self.diameter\n\n\n def _make_scene(self):\n # if target is None:\n # self.window_target = r3d.WindowTarget(self.window_w, self.window_h, resizable=self.resizable)\n # self.obs_target = r3d.FBOTarget(self.obs_hw[0], self.obs_hw[1])\n # self.video_target = r3d.FBOTarget(self.window_h, self.window_h)\n\n self.cam1p = r3d.Camera(fov=90.0)\n self.cam3p = r3d.Camera(fov=45.0)\n\n if self.model is not None:\n self.quad_transform = self._quadrotor_3dmodel(self.model)\n else:\n self.quad_transform = self._quadrotor_simple_3dmodel(self.diameter)\n\n self.shadow_transform = r3d.transform_and_color(\n np.eye(4), (0, 0, 0, 0.4), r3d.circle(0.75*self.diameter, 32))\n\n # TODO make floor size or walls to indicate world_box\n floor = r3d.ProceduralTexture(r3d.random_textype(), (0.15, 0.25),\n r3d.rect((1000, 1000), (0, 100), (0, 100)))\n\n self.update_goal_diameter()\n self.chase_cam.view_dist = self.diameter * 15\n\n self.create_goal(goal=(0,0,0))\n \n bodies = [r3d.BackToFront([floor, self.shadow_transform]),\n self.goal_transform, self.quad_transform] + self.goal_arrows\n \n \n\n if self.obstacles:\n bodies += self.obstacles.bodies\n\n world = r3d.World(bodies)\n batch = r3d.Batch()\n world.build(batch)\n\n self.scene = r3d.Scene(batches=[batch], bgcolor=(0,0,0))\n self.scene.initialize()\n\n def create_goal(self, goal):\n ## Goal\n self.goal_transform = r3d.transform_and_color(np.eye(4),\n (0.85, 0.55, 0), r3d.sphere(self.goal_diameter/2, 18))\n \n goal_arr_len, goal_arr_r, goal_arr_sect = 1.5 * self.goal_diameter, 0.02 * self.goal_diameter, 10\n self.goal_arrows = []\n\n self.goal_arrows_rot = []\n self.goal_arrows_rot.append(np.array([[0,0,1],[0,1,0],[-1,0,0]]))\n self.goal_arrows_rot.append(np.array([[1,0,0],[0,0,1],[0,-1,0]]))\n self.goal_arrows_rot.append(np.eye(3))\n\n self.goal_arrows.append(r3d.transform_and_color(\n np.array([[0,0,1,0],[0,1,0,0],[-1,0,0,0],[0,0,0,1]]), \n (1., 0., 0.), r3d.arrow(goal_arr_r, goal_arr_len, goal_arr_sect)))\n self.goal_arrows.append(r3d.transform_and_color(\n np.array([[1,0,0,0],[0,0,1,0],[0,-1,0,0],[0,0,0,1]]), \n (0., 1., 0.), r3d.arrow(goal_arr_r, goal_arr_len, goal_arr_sect)))\n self.goal_arrows.append(r3d.transform_and_color(\n np.eye(4), \n (0., 0., 1.), r3d.arrow(goal_arr_r, goal_arr_len, goal_arr_sect)))\n\n def update_goal(self, goal):\n self.goal_transform.set_transform(r3d.translate(goal[0:3]))\n\n self.goal_arrows[0].set_transform(r3d.trans_and_rot(goal[0:3], self.goal_arrows_rot[0]))\n self.goal_arrows[1].set_transform(r3d.trans_and_rot(goal[0:3], self.goal_arrows_rot[1]))\n self.goal_arrows[2].set_transform(r3d.trans_and_rot(goal[0:3], self.goal_arrows_rot[2]))\n\n\n def update_model(self, model):\n self.model = model\n if self.video_target is not None:\n self.video_target.finish()\n self.video_target = None\n if self.obs_target is not None:\n self.obs_target.finish()\n self.obs_target = None\n if self.window_target:\n self._make_scene()\n\n def _quadrotor_3dmodel(self, model):\n # params[\"body\"] = {\"l\": 0.03, \"w\": 0.03, \"h\": 0.004, \"m\": 0.005}\n # params[\"payload\"] = {\"l\": 0.035, \"w\": 0.02, \"h\": 0.008, \"m\": 0.01}\n # params[\"arms\"] = {\"l\": 0.022, \"w\":0.005, \"h\":0.005, \"m\":0.001}\n # params[\"motors\"] = {\"h\":0.02, \"r\":0.0035, \"m\":0.0015}\n # params[\"propellers\"] = {\"h\":0.002, \"r\":0.022, \"m\":0.00075}\n \n # params[\"motor_pos\"] = {\"xyz\": [0.065/2, 0.065/2, 0.]}\n # params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n # params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": 1}\n\n ## PROPELLERS \n # \"X\" propeller configuration, start fwd left, go clockwise\n # IDs: https://wiki.bitcraze.io/projects:crazyflie2:userguide:assembly\n link_colors = {\n \"body\": (0.67843137, 1. , 0.18431373),\n \"payload\": (0., 0., 1.),\n \"prop_0\":(1,0,0), \"prop_1\":(0,1,0), \"prop_2\":(0,1,0), \"prop_3\": (1,0,0),\n \"motor_0\":(0,0,0), \"motor_1\":(0,0,0), \"motor_2\":(0,0,0), \"motor_3\": (0,0,0),\n \"arm_0\":(0,0,1), \"arm_1\":(0,0,1), \"arm_2\":(0,0,1), \"arm_3\": (0,0,1),\n }\n \n links = []\n for i, link in enumerate(model.links):\n xyz, R, color = model.poses[i].xyz, model.poses[i].R, link_colors[link.name]\n rot = np.eye(4)\n rot[:3,:3] = R\n # print(\"LINK: \", link.name, \"R:\", rot, end=\" \")\n if link.name[:4] == \"prop\":\n prop_r = link.r\n color = 0.5 * np.array(color) + 0.2\n if link.type == \"box\":\n # print(\"Type: Box\")\n link_transf = r3d.transform_and_color(\n np.matmul(r3d.translate(xyz), rot), color, \n r3d.box(link.l, link.w, link.h))\n elif link.type == \"cylinder\":\n # print(\"Type: Cylinder\")\n link_transf = r3d.transform_and_color(r3d.translate(xyz), color,\n r3d.cylinder(link.r, link.h, 32))\n links.append(link_transf)\n\n\n ## ARROWS\n arrow = r3d.Color((0.2, 0.3, 0.9), r3d.arrow(0.12*prop_r, 2.5*prop_r, 16))\n links.append(arrow)\n\n self.have_state = False\n return r3d.Transform(np.eye(4), links)\n\n def _quadrotor_simple_3dmodel(self, diam):\n r = diam / 2\n prop_r = 0.3 * diam\n prop_h = prop_r / 15.0\n\n # \"X\" propeller configuration, start fwd left, go clockwise\n rr = r * np.sqrt(2)/2\n deltas = ((rr, rr, 0), (rr, -rr, 0), (-rr, -rr, 0), (-rr, rr, 0))\n colors = ((1,0,0), (1,0,0), (0,1,0), (0,1,0))\n def disc(translation, color):\n color = 0.5 * np.array(list(color)) + 0.2\n disc = r3d.transform_and_color(r3d.translate(translation), color,\n r3d.cylinder(prop_r, prop_h, 32))\n return disc\n props = [disc(d, c) for d, c in zip(deltas, colors)]\n\n arm_thicc = diam / 20.0\n arm_color = (0.6, 0.6, 0.6)\n arms = r3d.transform_and_color(\n np.matmul(r3d.translate((0, 0, -arm_thicc)), r3d.rotz(np.pi / 4)), arm_color,\n [r3d.box(diam/10, diam, arm_thicc), r3d.box(diam, diam/10, arm_thicc)])\n\n arrow = r3d.Color((0.2, 0.3, 0.9), r3d.arrow(0.12*prop_r, 2.5*prop_r, 16))\n\n bodies = props + [arms, arrow]\n self.have_state = False\n return r3d.Transform(np.eye(4), bodies)\n\n # TODO allow resampling obstacles?\n def reset(self, goal, dynamics):\n self.chase_cam.reset(goal[0:3], dynamics.pos, dynamics.vel)\n self.update_state(dynamics, goal)\n\n def update_state(self, dynamics, goal):\n if self.scene:\n self.chase_cam.step(dynamics.pos, dynamics.vel)\n self.have_state = True\n self.fpv_lookat = dynamics.look_at()\n \n self.update_goal(goal=goal)\n\n matrix = r3d.trans_and_rot(dynamics.pos, dynamics.rot)\n self.quad_transform.set_transform_nocollide(matrix)\n\n shadow_pos = 0 + dynamics.pos\n shadow_pos[2] = 0.001 # avoid z-fighting\n matrix = r3d.translate(shadow_pos)\n self.shadow_transform.set_transform_nocollide(matrix)\n\n def render_chase(self, dynamics, goal, mode=\"human\"):\n if mode == \"human\":\n if self.window_target is None: \n self.window_target = r3d.WindowTarget(self.window_w, self.window_h, resizable=self.resizable)\n self._make_scene()\n self.update_state(dynamics=dynamics, goal=goal)\n self.cam3p.look_at(*self.chase_cam.look_at())\n r3d.draw(self.scene, self.cam3p, self.window_target)\n return None\n elif mode == \"rgb_array\":\n if self.video_target is None:\n self.video_target = r3d.FBOTarget(self.window_h, self.window_h)\n self._make_scene()\n self.update_state(dynamics=dynamics, goal=goal)\n self.cam3p.look_at(*self.chase_cam.look_at())\n r3d.draw(self.scene, self.cam3p, self.video_target)\n return np.flipud(self.video_target.read())\n\n def render_obs(self, dynamics, goal):\n if self.obs_target is None: \n self.obs_target = r3d.FBOTarget(self.obs_hw[0], self.obs_hw[1])\n self._make_scene()\n self.update_state(dynamics=dynamics, goal=goal)\n self.cam1p.look_at(*self.fpv_lookat)\n r3d.draw(self.scene, self.cam1p, self.obs_target)\n return np.flipud(self.obs_target.read())"
},
{
"alpha_fraction": 0.40973517298698425,
"alphanum_fraction": 0.5091384053230286,
"avg_line_length": 40.25384521484375,
"blob_id": "a94650a9fd96252d41a24442946098f44d8e7329",
"content_id": "a3c8f014d8d223f9d9a8b87ed0fcf23f8b2a842f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5362,
"license_type": "no_license",
"max_line_length": 144,
"num_lines": 130,
"path": "/quad_sim/quad_models.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "def crazyflie_params():\n ## See: Ref[2] for details\n ## Geometric parameters for Inertia and the model\n geom_params = {}\n geom_params[\"body\"] = {\"l\": 0.03, \"w\": 0.03, \"h\": 0.004, \"m\": 0.005}\n geom_params[\"payload\"] = {\"l\": 0.035, \"w\": 0.02, \"h\": 0.008, \"m\": 0.01}\n geom_params[\"arms\"] = {\"l\": 0.022, \"w\":0.005, \"h\":0.005, \"m\":0.001}\n geom_params[\"motors\"] = {\"h\":0.02, \"r\":0.0035, \"m\":0.0015}\n geom_params[\"propellers\"] = {\"h\":0.002, \"r\":0.022, \"m\":0.00075}\n \n geom_params[\"motor_pos\"] = {\"xyz\": [0.065/2, 0.065/2, 0.]}\n geom_params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n geom_params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": 1}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n ## Damping parameters\n # damp_params = {\"vel\": 0.001, \"omega_quadratic\": 0.015}\n damp_params = {\"vel\": 0.0, \"omega_quadratic\": 0.0}\n\n ## Noise parameters\n noise_params = {}\n noise_params[\"thrust_noise_ratio\"] = 0.05\n\n ## Motor parameters\n motor_params = {\"thrust_to_weight\" : 1.9, #2.18\n \"assymetry\": [1.0, 1.0, 1.0, 1.0],\n \"torque_to_thrust\": 0.006, #0.005964552\n \"linearity\": 1.0, #0.424 for CrazyFlie w/o correction in firmware (See [2])\n \"C_drag\": 0.000, # 3052 * 9.1785e-07 #3052 * 8.06428e-05, # 0.246\n \"C_roll\": 0.000, #3052 * 0.000001 # 0.0003\n \"damp_time_up\": 0.15, #0.15, #0.15 - See: [4] for details on motor damping. Note: these are rotational velocity damp params.\n \"damp_time_down\": 0.15 #2.0, #2.0\n }\n\n ## Summarizing\n params = {\n \"geom\": geom_params, \n \"damp\": damp_params, \n \"noise\": noise_params,\n \"motor\": motor_params\n }\n return params\n\n\ndef defaultquad_params():\n # Similar to AscTec Hummingbird: Ref[3]\n ## Geometric parameters for Inertia and the model\n geom_params = {}\n geom_params[\"body\"] = {\"l\": 0.1, \"w\": 0.1, \"h\": 0.085, \"m\": 0.5}\n geom_params[\"payload\"] = {\"l\": 0.12, \"w\": 0.12, \"h\": 0.04, \"m\": 0.1}\n geom_params[\"arms\"] = {\"l\": 0.1, \"w\":0.015, \"h\":0.015, \"m\":0.025} #0.17 total arm\n geom_params[\"motors\"] = {\"h\":0.02, \"r\":0.025, \"m\":0.02}\n geom_params[\"propellers\"] = {\"h\":0.001, \"r\":0.1, \"m\":0.009}\n \n geom_params[\"motor_pos\"] = {\"xyz\": [0.12, 0.12, 0.]}\n geom_params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n geom_params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": -1}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n \n ## Damping parameters\n # damp_params = {\"vel\": 0.001, \"omega_quadratic\": 0.015}\n damp_params = {\"vel\": 0.0, \"omega_quadratic\": 0.0}\n\n ## Noise parameters\n noise_params = {}\n noise_params[\"thrust_noise_ratio\"] = 0.05\n \n ## Motor parameters\n motor_params = {\"thrust_to_weight\" : 2.8,\n \"assymetry\": [1.0, 1.0, 1.0, 1.0], \n \"torque_to_thrust\": 0.05,\n \"linearity\": 1.0, # 0.0476 for Hummingbird (See [5]) if we want to use RPMs instead of force.\n \"C_drag\": 0.,\n \"C_roll\": 0.,\n \"damp_time_up\": 0,\n \"damp_time_down\": 0\n }\n ## Summarizing\n params = {\n \"geom\": geom_params, \n \"damp\": damp_params, \n \"noise\": noise_params,\n \"motor\": motor_params\n }\n return params\n\n\ndef crazyflie_lowinertia_params():\n ## See: Ref[2] for details\n ## Geometric parameters for Inertia and the model\n geom_params = {}\n geom_params[\"body\"] = {\"l\": 0.03, \"w\": 0.03, \"h\": 0.004, \"m\": 0.014}\n geom_params[\"payload\"] = {\"l\": 0.035, \"w\": 0.02, \"h\": 0.008, \"m\": 0.01}\n geom_params[\"arms\"] = {\"l\": 0.022, \"w\":0.005, \"h\":0.005, \"m\":0.0005}\n geom_params[\"motors\"] = {\"h\":0.02, \"r\":0.0035, \"m\":0.0005}\n geom_params[\"propellers\"] = {\"h\":0.002, \"r\":0.022, \"m\":0.0000075}\n \n geom_params[\"motor_pos\"] = {\"xyz\": [0.065/2, 0.065/2, 0.]}\n geom_params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n geom_params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": 1}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n ## Damping parameters\n # damp_params = {\"vel\": 0.001, \"omega_quadratic\": 0.015}\n damp_params = {\"vel\": 0.0, \"omega_quadratic\": 0.0}\n\n ## Noise parameters\n noise_params = {}\n noise_params[\"thrust_noise_ratio\"] = 0.05\n\n ## Motor parameters\n motor_params = {\"thrust_to_weight\" : 1.9, #2.18\n \"assymetry\": [1.0, 1.0, 1.0, 1.0],\n \"torque_to_thrust\": 0.006, #0.005964552\n \"linearity\": 1.0, #0.424 for CrazyFlie w/o correction in firmware (See [2])\n \"C_drag\": 0.000, # 3052 * 9.1785e-07 #3052 * 8.06428e-05, # 0.246\n \"C_roll\": 0.000, #3052 * 0.000001 # 0.0003\n \"damp_time_up\": 0.15, #0.15, #0.15 - See: [4] for details on motor damping. Note: these are rotational velocity damp params.\n \"damp_time_down\": 0.15 #2.0, #2.0\n }\n\n ## Summarizing\n params = {\n \"geom\": geom_params, \n \"damp\": damp_params, \n \"noise\": noise_params,\n \"motor\": motor_params\n }\n # print(params)\n return params"
},
{
"alpha_fraction": 0.6575342416763306,
"alphanum_fraction": 0.6917808055877686,
"avg_line_length": 35.625,
"blob_id": "c92fa5b3d168d51264df11703f1892a08256f075",
"content_id": "9df1104fd2e1a8f27339c7915d187da4f66bc6d8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 292,
"license_type": "no_license",
"max_line_length": 132,
"num_lines": 8,
"path": "/quad_train/launchers/ppo_crazyflie_noisy_nodamp_nodelay.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nparallel ./train_quad.py config/ppo__crazyflie_noisy_nodamp__rew_pos_spin_0.1.yml _results_temp/ppo_crazyflie_noisy_nodamp_nodelay \\\n--seed {1} \\\n-p \\\nenv_param.dynamics_change.motor.damp_time_up,\\\nenv_param.dynamics_change.motor.damp_time_down \\\n-pv {2} \\\n::: {1..5} ::: 0.0,,0.0"
},
{
"alpha_fraction": 0.5826946496963501,
"alphanum_fraction": 0.5945945978164673,
"avg_line_length": 26.70391082763672,
"blob_id": "6c2ba41daf5a5cd85914800bb6576a5089d2ac13",
"content_id": "bca935c27a3a50216856523fd813ad1439fb2fea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4958,
"license_type": "no_license",
"max_line_length": 121,
"num_lines": 179,
"path": "/quad_gen/gaussian_mlp.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import argparse\nimport numpy as np \nimport os\n# import tensorflow as tf\n\nfrom code_blocks import (\n\theaders_network_evaluate,\n\tlinear_activation,\n\tsigmoid_activation,\n\trelu_activation,\n)\n\ndef generate(policy, sess, output_path=None):\n\t\"\"\"\n\tGenerate mlp model source code given a policy object\n\tArgs:\n\t\tpolicy [policy object]: the trained policy\n\t\tsess [tf.Session] a tensorflow session\n\t\toutput_path [str]: the path of the generated code (should include the file name)\n\t\"\"\"\n\t# TODO: check if the policy is really a mlp policy\n\ttrainable_list = policy.get_params()\n\n\ttrainable_shapes = []\n\ttrainable_evals = []\n\tfor tf_trainable in trainable_list:\n\t\ttrainable_shapes.append(tf_trainable.shape)\n\t\ttrainable_evals.append(tf_trainable.eval(session=sess))\n\n\t\"\"\"\n\tTo account for the last matrix which stores the std, \n\tthe # of layers must be subtracted by 1\n\t\"\"\"\n\tn_layers = len(trainable_shapes) - 1\n\tweights = []\t# strings\n\tbiases = []\t\t# strings\n\toutputs = []\t# strings\n\n\tstructure = \"\"\"static const int structure[\"\"\"+str(int(n_layers/2))+\"\"\"][2] = {\"\"\"\n\n\tn_weight = 0\n\tn_bias = 0\n\tfor n in range(n_layers): \n\t\tshape = trainable_shapes[n]\n\t\t\n\t\tif len(shape) == 2:\n\t\t\t## it is a weight matrix\n\t\t\tweight = \"\"\"static const float layer_\"\"\"+str(n_weight)+\"\"\"_weight[\"\"\"+str(shape[0])+\"\"\"][\"\"\"+str(shape[1])+\"\"\"] = {\"\"\"\n\t\t\tfor row in trainable_evals[n]:\n\t\t\t\tweight += \"\"\"{\"\"\"\n\t\t\t\tfor num in row:\n\t\t\t\t\tweight += str(num) + \"\"\",\"\"\"\n\t\t\t\t# get rid of the comma after the last number\n\t\t\t\tweight = weight[:-1]\n\t\t\t\tweight += \"\"\"},\"\"\"\n\t\t\t# get rid of the comma after the last curly bracket\n\t\t\tweight = weight[:-1]\n\t\t\tweight += \"\"\"};\\n\"\"\"\n\t\t\tweights.append(weight)\n\t\t\tn_weight += 1\n\n\t\t\t# augment the structure array\n\t\t\tstructure += \"\"\"{\"\"\"+str(shape[0])+\"\"\", \"\"\"+str(shape[1])+\"\"\"},\"\"\"\n\n\t\telif len(shape) == 1:\n\t\t\t## it is a bias vector \n\t\t\tbias = \"\"\"static const float layer_\"\"\"+str(n_bias)+\"\"\"_bias[\"\"\"+str(shape[0])+\"\"\"] = {\"\"\"\n\t\t\tfor num in trainable_evals[n]:\n\t\t\t\tbias += str(num) + \"\"\",\"\"\"\n\t\t\t# get rid of the comma after the last number\n\t\t\tbias = bias[:-1]\n\t\t\tbias += \"\"\"};\\n\"\"\"\n\t\t\tbiases.append(bias)\n\n\t\t\t## add the output arrays\n\t\t\toutput = \"\"\"static float output_\"\"\"+str(n_bias)+\"\"\"[\"\"\"+str(shape[0])+\"\"\"];\\n\"\"\"\n\t\t\toutputs.append(output)\n\n\t\t\tn_bias += 1\n\n\t# complete the structure array\n\t## get rid of the comma after the last curly bracket\n\tstructure = structure[:-1] \n\tstructure += \"\"\"};\\n\"\"\"\n\n\t\"\"\"\n\tMultiple for loops to do matrix multiplication\n\t - assuming using tanh activation\n\t\"\"\"\n\tfor_loops = []\t# strings \n\n\t# the first hidden layer\n\tinput_for_loop = \"\"\"\n\t\tfor (int i = 0; i < structure[0][1]; i++) {\n\t\t\toutput_0[i] = 0;\n\t\t\tfor (int j = 0; j < structure[0][0]; j++) {\n\t\t\t\toutput_0[i] += state_array[j] * layer_0_weight[j][i];\n\t\t\t}\n\t\t\toutput_0[i] += layer_0_bias[i];\n\t\t\toutput_0[i] = tanhf(output_0[i]);\n\t\t}\n\t\"\"\"\n\tfor_loops.append(input_for_loop)\n\n\t# rest of the hidden layers\n\tfor n in range(1, int(n_layers/2)-1):\n\t\tfor_loop = \"\"\"\n\t\tfor (int i = 0; i < structure[\"\"\"+str(n)+\"\"\"][1]; i++) {\n\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] = 0;\n\t\t\tfor (int j = 0; j < structure[\"\"\"+str(n)+\"\"\"][0]; j++) {\n\t\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] += output_\"\"\"+str(n-1)+\"\"\"[j] * layer_\"\"\"+str(n)+\"\"\"_weight[j][i];\n\t\t\t}\n\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] += layer_\"\"\"+str(n)+\"\"\"_bias[i];\n\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] = tanhf(output_\"\"\"+str(n)+\"\"\"[i]);\n\t\t}\n\t\t\"\"\"\n\t\tfor_loops.append(for_loop)\n\n\tn = int(n_layers/2)-1\n\t# the last hidden layer which is supposed to have no non-linearity\n\toutput_for_loop = \"\"\"\n\t\tfor (int i = 0; i < structure[\"\"\"+str(n)+\"\"\"][1]; i++) {\n\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] = 0;\n\t\t\tfor (int j = 0; j < structure[\"\"\"+str(n)+\"\"\"][0]; j++) {\n\t\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] += output_\"\"\"+str(n-1)+\"\"\"[j] * layer_\"\"\"+str(n)+\"\"\"_weight[j][i];\n\t\t\t}\n\t\t\toutput_\"\"\"+str(n)+\"\"\"[i] += layer_\"\"\"+str(n)+\"\"\"_bias[i];\n\t\t}\n\t\t\"\"\"\n\tfor_loops.append(output_for_loop)\n\n\t## assign network outputs to control\n\tassignment = \"\"\"\n\t\tcontrol_n->thrust_0 = output_\"\"\"+str(n)+\"\"\"[0];\n\t\tcontrol_n->thrust_1 = output_\"\"\"+str(n)+\"\"\"[1];\n\t\tcontrol_n->thrust_2 = output_\"\"\"+str(n)+\"\"\"[2];\n\t\tcontrol_n->thrust_3 = output_\"\"\"+str(n)+\"\"\"[3];\t\n\t\"\"\"\n\n\t## construct the network evaluation function\n\tcontroller_eval = \"\"\"\n\tvoid networkEvaluate(struct control_t_n *control_n, const float *state_array) {\n\t\"\"\"\n\tfor code in for_loops:\n\t\tcontroller_eval += code \n\t## assignment to control_n\n\tcontroller_eval += assignment\n\n\t## closing bracket\n\tcontroller_eval += \"\"\"\n\t}\n\t\"\"\"\n\n\t## combine the all the codes\n\tsource = \"\"\n\t## headers\n\tsource += headers_network_evaluate\n\t## helper functions\n\tsource += linear_activation\n\tsource += sigmoid_activation\n\tsource += relu_activation\n\t## the network evaluation function\n\tsource += structure\n\tfor output in outputs:\n\t\tsource += output \n\tfor weight in weights:\n\t\tsource += weight \n\tfor bias in biases:\n\t\tsource += bias\n\tsource += controller_eval\n\n\t## add log group for logging\n\t# source += log_group\n\n\tif output_path:\n\t\twith open(output_path, 'w') as f:\n\t\t\tf.write(source)\n\n\treturn source"
},
{
"alpha_fraction": 0.5070279836654663,
"alphanum_fraction": 0.5165917873382568,
"avg_line_length": 36.505435943603516,
"blob_id": "e71ac6365bd139a565a44265211786d98afa89e8",
"content_id": "b08fff198a2c67eb08b7547204b7d037d53e2ec5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6901,
"license_type": "no_license",
"max_line_length": 149,
"num_lines": 184,
"path": "/quad_train/misc/quad_record_oscilations.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nimport argparse\nimport os.path as osp\nimport sys\nimport time\nimport numpy as np\nimport copy\nimport matplotlib.pyplot as plt\nimport pickle\n\nfrom gym_art.quadrotor.quadrotor import QuadrotorEnv\n\n\ndef play(quad_params, u_freqs, u_magns, obs_params, out_filename=None, render=True, plot=True, gravity=0., ep_time=1., conf_name=\"\"):\n # Modifying some parameters\n quad_params[\"gravity\"] = gravity\n quad_params[\"init_random_state\"] = False\n quad_params[\"dynamics_change\"][\"noise\"][\"thrust_noise_ratio\"] = 0.\n\n quad_params[\"ep_time\"] = ep_time\n env = QuadrotorEnv(**quad_params)\n control_freq = env.control_freq\n ep_len = env.ep_len\n u_dt = 1./control_freq\n dt = env.dt\n \n obs_descr_str = \"freq x magn x time x obs\"\n act_descr_str = \"freq x magn x time x actions\"\n\n # import pdb;pdb.set_trace()\n\n obs_params = [obs.split(\",\") for obs in args.obs_params.split(\",,\")]\n obs_components = [(obs[0], int(obs[1])) for obs in obs_params]\n obs_params = dict(obs_components)\n\n sim_time_vec = []\n\n # Observations\n obs_vec = np.zeros([len(u_freqs), len(u_magns)] + [ep_len + 1] + list(env.observation_space.high.shape))\n action_vec = np.zeros([len(u_freqs), len(u_magns)] + [ep_len + 1] + list(env.action_space.high.shape))\n\n # Action generator (freq == Hz)\n def get_action(t, magn, freq, offset=0.0):\n u01 = magn * np.sin(2 * np.pi * freq * t) + offset\n u23 = magn * np.sin(2 * np.pi * freq * t + np.pi) + offset\n return np.array([u01,u01,u23,u23])\n\n for u_f_i, u_f in enumerate(u_freqs):\n for u_m_i, u_m in enumerate(u_magns):\n sim_step = 0\n obs = env.reset()\n while True:\n if render: env.render()\n obs_vec[u_f_i, u_m_i, sim_step, ...] = obs\n action = get_action(u_dt * sim_step, magn=u_m, freq=u_f)\n action_vec[u_f_i, u_m_i, sim_step, ...] = action\n obs, _, done, _ = env.step(action)\n \n if done:\n print(\"Sim time: \", u_dt * sim_step)\n sim_time_vec.append(u_dt * sim_step)\n break\n sim_step += 1\n\n # Report\n print(\"################################################\")\n print(\"Avg sim time: \", np.mean(sim_time_vec))\n\n ## Pickle everything\n if out_filename is not None:\n data = {\"obs\": obs_vec, \"actions\": action_vec, \n \"time\": np.linspace(0, env.ep_time, ep_len),\n \"description\": \n {\"obs_mx_dims\": obs_descr_str,\n \"obs_components\": obs_components,\n \"actions_mx_dims\": act_descr_str,\n \"actions_freq\": u_freqs,\n \"actions_magn\": u_magns\n } \n }\n with open(out_filename, 'wb') as handle:\n pickle.dump(data, handle)\n\n # import pdb; pdb.set_trace()\n if plot:\n obs_sizes = [obs_params[key] for key in obs_params.keys()]\n obs_indices = np.cumsum(obs_sizes)\n obs_vec = np.split(obs_vec, obs_indices[:-1], axis=3)\n obs_num = 0\n for obs_num, obs_id in enumerate(obs_params.keys()):\n plt.figure(obs_num+1)\n for obs_i in range(obs_sizes[obs_num]):\n ax = plt.subplot(obs_sizes[obs_num] + 2, 1, obs_i+1)\n \n for f_i, u_f in enumerate(u_freqs):\n for m_i, u_m in enumerate(u_magns):\n plt.plot(obs_vec[obs_num][f_i, m_i, :, obs_i], label=conf_name + \": freq: %.2f magn: %.2f\" % (u_f, u_m))\n plt.legend(loc=\"right\", borderaxespad=0.)\n\n \n ax.text(.5,.9, obs_id + \"_\" + str(obs_i),\n horizontalalignment='center',\n transform=ax.transAxes)\n \n ## Actions (on each graph for convenience)\n ax = plt.subplot(obs_sizes[obs_num] + 2, 1, obs_i+2)\n for f_i, u_f in enumerate(u_freqs):\n for m_i, u_m in enumerate(u_magns):\n for act in range(2):\n plt.plot(action_vec[f_i, m_i, :, act], label=str(act))\n ax.text(.5,.9, \"Actions\",\n horizontalalignment='center',\n transform=ax.transAxes)\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(description='Play a pickled policy.')\n parser.add_argument(\"-c\",\"--config\",\n help='Config file for a quadrotor env or a list of such files', nargs='+') \n parser.add_argument(\"-obs\",'--obs_params', \n help='Observation components: name1,size1,,name2,size2 etc.', \n default=\"xyz,3,,Vxyz,3,,R,9,,Omega,3\")\n parser.add_argument(\"-p\",'--plot',\n help=\"Set it if you dont want to plot data\", \n action=\"store_false\")\n parser.add_argument(\"-f\",'--freq',\n help=\"List of frequencies to apply (Hz) separated by comma\", \n default=\"1,10\")\n parser.add_argument(\"-m\",'--magn',\n help=\"List of magnitudes to apply separated by comma\", \n default=\"0.1,0.5\") \n parser.add_argument(\"-o\",'--out',\n help=\"Output pickle filename\") \n parser.add_argument(\"-r\",'--render',\n help=\"Set this flag if you don't want to render\",\n action=\"store_false\") \n parser.add_argument(\"-g\",'--gravity',\n help=\"Gravity\",\n type=float,\n default=0.) \n parser.add_argument(\"-t\",'--ep_time',\n help=\"Time (s) for the episode\",\n type=float,\n default=3.) \n args = parser.parse_args()\n\n freq = [float(freq) for freq in args.freq.split(\",\")]\n magn = [float(magn) for magn in args.magn.split(\",\")]\n\n # import pdb; pdb.set_trace()\n\n quad_params = []\n for confname in args.config:\n import yaml\n yaml_stream = open(confname, 'r')\n config = yaml.load(yaml_stream)\n\n if \"variant\" in config:\n quad_params.append(config[\"variant\"][\"env_param\"])\n else:\n quad_params.append(config)\n\n for quad_id, quad in enumerate(quad_params):\n print(\"####################################################\")\n print(\"Running: \", args.config[quad_id])\n play(quad_params=quad, \n obs_params=args.obs_params,\n u_freqs=freq, \n u_magns=magn, \n out_filename=args.out, \n render=args.render, \n plot=args.plot,\n gravity=args.gravity,\n ep_time=args.ep_time,\n conf_name=\"conf_\" + str(quad_id)\n )\n \n plt.show(block=False)\n input(\"Press ENter to continue ...\")\n\n## Unpickle example\n# file = open(\"_results_temp/yaw0/quad_oscilations_sim100hz.pkl\", \"rb\") \n# data = pickle.load(file) "
},
{
"alpha_fraction": 0.5691130757331848,
"alphanum_fraction": 0.5911156535148621,
"avg_line_length": 31.840795516967773,
"blob_id": "64077c0b6777ab2b71c677a5f49affe1314156cf",
"content_id": "71e82467a12249a644cfff3b2d5afe94d3d0441c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 26406,
"license_type": "no_license",
"max_line_length": 348,
"num_lines": 804,
"path": "/quad_sim/rendering3d.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "\"\"\"\n3D rendering framework\n\"\"\"\nfrom __future__ import division\nfrom copy import deepcopy\nimport os\nimport six\nimport sys\nimport itertools\nimport noise\nimport ctypes\n\nif \"Apple\" in sys.version:\n if 'DYLD_FALLBACK_LIBRARY_PATH' in os.environ:\n os.environ['DYLD_FALLBACK_LIBRARY_PATH'] += ':/usr/lib'\n # (JDS 2016/04/15): avoid bug on Anaconda 2.3.0 / Yosemite\n\n# from gym.utils import reraise\nfrom gym import error\nimport matplotlib.pyplot as plt\n\ntry:\n import pyglet\n pyglet.options['debug_gl'] = False\nexcept ImportError as e:\n raise ImportError('''\n Cannot import pyglet.\n HINT: you can install pyglet directly via 'pip install pyglet'.\n But if you really just want to install all Gym dependencies and not have to think about it,\n 'pip install -e .[all]' or 'pip install gym[all]' will do it.\n ''')\n # reraise(suffix=\"HINT: you can install pyglet directly via 'pip install pyglet'. But if you really just want to install all Gym dependencies and not have to think about it, 'pip install -e .[all]' or 'pip install gym[all]' will do it.\")\n\ntry:\n from pyglet.gl import *\nexcept ImportError as e:\n raise ImportError('''\n Cannot import pyglet.\n HINT: you can install pyglet directly via 'pip install pyglet'.\n But if you really just want to install all Gym dependencies and not have to think about it,\n 'pip install -e .[all]' or 'pip install gym[all]' will do it.\n ''')\n # reraise(prefix=\"Error occured while running `from pyglet.gl import *`\",suffix=\"HINT: make sure you have OpenGL install. On Ubuntu, you can run 'apt-get install python-opengl'. If you're running on a server, you may need a virtual frame buffer; something like this should work: 'xvfb-run -s \\\"-screen 0 1400x900x24\\\" python <your_script.py>'\")\n\nimport math\nimport numpy as np\n\ndef get_display(spec):\n \"\"\"Convert a display specification (such as :0) into an actual Display\n object.\n\n pyglet only supports multiple Displays on Linux.\n \"\"\"\n if spec is None:\n return None\n elif isinstance(spec, six.string_types):\n return pyglet.canvas.Display(spec)\n else:\n raise error.Error('Invalid display specification: {}. (Must be a string like :0 or None.)'.format(spec))\n\n# TODO can we get some of this from Pyglet?\nclass FBOTarget(object):\n def __init__(self, width, height):\n\n shape = (width, height, 3)\n self.shape = shape\n\n self.fbo = GLuint(0)\n glGenFramebuffers(1, ctypes.byref(self.fbo))\n glBindFramebuffer(GL_FRAMEBUFFER, self.fbo)\n\n # renderbuffer for depth\n self.depth = GLuint(0)\n glGenRenderbuffers(1, ctypes.byref(self.depth))\n glBindRenderbuffer(GL_RENDERBUFFER, self.depth)\n glRenderbufferStorage(GL_RENDERBUFFER, GL_DEPTH_COMPONENT, *shape)\n # ??? (from songho.ca/opengl/gl_fbo.html)\n glBindRenderbuffer(GL_RENDERBUFFER, 0)\n glFramebufferRenderbuffer(GL_FRAMEBUFFER, GL_DEPTH_ATTACHMENT,\n GL_RENDERBUFFER, self.depth)\n\n # texture for RGB\n self.tex = GLuint(0)\n glGenTextures(1, ctypes.byref(self.tex))\n glBindTexture(GL_TEXTURE_2D, self.tex)\n glTexImage2D(GL_TEXTURE_2D, 0, GL_RGB, shape[0], shape[1], 0,\n GL_RGB, GL_UNSIGNED_BYTE, 0)\n glFramebufferTexture2D(GL_FRAMEBUFFER, GL_COLOR_ATTACHMENT0,\n GL_TEXTURE_2D, self.tex, 0)\n\n # test - ok to comment out?\n draw_buffers = (GLenum * 1)(GL_COLOR_ATTACHMENT0)\n glDrawBuffers(1, draw_buffers)\n assert glCheckFramebufferStatus(GL_FRAMEBUFFER) == GL_FRAMEBUFFER_COMPLETE\n\n self.fb_array = np.zeros(shape, dtype=np.uint8)\n\n def bind(self):\n glBindFramebuffer(GL_FRAMEBUFFER, self.fbo)\n draw_buffers = (GLenum * 1)(GL_COLOR_ATTACHMENT0)\n glDrawBuffers(1, draw_buffers)\n glViewport(0, 0, *self.shape[:2])\n\n def finish(self):\n glReadPixels(0, 0, self.shape[1], self.shape[0],\n GL_RGB, GL_UNSIGNED_BYTE, self.fb_array.ctypes.data)\n\n def read(self):\n return self.fb_array\n\n\nclass WindowTarget(object):\n def __init__(self, width, height, display=None, resizable=True):\n\n config=Config(double_buffer=True, depth_size=16)\n display = get_display(display)\n # vsync is set to false to speed up FBO-only renders, we enable before draw\n self.window = pyglet.window.Window(display=display,\n width=width, height=height, resizable=resizable,\n visible=True, vsync=False, config=config\n )\n self.window.on_close = self.close\n self.shape = (width, height, 3)\n def on_resize(w, h):\n self.shape = (w, h, 3)\n if resizable:\n self.window.on_resize = on_resize\n\n def close(self):\n self.window.close()\n\n def bind(self):\n self.window.switch_to()\n self.window.set_vsync(True)\n self.window.dispatch_events()\n glViewport(0, 0, self.window.width, self.window.height)\n glBindFramebuffer(GL_FRAMEBUFFER, 0)\n\n def finish(self):\n self.window.flip()\n self.window.set_vsync(False)\n\n\nclass Camera(object):\n def __init__(self, fov):\n self.fov = fov\n self.lookat = None\n\n def look_at(self, eye, target, up):\n self.lookat = (eye, target, up)\n\n # TODO other ways to set the view matrix\n\n # private\n def _matrix(self, shape):\n aspect = float(shape[0]) / shape[1]\n znear = 0.1\n zfar = 100.0\n glMatrixMode(GL_PROJECTION)\n glLoadIdentity()\n gluPerspective(self.fov, aspect, znear, zfar)\n\n glMatrixMode(GL_MODELVIEW)\n glLoadIdentity()\n # will make sense once more than one way of setting view matrix\n assert sum([x is not None for x in (self.lookat,)]) < 2\n\n if self.lookat is not None:\n eye, target, up = (list(x) for x in self.lookat)\n gluLookAt(*(eye + target + up))\n\n\n# TODO we can add user-controlled lighting, etc. to this\nclass Scene(object):\n def __init__(self, batches, bgcolor=(0,0,0)):\n self.batches = batches\n self.bgcolor = bgcolor\n\n # [-1] == 0 means it's a directional light\n self.lights = [np.array([np.cos(t), np.sin(t), 0.0, 0.0])\n for t in 0.2 + np.linspace(0, 2*np.pi, 4)[:-1]]\n\n # call only once GL context is ready\n def initialize(self):\n glShadeModel(GL_SMOOTH)\n glEnable(GL_LIGHTING)\n\n #glFogi(GL_FOG_MODE, GL_LINEAR)\n #glFogf(GL_FOG_START, 20.0) # Fog Start Depth\n #glFogf(GL_FOG_END, 100.0) # Fog End Depth\n #glEnable(GL_FOG)\n\n amb, diff, spec = (1.0 / len(self.lights)) * np.array([0.4, 1.2, 0.5])\n for i, light in enumerate(self.lights):\n # TODO fix lights in world space instead of camera space\n glLightfv(GL_LIGHT0 + i, GL_POSITION, (GLfloat * 4)(*light))\n glLightfv(GL_LIGHT0 + i, GL_AMBIENT, (GLfloat * 4)(amb, amb, amb, 1))\n glLightfv(GL_LIGHT0 + i, GL_DIFFUSE, (GLfloat * 4)(diff, diff, diff, 1))\n glLightfv(GL_LIGHT0 + i, GL_SPECULAR, (GLfloat * 4)(spec, spec, spec, 1))\n glEnable(GL_LIGHT0 + i)\n\n\ndef draw(scene, camera, target):\n\n target.bind() # sets viewport\n\n r, g, b = scene.bgcolor\n glClearColor(r, g, b, 1.0)\n glFrontFace(GL_CCW)\n glCullFace(GL_BACK)\n glEnable(GL_CULL_FACE);\n glEnable(GL_DEPTH_TEST)\n glEnable(GL_NORMALIZE)\n glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT)\n\n camera._matrix(target.shape)\n #view = (GLfloat * 16)()\n #glGetFloatv(GL_MODELVIEW_MATRIX, view)\n #view = np.array(view).reshape((4,4)).T\n\n for batch in scene.batches:\n batch.draw()\n\n target.finish()\n\n\nclass SceneNode(object):\n def _build_children(self, batch):\n # hack - should go somewhere else\n if not isinstance(self.children, type([])):\n self.children = [self.children]\n for c in self.children:\n c.build(batch, self.pyg_grp)\n\n # default impl\n def collide_sphere(self, x, radius):\n return any(c.collide_sphere(x, radius) for c in self.children)\n\nclass World(SceneNode):\n def __init__(self, children):\n self.children = children\n self.pyg_grp = None\n\n def build(self, batch):\n self._build_children(batch)\n\nclass Transform(SceneNode):\n def __init__(self, transform, children):\n self.t = transform\n self.mat_inv = np.linalg.inv(transform)\n self.children = children\n\n def build(self, batch, parent):\n self.pyg_grp = _PygTransform(self.t, parent=parent)\n self._build_children(batch)\n return self.pyg_grp\n\n def set_transform(self, t):\n self.pyg_grp.set_matrix(t)\n self.mat_inv = np.linalg.inv(t)\n\n def set_transform_nocollide(self, t):\n self.pyg_grp.set_matrix(t)\n\n def collide_sphere(self, x, radius):\n xh = [x[0], x[1], x[2], 1]\n xlocal = np.matmul(self.mat_inv, xh)[:3]\n rlocal = radius * self.mat_inv[0,0]\n return any(c.collide_sphere(xlocal, rlocal) for c in self.children)\n\nclass BackToFront(SceneNode):\n def __init__(self, children):\n self.children = children\n\n def build(self, batch, parent):\n self.pyg_grp = pyglet.graphics.Group(parent=parent)\n for i, c in enumerate(self.children):\n ordering = pyglet.graphics.OrderedGroup(i, parent=self.pyg_grp)\n c.build(batch, ordering)\n return self.pyg_grp\n\nclass Color(SceneNode):\n def __init__(self, color, children):\n self.color = color\n self.children = children\n\n def build(self, batch, parent):\n self.pyg_grp = _PygColor(self.color, parent=parent)\n self._build_children(batch)\n return self.pyg_grp\n\n def set_rgb(self, r, g, b):\n self.pyg_grp.set_rgb(r, g, b)\n\ndef transform_and_color(transform, color, children):\n return Transform(transform, Color(color, children))\n\nTEX_CHECKER = 0\nTEX_XOR = 1\nTEX_NOISE_GAUSSIAN = 2\nTEX_NOISE_PERLIN = 3\nTEX_OILY = 4\nTEX_VORONOI = 5\n\ndef random_textype():\n return np.random.randint(TEX_VORONOI + 1)\n\nclass ProceduralTexture(SceneNode):\n def __init__(self, style, scale, children):\n self.children = children\n # linear is default, those w/ nearest must overwrite\n self.mag_filter = GL_LINEAR\n if style == TEX_CHECKER:\n image = np.zeros((256, 256))\n image[:128,:128] = 1.0\n image[128:,128:] = 1.0\n self.mag_filter = GL_NEAREST\n elif style == TEX_XOR:\n x, y = np.meshgrid(range(256), range(256))\n image = np.float32(np.bitwise_xor(np.uint8(x), np.uint8(y)))\n self.mag_filter = GL_NEAREST\n elif style == TEX_NOISE_GAUSSIAN:\n nz = np.random.normal(size=(256,256))\n image = np.clip(nz, -3, 3)\n elif style == TEX_NOISE_PERLIN:\n t = np.linspace(0, 1, 256)\n nzfun = lambda x, y: noise.pnoise2(x, y,\n octaves=10, persistence=0.8, repeatx=1, repeaty=1)\n image = np.vectorize(nzfun)(*np.meshgrid(t, t))\n elif style == TEX_OILY:\n # from upvector.com \"Intro to Procedural Textures\"\n t = np.linspace(0, 4, 256)\n nzfun = lambda x, y: noise.snoise2(x, y,\n octaves=10, persistence=0.45, repeatx=4, repeaty=4)\n nz = np.vectorize(nzfun)(*np.meshgrid(t, t))\n\n t = np.linspace(0, 20*np.pi, 257)[:-1]\n x, y = np.meshgrid(t, t)\n image = np.sin(x + 8*nz)\n elif style == TEX_VORONOI:\n npts = 64\n points = np.random.uniform(size=(npts, 2))\n # make it tile\n shifts = itertools.product([-1, 0, 1], [-1, 0, 1])\n points = np.vstack([points + shift for shift in shifts])\n unlikely = np.any(np.logical_or(points < -0.25, points > 1.25), axis=1)\n points = np.delete(points, np.where(unlikely), axis=0)\n a = np.full((256, 256), np.inf)\n t = np.linspace(0, 1, 256)\n x, y = np.meshgrid(t, t)\n for p in points:\n dist2 = (x - p[0])**2 + (y - p[1])**2\n a = np.minimum(a, dist2)\n image = np.sqrt(a)\n else:\n raise KeyError(\"style does not exist\")\n\n low, high = 255.0 * scale[0], 255.0 * scale[1]\n _scale_to_inplace(image, low, high)\n self.tex = _np2tex(image)\n\n def build(self, batch, parent):\n self.pyg_grp = _PygTexture(tex=self.tex,\n mag_filter=self.mag_filter, parent=parent)\n self._build_children(batch)\n return self.pyg_grp\n\n\n#\n# these functions return 4x4 rotation matrix suitable to construct Transform\n# or to mutate Transform via set_matrix\n#\ndef scale(s):\n return np.diag([s, s, s, 1.0])\n\ndef translate(x):\n r = np.eye(4)\n r[:3,3] = x\n return r\n\ndef trans_and_rot(t, r):\n m = np.eye(4)\n m[:3,:3] = r\n m[:3,3] = t\n return m\n\ndef rotz(theta):\n r = np.eye(4)\n r[:2,:2] = _rot2d(theta)\n return r\n\ndef roty(theta):\n r = np.eye(4)\n r2d = _rot2d(theta)\n r[[0,0,2,2],[0,2,0,2]] = _rot2d(theta).flatten()\n return r\n\ndef rotx(theta):\n r = np.eye(4)\n r[1:3,1:3] = _rot2d(theta)\n return r\n\nclass _PygTransform(pyglet.graphics.Group):\n def __init__(self, transform=np.eye(4), parent=None):\n super().__init__(parent)\n self.set_matrix(transform)\n\n def set_matrix(self, transform):\n assert transform.shape == (4, 4)\n assert np.all(transform[3,:] == [0, 0, 0, 1])\n self.matrix_raw = (GLfloat * 16)(*transform.T.flatten())\n\n def set_state(self):\n glPushMatrix()\n glMultMatrixf(self.matrix_raw)\n\n def unset_state(self):\n glPopMatrix()\n\nclass _PygColor(pyglet.graphics.Group):\n def __init__(self, color, parent=None):\n super().__init__(parent)\n if len(color) == 3:\n self.set_rgb(*color)\n else:\n self.set_rgba(*color)\n\n def set_rgb(self, r, g, b):\n self.set_rgba(r, g, b, 1.0)\n\n def set_rgba(self, r, g, b, a):\n self.dcolor = (GLfloat * 4)(r, g, b, a)\n spec_whiteness = 0.8\n r, g, b = (1.0 - spec_whiteness) * np.array([r, g, b]) + spec_whiteness\n self.scolor = (GLfloat * 4)(r, g, b, a)\n\n def set_state(self):\n if self.dcolor[-1] < 1.0:\n glEnable(GL_BLEND)\n glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA)\n\n glMaterialfv(GL_FRONT_AND_BACK, GL_AMBIENT_AND_DIFFUSE, self.dcolor)\n glMaterialfv(GL_FRONT_AND_BACK, GL_SPECULAR, self.scolor)\n glMaterialfv(GL_FRONT_AND_BACK, GL_SHININESS, (GLfloat)(8.0))\n\n def unset_state(self):\n if self.dcolor[-1] < 1.0:\n glDisable(GL_BLEND)\n\nclass _PygTexture(pyglet.graphics.Group):\n def __init__(self, tex, mag_filter, parent=None):\n super().__init__(parent=parent)\n\n self.tex = tex\n glBindTexture(GL_TEXTURE_2D, self.tex.id)\n glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT);\n glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT);\n glGenerateMipmap(GL_TEXTURE_2D);\n glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, mag_filter)\n glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR_MIPMAP_LINEAR)\n\n # anisotropic texturing helps a lot with checkerboard floors\n anisotropy = (GLfloat)()\n glGetFloatv(GL_MAX_TEXTURE_MAX_ANISOTROPY_EXT, anisotropy)\n glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MAX_ANISOTROPY_EXT, anisotropy)\n\n def set_state(self):\n glMaterialfv(GL_FRONT_AND_BACK, GL_AMBIENT_AND_DIFFUSE, (GLfloat * 4)(1,1,1,1))\n glMaterialfv(GL_FRONT_AND_BACK, GL_SPECULAR, (GLfloat * 4)(1,1,1,1))\n glEnable(self.tex.target)\n glBindTexture(self.tex.target, self.tex.id)\n\n def unset_state(self):\n glDisable(self.tex.target)\n\n\nclass _PygAlphaBlending(pyglet.graphics.Group):\n def __init__(self, parent=None):\n super().__init__(parent=parent)\n\n def set_state(self):\n glEnable(GL_BLEND)\n glBlendFunc(GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA)\n\n def unset_state(self):\n glDisable(GL_BLEND)\n\nBatch = pyglet.graphics.Batch\n\n# we only implement collision detection between primitives and spheres.\n# the world-coordinate sphere is transformed according to the scene graph\n# into the primitive's canonical coordinate system.\n# this simplifies the math a lot, although it might be less efficient\n# than directly testing the sphere against the transformed primitive\n# in world coordinates.\nclass SphereCollision(object):\n def __init__(self, radius):\n self.radius = radius\n def collide_sphere(self, x, radius):\n c = np.sum(x ** 2) < (self.radius + radius) ** 2\n if c: print(\"collided with sphere\")\n return c\n\nclass AxisBoxCollision(object):\n def __init__(self, corner0, corner1):\n self.corner0, self.corner1 = corner0, corner1\n def collide_sphere(self, x, radius):\n nearest = np.maximum(self.corner0, np.minimum(x, self.corner1))\n c = np.sum((x - nearest)**2) < radius**2\n if c: print(\"collided with box\")\n return c\n\nclass CapsuleCollision(object):\n def __init__(self, radius, height):\n self.radius, self.height = radius, height\n def collide_sphere(self, x, radius):\n z = min(max(0, x[2]), self.height)\n nearest = [0, 0, z]\n c = np.sum((x - nearest)**2) < (self.radius + radius)**2\n if c: print(\"collided with capsule\")\n return c\n\n#\n# these are the 3d primitives that can be added to a pyglet.graphics.Batch.\n# construct them with the shape functions below.\n#\nclass BatchElement(SceneNode):\n def build(self, batch, parent):\n self.batch_args[2] = parent\n batch.add(*self.batch_args)\n\n def collide_sphere(self, x, radius):\n if self.collider is not None:\n return self.collider.collide_sphere(x, radius)\n else:\n return False\n\nclass Mesh(BatchElement):\n def __init__(self, verts, normals=None, st=None, collider=None):\n if len(verts.shape) != 2 or verts.shape[1] != 3:\n raise ValueError('verts must be an N x 3 NumPy array')\n\n N = verts.shape[0]\n assert int(N) % 3 == 0\n\n if st is not None:\n assert st.shape == (N, 2)\n\n if normals is None:\n # compute normals implied by triangle faces\n normals = deepcopy(verts)\n\n for i in range(0, N, 3):\n v0, v1, v2 = verts[i:(i+3),:]\n d0, d1 = (v1 - v0), (v2 - v1)\n n = _normalize(np.cross(d0, d1))\n normals[i:(i+3),:] = n\n\n self.batch_args = [N, pyglet.gl.GL_TRIANGLES, None,\n ('v3f/static', list(verts.flatten())),\n ('n3f/static', list(normals.flatten())),\n ]\n if st is not None:\n self.batch_args.append(('t2f/static', list(st.flatten())))\n self.collider = collider\n\nclass TriStrip(BatchElement):\n def __init__(self, verts, normals, collider=None):\n N, dim = verts.shape\n assert dim == 3\n assert normals.shape == verts.shape\n\n self.batch_args = [N, pyglet.gl.GL_TRIANGLE_STRIP, None,\n ('v3f/static', list(verts.flatten())),\n ('n3f/static', list(normals.flatten()))\n ]\n self.collider = collider\n\nclass TriFan(BatchElement):\n def __init__(self, verts, normals, collider=None):\n N, dim = verts.shape\n assert dim == 3\n assert normals.shape == verts.shape\n\n self.batch_args = [N, pyglet.gl.GL_TRIANGLE_FAN, None,\n ('v3f/static', list(verts.flatten())),\n ('n3f/static', list(normals.flatten()))\n ]\n self.collider = collider\n\n# a box centered on the origin\ndef box(x, y, z):\n corner1 = np.array([x,y,z]) / 2\n corner0 = -corner1\n v = box_mesh(x, y, z)\n collider = AxisBoxCollision(corner0, corner1)\n return Mesh(v, collider=collider)\n\n# cylinder sitting on xy plane pointing +z\ndef cylinder(radius, height, sections):\n v, n = cylinder_strip(radius, height, sections)\n collider = CapsuleCollision(radius, height)\n return TriStrip(v, n, collider=collider)\n\n# cone sitting on xy plane pointing +z\ndef cone(radius, height, sections):\n # TODO collision detectoin\n v, n = cone_strip(radius, height, sections)\n return TriStrip(v, n)\n\n# arrow sitting on xy plane pointing +z\ndef arrow(radius, height, sections):\n v, n = arrow_strip(radius, height, sections)\n return TriStrip(v, n)\n\n# sphere centered on origin, n tris will be about TODO * facets\ndef sphere(radius, facets):\n v, n = sphere_strip(radius, facets)\n collider = SphereCollision(radius)\n return TriStrip(v, n, collider=collider)\n\n# square in xy plane centered on origin\n# dim: (w, h)\n# srange, trange: desired min/max (s, t) tex coords\ndef rect(dim, srange=(0,1), trange=(0,1)):\n v = np.array([\n [1, 1, 0], [-1, 1, 0], [1, -1, 0],\n [-1, 1, 0], [-1, -1, 0], [1, -1, 0]])\n v = np.matmul(v, np.diag([dim[0] / 2.0, dim[1] / 2.0, 0]))\n n = _withz(0 * v, 1)\n s0, s1 = srange\n t0, t1 = trange\n st = np.array([\n [s1, t1], [s0, t1], [s1, t0],\n [s0, t1], [s0, t0], [s1, t0]])\n return Mesh(v, n, st)\n\ndef circle(radius, facets):\n v, n = circle_fan(radius, facets)\n return TriFan(v, n)\n\n#\n# low-level primitive builders. return vertex/normal/texcoord arrays.\n# good if you want to apply transforms directly to the points, etc.\n#\n\n# box centered on origin with given dimensions.\n# no normals, but Mesh ctor will estimate them perfectly\ndef box_mesh(x, y, z):\n vtop = np.array([[x, y, z], [x, -y, z], [-x, -y, z], [-x, y, z]])\n vbottom = deepcopy(vtop)\n vbottom[:,2] = -vbottom[:,2]\n v = 0.5 * np.concatenate([vtop, vbottom], axis=0)\n t = np.array([[1, 3, 2,], [1, 4, 3,], [1, 2, 5,], [2, 6, 5,], [2, 3, 6,], [3, 7, 6,], [3, 4, 8,], [3, 8, 7,], [4, 1, 8,], [1, 5, 8,], [5, 6, 7,], [5, 7, 8,]]) - 1\n t = t.flatten()\n v = v[t,:]\n return v\n\n# circle in the x-y plane\ndef circle_fan(radius, sections):\n t = np.linspace(0, 2 * np.pi, sections + 1)[:,None]\n x = radius * np.cos(t)\n y = radius * np.sin(t)\n v = np.hstack([x, y, 0*t])\n v = np.vstack([[0, 0, 0], v])\n n = _withz(0 * v, 1)\n return v, n\n\n# cylinder sitting on the x-y plane\ndef cylinder_strip(radius, height, sections):\n t = np.linspace(0, 2 * np.pi, sections + 1)[:,None]\n x = radius * np.cos(t)\n y = radius * np.sin(t)\n\n base = np.hstack([x, y, 0*t])\n top = np.hstack([x, y, height + 0*t])\n strip_sides = _to_strip(np.hstack([base[:,None,:], top[:,None,:]]))\n normals_sides = _withz(strip_sides / radius, 0)\n\n def make_cap(circle, normal_z):\n height = circle[0,2]\n center = _withz(0 * circle, height)\n if normal_z > 0:\n strip = _to_strip(np.hstack([circle[:,None,:], center[:,None,:]]))\n else:\n strip = _to_strip(np.hstack([center[:,None,:], circle[:,None,:]]))\n normals = _withz(0 * strip, normal_z)\n return strip, normals\n\n vbase, nbase = make_cap(base, -1)\n vtop, ntop = make_cap(top, 1)\n return (\n np.vstack([strip_sides, vbase, vtop]),\n np.vstack([normals_sides, nbase, ntop]))\n\n# cone sitting on the x-y plane\ndef cone_strip(radius, height, sections):\n t = np.linspace(0, 2 * np.pi, sections + 1)[:,None]\n x = radius * np.cos(t)\n y = radius * np.sin(t)\n base = np.hstack([x, y, 0*t])\n\n top = _withz(0 * base, height)\n vside = _to_strip(np.hstack([base[:,None,:], top[:,None,:]]))\n base_tangent = np.cross(_npa(0, 0, 1), base)\n top_to_base = base - top\n normals = _normalize(np.cross(top_to_base, base_tangent))\n nside = _to_strip(np.hstack([normals[:,None,:], normals[:,None,:]]))\n\n base_ctr = 0 * base\n vbase = _to_strip(np.hstack([base_ctr[:,None,:], base[:,None,:]]))\n nbase = _withz(0 * vbase, -1)\n\n return np.vstack([vside, vbase]), np.vstack([nside, nbase])\n\n# sphere centered on origin\ndef sphere_strip(radius, resolution):\n t = np.linspace(-1, 1, resolution)\n u, v = np.meshgrid(t, t)\n vtx = []\n panel = np.zeros((resolution, resolution, 3))\n inds = list(range(3))\n for i in range(3):\n panel[:,:,inds[0]] = u\n panel[:,:,inds[1]] = v\n panel[:,:,inds[2]] = 1\n norms = np.linalg.norm(panel, axis=2)\n panel = panel / norms[:,:,None]\n for _ in range(2):\n for j in range(resolution - 1):\n strip = deepcopy(panel[[j,j+1],:,:].transpose([1,0,2]).reshape((-1,3)))\n degen0 = deepcopy(strip[0,:])\n degen1 = deepcopy(strip[-1,:])\n vtx.extend([degen0, strip, degen1])\n panel *= -1\n panel = np.flip(panel, axis=1)\n inds = [inds[-1]] + inds[:-1]\n\n n = np.vstack(vtx)\n v = radius * n\n return v, n\n\n# arrow sitting on x-y plane\ndef arrow_strip(radius, height, facets):\n cyl_r = radius\n cyl_h = 0.75 * height\n cone_h = height - cyl_h\n cone_half_angle = np.radians(30)\n cone_r = cone_h * np.tan(cone_half_angle)\n vcyl, ncyl = cylinder_strip(cyl_r, cyl_h, facets)\n vcone, ncone = cone_strip(cone_r, cone_h, facets)\n vcone[:,2] += cyl_h\n v = np.vstack([vcyl, vcone])\n n = np.vstack([ncyl, ncone])\n return v, n\n\n\n#\n# private helper functions, not part of API\n#\ndef _npa(*args):\n return np.array(args)\n\ndef _normalize(x):\n if len(x.shape) == 1:\n return x / np.linalg.norm(x)\n elif len(x.shape) == 2:\n return x / np.linalg.norm(x, axis=1)[:,None]\n else:\n assert False\n\ndef _withz(a, z):\n b = 0 + a\n b[:,2] = z\n return b\n\ndef _rot2d(theta):\n c = np.cos(theta)\n s = np.sin(theta)\n return np.array([[c, -s], [s, c]])\n\n# add degenerate tris, convert from N x 2 x 3 to 2N+2 x 3\ndef _to_strip(strip):\n s0 = strip[0,0,:]\n s1 = strip[-1,-1,:]\n return np.vstack([s0, np.reshape(strip, (-1, 3)), s1])\n\ndef _scale_to_inplace(a, min1, max1):\n id0 = id(a)\n min0 = np.min(a.flatten())\n max0 = np.max(a.flatten())\n scl = (max1 - min1) / (max0 - min0)\n shift = - (scl * min0) + min1\n a *= scl\n a += shift\n assert id(a) == id0\n\ndef _np2tex(a):\n # TODO color\n w, h = a.shape\n b = np.uint8(a).tobytes()\n assert len(b) == w * h\n img = pyglet.image.ImageData(w, h, \"L\", b)\n return img.get_texture()\n\n\n"
},
{
"alpha_fraction": 0.6714212894439697,
"alphanum_fraction": 0.6737986207008362,
"avg_line_length": 27.731706619262695,
"blob_id": "d3eb3d9c72c65587aa2dc9bce7261e128cc5fa3f",
"content_id": "99a597cc01881bb3d5bb46d8a5b865247589f171",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5889,
"license_type": "no_license",
"max_line_length": 96,
"num_lines": 205,
"path": "/quad_gen/get_models.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nimport argparse\nimport csv\nimport joblib\nimport os\nimport re\nimport sys\nimport shutil\nimport tensorflow as tf\nimport yaml\n\nimport gaussian_mlp as mlp\n\ndef subdir(root_dir):\n\t\"\"\"\n\treturn all subdirectories as a list\n\tArgs:\n\t\tfolder [str]: a root directory\n\trtype:\n\t\tList[str]\n\t\"\"\"\n\treturn [sub_f.path for sub_f in os.scandir(root_dir) if sub_f.is_dir() ]\n\ndef read_txt_to_get_dirs(root_dir, txt):\n\t\"\"\"\n\tRead a txt file containing directories to models\n\tAssuming that all the directories are sub directories\n\t(i.e. the full path to a model is root + '/' + sub_dir)\n\t\"\"\"\n\tsub_dirs = []\n\troot_dir = root_dir.strip().rstrip(os.sep)\n\twith open(txt, 'r') as f:\n\t\tfor line in f:\n\t\t\tline = line.strip().lstrip(os.sep)\n\t\t\tprint(root_dir + '/' + line)\n\t\t\tassert os.path.isdir(root_dir + '/' + line) == True\n\t\t\tsub_dirs.append(root_dir + '/' + line)\n\treturn sub_dirs\n\ndef analyze_seeds(experiment):\n\t'''\n\tArgs:\n\t\texperiment [str]: root directory of a single experiment containing multiple seeds\n\trtype [str]:\n\t\tthe directory of the seed with the highest average reward\n\t'''\n\n\tassert os.path.isdir(experiment) == True\n\n\tseeds = subdir(experiment)\n\n\thighest_reward = -float('inf')\n\tfor seed_dir in seeds:\n\t\t## check if it is a seed directory\n\t\tseed_dir_split = seed_dir.split('/')\n\t\tif not re.search(r'^seed_*', seed_dir_split[-1]):\n\t\t\tprint('Experiment %s has seed folder that is named incorrectly... terminating...' % seed_dir)\n\t\t\texit(1)\n\t\telse:\n\t\t\twith open(seed_dir + '/progress.csv', 'r') as csvfile:\n\t\t\t\tprogress_reader = csv.DictReader(csvfile)\n\t\t\t\tmain_reward_latest = list(progress_reader)[-1]['rewards/rew_main_avg']\n\t\t\t\tif highest_reward <= float(main_reward_latest):\n\t\t\t\t\ttarget_seed = seed_dir\n\t\t\t\t\tbest_seed = seed_dir_split[-1]\n\t\t\t\t\thighest_reward = float(main_reward_latest)\n\n\n\tprint('Best seed: %s' % best_seed)\n\treturn target_seed\n\ndef save_result(model_dir, out_dir, osi=False, absolute_path=False):\n\t\"\"\"\n\tSave the params.pkl file and the config file.\n\tConvert the graph to source code and save\n\tArgs:\n\t\tmodel_dir [str]: the directory of which the pickle file is located\n\t\tout_dir [str]: the root directory of which the model should be saved\n\t\tosi [bool]: indicates whether the model is an osi\n\t\tabsolute_path [bool]: (default False) indicated whether the out_dir \n\t\t\thas been modified to the desired sub location\n\t\"\"\"\n\tmodel_dir = model_dir.rstrip(os.sep)\n\tout_dir = out_dir.rstrip(os.sep)\n\t\n\tif not absolute_path:\n\t\t## the out_dir is still the out_dir provided at the command line\n\t\t## try to append the correct sub_dir to it\n\t\tdesired_sub_p = model_dir.split('/')[-5:]\n\t\tdesired_sub_p = '/'.join(desired_sub_p)\n\t\tout_dir += '/' + desired_sub_p\n\n\ttry:\n\t\tos.makedirs(out_dir, exist_ok=True)\n\texcept FileExistsError:\n\t\t# directory already exists\n\t\tpass\n\n\tshutil.copyfile(model_dir + '/params.pkl', out_dir + '/params.pkl')\n\tshutil.copyfile(model_dir + '/config.yml', out_dir + '/config.yml')\n\n\ttf.reset_default_graph()\n\twith tf.Session() as sess:\n\n\t\tprint(\"extrating parameters from file %s ...\" % model_dir + '/params.pkl')\n\t\tpkl_params = joblib.load(model_dir + '/params.pkl')\n\t\tpolicy = pkl_params['policy']\n\n\t\tmlp.generate(policy, sess, out_dir+'/network_evaluate.c')\n\ndef copy_by_best_seed(root_dir, out_dir):\n\t\"\"\"\n\tTODO: write comments\n\t\"\"\"\n\tprint('Searching root %s ...' % root_dir)\n\tprint('================================')\n\tsubdirs = subdir(root_dir)\n\n\tfor experiment in subdirs:\n\t\tprint('Searching subdir %s ... Analyzing seeds' % experiment)\n\t\t## grad the seed with the highest average reward\n\t\ttarget_seed = analyze_seeds(experiment)\n\t\tsave_result(target_seed, out_dir)\n\ndef copy_by_txt(root_dir, out_dir, txt):\n\t\"\"\"\n\tCopy the models specified in a txt file\n\tAll the models must be located under the root_dir\n\tArgs:\n\t\troot_dir [str]: the root directory\n\t\tout_dir [str]: the output directory [will create one if it doesn't exist]\n\t\ttxt [str]: the txt file specifying the model relative directories\n\t\"\"\"\n\tprint('searching root %s ...' % root_dir)\n\tprint('================================')\n\n\tsubdirs = read_txt_to_get_dirs(root_dir, txt)\n\tfor experiment in subdirs:\n\t\tprint('copying params.pkl from %s to %s...' % (experiment, out_dir))\n\t\tsave_result(experiment, out_dir)\n\n\ndef traverse_root(root_dir, out_dir):\n\t\"\"\"\n\tRecursively search for pickle files of models and \n\tcovert the model if found\n\n\tArgs:\n\t\troot_dir [str]: the root directory\n\t\tout_dir [str]: the output directory [will create one if it doesn't exist]\n\t\tosi [bool]: to indicate if a model is an osi\n\t\"\"\"\n\tsubdirs = subdir(root_dir)\n\tfor path in subdirs:\n\t\tpath = path.rstrip(os.sep)\n\t\tif os.path.isfile(path + '/params.pkl') == True:\n\t\t\tsave_path = '/'.join([i for i in path.split('/')[-5:]]) ## -5 is picked appropriately\n\t\t\tsave_path = out_dir.rstrip(os.sep)+'/'+save_path\n\t\t\tprint('copying params.pkl from %s to %s...' % (path, save_path))\n\t\t\tsave_result(path, save_path, absolute_path=True)\n\t\telse:\n\t\t\ttraverse_root(path, out_dir)\n\ndef main(args):\n\tif args.mode == 0:\n\t\tcopy_by_txt(args.root_dir, args.out_dir, args.txt)\n\telif args.mode == 1:\n\t\tcopy_by_best_seed(args.root_dir, args.out_dir)\n\telif args.mode == 2:\n\t\ttraverse_root(args.root_dir, args.out_dir)\n\nif __name__ == \"__main__\":\n\tparser = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter)\n\tparser.add_argument(\n\t\t'mode',\n\t\ttype=int,\n\t\tdefault=2,\n\t\thelp='select a mode to copy file.\\n'\n\t\t\t '0: a txt file with dirs\\n'\n\t\t\t '1: a root where all the experiments are stored and select the best seeds.\\n'\n\t\t\t '2: a root dir where all the subdirs that contain plk file will be copied.\\n', \n\t)\n\n\tparser.add_argument(\n\t\t'root_dir',\n\t\ttype=str,\n\t\thelp='Root dir of the experiments'\n\t)\n\n\tparser.add_argument(\n\t\t'out_dir', \n\t\ttype=str,\n\t\thelp='dir to save the experiments'\n\t)\n\n\tparser.add_argument(\n\t\t'-txt',\n\t\ttype=str,\n\t\thelp='txt file that contains all the models'\n\t)\n\n\targs = parser.parse_args() \n\n\tmain(args)"
},
{
"alpha_fraction": 0.6904761791229248,
"alphanum_fraction": 0.7083333134651184,
"avg_line_length": 41.25,
"blob_id": "63a9080a3dfc24d68c5864a6b7cdabc024c0cd54",
"content_id": "019bae0697bc38cf5debd2d5336edbffde4bdd2c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 168,
"license_type": "no_license",
"max_line_length": 132,
"num_lines": 4,
"path": "/quad_train/launchers/ppo_crazyflie_noisy_nodamp__rew_hwangbo.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nparallel ./train_quad.py config/ppo__crazyflie_noisy_nodamp__rew_hwangbo.yml _results_temp/ppo_crazyflie_noisy_nodamp__rew_hwangbo \\\n--seed {1} \\\n::: {1..3}"
},
{
"alpha_fraction": 0.5663020610809326,
"alphanum_fraction": 0.5874112248420715,
"avg_line_length": 37.32352828979492,
"blob_id": "1dbc8af208b1d7a480aa88d0b9ed2b837e3a20b2",
"content_id": "176ab523455a453a7b4f61dcba61bcc6ddefc8f3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5211,
"license_type": "no_license",
"max_line_length": 80,
"num_lines": 136,
"path": "/quad_sim/quadrotor_obstacles.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom numpy.linalg import norm\nfrom quad_sim.quad_utils import *\nimport quad_sim.rendering3d as r3d\n\n# determine where to put the obstacles such that no two obstacles intersect\n# and compute the list of obstacles to collision check at each 2d tile.\ndef _place_obstacles(np_random, N, box, radius_range, our_radius, tries=5):\n\n t = np.linspace(0, box, TILES+1)[:-1]\n scale = box / float(TILES)\n x, y = np.meshgrid(t, t)\n pts = np.zeros((N, 2))\n dist = x + np.inf\n\n radii = np_random.uniform(*radius_range, size=N)\n radii = np.sort(radii)[::-1]\n test_list = [[] for i in range(TILES**2)]\n\n for i in range(N):\n rad = radii[i]\n ok = np.where(dist.flat > rad)[0]\n if len(ok) == 0:\n if tries == 1:\n print(\"Warning: only able to place {}/{} obstacles. \"\n \"Increase box, decrease radius, or decrease N.\")\n return pts[:i,:], radii[:i]\n else:\n return _place_obstacles(N, box, radius_range, tries-1)\n pt = np.unravel_index(np_random.choice(ok), dist.shape)\n pt = scale * np.array(pt)\n d = np.sqrt((x - pt[1])**2 + (y - pt[0])**2) - rad\n # big slop factor for tile size, off-by-one errors, etc\n for ind1d in np.where(d.flat <= 2*our_radius + scale)[0]:\n test_list[ind1d].append(i)\n dist = np.minimum(dist, d)\n pts[i,:] = pt - box/2.0\n\n # very coarse to allow for binning bugs\n test_list = np.array(test_list).reshape((TILES, TILES))\n #amt_free = sum(len(a) == 0 for a in test_list.flat) / float(test_list.size)\n #print(amt_free * 100, \"pct free space\")\n return pts, radii, test_list\n\n\n# generate N obstacles w/ randomized primitive, size, color, TODO texture\n# arena: boundaries of world in xy plane\n# our_radius: quadrotor's radius\ndef _random_obstacles(np_random, N, arena, our_radius):\n arena = float(arena)\n # all primitives should be tightly bound by unit circle in xy plane\n boxside = np.sqrt(2)\n box = r3d.box(boxside, boxside, boxside)\n sphere = r3d.sphere(radius=1.0, facets=16)\n cylinder = r3d.cylinder(radius=1.0, height=2.0, sections=32)\n # TODO cone-sphere collision\n #cone = r3d.cone(radius=0.5, height=1.0, sections=32)\n primitives = [box, sphere, cylinder]\n\n bodies = []\n max_radius = 2.0\n positions, radii, test_list = _place_obstacles(\n np_random, N, arena, (0.5, max_radius), our_radius)\n for i in range(N):\n primitive = np_random.choice(primitives)\n tex_type = r3d.random_textype()\n tex_dark = 0.5 * np_random.uniform()\n tex_light = 0.5 * np_random.uniform() + 0.5\n color = 0.5 * np_random.uniform(size=3)\n heightscl = np.random.uniform(0.5, 2.0)\n height = heightscl * 2.0 * radii[i]\n z = (0 if primitive is cylinder else\n (height/2.0 if primitive is sphere else\n (height*boxside/4.0 if primitive is box\n else np.nan)))\n translation = np.append(positions[i,:], z)\n matrix = np.matmul(r3d.translate(translation), r3d.scale(radii[i]))\n matrix = np.matmul(matrix, np.diag([1, 1, heightscl, 1]))\n body = r3d.Transform(matrix,\n #r3d.ProceduralTexture(tex_type, (tex_dark, tex_light), primitive))\n r3d.Color(color, primitive))\n bodies.append(body)\n\n return ObstacleMap(arena, bodies, test_list)\n\n\n# main class for non-visual aspects of the obstacle map.\nclass ObstacleMap(object):\n def __init__(self, box, bodies, test_lists):\n self.box = box\n self.bodies = bodies\n self.test = test_lists\n\n def detect_collision(self, dynamics):\n pos = dynamics.pos\n if pos[2] <= dynamics.arm:\n print(\"collided with terrain\")\n return True\n r, c = self.coord2tile(*dynamics.pos[:2])\n if r < 0 or c < 0 or r >= TILES or c >= TILES:\n print(\"collided with wall\")\n return True\n if self.test is not None:\n radius = dynamics.arm + 0.1\n return any(self.bodies[k].collide_sphere(pos, radius)\n for k in self.test[r,c])\n return False\n\n def sample_start(self, np_random):\n pad = 4\n band = TILES // 8\n return self.sample_freespace((pad, pad + band), np_random)\n\n def sample_goal(self, np_random):\n pad = 4\n band = TILES // 8\n return self.sample_freespace((-(pad + band), -pad), np_random)\n\n def sample_freespace(self, rowrange, np_random):\n rfree, cfree = np.where(np.vectorize(lambda t: len(t) == 0)(\n self.test[rowrange[0]:rowrange[1],:]))\n choice = np_random.choice(len(rfree))\n r, c = rfree[choice], cfree[choice]\n r += rowrange[0]\n x, y = self.tile2coord(r, c)\n z = np_random.uniform(1.0, 3.0)\n return np.array([x, y, z])\n\n def tile2coord(self, r, c):\n #TODO consider moving origin to corner of world\n scale = self.box / float(TILES)\n return scale * np.array([r,c]) - self.box / 2.0\n\n def coord2tile(self, x, y):\n scale = float(TILES) / self.box\n return np.int32(scale * (np.array([x,y]) + self.box / 2.0))"
},
{
"alpha_fraction": 0.6666666865348816,
"alphanum_fraction": 0.6888889074325562,
"avg_line_length": 32.75,
"blob_id": "a3c89425881a96c2c23002a471eead8dd862a932",
"content_id": "a80ec18ea2d1f3891c856047722703d2dc2dcaf2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 135,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 4,
"path": "/quad_train/launchers/ppo_crazyflie_baseline.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nparallel ./train_quad.py config/ppo__crazyflie_baseline.yml _results_temp/ppo_crazyflie_baseline \\\n--seed {1} \\\n::: {1..5}\n"
},
{
"alpha_fraction": 0.5303810238838196,
"alphanum_fraction": 0.5708417892456055,
"avg_line_length": 43.12916564941406,
"blob_id": "fb787f8a2df23da2be5fb3b740c6088919ad3abe",
"content_id": "a0a0418ea24c040d6c89901d1fe1d15d446afaca",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 21181,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 480,
"path": "/quad_sim/quadrotor_randomization.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom numpy.linalg import norm\nfrom copy import deepcopy\n\nfrom quad_sim.quad_utils import *\nfrom quad_sim.quad_models import *\n\ndef clip_params_positive(params):\n def clip_positive(key, item):\n return np.clip(item, a_min=0., a_max=None)\n walk_dict(params, clip_positive)\n return params\n\ndef check_quad_param_limits(params, params_init=None):\n ## Body parameters (like lengths and masses) are always positive\n for key in [\"body\", \"payload\", \"arms\", \"motors\", \"propellers\"]:\n params[\"geom\"][key] = clip_params_positive(params[\"geom\"][key])\n\n params[\"geom\"][\"motor_pos\"][\"xyz\"][:2] = np.clip(params[\"geom\"][\"motor_pos\"][\"xyz\"][:2], a_min=0.005, a_max=None)\n body_w = params[\"geom\"][\"body\"][\"w\"]\n params[\"geom\"][\"payload_pos\"][\"xy\"] = np.clip(params[\"geom\"][\"payload_pos\"][\"xy\"], a_min=-body_w/4., a_max=body_w/4.) \n params[\"geom\"][\"arms_pos\"][\"angle\"] = np.clip(params[\"geom\"][\"arms_pos\"][\"angle\"], a_min=0., a_max=90.) \n \n ## Damping parameters\n params[\"damp\"][\"vel\"] = np.clip(params[\"damp\"][\"vel\"], a_min=0.00000, a_max=1.)\n params[\"damp\"][\"omega_quadratic\"] = np.clip(params[\"damp\"][\"omega_quadratic\"], a_min=0.00000, a_max=1.)\n \n ## Motor parameters\n params[\"motor\"][\"thrust_to_weight\"] = np.clip(params[\"motor\"][\"thrust_to_weight\"], a_min=1.2, a_max=None)\n params[\"motor\"][\"torque_to_thrust\"] = np.clip(params[\"motor\"][\"torque_to_thrust\"], a_min=0.001, a_max=1.)\n params[\"motor\"][\"linearity\"] = np.clip(params[\"motor\"][\"linearity\"], a_min=0., a_max=1.)\n params[\"motor\"][\"assymetry\"] = np.clip(params[\"motor\"][\"assymetry\"], a_min=0.9, a_max=1.1)\n params[\"motor\"][\"C_drag\"] = np.clip(params[\"motor\"][\"C_drag\"], a_min=0., a_max=None)\n params[\"motor\"][\"C_roll\"] = np.clip(params[\"motor\"][\"C_roll\"], a_min=0., a_max=None)\n params[\"motor\"][\"damp_time_up\"] = np.clip(params[\"motor\"][\"damp_time_up\"], a_min=0., a_max=None)\n params[\"motor\"][\"damp_time_down\"] = np.clip(params[\"motor\"][\"damp_time_down\"], a_min=0., a_max=None)\n\n ## Make sure propellers make sense in size\n if params_init is not None:\n r0 = params_init[\"geom\"][\"propellers\"][\"r\"]\n t2w, t2w0 = params_init[\"motor\"][\"thrust_to_weight\"], params[\"motor\"][\"thrust_to_weight\"]\n params[\"geom\"][\"propellers\"][\"r\"] = r0 * (t2w/t2w0)**0.5\n\n return params\n\ndef get_dyn_randomization_params(quad_params, noise_ratio=0., noise_ratio_params=None):\n \"\"\"\n The function updates noise params\n Args:\n noise_ratio (float): ratio of change relative to the nominal values\n noise_ratio_params (dict): if for some parameters you want to have different ratios relative to noise_ratio,\n you can provided it through this dictionary\n Returns:\n noise_params dictionary\n \"\"\"\n ## Setting the initial noise ratios (nominal ones)\n noise_params = deepcopy(quad_params)\n def set_noise_ratio(key, item):\n if isinstance(item, str):\n return None\n else:\n return noise_ratio\n \n walk_dict(noise_params, set_noise_ratio)\n\n ## Updating noise ratios\n if noise_ratio_params is not None:\n # noise_params.update(noise_ratio_params)\n dict_update_existing(noise_params, noise_ratio_params)\n return noise_params\n\n\ndef perturb_dyn_parameters(params, noise_params, sampler=\"normal\"):\n \"\"\"\n The function samples around nominal parameters provided noise parameters\n Args:\n params (dict): dictionary of quadrotor parameters\n noise_params (dict): dictionary of noise parameters with the same hierarchy as params, but\n contains ratio of deviation from the params\n Returns:\n dict: modified parameters\n \"\"\"\n ## Sampling parameters\n def sample_normal(key, param_val, ratio):\n #2*ratio since 2std contain 98% of all samples\n param_val_sample = np.random.normal(loc=param_val, scale=np.abs((ratio/2)*np.array(param_val)))\n return param_val_sample, ratio\n \n def sample_uniform(key, param_val, ratio):\n param_val = np.array(param_val)\n return np.random.uniform(low=param_val - param_val*ratio, high=param_val + param_val*ratio), ratio\n\n sample_param = locals()[\"sample_\" + sampler]\n\n params_new = deepcopy(params)\n walk_2dict(params_new, noise_params, sample_param)\n\n ## Fixing a few parameters if they go out of allowed limits\n params_new = check_quad_param_limits(params_new, params)\n # print_dic(params_new)\n\n return params_new\n\ndef sample_random_dyn():\n \"\"\"\n The function samples parameters for all possible quadrotors\n Args:\n scale (float): scale of sampling\n Returns:\n dict: sampled quadrotor parameters\n \"\"\"\n ###################################################################\n ## DENSITIES (body, payload, arms, motors, propellers)\n # Crazyflie estimated body / payload / arms / motors / props density: 1388.9 / 1785.7 / 1777.8 / 1948.8 / 246.6 kg/m^3\n # Hummingbird estimated body / payload / arms / motors/ props density: 588.2 / 173.6 / 1111.1 / 509.3 / 246.6 kg/m^3\n geom_params = {}\n dens_val = np.random.uniform(\n low=[500., 200., 500., 500., 200.], \n high=[2000., 2000., 2000., 4500., 300.])\n \n geom_params[\"body\"] = {\"density\": dens_val[0]}\n geom_params[\"payload\"] = {\"density\": dens_val[1]}\n geom_params[\"arms\"] = {\"density\": dens_val[2]}\n geom_params[\"motors\"] = {\"density\": dens_val[3]}\n geom_params[\"propellers\"] = {\"density\": dens_val[4]}\n\n ###################################################################\n ## GEOMETRIES\n # MOTORS (and overal size)\n total_w = np.random.uniform(low=0.05, high=0.2)\n total_l = np.clip(np.random.normal(loc=1., scale=0.1), a_min=1.0, a_max=None) * total_w\n motor_z = np.random.normal(loc=0., scale=total_w / 8.)\n geom_params[\"motor_pos\"] = {\"xyz\": [total_w / 2., total_l / 2., motor_z]}\n geom_params[\"motors\"][\"r\"] = total_w * np.random.normal(loc=0.1, scale=0.01)\n geom_params[\"motors\"][\"h\"] = geom_params[\"motors\"][\"r\"] * np.random.normal(loc=1.0, scale=0.05)\n \n # BODY\n w_low, w_high = 0.25, 0.5\n w_coeff = np.random.uniform(low=w_low, high=w_high)\n geom_params[\"body\"][\"w\"] = w_coeff * total_w\n ## Promotes more elangeted bodies when they are more narrow\n l_scale = (1. - (w_coeff - w_low) / (w_high - w_low))\n geom_params[\"body\"][\"l\"] = np.clip(np.random.normal(loc=1., scale=l_scale), a_min=1.0, a_max=None) * geom_params[\"body\"][\"w\"]\n geom_params[\"body\"][\"h\"] = np.random.uniform(low=0.1, high=1.5) * geom_params[\"body\"][\"w\"]\n\n # PAYLOAD\n pl_scl = np.random.uniform(low=0.25, high=1.0, size=3)\n geom_params[\"payload\"][\"w\"] = pl_scl[0] * geom_params[\"body\"][\"w\"]\n geom_params[\"payload\"][\"l\"] = pl_scl[1] * geom_params[\"body\"][\"l\"]\n geom_params[\"payload\"][\"h\"] = pl_scl[2] * geom_params[\"body\"][\"h\"]\n geom_params[\"payload_pos\"] = {\n \"xy\": np.random.normal(loc=0., scale=geom_params[\"body\"][\"w\"] / 10., size=2), \n \"z_sign\": np.sign(np.random.uniform(low=-1, high=1))}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n # ARMS\n geom_params[\"arms\"][\"w\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n geom_params[\"arms\"][\"h\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n geom_params[\"arms_pos\"] = {\"angle\": np.random.normal(loc=45., scale=10.), \"z\": motor_z - geom_params[\"motors\"][\"h\"]/2.}\n \n # PROPS\n thrust_to_weight = np.random.uniform(low=1.8, high=2.5)\n # thrust_to_weight = np.random.uniform(low=2.3, high=2.5)\n geom_params[\"propellers\"][\"h\"] = 0.01\n geom_params[\"propellers\"][\"r\"] = (0.3) * total_w * (thrust_to_weight / 2.0)**0.5\n \n ## Damping parameters\n # damp_vel_scale = np.random.uniform(low=0.01, high=2.)\n # damp_omega_scale = damp_vel_scale * np.random.uniform(low=0.75, high=1.25)\n # damp_params = {\n # \"vel\": 0.001 * damp_vel_scale, \n # \"omega_quadratic\": 0.015 * damp_omega_scale}\n damp_params = {\n \"vel\": 0.0, \n \"omega_quadratic\": 0.0}\n\n ## Noise parameters\n noise_params = {}\n noise_params[\"thrust_noise_ratio\"] = np.random.uniform(low=0.01, high=0.05) #0.01\n \n ## Motor parameters\n damp_time_up = np.random.uniform(low=0.15, high=0.2)\n damp_time_down_scale = np.random.uniform(low=1.0, high=1.0)\n motor_params = {\"thrust_to_weight\" : thrust_to_weight,\n \"torque_to_thrust\": np.random.uniform(low=0.005, high=0.025), #0.05 originally\n \"assymetry\": np.random.uniform(low=0.9, high=1.1, size=4),\n \"linearity\": 1.0,\n \"C_drag\": 0.,\n \"C_roll\": 0.,\n \"damp_time_up\": damp_time_up,\n \"damp_time_down\": damp_time_down_scale * damp_time_up\n # \"linearity\": np.random.normal(loc=0.5, scale=0.1)\n }\n\n ## Summarizing\n params = {\n \"geom\": geom_params, \n \"damp\": damp_params, \n \"noise\": noise_params,\n \"motor\": motor_params\n }\n\n ## Checking everything\n params = check_quad_param_limits(params=params)\n return params\n\ndef sample_random_dyn_nodelay():\n params = sample_random_dyn()\n params[\"motor\"][\"damp_time_up\"] = 0.\n params[\"motor\"][\"damp_time_down\"] = 0.\n return params\n\ndef sample_random_thrust2weight_15_25():\n params = sample_random_dyn()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=1.5, high=2.5)\n # params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.8, high=2.8)\n return params\n\ndef sample_random_thrust2weight_15_35():\n params = sample_random_dyn()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=1.5, high=3.5)\n return params\n\ndef sample_random_thrust2weight_20_30():\n params = sample_random_dyn()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=3.0)\n return params\n\ndef sample_random_thrust2weight_20_40():\n params = sample_random_dyn()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=4.0)\n return params\n\ndef sample_random_thrust2weight_20_50():\n params = sample_random_dyn()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=5.0)\n return params\n\ndef sample_random_with_linearity():\n params = sample_random_dyn()\n params[\"motor\"][\"linearity\"] = np.random.uniform(low=0., high=1.)\n return params\n\n\n\ndef sample_crazyflie_thrust2weight_18_25():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=1.8, high=2.5)\n return params\n\ndef sample_crazyflie_thrust2weight_15_25():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=1.5, high=2.5)\n return params\n\ndef sample_crazyflie_thrust2weight_15_35():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=1.5, high=3.5)\n return params\n\ndef sample_crazyflie_thrust2weight_20_30():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=3.0)\n return params\n\ndef sample_crazyflie_thrust2weight_20_40():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=4.0)\n return params\n\ndef sample_crazyflie_thrust2weight_20_50():\n params = crazyflie_params()\n params[\"motor\"][\"thrust_to_weight\"] = np.random.uniform(low=2.0, high=5.0)\n return params\n\n\ndef sample_random_dyn_lowinertia():\n \"\"\"\n The function samples parameters for all possible quadrotors\n Args:\n scale (float): scale of sampling\n Returns:\n dict: sampled quadrotor parameters\n \"\"\"\n ###################################################################\n ## DENSITIES (body, payload, arms, motors, propellers)\n # Crazyflie estimated body / payload / arms / motors / props density: 1388.9 / 1785.7 / 1777.8 / 1948.8 / 246.6 kg/m^3\n # Hummingbird estimated body / payload / arms / motors/ props density: 588.2 / 173.6 / 1111.1 / 509.3 / 246.6 kg/m^3\n geom_params = {}\n dens_val = np.random.uniform(\n low=[1500., 1500., 150., 150., 15.], \n high=[2500., 2500., 250., 250., 25.])\n \n geom_params[\"body\"] = {\"density\": dens_val[0]}\n geom_params[\"payload\"] = {\"density\": dens_val[1]}\n geom_params[\"arms\"] = {\"density\": dens_val[2]}\n geom_params[\"motors\"] = {\"density\": dens_val[3]}\n geom_params[\"propellers\"] = {\"density\": dens_val[4]}\n\n ###################################################################\n ## GEOMETRIES\n # MOTORS (and overal size)\n total_w = np.random.uniform(low=0.05, high=0.2)\n total_l = np.clip(np.random.normal(loc=1., scale=0.1), a_min=1.0, a_max=None) * total_w\n motor_z = np.random.normal(loc=0., scale=total_w / 8.)\n geom_params[\"motor_pos\"] = {\"xyz\": [total_w / 2., total_l / 2., motor_z]}\n geom_params[\"motors\"][\"r\"] = total_w * np.random.normal(loc=0.1, scale=0.01)\n geom_params[\"motors\"][\"h\"] = geom_params[\"motors\"][\"r\"] * np.random.normal(loc=1.0, scale=0.05)\n \n # BODY\n w_low, w_high = 0.2, 0.4\n w_coeff = np.random.uniform(low=w_low, high=w_high)\n geom_params[\"body\"][\"w\"] = w_coeff * total_w\n ## Promotes more elangeted bodies when they are more narrow\n l_scale = (1. - (w_coeff - w_low) / (w_high - w_low))\n geom_params[\"body\"][\"l\"] = np.clip(np.random.normal(loc=1., scale=l_scale), a_min=1.0, a_max=2.0) * geom_params[\"body\"][\"w\"]\n geom_params[\"body\"][\"h\"] = np.random.uniform(low=0.25, high=1.0) * geom_params[\"body\"][\"w\"]\n\n # PAYLOAD\n pl_scl = np.random.uniform(low=0.50, high=1.0, size=2)\n pl_scl_h = np.random.uniform(low=0.25, high=0.75, size=1)\n geom_params[\"payload\"][\"w\"] = pl_scl[0] * geom_params[\"body\"][\"w\"]\n geom_params[\"payload\"][\"l\"] = pl_scl[1] * geom_params[\"body\"][\"l\"]\n geom_params[\"payload\"][\"h\"] = pl_scl_h[0] * geom_params[\"body\"][\"h\"]\n geom_params[\"payload_pos\"] = {\n \"xy\": np.random.normal(loc=0., scale=geom_params[\"body\"][\"w\"] / 10., size=2), \n \"z_sign\": np.sign(np.random.uniform(low=-1, high=1))}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n # ARMS\n geom_params[\"arms\"][\"w\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n geom_params[\"arms\"][\"h\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n geom_params[\"arms_pos\"] = {\"angle\": np.random.normal(loc=45., scale=10.), \"z\": motor_z - geom_params[\"motors\"][\"h\"]/2.}\n \n # PROPS\n thrust_to_weight = np.random.uniform(low=1.8, high=2.5)\n geom_params[\"propellers\"][\"h\"] = 0.01\n geom_params[\"propellers\"][\"r\"] = (0.3) * total_w * (thrust_to_weight / 2.0)**0.5\n \n ## Damping parameters\n # damp_vel_scale = np.random.uniform(low=0.01, high=2.)\n # damp_omega_scale = damp_vel_scale * np.random.uniform(low=0.75, high=1.25)\n # damp_params = {\n # \"vel\": 0.001 * damp_vel_scale, \n # \"omega_quadratic\": 0.015 * damp_omega_scale}\n damp_params = {\n \"vel\": 0.0, \n \"omega_quadratic\": 0.0}\n\n ## Noise parameters\n noise_params = {}\n noise_params[\"thrust_noise_ratio\"] = np.random.uniform(low=0.05, high=0.1) #0.01\n \n ## Motor parameters\n damp_time_up = np.random.uniform(low=0.1, high=0.2)\n damp_time_down_scale = np.random.uniform(low=1.0, high=2.0)\n motor_params = {\"thrust_to_weight\" : thrust_to_weight,\n \"torque_to_thrust\": np.random.uniform(low=0.005, high=0.02), #0.05 originally\n \"assymetry\": np.random.uniform(low=0.9, high=1.1, size=4),\n \"linearity\": 1.0,\n \"C_drag\": 0.,\n \"C_roll\": 0.,\n \"damp_time_up\": damp_time_up,\n \"damp_time_down\": damp_time_down_scale * damp_time_up\n # \"linearity\": np.random.normal(loc=0.5, scale=0.1)\n }\n\n ## Summarizing\n params = {\n \"geom\": geom_params, \n \"damp\": damp_params, \n \"noise\": noise_params,\n \"motor\": motor_params\n }\n\n ## Checking everything\n params = check_quad_param_limits(params=params)\n return params\n\n\n\n # def sample_random_nondim_dyn():\n # \"\"\"\n # The function samples parameters for all possible non-dimensional quadrotors\n # Args:\n # scale (float): scale of sampling\n # Returns:\n # dict: sampled quadrotor parameters\n # \"\"\"\n # ###################################################################\n # ## DENSITIES (body, payload, arms, motors, propellers)\n # # Crazyflie estimated body / payload / arms / motors / props density: 1388.9 / 1785.7 / 1777.8 / 1948.8 / 246.6 kg/m^3\n # # Hummingbird estimated body / payload / arms / motors/ props density: 588.2 / 173.6 / 1111.1 / 509.3 / 246.6 kg/m^3\n # geom_params = {}\n \n # geom_params[\"body\"] = {\"mass\": 1.0}\n # geom_params[\"payload\"] = {\"mass\": 0}\n # geom_params[\"arms\"] = {\"mass\": 0.}\n # geom_params[\"motors\"] = {\"mass\": 0.}\n # geom_params[\"propellers\"] = {\"mass\": 0.}\n\n # ###################################################################\n # ## GEOMETRIES\n # # MOTORS (and overal size)\n # roll_authority = np.random.uniform(low=600, high=1200) #for our current low inertia CF ~ 1050\n # pitch_authority = np.random.uniform(low=0.8, high=1.0) * roll_authority\n # total_w = np.random.uniform(low=0.5, high=0.5)\n # total_l = total_w\n # motor_z = np.random.normal(loc=0., scale=total_w / 8.)\n # geom_params[\"motor_pos\"] = {\"xyz\": [total_w / 2., total_l / 2., motor_z]}\n # geom_params[\"motors\"][\"r\"] = total_w * np.random.normal(loc=0.1, scale=0.01)\n # geom_params[\"motors\"][\"h\"] = geom_params[\"motors\"][\"r\"] * np.random.normal(loc=1.0, scale=0.05)\n\n # # BODY\n # geom_params[\"body\"][\"w\"] = np.random.uniform(low=1.0, high=1.0)\n # ## Promotes more elangeted bodies when they are more narrow\n # geom_params[\"body\"][\"l\"] = np.random.uniform(low=1.0, high=2.0) * geom_params[\"body\"][\"w\"]\n # geom_params[\"body\"][\"h\"] = np.random.uniform(low=0.1, high=1.0) * geom_params[\"body\"][\"w\"]\n \n\n\n # # PAYLOAD\n # pl_scl = np.random.uniform(low=0.25, high=1.0, size=3)\n # geom_params[\"payload\"][\"w\"] = pl_scl[0] * geom_params[\"body\"][\"w\"]\n # geom_params[\"payload\"][\"l\"] = pl_scl[1] * geom_params[\"body\"][\"l\"]\n # geom_params[\"payload\"][\"h\"] = pl_scl[2] * geom_params[\"body\"][\"h\"]\n # geom_params[\"payload_pos\"] = {\n # \"xy\": np.random.normal(loc=0., scale=geom_params[\"body\"][\"w\"] / 10., size=2), \n # \"z_sign\": np.sign(np.random.uniform(low=-1, high=1))}\n # # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n # # ARMS\n # geom_params[\"arms\"][\"w\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n # geom_params[\"arms\"][\"h\"] = total_w * np.random.normal(loc=0.05, scale=0.005)\n # geom_params[\"arms_pos\"] = {\"angle\": np.random.normal(loc=45., scale=10.), \"z\": motor_z - geom_params[\"motors\"][\"h\"]/2.}\n \n # # PROPS\n # thrust_to_weight = np.random.uniform(low=1.8, high=2.5)\n # geom_params[\"propellers\"][\"h\"] = 0.01\n # geom_params[\"propellers\"][\"r\"] = (0.3) * total_w * (thrust_to_weight / 2.0)**0.5\n \n # ## Damping parameters\n # # damp_vel_scale = np.random.uniform(low=0.01, high=2.)\n # # damp_omega_scale = damp_vel_scale * np.random.uniform(low=0.75, high=1.25)\n # # damp_params = {\n # # \"vel\": 0.001 * damp_vel_scale, \n # # \"omega_quadratic\": 0.015 * damp_omega_scale}\n # damp_params = {\n # \"vel\": 0.0, \n # \"omega_quadratic\": 0.0}\n\n # ## Noise parameters\n # noise_params = {}\n # noise_params[\"thrust_noise_ratio\"] = np.random.uniform(low=0.01, high=0.05) #0.01\n \n # ## Motor parameters\n # damp_time_up = np.random.uniform(low=0.1, high=0.2)\n # damp_time_down_scale = np.random.uniform(low=1.0, high=2.0)\n # motor_params = {\"thrust_to_weight\" : thrust_to_weight,\n # \"torque_to_thrust\": np.random.uniform(low=0.005, high=0.025), #0.05 originally\n # \"assymetry\": np.random.uniform(low=0.9, high=1.1, size=4),\n # \"linearity\": 1.0,\n # \"C_drag\": 0.,\n # \"C_roll\": 0.,\n # \"damp_time_up\": damp_time_up,\n # \"damp_time_down\": damp_time_down_scale * damp_time_up\n # # \"linearity\": np.random.normal(loc=0.5, scale=0.1)\n # }\n\n # ## Summarizing\n # params = {\n # \"geom\": geom_params, \n # \"damp\": damp_params, \n # \"noise\": noise_params,\n # \"motor\": motor_params\n # }\n\n # ## Checking everything\n # params = check_quad_param_limits(params=params)\n # return params"
},
{
"alpha_fraction": 0.5202863812446594,
"alphanum_fraction": 0.5294351577758789,
"avg_line_length": 25.19791603088379,
"blob_id": "caa0fbf2abf346e483db4afa403d5ad3b48672b3",
"content_id": "d75bc4cf95ff3f890ad3f32b9ee7a813e43d9892",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2514,
"license_type": "no_license",
"max_line_length": 92,
"num_lines": 96,
"path": "/quad_train/plot_tools/plot_csv.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport pandas as pd\nfrom time import sleep\nfrom matplotlib import pyplot as plt\nimport argparse\n\n\ndef main():\n parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\"filename\", help='Name of the csv file')\n parser.add_argument(\"--time\", \"-t\", type=float, default=10, help='Sleep period')\n args = parser.parse_args()\n\n sleep_period = 10\n\n # MaxReturn,LossAfter,\n # BNN_DynModelSqLossAfter,\n # BNN_DynModelSqLossBefore,\n # AverageReturn,\n # Expl_MaxKL,\n # Iteration,\n # AverageDiscountedReturn,\n # MinReturn,\n # Expl_MinKL,\n # dLoss,Entropy,\n # AveragePolicyStd,\n # StdReturn,\n # Perplexity,\n # MeanKL,\n # ExplainedVariance,\n # Expl_MeanKL,\n # NumTrajs,\n # Expl_StdKL\n namelist = ['LossAfter',\n 'BNN_DynModelSqLossAfter',\n 'AverageReturn',\n 'AverageDiscountedReturn',\n 'Entropy',\n 'Perplexity',\n 'MeanKL',\n 'Expl_MeanKL',\n 'Expl_StdKL']\n\n plt.figure(1)\n subplot_indx = -1\n cols = 3\n rows = 3\n figures = {}\n for col_i in range(0, cols):\n for row_i in range(0, rows):\n subplot_indx += 1\n name = namelist[subplot_indx]\n figures[name] = plt.subplot('%d%d%d' % (cols, rows, subplot_indx + 1))\n\n plt.ion()\n plt.show()\n\n\n while True:\n data = pd.read_csv(args.filename, sep=',')\n namelist_cur = data.dtypes.index\n data = data.as_matrix()\n # print 'data= ', data\n\n # print 'namelist = ', namelist_cur\n # namelist_cur = data[0,:]\n # data = data[1:,:]\n\n # namelist_cur = namelist\n names_num = len(namelist_cur)\n\n subplot_indx = -1\n name_indx = {}\n for n_i in range(0,names_num):\n name_indx[namelist_cur[n_i]] = n_i\n # print 'dtype = ', type(data)\n\n for col_i in range(0, cols):\n for row_i in range(0, rows):\n subplot_indx += 1\n name = namelist[subplot_indx]\n n_i = name_indx[name]\n figures[name].clear()\n figures[name].plot(data[:, n_i])\n figures[name].set_title(name)\n plt.draw()\n plt.tight_layout()\n plt.pause(0.001)\n\n print('waiting for the next read ...')\n sleep(sleep_period)\n\n\n\nif __name__ == \"__main__\":\n main()"
},
{
"alpha_fraction": 0.5624568462371826,
"alphanum_fraction": 0.5679779052734375,
"avg_line_length": 33.23622131347656,
"blob_id": "25323dc255624147ed81a8b716bb4e96a74d90b3",
"content_id": "372c63688f1ada5aaad86cdac4d395b6e57ced49",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4347,
"license_type": "no_license",
"max_line_length": 108,
"num_lines": 127,
"path": "/quad_train/misc/variants_utils.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "\"\"\"\nDifferent utils helping with experiment variants generation\n\"\"\"\nimport argparse\nimport sys\nimport os\nimport datetime, time\nimport itertools\nimport os.path as osp\nimport uuid\nimport copy\n\nimport numpy as np\n\nimport dateutil.tz\nimport yaml\n\ndef set_dictval_by_name(dic, fullkey, val):\n \"\"\"\n Given a name like: param.subparam.subsubparam\n sets dict[param][subparam][subsubparam] = val\n \"\"\"\n keys = fullkey.split(\".\", 1)\n if len(keys) == 1:\n dic[keys[0]] = val\n else:\n if keys[0] not in dic:\n dic[keys[0]] = {}\n set_dictval_by_name(dic[keys[0]], keys[1], val)\n\ndef str2num(s):\n try:\n return int(s)\n except:\n try: \n return float(s)\n except:\n return s\n\ndef seed_str(seed):\n return \"%03d\" % seed\n\ndef grid_of_variants(args, param_def=None, remove_extra_folders=False):\n \"\"\"\n Grid parameter generation into a list of variants.\n @param: args: argument provided into a command line\n @param: param: default parameters provided (could be None)\n @param: remove_extra_folders: if a single experiment is - just dump in the root folder \n i.e. remove seed subfolder and subfolders named with param values\n \"\"\"\n ## Some auxiliary stuff if needed\n # rand_id = str(uuid.uuid4())[:5]\n # now = datetime.datetime.now(dateutil.tz.tzlocal())\n # timestamp = now.strftime('%Y_%m_%d_%H_%M_%S_%f_%Z')\n # exp_name = 'experiment_%s_%s' % (timestamp, rand_id)\n\n args.log_dir = args.log_dir.rstrip(os.sep) + os.sep\n\n if args.seed is None:\n seeds = [param_def[\"seed\"]]\n else:\n seeds = [int(x) for x in args.seed.split(',')]\n\n if args.param_name is None:\n # Just running with default settings\n param_name = None\n param_values = []\n else:\n param_name = [x for x in args.param_name.split(',')]\n if args.param_val is None:\n raise ValueError('No values provided for param %s' % param_name)\n else:\n param_values = [[str2num(y) for y in x.split(',')] for x in args.param_val.split(',,')]\n\n ## GRID of parameters to run: \n param_values.append(seeds)\n single_seed = len(seeds) == 1\n param_cart_product = itertools.product(*param_values)\n\n variants_list = []\n\n for param_tuple in param_cart_product:\n variant = copy.deepcopy(param_def)\n params = copy.deepcopy(param_def[\"variant\"])\n seed = param_tuple[-1]\n param_tuple = param_tuple[:-1]\n print('+++++++++++++++++++++++++++++++++++++++++++++++++++')\n print('PARAMETERS TUPLE: ', param_name, param_tuple, ' SEED: ', seed)\n\n if param_name is not None:\n log_dir = args.log_dir\n # In case we have a single parameter then we create subdirectories with values of this parameter\n if len(param_name) == 1:\n set_dictval_by_name(params, fullkey=param_name[0], val=param_tuple[0])\n log_dir += (param_name[0] + '/' + str(param_tuple[0]) + '/')\n else:\n for par_i, par in enumerate(param_name):\n set_dictval_by_name(params, fullkey=par, val=param_tuple[par_i])\n if par_i == 0:\n log_dir += (par + '_' + str(param_tuple[par_i]))\n else:\n log_dir += ('__' + par + '_' + str(param_tuple[par_i]))\n log_dir += '/'\n ## In case I want to eliminate unnecessary folders\n if not single_seed or not remove_extra_folders:\n log_dir += (\"seed_\" + seed_str(seed) + '/')\n else:\n log_dir = args.log_dir + \"seed_\" + seed_str(seed) + '/'\n log_dir_errors = log_dir + 'errors/'\n if not os.path.isdir(log_dir_errors):\n os.makedirs(log_dir_errors)\n\n variant['seed'] = seed\n variant['log_dir'] = log_dir\n variant[\"variant\"] = params #Confusing, but it is just a task variant (i.e. task parameters)\n\n # These are just copied from the args\n variant[\"n_parallel\"] = args.n_parallel \n variant[\"snapshot_mode\"] = args.snapshot_mode \n variant[\"plot\"] = args.plot \n\n variants_list.append(variant)\n\n if len(variants_list) == 1 and remove_extra_folders:\n variants_list[0][\"log_dir\"] = args.log_dir\n \n return variants_list"
},
{
"alpha_fraction": 0.5926532745361328,
"alphanum_fraction": 0.5987273454666138,
"avg_line_length": 32.788272857666016,
"blob_id": "c0d71714942cc17081c8d12c6a51abe9ccb0840e",
"content_id": "688d469702e2f088b84bcdbea874462a180c6004",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 10372,
"license_type": "no_license",
"max_line_length": 167,
"num_lines": 307,
"path": "/quad_train/plot_tools/plot_tools.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport numpy as np\nimport os, sys\nimport pandas as pd\nfrom scipy.signal import lfilter\nimport matplotlib.pyplot as plt\n\n\n\ndef subdir(folder):\n return [f.path for f in os.scandir(folder) if f.is_dir() ]\n\ndef get_opt_score(data, interval):\n \"\"\"\n Optimization score or fitness for the overal run\n \"\"\"\n return np.mean(data[-interval:])\n\ndef plot_seeds_stats(data_list, labels, fig_id=0, max_len=None, ylim_range=None, shade_alpha=0.2, \n xlabel_str=\"Iteration\", ylabel_str=None, \n width=6, height=4, linewidth = 2,\n top_n=None, top_n_interval=None):\n \"\"\"\n @param: data: list of numpy arrays with data\n @param: labels: how to call each numpy array of data\n \"\"\"\n\n # Preprocessing\n data_mean_list = []\n data_err_list = []\n data_len = []\n for di, data in enumerate(data_list):\n data_mean_list.append(np.mean(data, axis=0))\n data_err_list.append(np.std(data, axis=0))\n data_len.append(data_mean_list[-1].size)\n \n # Filtering out data that we should not plot\n if top_n is not None and top_n != 0:\n ## Calculating the score\n scores = []\n for di, data in enumerate(data_mean_list):\n scores.append(get_opt_score(data, top_n_interval))\n \n indx_sorted = np.argsort(scores)\n if top_n > 0:\n indices_retain = indx_sorted[-top_n:]\n elif top_n < 0:\n indices_retain = indx_sorted[:-top_n]\n \n labels_tmp , data_list_tmp, data_err_tmp, data_mean_tmp = [], [], [], []\n for i in indices_retain:\n labels_tmp.append(labels[i])\n data_list_tmp.append(data_list[i])\n data_err_tmp.append(data_err_list[i])\n data_mean_tmp.append(data_mean_list[i])\n\n labels, data_list, data_err_list, data_mean_list = labels_tmp , data_list_tmp, data_err_tmp, data_mean_tmp \n # import pdb; pdb.set_trace()\n\n # Getting default colors\n prop_cycle = plt.rcParams['axes.prop_cycle']\n colors = prop_cycle.by_key()['color']\n\n # Plotting (shades come first to avoid overlap with mean curves)\n plt.figure(fig_id, figsize=(width, height))\n for di, data in enumerate(data_list):\n error = data_err_list[di]\n mean = data_mean_list[di]\n x = np.arange(mean.shape[0])\n plt.fill_between(x, mean-error, mean+error,\n alpha=shade_alpha, facecolor=colors[di % len(colors)], antialiased=True)\n \n # Plotting Mean curves\n for di, data in enumerate(data_mean_list):\n x = np.arange(data.shape[0])\n plt.plot(data, linewidth=linewidth, color=colors[di % len(colors)], antialiased=True)\n\n # Setting properties\n plt.legend(labels)\n if max_len is not None:\n max_len = min(max_len, np.max(data_len))\n else:\n max_len = np.max(data_len)\n plt.xlim([0, max_len])\n if ylim_range is not None:\n plt.ylim(ylim_range)\n plt.xlabel(xlabel_str)\n plt.ylabel(ylabel_str)\n\n # TODO: Set font size if necessary\n\n # Remove white margins\n plt.tight_layout()\n\n plt.show(block=False)\n input(\"Enter to continue ...\")\n\ndef plot_seeds(data_list, labels, fig_id=0, max_len=None, ylim_range=None, shade_alpha=0.2, xlabel_str=\"Iteration\", ylabel_str=None, width=6, height=4, linewidth = 2):\n \"\"\"\n @param: data: list of numpy arrays with data\n @param: labels: how to call each numpy array of data\n \"\"\"\n\n # Preprocessing\n data_mean_list = []\n data_err_list = []\n data_len = []\n for di, data in enumerate(data_list):\n data_mean_list.append(np.mean(data, axis=0))\n data_err_list.append(np.std(data, axis=0))\n data_len.append(data_mean_list[-1].size)\n\n # Getting default colors\n # prop_cycle = plt.rcParams['axes.prop_cycle']\n # colors = prop_cycle.by_key()['color']\n\n # Plotting (shades come first to avoid overlap with mean curves)\n for di, data in enumerate(data_list):\n plt.figure(fig_id + di, figsize=(width, height))\n error = data_err_list[di]\n mean = data_mean_list[di]\n x = np.arange(mean.shape[0])\n plt.fill_between(x, mean-error, mean+error,\n alpha=shade_alpha, facecolor=\"blue\", antialiased=True)\n \n # Plotting Mean curves\n for di, data in enumerate(data_mean_list):\n plt.figure(fig_id + di, figsize=(width, height))\n x = np.arange(mean.shape[0])\n plt.plot(data, linewidth=linewidth, color=\"blue\", antialiased=True)\n for ds in range(data_list[di].shape[0]):\n plt.plot(data_list[di][ds, :], linewidth=1, antialiased=True)\n\n # Setting properties\n plt.title(labels[di])\n max_len = data.shape[0]\n plt.xlim([0, max_len])\n if ylim_range is not None:\n plt.ylim(ylim_range)\n plt.xlabel(xlabel_str)\n plt.ylabel(ylabel_str)\n\n # TODO: Set font size if necessary\n\n # Remove white margins\n plt.tight_layout()\n\n plt.show(block=False)\n input(\"Enter to continue ...\")\n\n\n\ndef read_graph_seeds(folders, graph_names, filter_width=1):\n \"\"\"\n Reads data in numpy arrays with the first dimension being a seed.\n Assumes that every specified folder contains \"seed_X\" folders over which it averages the graphs.\n @param: graph_names: one graph name for each folder (covers scenarios when different approaches may document same graph under different names)\n @param: filter_width: FIR filter width for data smoothing\n \"\"\"\n\n ###################################\n ## PARAMETERS\n progress_filename = \"progress.csv\"\n\n # Parameters of window filtering of graphs\n filt_a = 1.\n filt_b = np.ones(filter_width) * 1./filter_width\n\n graph_num = len(folders)\n\n data_all = []\n data_filtered_all = []\n\n for folder_j, folder in enumerate(folders):\n print('Searching folder %s ...' % folder)\n seed_folders = subdir(folder)\n seeds_num = len(seed_folders)\n data = []\n data_filtered = []\n data_lengths = []\n # Indices of corresponding graphs in csv files\n indices = []\n\n for seed_i in range(seeds_num):\n file_cur = os.path.join(seed_folders[seed_i], progress_filename)\n print('File %d = %s ' % (seed_i, file_cur))\n \n # Reading the csv file\n csv_data = pd.read_csv(file_cur, sep=',')\n header = list(csv_data.dtypes.index)\n data.append(csv_data.values)\n # alternative: csv_data[graph_names[folder_j]]\n\n # Finding the column corresponding to our data\n indices.append(header.index(graph_names[folder_j]))\n print('Field index = %d ' % indices[-1])\n \n # Filtering the data (for example if reward is too jerky)\n data_filtered.append(lfilter(filt_b, filt_a, data[-1][:, indices[-1]]))\n data_lengths.append(data_filtered[-1].size)\n print('Data length %d ' % data_lengths[-1])\n \n # Finding minimal data lenght\n mindata_len = np.min(data_lengths)\n maxdata_len = np.max(data_lengths)\n print('Min data length %d' % mindata_len)\n\n # Giving warning in case some of the seeds are longer than the minimal\n if mindata_len != maxdata_len: print(\"!!! WARN: Min (%d) != Max(%d) len: \" % (mindata_len, maxdata_len))\n\n # Trimming all seeds data to this length\n data_filtered = [data_i[:mindata_len] for data_i in data_filtered]\n\n # Converting to numpy array\n print('Converting to np.array with the frist dimension being a seed ...')\n data_filtered = np.array(data_filtered)\n data = np.array(data)\n \n # Storing\n data_all.append(data)\n data_filtered_all.append(data_filtered) \n\n return data_all, data_filtered_all\n\n\ndef read_and_plot_seeds(folders, graph_names, labels, filter_width=1, show_seeds=False, **kwargs):\n # Reading\n data, data_filtered = read_graph_seeds(folders=folders, graph_names=graph_names, filter_width=filter_width)\n # import pdb; pdb.set_trace()\n # Plotting\n if show_seeds:\n # Plotting individual seeds\n plot_seeds(data_list=data_filtered, labels=labels, **kwargs)\n else:\n # Plotting average + std among seeds\n plot_seeds_stats(data_list=data_filtered, labels=labels, **kwargs)\n return data, data_filtered\n\n\n################################################################################\n## Plotting a single\nimport argparse\nfrom argparse import RawTextHelpFormatter, ArgumentDefaultsHelpFormatter\nimport sys, os\n\nimport time\nimport datetime\nfrom dateutil.relativedelta import relativedelta\n\ndef runtime_str(t_diff):\n days = int(t_diff / (3600 * 24))\n hours = int((t_diff % (3600 * 24)) / 3600)\n minutes = int( (t_diff % 3600) / 60 )\n seconds = int(t_diff % 60)\n return '{d}d {h}h {m}m {s}s'.format(d=days, h=hours, m=minutes, s=seconds)\n\ndef main(argv):\n #Parsing command line arguments\n parser = argparse.ArgumentParser(\n description=\"Argument description: \",\n formatter_class=ArgumentDefaultsHelpFormatter)\n # formatter_class=RawTextHelpFormatter)\n parser.add_argument(\n \"dir\",\n help=\"Input directory\"\n )\n parser.add_argument(\n \"-g\",\"--graph\",\n default=\"rew_main_avg\",\n help=\"Name of data column in a csv file\"\n )\n parser.add_argument(\n \"-s\",\"--seeds\",\n action=\"store_true\",\n help=\"Show individual seeds\"\n )\n parser.add_argument(\n \"-sns\",\"--seaborn\",\n action=\"store_true\",\n help=\"Use seaborn for visualiztion\"\n )\n args = parser.parse_args()\n\n ###################################\n ### Main code\n print('Arguments: ')\n [print(arg, ': ',val) for arg,val in args.__dict__.items()]\n\n ## Printing runtime\n time_start = time.time()\n\n if args.seaborn:\n try:\n import seaborn as sns\n sns.set()\n except:\n print(\"WARN: No seaborn found. Continuing with classic theme ...\")\n\n # Reading and ploting\n read_and_plot_seeds(folders=[args.dir], graph_names=[args.graph], labels=[\"\"], ylabel_str=args.graph, show_seeds=args.seeds)\n\n \n time_end = time.time()\n print(\"RUNTIME: \", runtime_str(time_end-time_start))\n\nif __name__ == '__main__':\n main(sys.argv)"
},
{
"alpha_fraction": 0.6089522838592529,
"alphanum_fraction": 0.6151008605957031,
"avg_line_length": 34.06034469604492,
"blob_id": "9f77e26fab20136b9c329973fb6f70f5097b0557",
"content_id": "6e39377abafdd5e011bfaf3c0435702ae4a641a2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4066,
"license_type": "no_license",
"max_line_length": 123,
"num_lines": 116,
"path": "/quad_train/misc/tensor_utils.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport numpy as np\nimport inspect\n\nimport h5py\n# import os,sys\n\nimport garage_metadist.misc.dict2hdf5 as h5u\n\ndef stack_tensor_list(tensor_list):\n if tensor_list is None or len(tensor_list) == 0:\n # print('WARINING: Sampler: Empty tensor list provided')\n return tensor_list\n # In case we have tuple observations - we will have a list of tuples\n # Thus we have to re-pack it to tuple of lists and then stack them to np array\n if isinstance(tensor_list[0], tuple):\n lists = list(zip(*tensor_list))\n arrays = []\n for lst in lists:\n arrays.append(np.stack(lst))\n # print('!stack_tensor_list: array shape ', arrays[-1].shape)\n return tuple(arrays)\n else:\n stacked_array = np.array(tensor_list)\n # print('!!stack_tensor_list: array shape ', np.array(tensor_list).shape, ' Tensor shape = ', tensor_list[0].shape)\n return np.stack(tensor_list)\n\ndef truncate_tensor_list(tensor_list, truncated_len):\n # In case we have tuple observations - we will have a list of tuples\n if isinstance(tensor_list[0], tuple):\n tensor_list = list(tensor_list)\n for lst_i in range(len(tensor_list)):\n tensor_list[lst_i] = tensor_list[lst_i][:truncated_len]\n return tuple(tensor_list)\n else:\n return tensor_list[:truncated_len]\n\n\ndef concat_tensor_list(tensor_list):\n if isinstance(tensor_list[0], tuple):\n obs_lists = list(zip(*tensor_list))\n # print('concat_tensor_list: obs = ', [len(obs) for obs in obs_lists])\n return tuple([np.concatenate(obs, axis=0) for obs in obs_lists])\n else:\n return np.concatenate(tensor_list, axis=0)\n\n\ndef dict_make_list_leafs(dic_in, orig_dic):\n for key in orig_dic:\n if not isinstance(orig_dic[key], dict):\n dic_in[key] = []\n else:\n dic_in[key] = {}\n dict_make_list_leafs(dic_in[key], orig_dic[key])\n\ndef append2leafs(dic_append, orig_dic):\n for key in orig_dic:\n if not isinstance(orig_dic[key], dict):\n dic_append[key].append(orig_dic[key])\n else:\n append2leafs(dic_append[key], orig_dic[key]) \n\ndef stack_leafs(dic_stack):\n for key in dic_stack:\n if not isinstance(dic_stack[key], dict):\n dic_stack[key] = stack_tensor_list(dic_stack[key])\n else:\n stack_leafs(dic_stack[key]) \n\ndef dic_print_shapes(dic, indent=\"\"):\n for key in dic:\n if not isinstance(dic[key], dict):\n if isinstance(dic[key], np.ndarray):\n print(indent, key, \":\", dic[key].shape)\n else:\n print(indent, key, \":\", type(dic[key]))\n else:\n dic_print_shapes(dic[key], indent + \" \") \n\n## Let's assign nested list to each dict el\ndef repack2arrays(list_of_dic, path=\"/\"):\n \"\"\"\n Assuming that you have a dictionary of lists with the structure \n (that is used for keeping trajectories)\n [runs_num][iter_num][traj_per_iter]{dict_of_data}\n Repack it into:\n {dict_of_data} x np.array([runs_num x iter_num x traj_per_iter x data_dim])\n Assumes uniform sizes and structure (including dictionary names) through all lists\n \"\"\"\n\n if not isinstance(list_of_dic[0], dict):\n new_list_of_dic = []\n for eli, el in enumerate(list_of_dic):\n new_list_of_dic.append(repack2arrays(el, path=path + str(eli) + \"/\"))\n list_of_dic = new_list_of_dic\n \n # Replicating dict structure to a dict of lists\n dic_of_lists = {}\n dict_make_list_leafs(dic_of_lists, list_of_dic[0])\n\n # Crawling each of dicts and copying data to the dict of lists\n for el in list_of_dic:\n append2leafs(dic_of_lists, el)\n\n # Crawling dictionary to stack arrays\n stack_leafs(dic_of_lists)\n\n return dic_of_lists\n\ndef test():\n data = h5u.dict2h5.load(\"_results_temp/ppo_precred/joined.h5\", pack2list=True)\n dic_of_np = repack2arrays(data[\"traj_data\"])\n dic_print_shapes(dic_of_np)\n\nif __name__ == \"__main__\":\n test()"
},
{
"alpha_fraction": 0.7647058963775635,
"alphanum_fraction": 0.7647058963775635,
"avg_line_length": 16,
"blob_id": "fea0a9354843aaa85e69f4a4f89abd4f3e6a4ccd",
"content_id": "b45f29c1234dd8186389eff8d48c3a49723b8b9d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 34,
"license_type": "no_license",
"max_line_length": 21,
"num_lines": 2,
"path": "/install_depend_macos.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nbrew install parallel\n"
},
{
"alpha_fraction": 0.45228826999664307,
"alphanum_fraction": 0.5123473405838013,
"avg_line_length": 33.57540512084961,
"blob_id": "e52d1bf9b026ac610207a5ec4a9d0ea93619be58",
"content_id": "23dbc8748827044090865bfb38744b0ab7c2e8c4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14902,
"license_type": "no_license",
"max_line_length": 165,
"num_lines": 431,
"path": "/quad_sim/inertia.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\n\"\"\"\nComputing inertias of bodies.\nCoordinate frame:\nx - forward; y - left; z - up\nThe same coord frame is used for quads\nAll default inertias of objects are with respect to COM\nSource of inertias: https://en.wikipedia.org/wiki/List_of_moments_of_inertia\nWARNIGN: The h,w,l of the BoxLink are defined DIFFERENTLY compare to Wiki\n\"\"\"\n\nimport numpy as np\nimport copy\n\ndef rotate_I(I, R):\n \"\"\"\n Rotating inertia tensor I\n R - rotation matrix\n \"\"\"\n return R @ I @ R.T\n\ndef translate_I(I, m, xyz):\n \"\"\"\n Offsetting inertia tensor I by [x,y,z].T\n relative to COM\n \"\"\"\n x,y,z = xyz[0], xyz[1], xyz[2]\n I_new = np.zeros([3,3])\n I_new[0][0] = I[0][0] + m * (y**2 + z**2)\n I_new[1][1] = I[1][1] + m * (x**2 + z**2)\n I_new[2][2] = I[2][2] + m * (x**2 + y**2)\n I_new[0][1] = I_new[1][0] = I[0][1] + m * x * y\n I_new[0][2] = I_new[2][0] = I[0][1] + m * x * z\n I_new[1][2] = I_new[2][1] = I[1][2] + m * y * z\n return I_new\n\ndef deg2rad(deg):\n return deg / 180. * np.pi\n\nclass SphereLink():\n \"\"\"\n Box object\n \"\"\"\n type = \"sphere\"\n def __init__(self, r, m=None, density=None, name=\"sphere\"):\n \"\"\"\n m = mass\n dx = dy = dz = diameter = 2 * r\n \"\"\"\n self.name = name\n self.r = r\n if m is None:\n self.m = self.compute_m(density)\n else:\n self.m = m\n @property\n def I_com(self):\n r = self.r\n return np.array([\n [2/5. * self.m * r **2, 0., 0.],\n [0., 2/5. * self.m * r **2, 0.],\n [0., 0., 2/5. * self.m * r **2],\n ])\n\n def compute_m(self, density):\n return density * 4./3. * np.pi * self.r ** 3\n\n\nclass BoxLink():\n \"\"\"\n Box object\n \"\"\"\n type = \"box\"\n def __init__(self, l, w, h, m=None, density=None, name=\"box\"):\n \"\"\"\n m = mass\n dx = length = l\n dy = width = l\n dz = height = h\n \"\"\"\n self.name = name\n self.l, self.w, self.h = l, w, h\n if m is None:\n self.m = self.compute_m(density)\n else:\n self.m = m\n @property\n def I_com(self):\n l ,w, h = self.l, self.w, self.h\n return np.array([\n [1/12. * self.m * (h**2 + w**2), 0., 0.],\n [0., 1/12. * self.m * (l**2 + h**2), 0.],\n [0., 0., 1/12. * self.m * (w**2 + l**2)],\n ])\n \n def compute_m(self, density):\n return density * self.l * self.w * self.h\n\nclass RodLink():\n \"\"\"\n Rod == Horizontal Cylinder\n \"\"\"\n type = \"rod\"\n def __init__(self, l, r=0.002, m=None, density=None, name=\"rod\"):\n \"\"\"\n m = mass\n dx = length\n dy = dz = diameter == height\n \"\"\"\n self.name = name\n self.l = l\n self.r = r\n if m is None:\n self.m = self.compute_m(density)\n else:\n self.m = m\n @property\n def I_com(self):\n return np.array([\n [1/12. * self.m * self.l**2, 0., 0.],\n [0., 0., 0.],\n [0., 0., 1/12. * self.m * self.l**2],\n ])\n\n def compute_m(self, density):\n return density * np.pi * self.l * self.r ** 2\n\nclass CylinderLink():\n \"\"\"\n Vertical Cylinder\n \"\"\"\n type = \"cylinder\"\n def __init__(self, h, r, m=None, density=None, name=\"cylinder\"):\n \"\"\"\n m = mass\n dz = height = h\n dy = dx = 2*radius = 2*r = diameter\n \"\"\"\n self.name = name\n self.h, self.r = h, r\n if m is None:\n self.m = self.compute_m(density)\n else:\n self.m = m\n \n @property\n def I_com(self):\n h, r = self.h, self.r\n return np.array([\n [1/12. * self.m * (3*r**2 + h**2), 0., 0.],\n [0., 1/12. * self.m * (3*r**2 + h**2), 0.],\n [0., 0., 0.5 * self.m * r**2],\n ])\n def compute_m(self, density):\n return density * np.pi * self.h * self.r ** 2\n\nclass LinkPose(object):\n def __init__(self, R=None, xyz=None, alpha=None):\n \"\"\"\n One can provide either:\n R - rotation matrix or \n alpha - angle of roation in a xy (horizontal) plane [degrees]\n xyz - offset\n \"\"\"\n if xyz is not None:\n self.xyz = np.array(xyz)\n else:\n self.xyz = np.zeros(3)\n if R is not None:\n self.R = R\n elif alpha:\n self.R = np.array([\n [np.cos(alpha), -np.sin(alpha), 0.],\n [np.sin(alpha), np.cos(alpha), 0.],\n [0., 0., 1.]\n ])\n else:\n self.R = np.eye(3)\n\n\nclass QuadLink(object):\n \"\"\"\n Quadrotor link set to compute inertia.\n Initial coordinate system assumes being in the middle of the central body.\n Orientation of axes: x - forward; y - left; z - up\n arm_angle == |/ , i.e. between the x axis and the axis of the arm\n Quadrotor assumes X configuration.\n \"\"\"\n def __init__(self, params=None, verbose=False):\n # PARAMETERS (CrazyFlie by default)\n self.motors_num = 4\n self.params = {}\n self.params[\"body\"] = {\"l\": 0.03, \"w\": 0.03, \"h\": 0.004, \"m\": 0.005}\n self.params[\"payload\"] = {\"l\": 0.035, \"w\": 0.02, \"h\": 0.008, \"m\": 0.01}\n self.params[\"arms\"] = {\"w\":0.005, \"h\":0.005, \"m\":0.001}\n self.params[\"motors\"] = {\"h\":0.02, \"r\":0.0035, \"m\":0.0015}\n self.params[\"propellers\"] = {\"h\":0.002, \"r\":0.022, \"m\":0.00075}\n\n self.params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n\n self.params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": 1.}\n self.params[\"motor_pos\"] = {\"xyz\": [0.065/2, 0.065/2, 0.]}\n if params is not None:\n self.params.update(params)\n else:\n print(\"WARN: since params is None the CrazyFlie params will be used\")\n\n # Printing all params\n if verbose:\n print(\"######################################################\")\n print(\"QUAD PARAMETERS:\")\n [print(key,\":\", val) for key,val in self.params.items()]\n print(\"######################################################\")\n \n # Dependent parameters\n self.arm_angle = deg2rad(self.params[\"arms_pos\"][\"angle\"])\n if self.arm_angle == 0.:\n self.arm_angle = 0.01\n self.motor_xyz = np.array(self.params[\"motor_pos\"][\"xyz\"])\n delta_y = self.motor_xyz[1] - self.params[\"body\"][\"w\"] / 2.\n if \"l\" not in self.params[\"arms\"]:\n self.arm_length = delta_y / np.sin(self.arm_angle)\n self.params[\"arms\"][\"l\"] = self.arm_length\n else:\n self.arm_length = self.params[\"arms\"][\"l\"]\n # print(\"Arm length: \", self.arm_length, \"angle: \", self.arm_angle)\n\n # Vectors of coordinates of the COMs of arms, s.t. their ends will be exactly at motors locations\n self.arm_xyz = np.array([ self.motor_xyz[0] - delta_y /(2 * np.tan(self.arm_angle)),\n self.motor_xyz[1] - delta_y / 2,\n self.params[\"arms_pos\"][\"z\"] ])\n \n\n # X signs according to clockwise starting front-left\n # i.e. the list bodies are counting clockwise: front_right, back_right, back_left, front_left\n # See CrazyFlie doc for more details: https://wiki.bitcraze.io/projects:crazyflie2:userguide:assembly\n self.x_sign = np.array([1, -1, -1, 1])\n self.y_sign = np.array([-1, -1, 1, 1])\n self.sign_mx = np.array([self.x_sign, self.y_sign, np.array([1., 1., 1., 1.])])\n self.motors_coord = self.sign_mx * self.motor_xyz[:, None]\n self.props_coord = copy.deepcopy(self.motors_coord)\n self.props_coord[2,:] = (self.props_coord[2,:] + self.params[\"motors\"][\"h\"] / 2. + self.params[\"propellers\"][\"h\"])\n self.arm_angles = [\n -self.arm_angle, \n self.arm_angle, \n -self.arm_angle, \n self.arm_angle]\n self.arms_coord = self.sign_mx * self.arm_xyz[:, None]\n\n # First defining the bodies\n self.body = BoxLink(**self.params[\"body\"], name=\"body\") # Central body \n self.payload = BoxLink(**self.params[\"payload\"], name=\"payload\") # Could include battery\n self.arms = [BoxLink(**self.params[\"arms\"], name=\"arm_%d\" % i) for i in range(self.motors_num)] # Just arms\n self.motors = [CylinderLink(**self.params[\"motors\"], name=\"motor_%d\" % i) for i in range(self.motors_num)] # The motors itself\n self.props = [CylinderLink(**self.params[\"propellers\"], name=\"prop_%d\" % i) for i in range(self.motors_num)] # Propellers\n \n self.links = [self.body, self.payload] + self.arms + self.motors + self.props\n\n # print(\"######################################################\")\n # print(\"Inertias:\")\n # [print(link.I_com, \"\\n\") for link in self.links]\n # print(\"######################################################\")\n\n # Defining locations of all bodies\n self.body_pose = LinkPose()\n self.payload_pose = LinkPose(xyz=list(self.params[\"payload_pos\"][\"xy\"]) + [np.sign(self.params[\"payload_pos\"][\"z_sign\"])*(self.body.h + self.payload.h) / 2])\n self.arms_pose = [LinkPose(alpha=self.arm_angles[i], xyz=self.arms_coord[:, i]) \n for i in range(self.motors_num)]\n self.motors_pos = [LinkPose(xyz=self.motors_coord[:, i]) \n for i in range(self.motors_num)]\n self.props_pos = [LinkPose(xyz=self.props_coord[:, i]) \n for i in range(self.motors_num)]\n \n self.poses = [self.body_pose, self.payload_pose] + self.arms_pose + self.motors_pos + self.props_pos\n\n # Recomputing the center of mass of the new system of bodies\n masses = [link.m for link in self.links]\n self.com = sum([ masses[i] * pose.xyz for i, pose in enumerate(self.poses)]) / self.m\n\n # Recomputing corrections on posess with the respect to the new system\n self.poses_init = copy.deepcopy(self.poses)\n for pose in self.poses:\n pose.xyz -= self.com\n \n if verbose:\n print(\"Initial poses: \")\n [print(pose.xyz) for pose in self.poses_init]\n print(\"###################################\")\n print(\"Final poses: \")\n [print(pose.xyz) for pose in self.poses]\n print(\"###################################\")\n\n # Computing inertias\n self.links_I = []\n for link_i, link in enumerate(self.links):\n I_rot = rotate_I(I=link.I_com, R=self.poses[link_i].R)\n I_trans = translate_I(I=I_rot, m=link.m, xyz=self.poses[link_i].xyz)\n self.links_I.append(I_trans)\n \n # Total inertia\n self.I_com = sum(self.links_I)\n\n # Propeller poses\n self.prop_pos = np.array([pose.xyz for pose in self.motors_pos])\n \n @property\n def m(self):\n return np.sum([link.m for link in self.links]) \n\n\nif __name__ == \"__main__\":\n import time\n start_time = time.time()\n import argparse\n import yaml\n from gym_art.quadrotor.quad_models import *\n\n parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\n '-c',\"--config\",\n help=\"Config file to test\"\n )\n args = parser.parse_args()\n\n def report(quad):\n print(\"Time:\", time.time()-start_time)\n print(\"Quad inertia: \\n\", quad.I_com)\n print(\"Quad mass:\", quad.m)\n print(\"Quad arm_xyz:\", quad.arm_xyz)\n print(\"Quad COM: \", quad.com)\n print(\"Quad arm_length: \", quad.arm_length)\n print(\"Quad prop_pos: \\n\", quad.prop_pos, \"shape:\", quad.prop_pos.shape)\n\n ## CrazyFlie parameters\n # params = {}\n # params[\"body\"] = {\"l\": 0.03, \"w\": 0.03, \"h\": 0.004, \"m\": 0.005}\n # params[\"payload\"] = {\"l\": 0.035, \"w\": 0.02, \"h\": 0.008, \"m\": 0.01}\n # params[\"arms\"] = {\"l\": 0.022, \"w\":0.005, \"h\":0.005, \"m\":0.001}\n # params[\"motors\"] = {\"h\":0.02, \"r\":0.0035, \"m\":0.0015}\n # params[\"propellers\"] = {\"h\":0.002, \"r\":0.022, \"m\":0.00075}\n \n # params[\"motor_pos\"] = {\"xyz\": [0.065/2, 0.065/2, 0.]}\n # params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n # params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": 1}\n # z_sing corresponds to location (+1 - on top of the body, -1 - on the bottom of the body)\n\n quad_crazyflie = QuadLink(params=crazyflie_params()[\"geom\"], verbose=True)\n print(\"Crazyflie: \")\n report(quad_crazyflie)\n\n ## Aztec params\n geom_params = {}\n geom_params[\"body\"] = {\"l\": 0.1, \"w\": 0.1, \"h\": 0.085, \"m\": 0.5}\n geom_params[\"payload\"] = {\"l\": 0.12, \"w\": 0.12, \"h\": 0.04, \"m\": 0.1}\n geom_params[\"arms\"] = {\"l\": 0.1, \"w\":0.015, \"h\":0.015, \"m\":0.025} #0.17 total arm\n geom_params[\"motors\"] = {\"h\":0.02, \"r\":0.025, \"m\":0.02}\n geom_params[\"propellers\"] = {\"h\":0.01, \"r\":0.1, \"m\":0.009}\n \n geom_params[\"motor_pos\"] = {\"xyz\": [0.12, 0.12, 0.]}\n geom_params[\"arms_pos\"] = {\"angle\": 45., \"z\": 0.}\n geom_params[\"payload_pos\"] = {\"xy\": [0., 0.], \"z_sign\": -1}\n\n quad = QuadLink(params=geom_params, verbose=True)\n print(\"Aztec: \")\n report(quad)\n\n ## Crazyflie with lowered inertia\n quad = QuadLink(params=crazyflie_lowinertia_params()[\"geom\"], verbose=True)\n print(\"Crazyflie lowered inertia: \")\n print(\"factor: \", quad_crazyflie.I_com / quad.I_com)\n report(quad)\n\n\n ## Random params\n if args.config is not None:\n yaml_stream = open(args.config, 'r')\n params_load = yaml.load(yaml_stream)\n\n quad_load = QuadLink(params=params_load, verbose=True)\n print(\"Loaded quad: %s\" % args.config)\n report(quad_load)\n\n\n\n################################################\n## BUGS\n\n# geom:\n# body:\n# l: 0.03606089911004016\n# w: 0.0335657274378426\n# h: 0.006102479549661156\n# m: 0.0062767052677894074\n# payload:\n# l: 0.03838432440273057\n# w: 0.023816859339232426\n# h: 0.0070768000745466235\n# m: 0.011730161186989083\n# arms:\n# l: 0.03186274210023081\n# w: 0.004925117851085423\n# h: 0.003791035497312349\n# m: 0.0006186316884703438\n# motors:\n# h: 0.014114172356543832\n# r: 0.004954090517124884\n# m: 0.00019911121838799071\n# propellers:\n# h: 0.0003473493979756195\n# r: 0.018981731819806787\n# m: 0.0010610363239981538\n# motor_pos:\n# xyz: [0.0371103 0.0300385 0. ]\n# arms_pos:\n# angle: 0.0\n# z: 0.0\n# payload_pos:\n# xy: [0. 0.]\n# z_sign: 0.9631780811491029\n# damp:\n# vel: 0.0013677304461958925\n# omega_quadratic: 0.013233401772593535\n# noise:\n# thrust_noise_ratio: 0.00970067152725083\n# motor:\n# thrust_to_weight: 2.928398587847958\n# torque_to_thrust: 0.07219217705972501\n\n# self.dynamics.inertia\n# array([7.80390772e-06, nan, nan])\n"
},
{
"alpha_fraction": 0.7146464586257935,
"alphanum_fraction": 0.7247474789619446,
"avg_line_length": 19.894737243652344,
"blob_id": "dfb855ba5913d36e94ebcbf9cdd68c470704c019",
"content_id": "73842e5ae5e7576f498124aa21b9add5968b73a3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 396,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 19,
"path": "/quad_train/config/config_loader.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import argparse\nimport sys\nimport os\nimport datetime, time\nimport itertools\nimport os.path as osp\nimport uuid\nimport copy\n\nimport numpy as np\n\nimport dateutil.tz\nimport yaml\n\ndef trpo_ppo_default_params():\n path2conf = os.path.realpath(__file__).rsplit(os.sep, 1)[0]\n yaml_stream = open(path2conf + os.sep + \"trpo_ppo_default.yml\", 'r')\n params = yaml.load(yaml_stream)\n return params"
},
{
"alpha_fraction": 0.46192052960395813,
"alphanum_fraction": 0.4764072895050049,
"avg_line_length": 31.321069717407227,
"blob_id": "96b0839f9d8fb0bebfe911b99e5ea0e52b585519",
"content_id": "f720339991a5e8c51aabe6846a70993490f8319d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9664,
"license_type": "no_license",
"max_line_length": 131,
"num_lines": 299,
"path": "/quad_gen/test_controller.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "from gym_art.quadrotor.quad_utils import R2quat\nfrom gym_art.quadrotor.quad_models import *\nfrom gym_art.quadrotor.quadrotor_randomization import *\nfrom simulators_investigation.utils import *\nimport sys\nimport argparse\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport joblib\nimport os\nimport time\n\ndef test_rollout(\n param_file, \n traj_file=None, \n render=False, \n rollouts_num=1,\n dt=0.005,\n sim_steps=2,\n ep_time=7.0,\n render_each=2,\n use_noise=False, # if it's true, use what the env already has\n random_init=False, # if it's true, use what the env already has\n random_quad=False, # if it's true, use what the env already has\n excite=False, # whether to perturb the quad\n save=False, \n plot=False\n ):\n import tqdm\n\n if traj_file != None:\n print(\"Reading trajectory...\")\n traj = np.loadtxt(traj_file, delimiter=',')\n traj_freq = 1 ## every 1 time step(s), the goal is set to the next point in the traj\n\n import tensorflow as tf\n with tf.Session() as sess:\n print(\"extrating parameters from file %s ...\" % param_file)\n params = joblib.load(param_file)\n\n env = params['env'].env\n policy = params['policy']\n \n ## modify the environment\n if not use_noise:\n ## do not use noise\n env.update_sense_noise(sense_noise=None)\n if not random_init:\n ## set init random state to False\n env.init_random_state = False\n init_pos = np.array([0, 0, 0.05])\n init_vel = np.array([0, 0, 0])\n init_rot = rpy2R(0, 0, 0) # np.eye(3) \n init_omega = np.array([0, 0, 0])\n if not random_quad:\n ## no random quad\n env.dynamics_randomize_every = None\n ## set up a quad\n env.update_dynamics(dynamics_params=crazyflie_params())\n\n print(env.dynamics_params)\n\n env.dt = dt\n env.sim_steps = sim_steps\n env.ep_len = int(ep_time / (dt * sim_steps))\n ## output import info about the environment\n print('#############################')\n print('Episode time: {}'.format(ep_time))\n print('Integration step: {}'.format(dt))\n print('Simulation step: {}'.format(sim_steps))\n print('#############################')\n ## ========================================\n \n ## Diagnostics\n observations = []\n for rollouts_id in tqdm.tqdm(range(rollouts_num)):\n s = env.reset()\n policy.reset()\n \n ## reset the goal to x:0, y:0 z:0\n env.goal = np.array([0., 0., 1])\n \n dynamics = env.dynamics\n print(\"thrust to weight ratio set to: {}, and max thrust is {}\".format(dynamics.thrust_to_weight, dynamics.thrust_max))\n\n ## set the initial state\n if not random_init:\n dynamics.set_state(init_pos, init_vel, init_rot, init_omega)\n dynamics.reset()\n env.scene.reset(env.goal, dynamics)\n s = env.state_vector(env)\n \n\n t = 0\n traj_ptr = 0\n done = False\n while True:\n # =================================\n if render and (t % render_each == 0): env.render()\n\n if traj_file != None:\n if traj_ptr < traj.shape[0]:\n if t % traj_freq == 0:\n env.goal = traj[traj_ptr][:3]\n traj_ptr += 5 ## need to adjust this parameter according to the trajectory file frequency\n action = policy.get_action(s)[1]['mean']\n s, r, _, info = env.step(action)\n else:\n done = True\n elif excite and t % 1000 == 0:\n ## change the goal every 100 time step\n env.goal = np.concatenate([\n np.random.uniform(low=-1, high=1, size=(2,)),\n np.random.uniform(low=1, high=1, size=(1,))\n ])\n action = policy.get_action(s)[1]['mean']\n s, r, done, info = env.step(action)\n else:\n action = policy.get_action(s)[1]['mean']\n s, r, done, info = env.step(action)\n\n if done: break\n t += 1\n \n # ========== Diagnostics ==========\n real_pos = env.state_vector(env)\n pos = real_pos[0:3] + env.goal\n vel = real_pos[3:6]\n quat = R2quat(real_pos[6:15])\n # reformat to [x, y, z, w]\n quat[0], quat[1], quat[2], quat[3] = quat[1], quat[2], quat[3], quat[0]\n rpy = R2rpy(real_pos[6:15])\n omega = real_pos[15:18]\n \n # real_pos = np.concatenate([[t * dt * sim_steps], pos, quat, vel, omega, action])\n # real_pos = np.concatenate([[t * dt * sim_steps], \n # pos, quat, info['obs_comp']['Vxyz'][0], omega, info['obs_comp']['Act'][0], [r]])\n real_pos = np.concatenate([[t * dt * sim_steps], \n pos, rpy, vel, omega, env.goal, action])\n observations.append(real_pos)\n \n\n if save == True:\n save_path = './test_tmp/'\n try:\n os.makedirs(save_path, exist_ok=True)\n except FileExistsError:\n # directory already exists\n pass\n np.savetxt(save_path + 'observations.csv', observations, delimiter=',')\n\n if plot == True:\n TIME = 0\n X, Y, Z = 1, 2, 3 \n Roll, Pitch, Yaw = 4, 5, 6 \n VX, VY, VZ = 7, 8, 9\n Roll_rate, Pitch_rate, Yaw_rate = 10, 11, 12\n Xt, Yt, Zt = 13, 14, 15\n t0, t1, t2, t3 = 16, 17, 18, 19\n \n observations = np.array(observations)\n\n plot_comp = {\n 'Omega': {'roll rate': Roll_rate, 'pitch rate': Pitch_rate, 'yaw rate': Yaw_rate},\n 'Position': {'X': X, 'Target X': Xt, 'Y': Y, 'Target Y': Yt, 'Z': Z, 'Target Z': Zt},\n 'Velocity': {'VX': VX, 'VY': VY, 'VZ': VZ}, \n # 'Orientation': {'qx': QX, 'qy': QY, 'qz': QZ, 'qw': QW}, \n 'Orientation': {'R': Roll, 'P': Pitch, 'Y': Yaw}, \n 'Actions': {'t0': t0, 't1': t1, 't2': t2, 't3': t3},\n 'Reward' : {'reward': reward}\n }\n\n total_subplots = len(plot_comp)\n current_plot = 1\n for obs_comp in plot_comp:\n plt.subplot(total_subplots, 1, current_plot)\n for comp in plot_comp[obs_comp]:\n plt.plot(observations[:,plot_comp[obs_comp][comp]], '-', label=comp)\n plt.xlabel('Time [s]')\n plt.ylabel(obs_comp) \n plt.legend(loc=9, ncol=3, borderaxespad=0.)\n \n current_plot += 1\n\n plt.show()\n \n\n print(\"##############################################################\")\n\n\ndef main(argv):\n # parser = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter)\n parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n\n parser.add_argument(\n 'param_file',\n type=str,\n help=\"provide a param.pkl file\"\n )\n\n parser.add_argument(\n '-traj',\n type=str,\n default=None,\n help='a trajectory file' \n )\n\n parser.add_argument(\n '-rollouts_num',\n type=int,\n default=1,\n help='number of rollouts' \n )\n\n parser.add_argument(\n '-ep_time',\n type=int,\n default=7,\n help='episode time' \n )\n\n parser.add_argument(\n '-dt',\n type=float,\n default=0.005,\n help='time step size' \n )\n\n parser.add_argument(\n '-sim_steps',\n type=int,\n default=2,\n help='controller step' \n )\n\n parser.add_argument(\n '--render', \n action='store_true',\n help='whether to render'\n ) \n\n parser.add_argument(\n '--random_init', \n action='store_true',\n help='whether to randomly initialize the quad'\n ) \n\n parser.add_argument(\n '--random_quad', \n action='store_true',\n help='whether to use the env quad parameter'\n ) \n\n parser.add_argument(\n '--use_noise', \n action='store_true',\n help='whether to use noise'\n )\n\n parser.add_argument(\n '--excite', \n action='store_true',\n help='whether to perturb the quad'\n )\n\n parser.add_argument(\n '--plot', \n action='store_true',\n help='whether to plot'\n ) \n\n parser.add_argument(\n '--save', \n action='store_true',\n help='whether to record flight'\n ) \n\n args = parser.parse_args()\n\n print('Running test rollout...')\n test_rollout(\n args.param_file, \n traj_file=args.traj, \n render=args.render, \n rollouts_num=args.rollouts_num,\n dt=args.dt,\n sim_steps=args.sim_steps,\n ep_time=args.ep_time,\n use_noise=args.use_noise,\n random_init=args.random_init,\n random_quad=args.random_quad,\n excite=args.excite,\n save=args.save, \n plot=args.plot\n )\n\n\nif __name__ == '__main__':\n\tmain(sys.argv)\n"
},
{
"alpha_fraction": 0.5250617265701294,
"alphanum_fraction": 0.5571663975715637,
"avg_line_length": 41.295936584472656,
"blob_id": "88bc666f04900bd4983d672ce1b5541a7a039cfb",
"content_id": "13e83c1616f5ea1645c6c63537d4b5c13d9e4ccc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 21866,
"license_type": "no_license",
"max_line_length": 136,
"num_lines": 517,
"path": "/quad_sim/quadrotor_control.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom numpy.linalg import norm\nfrom copy import deepcopy\n\nimport gym\nfrom gym import spaces\nfrom quad_sim.quad_utils import *\n\nGRAV = 9.81\n\n# like raw motor control, but shifted such that a zero action\n# corresponds to the amount of thrust needed to hover.\nclass ShiftedMotorControl(object):\n def __init__(self, dynamics):\n pass\n\n def action_space(self, dynamics):\n # make it so the zero action corresponds to hovering\n low = -1.0 * np.ones(4)\n high = (dynamics.thrust_to_weight - 1.0) * np.ones(4)\n return spaces.Box(low, high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step(self, dynamics, action, dt):\n action = (action + 1.0) / dynamics.thrust_to_weight\n action[action < 0] = 0\n action[action > 1] = 1\n dynamics.step(action, dt)\n\nclass RawControl(object):\n def __init__(self, dynamics, zero_action_middle=True):\n self.zero_action_middle = zero_action_middle\n # print(\"RawControl: self.zero_action_middle\", self.zero_action_middle)\n self.action = None\n self.step_func = self.step\n\n def action_space(self, dynamics):\n if not self.zero_action_middle:\n # Range of actions 0 .. 1\n self.low = np.zeros(4)\n self.bias = 0\n self.scale = 1.0\n else:\n # Range of actions -1 .. 1\n self.low = -np.ones(4)\n self.bias = 1.0\n self.scale = 0.5\n self.high = np.ones(4)\n return spaces.Box(self.low, self.high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step(self, dynamics, action, goal, dt, observation=None):\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(action, dt)\n self.action = action.copy()\n\n def step_tf(self, dynamics, action, goal, dt, observation=None):\n # print('bias/scale: ', self.scale, self.bias)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(action, dt)\n self.action = action.copy()\n\nclass RawControl(object):\n def __init__(self, dynamics, zero_action_middle=True, dim_mode=\"3D\"):\n self.zero_action_middle = zero_action_middle\n # print(\"RawControl: self.zero_action_middle\", self.zero_action_middle)\n self.action = None\n self.step_func = self.step\n\n def action_space(self, dynamics):\n if not self.zero_action_middle:\n # Range of actions 0 .. 1\n self.low = np.zeros(4)\n self.bias = 0\n self.scale = 1.0\n else:\n # Range of actions -1 .. 1\n self.low = -np.ones(4)\n self.bias = 1.0\n self.scale = 0.5\n self.high = np.ones(4)\n return spaces.Box(self.low, self.high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step(self, dynamics, action, goal, dt, observation=None):\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(action, dt)\n self.action = action.copy()\n\n def step_tf(self, dynamics, action, goal, dt, observation=None):\n # print('bias/scale: ', self.scale, self.bias)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(action, dt)\n self.action = action.copy()\n\n\nclass VerticalControl(object):\n def __init__(self, dynamics, zero_action_middle=True, dim_mode=\"3D\"):\n self.zero_action_middle = zero_action_middle\n\n self.dim_mode = dim_mode\n if self.dim_mode == '1D':\n self.step = self.step1D\n elif self.dim_mode == '3D':\n self.step = self.step3D\n else:\n raise ValueError('QuadEnv: Unknown dimensionality mode %s' % self.dim_mode)\n self.step_func = self.step\n\n\n def action_space(self, dynamics):\n if not self.zero_action_middle:\n # Range of actions 0 .. 1\n self.low = np.zeros(1)\n self.bias = 0\n self.scale = 1.0\n else:\n # Range of actions -1 .. 1\n self.low = -np.ones(1)\n self.bias = 1.0\n self.scale = 0.5\n self.high = np.ones(1)\n return spaces.Box(self.low, self.high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step3D(self, dynamics, action, goal, dt, observation=None):\n # print('action: ', action)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(np.array([action[0]]*4), dt)\n\n # modifies the dynamics in place.\n def step1D(self, dynamics, action, goal, dt, observation=None):\n # print('action: ', action)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(np.array([action[0]]), dt)\n\nclass VertPlaneControl(object):\n def __init__(self, dynamics, zero_action_middle=True, dim_mode=\"3D\"):\n self.zero_action_middle = zero_action_middle\n\n self.dim_mode = dim_mode\n if self.dim_mode == '2D':\n self.step = self.step2D\n elif self.dim_mode == '3D':\n self.step = self.step3D\n else:\n raise ValueError('QuadEnv: Unknown dimensionality mode %s' % self.dim_mode)\n self.step_func = self.step\n\n def action_space(self, dynamics):\n if not self.zero_action_middle:\n # Range of actions 0 .. 1\n self.low = np.zeros(2)\n self.bias = 0\n self.scale = 1.0\n else:\n # Range of actions -1 .. 1\n self.low = -np.ones(2)\n self.bias = 1.0\n self.scale = 0.5\n self.high = np.ones(2)\n return spaces.Box(self.low, self.high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step3D(self, dynamics, action, goal, dt, observation=None):\n # print('action: ', action)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(np.array([action[0], action[0], action[1], action[1]]), dt)\n\n # modifies the dynamics in place.\n def step2D(self, dynamics, action, goal, dt, observation=None):\n # print('action: ', action)\n action = self.scale * (action + self.bias)\n action = np.clip(action, a_min=self.low, a_max=self.high)\n dynamics.step(np.array(action), dt)\n\n\n# jacobian of (acceleration magnitude, angular acceleration)\n# w.r.t (normalized motor thrusts) in range [0, 1]\ndef quadrotor_jacobian(dynamics):\n torque = dynamics.thrust_max * dynamics.prop_crossproducts.T\n torque[2,:] = dynamics.torque_max * dynamics.prop_ccw\n thrust = dynamics.thrust_max * np.ones((1,4))\n dw = (1.0 / dynamics.inertia)[:,None] * torque\n dv = thrust / dynamics.mass\n J = np.vstack([dv, dw])\n J_cond = np.linalg.cond(J)\n # assert J_cond < 100.0\n if J_cond > 50:\n print(\"WARN: Jacobian conditioning is high: \", J_cond)\n return J\n\n\n# P-only linear controller on angular velocity.\n# direct (ignoring motor lag) control of thrust magnitude.\nclass OmegaThrustControl(object):\n def __init__(self, dynamics):\n jacobian = quadrotor_jacobian(dynamics)\n self.Jinv = np.linalg.inv(jacobian)\n\n def action_space(self, dynamics):\n circle_per_sec = 2 * np.pi\n max_rp = 5 * circle_per_sec\n max_yaw = 1 * circle_per_sec\n min_g = -1.0\n max_g = dynamics.thrust_to_weight - 1.0\n low = np.array([min_g, -max_rp, -max_rp, -max_yaw])\n high = np.array([max_g, max_rp, max_rp, max_yaw])\n return spaces.Box(low, high, dtype=np.float32)\n\n # modifies the dynamics in place.\n def step(self, dynamics, action, dt):\n kp = 5.0 # could be more aggressive\n omega_err = dynamics.omega - action[1:]\n dw_des = -kp * omega_err\n acc_des = GRAV * (action[0] + 1.0)\n des = np.append(acc_des, dw_des)\n thrusts = np.matmul(self.Jinv, des)\n thrusts[thrusts < 0] = 0\n thrusts[thrusts > 1] = 1\n dynamics.step(thrusts, dt)\n\n\n# TODO: this has not been tested well yet.\nclass VelocityYawControl(object):\n def __init__(self, dynamics):\n jacobian = quadrotor_jacobian(dynamics)\n self.Jinv = np.linalg.inv(jacobian)\n\n def action_space(self, dynamics):\n vmax = 20.0 # meters / sec\n dymax = 4 * np.pi # radians / sec\n high = np.array([vmax, vmax, vmax, dymax])\n return spaces.Box(-high, high, dtype=np.float32)\n\n def step(self, dynamics, action, dt):\n # needs to be much bigger than in normal controller\n # so the random initial actions in RL create some signal\n kp_v = 5.0\n kp_a, kd_a = 100.0, 50.0\n\n e_v = dynamics.vel - action[:3]\n acc_des = -kp_v * e_v + npa(0, 0, GRAV)\n\n # rotation towards the ideal thrust direction\n # see Mellinger and Kumar 2011\n R = dynamics.rot\n zb_des, _ = normalize(acc_des)\n yb_des, _ = normalize(cross(zb_des, R[:,0]))\n xb_des = cross(yb_des, zb_des)\n R_des = np.column_stack((xb_des, yb_des, zb_des))\n\n def vee(R):\n return np.array([R[2,1], R[0,2], R[1,0]])\n e_R = 0.5 * vee(np.matmul(R_des.T, R) - np.matmul(R.T, R_des))\n omega_des = np.array([0, 0, action[3]])\n e_w = dynamics.omega - omega_des\n\n dw_des = -kp_a * e_R - kd_a * e_w\n # we want this acceleration, but we can only accelerate in one direction!\n thrust_mag = np.dot(acc_des, dynamics.rot[:,2])\n\n des = np.append(thrust_mag, dw_des)\n thrusts = np.matmul(self.Jinv, des)\n thrusts = np.clip(thrusts, a_min=0.0, a_max=1.0)\n dynamics.step(thrusts, dt)\n\n\n# this is an \"oracle\" policy to drive the quadrotor towards a goal\n# using the controller from Mellinger et al. 2011\nimport tensorflow as tf\nclass NonlinearPositionController(object):\n def __init__(self, dynamics, tf_control=True):\n jacobian = quadrotor_jacobian(dynamics)\n self.Jinv = np.linalg.inv(jacobian)\n ## Jacobian inverse for our quadrotor\n # Jinv = np.array([[0.0509684, 0.0043685, -0.0043685, 0.02038736],\n # [0.0509684, -0.0043685, -0.0043685, -0.02038736],\n # [0.0509684, -0.0043685, 0.0043685, 0.02038736],\n # [0.0509684, 0.0043685, 0.0043685, -0.02038736]])\n self.action = None\n\n self.kp_p, self.kd_p = 4.5, 3.5\n self.kp_a, self.kd_a = 200.0, 50.0\n\n self.rot_des = np.eye(3)\n\n self.tf_control = tf_control\n if tf_control:\n self.step_func = self.step_tf\n self.sess = tf.Session()\n self.thrusts_tf = self.step_graph_construct(Jinv_=self.Jinv, observation_provided=True)\n self.sess.run(tf.global_variables_initializer())\n else:\n self.step_func = self.step\n\n # modifies the dynamics in place.\n def step(self, dynamics, goal, dt, action=None, observation=None):\n to_goal = goal - dynamics.pos\n goal_dist = norm(to_goal)\n e_p = -clamp_norm(to_goal, 4.0)\n e_v = dynamics.vel\n # print('Mellinger: ', e_p, e_v, type(e_p), type(e_v))\n acc_des = -self.kp_p * e_p - self.kd_p * e_v + np.array([0, 0, GRAV])\n\n # I don't need to control yaw\n # if goal_dist > 2.0 * dynamics.arm:\n # # point towards goal\n # xc_des = to_xyhat(to_goal)\n # else:\n # # keep current\n # xc_des = to_xyhat(dynamics.rot[:,0])\n\n xc_des = self.rot_des[:, 0]\n # xc_des = np.array([1.0, 0.0, 0.0])\n\n # rotation towards the ideal thrust direction\n # see Mellinger and Kumar 2011\n zb_des, _ = normalize(acc_des)\n yb_des, _ = normalize(cross(zb_des, xc_des))\n xb_des = cross(yb_des, zb_des)\n R_des = np.column_stack((xb_des, yb_des, zb_des))\n R = dynamics.rot\n\n def vee(R):\n return np.array([R[2,1], R[0,2], R[1,0]])\n e_R = 0.5 * vee(np.matmul(R_des.T, R) - np.matmul(R.T, R_des))\n e_R[2] *= 0.2 # slow down yaw dynamics\n e_w = dynamics.omega\n\n dw_des = -self.kp_a * e_R - self.kd_a * e_w\n # we want this acceleration, but we can only accelerate in one direction!\n thrust_mag = np.dot(acc_des, R[:,2])\n\n des = np.append(thrust_mag, dw_des)\n # print('Jinv:', self.Jinv)\n thrusts = np.matmul(self.Jinv, des)\n thrusts[thrusts < 0] = 0\n thrusts[thrusts > 1] = 1\n\n dynamics.step(thrusts, dt)\n self.action = thrusts.copy()\n\n\n def step_tf(self, dynamics, goal, dt, action=None, observation=None):\n # print('step tf')\n if not self.observation_provided:\n xyz = np.expand_dims(dynamics.pos.astype(np.float32), axis=0)\n Vxyz = np.expand_dims(dynamics.vel.astype(np.float32), axis=0)\n Omega = np.expand_dims(dynamics.omega.astype(np.float32), axis=0)\n R = np.expand_dims(dynamics.rot.astype(np.float32), axis=0)\n # print('step_tf: goal type: ', type(goal), goal[:3])\n goal_xyz = np.expand_dims(goal[:3].astype(np.float32), axis=0)\n\n result = self.sess.run([self.thrusts_tf], feed_dict={self.xyz_tf: xyz,\n self.Vxyz_tf: Vxyz,\n self.Omega_tf: Omega,\n self.R_tf: R,\n self.goal_xyz_tf: goal_xyz})\n\n else:\n print('obs fed: ', observation)\n goal_xyz = np.expand_dims(goal[:3].astype(np.float32), axis=0)\n result = self.sess.run([self.thrusts_tf], feed_dict={self.observation: observation,\n self.goal_xyz_tf: goal_xyz})\n self.action = result[0].squeeze()\n dynamics.step(self.action, dt)\n\n def step_graph_construct(self, Jinv_=None, observation_provided=False):\n # import tensorflow as tf\n self.observation_provided = observation_provided\n with tf.variable_scope('MellingerControl'):\n\n if not observation_provided:\n #Here we will provide all components independently\n self.xyz_tf = tf.placeholder(name='xyz', dtype=tf.float32, shape=(None, 3))\n self.Vxyz_tf = tf.placeholder(name='Vxyz', dtype=tf.float32, shape=(None, 3))\n self.Omega_tf = tf.placeholder(name='Omega', dtype=tf.float32, shape=(None, 3))\n self.R_tf = tf.placeholder(name='R', dtype=tf.float32, shape=(None, 3, 3))\n else:\n #Here we will provide observations directly and split them\n self.observation = tf.placeholder(name='obs', dtype=tf.float32, shape=(None, 3 + 3 + 9 + 3))\n self.xyz_tf, self.Vxyz_tf, self.R_flat, self.Omega_tf = tf.split(self.observation, [3,3,9,3], axis=1)\n self.R_tf = tf.reshape(self.R_flat, shape=[-1, 3, 3], name='R')\n\n R = self.R_tf\n # R_flat = tf.placeholder(name='R_flat', type=tf.float32, shape=(None, 9))\n # R = tf.reshape(R_flat, shape=(-1, 3, 3), name='R')\n\n #GOAL = [x,y,z, Vx, Vy, Vz]\n self.goal_xyz_tf = tf.placeholder(name='goal_xyz', dtype=tf.float32, shape=(None, 3))\n # goal_Vxyz = tf.placeholder(name='goal_Vxyz', type=tf.float32, shape=(None, 3))\n\n # Learnable gains with static initialization\n kp_p = tf.get_variable('kp_p', shape=[], initializer=tf.constant_initializer(4.5), trainable=True) # 4.5\n kd_p = tf.get_variable('kd_p', shape=[], initializer=tf.constant_initializer(3.5), trainable=True) # 3.5\n kp_a = tf.get_variable('kp_a', shape=[], initializer=tf.constant_initializer(200.0), trainable=True) # 200.\n kd_a = tf.get_variable('kd_a', shape=[], initializer=tf.constant_initializer(50.0), trainable=True) # 50.\n\n ## IN case you want to optimize them from random values\n # kp_p = tf.get_variable('kp_p', initializer=tf.random_uniform(shape=[1], minval=0.0, maxval=10.0), trainable=True) # 4.5\n # kd_p = tf.get_variable('kd_p', initializer=tf.random_uniform(shape=[1], minval=0.0, maxval=10.0), trainable=True) # 3.5\n # kp_a = tf.get_variable('kp_a', initializer=tf.random_uniform(shape=[1], minval=0.0, maxval=100.0), trainable=True) # 200.\n # kd_a = tf.get_variable('kd_a', initializer=tf.random_uniform(shape=[1], minval=0.0, maxval=100.0), trainable=True) # 50.\n\n to_goal = self.goal_xyz_tf - self.xyz_tf\n e_p = -tf.clip_by_norm(to_goal, 4.0, name='e_p')\n e_v = self.Vxyz_tf\n acc_des = -kp_p * e_p - kd_p * e_v + tf.constant([0, 0, 9.81], name='GRAV')\n print('acc_des shape: ', acc_des.get_shape().as_list())\n\n def project_xy(x, name='project_xy'):\n # print('x_shape:', x.get_shape().as_list())\n # x = tf.squeeze(x, axis=2)\n return tf.multiply(x, tf.constant([1., 1., 0.]), name=name)\n\n # goal_dist = tf.norm(to_goal, name='goal_xyz_dist')\n xc_des = project_xy(tf.squeeze(tf.slice(R, begin=[0,0,2], size=[-1,3,1]), axis=2), name='xc_des')\n print('xc_des shape: ', xc_des.get_shape().as_list())\n # xc_des = project_xy(R[:, 0])\n\n\n # rotation towards the ideal thrust direction\n # see Mellinger and Kumar 2011\n zb_des = tf.nn.l2_normalize(acc_des, axis=1, name='zb_dex')\n yb_des = tf.nn.l2_normalize(tf.cross(zb_des, xc_des), axis=1, name='yb_des')\n xb_des = tf.cross(yb_des, zb_des, name='xb_des')\n R_des = tf.stack([xb_des, yb_des, zb_des], axis=2, name='R_des')\n\n print('zb_des shape: ', zb_des.get_shape().as_list())\n print('yb_des shape: ', yb_des.get_shape().as_list())\n print('xb_des shape: ', xb_des.get_shape().as_list())\n print('R_des shape: ', R_des.get_shape().as_list())\n\n def transpose(x):\n return tf.transpose(x, perm=[0, 2, 1])\n\n # Rotational difference\n Rdiff = tf.matmul(transpose(R_des), R) - tf.matmul(transpose(R), R_des, name='Rdiff')\n print('Rdiff shape: ', Rdiff.get_shape().as_list())\n\n def tf_vee(R, name='vee'):\n return tf.squeeze( tf.stack([\n tf.squeeze(tf.slice(R, [0, 2, 1], [-1, 1, 1]), axis=2),\n tf.squeeze(tf.slice(R, [0, 0, 2], [-1, 1, 1]), axis=2),\n tf.squeeze(tf.slice(R, [0, 1, 0], [-1, 1, 1]), axis=2)], axis=1, name=name), axis=2)\n # def vee(R):\n # return np.array([R[2, 1], R[0, 2], R[1, 0]])\n\n e_R = 0.5 * tf_vee(Rdiff, name='e_R')\n print('e_R shape: ', e_R.get_shape().as_list())\n # e_R[2] *= 0.2 # slow down yaw dynamics\n e_w = self.Omega_tf\n\n # Control orientation\n dw_des = -kp_a * e_R - kd_a * e_w\n print('dw_des shape: ', dw_des.get_shape().as_list())\n\n # we want this acceleration, but we can only accelerate in one direction!\n # thrust_mag = np.dot(acc_des, R[:, 2])\n acc_cur = tf.squeeze(tf.slice(R, begin=[0, 0, 2], size=[-1, 3, 1]), axis=2)\n print('acc_cur shape: ', acc_cur.get_shape().as_list())\n\n acc_dot = tf.multiply(acc_des, acc_cur)\n print('acc_dot shape: ', acc_dot.get_shape().as_list())\n\n thrust_mag = tf.reduce_sum(acc_dot, axis=1, keepdims=True, name='thrust_mag')\n print('thrust_mag shape: ', thrust_mag.get_shape().as_list())\n\n # des = np.append(thrust_mag, dw_des)\n des = tf.concat([thrust_mag, dw_des], axis=1, name='des')\n print('des shape: ', des.get_shape().as_list())\n\n if Jinv_ is None:\n # Learn the jacobian inverse\n Jinv = tf.get_variable('Jinv', initializer=tf.random_normal(shape=[4,4], mean=0.0, stddev=0.1), trainable=True)\n else:\n # Jacobian inverse is provided\n Jinv = tf.constant(Jinv_.astype(np.float32), name='Jinv')\n # Jinv = tf.get_variable('Jinv', shape=[4,4], initializer=tf.constant_initializer())\n\n print('Jinv shape: ', Jinv.get_shape().as_list())\n ## Jacobian inverse for our quadrotor\n # Jinv = np.array([[0.0509684, 0.0043685, -0.0043685, 0.02038736],\n # [0.0509684, -0.0043685, -0.0043685, -0.02038736],\n # [0.0509684, -0.0043685, 0.0043685, 0.02038736],\n # [0.0509684, 0.0043685, 0.0043685, -0.02038736]])\n\n # thrusts = np.matmul(self.Jinv, des)\n thrusts = tf.matmul(des, tf.transpose(Jinv), name='thrust')\n thrusts = tf.clip_by_value(thrusts, clip_value_min=0.0, clip_value_max=1.0, name='thrust_clipped')\n return thrusts\n\n\n\n\n def action_space(self, dynamics):\n circle_per_sec = 2 * np.pi\n max_rp = 5 * circle_per_sec\n max_yaw = 1 * circle_per_sec\n min_g = -1.0\n max_g = dynamics.thrust_to_weight - 1.0\n low = np.array([min_g, -max_rp, -max_rp, -max_yaw])\n high = np.array([max_g, max_rp, max_rp, max_yaw])\n return spaces.Box(low, high, dtype=np.float32)\n\n\n# TODO:\n# class AttitudeControl,\n# refactor common parts of VelocityYaw and NonlinearPosition"
},
{
"alpha_fraction": 0.5398473739624023,
"alphanum_fraction": 0.5617846250534058,
"avg_line_length": 40.385963439941406,
"blob_id": "98383eb14b7a5c7e45f2d535672cfc5b223d2dcc",
"content_id": "337b8fa3672e8225b5ac38f0f9ac1a5da7d532b1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9436,
"license_type": "no_license",
"max_line_length": 137,
"num_lines": 228,
"path": "/quad_train/misc/dict2hdf5.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nfrom __future__ import print_function\n\nimport numpy as np\nimport h5py\nimport os\nimport numbers\nimport inspect\n\n\n\ndef h5_is_simple_type(obj):\n return (\n isinstance(obj, numbers.Number) or\n type(obj) == str or \n isinstance(obj, np.bool_)\n )\n\nclass dict2h5(object):\n \"\"\"\n The class can save and load python dictionary into a hdf5 file\n \"\"\"\n indx_format = \"%04d\"\n @classmethod\n def indx2str(cls, indx):\n return cls.indx_format % indx\n\n @classmethod\n def strkey_val(cls, obj):\n if type(obj) == list or type(obj) == tuple:\n for i,v in enumerate(obj):\n yield cls.indx2str(i), v\n elif type(obj) == dict:\n for i,v in obj.items():\n yield str(i), v\n else:\n raise NotImplementedError(\"ERROR: %s: Unsupported data type: %s\" % (inspect.stack()[0][3], type(obj)))\n\n ## Saving a dictionary\n @classmethod\n def save(cls, dic, filename=None, h5file=None, float_nptype=None):\n ## The following check is not necessary\n # if os.path.exists(filename):\n # raise ValueError('File %s exists, will not overwrite.' % filename)\n if filename is None:\n cls.__recursively_save_dict_contents_to_group__(h5file, '/', dic, float_nptype=float_nptype)\n else:\n with h5py.File(filename, 'a') as h5file:\n cls.__recursively_save_dict_contents_to_group__(h5file, '/', dic, float_nptype=float_nptype)\n\n\n\n @classmethod\n def __recursively_save_dict_contents_to_group__(cls, h5file, path, dic, float_nptype=None):\n \"\"\"\n @param: float_nptype: allows reduction in float precision. \n If size of float_nptype < original size then data is converted\n \"\"\"\n # argument type checking\n # if not isinstance(dic, dict):\n # raise ValueError(\"must provide a dictionary\")\n if not isinstance(path, str):\n raise ValueError(\"path must be a string\")\n if not isinstance(h5file, h5py._hl.files.File):\n raise ValueError(\"must be an open h5py file\")\n # save items to the hdf5 file\n # for key, item in dic.items():\n for key, item in cls.strkey_val(dic):\n # save strings, numpy.intX, and numpy.floatX types\n if h5_is_simple_type(item):\n h5file[path + key] = item\n if not h5file[path + key].value == item:\n raise ValueError('The data representation in the HDF5 file does not match the original dict.')\n # save numpy arrays\n elif isinstance(item, np.ndarray):\n if float_nptype is not None and \\\n item.dtype in [np.float, np.float16, np.float32, np.float64] and \\\n item.dtype.itemsize > np.zeros(1,dtype=float_nptype).itemsize:\n item = item.astype(float_nptype)\n h5file[path + key] = item\n if not np.array_equal(h5file[path + key].value, item):\n raise ValueError('The data representation in the HDF5 file does not match the original dict.')\n # save dictionaries\n elif type(item) in [dict, list, tuple]:\n cls.__recursively_save_dict_contents_to_group__(h5file, path + key + '/', item, float_nptype=float_nptype)\n # attempt to convert to string\n else:\n print(\"WARNING: %s: Unknown HDF5 data type %s. Attempting to convert to a string\" % (inspect.stack()[0][3], type(item)))\n h5file[path + key] = str(item)\n if not h5file[path + key].value == str(item):\n raise ValueError('The data representation in the HDF5 file does not match the original dict.')\n # other types cannot be saved and will result in an error\n # else:\n # raise ValueError('Cannot save %s type.' % type(item))\n\n ## Load a hdf5 file\n @classmethod\n def load(cls, filename, pack2list=False):\n \"\"\"\n Loads HDF5 content into a dictionary\n \"\"\"\n with h5py.File(filename, 'r') as h5file:\n return cls.__recursively_load_dict_contents_from_group__(h5file, '/', pack2list=pack2list)\n\n @classmethod\n def __recursively_load_dict_contents_from_group__(cls, h5file, path, pack2list=False):\n \"\"\"\n A helper function to for recursive loading into a dictionary\n If pack2list == True then if the keys in the group are indices (i.e. int > 0 and sequential starting at 0)\n Then it will pack them into a list instead of a dict()\n \"\"\"\n ## Check if group val is a simple type\n keys = list(h5file[path].keys())\n # isdigit() checks if it is a positive integer\n keys_are_digits = [key.isdigit() for key in keys]\n\n ## Checking if subgroups names are just indices\n ## In that case we should create a list of values\n pack2list_here = pack2list and len(keys) > 0 and np.all(keys_are_digits)\n if pack2list_here:\n keys_val = np.array([int(key) for key in keys])\n keys_indx_sorted = np.argsort(keys_val)\n keys_val = keys_val[keys_indx_sorted]\n # keys_val = np.sort([int(key) for key in keys]) #This is correct. Excluded to avoid double sorting\n key_indices = np.arange(keys_val[0], keys_val[-1]+1)\n pack2list_here = pack2list_here and np.all(keys_val == key_indices) and len(keys_val) > 0\n\n if pack2list_here:\n ans = []\n # re-sorting, but now the strings\n # it is done to avoid situations when, say your indx is \"0000\" which is just 0\n # keys_val = np.sort(keys) #This may have problems, when you have \"11\", \"2\". It will be sorted incorrectly\n keys = np.array(keys)\n keys_sort = keys[keys_indx_sorted] #same sorting that is for keys numerical values\n for key in keys_sort:\n if isinstance(h5file[path + key], h5py._hl.group.Group):\n ans.append(cls.__recursively_load_dict_contents_from_group__(h5file, path + key + '/', pack2list=pack2list))\n elif isinstance(h5file[path + key], h5py._hl.dataset.Dataset):\n ans.append(h5file[path + key].value)\n else:\n ans = {}\n for key, item in h5file[path].items():\n if isinstance(item, h5py._hl.dataset.Dataset):\n ans[key] = item.value\n elif isinstance(item, h5py._hl.group.Group):\n ans[key] = cls.__recursively_load_dict_contents_from_group__(h5file, path + key + '/', pack2list=pack2list)\n return ans\n\n @classmethod\n def append_train_iter_data(cls, h5file, data, data_group=\"traj_data/\", teacher_indx=0, itr=None, float_nptype=np.float32):\n \"\"\"\n Appends data of training iteration [itr] to the existing list in hdf5\n If [itr] is None - tries to find max index and append\n If [itr] is provided writes data under the group with the name \"itr\".\n Assumed structure: \n data_group/teacher_indx/itr = data \n If you would like to avoid adding teacher_indx then set it to None.\n It will result in:\n data_group/itr = data\n \"\"\"\n data_group = data_group.rstrip(\"/\") + \"/\"\n if teacher_indx is None:\n teacher_group = data_group\n else:\n teacher_group = data_group + cls.indx2str(teacher_indx) + \"/\"\n if itr is None:\n iter_indices = [int(i) for i in iter(h5file[teacher_group])]\n if not iter_indices:\n itr = 0\n else:\n max_indx = np.max(iter_indices)\n itr = max_indx + 1\n cls.__recursively_save_dict_contents_to_group__(h5file, teacher_group + cls.indx2str(itr) + '/', data, float_nptype=float_nptype)\n \n @classmethod\n def add_dict(cls, h5file, dic, groupname=\"/\", float_nptype=None):\n groupname = groupname.rstrip(\"/\") + \"/\"\n cls.__recursively_save_dict_contents_to_group__(h5file, groupname, dic, float_nptype=float_nptype)\n \n @classmethod\n def add_cmd(h5file):\n # Saving command line to hdf\n h5file[\"cmd\"] = \" \".join(sys.argv)\n \n\n\n\n## Test\nif __name__ == \"__main__\":\n\n filename = 'foo.hdf5'\n if os.path.exists(filename):\n os.remove(filename)\n ex = {\n 'name': 'stefan',\n 'age': np.int64(24),\n 'fav_numbers': np.array([2,4,4.3]),\n 'fav_tensors': {\n 'levi_civita3d': np.array([\n [[0,0,0],[0,0,1],[0,-1,0]],\n [[0,0,-1],[0,0,0],[1,0,0]],\n [[0,1,0],[-1,0,0],[0,0,0]]\n ]),\n 'kronecker2d': np.identity(3)\n },\n 'lst': [1.1, 1.2, 1.3]\n }\n print(ex)\n dict2h5.save(ex, filename)\n loaded = dict2h5.load('foo.hdf5')\n print(loaded)\n np.testing.assert_equal(loaded, ex)\n print('check passed!')\n ex2 = {\n 'name2': 'stefan',\n 'age2': np.int64(24),\n 'fav_numbers2': np.array([2,4,4.3]),\n 'fav_tensors2': {\n 'levi_civita3d': np.array([\n [[0,0,0],[0,0,1],[0,-1,0]],\n [[0,0,-1],[0,0,0],[1,0,0]],\n [[0,1,0],[-1,0,0],[0,0,0]]\n ]),\n 'kronecker2d': np.identity(3)\n },\n 'lst2': [1.1, 1.2, 1.3]\n }\n dict2h5.save(ex2, filename)\n"
},
{
"alpha_fraction": 0.761904776096344,
"alphanum_fraction": 0.761904776096344,
"avg_line_length": 20,
"blob_id": "a9f19e4ecc08a9b80a66ed0fb2e6f2755db1d18a",
"content_id": "fe5d376b1a97b85d60a7d9a24a98bb52e8241ff3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 42,
"license_type": "no_license",
"max_line_length": 29,
"num_lines": 2,
"path": "/install_depend_linux.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nsudo apt-get install parallel\n"
},
{
"alpha_fraction": 0.6313559412956238,
"alphanum_fraction": 0.6822034120559692,
"avg_line_length": 32.85714340209961,
"blob_id": "d65dcd805e021c071062d7dee5442cad8b928441",
"content_id": "2d2f8c3a268f5ce922e41510d7d86e5117dce309",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 236,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 7,
"path": "/quad_train/launchers/ppo_crazyflie_randomization.sh",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\nparallel ./train_quad.py config/ppo__crazyflie_randomization_0.2_noisy_nodamp.yml _results_temp/ppo_crazyflie_randomization \\\n-c \\\n--seed {1} \\\n-p env_param.dynamics_randomization_ratio \\\n-pv {2} \\\n::: {1..5} ::: 0.1 0.2 0.3"
},
{
"alpha_fraction": 0.5638258457183838,
"alphanum_fraction": 0.574246346950531,
"avg_line_length": 27.595745086669922,
"blob_id": "eb18be74e7e38b4f64f047057a1088eccee41437",
"content_id": "3a1dbca34d3e9358668dd30898764723c3d7a6e0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2687,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 94,
"path": "/quad_train/plot_tools/plot_graphs_with_seeds.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport numpy as np\nimport os, sys\nimport matplotlib.pyplot as plt\n\nimport argparse\nfrom argparse import RawTextHelpFormatter, ArgumentDefaultsHelpFormatter\n\nimport time\nimport datetime\nfrom dateutil.relativedelta import relativedelta\n\nfrom quad_dynalearn.plot_tools import plot_tools as pt\n\ndef runtime_str(t_diff):\n days = int(t_diff / (3600 * 24))\n hours = int((t_diff % (3600 * 24)) / 3600)\n minutes = int( (t_diff % 3600) / 60 )\n seconds = int(t_diff % 60)\n return '{d}d {h}h {m}m {s}s'.format(d=days, h=hours, m=minutes, s=seconds)\n\ndef main(argv):\n #Parsing command line arguments\n parser = argparse.ArgumentParser(\n description=\"Argument description: \",\n formatter_class=ArgumentDefaultsHelpFormatter)\n # formatter_class=RawTextHelpFormatter)\n parser.add_argument(\n \"dir\",\n help=\"Input directory\"\n )\n parser.add_argument(\n \"-g\",\"--graph\",\n default=\"rewards/rew_main_avg\",\n help=\"Name of data column in a csv file\"\n )\n parser.add_argument(\n \"-s\",\"--seeds\",\n action=\"store_true\",\n help=\"Show individual seeds\"\n )\n parser.add_argument(\n \"-sns\",\"--seaborn\",\n action=\"store_true\",\n help=\"Use seaborn for visualiztion\"\n )\n parser.add_argument(\n \"-top\",\"--top_n\",\n type=int,\n help=\"Show top highest N results only. If N < 0 then takes top lowest N results\"\n )\n parser.add_argument(\n \"-ti\",\"--top_n_interval\",\n type=int,\n default=5,\n help=\"Averaging interval for the top performing agents\"\n )\n args = parser.parse_args()\n\n ###################################\n ### Main code\n print('Arguments: ')\n [print(arg, ': ',val) for arg,val in args.__dict__.items()]\n\n ## Printing runtime\n time_start = time.time()\n\n if args.seaborn:\n try:\n import seaborn as sns\n sns.set()\n except:\n print(\"WARN: No seaborn found. Continuing with classic theme ...\")\n\n # Reading subdirectories\n folders = pt.subdir(args.dir)\n\n # Forming labels\n labels = [sd.rsplit(os.sep,1)[1] for sd in folders]\n\n # Reading and ploting\n pt.read_and_plot_seeds(folders=folders, \n graph_names=[args.graph]*len(folders), \n labels=labels, \n ylabel_str=args.graph, \n show_seeds=args.seeds,\n top_n=args.top_n,\n top_n_interval=args.top_n_interval)\n \n time_end = time.time()\n print(\"RUNTIME: \", runtime_str(time_end-time_start))\n\nif __name__ == '__main__':\n main(sys.argv)"
},
{
"alpha_fraction": 0.6349658370018005,
"alphanum_fraction": 0.6391419768333435,
"avg_line_length": 36.09859085083008,
"blob_id": "b4c659347f4f300184896ceb622b8120e963eb0e",
"content_id": "82c29171be57bb15cdb99dd983876e2aca5841a8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5268,
"license_type": "no_license",
"max_line_length": 170,
"num_lines": 142,
"path": "/quad_train/train_quad.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\"\"\"\nThis is a parametrized script to run TRPO/PPO \nwith a custom env\n\"\"\"\nimport argparse\nimport sys\nimport os\nimport datetime, time\nimport itertools\nimport os.path as osp\nimport uuid\nimport copy\n\nimport numpy as np\n\nimport dateutil.tz\nimport yaml\n\nimport gym\n\nfrom garage.envs import normalize\nfrom garage.experiment import run_experiment\n\n# Custom stuff\nimport quad_train.config.config_loader as conf\nimport quad_train.misc.variants_utils as vu\n\n\n########################################################################\n## ARGUMENTS\nparser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\nparser.add_argument(\"config_file\", help='yaml file with default settings of parameters')\nparser.add_argument(\"log_dir\", default='_results_temp/trpo_ppo_last', help='Directory to log into')\nparser.add_argument(\"--seed\", '-s', default=\"1\", help='list of seeds to use separated by comma (or a single seed w/o comma). If None seeds from config_file will be used')\nparser.add_argument(\"--n_parallel\", '-n', type=int, default=1, help='Number of parallel workers to run a single task')\nparser.add_argument(\"--snapshot_mode\", '-snm', default='last', help='Snapshot mode. Opt: last')\nparser.add_argument(\"--plot\", '-plt', action=\"store_true\", help='Plotting')\nparser.add_argument(\"--param_name\", '-p', help='task hyperparameter names separated by comma')\nparser.add_argument(\"--param_val\", '-pv', help='task hyperparam values.'+ \n ' For a single par separated by comma.' +\n ' For adjacent params separated by double comma.' +\n ' Ex: \\\"-p par1,par2 -pv pv11,pv12,,pv21,pv22\\\"' + \n ' where pv11,pv12 - par values for par1 , pv21,pv22 - par values for par2')\nargs = parser.parse_args()\n\n########################################################################\n## PARAMETERS (non grid)\n# Loading parameters not specified in the arguments\nprint('Reading parameter file %s ...' % args.config_file)\nparams = conf.trpo_ppo_default_params()\nyaml_stream = open(args.config_file, 'r')\nparams_new = yaml.load(yaml_stream)\nparams.update(params_new)\nprint('###############################################################')\nprint('### PARAMETERS LOADED FROM CONFIG FILES (Later will be updated by arguments provided)')\nprint(params)\n\n## Get a grid of task variations and put it into list as parameter dictionaries\n## WARN: when you add more parameters to add_arguments you will have to modify grid_of_variants()\nvariants_list = vu.grid_of_variants(args, params)\n\n## Saving command line executing the script\ncmd = \" \".join(sys.argv)\nif not os.path.isdir(args.log_dir):\n os.makedirs(args.log_dir)\nwith open(args.log_dir + os.sep + \"cmd.sh\", \"w\") as cmdfile:\n cmdfile.write(\"#!/usr/bin/bash\\n\")\n cmdfile.write(cmd)\n\n\ndef run_task(task_param):\n \"\"\"\n Wrap PPO training task in the run_task function.\n\n :param _:\n :return:\n \"\"\"\n from garage.tf.baselines import GaussianMLPBaseline\n from garage.tf.envs import TfEnv\n from garage.tf.policies import GaussianMLPPolicy, DeterministicMLPPolicy, GaussianGRUPolicy, GaussianLSTMPolicy\n \n from quad_train.algos.cem import CEM\n from quad_train.algos.cma_es import CMAES\n from quad_train.algos.ppo import PPO\n from quad_train.algos.trpo import TRPO\n\n if task_param[\"env\"] == \"QuadrotorEnv\":\n from quad_sim.quadrotor import QuadrotorEnv\n env = TfEnv(QuadrotorEnv(**task_param[\"env_param\"]))\n del task_param[\"env_param\"]\n else:\n env = TfEnv(normalize(gym.make(task_param[\"env\"])))\n del task_param[\"env\"]\n \n print(task_param[\"policy_param\"])\n policy = locals()[task_param[\"policy_class\"]](env_spec=env.spec, **task_param[\"policy_param\"])\n del task_param[\"policy_class\"]\n del task_param[\"policy_param\"]\n\n if task_param[\"alg_class\"] != \"CEM\" and task_param[\"alg_class\"] != \"CMAES\":\n baseline = locals()[task_param[\"baseline_class\"]](env_spec=env.spec, **task_param[\"baseline_param\"])\n del task_param[\"baseline_class\"]\n del task_param[\"baseline_param\"]\n\n algo = locals()[task_param[\"alg_class\"]](\n env=env,\n policy=policy,\n baseline=baseline,\n **task_param[\"alg_param\"])\n else:\n algo = locals()[task_param[\"alg_class\"]](\n env=env,\n policy=policy,\n **task_param[\"alg_param\"])\n\n del task_param[\"alg_class\"]\n del task_param[\"alg_param\"]\n\n # Check that we used all parameters:\n # It helps revealing situations where you thought you set certain parameter\n # But in fact made spelling mistake and it failed\n del task_param[\"exp_name\"] #This is probably generated by garage\n assert task_param == {}, \"ERROR: Some of parameter values were not used: %s\" % str(task_param)\n\n algo.train()\n\nstart_time = time.time()\nfor var in variants_list:\n ## Dumping config\n with open(var[\"log_dir\"] + os.sep + \"config.yml\", 'w') as yaml_file:\n yaml_file.write(yaml.dump(var, default_flow_style=False))\n\n ## Running\n run_experiment(\n run_task,\n **var\n )\n\nend_time = time.time()\nprint(\"##################################################\")\nprint(\"Total Runtime: \", end_time - start_time)\n"
},
{
"alpha_fraction": 0.5348618626594543,
"alphanum_fraction": 0.5519986152648926,
"avg_line_length": 40.89594650268555,
"blob_id": "ce8076fa04ed2ee933f39cfbf5fd1c221b1964d5",
"content_id": "09ab05f9e4c25893d184ffa5fb3ab0779058b431",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 76502,
"license_type": "no_license",
"max_line_length": 216,
"num_lines": 1826,
"path": "/quad_sim/quadrotor.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\"\"\"\nQuadrotor simulation for OpenAI Gym, with components reusable elsewhere.\nAlso see: D. Mellinger, N. Michael, V.Kumar. \nTrajectory Generation and Control for Precise Aggressive Maneuvers with Quadrotors\nhttp://journals.sagepub.com/doi/pdf/10.1177/0278364911434236\n\nDevelopers:\nJames Preiss, Artem Molchanov, Tao Chen \n\nReferences:\n[1] RotorS: https://www.researchgate.net/profile/Fadri_Furrer/publication/309291237_RotorS_-_A_Modular_Gazebo_MAV_Simulator_Framework/links/5a0169c4a6fdcc82a3183f8f/RotorS-A-Modular-Gazebo-MAV-Simulator-Framework.pdf\n[2] CrazyFlie modelling: http://mikehamer.info/assets/papers/Crazyflie%20Modelling.pdf\n[3] HummingBird: http://www.asctec.de/en/uav-uas-drones-rpas-roav/asctec-hummingbird/\n[4] CrazyFlie thrusters transition functions: https://www.bitcraze.io/2015/02/measuring-propeller-rpm-part-3/\n[5] HummingBird modelling: https://digitalrepository.unm.edu/cgi/viewcontent.cgi?referer=https://www.google.com/&httpsredir=1&article=1189&context=ece_etds\n[6] Rotation b/w matrices: http://www.boris-belousov.net/2016/12/01/quat-dist/#using-rotation-matrices\n[7] Rodrigues' rotation formula: https://en.wikipedia.org/wiki/Rodrigues%27_rotation_formula\n\"\"\"\nimport argparse\nimport logging\nimport numpy as np\nfrom numpy.linalg import norm\nimport sys\nfrom copy import deepcopy\nimport matplotlib.pyplot as plt\nimport time\n\nimport gym\nfrom gym import spaces\nfrom gym.utils import seeding\nimport gym.envs.registration as gym_reg\n\nimport transforms3d as t3d\n\nfrom quad_sim.quadrotor_randomization import *\nfrom quad_sim.quadrotor_control import *\nfrom quad_sim.quadrotor_obstacles import *\nfrom quad_sim.quadrotor_visualization import *\nfrom quad_sim.quad_utils import *\nfrom quad_sim.inertia import QuadLink\nfrom quad_sim.sensor_noise import SensorNoise\n\nfrom quad_sim.quad_models import *\n\n\ntry:\n from garage.core import Serializable\nexcept:\n print(\"WARNING: garage.core.Serializable is not found. Substituting with a dummy class\")\n class Serializable:\n def __init__(self):\n pass\n def quick_init(self, locals_in):\n pass\n\n\nlogger = logging.getLogger(__name__)\n\nGRAV = 9.81 #default gravitational constant\nEPS = 1e-6 #small constant to avoid divisions by 0 and log(0)\n\n## WARN:\n# - linearity is set to 1 always, by means of check_quad_param_limits(). \n# The def. value of linarity for CF is set to 1 as well (due to firmware nonlinearity compensation)\n\nclass QuadrotorDynamics(object):\n \"\"\"\n Simple simulation of quadrotor dynamics.\n mass unit: kilogram\n arm_length unit: meter\n inertia unit: kg * m^2, 3-element vector representing diagonal matrix\n thrust_to_weight is the total, it will be divided among the 4 props\n torque_to_thrust is ratio of torque produced by prop to thrust\n thrust_noise_ratio is noise2signal ratio of the thrust noise, Ex: 0.05 = 5% of the current signal\n It is an approximate ratio, i.e. the upper bound could still be higher, due to how OU noise operates\n Coord frames: x configuration:\n - x axis between arms looking forward [x - configuration]\n - y axis pointing to the left\n - z axis up \n TODO:\n - only diagonal inertia is used at the moment\n \"\"\"\n def __init__(self, model_params,\n room_box=None,\n dynamics_steps_num=1, \n dim_mode=\"3D\",\n gravity=GRAV):\n\n self.dynamics_steps_num = dynamics_steps_num\n ###############################################################\n ## PARAMETERS \n self.prop_ccw = np.array([-1., 1., -1., 1.])\n # cw = 1 ; ccw = -1 [ccw, cw, ccw, cw]\n # Reference: https://docs.google.com/document/d/1wZMZQ6jilDbj0JtfeYt0TonjxoMPIgHwYbrFrMNls84/edit\n self.omega_max = 40. #rad/s The CF sensor can only show 35 rad/s (2000 deg/s), we allow some extra\n self.vxyz_max = 3. #m/s\n self.gravity = gravity\n self.acc_max = 3. * GRAV\n\n ###############################################################\n ## Internal State variables\n self.since_last_ort_check = 0 #counter\n self.since_last_ort_check_limit = 0.04 #when to check for non-orthogonality\n \n self.rot_nonort_limit = 0.01 # How much of non-orthogonality in the R matrix to tolerate\n self.rot_nonort_coeff_maxsofar = 0. # Statistics on the max number of nonorthogonality that we had\n \n self.since_last_svd = 0 #counter\n self.since_last_svd_limit = 0.5 #in sec - how ofthen mandatory orthogonalization should be applied\n\n self.eye = np.eye(3)\n ###############################################################\n ## Initializing model\n self.update_model(model_params)\n \n ## Sanity checks\n assert self.inertia.shape == (3,)\n\n ###############################################################\n ## OTHER PARAMETERS\n if room_box is None:\n self.room_box = np.array([[-10., -10., 0.], [10., 10., 10.]])\n else:\n self.room_box = np.array(room_box).copy()\n\n ## Selecting 1D, Planar or Full 3D modes\n self.dim_mode = dim_mode\n if self.dim_mode == '1D':\n self.control_mx = np.ones([4,1])\n elif self.dim_mode == '2D':\n self.control_mx = np.array([[1.,0.],[1.,0.],[0.,1.],[0.,1.]])\n elif self.dim_mode == '3D':\n self.control_mx = np.eye(4)\n else:\n raise ValueError('QuadEnv: Unknown dimensionality mode %s' % self.dim_mode)\n\n ## Selecting how many sim steps should be done b/w controller calls\n # i.e. controller frequency\n self._step = getattr(self, 'step%d' % dynamics_steps_num)\n # self.step = getattr(QuadrotorDynamics, 'step%d' % dynamics_steps_num)\n\n\n @staticmethod\n def angvel2thrust(w, linearity=0.424):\n \"\"\"\n Args:\n linearity (float): linearity factor factor [0 .. 1].\n CrazyFlie: linearity=0.424\n \"\"\"\n return (1 - linearity) * w**2 + linearity * w\n\n def update_model(self, model_params):\n self.model = QuadLink(params=model_params[\"geom\"])\n self.model_params = model_params\n\n ###############################################################\n ## PARAMETERS FOR RANDOMIZATION\n self.mass = self.model.m\n self.inertia = np.diagonal(self.model.I_com)\n\n self.thrust_to_weight = self.model_params[\"motor\"][\"thrust_to_weight\"]\n self.torque_to_thrust = self.model_params[\"motor\"][\"torque_to_thrust\"]\n self.motor_linearity = self.model_params[\"motor\"][\"linearity\"]\n self.C_rot_drag = self.model_params[\"motor\"][\"C_drag\"]\n self.C_rot_roll = self.model_params[\"motor\"][\"C_roll\"]\n self.motor_damp_time_up = self.model_params[\"motor\"][\"damp_time_up\"]\n self.motor_damp_time_down = self.model_params[\"motor\"][\"damp_time_down\"]\n\n self.thrust_noise_ratio = self.model_params[\"noise\"][\"thrust_noise_ratio\"]\n self.vel_damp = self.model_params[\"damp\"][\"vel\"]\n self.damp_omega_quadratic = self.model_params[\"damp\"][\"omega_quadratic\"]\n\n\n ###############################################################\n ## COMPUTED (Dependent) PARAMETERS\n try:\n self.motor_assymetry = np.array(self.model_params[\"motor\"][\"assymetry\"])\n except:\n self.motor_assymetry = np.array([1.0, 1.0, 1.0, 1.0])\n print(\"WARNING: Motor assymetry was not setup. Setting assymetry to:\", self.motor_assymetry)\n self.motor_assymetry = self.motor_assymetry * 4./np.sum(self.motor_assymetry) #re-normalizing to sum-up to 4\n self.thrust_max = GRAV * self.mass * self.thrust_to_weight * self.motor_assymetry / 4.0\n self.torque_max = self.torque_to_thrust * self.thrust_max # propeller torque scales\n\n # Propeller positions in X configurations\n self.prop_pos = self.model.prop_pos\n\n # unit: meters^2 ??? maybe wrong\n self.prop_crossproducts = np.cross(self.prop_pos, [0., 0., 1.])\n self.prop_ccw_mx = np.zeros([3,4]) # Matrix allows using matrix multiplication\n self.prop_ccw_mx[2,:] = self.prop_ccw \n\n ## Forced dynamics auxiliary matrices\n #Prop crossproduct give torque directions\n self.G_omega_thrust = self.thrust_max * self.prop_crossproducts.T # [3,4] @ [4,1]\n # additional torques along z-axis caused by propeller rotations\n self.C_omega_prop = self.torque_max * self.prop_ccw_mx # [3,4] @ [4,1] = [3,1]\n self.G_omega = (1.0 / self.inertia)[:,None] * (self.G_omega_thrust + self.C_omega_prop)\n\n # Allows to sum-up thrusts as a linear matrix operation\n self.thrust_sum_mx = np.zeros([3,4]) # [0,0,F_sum].T\n self.thrust_sum_mx[2,:] = 1# [0,0,F_sum].T\n\n # sigma = 0.2 gives roughly max noise of -1 .. 1\n self.thrust_noise = OUNoise(4, sigma=0.2*self.thrust_noise_ratio)\n\n self.arm = np.linalg.norm(self.model.motor_xyz[:2])\n\n self._step = getattr(self, 'step%d' % self.dynamics_steps_num)\n\n self.reset()\n\n # pos, vel, in world coords (meters)\n # rotation is 3x3 matrix (body coords) -> (world coords)dt\n # omega is angular velocity (radians/sec) in body coords, i.e. the gyroscope\n def set_state(self, position, velocity, rotation, omega, thrusts=np.zeros((4,))):\n for v in (position, velocity, omega):\n assert v.shape == (3,)\n assert thrusts.shape == (4,)\n assert rotation.shape == (3,3)\n self.pos = deepcopy(position)\n self.vel = deepcopy(velocity)\n self.acc = np.zeros(3)\n self.accelerometer = np.array([0, 0, GRAV])\n self.rot = deepcopy(rotation)\n self.omega = deepcopy(omega.astype(np.float32))\n self.thrusts = deepcopy(thrusts)\n\n # generate a random state (meters, meters/sec, radians/sec)\n def random_state(self, box, vel_max=15.0, omega_max=2*np.pi):\n pos = np.random.uniform(low=-box, high=box, size=(3,))\n \n vel = np.random.uniform(low=-vel_max, high=vel_max, size=(3,))\n vel_magn = np.random.uniform(low=0., high=vel_max)\n vel = vel_magn / (np.linalg.norm(vel) + EPS) * vel\n \n omega = np.random.uniform(low=-omega_max, high=omega_max, size=(3,))\n omega_magn = np.random.uniform(low=0., high=omega_max)\n omega = omega_magn / (np.linalg.norm(omega) + EPS) * omega\n \n rot = rand_uniform_rot3d()\n return pos, vel, rot, omega\n # self.set_state(pos, vel, rot, omega)\n\n # generate a random state (meters, meters/sec, radians/sec)\n def pitch_roll_restricted_random_state(self, box, vel_max=15.0, omega_max=2*np.pi, pitch_max=0.5, roll_max=0.5, yaw_max=3.14):\n pos = np.random.uniform(low=-box, high=box, size=(3,))\n \n vel = np.random.uniform(low=-vel_max, high=vel_max, size=(3,))\n vel_magn = np.random.uniform(low=0., high=vel_max)\n vel = vel_magn / (np.linalg.norm(vel) + EPS) * vel\n \n omega = np.random.uniform(low=-omega_max, high=omega_max, size=(3,))\n omega_magn = np.random.uniform(low=0., high=omega_max)\n omega = omega_magn / (np.linalg.norm(omega) + EPS) * omega\n \n pitch = np.random.uniform(low=-pitch_max, high=pitch_max)\n roll = np.random.uniform(low=-roll_max, high=roll_max)\n yaw = np.random.uniform(low=-yaw_max, high=yaw_max) \n rot = t3d.euler.euler2mat(roll, pitch, yaw)\n return pos, vel, rot, omega\n\n def step(self, thrust_cmds, dt):\n self._step(self, thrust_cmds, dt)\n\n # multiple dynamics steps\n @staticmethod\n def step2(self, thrust_cmds, dt):\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n\n\n # multiple dynamics steps\n @staticmethod\n def step4(self, thrust_cmds, dt):\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n # print('DYN: state:', self.state_vector(), 'thrust:', thrust_cmds, 'dt', dt)\n\n # multiple dynamics steps\n @staticmethod\n def step6(self, thrust_cmds, dt):\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n # print('DYN: state:', self.state_vector(), 'thrust:', thrust_cmds, 'dt', dt)\n\n # multiple dynamics steps\n @staticmethod\n def step8(self, thrust_cmds, dt):\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n\n # multiple dynamics steps\n @staticmethod\n def step10(self, thrust_cmds, dt):\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n self.step1(self, thrust_cmds, dt)\n\n ## Step function integrates based on current derivative values (best fits affine dynamics model)\n # thrust_cmds is motor thrusts given in normalized range [0, 1].\n # 1 represents the max possible thrust of the motor.\n ## Frames:\n # pos - global\n # vel - global\n # rot - global\n # omega - body frame\n # goal_pos - global\n # from numba import jit, autojit\n # @autojit\n @staticmethod\n def step1(self, thrust_cmds, dt):\n # print(\"thrust_cmds:\", thrust_cmds)\n # uncomment for debugging. they are slow\n #assert np.all(thrust_cmds >= 0)\n #assert np.all(thrust_cmds <= 1)\n\n thrust_cmds = np.clip(thrust_cmds, a_min=0., a_max=1.)\n ###################################\n ## Filtering the thruster and adding noise\n # I use the multiplier 4, since 4*T ~ time for a step response to finish, where\n # T is a time constant of the first-order filter\n self.motor_tau_up = 4*dt/(self.motor_damp_time_up + EPS)\n self.motor_tau_down = 4*dt/(self.motor_damp_time_down + EPS)\n motor_tau = self.motor_tau_up * np.ones([4,])\n motor_tau[thrust_cmds < self.thrust_cmds_damp] = self.motor_tau_down \n motor_tau[motor_tau > 1.] = 1.\n\n ## Since NN commands thrusts we need to convert to rot vel and back\n # WARNING: Unfortunately if the linearity != 1 then filtering using square root is not quite correct\n # since it likely means that you are using rotational velocities as an input instead of the thrust and hence\n # you are filtering square roots of angular velocities\n thrust_rot = thrust_cmds**0.5\n self.thrust_rot_damp = motor_tau * (thrust_rot - self.thrust_rot_damp) + self.thrust_rot_damp \n self.thrust_cmds_damp = self.thrust_rot_damp**2\n\n ## Adding noise\n thrust_noise = thrust_cmds * self.thrust_noise.noise()\n self.thrust_cmds_damp = np.clip(self.thrust_cmds_damp + thrust_noise, 0.0, 1.0) \n\n thrusts = self.thrust_max * self.angvel2thrust(self.thrust_cmds_damp, linearity=self.motor_linearity)\n #Prop crossproduct give torque directions\n torques = self.prop_crossproducts * thrusts[:,None] # (4,3)=(props, xyz)\n\n # additional torques along z-axis caused by propeller rotations\n torques[:, 2] += self.torque_max * self.prop_ccw * self.thrust_cmds_damp \n\n # net torque: sum over propellers\n thrust_torque = np.sum(torques, axis=0) \n\n ###################################\n ## Rotor drag and Rolling forces and moments\n ## See Ref[1] Sec:2.1 for detailes\n\n # self.C_rot_drag = 0.0028\n # self.C_rot_roll = 0.003 # 0.0003\n if self.C_rot_drag != 0 or self.C_rot_roll != 0:\n # self.vel = np.zeros_like(self.vel)\n # v_rotors[3,4] = (rot[3,3] @ vel[3,])[3,] + (omega[3,] x prop_pos[4,3])[4,3]\n # v_rotors = self.rot.T @ self.vel + np.cross(self.omega, self.model.prop_pos)\n vel_body = self.rot.T @ self.vel\n v_rotors = vel_body + cross_vec_mx4(self.omega, self.model.prop_pos)\n # assert v_rotors.shape == (4,3)\n v_rotors[:,2] = 0. #Projection to the rotor plane\n\n # Drag/Roll of rotors (both in body frame)\n rotor_drag_fi = - self.C_rot_drag * np.sqrt(self.thrust_cmds_damp)[:,None] * v_rotors #[4,3]\n rotor_drag_force = np.sum(rotor_drag_fi, axis=0)\n # rotor_drag_ti = np.cross(rotor_drag_fi, self.model.prop_pos)#[4,3] x [4,3]\n rotor_drag_ti = cross_mx4(rotor_drag_fi, self.model.prop_pos)#[4,3] x [4,3]\n rotor_drag_torque = np.sum(rotor_drag_ti, axis=0)\n \n rotor_roll_torque = - self.C_rot_roll * self.prop_ccw[:,None] * np.sqrt(self.thrust_cmds_damp)[:,None] * v_rotors #[4,3]\n rotor_roll_torque = np.sum(rotor_roll_torque, axis=0)\n rotor_visc_torque = rotor_drag_torque + rotor_roll_torque\n\n ## Constraints (prevent numerical instabilities)\n vel_norm = np.linalg.norm(vel_body)\n rdf_norm = np.linalg.norm(rotor_drag_force)\n rdf_norm_clip = np.clip(rdf_norm, a_min=0., a_max=vel_norm*self.mass/(2*dt))\n if rdf_norm > EPS:\n rotor_drag_force = (rotor_drag_force / rdf_norm) * rdf_norm_clip\n\n # omega_norm = np.linalg.norm(self.omega)\n rvt_norm = np.linalg.norm(rotor_visc_torque)\n rvt_norm_clipped = np.clip(rvt_norm, a_min=0., a_max=np.linalg.norm(self.omega*self.inertia)/(2*dt))\n if rvt_norm > EPS:\n rotor_visc_torque = (rotor_visc_torque / rvt_norm) * rvt_norm_clipped\n\n # print(\"v\", self.vel, \"\\nomega:\\n\",self.omega, \"\\nv_rotors:\\n\", v_rotors, \"\\nrotor_drag_fi:\\n\", rotor_drag_fi)\n # if rvt_norm_clipped/rvt_norm < 1 or rdf_norm_clip/rdf_norm < 1:\n # print(\"Clip:\", rvt_norm_clipped/rvt_norm, rdf_norm_clip/rdf_norm)\n # print(\"---------------------------------------------------------------\")\n else:\n rotor_visc_torque = rotor_drag_torque = rotor_drag_force = rotor_roll_torque = np.zeros(3)\n\n ###################################\n ## (Square) Damping using torques (in case we would like to add damping using torques)\n # damping_torque = - 0.3 * self.omega * np.fabs(self.omega)\n torque = thrust_torque + rotor_visc_torque\n thrust = npa(0,0,np.sum(thrusts))\n\n #########################################################\n ## ROTATIONAL DYNAMICS\n\n\n ###################################\n ## Integrating rotations (based on current values)\n omega_vec = np.matmul(self.rot, self.omega) # Change from body2world frame\n wx, wy, wz = omega_vec\n omega_norm = np.linalg.norm(omega_vec)\n if omega_norm != 0:\n # See [7]\n K = np.array([[0, -wz, wy], [wz, 0, -wx], [-wy, wx, 0]]) / omega_norm\n rot_angle = omega_norm * dt\n dRdt = self.eye + np.sin(rot_angle) * K + (1. - np.cos(rot_angle)) * (K @ K)\n self.rot = dRdt @ self.rot\n\n self.since_last_svd += dt\n if self.since_last_svd > self.since_last_svd_limit:\n ## Perform SVD orthogonolization\n # try:\n u, s, v = np.linalg.svd(self.rot)\n self.rot = np.matmul(u, v)\n self.since_last_svd = 0\n\n ###################################\n ## COMPUTING OMEGA UPDATE\n\n ## Damping using velocities (I find it more stable numerically)\n ## Linear damping\n\n # This is only for linear damping of angular velocity.\n # omega_damp = 0.999 \n # self.omega = omega_damp * self.omega + dt * omega_dot\n\n omega_dot = ((1.0 / self.inertia) *\n (cross(-self.omega, self.inertia * self.omega) + torque))\n\n ## Quadratic damping\n # 0.03 corresponds to roughly 1 revolution per sec\n omega_damp_quadratic = np.clip(self.damp_omega_quadratic * self.omega ** 2, a_min=0.0, a_max=1.0)\n self.omega = self.omega + (1.0 - omega_damp_quadratic) * dt * omega_dot\n self.omega = np.clip(self.omega, a_min=-self.omega_max, a_max=self.omega_max)\n\n ## When use square damping on torques - use simple integration\n ## since damping is accounted as part of the net torque\n # self.omega += dt * omega_dot\n\n #########################################################\n # TRANSLATIONAL DYNAMICS\n\n ## Room constraints\n mask = np.logical_or(self.pos <= self.room_box[0], self.pos >= self.room_box[1])\n \n ## Computing position\n self.pos = self.pos + dt * self.vel\n\n # Clipping if met the obstacle and nullify velocities (not sure what to do about accelerations)\n self.pos_before_clip = self.pos.copy()\n self.pos = np.clip(self.pos, a_min=self.room_box[0], a_max=self.room_box[1])\n # self.vel[np.equal(self.pos, self.pos_before_clip)] = 0.\n\n ## Computing accelerations\n acc = [0, 0, -GRAV] + (1.0 / self.mass) * np.matmul(self.rot, (thrust + rotor_drag_force))\n # acc[mask] = 0. #If we leave the room - stop accelerating\n self.acc = acc\n\n ## Computing velocities\n self.vel = (1.0 - self.vel_damp) * self.vel + dt * acc\n # self.vel[mask] = 0. #If we leave the room - stop flying\n\n ## Accelerometer measures so called \"proper acceleration\" \n # that includes gravity with the opposite sign\n self.accelerometer = np.matmul(self.rot.T, acc + [0, 0, self.gravity])\n\n def reset(self):\n self.thrust_cmds_damp = np.zeros([4])\n self.thrust_rot_damp = np.zeros([4])\n\n def rotors_drag_roll_glob_frame(self):\n # omega [3,] x prop_pos [4,3] = v_rot_body [4, 3]\n # R[3,3] @ prop_pos.T[3,4] = v_rotors[3,4] \n v_rotors = self.vel + self.rot @ np.cross(self.omega, self.model.prop_pos).T\n rot_z = self.rot[:,2]\n\n # [3,4] = [3,4] - ([3,4].T @ [3,1]).T * [3,4]\n v_rotors_perp = v_rotors - (v_rotors.T @ rot_z).T * np.repeat(rot_z,4, axis=1)\n\n # Drag/Roll of rotors\n rotor_drag = - self.C_rot_drag * np.sqrt(self.thrust_cmds_damp) * v_rotors_perp #[3,4]\n rotor_roll_torque = self.C_rot_roll * np.sqrt(self.thrust_cmds_damp) * v_rotors_perp #[3,4]\n\n\n #######################################################\n ## AFFINE DYNAMICS REPRESENTATION:\n # s = dt*(F(s) + G(s)*u)\n \n ## Unforced dynamics (integrator, damping_deceleration)\n def F(self, s, dt):\n xyz = s[0:3]\n Vxyz = s[3:6]\n rot = s[6:15].reshape([3,3])\n omega = s[15:18]\n goal = s[18:21]\n\n ###############################\n ## Linear position change\n dx = deepcopy(Vxyz)\n\n ###############################\n ## Linear velocity change\n dV = ((1.0 - self.vel_damp) * Vxyz - Vxyz) / dt + np.array([0, 0, -GRAV])\n\n ###############################\n ## Angular orientation change\n omega_vec = np.matmul(rot, omega) # Change from body2world frame\n wx, wy, wz = omega_vec\n omega_mat_deriv = np.array([[0, -wz, wy], [wz, 0, -wx], [-wy, wx, 0]])\n\n # ROtation matrix derivative\n dR = np.matmul(omega_mat_deriv, rot).flatten()\n\n ###############################\n ## Angular rate change\n F_omega = (1.0 / self.inertia) * (cross(-omega, self.inertia * omega))\n omega_damp_quadratic = np.clip(self.damp_omega_quadratic * omega ** 2, a_min=0.0, a_max=1.0)\n dOmega = (1.0 - omega_damp_quadratic) * F_omega\n\n ###############################\n ## Goal change\n dgoal = np.zeros_like(goal)\n\n return np.concatenate([dx, dV, dR, dOmega, dgoal])\n\n\n ## Forced affine dynamics (controlling acceleration only)\n def G(self, s):\n xyz = s[0:3]\n Vxyz = s[3:6]\n rot = s[6:15].reshape([3,3])\n omega = s[15:18]\n goal = s[18:21]\n\n ###############################\n ## dx, dV, dR, dgoal\n dx = np.zeros([3,4])\n dV = (rot / self.mass ) @ (self.thrust_max * self.thrust_sum_mx)\n dR = np.zeros([9,4])\n dgoal = np.zeros([3,4])\n \n ###############################\n ## Angular acceleration\n omega_damp_quadratic = np.clip(self.damp_omega_quadratic * omega ** 2, a_min=0.0, a_max=1.0)\n dOmega = (1.0 - omega_damp_quadratic)[:,None] * self.G_omega\n \n return np.concatenate([dx, dV, dR, dOmega, dgoal], axis=0) @ self.control_mx\n\n\n # return eye, center, up suitable for gluLookAt representing onboard camera\n def look_at(self):\n degrees_down = 45.0\n R = self.rot\n # camera slightly below COM\n eye = self.pos + np.matmul(R, [0, 0, -0.02])\n theta = np.radians(degrees_down)\n to, _ = normalize(np.cos(theta) * R[:,0] - np.sin(theta) * R[:,2])\n center = eye + to\n up = cross(to, R[:,1])\n return eye, center, up\n\n def state_vector(self):\n return np.concatenate([\n self.pos, self.vel, self.rot.flatten(), self.omega])\n\n def action_space(self):\n low = np.zeros(4)\n high = np.ones(4)\n return spaces.Box(low, high, dtype=np.float32)\n\n\n# reasonable reward function for hovering at a goal and not flying too high\ndef compute_reward_weighted(dynamics, goal, action, dt, crashed, time_remain, rew_coeff, action_prev):\n ##################################################\n ## log to create a sharp peak at the goal\n dist = np.linalg.norm(goal - dynamics.pos)\n loss_pos = rew_coeff[\"pos\"] * (rew_coeff[\"pos_log_weight\"] * np.log(dist + rew_coeff[\"pos_offset\"]) + rew_coeff[\"pos_linear_weight\"] * dist)\n # loss_pos = dist\n\n # dynamics_pos = dynamics.pos\n # print('dynamics.pos', dynamics.pos)\n\n ##################################################\n ## penalize altitude above this threshold\n # max_alt = 6.0\n # loss_alt = np.exp(2*(dynamics.pos[2] - max_alt))\n\n ##################################################\n # penalize amount of control effort\n loss_effort = rew_coeff[\"effort\"] * np.linalg.norm(action)\n dact = action - action_prev\n loss_act_change = rew_coeff[\"action_change\"] * (dact[0]**2 + dact[1]**2 + dact[2]**2 + dact[3]**2)**0.5\n\n ##################################################\n ## loss velocity\n # dx = goal - dynamics.pos\n # dx = dx / (np.linalg.norm(dx) + EPS)\n \n ## normalized \n # vel_direct = dynamics.vel / (np.linalg.norm(dynamics.vel) + EPS)\n # vel_magn = np.clip(np.linalg.norm(dynamics.vel),-1, 1)\n # vel_clipped = vel_magn * vel_direct \n # vel_proj = np.dot(dx, vel_clipped)\n # loss_vel_proj = - rew_coeff[\"vel_proj\"] * dist * vel_proj\n\n # loss_vel_proj = 0. \n loss_vel = rew_coeff[\"vel\"] * np.linalg.norm(dynamics.vel)\n\n ##################################################\n ## Loss orientation\n loss_orient = -rew_coeff[\"orient\"] * dynamics.rot[2,2] \n loss_yaw = -rew_coeff[\"yaw\"] * dynamics.rot[0,0]\n # Projection of the z-body axis to z-world axis\n # Negative, because the larger the projection the smaller the loss (i.e. the higher the reward)\n rot_cos = ((dynamics.rot[0,0] + dynamics.rot[1,1] + dynamics.rot[2,2]) - 1.)/2.\n #We have to clip since rotation matrix falls out of orthogonalization from time to time\n loss_rotation = rew_coeff[\"rot\"] * np.arccos(np.clip(rot_cos, -1.,1.)) #angle = arccos((trR-1)/2) See: [6]\n loss_attitude = rew_coeff[\"attitude\"] * np.arccos(np.clip(dynamics.rot[2,2], -1.,1.))\n\n ##################################################\n ## Loss for constant uncontrolled rotation around vertical axis\n # loss_spin_z = rew_coeff[\"spin_z\"] * abs(dynamics.omega[2])\n # loss_spin_xy = rew_coeff[\"spin_xy\"] * np.linalg.norm(dynamics.omega[:2])\n # loss_spin = rew_coeff[\"spin\"] * np.linalg.norm(dynamics.omega) \n loss_spin = rew_coeff[\"spin\"] * (dynamics.omega[0]**2 + dynamics.omega[1]**2 + dynamics.omega[2]**2)**0.5 \n\n ##################################################\n ## loss crash\n loss_crash = rew_coeff[\"crash\"] * float(crashed)\n\n # reward = -dt * np.sum([loss_pos, loss_effort, loss_alt, loss_vel_proj, loss_crash])\n # rew_info = {'rew_crash': -loss_crash, 'rew_altitude': -loss_alt, 'rew_action': -loss_effort, 'rew_pos': -loss_pos, 'rew_vel_proj': -loss_vel_proj}\n\n reward = -dt * np.sum([\n loss_pos, \n loss_effort, \n loss_crash, \n loss_orient,\n loss_yaw,\n loss_rotation,\n loss_attitude,\n loss_spin,\n # loss_spin_z,\n # loss_spin_xy,\n loss_act_change,\n loss_vel\n ])\n \n\n rew_info = {\n \"rew_main\": -loss_pos,\n 'rew_pos': -loss_pos, \n 'rew_action': -loss_effort, \n 'rew_crash': -loss_crash, \n \"rew_orient\": -loss_orient,\n \"rew_yaw\": -loss_yaw,\n \"rew_rot\": -loss_rotation,\n \"rew_attitude\": -loss_attitude,\n \"rew_spin\": -loss_spin,\n # \"rew_spin_z\": -loss_spin_z,\n # \"rew_spin_xy\": -loss_spin_xy,\n # \"rew_act_change\": -loss_act_change,\n \"rew_vel\": -loss_vel\n }\n\n # print('reward: ', reward, ' pos:', dynamics.pos, ' action', action)\n # print('pos', dynamics.pos)\n if np.isnan(reward) or not np.isfinite(reward):\n for key, value in locals().items():\n print('%s: %s \\n' % (key, str(value)))\n raise ValueError('QuadEnv: reward is Nan')\n\n return reward, rew_info\n\n\n####################################################################################################################################################################\n## ENV\n# Gym environment for quadrotor seeking the origin with no obstacles and full state observations.\n# NOTES:\n# - room size of the env and init state distribution are not the same !\n# It is done for the reason of having static (and preferably short) episode length, since for some distance it would be impossible to reach the goal\nclass QuadrotorEnv(gym.Env, Serializable):\n metadata = {\n 'render.modes': ['human', 'rgb_array'],\n 'video.frames_per_second' : 50\n }\n\n def __init__(self, dynamics_params=\"defaultquad\", dynamics_change=None, \n dynamics_randomize_every=None, dynamics_randomization_ratio=0., dynamics_randomization_ratio_params=None,\n raw_control=True, raw_control_zero_middle=True, dim_mode='3D', tf_control=False, sim_freq=200., sim_steps=2,\n obs_repr=\"xyz_vxyz_rot_omega\", ep_time=4, obstacles_num=0, room_size=10, init_random_state=False, \n rew_coeff=None, sense_noise=None, verbose=False, gravity=GRAV, resample_goal=False):\n np.seterr(under='ignore')\n \"\"\"\n Args:\n dynamics_params: [str or dict] loading dynamics params by name or by providing a dictionary. \n If \"random\": dynamics will be randomized completely (see sample_dyn_parameters() )\n If dynamics_randomize_every is None: it will be randomized only once at the beginning.\n One can randomize dynamics during the end of any episode using resample_dynamics()\n WARNING: randomization during an episode is not supported yet. Randomize ONLY before calling reset().\n dynamics_change: [dict] update to dynamics parameters relative to dynamics_params provided\n dynamics_randomize_every: [int] how often (trajectories) perform randomization\n dynamics_randomization_ratio: [float] randomization ratio relative to the nominal values of parameters\n dynamics_randomization_ratio_params: [dict] if a few dyn params require custom randomization ratios - provide them in this dict\n raw_control: [bool] use raw cantrol or the Mellinger controller as a default\n raw_control_zero_middle: [bool] meaning that control will be [-1 .. 1] rather than [0 .. 1]\n dim_mode: [str] Dimensionality of the env. Options: 1D(just a vertical stabilization), 2D(vertical plane), 3D(normal)\n tf_control: [bool] creates Mellinger controller using TensorFlow\n sim_freq (float): frequency of simulation\n sim_steps: [int] how many simulation steps for each control step\n obs_repr: [str] options: xyz_vxyz_rot_omega, xyz_vxyz_quat_omega\n ep_time: [float] episode time in simulated seconds. This parameter is used to compute env max time length in steps.\n obstacles_num: [int] number of obstacle in the env\n room_size: [int] env room size. Not the same as the initialization box to allow shorter episodes\n init_random_state: [bool] use random state initialization or horizontal initialization with 0 velocities\n rew_coeff: [dict] weights for different reward components (see compute_weighted_reward() function)\n sens_noise (dict or str): sensor noise parameters. If None - no noise. If \"default\" then the default params are loaded. Otherwise one can provide specific params.\n \"\"\"\n ## ARGS\n self.init_random_state = init_random_state\n self.room_size = room_size\n self.obs_repr = obs_repr\n self.sim_steps = sim_steps\n self.dim_mode = dim_mode\n self.raw_control_zero_middle = raw_control_zero_middle\n self.tf_control = tf_control\n self.dynamics_randomize_every = dynamics_randomize_every\n self.verbose = verbose\n self.obstacles_num = obstacles_num\n self.raw_control = raw_control\n self.scene = None\n self.update_sense_noise(sense_noise=sense_noise)\n self.gravity = gravity\n self.resample_goal = resample_goal\n \n ## PARAMS\n self.max_init_vel = 1. # m/s\n self.max_init_omega = 2 * np.pi #rad/s\n # self.pitch_max = 1. #rad\n # self.roll_max = 1. #rad\n # self.yaw_max = np.pi #rad\n\n self.room_box = np.array([[-self.room_size, -self.room_size, 0], [self.room_size, self.room_size, self.room_size]])\n self.state_vector = getattr(self, \"state_\" + self.obs_repr)\n ## WARN: If you\n # size of the box from which initial position will be randomly sampled\n # if box_scale > 1.0 then it will also growevery episode\n self.box = 2.0\n self.box_scale = 1.0 #scale the initialbox by this factor eache episode\n\n ## Statistics vars\n self.traj_count = 0\n\n ###############################################################################\n ## DYNAMICS (and randomization)\n if dynamics_params == \"random\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_dyn\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"random_with_linearity\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_with_linearity\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"random_t2w_15_25\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_thrust2weight_15_25\n self.dynamics_params = self.dyn_sampler() \n elif dynamics_params == \"random_t2w_15_35\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_thrust2weight_15_35\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"random_t2w_20_30\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_thrust2weight_20_30\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"random_t2w_20_40\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_thrust2weight_20_40\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"random_t2w_20_50\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_random_thrust2weight_20_50\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_18_25\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_18_25\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_15_25\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_15_25\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_15_35\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_15_35\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_20_30\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_20_30\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_20_40\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_20_40\n self.dynamics_params = self.dyn_sampler()\n elif dynamics_params == \"crazyflie_t2w_20_50\":\n self.dynamics_params_def = None\n self.dyn_sampler = sample_crazyflie_thrust2weight_20_50\n self.dynamics_params = self.dyn_sampler()\n else:\n ## Setting the quad dynamics params\n if isinstance(dynamics_params, str):\n self.dynamics_params_def = globals()[dynamics_params + \"_params\"]()\n elif isinstance(dynamics_params, dict):\n # This option is good when you only partially provide parameters of the model\n # For example if you are making some sort of a search, from the initial model\n self.dynamics_params_def = copy.deepcopy(dynamics_params)\n \n ## Now, updating if we are providing modifications\n if dynamics_change is not None:\n # self.dynamics_params_def.update(dynamics_change)\n dict_update_existing(self.dynamics_params_def, dynamics_change)\n\n ## Setting randomization params\n if self.dynamics_randomize_every is not None:\n self.dyn_randomization_params = get_dyn_randomization_params(\n quad_params=self.dynamics_params_def,\n noise_ratio=dynamics_randomization_ratio,\n noise_ratio_params=dynamics_randomization_ratio_params) \n if self.verbose:\n print(\"###############################################\")\n print(\"DYN RANDOMIZATION PARAMS:\")\n print_dic(self.dyn_randomization_params)\n print(\"###############################################\")\n self.dynamics_params = self.dynamics_params_def\n\n ## Updating dynamics\n dyn_upd_start_time = time.time()\n self.update_dynamics(dynamics_params=self.dynamics_params)\n print(\"QuadEnv: Dyn update time: \", time.time() - dyn_upd_start_time)\n\n ###############################################################################\n ## OBSERVATIONS\n self.observation_space = self.get_observation_space()\n\n ################################################################################\n ## DIMENSIONALITY\n if self.dim_mode =='1D':\n self.viewpoint = 'side'\n else:\n self.viewpoint = 'chase'\n\n ################################################################################\n ## EPISODE PARAMS\n # TODO get this from a wrapper\n self.ep_time = ep_time #In seconds\n self.dt = 1.0 / sim_freq\n self.metadata[\"video.frames_per_second\"] = sim_freq / self.sim_steps\n self.ep_len = int(self.ep_time / (self.dt * self.sim_steps))\n self.tick = 0\n self.crashed = False\n self.control_freq = sim_freq / sim_steps\n\n #########################################\n ## REWARDS PARAMS\n self.rew_coeff = {\n \"pos\": 1., \"pos_offset\": 0.1, \"pos_log_weight\": 1., \"pos_linear_weight\": 0.1,\n \"effort\": 0.01, \n \"action_change\": 0.,\n \"crash\": 1., \n \"orient\": 1., \"yaw\": 0., \"rot\": 0., \"attitude\": 0.,\n # \"spin_z\": 0.5, \"spin_xy\": 0.5,\n \"spin\": 0.,\n \"vel\": 0.}\n rew_coeff_orig = copy.deepcopy(self.rew_coeff)\n\n if rew_coeff is not None: \n assert isinstance(rew_coeff, dict)\n assert set(rew_coeff.keys()).issubset(set(self.rew_coeff.keys()))\n self.rew_coeff.update(rew_coeff)\n for key in self.rew_coeff.keys():\n self.rew_coeff[key] = float(self.rew_coeff[key])\n \n orig_keys = list(rew_coeff_orig.keys())\n # Checking to make sure we didn't provide some false rew_coeffs (for example by misspelling one of the params)\n assert np.all([key in orig_keys for key in self.rew_coeff.keys()])\n # print(\"rew_coeff:\", self.rew_coeff)\n\n #########################################\n ## RESET\n self._seed()\n self._reset()\n\n if self.spec is None:\n self.spec = gym_reg.EnvSpec(id='Quadrotor-v0', max_episode_steps=self.ep_len)\n \n # Always call Serializable constructor last\n Serializable.quick_init(self, locals())\n\n def save_dyn_params(self, filename):\n import yaml\n with open(filename, 'w') as yaml_file:\n def numpy_convert(key, item):\n return str(item)\n self.dynamics_params_converted = copy.deepcopy(self.dynamics_params)\n walk_dict(self.dynamics_params_converted, numpy_convert)\n yaml_file.write(yaml.dump(self.dynamics_params_converted, default_flow_style=False))\n\n def update_sense_noise(self, sense_noise):\n if isinstance(sense_noise, dict):\n self.sense_noise = SensorNoise(**sense_noise)\n elif isinstance(sense_noise, str):\n if sense_noise == \"default\":\n self.sense_noise = SensorNoise(bypass=False)\n else:\n ValueError(\"ERROR: QuadEnv: sense_noise parameter is of unknown type: \" + str(sense_noise))\n elif sense_noise is None:\n self.sense_noise = SensorNoise(bypass=True)\n else:\n raise ValueError(\"ERROR: QuadEnv: sense_noise parameter is of unknown type: \" + str(sense_noise))\n\n\n def update_dynamics(self, dynamics_params):\n ################################################################################\n ## DYNAMICS\n ## Then loading the dynamics\n self.dynamics_params = dynamics_params\n self.dynamics = QuadrotorDynamics(model_params=dynamics_params, \n dynamics_steps_num=self.sim_steps, room_box=self.room_box, dim_mode=self.dim_mode,\n gravity=self.gravity)\n \n if self.verbose:\n print(\"#################################################\")\n print(\"Dynamics params loaded:\")\n print_dic(dynamics_params)\n print(\"#################################################\")\n\n ################################################################################\n ## SCENE\n if self.obstacles_num > 0:\n self.obstacles = _random_obstacles(None, obstacles_num, self.room_size, self.dynamics.arm)\n else:\n self.obstacles = None\n\n ################################################################################\n ## CONTROL\n if self.raw_control:\n if self.dim_mode == '1D': # Z axis only\n self.controller = VerticalControl(self.dynamics, zero_action_middle=self.raw_control_zero_middle)\n elif self.dim_mode == '2D': # X and Z axes only\n self.controller = VertPlaneControl(self.dynamics, zero_action_middle=self.raw_control_zero_middle)\n elif self.dim_mode == '3D':\n self.controller = RawControl(self.dynamics, zero_action_middle=self.raw_control_zero_middle)\n else:\n raise ValueError('QuadEnv: Unknown dimensionality mode %s' % self.dim_mode)\n else:\n self.controller = NonlinearPositionController(self.dynamics, tf_control=self.tf_control)\n\n ################################################################################\n ## ACTIONS\n self.action_space = self.controller.action_space(self.dynamics)\n\n ################################################################################\n ## STATE VECTOR FUNCTION\n self.state_vector = getattr(self, \"state_\" + self.obs_repr)\n\n ## NOTE: the state_* methods are static because otherwise getattr memorizes self\n @staticmethod\n def state_xyz_vxyz_rot_omega(self): \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n # return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, (pos[2],)])\n return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega])\n\n @staticmethod\n def state_xyz_vxyz_rot_omega_h(self): \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, (pos[2],)])\n # return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega])\n\n @staticmethod\n def state_xyzr_vxyzr_rot_omega(self):\n \"\"\"\n xyz and Vxyz are given in a body frame\n \"\"\" \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n e_xyz_rel = self.dynamics.rot.T @ (pos - self.goal[:3])\n vel_rel = self.dynamics.rot.T @ vel\n return np.concatenate([e_xyz_rel, vel_rel, rot.flatten(), omega])\n\n @staticmethod\n def state_xyzr_vxyzr_rot_omega_h(self):\n \"\"\"\n xyz and Vxyz are given in a body frame\n \"\"\" \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n e_xyz_rel = self.dynamics.rot.T @ (pos - self.goal[:3])\n vel_rel = self.dynamics.rot.T @ vel\n return np.concatenate([e_xyz_rel, vel_rel, rot.flatten(), omega, (pos[2],)])\n\n @staticmethod\n def state_xyz_vxyz_rot_omega_acc_act(self): \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n # return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, (pos[2],)])\n return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, acc, self.actions[1]])\n\n @staticmethod\n def state_xyz_vxyz_rot_omega_act(self): \n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n # return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, (pos[2],)])\n return np.concatenate([pos - self.goal[:3], vel, rot.flatten(), omega, self.actions[1]])\n\n @staticmethod\n def state_xyz_vxyz_quat_omega(self):\n self.quat = R2quat(self.dynamics.rot)\n pos, vel, quat, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.quat,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n return np.concatenate([pos - self.goal[:3], vel, quat, omega])\n\n @staticmethod\n def state_xyzr_vxyzr_quat_omega(self):\n \"\"\"\n xyz and Vxyz are given in a body frame\n \"\"\" \n self.quat = R2quat(self.dynamics.rot)\n pos, vel, quat, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.quat,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n e_xyz_rel = self.dynamics.rot.T @ (pos - self.goal[:3])\n vel_rel = self.dynamics.rot.T @ vel\n return np.concatenate([e_xyz_rel, vel_rel, quat, omega])\n\n @staticmethod\n def state_xyzr_vxyzr_quat_omega_h(self):\n \"\"\"\n xyz and Vxyz are given in a body frame\n \"\"\" \n self.quat = R2quat(self.dynamics.rot)\n pos, vel, quat, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.quat,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n e_xyz_rel = self.dynamics.rot.T @ (pos - self.goal[:3])\n vel_rel = self.dynamics.rot.T @ vel\n return np.concatenate([e_xyz_rel, vel_rel, quat, omega, (pos[2],)])\n\n @staticmethod\n def state_xyz_vxyz_euler_omega(self):\n self.euler = t3d.euler.mat2euler(self.dynamics.rot)\n pos, vel, quat, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.euler,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n ) \n return np.concatenate([pos - self.goal[:3], vel, euler, omega])\n\n def get_observation_space(self):\n self.wall_offset = 0.3\n if self.obs_repr == \"xyz_vxyz_rot_omega\" or self.obs_repr == \"xyzr_vxyzr_rot_omega\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 9, 3]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"R\", \"Omega\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n \n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # R\n # indx range: 6:15\n\n # Omega\n obs_high[15:18] = self.dynamics.omega_max * obs_high[15:18]\n obs_low[15:18] = self.dynamics.omega_max * obs_low[15:18] \n\n # z - distance to ground\n # obs_high[-1] = self.room_box[1][2] \n # obs_low[-1] = self.room_box[0][2]\n\n # # xyz room constraints\n # obs_high[18:21] = self.room_box[1] - self.wall_offset\n # obs_low[18:21] = self.room_box[0] + self.wall_offset\n\n elif self.obs_repr == \"xyz_vxyz_rot_omega_h\" or self.obs_repr == \"xyzr_vxyzr_rot_omega_h\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 9, 3, 1]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"R\", \"Omega\", \"h\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n \n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # R\n # indx range: 6:15\n\n # Omega\n obs_high[15:18] = self.dynamics.omega_max * obs_high[15:18]\n obs_low[15:18] = self.dynamics.omega_max * obs_low[15:18] \n\n # h - distance to ground\n obs_high[-1] = self.room_box[1][2] \n obs_low[-1] = self.room_box[0][2]\n\n elif self.obs_repr == \"xyz_vxyz_rot_omega_acc_act\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 9, 3, 3, 4]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"R\", \"Omega\", \"Acc\", \"Act\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n \n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # R\n # indx range: 6:15\n\n # Omega\n obs_high[15:18] = self.dynamics.omega_max * obs_high[15:18]\n obs_low[15:18] = self.dynamics.omega_max * obs_low[15:18] \n \n # Acc\n obs_high[18:21] = self.dynamics.acc_max * obs_high[18:21]\n obs_low[18:21] = self.dynamics.acc_max * obs_low[18:21] \n\n # Action\n obs_high[21:25] = self.action_space.high\n obs_low[21:25] = self.action_space.low\n\n elif self.obs_repr == \"xyz_vxyz_rot_omega_act\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 9, 3, 4]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"R\", \"Omega\", \"Act\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n \n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # R\n # indx range: 6:15\n\n # Omega\n obs_high[15:18] = self.dynamics.omega_max * obs_high[15:18]\n obs_low[15:18] = self.dynamics.omega_max * obs_low[15:18] \n\n # Action\n obs_high[18:22] = self.action_space.high\n obs_low[18:22] = self.action_space.low\n\n elif self.obs_repr == \"xyz_vxyz_euler_omega\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 3, 3]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"euler\", \"Omega\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n \n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # Euler angles\n obs_high[6:9] = np.pi*obs_high[6:9] \n obs_low[6:9] = np.pi*obs_low[6:9]\n\n # Omega\n obs_high[9:12] = self.dynamics.omega_max * obs_high[9:12]\n obs_low[9:12] = self.dynamics.omega_max * obs_low[9:12] \n\n # z - distance to ground\n # obs_high[-1] = self.room_box[1][2] \n # obs_low[-1] = self.room_box[0][2] \n\n elif self.obs_repr == \"xyz_vxyz_quat_omega\" or self.obs_repr == \"xyzr_vxyzr_quat_omega\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 4, 3]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"quat\", \"Omega\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n\n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # Quat\n # indx range: 6:9\n\n # Omega\n obs_high[9:12] = self.dynamics.omega_max * obs_high[9:12]\n obs_low[9:12] = self.dynamics.omega_max * obs_low[9:12] \n\n # z - distance to ground\n # obs_high[-1] = self.room_box[1][2] \n # obs_low[-1] = self.room_box[0][2] \n\n elif self.obs_repr == \"xyzr_vxyzr_quat_omega_h\":\n ## Creating observation space\n # pos, vel, rot, rot vel\n self.obs_comp_sizes = [3, 3, 4, 3, 1]\n self.obs_comp_names = [\"xyz\", \"Vxyz\", \"quat\", \"Omega\", \"h\"]\n obs_dim = np.sum(self.obs_comp_sizes)\n obs_high = np.ones(obs_dim)\n obs_low = -np.ones(obs_dim)\n\n # xyz room constraints\n obs_high[0:3] = self.room_box[1] - self.room_box[0] #i.e. full room size\n obs_low[0:3] = -obs_high[0:3]\n\n # Vxyz\n obs_high[3:6] = self.dynamics.vxyz_max * obs_high[3:6]\n obs_low[3:6] = self.dynamics.vxyz_max * obs_low[3:6] \n\n # Quat\n # indx range: 6:9\n\n # Omega\n obs_high[9:12] = self.dynamics.omega_max * obs_high[9:12]\n obs_low[9:12] = self.dynamics.omega_max * obs_low[9:12] \n\n # h - distance to ground\n obs_high[-1] = self.room_box[1][2] \n obs_low[-1] = self.room_box[0][2] \n\n\n\n self.observation_space = spaces.Box(obs_low, obs_high, dtype=np.float32)\n return self.observation_space\n\n def _seed(self, seed=None):\n self.np_random, seed = seeding.np_random(seed)\n return [seed]\n\n def _step(self, action):\n self.actions[1] = copy.deepcopy(self.actions[0])\n self.actions[0] = copy.deepcopy(action)\n # print('actions_norm: ', np.linalg.norm(self.actions[0]-self.actions[1]))\n\n pos, vel, rot, omega, acc = self.sense_noise.add_noise(\n pos=self.dynamics.pos,\n vel=self.dynamics.vel,\n rot=self.dynamics.rot,\n omega=self.dynamics.omega,\n acc=self.dynamics.accelerometer,\n dt=self.dt\n )\n # print(\"accelerations:\", self.dynamics.accelerometer, \"noise_raio:\", np.abs(self.dynamics.accelerometer-acc)/np.abs(self.dynamics.accelerometer))\n\n # if not self.crashed:\n # print('goal: ', self.goal, 'goal_type: ', type(self.goal))\n self.controller.step_func(dynamics=self.dynamics,\n action=action,\n goal=self.goal,\n dt=self.dt,\n observation=np.expand_dims(self.state_vector(self), axis=0))\n # self.oracle.step(self.dynamics, self.goal, self.dt)\n # self.scene.update_state(self.dynamics, self.goal)\n\n if self.obstacles is not None:\n self.crashed = self.obstacles.detect_collision(self.dynamics)\n else:\n self.crashed = self.dynamics.pos[2] <= self.dynamics.arm\n self.crashed = self.crashed or not np.array_equal(self.dynamics.pos,\n np.clip(self.dynamics.pos,\n a_min=self.room_box[0],\n a_max=self.room_box[1]))\n\n self.time_remain = self.ep_len - self.tick\n reward, rew_info = compute_reward_weighted(self.dynamics, self.goal, action, self.dt, self.crashed, self.time_remain, \n rew_coeff=self.rew_coeff, action_prev=self.actions[1])\n self.tick += 1\n done = self.tick > self.ep_len #or self.crashed\n sv = self.state_vector(self)\n\n self.traj_count += int(done)\n # print('state', sv, 'goal', self.goal)\n # print('state', sv)\n # print('vel', sv[3], sv[4], sv[5])\n # print(sv, reward, done, rew_info)\n return sv, reward, done, {'rewards': rew_info}\n\n def resample_dynamics(self):\n \"\"\"\n Allows manual dynamics resampling when needed.\n WARNING: \n - Randomization dyring an episode is not supported\n - MUST call reset() after this function\n \"\"\"\n if self.dynamics_params_def is None:\n self.dynamics_params = self.dyn_sampler()\n else:\n ## Generating new params\n self.dynamics_params = perturb_dyn_parameters(\n params=copy.deepcopy(self.dynamics_params_def), \n noise_params=self.dyn_randomization_params\n )\n ## Updating params\n self.update_dynamics(dynamics_params=self.dynamics_params)\n\n\n def _reset(self):\n ## I have to update state vector \n ##############################################################\n ## DYNAMICS RANDOMIZATION AND UPDATE \n if self.dynamics_randomize_every is not None and \\\n (self.traj_count + 1) % (self.dynamics_randomize_every) == 0:\n \n self.resample_dynamics()\n\n ##############################################################\n ## VISUALIZATION\n if self.scene is None:\n self.scene = Quadrotor3DScene(model=self.dynamics.model,\n w=640, h=480, resizable=True, obstacles=self.obstacles, viewpoint=self.viewpoint)\n else:\n self.scene.update_model(self.dynamics.model)\n\n ##############################################################\n ## GOAL\n if self.resample_goal:\n self.goal = np.array([0., 0., np.random.uniform(0.5, 2.0)])\n else:\n self.goal = np.array([0., 0., 2.])\n\n ## CURRICULUM (NOT REALLY NEEDED ANYMORE)\n # from 0.5 to 10 after 100k episodes (a form of curriculum)\n if self.box < 10:\n self.box = self.box * self.box_scale\n x, y, z = self.np_random.uniform(-self.box, self.box, size=(3,)) + self.goal\n \n if self.dim_mode == '1D':\n x, y = self.goal[0], self.goal[1]\n elif self.dim_mode == '2D':\n y = self.goal[1]\n #Since being near the groud means crash we have to start above\n if z < 0.25 : z = 0.25 \n pos = npa(x, y, z)\n\n ##############################################################\n ## INIT STATE\n ## Initializing rotation and velocities\n if self.init_random_state:\n if self.dim_mode == '1D':\n omega, rotation = npa(0, 0, 0), np.eye(3)\n vel = np.array([0., 0., self.max_init_vel * np.random.rand()])\n elif self.dim_mode == '2D':\n omega = npa(0, self.max_init_omega * np.random.rand(), 0)\n vel = self.max_init_vel * np.random.rand(3)\n vel[1] = 0.\n c, s, theta = np.cos(theta), np.sin(theta), np.pi * np.random.rand()\n rotation = np.array(((c, 0., -s), (0., 1., 0.), (s, 0., c)))\n else:\n # It already sets the state internally\n _, vel, rotation, omega = self.dynamics.random_state(box=self.room_size, vel_max=self.max_init_vel, omega_max=self.max_init_omega)\n # _, vel, rotation, omega = self.dynamics.pitch_roll_restricted_random_state(\n # box=self.room_size, \n # vel_max=self.max_init_vel, \n # omega_max=self.max_init_omega,\n # pitch_max=self.pitch_max,\n # roll_max=self.roll_max,\n # yaw_max=self.yaw_max)\n else:\n ## INIT HORIZONTALLY WITH 0 VEL and OMEGA\n vel, omega = npa(0, 0, 0), npa(0, 0, 0)\n\n if self.dim_mode == '1D' or self.dim_mode == '2D':\n rotation = np.eye(3)\n else:\n # make sure we're sort of pointing towards goal (for mellinger controller)\n rotation = randyaw()\n while np.dot(rotation[:,0], to_xyhat(-pos)) < 0.5:\n rotation = randyaw()\n \n # Setting the generated state\n # print(\"QuadEnv: init: pos/vel/rot/omega:\", pos, vel, rotation, omega)\n self.init_state = [pos, vel, rotation, omega]\n self.dynamics.set_state(pos, vel, rotation, omega)\n self.dynamics.reset()\n\n # Resetting scene to reflect the state we have just set in dynamics\n self.scene.reset(self.goal, self.dynamics)\n # self.scene.update_state(self.dynamics)\n\n # Reseting some internal state (counters, etc)\n self.crashed = False\n self.tick = 0\n self.actions = [np.zeros([4,]), np.zeros([4,])]\n\n state = self.state_vector(self)\n return state\n\n def _render(self, mode='human', close=False):\n return self.scene.render_chase(dynamics=self.dynamics, goal=self.goal, mode=mode)\n \n def reset(self):\n return self._reset()\n\n def render(self, mode='human', **kwargs):\n return self._render(mode, **kwargs)\n \n def step(self, action):\n return self._step(action)\n\nclass DummyPolicy(object):\n def __init__(self, dt=0.01, switch_time=2.5):\n self.action = np.zeros([4,])\n self.dt = 0.\n \n def step(self, x):\n return self.action\n def reset(self):\n pass\n\nclass UpDownPolicy(object):\n def __init__(self, dt=0.01, switch_time=2.5):\n self.t = 0\n self.dt=dt\n self.switch_time = switch_time\n self.action_up = np.ones([4,])\n self.action_up[:2] = 0.\n self.action_down = np.zeros([4,])\n self.action_down[:2] = 1.\n \n def step(self, x):\n self.t += self.dt\n if self.t < self.switch_time:\n return self.action_up\n else:\n return self.action_down\n def reset(self):\n self.t = 0.\n\ndef test_rollout(quad, dyn_randomize_every=None, dyn_randomization_ratio=None, \n render=True, traj_num=10, plot_step=None, plot_dyn_change=True, plot_thrusts=False,\n sense_noise=None, policy_type=\"mellinger\", init_random_state=False, obs_repr=\"xyz_vxyz_rot_omega\",csv_filename=None):\n import tqdm\n #############################\n # Init plottting\n if plot_step is not None:\n fig = plt.figure(1)\n # ax = plt.subplot(111)\n plt.show(block=False)\n\n # render = True\n # plot_step = 50\n time_limit = 25\n render_each = 2\n rollouts_num = traj_num\n plot_obs = False\n\n if policy_type == \"mellinger\":\n raw_control=False\n raw_control_zero_middle=True\n policy = DummyPolicy() #since internal Mellinger takes care of the policy\n elif policy_type == \"updown\":\n raw_control=True\n raw_control_zero_middle=False\n policy = UpDownPolicy()\n\n\n env = QuadrotorEnv(dynamics_params=quad, raw_control=raw_control, raw_control_zero_middle=raw_control_zero_middle, \n dynamics_randomize_every=dyn_randomize_every, dynamics_randomization_ratio=dyn_randomization_ratio,\n sense_noise=sense_noise, init_random_state=init_random_state, obs_repr=obs_repr)\n\n\n policy.dt = 1./ env.control_freq\n\n env.max_episode_steps = time_limit\n print('Reseting env ...')\n\n try:\n print('Observation space:', env.observation_space.low, env.observation_space.high)\n print('Action space:', env.action_space.low, env.action_space.high)\n except:\n print('Observation space:', env.observation_space.spaces[0].low, env.observation_space[0].spaces[0].high)\n print('Action space:', env.action_space[0].spaces[0].low, env.action_space[0].spaces[0].high)\n # input('Press any key to continue ...')\n\n ## Collected statistics for dynamics\n dyn_param_names = [\n \"mass\",\n \"inertia\",\n \"thrust_to_weight\",\n \"torque_to_thrust\",\n \"thrust_noise_ratio\",\n \"vel_damp\",\n \"damp_omega_quadratic\"\n ]\n\n dyn_param_stats = [[] for i in dyn_param_names]\n\n action = np.array([0.0, 0.5, 0.0, 0.5])\n rollouts_id = 0\n\n start_time = time.time()\n # while rollouts_id < rollouts_num:\n for rollouts_id in tqdm.tqdm(range(rollouts_num)):\n rollouts_id += 1\n s = env.reset()\n policy.reset()\n ## Diagnostics\n observations = []\n velocities = []\n actions = []\n thrusts = []\n csv_data = []\n\n ## Collecting dynamics params\n if plot_dyn_change:\n for par_i, par in enumerate(dyn_param_names):\n dyn_param_stats[par_i].append(np.array(getattr(env.dynamics, par)).flatten())\n # print(par, dyn_param_stats[par_i][-1])\n\n t = 0\n while True:\n if render and (t % render_each == 0): env.render()\n action = policy.step(s)\n s, r, done, info = env.step(action)\n \n actions.append(action)\n thrusts.append(env.dynamics.thrust_cmds_damp)\n observations.append(s)\n # print('Step: ', t, ' Obs:', s)\n quat = R2quat(rot=s[6:15])\n csv_data.append(np.concatenate([np.array([1.0/env.control_freq * t]), s[0:3], quat]))\n\n if plot_step is not None and t % plot_step == 0:\n plt.clf()\n\n if plot_obs:\n observations_arr = np.array(observations)\n # print('observations array shape', observations_arr.shape)\n dimenstions = observations_arr.shape[1]\n for dim in range(dimenstions):\n plt.plot(observations_arr[:, dim])\n plt.legend([str(x) for x in range(observations_arr.shape[1])])\n\n plt.pause(0.05) #have to pause otherwise does not draw\n plt.draw()\n\n if done: break\n t += 1\n\n if plot_thrusts:\n plt.figure(3, figsize=(10, 10))\n ep_time = np.linspace(0, policy.dt * len(actions), len(actions))\n actions = np.array(actions)\n thrusts = np.array(thrusts)\n for i in range(4):\n plt.plot(ep_time, actions[:,i], label=\"Thrust desired %d\" % i)\n plt.plot(ep_time, thrusts[:,i], label=\"Thrust produced %d\" % i)\n plt.legend()\n plt.show(block=False)\n input(\"Press Enter to continue...\")\n \n if csv_filename is not None:\n import csv\n with open(csv_filename, mode=\"w\") as csv_file:\n csv_writer = csv.writer(csv_file, delimiter=',')\n for row in csv_data:\n csv_writer.writerow([i for i in row])\n\n\n if plot_dyn_change:\n dyn_par_normvar = []\n dyn_par_means = []\n dyn_par_var = []\n plt.figure(2, figsize=(10, 10))\n for par_i, par in enumerate(dyn_param_stats):\n plt.subplot(3, 3, par_i+1)\n par = np.array(par)\n\n ## Compute stats\n # print(dyn_param_names[par_i], par)\n dyn_par_means.append(np.mean(par, axis=0))\n dyn_par_var.append(np.std(par, axis=0))\n dyn_par_normvar.append(dyn_par_var[-1] / dyn_par_means[-1])\n\n if par.shape[1] > 1:\n for vi in range(par.shape[1]):\n plt.plot(par[:, vi])\n else:\n plt.plot(par)\n # plt.title(dyn_param_names[par_i] + \"\\n Normvar: %s\" % str(dyn_par_normvar[-1]))\n plt.title(dyn_param_names[par_i])\n print(dyn_param_names[par_i], \"NormVar: \", dyn_par_normvar[-1])\n \n print(\"##############################################################\")\n print(\"Total time: \", time.time() - start_time )\n\n # print('Rollouts are done!')\n # plt.pause(2.0)\n # plt.waitforbuttonpress()\n if plot_step is not None or plot_dyn_change:\n plt.show(block=False)\n input(\"Press Enter to continue...\")\n\ndef main(argv):\n # parser = argparse.ArgumentParser(formatter_class=argparse.RawTextHelpFormatter)\n parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\n '-m',\"--mode\",\n default=\"mellinger\",\n help=\"Test mode: \"\n \"mellinger - rollout with mellinger controller\"\n \"updown - rollout with UpDown controller (to test step responses)\"\n )\n parser.add_argument(\n '-q',\"--quad\",\n default=\"defaultquad\",\n help=\"Quadrotor model to use: \\n\" + \n \"- defaultquad \\n\" + \n \"- crazyflie \\n\" +\n \"- random\"\n )\n parser.add_argument(\n '-dre',\"--dyn_randomize_every\",\n type=int,\n help=\"How often (in terms of trajectories) to perform randomization\"\n )\n parser.add_argument(\n '-drr',\"--dyn_randomization_ratio\",\n type=float,\n default=0.5,\n help=\"Randomization ratio for random sampling of dynamics parameters\"\n )\n parser.add_argument(\n '-r',\"--render\",\n action=\"store_false\",\n help=\"Use this flag to turn off rendering\"\n )\n parser.add_argument(\n '-trj',\"--traj_num\",\n type=int,\n default=10,\n help=\"Number of trajectories to run\"\n )\n parser.add_argument(\n '-plt',\"--plot_step\",\n type=int,\n help=\"Plot step\"\n )\n parser.add_argument(\n '-pltdyn',\"--plot_dyn_change\",\n action=\"store_true\",\n help=\"Plot the dynamics change from trajectory to trajectory?\"\n )\n parser.add_argument(\n '-pltact',\"--plot_actions\",\n action=\"store_true\",\n help=\"Plot actions commanded and thrusts produced after damping\"\n )\n parser.add_argument(\n '-sn',\"--sense_noise\",\n action=\"store_false\",\n help=\"Add sensor noise? Use this flag to turn the noise off\"\n )\n parser.add_argument(\n '-irs',\"--init_random_state\",\n action=\"store_true\",\n help=\"Add sensor noise?\"\n )\n parser.add_argument(\n '-csv',\"--csv_filename\",\n help=\"Filename for qudrotor data\"\n )\n parser.add_argument(\n '-o',\"--obs_repr\",\n default=\"xyz_vxyz_rot_omega_acc_act\",\n help=\"State components. Options:\\n\" +\n \"xyz_vxyz_rot_omega\" +\n \"xyz_vxyz_rot_omega_act\" +\n \"xyz_vxyz_rot_omega_acc_act\" \n )\n args = parser.parse_args()\n\n if args.sense_noise:\n sense_noise=\"default\"\n else:\n sense_noise=None\n\n print('Running test rollout ...')\n test_rollout(\n quad=args.quad, \n dyn_randomize_every=args.dyn_randomize_every,\n dyn_randomization_ratio=args.dyn_randomization_ratio,\n render=args.render,\n traj_num=args.traj_num,\n plot_step=args.plot_step,\n plot_dyn_change=args.plot_dyn_change,\n plot_thrusts=args.plot_actions,\n sense_noise=sense_noise,\n policy_type=args.mode,\n init_random_state=args.init_random_state,\n obs_repr=args.obs_repr,\n csv_filename=args.csv_filename,\n )\n\nif __name__ == '__main__':\n main(sys.argv)\n"
},
{
"alpha_fraction": 0.5023102164268494,
"alphanum_fraction": 0.5455445647239685,
"avg_line_length": 29.918367385864258,
"blob_id": "d05c8bcfd3f8d6ffaeb0005bbe19ff7b1695fdf2",
"content_id": "ae24477a228fb62a93cc068586975845654c7da1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6062,
"license_type": "no_license",
"max_line_length": 122,
"num_lines": 196,
"path": "/quad_sim/quad_utils.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport numpy.random as nr\nfrom numpy.linalg import norm\nfrom copy import deepcopy\n\n# dict pretty printing\ndef print_dic(dic, indent=\"\"):\n for key, item in dic.items():\n if isinstance(item, dict):\n print(indent, key + \":\")\n print_dic(item, indent=indent+\" \")\n else:\n print(indent, key + \":\", item)\n\n# walk dictionary\ndef walk_dict(node, call):\n for key, item in node.items():\n if isinstance(item, dict):\n walk_dict(item, call)\n else:\n node[key] = call(key, item)\n\ndef walk_2dict(node1, node2, call):\n for key, item in node1.items():\n if isinstance(item, dict):\n walk_2dict(item, node2[key], call)\n else:\n node1[key], node2[key] = call(key, item, node2[key])\n\n# numpy's cross is really slow for some reason\ndef cross(a, b):\n return np.array([a[1]*b[2] - a[2]*b[1], a[2]*b[0] - a[0]*b[2], a[0]*b[1] - a[1]*b[0]])\n\n# returns (normalized vector, original norm)\ndef normalize(x):\n n = norm(x)\n if n < 0.00001:\n return x, 0\n return x / n, n\n\ndef norm2(x):\n return np.sum(x ** 2)\n\n# uniformly sample from the set of all 3D rotation matrices\ndef rand_uniform_rot3d():\n randunit = lambda: normalize(np.random.normal(size=(3,)))[0]\n up = randunit()\n fwd = randunit()\n while np.dot(fwd, up) > 0.95:\n fwd = randunit()\n left, _ = normalize(cross(up, fwd))\n # import pdb; pdb.set_trace()\n up = cross(fwd, left)\n rot = np.column_stack([fwd, left, up])\n return rot\n\n# shorter way to construct a numpy array\ndef npa(*args):\n return np.array(args)\n\ndef clamp_norm(x, maxnorm):\n n = np.linalg.norm(x)\n return x if n <= maxnorm else (maxnorm / n) * x\n\n# project a vector into the x-y plane and normalize it.\ndef to_xyhat(vec):\n v = deepcopy(vec)\n v[2] = 0\n v, _ = normalize(v)\n return v\n\ndef log_error(err_str, ):\n with open(\"/tmp/sac/errors.txt\", \"a\") as myfile:\n myfile.write(err_str)\n # myfile.write('###############################################')\n\n\ndef quat2R(qw, qx, qy, qz):\n R = \\\n [[1.0 - 2*qy**2 - 2*qz**2, 2*qx*qy - 2*qz*qw, 2*qx*qz + 2*qy*qw],\n [ 2*qx*qy + 2*qz*qw, 1.0 - 2*qx**2 - 2*qz**2, 2*qy*qz - 2*qx*qw],\n [ 2*qx*qz - 2*qy*qw, 2*qy*qz + 2*qx*qw, 1.0 - 2*qx**2 - 2*qy**2]]\n return np.array(R)\n\ndef qwxyz2R(quat):\n return quat2R(qw=quat[0], qx=quat[1], qy=quat[2], qz=quat[3])\n\ndef quatXquat(quat, quat_theta):\n ## quat * quat_theta\n noisy_quat = np.zeros(4)\n noisy_quat[0] = quat[0] * quat_theta[0] - quat[1] * quat_theta[1] - quat[2] * quat_theta[2] - quat[3] * quat_theta[3] \n noisy_quat[1] = quat[0] * quat_theta[1] + quat[1] * quat_theta[0] - quat[2] * quat_theta[3] + quat[3] * quat_theta[2] \n noisy_quat[2] = quat[0] * quat_theta[2] + quat[1] * quat_theta[3] + quat[2] * quat_theta[0] - quat[3] * quat_theta[1] \n noisy_quat[3] = quat[0] * quat_theta[3] - quat[1] * quat_theta[2] + quat[2] * quat_theta[1] + quat[3] * quat_theta[0]\n return noisy_quat\n\ndef R2quat(rot):\n # print('R2quat: ', rot, type(rot))\n R = rot.reshape([3,3])\n w = np.sqrt(1.0 + R[0,0] + R[1,1] + R[2,2]) / 2.0\n w4 = (4.0 * w)\n x = (R[2,1] - R[1,2]) / w4\n y = (R[0,2] - R[2,0]) / w4\n z = (R[1,0] - R[0,1]) / w4\n return np.array([w,x,y,z])\n\ndef rot2D(theta):\n c = np.cos(theta)\n s = np.sin(theta)\n return np.array([[c, -s], [s, c]])\n\ndef rotZ(theta):\n r = np.eye(4)\n r[:2,:2] = rot2D(theta)\n return r\n\ndef randyaw():\n rotz = np.random.uniform(-np.pi, np.pi)\n return rotZ(rotz)[:3,:3]\n\ndef exUxe(e,U):\n \"\"\"\n Cross product approximation\n exUxe = U - (U @ e) * e, where\n Args:\n e[3,1] - norm vector (assumes the same norm vector for all vectors in the batch U)\n U[3,batch_dim] - set of vectors to perform cross product on\n Returns:\n [3,batch_dim] - batch-wise cross product approximation\n \"\"\"\n return U - (U.T @ rot_z).T * np.repeat(rot_z, U.shape[1], axis=1)\n\ndef cross_vec(v1,v2):\n return np.array([[0, -v1[2], v1[1]], [v1[2], 0, -v1[0]], [-v1[1], v1[0], 0]]) @ v2\n\ndef cross_mx4(V1,V2):\n x1 = cross(V1[0,:],V2[0,:])\n x2 = cross(V1[1,:],V2[1,:])\n x3 = cross(V1[2,:],V2[2,:])\n x4 = cross(V1[3,:],V2[3,:])\n return np.array([x1,x2,x3,x4])\n\ndef cross_vec_mx4(V1,V2):\n x1 = cross(V1,V2[0,:])\n x2 = cross(V1,V2[1,:])\n x3 = cross(V1,V2[2,:])\n x4 = cross(V1,V2[3,:])\n return np.array([x1,x2,x3,x4])\n\ndef dict_update_existing(dic, dic_upd):\n for key in dic_upd.keys():\n if isinstance(dic[key], dict):\n dict_update_existing(dic[key], dic_upd[key])\n else:\n dic[key] = dic_upd[key]\n\nclass OUNoise:\n \"\"\"Ornstein–Uhlenbeck process\"\"\"\n def __init__(self, action_dimension, mu=0, theta=0.15, sigma=0.3):\n \"\"\"\n @param: mu: mean of noise\n @param: theta: stabilization coeff (i.e. noise return to mean)\n @param: sigma: noise scale coeff\n \"\"\"\n self.action_dimension = action_dimension\n self.mu = mu\n self.theta = theta\n self.sigma = sigma\n self.state = np.ones(self.action_dimension) * self.mu\n self.reset()\n\n def reset(self):\n self.state = np.ones(self.action_dimension) * self.mu\n\n def noise(self):\n x = self.state\n dx = self.theta * (self.mu - x) + self.sigma * nr.randn(len(x))\n self.state = x + dx\n return self.state\n\n\nif __name__ == \"__main__\":\n ## Cross product test\n import time\n rot_z = np.array([[3],[4],[5]])\n rot_z = rot_z / np.linalg.norm(rot_z)\n v_rotors = np.array([[1,2,3,4],[5,6,7,8],[9,8,7,6]])\n\n start_time = time.time()\n cr1_ = v_rotors - (v_rotors.T @ rot_z).T * np.repeat(rot_z,4, axis=1)\n print(\"cr1 time:\", time.time() - start_time)\n\n start_time = time.time()\n cr2 = np.cross(rot_z.T, np.cross(v_rotors.T, np.repeat(rot_z,4, axis=1).T)).T\n print(\"cr2 time:\", time.time() - start_time)\n print(\"cr1 == cr2:\", np.sum(cr1 - cr2) < 1e-10)\n"
},
{
"alpha_fraction": 0.5365168452262878,
"alphanum_fraction": 0.5432584285736084,
"avg_line_length": 31.381818771362305,
"blob_id": "36a4faca54f5dad217cf097b6d02c4ec8e2affa2",
"content_id": "3263c83472f70de643c6c4d53b00a8813dff94e3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1780,
"license_type": "no_license",
"max_line_length": 85,
"num_lines": 55,
"path": "/quad_train/misc/play_pkl.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nimport argparse\nimport json\nimport os.path as osp\nimport sys\nimport time\nimport numpy as np\n\nimport joblib\nimport tensorflow as tf\n\n\ndef play(pkl_file, n_rollout=20, rollout_length=200):\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n\n # Unpack the snapshot\n snapshot = joblib.load(pkl_file)\n print(\"Snapshot content: \", snapshot)\n env = snapshot[\"env\"]\n policy = snapshot[\"policy\"]\n\n sim_time_vec = []\n\n # Rollout\n for _ in range(n_rollout):\n sim_time = 0\n obs = env.reset()\n for _ in range(rollout_length):\n sim_time += 1\n env.render()\n action, _ = policy.get_action(obs)\n print(\"action:\", action)\n obs, _, done, _ = env.step(action)\n if done:\n print(\"Sim time: \", sim_time)\n sim_time_vec.append(sim_time)\n break\n # Report\n print(\"################################################\")\n print(\"Avg sime time: \", np.mean(sim_time_vec))\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(description='Play a pickled policy.')\n parser.add_argument('pkl_file', metavar='pkl_file', type=str,\n help='.pkl file containing the policy')\n parser.add_argument('--n_rollout', metavar='n_rollout', type=int,\n help='Number of rollouts.', default=20)\n parser.add_argument(\"-l\",'--rollout_length', metavar='rollout_length', type=int,\n help='The length of each rollout.', default=200)\n args = parser.parse_args()\n\n play(args.pkl_file, n_rollout=args.n_rollout, rollout_length=args.rollout_length)"
},
{
"alpha_fraction": 0.5225780010223389,
"alphanum_fraction": 0.5320196747779846,
"avg_line_length": 29.078189849853516,
"blob_id": "08e7f783126096a0d8bc40aa8c6cfef808c8a01f",
"content_id": "19760f77c5d7e54ffc651ca5031677db320ecfc6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7308,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 243,
"path": "/quad_train/plot_tools/plot_csvs.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport pandas as pd\nfrom time import sleep\nfrom matplotlib import pyplot as plt\nimport argparse\nimport os\n\ndef read_graph_names(fname):\n with open(fname) as f:\n content = f.readlines()\n return [x.strip() for x in content]\n\ndef main():\n parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)\n parser.add_argument(\"filename\", nargs='*', help='Names of the csv files')\n parser.add_argument(\"--legend\", \"-l\", nargs='*', help='Short names for the legend (must be as many as num of files provided)')\n parser.add_argument(\"--time\", \"-t\", type=float, default=10, help='Sleep period')\n parser.add_argument(\"--graphs\", \"-g\", nargs='*', help='Graphs to plot')\n args = parser.parse_args()\n\n sleep_period = 10\n\n # MaxReturn,LossAfter,\n # BNN_DynModelSqLossAfter,\n # BNN_DynModelSqLossBefore,\n # AverageReturn,\n # Expl_MaxKL,\n # Iteration,\n # AverageDiscountedReturn,\n # MinReturn,\n # Expl_MinKL,\n # dLoss,Entropy,\n # AveragePolicyStd,\n # StdReturn,\n # Perplexity,\n # MeanKL,\n # ExplainedVariance,\n # Expl_MeanKL,\n # NumTrajs,\n # Expl_StdKL\n # namelist = ['LossAfter',\n # 'BNN_DynModelSqLossAfter',\n # 'AverageReturn',\n # 'AverageDiscountedReturn',\n # 'Entropy',\n # 'Perplexity',\n # 'MeanKL',\n # 'Expl_MeanKL',\n # 'Expl_StdKL']\n\n # hide_rew_action\n # hide_rew_digit_entropy\n # hide_rew_digit_correct\n # seek_accuracy\n # seek_ep_len\n # seek_rew_digit_correct\n # seek_rew_digit_entropy\n # seek_digit_entropy\n # hide_RewAvg_Main\n # hide_AverageDiscountedReturn\n # hide_AverageReturn\n # hide_ExplainedVariance\n # hide_NumTrajs\n # hide_Entropy\n # hide_Perplexity\n # hide_StdReturn\n # hide_MaxReturn\n # hide_MinReturn\n # seek_RewAvg_Main\n # seek_AverageDiscountedReturn\n # seek_AverageReturn\n # seek_ExplainedVariance\n # seek_NumTrajs\n # seek_Entropy\n # seek_Perplexity\n # seek_StdReturn\n # seek_MaxReturn\n # seek_MinReturn\n # seek_vf_LossBefore\n # seek_vf_LossAfter\n # seek_vf_dLoss\n # AveragePolicyStd\n # AveragePolicyStd\n # hide_LossAfter\n # hide_MeanKL\n # hide_dLoss\n # seek_LossAfter\n # seek_MeanKL\n # seek_dLoss\n\n\n # hide_ep_len\n # hide_rew_action\n # hide_rew_digit_entropy\n # hide_rew_digit_correct\n # seek_accuracy\n # seek_ep_len\n # seek_rew_digit_correct\n # seek_rew_digit_entropy\n # seek_digit_entropy\n # hide_AverageReturn\n # hide_MaxReturn\n # seek_AverageReturn\n # seek_MaxReturn\n\n namelist = ['LossAfter',\n 'BNN_DynModelSqLossAfter',\n 'AverageReturn',\n 'Entropy',\n 'RewAvg_PredEntrChange',\n 'RewAvg_PredEntrGlobChange',\n 'RewAvg_Main',\n 'RewAvg_Dyn',\n 'RewAvg_PredEntr']\n\n # namelist = ['hide_ep_len',\n # 'seek_ep_len',\n # 'hide_AverageReturn',\n # 'seek_AverageReturn',\n # 'hide_rew_action',\n # 'hide_rew_digit_correct',\n # 'seek_rew_digit_entropy',\n # 'seek_digit_entropy',\n # 'seek_accuracy']\n\n # namelist = [\n # 'hide_ep_len',\n # 'hide_rew_seek_time',\n # 'hide_rew_action',\n # 'hide_rew_digit_entropy',\n # 'hide_rew_digit_correct',\n # 'hide_RewAvg_Main',\n # 'hide_AverageReturn',\n # 'seek_rew_digit_correct',\n # 'hide_MaxReturn'\n # ]\n\n namelist = [\n 'seek_ep_len',\n 'seek_AverageReturn',\n 'hide_rew_action',\n 'hide_rew_digit_correct_final',\n 'seek_rew_digit_entropy_final',\n 'seek_digit_entropy_final',\n 'seek_accuracy_final',\n 'seek_accuracy_samplewise',\n 'seek_rew_digit_correct_sum'\n ]\n\n if args.graphs is not None:\n namelist = args.graphs\n print('Graphs to plot = ', namelist)\n if len(namelist) < 9:\n diff = 9 - len(namelist)\n namelist.extend([namelist[-1]] * diff)\n\n fig = plt.figure(1)\n subplot_indx = -1\n cols = 3\n rows = 3\n figures = {}\n for col_i in range(0, cols):\n for row_i in range(0, rows):\n subplot_indx += 1\n name = namelist[subplot_indx]\n figures[name] = plt.subplot('%d%d%d' % (cols, rows, subplot_indx + 1))\n\n plt.ion()\n plt.show()\n\n colors_all = ['b', 'g', 'r', 'c', 'm', 'y', 'k', 'w']\n legend_lbl = args.legend\n if legend_lbl is None:\n legend_lbl = args.filename\n\n\n while True:\n lines = []\n file_i = -1\n for filename in args.filename:\n file_i+=1\n print('Plotting file = ', filename)\n\n if os.stat(filename).st_size == 0:\n print('File %s is empty. Skipping ...' % filename)\n sleep(2)\n break\n\n data = pd.read_csv(filename, sep=',')\n namelist_cur = data.dtypes.index\n data = data.as_matrix()\n # print 'data= ', data\n\n # print 'namelist = ', namelist_cur\n # namelist_cur = data[0,:]\n # data = data[1:,:]\n\n # namelist_cur = namelist\n names_num = len(namelist_cur)\n\n subplot_indx = -1\n name_indx = {}\n for n_i in range(0,names_num):\n name_indx[namelist_cur[n_i]] = n_i\n # print 'dtype = ', type(data)\n\n for col_i in range(0, cols):\n for row_i in range(0, rows):\n figures[name].clear()\n\n for col_i in range(0, cols):\n for row_i in range(0, rows):\n subplot_indx += 1\n name = namelist[subplot_indx]\n if name in name_indx:\n n_i = name_indx[name]\n line, = figures[name].plot(data[:, n_i], colors_all[file_i % len(colors_all)], label=legend_lbl[file_i])\n figures[name].set_title(name)\n\n lines.append(line)\n # self.axis[name_i].legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,\n # ncol=3, mode=\"expand\", borderaxespad=0.)\n # OBS: use this solution AFTER you use fig.set_size_inches() and BEFORE you use fig.tight_layout()\n plt.draw()\n # plt.legend(lines, legend_lbl, loc = 'upper center', bbox_to_anchor = (0.5, 0),\n # bbox_transform=plt.gcf().transFigure)\n # plt.legend(lines, legend_lbl, loc='lower center', bbox_to_anchor=(0, -0.1, 1, 1),\n # bbox_transform=plt.gcf().transFigure, ncol=2)\n # plt.figlegend(lines, legend_lbl, loc='upper center', bbox_to_anchor=(0.5, -0.05),\n # fancybox=True, shadow=True, ncol=1)\n # fig.legend(lines, legend_lbl, loc=(0.5, 0), ncol=1, bbox_to_anchor=(0, -0.1, 1, 1))\n plt.figlegend(lines, legend_lbl, loc='lower center', ncol=2, labelspacing=0.)\n # plt.show()\n plt.tight_layout()\n plt.pause(0.005)\n\n print('waiting for the next read ...')\n sleep(sleep_period)\n\n\n\nif __name__ == \"__main__\":\n main()"
},
{
"alpha_fraction": 0.5690721869468689,
"alphanum_fraction": 0.6164948344230652,
"avg_line_length": 22.100000381469727,
"blob_id": "1b9698cb50e7671b20f39817c342afca71b44b13",
"content_id": "0aeb3ad9af5f571f97ed633bdcfc11005cc03fe7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4850,
"license_type": "no_license",
"max_line_length": 80,
"num_lines": 210,
"path": "/quad_gen/code_blocks.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nheaders_controller_nn = \"\"\"\n#include \"math3d.h\"\n#include \"stabilizer_types.h\"\n#include <math.h>\n#include \"controller_nn.h\"\n\n\"\"\"\n\nheaders_network_evaluate = \"\"\"\n#include \"network_evaluate.h\"\n\n\"\"\"\n\nconstants = \"\"\"\n\n#define MAX_THRUST 0.1597\n// PWM to thrust coefficients\n#define A 2.130295e-11\n#define B 1.032633e-6\n#define C 5.484560e-4\n\n\"\"\"\n\ncontroller_init_function = \"\"\"\n\nvoid controllerNNInit(void) {}\n\n\"\"\"\n\ncontroller_test_function = \"\"\"\n\nbool controllerNNTest(void) {\n\treturn true;\n}\n\n\"\"\"\n\nlinear_activation = \"\"\"\n\nfloat linear(float num) {\n\treturn num;\n}\n\n\"\"\"\n\nsigmoid_activation = \"\"\"\n\nfloat sigmoid(float num) {\n\treturn 1 / (1 + exp(-num));\n}\n\n\"\"\"\n\nrelu_activation = \"\"\"\n\nfloat relu(float num) {\n\tif (num > 0) {\n\t\treturn num;\n\t} else {\n\t\treturn 0;\n\t}\n}\n\n\"\"\"\n\nscaling = \"\"\"\n// range of action -1 ... 1, need to scale to range 0 .. 1\nfloat scale(float v) {\n\treturn 0.5f * (v + 1);\n}\n\n\"\"\"\n\nclipping = \"\"\"\n\nfloat clip(float v, float min, float max) {\n\tif (v < min) return min;\n\tif (v > max) return max;\n\treturn v;\n}\n\n\"\"\"\n\ncontroller_entry = \"\"\"\nstatic control_t_n control_n;\nstatic struct mat33 rot;\nstatic float state_array[18];\n\nvoid controllerNN(control_t *control, \n\t\t\t\t setpoint_t *setpoint, \n\t\t\t\t const sensorData_t *sensors, \n\t\t\t\t const state_t *state, \n\t\t\t\t const uint32_t tick)\n{\n\tcontrol->enableDirectThrust = true;\n\tif (!RATE_DO_EXECUTE(RATE_250_HZ, tick)) {\n\t\treturn;\n\t}\n\n\t// Orientation\n\tstruct quat q = mkquat(state->attitudeQuaternion.x, \n\t\t\t\t\t\t state->attitudeQuaternion.y, \n\t\t\t\t\t\t state->attitudeQuaternion.z, \n\t\t\t\t\t\t state->attitudeQuaternion.w);\n\trot = quat2rotmat(q);\n\n\t// angular velocity\n\tfloat omega_roll = radians(sensors->gyro.x);\n\tfloat omega_pitch = radians(sensors->gyro.y);\n\tfloat omega_yaw = radians(sensors->gyro.z);\n\n\t// the state vector\n\tstate_array[0] = state->position.x - setpoint->position.x;\n\tstate_array[1] = state->position.y - setpoint->position.y;\n\tstate_array[2] = state->position.z - setpoint->position.z;\n\tstate_array[3] = state->velocity.x;\n\tstate_array[4] = state->velocity.y;\n\tstate_array[5] = state->velocity.z;\n\tstate_array[6] = rot.m[0][0];\n\tstate_array[7] = rot.m[0][1];\n\tstate_array[8] = rot.m[0][2];\n\tstate_array[9] = rot.m[1][0];\n\tstate_array[10] = rot.m[1][1];\n\tstate_array[11] = rot.m[1][2];\n\tstate_array[12] = rot.m[2][0];\n\tstate_array[13] = rot.m[2][1];\n\tstate_array[14] = rot.m[2][2];\n\tstate_array[15] = omega_roll;\n\tstate_array[16] = omega_pitch;\n\tstate_array[17] = omega_yaw;\n\tstate_array[18] = state->position.z;\n\n\n\t// run the neural neural network\n\tnetworkEvaluate(&control_n, state_array);\n\n\t// convert thrusts to directly to PWM\n\t// need to hack the firmware (stablizer.c and power_distribution_stock.c)\n\tint PWM_0, PWM_1, PWM_2, PWM_3; \n\tthrusts2PWM(&control_n, &PWM_0, &PWM_1, &PWM_2, &PWM_3);\n\n\tcontrol->motorRatios[0] = PWM_0;\n\tcontrol->motorRatios[1] = PWM_1;\n\tcontrol->motorRatios[2] = PWM_2;\n\tcontrol->motorRatios[3] = PWM_3;\n}\n\n\n/*\n * Crazyflie rotors positions (as opposed to what the neural network assumes): \n *\t\t\t\t\t\t\tx \n *\t\t\t\t\t\t\t|\n *\t\t\t\t\t\t3\t|\t0\n *\t\t\t\t (thrust 0)\t|\t(thrust 1)\n *\t\t\t\t y <---------------\n *\t\t\t\t\t \t\t|\n *\t\t\t\t\t \t2\t|\t1\n *\t\t\t (thrust 3) |\t(thrust 2)\n *\t(thrust projection must align with each motor, e.g thrust 1 is on rotor 0)\n */\nvoid thrusts2PWM(struct control_t_n *control_n, \n\tint *PWM_0, int *PWM_1, int *PWM_2, int *PWM_3){\n\n\t/*\n\t// scaling and cliping\n\tcontrol_n->thrust_0 = MAX_THRUST * clip(scale(control_n->thrust_0), 0.0, 1.0);\n\tcontrol_n->thrust_1 = MAX_THRUST * clip(scale(control_n->thrust_1), 0.0, 1.0);\n\tcontrol_n->thrust_2 = MAX_THRUST * clip(scale(control_n->thrust_2), 0.0, 1.0);\n\tcontrol_n->thrust_3 = MAX_THRUST * clip(scale(control_n->thrust_3), 0.0, 1.0);\n\n\t// motor 0\n\t*PWM_0 = (int)(-B + sqrt(B * B - 4 * A * (C - control_n->thrust_1))) / (2 * A);\n\t// motor 1\n\t*PWM_1 = (int)(-B + sqrt(B * B - 4 * A * (C - control_n->thrust_2))) / (2 * A);\n\t// motor 2\n\t*PWM_2 = (int)(-B + sqrt(B * B - 4 * A * (C - control_n->thrust_3))) / (2 * A);\n\t// motor 3 \n\t*PWM_3 = (int)(-B + sqrt(B * B - 4 * A * (C - control_n->thrust_0))) / (2 * A);\n\t*/\n\n\t// scaling and cliping\n\tcontrol_n->thrust_0 = UINT16_MAX * clip(scale(control_n->thrust_0), 0.0, 1.0);\n\tcontrol_n->thrust_1 = UINT16_MAX * clip(scale(control_n->thrust_1), 0.0, 1.0);\n\tcontrol_n->thrust_2 = UINT16_MAX * clip(scale(control_n->thrust_2), 0.0, 1.0);\n\tcontrol_n->thrust_3 = UINT16_MAX * clip(scale(control_n->thrust_3), 0.0, 1.0);\n\n\t// motor 0\n\t*PWM_0 = control_n->thrust_0;\n\t// motor 1\n\t*PWM_1 = control_n->thrust_1;\n\t// motor 2\n\t*PWM_2 = control_n->thrust_2;\n\t// motor 3 \n\t*PWM_3 = control_n->thrust_3;\n}\n\n\"\"\"\n\nlog_group = \"\"\"\n\nLOG_GROUP_START(ctrlNN)\nLOG_ADD(LOG_FLOAT, thrust0, &output_2[0])\nLOG_ADD(LOG_FLOAT, thrust1, &output_2[1])\nLOG_ADD(LOG_FLOAT, thrust2, &output_2[2])\nLOG_ADD(LOG_FLOAT, thrust3, &output_2[3])\nLOG_GROUP_STOP(ctrlNN)\n\n\"\"\""
},
{
"alpha_fraction": 0.5182651877403259,
"alphanum_fraction": 0.555086612701416,
"avg_line_length": 38.71676254272461,
"blob_id": "fca015adf00a3b29d1205145ccf6a1b70cf76fff",
"content_id": "908d9acb7477ad10a1e82c81f6e2281ee32a0ab5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6871,
"license_type": "no_license",
"max_line_length": 135,
"num_lines": 173,
"path": "/quad_sim/sensor_noise.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport numpy as np\nfrom numpy.random import normal \nfrom numpy.random import uniform\nimport matplotlib.pyplot as plt\nfrom math import exp\nfrom quad_sim.quad_utils import quat2R, quatXquat\n\ndef quat_from_small_angle(theta):\n assert theta.shape == (3,)\n\n q_squared = np.linalg.norm(theta)**2 / 4.0\n if q_squared < 1:\n q_theta = np.array([(1 - q_squared)**0.5, theta[0] * 0.5, theta[1] * 0.5, theta[2] * 0.5])\n else:\n w = 1.0 / (1 + q_squared)**0.5\n f = 0.5 * w\n q_theta = np.array([w, theta[0] * f, theta[1] * f, theta[2] * f])\n\n q_theta = q_theta / np.linalg.norm(q_theta)\n return q_theta\n\n'''\nhttp://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToQuaternion/\n'''\ndef rot2quat(rot):\n\tassert rot.shape == (3, 3)\n\n\ttrace = np.trace(rot)\n\tif trace > 0:\n\t\tS = (trace + 1.0)**0.5 * 2\n\t\tqw = 0.25 * S\n\t\tqx = (rot[2][1] - rot[1][2]) / S \n\t\tqy = (rot[0][2] - rot[2][0]) / S\n\t\tqz = (rot[1][0] - rot[0][1]) / S\n\telif rot[0][0] > rot[1][1] and rot[0][0] > rot[2][2]:\n\t\tS = (1.0 + rot[0][0] - rot[1][1] - rot[2][2])**0.5 * 2\n\t\tqw = (rot[2][1] - rot[1][2]) / S\n\t\tqx = 0.25 * S \n\t\tqy = (rot[0][1] + rot[1][0]) / S\n\t\tqz = (rot[0][2] + rot[2][0]) / S\n\telif rot[1][1] > rot[2][2]:\n\t\tS = (1.0 + rot[1][1] - rot[0][0] - rot[2][2])**0.5 * 2\n\t\tqw = (rot[0][2] - rot[2][0]) / S \n\t\tqx = (rot[0][1] + rot[1][0]) / S\n\t\tqy = 0.25 * S\n\t\tqz = (rot[1][2] + rot[2][1]) / S\n\telse:\n\t\tS = (1.0 + rot[2][2] - rot[0][0] - rot[1][1])**0.5 * 2\n\t\tqw = (rot[1][0] - rot[0][1]) / S\n\t\tqx = (rot[0][2] + rot[2][0]) / S \n\t\tqy = (rot[1][2] + rot[2][1]) / S\n\t\tqz = 0.25 * S\n\n\treturn np.array([qw, qx, qy, qz])\n\nclass SensorNoise:\n def __init__(self, pos_norm_std=0.005, pos_unif_range=0., \n vel_norm_std=0.01, vel_unif_range=0., \n quat_norm_std=0., quat_unif_range=0., \n gyro_noise_density=0.000175, gyro_random_walk=0.0105, \n gyro_bias_correlation_time=1000., bypass=False,\n acc_static_noise_std=0.002, acc_dynamic_noise_ratio=0.005): \n \"\"\"\n Args:\n pos_norm_std (float): std of pos gaus noise component\n pos_unif_range (float): range of pos unif noise component\n vel_norm_std (float): std of linear vel gaus noise component \n vel_unif_range (float): range of linear vel unif noise component\n quat_norm_std (float): std of rotational quaternion noisy angle gaus component\n quat_unif_range (float): range of rotational quaternion noisy angle gaus component\n gyro_gyro_noise_density: gyroscope noise, MPU-9250 spec\n gyro_random_walk: gyroscope noise, MPU-9250 spec\n gyro_bias_correlation_time: gyroscope noise, MPU-9250 spec\n # gyro_gyro_turn_on_bias_sigma: gyroscope noise, MPU-9250 spec (val 0.09)\n bypass: no noise\n \"\"\"\n\n self.pos_norm_std = pos_norm_std\n self.pos_unif_range = pos_unif_range\n\n self.vel_norm_std = vel_norm_std\n self.vel_unif_range = vel_unif_range\n\n self.quat_norm_std = quat_norm_std\n self.quat_unif_range = quat_unif_range\n\n self.gyro_noise_density = gyro_noise_density\n self.gyro_random_walk = gyro_random_walk\n self.gyro_bias_correlation_time = gyro_bias_correlation_time\n # self.gyro_turn_on_bias_sigma = gyro_turn_on_bias_sigma\n self.gyro_bias = np.zeros(3)\n\n self.acc_static_noise_std = acc_static_noise_std\n self.acc_dynamic_noise_ratio = acc_dynamic_noise_ratio\n\n self.bypass = bypass\n\n def add_noise(self, pos, vel, rot, omega, acc, dt):\n if self.bypass:\n return pos, vel, rot, omega, acc\n # \"\"\"\n # Args: \n # pos: ground truth of the position in world frame\n # vel: ground truth if the linear velocity in world frame\n # rot: ground truth of the orientation in rotational matrix / quaterions / euler angles\n # omega: ground truth of the angular velocity in body frame\n # dt: integration step\n # \"\"\"\n assert pos.shape == (3,)\n assert vel.shape == (3,)\n assert omega.shape == (3,)\n\n # add noise to position measurement\n noisy_pos = pos + \\\n normal(loc=0., scale=self.pos_norm_std, size=3) + \\\n uniform(low=-self.pos_unif_range, high=self.pos_unif_range, size=3)\n\n\n # add noise to linear velocity\n noisy_vel = vel + \\\n normal(loc=0., scale=self.vel_norm_std, size=3) + \\\n uniform(low=-self.vel_unif_range, high=self.vel_unif_range, size=3)\n\n ## Noise in omega\n noisy_omega = self.add_noise_to_omega(omega, dt)\n\n ## Noise in rotation\n theta = normal(0, self.quat_norm_std, size=3) + \\\n uniform(-self.quat_unif_range, self.quat_unif_range, size=3)\n \n if rot.shape == (3,):\n ## Euler angles (xyz: roll=[-pi, pi], pitch=[-pi/2, pi/2], yaw = [-pi, pi])\n noisy_rot = np.clip(rot + theta, \n a_min=[-np.pi, -np.pi/2, -np.pi], \n a_max=[ np.pi, np.pi/2, np.pi])\n elif rot.shape == (3,3):\n ## Rotation matrix\n quat_theta = quat_from_small_angle(theta)\n quat = rot2quat(rot)\n noisy_quat = quatXquat(quat, quat_theta)\n noisy_rot = quat2R(noisy_quat[0], noisy_quat[1], noisy_quat[2], noisy_quat[3])\n elif rot.shape == (4,):\n ## Quaternion\n quat_theta = quat_from_small_angle(theta)\n noisy_rot = quatXquat(rot, quat_theta)\n else:\n raise ValueError(\"ERROR: SensNoise: Unknown rotation type: \" + str(rot))\n \n ## Accelerometer noise\n noisy_acc = acc + normal(loc=0., scale=self.acc_static_noise_std, size=3) + \\\n acc * normal(loc=0., scale=self.acc_dynamic_noise_ratio, size=3)\n\n return noisy_pos, noisy_vel, noisy_rot, noisy_omega, noisy_acc\n\n ## copy from rotorS imu plugin\n def add_noise_to_omega(self, omega, dt):\n assert omega.shape == (3,)\n\n sigma_g_d = self.gyro_noise_density / (dt**0.5)\n sigma_b_g_d = (-(sigma_g_d**2) * (self.gyro_bias_correlation_time / 2) * (exp(-2*dt/self.gyro_bias_correlation_time) - 1))**0.5\n pi_g_d = exp(-dt / self.gyro_bias_correlation_time)\n\n self.gyro_bias = pi_g_d * self.gyro_bias + sigma_b_g_d * normal(0, 1, 3)\n return omega + self.gyro_bias + self.gyro_random_walk * normal(0, 1, 3) # + self.gyro_turn_on_bias_sigma * normal(0, 1, 3)\n\n\nif __name__ == \"__main__\":\n sens = SensorNoise()\n import time \n start_time = time.time()\n sens.add_noise(np.zeros(3), np.zeros(3), np.eye(3), np.zeros(3), 0.005)\n print(\"Noise generation time: \", time.time() - start_time)\n"
},
{
"alpha_fraction": 0.7247735857963562,
"alphanum_fraction": 0.7357380986213684,
"avg_line_length": 26.97333335876465,
"blob_id": "148cffcebf649c18955d28eefda75dea098950eb",
"content_id": "560ba5917809aeb4497ffb3c4a8590c7284affd4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 6293,
"license_type": "no_license",
"max_line_length": 265,
"num_lines": 225,
"path": "/README.md",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "# Sim-to-(Multi)-Real: Transfer of Low-Level Robust Control Policies to Multiple Quadrotors\n- Authors: [Artem Molchanov](https://amolchanov86.github.io/), [Tao Chen](https://taochenosu.github.io/), [Wolfgang Hönig](http://act.usc.edu/group.html), [James A. Preiss](http://jpreiss.github.io/), [Nora Ayanian](https://viterbi-web.usc.edu/~ayanian/), [Gaurav S. Sukhatme](http://robotics.usc.edu/~gaurav/)\n- Paper Link: [ArXiv](https://arxiv.org/abs/1903.04628)\n- Project site: [Google Site](https://sites.google.com/view/sim-to-multi-quad)\n\n<!-- - If you use our work in academic research, please cite us:) -->\n\n\n## Dependencies\n\n- [Garage](https://github.com/rlworkgroup/garage/)\n\n## Installation\n\n### Step 0\n\nCreate directory for all projects:\n\n```sh\nmkdir ~/sim2multireal\ncd ~/sim2multireal\n```\n\nInstead of `~/sim2multireal` you could use any directory you like. It is given just as an example.\n\n### Step 1\n\nPull [garage](https://github.com/rlworkgroup/garage/).\n\n```sh\ngit clone https://github.com/rlworkgroup/garage/\n```\n\nCheckout the following commit:\n\n```sh\ncd garage\ngit checkout 77714c38d5b575a5cfd6d1e42f0a045eebbe3484\n```\n\nFollow the garage [setup instructions](http://rlgarage.readthedocs.io/en/latest/user/installation.html) given below.\n\nThe setup requires a MuJoCo key, but since we are not using MuJoCo you can generate a placeholder keyfile.\n\n```sh\ntouch mjkey.txt\necho \"hello\" >> mjkey.txt\n```\n\nOn linux:\n\n```sh\n./scripts/setup_linux.sh --mjkey mjkey.txt --modify-bashrc\n```\n\nOn macOS:\n\n```sh\n./scripts/setup_macos.sh --mjkey mjkey.txt --modify-bashrc\n```\n\n### Step 2\n\nClone this repository:\n\n```sh\ncd ~/sim2multireal\ngit clone https://github.com/amolchanov86/quad_sim2multireal.git\ncd quad_sim2multireal\n```\n\n### Step 3\n\nInstall additional dependencies\n\nOn linux:\n\n```sh\nbash install_depend_linux.sh\n```\n\nOn macOS:\n\n```sh\nbash install_depend_macos.sh\n```\n\n### Step 4\n\nCreate a new conda environment:\n\n```sh\nconda env create -f conda_env.yml\n```\n\n## Preparing to run experiements\n\n### General\n\nEach time before running experiments make sure to -\n\n- Activate the conda environment for the experiment\n- Add all repos in your `$PYTHONPATH`\n\n```sh\nconda activate quad_s2r\n\nexport PYTHONPATH=$PYTHONPATH:~/sim2multireal/garage\nexport PYTHONPATH=$PYTHONPATH:~/sim2multireal/quad_sim2multireal\n```\n\n## Experiments\n\nFirst, go to the root folder:\n\n```sh\ncd ~/sim2multireal/quad_sim2multireal/quad_train\n```\n\n### Training\n\n#### Train Quadrotor to stabilize at the origin with random initialization and 5 seeds (you need many seeds since some will fail)\n\n```sh\nbash ./launchers/ppo_crazyflie_baseline.sh\n```\n\n#### Train Quadrotor to stabilize at the origin with random initialization and a default seed (may fail)\n\n```sh\npython ./train_quad.py config/ppo__crazyflie_baseline.yml _results_temp/ppo_crazyflie_baseline/seed_001\n```\n\n### Monitoring\n\n#### Use `tensorborad` to monitor the training progress\n\n```sh\ntensorboard --logdir ./_results_temp\n```\n\n#### To use a specific port\n\n```sh\ntensorboard --logdir ./_results_temp --port port_num\n```\n\n### Plotting\n\n`plot_tools` library allows nice plotting of statistics.\nIt assumes that the training results are organized as following: `_results_temp/experiment_folder/seed_{X}/progress.csv` , where:\n\n- `_results_temp`: is the folder containing all experiments and runs.\n- `experiment_folder`: is the folder containing an experiment (that could be run with one or multiple seeds).\n They typically named as `param1_paramval1__param2_paramval2`, etc. I.e. they reflect the key parameters and their values in the run.\n- `seed_{X}`: is the run folder, i.e. experiment with a particular seed wit value `{X}`\n\nThe plot_tools module contains:\n\n- `plot_tools.py`: the library containing all core functionality + it is also a script that can show results of a single experiment. Example:\n\n ```sh\n ./plot_tools/plot_tools experiment_folder\n ```\n\n- `plot_graphs_with_seeds.py`: a script to plot results with multiple seeds. Example:\n\n ```sh\n ./plot_tools/plot_graphs_with_seeds.py _results_temp\n ```\n\nLook into `--help` option for all the scripts mentioned above for more options.\n\n### Testing a newly trained model in simulation\n\n`test_controller.py` under `quad_gen` allows you test your fresh model in the simulation with some customizability to the environment. \n\nPlease use `test_controller.py -h` to see the options.\n\n### Generating source code for Crazyflie firmware\n\n`quad_gen` library allow fast generation of embedded source code for the Crazyflie firmware.\n\nOnce you have successfully trained a quadrotor stabilizing policy, you will get a pickle file `params.pkl` that is contained in a folder with other data that will be useful for analysis.\n\nIn this process, it also assumes the results are organized as following: `_results_temp/experiment_folder/seed_{X}/params.pkl`.\n\nFirst, go to `~/sim2multireal/quad_sim2multireal/quad_gen`\n\n```sh\ncd ~/sim2multireal/quad_sim2multireal/quad_gen\n```\n\n#### To generate source code for all training results\n\n```sh\npython ./get_models.py 2 _results_temp/ ./models/\n```\n\n`_results_temp/` may contain multiple experiments.\n\n#### To generate source code only for the best seeds\n\n```sh\npython ./get_models.py 1 _results_temp/ ./models/\n```\n\n`_results_temp/` may also contain multiple experiments.\n\n#### To generate source code for selected seeds\n\n```sh\npython ./get_models.py 0 _results_temp/ ./models/ -txt [dirs_file]\n```\n\nIn this case, the `-txt` option is required and allows you to specify relative path (to the `_results_temp/`) of the seeds you would like to generate the source code for. In general when selecting a seed, you will look at the plotting statistics or the tensorboard.\nIf you use tensorboard, we recommend to look at the position reward and the Gaussian policy variance.\n\nInstead of `./models/` you could use any directory you like. It is given just as an example.\nThe code for the NN baseline used on the paper is included in `models/` as an example.\n\n### Running on hardware\n\nTo run a train network on the Crazyflie hardware, please use a modified version of the Crazyswarm software: [quad_nn](https://github.com/TaoChenOSU/quad_nn)\nTo test your newly trained network, replace `network_evaluate.c` under `src/modules/src/` within `quad_nn_firmware` with the new `network_evaluate.c` generated from the previous step."
},
{
"alpha_fraction": 0.4901871383190155,
"alphanum_fraction": 0.5081393718719482,
"avg_line_length": 35.72625732421875,
"blob_id": "1f61b3fc22cadc178aa1aaa7c270d8b8743cf725",
"content_id": "b15d577b6ffca5cd7b2a8df1031e19f98d736821",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6573,
"license_type": "no_license",
"max_line_length": 122,
"num_lines": 179,
"path": "/quad_train/misc/play_pkl_quad.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n\nimport argparse\nimport json\nimport os.path as osp\nimport sys\nimport time\nimport numpy as np\n\nimport joblib\nimport tensorflow as tf\nimport transforms3d as t3d\n\n\ndef R2quat(rot):\n # print('R2quat: ', rot, type(rot))\n R = rot.reshape([3,3])\n w = np.sqrt(1.0 + R[0,0] + R[1,1] + R[2,2]) / 2.0\n w4 = (4.0 * w)\n x = (R[2,1] - R[1,2]) / w4\n y = (R[0,2] - R[2,0]) / w4\n z = (R[1,0] - R[0,1]) / w4\n return np.array([w,x,y,z])\n\ndef play(pkl_file, n_rollout=20, rollout_length=200, lowpass_coeff=0.9,\n obs_params=None, csv_filename=None, scale_down_inertia=1.0):\n\n with tf.Session() as sess:\n sess.run(tf.global_variables_initializer())\n\n # Unpack the snapshot\n snapshot = joblib.load(pkl_file)\n env = snapshot[\"env\"]\n policy = snapshot[\"policy\"]\n\n sim_time_vec = []\n\n # Observations\n obs_vec = []\n action_vec = []\n\n recording_time = 4.0\n inertia_scale = 1.0\n\n # Rollout\n for n in range(n_rollout):\n csv_data = []\n sim_time = 0\n time = 0\n\n print(\"Scale:\", 1.0/inertia_scale, \"Inertia: \", env.env.dynamics.inertia)\n print(\"T2W:\", env.env.dynamics.thrust_to_weight, \"goal:\", env.env.goal, \"sample_goal:\", env.env.resample_goal)\n policy.reset()\n obs = env.reset()\n for t in range(rollout_length):\n # print(\"obs:\", obs, \"shape: \", obs.shape)\n # print(\"obs:\", obs[:3])\n sim_time += 1\n time += 1./env.env.control_freq\n env.render()\n # obs = np.append(obs, 2. + obs[2])\n obs_vec.append(obs)\n action, action_components = policy.get_action(obs)\n action_vec.append(action_components[\"mean\"])\n if t == 0:\n action_lowpass = action\n else:\n action_lowpass = (1-lowpass_coeff) * action + lowpass_coeff * action_lowpass\n # print(\"action:\", action_lowpass)\n\n # quat = R2quat(rot=obs[6:15])\n if time > recording_time:\n quat = t3d.quaternions.mat2quat(obs[6:15])\n quat = np.array([quat[1], quat[2], quat[3], quat[0]])\n csv_data.append(np.concatenate([np.array([1.0/env.env.control_freq * t]), obs[0:3], quat]))\n\n obs, _, done, _ = env.step(action_components[\"mean\"])\n\n if done:\n print(\"Sim time: \", sim_time)\n sim_time_vec.append(sim_time)\n break\n \n if csv_filename is not None:\n import csv\n with open(csv_filename + \"_I_downscale_%.2f.csv\" % (1.0/inertia_scale), mode=\"w\") as csv_file:\n csv_writer = csv.writer(csv_file, delimiter=',')\n csv_writer.writerow([\"time\",\"x\",\"y\",\"z\", \"qx\",\"qy\",\"qz\",\"qw\"])\n for row in csv_data:\n csv_writer.writerow([i for i in row])\n # if n == 0:\n # env.env.dynamics.inertia = env.env.dynamics.inertia / 2.0\n # inertia_scale = 0.5\n # else:\n env.env.dynamics.inertia = env.env.dynamics.inertia * scale_down_inertia\n inertia_scale *= scale_down_inertia\n\n # Report\n print(\"################################################\")\n print(\"Avg sime time: \", np.mean(sim_time_vec))\n\n import matplotlib.pyplot as plt\n\n # import pdb; pdb.set_trace()\n if obs_params is not None:\n obs_sizes = [obs_params[key] for key in obs_params.keys()]\n obs_indices = np.cumsum(obs_sizes)\n obs_vec = np.split(np.array(obs_vec).T, obs_indices, axis=0)\n obs_ids_total = len(obs_params)\n obs_num = 0\n for obs_id in obs_params.keys():\n plt.subplot(obs_ids_total + 1, 1, obs_num+1)\n for obs_i in range(obs_vec[obs_num].shape[0]):\n plt.plot(obs_vec[obs_num][obs_i, :])\n plt.title(obs_id)\n obs_num += 1\n\n ## Actions\n plt.subplot(obs_ids_total + 1, 1, obs_num+1)\n action_vec = np.array(action_vec).T\n for act in range(action_vec.shape[0]):\n plt.plot(action_vec[act])\n plt.title(\"Actions\")\n else: \n ## Plotting actions\n plt.figure(2)\n action_vec = np.array(action_vec).T\n for act in range(action_vec.shape[0]):\n plt.plot(action_vec[act])\n plt.title(\"Actions\")\n plt.legend(list(range(action_vec.shape[0])))\n \n plt.show(block=False)\n input(\"Press ENter to continue ...\")\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser(description='Play a pickled policy.')\n parser.add_argument('pkl_file',\n type=str,\n help='.pkl file containing the policy')\n parser.add_argument(\"-n\",'--n_rollout',\n type=int,\n help='Number of rollouts.', default=20)\n parser.add_argument(\"-l\",'--rollout_length', \n type=int,\n help='The length of each rollout.', default=400)\n parser.add_argument(\"-obs\",'--obs_params', \n help='Observation components: name1,size1,,name2,size2 etc.', \n default=\"xyz,3,,Vxyz,3,,R,9,,Omega,3,,Z,1\")\n parser.add_argument(\"-pltobs\",'--plot_obs',\n help='Plot observations', \n action=\"store_true\")\n parser.add_argument(\"-lpc\",'--lowpass_coeff', \n help='Low pass coefficient for printing data',\n type=float,\n default=0.9)\n parser.add_argument(\"-is\",'--inertia_scale', \n help='How much to scale down inertia at each rollout',\n type=float,\n default=1.0)\n parser.add_argument(\n '-csv',\"--csv_filename\",\n help=\"Filename-base for qudrotor data\"\n )\n args = parser.parse_args()\n\n obs_params = [obs.split(\",\") for obs in args.obs_params.split(\",,\")]\n obs_params = dict([(obs[0], int(obs[1])) for obs in obs_params])\n if not args.plot_obs:\n obs_params = None\n\n play(args.pkl_file, \n n_rollout=args.n_rollout, \n rollout_length=args.rollout_length, \n obs_params=obs_params,\n lowpass_coeff=args.lowpass_coeff,\n csv_filename=args.csv_filename,\n scale_down_inertia=args.inertia_scale\n )"
},
{
"alpha_fraction": 0.5676867961883545,
"alphanum_fraction": 0.5731831192970276,
"avg_line_length": 40.050140380859375,
"blob_id": "1b54756d73668d64c267fb80733486a1c31b3bff",
"content_id": "2110ac5533a3b193b8f20bd931ab73740a55c65a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 14737,
"license_type": "no_license",
"max_line_length": 146,
"num_lines": 359,
"path": "/quad_train/algos/batch_polopt.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "import time\nimport h5py\nimport numbers\nimport inspect\nimport os, sys, atexit\nimport numpy as np\n\nimport tensorflow as tf\n\nfrom garage.algos import RLAlgorithm\nimport garage.misc.logger as logger\nfrom garage.tf.plotter import Plotter\nfrom garage.tf.samplers import BatchSampler\nfrom garage.tf.samplers import OnPolicyVectorizedSampler\n\nfrom quad_train.misc.dict2hdf5 import dict2h5 as h5u\nfrom quad_train.misc.video_recorder import VideoRecorder\n\n\nclass BatchPolopt(RLAlgorithm):\n \"\"\"\n Base class for batch sampling-based policy optimization methods.\n This includes various policy gradient methods like vpg, npg, ppo, trpo,\n etc.\n \"\"\"\n\n def __init__(self,\n env,\n policy,\n baseline,\n scope=None,\n n_itr=500,\n max_samples=None,\n start_itr=0,\n batch_size=5000,\n max_path_length=500,\n discount=0.99,\n gae_lambda=1,\n plot=False,\n pause_for_plot=False,\n center_adv=True,\n positive_adv=False,\n store_paths=False,\n paths_h5_filename=None,\n whole_paths=True,\n fixed_horizon=False,\n sampler_cls=None,\n sampler_args=None,\n force_batch_sampler=False,\n play_every_itr=None,\n record_every_itr=None,\n record_end_ep_num=3,\n **kwargs):\n \"\"\"\n :param env: Environment\n :param policy: Policy\n :type policy: Policy\n :param baseline: Baseline\n :param scope: Scope for identifying the algorithm. Must be specified if\n running multiple algorithms\n simultaneously, each using different environments and policies\n :param n_itr: Max umber of iterations.\n :param max_samples: If not None - exit when max env samples is collected (overrides n_itr)\n :param start_itr: Starting iteration.\n :param batch_size: Number of samples per iteration.\n :param max_path_length: Maximum length of a single rollout.\n :param discount: Discount.\n :param gae_lambda: Lambda used for generalized advantage estimation.\n :param plot: Plot evaluation run after each iteration.\n :param pause_for_plot: Whether to pause before contiuing when plotting.\n :param center_adv: Whether to rescale the advantages so that they have\n mean 0 and standard deviation 1.\n :param positive_adv: Whether to shift the advantages so that they are\n always positive. When used in conjunction with center_adv the\n advantages will be standardized before shifting.\n :param store_paths: Whether to save all paths data to the snapshot.\n :return:\n \"\"\"\n self.args = locals()\n del self.args[\"kwargs\"]\n del self.args[\"self\"]\n self.args = {**self.args, **kwargs} #merging dicts\n\n self.env = env\n try:\n self.env.env.save_dyn_params(filename=logger.get_snapshot_dir().rstrip(os.sep) + os.sep + \"dyn_params.yaml\")\n except:\n print(\"WARNING: BatchPolOpt: couldn't save dynamics params\")\n # import pdb; pdb.set_trace()\n from gym.wrappers import Monitor\n # self.env_rec = Monitor(self.env.env, logger.get_snapshot_dir() + os.sep + \"videos\", force=True)\n\n self.policy = policy\n self.baseline = baseline\n self.scope = scope\n self.n_itr = n_itr\n self.max_samples = max_samples\n self.start_itr = start_itr\n self.batch_size = batch_size\n self.max_path_length = max_path_length\n self.discount = discount\n self.gae_lambda = gae_lambda\n self.plot = plot\n self.pause_for_plot = pause_for_plot\n self.center_adv = center_adv\n self.positive_adv = positive_adv\n self.store_paths = store_paths\n self.whole_paths = whole_paths\n self.fixed_horizon = fixed_horizon\n self.play_every_itr = play_every_itr\n self.record_every_itr = record_every_itr\n self.record_end_ep_num = record_end_ep_num\n if sampler_cls is None:\n if self.policy.vectorized and not force_batch_sampler:\n sampler_cls = OnPolicyVectorizedSampler\n else:\n sampler_cls = BatchSampler\n if sampler_args is None:\n sampler_args = dict()\n self.sampler = sampler_cls(self, **sampler_args)\n self.init_opt()\n\n ## Initialization of HDF5 logging of trajectories\n if self.store_paths:\n self.h5_prepare_file(filename=paths_h5_filename, args=self.args)\n \n ## Initialize cleaner if we close\n atexit.register(self.clean_at_exit)\n \n\n def record_policy(self, env, policy, itr, n_rollout=1, path=None, postfix=\"\"):\n # Rollout\n if path is None: path = logger.get_snapshot_dir().rstrip(os.sep) + os.sep + \"videos\" + os.sep + \"itr_%05d%s.mp4\" % (itr, postfix)\n path_directory = path.rsplit(os.sep, 1)[0]\n if not os.path.exists(path_directory):\n os.makedirs(path_directory, exist_ok=True)\n for _ in range(n_rollout):\n obs = env.reset()\n recorder = VideoRecorder(env.env, path=path)\n while True:\n # env.render()\n # import pdb; pdb.set_trace()\n action, _ = policy.get_action(obs)\n obs, _, done, _ = env.step(action)\n recorder.capture_frame()\n if done:\n break\n recorder.close()\n\n def play_policy(self, env, policy, n_rollout=2):\n # Rollout\n for _ in range(n_rollout):\n obs = env.reset()\n while True:\n env.render()\n action, _ = policy.get_action(obs)\n obs, _, done, _ = env.step(action)\n if done:\n break\n\n @staticmethod\n def register_exit_handler(handler_fn):\n # Save will be executed upon normal exit of interpreter\n # NOTE: The functions registered via this module are not called when \n # the program is killed by a signal not handled by Python\n atexit.register(handler_fn)\n \n def clean_at_exit(self):\n # self.hdf.close()\n pass\n\n def h5_prepare_file(self, filename, args):\n # Assuming the following structure / indexing of the H5 file\n # teacher_info/\n # - [teacher_indx]: \n # - description\n # - params\n # traj_data/ \n # - [teacher_indx] * [iter_indx] * traj_data\n\n # Making names and opening h5 file\n if filename is None:\n self.h5_filename = logger.get_snapshot_dir() + os.sep + \"trajectories.h5\"\n else: #capability to store multiple teachers in a single file\n self.h5_filename = filename\n self.h5_filename = self.h5_filename if self.h5_filename[-3:] == '.h5' else (self.h5_filename + '.h5')\n\n if os.path.exists(self.h5_filename):\n # input(\"WARNING: output file %s already exists and will be appended. Press ENTER to continue. (exit with ctrl-C)\" % self.h5_filename)\n print(\"WARNING: output file %s already exists and will be appended\" % self.h5_filename)\n self.hdf = h5py.File(self.h5_filename, \"a\")\n\n # Creating proper groups\n groups = list(self.hdf.keys())\n # Groups to create: tuples: (group_name, structure_decscripton)\n create_groups = [\n (\"teacher_info\", \"Runs indices(Teachers)\"),\n (\"traj_data\", \"Runs(Teachers) x Iterations x Trajectories x Data\")\n ]\n \n for group in create_groups:\n if not group in groups:\n self.hdf.create_group(group[0])\n self.hdf[group[0]].attrs[\"structure\"] = np.string_(group[1])\n \n # Checking if other teachers' results already exist in the h5 file\n # If they exist - just append\n teacher_indices = list(self.hdf[\"traj_data\"].keys())\n if not teacher_indices:\n self.teacher_indx = 0\n else:\n teacher_indices = [int(indx) for indx in teacher_indices]\n teacher_indices = np.sort(teacher_indices)\n self.teacher_indx = teacher_indices[-1] + 1\n print(\"%s : Appended teacher index: \" % self.__class__.__name__, self.teacher_indx)\n \n self.hdf.create_group(\"traj_data/\" + h5u.indx2str(self.teacher_indx)) #Teacher group\n \n ## Saving info about the teacher\n teacher_info_group = \"teacher_info/\" + h5u.indx2str(self.teacher_indx) + \"/\"\n self.hdf.create_group(teacher_info_group) #Teacher group\n h5u.add_dict(self.hdf, self.args, groupname=teacher_info_group)\n\n return self.hdf\n\n def start_worker(self, sess):\n self.sampler.start_worker()\n if self.plot:\n self.plotter = Plotter(self.env, self.policy, sess)\n self.plotter.start()\n\n def shutdown_worker(self):\n self.sampler.shutdown_worker()\n if self.plot:\n self.plotter.close()\n\n def obtain_samples(self, itr):\n return self.sampler.obtain_samples(itr)\n\n def process_samples(self, itr, paths):\n return self.sampler.process_samples(itr, paths)\n\n def log_env_info(self, env_infos, prefix=\"\"):\n # Logging rewards\n rew_dic = env_infos[\"rewards\"]\n for key in rew_dic.keys():\n rew_sums = np.sum(rew_dic[key], axis=1)\n logger.record_tabular(\"rewards/\" + key + \"_avg\", np.mean(rew_sums))\n logger.record_tabular(\"rewards/\" + key + \"_std\", np.std(rew_sums))\n\n\n def train(self, sess=None):\n created_session = True if (sess is None) else False\n if sess is None:\n sess = tf.Session()\n sess.__enter__()\n sess.run(tf.global_variables_initializer())\n\n # Initialize some missing variables\n uninitialized_vars = []\n for var in tf.all_variables():\n try:\n sess.run(var)\n except tf.errors.FailedPreconditionError:\n print(\"Uninitialized var: \", var)\n uninitialized_vars.append(var)\n init_new_vars_op = tf.initialize_variables(uninitialized_vars)\n sess.run(init_new_vars_op)\n\n self.start_worker(sess)\n start_time = time.time()\n last_average_return = None\n samples_total = 0\n for itr in range(self.start_itr, self.n_itr):\n if samples_total >= self.max_samples:\n print(\"WARNING: Total max num of samples collected: %d >= %d\" % (samples_total, self.max_samples))\n break\n itr_start_time = time.time()\n with logger.prefix('itr #%d | ' % itr):\n logger.log(\"Obtaining samples...\")\n paths = self.obtain_samples(itr)\n samples_total += self.batch_size\n logger.log(\"Processing samples...\")\n samples_data = self.process_samples(itr, paths)\n last_average_return = samples_data[\"average_return\"]\n logger.log(\"Logging diagnostics...\")\n self.log_diagnostics(paths)\n logger.log(\"Optimizing policy...\")\n self.optimize_policy(itr, samples_data)\n logger.log(\"Saving snapshot...\")\n params = self.get_itr_snapshot(itr, samples_data)\n # import pdb; pdb.set_trace()\n if self.store_paths:\n ## WARN: Beware that data is saved to hdf in float32 by default\n # see param float_nptype\n h5u.append_train_iter_data(\n h5file=self.hdf, \n data=samples_data[\"paths\"], \n data_group=\"traj_data/\", \n teacher_indx=self.teacher_indx, \n itr=None,\n float_nptype=np.float32\n )\n # params[\"paths\"] = samples_data[\"paths\"]\n logger.save_itr_params(itr, params)\n logger.log(\"Saved\")\n logger.record_tabular('Time', time.time() - start_time)\n logger.record_tabular('ItrTime', time.time() - itr_start_time)\n self.log_env_info(samples_data[\"env_infos\"])\n logger.dump_tabular(with_prefix=False)\n if self.plot:\n self.plotter.update_plot(self.policy, self.max_path_length)\n if self.pause_for_plot:\n input(\"Plotting evaluation run: Press Enter to continue...\")\n # Showing policy from time to time\n if self.record_every_itr is not None and self.record_every_itr > 0 and itr % self.record_every_itr == 0:\n self.record_policy(env=self.env, policy=self.policy, itr=itr)\n if self.play_every_itr is not None and self.play_every_itr > 0 and itr % self.play_every_itr == 0:\n self.play_policy(env=self.env, policy=self.policy)\n\n # Recording a few episodes at the end\n if self.record_end_ep_num is not None:\n for i in range(self.record_end_ep_num):\n self.record_policy(env=self.env, policy=self.policy, itr=itr, postfix=\"_%02d\" % i)\n\n # Reporting termination criteria\n if itr >= self.n_itr-1:\n print(\"TERM CRITERIA: Max number of iterations reached itr: %d , itr_max: %d\" % (itr, self.n_itr-1))\n if samples_total >= self.max_samples:\n print(\"TERM CRITERIA: Total max num of samples collected: %d >= %d\" % (samples_total, self.max_samples))\n\n self.shutdown_worker()\n if created_session:\n sess.close()\n\n def log_diagnostics(self, paths):\n self.policy.log_diagnostics(paths)\n self.baseline.log_diagnostics(paths)\n\n path_lengths = [path[\"returns\"].size for path in paths]\n logger.record_tabular('ep_len_avg', np.mean(path_lengths))\n logger.record_tabular('ep_len_std', np.std(path_lengths))\n\n def init_opt(self):\n \"\"\"\n Initialize the optimization procedure. If using tensorflow, this may\n include declaring all the variables and compiling functions\n \"\"\"\n raise NotImplementedError\n\n def get_itr_snapshot(self, itr, samples_data):\n \"\"\"\n Returns all the data that should be saved in the snapshot for this\n iteration.\n \"\"\"\n raise NotImplementedError\n\n def optimize_policy(self, itr, samples_data):\n raise NotImplementedError\n"
},
{
"alpha_fraction": 0.5835250616073608,
"alphanum_fraction": 0.5951833128929138,
"avg_line_length": 32.6861686706543,
"blob_id": "1fbb3c70214259735dca887314e2af465844e212",
"content_id": "bfeab9c33cbb3cee156e8626e5741f275460e92a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6519,
"license_type": "no_license",
"max_line_length": 169,
"num_lines": 188,
"path": "/quad_train/plot_tools/cf_log_plot.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\r\n\"\"\"\r\nexample on how to plot decoded sensor data from crazyflie\r\n@author: jsschell\r\n\"\"\"\r\nimport CF_functions as cff\r\nimport matplotlib.pyplot as plt\r\nimport re\r\nimport numpy as np\r\nimport argparse\r\n\r\nparser = argparse.ArgumentParser(description='Play a pickled policy.')\r\nparser.add_argument(\"-l\", '--log',\r\n type=str,\r\n help='Logfile')\r\nargs = parser.parse_args()\r\nif args.log is not None:\r\n logfile = args.log\r\nelse:\r\n logfile = \"ctrlNN_feb_1/log01\"\r\n\r\n# decode binary log data\r\nlogData = cff.decode(logfile)\r\nprint(logData.keys())\r\nprint(logData['ctrlNN.out2'])\r\nOFFSET = 0\r\n\r\n# set window background to white\r\nplt.rcParams['figure.facecolor'] = 'w'\r\n \r\n# number of columns and rows for suplot\r\nplotCols = 1;\r\nplotRows = 1;\r\n\r\n# let's see which keys exists in current data set\r\nkeys = \"\"\r\nfor k, v in logData.items():\r\n keys += k\r\n\r\n# get plot config from user\r\nplotGyro = 0\r\nif re.search('gyro', keys):\r\n inStr = input(\"plot gyro data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotGyro = 1\r\n plotRows += 1\r\n\r\nplotAccel = 0\r\nif re.search('acc', keys):\r\n inStr = input(\"plot accel data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotAccel = 1\r\n plotRows += 1\r\n\r\nplotMag = 0\r\nif re.search('mag', keys):\r\n inStr = input(\"plot magnetometer data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotMag = 1\r\n plotRows += 1\r\n\r\nplotBaro = 0\r\nif re.search('baro', keys):\r\n inStr = input(\"plot barometer data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotBaro = 1\r\n plotRows += 1\r\n\r\nplotCtrl = 0\r\nif re.search('ctrltarget', keys):\r\n inStr = input(\"plot control data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotCtrl = 1\r\n plotRows += 1\r\n\r\nplotStab = 0\r\nif re.search('stabilizer', keys):\r\n inStr = input(\"plot stabilizer data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotStab = 1\r\n plotRows += 1\r\n\r\nplotVel = 0\r\nif re.search('vx', keys):\r\n inStr = input(\"plot velocity data? ([Y]es / [n]o): \")\r\n if ((re.search('^[Yy]', inStr)) or (inStr == '')):\r\n plotVel = 1\r\n plotRows += 1\r\n \r\n# current plot for simple subplot usage\r\nplotCurrent = 0;\r\n\r\n# new figure\r\nplt.figure(0)\r\n\r\ndef deg2rad(deg):\r\n return deg / 180. * np.pi\r\n\r\nif plotGyro:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'][OFFSET:], deg2rad(logData['gyro.x'][OFFSET:]), '-', label='X')\r\n plt.plot(logData['tick'][OFFSET:], deg2rad(logData['gyro.y'][OFFSET:]), '-', label='Y')\r\n plt.plot(logData['tick'][OFFSET:], deg2rad(logData['gyro.z'][OFFSET:]), '-', label='Z')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Gyroscope [rad/s]')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n print(\"gyro stddev [deg/s]: \", np.std(logData['gyro.x'][OFFSET:]), np.std(logData['gyro.y'][OFFSET:]), np.std(logData['gyro.z'][OFFSET:]))\r\n \r\nif plotAccel:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['acc.x'], '-', label='X')\r\n plt.plot(logData['tick'], logData['acc.y'], '-', label='Y')\r\n plt.plot(logData['tick'], logData['acc.z'], '-', label='Z')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Accelerometer [g]')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n \r\n\r\nif plotMag:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['mag.x'], '-', label='X')\r\n plt.plot(logData['tick'], logData['mag.y'], '-', label='Y')\r\n plt.plot(logData['tick'], logData['mag.z'], '-', label='Z')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Magnetometer')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n\r\nif plotBaro:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['baro.pressure'], '-')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Pressure [hPa]')\r\n \r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['baro.temp'], '-')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Temperature [degC]')\r\n\r\nif plotCtrl:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['ctrltarget.roll'], '-', label='roll')\r\n plt.plot(logData['tick'], logData['ctrltarget.pitch'], '-', label='pitch')\r\n plt.plot(logData['tick'], logData['ctrltarget.yaw'], '-', label='yaw')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Control')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n\r\nif plotStab:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'], logData['stabilizer.roll'], '-', label='roll')\r\n plt.plot(logData['tick'], logData['stabilizer.pitch'], '-', label='pitch')\r\n plt.plot(logData['tick'], logData['stabilizer.yaw'], '-', label='yaw')\r\n plt.plot(logData['tick'], logData['stabilizer.thrust'], '-', label='thrust')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Stabilizer')\r\n plt.legend(loc=9, ncol=4, borderaxespad=0.)\r\n\r\nif plotVel:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'][OFFSET:], logData['stateEstimate.vx'][OFFSET:], '-', label='X')\r\n plt.plot(logData['tick'][OFFSET:], logData['stateEstimate.vy'][OFFSET:], '-', label='Y')\r\n plt.plot(logData['tick'][OFFSET:], logData['stateEstimate.vz'][OFFSET:], '-', label='Z')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('Velocity [m/s]')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n print(\"vel stddev [m/s]: \", np.std(logData['stateEstimate.vx'][OFFSET:]), np.std(logData['stateEstimate.vy'][OFFSET:]), np.std(logData['stateEstimate.vz'][OFFSET:]))\r\n\r\nif True:\r\n plotCurrent += 1\r\n plt.subplot(plotRows, plotCols, plotCurrent)\r\n plt.plot(logData['tick'][OFFSET:], logData['ctrlNN.out0'][OFFSET:], '-', label='out0')\r\n plt.plot(logData['tick'][OFFSET:], logData['ctrlNN.out1'][OFFSET:], '-', label='out1')\r\n plt.plot(logData['tick'][OFFSET:], logData['ctrlNN.out2'][OFFSET:], '-', label='out2')\r\n plt.plot(logData['tick'][OFFSET:], logData['ctrlNN.out3'][OFFSET:], '-', label='out3')\r\n plt.xlabel('RTOS Ticks')\r\n plt.ylabel('NN output')\r\n plt.legend(loc=9, ncol=3, borderaxespad=0.)\r\n\r\n\r\nplt.show()"
},
{
"alpha_fraction": 0.6009585857391357,
"alphanum_fraction": 0.6446287035942078,
"avg_line_length": 36.664756774902344,
"blob_id": "36c58ed0cbc11c0452951786a13971e496fcfaa5",
"content_id": "e6221cfd33dbe5efd9abb2ec47e80205f59260f1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13144,
"license_type": "no_license",
"max_line_length": 197,
"num_lines": 349,
"path": "/quad_sim/omega_noise.py",
"repo_name": "amolchanov86/quad_sim2multireal",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\nimport numpy as np\nfrom numpy.random import normal \nfrom numpy.random import uniform\nimport matplotlib.pyplot as plt\nfrom math import exp\n\n\n'''\n[w, x, y, z]\n'''\ndef quat2rot(quat):\n\tassert quat.shape == (4,)\n\n\trot = np.zeros((3, 3))\n\n\trot[0][0] = 1 - 2 * quat[2] * quat[2] - 2 * quat[3] * quat[3]\n\trot[0][1] = 2 * quat[1] * quat[2] - 2 * quat[3] * quat[0]\n\trot[0][2] = 2 * quat[1] * quat[3] + 2 * quat[2] * quat[0]\n\trot[1][0] = 2 * quat[1] * quat[2] + 2 * quat[3] * quat[0]\n\trot[1][1] = 1 - 2 * quat[1] * quat[1] - 2 * quat[3] * quat[3]\n\trot[1][2] = 2 * quat[2] * quat[3] - 2 * quat[1] * quat[0]\n\trot[2][0] = 2 * quat[1] * quat[3] - 2 * quat[2] * quat[0]\n\trot[2][1] = 2 * quat[2] * quat[3] + 2 * quat[1] * quat[0]\n\trot[2][2] = 1 - 2 * quat[1] * quat[1] - 2 * quat[2] * quat[2]\n\n\treturn rot\n\n\n'''\nhttp://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToQuaternion/\n'''\ndef rot2quat(rot):\n\tassert rot.shape == (3, 3)\n\n\ttrace = np.trace(rot)\n\tif trace > 0:\n\t\tS = (trace + 1.0)**0.5 * 2\n\t\tqw = 0.25 * S\n\t\tqx = (rot[2][1] - rot[1][2]) / S \n\t\tqy = (rot[0][2] - rot[2][0]) / S\n\t\tqz = (rot[1][0] - rot[0][1]) / S\n\telif rot[0][0] > rot[1][1] and rot[0][0] > rot[2][2]:\n\t\tS = (1.0 + rot[0][0] - rot[1][1] - rot[2][2])**0.5 * 2\n\t\tqw = (rot[2][1] - rot[1][2]) / S\n\t\tqx = 0.25 * S \n\t\tqy = (rot[0][1] + rot[1][0]) / S\n\t\tqz = (rot[0][2] + rot[2][0]) / S\n\telif rot[1][1] > rot[2][2]:\n\t\tS = (1.0 + rot[1][1] - rot[0][0] - rot[2][2])**0.5 * 2\n\t\tqw = (rot[0][2] - rot[2][0]) / S \n\t\tqx = (rot[0][1] + rot[1][0]) / S\n\t\tqy = 0.25 * S\n\t\tqz = (rot[1][2] + rot[2][1]) / S\n\telse:\n\t\tS = (1.0 + rot[2][2] - rot[0][0] - rot[1][1])**0.5 * 2\n\t\tqw = (rot[1][0] - rot[0][1]) / S\n\t\tqx = (rot[0][2] + rot[2][0]) / S \n\t\tqy = (rot[1][2] + rot[2][1]) / S\n\t\tqz = 0.25 * S\n\n\treturn np.array([qw, qx, qy, qz])\n\ndef quat_from_small_angle(theta):\n\tassert theta.shape == (3,)\n\n\tq_squared = np.linalg.norm(theta)**2 / 4.0\n\tif q_squared < 1:\n\t\tq_theta = np.array([(1 - q_squared)**0.5, theta[0] * 0.5, theta[1] * 0.5, theta[2] * 0.5])\n\telse:\n\t\tw = 1.0 / (1 + q_squared)**0.5\n\t\tf = 0.5 * w\n\t\tq_theta = np.array([w, theta[0] * f, theta[1] * f, theta[2] * f])\n\n\tq_theta = q_theta / np.linalg.norm(q_theta)\n\n\treturn q_theta\n\nclass Noise:\n\tdef __init__(self, noise_normal_position=np.zeros(3), noise_uniform_position=np.zeros(3), \n\t\t\t\t\t noise_normal_linear_velocity=np.zeros(3), noise_uniform_linear_velocity=np.zeros(3), \n\t\t\t\t\t noise_normal_theta=np.zeros(3), noise_uniform_theta=np.zeros(3), \n\t\t\t\t\t noise_density=0.000175, random_walk=0.0105, bias_correlation_time=1000, turn_on_bias_sigma=0.09,\n\t\t\t\t\t measurement_delay=0): \n\n\n\t\t\"\"\"\n\t\tArgs:\n\t\tnoise_normal_position: numpy array of 3 elements representing the \n\t\t\t\tstandard deviation of the position noise, the noise is centered at 0\n\t\tnoise_uniform_position: numpy array of 3 elements representing the upper range \n\t\t\t\tof the uniform distribution\n\t\tnoise_normal_linear_velocity: numpy array of 3 elements representing the \n\t\t\t\tstandard deviation of the linear velocity noise, the noise is centered at 0\n\t\tnoise_uniform_linear_velocity: numpy array of 3 elements representing the upper range \n\t\t\t\tof the uniform distribution\n\t\tnoise_normal_theta: numpy array of 3 elements representing the \n\t\t\t\tstandard deviation of the orientation noise, the noise is centered at 0\n\t\tnoise_uniform_theta: numpy array of 3 elements representing the upper range \n\t\t\t\tof the uniform distribution\n\t\tnoise_density: gyroscope noise, MPU-9250 spec\n\t\trandom_walk: gyroscope noise, MPU-9250 spec\n\t\tbias_correlation_time: gyroscope noise, MPU-9250 spec\n\t\tturn_on_bias_sigma: gyroscope noise, MPU-9250 spec\n\t\tmeasurement_delay: integer, # time steps to delay messages \n\t\t\"\"\"\n\n\t\tself.noise_normal_position = noise_normal_position\n\t\tself.noise_uniform_position = noise_uniform_position\n\n\t\tself.noise_normal_linear_velocity = noise_normal_linear_velocity\n\t\tself.noise_uniform_linear_velocity = noise_uniform_linear_velocity\n\n\t\tself.noise_normal_theta = noise_uniform_theta\n\t\tself.noise_uniform_theta = noise_uniform_theta\n\n\t\tself.noise_density = noise_density\n\t\tself.random_walk = random_walk\n\t\tself.bias_correlation_time = bias_correlation_time\n\t\tself.turn_on_bias_sigma = turn_on_bias_sigma\n\t\tself.gyroscope_bias = np.zeros(3)\n\n\t\tself.measurement_delay = measurement_delay\n\n\t\tself.previous_pos = np.zeros(3)\n\t\tself.previous_vel = np.zeros(3)\n\t\tself.previous_rot = np.zeros((3, 3))\n\t\tself.previous_omega = np.zeros(3)\n\n\t\tself.states_queue = []\n\n\t\tself.omega_noise_comp = []\n\t\n\n\t\"\"\"\n\targs: \n\tpos: ground truth of the position\n\tvel: grond truth if the linear velocity\n\trot: ground truth of the orientation in rotational matrix\n\tomega: ground truth of the angular velocity\n\tdt: integration step\n\t\"\"\"\n\tdef add_noise(self, pos, vel, rot, omega, dt):\n\t\tassert pos.shape == (3,)\n\t\tassert vel.shape == (3,)\n\t\tassert rot.shape == (3,3)\n\t\tassert omega.shape == (3,)\n\n\t\t# add noise to position measurement\n\t\tnoisy_pos = np.zeros(3)\n\t\tnoisy_pos[0] = pos[0] + \\\n\t\t\t\t\t normal(0, self.noise_normal_position[0]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_position[0], self.noise_uniform_position[0])\n\t\tnoisy_pos[1] = pos[1] + \\\n\t\t\t\t\t normal(0, self.noise_normal_position[1]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_position[1], self.noise_uniform_position[1])\n\t\tnoisy_pos[2] = pos[2] + \\\n\t\t\t\t\t normal(0, self.noise_normal_position[2]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_position[2], self.noise_uniform_position[2])\n\n\t\t# add noise to linear velocity\n\t\tnoisy_vel = np.zeros(3)\t\t\n\t\tnoisy_vel[0] = vel[0] + \\\n\t\t\t\t\t normal(0, self.noise_normal_linear_velocity[0]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_linear_velocity[0], self.noise_uniform_linear_velocity[0])\n\t\tnoisy_vel[1] = vel[1] + \\\n\t\t\t\t\t normal(0, self.noise_normal_linear_velocity[1]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_linear_velocity[1], self.noise_uniform_linear_velocity[1])\n\t\tnoisy_vel[2] = vel[2] + \\\n\t\t\t\t\t normal(0, self.noise_normal_linear_velocity[2]) + \\\n\t\t\t\t\t uniform(-self.noise_uniform_linear_velocity[2], self.noise_uniform_linear_velocity[2])\n\n\t\t# add noise to orientation\n\t\tquat = rot2quat(rot)\n\n\t\ttheta = np.zeros(3)\n\t\ttheta[0] = normal(0, self.noise_normal_theta[0]) + uniform(-self.noise_uniform_theta[0], self.noise_uniform_theta[0])\n\t\ttheta[1] = normal(0, self.noise_normal_theta[1]) + uniform(-self.noise_uniform_theta[1], self.noise_uniform_theta[1])\n\t\ttheta[2] = normal(0, self.noise_normal_theta[2]) + uniform(-self.noise_uniform_theta[2], self.noise_uniform_theta[2])\n\n\t\t# convert theta to quaternion\n\t\tquat_theta = quat_from_small_angle(theta)\n\n\t\tnoisy_quat = np.zeros(4)\n\t\t## quat * quat_theta\n\t\tnoisy_quat[0] = quat[0] * quat_theta[0] - quat[1] * quat_theta[1] - quat[2] * quat_theta[2] - quat[3] * quat_theta[3] \n\t\tnoisy_quat[1] = quat[0] * quat_theta[1] + quat[1] * quat_theta[0] - quat[2] * quat_theta[3] + quat[3] * quat_theta[2] \n\t\tnoisy_quat[2] = quat[0] * quat_theta[2] + quat[1] * quat_theta[3] + quat[2] * quat_theta[0] - quat[3] * quat_theta[1] \n\t\tnoisy_quat[3] = quat[0] * quat_theta[3] - quat[1] * quat_theta[2] + quat[2] * quat_theta[1] + quat[3] * quat_theta[0]\n\n\t\t# TODO: make sure the rotational matrix is orthogonal\n\t\tnoisy_rot = quat2rot(noisy_quat)\n\n\t\tnoisy_omega = self.add_noise_to_omega(omega, dt)\n\n\t\tself.states_queue.append((noisy_pos, noisy_vel, noisy_rot, noisy_omega))\n\n\t\tif self.measurement_delay > len(self.states_queue):\n\t\t\treturn np.zeros(3), np.zeros(3), np.eye(3), np.zeros(3)\n\n\t\treturn self.states_queue.pop(0)\n\n\t## copy from rotorS imu plugin\n\tdef add_noise_to_omega(self, omega, dt):\n\t\tassert omega.shape == (3,)\n\n\t\tsigma_g_d = self.noise_density / (dt**0.5)\n\t\tsigma_b_g_d = (-(sigma_g_d**2) * (self.bias_correlation_time / 2) * (exp(-2*dt/self.bias_correlation_time) - 1))**0.5\n\t\tpi_g_d = exp(-dt / self.bias_correlation_time)\n\n\t\tself.gyroscope_bias = pi_g_d * self.gyroscope_bias + sigma_b_g_d * normal(0, 1, 3)\n\n\t\t# noise = self.gyroscope_bias + self.random_walk * normal(0, 1, 3) + self.turn_on_bias_sigma * normal(0, 1, 3)\n\t\tnoise = self.gyroscope_bias + self.random_walk * normal(0, 1, 3) #+ self.turn_on_bias_sigma * normal(0, 1, 3)\n\t\tnoise_comp = np.array([np.linalg.norm(self.gyroscope_bias), np.linalg.norm(self.random_walk * normal(0, 1, 3)), np.linalg.norm(self.turn_on_bias_sigma * normal(0, 1, 3))]) / np.linalg.norm(noise)\n\t\t\n\t\tself.omega_noise_comp.append(np.abs(noise_comp))\n\t\tprint(\"Noise components: \", np.mean( np.array(self.omega_noise_comp), axis=0))\n\n\t\tomega = omega + noise\n\t\treturn omega\n\n\n\ndef test():\n\tnnp = np.array([0.05, 0.05, 0.05])\n\tnup = np.array([0.05, 0.05, 0.05])\n\n\tnnlv = np.array([0.05, 0.05, 0.05])\n\tnulv = np.array([0.05, 0.05, 0.05])\n\n\tnnt = np.array([0.1, 0.1, 0.1])\n\tnut = np.array([0.1, 0.1, 0.1])\n\n\tnoise_generator = Noise(noise_normal_position=nnp, noise_uniform_position=nup, \n\t\t\t\t\t noise_normal_linear_velocity=nnlv, noise_uniform_linear_velocity=nulv, \n\t\t\t\t\t noise_normal_theta=nnt, noise_uniform_theta=nut, measurement_delay=10)\n\tdt = 0.005\n\n\tn = 1000\n\n\tground_truth_pos_x = np.sin(np.linspace(-20, 20, num=n))\n\tground_truth_pos_y = np.sin(np.linspace(-20, 20, num=n))\n\tground_truth_pos_z = np.sin(np.linspace(-20, 20, num=n))\n\n\tground_truth_vel_x = np.cos(np.linspace(-20, 20, num=n))\n\tground_truth_vel_y = np.cos(np.linspace(-20, 20, num=n))\n\tground_truth_vel_z = np.cos(np.linspace(-20, 20, num=n))\n\n\tground_truth_omega_x = np.zeros(n)\n\tground_truth_omega_y = np.zeros(n)\n\tground_truth_omega_z = np.zeros(n)\n\n\trot = np.eye(3)\n\tground_truth_orientation_x = np.sin(np.linspace(-20, 20, num=n)) # np.ones(n)\n\tground_truth_orientation_y = np.cos(np.linspace(-20, 20, num=n)) # np.ones(n)\n\tground_truth_orientation_z = np.sin(np.linspace(-20, 20, num=n)) # np.ones(n)\n\t\n\n\tground_truth_pos = np.column_stack((ground_truth_pos_x, ground_truth_pos_y, ground_truth_pos_z))\n\tground_truth_vel = np.column_stack((ground_truth_vel_x, ground_truth_vel_y, ground_truth_vel_z))\n\tground_truth_omega = np.column_stack((ground_truth_omega_x, ground_truth_omega_y, ground_truth_omega_z))\n\tground_truth_orientation = np.column_stack((ground_truth_orientation_x, ground_truth_orientation_y, ground_truth_orientation_z))\n\t## normalize the orientation\n\tnorms = np.linalg.norm(ground_truth_orientation, axis=1)\n\tground_truth_orientation = ground_truth_orientation / norms[:, None]\n\tprint(ground_truth_orientation)\n\n\tfor i in range(n):\n\t\tnoisy_pos, noisy_vel, noisy_rot, noisy_omega = noise_generator.add_noise(\n\t\t\tground_truth_pos[i], ground_truth_vel[i], rot, ground_truth_omega[i], dt)\n\n\t\t# test if the noisy rotation matrix is orthogonal\n\t\tif np.allclose(noisy_rot.T, np.linalg.inv(noisy_rot), 1e-5) != True:\n\t\t\tprint('Non-orthogonal rotation matrix:')\n\t\t\tprint(noisy_rot.T)\n\t\t\tprint(np.linalg.inv(noisy_rot))\n\t\t\texit(1)\n\n\t\tnoisy_orientation = np.matmul(noisy_rot, ground_truth_orientation[i])\n\n\t\tif i == 0:\n\t\t\tnoisy_pos_ = np.array([noisy_pos])\n\t\t\tnoisy_vel_ = np.array([noisy_vel])\n\t\t\tnoisy_omega_ = np.array([noisy_omega])\n\t\t\tnoisy_orientation_ = np.array([noisy_orientation])\n\t\telse:\n\t\t\tnoisy_pos_ = np.concatenate((noisy_pos_, np.array([noisy_pos])))\n\t\t\tnoisy_vel_ = np.concatenate((noisy_vel_, np.array([noisy_vel])))\n\t\t\tnoisy_omega_ = np.concatenate((noisy_omega_, np.array([noisy_omega])))\n\t\t\tnoisy_orientation_ = np.concatenate((noisy_orientation_, np.array([noisy_orientation])))\n\n\t## TODO: plot\n\tplt.subplot(431)\n\tplt.ylabel('pos x')\n\tplt.plot(range(n), noisy_pos_[:, 0], c='red')\n\tplt.plot(range(n), ground_truth_pos[:, 0], c='green')\n\tplt.subplot(432)\n\tplt.ylabel('pos y')\n\tplt.plot(range(n), noisy_pos_[:, 1], c='red')\n\tplt.plot(range(n), ground_truth_pos[:, 1], c='green')\n\tplt.subplot(433)\n\tplt.ylabel('pos z')\n\tplt.plot(range(n), noisy_pos_[:, 2], c='red')\n\tplt.plot(range(n), ground_truth_pos[:, 2], c='green')\n\n\tplt.subplot(434)\n\tplt.ylabel('vel x')\n\tplt.plot(range(n), noisy_vel_[:, 0], c='red')\n\tplt.plot(range(n), ground_truth_vel[:, 0], c='green')\n\tplt.subplot(435)\n\tplt.ylabel('vel y')\n\tplt.plot(range(n), noisy_vel_[:, 1], c='red')\n\tplt.plot(range(n), ground_truth_vel[:, 1], c='green')\n\tplt.subplot(436)\n\tplt.ylabel('vel z')\n\tplt.plot(range(n), noisy_vel_[:, 2], c='red')\n\tplt.plot(range(n), ground_truth_vel[:, 2], c='green')\n\n\tplt.subplot(437)\n\tplt.ylabel('omega x')\n\tplt.plot(range(n), noisy_omega_[:, 0], c='red')\n\tplt.plot(range(n), ground_truth_omega[:, 0], c='green')\n\tplt.subplot(438)\n\tplt.ylabel('omega y')\n\tplt.plot(range(n), noisy_omega_[:, 1], c='red')\n\tplt.plot(range(n), ground_truth_omega[:, 1], c='green')\n\tplt.subplot(439)\n\tplt.ylabel('omega z')\n\tplt.plot(range(n), noisy_omega_[:, 2], c='red')\n\tplt.plot(range(n), ground_truth_omega[:, 2], c='green')\n\n\tplt.subplot(4, 3, 10)\n\tplt.ylabel('orientation in x')\n\tplt.plot(range(n), noisy_orientation_[:, 0], c='red')\n\tplt.plot(range(n), ground_truth_orientation[:, 0], c='green')\n\tplt.subplot(4, 3, 11)\n\tplt.ylabel('orientation in y')\n\tplt.plot(range(n), noisy_orientation_[:, 1], c='red')\n\tplt.plot(range(n), ground_truth_orientation[:, 1], c='green')\n\tplt.subplot(4, 3, 12)\n\tplt.ylabel('orientation in z')\n\tplt.plot(range(n), noisy_orientation_[:, 2], c='red')\n\tplt.plot(range(n), ground_truth_orientation[:, 2], c='green')\n\n\tplt.show()\n\nif __name__ == '__main__':\n\ttest()"
}
] | 36
|
zzsqwq/emoji2pic-python
|
https://github.com/zzsqwq/emoji2pic-python
|
f50e536860901d828fd30f9c3c35af81835fdded
|
3b48f59142a7ec16e27fface98d57df4e24efd92
|
7e019b1873bc6bd70a0ba0509afdb95f0372f19c
|
refs/heads/master
| 2022-02-10T21:41:56.775307
| 2019-03-11T09:11:34
| 2019-03-11T09:11:34
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7256267666816711,
"alphanum_fraction": 0.7395543456077576,
"avg_line_length": 21.092308044433594,
"blob_id": "33c0e1820870e083495082a0dc41c3894b6ba1be",
"content_id": "718b6097107c48a6194c8d56f17d81c88f7cddd2",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 2121,
"license_type": "permissive",
"max_line_length": 98,
"num_lines": 65,
"path": "/README.md",
"repo_name": "zzsqwq/emoji2pic-python",
"src_encoding": "UTF-8",
"text": "# emoji2pic-python\nApple emoji and text to picture\n\n[TOC]\n\n## 介绍 Introduction\n\n使用Python Pillow根据unicode将文本和emoji绘制到图片上 \n可自选字体，字号，行距，页边距，颜色，图片宽度和透明度等\n\n## 开发进度 Progress\nhttps://emojipedia.org/apple/ios-12.1/ \n目前完成匹配Apple iOS 12.1 emoji 共2776个\n\n## 依赖库 Dependencies\n\nPillow\n\n## 简单入门实例 Example\n```python\nfrom emoji2pic import Emoji2Pic\n\ninstance = Emoji2Pic(text='🌷👌🌙⭕\\n花好月圆', font='SourceHanSans-Light.ttc', emoji_folder='AppleEmoji')\nimg = instance.make_img()\nimg.save('example.jpg')\n```\n\n## 使用方法 Instructions\n\n|参数|说明|格式|是否必须|\n|:---:|:---:|:---:|:---:|\n|text|文本内容|char|yes|\n|font|字体文件路径|char|yes|\n|emoji_folder|emoji图片文件夹路径|char|yes|\n|width|图片宽度|int|no|\n|font_size|文字大小|int|no|\n|font_color|文字颜色|RGB/RGBA|no|\n|color_mode|图片底色模式|char|no|\n|background_color|图片底色|RGB/RGBA|no|\n|line_space|行间距|int|no|\n|left|左边距|int|no|\n|right|右边距|int|no|\n|top|上边距|int|no|\n|bottom|下边距|int|no|\n|half_font|半角字符字体路径|char|no|\n|half_font_width|半角字符字体宽度|int|no|\n|half_font_offset|半角字符纵轴偏移量|int|no|\n|emoji_offset|emoji纵轴偏移量|int|no|\n|progress_bar|控制台输出进度条|boolean|no|\n\n1. make_img() 方法，返回 PIL.Image.Image\n2. 图片包在 releases\n3. get_unicode_from_file_name.py 从图片文件名获取对应的 Unicode，写入 emoji_directory.py\n\n#### 注意 Note\n\n1. 根据像素绘制文本，只适合等宽字体。很多字体的半角字符都不等宽，比如微软雅黑 \n解决方法：自定义 half_font ，支持ASCII范围的半角字符，也可使用 half_font_width 调节半角字符宽度 \n2. 使用半角字符字体时，会造成半角字符纵轴偏移几像素 \n解决方法：使用half_font_offset，自定义半角字符纵轴偏移\n3. emoji纵轴偏移几像素 \n解决方法：使用emoji_offset，自定义emoji字符纵轴偏移\n\n# 许可 License\nMIT license.\n"
},
{
"alpha_fraction": 0.5214534401893616,
"alphanum_fraction": 0.5287011861801147,
"avg_line_length": 33.03947448730469,
"blob_id": "c7b1dc40b8d23bb5345c0cc21be4f4cbf150120d",
"content_id": "51f648ed15469ab3979d8a492a3cff4ad75d311f",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 10870,
"license_type": "permissive",
"max_line_length": 111,
"num_lines": 304,
"path": "/emoji2pic/main.py",
"repo_name": "zzsqwq/emoji2pic-python",
"src_encoding": "UTF-8",
"text": "import os\nimport sys\nfrom PIL import Image, ImageFont, ImageDraw\n\nfrom .emoji_directory import INITIAL_UNICODE, UNICODE_TO_PATH\n\nRGB = 'RGB'\nRGB_WHITE = (255, 255, 255)\nRGB_BLACK = (0, 0, 0)\nRGBA = 'RGBA'\nRGBA_WHITE = (255, 255, 255, 255)\nRGBA_BLACK = (0, 0, 0, 255)\nRGBA_TRANSPARENT = (0, 0, 0, 0)\nZERO = 0\nNEGATIVE = -1\n\nDEFAULT_FONT_SIZE = 72\nDEFAULT_IMAGE_WIDTH = 1080\n\nEMOJI = 4\nFULL_WIDTH = 3\nHALF_WIDTH = 1\nEMOJI_IMG_SIZE = 72\n\n\nclass Emoji2Pic(object):\n \"\"\"将带有emoji的文本绘制到图片上，返回 'PIL.Image.Image'。\n Text with emoji draw to the image.return class 'PIL.Image.Image'\n\n :param text: 文本内容\n :param font: 字体文件路径\n :param emoji_folder: emoji图片文件夹路径\n\n :param width: 图片宽度（像素）\n :param font_size: 文字大小（像素）\n :param font_color: 文字颜色\n :param color_mode: 图片底色模式\n :param background_color: 图片底色\n :param line_space: 行间距（像素）\n :param left: 左边距（像素） left margins\n :param right: 右边距（像素）\n :param top: 上边距（像素）\n :param bottom: 下边距（像素）\n :param half_font: 半角字符字体路径\n :param half_font_width: 半角字符字体宽度（像素）\n :param half_font_offset: 半角字符纵轴偏移量（像素）\n :param emoji_offset: emoji纵轴偏移量（像素）\n :param progress_bar: 控制台输出进度条\n\n :return:class 'PIL.Image.Image'\n \"\"\"\n\n def __init__(self, text, font, emoji_folder,\n width=DEFAULT_IMAGE_WIDTH,\n font_size=DEFAULT_FONT_SIZE,\n font_color=RGB_BLACK,\n color_mode=RGB,\n background_color=RGB_WHITE,\n line_space=DEFAULT_FONT_SIZE,\n left=DEFAULT_FONT_SIZE,\n right=DEFAULT_FONT_SIZE,\n top=DEFAULT_FONT_SIZE,\n bottom=ZERO,\n half_font=None,\n half_font_width=None,\n half_font_offset=ZERO,\n emoji_offset=ZERO,\n progress_bar=True\n ):\n self.text = str(text)\n self.font = font\n self.emoji_folder = emoji_folder\n self.img_width = int(width)\n self.font_size = int(font_size)\n self.font_color = font_color\n self.background_color_mode = color_mode\n self.background_color = background_color\n self.line_space = int(line_space)\n self.margin_left = int(left)\n self.margin_right = int(right)\n self.margin_top = int(top)\n self.margin_bottom = int(bottom)\n self.half_font = half_font if half_font is not None else font\n self.half_font_width = int(half_font_width) if half_font_width is not None else int(self.font_size / 2)\n self.half_font_offset = half_font_offset\n self.emoji_offset = int(emoji_offset)\n self.need_progress_bar = progress_bar\n\n self.x = ZERO\n self.y = ZERO\n self.progress_bar_count = ZERO\n self.text_length = ZERO\n self.paragraph_list = list()\n self.img_list = list()\n self.img = None\n self.paragraph = None\n self.char = None\n self.char_next = None\n self.char_index = None\n self.char_kind = None\n self.full_width_font_type = ImageFont.truetype(self.font, size=self.font_size)\n self.half_font_type = ImageFont.truetype(self.half_font, size=self.font_size)\n\n def split_paragraph(self):\n \"\"\"\n 分割段落\n Split paragraph\n \"\"\"\n self.paragraph_list = self.text.replace('\\n\\n', '\\n \\n').split('\\n')\n for paragraph in self.paragraph_list:\n self.text_length += len(paragraph)\n return\n\n def make_blank_img(self, img_width=None, img_height=None):\n \"\"\"\n 创建空白图片\n Make a blank image\n \"\"\"\n if img_width is None:\n img_width = self.img_width\n if img_height is None:\n img_height = self.font_size + self.line_space\n img = Image.new(mode=self.background_color_mode,\n size=(img_width, img_height),\n color=self.background_color)\n return img\n\n def stdout_progress_bar(self):\n \"\"\"\n 输出进度条\n Progress bar\n \"\"\"\n self.progress_bar_count += 1\n display_length = 50\n percent_num = int(self.progress_bar_count / self.text_length * 100)\n percent_length = int(self.progress_bar_count / self.text_length * display_length)\n sys.stdout.write('\\r')\n sys.stdout.write(\n 'Drawing | [%s>%s] %s' % ('=' * percent_length,\n ' ' * (display_length - percent_length),\n str(percent_num) + '%'))\n sys.stdout.flush()\n return\n\n def draw_text(self):\n \"\"\"\n 每个字符按坐标绘制\n Each character is plotted by coordinates\n \"\"\"\n for paragraph in self.paragraph_list:\n self.paragraph = paragraph\n self.img = self.make_blank_img()\n self.x = self.margin_left\n self.y = ZERO\n self.char_next = NEGATIVE\n for index in range(len(paragraph)):\n # 进度条\n if self.need_progress_bar is True:\n self.stdout_progress_bar()\n # 绘制\n self.char_index = index\n if index >= self.char_next:\n self.char = paragraph[index]\n char_kind = self.classify_character()\n if char_kind == HALF_WIDTH: # 半角字符\n self.draw_character(half_width=True)\n self.x += self.half_font_width\n elif char_kind == FULL_WIDTH: # 全角字符\n self.draw_character()\n self.x += self.font_size\n elif char_kind == EMOJI: # emoji\n self.draw_emoji()\n self.x += self.font_size\n # 换行\n if self.x > self.img_width - (\n self.margin_right + self.font_size) or index >= len(paragraph) - 1:\n self.img_list.append(self.img)\n self.img = self.make_blank_img()\n self.x = self.margin_left\n self.y = ZERO\n return\n\n def classify_character(self):\n \"\"\"字符分类\n Character classification\n \"\"\"\n if self.char in INITIAL_UNICODE:\n if u'\\x2a' <= self.char <= u'\\x39' \\\n and self.paragraph[self.char_index:self.char_index + 3] not in UNICODE_TO_PATH \\\n and self.paragraph[self.char_index:self.char_index + 2] not in UNICODE_TO_PATH:\n return HALF_WIDTH # 半角字符\n return EMOJI # emoji\n elif u'\\x20' <= self.char <= u'\\x7e':\n return HALF_WIDTH # 半角字符\n else:\n return FULL_WIDTH # 全角字符\n\n def draw_character(self, half_width=False):\n \"\"\"\n 绘制文本\n Draw character\n \"\"\"\n if self.char in ('\\u200d', '\\ufe0f', '\\u20e3'):\n self.x -= self.font_size\n return\n if half_width is True:\n font_type = self.half_font_type\n y = self.y - self.half_font_offset\n else:\n font_type = self.full_width_font_type\n y = self.y\n ImageDraw.Draw(self.img).text(xy=(self.x, y),\n text=self.char,\n fill=self.font_color,\n font=font_type)\n return\n\n def get_emoji_img(self):\n \"\"\"\n 打开emoji图片\n Open emoji image\n \"\"\"\n length_list = INITIAL_UNICODE[self.char]\n emoji_unicode = None\n for length in length_list:\n emoji_unicode_temp = self.paragraph[self.char_index:self.char_index + length]\n if emoji_unicode_temp in UNICODE_TO_PATH:\n emoji_unicode = emoji_unicode_temp\n self.char_next = self.char_index + length # 跳过字符\n break\n\n if emoji_unicode is None:\n self.char_next = NEGATIVE\n return None\n emoji_file_name = UNICODE_TO_PATH.get(emoji_unicode)\n if emoji_file_name is None:\n self.char_next = NEGATIVE\n return None\n emoji_img = Image.open(os.path.join(self.emoji_folder, emoji_file_name))\n\n return emoji_img\n\n def draw_emoji(self):\n \"\"\"\n 绘制emoji\n Draw emoji\n \"\"\"\n emoji_img = self.get_emoji_img()\n if emoji_img is None:\n self.x -= self.font_size\n return\n\n # 更改尺寸\n if self.font_size != EMOJI_IMG_SIZE:\n emoji_img = emoji_img.resize((self.font_size, self.font_size), Image.ANTIALIAS)\n # 分离通道\n if emoji_img.mode == 'RGBA':\n r, g, b, a = emoji_img.split() # 分离alpha通道 split alpha channel\n elif emoji_img.mode == 'LA':\n l, a = emoji_img.split()\n else: # image.mode == 'P'\n emoji_img = emoji_img.convert('RGBA')\n r, g, b, a = emoji_img.split()\n # 绘制\n self.img.paste(emoji_img, (self.x, self.y + self.emoji_offset), mask=a)\n return\n\n def combine_img(self):\n \"\"\"\n 合并图片\n Merge image\n \"\"\"\n # 创建上边距图片 Create top margin image\n img_top = self.make_blank_img(img_width=self.img_width, img_height=self.margin_top)\n self.img_list.insert(0, img_top)\n # 创建下边距图片 Create bottom margin image\n img_bottom = self.make_blank_img(img_width=self.img_width, img_height=self.margin_bottom)\n self.img_list.append(img_bottom)\n\n background_height = ZERO\n y = ZERO\n for img in self.img_list:\n background_height += img.size[1]\n # 创建背景图片图片 Create background image\n background_img = self.make_blank_img(img_width=self.img_width, img_height=background_height)\n\n for img in self.img_list:\n if self.background_color_mode == RGB:\n background_img.paste(img, (ZERO, y))\n y += img.size[1]\n elif self.background_color_mode == RGBA:\n r, g, b, a = img.split() # 分离alpha通道\n background_img.paste(img, (ZERO, y), mask=a)\n y += img.size[1]\n\n return background_img\n\n def make_img(self):\n \"\"\"\n Main program\n \"\"\"\n self.split_paragraph()\n self.draw_text()\n return self.combine_img()\n"
},
{
"alpha_fraction": 0.5271889567375183,
"alphanum_fraction": 0.5497695803642273,
"avg_line_length": 36.41379165649414,
"blob_id": "6fc9e344f72a233b7023469b636f96e9ba56c5b0",
"content_id": "2dcb8ff66e5b340421094bc563735436432d1177",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2198,
"license_type": "permissive",
"max_line_length": 115,
"num_lines": 58,
"path": "/emoji2pic/get_unicode_from_file_name.py",
"repo_name": "zzsqwq/emoji2pic-python",
"src_encoding": "UTF-8",
"text": "import os\n\n\ndef organize_file_name(file_dir='AppleEmoji'):\n \"\"\"\n 从emoji图片文件名整理出对应的Unicode\n GET Unicode from file name\n \"\"\"\n for root, dirs, files in os.walk(file_dir):\n pass\n\n unicode_to_path = dict()\n initial_unicode = dict()\n\n for file in files:\n chip_list = file.split('_')\n eng = len(chip_list[0]) + 1 if chip_list[1][:5] != 'emoji' else len(chip_list[0] + chip_list[1]) + 2\n base_name = file[eng:-4].replace('_', '-')\n base_name_chip_list = base_name.split('-')\n\n keycap = False\n unicode_chip_list = list()\n for chip in base_name_chip_list:\n if len(chip) == 2:\n if chip in ('23', '2a', '30', '31', '32', '33', '34', '35', '36', '37', '38', '39',):\n keycap = True\n unicode_chip = u'\\\\x' + chip\n elif len(chip) == 4:\n unicode_chip = u'\\\\u' + chip\n elif len(chip) == 5:\n unicode_chip = u'\\\\U000' + chip\n else:\n raise ValueError(chip)\n unicode_chip_list.append(unicode_chip.encode('utf-8').decode('unicode_escape'))\n\n if initial_unicode.get(unicode_chip_list[0]) is None:\n initial_unicode[unicode_chip_list[0]] = [len(unicode_chip_list)]\n else:\n if len(unicode_chip_list) not in initial_unicode[unicode_chip_list[0]]:\n initial_unicode[unicode_chip_list[0]].append(len(unicode_chip_list))\n initial_unicode[unicode_chip_list[0]] = sorted(initial_unicode[unicode_chip_list[0]], reverse=True)\n\n unicode_name = ''.join(unicode_chip_list)\n unicode_to_path[unicode_name] = file\n\n if keycap is True: # 数字emoji\n initial_unicode[unicode_chip_list[0]].append(2)\n keycap_unicode_name = ''.join([unicode_chip_list[0], unicode_chip_list[2]])\n unicode_to_path[keycap_unicode_name] = file\n\n with open('emoji_directory.py', 'w', encoding='utf8') as f:\n f.write('INITIAL_UNICODE = ' + str(initial_unicode) + '\\n'+'UNICODE_TO_PATH = '+str(unicode_to_path)+'\\n')\n\n return\n\n\nif __name__ == '__main__':\n organize_file_name()\n"
},
{
"alpha_fraction": 0.8120805621147156,
"alphanum_fraction": 0.818791925907135,
"avg_line_length": 48.66666793823242,
"blob_id": "df6110016ac2eea75aef1080ecc64fb510d0f1af",
"content_id": "3ce3e2bd80bfbac79e453c0c416aa3d4f7d9169d",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 149,
"license_type": "permissive",
"max_line_length": 61,
"num_lines": 3,
"path": "/emoji2pic/__init__.py",
"repo_name": "zzsqwq/emoji2pic-python",
"src_encoding": "UTF-8",
"text": "from .get_unicode_from_file_name import organize_file_name\nfrom .emoji_directory import UNICODE_TO_PATH, INITIAL_UNICODE\nfrom .main import Emoji2Pic\n"
}
] | 4
|
NhanGiaHuy/CP1404_Pactical
|
https://github.com/NhanGiaHuy/CP1404_Pactical
|
0403d7709a44b639a40df90dc8ba7f058ab5515d
|
cf47ebcafd17ffc1f2a2aff9dadbdd0b94d44d31
|
fc13c5fa9d2c574f566457cafb622be89b8c65e7
|
refs/heads/master
| 2020-04-07T11:21:47.985726
| 2018-12-18T03:48:44
| 2018-12-18T03:48:44
| 158,323,002
| 0
| 0
| null | 2018-11-20T03:02:49
| 2018-12-18T03:48:11
| 2018-12-18T03:48:45
|
Python
|
[
{
"alpha_fraction": 0.6485195755958557,
"alphanum_fraction": 0.6924546360969543,
"avg_line_length": 39.30769348144531,
"blob_id": "dea3ce9622455169ec67077b7d6be389dc1ed08f",
"content_id": "f366e7f8f9ff021ce05e11ab9429573a4cac5096",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1047,
"license_type": "no_license",
"max_line_length": 111,
"num_lines": 26,
"path": "/Prac_06/language.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "from Prac_06.programming_language import ProgrammingLanguage\nruby = ProgrammingLanguage(\"Ruby\", \"Dynamic\", True, 1995)\npython = ProgrammingLanguage(\"Python\", \"Dynamic\", True, 1991)\nvisual_basic = ProgrammingLanguage(\"Visual Basic\", \"Static\", False, 1991)\nc_plus_plus = ProgrammingLanguage(\"C++\", \"Static\", False, 1983)\njava = ProgrammingLanguage(\"Java\", \"Static\", \"True\", 1995)\nprogramming_language = [\"Ruby,Dynamic,True,1995\", \"Python,Dynamic,True,1991\", \"Visual Basic,Static,False,1991\",\n \"C++,Static,False,1983\", \"Java,Static,True,1995\"]\nruby.get_field()\nruby.get_typing()\nruby.get_reflection()\nruby.get_field()\nfor i in range(len(programming_language)):\n language = programming_language[i].split(\",\")\n language = ProgrammingLanguage(language[0], language[1], language[2], language[3])\n language.get_field()\n language.get_typing()\n language.get_reflection()\n language.get_field()\n print(language.__str__())\n\n\n# print(str(ruby.is_dynamic()))\n#\n# print(python.__str__())\n# print(visual_basic.__str__())"
},
{
"alpha_fraction": 0.6366906762123108,
"alphanum_fraction": 0.6366906762123108,
"avg_line_length": 22.25,
"blob_id": "148a36d1b5e28616adfaca11047984c29090d27c",
"content_id": "212baac42dcc62b537eed07e0b27b50366fed53a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 278,
"license_type": "no_license",
"max_line_length": 45,
"num_lines": 12,
"path": "/Prac_05/count_word.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "COUNT_WORD = {}\ntext = str(input(\"please insert a text: \"))\nword_list = text.split(\" \")\n\nprint(word_list)\nfor word in word_list:\n count = word_list.count(word)\n COUNT_WORD[word] = count\n\n\nfor key, value in sorted(COUNT_WORD.items()):\n print(\"{}: {}\".format(key, value))"
},
{
"alpha_fraction": 0.40283286571502686,
"alphanum_fraction": 0.423229455947876,
"avg_line_length": 40.069766998291016,
"blob_id": "b6487a2730c3650e73e55ec00f014ca0d8d3458c",
"content_id": "f75df00b5ffdf035287b688735954d592aef50ea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1765,
"license_type": "no_license",
"max_line_length": 165,
"num_lines": 43,
"path": "/Prac_01/sequence_generator.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def main():\n x = int(input(\"Enter x\"))\n y = int(input(\"Enter y\"))\n user_choice = str(input(\"1. Show the even numbers from x to y\\n2. Show the odd numbers from x to y\\n3. Show the squares from x to y\\n4. Exit the program\\n\"))\n while user_choice != \"1\" and user_choice != \"2\" and user_choice != \"3\" and user_choice != \"4\":\n print(\"invalid value\")\n user_choice = str(input(\"1. Show the even numbers from x to y\\n2. Show the odd numbers from x to y\\n3. Show the squares from x to y\\n4. Exit the program\\n\"))\n while user_choice != \"4\":\n if user_choice == \"1\":\n if x > y:\n for i in range(x, y, -1):\n if i % 2 == 0:\n print(i, end=' ')\n print()\n else:\n for i in range(x, y, 1):\n if i % 2 == 0:\n print(i, end=' ')\n print()\n elif user_choice == \"2\":\n if x > y:\n for i in range(x, y, -1):\n if i % 2 != 0:\n print(i, end=' ')\n print()\n else:\n for i in range(x, y, 1):\n if i % 2 != 0:\n print(i, end=' ')\n print()\n elif user_choice == \"3\":\n if x > y:\n for i in range(x, y, -1):\n print(pow(i, 2), end=' ')\n print()\n else:\n for i in range(x, y, 1):\n print(pow(i, 2), end=' ')\n print()\n user_choice = str(input(\"1. Show the even numbers from x to y\\n2. Show the odd numbers from x to y\\n3. Show the squares from x to y\\n4. Exit the program\\n\"))\n print(\"Finished\")\n\nmain()"
},
{
"alpha_fraction": 0.4955125153064728,
"alphanum_fraction": 0.4983467161655426,
"avg_line_length": 38.96226501464844,
"blob_id": "3b02c77d7d6a9f95672bccf07ba52a0574868546",
"content_id": "c822a846f75f8dfa9b4b7827a11fc23d9d06b8af",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2117,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 53,
"path": "/Prac_06/car_driving_simulator.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "from Prac_06.car import Car\ndef main():\n print(\"Let's drive!\")\n car_name = str(input(\"Enter your car name\"))\n my_car = Car(car_name)\n print(\"{}, fuel = {}, odo = {}\".format(my_car.name, my_car.fuel, my_car.odometer))\n menu_choice = insert_menu()\n while menu_choice.lower() == \"d\" or menu_choice.lower() == \"r\":\n\n if menu_choice.lower() == \"d\":\n while True:\n try:\n distance = float(input(\"how many km you want to drive? \"))\n while distance < 0:\n print(\"the distance must be >=0\")\n distance = float(input(\"how many km you want to drive? \"))\n\n break;\n except ValueError:\n print(\"Invalid Input Value\")\n my_car.drive(distance)\n print(\"{}, fuel = {}, odo = {}\".format(my_car.name, my_car.fuel, my_car.odometer))\n menu_choice = insert_menu()\n else:\n while True:\n try:\n amount = float(input(\"How many units of fuel do you want to add to the car? \"))\n while amount < 0:\n print(\"Fuel amount must be >= 0\")\n amount = float(input(\"How many units of fuel do you want to add to the car? \"))\n\n break;\n except ValueError:\n print(\"Invalid Input Value\")\n my_car.add_fuel(amount)\n print(\"{}, fuel = {}, odo = {}\".format(my_car.name, my_car.fuel, my_car.odometer))\n menu_choice = insert_menu()\n\n\ndef insert_menu():\n while True:\n try:\n menu_choice = str(input(\"Menu\\nd) drive\\nr) refuel\\nq) quit\\nEnter your choice: \"))\n while menu_choice.lower() != \"d\" and menu_choice.lower() != \"r\" and menu_choice.lower() != \"q\":\n print(\"Invalid input value!\")\n menu_choice = str(input(\"Menu\\nd) drive\\nr) refuel\\nq) quit\\nEnter your choice: \"))\n break;\n except ValueError:\n print(\"Invalid input value!\")\n return menu_choice\n\n\nmain()"
},
{
"alpha_fraction": 0.5529412031173706,
"alphanum_fraction": 0.5666666626930237,
"avg_line_length": 30.9375,
"blob_id": "5840e67f537664baf6822973f40dd5f3879624d3",
"content_id": "44717d2148e93b849caf90322f017e095db87435",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 510,
"license_type": "no_license",
"max_line_length": 75,
"num_lines": 16,
"path": "/Prac_01/shop_calculator.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def main():\n list_price = []\n total = 0\n number_item = int(input(\"Enter Number of Item: \"))\n while number_item <= 0:\n print(\"invalid Number!\")\n number_item = int(input(\"Enter Number of Item: \"))\n for i in range(number_item):\n price = float(input(\"Price of Item: \"))\n list_price.append(price)\n total = total + list_price[i]\n if total > 100:\n total = total - total*0.1\n print(\"Total price for \" + str(number_item) + \"item is $\" + str(total))\n\nmain()"
},
{
"alpha_fraction": 0.5871921181678772,
"alphanum_fraction": 0.626600980758667,
"avg_line_length": 35.25,
"blob_id": "9d7027dafd610042885496fff660187fa1d990a1",
"content_id": "8bf49479ce09c96ad8d49df1941f79519fada038",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1015,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 28,
"path": "/Prac_07/Simple_App.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "from kivy.app import App\nfrom kivy.lang import Builder\nfrom kivy.uix.label import Label\nfrom kivy.uix.button import Button\nfrom kivy.properties import StringProperty\n\n\nclass SimpleApp(App):\n def __init__(self, **kwargs):\n \"\"\"Construct main app.\"\"\"\n super().__init__(**kwargs)\n # basic data example - dictionary of names: phone numbers\n self.name_to_phone = {\"Bob Brown\": \"0414144411\", \"Cat Cyan\": \"0441411211\", \"Oren Ochre\": \"0432123456\", \"Nhan Gia Huy\": \"0128947133\"}\n\n def build(self):\n \"\"\"Build the Kivy GUI.\"\"\"\n self.title = \"Dynamic Widgets\"\n self.root = Builder.load_file('Simple_App.kv')\n self.create_widgets()\n return self.root\n\n def create_widgets(self):\n \"\"\"Create buttons from dictionary entries and add them to the GUI.\"\"\"\n for name in self.name_to_phone:\n label = Label(text= \"{}'s number is {}\".format(name, self.name_to_phone[name]), id=name)\n self.root.ids.entries_box.add_widget(label)\n\nSimpleApp().run()\n"
},
{
"alpha_fraction": 0.5579832196235657,
"alphanum_fraction": 0.5579832196235657,
"avg_line_length": 36.25,
"blob_id": "8ef9552d900dc5825a4c34fad8ccc0a4badc5f0f",
"content_id": "2cc2ae5715282812671496c02e6fd1f96fa9b033",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 595,
"license_type": "no_license",
"max_line_length": 91,
"num_lines": 16,
"path": "/Prac_01/menu.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def main():\n user_name = str(input(\"Enter Name: \"))\n print(\"(H)ello\\n(G)oodbye\\n(Q)uit\\n\")\n user_choice = str(input(\"Please Enter Choice!\\n\"))\n while user_choice.upper() != \"H\" and user_choice.upper() != \"G\" and user_choice != \"Q\":\n print(\"invalid menu!\")\n user_choice = str(input(\"Please Enter Choice!\\n\"))\n while user_choice.upper() != \"Q\":\n if user_choice.upper() == \"H\":\n print(\"Hello \" + user_name)\n else:\n print(\"Goodbye \" + user_name)\n user_choice = str(input(\"Please Enter Choice!\\n\"))\n print(\"Finished\")\n\nmain()"
},
{
"alpha_fraction": 0.5736040472984314,
"alphanum_fraction": 0.5913705825805664,
"avg_line_length": 25.066667556762695,
"blob_id": "f67ebc24ea5b71f270ee94f66514fc8cb348fd51",
"content_id": "1335adef9ed872e6db35c304385d0a37c257d7a2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 394,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 15,
"path": "/Prac_05/extension_1.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "from datetime import datetime\nnow = datetime.now()\n\nNAME = []\nDOBS = []\nLIST_NAME = {}\n\nfor i in range(5):\n name = str(input(\"Name: \"))\n LIST_NAME[name] = str(input(\"Day of Birth: \"))\n\nfor key in LIST_NAME:\n date_of_birth = LIST_NAME[key].split(\"/\")\n age = now.year - int(date_of_birth[-1])\n print(\"Name: {:<10} Date of Birth{:<10} Age{:<5}\".format(key, LIST_NAME[key], age))\n\n\n\n"
},
{
"alpha_fraction": 0.5856904983520508,
"alphanum_fraction": 0.662229597568512,
"avg_line_length": 36.5625,
"blob_id": "034f8c2bda9ebb520c4dd4175766ced8fea63166",
"content_id": "48763a53c9f86f8ded209cf6e4262f609174786a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 601,
"license_type": "no_license",
"max_line_length": 74,
"num_lines": 16,
"path": "/Prac_05/extension3.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "\nTARIFF = {\"11\": 0.244618, \"31\": 0.136928, \"22\": 0.152412}\nprint(\"Electricity Bill Estimator 2.0\")\ntype_tariff = str(input(\"Which tariff? 11 or 31: \"))\n\nwhile type_tariff != \"13\" and type_tariff != \"11\" and type_tariff != \"22\":\n print(\"invalid type! Please enter again!\")\n type_tariff = int(input(\"which tariff? 11 or 13 or 22: \"))\nprice_tariff = TARIFF[type_tariff]\n\ndaily_use = float(input(\"Enter daily use in kWh: \"))\n\nbilling_days = int(input(\"Enter number of billing days: \"))\n\ntotal_bill = (daily_use * billing_days * price_tariff)\n\nprint (\"Estimated bill : $\" + str(round(total_bill, 2)))"
},
{
"alpha_fraction": 0.6107010841369629,
"alphanum_fraction": 0.6236162185668945,
"avg_line_length": 29.16666603088379,
"blob_id": "24fcc6446efd24dfcf4847c122eb3299dbbc45f3",
"content_id": "35c86e17113cc687b7a968ce8ba105b6870fb5a0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 542,
"license_type": "no_license",
"max_line_length": 96,
"num_lines": 18,
"path": "/Prac_04/cumulative_total.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "INCOME = []\ndef main():\n number_month = int(input(\"how many month?\"))\n insert_income(number_month)\n show_income_report()\n\ndef insert_income(number_month):\n for month in range(number_month):\n monthly_income = float(input(\"enter income for month \" + str(month + 1)))\n INCOME.append(monthly_income)\n\ndef show_income_report():\n total = 0\n for month in range(len(INCOME)):\n total = total + INCOME[month]\n print(\"Month {} - Income: ${:10} Total: ${:10}\".format(month + 1, INCOME[month], total))\n\nmain()"
},
{
"alpha_fraction": 0.5113500356674194,
"alphanum_fraction": 0.5280764698982239,
"avg_line_length": 28.75,
"blob_id": "c18c223338cfe9c193a977f8f7a673d460b782fb",
"content_id": "3cfefaf8ec13b5eb7c722e55542e501a12c8544b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 837,
"license_type": "no_license",
"max_line_length": 127,
"num_lines": 28,
"path": "/Prac_06/guitar_test.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "from Prac_06.guitar import Guitar\n\n\nmy_guitar = []\nstr1 = \"\"\nname = str(input(\"Name: \"))\nyear = int(input(\"Year: \"))\ncost = float(input(\"Cost: \"))\n\nwhile name != \"\":\n print(\"{} ({}) : ${:,} added.\".format(name, year, cost))\n str1 = str1 + name + \",\" + str(year) + \",\" + str(cost)\n my_guitar.append(str1)\n name = str(input(\"Name: \"))\n if name == \"\":\n break;\n year = int(input(\"Year: \"))\n cost = float(input(\"Cost: \"))\n\nfor i in range(len(my_guitar)):\n guitar = my_guitar[i].split(\",\")\n guitar = Guitar(guitar[0], int(guitar[1]), guitar[2])\n print(\"Guitar {}: {:>10} ({}), worth ${:>15}\".format(i+1, guitar.get_name(), guitar.get_year(), guitar.get_cost()), end=\"\")\n guitar.get_age()\n if guitar.is_vintage() == True:\n print(\"(Vintage)\", end=\"\\n\")\n else:\n print(\"\", end=\"\\n\")\n\n\n\n\n"
},
{
"alpha_fraction": 0.6169154047966003,
"alphanum_fraction": 0.6368159055709839,
"avg_line_length": 27.85714340209961,
"blob_id": "f6881d9c9af1967fb310397bb9e7605e5005f949",
"content_id": "735accd9a70b5e9e8fd142c1d68de5e60ca7bdff",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 201,
"license_type": "no_license",
"max_line_length": 74,
"num_lines": 7,
"path": "/Prac_04/Lottery_Ticket_Generator.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "import random\n\nquick_pick = int(input(\"how many quick picks do you wish to generate?\\n\"))\nfor i in range(quick_pick):\n for j in range(5):\n print(random.randint(1, 45), end=\"\\t\")\n print(\"\")"
},
{
"alpha_fraction": 0.6334037780761719,
"alphanum_fraction": 0.6418604850769043,
"avg_line_length": 41.25,
"blob_id": "db77f2af581f7bbdf4989578133b2ee2a8322def",
"content_id": "104ed3bcb7fb606c9782bc35bac8ace1faf52392",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2365,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 56,
"path": "/Prac_02/password_generator.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "import random\n\nMIN_LENGTH = 5\nMAX_LENGTH = 15\nCHARACTERS = \"qwertyuiopasdfghjklzxcvbnm\"\nNUMERIC = \"0123456789\"\nSPECIAL_CHARACTERS = \"!@#$%^&*()_-=+`~,./'[]<>?{}|\\\\\"\npassword = \"\"\nwhile True:\n try:\n password_length = int(input(\"enter length of password between {} and {}\".format(MIN_LENGTH, MAX_LENGTH)))\n if password_length >= 5 and password_length <= 15:\n break\n else:\n print(\"invalid password length! Please enter again!\")\n except ValueError:\n print(\"invalid password length! Please enter again!\")\nwhile True:\n try:\n number_upper_character = int(input(\"enter number of upper character\"))\n if number_upper_character <= password_length:\n for i in range(0, number_upper_character):\n password += random.choice(CHARACTERS.upper())\n break\n else:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n except ValueError:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n\nwhile True:\n try:\n number_special_character = int(input(\"enter number of special character\"))\n if number_upper_character + number_special_character <= password_length:\n for i in range(0, number_special_character):\n password += random.choice(SPECIAL_CHARACTERS)\n break\n else:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n except ValueError:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n\nwhile True:\n try:\n number_numeric = int(input(\"enter number of numeric\"))\n if number_upper_character + number_special_character + number_numeric <= password_length:\n for i in range(0, number_numeric):\n password += random.choice(NUMERIC)\n break\n else:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n except ValueError:\n print(\"total number of character must be less than or equal {}\".format(password_length))\n\nfor i in range(0, password_length - number_upper_character - number_numeric - number_special_character):\n password += random.choice(CHARACTERS)\nprint(\"your password is {}\".format(password))"
},
{
"alpha_fraction": 0.5579567551612854,
"alphanum_fraction": 0.5913556218147278,
"avg_line_length": 17.88888931274414,
"blob_id": "d41b2e29a48bc8b239e65cc740b2206a9bb81a4d",
"content_id": "af7c49475a8649f5593c0a24e0a0d3ba9eba70b4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 509,
"license_type": "no_license",
"max_line_length": 37,
"num_lines": 27,
"path": "/Prac_04/warm_up.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "NUMBER = [3, 1, 4, 1, 5, 0, 2]\n\ndef main():\n length = len(NUMBER)\n change_first_element()\n change_last_element(length)\n get_element()\n check_value()\n\ndef change_first_element():\n NUMBER[0] = 10\n print(NUMBER)\n\ndef change_last_element(length):\n NUMBER[length - 1] = 1\n print(NUMBER)\n\ndef get_element():\n new_number = NUMBER[1:-1]\n print(new_number)\n\ndef check_value():\n if 9 in NUMBER:\n print(\"9 is in the list\")\n else:\n print(\"9 is not in the list\")\nmain()"
},
{
"alpha_fraction": 0.527566134929657,
"alphanum_fraction": 0.5450470447540283,
"avg_line_length": 41.903846740722656,
"blob_id": "70850d69770006cdeacb31ada420776991a12daa",
"content_id": "2d4d98bd1d12645050addadf5ca078ecbf2144df",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2231,
"license_type": "no_license",
"max_line_length": 122,
"num_lines": 52,
"path": "/Prac_03/acsii_table.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def main():\n MAX_NUMBER = 127\n MIN_NUMBER = 33\n choice = int(input(\"main menu\\n1.character --> ASCII code\\n2.ASCII code -->character\\n3.ascii table\\n4.quit\\n\"))\n while choice != 1 and choice != 2 and choice != 3 and choice != 4:\n print(\"invalid choice!\")\n choice = int(input(\"main menu\\n1.character --> ASCII code\\n2.ASCII code -->character\\n3.ascii table\\n4.quit\\n\"))\n while choice != 4:\n if choice == 1:\n character = str(input(\"enter character\\n\"))\n while len(character) > 1:\n character = str(input(\"please enter single character\\n\"))\n ascii_code = ord(character)\n print(\"The ASCII code for {} is {}\".format(character, ascii_code))\n elif choice == 2:\n number = get_number(MIN_NUMBER,MAX_NUMBER)\n character = chr(number)\n print(\"The character for {} is {}\".format(number, character))\n else:\n number_column = int(input(\"how many column do you want to print in ascii table?\\n\"))\n number_row = (MAX_NUMBER + MIN_NUMBER + 1) // number_column\n for row in range(number_row + 1):\n starting_value = MIN_NUMBER + row\n value = starting_value\n for column in range(number_column - 1):\n print_value = value + (number_row * column)\n print(\"{:6} {:>2}\".format(print_value, chr(print_value)), end=\"\")\n value += 1\n value_to_print = value + ((column + 1) * number_row)\n if value_to_print <= MAX_NUMBER:\n print(\"{:6} {:>2}\".format(value_to_print, chr(value_to_print)), end=\"\")\n print()\n choice = int(input(\"\\nmain menu\\n1.character --> ASCII code\\n2.ASCII code -->character\\n3.ascii table\\n4.quit\\n\"))\n print(\"thank you for using program!\")\n\n\ndef get_number(lower, upper):\n while True:\n try:\n number = int(input(\"enter number between {} and {}\\n\".format(lower, upper)))\n if number >= 33 and number <= 127:\n break\n else:\n print(\"invalid number\\n\")\n except ValueError:\n print(\"invalid number\\n\")\n return number\n\n\n\n\nmain()\n"
},
{
"alpha_fraction": 0.4597315490245819,
"alphanum_fraction": 0.4932885766029358,
"avg_line_length": 28.899999618530273,
"blob_id": "47c9d0306a682af091c9456c213b0403b2068393",
"content_id": "4bb90e3327af84669cf3b18a77eff453e8e6fa28",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 298,
"license_type": "no_license",
"max_line_length": 50,
"num_lines": 10,
"path": "/Prac_01/sales_bonus.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def main():\n sales = float(input(\"Enter sales: $ \"))\n while sales >= 0:\n if sales >= 1000:\n user_bonus = 0.15 * sales\n else:\n user_bonus = 0.1 * sales\n print(\"user's bonus = \" + str(user_bonus))\n sales = float(input(\"Enter sales: $ \"))\nmain()"
},
{
"alpha_fraction": 0.5925176739692688,
"alphanum_fraction": 0.62992924451828,
"avg_line_length": 40.25,
"blob_id": "1201f02a066bbc363cc32dc800eebc0a79d90ff1",
"content_id": "c2626a6b59e70920f0a7a0701d9d99a5a09d526d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 989,
"license_type": "no_license",
"max_line_length": 63,
"num_lines": 24,
"path": "/Prac_01/electric_bill.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def Estimator_1():\n print(\"Electric bill estimator\")\n price = int(input(\"Enter the cents per kWh: \"))\n amount_enegy = float(input(\"Enter the daily use in kWh: \"))\n billing_day = int(input(\"Enter number of billing days: \"))\n total_bill = (amount_enegy * billing_day * price) / 100\n print(\"Estimated bill: $\" + str(total_bill))\n\ndef Estimator_2():\n print(\"Electric bill estimator 2.0\")\n type_tariff = int(input(\"which tariff? 11 or 13: \"))\n while type_tariff != 13 and type_tariff != 11:\n print(\"invalid type! Please enter again!\")\n type_tariff = int(input(\"which tariff? 11 or 13: \"))\n if type_tariff == 11:\n price_tariff = 0.244618\n else:\n price_tariff = 0.136928\n amount_enegy = float(input(\"Enter the daily use in kWh: \"))\n billing_day = int(input(\"Enter number of billing days: \"))\n total_bill = (amount_enegy * billing_day * price_tariff)\n print (\"Estimated bill : $\" + str(round(total_bill, 2)))\n\nEstimator_2()"
},
{
"alpha_fraction": 0.5231481194496155,
"alphanum_fraction": 0.5694444179534912,
"avg_line_length": 26.125,
"blob_id": "6cbe038011ce409ba75944dbe0c601db8892abee",
"content_id": "7e85bbe97930226ea2163b35bd844536196291e1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 216,
"license_type": "no_license",
"max_line_length": 46,
"num_lines": 8,
"path": "/Prac_05/Nhap.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "name = [\"huy\", \"nhan\", \"gia\", \"nhung\", \"rosy\"]\nage = [20, 19, 31, 23, 21]\nlist_of_person = {}\n\ndef createdictionary():\n for i in range(len(name)):\n list_of_person[name[i]] = age[i]\n print(list_of_person)"
},
{
"alpha_fraction": 0.66105055809021,
"alphanum_fraction": 0.6868186593055725,
"avg_line_length": 41.08333206176758,
"blob_id": "ab99bdb883e2f49183c2c20e232869bd08687e92",
"content_id": "1aedde04816c98d1b840b55e735c3faeb19b7fea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1009,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 24,
"path": "/Prac_03/GPS.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "import random\ndef main():\n POPULATION = 1000\n MAX_INCREASE_BORN = 20\n MIN_INCREASE_BORN = 10\n MAX_DECREASE_DIED = 25\n MIM_DECREASE_DIED = 5\n print(\"Welcome to the Gopher Population Simulator\\nStarting population: 1000\")\n for year in range(1, 10):\n print(\"year {}\\n*****\".format(year))\n number_gopher_born = random_born(POPULATION, MAX_INCREASE_BORN, MIN_INCREASE_BORN)\n number_gopher_died = random_died(POPULATION, MAX_DECREASE_DIED, MIM_DECREASE_DIED)\n POPULATION = POPULATION + number_gopher_born - number_gopher_died\n print(\"{} gophers were born. {} died.\\nPopulation: {}\".format(number_gopher_born,number_gopher_died,POPULATION))\n\ndef random_born(population, max, min):\n number_gopher_born = round(population * (round(random.randint(min, max), 0)/100))\n return number_gopher_born\n\ndef random_died(population, max, min):\n number_gopher_died = round(population * (round(random.randint(min, max), 0)/100))\n return number_gopher_died\n\nmain()"
},
{
"alpha_fraction": 0.47154471278190613,
"alphanum_fraction": 0.5284552574157715,
"avg_line_length": 19.33333396911621,
"blob_id": "0c3ce4e8ba5e1dc3f3301201513a285b72e87781",
"content_id": "7b3475c607f253b4033d9be7fbcf318d59487a70",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 123,
"license_type": "no_license",
"max_line_length": 40,
"num_lines": 6,
"path": "/Prac_02/string_formatting_examples.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "\ndef main():\n numbers = [0, 50, 100]\n for i in range(len(numbers)):\n print(\"{:3}\".format(numbers[i]))\n\nmain()\n"
},
{
"alpha_fraction": 0.7377278804779053,
"alphanum_fraction": 0.7503506541252136,
"avg_line_length": 40.882354736328125,
"blob_id": "11c1f8bd39afa8dac24f07b456c1fc12539f093d",
"content_id": "0a23c5fabf84a7a802489dd3f3534d5fb24bfba7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 713,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 17,
"path": "/Prac_03/temperatures.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "\ndef main():\n celsius_temperature = float(input(\"Enter the temperature in Celsius format\"))\n fahrenheit_temperature = Celsius_to_Fahrenheit(celsius_temperature)\n print(fahrenheit_temperature)\n fahrenheit_temperature = float(input(\"Enter the temperature in Fahrenheit format\"))\n celsius_temperature = Fahrenheit_to_Celsius(fahrenheit_temperature)\n print(str(round(celsius_temperature, 2)))\n\ndef Celsius_to_Fahrenheit(celsius_temperature):\n fahrenheit_temperature = (celsius_temperature * (9 / 5)) + 32\n return fahrenheit_temperature\n\ndef Fahrenheit_to_Celsius(fahrenheit_temperature):\n celsius_temperature = (fahrenheit_temperature - 32) * (5 / 9)\n return celsius_temperature\n\nmain()\n"
},
{
"alpha_fraction": 0.5600000023841858,
"alphanum_fraction": 0.6028571724891663,
"avg_line_length": 37.88888931274414,
"blob_id": "9f298c2f2762d0f7c531b3f8290022d4c7f50928",
"content_id": "6c852edcfda22f2043bc1f2c8e578a3b898ca955",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 350,
"license_type": "no_license",
"max_line_length": 129,
"num_lines": 9,
"path": "/Prac_05/color_dictionary.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "\nCOLOR_LIST = {\"AliceBlue\": \"#f0f8ff\", \"aquamarine1\": \"#7fffd4\", \"azure1\": \"#f0ffff\", \"blue1\": \"#0000ff\", \"BlueViolet\": \"#8a2be2\"}\n\ncolor = input(\"Enter name of color \")\nwhile color != \"\":\n if color in COLOR_LIST:\n print(color, \"is\", COLOR_LIST[color])\n else:\n print(\"Invalid short state\")\n color = input(\"Enter short state: \")"
},
{
"alpha_fraction": 0.5359588861465454,
"alphanum_fraction": 0.5410959124565125,
"avg_line_length": 20.66666603088379,
"blob_id": "21eca9d9e548205b8a8776c126d4037538dafe1d",
"content_id": "355c00031b987a6a95740eb03022f704315ab0e5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 584,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 27,
"path": "/Prac_02/File.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "def one():\n user_name = str(input(\"enter your name: \"))\n out_file = open(\"name.txt\", \"w\")\n print(user_name, file = out_file)\n out_file.close()\n\ndef two():\n out_file = open(\"name.txt\", \"r\")\n print(\"your name is \" + out_file.read())\n out_file.close()\n\ndef three():\n file = open(\"number\", \"r\")\n a = int(file.readline())\n b = int(file.readline())\n print(a + b)\n file.close()\n\ndef four():\n total = 0.0\n file = open(\"numbers\", \"r\")\n for i in file:\n total += float(i)\n print(\"the total is:{:.2f}\".format(total))\n file.close()\n\nfour()"
},
{
"alpha_fraction": 0.5729265809059143,
"alphanum_fraction": 0.5805529356002808,
"avg_line_length": 22.33333396911621,
"blob_id": "a28f5aca9649693bb04f31bbec9c62eaccd2bb6d",
"content_id": "88c285f9236c713df5f4d674c673be6f4cb9f7f6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1049,
"license_type": "no_license",
"max_line_length": 57,
"num_lines": 45,
"path": "/Prac_04/intermediate_exercises_1.py",
"repo_name": "NhanGiaHuy/CP1404_Pactical",
"src_encoding": "UTF-8",
"text": "NUMBER = []\n\ndef main():\n count = 1\n number = int(input(\"Enter Number\" + str(count)))\n NUMBER.append(number)\n\n while number > 0:\n count += 1\n number = int(input(\"Enter Number\" + str(count)))\n NUMBER.append(number)\n\n print(\"the first number is: \" + str(NUMBER[0]))\n print(\"the last number is: \" + str(NUMBER[-1]))\n min_number = find_min()\n print(\"the smallest number is:\" + str(min_number))\n max_number = find_max()\n print(\"the largest number is:\" + str(max_number))\n average = find_average()\n print(\"the average of the number is:\" + str(average))\ndef find_min():\n min_value = NUMBER[0]\n for value in NUMBER:\n if value < min_value:\n min_value = value\n return min_value\n\n\n\ndef find_max():\n max_value = NUMBER[0]\n for value in NUMBER:\n if value > max_value:\n max_value = value\n return max_value\n\ndef find_average():\n total = 0\n for value in NUMBER:\n total += value\n average = total / len(NUMBER)\n return average\n\n\nmain()"
}
] | 24
|
arbaazkhan2/finalproj650
|
https://github.com/arbaazkhan2/finalproj650
|
2ecb093fff72dd4491f07a52da823574cc60e658
|
a8f51f37826756f60a9bf23dbb1a9c6941bb6ead
|
dd11b5adbda7087e332d7f016088704f24c3cd80
|
refs/heads/master
| 2019-01-26T21:29:10.241292
| 2017-05-02T01:13:16
| 2017-05-02T01:13:16
| 86,270,601
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5714612603187561,
"alphanum_fraction": 0.6016464829444885,
"avg_line_length": 45.53191375732422,
"blob_id": "b224e771dea7042cb35284d53a71dc2137a30519",
"content_id": "85ef9a7859844a4fca03e867b10cc834e20f85b2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4373,
"license_type": "no_license",
"max_line_length": 131,
"num_lines": 94,
"path": "/tensorflow-value-iteration-networks/Refactoring/CPU_version/vin_class/model.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport tensorflow as tf\nfrom utils import *\nimport pdb\n\nclass dnc(object):\n\n \n def __init__(self,config):\n self.config = config\n self.k = self.config.k # Number of value iterations performed\n self.ch_i = self.config.ch_i # Channels in input layer\n self.ch_h = self.config.ch_h # Channels in initial hidden layer\n self.ch_q = self.config.ch_q # Channels in q layer (~actions)\n self.state_batch_size = self.config.statebatchsize # k+1 state inputs for each channel\n\n self.bias = tf.Variable(np.random.randn(1, 1, 1, self.ch_h) * 0.01, dtype=tf.float16)\n # weights from inputs to q layer (~reward in Bellman equation)\n self.w0 = tf.Variable(np.random.randn(3, 3, self.ch_i, self.ch_h) * 0.01, dtype=tf.float16)\n self.w1 = tf.Variable(np.random.randn(1, 1, self.ch_h, 1) * 0.01, dtype=tf.float16)\n self.w = tf.Variable(np.random.randn(3, 3, 1, self.ch_q) * 0.01, dtype=tf.float16)\n self.w_fb = tf.Variable(np.random.randn(3, 3, 1, self.ch_q) * 0.01, dtype=tf.float16)\n self.w_o = tf.Variable(np.random.randn(self.ch_q, 5) * 0.01, dtype=tf.float16)\n self.X = tf.placeholder(tf.float16, name=\"X\", shape=[None, self.config.imsize, self.config.imsize, self.config.ch_i])\n self.S1 = tf.placeholder(tf.int32, name=\"S1\", shape=[None, self.config.statebatchsize])\n self.S2 = tf.placeholder(tf.int32, name=\"S2\", shape=[None, self.config.statebatchsize])\n self.y = tf.placeholder(tf.int32, name=\"y\", shape=[None])\n \n self.VI_Block()\n self.sess = tf.Session() \n init = tf.global_variables_initializer()\n saver = tf.train.Saver()\n if self.config.log:\n for var in tf.trainable_variables():\n tf.summary.histogram(var.op.name, var)\n summary_op = tf.summary.merge_all()\n summary_writer = tf.summary.FileWriter(self.config.logdir, self.sess.graph)\n self.sess.run(init)\n\n\n def VI_Block(self):\n \n def conv2d_flipkernel(x, k, name=None):\n return tf.nn.conv2d(x, flipkernel(k), name=name,strides=(1, 1, 1, 1), padding='SAME')\n\n\n # initial conv layer over image+reward prior\n h = conv2d_flipkernel(self.X, self.w0, name=\"h0\") + self.bias\n\n r = conv2d_flipkernel(h, self.w1, name=\"r\")\n q = conv2d_flipkernel(r, self.w, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n\n for i in range(0, self.k-1):\n rv = tf.concat_v2([r, v], 3)\n wwfb = tf.concat_v2([self.w, self.w_fb], 2)\n\n q = conv2d_flipkernel(rv, wwfb, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n\n q = conv2d_flipkernel(tf.concat_v2([r, v], 3),\n tf.concat_v2([self.w, self.w_fb], 2), name=\"q\")\n q = tf.transpose(q, perm=[0, 3, 1, 2])\n bs = tf.shape(q)[0]\n rprn = tf.reshape(tf.tile(tf.reshape(tf.range(bs), [-1, 1]), [1, self.state_batch_size]), [-1])\n ins1 = tf.cast(tf.reshape(self.S1, [-1]), tf.int32)\n ins2 = tf.cast(tf.reshape(self.S2, [-1]), tf.int32)\n idx_in = tf.transpose(tf.stack([ins1, ins2, rprn]), [1, 0])\n q_out = tf.gather_nd(tf.transpose(q, [2, 3, 0, 1]), idx_in, name=\"q_out\")\n \n self.logits = tf.matmul(q_out, self.w_o)\n self.nn = tf.nn.softmax(self.logits, name=\"output\")\n \n self.y_ = tf.cast(self.y, tf.int64)\n self.cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(logits=self.logits, labels=self.y_, name='cross_entropy')\n self.cross_entropy_mean = tf.reduce_mean(self.cross_entropy, name='cross_entropy_mean')\n tf.add_to_collection('losses', self.cross_entropy_mean)\n self.cost = tf.add_n(tf.get_collection('losses'), name='total_loss')\n self.optimizer = tf.train.RMSPropOptimizer(learning_rate=self.config.lr, epsilon=1e-6, centered=True).minimize(self.cost)\n\n self.cp = tf.cast(tf.argmax(self.nn, 1), tf.int32)\n self.err = tf.reduce_mean(tf.cast(tf.not_equal(self.cp, self.y), dtype=tf.float16))\n\n\n def learner(self,X_,S1_,S2_,y1):\n rew = X_[:, :, :, 1]\n goal = np.where(rew != 0)\n fd = {self.X: X_, self.S1: S1_, self.S2: S2_,self.y: y1}\n _, e_, c_ = self.sess.run([self.optimizer, self.err, self.cost], feed_dict=fd)\n #print e_ \n #print c_\n \n return e_,c_\n #pdb.set_trace()"
},
{
"alpha_fraction": 0.5990680456161499,
"alphanum_fraction": 0.6349270939826965,
"avg_line_length": 39.121952056884766,
"blob_id": "986814aebce559cfbea51243202fa77d957b893b",
"content_id": "d8cf934e97827e4b27adafb12a5f7614feadd5cd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4936,
"license_type": "no_license",
"max_line_length": 123,
"num_lines": 123,
"path": "/tensorflow-value-iteration-networks/Refactoring/GPU_version/model_lstm_previn.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport tensorflow as tf\nfrom utils import *\nimport pdb\n\ndef conv2d_flipkernel(x, k, name=None):\n return tf.nn.conv2d(x, flipkernel(k), name=name,\n strides=(1, 1, 1, 1), padding='SAME')\n\ndef VI_Block(X, S1, S2, config,c_in,h_in, img_copy):\n k = config.k # Number of value iterations performed\n ch_i = config.ch_i # Channels in input layer\n ch_h = config.ch_h # Channels in initial hidden layer\n ch_q = config.ch_q # Channels in q layer (~actions)\n state_batch_size = config.statebatchsize # k+1 state inputs for each channel\n \n x = img_copy\n x = tf.expand_dims(flatten(img_copy), [1])\n size = 512\n lstm = tf.contrib.rnn.BasicLSTMCell(size, state_is_tuple=True)\n lstm = tf.contrib.rnn.DropoutWrapper(lstm, input_keep_prob=0.75, output_keep_prob=0.75)\n state_size = lstm.state_size\n step_size = tf.shape(x)[:1]\n c_init = np.zeros((1, lstm.state_size.c), np.float16)\n h_init = np.zeros((1, lstm.state_size.h), np.float16)\n state_init = [c_init, h_init]\n state_in = [c_in, h_in]\n state_in = tf.contrib.rnn.LSTMStateTuple(c_in, h_in)\n lstm_outputs, lstm_state = tf.nn.dynamic_rnn(lstm, x, initial_state=state_in, sequence_length=step_size,time_major=False)\n lstm_c, lstm_h = lstm_state\n x = tf.reshape(lstm_outputs, [-1, size])\n logits = linear(x, 1024, \"action\", normalized_columns_initializer(0.01))\n inter = tf.reshape(logits, [1,32,32])\n img_copy = inter\n \n\n reward_prior = X[:,:,:,1]\n inter_lstm = tf.stack([img_copy,reward_prior, inter])\n inter_lstm = tf.transpose(inter_lstm, perm = [1,3,2,0])\n \n \n bias = tf.Variable(np.random.randn(1, 1, 1, ch_h) * 0.01, dtype=tf.float16)\n w0 = tf.Variable(np.random.randn(3, 3, 3, ch_h) * 0.01, dtype=tf.float16)\n w1 = tf.Variable(np.random.randn(1, 1, ch_h, 1) * 0.01, dtype=tf.float16)\n w = tf.Variable(np.random.randn(3, 3, 1, ch_q) * 0.01, dtype=tf.float16)\n w_fb = tf.Variable(np.random.randn(3, 3, 1, ch_q) * 0.01, dtype=tf.float16)\n w_o = tf.Variable(np.random.randn(ch_q, 5) * 0.01, dtype=tf.float16)\n\n h = conv2d_flipkernel(inter_lstm, w0, name=\"h0\") + bias\n\n r = conv2d_flipkernel(h, w1, name=\"r\")\n q = conv2d_flipkernel(r, w, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n\n \n for i in range(0, k-1):\n rv = tf.concat([r, v], 3)\n wwfb = tf.concat([w, w_fb], 2)\n\n q = conv2d_flipkernel(rv, wwfb, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n q = conv2d_flipkernel(tf.concat([r, v], 3),\n tf.concat([w, w_fb], 2), name=\"q\")\n q = tf.transpose(q, perm=[0, 3, 1, 2])\n\n bs = tf.shape(q)[0]\n rprn = tf.reshape(tf.tile(tf.reshape(tf.range(bs), [-1, 1]), [1, state_batch_size]), [-1])\n ins1 = tf.cast(tf.reshape(S1, [-1]), tf.int32)\n ins2 = tf.cast(tf.reshape(S2, [-1]), tf.int32)\n idx_in = tf.transpose(tf.stack([ins1, ins2, rprn]), [1, 0])\n q_out = tf.gather_nd(tf.transpose(q, [2, 3, 0, 1]), idx_in, name=\"q_out\")\n \n '''\n x = tf.expand_dims(flatten(q_out), [0])\n\n size = 512\n lstm = tf.contrib.rnn.BasicLSTMCell(size, state_is_tuple=True)\n #lstm = tf.contrib.rnn.DropoutWrapper(lstm, input_keep_prob=0.75, output_keep_prob=0.75)\n state_size = lstm.state_size\n step_size = tf.shape(x)[:1]\n c_init = np.zeros((1, lstm.state_size.c), np.float16)\n h_init = np.zeros((1, lstm.state_size.h), np.float16)\n state_init = [c_init, h_init]\n #c_in = tf.placeholder(tf.float16, [1, lstm.state_size.c])\n #h_in = tf.placeholder(tf.float16, [1, lstm.state_size.h])\n state_in = [c_in, h_in]\n state_in = tf.contrib.rnn.LSTMStateTuple(c_in, h_in)\n\n lstm_outputs, lstm_state = tf.nn.dynamic_rnn(lstm, x, initial_state=state_in, sequence_length=step_size,time_major=False)\n lstm_c, lstm_h = lstm_state\n x = tf.reshape(lstm_outputs, [-1, size])\n '''\n\n \n state_out = [lstm_c[:1, :], lstm_h[:1, :]]\n \n\n \n logits = tf.matmul(q_out, w_o, name=\"logits_output\")\n output = tf.nn.softmax(logits, name=\"prob_output\")\n \n return logits, output,state_out\n\n# similar to the normal VI_Block except there are separate weights for each q layer\n\ndef linear(x, size, name, initializer=None, bias_init=0):\n w = tf.get_variable(name + \"/w\", [x.get_shape()[1], size], initializer=initializer, dtype=tf.float16)\n b = tf.get_variable(name + \"/b\", [size], initializer=tf.constant_initializer(bias_init), dtype=tf.float16)\n return tf.matmul(x, w) + b\n\ndef flatten(x):\n return tf.reshape(x, [-1, np.prod(x.get_shape().as_list()[1:])])\n\ndef normalized_columns_initializer(std=1.0):\n def _initializer(shape, dtype=None, partition_info=None):\n out = np.random.randn(*shape).astype(np.float16)\n out *= std / np.sqrt(np.square(out).sum(axis=0, keepdims=True))\n return tf.constant(out)\n return _initializer\n\ndef categorical_sample(logits, d):\n value = tf.squeeze(tf.multinomial(logits - tf.reduce_max(logits, [1], keep_dims=True), 1), [1])\n return tf.one_hot(value, d)\n\n"
},
{
"alpha_fraction": 0.601783812046051,
"alphanum_fraction": 0.6214585304260254,
"avg_line_length": 25.533641815185547,
"blob_id": "bbfffc10d74dbc3afa96ed7828a77233c37c4d0a",
"content_id": "52d5ebe2067da797f089d918ea1c530c3f281571",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 11436,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 431,
"path": "/simulator/GenerateTraining.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport argparse\nimport sys\nfrom Map import *\nfrom PathPlanners import *\nfrom Simulator import *\nimport pickle\nimport time\n\ntunnel_options = {'opening': 1, 'length': 20, 'closed': True, 'dir': 'Left', 'spawn_rand': False}\n\ndef rand_int(a, b):\n\t\"\"\"\n\tUniformly samples integers on the closed interval [a, b]\n\t\"\"\"\n\treturn int(np.round(np.random.random_sample() * (b - a) + a))\n\ndef select_rand_direction():\n\tdirection = ['Left', 'Right', 'Up', 'Down']\n\trand_dir = direction[rand_int(0, 3)]\n\treturn rand_dir\n\n\ndef im_to_rgb(im):\n\t# convert the representation of obstacles, free space\n\t# unknown into colors\n\tnew_im = 1 - im\n\tnew_im = np.array(new_im, dtype=np.float32)\n\tnew_im[new_im > 1.5] = 0.5\n\tnew_im = cv2.cvtColor(new_im, cv2.COLOR_GRAY2RGB)\n\tnew_im *= 255\n\treturn np.array(new_im, dtype=np.uint8)\n\ndef upscale_im(im, factor):\n\tim_shape = np.shape(im)\n\tim = cv2.resize(im, (im_shape[1] * factor, im_shape[0] * factor), interpolation=cv2.INTER_NEAREST)\n\treturn im\n\n\ndef gen_empty_data(num_maps, map_size):\n\tim_and_rewards = [] # list of (map_size, map_size, 2) arrays\n\tS1 = [] # x state\n\tS2 = [] # y state\n\tlabels = [] # list of actions\n\n\n\ttime0 = time.time()\n\tfor i in range(num_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\t\tmap.gen_map(map_size, map_size, 'empty', tunnel_options)\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tsim = Simulator(map)\n\t\tsim.set_pos(map.start)\n\n\t\twhile not np.all(sim.get_pos() == map.goal):\n\t\t\t[_, action] = astar(sim.map_seen, sim.get_pos(), map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tbreak\n\n\t\t\tim[:, :, 0] = sim.map_seen\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tstate = sim.get_pos()\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\t\t\tsim.step(action)\n\t\t\n\t\t# append goal state\n\t\tim[:, :, 0] = sim.map_seen\n\t\tim_and_rewards.append(im.copy())\n\t\tS1.append(map.goal[0])\n\t\tS2.append(map.goal[1])\n\t\tlabels.append(Actions.STAY)\n\t\t\t\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\tim_and_rewards = np.array(im_and_rewards)\n\tS1 = np.array(S1)\n\tS2 = np.array(S2)\n\tlabels = np.array(labels)\n\n\tret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n\n\treturn ret\n\n\ndef gen_partial_map_data2(num_maps, map_size):\n\tim_and_rewards = [] # list of (map_size, map_size, 2) arrays\n\tS1 = [] # x state\n\tS2 = [] # y state\n\tlabels = [] # list of actions\n\n\tnum_rand_maps = int(num_maps / 2)\n\tnum_normal_maps = num_maps - num_rand_maps\n\n\ttime0 = time.time()\n\tfor i in range(num_normal_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\n\t\ttunnel_options['dir'] = select_rand_direction()\n\t\ttunnel_options['opening'] = rand_int(1, 6)\n\n\t\tmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tsim = Simulator(map)\n\t\tsim.set_pos(map.start)\n\n\t\twhile not np.all(sim.get_pos() == map.goal):\n\t\t\t[_, action] = astar(sim.map_seen, sim.get_pos(), map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tbreak\n\n\t\t\tim[:, :, 0] = sim.map_seen\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tstate = sim.get_pos()\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\t\t\tsim.step(action)\n\t\t\t\n\t\t# append goal state\n\t\tim[:, :, 0] = sim.map_seen\n\t\tim_and_rewards.append(im.copy())\n\t\tS1.append(map.goal[0])\n\t\tS2.append(map.goal[1])\n\t\tlabels.append(Actions.STAY)\n\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\tfor i in range(num_rand_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\n\t\ttunnel_options['dir'] = select_rand_direction()\n\t\ttunnel_options['opening'] = rand_int(1, 6)\n\t\ttunnel_options['spawn_rand'] = True\n\n\t\tmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tsim = Simulator(map)\n\t\tsim.set_pos(map.start)\n\n\t\twhile not np.all(sim.get_pos() == map.goal):\n\t\t\t[_, action] = astar(sim.map_seen, sim.get_pos(), map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tbreak\n\n\t\t\tim[:, :, 0] = sim.map_seen\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tstate = sim.get_pos()\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\t\t\tsim.step(action)\n\t\t\t\n\t\t# append goal state\n\t\tim[:, :, 0] = sim.map_seen\n\t\tim_and_rewards.append(im.copy())\n\t\tS1.append(map.goal[0])\n\t\tS2.append(map.goal[1])\n\t\tlabels.append(Actions.STAY)\n\t\t\t\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i + num_normal_maps) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\n\tim_and_rewards = np.array(im_and_rewards)\n\tS1 = np.array(S1)\n\tS2 = np.array(S2)\n\tlabels = np.array(labels)\n\n\tret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n\n\treturn ret\n\ndef gen_partial_map_data(num_maps, map_size):\n\tim_and_rewards = [] # list of (map_size, map_size, 2) arrays\n\tS1 = [] # x state\n\tS2 = [] # y state\n\tlabels = [] # list of actions\n\n\n\ttime0 = time.time()\n\tfor i in range(num_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\t\tmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tsim = Simulator(map)\n\t\tsim.set_pos(map.start)\n\n\t\twhile not np.all(sim.get_pos() == map.goal):\n\t\t\t[_, action] = astar(sim.map_seen, sim.get_pos(), map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tbreak\n\n\t\t\tim[:, :, 0] = sim.map_seen\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tstate = sim.get_pos()\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\t\t\tsim.step(action)\n\t\t\n\t\t# append goal state\n\t\tim[:, :, 0] = sim.map_seen\n\t\tim_and_rewards.append(im.copy())\n\t\tS1.append(map.goal[0])\n\t\tS2.append(map.goal[1])\n\t\tlabels.append(Actions.STAY)\n\t\t\t\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\tim_and_rewards = np.array(im_and_rewards)\n\tS1 = np.array(S1)\n\tS2 = np.array(S2)\n\tlabels = np.array(labels)\n\n\tret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n\n\treturn ret\n\ndef gen_sensor_data(num_maps, map_size):\n\tim_and_rewards = [] # list of (map_size, map_size, 2) arrays\n\tS1 = [] # x state\n\tS2 = [] # y state\n\tlabels = [] # list of actions\n\n\n\ttime0 = time.time()\n\tfor i in range(num_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\t\tmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n\n\t\t# image = im_to_rgb(map.map_arr)\n\t\t# image = upscale_im(image, 20)\n\t\t# cv2.imshow('image', image)\n\t\t# cv2.waitKey(0)\n\n\t\tsim = Simulator(map)\n\n\t\t# generating samples along optimal path given full map information\n\t\t[path, _] = astar(map.map_arr, map.start + np.array([0, tunnel_options['length']-1]), map.goal)\n\t\tif path == None:\n\t\t\tcontinue\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tfor state in path:\n\t\t\tsensor = sim.get_sensor(state)\n\n\t\t\t[_, action] = astar(sensor, state, map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tcontinue\n\n\t\t\tim[:, :, 0] = sensor\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\n\t\t# generating random samples\n\t\trandom_states = np.random.randint(1, map_size-1, (10, 2))\n\t\tfor state in random_states:\n\t\t\tif map.map_arr[state[0], state[1]] == 1:\n\t\t\t\tcontinue\n\n\t\t\tsensor = sim.get_sensor(state)\n\t\t\t[_, action] = astar(sensor, state, map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tcontinue\n\n\t\t\tim[:, :, 0] = sensor\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\n\n\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\tim_and_rewards = np.array(im_and_rewards)\n\tS1 = np.array(S1)\n\tS2 = np.array(S2)\n\tlabels = np.array(labels)\n\n\tret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n\n\treturn ret\n\ndef gen_sensor2_data(num_maps, map_size):\n\tim_and_rewards = [] # list of (map_size, map_size, 2) arrays\n\tS1 = [] # x state\n\tS2 = [] # y state\n\tlabels = [] # list of actions\n\n\n\ttime0 = time.time()\n\tfor i in range(num_maps):\n\t\tstart = time.time()\n\t\tmap = Map();\n\n\t\ttunnel_options['spawn_rand'] = False\n\n\t\tmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n\n\t\tim = np.zeros((map_size, map_size, 2))\n\t\tim[map.goal[0], map.goal[1], 1] = 10\n\n\t\tsim = Simulator(map)\n\t\tsim.set_pos(map.start)\n\n\t\twhile not np.all(sim.get_pos() == map.goal):\n\t\t\t[_, action] = astar(sim.map_seen, sim.get_pos(), map.goal, get_first_action=True)\n\t\t\tif action == None:\n\t\t\t\tbreak\n\n\t\t\tim[:, :, 0] = sim.get_sensor(sim.get_pos())\n\n\t\t\tim_and_rewards.append(im.copy())\n\t\t\tstate = sim.get_pos()\n\t\t\tS1.append(state[0])\n\t\t\tS2.append(state[1])\n\t\t\tlabels.append(action)\n\t\t\tsim.step(action)\n\n\t\t# append goal state\n\t\tim[:, :, 0] = sim.map_seen\n\t\tim_and_rewards.append(im.copy())\n\t\tS1.append(map.goal[0])\n\t\tS2.append(map.goal[1])\n\t\tlabels.append(Actions.STAY)\n\t\t\t\n\t\tend = time.time()\n\t\tdt = end - start\n\t\ttime_taken_so_far = end - time0\n\t\test_time = ((num_maps) * time_taken_so_far / (i+1)) - time_taken_so_far\n\t\tprint(\"Iteration \" + str(i) + \" took \" + str(dt) + \" seconds. est time remaining: \" + str(est_time))\n\n\tim_and_rewards = np.array(im_and_rewards)\n\tS1 = np.array(S1)\n\tS2 = np.array(S2)\n\tlabels = np.array(labels)\n\n\tret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n\n\treturn ret\n\n\nif __name__ == '__main__':\n\tparser = argparse.ArgumentParser(description='Generate Training Data')\n\tparser.add_argument('--type', dest='data_type', action='store',\n\t\tchoices=['full_map', 'sensor', 'sensor2', 'partial_map', 'empty'],\n\t\thelp='')\n\tparser.add_argument('-k', dest='num_maps', action='store',\n\t\thelp='number of maps to generate data for')\n\tparser.add_argument('-n', dest='map_size', action='store',\n\t\thelp='map will be map_size X map_size')\n\tparser.add_argument('-o', dest='output_file', action='store',\n\t\thelp='output file to store training data in', required=True)\n\n\targs = parser.parse_args(sys.argv[1:])\n\tfile = open(args.output_file, \"wb\" )\n\n\tnum_maps = int(args.num_maps)\n\tmap_size = int(args.map_size)\n\tif args.data_type == 'full_map':\n\t\tdata = gen_full_data(num_maps, map_size)\n\telif args.data_type == 'sensor':\n\t\tdata = gen_sensor_data(num_maps, map_size)\n\telif args.data_type == 'sensor2':\n\t\tdata = gen_sensor2_data(num_maps, map_size)\n\telif args.data_type == 'partial_map':\n\t\tdata = gen_partial_map_data(num_maps, map_size)\n\telif args.data_type == 'empty':\n\t\tdata = gen_empty_data(num_maps, map_size)\n\n\tpickle.dump(data, file)\n\n\t# import cv2\n\t# im = data['im']\n\t# label = data['label']\n\t# for i in range(im.shape[0]):\n\t# \tprint(str(i) + \": \" + ActionsStrings[label[i]])\n\t# \timage = im[i, :, :, 0]\n\t# \timage = im_to_rgb(image)\n\t# \timage = upscale_im(image, 20)\n\t# \tcv2.imshow('image', image)\n\t# \tcv2.waitKey(0)\n"
},
{
"alpha_fraction": 0.6083548069000244,
"alphanum_fraction": 0.6326972842216492,
"avg_line_length": 29.77142906188965,
"blob_id": "0205c31ef59b958c2c1655800fc11ed3ae225aeb",
"content_id": "d7c14b969c3d6ebd4a38e0646ae970badff8bbcb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9695,
"license_type": "no_license",
"max_line_length": 142,
"num_lines": 315,
"path": "/simulator/Map.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\n\nclass Actions:\n\tRIGHT = 0\n\tUP = 1\n\tLEFT = 2\n\tDOWN = 3\n\tSTAY = 4\n\tEND_ENUM = 5\n\nActionsStrings = ['Right', 'Up', 'Left', 'Down', 'Stay']\nActionMotions = np.array([[0, 1], [-1, 0], [0, -1], [1, 0]])\nOppositeActions = [Actions.LEFT, Actions.DOWN, Actions.RIGHT, Actions.UP]\n\n\ndef rand_int(a, b):\n\t\"\"\"\n\tUniformly samples integers on the closed interval [a, b]\n\t\"\"\"\n\treturn int(np.round(np.random.random_sample() * (b - a) + a))\n\nclass Map(object):\n\t\"\"\"\n\tClass for generating maps\n\tMaps will be a numpy array indexed by [x, y]\n\twhere (0, 0) is the top left hand corner\n\tThe coordinate system is drawn below.\n\t(0, 0) ----------> y\n\t|\n\t|\n\t|\n\t|\n\tv\n\tx\n\t\"\"\"\n\tdef __init__(self):\n\t\tself.map_arr = None\n\t\tself.start = None\n\t\tself.goal = None\n\n\n\tdef gen_map(self, nrows, ncols, map_type, options_dict):\n\t\tself.map_arr = np.zeros((nrows, ncols), dtype=np.int)\n\n\t\tself.nrows = nrows\n\t\tself.ncols = ncols\n\n\t\t# creating map boundaries\n\t\tself.map_arr[0, :] = 1\n\t\tself.map_arr[-1, :] = 1\n\t\tself.map_arr[:, 0] = 1\n\t\tself.map_arr[:, -1] = 1\n\n\t\tself.start = None # starting position\n\t\tself.goal = None # goal position\n\n\t\tself.map_type = map_type\n\t\tif map_type == 'obst':\n\t\t\tself.__gen_obstacles(options_dict)\n\t\telif map_type == 'tunnel':\n\t\t\tself.__gen_tunnel(options_dict)\n\t\telse:\n\t\t\tself.__gen_empty(options_dict)\n\n\n\tdef query(self, state, sensor_size=2, return_partial=False):\n\t\t\"\"\"\n\t\tGets a window of cells around a state\n\t\tThe window will be a box and will extend sensor_size in each direction\n\t\tIf the sensor goes out of bounds, it will either\n\t\t1) fill the area with -1 if return_partial is false\n\t\tor \n\t\t2) return a smaller area if return_partial is true\n\n\t\tArgs:\n\t\t state (TYPE): numpy array of length 2\n\t\t sensor_size (int, optional)\n\t\t return_partial (bool, optional): \n\t\t\n\t\tReturns:\n\t\t numpy array: window around state\n\t\t\"\"\"\n\t\tif state[0] < 0 or state[0] >= self.nrows:\n\t\t\traise ValueError('state[0] not in range')\n\t\tif state[1] < 0 or state[1] >= self.ncols:\n\t\t\traise ValueError('state[1] not in range')\n\n\t\tx_corner = 0\n\t\ty_corner = 0\n\n\t\tlower_window_x = state[0] - sensor_size\n\t\tif lower_window_x < 0:\n\t\t\tx_corner = -lower_window_x\n\t\t\tlower_window_x = 0\n\t\tlower_window_y = state[1] - sensor_size\n\t\tif lower_window_y < 0:\n\t\t\ty_corner = -lower_window_y\n\t\t\tlower_window_y = 0\n\n\t\tupper_window_x = min(state[0] + sensor_size, self.nrows-1)\n\t\tupper_window_y = min(state[1] + sensor_size, self.ncols-1)\n\n\t\tx_size = upper_window_x - lower_window_x + 1\n\t\ty_size = upper_window_y - lower_window_y + 1\n\n\n\t\tif return_partial:\n\t\t\treturn self.map_arr[lower_window_x:upper_window_x+1, lower_window_y:upper_window_y+1]\n\t\telse:\n\t\t\tsensor = np.ones((2*sensor_size+1, 2*sensor_size+1)) * -1\n\t\t\tsensor[x_corner:x_corner+x_size, y_corner:y_corner+y_size] = self.map_arr[lower_window_x:upper_window_x+1, lower_window_y:upper_window_y+1]\n\t\t\treturn sensor\n\n\tdef print_map(self):\n\t\tmap_im = self.map_arr.copy()\n\t\tmap_im[self.start[0], self.start[1]] = 2\n\t\tmap_im[self.goal[0], self.goal[1]] = 3\n\t\tprint map_im\n\n\tdef __gen_empty(self, options_dict):\n\t\tnrows = self.map_arr.shape[0]\n\t\tncols = self.map_arr.shape[1]\n\t\tself.start = np.array([rand_int(1, nrows-2), rand_int(1, ncols-2)])\n\t\tself.goal = np.array([rand_int(1, nrows-2), rand_int(1, ncols-2)])\n\n\tdef __gen_obstacles(self, options_dict):\n\t\t\"\"\"\n\t\tGenerates rectangular obstacles and start/end positions\n\t\t\n\t\tArgs:\n\t\t options_dict (dict): \n\t\t must contain \n\t\t 'max_nobst': the maximum number of obstacles to generate\n\t\t\t'max_obst_size': size 2 list of [max_height, max_width] of each obstacle\t\t\n\t\t\"\"\"\n\t\tmax_nobst = options_dict['max_nobst']\n\t\tmax_obst_size = options_dict['max_obst_size']\n\n\t\tnrows = self.map_arr.shape[0]\n\t\tncols = self.map_arr.shape[1]\n\n\t\t# generating random number of obstacles\n\t\tnum_obst = rand_int(0, max_nobst)\n\n\t\t# generating starting upper left coordinates for each obstacle\n\t\tobst_coords = np.random.random_sample((num_obst, 2))\n\t\tobst_coords[:, 0] *= (nrows-1)\n\t\tobst_coords[:, 1] *= (ncols-1)\n\t\tobst_coords = np.array(np.round(obst_coords), dtype=np.int)\n\n\t\t# generating height and width of each obstacle\n\t\tobst_sizes = np.random.random_sample((num_obst, 2))\n\t\tobst_sizes[:, 0] = (obst_sizes[:, 0] * (max_obst_size[0] - 1)) + 1\n\t\tobst_sizes[:, 1] = (obst_sizes[:, 1] * (max_obst_size[1] - 1)) + 1\n\t\tobst_sizes = np.array(np.round(obst_sizes), dtype=np.int)\n\n\t\tfor i in range(num_obst):\n\t\t\tself.map_arr[obst_coords[i, 0]:obst_coords[i, 0]+obst_sizes[i, 0], \n\t\t\t\tobst_coords[i, 1]:obst_coords[i, 1]+obst_sizes[i, 1]] = 1\n\n\t\tself.start = np.array([rand_int(1, nrows-2), rand_int(1, ncols-2)])\n\n\t\tself.goal = np.array([rand_int(1, nrows-2), rand_int(1, ncols-2)])\n\t\t# make sure goal is not the same as start\n\t\twhile np.all(self.goal == self.start):\n\t\t\tself.goal = np.array([rand_int(1, nrows-2), rand_int(1, ncols-2)])\n\n\tdef __gen_tunnel(self, options_dict):\n\t\t\"\"\"\n\t\tGenerates a single tunnel in the map along with a start and end position\n\t\t\n\t\tArgs:\n\t\t options_dict (dict): \n\t\t must contain \n\t\t 'opening': size of the opening of the tunnel\n\t\t\t'length': length of the tunnel\n\t\t\t'closed': whether or not the tunnel is closed\n\t\t\t'tunnel_dir': which side the tunnel opening is on. decides rotation of tunnel\n\t\t\t'spawn_rand': if true, spawns starts and goals randomly\n\t\t\totherwise, will spawn a start near opening of tunnel and an end near ending of tunnel\n\t\t\"\"\"\n\t\topening = options_dict['opening']\n\t\tlength = options_dict['length']\n\t\tclosed = options_dict['closed']\n\t\ttunnel_dir = options_dict['dir'] # [Left, Up, Right, Down]\n\t\tspawn_rand = options_dict['spawn_rand']\n\n\t\tnrows = self.map_arr.shape[0]\n\t\tncols = self.map_arr.shape[1]\n\n\t\tif tunnel_dir == 'Left' or tunnel_dir == 'Right':\n\t\t\tx_size = opening\n\t\t\ty_size = length\n\t\telse:\n\t\t\tx_size = length\n\t\t\ty_size = opening\n\n\t\t# generating top left corner of tunnel\n\t\t# while making sure tunnel stays within map bounds and\n\t\t# has enough space for a start and goal position\n\t\tif tunnel_dir == 'Left' or tunnel_dir == 'Right':\n\t\t\tx_tunnel = rand_int(1, nrows-x_size-3)\n\t\t\ty_tunnel = rand_int(2, ncols-y_size-2)\n\t\telse:\n\t\t\tx_tunnel = rand_int(2, nrows-x_size-2)\n\t\t\ty_tunnel = rand_int(1, ncols-y_size-3)\n\n\t\t\n\t\tif tunnel_dir == 'Left' or tunnel_dir == 'Right':\n\t\t\tself.map_arr[x_tunnel, y_tunnel:y_tunnel+y_size] = 1\n\t\t\tself.map_arr[x_tunnel+x_size+1, y_tunnel:y_tunnel+y_size] = 1\n\t\telse:\n\t\t\tself.map_arr[x_tunnel:x_tunnel+x_size, y_tunnel] = 1\n\t\t\tself.map_arr[x_tunnel:x_tunnel+x_size, y_tunnel+y_size+1] = 1\n\n\n\t\tif closed:\n\t\t\tif tunnel_dir == 'Left':\n\t\t\t\tself.map_arr[x_tunnel:x_tunnel+x_size+2, y_tunnel+y_size-1] = 1\n\t\t\telif tunnel_dir == 'Right':\n\t\t\t\tself.map_arr[x_tunnel:x_tunnel+x_size+2, y_tunnel] = 1\n\t\t\telif tunnel_dir == 'Up':\n\t\t\t\tself.map_arr[x_tunnel+x_size-1, y_tunnel:y_tunnel+y_size+2] = 1\n\t\t\telse:\n\t\t\t\tself.map_arr[x_tunnel, y_tunnel:y_tunnel+y_size+2] = 1\n\n\n\n\t\tif spawn_rand:\n\t\t\tself.start = np.array([rand_int(1, nrows-1), rand_int(1, ncols-1)])\n\t\t\twhile (self.map_arr[self.start[0], self.start[1]] == 1):\n\t\t\t\tself.start = np.array([rand_int(1, nrows), rand_int(1, ncols)])\n\n\n\t\t\tself.goal = np.array([rand_int(1, nrows-1), rand_int(1, ncols-1)])\n\t\t\twhile (self.map_arr[self.goal[0], self.goal[1]] == 1):\n\t\t\t\tself.goal = np.array([rand_int(1, nrows-1), rand_int(1, ncols-1)])\n\t\telse:\n\t\t\tif tunnel_dir == 'Left':\n\t\t\t\tstart_x = rand_int(x_tunnel+1, x_tunnel+x_size)\n\t\t\t\tstart_y = rand_int(1, y_tunnel + y_size - 2)\n\t\t\t\tend_x = rand_int(max(1, x_tunnel-2), min(nrows-2, x_tunnel+x_size+2))\n\t\t\t\tend_y = rand_int(y_tunnel+y_size, ncols-2)\n\t\t\t\t\n\t\t\t\t# start_x = x_tunnel+1\n\t\t\t\t# start_y = y_tunnel\n\n\t\t\t\tend_x = x_tunnel+1\n\t\t\t\tend_y = y_tunnel+y_size\n\t\t\telif tunnel_dir == 'Right':\n\t\t\t\tstart_x = rand_int(x_tunnel+1, x_tunnel+x_size)\n\t\t\t\tstart_y = rand_int(y_tunnel+1, ncols-2)\n\t\t\t\tend_x = rand_int(max(1, x_tunnel-2), min(nrows-2, x_tunnel+x_size+2))\n\t\t\t\tend_y = rand_int(1, y_tunnel-1)\n\n\t\t\t\t# start_x = x_tunnel+1\n\t\t\t\t# start_y = y_tunnel+y_size-2\n\t\t\t\tend_x = x_tunnel+1\n\t\t\t\tend_y = y_tunnel-1\n\n\t\t\telif tunnel_dir == 'Up':\n\t\t\t\tstart_x = rand_int(1, x_tunnel+x_size-2)\n\t\t\t\tstart_y = rand_int(y_tunnel+1, y_tunnel+y_size)\n\t\t\t\tend_x = rand_int(x_tunnel+x_size, nrows-2)\n\t\t\t\tend_y = rand_int(max(1, y_tunnel-2), min(nrows-2, y_tunnel+y_size+2))\n\n\t\t\t\tend_x = x_tunnel+x_size\n\t\t\t\tend_y = y_tunnel+1\n\n\t\t\telse:\n\t\t\t\tstart_x = rand_int(x_tunnel+1, nrows-2)\n\t\t\t\tstart_y = rand_int(y_tunnel+1, y_tunnel+y_size)\n\t\t\t\tend_x = rand_int(1, x_tunnel-1)\n\t\t\t\tend_y = rand_int(max(1, y_tunnel-2), min(nrows-2, y_tunnel+y_size+2))\n\t\t\t\t\n\t\t\t\tend_x = x_tunnel-1\n\t\t\t\tend_y = y_tunnel+1\n\t\t\t\t\n\t\t\tself.start = np.array([start_x, start_y])\n\t\t\tself.goal = np.array([end_x, end_y])\n\n\n\t\t# # generating top left corner of tunnel\n\t\t# # while making sure tunnel stays within map bounds and\n\t\t# # has enough space for a start and goal position\n\t\t# x_tunnel = rand_int(1, nrows-opening-3)\n\t\t# y_tunnel = rand_int(2, ncols-length-3)\n\n\t\t# self.map_arr[x_tunnel, y_tunnel:y_tunnel+length] = 1\n\t\t# self.map_arr[x_tunnel+opening+1, y_tunnel:y_tunnel+length] = 1\n\n\t\t# if closed:\n\t\t# \tself.map_arr[x_tunnel:x_tunnel+opening+2, y_tunnel+length] = 1\n\n\t\t# # generating start and end positions\n\t\t# start_y = y_tunnel\n\t\t# start_x = rand_int(x_tunnel+1, x_tunnel+opening)\n\t\t# self.start = np.array([start_x, start_y])\n\n\t\t# end_y = rand_int(y_tunnel+length+1, ncols-2)\n\t\t# end_x = rand_int(max(1, x_tunnel-2), min(nrows-2, x_tunnel+opening+2))\n\t\t# self.goal = np.array([end_x, end_y])\n\n\n\nif __name__ == '__main__':\n\ttunnel_options = {'opening': 1, 'length': 4, 'closed': True, 'dir': 'Down', 'spawn_rand': False}\n\tobst_options = {'max_nobst': 2, 'max_obst_size': [2, 2]}\n\n\t# np.random.seed(0)\n\tmap1 = Map()\n\tmap1.gen_map(8, 8, 'tunnel', tunnel_options)\n\tmap1.print_map()\n\n\t# map1.query([8, 7])\n\n\n"
},
{
"alpha_fraction": 0.4785754084587097,
"alphanum_fraction": 0.5125208497047424,
"avg_line_length": 28.67768669128418,
"blob_id": "708152cf761a6d5d766a303ae7a22ca0a2ec6d9d",
"content_id": "77d014f339d42aaf67ede93c0fd4dc4cb83e814a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3594,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 121,
"path": "/simulator/flooding.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport Map\nimport pickle\n\ndef get_neighbors(node):\n \n neighbors = {}\n \n neighbors[\"Right\"] = np.array([node[0],node[1]+1])\n neighbors[\"Up\"] = np.array([node[0]-1,node[1]])\n neighbors[\"Left\"] = np.array([node[0],node[1]-1])\n neighbors[\"Down\"] = np.array([node[0]+1,node[1]])\n \n return neighbors\n\ndef get_action_num(action):\n if action == \"Right\":\n action_no = Map.Actions.RIGHT\n elif action == \"Up\":\n action_no = Map.Actions.UP\n elif action == \"Left\":\n action_no = Map.Actions.LEFT\n elif action == \"Down\":\n action_no = Map.Actions.DOWN\n return action_no\n \n\ndef gen_training(map1):\n \n m = map1.map_arr\n goal = map1.goal\n \n open_list = [goal]\n \n visited = np.zeros([m.shape[0],m.shape[1]])\n# state_action = dict()\n action_map = np.full([m.shape[0],m.shape[1]],-1,dtype = np.int32)\n action_map[goal[0],goal[1]] = 10 \n \n while open_list != []:\n \n element = open_list.pop(0)\n \n if visited[element[0],element[1]] ==1:\n continue\n visited[element[0],element[1]] = 1\n \n neighbors = get_neighbors(element)\n \n for n in neighbors:\n if m[neighbors[n][0],neighbors[n][1]] != 1 and visited[neighbors[n][0],neighbors[n][1]]!=1:\n \n# state_action.setdefault(\"state1\",[]).append(neighbors[n][0])\n# state_action.setdefault(\"state2\",[]).append(neighbors[n][1])\n# state_action.setdefault(\"action\",[]).append((get_action_num(n)-2)%4)\n action_map[neighbors[n][0],neighbors[n][1]] = (get_action_num(n)-2)%4\n open_list.append(neighbors[n])\n \n \n return action_map\n\nif __name__ == '__main__':\n tunnel_options = {'opening': 1, 'length': 3, 'closed': True}\n \n map_size = 32 \n map1 = Map.Map()\n\n \n num_images = 400\n\n im_and_rewards =[] \n S1 = []\n S2 = []\n labels = []\n im = np.zeros((map_size, map_size, 2))\n for i in range(0, num_images):\n map1.gen_map(map_size, map_size, 'tunnel', tunnel_options)\n action_map = gen_training(map1)\n reward_map = np.zeros([map1.map_arr.shape[0],map1.map_arr.shape[1]])\n reward_map[map1.goal[0],map1.goal[1]] = 10\n\n im = np.zeros((map_size, map_size, 2))\n im[map1.goal[0], map1.goal[1], 1] = 10\n im[:, :, 0] = map1.map_arr.copy()\n\n # get mask of all elements that are in free space\n mask = np.logical_and((map1.map_arr == 0), action_map != 10)\n\n num_samples = np.sum(mask)\n\n actions = action_map[mask]\n\n locs = np.where(mask)\n x_locs = locs[0]\n y_locs = locs[1]\n\n num_samples_to_take = num_samples - (num_samples % 10)\n\n num_batches = num_samples_to_take / 10\n\n for j in range(num_batches):\n idx1 = j * 10\n idx2 = (j+1) * 10\n im_and_rewards.append(im)\n S1.append(x_locs[idx1:idx2])\n S2.append(y_locs[idx1:idx2])\n labels.append(actions[idx1:idx2])\n\n\n im_and_rewards = np.array(im_and_rewards)\n S1 = np.array(S1)\n S2 = np.array(S2)\n labels = np.array(labels)\n num_data = im_and_rewards.shape[0]\n labels = labels.reshape(num_data * 10)\n\n\n ret = {'im': im_and_rewards, 'S1': S1, 'S2': S2, 'label': labels}\n \n\n pickle.dump(ret, open(\"../data/phase0_32.pickle\", 'wb'))\n\n\n\n"
},
{
"alpha_fraction": 0.6149855852127075,
"alphanum_fraction": 0.6418827772140503,
"avg_line_length": 27.27717399597168,
"blob_id": "feb56fdb9bc4ca55ed66b9d15d9b7def77a019a6",
"content_id": "b48f2ce5966576c2a3365e32d9a28437b5d24088",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5205,
"license_type": "no_license",
"max_line_length": 99,
"num_lines": 184,
"path": "/simulator/Simulator.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport matplotlib.pyplot as plt\nfrom Map import *\nimport cv2\n\ndef sample(probs):\n\tprob_cumulative = np.cumsum(probs)\n\tnum = np.random.uniform()\n\t\n\tidx = 0\n\tfor i in range(len(probs)):\n\t\tif prob_cumulative[i] > num:\n\t\t\tidx = i\n\t\t\tbreak\n\treturn idx\n\ndef im_to_rgb(im):\n\t# convert the representation of obstacles, free space\n\t# unknown into colors\n\tnew_im = 1 - im\n\tnew_im = np.array(new_im, dtype=np.float32)\n\tnew_im[new_im > 1.5] = 0.5\n\tnew_im = cv2.cvtColor(new_im, cv2.COLOR_GRAY2RGB)\n\tnew_im *= 255\n\treturn np.array(new_im, dtype=np.uint8)\n\ndef upscale_im(im, factor):\n\tim_shape = np.shape(im)\n\tim = cv2.resize(im, (im_shape[1] * factor, im_shape[0] * factor), interpolation=cv2.INTER_NEAREST)\n\treturn im\n\nclass Simulator(object):\n\tdef __init__(self, map_obj):\n\t\tself.map_obj = map_obj\n\t\tself.pos = None\n\n\t\tself.map_seen = np.ones(self.map_obj.map_arr.shape) * -1\n\t\tself.sensor_size = 3\n\n\t\t# setting up transition probabilities\n\t\t# the (i, j)th entry\n\t\t# is the probability of moving in the j direction\n\t\t# given a command to move in the i direction\n\t\t# thus, if it is the identity, you will always move\n\t\t# in the direction you desire\n\t\tself.transition_prob = np.eye(5)\n\t\t# self.transition_prob = np.eye(4) * 0.8\n\t\t# for i in range(4):\n\t\t# \tself.transition_prob[i, i-1] = 0.1\n\t\t# \tself.transition_prob[i, (i+1)%4] = 0.1\n\n\tdef print_map(self):\n\t\tmap_im = self.map_obj.map_arr.copy()\n\t\tmap_im[self.pos[0], self.pos[1]] = 2\n\t\tmap_im[self.map_obj.goal[0], self.map_obj.goal[1]] = 3\n\t\tprint map_im\n\n\tdef get_pos(self):\n\t\treturn self.pos\n\n\tdef set_pos(self, pos):\n\t\tself.pos = np.array(pos)\n\t\tself.__update_map_seen(pos)\n\n\tdef __update_map_seen(self, pos):\n\t\tmap_x_coords = [pos[0] - self.sensor_size, pos[0] + self.sensor_size]\n\t\tmap_y_coords = [pos[1] - self.sensor_size, pos[1] + self.sensor_size]\n\n\t\tif pos[0] < self.sensor_size:\n\t\t\tmap_x_coords[0] = 0\t\n\t\telif pos[0] >= self.map_obj.nrows - self.sensor_size:\n\t\t\tmap_x_coords[1] = self.map_obj.nrows - 1\n\t\tif pos[1] < self.sensor_size:\n\t\t\tmap_y_coords[0] = 0\n\t\telif pos[1] >= self.map_obj.ncols - self.sensor_size:\n\t\t\tmap_y_coords[1] = self.map_obj.ncols - 1\n\n\t\tsensor = self.map_obj.query(pos, sensor_size=self.sensor_size, return_partial=True)\n\t\tself.map_seen[map_x_coords[0]:map_x_coords[1]+1, map_y_coords[0]:map_y_coords[1]+1] = sensor\n\n\tdef get_sensor(self, pos):\n\t\tmap_x_coords = [pos[0] - self.sensor_size, pos[0] + self.sensor_size]\n\t\tmap_y_coords = [pos[1] - self.sensor_size, pos[1] + self.sensor_size]\n\n\t\tif pos[0] < self.sensor_size:\n\t\t\tmap_x_coords[0] = 0\t\n\t\telif pos[0] >= self.map_obj.nrows - self.sensor_size:\n\t\t\tmap_x_coords[1] = self.map_obj.nrows - 1\n\t\tif pos[1] < self.sensor_size:\n\t\t\tmap_y_coords[0] = 0\n\t\telif pos[1] >= self.map_obj.ncols - self.sensor_size:\n\t\t\tmap_y_coords[1] = self.map_obj.ncols - 1\n\n\t\tsensor = self.map_obj.query(pos, sensor_size=self.sensor_size, return_partial=True)\n\t\tempty_map = np.ones(self.map_seen.shape) * -1\n\t\tempty_map[map_x_coords[0]:map_x_coords[1]+1, map_y_coords[0]:map_y_coords[1]+1] = sensor\n\n\t\treturn empty_map\n\n\n\tdef step(self, action):\n\t\t\"\"\"\n\t\tTakes an action specified by the Acions enum\n\t\tReturns:\n\t\t [new state, sensor reading]\n\t\t\"\"\"\n\t\tif action >= Actions.END_ENUM:\n\t\t\traise ValueError(\"action must be between 0 and 3 (inclusive)\")\n\n\t\tprobs = self.transition_prob[action, :]\n\t\tres_action = sample(probs)\n\t\tnew_pos = self.pos.copy()\n\t\tif res_action == Actions.RIGHT:\n\t\t\tnew_pos[1] += 1\n\t\telif res_action == Actions.UP:\n\t\t\tnew_pos[0] -= 1\n\t\telif res_action == Actions.LEFT:\n\t\t\tnew_pos[1] -= 1\n\t\telif res_action == Actions.DOWN:\n\t\t\tnew_pos[0] += 1\n\t\telse:\n\t\t\t# do nothing\n\t\t\tpass\n\n\t\tif self.map_obj.map_arr[new_pos[0], new_pos[1]] != 1:\n\t\t\tself.pos = new_pos\n\t\t\tself.__update_map_seen(new_pos)\n\n\t\treturn self.pos\n\t\t# return [self.pos, self.map_obj.query(self.pos, self.sensor_size)]\n\n\tdef show(self):\n\t\tmap_im_rgb = im_to_rgb(self.map_obj.map_arr)\n\t\tmap_im_rgb[self.pos[0], self.pos[1], :] = [0, 0, 255]\n\t\tmap_im_rgb[self.map_obj.goal[0], self.map_obj.goal[1]] = [255, 0, 0]\n\n\t\tsensor_im_rgb = im_to_rgb(self.get_sensor(self.pos))\n\n\t\tpartial_map_rgb = im_to_rgb(self.map_seen)\n\n\t\tfig = plt.figure(1)\n\t\tplt.clf()\n\t\tplt.subplot(1, 3, 1)\n\t\tplt.imshow(map_im_rgb, interpolation='nearest')\n\t\tplt.title('Full Map')\n\n\t\tplt.subplot(1, 3, 2)\n\t\tplt.imshow(partial_map_rgb, interpolation='nearest')\n\t\tplt.title('Partial Map')\n\n\t\tplt.subplot(1, 3, 3)\n\t\tplt.imshow(sensor_im_rgb, interpolation='nearest')\n\t\tplt.show(block=False)\n\t\tplt.title(\"Sensor\")\t\n\n\t\tplt.tight_layout()\n\n\nif __name__ == '__main__':\n\ttunnel_options = {'opening': 2, 'length': 15, 'closed': True, 'dir': 'Down', 'spawn_rand': False}\n\tobst_options = {'max_nobst': 2, 'max_obst_size': [2, 2]}\n\n\tnp.random.seed(0)\n\tmap1 = Map()\n\tmap1.gen_map(30, 40, 'tunnel', tunnel_options)\n\n\tsim = Simulator(map1)\n\tsim.set_pos(np.array([15, 1]))\n\n\tmotion_dict = {'d': Actions.RIGHT, \n\t\t'w': Actions.UP,\n\t\t'a': Actions.LEFT,\n\t\t's': Actions.DOWN}\n\n\twhile (1):\n\t\tsim.show()\n\t\tinput = raw_input(\"Type one of [w, a, s, d] to move (or q to quit): \")\n\t\tif input == 'q':\n\t\t\tquit()\n\t\tif input not in motion_dict:\n\t\t\tprint(\"Not a valid input, try again\")\n\t\t\tcontinue\n\t\tpos = sim.step(motion_dict[input])\n\t\tprint(\"Moved to: \" + str(pos))\n\n\n"
},
{
"alpha_fraction": 0.6190130710601807,
"alphanum_fraction": 0.6453192830085754,
"avg_line_length": 38.349998474121094,
"blob_id": "2d9022b9788c93ede606e834d54726c01469658a",
"content_id": "240ee27c5f41e898c3505dbd9267781074162d39",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5512,
"license_type": "no_license",
"max_line_length": 145,
"num_lines": 140,
"path": "/tensorflow-value-iteration-networks/Refactoring/CPU_version/test.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import time\nimport numpy as np\nimport tensorflow as tf\nfrom data import *\nfrom model import *\nfrom utils import *\nimport cv2\nimport matplotlib.pyplot as plt\n\ndef upscale_im(im, scale):\n im = np.array(im, dtype=np.float32)\n im_shape = np.shape(im)\n im = cv2.resize(im, (im_shape[1] * scale, im_shape[0] * scale), interpolation=cv2.INTER_NEAREST)\n im = cv2.cvtColor(im, cv2.COLOR_GRAY2BGR)\n im = np.array(np.round(im * 255), dtype=np.uint8)\n return im\n\nnp.random.seed(0)\n\n# Data\ntf.app.flags.DEFINE_string('input', 'data/gridworld_8.mat', 'Path to data')\ntf.app.flags.DEFINE_integer('imsize', 8, 'Size of input image')\n# Parameters\ntf.app.flags.DEFINE_float('lr', 0.001, 'Learning rate for RMSProp')\ntf.app.flags.DEFINE_integer('epochs', 30, 'Maximum epochs to train for')\ntf.app.flags.DEFINE_integer('k', 10, 'Number of value iterations')\ntf.app.flags.DEFINE_integer('ch_i', 2, 'Channels in input layer')\ntf.app.flags.DEFINE_integer('ch_h', 150, 'Channels in initial hidden layer')\ntf.app.flags.DEFINE_integer('ch_q', 10, 'Channels in q layer (~actions)')\ntf.app.flags.DEFINE_integer('batchsize', 12, 'Batch size')\ntf.app.flags.DEFINE_integer('statebatchsize', 10, 'Number of state inputs for each sample (real number, technically is k+1)')\ntf.app.flags.DEFINE_boolean('untied_weights', False, 'Untie weights of VI network')\n# Misc.\ntf.app.flags.DEFINE_integer('display_step', 1, 'Print summary output every n epochs')\ntf.app.flags.DEFINE_boolean('log', False, 'Enable for tensorboard summary')\ntf.app.flags.DEFINE_string('logdir', '/tmp/vintf/', 'Directory to store tensorboard summary')\n\nconfig = tf.app.flags.FLAGS\n\n# symbolic input image tensor where typically first channel is image, second is the reward prior\nX = tf.placeholder(tf.float32, name=\"X\", shape=[None, config.imsize, config.imsize, config.ch_i])\n# symbolic input batches of vertical positions\nS1 = tf.placeholder(tf.int32, name=\"S1\", shape=[None, config.statebatchsize])\n# symbolic input batches of horizontal positions\nS2 = tf.placeholder(tf.int32, name=\"S2\", shape=[None, config.statebatchsize])\ny = tf.placeholder(tf.int32, name=\"y\", shape=[None])\n\n# Construct model (Value Iteration Network)\n# if (config.untied_weights):\n# logits, nn = VI_Untied_Block(X, S1, S2, config)\n# else:\n# logits, nn = VI_Block(X, S1, S2, config)\n\nlogits, nn, reward, transitions, h = VI_Block2(X, S1, S2, config)\n\n# Define loss and optimizer\n# use sparse_softmax_cross_entropy_with_logits replacing log(nn)\ny_ = tf.cast(y, tf.int64)\ncross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(\n logits=logits, labels=y_, name='cross_entropy')\ncross_entropy_mean = tf.reduce_mean(cross_entropy, name='cross_entropy_mean')\ntf.add_to_collection('losses', cross_entropy_mean)\n\ncost = tf.add_n(tf.get_collection('losses'), name='total_loss')\n#dim = tf.shape(y)[0]\n#cost_idx = tf.concat(1, [tf.reshape(tf.range(dim), [dim,1]), tf.reshape(y, [dim,1])])\n#cost = -tf.reduce_mean(tf.gather_nd(tf.log(nn), [cost_idx]))\n\noptimizer = tf.train.RMSPropOptimizer(learning_rate=config.lr, epsilon=1e-6, centered=True).minimize(cost)\n\n# Test model & calculate accuracy\ncp = tf.cast(tf.argmax(nn, 1), tf.int32)\nerr = tf.reduce_mean(tf.cast(tf.not_equal(cp, y), dtype=tf.float32))\n\n# Initializing the variables\ninit = tf.global_variables_initializer()\nsaver = tf.train.Saver()\n\nXtrain, S1train, S2train, ytrain, Xtest, S1test, S2test, ytest = process_gridworld_data(input=config.input, imsize=config.imsize)\nconfig.log = True \n# Launch the graph\nwith tf.Session() as sess:\n if config.log:\n for var in tf.trainable_variables():\n tf.summary.histogram(var.op.name, var)\n summary_op = tf.summary.merge_all()\n summary_writer = tf.summary.FileWriter(config.logdir, sess.graph)\n sess.run(init)\n saver.restore(sess, \"data/model.ckpt\")\n\n # Test model\n correct_prediction = tf.cast(tf.argmax(nn, 1), tf.int32)\n # Calculate accuracy\n accuracy = tf.reduce_mean(tf.cast(tf.not_equal(correct_prediction, y), dtype=tf.float32))\n\n\n\n sample_idx = 0\n\n Xsample = np.array([Xtest[sample_idx, :, :, :]])\n S1sample = np.array([S1test[sample_idx, :]])\n S2sample = np.array([S2test[sample_idx, :]])\n ysample = ytest[sample_idx * 10:(sample_idx+1) * 10]\n\n\n feed_dict = {X: Xsample, S1: S1sample, S2: S2sample, y: ysample}\n [acc, pred, rew, trans, temp] = sess.run([accuracy, correct_prediction, reward, transitions, h], feed_dict=feed_dict)\n\n print(\"Accuracy: {}%\".format(100 * (1 - acc)))\n print Xsample[:, :, :, 1]\n\n obst_im = upscale_im(1 - np.reshape(Xsample[0, :, :, 0].squeeze(), (8, 8)), 50)\n fig1 = plt.figure(1)\n ax1 = fig1.gca()\n ax1.imshow(obst_im)\n ax1.grid()\n \n rew_im = upscale_im(1 - np.reshape(rew.T, (8, 8)), 50)\n fig2 = plt.figure(2)\n ax2 = fig2.gca()\n ax2.imshow(rew_im)\n ax2.grid()\n\n trans_im = upscale_im(1 - np.reshape(trans[:, :, :, 0], (3, 3)), 50)\n fig2 = plt.figure(3)\n ax2 = fig2.gca()\n ax2.imshow(trans_im)\n ax2.grid()\n\n plt.show()\n\n # cv2.imshow(\"obstacles\", obst_im)\n\n # cv2.imshow(\"rewards\", rew_im)\n\n # # obst_im = upscale_im(1 - np.reshape(Xsample[0, :, :, 0].squeeze(), (8, 8)), 50)\n # # cv2.imshow(\"obstacles\", obst_im)\n\n\n # cv2.waitKey(0)\n\n\n\n"
},
{
"alpha_fraction": 0.6070064902305603,
"alphanum_fraction": 0.6326072216033936,
"avg_line_length": 36.72881317138672,
"blob_id": "db2a20e37437a61ed6c514602e1699ca05ee0c52",
"content_id": "9fc6a878c7cf2cef16d14d4c6a310daaee42663d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4453,
"license_type": "no_license",
"max_line_length": 144,
"num_lines": 118,
"path": "/simulator/Test_Simulator_LSTM.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom Simulator import Simulator\nfrom Map import *\nimport time\nimport numpy as np\nimport tensorflow as tf\nimport sys\nsys.path.append(\"../tensorflow-value-iteration-networks/Refactoring/CPU_version\")\n\nfrom model_lstm import *\nfrom utils import *\nimport cv2\nimport matplotlib.pyplot as plt\nimport pdb\n\n\ndef upscale_im(im, scale):\n im = np.array(im, dtype=np.float16)\n im_shape = np.shape(im)\n im = cv2.resize(im, (im_shape[1] * scale, im_shape[0] * scale), interpolation=cv2.INTER_NEAREST)\n im = cv2.cvtColor(im, cv2.COLOR_GRAY2BGR)\n im = np.array(np.round(im * 255), dtype=np.uint8)\n return im\n\nmap_size = 64\n\n# Data\ntf.app.flags.DEFINE_string('input', 'data/gridworld_8.mat', 'Path to data')\ntf.app.flags.DEFINE_integer('imsize', map_size, 'Size of input image')\n# Parameters\ntf.app.flags.DEFINE_float('lr', 0.001, 'Learning rate for RMSProp')\ntf.app.flags.DEFINE_integer('epochs', 30, 'Maximum epochs to train for')\ntf.app.flags.DEFINE_integer('k', 10, 'Number of value iterations')\ntf.app.flags.DEFINE_integer('ch_i', 2, 'Channels in input layer')\ntf.app.flags.DEFINE_integer('ch_h', 150, 'Channels in initial hidden layer')\ntf.app.flags.DEFINE_integer('ch_q', 4, 'Channels in q layer (~actions)')\ntf.app.flags.DEFINE_integer('batchsize', 1, 'Batch size')\ntf.app.flags.DEFINE_integer('statebatchsize', 1, 'Number of state inputs for each sample (real number, technically is k+1)')\ntf.app.flags.DEFINE_boolean('untied_weights', False, 'Untie weights of VI network')\n# Misc.\ntf.app.flags.DEFINE_integer('display_step', 1, 'Print summary output every n epochs')\ntf.app.flags.DEFINE_boolean('log', False, 'Enable for tensorboard summary')\ntf.app.flags.DEFINE_string('logdir', '/tmp/vintf/', 'Directory to store tensorboard summary')\n\nconfig = tf.app.flags.FLAGS\n\n# symbolic input image tensor where typically first channel is image, second is the reward prior\nX = tf.placeholder(tf.float32, name=\"X\", shape=[None, config.imsize, config.imsize, config.ch_i])\n# symbolic input batches of vertical positions\nS1 = tf.placeholder(tf.int32, name=\"S1\", shape=[None, config.statebatchsize])\n# symbolic input batches of horizontal positions\nS2 = tf.placeholder(tf.int32, name=\"S2\", shape=[None, config.statebatchsize])\ny = tf.placeholder(tf.int32, name=\"y\", shape=[None])\nc_in = tf.placeholder(tf.float32, [1, 256])\nh_in = tf.placeholder(tf.float32, [1, 256])\n\nlogits, nn, state_out = VI_Block(X, S1, S2, config,c_in,h_in)\nstate_spaces = tf.identity(state_out)\n\ntunnel_options = {'opening': 1, 'length': 40, 'closed': True, 'spawn_rand':False, 'dir': 'Left'}\nmap = Map()\nmap.gen_map(map_size, map_size, 'tunnel', tunnel_options)\nsim = Simulator(map)\nsim.set_pos(map.start)\n\n\nX_data = np.zeros((1, config.imsize, config.imsize, 2))\nS1_data = np.zeros((1, 1))\nS2_data = np.zeros((1, 1))\nX_data[0, map.goal[0], map.goal[1], 1] = 10\n\n\n\n\ninit = tf.global_variables_initializer()\nsaver = tf.train.Saver()\nconfig.log = True\n# Launch the graph\nwith tf.Session() as sess:\n if config.log:\n for var in tf.trainable_variables():\n tf.summary.histogram(var.op.name, var)\n summary_op = tf.summary.merge_all()\n summary_writer = tf.summary.FileWriter(config.logdir, sess.graph)\n sess.run(init)\n saver.restore(sess, \"../tensorflow-value-iteration-networks/new_data/phase3_model/model.ckpt\")\n\n c = np.zeros((1, 256), np.float32)\n h = np.zeros((1, 256), np.float32)\n\n\n raw_input(\"Press Enter to continue\")\n\n while (1):\n curr_state = sim.get_pos()\n X_data[0, :, :, 0] = sim.get_sensor(curr_state)\n #X_data[0, :, :, 0] = sim.map_seen\n S1_data[0] = curr_state[0]\n S2_data[0] = curr_state[1]\n\n\n feed_dict = {X: X_data, S1: S1_data, S2: S2_data}\n fd = {X: X_data, S1: S1_data, S2: S2_data,c_in:c,h_in: h}\n state_p = sess.run(state_spaces, feed_dict=fd)\n \n \n c = np.array(state_p[0,:,:])\n h = np.array(state_p[1,:,:])\n nn = logits.eval(fd)\n\n # choose action from nn\n action = np.argmax(nn) # something nn\n print ActionsStrings[action]\n\n sim.step(action)\n sim.show()\n # plt.pause(0.01)\n raw_input(\"Press Enter to continue\")\n\n"
},
{
"alpha_fraction": 0.6013906598091125,
"alphanum_fraction": 0.6216830015182495,
"avg_line_length": 41.18562698364258,
"blob_id": "65e0d57af542a0ea82a8cfd69b6ad0e9d0d12c97",
"content_id": "71934faa6d234c991ca6f89b4714026b71c67057",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7047,
"license_type": "no_license",
"max_line_length": 145,
"num_lines": 167,
"path": "/tensorflow-value-iteration-networks/Refactoring/GPU_version/refactored_train.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import time\nimport numpy as np\nimport tensorflow as tf\nfrom data import *\nfrom model import *\nfrom utils import *\nimport pickle \nimport pdb\nimport cv2\nfrom tqdm import tqdm\n\n\ntf.app.flags.DEFINE_integer('imsize', 32, 'Size of input image')\n# Parameters\ntf.app.flags.DEFINE_float('lr', 0.001, 'Learning rate for RMSProp')\ntf.app.flags.DEFINE_integer('epochs', 15, 'Maximum epochs to train for')\ntf.app.flags.DEFINE_integer('k', 10, 'Number of value iterations')\ntf.app.flags.DEFINE_integer('ch_i', 2, 'Channels in input layer')\ntf.app.flags.DEFINE_integer('ch_h', 150, 'Channels in initial hidden layer')\ntf.app.flags.DEFINE_integer('ch_q', 4, 'Channels in q layer (~actions)')\ntf.app.flags.DEFINE_integer('batchsize', 128, 'Batch size')\ntf.app.flags.DEFINE_integer('statebatchsize', 1, 'Number of state inputs for each sample (real number, technically is k+1)')\ntf.app.flags.DEFINE_boolean('untied_weights', False, 'Untie weights of VI network')\n# Misc.\ntf.app.flags.DEFINE_integer('display_step', 1, 'Print summary output every n epochs')\ntf.app.flags.DEFINE_boolean('log', False, 'Enable for tensorboard summary')\ntf.app.flags.DEFINE_string('logdir', '/tmp/vintf/', 'Directory to store tensorboard summary')\n\nparameters = tf.app.flags.FLAGS\n\n\nwith tf.device('/gpu:0'):\n # symbolic input image tensor where typically first channel is image, second is the reward prior\n X = tf.placeholder(tf.float16, name=\"X\", shape=[None, parameters.imsize, parameters.imsize, parameters.ch_i])\n # symbolic input batches of vertical positions\n S1 = tf.placeholder(tf.int32, name=\"S1\", shape=[None, parameters.statebatchsize])\n # symbolic input batches of horizontal positions\n S2 = tf.placeholder(tf.int32, name=\"S2\", shape=[None, parameters.statebatchsize])\n y = tf.placeholder(tf.int32, name=\"y\", shape=[None])\n\n # Construct model (Value Iteration Network)\n if (parameters.untied_weights):\n logits, nn = VI_Untied_Block(X, S1, S2, parameters)\n else:\n logits, nn = VI_Block(X, S1, S2, parameters)\n\n\n with open('partial.pickle', 'rb') as handle:\n b = pickle.load(handle)\n im = b['im']\n S1_ = b['S1']\n S2_ = b['S2']\n label = b['label']\n #pdb.set_trace()\n\n # Define loss and optimizer\n # use sparse_softmax_cross_entropy_with_logits replacing log(nn)\n y_ = tf.cast(y, tf.int64)\n cross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(\n logits=logits, labels=y_, name='cross_entropy')\n cross_entropy_mean = tf.reduce_mean(cross_entropy, name='cross_entropy_mean')\n tf.add_to_collection('losses', cross_entropy_mean)\n\n cost = tf.add_n(tf.get_collection('losses'), name='total_loss')\n #dim = tf.shape(y)[0]\n #cost_idx = tf.concat(1, [tf.reshape(tf.range(dim), [dim,1]), tf.reshape(y, [dim,1])])\n #cost = -tf.reduce_mean(tf.gather_nd(tf.log(nn), [cost_idx]))\n\n optimizer = tf.train.RMSPropOptimizer(learning_rate=parameters.lr, epsilon=1e-6, centered=True).minimize(cost)\n\n # Test model & calculate accuracy\n cp = tf.cast(tf.argmax(nn, 1), tf.int32)\n err = tf.reduce_mean(tf.cast(tf.not_equal(cp, y), dtype=tf.float16))\n\n \n total_size = np.shape(im)\n train_size = np.round(total_size[0]*0.75)\n train_size = train_size.astype(int)\n test_size = total_size[0] - train_size\n\n Xtrain = im\n S1train = S1_\n S1shape = np.shape(S1train)\n S1train = np.reshape(S1train,(S1shape[0],parameters.statebatchsize))\n S2train = S2_\n S2shape = np.shape(S2train)\n S2train = np.reshape(S2train,(S2shape[0],parameters.statebatchsize))\n ytrain= label\n\n Xtest = Xtrain[train_size:total_size[0],:,:]\n S1test = S1train[train_size:total_size[0],:]\n S2test = S2train[train_size:total_size[0],:]\n ytest = ytrain[train_size:total_size[0],]\n\n Xtrain = Xtrain[0:train_size,:,:]\n S1train = S1train[0:train_size,:]\n S2train = S2train[0:train_size,:]\n ytrain = ytrain[0:train_size:,]\n \n\n\n gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.3)\n\n\n sess = tf.InteractiveSession(config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=True))\n\n #config = tf.ConfigProto(allow_soft_placement=True)\n #config.gpu_options.allow_growth = True\n #sess = tf.InteractiveSession(config=config)\n saver = tf.train.Saver(max_to_keep=10)\n\n\n batch_size = parameters.batchsize\n\n tf.initialize_all_variables().run()\n\n\n\n print(fmt_row(10, [\"Epoch\", \"Train Cost\", \"Train Err\", \"test err\", \"Epoch Time\"]))\n for epoch in range(int(parameters.epochs)):\n tstart = time.time()\n avg_err, avg_cost = 0.0, 0.0\n num_batches = int(Xtrain.shape[0]/batch_size)\n # Loop over all batches\n for i in tqdm(range(0, Xtrain.shape[0], batch_size)):\n j = i + batch_size\n #pdb.set_trace()\n\n if j <= Xtrain.shape[0]:\n # Run optimization op (backprop) and cost op (to get loss value)\n fd = {X: Xtrain[i:j], S1: S1train[i:j], S2: S2train[i:j],y: ytrain[i * parameters.statebatchsize:j * parameters.statebatchsize]}\n #fd = {X: Xtrain[i:j], S1: S1train[i:j], S2: S2train[i:j]}\n #fd = {X: Xtrain[i:j]}\n #fd = {S2: S2train[i:j]} \n #pdb.set_trace()\n _, e_, c_ = sess.run([optimizer, err, cost], feed_dict=fd)\n avg_err += e_\n avg_cost += c_\n \n fd = {X: Xtest, S1: S1test, S2: S2test, y: ytest}\n #[test_err] = sess.run([err], feed_dict=fd)\n print sess.run([err], feed_dict = fd)\n test_err = 0\n\t# Display logs per epoch step\n if epoch % parameters.display_step == 0:\n elapsed = time.time() - tstart\n print(fmt_row(10, [epoch, avg_cost/num_batches, avg_err/num_batches, test_err, elapsed]))\n if parameters.log:\n summary = tf.Summary()\n summary.ParseFromString(sess.run(summary_op))\n summary.value.add(tag='Average error', simple_value=float(avg_err/num_batches))\n summary.value.add(tag='Average cost', simple_value=float(avg_cost/num_batches))\n summary.value.add(tag='test err', simple_value=float(test_err))\n\tsummary_writer.add_summary(summary, epoch)\n print(\"Finished training!\")\n save_path = saver.save(sess, \"data/model.ckpt\")\n print(\"Model saved in file: %s\" % save_path)\n '''\n # Test model\n correct_prediction = tf.argmax(nn, 1)\n #correct_prediction = tf.cast(tf.argmax(nn, 1), tf.int32)\n # Calculate accuracy\n #correct_prediction = tf.cast(correct_prediction,tf.int32)\n accuracy = tf.reduce_mean(tf.cast(tf.not_equal(correct_prediction, tf.cast(y,tf.int64)), dtype=tf.float32))\n acc = accuracy.eval({X: Xtest, S1: S1test, S2: S2test, y: ytest})\n print(\"Accuracy: {}%\".format(100 * (1 - acc)))\n '''\n\t\n"
},
{
"alpha_fraction": 0.6180344223976135,
"alphanum_fraction": 0.6405268311500549,
"avg_line_length": 36.9461555480957,
"blob_id": "db4fee91d7bacab90e032ca729ea62b99309ae01",
"content_id": "0a15742ad4b03898121c7f60d0a84491692bfac5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4935,
"license_type": "no_license",
"max_line_length": 145,
"num_lines": 130,
"path": "/tensorflow-value-iteration-networks/Refactoring/CPU_version/vin_class/refactored_train.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import time\nimport numpy as np\nimport tensorflow as tf\nfrom model import dnc\nfrom utils import *\nimport pickle \nnp.random.seed(0)\nimport pdb\nfrom tqdm import tqdm\n# Data\n\ntf.app.flags.DEFINE_integer('imsize', 32, 'Size of input image')\n# Parameters\ntf.app.flags.DEFINE_float('lr', 0.001, 'Learning rate for RMSProp')\ntf.app.flags.DEFINE_integer('epochs', 40, 'Maximum epochs to train for')\ntf.app.flags.DEFINE_integer('k', 10, 'Number of value iterations')\ntf.app.flags.DEFINE_integer('ch_i', 2, 'Channels in input layer')\ntf.app.flags.DEFINE_integer('ch_h', 150, 'Channels in initial hidden layer')\ntf.app.flags.DEFINE_integer('ch_q', 5, 'Channels in q layer (~actions)')\ntf.app.flags.DEFINE_integer('batchsize', 1, 'Batch size')\ntf.app.flags.DEFINE_integer('statebatchsize', 1, 'Number of state inputs for each sample (real number, technically is k+1)')\ntf.app.flags.DEFINE_boolean('untied_weights', False, 'Untie weights of VI network')\n# Misc.\ntf.app.flags.DEFINE_integer('display_step', 1, 'Print summary output every n epochs')\ntf.app.flags.DEFINE_boolean('log', False, 'Enable for tensorboard summary')\ntf.app.flags.DEFINE_string('logdir', '/tmp/vintf/', 'Directory to store tensorboard summary')\n\nconfig = tf.app.flags.FLAGS\n\n\n'''\nif (config.untied_weights):\n logits, nn = VI_Untied_Block(X, S1, S2, config)\nelse:\n logits, nn = VI_Block(X, S1, S2, config)\n'''\n\nwith open('sensor2_32_4.pickle', 'rb') as handle:\n b = pickle.load(handle)\nim = b['im']\nS1_ = b['S1']\nS2_ = b['S2']\nlabel = b['label']\n\n'''\ny_ = tf.cast(y, tf.int64)\ncross_entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(logits=logits, labels=y_, name='cross_entropy')\ncross_entropy_mean = tf.reduce_mean(cross_entropy, name='cross_entropy_mean')\ntf.add_to_collection('losses', cross_entropy_mean)\ncost = tf.add_n(tf.get_collection('losses'), name='total_loss')\noptimizer = tf.train.RMSPropOptimizer(learning_rate=config.lr, epsilon=1e-6, centered=True).minimize(cost)\n\n\ncp = tf.cast(tf.argmax(nn, 1), tf.int32)\nerr = tf.reduce_mean(tf.cast(tf.not_equal(cp, y), dtype=tf.float16))\n'''\n\ntotal_size = np.shape(im)\ntrain_size = np.round(total_size[0]*0.75)\ntrain_size = train_size.astype(int)\ntest_size = total_size[0] - train_size\n\nXtrain = im\nS1train = S1_\nS1shape = np.shape(S1train)\nS1train = np.reshape(S1train,(S1shape[0],config.statebatchsize))\nS2train = S2_\nS2shape = np.shape(S2train)\nS2train = np.reshape(S2train,(S2shape[0],config.statebatchsize))\nytrain= label\n\nXtest = Xtrain[train_size:total_size[0],:,:]\nS1test = S1train[train_size:total_size[0],:]\nS2test = S2train[train_size:total_size[0],:]\nytest = ytrain[train_size:total_size[0],]\n\nXtrain = Xtrain[0:train_size,:,:]\nS1train = S1train[0:train_size,:]\nS2train = S2train[0:train_size,:]\nytrain = ytrain[0:train_size:,]\nconfig.log = True \n\n\n \ndnc_ = dnc(config)\n\n\nbatch_size = config.batchsize\n#print(fmt_row(10, [\"Epoch\", \"Train Cost\", \"Train Err\", \"Test Err\", \"Epoch Time\"]))\nfor epoch in range(int(config.epochs)):\n tstart = time.time()\n avg_err, avg_cost = 0.0, 0.0\n num_batches = int(Xtrain.shape[0]/batch_size)\n # Loop over all batches\n for i in tqdm(range(0, Xtrain.shape[0], batch_size)):\n j = i + batch_size\n if j <= Xtrain.shape[0]:\n e_,c_ = dnc_.learner(Xtrain[i:j],S1train[i:j],S2train[i:j],ytrain[i * config.statebatchsize:j * config.statebatchsize])\n #fd = {X: Xtrain[i:j], S1: S1train[i:j], S2: S2train[i:j],y: ytrain[i * config.statebatchsize:j * config.statebatchsize]}\n #_, e_, c_ = sess.run([optimizer, err, cost], feed_dict=fd)\n avg_err += e_\n avg_cost += c_\n\n print \"train_err\"\n print avg_err/num_batches\n # Display logs per epoch step\n test_err = 0\n #if epoch % config.display_step == 0:\n #elapsed = time.time() - tstart\n #print(fmt_row(10, [epoch, avg_cost/num_batches, avg_err/num_batches, test_err, elapsed]))\n \n if config.log:\n summary = tf.Summary()\n summary.ParseFromString(sess.run(summary_op))\n summary.value.add(tag='Average error', simple_value=float(avg_err/num_batches))\n summary.value.add(tag='Average cost', simple_value=float(avg_cost/num_batches))\n summary_writer.add_summary(summary, epoch)\nprint(\"Finished training!\")\n\n\n # # Test model\n # correct_prediction = tf.cast(tf.argmax(nn, 1), tf.int32)\n # # Calculate accuracy\n # accuracy = tf.reduce_mean(tf.cast(tf.not_equal(correct_prediction, y), dtype=tf.float16))\n # acc = accuracy.eval({X: Xtest, S1: S1test, S2: S2test, y: ytest})\n # print(\"Accuracy: {}%\".format(100 * (1 - acc)))\n \n\nsave_path = saver.save(sess, \"data/model.ckpt\")\nprint(\"Model saved in file: %s\" % save_path)\n\n\n"
},
{
"alpha_fraction": 0.5524126291275024,
"alphanum_fraction": 0.5978924036026001,
"avg_line_length": 20.35714340209961,
"blob_id": "1c7e6a32e77f1c7542178d324811cfa6f4730182",
"content_id": "a395ce4cce891e958b9a7c12f51d923bea7e93e6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1803,
"license_type": "no_license",
"max_line_length": 99,
"num_lines": 84,
"path": "/data/read_data.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport pickle\nimport cv2\n\n\ndef im_to_rgb(im):\n\t# convert the representation of obstacles, free space\n\t# unknown into colors\n\tnew_im = 1 - im\n\tnew_im = np.array(new_im, dtype=np.float32)\n\tnew_im[new_im > 1.5] = 0.5\n\tnew_im = cv2.cvtColor(new_im, cv2.COLOR_GRAY2RGB)\n\tnew_im *= 255\n\treturn np.array(new_im, dtype=np.uint8)\n\ndef upscale_im(im, factor):\n\tim_shape = np.shape(im)\n\tim = cv2.resize(im, (im_shape[1] * factor, im_shape[0] * factor), interpolation=cv2.INTER_NEAREST)\n\treturn im\n\nfilename = \"sensor2_100.pickle\"\n\ndata = pickle.load(open(filename, \"rb\"))\nActionsStrings = ['Right', 'Up', 'Left', 'Down', 'Stay']\n\n\n# print data\nprint data['im'].shape\nprint data['S1'].shape\nprint data['S2'].shape\nprint data['label'].shape\n\nnum_data = data['S1'].shape[0]\n\nim = data['im']\nlabel = data['label']\nS1 = data['S1']\nS2 = data['S2']\n\ntry:\n\tminibatch_size = S1.shape[1]\nexcept:\n\tminibatch_size = 1\n\nlabel_idx = 0\nfor i in range(num_data):\n\tfor j in range(minibatch_size):\n\t\ty = int(label[label_idx])\n\t\tprint(str(i) + \", \" + str(j) + \" : \" + ActionsStrings[y])\n\t\tprint(im[i, :, :, 1])\n\t\tlabel_idx += 1\n\t\timage = im[i, :, :, 0].copy()\n\t\trew = im[i, :, :, 1]\n\n\n\t\timage = im_to_rgb(image)\n\n\t\ttry:\n\t\t\timage[S1[i][j], S2[i][j]] = [255, 0, 0]\n\t\texcept:\n\t\t\timage[S1[i], S2[i]] = [255, 0, 0]\n\n\t\tgoal = np.where(rew != 0)\n\t\timage[np.asscalar(goal[0]), np.asscalar(goal[1])] = [0, 0, 255]\n\n\n\t\timage = upscale_im(image, 20)\n\t\tcv2.imshow('image', image)\n\t\tcv2.waitKey(0)\n\n\n\n\n# for i in range(num_data):\n# \tfor i in range(im.shape[0]):\n\n# \t\ty = int(label[(i-1) * 10 + 1])\n# \t\tprint(str(i) + \": \" + ActionsStrings[y])\n# \t\timage = im[i, :, :, 0]\n# \t\timage[S1[i][0], S2[i][0]] = -1\n# \t\timage = im_to_rgb(image)\n# \t\timage = upscale_im(image, 20)\n# \t\tcv2.imshow('image', image)\n# \t\tcv2.waitKey(0)\n\n\n\n\n\n\n\n\n\n"
},
{
"alpha_fraction": 0.5213114619255066,
"alphanum_fraction": 0.5737704634666443,
"avg_line_length": 14.300000190734863,
"blob_id": "e850e6c14bc2add12d47ddc000dcd4c90ad93a6b",
"content_id": "35ba4411dec33b77033e08d81fb97b4fc7ca05ed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 305,
"license_type": "no_license",
"max_line_length": 41,
"num_lines": 20,
"path": "/tensorflow-value-iteration-networks/Refactoring/GPU_version/read_data.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import pickle \nimport pdb\nimport numpy as np \nimport cv2\n\nwith open('temp.pickle', 'rb') as handle:\n b = pickle.load(handle)\n\n\nim = b['im']\nS1 = b['S1']\nS2 = b['S2']\nlabel = b['label']\na = im[0,:,:,0]\nprint im[0,:,:,1]\na[a == -1] = 0\na[a == 0] = 1\n#cv2.imshow('image',a)\n#cv2.waitKey(0)\npdb.set_trace()"
},
{
"alpha_fraction": 0.7021276354789734,
"alphanum_fraction": 0.7659574747085571,
"avg_line_length": 22.5,
"blob_id": "2c3087f2fb2388cc3e927467b89753ea10c89127",
"content_id": "a3c38e3218d396a210ef88ae3bdaf07e2a39483f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 47,
"license_type": "no_license",
"max_line_length": 31,
"num_lines": 2,
"path": "/README.md",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "# finalproj650\n# python train.py to train VVIN\n"
},
{
"alpha_fraction": 0.6186338067054749,
"alphanum_fraction": 0.6503638029098511,
"avg_line_length": 41.28205108642578,
"blob_id": "32c3c99c5481968dbc94c436cf8b64d14234d680",
"content_id": "68c0d341908abe60758a9347c69f888b60ae6ccb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4948,
"license_type": "no_license",
"max_line_length": 123,
"num_lines": 117,
"path": "/tensorflow-value-iteration-networks/Refactoring/CPU_version/model_lstm.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport tensorflow as tf\nfrom utils import *\nimport pdb\nimport tensorflow.contrib.rnn as rnn\n\ndef conv2d_flipkernel(x, k, name=None):\n return tf.nn.conv2d(x, flipkernel(k), name=name,\n strides=(1, 1, 1, 1), padding='SAME')\n\ndef VI_Block(X, S1, S2, config,c_in,h_in):\n k = config.k # Number of value iterations performed\n ch_i = config.ch_i # Channels in input layer\n ch_h = config.ch_h # Channels in initial hidden layer\n ch_q = config.ch_q # Channels in q layer (~actions)\n state_batch_size = config.statebatchsize # k+1 state inputs for each channel\n \n bias = tf.Variable(np.random.randn(1, 1, 1, ch_h) * 0.01, dtype=tf.float32)\n # weights from inputs to q layer (~reward in Bel \n w0 = tf.Variable(np.random.randn(3, 3, ch_i, ch_h) * 0.01, dtype=tf.float32)\n w1 = tf.Variable(np.random.randn(1, 1, ch_h, 1) * 0.01, dtype=tf.float32)\n w = tf.Variable(np.random.randn(3, 3, 1, ch_q) * 0.01, dtype=tf.float32)\n # feedback weights from v layer into q layer (~transition probabilities in Bellman equation)\n w_fb = tf.Variable(np.random.randn(3, 3, 1, ch_q) * 0.01, dtype=tf.float32)\n w_o = tf.Variable(np.random.randn(ch_q, 4) * 0.01, dtype=tf.float32)\n\n # initial conv layer over image+reward prior\n h = conv2d_flipkernel(X, w0, name=\"h0\") + bias\n\n r = conv2d_flipkernel(h, w1, name=\"r\")\n q = conv2d_flipkernel(r, w, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n\n\n\n for i in range(0, k-1):\n rv = tf.concat([r, v], 3)\n wwfb = tf.concat([w, w_fb], 2)\n\n q = conv2d_flipkernel(rv, wwfb, name=\"q\")\n v = tf.reduce_max(q, axis=3, keep_dims=True, name=\"v\")\n\n\n # do one last convolution\n q = conv2d_flipkernel(tf.concat([r, v], 3),\n tf.concat([w, w_fb], 2), name=\"q\")\n\n\n\n\n # CHANGE TO THEANO ORDERING\n # Since we are selecting over channels, it becomes easier to work with\n # the tensor when it is in NCHW format vs NHWC\n q = tf.transpose(q, perm=[0, 3, 1, 2])\n\n # Select the conv-net channels at the state position (S1,S2).\n # This intuitively corresponds to each channel representing an action, and the convnet the Q function.\n # The tricky thing is we want to select the same (S1,S2) position *for each* channel and for each sample\n # TODO: performance can be improved here by substituting expensive\n # transpose calls with better indexing for gather_nd\n bs = tf.shape(q)[0]\n rprn = tf.reshape(tf.tile(tf.reshape(tf.range(bs), [-1, 1]), [1, state_batch_size]), [-1])\n ins1 = tf.cast(tf.reshape(S1, [-1]), tf.int32)\n ins2 = tf.cast(tf.reshape(S2, [-1]), tf.int32)\n idx_in = tf.transpose(tf.stack([ins1, ins2, rprn]), [1, 0])\n q_out = tf.gather_nd(tf.transpose(q, [2, 3, 0, 1]), idx_in, name=\"q_out\")\n \n x = tf.expand_dims(flatten(q_out), [0])\n\n size = 256\n lstm = tf.contrib.rnn.BasicLSTMCell(size, state_is_tuple=True)\n #lstm = tf.contrib.rnn.DropoutWrapper(lstm, input_keep_prob=0.75, output_keep_prob=0.75)\n state_size = lstm.state_size\n step_size = tf.shape(x)[:1]\n c_init = np.zeros((1, lstm.state_size.c), np.float32)\n h_init = np.zeros((1, lstm.state_size.h), np.float32)\n state_init = [c_init, h_init]\n #c_in = tf.placeholder(tf.float32, [1, lstm.state_size.c])\n #h_in = tf.placeholder(tf.float32, [1, lstm.state_size.h])\n state_in = [c_in, h_in]\n state_in = tf.contrib.rnn.LSTMStateTuple(c_in, h_in)\n\n lstm_outputs, lstm_state = tf.nn.dynamic_rnn(lstm, x, initial_state=state_in, sequence_length=step_size,time_major=False)\n lstm_c, lstm_h = lstm_state\n x = tf.reshape(lstm_outputs, [-1, size])\n logits = linear(x, 4, \"action\", normalized_columns_initializer(0.01))\n vf = tf.reshape(linear(x, 1, \"value\", normalized_columns_initializer(1.0)), [-1])\n state_out = [lstm_c[:1, :], lstm_h[:1, :]]\n sample = categorical_sample(logits, 4)[0, :]\n\n logits = tf.matmul(logits, w_o)\n output = tf.nn.softmax(logits, name=\"output\")\n\n \n state_out = [lstm_c[:1, :], lstm_h[:1, :]]\n return logits, output,state_out \n\n# similar to the normal VI_Block except there are separate weights for each q layer\n\ndef linear(x, size, name, initializer=None, bias_init=0):\n w = tf.get_variable(name + \"/w\", [x.get_shape()[1], size], initializer=initializer, dtype=tf.float32)\n b = tf.get_variable(name + \"/b\", [size], initializer=tf.constant_initializer(bias_init), dtype=tf.float32)\n return tf.matmul(x, w) + b\n\ndef flatten(x):\n return tf.reshape(x, [-1, np.prod(x.get_shape().as_list()[1:])])\n\ndef normalized_columns_initializer(std=1.0):\n def _initializer(shape, dtype=None, partition_info=None):\n out = np.random.randn(*shape).astype(np.float32)\n out *= std / np.sqrt(np.square(out).sum(axis=0, keepdims=True))\n return tf.constant(out)\n return _initializer\n\ndef categorical_sample(logits, d):\n value = tf.squeeze(tf.multinomial(logits - tf.reduce_max(logits, [1], keep_dims=True), 1), [1])\n return tf.one_hot(value, d)\n\n"
},
{
"alpha_fraction": 0.6493803262710571,
"alphanum_fraction": 0.6679713129997253,
"avg_line_length": 25.65217399597168,
"blob_id": "fa7109c752207eb3bd74ca078d9c19d795412b14",
"content_id": "2e7a9b73424fe03561f1cd6fd929e130daacb62a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3066,
"license_type": "no_license",
"max_line_length": 94,
"num_lines": 115,
"path": "/simulator/PathPlanners.py",
"repo_name": "arbaazkhan2/finalproj650",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport heapq\nfrom Map import Actions, ActionsStrings, ActionMotions, OppositeActions\n\n\ndef astar(map, start, goal, get_first_action=False):\n\t\"\"\"\n\tRuns astar\n\t\n\tArgs:\n\t\tmap (numpy arr): 2d map of environment\n\t\tstart (numpy arr): [x, y] position of start in map coordinates (see Map.py)\n\t\tgoal (numpy arr): [x, y] position of goal in map coordinates (see Map.py)\n\t\n\tReturns:\n\t\tTYPE: Description\n\t\"\"\"\n\tdef heuristic(pos, goal):\n\t\t# manhattan distance\n\t\treturn np.sum(np.abs(goal - pos))\n\n\tdef get_open_neighbors(pos, map):\n\t\tmapsize = map.shape\n\t\topen_neighbors = []\n\t\tfor idx, motion in enumerate(ActionMotions):\n\t\t\tnew_pos = pos + motion\n\n\t\t\tif new_pos[0] < 0 or new_pos[0] >= mapsize[0]:\n\t\t\t\t# if out of bounds\n\t\t\t\tcontinue\n\t\t\tif new_pos[1] < 0 or new_pos[1] >= mapsize[1]:\n\t\t\t\t# if out of bounds\n\t\t\t\tcontinue\n\t\t\tif map[new_pos[0], new_pos[1]] == 1:\n\t\t\t\t# if obstacle\n\t\t\t\tcontinue\n\t\t\topen_neighbors.append((new_pos, OppositeActions[idx]))\n\t\treturn open_neighbors\n\n\tmap_shape = map.shape\n\n\tshortest_distance = np.ones(map_shape) * (map_shape[0]*map_shape[1]*2)\n\thistory = np.ones(map_shape, dtype=np.int) * -1\n\n\t# make start position 0 distance\n\tshortest_distance[start[0], start[1]] = 0\n\t\n\t# used so that python implementation of heap works\n\tunique_id = 0\n\n\t# maintains list of nodes to visit \n\topen_list = []\n\theapq.heappush(open_list, \n\t\t(heuristic(start, goal) + shortest_distance[start[0], start[1]], unique_id, start))\n\tunique_id += 1\n\n\t# while list is not empty\n\t# update shortest_distance and history \n\tpath_found = False\n\twhile (len(open_list) != 0): \n\t\tnode = heapq.heappop(open_list)\n\t\tnode_pos = node[2]\n\t\tneighbor_dist = shortest_distance[node_pos[0], node_pos[1]] + 1\n\t\topen_neighbors = get_open_neighbors(node_pos, map)\n\t\tfor neighbor in open_neighbors:\t\n\t\t\tneighbor_pos = neighbor[0]\n\t\t\tif neighbor_dist < shortest_distance[neighbor_pos[0], neighbor_pos[1]]:\n\t\t\t\topen_list.append((heuristic(neighbor_pos, goal) + neighbor_dist, unique_id, neighbor_pos))\n\t\t\t\tunique_id += 1\n\n\t\t\t\tshortest_distance[neighbor_pos[0], neighbor_pos[1]] = neighbor_dist\n\t\t\t\tneighbor_action = neighbor[1]\n\t\t\t\thistory[neighbor_pos[0], neighbor_pos[1]] = neighbor_action\n\t\t\t\tif np.all(neighbor_pos == goal):\n\t\t\t\t\tpath_found = True\n\t\t\t\t\tbreak\n\n\tif (not path_found):\n\t\treturn [None, None]\n\n\t# extract shortest path\n\tpath = []\n\tactions = []\n\tcurr_pos = goal\n\twhile not np.all(curr_pos == start):\n\t\tnode_action = history[curr_pos[0], curr_pos[1]]\n\n\t\tpath.append(curr_pos)\n\t\tactions.append(OppositeActions[node_action])\n\n\t\tdiff = ActionMotions[node_action]\n\t\tcurr_pos = curr_pos + diff\n\n\tif get_first_action:\n\t\treturn [start, actions[-1]]\n\telse:\n\t\tpath.append(curr_pos)\n\t\tpath.reverse()\n\t\tpath.pop()\n\n\t\tactions.reverse()\n\t\treturn [path, actions]\n\n\nif __name__ == '__main__':\n\tfrom Map import Map\n\ttunnel_options = {'opening': 1, 'length': 3, 'closed': True}\n\tobst_options = {'max_nobst': 2, 'max_obst_size': [2, 2]}\n\n\t# np.random.seed(0)\n\tmap1 = Map()\n\tmap1.gen_map(10, 10, 'tunnel', tunnel_options)\n\tmap1.print_map()\n\n\tastar(map1.map_arr, map1.start, map1.goal)\n\n"
}
] | 15
|
shashaank-shankar/OFS-Intern-2019
|
https://github.com/shashaank-shankar/OFS-Intern-2019
|
3bfa19898763b6516f9ea94d5dded5a571182709
|
bafcc1df02a2bc3a2758b5441ba7f5903e9b30ac
|
a9e2f50ae4dfd360316ff80a552234b8a887a144
|
refs/heads/master
| 2020-06-10T20:10:29.910160
| 2019-07-25T13:32:16
| 2019-07-25T13:32:16
| 193,730,244
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.653333306312561,
"alphanum_fraction": 0.6800000071525574,
"avg_line_length": 24.16666603088379,
"blob_id": "c8debcb15de72ae10a72d75cd616903ea7cd7a0c",
"content_id": "542dad31ec44763ad4420e50d2a7c3e249448f16",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 150,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 6,
"path": "/Python Exercises/Array/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to append a new item to the end of the array.\nimport array as arr\na = arr.array('i', [1, 2, 3])\nprint(a)\na.append(4)\nprint(a)"
},
{
"alpha_fraction": 0.7126436829566956,
"alphanum_fraction": 0.7298850417137146,
"avg_line_length": 24,
"blob_id": "ea0686fcbd11f5eab32efdd09ba64063de4aac6c",
"content_id": "1fb1176fd5b827542011c049fb3a4a660040e9c7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 174,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 7,
"path": "/SQL-Lite Example/update-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()\ncursorObj.execute(\n 'update employees set firstname = \"Niyanth\" where id = 3'\n)\ncon.commit()"
},
{
"alpha_fraction": 0.6115485429763794,
"alphanum_fraction": 0.6194225549697876,
"avg_line_length": 20.58490562438965,
"blob_id": "1aeaf7a9a92b8539b9f3180d8aa8fb9b4f3eeb0f",
"content_id": "c5a0b322eca5db939ee9e67d9f982d14dcd80872",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1143,
"license_type": "no_license",
"max_line_length": 86,
"num_lines": 53,
"path": "/SQL-Lite Practice/create db-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('userdb.db')\ncursorObj = con.cursor()\n\ndef selectTable (val):\n cursorObj.execute(\n \"select \" + val + \" from user\"\n )\n rows = cursorObj.fetchall()\n for row in rows:\n print(row)\n con.commit()\n\ndef createTable ():\n cursorObj.execute(\n \"create table user(userid integer primary key, username text)\"\n )\n con.commit()\n#createTable()\nprint(\"\\n\")\nprint(\"Create table:\")\nselectTable(\"*\")\nprint(\"\\n\")\n\ndef insertTable (entities):\n cursorObj.executemany(\n 'insert into user(userid, username) values(?,?)',entities\n )\n con.commit()\nentities = [(1, \"Shashaank\"), (2, \"Natalie\"), (3, \"Niyanth\"), (4, \"John\"), (5, \"Bob\")]\n#insertTable(entities)\nprint(\"Insert values:\")\nselectTable(\"*\")\nprint(\"\\n\")\n\ndef updateTable ():\n cursorObj.execute(\n 'update user set username = \"Mark\" where userid = 5'\n )\n con.commit()\n#updateTable()\nprint(\"Update table:\")\nselectTable(\"*\")\nprint(\"\\n\")\n\ndef deleteTable ():\n cursorObj.execute(\n 'delete from user where userid = 4'\n )\n con.commit()\n#deleteTable()\nprint(\"Delete one row:\")\nselectTable(\"*\")"
},
{
"alpha_fraction": 0.5726103186607361,
"alphanum_fraction": 0.5818014740943909,
"avg_line_length": 39.22222137451172,
"blob_id": "11f50308cb6450ee304af690d61f072c70924277",
"content_id": "b210bbebf504601662fba2899bfd786c9aa9bec6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1088,
"license_type": "no_license",
"max_line_length": 115,
"num_lines": 27,
"path": "/Python Exercises/Condition Statements and Loops/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to convert temperatures to and from celsius, fahrenheit.\nprint(\"\\nThis program converts Celsius and Farenheit temperatures.\")\n\ndef tempConvert (type):\n if type == \"C\":\n # convert to C\n new_temp = (temp_input - 32) * (5/9)\n new_temp = round(new_temp, 2)\n print(\"\\n\" + str(temp_input) + \"F is equal to \" + str(new_temp) + \"C.\")\n elif type == \"F\":\n # convert to F\n new_temp = (temp_input * (9/5)) + 32\n new_temp = round(new_temp, 2)\n print(\"\\n\" + str(temp_input) + \"C is equal to \" + str(new_temp) + \"F.\")\n\n# repeats until 'C' or 'F' is entered\nwhile True:\n type_input = input(\"\\nEnter 'C' to convert to Celsius\\nEnter 'F' to convert to Farenheit\\nEnter 'E' to Exit: \")\n type_input = type_input.upper()\n if type_input == \"C\":\n temp_input = float(input(\"\\nEnter a temperature in Farenheit: \"))\n tempConvert(\"C\")\n elif type_input == \"F\":\n temp_input = float(input(\"\\nEnter a temperature in Celsius: \"))\n tempConvert(\"F\")\n elif type_input == \"E\":\n break "
},
{
"alpha_fraction": 0.5,
"alphanum_fraction": 0.5441176295280457,
"avg_line_length": 14.222222328186035,
"blob_id": "83cff5f768b4ee439ff42ca07be875fdc2d4cd19",
"content_id": "aa8e4f5ade46978c96d68a0fbe790693557dcb36",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 136,
"license_type": "no_license",
"max_line_length": 28,
"num_lines": 9,
"path": "/Python Exercises/Recursion/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# sum of list\n\ndef list_sum(list):\n sum = 0\n for val in list:\n sum = val + sum\n return sum\n\nprint(list_sum([2,4,5,6,7]))"
},
{
"alpha_fraction": 0.7435897588729858,
"alphanum_fraction": 0.7692307829856873,
"avg_line_length": 25.33333396911621,
"blob_id": "25d431d4a1f8b87942febe9897693decb1c10d62",
"content_id": "812c15c85b6d8453e29ec5b495793d7fdd971968",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 78,
"license_type": "no_license",
"max_line_length": 38,
"num_lines": 3,
"path": "/SQL-Lite Example/create-database.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()"
},
{
"alpha_fraction": 0.7083333134651184,
"alphanum_fraction": 0.734375,
"avg_line_length": 47,
"blob_id": "3e556f17888441b4db7f1ce43b4898f91cfba788",
"content_id": "d72252ef214eac5fac3fda8fabb4660b6647d52c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 192,
"license_type": "no_license",
"max_line_length": 129,
"num_lines": 4,
"path": "/Python Exercises/Array/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to create an array of 5 integers and display the array items. Access individual element through indexes.\nimport array as arr\na = arr.array('i', [1, 2, 3])\nprint(a[1])\n"
},
{
"alpha_fraction": 0.616216242313385,
"alphanum_fraction": 0.6486486196517944,
"avg_line_length": 25.428571701049805,
"blob_id": "688103b219a3a6f7ae0fd7b06e8219d1ce9d1802",
"content_id": "0e0abe5936b6459abf866b681b614fcb8cdc3c6f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 185,
"license_type": "no_license",
"max_line_length": 62,
"num_lines": 7,
"path": "/Python Exercises/List/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a python program to multiply all the items in a list\")\n\nlist = [1, 2, 3, 4, 5]\nproduct = 1\nfor num in list:\n product = product * num\nprint(\"The product is: \" + str(product))\n"
},
{
"alpha_fraction": 0.6739130616188049,
"alphanum_fraction": 0.717391312122345,
"avg_line_length": 26.799999237060547,
"blob_id": "77e7bcd2a71cb70455f0fdc41284f62046d3944b",
"content_id": "a9a0e44280fd7773b951aa2f18be779504f19b19",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 138,
"license_type": "no_license",
"max_line_length": 75,
"num_lines": 5,
"path": "/Python Exercises/Tuple/Exercise 3.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to create a tuple with numbers and print one item.\ntuplex = 1, 2, 3, 4, 5\nprint(tuplex)\ntuplex = 4,\nprint(tuplex)"
},
{
"alpha_fraction": 0.6849315166473389,
"alphanum_fraction": 0.698630154132843,
"avg_line_length": 26.375,
"blob_id": "899d22140183353492260fe759ee801bc33464d5",
"content_id": "3550655f8bb025471a782441dbcf5b0db4a4f17e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 219,
"license_type": "no_license",
"max_line_length": 75,
"num_lines": 8,
"path": "/SQL-Lite Example/insert-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()\nentities = (3, 'Bob', 'Ross')\ncursorObj.execute(\n 'insert into employees(id, firstname, lastname) values(?,?,?)',entities\n)\ncon.commit()\n"
},
{
"alpha_fraction": 0.5562499761581421,
"alphanum_fraction": 0.59375,
"avg_line_length": 21.85714340209961,
"blob_id": "3d91c662d7e9af67bf570765df36252317f23e17",
"content_id": "68b4d56676a5017e648e54038aa2ea42ac913636",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 160,
"license_type": "no_license",
"max_line_length": 57,
"num_lines": 7,
"path": "/Python Exercises/Functions/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a python program to sum all the items in a list\")\n\nlist = [8, 2, 3, 0, 7]\nsum = 0\nfor num in list:\n sum = sum + num\nprint(\"The sum is: \" + str(sum))\n"
},
{
"alpha_fraction": 0.5659090876579285,
"alphanum_fraction": 0.574999988079071,
"avg_line_length": 23.5,
"blob_id": "6827bcff2f865fab4303f75003b420841cf348b0",
"content_id": "871f30710bafddd0008fad3955e0bb39176d6e8f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 440,
"license_type": "no_license",
"max_line_length": 36,
"num_lines": 18,
"path": "/Python Exercises/String/Exercise 6.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program \n# to add 'ing' at the end of a \n# given string (length should \n# be at least 3). If the given \n# string already ends with 'ing' \n# then add 'ly' instead. If the \n# string length of the given string \n# is less than 3, leave it unchanged\n\na = input(\"Enter: \")\nlength = len(a)\nif length >= 3:\n if a[-3:] == \"ing\":\n a = a.replace('ing', 'ly')\n print(a)\n else:\n a = a + \"ing\"\n print(a)"
},
{
"alpha_fraction": 0.5,
"alphanum_fraction": 0.7222222089767456,
"avg_line_length": 17,
"blob_id": "3359def4dd660e5b738f9d53d653f0ee435fda3e",
"content_id": "738acc2eeaf3f3aa2a782cbdce3d5a5d3c7fc09e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 18,
"license_type": "no_license",
"max_line_length": 17,
"num_lines": 1,
"path": "/README.md",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# OFS-Intern-2019\n"
},
{
"alpha_fraction": 0.7171052694320679,
"alphanum_fraction": 0.7368420958518982,
"avg_line_length": 18.125,
"blob_id": "210cdb7e0898a882a1b9d00c51aaddf5b40f9156",
"content_id": "94a0f417e88e272ba31861b0d2765e0667505c10",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 152,
"license_type": "no_license",
"max_line_length": 38,
"num_lines": 8,
"path": "/SQL-Lite Example/delete-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()\ncursorObj.execute(\n 'delete from employees where id=2'\n)\n\ncon.commit()"
},
{
"alpha_fraction": 0.6491661667823792,
"alphanum_fraction": 0.6596664786338806,
"avg_line_length": 31.059406280517578,
"blob_id": "828eaf201d0539a1e76ec6c17a8bbacd7b66c3f1",
"content_id": "3ea0b01964908e053e2470b2f4d994bc59d0b810",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3238,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 101,
"path": "/temp_functions.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import mysql.connector\n\n# Connects this file to Temperature Database\nIOTdb = mysql.connector.connect(\n host=\"iotplatform.c66jtrv2jovs.us-east-1.rds.amazonaws.com\",\n user=\"iotplatformusr\",\n passwd=\"iotplatformpwd\",\n database =\"temperature_data_logger\"\n)\n\n# What allows Python to execute SQL queries\ncursorObj = IOTdb.cursor()\n\n# List of all values from a column (EX: Decimal('89.00'))\ncolumn_values = []\n# List of all isolated values from a column (EX: '89.00')\ncolumn_values_iso = []\n\n# 'tablename' is the name of the table\n# 'column_num' is the number of the column that is selected\n# 'list' is the list the values are appended to\ndef selectTable (tablename, column_num, list):\n cursorObj.execute(\n \"select * from \" + tablename\n )\n records = cursorObj.fetchall()\n for row in records:\n list.append(row[column_num])\n IOTdb.commit()\n\n# Adds all values from 'RECORD_TEMPERAURE' to column_values\nselectTable(\"RECORD_TEMPERATURE\", 2, column_values)\n\n# Isolates value from 'list'\n# Appends value to 'list_append'\ndef value_strip (list, list_append):\n for value in list:\n value = str(value)\n value.strip()\n list_append.append(value)\n\n# Isolates temperature from 'column_values' and appends to 'column_values_iso'\nvalue_strip(column_values, column_values_iso)\n\n# Converts temperature to either F or C\ndef tempConvert (type, temperature):\n if type.upper() == \"C\":\n # Converts temperature to C\n new_temp = (temperature - 32.0) * (5.0/9.0)\n new_temp = round(new_temp, 2)\n return new_temp\n elif type.upper() == \"F\":\n # Converts temperature to F\n new_temp = (temperature * (9.0/5.0)) + 32.0\n new_temp = round(new_temp, 2.0)\n return new_temp\n\n# Returns average of values in 'list'\ndef average (list):\n sum = 0\n count = 0\n for value in list:\n sum = sum + float(value)\n count += 1\n average = round(sum/count, 2)\n return average\n\n# Prints average temperature of 'columns_values_iso' in F and C\nprint(\"\\nAVERAGE:\")\nprint(\"The average is \"+ str(average(column_values_iso)) + \" degrees Farenheit\")\nprint(\"and \" + str(tempConvert('c', average(column_values_iso))) + \" degrees Celsius.\")\n\n#Find the min value\ndef min_function(list):\n min_value = None\n for value in list:\n if not min_value:\n min_value = value\n elif value < min_value:\n min_value = value\n return min_value\n\n# Prints the minimum temperature of 'columns_values_iso' in F and C\nprint(\"\\nMINIMUM:\")\nprint(\"The minimum temperature is \" + min_function(column_values_iso) + \" degrees Farenheit\")\nprint(\"and \" + str(tempConvert('c', float(min_function(column_values_iso)))) + \" degrees Celsius.\\n\")\n\n# Find the max value\ndef max_function(list):\n max_value = None\n for value in list:\n if not max_value:\n max_value = value\n elif value > max_value:\n max_value = value\n return max_value\n\n# Prints the maximum temperature of 'columns_values_iso' in F and C\nprint('\\nMAXIMUM:')\nprint(\"The minimum temperature is \" + max_function(column_values_iso) + \" degrees Farenheit\")\nprint(\"and \" + str(tempConvert('c', float(max_function(column_values_iso)))) + \" degrees Celsius.\\n\")\n"
},
{
"alpha_fraction": 0.5423280596733093,
"alphanum_fraction": 0.5573192238807678,
"avg_line_length": 38.034481048583984,
"blob_id": "1cd835ce6c2047ec21cc0608101d7fd1d58efff2",
"content_id": "b5fb6a471cf9d60c263eb42e285136c7c1cacddb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1134,
"license_type": "no_license",
"max_line_length": 117,
"num_lines": 29,
"path": "/TempConverter.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "#print(\"\\nThis program converts Celsius and Farenheit temperatures.\")\n\ndef tempConvert (type, temperature):\n if type.upper() == \"C\":\n # convert to C\n new_temp = (temperature - 32.0) * (5.0/9.0)\n new_temp = round(new_temp, 2)\n #print(\"\\n\" + str(temperature) + \"F is equal to \" + str(new_temp) + \"C.\")\n return new_temp\n elif type.upper() == \"F\":\n # convert to F\n new_temp = (temperature * (9.0/5.0)) + 32.0\n new_temp = round(new_temp, 2.0)\n #print(\"\\n\" + str(temperature) + \"C is equal to \" + str(new_temp) + \"F.\")\n return new_temp\n\n\n# repeats until 'C' or 'F' or 'E' is entered\n# while True:\n# type_input = input(\"\\nEnter 'C' to convert to Celsius\\nEnter 'F' to convert to Farenheit\\nEnter 'E' to Exit: \")\n# type_input = type_input.upper()\n# if type_input == \"C\":\n# temp_input = float(input(\"\\nEnter a temperature in Farenheit: \"))\n# tempConvert(\"C\")\n# elif type_input == \"F\":\n# temp_input = float(input(\"\\nEnter a temperature in Celsius: \"))\n# tempConvert(\"F\")\n# elif type_input == \"E\":\n# break "
},
{
"alpha_fraction": 0.5869947075843811,
"alphanum_fraction": 0.5887522101402283,
"avg_line_length": 27.399999618530273,
"blob_id": "7ca52adb6c4444fcb7c02e91539e7f962633df89",
"content_id": "cf3e7d90e5a01c02ba4d42b86fe51ec1770b9173",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 569,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 20,
"path": "/06-13-19/palindrome.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "\ndef reverse (text):\n return text[::-1]\n\ndef checkPalindrome ():\n if reverse(new_phrase) == new_phrase:\n return True\n else:\n return False\n\nprint(\"\\nThis program checks if a phrase you enter is a palindrome.\")\n\nwhile True:\n phrase = input(\"\\nEnter 'E' to exit\\nEnter a phrase to check if its a palindrome: \")\n new_phrase = phrase.replace(\" \", \"\")\n if new_phrase.lower() == \"e\":\n break\n if checkPalindrome():\n print(\"\\n'\" + phrase + \"' is a palindrome!\")\n else:\n print(\"\\n'\" + phrase + \"' is not a palindrome.\")\n"
},
{
"alpha_fraction": 0.5787965655326843,
"alphanum_fraction": 0.6189111471176147,
"avg_line_length": 28.16666603088379,
"blob_id": "3b90dadf8efe9c222a577c1159aeed29f438ff0e",
"content_id": "05fe72b1ad5b3210668cbc38540eecea9dc60c42",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 349,
"license_type": "no_license",
"max_line_length": 81,
"num_lines": 12,
"path": "/Python Exercises/Functions/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python function to find the Max of three numbers\n\ndef max(num1, num2, num3):\n print(\"The biggest number is:\")\n if num1 > num2 and num1 > num3:\n print(num1)\n elif num2 > num1 and num2 > num3:\n print(num2)\n else:\n print(num3)\n\nmax(input(\"Enter a number:\"), input(\"Enter a number:\"), input(\"Enter a number:\"))"
},
{
"alpha_fraction": 0.4923076927661896,
"alphanum_fraction": 0.5230769515037537,
"avg_line_length": 19.076923370361328,
"blob_id": "437d7a31492aef682160c33e887fcfc822897e26",
"content_id": "6736f9cca650a5acec5f84da8c422e2a7dbae095",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 260,
"license_type": "no_license",
"max_line_length": 37,
"num_lines": 13,
"path": "/Python Exercises/Search and Sorting/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# sequential search\n\ndef seq_search(item_list, item):\n found = False\n for val in item_list:\n if val == item:\n found = True\n break\n else:\n found = False\n return found\n\nprint(seq_search([1,4,2,5,6,5,9], 2))"
},
{
"alpha_fraction": 0.6797385811805725,
"alphanum_fraction": 0.7058823704719543,
"avg_line_length": 29.799999237060547,
"blob_id": "1a6b04996ac2243e120004eff2a254ad18ee21d0",
"content_id": "bd586a0e03fc79dcb344da7ce8647c6760ab6dab",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 153,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 5,
"path": "/Python Exercises/File IO/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "def file_read (file):\n txt = open(file)\n print(txt.read())\n\nfile_read('/Users/Shashaank/Desktop/OFS-Intern-2019/Python Exercises/File IO/test.txt')"
},
{
"alpha_fraction": 0.6497175097465515,
"alphanum_fraction": 0.7062146663665771,
"avg_line_length": 24.285715103149414,
"blob_id": "057e42872ce2bdf55f6bf5346ac66b31f0f1fde2",
"content_id": "44a1af8dad195143d653f293fc5b321babc61a01",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 354,
"license_type": "no_license",
"max_line_length": 94,
"num_lines": 14,
"path": "/POST.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import requests\n\nAPI_ENDPOINT = \"https://3agy2aan5j.execute-api.us-east-1.amazonaws.com/dev/record_temperature\"\n\ndata = {\n \"SENSOR_ID\": \"RASPBERRYPI\",\n\t\"TEMPERATURE_CAPTURE_TS\": \"2019-07-11 10:31:30\",\n\t\"TEMPERATURE_READING\": 90\n}\n\nr = requests.post(url = API_ENDPOINT, data = data)\n\npastebin_url = r.text \nprint(\"The pastebin URL is:%s\"%pastebin_url) "
},
{
"alpha_fraction": 0.625,
"alphanum_fraction": 0.6730769276618958,
"avg_line_length": 25.25,
"blob_id": "d661071462e00bbc86e134593229f3bab9c42d63",
"content_id": "ee3cb5e521da9665bf83ea5e53856a93acef82fa",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 104,
"license_type": "no_license",
"max_line_length": 48,
"num_lines": 4,
"path": "/Python Exercises/Sets/Exercise 2.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to iteration over sets.\nnums = set([1,2,3,4,5])\nfor num in nums:\n print(num)"
},
{
"alpha_fraction": 0.6835748553276062,
"alphanum_fraction": 0.6835748553276062,
"avg_line_length": 38.47618865966797,
"blob_id": "496564b8ddf402886c1f7d9dbeb911f389547e4d",
"content_id": "edd6cf15a8991c384d6fe0d4caf3349cb6b0b663",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 828,
"license_type": "no_license",
"max_line_length": 70,
"num_lines": 21,
"path": "/Python Exercises/Date Time/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python script to display the various Date Time formats.\nimport time\nimport datetime\nprint('\\n')\n# a) Current date and time\nprint(\"Current date and time: \" , datetime.datetime.now())\n# b) Current year\nprint(\"Current Year: \" , datetime.date.today().strftime(\"%Y\"))\n# c) Month of year\nprint(\"Current Month: \" , datetime.date.today().strftime(\"%B\"))\n# d) Week number of the year\nprint(\"Current Week Number: \" , datetime.date.today().strftime(\"%W\"))\n# e) Weekday of the week\nprint(\"Current Day of Week: \" , datetime.date.today().strftime(\"%w\"))\n# f) Day of year\nprint(\"Current Day of Year: \" , datetime.date.today().strftime(\"%j\"))\n# g) Day of the month\nprint(\"Current Day of Month: \" , datetime.date.today().strftime(\"%d\"))\n# h) Day of week\nprint(\"Current Day of Week: \" , datetime.date.today().strftime(\"%A\"))\nprint('\\n')"
},
{
"alpha_fraction": 0.4781976640224457,
"alphanum_fraction": 0.4883720874786377,
"avg_line_length": 36.94444274902344,
"blob_id": "c792441e4475e2189afef6b9f4b38eed3e7c4aee",
"content_id": "4c68deddfe01c33f17e73b6c9552fccb85e73ac3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 688,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 18,
"path": "/06-13-19/PrimeNumber.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "\nwhile True:\n num = input(\"\\nEnter 'E' to exit\\nEnter a number above one to check if it's a prime number: \")\n if num.lower() == 'e':\n break\n elif num.isdigit() == False:\n print(\"Enter a number above 1!\")\n elif int(num) <= 1:\n print(\"Enter a number above 1!\")\n else:\n for val in range(2, int(num) + 1):\n # if test below doesn't pass its a prime num\n if val == int(num):\n print(\"\\n\"+str(num) + \" is a prime number.\\n\")\n break\n # checks if remainder is 0\n elif int(num) % val == 0:\n print(\"\\n\"+str(num) + \" isn't a prime number!\\n\")\n break\n "
},
{
"alpha_fraction": 0.5542522072792053,
"alphanum_fraction": 0.6480938196182251,
"avg_line_length": 47.71428680419922,
"blob_id": "0669fa9486066c0a53b54f782a5f9d4d0e816264",
"content_id": "bf17e0fb2e371093fea611d072a07e5b1aedafe4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 341,
"license_type": "no_license",
"max_line_length": 129,
"num_lines": 7,
"path": "/Python Exercises/Condition Statements and Loops/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to find those numbers which are divisible by 7 and multiple of 5, between 1500 and 2700 (both included).\n\ninput = int(input(\"Enter a number: \"))\nif input >= 1500 and input <= 2700:\n if input%7 == 0:\n if input%5 == 0:\n print(input + \" is between 1500 and 2700. It is also divisable by 7 and 5.\")\n"
},
{
"alpha_fraction": 0.5834810137748718,
"alphanum_fraction": 0.5937610864639282,
"avg_line_length": 34.7088623046875,
"blob_id": "8ddc7d59881ef8f2e2f3345271b355f7a886f037",
"content_id": "e9626f3fdad4c9889fd2dcfd13b3a1d7785c4e95",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2821,
"license_type": "no_license",
"max_line_length": 103,
"num_lines": 79,
"path": "/RestAPI_temp_functions.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import requests, json\n\ndef get_data():\n API_ENDPOINT = \"https://3agy2aan5j.execute-api.us-east-1.amazonaws.com/dev/record_temperature?\"\n response = requests.get(url = API_ENDPOINT)\n if(response.ok):\n response_json = json.loads(response.content)\n for key in response_json[\"message\"]:\n print(\"RECORD_INSERT_TS :\" + key[\"RECORD_INSERT_TS\"])\n print(\"SENSOR_ID :\" + key[\"SENSOR_ID\"])\n print(\"TEMPERATURE_CAPTURE_TS :\" + key[\"TEMPERATURE_CAPTURE_TS\"])\n print(\"TEMPERATURE_READING :\" + key[\"TEMPERATURE_READING\"])\n print(\"UNIQUE_GUID:\" + str(key[\"UNIQUE_GUID\"]))\n print(\"\\n\")\n else:\n print('Error on API request')\n\ndef create_data_list():\n data_list = []\n API_ENDPOINT = \"https://3agy2aan5j.execute-api.us-east-1.amazonaws.com/dev/record_temperature?\"\n response = requests.get(url = API_ENDPOINT)\n if(response.ok):\n response_json = json.loads(response.content)\n for key in response_json[\"message\"]:\n data_list.append(key[\"TEMPERATURE_READING\"])\n return data_list\n else:\n print('Error on API request')\n\ndef tempConvert (type, temperature):\n if type.upper() == \"C\":\n # Converts temperature to C\n new_temp = (temperature - 32.0) * (5.0/9.0)\n new_temp = round(new_temp, 2)\n return new_temp\n elif type.upper() == \"F\":\n # Converts temperature to F\n new_temp = (temperature * (9.0/5.0)) + 32.0\n new_temp = round(new_temp, 2.0)\n return new_temp\n\ndef average (list):\n sum = 0\n count = 0\n for value in list:\n sum = sum + float(value)\n count += 1\n average = round(sum/count, 2)\n return average\n\nprint(\"\\nAVERAGE:\")\nprint(\"The average is \" + str(average(create_data_list())) + \" degrees Farenheit.\")\nprint(\"and \" + str(tempConvert('c', average(create_data_list()))) + \" degrees Celsius.\")\n\ndef min_function(list):\n min_value = None\n for value in list:\n if not min_value:\n min_value = value\n elif value < min_value:\n min_value = value\n return min_value\n\nprint(\"\\nMINIMUM:\")\nprint(\"The minimum temperature is \" + min_function(create_data_list()) + \" degrees Farenheit\")\nprint(\"and \" + str(tempConvert('c', float(min_function(create_data_list())))) + \" degrees Celsius.\\n\")\n\ndef max_function(list):\n max_value = None\n for value in list:\n if not max_value:\n max_value = value\n elif value > max_value:\n max_value = value\n return max_value\n\nprint('\\nMAXIMUM:')\nprint(\"The maximum temperature is \" + max_function(create_data_list()) + \" degrees Farenheit\")\nprint(\"and \" + str(tempConvert('c', float(max_function(create_data_list())))) + \" degrees Celsius.\\n\")\n"
},
{
"alpha_fraction": 0.443736732006073,
"alphanum_fraction": 0.46921443939208984,
"avg_line_length": 33.85185241699219,
"blob_id": "0167547e107b5dda5557440d12053a2bcab04dd0",
"content_id": "e407d61e1764bb5554dc6b00bc44bd847c1f0a4c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 942,
"license_type": "no_license",
"max_line_length": 107,
"num_lines": 27,
"path": "/06-13-19/fibonacci.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "\nwhile True:\n upper = 1000\n count = 0\n num1 = 0\n num2 = 1\n limit = input(\"\\nEnter 'E' to Exit\\nEnter a number to display\\nFibonacci Sequence up to that number: \")\n if limit.lower() == 'e':\n break\n elif limit.isdigit() == False:\n print(\"Enter only numbers above 0!\")\n else:\n if int(limit) <= 0:\n print(\"\\nEnter a postive number!\")\n elif int(limit) >= upper:\n print(\"Enter a number smaller than 1000!\")\n else:\n if int(limit) == 1:\n print(\"\\nThe Fibonacci Sequence for \" + str(limit) + \" is:\")\n print(num1)\n else:\n print(\"\\nThe Fibonacci Sequence for \" + str(limit) + \" is:\")\n while count < int(limit):\n print(str(num1))\n temp_num = num1 + num2\n num1 = num2\n num2 = temp_num\n count += 1\n"
},
{
"alpha_fraction": 0.7459016442298889,
"alphanum_fraction": 0.7459016442298889,
"avg_line_length": 40,
"blob_id": "ccf7c78353e03e1d21e339415423cfe017fac7cc",
"content_id": "62a1afebf398dceb3ed863a22698613d8a78be32",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 122,
"license_type": "no_license",
"max_line_length": 56,
"num_lines": 3,
"path": "/Python Exercises/Date Time/Exercise 4.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to get the current time.\nimport datetime\nprint(\"Current time: \" , datetime.datetime.now().time())"
},
{
"alpha_fraction": 0.5562499761581421,
"alphanum_fraction": 0.59375,
"avg_line_length": 21.85714340209961,
"blob_id": "b6bbbbe7792db5823a41ce83c6738c37ff263d92",
"content_id": "370f35956c9be1e99ad178e820778e3da26e2941",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 160,
"license_type": "no_license",
"max_line_length": 57,
"num_lines": 7,
"path": "/Python Exercises/List/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a python program to sum all the items in a list\")\n\nlist = [1, 2, 3, 4, 5]\nsum = 0\nfor num in list:\n sum = sum + num\nprint(\"The sum is: \" + str(sum))\n"
},
{
"alpha_fraction": 0.6851851940155029,
"alphanum_fraction": 0.6851851940155029,
"avg_line_length": 20.799999237060547,
"blob_id": "3c7ce51e8bd2d8f2d691b1d49bc65f2d0daf6dd5",
"content_id": "266c9b0ac168652fb3e1831e5cf46ecb4ddc6277",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 108,
"license_type": "no_license",
"max_line_length": 33,
"num_lines": 5,
"path": "/Python Exercises/Sets/Exercise 3.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "color_set = set()\ncolor_set.add(\"White\")\nprint(color_set)\ncolor_set.update([\"Red\", \"Blue\"])\nprint(color_set)"
},
{
"alpha_fraction": 0.7079207897186279,
"alphanum_fraction": 0.7178217768669128,
"avg_line_length": 19.299999237060547,
"blob_id": "9afb6814ebf558be35284750ec15ccb38ff5fce6",
"content_id": "2db2929d3015cba048c2b839a07de0cbd92791c1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 202,
"license_type": "no_license",
"max_line_length": 38,
"num_lines": 10,
"path": "/SQL-Lite Example/select-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()\ncursorObj.execute(\n 'select * from employees'\n)\nrows = cursorObj.fetchall()\nfor row in rows:\n print(row)\ncon.commit()"
},
{
"alpha_fraction": 0.6423841118812561,
"alphanum_fraction": 0.6556291580200195,
"avg_line_length": 32.11111068725586,
"blob_id": "b6cd60709f82ec33dac0d3d45019eddb4182124b",
"content_id": "57c4abeeff432bd22c0489e13d0bb12632ca7d83",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 302,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 9,
"path": "/Python Exercises/File IO/Exercise 3.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "def file_read(file):\n from itertools import islice\n with open(file, \"w\") as myfile:\n myfile.write(\"\\nTest\\n\")\n myfile.write(\"Python Exercises\\n\")\n txt = open(file)\n print(txt.read())\n\nfile_read('/Users/Shashaank/Desktop/OFS-Intern-2019/Python Exercises/File IO/test.txt')\n "
},
{
"alpha_fraction": 0.6137565970420837,
"alphanum_fraction": 0.6243386268615723,
"avg_line_length": 26.14285659790039,
"blob_id": "85620f5d3fb201952c6f27ae7d34bc117bb9e7c9",
"content_id": "1751da402824394506b175f0ba406d069d12397c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 189,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 7,
"path": "/Python Exercises/String/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Write a Python program to calculate the length of a string\n\na = input(\"Enter: \")\ncount = 0\nfor char in a:\n count += 1\nprint(\"The length of \" + a + \" is \" + str(count) + \" characters.\")"
},
{
"alpha_fraction": 0.7142857313156128,
"alphanum_fraction": 0.7142857313156128,
"avg_line_length": 15.666666984558105,
"blob_id": "c37486c4988593f7642aea7c8615f51f1b796538",
"content_id": "93d9f4c2ba42bad54cbe57cf4d365aaa4034fc61",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 49,
"license_type": "no_license",
"max_line_length": 23,
"num_lines": 3,
"path": "/Python Exercises/Tuple/Exercise 1.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "# Create an empty tuple\ntuplex = ()\nprint(tuplex)"
},
{
"alpha_fraction": 0.75,
"alphanum_fraction": 0.7602040767669678,
"avg_line_length": 27.14285659790039,
"blob_id": "b86da0a82f4763151b8b508be52e9e8acefdc47c",
"content_id": "1ff2e4dbe9589d06cead2ddfe850fd24acc4300d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 196,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 7,
"path": "/SQL-Lite Example/create-table.py",
"repo_name": "shashaank-shankar/OFS-Intern-2019",
"src_encoding": "UTF-8",
"text": "import sqlite3\ncon = sqlite3.connect('mydatabase.db')\ncursorObj = con.cursor()\ncursorObj.execute(\n \"Create table employees(id integer primary key, firstname text, lastname text)\"\n)\ncon.commit()"
}
] | 35
|
m00np/TRABALHO-PYTHON
|
https://github.com/m00np/TRABALHO-PYTHON
|
8c54e9f78616073e6be955287db99e1327746eb5
|
78625d112661ae44ef436c386bfc6088de72e14b
|
3642041c25838d25ea3fa9ac5e57a96011b9201d
|
refs/heads/master
| 2020-07-16T09:41:00.240785
| 2019-09-02T02:54:55
| 2019-09-02T02:54:55
| 205,765,741
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6193029284477234,
"alphanum_fraction": 0.6461126208305359,
"avg_line_length": 29.08333396911621,
"blob_id": "6cd1bdafe0709617b0d57fc098d1e44a97784453",
"content_id": "2f5266e60d137df81efd9c94f791c98b7c2b4180",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 386,
"license_type": "no_license",
"max_line_length": 59,
"num_lines": 12,
"path": "/QUESTÃO 10 (difícil).py",
"repo_name": "m00np/TRABALHO-PYTHON",
"src_encoding": "UTF-8",
"text": "n1= float(input('Digite sua primeira nota: '))\r\nn2= float(input('Digite sua segunda nota: '))\r\nmedia= (n1 + n2)/2\r\nif media >=7:\r\n print('APROVADO')\r\nif media <=7:\r\n print('RECUPERAÇÃO')\r\nrecuperação= float(input('Digite a nota da recuperação: '))\r\nif (media + recuperação)/2 >=5:\r\n print('APROVADO APÓS RECUPERAÇÃO')\r\nif recuperação <=5:\r\n print('REPROVADO')\r\n"
},
{
"alpha_fraction": 0.6323529481887817,
"alphanum_fraction": 0.6323529481887817,
"avg_line_length": 32,
"blob_id": "291fd53d3f7ed47248cf1fdbe71b6afcfa67e046",
"content_id": "acc4d9484555efcb3d761b998a7d56d529af30d4",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 207,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 6,
"path": "/QUESTÃO 4 (intermediária).py",
"repo_name": "m00np/TRABALHO-PYTHON",
"src_encoding": "UTF-8",
"text": "usuário= input('digite seu nome de usuário: ')\r\nsenha= input('digite sua senha: ')\r\nif (usuário == 'fernanda' and senha == '12345'):\r\n print('SEJA BEM-VINDA!')\r\nelse:\r\n print('ACESSO NEGADO')\r\n"
},
{
"alpha_fraction": 0.5524296760559082,
"alphanum_fraction": 0.5754475593566895,
"avg_line_length": 17.549999237060547,
"blob_id": "c3a3cd3faa28a724b24d866e7591409dea0e01dc",
"content_id": "902c266345a382f4438aa531c440f71893fa63a5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 400,
"license_type": "no_license",
"max_line_length": 37,
"num_lines": 20,
"path": "/QUESTÃO 10 (fácil).py",
"repo_name": "m00np/TRABALHO-PYTHON",
"src_encoding": "UTF-8",
"text": "n1 = int(input('digite um número: '))\r\nn2 = int(input('digite um número: '))\r\nn3 = int(input('digite um número: '))\r\n\r\n\r\n\r\nif n1 <=0:\r\n print(\"o numero é negativo\")\r\nelse: \r\n print(\"o numero é positivo\")\r\n\r\nif n2 >=0:\r\n print(\"o numero é positivo\")\r\nelse: \r\n print(\"o numero é negativo\")\r\n\r\nif n3 >=0:\r\n print(\"o numero é positivo\")\r\nelse: \r\n print(\"o numero é negativo\")\r\n"
}
] | 3
|
Elizaveta100000/SelectionCinemaBot
|
https://github.com/Elizaveta100000/SelectionCinemaBot
|
ada24c8f10fbc7799d7a6408cf4a81989a0a2f33
|
aa091115bf7b56b92507f253578f7df8426ea8ab
|
d1e7b4b7f9d4dfb6488fedd88dc22ad8686b6bd3
|
refs/heads/master
| 2021-08-31T17:26:48.393165
| 2017-12-22T07:41:24
| 2017-12-22T07:41:24
| 111,251,939
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4925023317337036,
"alphanum_fraction": 0.49718838930130005,
"avg_line_length": 38.28220748901367,
"blob_id": "be121c2ac31c34f0468c9ebe9c4d718a9d778ba5",
"content_id": "06289d7a8d675760c12798126bfb7b5659b30d41",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6402,
"license_type": "no_license",
"max_line_length": 110,
"num_lines": 163,
"path": "/tele.py",
"repo_name": "Elizaveta100000/SelectionCinemaBot",
"src_encoding": "UTF-8",
"text": "import requests\nimport telegram\nimport random\nimport re\nfrom bs4 import BeautifulSoup\n\ntoken_tele = '492227439:AAF3wwl73zSTGFYyo3QqLA2tqrhKz7gsEa4'\napi_key = '35c2d6b4'\nimdb_url = 'http://www.imdb.com/search/keyword'\n\nclass MoviesBot():\n readyStrings = ['Ready to /help!']\n whatStrings = ['Yes?', 'Hmmm?', 'What do you want?']\n yesStrings = ['I can do that.', 'Be happy to.', 'Sure!']\n noStrings = [\"I can't do that.\", \"You stupid?\", \"Not right...\", \"Don't think that I can do that...\"]\n\n options = [\"search\", \"recommend\", \"tag\"]\n\n helpMessage = \"\"\" Hello, fellow user! I'm the Movies Bot!\n\n\tHere is what I can do now:\n\t/search Give me a series/movie title and I'll get information about it for you!\n\t/tag without parameters gives you the whole list of tags from IMDb\n\t/tag with a tags from a list gives you a movie-list, based on tags you have chosen before\n\n\tNote! All tags have to be written with a delimiter ','!\n\t\"\"\"\n def_url = 'http://www.omdbapi.com/?t=TITLE&apikey=API&plot=short&tomatoes=false&r=json'\n default_url = def_url.replace(\"API\", api_key)\n\n def __init__(self, token=token_tele):\n self.token = token\n self.bot = telegram.Bot(token)\n try:\n self.lastUpdate = self.bot.getUpdates()[-1].update_id\n except IndexError:\n self.lastUpdate = None\n\n def startBot(self):\n while True:\n for update in self.bot.getUpdates(offset=self.lastUpdate, timeout=10):\n chat_id = update.message.chat_id\n message = update.message.text\n\n if message:\n if \"@SelectionCinemaBot\" in message:\n botid = \"@SelectionCinemaBot\"\n message = message[:message.find(botid)] + message[message.find(botid) + len(botid):]\n if (message.startswith('/')):\n command, _, arguments = message.partition(' ')\n if command == '/start':\n self.bot.sendMessage(chat_id=chat_id, text=MoviesBot.readyStrings[0])\n elif command == '/help':\n self.bot.sendMessage(chat_id=chat_id, text=MoviesBot.helpMessage)\n elif command[1:] in MoviesBot.options:\n noArgument = False\n if arguments == '':\n noArgument = True\n\n rand = random.randint(0, len(MoviesBot.yesStrings) - 1)\n self.bot.sendMessage(chat_id=chat_id, text=MoviesBot.yesStrings[rand])\n\n if command == '/search':\n if noArgument:\n self.bot.sendMessage(chat_id=chat_id, text=\"Give me something to search.\")\n else:\n msg, poster = self.searchMovie(arguments)\n self.bot.sendPhoto(chat_id=chat_id, photo=poster)\n self.bot.sendMessage(chat_id=chat_id, text=msg)\n\n if command == '/tag':\n if noArgument:\n self.bot.sendMessage(chat_id=chat_id, text=self.getTags(command='/tag'))\n else:\n try:\n m = self.searchTag(arguments)\n self.bot.sendMessage(chat_id=chat_id, text=m)\n except Exception:\n rand = random.randint(0, len(MoviesBot.noStrings) - 1)\n self.bot.sendMessage(chat_id=chat_id, text=MoviesBot.noStrings[rand])\n else:\n rand = random.randint(0, len(MoviesBot.whatStrings) - 1)\n self.bot.sendMessage(chat_id=chat_id, text=MoviesBot.whatStrings[rand])\n\n self.lastUpdate = update.update_id + 1\n\n def searchMovie(self, title):\n usr_request = MoviesBot.default_url.replace(\"TITLE\", title)\n mov = requests.get(usr_request).json()\n message = mov['Title'] + \"\\n\" + 'Year: ' + mov['Year'] + \"\\n\"\n poster = mov['Poster']\n return message, poster\n\n def searchTag(self, message):\n chr = ','\n a = message.split(chr)\n msg = str()\n for word in a:\n msg += str(word.rstrip('')) + '%2C'\n msg = msg.strip('%2C')\n msg = msg.replace(' ', '')\n movie_url = imdb_url + '?keywords=' + msg\n movie = requests.get(movie_url).text\n soup = BeautifulSoup(movie, \"html.parser\")\n m = soup.find('div', class_=\"lister-list\")\n r = self.Parser(m)\n return r\n\n def getTags(self, command):\n if command == '/tag':\n tags = requests.get(imdb_url).text\n soup = BeautifulSoup(tags, \"html.parser\")\n m = soup.find('div', class_=\"widget_nested\")\n r = self.Parser(m)\n return r\n\n def Parser(self, m):\n m = str(m)\n k = str(re.findall('> ?\\w+ ?</a>', m))\n k = k.replace('</a>', '')\n k = k.replace('>', '')\n k = k.replace(\"'\", '\\n')\n k = k.replace(',', '')\n k = k.rstrip(']')\n k = k.lstrip('[')\n return k\n\"\"\"\n def PosterID(self, m):\n m = str(m)\n x = str(re.findall('tt\\d+/+', m))\n x = x.replace('/', '')\n x = x.replace(\"'\", '')\n x = x.rstrip(']')\n x = x.lstrip('[')\n return x\n\n def poster(self, m):\n url = 'http://www.omdbapi.com/?i=IMDB&apikey=API'\n url = url.replace('API', api_key)\n l = self.PosterID(m)\n l = l.rstrip(']')\n l = l.lstrip('[')\n l = l.split(',')\n ret_lst = []\n from collections import OrderedDict\n l = list(OrderedDict((element, None) for element in l))\n id = random.randint(1, len(l))\n url = url.replace('IMDB', l[id])\n movie = requests.get(url).json()\n title = movie['Title']\n poster = movie['Poster']\n ret_lst.append(title)\n ret_lst.append(poster)\n ret_lst = list(OrderedDict((element, None) for element in ret_lst))\n return ret_lst\n\"\"\"\ndef main():\n moviesbot = MoviesBot()\n moviesbot.startBot()\n\n\nif __name__ == '__main__':\n main()"
},
{
"alpha_fraction": 0.5604395866394043,
"alphanum_fraction": 0.7252747416496277,
"avg_line_length": 17,
"blob_id": "70ece5562a2271c8f75866d31e2e51339b8be1b6",
"content_id": "b9f6698910cbf71f90551ca163263c77514d5c90",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 91,
"license_type": "no_license",
"max_line_length": 23,
"num_lines": 5,
"path": "/requirements.txt",
"repo_name": "Elizaveta100000/SelectionCinemaBot",
"src_encoding": "UTF-8",
"text": "telegram==0.0.1\nrequests==2.7.0\nbeautifulsoup4==4.6.0\nIMDbPY==6.2\npyTelegramBotAPI==3.5.1\n\n"
}
] | 2
|
ggiesa/Seattle-Housing-Model
|
https://github.com/ggiesa/Seattle-Housing-Model
|
7986ed175e87b43b46c2edb46de5624a2fa13fe1
|
1cc694860d9c82632c8e63bce229d5e8222ce3ec
|
6dac21276233a9bf7d03e41f5178ab1d1a390812
|
refs/heads/master
| 2021-08-11T19:31:58.679325
| 2017-11-14T03:29:54
| 2017-11-14T03:29:54
| 110,629,147
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6937702298164368,
"alphanum_fraction": 0.7048948407173157,
"avg_line_length": 32.551021575927734,
"blob_id": "d381a7159a6f01ad06d8007d5cb90c507a82e9b5",
"content_id": "918ece973d062e615c44e916d8b4b7dc0ce2cc91",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4944,
"license_type": "no_license",
"max_line_length": 139,
"num_lines": 147,
"path": "/data_preprocessing.py",
"repo_name": "ggiesa/Seattle-Housing-Model",
"src_encoding": "UTF-8",
"text": " \nimport pandas as pd\nimport numpy as np\nimport seaborn as sb\nimport matplotlib.pyplot as plot\nimport copy\n\n#%% \n''' Data importing and feature engineering '''\n\n# Load the data into a Pandas dataframe\ndata = pd.read_csv('./Data/kc_house_data.csv')\n\n# Sort according to date\ndata = data.sort_values('date')\n\n# Creating new index, ordered by date\ndata = data.reset_index(drop=True)\n\n# Drop features that won't be used\ncompdata = data.drop(['id', 'date', 'long'], axis = 1) # 'long' is just one value all throughout the dataset, so it's useless in this model\n\n# Checking for null values:\nnulls = sum(data.isnull().sum()) # No missing values!\n\n# Checking for negative values:\nfor column in compdata:\n if np.sum(compdata[column] < 0) > 0:\n print('Negative values exist in %s' %(column))\n# No negative values!\n\n \n#%% \n''' Plotting for an overview of the data: distribution and correlation plots to check for skew and multicollinearity '''\n\n# First, a correlation matrix\ncorr = compdata.corr()\nsb.heatmap(corr, annot=True)\nplot.xticks(rotation = 45)\nplot.yticks(rotation = 0)\n\n#It looks like the dataset is fairly well behaved in terms of multicorrilarity, but it looks like 'sqft_above' and 'sqft_living' \n#are so closely correlated that it's probably best to drop one of them. I'll arbitrarily choose 'sqft_above' to drop.\ncompdata = compdata.drop('sqft_above', axis = 1)\n\n#investigate = ['sqft_lot', 'condition', 'yr_built', 'zipcode', 'long']\n#\n## Plot the features in question vs. price\n#f1, ax1 = plot.subplots(2,3)\n#ax1 = ax1.ravel()\n#\n#for i in range(len(investigate)):\n# ax1[i].scatter(data[investigate[i]], y, s=1, c='k')\n# ax1[i].set_title(investigate[i])\n\n#%%\n''' Engineering some features '''\n\n# Instead of using the actual zipcode as a feature, I'll use the average price of the zipcode from the entire dataset\ntempzip = data['zipcode']\n \n# Making an array with all unique zipcodes:\nzips, inverse = np.unique(tempzip, return_inverse = True)\n\n# Making an array with the mean price per zipcode \nzipmeans = np.ones(len(zips))\nfor i in range(len(zips)):\n tempy = copy.copy(compdata.price)\n zipmask = 1*(tempzip == zips[i])\n tempy *= zipmask\n zipmeans[i] = tempy[tempy!=0].mean()\n\n# Creating an array with the new values\ntempzip = np.ones(len(inverse))\nfor i in range(len(tempzip)):\n tempzip[i] = zipmeans[inverse[i]] \ncompdata.zipcode = tempzip\n\n# Renaming zipcode feature\ncompdata = compdata.rename(columns = {'zipcode':'meanzip'}) \n\n# Make a plot of the new feature\nf2 = plot.figure() \nax2 = f2.add_subplot(111)\nax2.scatter(compdata.meanzip, compdata.price, s=1, c='k')\nax2.axes.set_title('meanzip')\n\n# For now, drop the other poorly correlated features\n#drop = ['sqft_lot', 'condition', 'yr_built', 'long']\n#compdata = compdata.drop(drop, axis=1)\n\n# Make a new correlation heatmap to check on things\ncorr = compdata.corr()\nsb.heatmap(corr, annot = True)\nplot.xticks(rotation = 45)\nplot.yticks(rotation = 0)\n\n#%% \n\n''' Features are selected and ready for the next step of preprocessing. '''\n\n# Features are very different in terms of scale, so time for feature scaling. I'm choosing to do mean-normalization.\n#for column in compdata:\n# compdata[column] = (compdata[column] - compdata[column].min())/(compdata[column].max() - compdata[column].min())\n#\n\n# Making a list of features to label the plot with, and a matrix from compdata for plotting\nfeatures = list(compdata.axes[1])\nplotdata = np.asmatrix(compdata)\n\n# Making the distribution plot\nf3, ax3 = plot.subplots(3,6)\nax3 = ax3.ravel()\n\nfor i in range(len(features)):\n sb.distplot(plotdata[:,i], ax = ax3[i])\n ax3[i].set_title(features[i])\n\n# There is significant right skew in most of the variables, and left skew in a couple, so it's probably worth normalizing them.\nright_normalize = ['price', 'bedrooms', 'bathrooms', 'sqft_living', 'sqft_basement', 'meanzip', 'sqft_living15', 'floors']\nleft_normalize = ['lat', 'yr_built', ]\n\n# log+1 transformation to correct for right skew\nfor feature in right_normalize:\n compdata[feature] = np.log1p(compdata[feature])\n\n# Power transformations to correct for left skew\ncompdata.lat = compdata.lat**7\ncompdata.yr_built = compdata.yr_built**5\n\n# Plot again to visualize transformation\nplotdata = np.asmatrix(compdata)\nf4, ax4 = plot.subplots(3,6)\nax4 = ax4.ravel()\n\nfor i in range(len(features)):\n sb.distplot(plotdata[:,i], ax = ax4[i])\n ax4[i].set_title(features[i])\n# Features look much better.\n\n# Features are very different in terms of scale, so time for feature scaling. I'm choosing to do mean-normalization.\nfor column in compdata.columns: #.drop('price', axis = 1):\n compdata[column] = (compdata[column] - compdata[column].min())/(compdata[column].max() - compdata[column].min())\n#%% \n''' I think the data is ready for a preliminary model. Time to split the data into training and CV sets ''' \n\n# Saving to CSV\ncompdata.to_csv('./Data/data.csv', index = False)\n\n\n\n\n\n\n"
},
{
"alpha_fraction": 0.6471516489982605,
"alphanum_fraction": 0.656335175037384,
"avg_line_length": 35.85714340209961,
"blob_id": "f5d79d521e8b8e9d36a4b3172169113b08b83ef0",
"content_id": "cd541fff4242d12847520cdf6eda2f088dc375fb",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6969,
"license_type": "no_license",
"max_line_length": 124,
"num_lines": 189,
"path": "/model.py",
"repo_name": "ggiesa/Seattle-Housing-Model",
"src_encoding": "UTF-8",
"text": "''' This script impliments an ensemble model '''\n\n# Basics \nimport pandas as pd\nimport sklearn as sk\nimport numpy as np\nfrom sklearn.metrics import r2_score as r2\n\n\n# Machine learning \nfrom sklearn import svm\nfrom sklearn.ensemble import RandomForestRegressor, AdaBoostRegressor\nfrom sklearn.linear_model import BayesianRidge\nfrom sklearn.neural_network import MLPRegressor\nfrom sklearn.model_selection import TimeSeriesSplit\n\n# Plotting \nimport seaborn as sb\nimport matplotlib as matplot\nimport matplotlib.pyplot as plot\n\n\n# Import data\ndata = pd.read_csv('./Data/data.csv')\nx = data.drop('price', axis = 1)\ny = data.price\nx = x.as_matrix()\ny = y.as_matrix()\n\n# Split into simple training and test sets\nXtrain = x[0:18000, :]\nYtrain = y[0:18000]\nXtest = x[18001:len(x), :]\nYtest = y[18001:len(y)]\n\n# Because this is time series data, I use TimeSeriesSplit to obtain indices of training and CV sets (k-fold for time series)\ntscv = TimeSeriesSplit(n_splits = 10)\n\n#%%\n\n# Creating model objects and list that will contain info from each CV fold\nSVR = svm.SVR()\nSVRinfo = []\n\nRFR = RandomForestRegressor(max_depth = 4, random_state=0)\nRFRinfo = []\n\nBR = BayesianRidge()\nBRinfo = []\n\nNN = MLPRegressor()\nNNinfo = []\n\nADA = AdaBoostRegressor()\nADAinfo = []\n\n\n# Training and displaying the R2 and squared error for each iteration of K-fold\niteration = 1\nfor train_index, test_index in tscv.split(Ytrain):\n print('CV Fold %d' %(iteration))\n \n '''SVR'''\n # Train the model\n SVR.fit(Xtrain[train_index, :], Ytrain[train_index])\n \n # Calculate R2 scores for training and CV set\n train_score = SVR.score(Xtrain[train_index], Ytrain[train_index])\n test_score = SVR.score(Xtrain[test_index], Ytrain[test_index])\n \n # Calculate the squared error for training and CV set, save in list\n train_error = (1/len(train_index))*sum((SVR.predict(Xtrain[train_index]) - Ytrain[train_index])**2)\n test_error = (1/len(test_index))*sum((SVR.predict(Xtrain[test_index]) - Ytrain[test_index])**2)\n SVRinfo.append('**SVR** R2 in I%d: Train: %f, Test: %f' %(iteration, train_score, test_score))\n SVRinfo.append('**SVR** Error in I%d: Train: %f, Test: %f' %(iteration, train_error, test_error))\n\n\n\n '''Random Forest Regressor'''\n # Train the model\n RFR.fit(Xtrain[train_index, :], Ytrain[train_index])\n \n # Calculate R2 scores for training and CV set\n train_score = RFR.score(Xtrain[train_index], Ytrain[train_index])\n test_score = RFR.score(Xtrain[test_index], Ytrain[test_index])\n \n # Calculate the squared error for training and CV set, save in list\n train_error = (1/len(train_index))*sum((RFR.predict(Xtrain[train_index]) - Ytrain[train_index])**2)\n test_error = (1/len(test_index))*sum((RFR.predict(Xtrain[test_index]) - Ytrain[test_index])**2)\n RFRinfo.append('**RFR** R2 in I%d: Train: %f, Test: %f' %(iteration, train_score, test_score))\n RFRinfo.append('**RFR** Error in I%d: Train: %f, Test: %f' %(iteration, train_error, test_error))\n \n \n \n '''Bayesian Ridge'''\n # Train the model\n BR.fit(Xtrain[train_index, :], Ytrain[train_index])\n \n # Calculate R2 scores for training and CV set\n train_score = BR.score(Xtrain[train_index], Ytrain[train_index])\n test_score = BR.score(Xtrain[test_index], Ytrain[test_index])\n \n # Calculate the squared error for training and CV set, save in list\n train_error = (1/len(train_index))*sum((BR.predict(Xtrain[train_index]) - Ytrain[train_index])**2)\n test_error = (1/len(test_index))*sum((BR.predict(Xtrain[test_index]) - Ytrain[test_index])**2)\n BRinfo.append('**BR** R2 in I%d: Train: %f, Test: %f' %(iteration, train_score, test_score))\n BRinfo.append('**BR** Error in I%d: Train: %f, Test: %f' %(iteration, train_error, test_error))\n \n \n \n '''Neural Network Regressor'''\n # Train the model\n NN.fit(Xtrain[train_index, :], Ytrain[train_index])\n \n # Calculate R2 scores for training and CV set\n train_score = NN.score(Xtrain[train_index], Ytrain[train_index])\n test_score = NN.score(Xtrain[test_index], Ytrain[test_index])\n \n # Calculate the squared error for training and CV set, save in list\n train_error = (1/len(train_index))*sum((NN.predict(Xtrain[train_index]) - Ytrain[train_index])**2)\n test_error = (1/len(test_index))*sum((NN.predict(Xtrain[test_index]) - Ytrain[test_index])**2)\n NNinfo.append('**NN** R2 in I%d: Train: %f, Test: %f' %(iteration, train_score, test_score))\n NNinfo.append('**NN** Error in I%d: Train: %f, Test: %f' %(iteration, train_error, test_error))\n \n \n \n '''AdaBoost Regressor'''\n # Train the model\n ADA.fit(Xtrain[train_index, :], Ytrain[train_index])\n \n # Calculate R2 scores for training and CV set\n train_score = ADA.score(Xtrain[train_index], Ytrain[train_index])\n test_score = ADA.score(Xtrain[test_index], Ytrain[test_index])\n \n # Calculate the squared error for training and CV set, save in list\n train_error = (1/len(train_index))*sum((ADA.predict(Xtrain[train_index]) - Ytrain[train_index])**2)\n test_error = (1/len(test_index))*sum((ADA.predict(Xtrain[test_index]) - Ytrain[test_index])**2)\n ADAinfo.append('**ADA** R2 in I%d: Train: %f, Test: %f' %(iteration, train_score, test_score))\n ADAinfo.append('**ADA** Error in I%d: Train: %f, Test: %f' %(iteration, train_error, test_error))\n \n \n \n iteration += 1\n\n# Printing training info\nprint(*SVRinfo, sep='\\n')\nprint('\\n**********************')\nprint(*RFRinfo, sep='\\n')\nprint('\\n**********************')\nprint(*BRinfo, sep='\\n')\nprint('\\n**********************')\nprint(*NNinfo, sep='\\n')\nprint('**********************\\n')\nprint(*ADAinfo, sep='\\n')\nprint('**********************\\n')\n\n\n# Printing score on test set\nprint('SVR test score: %f' %(SVR.score(Xtest, Ytest)))\nprint('RFR test score: %f' %(RFR.score(Xtest, Ytest)))\nprint('BR test score: %f' %(BR.score(Xtest, Ytest)))\nprint('NN test score: %f' %(NN.score(Xtest, Ytest)))\nprint('ADA test score: %f' %(ADA.score(Xtest, Ytest)))\n\n\n#%% \n'''Simple Stacking: Averaging results'''\n\n\n# Calcuating predictions with test set\nSVRstack = SVR.predict(Xtest)\nRFRstack = RFR.predict(Xtest)\nBRstack = BR.predict(Xtest)\nNNstack = NN.predict(Xtest)\nADAstack = ADA.predict(Xtest)\n\n# Calculating mean of predictions\nnumber_of_estimators = 5\nmeanPrediction = (SVRstack + RFRstack + BRstack + NNstack + ADAstack)/number_of_estimators\n\nprint('Simple Average Ensemble Score: %f' %(r2(meanPrediction, Ytest)))\n\n# Saving predictions to CSV\nSVRstack.tofile('./Data/SVR_prediction.csv', sep = ',', format = '%f')\nRFRstack.tofile('./Data/RFR_prediction.csv', sep = ',', format = '%f')\nBRstack.tofile('./Data/BR_prediction.csv', sep = ',', format = '%f')\nNNstack.tofile('./Data/NN_prediction.csv', sep = ',', format = '%f')\nADAstack.tofile('./Data/ADA_prediction.csv', sep = ',', format = '%f')\nmeanPrediction.tofile('./Data/mean_prediction.csv', sep = ',', format = '%f')\n\n\n\n"
},
{
"alpha_fraction": 0.7895299196243286,
"alphanum_fraction": 0.8044871687889099,
"avg_line_length": 232.5,
"blob_id": "138874e8826a17cdadfcb3b5b07533a8e747d833",
"content_id": "be546452ede374e4b13c98196ff12d6c4a6cde90",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 936,
"license_type": "no_license",
"max_line_length": 676,
"num_lines": 4,
"path": "/README.md",
"repo_name": "ggiesa/Seattle-Housing-Model",
"src_encoding": "UTF-8",
"text": "# Seattle-Housing-Model\nThis is a relatively simple machine learning project, with the goal of prediciting Seattle housing prices from a 2014-2015 dataset found [here](https://www.kaggle.com/harlfoxem/housesalesprediction/data \"King County Housing Data\").\n\nI've implemented a simple ensemble regression technique using SVM, Bayesian ridge, random forest, adaboost, and neural network regressors from Scikit-learn. The project is on ice at the moment, after achieving a moderate R2 score of ~80. In terms of improving the model, there are many low hanging fruit, but from my preliminary analysis I've come to suspect that that the dataset lacks the complexity necessary to build a truly useful predictive model. For example, the model achieves a percent error of around 3%, but an absolute percent error of around 20%, indicating to me that there are trends in the target variable that cannot be explained by the rest of the features. \n\n"
}
] | 3
|
ValidPoint/User-signup
|
https://github.com/ValidPoint/User-signup
|
a204dd6afd5b3468632a17fba1acea808a9874b5
|
01ebf3cbdeb82df9b620dc7f415bedb4cac562bf
|
30fff5efe8f417fadad6d615d91dbc08cad2beb5
|
refs/heads/master
| 2020-05-07T21:18:26.579992
| 2019-04-12T00:29:14
| 2019-04-12T00:29:14
| 180,899,671
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6102856993675232,
"alphanum_fraction": 0.6154285669326782,
"avg_line_length": 26.265625,
"blob_id": "d66427b5c3f8fa159882945dcf3c93a8b7032c08",
"content_id": "8c965248afa9f23a833f16c7ef137449c7d21790",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1750,
"license_type": "no_license",
"max_line_length": 194,
"num_lines": 64,
"path": "/main.py",
"repo_name": "ValidPoint/User-signup",
"src_encoding": "UTF-8",
"text": "from flask import Flask, request, redirect, render_template\nimport cgi\nimport os\n\n\n\napp = Flask(__name__)\napp.config['DEBUG'] = True\n\n\n@app.route(\"/\")\ndef index():\n return render_template('index.html')\n\n@app.route(\"/\", methods=['POST'])\ndef user_login():\n\n username = request.form['username']\n password = request.form['password']\n pwd = request.form['pwd']\n\n username_error = ''\n password_error = ''\n verification_error = ''\n\n#def username():\n if len(username) == 0:\n username_error = 'Nothing has been put in'\n username = ''\n elif ' ' in username:\n username_error = 'Can not have a space'\n username = ''\n elif len(username) < 3 or len(username) > 20:\n username_error = 'Incorrect number of characters'\n username = ''\n\n#def password():\n if len(password) == 0:\n password_error = 'Nothing has been put in'\n password = ''\n elif ' ' in password:\n password_error = 'Can not have a space'\n password = ''\n elif len(password) < 3 or len(password) > 20:\n password_error = 'Incorrect number of characters'\n password = ''\n\n#def pwd():\n if pwd != password:\n verification_error = 'Passwords do not match'\n pwd = ''\n elif len(pwd) == 0:\n verification_error = 'Nothing has been put in'\n pwd = ''\n\n#def welcome():\n if not username_error and not password_error and not verification_error:\n username = request.form['username']\n return render_template('welcome.html', name=username)\n else:\n return render_template('index.html', username_error=username_error, password_error=password_error, verification_error=verification_error, username=username, password=password, pwd=pwd)\n\n\napp.run()\n \n"
}
] | 1
|
Elwena/nauka_pythona
|
https://github.com/Elwena/nauka_pythona
|
ce009b8c650c8d604398820a8fd8cf44ce0cbbe8
|
c43bc5f342f7748be73948adb92ee364f59c6153
|
3301958378217200b9daf3691a77a951283c09f1
|
refs/heads/master
| 2023-01-06T18:17:56.651492
| 2020-11-12T14:13:36
| 2020-11-12T14:13:36
| 311,015,336
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5723077058792114,
"alphanum_fraction": 0.6153846383094788,
"avg_line_length": 18.117647171020508,
"blob_id": "f08199245fe02871565e20ee1c6772ce604a4e72",
"content_id": "6c80bd0572d223cfd658fe821c81e8ed277f1608",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 325,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 17,
"path": "/prog8.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "samochody = ['syrena', 'polonez']\n# lotto = [59, 89, 2, 3, 4]\n\nprint(samochody[0])\nprint(samochody[1])\n #print (samochody[2])\n\nprint(\"===petla 1===\")\nfor s in samochody:\n print(s)\n\nfor idx in [0,1]:\n print(samochody[idx])\n\nprint(\"== petla2 po indexie ===\")\nfor idx in range( len(samochody) ):\n print(samochody[idx])\n"
},
{
"alpha_fraction": 0.5514771938323975,
"alphanum_fraction": 0.5675917863845825,
"avg_line_length": 23.282608032226562,
"blob_id": "f6975edf2613890ae016e98fe451d962b82b0e1a",
"content_id": "a2202877fb3494207962d65741e87b07f61d8b2d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1117,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 46,
"path": "/prog13.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "# # klucz wartosc\n# samolot = {'name': 'boeing',\n# 'przebieg': 1000.50,\n# 'type': 'pasazerki' }\n#\n# # lista_dostep_po_kluczy = {'PESEL1': 'Wotjek', 'PESEL2': 'Kat'}\n#\n# print(samolot['name'])\n# print(samolot['przebieg'])\n# print(samolot['type'])\n#\n# samolot['silnik'] = 'odrzutowy'\n# # co stanie\n# # print(samolot['xyz'])\n# # print(samolot.get('xyz'))\n#\n# print(\"==== petla po kluczu - key ===\")\n# for klucz in samolot:\n# print(\"{0}: {1}\".format(klucz, samolot[klucz]))\n#\n# print(\"=== petla klucz/wartosc - key/value ===\")\n# for key, value in samolot.items():\n# print(\"{0} {1}\".format(key, value))\n\n###\n # klucz wartosc\nzwierze = {'gatunek': 'kot',\n 'wielkosc': 50,\n 'kolor': 'szary',\n 'rasa': 'syberyjski' }\n\nprint(zwierze['gatunek'])\nprint(zwierze['wielkosc'])\nprint(zwierze['kolor'])\nprint(zwierze['rasa'])\n\n\nprint(\"==== petla po kluczu - key ===\")\nfor klucz in zwierze:\n print(\"{0}: {1}\".format(klucz, zwierze[klucz]))\n\nprint(\"=== petla klucz/wartosc - key/value ===\")\nfor key, value in zwierze.items():\n print(\"{0} {1}\".format(key, value))\n\n###\n"
},
{
"alpha_fraction": 0.44519391655921936,
"alphanum_fraction": 0.47217538952827454,
"avg_line_length": 21.769229888916016,
"blob_id": "fbcb3d4feac49d33930a2688c334ffb9f7717361",
"content_id": "e5f1906e91d729946b278344f9fec6b96400854b",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 593,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 26,
"path": "/prog14.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "\n# produkty = {'SS12': 'sukienka_trojka',\n # 'P1222':'spodnie krata',\n\n# 'P12': 'spodnia'}\n#\n# igla = 'P12'\n#\n# if igla in produkty:\n# print('istnieje!')\n# print(produkty['P12'])\n\nprodukty = {\n 'SS12': {'nazwa': 'sukienka_trojka', 'rozmiary': ['s','l','xl']},\n 'P12': {'nazwa': 'spodnia', 'rozmiary': ['s', 'xl']}\n }\n\nfor id in produkty:\n p = produkty[id]\n rozmiary = p['rozmiary']\n print(p)\n print(p['rozmiary'])\n\n # for id in produkty:\n # p = produkty[id]\n # print(p)\n # print(p['nazwa'])\n"
},
{
"alpha_fraction": 0.49568966031074524,
"alphanum_fraction": 0.5517241358757019,
"avg_line_length": 22.200000762939453,
"blob_id": "30dee054042aec6a9ded92443d7c1399cb1aa7d5",
"content_id": "8eea0faf311b7cbf123e237781f873bade327b0f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 232,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 10,
"path": "/prog6.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "imie = 'Ala'\nile = 2 #2 5\nzwierze = 'kot'\n\nif ile == 1:\n print('{0} ma {1}a'.format(imie, zwierze))\nelif ile == 2:\n print('{0} ma {1} {2}y'.format(imie, ile, zwierze))\nelse:\n print('{0} ma {1} {2}ow'.format(imie, zwierze))\n"
},
{
"alpha_fraction": 0.625,
"alphanum_fraction": 0.6416666507720947,
"avg_line_length": 20.81818199157715,
"blob_id": "9d39e130e1e4bbeb536cb6abd5b6175cc7f75779",
"content_id": "ba6c7e7dd8ee24d1f85419599b49a5be1ba746e8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 240,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 11,
"path": "/prog1.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "marka = 'Peugot'\nilosc_drzwi = 5\npojemnosc = 1.3\n\nmarka_up = marka.upper()\n\nmarka_up = marka.lower()\n\nprint(\"Samochod \" + marka + \" ma \" + str (ilosc_drzwi) + \" drzwi\")\nprint(marka_up)\nprint(\"Pojemnosc po zmianach: \" + str (pojemnosc * 2))\n"
},
{
"alpha_fraction": 0.6388888955116272,
"alphanum_fraction": 0.6538461446762085,
"avg_line_length": 22.399999618530273,
"blob_id": "59dda1121c28fe7dd2d7f90e14aa139788cea51e",
"content_id": "7d93cd56060da6e9f92bc6bdc2ca20bfb6610f04",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 479,
"license_type": "no_license",
"max_line_length": 50,
"num_lines": 20,
"path": "/prog0.py",
"repo_name": "Elwena/nauka_pythona",
"src_encoding": "UTF-8",
"text": "print ('Hello Word')\nimie = 'Wioletta'\nnazwa = 'Terelak'\nilosc_ksiazek = 10\nsrednia = 4.5 # float\n\nprint('Hello World' + imie + ' ' +nazwa)\nprint('srednia: ' +str(srednia))\nprint('ilosc ' + str(ilosc_ksiazek))\n\n# na dole jest moj program\n\ngatunek_zwierzęcia = 'Kot'\nilosc_łap = 4\nilosc_posiłków = 4.5\n\nprint ('Cześć ' + gatunek_zwierzęcia+ 'ku')\ninput('Podaj imie kota:')\nprint('Kot ma: ' +str(ilosc_łap) + ' łapy')\nprint('zjada ' + str(ilosc_posiłków) + ' posilki')\n"
}
] | 6
|
bbangasser/Chess_Club
|
https://github.com/bbangasser/Chess_Club
|
127d2a0fa473b4f90b794c8bc14ca6e55920af76
|
db69c9bde065c532d4d1ac83884ec5371c0ff563
|
d7134e2a5d5573f1dadb45179b35da0dd1217b19
|
refs/heads/master
| 2022-07-09T09:42:32.370471
| 2020-05-14T02:09:37
| 2020-05-14T02:09:37
| 258,264,464
| 0
| 2
| null | 2020-04-23T16:28:16
| 2020-05-08T00:36:25
| 2020-05-14T02:09:38
|
Python
|
[
{
"alpha_fraction": 0.5950142741203308,
"alphanum_fraction": 0.6207601428031921,
"avg_line_length": 36.841270446777344,
"blob_id": "515e71c7fa5ecad9e1e08e25e3683fbdd929ff95",
"content_id": "6436634d1b135bec463241c929257d02838f6b25",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2447,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 63,
"path": "/NewPlayerScreen.py",
"repo_name": "bbangasser/Chess_Club",
"src_encoding": "UTF-8",
"text": "# Programmer: Brock Bangasser\r\n# Program: Final\r\n# Date: 4/27/20\r\n\r\n\r\nimport tkinter as tk\r\nfrom tkinter import ttk\r\n\r\n\r\n# from builtins import True\r\n\r\nclass PlayerFrame(ttk.Frame):\r\n def __init__(self, parent):\r\n ttk.Frame.__init__(self, parent, padding=\"10 10 10 10\")\r\n self.pack(fill=tk.BOTH, expand=True)\r\n\r\n # Define string variable for the first entry field\r\n self.playerName = tk.StringVar()\r\n self.firstName = tk.StringVar()\r\n self.lastName = tk.StringVar()\r\n self.address = tk.StringVar()\r\n self.phone = tk.StringVar()\r\n self.rating = tk.StringVar()\r\n\r\n # Create a label, entry field, and a button\r\n ttk.Label(self, text=\"First Name\").grid(column=0, row=0, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.firstName).grid(column=1, row=0)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=0)\r\n\r\n ttk.Label(self, text='Last Name').grid(column=0, row=1, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.lastName).grid(column=1, row=1)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=1)\r\n\r\n ttk.Label(self, text='Address').grid(column=0, row=2, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.address).grid(column=1, row=2)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=2)\r\n\r\n ttk.Label(self, text='Phone Number').grid(column=0, row=3, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.phone).grid(column=1, row=3)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=3)\r\n\r\n ttk.Label(self, text='Rating').grid(column=0, row=4, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.rating).grid(column=1, row=4)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=4)\r\n\r\n ttk.Button(self, text='Exit', command=self.destroy).grid(column=1, row=5)\r\n\r\n # Add padding to all child components\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=8, pady=6)\r\n\r\n # Define the event listener for the Clear button\r\n def clear(self):\r\n print(\"Player Name\", self.firstName.get())\r\n self.playerName.set(\"\")\r\n\r\n\r\nif __name__ == \"__main__\":\r\n root = tk.Tk()\r\n root.title(\"Add Player\")\r\n root.geometry(\"400x200\")\r\n PlayerFrame(root)\r\n root.mainloop()\r\n"
},
{
"alpha_fraction": 0.5516921877861023,
"alphanum_fraction": 0.5702364444732666,
"avg_line_length": 35.51304244995117,
"blob_id": "cd2aa7e6ac897d4495b2e921101404a8942c6fc5",
"content_id": "1a6cf2226eb81699ea4124746f4b02ee20a5ba67",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 8628,
"license_type": "no_license",
"max_line_length": 119,
"num_lines": 230,
"path": "/ChessFinal(4.30.20).py",
"repo_name": "bbangasser/Chess_Club",
"src_encoding": "UTF-8",
"text": "import tkinter as tk\r\nimport math\r\nimport sqlite3\r\n\r\nLARGE_FONT = (\"Verdana\", 12)\r\n\r\n\r\nclass ChessProgram(tk.Tk):\r\n def __init__(self):\r\n tk.Tk.__init__(self)\r\n self._frame = None\r\n self.switch_frame(StartPage)\r\n\r\n def switch_frame(self, frame_class):\r\n new_frame = frame_class(self)\r\n if self._frame is not None:\r\n self._frame.destroy()\r\n self._frame = new_frame\r\n self._frame.pack()\r\n\r\n # exit frame\r\n def delete_frame(self):\r\n self._frame.destroy()\r\n app.destroy()\r\n\r\n\r\n# Main Menu\r\nclass StartPage(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Chess Club Program\", font=LARGE_FONT).pack(side=\"top\", fill=\"x\", pady=10)\r\n\r\n tk.Button(self, text=\"Record a Match\",\r\n command=lambda: master.switch_frame(RecordMatch)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Add a Player\",\r\n command=lambda: master.switch_frame(AddPlayer)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Delete Player\",\r\n command=lambda: master.switch_frame(DeletePlayer)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"LeaderBoard\",\r\n command=lambda: master.switch_frame(LeaderBoard)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Exit\",\r\n command=lambda: master.delete_frame()).pack(fill=\"both\", pady=3)\r\n\r\n\r\n# Recording a match/Determine player rating\r\nclass RecordMatch(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n\r\n # defining variables\r\n self.player1ID = tk.StringVar()\r\n self.player2ID = tk.StringVar()\r\n self.player1winner = tk.IntVar()\r\n self.player2winner = tk.IntVar()\r\n\r\n tk.Label(self, text=\"Record the Match\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # Create text entries for players\r\n tk.Label(self, text=\"Player One ID\").grid(column=0, row=1, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player1ID).grid(column=1, row=1)\r\n tk.Label(self, text=\"Player Two ID\").grid(column=0, row=2, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player2ID).grid(column=1, row=2)\r\n tk.Label(self, text=\"Winner?\").grid(column=0, row=3, sticky=tk.E)\r\n tk.Checkbutton(self, text=\"Player 1\", variable=self.player1winner).grid(column=1, row=3, sticky=tk.W)\r\n tk.Checkbutton(self, text=\"Player 2\", variable=self.player2winner).grid(column=1, row=3, sticky=tk.E)\r\n\r\n # Create a enterButton\r\n tk.Button(self, text=\"Enter\", command=self.enter).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=4)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Enters the values into the database\r\n def enter(self):\r\n\r\n if self.player1winner.get() == 1:\r\n print(\"Player\", self.player1ID.get(), \"won!\")\r\n print(\"The new ratings are: \", RecordMatch.CalculateNewRating(1000, 1000, 50, 1))\r\n else:\r\n print(\"Player\", self.player2ID.get(), \"won!\")\r\n\r\n # Function to calculate Elo rating\r\n # K is a constant.\r\n # d determines whether\r\n # Player A wins or Player B.\r\n def CalculateNewRating(Ra, Rb, K, d):\r\n\r\n # To calculate the Winning\r\n # Probability of Player B\r\n Pb = 1.0 * 1.0 / (1 + 1.0 * math.pow(10, 1.0 * (Ra - Rb) / 400))\r\n\r\n # To calculate the Winning\r\n # Probability of Player A\r\n Pa = 1.0 * 1.0 / (1 + 1.0 * math.pow(10, 1.0 * (Rb - Ra) / 400))\r\n\r\n # Case -1 When Player A wins\r\n # Updating the Elo Ratings\r\n if d == 1:\r\n Ra = Ra + K * (1 - Pa)\r\n Rb = Rb + K * (0 - Pb)\r\n\r\n # Case -2 When Player B wins\r\n # Updating the Elo Ratings\r\n else:\r\n Ra = Ra + K * (0 - Pa)\r\n Rb = Rb + K * (1 - Pb)\r\n\r\n # print(\"Updated Ratings:-\")\r\n # print(\"Ra =\", round(Ra, 6), \" Rb =\", round(Rb, 6))\r\n\r\n return round(Ra, 6)\r\n\r\n\r\n# Add player\r\nclass AddPlayer(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n\r\n self.firstName = tk.StringVar()\r\n self.lastName = tk.StringVar()\r\n self.address = tk.StringVar()\r\n self.phone = tk.StringVar()\r\n self.rating = tk.StringVar()\r\n\r\n # Create label, entry field for new player\r\n tk.Label(self, text=\"First Name\").grid(column=0, row=0, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.firstName).grid(column=1, row=0)\r\n\r\n tk.Label(self, text='Last Name').grid(column=0, row=1, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.lastName).grid(column=1, row=1)\r\n\r\n tk.Label(self, text='Address').grid(column=0, row=2, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.address).grid(column=1, row=2)\r\n\r\n tk.Label(self, text='Phone Number').grid(column=0, row=3, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.phone).grid(column=1, row=3)\r\n\r\n tk.Label(self, text='Rating').grid(column=0, row=4, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.rating).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=1, row=5, sticky=tk.W)\r\n\r\n # Create Enter Button\r\n tk.Button(self, text=\"Enter\", command=self.appendPlayer).grid(column=1, row=5, sticky=tk.E)\r\n\r\n # configure grid\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n def appendPlayer(self):\r\n # Get player's name and create table\r\n c.execute(\"\"\"CREATE TABLE IF NOT EXISTS club_members (playerID INTEGER, firstName TEXT, lastName TEXT, \r\n address TEXT, phone TEXT, rating TEXT); \"\"\")\r\n\r\n first_new = self.firstName.get()\r\n last_new = self.lastName.get()\r\n address_new = self.address.get()\r\n phone_new = self.phone.get()\r\n rating_new = self.rating.get()\r\n c.execute(\"SELECT MAX(playerID) FROM club_members;\")\r\n maxPlayerID = c.fetchone()\r\n print(maxPlayerID)\r\n print(\"why\")\r\n maxPlayerID = + 1\r\n print(maxPlayerID)\r\n\r\n print(first_new, last_new)\r\n sql = 'INSERT INTO club_members (playerID, firstName, lastName, address, phone, rating) VALUES (?, ?, ?, ?, ' \\\r\n ' ?, ?) '\r\n\r\n c.execute(sql, (maxPlayerID, first_new, last_new, address_new, phone_new, rating_new))\r\n conn.commit()\r\n print(first_new)\r\n\r\n\r\n# Delete player\r\nclass DeletePlayer(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Delete Player\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # define variable\r\n self.deletedPlayerID = tk.StringVar()\r\n\r\n # Create a Label and Text Entry for player ID\r\n tk.Label(self, text=\"Player's ID\").grid(column=0, row=1, sticky=tk.W, columnspan=1)\r\n tk.Entry(self, width=25, textvariable=self.deletedPlayerID).grid(column=1, row=1)\r\n\r\n # Create a DeleteButton\r\n tk.Button(self, text=\"Enter\", command=self.deleted).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=4)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Deletes player from database\r\n def deleted(self):\r\n print(self.deletedPlayerID.get(), \"was deleted!\")\r\n self.deletedPlayerID.set(\"\")\r\n\r\n\r\n# LeaderBoard\r\nclass LeaderBoard(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"LeaderBoard\").pack(side=\"top\", fill=\"x\", pady=10)\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).pack()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n conn = sqlite3.connect(\"club_members.db\")\r\n c = conn.cursor()\r\n\r\n app = ChessProgram()\r\n app.title(\"Chess Program\")\r\n app.geometry('400x200')\r\n app.mainloop()\r\n\r\n c.close()\r\n conn.close()\r\n"
},
{
"alpha_fraction": 0.5824483633041382,
"alphanum_fraction": 0.599262535572052,
"avg_line_length": 34.462364196777344,
"blob_id": "749d34ac39b119c727291c6ce788bd9becf93f72",
"content_id": "74f6710df2857daa1a4740074ceff6d066a0c416",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6780,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 186,
"path": "/TESTING.py",
"repo_name": "bbangasser/Chess_Club",
"src_encoding": "UTF-8",
"text": "import tkinter as tk\r\nimport tkinter.ttk as ttk\r\nimport sqlite3\r\n\r\nLARGE_FONT = (\"Verdana\", 12)\r\n\r\n\r\nclass ChessProgram(tk.Tk):\r\n def __init__(self):\r\n tk.Tk.__init__(self)\r\n self._frame = None\r\n self.switch_frame(StartPage)\r\n\r\n def switch_frame(self, frame_class):\r\n new_frame = frame_class(self)\r\n if self._frame is not None:\r\n self._frame.destroy()\r\n self._frame = new_frame\r\n self._frame.pack()\r\n\r\n # exit frame\r\n def delete_frame(self):\r\n self._frame.destroy()\r\n app.destroy()\r\n\r\n\r\n# Main Menu\r\nclass StartPage(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Chess Club Program\", font=LARGE_FONT).pack(side=\"top\", fill=\"x\", pady=10)\r\n\r\n tk.Button(self, text=\"Record a Match\",\r\n command=lambda: master.switch_frame(PageOne)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Add a Player\",\r\n command=lambda: master.switch_frame(PageTwo)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Delete Player\",\r\n command=lambda: master.switch_frame(PageThree)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"LeaderBoard\",\r\n command=lambda: master.switch_frame(PageFour)).pack(fill=\"both\", pady=3)\r\n tk.Button(self, text=\"Exit\",\r\n command=lambda: master.delete_frame()).pack(fill=\"both\", pady=3)\r\n\r\n\r\n# Recording a match\r\nclass PageOne(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n self.create_table()\r\n\r\n # defining variables\r\n self.player1ID = tk.StringVar()\r\n self.player2ID = tk.StringVar()\r\n\r\n tk.Label(self, text=\"Record the Match\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # Create text entries for players\r\n tk.Label(self, text=\"Player One ID\").grid(column=0, row=1, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player1ID).grid(column=1, row=1)\r\n\r\n tk.Label(self, text=\"Player Two ID\").grid(column=0, row=2, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player2ID).grid(column=1, row=2)\r\n\r\n # Create a enterButton\r\n tk.Button(self, text=\"Enter\", command=self.enter).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=4)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Enters the values into the database\r\n def enter(self):\r\n print(self.player1ID.get(), \" was entered!\")\r\n print(self.player2ID.get(), \" was entered!\")\r\n\r\n\r\n# Add player\r\nclass PageTwo(ttk.Frame):\r\n def __init__(self, parent):\r\n ttk.Frame.__init__(self, parent, padding=\"10 10 10 10\")\r\n self.pack(fill=tk.BOTH, expand=True)\r\n\r\n # Define string variable for the first entry field\r\n self.playerName = tk.StringVar()\r\n self.firstName = tk.StringVar()\r\n self.lastName = tk.StringVar()\r\n self.address = tk.StringVar()\r\n self.phone = tk.StringVar()\r\n self.rating = tk.StringVar()\r\n\r\n # Create a label, entry field, and a button\r\n ttk.Label(self, text=\"First Name\").grid(column=0, row=0, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.firstName).grid(column=1, row=0)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=0)\r\n\r\n ttk.Label(self, text='Last Name').grid(column=0, row=1, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.lastName).grid(column=1, row=1)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=1)\r\n\r\n ttk.Label(self, text='Address').grid(column=0, row=2, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.address).grid(column=1, row=2)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=2)\r\n\r\n ttk.Label(self, text='Phone Number').grid(column=0, row=3, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.phone).grid(column=1, row=3)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=3)\r\n\r\n ttk.Label(self, text='Rating').grid(column=0, row=4, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.rating).grid(column=1, row=4)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row=4)\r\n\r\n ttk.Button(self, text='Exit', command=self.destroy).grid(column=1, row=5)\r\n\r\n # Add padding to all child components\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=8, pady=6)\r\n\r\n # Define the event listener for the Clear button\r\n def clear(self):\r\n print(\"Player Name\", self.firstName.get())\r\n self.playerName.set(\"\")\r\n\r\n\r\n\r\n\r\n\r\n tk.Label(self, text=\"Add Player\").pack(side=\"top\", fill=\"x\", pady=10)\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).pack()\r\n\r\n\r\n\r\n\r\n\r\n\r\n# Delete player\r\nclass PageThree(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Delete Player\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # define variable\r\n self.deletedPlayerID = tk.StringVar()\r\n\r\n # Create a Label and Text Entry for player ID\r\n tk.Label(self, text=\"Player's ID\").grid(column=0, row=1, sticky=tk.W, columnspan=1)\r\n tk.Entry(self, width=25, textvariable=self.deletedPlayerID).grid(column=1, row=1)\r\n\r\n # Create a DeleteButton\r\n tk.Button(self, text=\"Enter\", command=self.deleted).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=4)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Deletes player from database\r\n def deleted(self):\r\n print(self.deletedPlayerID.get(), \"was deleted!\")\r\n self.deletedPlayerID.set(\"\")\r\n\r\n\r\n# LeaderBoard\r\nclass PageFour(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"LeaderBoard\").pack(side=\"top\", fill=\"x\", pady=10)\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).pack()\r\n\r\n\r\nif __name__ == \"__main__\":\r\n conn = sqlite3.connect(\"chess_club.db\")\r\n c = conn.cursor()\r\n app = ChessProgram()\r\n app.title(\"Chess Program\")\r\n app.geometry('400x200')\r\n app.mainloop()\r\n\r\n c.close()\r\n conn.close()"
},
{
"alpha_fraction": 0.5611928701400757,
"alphanum_fraction": 0.5836560726165771,
"avg_line_length": 40.36065673828125,
"blob_id": "a8990867771c8ee80af27b4b7ff495bec2ba6d2d",
"content_id": "db21c8c4d558822f60ab76a089b837964c9b99d1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2582,
"license_type": "no_license",
"max_line_length": 87,
"num_lines": 61,
"path": "/tkCustomer.py",
"repo_name": "bbangasser/Chess_Club",
"src_encoding": "UTF-8",
"text": "#Programmer: Brock Bangasser\r\n#Program:\r\n#Date: \r\n\r\nimport tkinter as tk\r\nfrom tkinter import ttk\r\n#from builtins import True\r\n\r\nclass CustomerFrame(ttk.Frame):\r\n def __init__(self, parent):\r\n ttk.Frame.__init__(self, parent, padding=\"10 10 10 10\")\r\n self.pack(fill=tk.BOTH, expand=True)\r\n \r\n #Define string variable for the first entry field\r\n self.customerName = tk.StringVar()\r\n self.street = tk.StringVar()\r\n self.city = tk.StringVar()\r\n self.state = tk.StringVar()\r\n self.phone = tk.StringVar()\r\n \r\n \r\n \r\n #Create a label, entry field, and a button\r\n ttk.Label(self, text=\"Customer Name\").grid(column=0, row=0, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.customerName).grid(column=1, row=0)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row = 0)\r\n \r\n ttk.Label(self, text = 'Street').grid(column=0, row=1, sticky=tk.E)\r\n ttk.Entry(self, width=25, textvariable=self.street).grid(column=1, row=1)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row = 1)\r\n \r\n ttk.Label(self, text = 'City').grid(column=0, row = 2,sticky=tk.E)\r\n ttk.Entry(self, width = 25, textvariable=self.city).grid(column=1,row=2)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row = 2)\r\n \r\n ttk.Label(self, text = 'State').grid(column=0, row = 3,sticky=tk.E)\r\n ttk.Entry(self, width = 25, textvariable=self.state).grid(column=1,row=3)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row = 3)\r\n \r\n ttk.Label(self, text = 'Phone').grid(column=0, row = 4,sticky=tk.E)\r\n ttk.Entry(self, width = 25, textvariable=self.phone).grid(column=1,row=4)\r\n ttk.Button(self, text=\"Clear\", command=self.clear).grid(column=2, row = 4)\r\n \r\n ttk.Button(self, text='Exit', command = self.destroy).grid(column=1, row = 5)\r\n \r\n #Add padding to all child components\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n \r\n #Define the event listener for the Clear button\r\n def clear(self):\r\n print(\"Customer Name\", self.customerName.get())\r\n self.customerName.set(\"\")\r\n \r\nif __name__ == \"__main__\":\r\n print(\"This has been edited by Stephen Kasahara\")\r\n root = tk.Tk()\r\n root.title(\"Customer\")\r\n root.geometry(\"400x200\")\r\n CustomerFrame(root)\r\n root.mainloop()"
},
{
"alpha_fraction": 0.5243831276893616,
"alphanum_fraction": 0.5430347919464111,
"avg_line_length": 36.12592697143555,
"blob_id": "702e838b9a32e83a67079592de2eebc1d08f00df",
"content_id": "c5b8a4b0334b2b78a0d054700b2c328b8a9b8a3d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 15441,
"license_type": "no_license",
"max_line_length": 119,
"num_lines": 405,
"path": "/MainCodeV2.py",
"repo_name": "bbangasser/Chess_Club",
"src_encoding": "UTF-8",
"text": "\r\nimport tkinter as tk\r\nimport math\r\nimport sqlite3\r\n\r\nLARGE_FONT = (\"Verdana\", 15)\r\nBOLD_FONT = (\"Verdana\", 7, \"bold underline\")\r\n\r\n\r\nclass ChessProgram(tk.Tk):\r\n def __init__(self):\r\n tk.Tk.__init__(self)\r\n self._frame = None\r\n self.switch_frame(StartPage)\r\n\r\n def switch_frame(self, frame_class):\r\n new_frame = frame_class(self)\r\n if self._frame is not None:\r\n self._frame.destroy()\r\n self._frame = new_frame\r\n self._frame.pack()\r\n\r\n # destroy root frame\r\n def delete_frame(self):\r\n self._frame.destroy()\r\n app.destroy()\r\n\r\n\r\n# Main Menu\r\nclass StartPage(tk.Frame):\r\n def __init__(self, master):\r\n\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Chess Club Program\", font=LARGE_FONT).pack(side=\"top\", fill=\"x\", pady=20)\r\n\r\n tk.Button(self, text=\"Record a Match\",\r\n command=lambda: master.switch_frame(RecordMatch)).pack(fill=\"both\", pady=10)\r\n tk.Button(self, text=\"Add a Player\",\r\n command=lambda: master.switch_frame(AddPlayer)).pack(fill=\"both\", pady=10)\r\n tk.Button(self, text=\"Delete Player\",\r\n command=lambda: master.switch_frame(DeletePlayer)).pack(fill=\"both\", pady=10)\r\n tk.Button(self, text=\"Member List\",\r\n command=lambda: master.switch_frame(LeaderBoard)).pack(fill=\"both\", pady=10)\r\n tk.Button(self, text='Match History',\r\n command=lambda: master.switch_frame(MatchHistory)).pack(fill='both', pady=10)\r\n tk.Button(self, text=\"Exit\",\r\n command=lambda: master.delete_frame()).pack(fill=\"both\", pady=8)\r\n\r\n\r\n# Recording a match/Determine player rating\r\nclass RecordMatch(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n\r\n # Define StringVer object\r\n self.player1ID = tk.StringVar()\r\n self.player2ID = tk.StringVar()\r\n self.player1winner = tk.IntVar()\r\n self.player2winner = tk.IntVar()\r\n\r\n tk.Label(self, text=\"Record the Match\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # Create text entries for players\r\n tk.Label(self, text=\"Player One ID\").grid(column=0, row=1, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player1ID).grid(column=1, row=1)\r\n tk.Label(self, text=\"Player Two ID\").grid(column=0, row=2, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.player2ID).grid(column=1, row=2)\r\n tk.Label(self, text=\"Winner?\").grid(column=0, row=3, sticky=tk.E)\r\n tk.Checkbutton(self, text=\"Player 1\", variable=self.player1winner).grid(column=1, row=3, sticky=tk.W)\r\n tk.Checkbutton(self, text=\"Player 2\", variable=self.player2winner).grid(column=1, row=3, sticky=tk.E)\r\n\r\n # Create a enterButton\r\n tk.Button(self, text=\"Enter\", command=self.enter).grid(column=1, row=5)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=5)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Enters the values into the database\r\n def enter(self):\r\n\r\n # Get player ID's\r\n id1 = self.player1ID.get()\r\n id2 = self.player2ID.get()\r\n\r\n # Collect player rating\r\n sql = '''SELECT rating FROM chess_players WHERE playerID = ?'''\r\n\r\n c.execute(sql, (id1,))\r\n conn.commit()\r\n\r\n # Change ratings into a float variable\r\n rating1 = c.fetchone()\r\n x = ''.join(map(str, rating1))\r\n new_rating1 = float(x)\r\n\r\n c.execute(sql, (id2,))\r\n conn.commit()\r\n\r\n rating2 = c.fetchone()\r\n y = ''.join(map(str, rating2))\r\n new_rating2 = float(y)\r\n\r\n # Calculate Winner\r\n if self.player1winner.get() == 1:\r\n if self.player2winner.get() == 1:\r\n # Calculate Tie\r\n print(\"Both players tie!\")\r\n else:\r\n # Player 1 Wins\r\n self.winnerID = self.player1ID\r\n RecordMatch.appendMatch(self)\r\n RecordMatch.CalculateNewRating(self, new_rating1, new_rating2, 50, 1)\r\n else:\r\n # Player 2 Wins\r\n self.winnerID = self.player2ID\r\n RecordMatch.appendMatch(self)\r\n RecordMatch.CalculateNewRating(self, new_rating1, new_rating2, 50, 0)\r\n\r\n self.player1ID.set(\"\")\r\n self.player2ID.set(\"\")\r\n self.player1winner.set(0)\r\n self.player2winner.set(0)\r\n\r\n # Function to calculate Elo rating\r\n # K is a constant.\r\n # d determines whether\r\n # Player A wins or Player B.\r\n def CalculateNewRating(self, Ra, Rb, K, d):\r\n\r\n # To calculate the Winning\r\n # Probability of Player B\r\n Pb = 1.0 * 1.0 / (1 + 1.0 * math.pow(10, 1.0 * (Ra - Rb) / 400))\r\n\r\n # To calculate the Winning\r\n # Probability of Player A\r\n Pa = 1.0 * 1.0 / (1 + 1.0 * math.pow(10, 1.0 * (Rb - Ra) / 400))\r\n\r\n # Case 1 When Player A wins\r\n # Updating the Elo Ratings\r\n if d == 1:\r\n Ra = Ra + K * (1 - Pa)\r\n Rb = Rb + K * (0 - Pb)\r\n\r\n # Case 2 When Player B wins\r\n # Updating the Elo Ratings\r\n elif d == 0:\r\n Ra = Ra + K * (0 - Pa)\r\n Rb = Rb + K * (1 - Pb)\r\n\r\n # Update SQL with player's ratings\r\n sql = '''UPDATE chess_players SET rating = ? WHERE playerID =?'''\r\n # Updating player 1's rating\r\n c.execute(sql, (round(Ra), self.player1ID.get()))\r\n conn.commit()\r\n # Updating player 2's rating\r\n c.execute(sql, (round(Rb), self.player2ID.get()))\r\n conn.commit()\r\n\r\n def appendMatch(self):\r\n # Get player's name and create match table\r\n co.execute(\"\"\" CREATE TABLE IF NOT EXISTS chess_matches (\r\n matchID INTEGER Primary Key,\r\n player1ID character(20) NOT NULL,\r\n player2ID character(20) NOT NULL,\r\n winnerID character(20) NOT NULL\r\n ); \"\"\")\r\n\r\n # Get player ID\r\n player1ID_new = self.player1ID.get()\r\n player2ID_new = self.player2ID.get()\r\n winnerID_new = self.winnerID.get()\r\n # Insert into SQL\r\n sql = 'INSERT INTO chess_matches (player1ID, player2ID, winnerID) VALUES ( ?, ?, ?) '\r\n # Execute SQL\r\n co.execute(sql, (player1ID_new, player2ID_new, winnerID_new))\r\n match_conn.commit()\r\n\r\n\r\n# Add player\r\nclass AddPlayer(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n\r\n # Define StringVar objects\r\n self.firstName = tk.StringVar()\r\n self.lastName = tk.StringVar()\r\n self.address = tk.StringVar()\r\n self.phone = tk.StringVar()\r\n self.rating = tk.StringVar()\r\n\r\n # Create label, entry field for new player\r\n tk.Label(self, text=\"First Name\").grid(column=0, row=0, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.firstName).grid(column=1, row=0)\r\n\r\n tk.Label(self, text='Last Name').grid(column=0, row=1, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.lastName).grid(column=1, row=1)\r\n\r\n tk.Label(self, text='Address').grid(column=0, row=2, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.address).grid(column=1, row=2)\r\n\r\n tk.Label(self, text='Phone Number').grid(column=0, row=3, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.phone).grid(column=1, row=3)\r\n\r\n tk.Label(self, text='Rating').grid(column=0, row=4, sticky=tk.E)\r\n tk.Entry(self, width=25, textvariable=self.rating).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=1, row=5, sticky=tk.W)\r\n\r\n # Create Enter Button\r\n tk.Button(self, text=\"Enter\", command=self.appendPlayer).grid(column=1, row=5, sticky=tk.E)\r\n\r\n # configure grid\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n def appendPlayer(self):\r\n # Create player table and add players to the database\r\n c.execute(\"\"\" CREATE TABLE IF NOT EXISTS chess_players (\r\n playerID INTEGER Primary Key,\r\n firstName character(20) NOT NULL,\r\n lastName character(20) NOT NULL,\r\n address character(50) NOT NULL,\r\n phone character(12) NOT NULL,\r\n rating integer(4) NOT NULL,\r\n active boolean NOT NULL\r\n ); \"\"\")\r\n # Get player data\r\n first_new = self.firstName.get()\r\n last_new = self.lastName.get()\r\n address_new = self.address.get()\r\n phone_new = self.phone.get()\r\n rating_new = int(self.rating.get())\r\n active_new = True\r\n\r\n # Insert into the SQL\r\n sql = 'INSERT INTO chess_players (firstName, lastName, address, phone, rating, active) VALUES (?, ?, ?, ?, ' \\\r\n ' ?, ?) '\r\n c.execute(sql, (first_new, last_new, address_new, phone_new, rating_new, active_new))\r\n conn.commit()\r\n\r\n # Reset text boxes\r\n self.firstName.set(\"\")\r\n self.lastName.set(\"\")\r\n self.address.set(\"\")\r\n self.phone.set(\"\")\r\n self.rating.set(\"\")\r\n\r\n\r\n# Delete player\r\nclass DeletePlayer(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Delete Player\").grid(column=1, row=0, sticky=tk.N)\r\n\r\n # Define StringVar object\r\n self.deletePlayerID = tk.StringVar()\r\n\r\n # Create a Label and Text Entry for player ID\r\n tk.Label(self, text=\"Player's ID\").grid(column=0, row=1, sticky=tk.W, columnspan=1)\r\n tk.Entry(self, width=25, textvariable=self.deletePlayerID).grid(column=1, row=1)\r\n\r\n # Create a DeleteButton\r\n tk.Button(self, text=\"Enter\", command=self.delete).grid(column=1, row=4)\r\n\r\n # Create ExitButton\r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=0, row=4)\r\n\r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n # Deletes player from database\r\n def delete(self):\r\n # Get player ID and set active to false\r\n id = int(self.deletePlayerID.get())\r\n active = False\r\n\r\n # Update database to set active to False\r\n sql = '''UPDATE chess_players SET active = ? WHERE playerID =?'''\r\n c.execute(sql, (active, id))\r\n conn.commit()\r\n\r\n self.deletePlayerID.set(\"\")\r\n\r\n# LeaderBoard\r\nclass LeaderBoard(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Member List\").grid(column=3, row =0)\r\n\r\n # Select players who are active\r\n query = \"SELECT * FROM chess_players WHERE active = ?\"\r\n c.execute(query, (True,))\r\n database = c.fetchall()\r\n \r\n tk.Label(self, text='ID', font=BOLD_FONT).grid(column=0, row=1)\r\n tk.Label(self, text='First Name' , font = BOLD_FONT).grid(column=1, row=1)\r\n tk.Label(self, text='Last Name', font = BOLD_FONT).grid(column=2, row=1)\r\n tk.Label(self, text='Address', font=BOLD_FONT).grid(column=3, row=1)\r\n tk.Label(self, text='Phone',font=BOLD_FONT).grid(column=4, row=1)\r\n tk.Label(self, text='Rating', font=BOLD_FONT).grid(column=5, row=1)\r\n tk.Label(self, text='Active', font=BOLD_FONT).grid(column=6, row=1)\r\n \r\n print(database)\r\n \r\n print_id = ''\r\n print_fName=''\r\n print_lName=''\r\n print_addreses=''\r\n print_phone=''\r\n print_rating=''\r\n print_active=''\r\n for data in database:\r\n print_id += str(data[0]) + '\\n'\r\n print_fName += str(data[1]) + '\\n'\r\n print_lName += str(data[2]) + '\\n'\r\n print_addreses += str(data[3])+ '\\n'\r\n print_phone += str(data[4]) + '\\n'\r\n print_rating += str(data[5]) + '\\n'\r\n print_active += str(data[6]) + '\\n'\r\n \r\n tk.Label(self, text = print_id).grid(column=0, row =2)\r\n tk.Label(self, text = print_fName).grid(column=1, row =2)\r\n tk.Label(self, text = print_lName).grid(column=2, row =2)\r\n tk.Label(self, text = print_addreses).grid(column=3, row =2)\r\n tk.Label(self, text = print_phone).grid(column=4, row =2)\r\n tk.Label(self, text = print_rating).grid(column=5, row =2)\r\n tk.Label(self, text = print_active).grid(column=6, row =2)\r\n \r\n \r\n \r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n \r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=3, row = 3)\r\n\r\nclass MatchHistory(tk.Frame):\r\n def __init__(self, master):\r\n tk.Frame.__init__(self, master)\r\n tk.Label(self, text=\"Match History\").grid(column=3, row =0)\r\n\r\n query = 'SELECT * FROM chess_matches'\r\n \r\n c.execute(query, (True,))\r\n database = co.fetchall()\r\n \r\n tk.Label(self, text='Match Number', font=BOLD_FONT).grid(column=0, row=1)\r\n tk.Label(self, text='Player 1 ID' , font = BOLD_FONT).grid(column=1, row=1)\r\n tk.Label(self, text='Player 2 ID', font = BOLD_FONT).grid(column=2, row=1)\r\n tk.Label(self, text='Winner ID', font=BOLD_FONT).grid(column=3, row=1)\r\n \r\n \r\n print_match_id = ''\r\n print_player1=''\r\n print_player2=''\r\n print_winner=''\r\n \r\n for data in database:\r\n print_match_id += str(data[0]) + '\\n'\r\n print_player1 += str(data[1]) + '\\n'\r\n print_player2 += str(data[2]) + '\\n'\r\n print_winner += str(data[3])+ '\\n'\r\n \r\n tk.Label(self, text = print_match_id).grid(column=0, row =2)\r\n tk.Label(self, text = print_player1).grid(column=1, row =2)\r\n tk.Label(self, text = print_player2).grid(column=2, row =2)\r\n tk.Label(self, text = print_winner).grid(column=3, row =2)\r\n \r\n \r\n \r\n for child in self.winfo_children():\r\n child.grid_configure(padx=5, pady=3)\r\n\r\n \r\n tk.Button(self, text=\"Return to start page\",\r\n command=lambda: master.switch_frame(StartPage)).grid(column=3, row = 3)\r\n\r\n\r\n\r\n\r\nif __name__ == \"__main__\":\r\n conn = sqlite3.connect(\"chess_players.db\")\r\n match_conn = sqlite3.connect(\"chess_matches.db\")\r\n c = conn.cursor()\r\n co = match_conn.cursor()\r\n\r\n app = ChessProgram()\r\n app.title(\"Chess Program\")\r\n app.geometry('600x400')\r\n app.mainloop()\r\n\r\n # close player database\r\n c.close()\r\n conn.close()\r\n\r\n # close the match database\r\n co.close()\r\n match_conn.close()"
}
] | 5
|
mawicks/hmm
|
https://github.com/mawicks/hmm
|
3b29b6fc571ad901334484cca3a77370a7b59e0e
|
1b6702298dc3d44a228c7db6acafa8aaf78c7415
|
971a32d31c4cd3140d7d8182e9db1429d78b8644
|
refs/heads/master
| 2021-01-12T05:19:25.782055
| 2017-01-03T11:41:08
| 2017-01-03T11:41:08
| 77,911,948
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5221518874168396,
"alphanum_fraction": 0.5928270220756531,
"avg_line_length": 31.689655303955078,
"blob_id": "b238b7cc3166551a55e196a8bbd22a6b8b25f162",
"content_id": "14b27249e7fd0c2f94b008779cc3302041d60ee1",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1896,
"license_type": "no_license",
"max_line_length": 90,
"num_lines": 58,
"path": "/main.py",
"repo_name": "mawicks/hmm",
"src_encoding": "UTF-8",
"text": "import hmm\n\n# Example from: http://www.indiana.edu/~iulg/moss/hmmcalculations.pdf\nexample1 = hmm.HMM()\nexample1.set_parameters(transitions = [[0.3, 0.7], [0.1, 0.9]],\n emissions = [[0.4, 0.6], [0.5, 0.5]],\n initial = [0.85, 0.15])\ne1 = [0, 1, 1, 0]\ne2 = [1, 0, 1]\n\nexample1.update(e1)\nexample1.update(e2)\n\n# Example 2\nprint('********* Example 2 ********')\n\n# Set some known parameters and use them to generate an observation sequence.\nexample2 = hmm.HMM()\nexample2.set_parameters(transitions = [[0.95, 0.05], [0.50, 0.50]],\n emissions = [[0.1, 0.2, 0.7], [0.5, 0.3, 0.2]],\n initial = [0.25, 0.75])\ne, s = example2.sim(10000)\n\nd = {}\nfor o in e:\n d[o] = d.get(o, 0) + 1\n\nprint('counts: {0}'.format(d))\ncounts = [d[o] for o in sorted(d.keys())]\nprint('counts: {0}'.format(counts))\n\n# Set incorrect parameters as an initial guess and try to estimate the original parameters\n# from the observations\nexample3 = hmm.HMM()\nexample3.set_parameters(transitions = [[0.6, 0.4], [0.4, 0.6]],\n emissions = [[0.33, 0.33, 0.34], [0.05, 0.55, 0.40]],\n initial = [0.3, 0.7])\nexample3.random_parameters(2, 3)\n\nprint('observations: {0}'.format(e[:50]))\nprint('actual state sequence: {0}'.format(s[:50]))\n\nfor i in range(50):\n print (' ***** ITERATION {0} *****'.format(i))\n tr, em, init, likelihood = example3.update(e)\n if i == 0:\n original_likelihood = likelihood\n\n print('current log likelihood: {0}'.format(likelihood))\n example3.set_parameters(transitions = tr, emissions = em, initial = init)\n\nprint('initial log likelihood: {0}'.format( original_likelihood))\nprint('final log likelihood: {0}'.format(likelihood))\n \nprint('final parameters:')\nprint('transitions:\\n{0}'.format(tr))\nprint('emissions:\\n{0}'.format(em))\nprint('initial:\\n{0}'.format(init))\n"
},
{
"alpha_fraction": 0.5672499537467957,
"alphanum_fraction": 0.5722120404243469,
"avg_line_length": 41.77653503417969,
"blob_id": "078a80c50f4a4f3b5b127d10e1b9c1e6303d7cbb",
"content_id": "ec070d0af8c8e727dabde7cdb2976d8e89f9128c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7658,
"license_type": "no_license",
"max_line_length": 139,
"num_lines": 179,
"path": "/hmm.py",
"repo_name": "mawicks/hmm",
"src_encoding": "UTF-8",
"text": "import logging\nfrom tools import cumsum, find\nfrom random import randrange, uniform\nimport numpy\nimport operator\n\nlogger = logging.getLogger()\n\ndef draw(cdf):\n '''Draw a random sample from the distribution defined by cdf. The values in a cdf must be non-descreasing, but need not be normalized.\nThey can represent cumulative counts, for example, rather than cumulative probabilities.'''\n if len(cdf) > 0:\n return find(cdf, uniform(0, cdf[-1]))\n else:\n return None\n\ndef random_distribution(n):\n l = [uniform(0, 1) for _ in range(n)]\n s = sum(l)\n return tuple(x / s for x in l)\n\ndef log_sum_exp(a):\n '''Compute log(sum[exp(row) for row in a]) without underflows'''\n col_max = numpy.max(a, axis=0)\n\n result = numpy.log(numpy.sum(numpy.exp(numpy.array([c - m for c, m in zip(a.T, col_max)])),\n axis=1)) + col_max\n\n return result\n\ndef print_large(array, name):\n print ('{0}:'.format(name))\n \n if len(array) < 10:\n print(array)\n else:\n for r in array[:5]:\n print ('\\t{0}'.format(r))\n print ('\\t...')\n for r in array[-5:]:\n print ('\\t{0}'.format(r))\n \nclass HMM:\n def set_parameters(self, transitions=None, emissions=None, initial=None):\n if len(transitions) == 0:\n raise Exception('Must have at least one state')\n \n row_lengths = [len(row) for row in transitions]\n mx,mn = (max(row_lengths), min(row_lengths))\n if mx != mn or mx != len(transitions):\n raise Exception('Transition matrix is not square')\n \n if len(transitions) != len(emissions):\n raise Exception('Transition matrix and emissions length have different numbers of rows')\n \n if len(transitions) != len(initial):\n raise Exception('Transition matrix and initial state probability distribution have different numbers of rows')\n\n self._n_states = len(transitions)\n self._n_symbols = len(emissions[0])\n \n self._transitions = numpy.array(transitions)\n self._log_transitions = numpy.log(self._transitions+1e-30)\n \n self._emissions = numpy.array(emissions)\n self._log_emissions = numpy.log(self._emissions+1e-30)\n \n self._initial = numpy.array(initial)\n self._log_initial = numpy.log(self._initial+1e-30)\n \n def random_parameters(self, n_states, n_symbols):\n '''Set a random set of initial parameters. Counts of observations are used to estimate an initial set of emission probabilities.\nState transitions are set randomly.'''\n self.set_parameters(tuple(random_distribution(n_states) for _ in range(n_states)),\n tuple(random_distribution(n_symbols) for _ in range(n_states)),\n random_distribution(n_states))\n \n def sim(self, n):\n '''emissions, states = sim(n): Simulate n iterations and return the emission and state trajectories'''\n cum_transitions = tuple(tuple(cumsum(row)) for row in self._transitions)\n cum_emissions = tuple(tuple(cumsum(row)) for row in self._emissions)\n cum_initial = tuple(cumsum(self._initial))\n \n path = []\n state = draw(cum_initial)\n for _ in range(n):\n emission = draw(cum_emissions[state])\n path.append((emission, state))\n \n # Update for next iteration\n state = draw(cum_transitions[state])\n return zip(*path)\n\n def forward(self, observations):\n '''Apply so-called \"forward procedure\" and return sequence of alpha probabilities'''\n logger.info('forward() entered')\n \n log_alpha = self._log_initial + self._log_emissions[:,observations[0]]\n log_alpha_series = [log_alpha]\n\n for y in observations[1:]:\n log_alpha = (self._log_emissions[:,y] +\n log_sum_exp(numpy.array([log_alpha_i + log_trans_i\n for log_alpha_i, log_trans_i\n in zip(log_alpha, self._log_transitions)])))\n log_alpha_series.append(log_alpha)\n\n logger.info('forward() exited')\n return numpy.array(log_alpha_series)\n \n def backward(self, observations):\n '''Apply so-called \"backward procedure\" and return sequence of beta probabilities'''\n logger.info('backward() entered')\n\n log_beta = numpy.array([ 0.0 ] * self._n_states)\n log_beta_series = [log_beta]\n \n for y in reversed(observations[1:]):\n log_beta = log_sum_exp(numpy.array([log_beta_j + log_em_j[y] + log_trans_j\n for log_beta_j, log_trans_j, log_em_j\n in zip(log_beta, self._log_transitions.T, self._log_emissions)]))\n log_beta_series.append(log_beta)\n \n logger.info('backward() exited')\n return numpy.array(list(reversed(log_beta_series)))\n \n def update(self, observations):\n '''Perform one iteration of Baum-Welch algorithm and return new parameter estimate and observation likelihood:\n transition, emission, pi = update(observations)\nThe observation likelihood is for the observed sequence given the original parameters, not the new parameters.\n'''\n logger.info('update() entered')\n\n log_alpha = self.forward(observations)\n log_beta = self.backward(observations)\n\n gamma_num = log_alpha + log_beta\n gamma = numpy.exp(numpy.array([n-d\n for n,d\n in zip(gamma_num,\n log_sum_exp(gamma_num.T))]))\n \n# print_large(log_alpha, 'log alpha')\n# print_large(log_beta, 'log beta')\n# print_large(gamma, 'gamma')\n \n new_transition_num = numpy.zeros((self._n_states, self._n_states))\n new_transition_den = numpy.zeros(self._n_states)\n\n for gamma_k, log_alpha_k, log_beta_k, y in zip(gamma[:-1], log_alpha[:-1], log_beta[1:], observations[1:]):\n log_xi_num = numpy.empty((self._n_states, self._n_states))\n for i in range(self._n_states):\n for j in range(self._n_states):\n log_xi_num[i,j] = log_alpha_k[i] + log_beta_k[j] + self._log_transitions[i][j] + self._log_emissions[j][y]\n \n # This clumsy because numpy turns single rows/colums into vectors.\n # log_sum_exp requires a matrix argument, so we force it to be a matrix.\n log_xi_den = log_sum_exp(numpy.array([[r] for r in log_sum_exp(log_xi_num)]))\n \n xi = numpy.exp(log_xi_num - log_xi_den)\n# print('xi:\\n{0}'.format(xi))\n \n new_transition_num += xi\n new_transition_den += gamma_k\n \n new_transition = (new_transition_num.T/new_transition_den).T\n\n ind = numpy.array(range(self._n_symbols))\n new_emission_num = sum((numpy.outer(gamma_k, (ind == yk)) for yk, gamma_k in zip(observations, gamma)))\n new_emission_den = new_transition_den + gamma[-1]\n new_emission = (new_emission_num.T/new_emission_den).T\n\n new_initial = gamma[0]\n\n # Same clumsy trick\n observation_likelihood = log_sum_exp(numpy.array([[la] for la in log_alpha[-1]]))\n \n logger.info('update() exited')\n return new_transition, new_emission, new_initial, float(observation_likelihood)\n\n"
},
{
"alpha_fraction": 0.5195729732513428,
"alphanum_fraction": 0.5266903638839722,
"avg_line_length": 27.724138259887695,
"blob_id": "f192525284d921e0055904ab590e9e87bd2b58fc",
"content_id": "a40a042c9156468938fdef9522e5141aa8000954",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 843,
"license_type": "no_license",
"max_line_length": 158,
"num_lines": 29,
"path": "/tools.py",
"repo_name": "mawicks/hmm",
"src_encoding": "UTF-8",
"text": "def find(vector, value):\n '''Return the index of the first element of \"vector\" that equals or exceeds \"value\" (\"vector\" must be pre-sorted). If no such element exist return None'''\n\n def helper(vector, first, n, value):\n if n == 1:\n if vector[first] >= value:\n return first\n else:\n return None\n \n half_n = n // 2\n mid = first + half_n - 1\n\n if vector[mid] >= value:\n return helper(vector, first, half_n, value)\n else:\n return helper(vector, first + half_n, n - half_n, value)\n\n if len(vector) > 0:\n return helper(vector, 0, len(vector), value)\n else:\n return None\n \n\ndef cumsum(sequence, initial = 0):\n sum = initial\n for item in sequence:\n sum += item\n yield sum\n \n \n"
}
] | 3
|
chanchan69/truecolor
|
https://github.com/chanchan69/truecolor
|
530fd7e5b7c914cce53c84f2663d800cd9b9d3fa
|
5633e00fc5df5183ccb4e8d8dfa7165ea5dd1e89
|
e03532f33da197d208f0e63ee50762a0aa216729
|
refs/heads/main
| 2023-09-02T05:59:37.800974
| 2021-10-09T04:02:31
| 2021-10-09T04:02:31
| 411,485,604
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6452074646949768,
"alphanum_fraction": 0.7181687951087952,
"avg_line_length": 23.10344886779785,
"blob_id": "294b215409078354e70f3d31fb2a9161754f72d6",
"content_id": "8ab95712713a89119204b0a4ccd2e55d61590437",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 699,
"license_type": "permissive",
"max_line_length": 139,
"num_lines": 29,
"path": "/README.md",
"repo_name": "chanchan69/truecolor",
"src_encoding": "UTF-8",
"text": "# truecolor\n\nA better console color library for python\n\n[GitHub](https://github.com/chanchan69/truecolor/)\n\n[PyPI](https://pypi.org/project/truecolor.py/)\n\n### Print Colored Text\n```py\nfrom truecolor import fg, reset\nfrom os import system\n\nsystem('cls')\nprint(f\"{fg('magenta')}This {fg((255, 0, 0))}is{fg('magenta')} magenta text!{fg('#ff8243')} This is the exact hex color #ff8243 :){reset}\")\n```\n\n### Output\n\n\n\n### Another Way\n```py\nfrom truecolor import colors, reset\nfrom os import system\n\nsystem('cls')\nprint(f\"{colors.magenta}This {colors.red)}is{colors.magenta} magenta text!{reset}\")\n```\n"
},
{
"alpha_fraction": 0.4779411852359772,
"alphanum_fraction": 0.5441176295280457,
"avg_line_length": 16.266666412353516,
"blob_id": "7f3580156777a76c7089a72a05c5e3a0523ef9c0",
"content_id": "a4e5c7b8f0ee6422821ab646745ce81da0ab4db6",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 276,
"license_type": "permissive",
"max_line_length": 75,
"num_lines": 15,
"path": "/example.py",
"repo_name": "chanchan69/truecolor",
"src_encoding": "UTF-8",
"text": "from truecolor import fg\r\nfrom os import system\r\nfrom random import randint\r\n\r\n\r\nt = \"\"\r\nfor x in range(100):\r\n s = \"\"\r\n for z in range(158):\r\n s += f\"{fg((randint(0, 255), randint(0, 255), randint(0, 255)))}██\"\r\n t += f\"{s}\\n\"\r\n\r\n\r\nsystem('cls')\r\ninput(t)"
},
{
"alpha_fraction": 0.2684931457042694,
"alphanum_fraction": 0.48756974935531616,
"avg_line_length": 83.71304321289062,
"blob_id": "72750180d0172f444373f7c642a12d44cbd3e4c5",
"content_id": "f24b1d94c1405bc905d47aa97842866fd8b59af6",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9855,
"license_type": "permissive",
"max_line_length": 137,
"num_lines": 115,
"path": "/src/truecolor/functions.py",
"repo_name": "chanchan69/truecolor",
"src_encoding": "UTF-8",
"text": "def fg(color: any) -> str:\r\n \"\"\"\r\n Returns an ANSI escape code\r\n\r\n :param color: a hex color as a str (ie #123456), a rgb color as a tuple (ie (1,2,3)), or a supported color name as a str (ie magenta)\r\n \"\"\"\r\n if isinstance(color, tuple):\r\n rgb = color\r\n\r\n elif isinstance(color, str) and color.__contains__(\"#\"):\r\n rgb = hex_to_rgb(color)\r\n\r\n elif isinstance(color, str) and not color.__contains__(\"#\"):\r\n rgb = name_to_rgb(color)\r\n else:\r\n return \"\"\r\n\r\n r = rgb[0]\r\n g = rgb[1]\r\n b = rgb[2]\r\n\r\n return f\"\\033[38;2;{r};{g};{b}m\"\r\n\r\n\r\ndef hex_to_rgb(hex_code: str) -> list:\r\n return [int(hex_code[i:i + 2], 16) for i in range(1, 6, 2)]\r\n\r\n\r\ndef name_to_rgb(name: str) -> tuple:\r\n color_names = dict(black=(0, 0, 0), red=(128, 0, 0), green=(0, 128, 0), yellow=(128, 128, 0), blue=(0, 0, 128),\r\n magenta=(128, 0, 128), cyan=(0, 128, 128), light_gray=(192, 192, 192), dark_gray=(128, 128, 128),\r\n light_red=(255, 0, 0), light_green=(0, 255, 0), light_yellow=(255, 255, 0),\r\n light_blue=(0, 0, 255), light_magenta=(255, 0, 255), light_cyan=(0, 255, 255),\r\n white=(255, 255, 255), grey_0=(0, 0, 0), navy_blue=(0, 0, 95), dark_blue=(0, 0, 135),\r\n blue_3a=(0, 0, 175), blue_3b=(0, 0, 215), blue_1=(0, 0, 255), dark_green=(0, 95, 0),\r\n deep_sky_blue_4a=(0, 95, 95), deep_sky_blue_4b=(0, 95, 135), deep_sky_blue_4c=(0, 95, 175),\r\n dodger_blue_3=(0, 95, 215), dodger_blue_2=(0, 95, 255), green_4=(0, 135, 0),\r\n spring_green_4=(0, 135, 95), turquoise_4=(0, 135, 135), deep_sky_blue_3a=(0, 135, 175),\r\n deep_sky_blue_3b=(0, 135, 215), dodger_blue_1=(0, 135, 255), green_3a=(0, 175, 0),\r\n spring_green_3a=(0, 175, 95), dark_cyan=(0, 175, 135), light_sea_green=(0, 175, 175),\r\n deep_sky_blue_2=(0, 175, 215), deep_sky_blue_1=(0, 175, 255), green_3b=(0, 215, 0),\r\n spring_green_3b=(0, 215, 95), spring_green_2a=(0, 215, 135), cyan_3=(0, 215, 175),\r\n dark_turquoise=(0, 215, 215), turquoise_2=(0, 215, 255), green_1=(0, 255, 0),\r\n spring_green_2b=(0, 255, 95), spring_green_1=(0, 255, 135), medium_spring_green=(0, 255, 175),\r\n cyan_2=(0, 255, 215), cyan_1=(0, 255, 255), dark_red_1=(95, 0, 0), deep_pink_4a=(95, 0, 95),\r\n purple_4a=(95, 0, 135), purple_4b=(95, 0, 175), purple_3=(95, 0, 215), blue_violet=(95, 0, 255),\r\n orange_4a=(95, 95, 0), grey_37=(95, 95, 95), medium_purple_4=(95, 95, 135),\r\n slate_blue_3a=(95, 95, 175), slate_blue_3b=(95, 95, 215), royal_blue_1=(95, 95, 255),\r\n chartreuse_4=(95, 135, 0), dark_sea_green_4a=(95, 135, 95), pale_turquoise_4=(95, 135, 135),\r\n steel_blue=(95, 135, 175), steel_blue_3=(95, 135, 215), cornflower_blue=(95, 135, 255),\r\n chartreuse_3a=(95, 175, 0), dark_sea_green_4b=(95, 175, 95), cadet_blue_2=(95, 175, 135),\r\n cadet_blue_1=(95, 175, 175), sky_blue_3=(95, 175, 215), steel_blue_1a=(95, 175, 255),\r\n chartreuse_3b=(95, 215, 0), pale_green_3a=(95, 215, 95), sea_green_3=(95, 215, 135),\r\n aquamarine_3=(95, 215, 175), medium_turquoise=(95, 215, 215), steel_blue_1b=(95, 215, 255),\r\n chartreuse_2a=(95, 255, 0), sea_green_2=(95, 255, 95), sea_green_1a=(95, 255, 135),\r\n sea_green_1b=(95, 255, 175), aquamarine_1a=(95, 255, 215), dark_slate_gray_2=(95, 255, 255),\r\n dark_red_2=(135, 0, 0), deep_pink_4b=(135, 0, 95), dark_magenta_1=(135, 0, 135),\r\n dark_magenta_2=(135, 0, 175), dark_violet_1a=(135, 0, 215), purple_1a=(135, 0, 255),\r\n orange_4b=(135, 95, 0), light_pink_4=(135, 95, 95), plum_4=(135, 95, 135),\r\n medium_purple_3a=(135, 95, 175), medium_purple_3b=(135, 95, 215), slate_blue_1=(135, 95, 255),\r\n yellow_4a=(135, 135, 0), wheat_4=(135, 135, 95), grey_53=(135, 135, 135),\r\n light_slate_grey=(135, 135, 175), medium_purple=(135, 135, 215),\r\n light_slate_blue=(135, 135, 255), yellow_4b=(135, 175, 0), dark_olive_green_3a=(135, 175, 95),\r\n dark_green_sea=(135, 175, 135), light_sky_blue_3a=(135, 175, 175),\r\n light_sky_blue_3b=(135, 175, 215), sky_blue_2=(135, 175, 255), chartreuse_2b=(135, 215, 0),\r\n dark_olive_green_3b=(135, 215, 95), pale_green_3b=(135, 215, 135),\r\n dark_sea_green_3a=(135, 215, 175), dark_slate_gray_3=(135, 215, 215), sky_blue_1=(135, 215, 255),\r\n chartreuse_1=(135, 255, 0), light_green_2=(135, 255, 95), light_green_3=(135, 255, 135),\r\n pale_green_1a=(135, 255, 175), aquamarine_1b=(135, 255, 215), dark_slate_gray_1=(135, 255, 255),\r\n red_3a=(175, 0, 0), deep_pink_4c=(175, 0, 95), medium_violet_red=(175, 0, 135),\r\n magenta_3a=(175, 0, 175), dark_violet_1b=(175, 0, 215), purple_1b=(175, 0, 255),\r\n dark_orange_3a=(175, 95, 0), indian_red_1a=(175, 95, 95), hot_pink_3a=(175, 95, 135),\r\n medium_orchid_3=(175, 95, 175), medium_orchid=(175, 95, 215), medium_purple_2a=(175, 95, 255),\r\n dark_goldenrod=(175, 135, 0), light_salmon_3a=(175, 135, 95), rosy_brown=(175, 135, 135),\r\n grey_63=(175, 135, 175), medium_purple_2b=(175, 135, 215), medium_purple_1=(175, 135, 255),\r\n gold_3a=(175, 175, 0), dark_khaki=(175, 175, 95), navajo_white_3=(175, 175, 135),\r\n grey_69=(175, 175, 175), light_steel_blue_3=(175, 175, 215), light_steel_blue=(175, 175, 255),\r\n yellow_3a=(175, 215, 0), dark_olive_green_3=(175, 215, 95), dark_sea_green_3b=(175, 215, 135),\r\n dark_sea_green_2=(175, 215, 175), light_cyan_3=(175, 215, 215), light_sky_blue_1=(175, 215, 255),\r\n green_yellow=(175, 255, 0), dark_olive_green_2=(175, 255, 95), pale_green_1b=(175, 255, 135),\r\n dark_sea_green_5b=(175, 255, 175), dark_sea_green_5a=(175, 255, 215),\r\n pale_turquoise_1=(175, 255, 255), red_3b=(215, 0, 0), deep_pink_3a=(215, 0, 95),\r\n deep_pink_3b=(215, 0, 135), magenta_3b=(215, 0, 175), magenta_3c=(215, 0, 215),\r\n magenta_2a=(215, 0, 255), dark_orange_3b=(215, 95, 0), indian_red_1b=(215, 95, 95),\r\n hot_pink_3b=(215, 95, 135), hot_pink_2=(215, 95, 175), orchid=(215, 95, 215),\r\n medium_orchid_1a=(215, 95, 255), orange_3=(215, 135, 0), light_salmon_3b=(215, 135, 95),\r\n light_pink_3=(215, 135, 135), pink_3=(215, 135, 175), plum_3=(215, 135, 215),\r\n violet=(215, 135, 255), gold_3b=(215, 175, 0), light_goldenrod_3=(215, 175, 95),\r\n tan=(215, 175, 135), misty_rose_3=(215, 175, 175), thistle_3=(215, 175, 215),\r\n plum_2=(215, 175, 255), yellow_3b=(215, 215, 0), khaki_3=(215, 215, 95),\r\n light_goldenrod_2a=(215, 215, 135), light_yellow_3=(215, 215, 175), grey_84=(215, 215, 215),\r\n light_steel_blue_1=(215, 215, 255), yellow_2=(215, 255, 0), dark_olive_green_1a=(215, 255, 95),\r\n dark_olive_green_1b=(215, 255, 135), dark_sea_green_1=(215, 255, 175),\r\n honeydew_2=(215, 255, 215), light_cyan_1=(215, 255, 255), red_1=(255, 0, 0),\r\n deep_pink_2=(255, 0, 95), deep_pink_1a=(255, 0, 135), deep_pink_1b=(255, 0, 175),\r\n magenta_2b=(255, 0, 215), magenta_1=(255, 0, 255), orange_red_1=(255, 95, 0),\r\n indian_red_1c=(255, 95, 95), indian_red_1d=(255, 95, 135), hot_pink_1a=(255, 95, 175),\r\n hot_pink_1b=(255, 95, 215), medium_orchid_1b=(255, 95, 255), dark_orange=(255, 135, 0),\r\n salmon_1=(255, 135, 95), light_coral=(255, 135, 135), pale_violet_red_1=(255, 135, 175),\r\n orchid_2=(255, 135, 215), orchid_1=(255, 135, 255), orange_1=(255, 175, 0),\r\n sandy_brown=(255, 175, 95), light_salmon_1=(255, 175, 135), light_pink_1=(255, 175, 175),\r\n pink_1=(255, 175, 215), plum_1=(255, 175, 255), gold_1=(255, 215, 0),\r\n light_goldenrod_2b=(255, 215, 95), light_goldenrod_2c=(255, 215, 135),\r\n navajo_white_1=(255, 215, 175), misty_rose1=(255, 215, 215), thistle_1=(255, 215, 255),\r\n yellow_1=(255, 255, 0), light_goldenrod_1=(255, 255, 95), khaki_1=(255, 255, 135),\r\n wheat_1=(255, 255, 175), cornsilk_1=(255, 255, 215), grey_100=(255, 255, 255), grey_3=(8, 8, 8),\r\n grey_7=(18, 18, 18), grey_11=(28, 28, 28), grey_15=(38, 38, 38), grey_19=(48, 48, 48),\r\n grey_23=(58, 58, 58), grey_27=(68, 68, 68), grey_30=(78, 78, 78), grey_35=(88, 88, 88),\r\n grey_39=(98, 98, 98), grey_42=(108, 108, 108), grey_46=(118, 118, 118), grey_50=(128, 128, 128),\r\n grey_54=(138, 138, 138), grey_58=(148, 148, 148), grey_62=(158, 158, 158),\r\n grey_66=(168, 168, 168), grey_70=(178, 178, 178), grey_74=(188, 188, 188),\r\n grey_78=(198, 198, 198), grey_82=(208, 208, 208), grey_85=(218, 218, 218),\r\n grey_89=(228, 228, 228))\r\n\r\n return color_names[name]"
},
{
"alpha_fraction": 0.5901639461517334,
"alphanum_fraction": 0.6557376980781555,
"avg_line_length": 25.5,
"blob_id": "6138c08abf579d6647985c95531741a727551798",
"content_id": "36cc27df1c2c19625238520eedc42aaaaea18c96",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 61,
"license_type": "permissive",
"max_line_length": 34,
"num_lines": 2,
"path": "/src/truecolor/__init__.py",
"repo_name": "chanchan69/truecolor",
"src_encoding": "UTF-8",
"text": "from truecolor.functions import fg\r\nreset = \"\\033[0m\"\r\n\r\n\r\n\r\n"
},
{
"alpha_fraction": 0.27389585971832275,
"alphanum_fraction": 0.5925071239471436,
"avg_line_length": 33.701961517333984,
"blob_id": "bf672ba797a101b413954923abf6afe7c6d36ad5",
"content_id": "d2c84426773cec52009db70b9a075188015298a1",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9612,
"license_type": "permissive",
"max_line_length": 43,
"num_lines": 255,
"path": "/src/truecolor/colors.py",
"repo_name": "chanchan69/truecolor",
"src_encoding": "UTF-8",
"text": "black = '←[38;2;0;0;0m'\r\nred = '←[38;2;128;0;0m'\r\ngreen = '←[38;2;0;128;0m'\r\nyellow = '←[38;2;128;128;0m'\r\nblue = '←[38;2;0;0;128m'\r\nmagenta = '←[38;2;128;0;128m'\r\ncyan = '←[38;2;0;128;128m'\r\nlight_gray = '←[38;2;192;192;192m'\r\ndark_gray = '←[38;2;128;128;128m'\r\nlight_red = '←[38;2;255;0;0m'\r\nlight_green = '←[38;2;0;255;0m'\r\nlight_yellow = '←[38;2;255;255;0m'\r\nlight_blue = '←[38;2;0;0;255m'\r\nlight_magenta = '←[38;2;255;0;255m'\r\nlight_cyan = '←[38;2;0;255;255m'\r\nwhite = '←[38;2;255;255;255m'\r\ngrey_0 = '←[38;2;0;0;0m'\r\nnavy_blue = '←[38;2;0;0;95m'\r\ndark_blue = '←[38;2;0;0;135m'\r\nblue_3a = '←[38;2;0;0;175m'\r\nblue_3b = '←[38;2;0;0;215m'\r\nblue_1 = '←[38;2;0;0;255m'\r\ndark_green = '←[38;2;0;95;0m'\r\ndeep_sky_blue_4a = '←[38;2;0;95;95m'\r\ndeep_sky_blue_4b = '←[38;2;0;95;135m'\r\ndeep_sky_blue_4c = '←[38;2;0;95;175m'\r\ndodger_blue_3 = '←[38;2;0;95;215m'\r\ndodger_blue_2 = '←[38;2;0;95;255m'\r\ngreen_4 = '←[38;2;0;135;0m'\r\nspring_green_4 = '←[38;2;0;135;95m'\r\nturquoise_4 = '←[38;2;0;135;135m'\r\ndeep_sky_blue_3a = '←[38;2;0;135;175m'\r\ndeep_sky_blue_3b = '←[38;2;0;135;215m'\r\ndodger_blue_1 = '←[38;2;0;135;255m'\r\ngreen_3a = '←[38;2;0;175;0m'\r\nspring_green_3a = '←[38;2;0;175;95m'\r\ndark_cyan = '←[38;2;0;175;135m'\r\nlight_sea_green = '←[38;2;0;175;175m'\r\ndeep_sky_blue_2 = '←[38;2;0;175;215m'\r\ndeep_sky_blue_1 = '←[38;2;0;175;255m'\r\ngreen_3b = '←[38;2;0;215;0m'\r\nspring_green_3b = '←[38;2;0;215;95m'\r\nspring_green_2a = '←[38;2;0;215;135m'\r\ncyan_3 = '←[38;2;0;215;175m'\r\ndark_turquoise = '←[38;2;0;215;215m'\r\nturquoise_2 = '←[38;2;0;215;255m'\r\ngreen_1 = '←[38;2;0;255;0m'\r\nspring_green_2b = '←[38;2;0;255;95m'\r\nspring_green_1 = '←[38;2;0;255;135m'\r\nmedium_spring_green = '←[38;2;0;255;175m'\r\ncyan_2 = '←[38;2;0;255;215m'\r\ncyan_1 = '←[38;2;0;255;255m'\r\ndark_red_1 = '←[38;2;95;0;0m'\r\ndeep_pink_4a = '←[38;2;95;0;95m'\r\npurple_4a = '←[38;2;95;0;135m'\r\npurple_4b = '←[38;2;95;0;175m'\r\npurple_3 = '←[38;2;95;0;215m'\r\nblue_violet = '←[38;2;95;0;255m'\r\norange_4a = '←[38;2;95;95;0m'\r\ngrey_37 = '←[38;2;95;95;95m'\r\nmedium_purple_4 = '←[38;2;95;95;135m'\r\nslate_blue_3a = '←[38;2;95;95;175m'\r\nslate_blue_3b = '←[38;2;95;95;215m'\r\nroyal_blue_1 = '←[38;2;95;95;255m'\r\nchartreuse_4 = '←[38;2;95;135;0m'\r\ndark_sea_green_4a = '←[38;2;95;135;95m'\r\npale_turquoise_4 = '←[38;2;95;135;135m'\r\nsteel_blue = '←[38;2;95;135;175m'\r\nsteel_blue_3 = '←[38;2;95;135;215m'\r\ncornflower_blue = '←[38;2;95;135;255m'\r\nchartreuse_3a = '←[38;2;95;175;0m'\r\ndark_sea_green_4b = '←[38;2;95;175;95m'\r\ncadet_blue_2 = '←[38;2;95;175;135m'\r\ncadet_blue_1 = '←[38;2;95;175;175m'\r\nsky_blue_3 = '←[38;2;95;175;215m'\r\nsteel_blue_1a = '←[38;2;95;175;255m'\r\nchartreuse_3b = '←[38;2;95;215;0m'\r\npale_green_3a = '←[38;2;95;215;95m'\r\nsea_green_3 = '←[38;2;95;215;135m'\r\naquamarine_3 = '←[38;2;95;215;175m'\r\nmedium_turquoise = '←[38;2;95;215;215m'\r\nsteel_blue_1b = '←[38;2;95;215;255m'\r\nchartreuse_2a = '←[38;2;95;255;0m'\r\nsea_green_2 = '←[38;2;95;255;95m'\r\nsea_green_1a = '←[38;2;95;255;135m'\r\nsea_green_1b = '←[38;2;95;255;175m'\r\naquamarine_1a = '←[38;2;95;255;215m'\r\ndark_slate_gray_2 = '←[38;2;95;255;255m'\r\ndark_red_2 = '←[38;2;135;0;0m'\r\ndeep_pink_4b = '←[38;2;135;0;95m'\r\ndark_magenta_1 = '←[38;2;135;0;135m'\r\ndark_magenta_2 = '←[38;2;135;0;175m'\r\ndark_violet_1a = '←[38;2;135;0;215m'\r\npurple_1a = '←[38;2;135;0;255m'\r\norange_4b = '←[38;2;135;95;0m'\r\nlight_pink_4 = '←[38;2;135;95;95m'\r\nplum_4 = '←[38;2;135;95;135m'\r\nmedium_purple_3a = '←[38;2;135;95;175m'\r\nmedium_purple_3b = '←[38;2;135;95;215m'\r\nslate_blue_1 = '←[38;2;135;95;255m'\r\nyellow_4a = '←[38;2;135;135;0m'\r\nwheat_4 = '←[38;2;135;135;95m'\r\ngrey_53 = '←[38;2;135;135;135m'\r\nlight_slate_grey = '←[38;2;135;135;175m'\r\nmedium_purple = '←[38;2;135;135;215m'\r\nlight_slate_blue = '←[38;2;135;135;255m'\r\nyellow_4b = '←[38;2;135;175;0m'\r\ndark_olive_green_3a = '←[38;2;135;175;95m'\r\ndark_green_sea = '←[38;2;135;175;135m'\r\nlight_sky_blue_3a = '←[38;2;135;175;175m'\r\nlight_sky_blue_3b = '←[38;2;135;175;215m'\r\nsky_blue_2 = '←[38;2;135;175;255m'\r\nchartreuse_2b = '←[38;2;135;215;0m'\r\ndark_olive_green_3b = '←[38;2;135;215;95m'\r\npale_green_3b = '←[38;2;135;215;135m'\r\ndark_sea_green_3a = '←[38;2;135;215;175m'\r\ndark_slate_gray_3 = '←[38;2;135;215;215m'\r\nsky_blue_1 = '←[38;2;135;215;255m'\r\nchartreuse_1 = '←[38;2;135;255;0m'\r\nlight_green_2 = '←[38;2;135;255;95m'\r\nlight_green_3 = '←[38;2;135;255;135m'\r\npale_green_1a = '←[38;2;135;255;175m'\r\naquamarine_1b = '←[38;2;135;255;215m'\r\ndark_slate_gray_1 = '←[38;2;135;255;255m'\r\nred_3a = '←[38;2;175;0;0m'\r\ndeep_pink_4c = '←[38;2;175;0;95m'\r\nmedium_violet_red = '←[38;2;175;0;135m'\r\nmagenta_3a = '←[38;2;175;0;175m'\r\ndark_violet_1b = '←[38;2;175;0;215m'\r\npurple_1b = '←[38;2;175;0;255m'\r\ndark_orange_3a = '←[38;2;175;95;0m'\r\nindian_red_1a = '←[38;2;175;95;95m'\r\nhot_pink_3a = '←[38;2;175;95;135m'\r\nmedium_orchid_3 = '←[38;2;175;95;175m'\r\nmedium_orchid = '←[38;2;175;95;215m'\r\nmedium_purple_2a = '←[38;2;175;95;255m'\r\ndark_goldenrod = '←[38;2;175;135;0m'\r\nlight_salmon_3a = '←[38;2;175;135;95m'\r\nrosy_brown = '←[38;2;175;135;135m'\r\ngrey_63 = '←[38;2;175;135;175m'\r\nmedium_purple_2b = '←[38;2;175;135;215m'\r\nmedium_purple_1 = '←[38;2;175;135;255m'\r\ngold_3a = '←[38;2;175;175;0m'\r\ndark_khaki = '←[38;2;175;175;95m'\r\nnavajo_white_3 = '←[38;2;175;175;135m'\r\ngrey_69 = '←[38;2;175;175;175m'\r\nlight_steel_blue_3 = '←[38;2;175;175;215m'\r\nlight_steel_blue = '←[38;2;175;175;255m'\r\nyellow_3a = '←[38;2;175;215;0m'\r\ndark_olive_green_3 = '←[38;2;175;215;95m'\r\ndark_sea_green_3b = '←[38;2;175;215;135m'\r\ndark_sea_green_2 = '←[38;2;175;215;175m'\r\nlight_cyan_3 = '←[38;2;175;215;215m'\r\nlight_sky_blue_1 = '←[38;2;175;215;255m'\r\ngreen_yellow = '←[38;2;175;255;0m'\r\ndark_olive_green_2 = '←[38;2;175;255;95m'\r\npale_green_1b = '←[38;2;175;255;135m'\r\ndark_sea_green_5b = '←[38;2;175;255;175m'\r\ndark_sea_green_5a = '←[38;2;175;255;215m'\r\npale_turquoise_1 = '←[38;2;175;255;255m'\r\nred_3b = '←[38;2;215;0;0m'\r\ndeep_pink_3a = '←[38;2;215;0;95m'\r\ndeep_pink_3b = '←[38;2;215;0;135m'\r\nmagenta_3b = '←[38;2;215;0;175m'\r\nmagenta_3c = '←[38;2;215;0;215m'\r\nmagenta_2a = '←[38;2;215;0;255m'\r\ndark_orange_3b = '←[38;2;215;95;0m'\r\nindian_red_1b = '←[38;2;215;95;95m'\r\nhot_pink_3b = '←[38;2;215;95;135m'\r\nhot_pink_2 = '←[38;2;215;95;175m'\r\norchid = '←[38;2;215;95;215m'\r\nmedium_orchid_1a = '←[38;2;215;95;255m'\r\norange_3 = '←[38;2;215;135;0m'\r\nlight_salmon_3b = '←[38;2;215;135;95m'\r\nlight_pink_3 = '←[38;2;215;135;135m'\r\npink_3 = '←[38;2;215;135;175m'\r\nplum_3 = '←[38;2;215;135;215m'\r\nviolet = '←[38;2;215;135;255m'\r\ngold_3b = '←[38;2;215;175;0m'\r\nlight_goldenrod_3 = '←[38;2;215;175;95m'\r\ntan = '←[38;2;215;175;135m'\r\nmisty_rose_3 = '←[38;2;215;175;175m'\r\nthistle_3 = '←[38;2;215;175;215m'\r\nplum_2 = '←[38;2;215;175;255m'\r\nyellow_3b = '←[38;2;215;215;0m'\r\nkhaki_3 = '←[38;2;215;215;95m'\r\nlight_goldenrod_2a = '←[38;2;215;215;135m'\r\nlight_yellow_3 = '←[38;2;215;215;175m'\r\ngrey_84 = '←[38;2;215;215;215m'\r\nlight_steel_blue_1 = '←[38;2;215;215;255m'\r\nyellow_2 = '←[38;2;215;255;0m'\r\ndark_olive_green_1a = '←[38;2;215;255;95m'\r\ndark_olive_green_1b = '←[38;2;215;255;135m'\r\ndark_sea_green_1 = '←[38;2;215;255;175m'\r\nhoneydew_2 = '←[38;2;215;255;215m'\r\nlight_cyan_1 = '←[38;2;215;255;255m'\r\nred_1 = '←[38;2;255;0;0m'\r\ndeep_pink_2 = '←[38;2;255;0;95m'\r\ndeep_pink_1a = '←[38;2;255;0;135m'\r\ndeep_pink_1b = '←[38;2;255;0;175m'\r\nmagenta_2b = '←[38;2;255;0;215m'\r\nmagenta_1 = '←[38;2;255;0;255m'\r\norange_red_1 = '←[38;2;255;95;0m'\r\nindian_red_1c = '←[38;2;255;95;95m'\r\nindian_red_1d = '←[38;2;255;95;135m'\r\nhot_pink_1a = '←[38;2;255;95;175m'\r\nhot_pink_1b = '←[38;2;255;95;215m'\r\nmedium_orchid_1b = '←[38;2;255;95;255m'\r\ndark_orange = '←[38;2;255;135;0m'\r\nsalmon_1 = '←[38;2;255;135;95m'\r\nlight_coral = '←[38;2;255;135;135m'\r\npale_violet_red_1 = '←[38;2;255;135;175m'\r\norchid_2 = '←[38;2;255;135;215m'\r\norchid_1 = '←[38;2;255;135;255m'\r\norange_1 = '←[38;2;255;175;0m'\r\nsandy_brown = '←[38;2;255;175;95m'\r\nlight_salmon_1 = '←[38;2;255;175;135m'\r\nlight_pink_1 = '←[38;2;255;175;175m'\r\npink_1 = '←[38;2;255;175;215m'\r\nplum_1 = '←[38;2;255;175;255m'\r\ngold_1 = '←[38;2;255;215;0m'\r\nlight_goldenrod_2b = '←[38;2;255;215;95m'\r\nlight_goldenrod_2c = '←[38;2;255;215;135m'\r\nnavajo_white_1 = '←[38;2;255;215;175m'\r\nmisty_rose1 = '←[38;2;255;215;215m'\r\nthistle_1 = '←[38;2;255;215;255m'\r\nyellow_1 = '←[38;2;255;255;0m'\r\nlight_goldenrod_1 = '←[38;2;255;255;95m'\r\nkhaki_1 = '←[38;2;255;255;135m'\r\nwheat_1 = '←[38;2;255;255;175m'\r\ncornsilk_1 = '←[38;2;255;255;215m'\r\ngrey_100 = '←[38;2;255;255;255m'\r\ngrey_3 = '←[38;2;8;8;8m'\r\ngrey_7 = '←[38;2;18;18;18m'\r\ngrey_11 = '←[38;2;28;28;28m'\r\ngrey_15 = '←[38;2;38;38;38m'\r\ngrey_19 = '←[38;2;48;48;48m'\r\ngrey_23 = '←[38;2;58;58;58m'\r\ngrey_27 = '←[38;2;68;68;68m'\r\ngrey_30 = '←[38;2;78;78;78m'\r\ngrey_35 = '←[38;2;88;88;88m'\r\ngrey_39 = '←[38;2;98;98;98m'\r\ngrey_42 = '←[38;2;108;108;108m'\r\ngrey_46 = '←[38;2;118;118;118m'\r\ngrey_50 = '←[38;2;128;128;128m'\r\ngrey_54 = '←[38;2;138;138;138m'\r\ngrey_58 = '←[38;2;148;148;148m'\r\ngrey_62 = '←[38;2;158;158;158m'\r\ngrey_66 = '←[38;2;168;168;168m'\r\ngrey_70 = '←[38;2;178;178;178m'\r\ngrey_74 = '←[38;2;188;188;188m'\r\ngrey_78 = '←[38;2;198;198;198m'\r\ngrey_82 = '←[38;2;208;208;208m'\r\ngrey_85 = '←[38;2;218;218;218m'\r\ngrey_89 = '←[38;2;228;228;228m'"
}
] | 5
|
logeekical/Inform_ret
|
https://github.com/logeekical/Inform_ret
|
39d5a0655169f5bc89c5b2615bcdddbf3c2ffa1b
|
22af79e72a52d19f9f42d7ff9a21c61f125623d6
|
770d15ead70cbeb47bfadb641bd16efbe5a88c35
|
refs/heads/master
| 2018-01-10T03:24:08.129972
| 2016-01-05T16:53:18
| 2016-01-05T16:53:18
| 48,704,197
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6185818910598755,
"alphanum_fraction": 0.6283618807792664,
"avg_line_length": 17.590909957885742,
"blob_id": "2ffe63d8daf6b04c77d166f1102a08591ac05148",
"content_id": "12c78b969baee8ae84ab12a6e638c7973713a061",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 409,
"license_type": "no_license",
"max_line_length": 60,
"num_lines": 22,
"path": "/inv_idx.py",
"repo_name": "logeekical/Inform_ret",
"src_encoding": "UTF-8",
"text": "from utils.linked_list import LinkedList as LL\nimport os.path as path\n\nwith open(path.realpath('.')+ '/resrc/illiad.txt','r') as f:\n\tcontent = f.read()\nf.closed\n\nprint type(content)\n\ndef getWList():\n\tbuff = ''\n\tresult = []\n\tfor char in content:\n\t\tif char in [' ',',','.']:\n\t\t\tif buff not in result:\n\t\t\t\tresult.append(buff)\n\t\t\tbuff = ''\n\t\telse:\n\t\t\tbuff = buff + char\n\treturn result\n\nprint getWList()[1:300]\n"
},
{
"alpha_fraction": 0.5891148447990417,
"alphanum_fraction": 0.5998803973197937,
"avg_line_length": 19.132530212402344,
"blob_id": "9327676fd3bbd54935c45df4ba5b1124e6da0347",
"content_id": "702caecb8af88349481dfe39c49a661775abd50f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1672,
"license_type": "no_license",
"max_line_length": 66,
"num_lines": 83,
"path": "/utils/char_msort.py",
"repo_name": "logeekical/Inform_ret",
"src_encoding": "UTF-8",
"text": "def greaterThan(A,B):\n\t\"\"\"\n\tCompares two strings in lexicon manner.\n\t\"\"\"\n\ta = len(A)\n\tb = len(B)\n\tcount = 0\n\twhile count < min(a,b) and A[count] == B[count]:\n\t\tcount = count + 1\n\tif count == min(a,b):\n\t\tcount = count - 1\n\tif ord(A[count]) < ord(B[count]):\n\t\treturn False\n\telif ord(A[count]) == ord(B[count]):\n\t\tif a<b:\n\t\t\treturn False\n\t\telse:\n\t\t\treturn True\n\telse:\n\t\treturn True\n\n\n\ndef combine(A, B):\n\t\"\"\"\n\tCombine the sorted arrays in sorted order\n\t\"\"\"\n\tresult = []\n\talen = len(A)\n\tblen = len(B)\n\taidx = 0 \n\tbidx = 0\n\twhile aidx < alen or bidx < blen:\n\t\tif aidx < alen and bidx < blen:\n\t\t\ta = A[aidx]\n\t\t\tb = B[bidx]\n\t\t\tif not greaterThan(a,b):\n\t\t\t\tresult.append(A[aidx])\n\t\t\t\taidx = aidx + 1\n\t\t\telse:\n\t\t\t\tresult.append(B[bidx])\n\t\t\t\tbidx = bidx + 1\n\t\telif aidx < alen and bidx == blen:\n\t\t\tresult.append(A[aidx])\n\t\t\taidx = aidx + 1\n\t\telse:\n\t\t\tresult.append(B[bidx])\n\t\t\tbidx = bidx + 1\n\treturn result\n\ndef cMSort(A, start, end):\n\t\"\"\"\n\tDictionary Sort for Strings.\n\t\"\"\"\n#\tprint 'A : ', A, start, end\n\tmid = (start + end)/2\n#\tprint 'mid : ' , mid\n\tleft = A[start:mid+1]\n#\tprint 'left ', left\n\tright = A[mid+1: end+1]\n#\tprint 'right ' , right\n\tl= len(left)\n\tr = len(right)\n\tif l>1:\n\t\tleft = cMSort(A, start, mid)\n\tif r > 1:\n\t\tright = cMSort(A, mid+1, end)\n\treturn combine(left, right)\n\ndef main():\n\tlst = []\n\tprint \"Please enter the length of the array : \"\n\tl = int(raw_input())\n\tfor i in xrange(l):\n\t\tlst.append(raw_input('Please enter the '+str(i)+'th string : '))\n\tprint cMSort(lst, 0, l-1)\n\n\nprint greaterThan('representation','represent')\nprint greaterThan('present','presence')\nprint greaterThan('aaaaa','ab')\nprint combine(['a','abcd'],['aapleasing','abc'])\nmain()\n\n"
},
{
"alpha_fraction": 0.6198793053627014,
"alphanum_fraction": 0.6275007724761963,
"avg_line_length": 26.86725616455078,
"blob_id": "a064e00d7f4eb35f11e32a93d722b5d3f57683b9",
"content_id": "60e165e5e7cab1977b240ad6a4207c18ad64b106",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3149,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 113,
"path": "/utils/linked_list.py",
"repo_name": "logeekical/Inform_ret",
"src_encoding": "UTF-8",
"text": "class LinkedListNode(object):\n\tdef __init__(self, data):\n\t\tself.data = data\n\t\tself.next = None\n\t\t\nclass LinkedList(object):\n\n\tdef __init__(self):\n\t\tself.first = LinkedListNode(None)\n\t\tself.last = self.first\n\t\tself.size = 0\n\t#Add any Element at a given position(None for the addition of new Node at the end)\n\tdef add(self,data,pos=None):\n\t\tnew_node = LinkedListNode(data)\n\t\tif pos is None:\n\t\t\tif self.size == 0:\n\t\t\t\tself.first.data = data\n\t\t\telse:\n\n\t\t\t\tself.last.next = new_node\n\t\t\t\tself.last = new_node\n\t\telse:\n\t\t\tcurrent_node = self.first\n\t\t\tif pos == 1:\n\t\t\t\tnew_node.next = self.first\n\t\t\t\tself.first = new_node\n\t\t\telse:\n\t\t\t\tfor index in range(1,pos - 1):\n\t\t\t\t\tcurrent_node = current_node.next\n\t\t\t\tnew_node.next = current_node.next\n\t\t\t\tcurrent_node.next = new_node\n\n\t\tself.size += 1\n\n\t#get Data on a particular index\n\tdef getdata(self,index):\n\t\tif index > self.size :\n\t\t\traise IndexError(\"Index cannot be greater than the maximum size : \" + str(self.getSize()))\n\t\tcurrent_node = self.first\n\t\tfor indx in range(index - 1):\n\t\t\tcurrent_node = current_node.next\n\t\tprint current_node.data\n\n\t#Add multiple item by a list or tuple\n\tdef addAll(self,lst):\n\t\tfor item in lst:\n\t\t\tself.add(item)\n\n\t#Get the size of linkedList\n\tdef getSize(self):\n\t\treturn self.size\n\n\t#Print all the elements of LinkedList\n\tdef prnt(self):\n\t\tcurrent_node = self.first\n\t\tfor i in range(self.size):\n if current_node.data == None:\n print \"None\" ,\n else:\n print current_node.data ,\n current_node = current_node.next\n\t#Deleting a node from an index\n\tdef delete(self,index):\n\t\tcurrent = self.first\n\t\tif index == 0:\n\t\t\tself.first = self.first.next\n\t\t\tself.size -= 1\n\t\t\treturn True\n\t\tfor i in range(0,self.size-1):\n\t\t\tif i == index - 1:\n\t\t\t\t#print i,current.data\n\t\t\t\tif current.next.next is not None: #in case of last element\n\t\t\t\t\tcurrent.next = current.next.next #skips the element to be deleted which is current.next\n\t\t\t\t\tself.size -= 1 #Reduce size by 1\n\t\t\t\t\treturn True\n\t\t\t\telse:\n\t\t\t\t\tcurrent.next = None\n\t\t\t\t\tself.last = current\n\t\t\t\t\tself.size -= 1\n\t\t\t\t\treturn True\n\t\t\tcurrent = current.next\n\t\t\t#print \"New size is : \", self.size\n\t\treturn False\n\t#\n\t#Method for deleting an element in the Linked List\n\t#\n\tdef del_node(self,value,occurence=0):\n\t\toccur = 0\n\t\ti = 0\n\t\tk = 0 #Keeps track of number of deletions and thus will maintain the length of loop running.\n\t\tcurrent_node = self.first\n\t\tfor i in range(0, self.size - k):\n #print \"size : \" , self.size\n\t\t\tif current_node.data == value:\n\t\t\t\tprint \"Deleting Node at index \" , i , \" in array \" , self.prnt() ,\"and size\",self.getSize()\n\t\t\t\tself.delete(i-k)\n\t\t\t\tk += 1\n\t\t\t\toccur += 1\n\t\t\tcurrent_node = current_node.next\n\t\t\tif occurence != 0 and occur == occurence:\n\t\t\t\tbreak\n\tdef lookup(self, value):\n\t\t\"\"\" Searches for a particular record and returns index in case it is found else False\"\"\"\n\t\tcurrent = self.first\n\t\tfound = False\n\t\tfor i in range(self.size):\n\t\t\tif current.data == value:\n\t\t\t\tfound = True\n\t\t\t\treturn i\n\t\t\telse :\n\t\t\t\tcurrent = current.next\n\t\tif not found:\n\t\t\treturn -1\n"
}
] | 3
|
Codilis/Image-Recognition
|
https://github.com/Codilis/Image-Recognition
|
b541c0b68b196e9617a61e17a82086624d1f3522
|
5e67323e858a5de32b9a4279db816484734b5b00
|
a8a8b006e541b6c1afe8a3bc94641e0b2224d312
|
refs/heads/master
| 2018-10-25T17:10:18.824009
| 2018-08-29T17:59:01
| 2018-08-29T17:59:01
| 145,569,214
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6230216026306152,
"alphanum_fraction": 0.6633093357086182,
"avg_line_length": 33.64102554321289,
"blob_id": "f70e5bb1f785a001fa4c128257f79c6204c04e6a",
"content_id": "cde2763cdb838211327601fc45d38dfea08856ab",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1390,
"license_type": "permissive",
"max_line_length": 128,
"num_lines": 39,
"path": "/Src/detector.py",
"repo_name": "Codilis/Image-Recognition",
"src_encoding": "UTF-8",
"text": "import cv2\r\nfrom database import Connection\r\n\r\nusername, password = 'username', 'password'\r\nconn = Connection(username, password)\r\nconn.connect()\r\ndata = conn.select_all()\r\nnames_dict = {}\r\nfor ids, name in data:\r\n names_dict[str(ids)] = name\r\nconn.close_connection()\r\n\r\nrecognizer = cv2.face.LBPHFaceRecognizer_create()\r\n\r\nrecognizer.read('trainer/trainer.yml')\r\ncascadePath = \"cascade/haarcascade_frontalface_default.xml\"\r\nfaceCascade = cv2.CascadeClassifier(cascadePath);\r\npath = 'dataSet'\r\n\r\ncam = cv2.VideoCapture(0)\r\n\r\nfontFace = cv2.FONT_HERSHEY_SIMPLEX\r\nfontScale = 1\r\nfontColor = (255, 255, 255)\r\n##width_d, height_d = 720, 720\r\n\r\nwhile True:\r\n ret, im =cam.read()\r\n gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)\r\n faces=faceCascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=6, minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)\r\n for(x,y,w,h) in faces:\r\n## nbr_predicted, conf = recognizer.predict(cv2.resize(gray[y:y+h,x:x+w], (width_d, height_d)))\r\n nbr_predicted, conf = recognizer.predict(gray[y:y+h,x:x+w])\r\n cv2.rectangle(im,(x-50,y-50),(x+w+50,y+h+50),(225,0,0),2)\r\n #print(names_dict[str(nbr_predicted)], str(nbr_predicted)+\"--\"+str(conf))\r\n cv2.putText(im,names_dict[str(nbr_predicted)],\r\n (x,y+h),fontFace , fontScale , fontColor) #Draw the text\r\n cv2.imshow('im',im)\r\n cv2.waitKey(10)\r\n"
},
{
"alpha_fraction": 0.5190989375114441,
"alphanum_fraction": 0.5249755382537842,
"avg_line_length": 30.935483932495117,
"blob_id": "7c2e2e1d5947ea60cc41291dbe8dff3600d55085",
"content_id": "9406e1b52ef993465cac986b72b55f092961d5d3",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2042,
"license_type": "permissive",
"max_line_length": 127,
"num_lines": 62,
"path": "/Src/database.py",
"repo_name": "Codilis/Image-Recognition",
"src_encoding": "UTF-8",
"text": "import mysql.connector\r\nfrom mysql.connector import errorcode\r\n\r\nclass Connection:\r\n def __init__(self, user, password):\r\n self.config = {\r\n 'user': user,\r\n 'password': password,\r\n 'host': '127.0.0.1',\r\n 'raise_on_warnings': False,\r\n }\r\n\r\n def connect(self):\r\n self.cnx = mysql.connector.connect(**self.config) \r\n self.c = self.cnx.cursor()\r\n try:\r\n self.c.execute(\"CREATE DATABASE images\")\r\n except mysql.connector.Error as err:\r\n if err.errno == errorcode.ER_DB_CREATE_EXISTS:\r\n pass\r\n self.c.execute(\"USE images\")\r\n\r\n def create_table(self):\r\n try:\r\n self.c.execute('CREATE TABLE IF NOT EXISTS names (id integer PRIMARY KEY AUTO_INCREMENT, name varchar(50) UNIQUE)')\r\n except mysql.connector.Error as err:\r\n if err.errno == errorcode.ER_TABLE_EXISTS_ERROR:\r\n print(\"Table already exists.\")\r\n else:\r\n print(err.msg)\r\n\r\n def insert_value(self,value):\r\n idd = self.c.lastrowid\r\n data = {'id':idd, 'name':value}\r\n sql = (\"INSERT INTO names (id, name) VALUES (%(id)s, %(name)s)\")\r\n x = 0\r\n try:\r\n self.c.execute(sql, data)\r\n except mysql.connector.Error as err:\r\n if err.errno == errorcode.ER_DUP_ENTRY:\r\n print('name already exist')\r\n x = input('Input 1 to enter more images to dataset ')\r\n self.cnx.commit()\r\n return x\r\n\r\n def select_value(self,value):\r\n sql = (\"SELECT * FROM names where name = %(name)s\")\r\n data = {'name':value}\r\n sel = self.c.execute(sql, data)\r\n data = self.c.fetchall()\r\n ids = data[-1][0]\r\n return ids\r\n\r\n def select_all(self):\r\n sql = (\"SELECT * FROM names\")\r\n sel = self.c.execute(sql)\r\n data = self.c.fetchall()\r\n return data\r\n\r\n def close_connection(self):\r\n self.c.close()\r\n self.cnx.close()\r\n"
},
{
"alpha_fraction": 0.5219605565071106,
"alphanum_fraction": 0.5544239282608032,
"avg_line_length": 31.4255313873291,
"blob_id": "87f55a56213ce54c7accada5eb1118e5ce9de22b",
"content_id": "468e11fa5d17a49ec64981222aa122bceb77a06c",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1571,
"license_type": "permissive",
"max_line_length": 125,
"num_lines": 47,
"path": "/Src/create_dataset.py",
"repo_name": "Codilis/Image-Recognition",
"src_encoding": "UTF-8",
"text": "import cv2\r\nimport os\r\nimport glob\r\nfrom database import Connection\r\n\r\n##===================Connection Establishment=====================================================================\r\nusername, password = 'username', 'password'\r\nconn = Connection(username, password)\r\nconn.connect()\r\nconn.create_table()\r\n\r\nname=input('Enter your name ')\r\nx = conn.insert_value(name)\r\n\r\nids = conn.select_value(name)\r\nconn.close_connection()\r\n##=====================Camera Starts for dataset creation==========================================================\r\n\r\ncam = cv2.VideoCapture(0)\r\ndetector=cv2.CascadeClassifier('cascade/haarcascade_frontalface_default.xml')\r\nif(int(x) == 1):\r\n q = \"dataset/\"+str(ids)+\"*.jpg\"\r\n w = []\r\n for file in glob.glob(q):\r\n w.append(int(file.strip().split('\\\\')[-1].split('.')[1]))\r\n i = sorted(w)[-1]\r\n print(\"i =\",i) \r\nelse:\r\n i=0\r\noffset=50\r\nos.makedirs('dataset', exist_ok=True)\r\nj = i+21\r\nprint(\"j =\",j)\r\nwhile True:\r\n ret, im =cam.read()\r\n gray=cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)\r\n faces=detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=5, minSize=(100, 100), flags=cv2.CASCADE_SCALE_IMAGE)\r\n for(x,y,w,h) in faces:\r\n i=i+1\r\n cv2.imwrite(\"dataSet/\"+str(ids) +'.'+ str(i) + \".jpg\", gray[y-offset:y+h+offset,x-offset:x+w+offset])\r\n cv2.rectangle(im,(x-50,y-50),(x+w+100,y+h+100),(225,0,0),2)\r\n cv2.imshow('im',im[y-offset:y+h+offset,x-offset:x+w+offset])\r\n cv2.waitKey(100)\r\n if i>j:\r\n cam.release()\r\n cv2.destroyAllWindows()\r\n break\r\n"
},
{
"alpha_fraction": 0.800000011920929,
"alphanum_fraction": 0.8091953992843628,
"avg_line_length": 38.54545593261719,
"blob_id": "5a7d464b16ec09baec155321ac3d0320eaeafd68",
"content_id": "261ba216615d5872654909607e82e82ca74174d5",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 435,
"license_type": "permissive",
"max_line_length": 106,
"num_lines": 11,
"path": "/README.md",
"repo_name": "Codilis/Image-Recognition",
"src_encoding": "UTF-8",
"text": "# Image-Recognition\nRecognise the face of a person using a video camera\n\nUsed Python, OpenCV for recognition and MySQL for database management\n\nSoftware Requirements:\n1. Python 3\n2. install opencv-contrib-python using pip\n3. MySQL to Python connector that can be downloaded from https://dev.mysql.com/downloads/connector/python/\n\nAdd Your MySQL username and password in the files detector.py and create_dataset.py before running them.\n"
}
] | 4
|
AjayMudhai/Traffic-Flow-Detection
|
https://github.com/AjayMudhai/Traffic-Flow-Detection
|
8f27d8e031f819d55839340030f257ec15e8da37
|
f017a8502e97b6c120f81c6965df0b7df408147e
|
03fa2e47a2d3c65b1932697ee94db039cc9442d9
|
refs/heads/master
| 2022-12-23T10:56:04.684626
| 2020-08-19T06:28:25
| 2020-08-19T06:28:25
| 288,649,143
| 2
| 1
| null | null | null | null | null |
[
{
"alpha_fraction": 0.739234447479248,
"alphanum_fraction": 0.7488038539886475,
"avg_line_length": 51,
"blob_id": "e1591a651d015214d3567281a8273733cbe4dc1d",
"content_id": "3f41e1da9e4fac047b5e178816b4995987a32ced",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 422,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 8,
"path": "/README.md",
"repo_name": "AjayMudhai/Traffic-Flow-Detection",
"src_encoding": "UTF-8",
"text": "# Traffic-Flow-Detection\n## Using Deep Learning detect Traffic Flow Direction and detect Iif vehicles are going in wrong direction\n\n## Instructions :\n## 1. Download Yolo Weights file and put in model data folder. \n### (wget -P model_data https://pjreddie.com/media/files/yolov3.weights)\n## 2. Insert videos in Video folder and In main.py insert video file path in MainClass ‘video_path’ variable.\n## 3. Run main.py.\n\n\n"
},
{
"alpha_fraction": 0.514510989189148,
"alphanum_fraction": 0.5380571484565735,
"avg_line_length": 29.505016326904297,
"blob_id": "0f1d338f7e7aeef370ede01d5ef8355589cb1a05",
"content_id": "4261eaee7a2af6261d22a3d1dffd6cf28cad5c02",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 9131,
"license_type": "no_license",
"max_line_length": 154,
"num_lines": 299,
"path": "/main.py",
"repo_name": "AjayMudhai/Traffic-Flow-Detection",
"src_encoding": "UTF-8",
"text": "import os\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\nimport cv2\nimport numpy as np\nimport tensorflow as tf\n\nimport time\nimport colorsys\nimport imutils\nfrom moviepy.editor import VideoFileClip\nfrom deep_sort import nn_matching\nfrom deep_sort.detection import Detection\nfrom deep_sort.tracker import Tracker\nfrom deep_sort import generate_detections as gdet\nimport random\nfrom YOLO.utils_class import Utilities\nfrom YOLO.yolo import *\n\n\nclass MainClass:\n def __init__(self):\n self.utils=Utilities()\n self.input_size=416\n self.score_threshold=0.6\n self.iou_threshold=0.45\n self.max_cosine_distance = 0.7\n self.nn_budget = None\n self.times=[]\n \n self.video_path = '/Users/ajaymudhai/Desktop/SL/Videos/NVR_ch1_main_20200207140000_20200207143000.asf' #### Enter video path for video file\n class_name_path=\"model_data/coco/coco.names\"\n self.NUM_CLASS = self.utils.read_class_names(class_name_path)\n self.key_list = list(self.NUM_CLASS.keys()) \n self.val_list = list(self.NUM_CLASS.values())\n self.Track_only=['person','car','bicycle','motorbike','bus','truck']\n\n self.load_yolo()\n self.load_tracker()\n self.load_video()\n\n self.traffic_direction_x=0\n self.traffic_direction_y=0\n self.traffic_movement={}\n self.vehicle_movement={}\n self.diff_x=0\n self.diff_y=0\n \n\n\n\n\n\n \n def load_yolo(self):\n Darknet_weights = \"model_data/yolov3.weights\"\n self.yolo = Create_Yolo(input_size=416)\n self.utils.load_yolo_weights(self.yolo, Darknet_weights)\n\n def load_tracker(self):\n model_filename = '/Users/ajaymudhai/Desktop/SL/model_data/mars1-small128.pb'\n self.encoder = gdet.create_box_encoder(model_filename, batch_size=1)\n metric = nn_matching.NearestNeighborDistanceMetric(\"cosine\",self.max_cosine_distance,self.nn_budget)\n self.tracker = Tracker(metric)\n\n def load_video(self):\n self.vid = cv2.VideoCapture(self.video_path)\n self.width = int(self.vid.get(cv2.CAP_PROP_FRAME_WIDTH))\n self.height = int(self.vid.get(cv2.CAP_PROP_FRAME_HEIGHT))\n self.fps = int(self.vid.get(cv2.CAP_PROP_FPS))\n \n prop = cv2.cv.CV_CAP_PROP_FRAME_COUNT if imutils.is_cv2() \\\n else cv2.CAP_PROP_FRAME_COUNT\n self.totalFrames = int(self.vid.get(prop))\n print('........................................ \\n')\n print('Total Frames in Video : {}'.format(self.totalFrames))\n print('......................................... \\n')\n \n \n\n def detectTrack(self,img):\n \n try:\n original_image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)\n except:\n pass\n\n image_data = self.utils.img_preprocessing(np.copy(original_image))\n image_data = tf.expand_dims(image_data, 0)\n\n\n pred_bbox = self.yolo.predict(image_data)\n \n \n\n \n\n \n pred_bbox = [tf.reshape(x, (-1, tf.shape(x)[-1])) for x in pred_bbox]\n pred_bbox = tf.concat(pred_bbox, axis=0)\n \n\n\n \n bboxes = self.utils.box_postprocessing(pred_bbox, original_image)\n bboxes = self.utils.nms(bboxes)\n \n\n # extract bboxes to boxes (x, y, width, height), scores and names\n boxes, scores, names = [], [], []\n for bbox in bboxes:\n if len(self.Track_only) !=0 and self.NUM_CLASS[int(bbox[5])] in self.Track_only or len(self.Track_only) == 0:\n boxes.append([bbox[0].astype(int), bbox[1].astype(int), bbox[2].astype(int)-bbox[0].astype(int), bbox[3].astype(int)-bbox[1].astype(int)])\n scores.append(bbox[4])\n names.append(self.NUM_CLASS[int(bbox[5])])\n\n boxes = np.array(boxes) \n \n names = np.array(names)\n scores = np.array(scores)\n features = np.array(self.encoder(original_image, boxes))\n \n detections = [Detection(bbox, score, class_name, feature) for bbox, score, class_name, feature in zip(boxes, scores, names, features)]\n self.tracker.predict()\n self.tracker.update(detections)\n\n\n tracked_bboxes = []\n for track in self.tracker.tracks:\n if not track.is_confirmed() or track.time_since_update > 5:\n continue \n bbox = track.to_tlbr() # Get the corrected/predicted bounding box\n class_name = track.get_class() #Get the class name of particular object\n tracking_id = track.track_id # Get the ID for the particular track\n index = self.key_list[self.val_list.index(class_name)] # Get predicted object index by object name\n tracked_bboxes.append(bbox.tolist() + [tracking_id, index]) # Structure data, that we could use it with our draw_bbox function\n\n\n \n self.traffic_flow_direction(tracked_bboxes)\n\n \n image = self.draw_rect(original_image,tracked_bboxes)\n \n\n return image\n\n \n\n \n \n \n def draw_rect(self,image,bboxes): \n \n num_classes = len(self.NUM_CLASS)\n image_h, image_w, _ = image.shape\n for i, bbox in enumerate(bboxes):\n coor = np.array(bbox[:4], dtype=np.int32)\n score = bbox[4]\n class_ind = int(bbox[5])\n bbox_color = (0,255,0)\n bbox_thick = 1\n \n fontScale = 0.75 * bbox_thick\n (x1, y1), (x2, y2) = (coor[0], coor[1]), (coor[2], coor[3])\n\n \n \n\n \n \n\n \n score_str = \" \"+str(score)\n \n\n if(abs(self.diff_x)<2 and abs(self.diff_y)<2):\n bbox_color=(255,255,255)\n\n\n elif(abs(self.diff_x)>abs(self.diff_y)):\n if(self.vehicle_movement[score][2]*self.diff_x>0): ##### To test if vehicle and traffic flow is in same direction\n bbox_color=(0,255,0)\n else:\n bbox_color=(0,0,255)\n else:\n if(self.vehicle_movement[score][3]*self.diff_y>0): ##### To test if vehicle and traffic flow is in same direction\n bbox_color=(0,255,0)\n else:\n bbox_color=(0,0,255)\n\n\n\n \n\n \n\n cv2.rectangle(image, (x1, y1), (x2, y2), bbox_color, bbox_thick*2)\n \n \n \n\n \n \n\n\n\n\n label = \"{}\".format(self.NUM_CLASS[class_ind]) + score_str\n\n \n (text_width, text_height), baseline = cv2.getTextSize(label, cv2.FONT_HERSHEY_COMPLEX_SMALL,\n fontScale, thickness=bbox_thick)\n \n cv2.rectangle(image, (x1, y1), (x1 + text_width, y1 - text_height - baseline), bbox_color, thickness=cv2.FILLED)\n\n \n cv2.putText(image, label, (x1, y1-4), cv2.FONT_HERSHEY_COMPLEX_SMALL,\n fontScale,(255,255,255), bbox_thick, lineType=cv2.LINE_AA)\n \n return image\n\n\n \n def traffic_flow_direction(self,bboxes):\n for i, bbox in enumerate(bboxes):\n \n coor = np.array(bbox[:4], dtype=np.int32)\n (x1, y1), (x2, y2) = (coor[0], coor[1]), (coor[2], coor[3])\n center_x=(x1+x2)/2\n center_y=(y1+y2)/2\n score = bbox[4]\n if (score not in self.vehicle_movement):\n \n self.vehicle_movement[score]=[center_x,center_y,0,0]\n # print(self.vehicle_movement)\n else:\n\n prev_coor=self.vehicle_movement[score]\n prev_x,prev_y=prev_coor[0],prev_coor[1]\n vehicle_diff_x,vehicle_diff_y=prev_coor[2],prev_coor[3]\n vehicle_diff_x+=center_x-prev_x\n vehicle_diff_y+=center_y-prev_y\n \n self.vehicle_movement[score]=[center_x,center_y,vehicle_diff_x,vehicle_diff_y]\n # print(self.vehicle_movement)\n self.diff_x+=center_x-prev_x\n self.diff_y+=center_y-prev_y\n\n \n\n\n\n\n\n \n \n \n \n\n\n \n\n\n \n \n\n \n \n\n\n \n\n def capture_frame(self):\n result = cv2.VideoWriter('result_test.avi', \n cv2.VideoWriter_fourcc(*'MJPG'), \n 10,(1920,1080)) \n\n frame_count=0\n while frame_count<self.totalFrames:\n ret,frame = self.vid.read()\n \n if ret:\n frame=self.detectTrack(frame)\n frame_count+=1\n percent_comp=(frame_count/self.totalFrames)*100\n result.write(frame)\n # print('Frames Completed : {}/{} {} %'.format(frame_count,self.totalFrames,percent_comp))\n cv2.imshow('frame',frame)\n if cv2.waitKey(25) & 0xFF == ord('q'): \n break\n \n\n\n\n\nif __name__=='__main__':\n main=MainClass()\n main.capture_frame()\n \n\n\n\n\n\n"
}
] | 2
|
frenzymadness/snake-game
|
https://github.com/frenzymadness/snake-game
|
2326aec97964429da2787ce9eb156cfe15549b81
|
dff011bbadb2adf0240f83512002769e17ff6624
|
5846e7f47c2dcbbacd111ade47565eb38f8695db
|
refs/heads/master
| 2021-09-06T02:07:11.111978
| 2018-02-01T15:01:35
| 2018-02-01T15:01:35
| 119,843,169
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4760383367538452,
"alphanum_fraction": 0.48602235317230225,
"avg_line_length": 25.357894897460938,
"blob_id": "f58d15fb0f8c8c48ebce00a2682fbf34614fa27a",
"content_id": "e4bcf11034aacc3aedabab47201415809fde8b60",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2504,
"license_type": "permissive",
"max_line_length": 73,
"num_lines": 95,
"path": "/snake-cli.py",
"repo_name": "frenzymadness/snake-game",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python3\nimport platform\nimport os\nimport sys\nfrom random import randint\n\nCLEAR_COMMAND = 'clear' if platform.system() == 'Linux' else 'cls'\n\nSNAKE_CHAR = 'X'\nFOOD_CHAR = 'O'\nEMPTY_CHAR = ' '\n\nFOOD_LIMIT = 3\n\nPOSSIBLE_MOVES = ['N', 'S', 'W', 'E']\n\n\nclass SnakeGame(object):\n def __init__(self):\n self.snake_position = [(5, 5), (5, 6), (5, 7), (5, 8)]\n self.food_position = []\n self.grid_size = 30\n\n def ask_for_move(self):\n while True:\n move = input('Where to move? {} :'.format(POSSIBLE_MOVES))\n move = move.upper()\n\n if move not in POSSIBLE_MOVES:\n print('Unrecognized answer! Try it again.')\n continue\n else:\n return move\n\n def do_move(self, move):\n head = self.snake_position[-1]\n x, y = head\n if move == 'N':\n x -= 1\n elif move == 'S':\n x += 1\n elif move == 'W':\n y -= 1\n elif move == 'E':\n y += 1\n\n if (x < 0 or y < 0) or (x > self.grid_size - 1 or\n y > self.grid_size - 1):\n print(\"It's not possible to break the limits!\")\n self.game_over()\n elif (x, y) in self.snake_position:\n print(\"It's not possible to eat yourself!\")\n self.game_over()\n\n if (x, y) not in self.food_position:\n self.snake_position = list(self.snake_position[1:])\n else:\n self.food_position.remove((x, y))\n self.snake_position.append((x, y))\n\n def handle_food(self):\n while len(self.food_position) < FOOD_LIMIT:\n self.food_position.append(\n (randint(0, self.grid_size), randint(0, self.grid_size)))\n\n def print_game(self):\n os.system(CLEAR_COMMAND)\n for x in range(self.grid_size):\n for y in range(self.grid_size):\n if (x, y) in self.snake_position:\n print(SNAKE_CHAR, end='')\n elif (x, y) in self.food_position:\n print(FOOD_CHAR, end='')\n else:\n print(EMPTY_CHAR, end='')\n print()\n\n def game_over(self):\n sys.exit(1)\n\n def main(self):\n while True:\n self.handle_food()\n self.print_game()\n move = self.ask_for_move()\n self.do_move(move)\n\n\ndef main():\n game = SnakeGame()\n game.main()\n\n\nif __name__ == '__main__':\n main()\n"
},
{
"alpha_fraction": 0.8135592937469482,
"alphanum_fraction": 0.8135592937469482,
"avg_line_length": 28.5,
"blob_id": "6a30e3c4997226e8225ce905b71566cbfd675b84",
"content_id": "844a46e5bcb26622310fb405957f09cc47b35e70",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 59,
"license_type": "permissive",
"max_line_length": 45,
"num_lines": 2,
"path": "/README.md",
"repo_name": "frenzymadness/snake-game",
"src_encoding": "UTF-8",
"text": "# snake-game\nSimple implementation of snake game in Python\n"
}
] | 2
|
soraxas/ICRA19_Disjointed-RRT
|
https://github.com/soraxas/ICRA19_Disjointed-RRT
|
6325f2edc7ae0adea48e286df7ada79793069ac6
|
57d19d9e0994469a7ebe16eb349e5dcf82769f25
|
f63b48029928739b8240167c034eec331b8b8aa7
|
refs/heads/master
| 2023-08-02T05:31:52.962297
| 2019-04-11T07:32:06
| 2019-04-11T07:32:06
| 407,388,119
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.4759010076522827,
"alphanum_fraction": 0.4897959232330322,
"avg_line_length": 28.716129302978516,
"blob_id": "0d51f2109b828170387cd64aaa566df5e8554067",
"content_id": "ddd5c30071a55118960ded8d596369aa718e4dd7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4606,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 155,
"path": "/kde.py",
"repo_name": "soraxas/ICRA19_Disjointed-RRT",
"src_encoding": "UTF-8",
"text": "import numpy as np\nfrom fastkde import fastKDE\nfrom matplotlib import pyplot as plt\nfrom scipy.stats import gaussian_kde\n\nwidth = 300\nheight = 100\n\n\n\n\n\nclass realtime_kde:\n\n def __init__(self, width, height):\n self.width = width\n self.height = height\n\n # setup coordinates grid for this kde\n self.x, self.y = np.mgrid[0:width+1,0:height+1]\n self.coor_grid = (self.x.ravel(),self.y.ravel())\n self.discret_coordinate = np.array(list(zip(*self.coor_grid)))\n\n # setup plot\n plt.ion()\n _fig, self.ax = plt.subplots(1,1)\n\n # inverse y axis\n axes = plt.gca()\n axes.set_xlim([0,width])\n axes.set_ylim([0,height])\n axes.invert_yaxis()\n\n # dummpy data at init\n empty_points = np.array([0,0])\n empty_points = np.random.rand(2,5) * 10\n kde = gaussian_kde(empty_points)\n # setup plot\n z = kde(self.coor_grid).reshape(*self.x.shape)\n pc = self.ax.pcolor(self.x,self.y,z)\n self.cb = plt.colorbar(pc)\n self.cb.ax.set_ylabel('Probability density')\n\n self.prob = None\n\n plt.show()\n\n def update_kde(self, points):\n myPDF, axes = fastKDE.pdf(points[0],points[1])\n # print(' pdf sum: ',myPDF.sum())\n _a = myPDF\n _b = axes\n # print(myPDF.shape)\n # print(np.array(axes).shape)\n # exit()\n # myPDF /= myPDF.sum()\n\n x,y = axes\n pc = self.ax.pcolor(x,y, myPDF)\n self.cb.on_mappable_changed(pc)\n\n return _a, _b\n\n # kernel density estimate of the PDF\n # print(1)\n # kde = gaussian_kde(points)\n # print(2)\n # # print(dir(kde))\n # # exit()\n # # evaluate the estimated PDF on a grid\n #\n # if self.prob is None:\n # self.prob = kde(self.coor_grid).reshape(*self.x.shape)\n # else:\n # self.prob += kde(self.coor_grid).reshape(*self.x.shape)\n\n print(3)\n # At this point prob is the probability of having an obstacle\n # We want the probability of having free space so we inverse the probability\n # First multiple the probability by the percision of digit we want so we\n # wont loose percision\n # print(self.prob)\n ########################################################################\n # self.prob = 1 - self.prob\n\n ########################################################################\n self.prob /= self.prob.sum()\n print(4)\n # # print(self.prob)\n # self.prob = 1 - self.prob\n # self.prob /= self.prob.sum()\n # ########################################################\n # self.prob = 1 - self.prob\n # self.prob /= self.prob.sum()\n ########################################################################\n # percision = 4\n # self.prob * 10**percision\n # self.prob = 10**(percision+2)-self.prob\n # # make probability sums to one\n # self.prob /= self.prob.sum()\n #\n # if 1:\n # percision = 4\n # self.prob * 10**percision\n # self.prob = 10**(percision+2)-self.prob\n # # make probability sums to one\n # self.prob /= self.prob.sum()\n\n pc = self.ax.pcolor(self.x, self.y, self.prob)\n self.cb.on_mappable_changed(pc)\n print(5)\n\n def get_coor(self):\n \"\"\" Return a coordinate according to kde probability\"\"\"\n print('sums to {}'.format(self.prob.sum()))\n # print(self.discret_coordinate)\n # print(self.discret_coordinate.shape)\n\n # exit()\n # return None05\n # return None\n # print(self.prob)\n # return None\n idx = np.random.choice(len(self.discret_coordinate), p=self.prob.ravel())\n return self.discret_coordinate[idx]\n # return np.random.choice(self.discret_coordinate, p=self.prob.ravel())\n\n#\n#\n#\n\nif __name__ == \"__main__\":\n\n kde = realtime_kde(width, height)\n\n while True:\n points = np.random.rand(2,3)\n # print(points)\n ########################################\n # points = points * 0.1 + 0.5\n ########################################\n # points = [[0.5] * 20]\n # points.append(points)\n # points = np.array([points[0], points[1]])\n # print(points)\n # exit()\n points[0] = points[0] * width\n points[1] = points[1] * height\n\n print('>')\n kde.update_kde(points)\n print(kde.get_coor())\n print('<')\n plt.pause(0.05)\n print('<')\n"
},
{
"alpha_fraction": 0.5683587789535522,
"alphanum_fraction": 0.5786359310150146,
"avg_line_length": 35.078651428222656,
"blob_id": "39b82be0aba59f6f1d02959942d0cb3f3f41b1e1",
"content_id": "87d4100ec73b86ace8b42bcfe6e8070f2e9ef2e0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3211,
"license_type": "no_license",
"max_line_length": 126,
"num_lines": 89,
"path": "/planners/multirrtPlanner.py",
"repo_name": "soraxas/ICRA19_Disjointed-RRT",
"src_encoding": "UTF-8",
"text": "import logging\n\nfrom overrides import overrides\n\nfrom helpers import *\nfrom planners.randomPolicySampler import RandomPolicySampler\nfrom planners.rrdtPlanner import RRdTPlanner, RRdTSampler, Node\n\n############################################################\n## Disjointed Particles Sampler ##\n############################################################\n\nLOGGER = logging.getLogger(__name__)\n\nMAX_NUMBER_NODES = 20000\n\n\n\nclass MultiRRTSampler(RRdTSampler):\n\n @overrides\n def init(self, **kwargs):\n super().init(**kwargs)\n\n self.randomSampler = RandomPolicySampler()\n self.randomSampler.init(**kwargs)\n\n self.particle_root_pos = []\n for p in self.p_manager.particles:\n self.particle_root_pos.append(p.pos.copy())\n\n @overrides\n def get_next_pos(self):\n choice = self.get_random_choice()\n pos = self.randomSampler.get_valid_next_pos()[0]\n return (pos, None,\n None,\n lambda **kwargs: 1,\n lambda **kwargs: 1)\n\n @overrides\n def paint(self, window):\n if self._last_prob is None:\n return\n for i, p in enumerate(self.particle_root_pos):\n self.particles_layer.fill((255, 128, 255, 0))\n # get a transition from green to red\n self.args.env.draw_circle(pos=p, colour=Colour.blue, radius=3, layer=self.particles_layer)\n window.blit(self.particles_layer, (0, 0))\n\n\nclass MultiRRTPlanner(RRdTPlanner):\n\n @overrides\n def run_once(self):\n # Get an sample that is free (not in blocked space)\n _tmp = self.args.sampler.get_valid_next_pos()\n if _tmp is None:\n # we have added a new samples when respawning a local sampler\n return\n rand_pos, parent_tree, last_node, report_success, report_fail = _tmp\n\n # idx = np.random.randint(0, len(self.args.sampler.tree_manager.disjointedTrees))\n # parent_tree = self.args.sampler.tree[idx]\n parent_tree = np.random.choice((self.args.sampler.tree_manager.root, *self.args.sampler.tree_manager.disjointedTrees))\n\n\n ###################33\n idx = self.find_nearest_neighbour_idx(\n rand_pos, parent_tree.poses[:len(parent_tree.nodes)])\n nn = parent_tree.nodes[idx]\n # get an intermediate node according to step-size\n newpos = self.args.env.step_from_to(nn.pos, rand_pos)\n ##########################333333333\n # check if it is free or not ofree\n if not self.args.env.cc.path_is_free(nn.pos, newpos):\n self.args.env.stats.add_invalid(obs=False)\n report_fail(pos=rand_pos, free=False)\n else:\n newnode = Node(newpos)\n self.args.env.stats.add_free()\n self.args.sampler.add_tree_node(newnode.pos)\n report_success(newnode=newnode, pos=newnode.pos)\n ######################\n newnode, nn = self.args.sampler.tree_manager.connect_two_nodes(\n newnode, nn, parent_tree)\n # try to add this newnode to existing trees\n self.args.sampler.tree_manager.add_pos_to_existing_tree(\n newnode, parent_tree)\n"
},
{
"alpha_fraction": 0.7850000262260437,
"alphanum_fraction": 0.7850000262260437,
"avg_line_length": 48.875,
"blob_id": "eebf5c4f666ff6f240d2aa1933500255d7c1c0bc",
"content_id": "2bf6253bf4339c69f00ab699c6d05c963c99be14",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 400,
"license_type": "no_license",
"max_line_length": 243,
"num_lines": 8,
"path": "/README.md",
"repo_name": "soraxas/ICRA19_Disjointed-RRT",
"src_encoding": "UTF-8",
"text": "\n## Benchmarking with other sampler\n\nIn order to keep this repository small, the benchmark dumps had been separated into a different submodule repository. To clone the benchmark dumps that had been previously ran (and processed), simply initialise the submodule and clone it with:\n\n```sh\n# initialise and show progress (since it's relatively slow) of clone\ngit submodule update --init --progress\n```\n"
},
{
"alpha_fraction": 0.8679245114326477,
"alphanum_fraction": 0.8679245114326477,
"avg_line_length": 6.5714287757873535,
"blob_id": "92066d97810ff57c0da1c300ff354a534e6c589a",
"content_id": "a7a1bf1bed15ee0aa4b10429be0618a6f21b42a8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 53,
"license_type": "no_license",
"max_line_length": 10,
"num_lines": 7,
"path": "/requirements.txt",
"repo_name": "soraxas/ICRA19_Disjointed-RRT",
"src_encoding": "UTF-8",
"text": "docopt\npygame\noverrides\nnumpy\nmatplotlib\nscipy\nSALib\n"
}
] | 4
|
Yanis-Mansouri/US-School
|
https://github.com/Yanis-Mansouri/US-School
|
fa766350049a80a1e49f4244ee5cbe915d0d0270
|
597ed28f56beae8ff7349bb07ad159ff5092396a
|
2dead3488b95c1a117cc29270f0e28c81b2173af
|
refs/heads/master
| 2023-05-28T07:09:10.282573
| 2021-06-07T22:56:08
| 2021-06-07T22:56:08
| 373,938,155
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.8181818127632141,
"alphanum_fraction": 0.8333333134651184,
"avg_line_length": 32,
"blob_id": "47ca45c8abab4ac8e605303b07d32671834876f1",
"content_id": "7fcd1813c5e256f64a66b84f4bede377df11120a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "INI",
"length_bytes": 66,
"license_type": "no_license",
"max_line_length": 44,
"num_lines": 2,
"path": "/desktop.ini",
"repo_name": "Yanis-Mansouri/US-School",
"src_encoding": "UTF-8",
"text": "[LocalizedFileNames]\nfalcosun-nebulas.zip=@falcosun-nebulas.zip,0\n"
},
{
"alpha_fraction": 0.5668662786483765,
"alphanum_fraction": 0.589820384979248,
"avg_line_length": 29.83846092224121,
"blob_id": "57e812cb06c8e53cb5bb2be21417673be851d135",
"content_id": "751f155140bdd2bbce33b448df0c836358bee5f2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4008,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 130,
"path": "/Other/d.py",
"repo_name": "Yanis-Mansouri/US-School",
"src_encoding": "UTF-8",
"text": "import pygame\nimport os\nimport random\nimport math\nimport winsound\n# winsound.PlaySound(\"explosion.wav\", winsound.SND_ALIAS)\n\nos.environ['SDL_VIDEO_WINDOW_POS'] = \"%d,%d\" % (0, 30)\nwn = pygame.display.set_mode((1920, 1020))\nclock = pygame.time.Clock()\n\n\nvel = 5\n\nclass Player(pygame.sprite.Sprite):\n def __init__(self, x, y):\n pygame.sprite.Sprite.__init__(self)\n z = random.randint(0, 101)\n if z <= 51:\n self.original_image = pygame.Surface((75,75))\n else:\n self.original_image = pygame.Surface((75,75))\n if z == 41:\n self.original_image = pygame.Surface((75,75))\n self.image = self.original_image\n self.rect = self.image.get_rect(center=(x, y))\n self.direction = pygame.math.Vector2((0, -1))\n self.velocity = 5\n self.position = pygame.math.Vector2(x, y)\n self.x = pygame.math.Vector2(x)\n self.y = pygame.math.Vector2(y)\n self.health = 10\n self.visible = True\n\n\n def point_at(self, x, y):\n self.direction = pygame.math.Vector2(x, y) - self.rect.center\n if self.direction.length() > 0:\n self.direction = self.direction.normalize()\n angle = self.direction.angle_to((0, -1))\n self.image = pygame.transform.rotate(self.original_image, angle)\n self.rect = self.image.get_rect(center=self.rect.center)\n\n def move(self, x, y):\n self.position -= self.direction * y * self.velocity\n self.position += pygame.math.Vector2(-self.direction.y, self.direction.x) * x * self.velocity\n self.rect.center = round(self.position.x), round(self.position.y)\n\n\n def reflect(self, NV):\n self.direction = self.direction.reflect(pygame.math.Vector2(NV))\n\n def update(self):\n self.position += self.direction * self.velocity\n self.rect.center = round(self.position.x), round(self.position.y)\n\n def hit(self, player):\n if self.health > 0:\n self.health -= 1\n else:\n self.visible = False\n distance = math.sqrt(math.pow(player.x - player.x(), 2) + math.pow(player.y - player.y(), 2))\n if distance < 20:\n return True\n\n else:\n return False\n\n\n\n def move(self, x, y, clamp_rect):\n self.position -= self.direction * y * self.velocity\n self.position += pygame.math.Vector2(-self.direction.y, self.direction.x) * x * self.velocity\n self.rect.center = round(self.position.x), round(self.position.y)\n\n if self.rect.left < clamp_rect.left:\n self.rect.left = clamp_rect.left\n self.position.x = self.rect.centerx\n if self.rect.right > clamp_rect.right:\n self.rect.right = clamp_rect.right\n self.position.x = self.rect.centerx\n if self.rect.top < clamp_rect.top:\n self.rect.top = clamp_rect.top\n self.position.y = self.rect.centery\n if self.rect.bottom > clamp_rect.bottom:\n self.rect.bottom = clamp_rect.bottom\n self.position.y = self.rect.centery\n\n class Projectile(object):\n def __init__(self, x, y, radius, color, facing):\n self.x = x\n self.y = y\n self.radius = radius\n self.color = color\n self.facing = facing\n self.vel = 8 * facing\n\n def draw(self, win):\n pygame.draw.circle(win, self.color, (self.x, self.y), self.radius)\n\n\n\n\n\n\nplayer = Player(200, 200)\nall_sprites = pygame.sprite.Group(player)\n\n\nrun = True\nwhile run:\n clock.tick(60)\n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n run = False\n elif event.type == pygame.MOUSEMOTION:\n player.point_at(*event.pos)\n\n pygame.draw.rect(wn, (0, 0, 0), (50, 50, 10000, 100000))\n\n\n\n keys = pygame.key.get_pressed()\n if keys[pygame.K_w] or keys[pygame.K_UP]:\n player.move(0, -1, wn.get_rect())\n\n\n wn.fill((255, 255, 255))\n all_sprites.draw(wn)\n pygame.display.update()"
},
{
"alpha_fraction": 0.48652419447898865,
"alphanum_fraction": 0.5161929726600647,
"avg_line_length": 30.303447723388672,
"blob_id": "a124ec7c8ac2c11ade29f57dc5ec6a8028318216",
"content_id": "3860d39ff0c1aa91b860683a9eb5582704e4670d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 13619,
"license_type": "no_license",
"max_line_length": 394,
"num_lines": 435,
"path": "/main.py",
"repo_name": "Yanis-Mansouri/US-School",
"src_encoding": "UTF-8",
"text": "import pygame\n\n# Import random for random numbers\nimport random\nimport pathlib\npath = pathlib.Path(__file__).parent.absolute()\nprint(path)\n# Import pygame.locals for easier access to key coordinates\n# Updated to conform to flake8 and black standards\nfrom pygame.locals import (\n K_UP,\n K_DOWN,\n K_LEFT,\n K_RIGHT,\n K_ESCAPE,\n KEYDOWN,\n QUIT,\n)\n\n# Define constants for the screen width and height\nSCREEN_WIDTH = 1920//3\nSCREEN_HEIGHT = 1000\nimport time\n\n\nclock = pygame.time.Clock()\n\nclass Particule(pygame.sprite.Sprite):\n def __init__(self,rectBottom,rectLeft):\n import os.path\n num_files = len([f for f in os.listdir(path)if os.path.isfile(os.path.join(path, f))])\n super(Particule, self).__init__()\n self.motion = [pygame.image.load(\"attacks/explosion_1/frame_0.png\"),pygame.image.load(\"attacks/explosion_1/frame_1.png\"),pygame.image.load(\"attacks/explosion_1/frame_2.png\"),pygame.image.load(\"attacks/explosion_1/frame_3.png\"),pygame.image.load(\"attacks/explosion_1/frame_4.png\"),pygame.image.load(\"attacks/explosion_1/frame_5.png\"),pygame.image.load(\"attacks/explosion_1/frame_6.png\")]\n for x in range(num_files):\n pygame.image.load(\"attacks/explosion_1/frame_0.png\")\n \n \n\n self.surf =self.motion[0]\n self.rect = self.surf.get_rect()\n self.rect.bottom = rectBottom\n self.rect.left = rectLeft\n self.cooldown = 100\n self.lastAnimation= 0\n self.animNum = 0\n \n def update(self):\n now = pygame.time.get_ticks()\n if now - self.lastAnimation >= self.cooldown:\n self.lastAnimation = pygame.time.get_ticks()\n \n if 6>=self.animNum :\n \n \n self.surf = self.motion[self.animNum]\n self.animNum += 1\n else:\n self.animNum = 0\n self.kill()\n \n \n \n\n \n\n\n\n\n\nclass Player(pygame.sprite.Sprite):\n def __init__(self):\n super(Player, self).__init__()\n \n self.surf = pygame.image.load(f\"{path}\\Ships\\Ship_1.png\").convert_alpha()\n self.score = 160\n self.rect = self.surf.get_rect()\n self.lastBullet= 0\n self.cooldown = 100\n self.life = 200\n self.maxLife = 200\n\n # Move the sprite based on keypresses\n def update(self,mousePos):\n global running\n self.rect.left = mousePos[0] -75//2\n self.rect.bottom = 900\n # Keep player on the screen\n if self.rect.left < 0:\n self.rect.left = 0\n elif self.rect.right > SCREEN_WIDTH:\n self.rect.right = SCREEN_WIDTH\n\n\n if pygame.sprite.spritecollideany(self, bullet):\n CollidedBullet = pygame.sprite.spritecollideany(self, bullet)\n if CollidedBullet.ally == False:\n\n self.life -= CollidedBullet.damage\n CollidedBullet.kill()\n \n if self.life <= 0:\n self.kill()\n running = False\n self.size = self.surf.get_size()\n \n def fire(self ,mousePos,isSuper ):\n now = pygame.time.get_ticks()\n if now - self.lastBullet >= self.cooldown:\n self.lastBullet = pygame.time.get_ticks()\n bul = Bullet(True,isSuper)\n if isSuper == 1 : \n bul.rect.left = mousePos[0] -21\n elif isSuper ==0 :\n bul.rect.left = mousePos[0] -9\n bullet.add(bul)\n all_sprites.add(bul)\n\nclass Bullet(pygame.sprite.Sprite):\n def __init__(self,ally,isSuper):\n super(Bullet, self).__init__()\n self.ally = ally\n self.super= isSuper\n if self.ally :\n if isSuper == 0 : \n self.surf = pygame.image.load(\"attacks/fire_1/Fire_1_3.png\").convert_alpha()\n self.damage =10\n elif isSuper == 1 :\n self.surf = pygame.image.load(\"attacks/Special_1/Special_1.png\").convert_alpha()\n self.damage = 50\n else:\n if isSuper == 3:\n self.surf = pygame.image.load(\"attacks/Special_2/Special_2.png\").convert_alpha()\n self.damage = 20\n\n \n else:\n self.surf = pygame.image.load(\"attacks/fire_2/Fire_1_3.png\").convert_alpha()\n self.damage = 10\n\n \n self.rect = self.surf.get_rect()\n self.rect.bottom = 860\n self.rect.left = 0\n \n \n \n \n def update(self):\n if self.rect.bottom < 0 or self.rect.bottom > SCREEN_HEIGHT:\n self.kill()\n if self.ally :\n \n self.speed = 5\n self.rect.move_ip(0,-self.speed)\n \n else :\n if self.super == 3:\n self.speed = 10\n self.rect.move_ip(0,self.speed)\n else:\n self.speed = 3\n self.rect.move_ip(0,self.speed)\n\n\nclass Ennemy(pygame.sprite.Sprite):\n def __init__(self,EnemyType):\n super(Ennemy, self).__init__()\n if EnemyType == 1 :\n self.surf = pygame.image.load(\"Enemy/Enemy_1/ship/ship.png\").convert_alpha()\n self.rect = self.surf.get_rect()\n self.rect.left = random.randint(50,590)\n self.maxLife = 100\n self.life = 100\n self.cooldown = 2000\n self.typeEnemy= EnemyType\n self.speed = 1\n elif EnemyType == 2 : \n self.surf = pygame.image.load(\"Enemy/Enemy_2/ship/ship.png\").convert_alpha()\n self.rect = self.surf.get_rect()\n self.rect.left = random.randint(50,590)\n self.maxLife = 40\n self.life = 40\n self.cooldown = 1000\n self.typeEnemy= EnemyType\n self.speed = 2\n elif EnemyType == 3 : \n self.surf = pygame.image.load(\"Enemy/Enemy_3/ship/ship.png\").convert_alpha()\n self.rect = self.surf.get_rect()\n self.rect.left = random.randint(50,590)\n self.maxLife = 20\n self.life = 20\n self.cooldown = 1000\n self.typeEnemy= EnemyType\n self.speed = 2\n elif EnemyType == 4 : \n self.surf = pygame.image.load(\"Enemy/Boss_1/ship.png\").convert_alpha()\n self.surf = pygame.transform.scale(self.surf, (int(72*2.5), int(73*2.5)))\n self.rect = self.surf.get_rect()\n self.rect.left = random.randint(0,450)\n self.maxLife = 1500\n self.life = 1500\n self.cooldown = 300\n self.typeEnemy= EnemyType\n self.speed = 2\n self.wall = False\n elif EnemyType == 5 : \n self.surf = pygame.image.load(\"Enemy/Boss_2/ship.png\").convert_alpha()\n self.surf = pygame.transform.scale(self.surf, (int(72*2.5), int(73*2.5)))\n self.rect = self.surf.get_rect()\n self.rect.left = random.randint(0,450)\n self.maxLife = 1500\n self.life = 1500\n self.cooldown = 700\n self.typeEnemy= EnemyType\n self.speed = 2\n self.wall = False\n \n self.lastBullet = 0\n \n self.rect.bottom = -100\n \n \n \n def fire(self):\n now = pygame.time.get_ticks()\n if now - self.lastBullet >= self.cooldown:\n self.lastBullet = pygame.time.get_ticks()\n \n if self.typeEnemy == 1 :\n bul = Bullet(False, 0)\n bul.rect.left = self.rect.left +45\n elif self.typeEnemy == 2 :\n bul = Bullet(False, 0)\n bul.rect.left = self.rect.left +20\n elif self.typeEnemy == 3 :\n bul = Bullet(False, 0)\n bul.rect.left = self.rect.left +20\n elif self.typeEnemy == 4 :\n bul = Bullet(False, 0)\n bul.rect.left = self.rect.left +85\n elif self.typeEnemy == 5 :\n bul = Bullet(False, 3)\n bul.rect.left = self.rect.left +75\n\n bul.rect.bottom = self.rect.bottom+9\n bullet.add(bul)\n all_sprites.add(bul)\n \n def update(self):\n if self.typeEnemy == 4 or self.typeEnemy == 5 :\n if self.rect.bottom < 350:\n self.rect.move_ip(0,self.speed)\n\n elif self.rect.left < 450 and not(self.wall):\n self.rect.move_ip(self.speed,0)\n elif self.rect.left > 0 :\n self.wall = True\n self.rect.move_ip(-self.speed,0)\n else : \n self.wall = False\n\n \n \n \n \n \n\n self.size = self.surf.get_size()\n pygame.draw.rect(screen, (0,255,0), (self.rect.left , self.rect.bottom -self.size[1] -13,self.size[0] * (self.life / self.maxLife),10))\n self.fire()\n\n else:\n self.rect.move_ip(0,self.speed)\n self.size = self.surf.get_size()\n pygame.draw.rect(screen, (0,255,0), (self.rect.left , self.rect.bottom -self.size[1] -13,self.size[0] * (self.life / self.maxLife),10))\n self.fire()\n #pygame.draw.rect(screen, (0,255,0), (self.rect.left , self.rect.bottom , self.rect.left+1, self.rect.bottom ))\n\n \n \n if pygame.sprite.spritecollideany(self, bullet):\n CollidedBullet = pygame.sprite.spritecollideany(self, bullet)\n if CollidedBullet.ally == True:\n \n self.life -= CollidedBullet.damage\n CollidedBullet.kill()\n if self.life <= 0:\n if self.typeEnemy == 1 :\n player.score += 10\n elif self.typeEnemy == 2 :\n player.score += 5\n elif self.typeEnemy == 3 :\n player.score += 15\n elif self.typeEnemy == 4 or self.typeEnemy == 5:\n player.score += 200\n global combatBoss\n combatBoss = False\n \n par = Particule(self.rect.bottom, self.rect.left)\n particule.add(par)\n all_sprites.add(par)\n self.kill()\n\n\n\n \n\n \n \n \n \n\n \n \n \ndef display():\n pygame.draw.rect(screen, (255,0,0), (20 , SCREEN_HEIGHT - 50, 400, 30))\n pygame.draw.rect(screen, (0,255,0), (20 , SCREEN_HEIGHT - 50, 400* (player.life / player.maxLife), 30))\n\n\n screen.blit(pixelFont.render(\"LIFE\", True, (0,0,255)), (20 , SCREEN_HEIGHT - 85)) \n screen.blit(pixelFont.render(f\"SCORE : {player.score}\" , True, (255,255,255)), (20 , 30)) \n\n\npygame.init()\nscreen = pygame.display.set_mode((SCREEN_WIDTH, SCREEN_HEIGHT))\n\nMapsurf = pygame.image.load(f\"Map/map_3.png\").convert_alpha()\ny = -8192 \ny1 = 0\ndef update():\n global y\n global y1\n global surf\n \n y1 += 5\n y += 5\n screen.blit( Mapsurf,(0,y))\n screen.blit( Mapsurf,(0,y1))\n if y > 8192:\n y = -8190\n if y1 > 8192:\n y1 = -8190\nplayer= Player()\n\n\nbullet = pygame.sprite.Group()\nennemy = pygame.sprite.Group()\nparticule = pygame.sprite.Group()\n\n\n\n\nall_sprites = pygame.sprite.Group()\nall_sprites.add(player)\n\nADDENEMY = pygame.USEREVENT + 1\npygame.time.set_timer(ADDENEMY, 5000)\nADDBOSS = pygame.USEREVENT + 2\npygame.time.set_timer(ADDBOSS, 10000)\npixelFont = pygame.font.Font(\"font/Pixeboy.ttf\", 50)\n\nrunning=True\nmouseIsDown= False\nEIsDown = False\nclock = pygame.time.Clock()\ncombatBoss = False\nk=0\nwhile running:\n #Verifie si l'événement close window a eu lieu\n \n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n running = False\n elif event.type == pygame.MOUSEBUTTONDOWN:\n mouseIsDown = True\n elif event.type == pygame.MOUSEBUTTONUP:\n mouseIsDown = False\n elif event.type == pygame.KEYDOWN:\n if event.key == pygame.K_e:\n EIsDown= True\n elif event.type == pygame.KEYUP:\n if event.key == pygame.K_e:\n EIsDown= False\n \n elif event.type == ADDENEMY :\n \n for i in range(random.randint(1, 5)):\n en = Ennemy(random.randint(1,3))\n ennemy.add(en)\n \n all_sprites.add(en)\n \n elif event.type == ADDBOSS:\n if player.score >= 50:\n if combatBoss == False:\n k+=1\n print(combatBoss)\n combatBoss=True\n if k%2 ==1 :\n n=4\n else: n = 5\n en= Ennemy(n)\n ennemy.add(en) \n all_sprites.add(en)\n \n\n if mouseIsDown == True :\n player.fire(mousePos, 0)\n\n elif EIsDown == True:\n player.fire(mousePos, 1)\n \n \n \n screen.fill((0,0,0))\n pressed_keys = pygame.key.get_pressed()\n mousePos = pygame.mouse.get_pos()\n update()\n player.update(mousePos)\n bullet.update()\n particule.update()\n ennemy.update()\n \n \n \n for entity in all_sprites:\n #mousePos = pygame.mouse.get_pos()\n #screen.blit(entity.surf, (mousePos[0] - 75//2, 900))\n screen.blit(entity.surf, entity.rect)\n \n \n display()\n pygame.display.flip()\n clock.tick(144)\n"
},
{
"alpha_fraction": 0.5770348906517029,
"alphanum_fraction": 0.6148256063461304,
"avg_line_length": 17.62162208557129,
"blob_id": "c7ccd69163668f4f2c671c4f2ac819124f015d82",
"content_id": "9119da42adc8cc8ba03e3dda7aa4106d602f840f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 688,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 37,
"path": "/Other/test.py",
"repo_name": "Yanis-Mansouri/US-School",
"src_encoding": "UTF-8",
"text": "import pygame\nimport sys\nimport pygame.sprite as sprite\n\ntheClock = pygame.time.Clock()\n\nbackground = pygame.image.load('Map/map_3.png')\n\nbackground_size = background.get_size()\nbackground_rect = background.get_rect()\nscreen = pygame.display.set_mode((640,1000))\nw,h = background_size\nx = 0\ny = 0\n\nx1 = 0\ny1 = -h\n\nrunning = True\n\nwhile running:\n \n \n for event in pygame.event.get():\n if event.type == pygame.QUIT:\n running = False\n y1 += 20\n y += 20\n screen.blit(background,(0,y))\n screen.blit(background,(0,y1))\n if y > h:\n y = -h\n if y1 > h:\n y1 = -h\n pygame.display.flip()\n pygame.display.update()\n theClock.tick(144)"
}
] | 4
|
zhangjoto/simplesched
|
https://github.com/zhangjoto/simplesched
|
4427e135390791bd2a8afdfb0e8db969642d7457
|
d403c8d329db092fd0eb855dbfd31b66ba6ec2c5
|
725d7523525e01dc02dbdf5e15ad082927cfc5fe
|
refs/heads/master
| 2020-03-29T13:55:46.060297
| 2019-08-26T11:41:02
| 2019-08-26T11:41:02
| 149,989,357
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6024844646453857,
"alphanum_fraction": 0.6521739363670349,
"avg_line_length": 15.100000381469727,
"blob_id": "8b47b9029d507aa43f3fb0874b15caab93326dcb",
"content_id": "adc8870e7a182442bc6725590efcfc538ffb914e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 161,
"license_type": "no_license",
"max_line_length": 39,
"num_lines": 10,
"path": "/__init__.py",
"repo_name": "zhangjoto/simplesched",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n#\n# Author: Zhang Zhen\n# E-Mail: zhangjoto@gmail.com\n#\n# Create Date: 2018-09-23\n#\n\nfrom .base import BaseScheduler # noqa\nfrom .senders import * # noqa\n"
},
{
"alpha_fraction": 0.8144329786300659,
"alphanum_fraction": 0.8144329786300659,
"avg_line_length": 18.399999618530273,
"blob_id": "856d1f1eef2a4bbdc5908ec4fbf5e3e0c5e09511",
"content_id": "3333e0688abc35047edd3ae503843d4b523231e2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 195,
"license_type": "no_license",
"max_line_length": 43,
"num_lines": 5,
"path": "/README.md",
"repo_name": "zhangjoto/simplesched",
"src_encoding": "UTF-8",
"text": "# simplesched\n\n用于调度小型定时任务、周期任务的库，以标准库内的 sched 库为基础。\n\n目前支持将任务执行结果发送到倍洽 /Rocket.Chat Incoming 机器人。\n"
},
{
"alpha_fraction": 0.6193832755088806,
"alphanum_fraction": 0.6352422833442688,
"avg_line_length": 22.163265228271484,
"blob_id": "cabf84f0f0d2635919f28b1db1fd12df64ef39e2",
"content_id": "4d37de2ab127f15f5be1d683ced3a8df5cb258ca",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1389,
"license_type": "no_license",
"max_line_length": 78,
"num_lines": 49,
"path": "/senders.py",
"repo_name": "zhangjoto/simplesched",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n#\n# Author: Zhang Zhen\n# E-Mail: zhangjoto@gmail.com\n#\n# Create Date: 2018-09-15\n#\n\nimport logging\nfrom enum import Enum\n\nimport requests\n\nlogger = logging.getLogger(__name__)\n\n\nclass NotifyColor(Enum):\n warn = '#ffc000'\n error = '#ff0000'\n\n\nclass BearyChatSender:\n \"\"\"将消息发送到倍洽 Incoming 机器人。\n\n 发送时可以 channel 指定接收消息的讨论组名字，Incoming 机器人的\n WebHook 地址由外部调用者直接设置 self.url 即可。\"\"\"\n def send(self, rcver, pack, color):\n pack = {'channel': rcver, 'text': pack['from'],\n 'attachments': [{'text': pack['text'], 'color': color.value}]}\n resp = requests.post(self.url, json=pack)\n if resp.status_code != 200:\n logger.error(resp.status_code, resp.text)\n\n def warn(self, rcver, pack):\n self.send(rcver, pack, NotifyColor.warn)\n\n def error(self, rcver, pack):\n self.send(rcver, pack, NotifyColor.error)\n\n\nclass RocketChatSender(BearyChatSender):\n \"\"\"将消息发送到 Rocket.Chat Incoming 机器人。\n\n 发送时可以 channel 指定消息的接收者：\n - #channel 发送到指定频道\n - @user 发送到指定用户\n - XXXXXXXXXXXX 发送到指定讨论组，讨论组 ID 需要从管理界面上查询获取。\n\n WebHook 地址由外部调用者直接设置 self.url 即可。\"\"\"\n"
},
{
"alpha_fraction": 0.5331452488899231,
"alphanum_fraction": 0.5514809489250183,
"avg_line_length": 20.484848022460938,
"blob_id": "6c0b6729158081977996285e249722d57a082795",
"content_id": "7b8ebabc631e1fdcefe3aad31c7d6a68e6d7a14c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 709,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 33,
"path": "/utils.py",
"repo_name": "zhangjoto/simplesched",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n#\n# Author: Zhang Zhen\n# E-Mail: zhangjoto@gmail.com\n#\n# Create Date: 2018-09-15\n#\n\nimport datetime\nimport time\n\n\ndef next_time(timetuple):\n now = datetime.datetime.now()\n curtimestr = now.strftime('%H%M%S')\n\n items = [i for i in timetuple if i > curtimestr]\n if items:\n dst = min(items)\n delta = 0\n else:\n dst = min(timetuple)\n delta = 1\n\n t = {j: int(dst[i:i + 2]) for i, j in zip(range(0, len(dst), 2),\n ('hour', 'minute', 'second'))}\n\n day = now.replace(**t) + datetime.timedelta(days=delta)\n return day.timestamp()\n\n\ndef timestamp(secs):\n return time.strftime(\"%Y%m%d%H%M%S\", time.localtime(secs))\n"
},
{
"alpha_fraction": 0.5531716346740723,
"alphanum_fraction": 0.5559701323509216,
"avg_line_length": 29.056074142456055,
"blob_id": "d451e80464401bdf289cf4d3fc8f2d1db3994009",
"content_id": "c19d8691795cade5f52ec34bfab44b72ae0f0f95",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3762,
"license_type": "no_license",
"max_line_length": 78,
"num_lines": 107,
"path": "/base.py",
"repo_name": "zhangjoto/simplesched",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/env python\n#\n# Author: Zhang Zhen\n# E-Mail: zhangjoto@gmail.com\n#\n# Create Date: 2018-09-15\n#\n\nimport importlib\nimport logging\nimport sched\nimport time\n\nimport yaml\n\nfrom . import utils\n\nlogger = logging.getLogger(__name__)\n\n\nclass BaseScheduler:\n \"\"\"执行小型定期任务、周期任务的基本类。\n\n 执行任务时需要的外部资源由名为 context 的 mapper 参数传入，包括但\n 不限于数据库连接等。\n 对外发送任务执行结果则由传入的 sender （实例化）对象执行，该对象应\n 有 send 方法。\n 读取的配置文件格式如 tests/tasks.yml.sample 文件所示。\"\"\"\n # TODO: daemonize\n # TODO: hot reload，两套配置定期切换需要此功能支持\n\n def __init__(self, config_file='tests/tasks.yml.sample', sender=None,\n context=None):\n \"\"\"测试 docstring\"\"\"\n self.conf = self.load_conf(config_file)\n self.scheder = sched.scheduler(time.time, time.sleep)\n self.sender = sender\n self.ctx = context\n\n def load_conf(self, fname):\n with open(fname) as fp:\n conf = yaml.load(fp.read())\n try:\n conf['default']['to']['error']\n except (KeyError, TypeError):\n logger.error('key default->to->error missing.')\n raise SystemExit(1)\n\n # 将配置中的默认属性展开到每个任务，便于使用\n for actor in conf['actors']:\n for key in ('module', 'priority', 'interval'):\n if key not in actor:\n actor[key] = conf['default'][key]\n logger.debug(conf)\n return conf\n\n def one_task_reg(self, task):\n \"\"\"运行任务，并将下次运行的时间注册到待运行队列。\"\"\"\n\n prior = task['priority']\n\n # 每次执行任务之前要将下次任务加入执行队列，以避免运行时间逐渐偏移\n if task['trigger'] == 'interval': # 周期性运行的任务\n interval = task['interval']\n self.scheder.enter(interval, prior, self.one_task_reg, (task,))\n else: # 在指定时间点运行的任务\n nexttime = utils.next_time(task['times'])\n self.scheder.enterabs(nexttime, prior, self.one_task_reg, (task,))\n return self.task_wrapper(task)\n\n def task_no_exception(self, one_task):\n \"\"\"根据配置项加载任务函数。\n\n 使用闭包包装动作函数，目的是捕捉所有异常，避免外部代码质量导致\n 进程退出，并保证发送异常情况通知。\"\"\"\n module_name = one_task['module']\n module = importlib.import_module(module_name)\n action = getattr(module, one_task['program'])\n\n def func(*args):\n try:\n return action(*args)\n except Exception as err:\n logger.exception(err)\n self.sender.error(\n self.conf['default']['to']['error'],\n {'from': self.conf['identifier'],\n 'text': '{} {}'.format(one_task['program'], str(err))})\n return func\n\n def all_task_reg(self):\n for task in self.conf['actors']:\n logger.debug('wrapper action: %s', task['program'])\n task['wrapped'] = self.task_no_exception(task)\n self.one_task_reg(task)\n\n def task_wrapper(self, task):\n pack = task['wrapped'](self.ctx, *task['arguments'])\n if pack:\n pack = {'from': self.conf['identifier'], 'text': pack}\n logger.debug('pack: %s', pack)\n to = task.get('to', self.conf['default']['to']['normal'])\n self.sender.warn(to, pack)\n\n def run(self):\n self.all_task_reg()\n self.scheder.run()\n"
}
] | 5
|
philip-khor/category_encoders
|
https://github.com/philip-khor/category_encoders
|
48b033031821acb099f8aad8a119c24d941aa153
|
f8a00789d09bca26997ebe480c1736cf11abaea6
|
739fdfc647acec0a90b0b1ba7fb4a46191377c87
|
refs/heads/master
| 2022-12-01T02:43:39.844864
| 2020-08-13T03:42:46
| 2020-08-13T03:42:46
| 287,173,650
| 0
| 0
|
BSD-3-Clause
| 2020-08-13T03:39:57
| 2020-08-12T10:28:11
| 2020-07-31T10:47:30
| null |
[
{
"alpha_fraction": 0.6036803126335144,
"alphanum_fraction": 0.6091732978820801,
"avg_line_length": 50.645389556884766,
"blob_id": "e4b92aea2b3079a00d72ebb7e639d4da0fee0a81",
"content_id": "a62efbe8d9fc1f45f760d9e8dc50749c1e37cec1",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7282,
"license_type": "permissive",
"max_line_length": 168,
"num_lines": 141,
"path": "/examples/benchmarking_large/catboost_comparison.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "\"\"\"\nCompare performance of CatBoost internal categorical encoding with our categorical encoding.\nConclusion: CatBoost beats our encoders by large margin.\n\"\"\"\nimport os\n\nimport pandas as pd\nimport numpy as np\nfrom catboost import Pool, cv, CatBoostClassifier\n\nimport category_encoders\nfrom examples.benchmarking_large import arff_loader, csv_loader\nfrom examples.benchmarking_large.util import train_model, train_encoder\n\n# The settings are taken from:\n# Data-driven advice for applying machine learning to bioinformatics problems, Olson et al.\nmodel = CatBoostClassifier(iterations=50, max_depth=3)\n\n# We use Arff datasets on GitHub. But once OpenML loader will be part of scikit-learn:\n# https://github.com/scikit-learn/scikit-learn/pull/11419\n# the plan is to move on OpenML.\n# We ignore datasets without any polynomial feature.\n# We also ignore 'splice.arff', 'anneal.arff', 'anneal.orig.arff' due to high runtime.\n# Datasets sensitive to amount of regularization are:\n# audiology.arff Medium impact (contains missing values)\n# breast.cancer.arff Medium impact\n# bridges.version1.arff Medium impact (contains an ID + missing values)\n# bridges.version2.arff (contains an ID)\n# car.arff\n# colic.arff\n# cylinder.bands.arff Large impact (contains a constant column + almost an ID)\n# flags.arff Large impact\n# heart.c.arff (contains missing values)\n# hepatitis.arff\n# hypothyroid.arff (contains a constant column)\n# kr.vs.kp.arff\n# labor.arff Large impact\n# lymph.arff\n# nursery.arff\n# postoperative.patient.data.arff Large impact (testing AUC is commonly <0.5, see: https://www.openml.org/t/4528)\n# primary.tumor.arff (contains missing values)\n# solar.flare1.arff Medium impact\n# solar.flare2.arff Medium impact\n# soybean.arff Large impact\n# sick.arff\n# spectrometer.arff Medium impact (contains an ID)\n# sponge.arff Large impact\n# tic-tac-toe.arff\n# trains.arff Medium impact (tiny dataset -> with high variance)\ndatasets = [#'audiology.arff',\n 'autos.arff', 'breast.cancer.arff', 'bridges.version1.arff', 'bridges.version2.arff', 'car.arff',\n 'colic.arff', 'credit.a.arff', 'credit.g.arff', 'cylinder.bands.arff', 'flags.arff', 'heart.c.arff', 'heart.h.arff',\n 'hepatitis.arff', 'hypothyroid.arff', 'kr.vs.kp.arff', 'labor.arff', 'lymph.arff', 'mushroom.arff', 'nursery.arff',\n 'postoperative.patient.data.arff', 'primary.tumor.arff', 'sick.arff', 'solar.flare1.arff', 'solar.flare2.arff',\n 'soybean.arff', 'spectrometer.arff', 'sponge.arff', 'tic-tac-toe.arff', 'trains.arff', 'vote.arff', 'vowel.arff']\n\ndatasets = ['carvana.csv', 'erasmus.csv', 'internetusage.csv', 'ipumsla97small.csv', 'kobe.csv', 'pbcseq.csv', 'phpvcoG8S.csv', 'westnile.csv'] # amazon is too large...\n\n\n# We painstakingly initialize each encoder here because that gives us the freedom to initialize the\n# encoders with any setting we want.\nencoders = [ #category_encoders.BackwardDifferenceEncoder(),\n category_encoders.BaseNEncoder(),\n category_encoders.BinaryEncoder(),\n category_encoders.HashingEncoder(),\n # category_encoders.HelmertEncoder(),\n category_encoders.JamesSteinEncoder(),\n category_encoders.LeaveOneOutEncoder(),\n category_encoders.MEstimateEncoder(),\n category_encoders.OneHotEncoder(),\n category_encoders.OrdinalEncoder(),\n # category_encoders.PolynomialEncoder(),\n # category_encoders.SumEncoder(),\n category_encoders.TargetEncoder(),\n category_encoders.WOEEncoder()]\n\nencoders = [category_encoders.TargetEncoder(), category_encoders.JamesSteinEncoder(), category_encoders.WOEEncoder()]\n\n# Initialization\nif os.path.isfile('./output/result.csv'):\n os.remove('./output/result.csv')\n\n# Loop over datasets, then over encoders\nfor dataset_name in datasets:\n # X, y, fold_count = arff_loader.load(dataset_name)\n X, y, fold_count, nominal_columns = csv_loader.load(dataset_name)\n\n # Get indexes (not names) of categorical features\n categorical_indexes = []\n for col in X.select_dtypes(exclude=[np.number]).columns.values:\n for i, col2 in enumerate(X.columns):\n if col == col2:\n categorical_indexes.append(i)\n\n # Simple missing value treatment\n X.fillna(-999, inplace=True)\n\n # Perform cross-validation\n pool = Pool(X, y, categorical_indexes)\n params = {'iterations': 50,\n 'depth': 3,\n 'loss_function': 'Logloss',\n 'eval_metric': 'AUC',\n 'verbose': False}\n scores = cv(pool, params, logging_level='Silent')\n auc = scores.iloc[-1,0]\n\n\n # Log into csv\n result = pd.DataFrame([dataset_name, y.name, 'CatBoost', 'default', model.__class__.__name__, X.shape[1],\n '', '', '', '', '', '', '', auc, '', '', '']).T\n if not os.path.isfile('./output/result.csv'):\n result.to_csv('./output/result.csv',\n header=['dataset', 'target', 'encoder', 'encoder_setting', 'model', 'input_features', 'output_features',\n 'fit_encoder_time', 'score_encoder_time', 'fit_model_time', 'score_model_time', 'test_matthews',\n 'train_matthews', 'test_auc', 'train_auc', 'test_brier', 'train_brier'], index=False)\n else:\n result.to_csv('./output/result.csv', mode='a', header=False, index=False)\n\n # Our encoding\n for encoder in encoders:\n print(\"Encoding:\", dataset_name, y.name, encoder.__class__.__name__)\n folds, fit_encoder_time, score_encoder_time = train_encoder(X, y, fold_count, encoder)\n\n print('Evaluating:', dataset_name, encoder.__class__.__name__, model.__class__.__name__)\n scores, fit_model_time, score_model_time = train_model(folds, model)\n\n # Log into csv\n result = pd.DataFrame([dataset_name, y.name, encoder.__class__.__name__, encoder.__dict__, model.__class__.__name__, X.shape[1],\n folds[0][0].shape[1], fit_encoder_time, score_encoder_time, fit_model_time, score_model_time]\n + list(scores)).T\n if not os.path.isfile('./output/result.csv'):\n result.to_csv('./output/result.csv',\n header=['dataset', 'target', 'encoder', 'encoder_setting', 'model', 'input_features', 'output_features',\n 'fit_encoder_time', 'score_encoder_time', 'fit_model_time', 'score_model_time', 'test_matthews',\n 'train_matthews', 'test_auc', 'train_auc', 'test_brier', 'train_brier'], index=False)\n else:\n result.to_csv('./output/result.csv', mode='a', header=False, index=False)\n\nprint('Finished. The result was stored into ./output/result.csv.')\nprint(result)\n"
},
{
"alpha_fraction": 0.530502200126648,
"alphanum_fraction": 0.583080530166626,
"avg_line_length": 49.28813552856445,
"blob_id": "d3f268be32bef8bd3e5bca25630cc27565b50dca",
"content_id": "f0e45df2968b5d65e2a5b0b1b5137ce0279bc8bf",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2967,
"license_type": "permissive",
"max_line_length": 147,
"num_lines": 59,
"path": "/tests/test_cat_boost.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "import pandas as pd\nimport numpy as np\nfrom unittest import TestCase # or `from unittest import ...` if on Python 3.4+\n\nimport category_encoders as encoders\n\n\nclass TestCatBoostEncoder(TestCase):\n\n def test_catBoost(self):\n X = pd.DataFrame({'col1': ['A', 'B', 'B', 'C', 'A']})\n y = pd.Series([1, 0, 1, 0, 1])\n enc = encoders.CatBoostEncoder()\n obtained = enc.fit_transform(X, y)\n self.assertEqual(list(obtained['col1']), [0.6, 0.6, 0.6/2, 0.6, 1.6/2], 'The nominator is incremented by the prior. The denominator by 1.')\n\n # For testing set, use statistics calculated on all the training data.\n # See: CatBoost: unbiased boosting with categorical features, page 4.\n X_t = pd.DataFrame({'col1': ['B', 'B', 'A']})\n obtained = enc.transform(X_t)\n self.assertEqual(list(obtained['col1']), [1.6/3, 1.6/3, 2.6/3])\n\n def test_catBoost_missing(self):\n X = pd.DataFrame({'col1': ['A', 'B', 'B', 'C', 'A', np.NaN, np.NaN, np.NaN]})\n y = pd.Series([1, 0, 1, 0, 1, 0, 1, 0])\n enc = encoders.CatBoostEncoder(handle_missing='value')\n obtained = enc.fit_transform(X, y)\n self.assertEqual(list(obtained['col1']), [0.5, 0.5, 0.5/2, 0.5, 1.5/2, 0.5, 0.5/2, 1.5/3], 'We treat None as another category.')\n\n X_t = pd.DataFrame({'col1': ['B', 'B', 'A', np.NaN]})\n obtained = enc.transform(X_t)\n self.assertEqual(list(obtained['col1']), [1.5/3, 1.5/3, 2.5/3, 1.5/4])\n\n def test_catBoost_reference(self):\n # The reference is from:\n # https://catboost.ai/docs/concepts/algorithm-main-stages_cat-to-numberic.html\n # paragraph:\n # Transforming categorical features to numerical features in classification\n # as obtained on 17 Aug 2019.\n X = pd.DataFrame({'col1': ['rock', 'indie', 'rock', 'rock', 'pop', 'indie', 'rock']})\n y = pd.Series([0, 0, 1, 1, 1, 0, 0])\n enc = encoders.CatBoostEncoder()\n obtained = enc.fit_transform(X, y)\n prior = 3./7 # Since we do not support prior passing, we replace the prior in the reference = 0.05 with the sample prior = 3/7.\n self.assertEqual(list(obtained['col1']), [prior, prior, prior/2, (1+prior)/3, prior, prior/2, (2+prior)/4])\n\n def test_catBoost_reference2(self):\n # The reference is from:\n # https://www.youtube.com/watch?v=hqYQ8Yj9vB0\n # time:\n # 35:03\n # as obtained on 21 Aug 2019.\n # Note: they have an error at line [smooth 6 4.3 4.1]. It should be [smooth 6 4 4.1 3.9]\n X = pd.DataFrame({'col1': ['fuzzy', 'soft', 'smooth', 'fuzzy', 'smooth', 'soft', 'smooth', 'smooth']})\n y = pd.Series([4, 1, 4, 3, 6, 0, 7, 5])\n enc = encoders.CatBoostEncoder()\n obtained = enc.fit_transform(X, y)\n prior = 30./8\n self.assertEqual(list(obtained['col1']), [prior, prior, prior, (4+prior)/2, (4+prior)/2, (1+prior)/2, (10+prior)/3, (17+prior)/4])\n"
},
{
"alpha_fraction": 0.6470588445663452,
"alphanum_fraction": 0.6470588445663452,
"avg_line_length": 19.399999618530273,
"blob_id": "f79742525ac0dd826c574618b122ef161e575195",
"content_id": "67a27a10602323bd60d9bc075470596d6fad0e43",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "reStructuredText",
"length_bytes": 102,
"license_type": "permissive",
"max_line_length": 60,
"num_lines": 5,
"path": "/docs/source/mestimate.rst",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "M-estimate\n==============\n\n.. autoclass:: category_encoders.m_estimate.MEstimateEncoder\n :members:\n"
},
{
"alpha_fraction": 0.730512261390686,
"alphanum_fraction": 0.730512261390686,
"avg_line_length": 25.41176414489746,
"blob_id": "1dab4fd1df74efc383553104143152011c589ae1",
"content_id": "368281e7c1f36b13a3d9321e673210f0b60f054c",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 449,
"license_type": "permissive",
"max_line_length": 65,
"num_lines": 17,
"path": "/examples/column_transformer_example.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "from examples.source_data.loaders import get_mushroom_data\nfrom sklearn.compose import ColumnTransformer\nfrom category_encoders import TargetEncoder\n\n# get data from the mushroom dataset\nX, y, _ = get_mushroom_data()\n\n# encode the specified columns\nct = ColumnTransformer(\n [\n ('Target encoding', TargetEncoder(), ['bruises', 'odor'])\n ], remainder='passthrough'\n)\nencoded = ct.fit_transform(X=X, y=y)\n\n# show the result\nprint(encoded)\n"
},
{
"alpha_fraction": 0.6603773832321167,
"alphanum_fraction": 0.6603773832321167,
"avg_line_length": 20.200000762939453,
"blob_id": "3d2b2a265fe99e9ffda440c3e8e23f157306ca88",
"content_id": "1629ee7b2f0074c632e8d2549a19200f4f94a3b8",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "reStructuredText",
"length_bytes": 106,
"license_type": "permissive",
"max_line_length": 58,
"num_lines": 5,
"path": "/docs/source/catboost.rst",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "CatBoost Encoder\n==============\n\n.. autoclass:: category_encoders.cat_boost.CatBoostEncoder\n :members:\n"
},
{
"alpha_fraction": 0.478270560503006,
"alphanum_fraction": 0.49387118220329285,
"avg_line_length": 37.02542495727539,
"blob_id": "d139622fb97412bd176d30a334a539123c6a800e",
"content_id": "299468a4339e31a9d2ffb98ff8fd1bebc08dff23",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4487,
"license_type": "permissive",
"max_line_length": 152,
"num_lines": 118,
"path": "/tests/test_wrapper.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport pandas as pd\nfrom unittest import TestCase\nfrom sklearn.model_selection import GroupKFold\n\nimport category_encoders as encoders\nimport tests.helpers as th\nfrom category_encoders.wrapper import PolynomialWrapper, NestedCVWrapper\n\n\nclass TestMultiClassWrapper(TestCase):\n def test_invariance_to_data_types(self):\n x = np.array([\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['a', 'b', 'a'],\n ])\n y = [1, 2, 3, 3, 3, 3]\n wrapper = PolynomialWrapper(encoders.TargetEncoder())\n result = wrapper.fit_transform(x, y)\n th.verify_numeric(result)\n\n x = pd.DataFrame([\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['a', 'b', 'a'],\n ], columns=['f1', 'f2', 'f3'])\n y = ['bee', 'cat', 'dog', 'dog', 'dog', 'dog']\n wrapper = PolynomialWrapper(encoders.TargetEncoder())\n result2 = wrapper.fit_transform(x, y)\n\n self.assertTrue((result.values == result2.values).all(), 'The content should be the same regardless whether we pass Numpy or Pandas data type.')\n\n def test_transform_only_selected(self):\n x = pd.DataFrame([\n ['a', 'b', 'c'],\n ['a', 'a', 'c'],\n ['b', 'a', 'c'],\n ['b', 'c', 'b'],\n ['b', 'b', 'b'],\n ['a', 'b', 'a'],\n ], columns=['f1', 'f2', 'f3'])\n y = ['bee', 'cat', 'dog', 'dog', 'dog', 'dog']\n wrapper = PolynomialWrapper(encoders.LeaveOneOutEncoder(cols=['f2']))\n\n # combination fit() + transform()\n wrapper.fit(x, y)\n result = wrapper.transform(x)\n print(result)\n self.assertEqual(len(result.columns), 4, 'We expect 2 untouched features + f2 target encoded into 2 features')\n\n # directly fit_transform()\n wrapper = PolynomialWrapper(encoders.LeaveOneOutEncoder(cols=['f2']))\n result2 = wrapper.fit_transform(x, y)\n print(result2)\n self.assertEqual(len(result2.columns), 4, 'We expect 2 untouched features + f2 target encoded into 2 features')\n\n # in the case of leave-one-out, we expect different results, because leave-one-out principle\n # is applied only on the training data (to decrease overfitting) while the testing data\n # use the whole statistics (to be as accurate as possible).\n self.assertFalse(result.iloc[0, 3] == result2.iloc[0, 3])\n\n\nclass TestNestedCVWrapper(TestCase):\n def test_train_not_equal_to_valid(self):\n x = np.array([\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['a', 'b', 'a'],\n ['a', 'b', 'a'],\n ])\n y = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3]\n wrapper = NestedCVWrapper(encoders.TargetEncoder(), cv=3)\n result_train, result_valid = wrapper.fit_transform(x, y, X_test=x)\n\n # We would expect result_train != result_valid since result_train has been generated using nested\n # folds and result_valid is generated by fitting the encoder on all of the x & y daya\n self.assertFalse(np.allclose(result_train, result_valid))\n\n\n def test_custom_cv(self):\n x = np.array([\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['a', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'c'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['b', 'b', 'b'],\n ['a', 'b', 'a'],\n ['a', 'b', 'a'],\n ])\n groups = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3]\n y = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3]\n gkfold = GroupKFold(n_splits=3)\n wrapper = NestedCVWrapper(encoders.TargetEncoder(), cv=gkfold)\n result_train, result_valid = wrapper.fit_transform(x, y, X_test=x, groups=groups)\n\n # We would expect result_train != result_valid since result_train has been generated using nested\n # folds and result_valid is generated by fitting the encoder on all of the x & y daya\n self.assertFalse(np.allclose(result_train, result_valid))\n"
},
{
"alpha_fraction": 0.6496326923370361,
"alphanum_fraction": 0.6572979688644409,
"avg_line_length": 31.278350830078125,
"blob_id": "63dd8557759624df27fce0db93d1b0e22d02ac2d",
"content_id": "f4e7bc2075cd35009185bb7b266a3112f9005d8d",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3131,
"license_type": "permissive",
"max_line_length": 144,
"num_lines": 97,
"path": "/examples/benchmarking_cpu/benchmarking_cpu.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "import psutil\nimport time\nimport pandas as pd\nimport numpy as np\nimport multiprocessing\nimport category_encoders as encoders\nimport tests.helpers as th\n\n__author__ = 'LiuShulun'\n\n\n\"\"\"\nRecord the average and peak system-wide CPU utilization during encoder training and scoring.\nThe utilization is reported as a percentage and as such should always be in the range 0..100%.\nE.g.: 50% means half of the logical CPUs are completely utilized in a multi-core device,\nor half of the CPU is utilized in a single-core device.\n\nTODO: Add a time counter to terminate training and scoring after timeout.\n\"\"\"\n\n# sampling rate of cpu utilization, smaller for more accurate\ncpu_sampling_rate = 0.2\n\n# loop times of benchmarking in every encoding, larger for more accurate but longer benchmarking time\nbenchmark_repeat = 3\n\n# sample num of data\ndata_lines = 10000\n\n# benchmarking result format\nresult_cols = ['encoder', 'used_processes', 'X_shape', 'min_time(s)', 'average_time(s)', 'max_cpu_utilization(%)', 'average_cpu_utilization(%)']\nresults = []\ncpu_utilization = multiprocessing.Manager().Queue()\n\n# define data_set\nnp_X = th.create_array(n_rows=data_lines)\nnp_y = np.random.randn(np_X.shape[0]) > 0.5\nX = th.create_dataset(n_rows=data_lines)\nX_t = th.create_dataset(n_rows=int(data_lines / 2), extras=True)\n\ncols = ['unique_str', 'underscore', 'extra', 'none', 'invariant', 321, 'categorical', 'na_categorical']\n\n\ndef get_cpu_utilization():\n \"\"\"\n new process for recording cpu utilization\n record cpu utilization every [cpu_sampling_rate] second & calculate its mean value\n the value is the cpu utilization during every encoding\n \"\"\"\n global cpu_utilization\n psutil.cpu_percent(None)\n while True:\n cpu_utilization.put(psutil.cpu_percent(None))\n time.sleep(cpu_sampling_rate)\n\n\npsutil.cpu_percent(None)\nfor encoder_name in encoders.__all__:\n \"\"\"\n HashingEncoder gets more benchmarking for different max_process\n \"\"\"\n num = multiprocessing.cpu_count() if encoder_name == 'HashingEncoder' else 1\n\n for index in range(num):\n rsl = [encoder_name, index + 1, X.shape]\n\n if encoder_name == 'HashingEncoder':\n enc = encoders.HashingEncoder(max_process=index+1, cols=cols)\n else:\n enc = getattr(encoders, encoder_name)(cols=cols)\n\n t = []\n c = []\n for _ in range(benchmark_repeat):\n start = time.time()\n proc = multiprocessing.Process(target=get_cpu_utilization, args=())\n proc.start()\n enc.fit(X, np_y)\n th.verify_numeric(enc.transform(X_t))\n end = time.time()\n proc.terminate()\n proc.join()\n cost = []\n while not cpu_utilization.empty():\n cost.append(cpu_utilization.get())\n t.append(end - start)\n c.append(np.mean(cost))\n rsl.append(min(t))\n rsl.append(np.mean(t))\n rsl.append(max(c))\n rsl.append(np.mean(c))\n\n results.append(rsl)\n print(rsl)\n\nresult_df = pd.DataFrame(results, columns=result_cols)\nresult_df.to_csv('./output/result.csv')\n"
},
{
"alpha_fraction": 0.695652186870575,
"alphanum_fraction": 0.695652186870575,
"avg_line_length": 24.875,
"blob_id": "ae2e75d1571d9a18716fb092c39acc5cf9becf70",
"content_id": "a977f967a13870f681cc1ca89d0ad9247726ad47",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "reStructuredText",
"length_bytes": 207,
"license_type": "permissive",
"max_line_length": 94,
"num_lines": 8,
"path": "/examples/benchmarking_large/datasets/arff-datasets-master/README.rst",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "=============\nARFF Datasets\n=============\n\nThe collection of ARFF datasets of the Connectionist Artificial Intelligence Laboratory (LIAC)\n- http://inf.ufrgs.br/liac\n\nPull request to add or modify something!\n"
},
{
"alpha_fraction": 0.7239263653755188,
"alphanum_fraction": 0.7239263653755188,
"avg_line_length": 19.5,
"blob_id": "59dd2309e6e981303089723b7e8faa5ca3136406",
"content_id": "084666944f705a48367778a7a3f079bf6ca6fe86",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "reStructuredText",
"length_bytes": 163,
"license_type": "permissive",
"max_line_length": 58,
"num_lines": 8,
"path": "/docs/source/wrapper.rst",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "Wrappers\n========\n\n.. autoclass:: category_encoders.wrapper.PolynomialWrapper\n :members:\n\n.. autoclass:: category_encoders.wrapper.NestedCVWrapper\n :members:"
},
{
"alpha_fraction": 0.6303164958953857,
"alphanum_fraction": 0.6342729926109314,
"avg_line_length": 35.423423767089844,
"blob_id": "038a0eb27aa47c38e9bf506cf90f3dd4e89e02d1",
"content_id": "2806205afa43d08a5ac08318a4010e2dcf9c43c5",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4044,
"license_type": "permissive",
"max_line_length": 140,
"num_lines": 111,
"path": "/examples/benchmarking_large/csv_loader.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "import arff\nimport numpy as np\nimport pandas as pd\nimport requests\n\n\n\"\"\"\nRead data in arff format from URL. \n\nE.g.: csv_loader.load('car.csv')\n\n\"\"\"\ndef load(file_name):\n # Load CSV from file\n df = pd.read_csv('./datasets/article/' + file_name, sep = None, na_values='?')\n\n # Target column estimation\n if 'class' in list(df):\n target = 'class'\n elif 'Class' in list(df):\n target = 'Class'\n elif 'type' in list(df):\n target = 'type'\n elif 'TYPE' in list(df):\n target = 'TYPE'\n elif 'Type' in list(df):\n target = 'Type'\n elif 'symboling' in list(df):\n target = 'symboling'\n elif 'OVERALL_DIAGNOSIS' in list(df):\n target = 'OVERALL_DIAGNOSIS'\n elif 'LRS-class' in list(df):\n target = 'LRS-class'\n elif 'num' in list(df):\n target = 'num'\n elif 'Class_attribute' in list(df):\n target = 'Class_attribute'\n elif 'Contraceptive_method_used' in list(df):\n target = 'Contraceptive_method_used'\n elif 'surgical_lesion' in list(df):\n target = 'surgical_lesion'\n elif 'band_type' in list(df):\n target = 'band_type'\n elif 'Survival_status' in list(df):\n target = 'Survival_status'\n elif 'surgical lesion' in list(df):\n target = 'surgical lesion'\n elif 'decision' in list(df):\n target = 'decision'\n elif 'ACTION' in list(df):\n target = 'ACTION'\n elif 'IsBadBuy' in list(df):\n target = 'IsBadBuy'\n elif 'TEACHER_FIRST_VISIT_FLAG' in list(df):\n target = 'TEACHER_FIRST_VISIT_FLAG'\n elif 'Community' in list(df):\n target = 'Community'\n elif 'shot_made_flag' in list(df):\n target = 'shot_made_flag'\n elif 'presence_of_spiders' in list(df):\n target = 'presence_of_spiders'\n elif 'Delay' in list(df):\n target = 'Delay'\n elif 'WnvPresent' in list(df):\n target = 'WnvPresent'\n elif 'Community Membership_Family' in list(df):\n target = 'Community Membership_Family'\n elif 'sex' in list(df):\n target = 'sex'\n else:\n print('Using the last column...', list(df)[-1])\n target = list(df)[-1]\n\n # Remove rows with a missing target value\n # Justification: They are of no use for strictly supervised learning (semi-supervised learning would still benefit from them)\n df = df.dropna(subset=[target]).reset_index(drop=True)\n\n # Get class metadata\n y_unique, y_inversed = np.unique(df[target], return_inverse=True)\n y_counts = np.bincount(y_inversed)\n\n # Convert the problem into binary classification with {0,1} as class values.\n # Justification: OneHotEncoding and TargetEncoder work only with binary numerical output.\n # Approach: Take a majority class as 1 and the rest as 0.\n majority_class = y_unique[np.argmax(y_counts)]\n df[target] = (df[target]==majority_class).astype('uint8')\n\n # Determine the count of folds that is not going to cause issues.\n # We identify the least common class label and then return min(10, minority_class_count).\n # Justification: If we have only 5 positive samples and 5 negative samples, we can use at best 5 folds with stratified cross-validation.\n y_unique, y_inversed = np.unique(df[target], return_inverse=True)\n y_counts = np.bincount(y_inversed)\n fold_count = min(np.min(y_counts), 10)\n\n # Target/features split. Encoders expect the target to be in pandas.Series and features in pandas.DataFrame.\n y = df.loc[:, target]\n X = df.drop(target, axis=1)\n\n # Estimate, which columns are nominal. If there is no string column in the data, assume that all integers are nominal.\n nominal_columns = [key for key, value in X.dtypes.items() if ('object' in value.name)]\n if len(nominal_columns)==0:\n nominal_columns = [key for key, value in X.dtypes.items() if ('int' in value.name)]\n\n # Data type estimation\n for col in X:\n try:\n X[col] = X[col].astype('float', copy=False)\n except ValueError:\n pass\n\n return X, y, fold_count, nominal_columns\n\n"
},
{
"alpha_fraction": 0.5927940011024475,
"alphanum_fraction": 0.6104690432548523,
"avg_line_length": 34.02381134033203,
"blob_id": "1bde45b9320c70cf4c24c7a659d50506164e8d96",
"content_id": "137649fda0084aaa9c26d99a4b9e3e8d5d95297e",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1471,
"license_type": "permissive",
"max_line_length": 87,
"num_lines": 42,
"path": "/tests/test_helpers.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "import numpy as np\nimport pandas as pd\nfrom unittest import TestCase # or `from unittest import ...` if on Python 3.4+\n\nfrom tests.helpers import verify_numeric\n\n\nclass TestHelpers(TestCase):\n\n def test_is_numeric_pandas(self):\n # Whole numbers, regardless of the byte length, should not raise AssertionError\n X = pd.DataFrame(np.ones([5, 5]), dtype='int32')\n verify_numeric(pd.DataFrame(X))\n\n X = pd.DataFrame(np.ones([5, 5]), dtype='int64')\n verify_numeric(pd.DataFrame(X))\n\n # Strings should raise AssertionError\n X = pd.DataFrame([['a', 'b', 'c'], ['d', 'e', 'f']])\n with self.assertRaises(Exception):\n verify_numeric(pd.DataFrame(X))\n\n def test_is_numeric_numpy(self):\n # Whole numbers, regardless of the byte length, should not raise AssertionError\n X = np.ones([5, 5], dtype='int32')\n verify_numeric(pd.DataFrame(X))\n\n X = np.ones([5, 5], dtype='int64')\n verify_numeric(pd.DataFrame(X))\n\n # Floats\n X = np.ones([5, 5], dtype='float32')\n verify_numeric(pd.DataFrame(X))\n\n X = np.ones([5, 5], dtype='float64')\n verify_numeric(pd.DataFrame(X))\n\n def test_verify_raises_AssertionError_on_categories(self):\n # Categories should raise AssertionError\n X = pd.DataFrame([['a', 'b', 'c'], ['d', 'e', 'f']], dtype='category')\n with self.assertRaises(Exception):\n verify_numeric(pd.DataFrame(X))\n"
},
{
"alpha_fraction": 0.48621323704719543,
"alphanum_fraction": 0.5147058963775635,
"avg_line_length": 31.969696044921875,
"blob_id": "8e12f955758ca91418cd4ab4b8b558f0562d8100",
"content_id": "b52ac43894e28ab71c0770c811305a413d8eed31",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1088,
"license_type": "permissive",
"max_line_length": 96,
"num_lines": 33,
"path": "/tests/test_m_estimate.py",
"repo_name": "philip-khor/category_encoders",
"src_encoding": "UTF-8",
"text": "from unittest import TestCase # or `from unittest import ...` if on Python 3.4+\nimport category_encoders as encoders\n\n\nclass TestMEstimateEncoder(TestCase):\n\n def test_reference_m0(self):\n x = ['A', 'A', 'B', 'B']\n y = [1, 1, 0, 1]\n x_t = ['A', 'B', 'C']\n\n encoder = encoders.MEstimateEncoder(m=0, handle_unknown='value', handle_missing='value')\n encoder.fit(x, y)\n scored = encoder.transform(x_t)\n\n expected = [[1],\n [0.5],\n [3./4.]] # The prior probability\n self.assertEqual(scored.values.tolist(), expected)\n\n def test_reference_m1(self):\n x = ['A', 'A', 'B', 'B']\n y = [1, 1, 0, 1]\n x_t = ['A', 'B', 'C']\n\n encoder = encoders.MEstimateEncoder(m=1, handle_unknown='value', handle_missing='value')\n encoder.fit(x, y)\n scored = encoder.transform(x_t)\n\n expected = [[(2+3./4.)/(2+1)],\n [(1+3./4.)/(2+1)],\n [3./4.]] # The prior probability\n self.assertEqual(scored.values.tolist(), expected)\n"
}
] | 12
|
Paletech35/CHIP-
|
https://github.com/Paletech35/CHIP-
|
c2f82dfef1cb1d9307cc6cbb63ed5f943c4ab40f
|
85ea108b88077a85fb4da3b53c7c5d9b7ec59a76
|
3af09d08ae93492a6fa970a647584854b0956c32
|
refs/heads/master
| 2023-03-25T01:32:04.505219
| 2021-03-22T14:44:38
| 2021-03-22T14:44:38
| 238,701,821
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.3537958562374115,
"alphanum_fraction": 0.4304395318031311,
"avg_line_length": 37.46953582763672,
"blob_id": "88dc8fba61bd64634ca6c3814f3d80f40fc8bab7",
"content_id": "e75a308b4e99368c13736b7420064c08d215238c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 11012,
"license_type": "no_license",
"max_line_length": 214,
"num_lines": 279,
"path": "/CHIP8.py",
"repo_name": "Paletech35/CHIP-",
"src_encoding": "UTF-8",
"text": "import random, pygame, sys\r\nclass CHIP8:\r\n def __init__(self):\r\n pygame.init()\r\n self.keypad = [pygame.K_x, pygame.K_1, pygame.K_2, pygame.K_3, pygame.K_q, pygame.K_w, pygame.K_e, pygame.K_a, pygame.K_s, pygame.K_d, pygame.K_z, pygame.K_c, pygame.K_4, pygame.K_r, pygame.K_f, pygame.K_v]\r\n self.clock = pygame.time.Clock()\r\n self.offColour = (0, 0, 0)\r\n self.onColour = (255, 255, 255)\r\n self.DISPLAYSURF = pygame.display.set_mode((640, 320))\r\n self.memory = [0] * 4096\r\n self.V = [0] * 16\r\n self.opcode = 0x0000\r\n self.IR = 0x000\r\n self.PC = 0x200\r\n self.graphics = [0] * 2048\r\n self.dTimer = 0\r\n self.sTimer = 0\r\n self.stack = [0] * 16\r\n self.SP = 0x0\r\n self.key = [0] * 16\r\n chip8fontset = [\r\n 0xF0, 0x90, 0x90, 0x90, 0xF0, # 0\r\n 0x20, 0x60, 0x20, 0x20, 0x70, # 1\r\n 0xF0, 0x10, 0xF0, 0x80, 0xF0, # 2\r\n 0xF0, 0x10, 0xF0, 0x10, 0xF0, # 3\r\n 0x90, 0x90, 0xF0, 0x10, 0x10, # 4\r\n 0xF0, 0x80, 0xF0, 0x10, 0xF0, # 5\r\n 0xF0, 0x80, 0xF0, 0x90, 0xF0, # 6\r\n 0xF0, 0x10, 0x20, 0x40, 0x40, # 7\r\n 0xF0, 0x90, 0xF0, 0x90, 0xF0, # 8\r\n 0xF0, 0x90, 0xF0, 0x10, 0xF0, # 9\r\n 0xF0, 0x90, 0xF0, 0x90, 0x90, # A\r\n 0xE0, 0x90, 0xE0, 0x90, 0xE0, # B\r\n 0xF0, 0x80, 0x80, 0x80, 0xF0, # C\r\n 0xE0, 0x90, 0x90, 0x90, 0xE0, # D\r\n 0xF0, 0x80, 0xF0, 0x80, 0xF0, # E\r\n 0xF0, 0x80, 0xF0, 0x80, 0x80 # F\r\n ]\r\n for i in range(len(chip8fontset)):\r\n self.memory[i + 0x0] = chip8fontset[i]\r\n def loadProgram(self, program):\r\n for i in range(len(program)):\r\n self.memory[i + 0x200] = program[i]\r\n def updateDisplay(self):\r\n self.DISPLAYSURF.fill(self.offColour)\r\n for i in range(2048):\r\n if self.graphics[i]:\r\n pygame.draw.rect(self.DISPLAYSURF, self.onColour, ((i % 64) * 10, ((i - (i % 64)) // 64) * 10, 10, 10))\r\n pygame.display.update()\r\n def cycle(self):\r\n op1 = self.memory[self.PC]\r\n op2 = self.memory[self.PC + 1]\r\n op1 = op1 << 8\r\n self.opcode = op1 | op2\r\n firstDigit = self.opcode & 0xF000\r\n otherDigits = self.opcode & 0x0FFF\r\n if firstDigit == 0x0000:\r\n if self.opcode == 0x00E0:\r\n self.graphics = [0] * 2048\r\n self.PC += 2\r\n elif self.opcode == 0x00EE:\r\n self.PC = self.stack[self.SP - 1] + 2\r\n self.stack[self.SP] = 0x000\r\n self.SP -= 1\r\n else:\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x1000:\r\n self.PC = otherDigits\r\n \r\n elif firstDigit == 0x2000:\r\n self.stack[self.SP] = self.PC\r\n self.SP += 1\r\n self.PC = otherDigits\r\n \r\n elif firstDigit == 0x3000:\r\n if self.V[(otherDigits & 0x0F00) >> 8] == otherDigits & 0x00FF:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x4000:\r\n if self.V[(otherDigits & 0x0F00) >> 8] != otherDigits & 0x00FF:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n elif firstDigit == 0x5000:\r\n if self.V[(otherDigits & 0x0F00) >> 8] == self.V[(otherDigits & 0x00F0) >> 4]:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x6000:\r\n self.V[(otherDigits & 0x0F00) >> 8] = otherDigits & 0x00FF\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x7000:\r\n self.V[(otherDigits & 0x0F00) >> 8] += otherDigits & 0x00FF\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x8000:\r\n lastDigit = self.opcode & 0x000F\r\n if lastDigit == 0x0000:\r\n self.V[(self.opcode & 0x0F00) >> 8] = self.V[(self.opcode & 0x00F0) >> 4]\r\n elif lastDigit == 0x0001:\r\n self.V[(self.opcode & 0x0F00) >> 8] |= self.V[(self.opcode & 0x00F0) >> 4]\r\n elif lastDigit == 0x0002:\r\n self.V[(self.opcode & 0x0F00) >> 8] &= self.V[(self.opcode & 0x00F0) >> 4]\r\n elif lastDigit == 0x0003:\r\n self.V[(self.opcode & 0x0F00) >> 8] ^= self.V[(self.opcode & 0x00F0) >> 4]\r\n elif lastDigit == 0x0004:\r\n XYsum = self.V[(self.opcode & 0x0F00) >> 8] + self.V[(self.opcode & 0x00F0) >> 4]\r\n if XYsum > 0xFF:\r\n self.V[0xF] = 0x01\r\n else:\r\n self.V[0xF] = 0x00\r\n self.V[(self.opcode & 0x0F00) >> 8] = (XYsum & 0xFF)\r\n elif lastDigit == 0x0005:\r\n XYdif = self.V[(self.opcode & 0x0F00) >> 8] - self.V[(self.opcode & 0x00F0) >> 4]\r\n if XYdif >= 0:\r\n self.V[0xF] = 1\r\n else:\r\n self.V[0xF] = 0\r\n self.V[(self.opcode & 0x0F00) >> 8] = XYdif & 0xFF\r\n elif lastDigit == 0x0006:\r\n self.V[0xF] = (self.V[(otherDigits & 0x0F00) >> 8]) & 0x1\r\n self.V[(otherDigits & 0x0F00) >> 8] = (self.V[(otherDigits & 0x0F00) >> 8] >> 1)\r\n elif lastDigit == 0x0007:\r\n YXdif = self.V[(self.opcode & 0x00F0) >> 4] - self.V[(self.opcode & 0x0F00) >> 8]\r\n self.V[(otherDigits & 0x0F00) >> 8] = YXdif & 0xFF\r\n if YXdif >= 0:\r\n self.V[0xF] = 1\r\n else:\r\n self.V[0xF] = 0\r\n elif lastDigit == 0x000E:\r\n self.V[0xF] = (self.V[(otherDigits & 0x0F00) >> 8]) & 0b10000000\r\n self.V[(otherDigits & 0x0F00) >> 8] = (self.V[(otherDigits & 0x0F00) >> 8]) << 1\r\n self.PC += 2\r\n \r\n elif firstDigit == 0x9000:\r\n if self.V[(otherDigits & 0x0F00) >> 8] != self.V[(otherDigits & 0x00F0) >> 4]:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n \r\n elif firstDigit == 0xA000:\r\n self.IR = otherDigits\r\n self.PC += 2\r\n \r\n elif firstDigit == 0xB000:\r\n self.PC = self.V[0] + otherDigits\r\n \r\n elif firstDigit == 0xC000:\r\n self.V[(otherDigits & 0x0F00) >> 8] = random.randint(-1, 0xFF) & (otherDigits & 0xFF)\r\n self.PC += 2\r\n \r\n elif firstDigit == 0xD000:\r\n posX = self.V[(otherDigits & 0x0F00) >> 8]\r\n posY = self.V[(otherDigits & 0x00F0) >> 4]\r\n spriteHeight = otherDigits & 0xF\r\n flipped = False\r\n for yOff in range(spriteHeight):\r\n row = self.memory[self.IR + yOff]\r\n for xOff in range(8):\r\n #print(posX, posY, xOff, yOff)\r\n #print(posX + xOff + (64 * posY + yOff))\r\n self.graphics[(posX + xOff + (64 * (posY + yOff))) % 2048] ^= (((row & (1 << (7 - xOff))) >> (7 - xOff)))\r\n #print((row & (1 << (7 - xOff))))\r\n #print(1 << 7, 7 - xOff)\r\n if (row & (1 << (7 - xOff))) and not self.graphics[(posX + xOff + (64 * (posY + yOff))) % 2048]:\r\n flipped = True\r\n \r\n if flipped:\r\n self.V[0xF] = 1\r\n else:\r\n self.V[0xF] = 0\r\n self.PC += 2\r\n self.updateDisplay()\r\n \r\n elif firstDigit == 0xE000:\r\n lastDigits = self.opcode & 0xFF\r\n X = self.opcode & 0xF00\r\n X >>= 8\r\n if lastDigits == 0x9E:\r\n if self.key[self.V[X]]:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n if lastDigits == 0xA1:\r\n if not self.key[self.V[X]]:\r\n self.PC += 4\r\n else:\r\n self.PC += 2\r\n \r\n elif firstDigit == 0xF000:\r\n lastDigits = self.opcode & 0xFF\r\n X = self.opcode & 0xF00\r\n X >>= 8\r\n if lastDigits == 0x07:\r\n self.V[X] = self.dTimer\r\n elif lastDigits == 0x0A:\r\n done = False\r\n while not done:\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n elif event.type == pygame.KEYUP:\r\n if event.key in self.keypad:\r\n done = True\r\n self.V[X] = self.keypad.index(event.key)\r\n elif lastDigits == 0x15:\r\n self.dTimer = self.V[X]\r\n elif lastDigits == 0x18:\r\n pass\r\n elif lastDigits == 0x1E:\r\n newI = self.IR + X\r\n if newI > 0xFFF:\r\n newI &= 0xFFF\r\n self.V[0xF] = 1\r\n else:\r\n self.V[0xF] = 0\r\n self.IR = newI\r\n elif lastDigits == 0x29:\r\n self.IR = self.V[X] * 5\r\n elif lastDigits == 0x33:\r\n num = self.V[X]\r\n num100 = num - num % 100\r\n num10 = num - num % 10\r\n num10 -= num100\r\n num1 = num % 10\r\n num100 //= 100\r\n num10 //= 10\r\n self.memory[self.IR] = num100\r\n self.memory[self.IR + 1] = num10\r\n self.memory[self.IR + 2] = num1\r\n elif lastDigits == 0x55:\r\n for i in range(X + 1):\r\n self.memory[self.IR + i] = self.V[i]\r\n elif lastDigits == 0x65:\r\n for i in range(X + 1):\r\n self.V[i] = self.memory[self.IR + i]\r\n \r\n self.PC += 2\r\n #print(self.PC, self.V, hex(self.opcode))\r\n\r\nx = CHIP8()\r\nbyteCode = []\r\nwith open(input(\"Choose a .ch8 file to open\\n>>> \"), mode = \"rb\") as file:\r\n for each in file.readlines():\r\n for byte in each:\r\n byteCode.append(byte)\r\n\r\n#byteCode = [0xF0, 0x29, 0xD0, 0x05]\r\n\r\n#print(len(byteCode))\r\nfor i in range(len(byteCode) // 2):\r\n p1 = byteCode[2 * i]\r\n p1 <<= 8\r\n p2 = byteCode[2 * i + 1]\r\n print(hex(p1 | p2))\r\nx.loadProgram(byteCode)\r\nwhile True:\r\n for event in pygame.event.get():\r\n if event.type == pygame.QUIT:\r\n pygame.quit()\r\n sys.exit()\r\n currKeys = pygame.key.get_pressed()\r\n for each in range(len(x.keypad)):\r\n if currKeys[x.keypad[each]]:\r\n x.key[each] = 1\r\n else:\r\n x.key[each] = 0\r\n x.cycle()\r\n if x.dTimer > 0:\r\n x.dTimer -= 1\r\n if x.sTimer > 0:\r\n x.sTimer -= 1\r\n x.clock.tick(60)\r\n"
},
{
"alpha_fraction": 0.75,
"alphanum_fraction": 0.7653061151504517,
"avg_line_length": 64.33333587646484,
"blob_id": "476c020f0e05d7215fa6b2193b58651d32df339e",
"content_id": "3926c85ca953511c40403c6edb72f046b8bdc6ed",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 196,
"license_type": "no_license",
"max_line_length": 94,
"num_lines": 3,
"path": "/README.md",
"repo_name": "Paletech35/CHIP-",
"src_encoding": "UTF-8",
"text": "# CHIP-\nCHIP8.py is an emulator for the CHIP 8 system, and all the other files are .ch8 files, which\ncontain the code the emulator can run. The file is chosen upon startup by a text input prompt.\n"
}
] | 2
|
Suenweek/some_stuff
|
https://github.com/Suenweek/some_stuff
|
9a40264e9e913b5a8d3401d8df1ebbf654fa39c2
|
c4210016d7a8a71487faa4e5fc42316e1927679f
|
62427844b1c7ae39ec06e15d0f5b7b3e32dd1abf
|
refs/heads/master
| 2017-04-04T14:34:05.220759
| 2017-03-20T16:28:39
| 2017-03-20T16:28:39
| 80,747,081
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5916052460670471,
"alphanum_fraction": 0.604651153087616,
"avg_line_length": 25.313432693481445,
"blob_id": "7fa1d24b8e0ba58f797fbab31907f9cf212d2dda",
"content_id": "5951bb1200a1d1f2ff0f64d6aacd776c4ad83494",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1763,
"license_type": "no_license",
"max_line_length": 69,
"num_lines": 67,
"path": "/md5bf.py",
"repo_name": "Suenweek/some_stuff",
"src_encoding": "UTF-8",
"text": "#! /usr/bin/env python\n\nimport os\nimport hashlib\nimport argparse\nfrom tqdm import tqdm\nfrom itertools import takewhile, repeat\n\n\ndef reverse_md5(md5_sum, path_to_wordlist):\n \"\"\"\n Brute-forces md5 hash sum with given dict\n \"\"\"\n # Checking if wordlist exists\n if not os.path.exists(path_to_wordlist):\n raise ValueError(\"Wordlist not found.\")\n\n # Checking md5_sum length\n if len(md5_sum) != 32:\n raise ValueError(\"Incorrect md5_sum.\")\n\n # Counting amount of lines in wordlist\n lines_amount = rawincount(path_to_wordlist)\n\n # Iterating through wordlist\n with open(path_to_wordlist, \"r\") as wordlist:\n for word in tqdm(wordlist, total=lines_amount):\n # Stripping \\s and \\n\n word = word.strip()\n # Generating md5 sum from word\n word_hash = hashlib.md5(word).hexdigest()\n # Checking if sums match\n if word_hash == md5_sum:\n # Success\n return word\n\n\ndef rawincount(filename):\n \"\"\"\n Counts number of lines in file\n \"\"\"\n f = open(filename, \"r\")\n bufgen = takewhile(\n lambda x: x,\n (f.read(1024*1024) for _ in repeat(None))\n )\n return sum( buf.count(b'\\n') for buf in bufgen )\n\n\nif __name__ == \"__main__\":\n # Parsing command line arguments\n parser = argparse.ArgumentParser()\n parser.add_argument(\n \"md5_sum\",\n help=\"md5 sum to reverse\"\n )\n parser.add_argument(\n \"path_to_wordlist\",\n help=\"path to wordlist to use for brute-force\",\n )\n args = parser.parse_args()\n\n # Getting result\n result = reverse_md5(args.md5_sum, args.path_to_wordlist)\n\n # Printing result\n print result is not None and \"Result: %s\" % result or \"No result\"\n"
},
{
"alpha_fraction": 0.574400007724762,
"alphanum_fraction": 0.576457142829895,
"avg_line_length": 29.172412872314453,
"blob_id": "e5967a267b18ffba1eee45cdab87c2e358691ebe",
"content_id": "2ee3905342134278c87ad139fdbb0bcc5916a5e6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4375,
"license_type": "no_license",
"max_line_length": 76,
"num_lines": 145,
"path": "/prelandator.py",
"repo_name": "Suenweek/some_stuff",
"src_encoding": "UTF-8",
"text": "#! /usr/bin/env python\n\n\nimport os\nimport shutil\nimport bs4\nfrom argparse import ArgumentParser\n\n\nclass Prelandator(object):\n \"\"\"\n Serves for appending/deleting script tag to/from prelandings\n \"\"\"\n def __init__(self, script_url=\"http://track.alfaleads.ru/preland.js\",\n nb=False):\n self.script_url = script_url\n self.nb = nb\n self.comment_text = \" Generated by Prelandator \"\n\n def prelandate(self, filename):\n print(\"Prelandating %s...\" % filename)\n\n # Getting soup\n soup = self.get_soup(filename)\n\n # Checking if not prelandated\n if soup.find(\"script\", src=self.script_url) is not None:\n quit(\"Already prelandated\")\n \n # Finding body tag\n body = soup.find(\"body\")\n if body is None:\n quit(\"No body tag found\")\n\n # Creating new script tag\n script_tag = soup.new_tag(\"script\", type=\"text/javascript\",\n src=self.script_url)\n\n # Appending created tag to the end of body tag\n body.append(script_tag)\n\n # Wrapping script tag with comments\n script_tag.insert_before(bs4.Comment(self.comment_text))\n script_tag.insert_after(bs4.Comment(self.comment_text))\n\n if not self.nb:\n # Making backup\n self.backup(filename)\n\n # Saving results\n self.save_soup(filename, soup.prettify())\n\n def deprelandate(self, filename):\n print(\"Deprelandating %s...\" % filename)\n\n # Getting soup\n soup = self.get_soup(filename)\n\n # Finding script tag\n script_tag = soup.find(\"script\", src=self.script_url)\n\n # Checking if it exists\n if script_tag is None:\n quit(\"No script tag found\")\n\n print(\"Removing script tag...\")\n script_tag.extract()\n\n print(\"Removing comments...\")\n for c in soup.find_all(string=lambda e: isinstance(e, bs4.Comment)):\n if c == self.comment_text:\n c.extract()\n\n if not self.nb:\n # Making backup\n self.backup(filename)\n\n # Saving results\n self.save_soup(filename, soup.prettify())\n\n\n def get_soup(self, filename, parser=\"lxml\"):\n # Getting contents\n contents = self.get_file_contents(filename)\n\n # Checking if successfully got contents\n if contents is None:\n quit(\"Could not get %s contents\" % filename)\n\n # Trying to instantiate and return soup from contents\n try:\n return bs4.BeautifulSoup(contents, parser)\n except bs4.FeatureNotFound as e:\n quit(\"%s\" % e)\n\n def backup(self, filename, number=0):\n \"\"\"\n Copies original file using shutil.\n If backup already exists, increments its number\n \"\"\"\n if not os.path.exists(\"%s.bak_%d\" % (filename, number)):\n try:\n shutil.copy(filename, \"%s.bak_%d\" % (filename, number))\n print(\"Backed up as %s.bak_%d\" % (filename, number))\n except IOError:\n quit(\"Location %s not writable\")\n except Exception as e:\n quit(\"Unexpected error: %s\" % e)\n else:\n self.backup(filename, number + 1)\n\n def get_file_contents(self, filename):\n \"\"\"Just safely reads the file\"\"\"\n if not os.path.exists(filename):\n quit(\"Path %s does not exist\" % filename)\n\n with open(filename, \"r\") as f:\n return f.read()\n\n def save_soup(self, filename, soup):\n \"\"\"Just safely saves given soup as given filename\"\"\"\n print(\"Saving...\")\n with open(filename, \"w\") as f:\n f.write(soup.encode(\"utf-8\"))\n print(\"Saved as %s\" % filename)\n\n\n\nif __name__ == \"__main__\":\n parser = ArgumentParser(description=Prelandator.__doc__)\n parser.add_argument(\"filename\", help=\"name of the file to prelandate\")\n parser.add_argument(\"-d\", dest=\"depr\", action=\"store_true\",\n default=False, help=\"\"\"\n if set, given file will be deprelandated instead\n \"\"\")\n parser.add_argument(\"-nb\", dest=\"nb\", action=\"store_true\",\n default=False, help=\"\"\"if set, no backups will be made\"\"\")\n args = parser.parse_args()\n\n pl = Prelandator(nb=args.nb)\n\n if args.depr:\n pl.deprelandate(args.filename)\n else:\n pl.prelandate(args.filename)\n"
},
{
"alpha_fraction": 0.453494668006897,
"alphanum_fraction": 0.45782914757728577,
"avg_line_length": 28.296297073364258,
"blob_id": "1fb2d89582b5c06c12a2bace211ea3f72fb7c5bf",
"content_id": "174d532c3c1d3f4c14ab9482f1b12cc43f5d53a8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5619,
"license_type": "no_license",
"max_line_length": 98,
"num_lines": 189,
"path": "/cv_response.py",
"repo_name": "Suenweek/some_stuff",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\n\nimport datetime\nfrom pprint import pprint as pp\n\n\nclass ResponseComposer(object):\n \"\"\"\n \"\"\"\n def __init__(self):\n self.week_days = [\n \"Monday\",\n \"Tuesday\",\n \"Wednesday\",\n \"Thursday\",\n \"Friday\",\n \"Saturday\",\n \"Sunday\"\n ]\n self.templates = {\n \"russian\": u\"\"\"\n\nМогу подъехать на собеседование:\n\n в течение текущей недели ({this week days}):\n{this week time}\n\n в течение следующей недели ({next week days}):\n{next week time}\n\n--\n С уважением, Новаторов Роман.\n\n \"\"\",\n\n \"english\": \"\"\"\n\nwill be added later\n \n \"\"\"\n }\n\n def compose(self, lang):\n lang = lang.lower()\n if not lang in self.templates:\n error_message = (\n \"There is currently no templates for %s. \"\n \"But there are for:\\n\" % lang.capitalize()\n )\n for key in self.templates:\n error_message += \"%s\\n\" % key.capitalize()\n raise KeyError(error_message)\n\n raw_data = self.gather_data_from_user_input()\n formatted = self.format_data(raw_data)\n response = self.templates[lang].format(**formatted)\n\n return response\n\n def format_data(self, raw_data):\n data = {}\n\n # Forming weeks dates\n today = datetime.date.today()\n current_week, next_week = map(\n self.get_week_days_from_date,\n [today, today + datetime.timedelta(days=7)]\n )\n data[\"this week days\"] = \"%s-%s\" % (\n current_week[0].strftime(\"%d.%m\"),\n current_week[-1].strftime(\"%d.%m\")\n )\n data[\"next week days\"] = \"%s-%s\" % (\n next_week[0].strftime(\"%d.%m\"),\n next_week[-1].strftime(\"%d.%m\")\n )\n\n def form_time_groups(week):\n \"\"\"\n I am ashamed of this \n \"\"\"\n groups = []\n processed = []\n\n for i, day in enumerate(self.week_days):\n group = {}\n\n if day in processed:\n continue\n processed.append(day)\n\n if day in week:\n free_time = week[day]\n if free_time in group:\n group[free_time].append(day)\n else:\n group[free_time] = [day]\n done = False\n for j in range(i + 1, 7):\n if done:\n break\n another_day = self.week_days[j]\n if another_day in week:\n if week[another_day] == free_time:\n group[free_time].append(another_day)\n processed.append(another_day)\n else:\n done = True\n else:\n done = True\n if group:\n groups.append(group)\n\n return [(tuple(td.items()[0][1]), td.items()[0][0])\n for td in groups]\n\n def format_schedule(time_groups, longest_line=26):\n indent = \" \" * 8\n\n if not time_groups:\n return indent + \".\" * longest_line\n\n schedule = \"\"\n\n for n, (days, time) in enumerate(time_groups):\n last_char = n + 1 == len(time_groups) and \";\" or \",\"\n schedule += (\n indent\n + (\", \".join([d[:3] for d in days]) + \" - \")[:33].ljust(longest_line + 2, \".\")\n + (\" - %s%s\\n\" % (time, last_char))\n )\n\n return schedule\n\n for week_name in [\"this week time\", \"next week time\"]:\n week = raw_data[week_name]\n time_groups = form_time_groups(week)\n schedule = format_schedule(time_groups)\n data[week_name] = schedule\n\n return data\n\n def get_week_days_from_date(self, date):\n \"\"\"\n Forms a list of week days of the week the date belongs to\n \"\"\"\n if not isinstance(date, datetime.date):\n raise TypeError(\"date must be datetime.date isinstance\")\n\n weekday = date.weekday()\n deltas = [i - weekday for i in range(7)]\n week = [date + datetime.timedelta(days=d) for d in deltas]\n\n return week\n\n def gather_data_from_user_input(self):\n raw_data = {}\n\n previous_free_time = \"\"\n for week in [\"this week time\", \"next week time\"]:\n week_dict = {}\n print(\"What about %s?\" % week)\n for day in self.week_days:\n free_time = self.get_user_input(\"Free time on %s?\" % day)\n if free_time == \"-\":\n free_time = previous_free_time\n if free_time:\n week_dict[day] = free_time\n previous_free_time = free_time\n raw_data[week] = week_dict\n\n return raw_data\n\n def get_user_input(self, prompt, longest_line=23):\n \"\"\"\n Gets user's input\n \"\"\"\n if not isinstance(prompt, basestring):\n raise TypeError(\"prompt must be basestring\")\n\n answer = raw_input(prompt.ljust(longest_line) + \" > \")\n\n return answer.decode(\"utf-8\")\n\n\nif __name__ == \"__main__\":\n composer = ResponseComposer()\n response = composer.compose(\"russian\")\n print response\n"
}
] | 3
|
dont-touch-my-guitar/hello-world
|
https://github.com/dont-touch-my-guitar/hello-world
|
31bcaa07e229ac068f5857daa2105b3bc4e857fb
|
6657e49fab0628a88b02bbf9c377736f158a0d36
|
8f839c1656e5267e411426dc9131a736581f1d45
|
refs/heads/master
| 2020-04-05T13:05:34.321598
| 2017-07-05T08:31:15
| 2017-07-05T08:31:15
| 95,077,189
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5669755935668945,
"alphanum_fraction": 0.57413649559021,
"avg_line_length": 28.320987701416016,
"blob_id": "b637822302d59267c3252e5fce59a5c3c26ae370",
"content_id": "42d013c304cb14a77283ca9a19c2b95f43ca5d01",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2374,
"license_type": "no_license",
"max_line_length": 92,
"num_lines": 81,
"path": "/lib.py",
"repo_name": "dont-touch-my-guitar/hello-world",
"src_encoding": "UTF-8",
"text": "import mysql.connector\nfrom mysql.connector import errorcode\nimport time\n\nquery_dict = {\n \"select_all\" : \"SELECT * FROM new_schema.test_table\",\n \"select_by_id\" : \"SELECT * FROM new_schema.test_table WHERE id = {0}\",\n \"insert_data\" : 'INSERT INTO `new_schema`.`test_table`(`data`) VALUES (\"{0}\")'\n}\n\ndef commonSelect (query):\n #print 0\n returnvalue = None\n try:\n cnx = mysql.connector.connect(user='root', password='toor',\n host='127.0.0.1',\n database='new_schema')\n cursor = cnx.cursor()\n\n cursor.execute(query)\n\n returnvalue = list()\n for line in cursor:\n returnvalue.append(line)\n\n cursor.close()\n\n except mysql.connector.Error as err:\n if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:\n print(\"Something is wrong with your user name or password\")\n elif err.errno == errorcode.ER_BAD_DB_ERROR:\n print(\"Database does not exist\")\n else:\n print(err)\n return returnvalue\n\ndef selectAll():\n return commonSelect(query_dict[\"select_all\"])\n\ndef selectByID(id):\n return commonSelect(query_dict[\"select_by_id\"].format(id))\n\ndef insertData(name):\n try:\n cnx = mysql.connector.connect(user='root', password='toor',\n host='127.0.0.1',\n database='new_schema')\n cursor = cnx.cursor()\n\n #name = \"{0}\".format(time.time())\n\n #query = 'INSERT INTO `new_schema`.`test_table`(`data`) VALUES (\"{0}\")'.format(name)\n #s = query_dict[\"insert_data\"]\n\n\n cursor.execute(query_dict[\"insert_data\"].format(name))\n\n cnx.commit()\n cursor.close()\n\n except mysql.connector.Error as err:\n if err.errno == errorcode.ER_ACCESS_DENIED_ERROR:\n print(\"Something is wrong with your user name or password\")\n elif err.errno == errorcode.ER_BAD_DB_ERROR:\n print(\"Database does not exist\")\n else:\n print(err)\n else:\n cnx.close()\n\n\n\nif __name__ == '__main__':\n import argparse\n parser = argparse.ArgumentParser(description='HTTP Server')\n parser.add_argument('id', type=int, help='database id')\n args = parser.parse_args()\n insertData(name = args.id)\n\n\n#print selectByID(args.id)"
}
] | 1
|
brothergomez/luigi
|
https://github.com/brothergomez/luigi
|
12ff188a933abad5853b7bfbfb7a25601f9ce1c9
|
5428dd4a705ffe12e15b223556e0ed5158aaa5a5
|
672f6b29ffcd3c515eb1dccbcb8218a586e0fd5c
|
refs/heads/master
| 2020-03-12T00:34:16.421896
| 2018-04-20T11:27:35
| 2018-04-20T11:27:35
| 130,352,451
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.5102936029434204,
"alphanum_fraction": 0.5165373086929321,
"avg_line_length": 35.025001525878906,
"blob_id": "1bfbd93b57bd324ffdeb415aedf55a5ffd804053",
"content_id": "81b30c0399de8a38efb4f4ab1a3d2e390aa411fc",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5926,
"license_type": "permissive",
"max_line_length": 84,
"num_lines": 160,
"path": "/luigi/contrib/azuredb.py",
"repo_name": "brothergomez/luigi",
"src_encoding": "UTF-8",
"text": "# -*- coding: utf-8 -*-\r\n#\r\n# Copyright 2012-2015 Spotify AB\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless required by applicable law or agreed to in writing, software\r\n# distributed under the License is distributed on an \"AS IS\" BASIS,\r\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\r\n# See the License for the specific language governing permissions and\r\n# limitations under the License.\r\n#\r\n\r\nimport logging\r\n\r\nimport luigi\r\n\r\nlogger = logging.getLogger('luigi-interface')\r\n\r\ntry:\r\n import pypyodbc\r\nexcept ImportError as e:\r\n logger.warning(\r\n \"\"\"\r\n Loading Azure module without the python package pypyodbc. \r\n This will crash at runtime if Azure SQL functionality is used.\r\n \"\"\"\r\n )\r\n\r\n\r\nclass AzureTarget(luigi.Target):\r\n \"\"\"\r\n Target for a resource in Azure database.\r\n This module is primarily derived from mysqldb.py. Much of AzureTarget,\r\n MySqlTarget and PostgresTarget are similar enough to potentially add a\r\n RDBMSTarget abstract base class to rdbms.py that these classes could be\r\n derived from.\r\n \"\"\"\r\n\r\n marker_table = luigi.configuration.get_config().get('azure',\r\n 'marker-table')\r\n\r\n def __init__(self, driver, host, database, user, password, table, update_id):\r\n \"\"\"\r\n Initializes a AzureTarget instance.\r\n\r\n :param host: Azure server address. Usually your_server.database.windows.net\r\n :type host: str\r\n :param database: database name.\r\n :type database: str\r\n :param user: database user\r\n :type user: str\r\n :param password: password for specified user.\r\n :type password: str\r\n :param update_id: an identifier for this data set.\r\n :type update_id: str\r\n \"\"\"\r\n if ':' in host:\r\n self.host, self.port = host.split(':')\r\n self.port = int(self.port)\r\n else:\r\n self.host = host\r\n self.port = 1433\r\n self.driver = '{ODBC Driver 13 for SQL Server}'\r\n self.database = database\r\n self.user = user\r\n self.password = password\r\n self.table = table\r\n self.update_id = update_id\r\n\r\n def touch(self, connection=None):\r\n \"\"\"\r\n Mark this update as complete.\r\n\r\n IMPORTANT, If the marker table doesn't exist,\r\n the connection transaction will be aborted and the connection reset.\r\n Then the marker table will be created.\r\n \"\"\"\r\n self.create_marker_table()\r\n\r\n if connection is None:\r\n connection = self.connect()\r\n\r\n connection.execute_non_query(\r\n \"\"\"IF NOT EXISTS(SELECT 1\r\n FROM {marker_table}\r\n WHERE update_id = %(update_id)s)\r\n INSERT INTO {marker_table} (update_id, target_table)\r\n VALUES (%(update_id)s, %(table)s)\r\n ELSE\r\n UPDATE t\r\n SET target_table = %(table)s\r\n , inserted = GETDATE()\r\n FROM {marker_table} t\r\n WHERE update_id = %(update_id)s\r\n \"\"\".format(marker_table=self.marker_table),\r\n {\"update_id\": self.update_id, \"table\": self.table})\r\n\r\n # make sure update is properly marked\r\n assert self.exists(connection)\r\n\r\n def exists(self, connection=None):\r\n if connection is None:\r\n connection = self.connect()\r\n cursor = connection.cursor()\r\n if not cursor.tables(table=self.marker_table, tableType='TABLE').fetchone():\r\n row = None\r\n else:\r\n try:\r\n row = connection.execute_row(\"\"\"SELECT 1 FROM {marker_table}\r\n WHERE update_id = %s\r\n \"\"\".format(marker_table=self.marker_table),\r\n (self.update_id,))\r\n except pyodbc.Error as e:\r\n raise\r\n\r\n return row is not None\r\n\r\n def connect(self):\r\n \"\"\"\r\n Create a SQL Server connection and return a connection object\r\n \"\"\"\r\n connection = pyodbc.connect('DRIVER='+ self.driver +\r\n ';PORT=1433;SERVER='+ self.host +\r\n ';PORT=1443;DATABASE='+ self.database +\r\n ';UID=' + self.user +\r\n ';PWD=' + self.password)\r\n \r\n return connection\r\n\r\n def create_marker_table(self):\r\n \"\"\"\r\n Create marker table if it doesn't exist.\r\n Use a separate connection since the transaction might have to be reset.\r\n \"\"\"\r\n connection = self.connect()\r\n cursor = connection.cursor()\r\n if cursor.tables(table=self.marker_table, tableType='TABLE').fetchone():\r\n pass\r\n else:\r\n try:\r\n connection.execute(\r\n \"\"\" CREATE TABLE {marker_table} (\r\n id BIGINT NOT NULL IDENTITY(1,1),\r\n update_id VARCHAR(128) NOT NULL,\r\n target_table VARCHAR(128),\r\n inserted DATETIME DEFAULT(GETDATE()),\r\n PRIMARY KEY (update_id)\r\n )\r\n \"\"\"\r\n .format(marker_table=self.marker_table)\r\n )\r\n except pyodbc.Error as e:\r\n raise\r\n cursor.close()\r\n connection.close()\r\n\r\n"
}
] | 1
|
aayushsnepal/hangmandiscord
|
https://github.com/aayushsnepal/hangmandiscord
|
86197d41896b5924a8fc772895bee4f87d3da2f4
|
a350ddf029081e752590565387647653910a398d
|
60d5fa3449ae035d9b8d7d1604027ebb2d786a47
|
refs/heads/main
| 2023-03-20T10:57:29.904982
| 2021-03-13T22:05:40
| 2021-03-13T22:05:40
| 346,986,871
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.37599313259124756,
"alphanum_fraction": 0.38436761498451233,
"avg_line_length": 42.933963775634766,
"blob_id": "650e4a1014d7548c54fffe70862c8df6001c079f",
"content_id": "398f314ef94ac8e7a2472f50c028177e70fe1b7d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4657,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 106,
"path": "/hangman.py",
"repo_name": "aayushsnepal/hangmandiscord",
"src_encoding": "UTF-8",
"text": "async def hangman(message):\n gameOver = False\n channel = message.channel\n user = message.author\n r = RandomWords()\n words = (str(r.get_random_word(maxLength=8))).lower()\n wo = words.lower()\n word = list(words)\n w = \"\"\n for x in word:\n w += x\n wordlength = len(word)\n await channel.send(\"Hangman started by \" + user.mention)\n await channel.send(\"Word is \" + str(wordlength) + \" letters long!\")\n\n attempts = 6\n\n correctguesses = []\n wrongguesses = []\n current = []\n for x in range(0, wordlength * 2 - 1):\n current.append(x)\n\n for x in range(0, wordlength * 2 - 1):\n if x % 2 == 0:\n current[x] = '_'\n else:\n current[x] = ' '\n\n st = \"`\"\n for e in current:\n st += e\n st += '`'\n await channel.send(st)\n while not gameOver and attempts > 0:\n await channel.send(\"Enter a letter: \")\n try:\n guess = await client.wait_for(\"message\", timeout=20)\n if not guess.author.bot:\n if guess.author == message.author and len(guess.content.lower()) != 1 and \\\n guess.content.lower() != \"quit\" and \\\n guess.content.lower() != wo:\n await channel.send(\"One letter at a time.\")\n else:\n if guess.author == message.author:\n if guess.content == \"quit\":\n await channel.send(\"Game exited. The word was `\" + w + \"`\")\n return\n elif guess.content.lower() == wo:\n gameOver = True\n await channel.send(\"You guessed the word! The word was: `\" + w + \"`\")\n elif guess.content.lower() in word and guess.content.lower() not in correctguesses:\n await channel.send(\"A correct letter!\")\n correctguesses.append(guess.content.lower())\n x = 0\n for i in word:\n if i == guess.content.lower():\n current[x * 2] = word[x]\n x += 1\n elif guess.content.lower() in correctguesses:\n await channel.send(\n \"`\" + guess.content.lower() + \"` has already been guessed **correctly**!\")\n elif not gameOver:\n if guess.content.lower() not in wrongguesses:\n wrongguesses.append(guess.content.lower())\n attempts -= 1\n await channel.send(\"Wrong guess. Attempts left: \" + str(attempts))\n elif guess.content.lower() in wrongguesses:\n await channel.send(\n \"`\" + guess.content.lower() + \"` has already been guessed **incorrectly**! Guess again.\")\n if not gameOver:\n st = \"`\"\n for e in current:\n st += e\n st += '`'\n await channel.send(st)\n\n if len(correctguesses) == 0:\n s1 = \"\"\n else:\n s1 = \"`\"\n for a in correctguesses:\n s1 += a\n s1 += \", \"\n s1 = s1[:-2]\n s1 += '`'\n await channel.send(\"Correct guesses: \" + s1)\n if len(wrongguesses) == 0:\n s2 = \"\"\n else:\n s2 = \"`\"\n for a in wrongguesses:\n s2 += a\n s2 += \", \"\n s2 = s2[:-2]\n s2 += '`'\n await channel.send(\"Wrong guesses: \" + s2)\n\n if len(set(word)) == len(correctguesses):\n gameOver = True\n await channel.send(\"You won! The word was: `\" + w + \"`\")\n if attempts == 0:\n await channel.send(\"Out of attempts. The word was: `\" + w + \"`\")\n except:\n await channel.send(\"Timed out! The word was: \" + w)\n gameOver = True\n"
},
{
"alpha_fraction": 0.8222222328186035,
"alphanum_fraction": 0.8222222328186035,
"avg_line_length": 21.5,
"blob_id": "337df86342e152f9906d2bca0b39cbec25189775",
"content_id": "e829530e08abded4ebdca03718c9e651cb763c3d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 45,
"license_type": "no_license",
"max_line_length": 27,
"num_lines": 2,
"path": "/README.md",
"repo_name": "aayushsnepal/hangmandiscord",
"src_encoding": "UTF-8",
"text": "# hangmandiscord\nHangman game for Discord.py\n"
}
] | 2
|
Baakel/contratosexpress
|
https://github.com/Baakel/contratosexpress
|
d0a90bcf0476e05c015114ea1157016f16744e54
|
f58b67215aa2a346f855f37186f927d4f0a5e67d
|
356c63266acb08e74a8a79ae3d6869bef8e1f948
|
refs/heads/master
| 2020-03-13T16:29:37.247626
| 2018-08-30T18:27:18
| 2018-08-30T18:27:18
| 131,199,110
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7196587920188904,
"alphanum_fraction": 0.7250872254371643,
"avg_line_length": 59,
"blob_id": "5f6b4cda01aa6e4eb5f31ea192a3e52e41b2d893",
"content_id": "da91f30861086c9b0cc98f33574dafe85c4f1190",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2603,
"license_type": "no_license",
"max_line_length": 170,
"num_lines": 43,
"path": "/app/auth/forms.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from flask_wtf import FlaskForm, RecaptchaField\nfrom wtforms import StringField, PasswordField, BooleanField, SubmitField\nfrom wtforms.validators import ValidationError, DataRequired, Email, EqualTo, Length\nfrom itsdangerous import URLSafeTimedSerializer\nfrom app.models import User\n\n\nclass LoginForm(FlaskForm):\n username = StringField('Nombre de Usuario', validators=[DataRequired('El campo no puede quedar vacío')])\n password = PasswordField('Contraseña', validators=[DataRequired('El campo no puede quedar vacío')])\n remember_me = BooleanField('Recuérdame')\n submit = SubmitField('Iniciar Sesión')\n\n\nclass RegistrationForm(FlaskForm):\n username = StringField('Nombre de Usuario', validators=[DataRequired('El campo no puede quedar vacío')])\n email = StringField('Correo Electrónico', validators=[DataRequired('El campo no puede quedar vacío'), Email('Por favor intrudocue un correo electrónico válido')])\n password = PasswordField('Contraseña', validators=[DataRequired('El campo no puede quedar vacío'), Length(8, 25, 'La contraseña debe tener entre 8 y 25 caracteres')])\n password2 = PasswordField('Contraseña Nuevamente', validators=[DataRequired('El campo no puede quedar vacío'), EqualTo('password', 'Las contraseñas no son iguales')])\n submit = SubmitField('Registrarse')\n recaptcha = RecaptchaField('Por favor completa el reCAPTCHA correctamente')\n\n def validate_username(self, username):\n user = User.query.filter_by(usuario=username.data).first()\n if user is not None:\n raise ValidationError('Ese nombre de usuario ya existe. Por favor utiliza otro nombre de usuario')\n\n def validate_email(self, email):\n user = User.query.filter_by(correo=email.data).first()\n if user is not None:\n raise ValidationError('Ese correo ya está en uso. Por favor utiliza otro correo electrónico')\n\n\nclass ResetPasswordRequestForm(FlaskForm):\n email = StringField('Email', validators=[DataRequired('El campo no puede quedar vacío'), Email('Por favor introduce un correo electrónico válido')])\n submit = SubmitField('Reestablecer Contraseña')\n\n\nclass ResetPasswordForm(FlaskForm):\n password = PasswordField('Contraseña', validators=[DataRequired('El campo no puede quedar vacío'), Length(8, 25, 'La contraseña debe tener entre 8 y 25 caracteres')])\n password2 = PasswordField('Repite la contraseña', validators=[DataRequired('El campo no puede quedar vacío'),\n EqualTo('password', 'Las contraseñas no son iguales')])\n submit = SubmitField('Reestablecer Contraseña')"
},
{
"alpha_fraction": 0.7209528684616089,
"alphanum_fraction": 0.7243558764457703,
"avg_line_length": 50.45000076293945,
"blob_id": "73442be3aafe2d5dea175c5d808e02d34020cd17",
"content_id": "923e9ed22f37dcf02d39710234ae304577edccf5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2067,
"license_type": "no_license",
"max_line_length": 175,
"num_lines": 40,
"path": "/app/main/forms.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from flask_wtf import FlaskForm\nfrom wtforms import StringField, PasswordField, BooleanField, SubmitField, TextAreaField\nfrom wtforms.validators import DataRequired, Email, EqualTo, ValidationError,Length\nfrom app.models import User\n\n\nclass PdfForm(FlaskForm):\n comprador = StringField(validators=[DataRequired()])\n vendedor = StringField(validators=[DataRequired()])\n\n\nclass EditProfileForm(FlaskForm):\n # usuario = StringField('Nombre de Usuario', validators=[DataRequired()])\n # nombre = StringField('Nombre', validators=[DataRequired()])\n # apellido = StringField('Apellidos', validators=[DataRequired()])\n contra = PasswordField('Contraseña Actual', validators=[DataRequired('El campo no puede quedar vacío')])\n new_pass = PasswordField('Nueva Contraseña', validators=[DataRequired('El campo no puede quedar vacío'),Length(8, 25, 'La contraseá debe tener entre 8 y 25 caracteres')])\n new_pass2 = PasswordField('Nueva Contraseña Nuevamente', validators=[DataRequired('El campo no puede quedar vacío'), EqualTo('new_pass', 'Las contraseñas no son iguales')])\n submit = SubmitField('Cambiar')\n\n def __init__(self, original_username, *args, **kwargs):\n super(EditProfileForm, self).__init__(*args, **kwargs)\n self.original_username = original_username\n\n def validate_username(self, username):\n if username.data != self.original_username:\n user = User.query.filter_by(usuario=self.usuario.data).first()\n if user is not None:\n raise ValidationError('Por favor usa un nombre de usuario diferente.')\n\n\nclass RenameContract(FlaskForm):\n nombre = StringField(validators=[DataRequired()])\n\n\nclass ContactForm(FlaskForm):\n email = StringField('Correo Electrónico', validators=[DataRequired('El campo no puede quedar vacío'), Email('Por favor introduce un correo válido')])\n name = StringField('Nombre', validators=[DataRequired('Nombre Completo')])\n msg = TextAreaField('Dejanos tu mensaje y te responderemos a la brevedad posible.')\n submit = SubmitField('Enviar')"
},
{
"alpha_fraction": 0.5864453911781311,
"alphanum_fraction": 0.5988935232162476,
"avg_line_length": 35.20000076293945,
"blob_id": "eac83a10c7f0f4e227751e9cf2bd4ceaf8afb38b",
"content_id": "9cfa55fce47856bc4a317d55781e7daf167a4959",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 723,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 20,
"path": "/app/templates/pdfpreview.html",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "{% extends \"base.html\" %}\n\n{% block extracss %}\n <link rel=\"stylesheet\" href=\"/static/pdfpage.css\">\n{% endblock %}\n{% block content %}\n <div class=\"form-group\">\n <form action=\"\" method=\"post\">\n {{ form.hidden_tag() }}\n <div class=\"pagina\">\n {{ cont }}{{ form.vendedor(class=\"form-control\", id=\"vendedorname\", type=\"text\", placeholder=\"nombre\", size=10) }}\n {% if form.name0 %}\n {{ form.name0(class=\"form-control\", type=\"text\", placeholder=\"form.1\", size=\"30\") }}\n {% endif %}\n {{ form.comprador(class=\"form-control\", type=\"text\", placeholder=\"comprador\", size=50) }}\n <button class=\"btn btn-raised btn-dark\" type=\"submit\">See wtf's up</button>\n </div>\n </form>\n </div>\n{% endblock %}"
},
{
"alpha_fraction": 0.6845238208770752,
"alphanum_fraction": 0.6845238208770752,
"avg_line_length": 32.66666793823242,
"blob_id": "50de1e38a80c68164d29be8ae00dc276e97fd039",
"content_id": "b6928b83d07f160cf814096694f95508937e0a06",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 508,
"license_type": "no_license",
"max_line_length": 103,
"num_lines": 15,
"path": "/app/templates/email/reset_password.html",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "<p>Hola {{ user.usuario }},</p>\n\n<p>\n Para reestablecer tu contraseña, por favor, haz\n\n <a href=\"{{ url_for('auth.reset_password', token=token, _external=True) }}\">\n click aquí\n </a>\n</p>\n<p>De otra forma, puedes pegar el siguiente link en tu navegador:</p>\n<p>{{ url_for('auth.reset_password', token=token, _external=True) }}</p>\n<p>Si no haz sido tu quien pidió reestabler tu contraseña, puedes simplemente ignorar este mensaje.</p>\n\n<p>Saludos Cordiales,</p>\n<p>El Equipo de ContratosExpress</p>"
},
{
"alpha_fraction": 0.6678082346916199,
"alphanum_fraction": 0.6952054500579834,
"avg_line_length": 23.33333396911621,
"blob_id": "1267e6205a6f571732486f391c5349e65baf8c03",
"content_id": "980f803a3123d430bd3e8acee7947bed272dec6c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 292,
"license_type": "no_license",
"max_line_length": 92,
"num_lines": 12,
"path": "/boot.sh",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "#!/bin/sh\nsource venv/bin/activate\nwhile true; do\n\tflask db upgrade\n\tif [[ \"$?\" == \"0\" ]]; then\n\t\techo Upgrade Successful\n\t\tbreak\n\tfi\n\techo Upgrade command failed, retring in 5 secs...\n\tsleep 5\ndone\nexec gunicorn -b :5000 --workers=3 --access-logfile - --error-logfile - contratosexpress:app\n"
},
{
"alpha_fraction": 0.5218604803085327,
"alphanum_fraction": 0.5262241363525391,
"avg_line_length": 80.21243286132812,
"blob_id": "b2d7d39ac11abf51818ab3f20ff701adb07ee984",
"content_id": "ec7e476b967ac16f2a1c435caaaa69be7c7f978c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 169770,
"license_type": "no_license",
"max_line_length": 206,
"num_lines": 2043,
"path": "/app/main/contratos.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from app.models import User, Contratos, Clausulas, Declaraciones\nfrom app import db\nfrom passlib.hash import pbkdf2_sha256\n\ndef db_population():\n usuario = User.query.filter_by(usuario='rolando').first()\n if usuario is None:\n rol = User(id=20, password_hash=pbkdf2_sha256.hash(\"Contratos1\"), usuario='rolando', correo='rol@gmail.com')\n db.session.add(rol)\n db.session.commit()\n contratos_dict = {\n 'compraventa-bienes':\n {\n 'contenido': '<h5 id=\"binicio\">CONTRATO DE COMPRAVENTA EN LO SUCESIVO EL “CONTRATO” QUE CELEBRAN '\n 'POR UNA PARTE </h5>*<h5>, A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ '\n '“VENDEDOR” Y POR LA OTRA </h5>*<h5> QUIEN EN LO SUCESIVO SE LE '\n 'DENOMINARÁ “COMPRADOR”, Y A QUIENES EN CONJUNTO SE LES DENOMINARÁ COMO LAS '\n '“PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES DECLARACIONES Y '\n 'CLÁUSULAS:</h5>',\n 'tipo': 'compraventa-bienes',\n 'fin': ''\n },\n 'arrendamiento-inmueble':\n {\n 'contenido': '<h5 id=\"binicio\">CONTRATO DE ARRENDAMIENTO (\"CONTRATO\") QUE CELEBRAN'\n ' POR UNA PARTE <input class=\"inpcont\" name=\"arrendador\" id=\"arrendador\" placeholder=\"NOMBRE DEL ARRENDADOR\" size=\"1\">'\n ', A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ '\n '“ARRENDADOR” Y POR LA OTRA <input class=\"inpcont\" name=\"arrendatario\" id=\"arrendatario\" size=\"1\" placeholder=\"NOMBRE DEL ARRENDATARIO\"> A QUIEN EN LO '\n 'SUCESIVO SE LE '\n 'DENOMINARÁ “ARRENDATARIO”, Y A QUIENES EN CONJUNTO SE LES DENOMINARÁ '\n 'COMO LAS “PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES '\n 'DECLARACIONES Y CLÁUSULAS:</h5>',\n 'tipo': 'arrendamiento-inmueble',\n 'fin': '<p id=\"bfin\">Leído que fue el presente “CONTRATO” por las “PARTES”, y enteradas de los alcances legales '\n 'del mismo, lo firman de conformidad ante dos testigos por duplicado, en la ciudad donde se encuentra localizado el “INMUEBLE”,'\n ' el día <input class=\"inpcont\" type=\"date\" name=\"fechafirma\" id=\"fechafirma\" size=\"1\" placeholder=\"Fecha de firma (dd/mm/aaaa)\">, quedando un ejemplar para cada una de las “PARTES” '\n 'que intervienen en él.</p>' +\n '''<div class=\"container-fluid mt-5\">\n <div class=\"row mb-4\">\n <div id=\"bnf1\" class=\"col mb-4 text-center\">ARRENDADOR</div>\n <div id=\"bnf2\" class=\"col mb-4 text-center\">ARRENDATARIO</div>\n </div>\n <div class=\"row mb-0\">\n <div id=\"bf1\" class=\"col mb-0 text-center\">__________________________________</div>\n <div id=\"bf2\" class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">(nombre)</div>\n <div class=\"col mb-4 text-center\">(nombre)</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n </div>\n <div class=\"row mb-0\">\n <div class=\"col mb-0 text-center\">__________________________________</div>\n <div class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div id=\"bnt1\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test1\" id=\"test1\" size=\"1\" placeholder=\"Nombre Testigo 1\"></div>\n <div id=\"bnt2\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test2\" id=\"test2\" size=\"1\" placeholder=\"Nombre Testigo 2\"></div>\n </div>\n </div>'''\n },\n 'arrendamientoin-mm':\n {\n 'contenido': '<h5 id=\"binicio\">CONTRATO DE ARRENDAMIENTO (\"CONTRATO\") QUE CELEBRAN'\n ' POR UNA PARTE <input class=\"inpcont\" name=\"arrendador\" id=\"arrendador\" placeholder=\"NOMBRE DEL ARRENDADOR\" size=\"1\">'\n ', A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ '\n '“ARRENDADOR” Y POR LA OTRA <input class=\"inpcont\" name=\"arrendatario\" id=\"arrendatario\" size=\"1\" placeholder=\"NOMBRE DEL ARRENDATARIO\"> A QUIEN EN LO '\n 'SUCESIVO SE LE '\n 'DENOMINARÁ “ARRENDATARIO”, Y A QUIENES EN CONJUNTO SE LES DENOMINARÁ '\n 'COMO LAS “PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES '\n 'DECLARACIONES Y CLÁUSULAS:</h5>',\n 'tipo': 'arrendamientoin-mm',\n 'fin': '<p id=\"bfin\">Leído que fue el presente “CONTRATO” por las “PARTES”, y enteradas de los alcances legales '\n 'del mismo, lo firman de conformidad ante dos testigos por duplicado, en la ciudad donde se encuentra localizado el “INMUEBLE”,'\n ' el día <input class=\"inpcont\" type=\"date\" name=\"fechafirma\" id=\"fechafirma\" size=\"1\" placeholder=\"Fecha de firma (dd/mm/aaaa)\">, quedando un ejemplar para cada una de las “PARTES” '\n 'que intervienen en él.</p>' +\n '''<div class=\"container-fluid mt-5\">\n <div class=\"row mb-4\">\n <div id=\"bnf1\" class=\"col mb-4 text-center\">ARRENDADOR</div>\n <div id=\"bnf2\" class=\"col mb-4 text-center\">ARRENDATARIO</div>\n </div>\n <div class=\"row mb-0\">\n <div id=\"bf1\" class=\"col mb-0 text-center\">__________________________________</div>\n <div id=\"bf2\" class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">(nombre)</div>\n <div class=\"col mb-4 text-center\">(nombre)</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n </div>\n <div class=\"row mb-0\">\n <div class=\"col mb-0 text-center\">__________________________________</div>\n <div class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div id=\"bnt1\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test1\" id=\"test1\" size=\"1\" placeholder=\"Nombre Testigo 1\"></div>\n <div id=\"bnt2\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test2\" id=\"test2\" size=\"1\" placeholder=\"Nombre Testigo 2\"></div>\n </div>\n </div>'''\n },\n 'arrendamientoin-fm':\n {\n 'contenido': '<h5 id=\"binicio\">CONTRATO DE ARRENDAMIENTO (\"CONTRATO\") QUE CELEBRAN'\n ' POR UNA PARTE <input class=\"inpcont\" name=\"arrendador\" id=\"arrendador\" placeholder=\"NOMBRE DEL ARRENDADOR\" size=\"1\">'\n ', A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ '\n '“ARRENDADOR” Y POR LA OTRA <input class=\"inpcont\" name=\"arrendatario\" id=\"arrendatario\" size=\"1\" placeholder=\"NOMBRE DEL ARRENDATARIO\"> A QUIEN EN LO '\n 'SUCESIVO SE LE '\n 'DENOMINARÁ “ARRENDATARIO”, Y A QUIENES EN CONJUNTO SE LES DENOMINARÁ '\n 'COMO LAS “PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES '\n 'DECLARACIONES Y CLÁUSULAS:</h5>',\n 'tipo': 'arrendamientoin-fm',\n 'fin': '<p id=\"bfin\">Leído que fue el presente “CONTRATO” por las “PARTES”, y enteradas de los alcances legales '\n 'del mismo, lo firman de conformidad ante dos testigos por duplicado, en la ciudad donde se encuentra localizado el “INMUEBLE”,'\n ' el día <input class=\"inpcont\" type=\"date\" name=\"fechafirma\" id=\"fechafirma\" size=\"1\" placeholder=\"Fecha de firma (dd/mm/aaaa)\">, quedando un ejemplar para cada una de las “PARTES” '\n 'que intervienen en él.</p>' +\n '''<div class=\"container-fluid mt-5\">\n <div class=\"row mb-4\">\n <div id=\"bnf1\" class=\"col mb-4 text-center\">ARRENDADOR</div>\n <div id=\"bnf2\" class=\"col mb-4 text-center\">ARRENDATARIO</div>\n </div>\n <div class=\"row mb-0\">\n <div id=\"bf1\" class=\"col mb-0 text-center\">__________________________________</div>\n <div id=\"bf2\" class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">(nombre)</div>\n <div class=\"col mb-4 text-center\">(nombre)</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n </div>\n <div class=\"row mb-0\">\n <div class=\"col mb-0 text-center\">__________________________________</div>\n <div class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div id=\"bnt1\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test1\" id=\"test1\" size=\"1\" placeholder=\"Nombre Testigo 1\"></div>\n <div id=\"bnt2\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test2\" id=\"test2\" size=\"1\" placeholder=\"Nombre Testigo 2\"></div>\n </div>\n </div>'''\n },\n 'arrendamientoin-mf':\n {\n 'contenido': '<h5 id=\"binicio\">CONTRATO DE ARRENDAMIENTO (\"CONTRATO\") QUE CELEBRAN'\n ' POR UNA PARTE <input class=\"inpcont\" name=\"arrendador\" id=\"arrendador\" placeholder=\"NOMBRE DEL ARRENDADOR\" size=\"1\">'\n ', A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ '\n '“ARRENDADOR” Y POR LA OTRA <input class=\"inpcont\" name=\"arrendatario\" id=\"arrendatario\" size=\"1\" placeholder=\"NOMBRE DEL ARRENDATARIO\"> A QUIEN EN LO '\n 'SUCESIVO SE LE '\n 'DENOMINARÁ “ARRENDATARIO”, Y A QUIENES EN CONJUNTO SE LES DENOMINARÁ '\n 'COMO LAS “PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES '\n 'DECLARACIONES Y CLÁUSULAS:</h5>',\n 'tipo': 'arrendamientoin-mf',\n 'fin': '<p id=\"bfin\">Leído que fue el presente “CONTRATO” por las “PARTES”, y enteradas de los alcances legales '\n 'del mismo, lo firman de conformidad ante dos testigos por duplicado, en la ciudad donde se encuentra localizado el “INMUEBLE”,'\n ' el día <input class=\"inpcont\" type=\"date\" name=\"fechafirma\" id=\"fechafirma\" size=\"1\" placeholder=\"Fecha de firma (dd/mm/aaaa)\">, quedando un ejemplar para cada una de las “PARTES” '\n 'que intervienen en él.</p>' +\n '''<div class=\"container-fluid mt-5\">\n <div class=\"row mb-4\">\n <div id=\"bnf1\" class=\"col mb-4 text-center\">ARRENDADOR</div>\n <div id=\"bnf2\" class=\"col mb-4 text-center\">ARRENDATARIO</div>\n </div>\n <div class=\"row mb-0\">\n <div id=\"bf1\" class=\"col mb-0 text-center\">__________________________________</div>\n <div id=\"bf2\" class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">(nombre)</div>\n <div class=\"col mb-4 text-center\">(nombre)</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n </div>\n <div class=\"row mb-0\">\n <div class=\"col mb-0 text-center\">__________________________________</div>\n <div class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div id=\"bnt1\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test1\" id=\"test1\" size=\"1\" placeholder=\"Nombre Testigo 1\"></div>\n <div id=\"bnt2\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test2\" id=\"test2\" size=\"1\" placeholder=\"Nombre Testigo 2\"></div>\n </div>\n </div>'''\n },\n 'donacion':\n {\n 'contenido':'<h5 id=\"binicio\">CONTRATO DE DONACIÓN EN LO SUCESIVO EL “CONTRATO” QUE CELEBRAN POR UNA '\n 'PARTE <input class=\"inpcont\" name=\"donante\" id=\"donante\" placeholder=\"NOMBRE DEL DONANTE\"'\n ' size=\"1\"> A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ “DONANTE” Y POR LA OTRA <input '\n 'class=\"inpcont\" name=\"donatario\" id=\"donatario\" placeholder=\"NOMBRE DEL DONATARIO\" '\n 'size=\"1\"> A QUIEN EN LO SUCESIVO SE LE DENOMINARÁ “DONATARIO”, Y A QUIENES EN CONJUNTO SE '\n 'LES DENOMINARÁ COMO LAS “PARTES”, MISMAS QUE SE SUJETAN AL TENOR DE LAS SIGUIENTES '\n 'DECLARACIONES Y CLÁUSULAS:</h5>',\n 'tipo': 'donacion',\n 'fin': '<p id=\"bfin\">Leído que fue el presente “CONTRATO” por las “PARTES”, y enteradas de los alcances legales '\n 'del mismo, lo firman de conformidad ante dos testigos por duplicado, en la ciudad de <input '\n 'class=\"inpcont\" name=\"ciudadfirma\" id=\"ciudadfirma\" size=\"1\" placeholder=\"Ciudad de Firma\">'\n ' al día <input class=\"inpcont\" type=\"date\" name=\"fechafirma\" id=\"fechafirma\" '\n 'size=\"1\" placeholder=\"Fecha de firma AAAA-MM-DD\">, quedando un ejemplar para cada una de las “PARTES” '\n 'que intervienen en él.</p>' +\n '''<div class=\"container-fluid mt-5\">\n <div class=\"row mb-4\">\n <div id=\"bnf1\" class=\"col mb-4 text-center\">DONANTE</div>\n <div id=\"bnf2\" class=\"col mb-4 text-center\">DONATARIO</div>\n </div>\n <div class=\"row mb-0\">\n <div id=\"bf1\" class=\"col mb-0 text-center\">__________________________________</div>\n <div id=\"bf2\" class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">(nombre)</div>\n <div class=\"col mb-4 text-center\">(nombre)</div>\n </div>\n <div class=\"row mb-4\">\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n <div class=\"col mb-4 text-center\">TESTIGO</div>\n </div>\n <div class=\"row mb-0\">\n <div class=\"col mb-0 text-center\">__________________________________</div>\n <div class=\"col mb-0 text-center\">__________________________________</div>\n </div>\n <div class=\"row mb-4\">\n <div id=\"bnt1\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test1\" id=\"test1\" size=\"1\" placeholder=\"Nombre Testigo 1\"></div>\n <div id=\"bnt2\" class=\"col mb-4 text-center\"><input class=\"inpcont\" name=\"test2\" id=\"test2\" size=\"1\" placeholder=\"Nombre Testigo 2\"></div>\n </div>\n </div>'''\n }\n }\n for key,contrato in contratos_dict.items():\n cont = Contratos.query.filter_by(tipo=contrato['tipo']).first()\n if cont is None:\n cont = Contratos(**contrato)\n db.session.add(cont)\n db.session.commit()\n else:\n if cont.contenido != contrato['contenido']:\n cont.contenido = contrato['contenido']\n db.session.commit()\n if cont.fin != contrato['fin']:\n cont.fin = contrato['fin']\n db.session.commit()\n lista_contratos = Contratos.query.all()\n ids_contratos = {}\n for contrato in lista_contratos:\n ids_contratos[contrato.tipo] = contrato.id\n clausulas_dict = {\n 'compraventa-bienes':\n [\n {\n 'titulo': 'Objeto',\n 'no': 'PRIMERA',\n 'desc': 'Por virtud de este acto jurídico, el “<span style=\"background: yellow\">'\n 'VENDEDOR</span>” vende, y el “COMPRADOR” compra el bien especificado en la '\n 'declaración I, fracción c. del presente CONTRATO.',\n 'id_contrato': ''\n },\n {\n 'titulo': 'Transmisión',\n 'no': 'TERCERA',\n 'desc': 'Al ser este un contrato de compraventab y estar las PARTES de acuerdo tanto en'\n ' el numero como en el objeto materia del mismo, el “COMPRADOR” adquiere la '\n 'propiedad del bien, con los efectos legales que ello conlleva, sirviendo como '\n 'el más amplio recibo el presente CONTRATO.',\n 'id_contrato': ''\n },\n {\n 'titulo': 'Notificaciones',\n 'no': 'SEXTA',\n 'desc': 'Todos los avisos y notificaciones que las PARTES deseen hacerse en relación '\n 'con el presente CONTRATO, deberán ser en los domicilios que se indican en el '\n 'capítulo de Declaraciones del presente CONTRATO.',\n 'id_contrato': ''\n }\n ],\n 'arrendamiento-inmueble':\n [\n {\n 'titulo': 'Entrega',\n 'no': '<span class=\"numi\">1</span>',\n 'desc': 'El “ARRENDADOR” entrega en arrendamiento el “INMUEBLE” en'\n ' buen estado al “ARRENDATARIO”, quien lo recibe a su entera'\n ' satisfacción el <input size=\"1\" type=\"date\" name=\"fechaentrega\" id=\"fechaentrega\" class=\"inpcont\" placeholder=\"Fecha(dd/mm/aaaa)\">,'\n ' en las '\n 'condiciones y para los fines convenidos en el “CONTRATO”.'},\n {\n 'titulo': 'Precio',\n 'no': '<span class=\"numi\">2</span>',\n 'desc': 'Las “PARTES” acuerdan la cantidad de $<input class=\"inpcont\" type=\"number\" step=\"0.01\" min=0 name=\"precio\" '\n 'id=\"precio\" size=\"1\" placeholder=\"Precio con Número\"> (_d pesos 00/100 M.N.) mensuales como '\n 'contraprestación del arrendamiento, dicha cantidad deberá pagarse en mensualidades '\n 'anticipadas en la cuenta bancaria número <input class=\"inpcont\" type=\"number\" min=0 name=\"nocuenta\" id=\"nocuenta\" size=\"1\" '\n 'placeholder=\"No. de Cuenta\"> del banco <input class=\"inpcont\" size=\"1\" name=\"banco\" id=\"banco\" '\n 'placeholder=\"Nombre del Banco\">, clabe <input class=\"inpcont\" size=\"1\" name=\"clabe\" id=\"clabe\" '\n 'placeholder=\"Clabe Bancaria\"> a nombre del “ARRENDADOR” a más '\n 'tardar el día 15 de cada mes o el día hábil siguiente cuando el día 15 sea inhábil.</p>'\n '<p>En caso de que el “ARRENDATARIO” incurra en mora en el pago de la renta, éste se obliga a '\n 'pagar al “ARRENDADOR” un interés del <input class=\"inpcont\" type=\"number\" min=0 step=\"0.01\" size=\"1\" name=\"interes\" id=\"interes\" '\n 'placeholder=\"% de Interés Moratorio\">% (_p por ciento) mensual sobre el '\n 'monto de renta '\n 'adeudado hasta que el se liquide la cantidad adeudada, los pagos que haga el “ARRENDATARIO” se '\n 'aplicarán primeramente a intereses y posteriormente a capital.</p>'\n '<p>El “ARRENDADOR” se compromete a entregar el recibo correspondiente que compruebe el pago de la'\n ' renta a nombre del “ARRENDATARIO”, el cual se deberá entregar sin falta al momento en que el '\n '“ARRENDADOR” reciba el pago o dentro de los siguientes 5 días hábiles.</p>'\n '<p>El “ARRENDATARIO” bajo protesta de decir verdad manifiesta que los recursos monetarios con los'\n ' que hará el pago de la renta estipulada en el “CONTRATO”, son de origen lícito, por lo que no '\n 'representan directa o indirectamente ni provienen de la comisión de algún delito como el lavado '\n 'de dinero, delincuencia organizada o cualquier otra actividad considerada como ilícita por ley.'\n },\n {\n 'titulo': 'Renovación',\n 'no': '<span class=\"numi\">3</span>',\n 'desc': 'En caso de que el “ARRENDADOR” aceptará renovar el “CONTRATO” previo a la fecha de vencimiento del '\n 'mismo, el importe de la renta pactado en la cláusula anterior aumentará anualmente basándose '\n 'en el Índice Nacional de Precios al Consumidor más 3 puntos o proporcionalmente al aumento del'\n ' salario mínimo del estado donde se localiza el INMUEBLE, lo que resulte más alto'\n },\n {\n 'titulo': 'Recepción y Entrega',\n 'no': '<span class=numi\">4</span>',\n 'desc': 'El “ARRENDATARIO” acepta el “INMUEBLE” en excelentes condiciones y en perfecto estado para el '\n 'uso convenido, y se compromete a hacer las reparaciones necesarias al vencimiento del '\n '“CONTRATO”, para entregar el “INMUEBLE” al “ARRENDADOR” en las mismas condiciones en las que '\n 'lo recibió.</p>'\n '<p>En cuanto a las reparaciones arriba mencionadas, el “ARRENDATARIO” no está '\n 'obligado a realizar reparaciones derivadas por el uso o deterioro normal del “INMUEBLE”, sino '\n 'únicamente por los daños ocasionados por negligencia o uso inapropiado de las instalaciones '\n 'del mismo. El “ARRENDADOR” estará encargado de realizar las reparaciones mayores como muros '\n 'interiores y exteriores, techos, pisos y cimentación.</p>'\n '<p>El “ARRENDATARIO” se obliga a dar aviso oportuno al “ARRENDADOR” de cualquier daño en que '\n 'pudiera perjudicar al “INMUEBLE”, siendo el “ARRENDATARIO” responsable de los daños y '\n 'perjuicios ocasionados por la falta de dicho aviso oportuno.</p>'\n '<p>El “ARRENDATARIO” podrá realizar modificaciones y mejoras al “INMUEBLE” con previa '\n 'autorización por escrito al “ARRENDADOR”. En caso de que dichas modificaciones no puedan '\n 'removerse sin dañar la estructura del “INMUEBLE” quedarán en beneficio del “ARRENDADOR” sin '\n 'derecho al “ARRENDATARIO” de cobrar indemnización alguna, las mejoras que puedan removerse sin'\n ' dañar el “INMUEBLE” podrán ser retiradas por el “ARRENDATARIO”.'\n },\n {\n 'titulo': 'Vigencia',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “CONTRATO” tendrá una duración de 1 (uno) año obligatorio y forzoso para las ”PARTES”, '\n 'iniciando su vigencia el día señalado en la Cláusula 1 y terminando el día <input '\n 'class=\"inpcont\" type=\"date\" name=\"fechatermcont\" id=\"fechatermcont\" size=\"1\" placeholder=\"Fecha de Terminación del Contrato (dd/mm/aaaa)\">.'\n '</p>'\n '<p>A la fecha de vencimiento no se entenderá prorrogado el “CONTRATO”, teniendo las '\n '“PARTES” que acordar por escrito la renovación. El “ARRENDATARIO” deberá solicitar por escrito'\n ' y con 45 (cuarenta y cinco) días de anticipación a la fecha de vencimiento, la'\n ' renovación al “ARRENDADOR” éste último se obliga a responder 30 (treinta) días '\n 'previos a la fecha de vencimiento su decisión final.',\n 'movable': True\n },\n {\n 'titulo': 'No Entrega',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En caso de que el “ARRENDATARIO” no desocupe el “INMUEBLE” al término de la vigencia del '\n '“CONTRATO” a entera satisfacción del “ARRENDADOR”, pagará a éste último como penalidad el '\n '50% más del importe '\n 'de la renta mensual que seguirá generando hasta la entrega'\n ' del “INMUEBLE” de acuerdo a lo pactado en el “CONTRATO”.',\n 'movable': True\n },\n {\n 'titulo': 'Caso Fortuito',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que no habrá responsabilidad civil o penal para el “ARRENDADOR” por '\n 'caso fortuito o fuerza mayor, entendiéndose pero no limitando a fenómenos naturales, '\n 'incendios, derrumbes, explosiones y demás que sufriere el “INMUEBLE”, y que afectará al '\n '“ARRENDATARIO” en sus bienes, persona, familiares o visitantes.',\n 'movable': True\n },\n {\n 'titulo': 'Rescisión',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDADOR” podrá rescindir el “CONTRATO” dando 30 (treinta) días naturales al “ARRENDATARIO” para '\n 'la desocupación del “INMUEBLE”, sin obligación alguna ni declaración judicial para el '\n '“ARRENDADOR”, por las siguientes causas:</p>'\n '<ol id=\"Recisión-list-1\"><li>En caso de insolvencia por parte del “ARRENDATARIO” Cuando el “ARRENDATARIO” dejare de'\n ' pagar 2 (dos) '\n 'meses de renta.</li> <li>Cuando el “ARRENDATARIO” incumpla con alguna de las cláusulas '\n 'pactadas en el “CONTRATO”.</li> <li>Cuando se haga mal uso del “INMUEBLE”, que pueda destruirlo o'\n ' causar daños mayores.</li><li> Cuando el “ARRENDATARIO”, sus familiares o visitantes, falten'\n ' al orden moral o lleven a cabo actividades ilícitas dentro del “INMUEBLE”.</li></ol></p>'\n '<p>El “ARRENDATARIO” podrá dar por terminado el “CONTRATO”, sin responsabilidad alguna ni '\n 'necesidad de declaración judicial, en los siguientes casos:'\n '<ol id=\"Recisión-list-2\"><li>Cuando por causas ajenas esté impedido del uso de cualquier servicio básico, '\n 'entendiéndose éstos como luz, agua potable y gas, siempre y cuando sea por causas imputables '\n 'al “ARRENDADOR”.</li><li>Cuando el “ARRENDADOR” le impida el acceso total o parcial al '\n '“INMUEBLE”, sin causa justificada y por razones inimputables al “ARRENDATARIO”.</li><li>Cuando'\n ' el “ARRENDADOR” no lleve a cabo las reparaciones acordadas en el “CONTRATO”.</li></ol>',\n 'movable': True\n },\n {\n 'titulo': 'Inspecciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a permitir el acceso al “ARRENDADOR” o a la persona que éste '\n 'designe para revisar el estado que guarda el “INMUEBLE” y/o realizar reparaciones, siempre y '\n 'cuando el “ARRENDADOR” avise con por lo menos 3 (tres) días hábiles de anticipación.',\n 'movable': True\n },\n {\n 'titulo': 'Prohibiciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” no podrá guardar o conservar en el “INMUEBLE” materiales prohibidos por la '\n 'ley, materiales inflamables o explosivos y mascotas de cualquier índole, siendo éste '\n 'responsable de los daños y perjuicios que se ocasiones por el incumplimiento de ésta cláusula,'\n ' incluyendo la rescisión del “CONTRATO”',\n 'movable': True\n },\n {\n 'titulo': 'Depósito en Garantía',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a pagar la cantidad de equivalente a 1 (uno) mes de renta como '\n 'depósito en garantía, mismo que se entregará 15 (quince) días calendario posteriores a la '\n 'fecha de vencimiento del “CONTRATO” siempre y cuando el “ARRENDATARIO” haya cumplido con lo '\n 'pactado en el “CONTRATO”. Éste depósito en garantía no podrá ser tomado a cuenta de renta. La '\n 'firma del “CONTRATO” hace la función de recibo del depósito en garantía.</p>'\n '<p>En caso de renovación del “CONTRATO”, la cantidad mencionada en el párrafo anterior sufrirá '\n 'un aumento en la misma proporción de acuerdo a lo pactado en la cláusula tercera del “CONTRATO'\n '”.</p>'\n '<p>Adicional a lo establecido en los párrafos anteriores, El “ARRENDATARIO” entrega al '\n '“ARRENDADOR” la cantidad equivalente a 1 (uno) mes de renta por concepto del primer mes de '\n 'renta anticipada. La firma del “CONTRATO” sirve como recibo de dicho pago.',\n 'movable': True\n },\n {\n 'titulo': 'Acuerdo Total',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El presente “CONTRATO” constituye el acuerdo total entre las “PARTES”, por lo que éstas '\n 'expresamente manifiestan que cualquier otro acuerdo, previo a la firma del “CONTRATO”, oral o '\n 'escrito, tácito o expreso que directa o indirectamente se relacionen con el objeto del '\n '“CONTRATO”, queda desde ahora terminado, siendo el “CONTRATO” el único documento legal que '\n 'rige las obligaciones existentes entre las “PARTES” respecto a lo aquí pactado.</p>'\n '<p>En caso de alguna controversia, judicial o extrajudicial, suscitada respecto de la '\n 'interpretación y cumplimiento del “CONTRATO”, el “ARRENDATARIO” será responsable de los gastos'\n ' y honorarios que se generen, siempre y cuando sea por su culpa o negligencia. '\n 'En caso de suscitarse lo anterior por culpa o negligencia del “ARRENDADOR” éste será '\n 'responsable del pago de gastos y honorarios mencionados.',\n 'movable': True\n },\n {\n 'titulo': 'Penalidad',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Si el “ARRENDATARIO” llegara a desocupar el “INMUEBLE” antes del término pactado por las '\n '“PARTES”, o incurra dentro de ése término en alguna causa de rescisión, se compromete a pagar '\n 'al “ARRENDADOR” el equivalente a las mensualidades restantes. Lo anterior no será aplicable '\n 'cuando la causa de rescisión sea imputable al “ARRENDADOR”.</p>'\n '<p>Las “PARTES” acuerdan que en caso de que al “ARRENDATARIO” se le impida el uso o goce '\n 'parcial del “INMUEBLE”, éste podrá pedir la reducción proporcional de la renta o la rescisión '\n 'del “CONTRATO”, si dicho impedimento durara más de 1 mes.',\n 'movable': True\n },\n {\n 'titulo': 'Buena fe',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” manifiestan que en la elaboración del “CONTRATO” no existe dolo, mala fe ni '\n 'ningún otro vicio del consentimiento que pudiera invalidar parcial o totalmente',\n 'movable': True\n },\n {\n 'titulo': 'Encabezados',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los encabezados de las cláusulas del “CONTRATO” se incluyen como referencia, por lo que la '\n 'interpretación del mismo se hará basado en el contenido de las cláusulas aquí pactadas y no '\n 'respecto a sus encabezados.',\n 'movable': True\n },\n {\n 'titulo': 'Jurisdicción aplicable',\n 'no': '<span class=\"num\">#</span>',\n 'desc': 'Las “PARTES” acuerdan en someterse a la jurisdicción de las leyes, tribunales y jueces del '\n 'estado en donde se encuentra localizado el “INMUEBLE”, para la interpretación y solución de '\n 'controversias que pudieran suscitarse respecto al “CONTRATO”, renunciando así al fuero que les'\n ' corresponda por su domicilio actual o futuro.',\n 'movable': False,\n 'end': True\n },\n {\n 'titulo': 'Mascotas',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Durante la totalidad de la vigencia del contrato, el “ARRENDATARIO” se obliga a no ingresar, '\n 'y/o mantener mascotas de cualquier tipo, raza, o tamaño. Cualquier acto en contravención de lo'\n ' dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a demandar la rescisión del \"CONTRATO\"',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'La cuota mensual de mantenimiento está incluida en el precio de la renta, siendo '\n 'responsabilidad del “ARRENDADOR” realizar este pago en tiempo y forma a la oficina necesaria.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento No Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a cubrir la cuota de mantenimiento que la administración del '\n 'Régimen de Condominio del edificio en donde se encuentra el \"INMUEBLE\", en los días '\n 'que el Consejo de Administración lo determine, debiendo de cubrir dicha cuota en forma mensual y en los '\n 'días establecidos. La falta de pago de más de una mensualidad de la cuota de mantenimiento, '\n 'dará lugar a la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Prohibición de Subarrendamiento',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Queda prohibido traspasar, subarrendar, ceder sus derechos u otorgar en comodato todo o parte '\n 'del \"INMUEBLE\", sin el previo consentimiento por escrito del \"ARRENDADOR\". Cualquier '\n 'acto en contravención de lo dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a '\n 'demandar la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble CASA HABITACIÓN',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del INMUEBLE será exclusivamente el de CASA HABITACIÓN, por lo que si se le da un uso '\n 'distinto al aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble COMERCIAL',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del \"INMUEBLE\" será exclusivamente COMERCIAL, por lo que si se le da un uso distinto al '\n 'aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Seguro',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En todo momento durante el término del “CONTRATO”, el “ARRENDATARIO” deberá mantener el seguro'\n ' que el “ARRENDADOR” razonablemente pueda exigir, incluidos, entre otros, los bienes '\n 'personales y de responsabilidad civil. Específicamente, el \"ARRENDATARIO\" obtendrá y mantendrá '\n 'durante el período, un seguro de responsabilidad general escrito sobre una base de ocurrencia,'\n ' asegurando su responsabilidad por la pérdida o daño de los bienes y lesiones o '\n 'muerte de terceros.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Aval',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Para garantizar el estricto y fiel cumplimiento de todas y cada una de las obligaciones a '\n 'cargo del “ARRENDATARIO” firma este contrato el(la) Señor(a) <input class=\"inpcont\" '\n 'name=\"nombaval\" id=\"nombaval\" size=\"1\" placeholder=\"Nombre del Aval\">, quien se '\n 'constituye como \"AVAL\" único y principal obligado solidario del “ARRENDATARIO”, por todas las'\n ' obligaciones contraídas responsabilidad que no cesará hasta que el “ARRENDATARIO” desocupe el'\n ' \"INMUEBLE\" y no exista obligación alguna por la entrega del \"INMUEBLE\" a '\n 'satisfacción del \"ARRENDADOR\", pudiendo el “AVAL” entregar el \"INMUEBLE\" a nombre del '\n '“ARRENDATARIO”.</p>'\n '<p>El \"AVAL\" señala como domicilio para cumplir sus obligaciones, el ubicado en <input '\n 'class=\"inpcont\" name=\"domaval\" id=\"domaval\" size=\"1\" placeholder=\"Domicilio del Aval\">'\n ', manifestando que es de su propiedad y lo acredita con la copia simple de la escritura '\n 'pública número <input class=\"inpcont\" name=\"noescaval\" id=\"noescaval\" size=\"1\" placeholder=\"No. de escritura'\n ' del aval\">, otorgada ante la fe del Notario Público número <input class=\"inpcont\" '\n 'name=\"nonotaval\" id=\"nonotaval\" size=\"1\" placeholder=\"Número de Notario del Aval\"> de <input class=\"inpcont\" '\n 'name=\"munnotaval\" id=\"munnotaval\" size=\"1\" placeholder=\"Municipio del Notario del Aval\">,'\n ' <input class=\"inpcont\" name=\"estnotaval\" id=\"estnotaval\" size=\"1\" placeholder=\"Estado del Notario del Aval\">, '\n 'con fecha del <input class=\"inpcont\" type=\"date\" name=\"fechaescaval\" id=\"fechaescaval\" size=\"1\" placeholder=\"Fecha de '\n 'escritura del Aval (dd/mm/aaaa)\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input class=\"inpcont\" type=\"date\" name=\"fecharegaval\" id=\"fecharegaval\" size=\"1\" '\n 'placeholder=\"Fecha de registro del Aval\">, bajo el folio '\n 'mercantil número <input class=\"inpcont\" type=\"number\" min=0 name=\"folmerc\" id=\"folmerc\" size=\"1\" '\n 'placeholder=\"Folio Mercantil de la escritura del Aval\">, del Registro Público de la Propiedad '\n 'y Comercio del estado de <input class=\"inpcont\" name=\"estregescaval\" id=\"estregescaval\" size=\"1\" '\n 'placeholder=\"Estado donde fue registrada la escritura del Aval\">'\n ', que se anexa al \"CONTRATO\", mismo que así lo mantendrá hasta que se haya dado '\n 'cumplimiento a todos los términos del \"CONTRATO\" y se haya entregado el \"INMUEBLE\" a '\n 'satisfacción del “ARRENDADOR”, siendo causa de rescisión del \"CONTRATO\", la '\n 'contravención a lo antes estipulado, renunciando a los beneficios de orden y exclusión '\n 'señalados en las leyes aplicables.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Pago Propio de Servicios',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'A partir del inicio de vigencia del “CONTRATO” pactada en la cláusula anterior el '\n '“ARRENDATARIO” se compromete a pagar los servicios de luz, gas, agua, teléfono, cable, '\n 'internet o cualquier otro servicio que llegara a contratar por su cuenta, siendo responsable '\n 'de la cancelación de los mismos al término de la vigencia del “CONTRATO”. Será necesario '\n 'entregar el último recibo pagado de cada uno de los servicios contratados por el “ARRENDATARIO'\n '” al término del “CONTRATO” para la devolución del depósito dejado en garantía.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Servicios Incluidos',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los costos de los servicios de luz, gas, agua, teléfono, cable e internet se verán reflejados'\n ' en el monto mensual de la renta pactado en la Cláusula de Precio. Será responsabilidad del '\n '“ARRENDADOR” mantener el pago actualizado y los servicios necesarios para el “ARRENDATARIO”. '\n 'La cancelación de los servicios por causas imputables al “ARRENDADOR” que duren más de 2 (dos)'\n ' meses, será causal de rescisión del contrato, sin responsabilidad adicional para el '\n '“ARRENDATARIO”.',\n 'movable': True,\n 'optional': True\n }\n ],\n\n 'arrendamientoin-mm':\n [\n {\n 'titulo': 'Entrega',\n 'no': '<span class=\"numi\">1</span>',\n 'desc': 'El “ARRENDADOR” entrega en arrendamiento el “INMUEBLE” en'\n ' buen estado al “ARRENDATARIO”, quien lo recibe a su entera'\n ' satisfacción el <input size=\"1\" type=\"date\" name=\"fechaentrega\" id=\"fechaentrega\" class=\"inpcont\" placeholder=\"Fecha(dd/mm/aaaa)\">,'\n ' en las '\n 'condiciones y para los fines convenidos en el “CONTRATO”.'},\n {\n 'titulo': 'Precio',\n 'no': '<span class=\"numi\">2</span>',\n 'desc': 'Las “PARTES” acuerdan la cantidad de $<input class=\"inpcont\" type=\"number\" step=\"0.01\" min=0 name=\"precio\" '\n 'id=\"precio\" size=\"1\" placeholder=\"Precio con Número\"> (_d pesos 00/100 M.N.) mensuales como '\n 'contraprestación del arrendamiento, dicha cantidad deberá pagarse en mensualidades '\n 'anticipadas en la cuenta bancaria número <input class=\"inpcont\" type=\"number\" min=0 name=\"nocuenta\" id=\"nocuenta\" size=\"1\" '\n 'placeholder=\"No. de Cuenta\"> del banco <input class=\"inpcont\" size=\"1\" name=\"banco\" id=\"banco\" '\n 'placeholder=\"Nombre del Banco\">, clabe <input class=\"inpcont\" size=\"1\" name=\"clabe\" id=\"clabe\" '\n 'placeholder=\"Clabe Bancaria\"> a nombre del “ARRENDADOR” a más '\n 'tardar el día 15 de cada mes o el día hábil siguiente cuando el día 15 sea inhábil.</p>'\n '<p>En caso de que el “ARRENDATARIO” incurra en mora en el pago de la renta, éste se obliga a '\n 'pagar al “ARRENDADOR” un interés del <input class=\"inpcont\" type=\"number\" min=0 step=\"0.01\" size=\"1\" name=\"interes\" id=\"interes\" '\n 'placeholder=\"% de Interés Moratorio\">% (_p por ciento) mensual sobre el '\n 'monto de renta '\n 'adeudado hasta que el se liquide la cantidad adeudada, los pagos que haga el “ARRENDATARIO” se '\n 'aplicarán primeramente a intereses y posteriormente a capital.</p>'\n '<p>El “ARRENDADOR” se compromete a entregar el recibo correspondiente que compruebe el pago de la'\n ' renta a nombre del “ARRENDATARIO”, el cual se deberá entregar sin falta al momento en que el '\n '“ARRENDADOR” reciba el pago o dentro de los siguientes 5 días hábiles.</p>'\n '<p>El “ARRENDATARIO” bajo protesta de decir verdad manifiesta que los recursos monetarios con los'\n ' que hará el pago de la renta estipulada en el “CONTRATO”, son de origen lícito, por lo que no '\n 'representan directa o indirectamente ni provienen de la comisión de algún delito como el lavado '\n 'de dinero, delincuencia organizada o cualquier otra actividad considerada como ilícita por ley.'\n },\n {\n 'titulo': 'Renovación',\n 'no': '<span class=\"numi\">3</span>',\n 'desc': 'En caso de que el “ARRENDADOR” aceptará renovar el “CONTRATO” previo a la fecha de vencimiento del '\n 'mismo, el importe de la renta pactado en la cláusula anterior aumentará anualmente basándose '\n 'en el Índice Nacional de Precios al Consumidor más 3 puntos o proporcionalmente al aumento del'\n ' salario mínimo del estado donde se localiza el INMUEBLE, lo que resulte más alto'\n },\n {\n 'titulo': 'Recepción y Entrega',\n 'no': '<span class=numi\">4</span>',\n 'desc': 'El “ARRENDATARIO” acepta el “INMUEBLE” en excelentes condiciones y en perfecto estado para el '\n 'uso convenido, y se compromete a hacer las reparaciones necesarias al vencimiento del '\n '“CONTRATO”, para entregar el “INMUEBLE” al “ARRENDADOR” en las mismas condiciones en las que '\n 'lo recibió.</p>'\n '<p>En cuanto a las reparaciones arriba mencionadas, el “ARRENDATARIO” no está '\n 'obligado a realizar reparaciones derivadas por el uso o deterioro normal del “INMUEBLE”, sino '\n 'únicamente por los daños ocasionados por negligencia o uso inapropiado de las instalaciones '\n 'del mismo. El “ARRENDADOR” estará encargado de realizar las reparaciones mayores como muros '\n 'interiores y exteriores, techos, pisos y cimentación.</p>'\n '<p>El “ARRENDATARIO” se obliga a dar aviso oportuno al “ARRENDADOR” de cualquier daño en que '\n 'pudiera perjudicar al “INMUEBLE”, siendo el “ARRENDATARIO” responsable de los daños y '\n 'perjuicios ocasionados por la falta de dicho aviso oportuno.</p>'\n '<p>El “ARRENDATARIO” podrá realizar modificaciones y mejoras al “INMUEBLE” con previa '\n 'autorización por escrito al “ARRENDADOR”. En caso de que dichas modificaciones no puedan '\n 'removerse sin dañar la estructura del “INMUEBLE” quedarán en beneficio del “ARRENDADOR” sin '\n 'derecho al “ARRENDATARIO” de cobrar indemnización alguna, las mejoras que puedan removerse sin'\n ' dañar el “INMUEBLE” podrán ser retiradas por el “ARRENDATARIO”.'\n },\n {\n 'titulo': 'Vigencia',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “CONTRATO” tendrá una duración de 1 (uno) año obligatorio y forzoso para las ”PARTES”, '\n 'iniciando su vigencia el día señalado en la Cláusula 1 y terminando el día <input '\n 'class=\"inpcont\" type=\"date\" name=\"fechatermcont\" id=\"fechatermcont\" size=\"1\" placeholder=\"Fecha de Terminación del Contrato (dd/mm/aaaa)\">.'\n '</p>'\n '<p>A la fecha de vencimiento no se entenderá prorrogado el “CONTRATO”, teniendo las '\n '“PARTES” que acordar por escrito la renovación. El “ARRENDATARIO” deberá solicitar por escrito'\n ' y con 45 (cuarenta y cinco) días de anticipación a la fecha de vencimiento, la'\n ' renovación al “ARRENDADOR” éste último se obliga a responder 30 (treinta) días '\n 'previos a la fecha de vencimiento su decisión final.',\n 'movable': True\n },\n {\n 'titulo': 'No Entrega',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En caso de que el “ARRENDATARIO” no desocupe el “INMUEBLE” al término de la vigencia del '\n '“CONTRATO” a entera satisfacción del “ARRENDADOR”, pagará a éste último como penalidad el '\n '50% más del importe '\n 'de la renta mensual que seguirá generando hasta la entrega'\n ' del “INMUEBLE” de acuerdo a lo pactado en el “CONTRATO”.',\n 'movable': True\n },\n {\n 'titulo': 'Caso Fortuito',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que no habrá responsabilidad civil o penal para el “ARRENDADOR” por '\n 'caso fortuito o fuerza mayor, entendiéndose pero no limitando a fenómenos naturales, '\n 'incendios, derrumbes, explosiones y demás que sufriere el “INMUEBLE”, y que afectará al '\n '“ARRENDATARIO” en sus bienes, persona, familiares o visitantes.',\n 'movable': True\n },\n {\n 'titulo': 'Rescisión',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDADOR” podrá rescindir el “CONTRATO” dando 30 (treinta) días naturales al “ARRENDATARIO” para '\n 'la desocupación del “INMUEBLE”, sin obligación alguna ni declaración judicial para el '\n '“ARRENDADOR”, por las siguientes causas:</p>'\n '<ol id=\"Recisión-list-1\"><li>En caso de insolvencia por parte del “ARRENDATARIO” Cuando el “ARRENDATARIO” dejare de'\n ' pagar 2 (dos) '\n 'meses de renta.</li> <li>Cuando el “ARRENDATARIO” incumpla con alguna de las cláusulas '\n 'pactadas en el “CONTRATO”.</li> <li>Cuando se haga mal uso del “INMUEBLE”, que pueda destruirlo o'\n ' causar daños mayores.</li><li> Cuando el “ARRENDATARIO”, sus familiares o visitantes, falten'\n ' al orden moral o lleven a cabo actividades ilícitas dentro del “INMUEBLE”.</li></ol></p>'\n '<p>El “ARRENDATARIO” podrá dar por terminado el “CONTRATO”, sin responsabilidad alguna ni '\n 'necesidad de declaración judicial, en los siguientes casos:'\n '<ol id=\"Recisión-list-2\"><li>Cuando por causas ajenas esté impedido del uso de cualquier servicio básico, '\n 'entendiéndose éstos como luz, agua potable y gas, siempre y cuando sea por causas imputables '\n 'al “ARRENDADOR”.</li><li>Cuando el “ARRENDADOR” le impida el acceso total o parcial al '\n '“INMUEBLE”, sin causa justificada y por razones inimputables al “ARRENDATARIO”.</li><li>Cuando'\n ' el “ARRENDADOR” no lleve a cabo las reparaciones acordadas en el “CONTRATO”.</li></ol>',\n 'movable': True\n },\n {\n 'titulo': 'Inspecciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a permitir el acceso al “ARRENDADOR” o a la persona que éste '\n 'designe para revisar el estado que guarda el “INMUEBLE” y/o realizar reparaciones, siempre y '\n 'cuando el “ARRENDADOR” avise con por lo menos 3 (tres) días hábiles de anticipación.',\n 'movable': True\n },\n {\n 'titulo': 'Prohibiciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” no podrá guardar o conservar en el “INMUEBLE” materiales prohibidos por la '\n 'ley, materiales inflamables o explosivos y mascotas de cualquier índole, siendo éste '\n 'responsable de los daños y perjuicios que se ocasiones por el incumplimiento de ésta cláusula,'\n ' incluyendo la rescisión del “CONTRATO”',\n 'movable': True\n },\n {\n 'titulo': 'Depósito en Garantía',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a pagar la cantidad de equivalente a 1 (uno) mes de renta como '\n 'depósito en garantía, mismo que se entregará 15 (quince) días calendario posteriores a la '\n 'fecha de vencimiento del “CONTRATO” siempre y cuando el “ARRENDATARIO” haya cumplido con lo '\n 'pactado en el “CONTRATO”. Éste depósito en garantía no podrá ser tomado a cuenta de renta. La '\n 'firma del “CONTRATO” hace la función de recibo del depósito en garantía.</p>'\n '<p>En caso de renovación del “CONTRATO”, la cantidad mencionada en el párrafo anterior sufrirá '\n 'un aumento en la misma proporción de acuerdo a lo pactado en la cláusula tercera del “CONTRATO'\n '”.</p>'\n '<p>Adicional a lo establecido en los párrafos anteriores, El “ARRENDATARIO” entrega al '\n '“ARRENDADOR” la cantidad equivalente a 1 (uno) mes de renta por concepto del primer mes de '\n 'renta anticipada. La firma del “CONTRATO” sirve como recibo de dicho pago.',\n 'movable': True\n },\n {\n 'titulo': 'Acuerdo Total',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El presente “CONTRATO” constituye el acuerdo total entre las “PARTES”, por lo que éstas '\n 'expresamente manifiestan que cualquier otro acuerdo, previo a la firma del “CONTRATO”, oral o '\n 'escrito, tácito o expreso que directa o indirectamente se relacionen con el objeto del '\n '“CONTRATO”, queda desde ahora terminado, siendo el “CONTRATO” el único documento legal que '\n 'rige las obligaciones existentes entre las “PARTES” respecto a lo aquí pactado.</p>'\n '<p>En caso de alguna controversia, judicial o extrajudicial, suscitada respecto de la '\n 'interpretación y cumplimiento del “CONTRATO”, el “ARRENDATARIO” será responsable de los gastos'\n ' y honorarios que se generen, siempre y cuando sea por su culpa o negligencia. '\n 'En caso de suscitarse lo anterior por culpa o negligencia del “ARRENDADOR” éste será '\n 'responsable del pago de gastos y honorarios mencionados.',\n 'movable': True\n },\n {\n 'titulo': 'Penalidad',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Si el “ARRENDATARIO” llegara a desocupar el “INMUEBLE” antes del término pactado por las '\n '“PARTES”, o incurra dentro de ése término en alguna causa de rescisión, se compromete a pagar '\n 'al “ARRENDADOR” el equivalente a las mensualidades restantes. Lo anterior no será aplicable '\n 'cuando la causa de rescisión sea imputable al “ARRENDADOR”.</p>'\n '<p>Las “PARTES” acuerdan que en caso de que al “ARRENDATARIO” se le impida el uso o goce '\n 'parcial del “INMUEBLE”, éste podrá pedir la reducción proporcional de la renta o la rescisión '\n 'del “CONTRATO”, si dicho impedimento durara más de 1 mes.',\n 'movable': True\n },\n {\n 'titulo': 'Buena fe',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” manifiestan que en la elaboración del “CONTRATO” no existe dolo, mala fe ni '\n 'ningún otro vicio del consentimiento que pudiera invalidar parcial o totalmente',\n 'movable': True\n },\n {\n 'titulo': 'Encabezados',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los encabezados de las cláusulas del “CONTRATO” se incluyen como referencia, por lo que la '\n 'interpretación del mismo se hará basado en el contenido de las cláusulas aquí pactadas y no '\n 'respecto a sus encabezados.',\n 'movable': True\n },\n {\n 'titulo': 'Jurisdicción aplicable',\n 'no': '<span class=\"num\">#</span>',\n 'desc': 'Las “PARTES” acuerdan en someterse a la jurisdicción de las leyes, tribunales y jueces del '\n 'estado en donde se encuentra localizado el “INMUEBLE”, para la interpretación y solución de '\n 'controversias que pudieran suscitarse respecto al “CONTRATO”, renunciando así al fuero que les'\n ' corresponda por su domicilio actual o futuro.',\n 'movable': False,\n 'end': True\n },\n {\n 'titulo': 'Mascotas',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Durante la totalidad de la vigencia del contrato, el “ARRENDATARIO” se obliga a no ingresar, '\n 'y/o mantener mascotas de cualquier tipo, raza, o tamaño. Cualquier acto en contravención de lo'\n ' dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a demandar la rescisión del \"CONTRATO\"',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'La cuota mensual de mantenimiento está incluida en el precio de la renta, siendo '\n 'responsabilidad del “ARRENDADOR” realizar este pago en tiempo y forma a la oficina necesaria.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento No Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a cubrir la cuota de mantenimiento que la administración del '\n 'Régimen de Condominio del edificio en donde se encuentra el \"INMUEBLE\", en los días '\n 'que el Consejo de Administración lo determine, debiendo de cubrir dicha cuota en forma mensual y en los '\n 'días establecidos. La falta de pago de más de una mensualidad de la cuota de mantenimiento, '\n 'dará lugar a la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Prohibición de Subarrendamiento',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Queda prohibido traspasar, subarrendar, ceder sus derechos u otorgar en comodato todo o parte '\n 'del \"INMUEBLE\", sin el previo consentimiento por escrito del \"ARRENDADOR\". Cualquier '\n 'acto en contravención de lo dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a '\n 'demandar la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble CASA HABITACIÓN',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del INMUEBLE será exclusivamente el de CASA HABITACIÓN, por lo que si se le da un uso '\n 'distinto al aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble COMERCIAL',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del \"INMUEBLE\" será exclusivamente COMERCIAL, por lo que si se le da un uso distinto al '\n 'aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Seguro',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En todo momento durante el término del “CONTRATO”, el “ARRENDATARIO” deberá mantener el seguro'\n ' que el “ARRENDADOR” razonablemente pueda exigir, incluidos, entre otros, los bienes '\n 'personales y de responsabilidad civil. Específicamente, el \"ARRENDATARIO\" obtendrá y mantendrá '\n 'durante el período, un seguro de responsabilidad general escrito sobre una base de ocurrencia,'\n ' asegurando su responsabilidad por la pérdida o daño de los bienes y lesiones o '\n 'muerte de terceros.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Aval',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Para garantizar el estricto y fiel cumplimiento de todas y cada una de las obligaciones a '\n 'cargo del “ARRENDATARIO” firma este contrato el(la) Señor(a) <input class=\"inpcont\" '\n 'name=\"nombaval\" id=\"nombaval\" size=\"1\" placeholder=\"Nombre del Aval\">, quien se '\n 'constituye como \"AVAL\" único y principal obligado solidario del “ARRENDATARIO”, por todas las'\n ' obligaciones contraídas responsabilidad que no cesará hasta que el “ARRENDATARIO” desocupe el'\n ' \"INMUEBLE\" y no exista obligación alguna por la entrega del \"INMUEBLE\" a '\n 'satisfacción del \"ARRENDADOR\", pudiendo el “AVAL” entregar el \"INMUEBLE\" a nombre del '\n '“ARRENDATARIO”.</p>'\n '<p>El \"AVAL\" señala como domicilio para cumplir sus obligaciones, el ubicado en <input '\n 'class=\"inpcont\" name=\"domaval\" id=\"domaval\" size=\"1\" placeholder=\"Domicilio del Aval\">'\n ', manifestando que es de su propiedad y lo acredita con la copia simple de la escritura '\n 'pública número <input class=\"inpcont\" name=\"noescaval\" id=\"noescaval\" size=\"1\" placeholder=\"No. de escritura'\n ' del aval\">, otorgada ante la fe del Notario Público número <input class=\"inpcont\" '\n 'name=\"nonotaval\" id=\"nonotaval\" size=\"1\" placeholder=\"Número de Notario del Aval\"> de <input class=\"inpcont\" '\n 'name=\"munnotaval\" id=\"munnotaval\" size=\"1\" placeholder=\"Municipio del Notario del Aval\">,'\n ' <input class=\"inpcont\" name=\"estnotaval\" id=\"estnotaval\" size=\"1\" placeholder=\"Estado del Notario del Aval\">, '\n 'con fecha del <input class=\"inpcont\" type=\"date\" name=\"fechaescaval\" id=\"fechaescaval\" size=\"1\" placeholder=\"Fecha de '\n 'escritura del Aval (dd/mm/aaaa)\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input class=\"inpcont\" type=\"date\" name=\"fecharegaval\" id=\"fecharegaval\" size=\"1\" '\n 'placeholder=\"Fecha de registro del Aval\">, bajo el folio '\n 'mercantil número <input class=\"inpcont\" type=\"number\" min=0 name=\"folmerc\" id=\"folmerc\" size=\"1\" '\n 'placeholder=\"Folio Mercantil de la escritura del Aval\">, del Registro Público de la Propiedad '\n 'y Comercio del estado de <input class=\"inpcont\" name=\"estregescaval\" id=\"estregescaval\" size=\"1\" '\n 'placeholder=\"Estado donde fue registrada la escritura del Aval\">'\n ', que se anexa al \"CONTRATO\", mismo que así lo mantendrá hasta que se haya dado '\n 'cumplimiento a todos los términos del \"CONTRATO\" y se haya entregado el \"INMUEBLE\" a '\n 'satisfacción del “ARRENDADOR”, siendo causa de rescisión del \"CONTRATO\", la '\n 'contravención a lo antes estipulado, renunciando a los beneficios de orden y exclusión '\n 'señalados en las leyes aplicables.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Pago Propio de Servicios',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'A partir del inicio de vigencia del “CONTRATO” pactada en la cláusula anterior el '\n '“ARRENDATARIO” se compromete a pagar los servicios de luz, gas, agua, teléfono, cable, '\n 'internet o cualquier otro servicio que llegara a contratar por su cuenta, siendo responsable '\n 'de la cancelación de los mismos al término de la vigencia del “CONTRATO”. Será necesario '\n 'entregar el último recibo pagado de cada uno de los servicios contratados por el “ARRENDATARIO'\n '” al término del “CONTRATO” para la devolución del depósito dejado en garantía.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Servicios Incluidos',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los costos de los servicios de luz, gas, agua, teléfono, cable e internet se verán reflejados'\n ' en el monto mensual de la renta pactado en la Cláusula de Precio. Será responsabilidad del '\n '“ARRENDADOR” mantener el pago actualizado y los servicios necesarios para el “ARRENDATARIO”. '\n 'La cancelación de los servicios por causas imputables al “ARRENDADOR” que duren más de 2 (dos)'\n ' meses, será causal de rescisión del contrato, sin responsabilidad adicional para el '\n '“ARRENDATARIO”.',\n 'movable': True,\n 'optional': True\n }\n ],\n\n 'arrendamientoin-fm':\n [\n {\n 'titulo': 'Entrega',\n 'no': '<span class=\"numi\">1</span>',\n 'desc': 'El “ARRENDADOR” entrega en arrendamiento el “INMUEBLE” en'\n ' buen estado al “ARRENDATARIO”, quien lo recibe a su entera'\n ' satisfacción el <input size=\"1\" type=\"date\" name=\"fechaentrega\" id=\"fechaentrega\" class=\"inpcont\" placeholder=\"Fecha(dd/mm/aaaa)\">,'\n ' en las '\n 'condiciones y para los fines convenidos en el “CONTRATO”.'},\n {\n 'titulo': 'Precio',\n 'no': '<span class=\"numi\">2</span>',\n 'desc': 'Las “PARTES” acuerdan la cantidad de $<input class=\"inpcont\" type=\"number\" step=\"0.01\" min=0 name=\"precio\" '\n 'id=\"precio\" size=\"1\" placeholder=\"Precio con Número\"> (_d pesos 00/100 M.N.) mensuales como '\n 'contraprestación del arrendamiento, dicha cantidad deberá pagarse en mensualidades '\n 'anticipadas en la cuenta bancaria número <input class=\"inpcont\" type=\"number\" min=0 name=\"nocuenta\" id=\"nocuenta\" size=\"1\" '\n 'placeholder=\"No. de Cuenta\"> del banco <input class=\"inpcont\" size=\"1\" name=\"banco\" id=\"banco\" '\n 'placeholder=\"Nombre del Banco\">, clabe <input class=\"inpcont\" size=\"1\" name=\"clabe\" id=\"clabe\" '\n 'placeholder=\"Clabe Bancaria\"> a nombre del “ARRENDADOR” a más '\n 'tardar el día 15 de cada mes o el día hábil siguiente cuando el día 15 sea inhábil.</p>'\n '<p>En caso de que el “ARRENDATARIO” incurra en mora en el pago de la renta, éste se obliga a '\n 'pagar al “ARRENDADOR” un interés del <input class=\"inpcont\" type=\"number\" min=0 step=\"0.01\" size=\"1\" name=\"interes\" id=\"interes\" '\n 'placeholder=\"% de Interés Moratorio\">% (_p por ciento) mensual sobre el '\n 'monto de renta '\n 'adeudado hasta que el se liquide la cantidad adeudada, los pagos que haga el “ARRENDATARIO” se '\n 'aplicarán primeramente a intereses y posteriormente a capital.</p>'\n '<p>El “ARRENDADOR” se compromete a entregar el recibo correspondiente que compruebe el pago de la'\n ' renta a nombre del “ARRENDATARIO”, el cual se deberá entregar sin falta al momento en que el '\n '“ARRENDADOR” reciba el pago o dentro de los siguientes 5 días hábiles.</p>'\n '<p>El “ARRENDATARIO” bajo protesta de decir verdad manifiesta que los recursos monetarios con los'\n ' que hará el pago de la renta estipulada en el “CONTRATO”, son de origen lícito, por lo que no '\n 'representan directa o indirectamente ni provienen de la comisión de algún delito como el lavado '\n 'de dinero, delincuencia organizada o cualquier otra actividad considerada como ilícita por ley.'\n },\n {\n 'titulo': 'Renovación',\n 'no': '<span class=\"numi\">3</span>',\n 'desc': 'En caso de que el “ARRENDADOR” aceptará renovar el “CONTRATO” previo a la fecha de vencimiento del '\n 'mismo, el importe de la renta pactado en la cláusula anterior aumentará anualmente basándose '\n 'en el Índice Nacional de Precios al Consumidor más 3 puntos o proporcionalmente al aumento del'\n ' salario mínimo del estado donde se localiza el INMUEBLE, lo que resulte más alto'\n },\n {\n 'titulo': 'Recepción y Entrega',\n 'no': '<span class=numi\">4</span>',\n 'desc': 'El “ARRENDATARIO” acepta el “INMUEBLE” en excelentes condiciones y en perfecto estado para el '\n 'uso convenido, y se compromete a hacer las reparaciones necesarias al vencimiento del '\n '“CONTRATO”, para entregar el “INMUEBLE” al “ARRENDADOR” en las mismas condiciones en las que '\n 'lo recibió.</p>'\n '<p>En cuanto a las reparaciones arriba mencionadas, el “ARRENDATARIO” no está '\n 'obligado a realizar reparaciones derivadas por el uso o deterioro normal del “INMUEBLE”, sino '\n 'únicamente por los daños ocasionados por negligencia o uso inapropiado de las instalaciones '\n 'del mismo. El “ARRENDADOR” estará encargado de realizar las reparaciones mayores como muros '\n 'interiores y exteriores, techos, pisos y cimentación.</p>'\n '<p>El “ARRENDATARIO” se obliga a dar aviso oportuno al “ARRENDADOR” de cualquier daño en que '\n 'pudiera perjudicar al “INMUEBLE”, siendo el “ARRENDATARIO” responsable de los daños y '\n 'perjuicios ocasionados por la falta de dicho aviso oportuno.</p>'\n '<p>El “ARRENDATARIO” podrá realizar modificaciones y mejoras al “INMUEBLE” con previa '\n 'autorización por escrito al “ARRENDADOR”. En caso de que dichas modificaciones no puedan '\n 'removerse sin dañar la estructura del “INMUEBLE” quedarán en beneficio del “ARRENDADOR” sin '\n 'derecho al “ARRENDATARIO” de cobrar indemnización alguna, las mejoras que puedan removerse sin'\n ' dañar el “INMUEBLE” podrán ser retiradas por el “ARRENDATARIO”.'\n },\n {\n 'titulo': 'Vigencia',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “CONTRATO” tendrá una duración de 1 (uno) año obligatorio y forzoso para las ”PARTES”, '\n 'iniciando su vigencia el día señalado en la Cláusula 1 y terminando el día <input '\n 'class=\"inpcont\" type=\"date\" name=\"fechatermcont\" id=\"fechatermcont\" size=\"1\" placeholder=\"Fecha de Terminación del Contrato (dd/mm/aaaa)\">.'\n '</p>'\n '<p>A la fecha de vencimiento no se entenderá prorrogado el “CONTRATO”, teniendo las '\n '“PARTES” que acordar por escrito la renovación. El “ARRENDATARIO” deberá solicitar por escrito'\n ' y con 45 (cuarenta y cinco) días de anticipación a la fecha de vencimiento, la'\n ' renovación al “ARRENDADOR” éste último se obliga a responder 30 (treinta) días '\n 'previos a la fecha de vencimiento su decisión final.',\n 'movable': True\n },\n {\n 'titulo': 'No Entrega',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En caso de que el “ARRENDATARIO” no desocupe el “INMUEBLE” al término de la vigencia del '\n '“CONTRATO” a entera satisfacción del “ARRENDADOR”, pagará a éste último como penalidad el '\n '50% más del importe '\n 'de la renta mensual que seguirá generando hasta la entrega'\n ' del “INMUEBLE” de acuerdo a lo pactado en el “CONTRATO”.',\n 'movable': True\n },\n {\n 'titulo': 'Caso Fortuito',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que no habrá responsabilidad civil o penal para el “ARRENDADOR” por '\n 'caso fortuito o fuerza mayor, entendiéndose pero no limitando a fenómenos naturales, '\n 'incendios, derrumbes, explosiones y demás que sufriere el “INMUEBLE”, y que afectará al '\n '“ARRENDATARIO” en sus bienes, persona, familiares o visitantes.',\n 'movable': True\n },\n {\n 'titulo': 'Rescisión',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDADOR” podrá rescindir el “CONTRATO” dando 30 (treinta) días naturales al “ARRENDATARIO” para '\n 'la desocupación del “INMUEBLE”, sin obligación alguna ni declaración judicial para el '\n '“ARRENDADOR”, por las siguientes causas:</p>'\n '<ol id=\"Recisión-list-1\"><li>En caso de insolvencia por parte del “ARRENDATARIO” Cuando el “ARRENDATARIO” dejare de'\n ' pagar 2 (dos) '\n 'meses de renta.</li> <li>Cuando el “ARRENDATARIO” incumpla con alguna de las cláusulas '\n 'pactadas en el “CONTRATO”.</li> <li>Cuando se haga mal uso del “INMUEBLE”, que pueda destruirlo o'\n ' causar daños mayores.</li><li> Cuando el “ARRENDATARIO”, sus familiares o visitantes, falten'\n ' al orden moral o lleven a cabo actividades ilícitas dentro del “INMUEBLE”.</li></ol></p>'\n '<p>El “ARRENDATARIO” podrá dar por terminado el “CONTRATO”, sin responsabilidad alguna ni '\n 'necesidad de declaración judicial, en los siguientes casos:'\n '<ol id=\"Recisión-list-2\"><li>Cuando por causas ajenas esté impedido del uso de cualquier servicio básico, '\n 'entendiéndose éstos como luz, agua potable y gas, siempre y cuando sea por causas imputables '\n 'al “ARRENDADOR”.</li><li>Cuando el “ARRENDADOR” le impida el acceso total o parcial al '\n '“INMUEBLE”, sin causa justificada y por razones inimputables al “ARRENDATARIO”.</li><li>Cuando'\n ' el “ARRENDADOR” no lleve a cabo las reparaciones acordadas en el “CONTRATO”.</li></ol>',\n 'movable': True\n },\n {\n 'titulo': 'Inspecciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a permitir el acceso al “ARRENDADOR” o a la persona que éste '\n 'designe para revisar el estado que guarda el “INMUEBLE” y/o realizar reparaciones, siempre y '\n 'cuando el “ARRENDADOR” avise con por lo menos 3 (tres) días hábiles de anticipación.',\n 'movable': True\n },\n {\n 'titulo': 'Prohibiciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” no podrá guardar o conservar en el “INMUEBLE” materiales prohibidos por la '\n 'ley, materiales inflamables o explosivos y mascotas de cualquier índole, siendo éste '\n 'responsable de los daños y perjuicios que se ocasiones por el incumplimiento de ésta cláusula,'\n ' incluyendo la rescisión del “CONTRATO”',\n 'movable': True\n },\n {\n 'titulo': 'Depósito en Garantía',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a pagar la cantidad de equivalente a 1 (uno) mes de renta como '\n 'depósito en garantía, mismo que se entregará 15 (quince) días calendario posteriores a la '\n 'fecha de vencimiento del “CONTRATO” siempre y cuando el “ARRENDATARIO” haya cumplido con lo '\n 'pactado en el “CONTRATO”. Éste depósito en garantía no podrá ser tomado a cuenta de renta. La '\n 'firma del “CONTRATO” hace la función de recibo del depósito en garantía.</p>'\n '<p>En caso de renovación del “CONTRATO”, la cantidad mencionada en el párrafo anterior sufrirá '\n 'un aumento en la misma proporción de acuerdo a lo pactado en la cláusula tercera del “CONTRATO'\n '”.</p>'\n '<p>Adicional a lo establecido en los párrafos anteriores, El “ARRENDATARIO” entrega al '\n '“ARRENDADOR” la cantidad equivalente a 1 (uno) mes de renta por concepto del primer mes de '\n 'renta anticipada. La firma del “CONTRATO” sirve como recibo de dicho pago.',\n 'movable': True\n },\n {\n 'titulo': 'Acuerdo Total',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El presente “CONTRATO” constituye el acuerdo total entre las “PARTES”, por lo que éstas '\n 'expresamente manifiestan que cualquier otro acuerdo, previo a la firma del “CONTRATO”, oral o '\n 'escrito, tácito o expreso que directa o indirectamente se relacionen con el objeto del '\n '“CONTRATO”, queda desde ahora terminado, siendo el “CONTRATO” el único documento legal que '\n 'rige las obligaciones existentes entre las “PARTES” respecto a lo aquí pactado.</p>'\n '<p>En caso de alguna controversia, judicial o extrajudicial, suscitada respecto de la '\n 'interpretación y cumplimiento del “CONTRATO”, el “ARRENDATARIO” será responsable de los gastos'\n ' y honorarios que se generen, siempre y cuando sea por su culpa o negligencia. '\n 'En caso de suscitarse lo anterior por culpa o negligencia del “ARRENDADOR” éste será '\n 'responsable del pago de gastos y honorarios mencionados.',\n 'movable': True\n },\n {\n 'titulo': 'Penalidad',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Si el “ARRENDATARIO” llegara a desocupar el “INMUEBLE” antes del término pactado por las '\n '“PARTES”, o incurra dentro de ése término en alguna causa de rescisión, se compromete a pagar '\n 'al “ARRENDADOR” el equivalente a las mensualidades restantes. Lo anterior no será aplicable '\n 'cuando la causa de rescisión sea imputable al “ARRENDADOR”.</p>'\n '<p>Las “PARTES” acuerdan que en caso de que al “ARRENDATARIO” se le impida el uso o goce '\n 'parcial del “INMUEBLE”, éste podrá pedir la reducción proporcional de la renta o la rescisión '\n 'del “CONTRATO”, si dicho impedimento durara más de 1 mes.',\n 'movable': True\n },\n {\n 'titulo': 'Buena fe',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” manifiestan que en la elaboración del “CONTRATO” no existe dolo, mala fe ni '\n 'ningún otro vicio del consentimiento que pudiera invalidar parcial o totalmente',\n 'movable': True\n },\n {\n 'titulo': 'Encabezados',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los encabezados de las cláusulas del “CONTRATO” se incluyen como referencia, por lo que la '\n 'interpretación del mismo se hará basado en el contenido de las cláusulas aquí pactadas y no '\n 'respecto a sus encabezados.',\n 'movable': True\n },\n {\n 'titulo': 'Jurisdicción aplicable',\n 'no': '<span class=\"num\">#</span>',\n 'desc': 'Las “PARTES” acuerdan en someterse a la jurisdicción de las leyes, tribunales y jueces del '\n 'estado en donde se encuentra localizado el “INMUEBLE”, para la interpretación y solución de '\n 'controversias que pudieran suscitarse respecto al “CONTRATO”, renunciando así al fuero que les'\n ' corresponda por su domicilio actual o futuro.',\n 'movable': False,\n 'end': True\n },\n {\n 'titulo': 'Mascotas',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Durante la totalidad de la vigencia del contrato, el “ARRENDATARIO” se obliga a no ingresar, '\n 'y/o mantener mascotas de cualquier tipo, raza, o tamaño. Cualquier acto en contravención de lo'\n ' dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a demandar la rescisión del \"CONTRATO\"',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'La cuota mensual de mantenimiento está incluida en el precio de la renta, siendo '\n 'responsabilidad del “ARRENDADOR” realizar este pago en tiempo y forma a la oficina necesaria.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento No Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a cubrir la cuota de mantenimiento que la administración del '\n 'Régimen de Condominio del edificio en donde se encuentra el \"INMUEBLE\", en los días '\n 'que el Consejo de Administración lo determine, debiendo de cubrir dicha cuota en forma mensual y en los '\n 'días establecidos. La falta de pago de más de una mensualidad de la cuota de mantenimiento, '\n 'dará lugar a la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Prohibición de Subarrendamiento',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Queda prohibido traspasar, subarrendar, ceder sus derechos u otorgar en comodato todo o parte '\n 'del \"INMUEBLE\", sin el previo consentimiento por escrito del \"ARRENDADOR\". Cualquier '\n 'acto en contravención de lo dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a '\n 'demandar la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble CASA HABITACIÓN',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del INMUEBLE será exclusivamente el de CASA HABITACIÓN, por lo que si se le da un uso '\n 'distinto al aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble COMERCIAL',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del \"INMUEBLE\" será exclusivamente COMERCIAL, por lo que si se le da un uso distinto al '\n 'aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Seguro',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En todo momento durante el término del “CONTRATO”, el “ARRENDATARIO” deberá mantener el seguro'\n ' que el “ARRENDADOR” razonablemente pueda exigir, incluidos, entre otros, los bienes '\n 'personales y de responsabilidad civil. Específicamente, el \"ARRENDATARIO\" obtendrá y mantendrá '\n 'durante el período, un seguro de responsabilidad general escrito sobre una base de ocurrencia,'\n ' asegurando su responsabilidad por la pérdida o daño de los bienes y lesiones o '\n 'muerte de terceros.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Aval',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Para garantizar el estricto y fiel cumplimiento de todas y cada una de las obligaciones a '\n 'cargo del “ARRENDATARIO” firma este contrato el(la) Señor(a) <input class=\"inpcont\" '\n 'name=\"nombaval\" id=\"nombaval\" size=\"1\" placeholder=\"Nombre del Aval\">, quien se '\n 'constituye como \"AVAL\" único y principal obligado solidario del “ARRENDATARIO”, por todas las'\n ' obligaciones contraídas responsabilidad que no cesará hasta que el “ARRENDATARIO” desocupe el'\n ' \"INMUEBLE\" y no exista obligación alguna por la entrega del \"INMUEBLE\" a '\n 'satisfacción del \"ARRENDADOR\", pudiendo el “AVAL” entregar el \"INMUEBLE\" a nombre del '\n '“ARRENDATARIO”.</p>'\n '<p>El \"AVAL\" señala como domicilio para cumplir sus obligaciones, el ubicado en <input '\n 'class=\"inpcont\" name=\"domaval\" id=\"domaval\" size=\"1\" placeholder=\"Domicilio del Aval\">'\n ', manifestando que es de su propiedad y lo acredita con la copia simple de la escritura '\n 'pública número <input class=\"inpcont\" name=\"noescaval\" id=\"noescaval\" size=\"1\" placeholder=\"No. de escritura'\n ' del aval\">, otorgada ante la fe del Notario Público número <input class=\"inpcont\" '\n 'name=\"nonotaval\" id=\"nonotaval\" size=\"1\" placeholder=\"Número de Notario del Aval\"> de <input class=\"inpcont\" '\n 'name=\"munnotaval\" id=\"munnotaval\" size=\"1\" placeholder=\"Municipio del Notario del Aval\">,'\n ' <input class=\"inpcont\" name=\"estnotaval\" id=\"estnotaval\" size=\"1\" placeholder=\"Estado del Notario del Aval\">, '\n 'con fecha del <input class=\"inpcont\" type=\"date\" name=\"fechaescaval\" id=\"fechaescaval\" size=\"1\" placeholder=\"Fecha de '\n 'escritura del Aval (dd/mm/aaaa)\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input class=\"inpcont\" type=\"date\" name=\"fecharegaval\" id=\"fecharegaval\" size=\"1\" '\n 'placeholder=\"Fecha de registro del Aval\">, bajo el folio '\n 'mercantil número <input class=\"inpcont\" type=\"number\" min=0 name=\"folmerc\" id=\"folmerc\" size=\"1\" '\n 'placeholder=\"Folio Mercantil de la escritura del Aval\">, del Registro Público de la Propiedad '\n 'y Comercio del estado de <input class=\"inpcont\" name=\"estregescaval\" id=\"estregescaval\" size=\"1\" '\n 'placeholder=\"Estado donde fue registrada la escritura del Aval\">'\n ', que se anexa al \"CONTRATO\", mismo que así lo mantendrá hasta que se haya dado '\n 'cumplimiento a todos los términos del \"CONTRATO\" y se haya entregado el \"INMUEBLE\" a '\n 'satisfacción del “ARRENDADOR”, siendo causa de rescisión del \"CONTRATO\", la '\n 'contravención a lo antes estipulado, renunciando a los beneficios de orden y exclusión '\n 'señalados en las leyes aplicables.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Pago Propio de Servicios',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'A partir del inicio de vigencia del “CONTRATO” pactada en la cláusula anterior el '\n '“ARRENDATARIO” se compromete a pagar los servicios de luz, gas, agua, teléfono, cable, '\n 'internet o cualquier otro servicio que llegara a contratar por su cuenta, siendo responsable '\n 'de la cancelación de los mismos al término de la vigencia del “CONTRATO”. Será necesario '\n 'entregar el último recibo pagado de cada uno de los servicios contratados por el “ARRENDATARIO'\n '” al término del “CONTRATO” para la devolución del depósito dejado en garantía.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Servicios Incluidos',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los costos de los servicios de luz, gas, agua, teléfono, cable e internet se verán reflejados'\n ' en el monto mensual de la renta pactado en la Cláusula de Precio. Será responsabilidad del '\n '“ARRENDADOR” mantener el pago actualizado y los servicios necesarios para el “ARRENDATARIO”. '\n 'La cancelación de los servicios por causas imputables al “ARRENDADOR” que duren más de 2 (dos)'\n ' meses, será causal de rescisión del contrato, sin responsabilidad adicional para el '\n '“ARRENDATARIO”.',\n 'movable': True,\n 'optional': True\n }\n ],\n\n 'arrendamientoin-mf':\n [\n {\n 'titulo': 'Entrega',\n 'no': '<span class=\"numi\">1</span>',\n 'desc': 'El “ARRENDADOR” entrega en arrendamiento el “INMUEBLE” en'\n ' buen estado al “ARRENDATARIO”, quien lo recibe a su entera'\n ' satisfacción el <input size=\"1\" type=\"date\" name=\"fechaentrega\" id=\"fechaentrega\" class=\"inpcont\" placeholder=\"Fecha(dd/mm/aaaa)\">,'\n ' en las '\n 'condiciones y para los fines convenidos en el “CONTRATO”.'},\n {\n 'titulo': 'Precio',\n 'no': '<span class=\"numi\">2</span>',\n 'desc': 'Las “PARTES” acuerdan la cantidad de $<input class=\"inpcont\" type=\"number\" step=\"0.01\" min=0 name=\"precio\" '\n 'id=\"precio\" size=\"1\" placeholder=\"Precio con Número\"> (_d pesos 00/100 M.N.) mensuales como '\n 'contraprestación del arrendamiento, dicha cantidad deberá pagarse en mensualidades '\n 'anticipadas en la cuenta bancaria número <input class=\"inpcont\" type=\"number\" min=0 name=\"nocuenta\" id=\"nocuenta\" size=\"1\" '\n 'placeholder=\"No. de Cuenta\"> del banco <input class=\"inpcont\" size=\"1\" name=\"banco\" id=\"banco\" '\n 'placeholder=\"Nombre del Banco\">, clabe <input class=\"inpcont\" size=\"1\" name=\"clabe\" id=\"clabe\" '\n 'placeholder=\"Clabe Bancaria\"> a nombre del “ARRENDADOR” a más '\n 'tardar el día 15 de cada mes o el día hábil siguiente cuando el día 15 sea inhábil.</p>'\n '<p>En caso de que el “ARRENDATARIO” incurra en mora en el pago de la renta, éste se obliga a '\n 'pagar al “ARRENDADOR” un interés del <input class=\"inpcont\" type=\"number\" min=0 step=\"0.01\" size=\"1\" name=\"interes\" id=\"interes\" '\n 'placeholder=\"% de Interés Moratorio\">% (_p por ciento) mensual sobre el '\n 'monto de renta '\n 'adeudado hasta que el se liquide la cantidad adeudada, los pagos que haga el “ARRENDATARIO” se '\n 'aplicarán primeramente a intereses y posteriormente a capital.</p>'\n '<p>El “ARRENDADOR” se compromete a entregar el recibo correspondiente que compruebe el pago de la'\n ' renta a nombre del “ARRENDATARIO”, el cual se deberá entregar sin falta al momento en que el '\n '“ARRENDADOR” reciba el pago o dentro de los siguientes 5 días hábiles.</p>'\n '<p>El “ARRENDATARIO” bajo protesta de decir verdad manifiesta que los recursos monetarios con los'\n ' que hará el pago de la renta estipulada en el “CONTRATO”, son de origen lícito, por lo que no '\n 'representan directa o indirectamente ni provienen de la comisión de algún delito como el lavado '\n 'de dinero, delincuencia organizada o cualquier otra actividad considerada como ilícita por ley.'\n },\n {\n 'titulo': 'Renovación',\n 'no': '<span class=\"numi\">3</span>',\n 'desc': 'En caso de que el “ARRENDADOR” aceptará renovar el “CONTRATO” previo a la fecha de vencimiento del '\n 'mismo, el importe de la renta pactado en la cláusula anterior aumentará anualmente basándose '\n 'en el Índice Nacional de Precios al Consumidor más 3 puntos o proporcionalmente al aumento del'\n ' salario mínimo del estado donde se localiza el INMUEBLE, lo que resulte más alto'\n },\n {\n 'titulo': 'Recepción y Entrega',\n 'no': '<span class=numi\">4</span>',\n 'desc': 'El “ARRENDATARIO” acepta el “INMUEBLE” en excelentes condiciones y en perfecto estado para el '\n 'uso convenido, y se compromete a hacer las reparaciones necesarias al vencimiento del '\n '“CONTRATO”, para entregar el “INMUEBLE” al “ARRENDADOR” en las mismas condiciones en las que '\n 'lo recibió.</p>'\n '<p>En cuanto a las reparaciones arriba mencionadas, el “ARRENDATARIO” no está '\n 'obligado a realizar reparaciones derivadas por el uso o deterioro normal del “INMUEBLE”, sino '\n 'únicamente por los daños ocasionados por negligencia o uso inapropiado de las instalaciones '\n 'del mismo. El “ARRENDADOR” estará encargado de realizar las reparaciones mayores como muros '\n 'interiores y exteriores, techos, pisos y cimentación.</p>'\n '<p>El “ARRENDATARIO” se obliga a dar aviso oportuno al “ARRENDADOR” de cualquier daño en que '\n 'pudiera perjudicar al “INMUEBLE”, siendo el “ARRENDATARIO” responsable de los daños y '\n 'perjuicios ocasionados por la falta de dicho aviso oportuno.</p>'\n '<p>El “ARRENDATARIO” podrá realizar modificaciones y mejoras al “INMUEBLE” con previa '\n 'autorización por escrito al “ARRENDADOR”. En caso de que dichas modificaciones no puedan '\n 'removerse sin dañar la estructura del “INMUEBLE” quedarán en beneficio del “ARRENDADOR” sin '\n 'derecho al “ARRENDATARIO” de cobrar indemnización alguna, las mejoras que puedan removerse sin'\n ' dañar el “INMUEBLE” podrán ser retiradas por el “ARRENDATARIO”.'\n },\n {\n 'titulo': 'Vigencia',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “CONTRATO” tendrá una duración de 1 (uno) año obligatorio y forzoso para las ”PARTES”, '\n 'iniciando su vigencia el día señalado en la Cláusula 1 y terminando el día <input '\n 'class=\"inpcont\" type=\"date\" name=\"fechatermcont\" id=\"fechatermcont\" size=\"1\" placeholder=\"Fecha de Terminación del Contrato (dd/mm/aaaa)\">.'\n '</p>'\n '<p>A la fecha de vencimiento no se entenderá prorrogado el “CONTRATO”, teniendo las '\n '“PARTES” que acordar por escrito la renovación. El “ARRENDATARIO” deberá solicitar por escrito'\n ' y con 45 (cuarenta y cinco) días de anticipación a la fecha de vencimiento, la'\n ' renovación al “ARRENDADOR” éste último se obliga a responder 30 (treinta) días '\n 'previos a la fecha de vencimiento su decisión final.',\n 'movable': True\n },\n {\n 'titulo': 'No Entrega',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En caso de que el “ARRENDATARIO” no desocupe el “INMUEBLE” al término de la vigencia del '\n '“CONTRATO” a entera satisfacción del “ARRENDADOR”, pagará a éste último como penalidad el '\n '50% más del importe '\n 'de la renta mensual que seguirá generando hasta la entrega'\n ' del “INMUEBLE” de acuerdo a lo pactado en el “CONTRATO”.',\n 'movable': True\n },\n {\n 'titulo': 'Caso Fortuito',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que no habrá responsabilidad civil o penal para el “ARRENDADOR” por '\n 'caso fortuito o fuerza mayor, entendiéndose pero no limitando a fenómenos naturales, '\n 'incendios, derrumbes, explosiones y demás que sufriere el “INMUEBLE”, y que afectará al '\n '“ARRENDATARIO” en sus bienes, persona, familiares o visitantes.',\n 'movable': True\n },\n {\n 'titulo': 'Rescisión',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDADOR” podrá rescindir el “CONTRATO” dando 30 (treinta) días naturales al “ARRENDATARIO” para '\n 'la desocupación del “INMUEBLE”, sin obligación alguna ni declaración judicial para el '\n '“ARRENDADOR”, por las siguientes causas:</p>'\n '<ol id=\"Recisión-list-1\"><li>En caso de insolvencia por parte del “ARRENDATARIO” Cuando el “ARRENDATARIO” dejare de'\n ' pagar 2 (dos) '\n 'meses de renta.</li> <li>Cuando el “ARRENDATARIO” incumpla con alguna de las cláusulas '\n 'pactadas en el “CONTRATO”.</li> <li>Cuando se haga mal uso del “INMUEBLE”, que pueda destruirlo o'\n ' causar daños mayores.</li><li> Cuando el “ARRENDATARIO”, sus familiares o visitantes, falten'\n ' al orden moral o lleven a cabo actividades ilícitas dentro del “INMUEBLE”.</li></ol></p>'\n '<p>El “ARRENDATARIO” podrá dar por terminado el “CONTRATO”, sin responsabilidad alguna ni '\n 'necesidad de declaración judicial, en los siguientes casos:'\n '<ol id=\"Recisión-list-2\"><li>Cuando por causas ajenas esté impedido del uso de cualquier servicio básico, '\n 'entendiéndose éstos como luz, agua potable y gas, siempre y cuando sea por causas imputables '\n 'al “ARRENDADOR”.</li><li>Cuando el “ARRENDADOR” le impida el acceso total o parcial al '\n '“INMUEBLE”, sin causa justificada y por razones inimputables al “ARRENDATARIO”.</li><li>Cuando'\n ' el “ARRENDADOR” no lleve a cabo las reparaciones acordadas en el “CONTRATO”.</li></ol>',\n 'movable': True\n },\n {\n 'titulo': 'Inspecciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a permitir el acceso al “ARRENDADOR” o a la persona que éste '\n 'designe para revisar el estado que guarda el “INMUEBLE” y/o realizar reparaciones, siempre y '\n 'cuando el “ARRENDADOR” avise con por lo menos 3 (tres) días hábiles de anticipación.',\n 'movable': True\n },\n {\n 'titulo': 'Prohibiciones',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” no podrá guardar o conservar en el “INMUEBLE” materiales prohibidos por la '\n 'ley, materiales inflamables o explosivos y mascotas de cualquier índole, siendo éste '\n 'responsable de los daños y perjuicios que se ocasiones por el incumplimiento de ésta cláusula,'\n ' incluyendo la rescisión del “CONTRATO”',\n 'movable': True\n },\n {\n 'titulo': 'Depósito en Garantía',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a pagar la cantidad de equivalente a 1 (uno) mes de renta como '\n 'depósito en garantía, mismo que se entregará 15 (quince) días calendario posteriores a la '\n 'fecha de vencimiento del “CONTRATO” siempre y cuando el “ARRENDATARIO” haya cumplido con lo '\n 'pactado en el “CONTRATO”. Éste depósito en garantía no podrá ser tomado a cuenta de renta. La '\n 'firma del “CONTRATO” hace la función de recibo del depósito en garantía.</p>'\n '<p>En caso de renovación del “CONTRATO”, la cantidad mencionada en el párrafo anterior sufrirá '\n 'un aumento en la misma proporción de acuerdo a lo pactado en la cláusula tercera del “CONTRATO'\n '”.</p>'\n '<p>Adicional a lo establecido en los párrafos anteriores, El “ARRENDATARIO” entrega al '\n '“ARRENDADOR” la cantidad equivalente a 1 (uno) mes de renta por concepto del primer mes de '\n 'renta anticipada. La firma del “CONTRATO” sirve como recibo de dicho pago.',\n 'movable': True\n },\n {\n 'titulo': 'Acuerdo Total',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El presente “CONTRATO” constituye el acuerdo total entre las “PARTES”, por lo que éstas '\n 'expresamente manifiestan que cualquier otro acuerdo, previo a la firma del “CONTRATO”, oral o '\n 'escrito, tácito o expreso que directa o indirectamente se relacionen con el objeto del '\n '“CONTRATO”, queda desde ahora terminado, siendo el “CONTRATO” el único documento legal que '\n 'rige las obligaciones existentes entre las “PARTES” respecto a lo aquí pactado.</p>'\n '<p>En caso de alguna controversia, judicial o extrajudicial, suscitada respecto de la '\n 'interpretación y cumplimiento del “CONTRATO”, el “ARRENDATARIO” será responsable de los gastos'\n ' y honorarios que se generen, siempre y cuando sea por su culpa o negligencia. '\n 'En caso de suscitarse lo anterior por culpa o negligencia del “ARRENDADOR” éste será '\n 'responsable del pago de gastos y honorarios mencionados.',\n 'movable': True\n },\n {\n 'titulo': 'Penalidad',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Si el “ARRENDATARIO” llegara a desocupar el “INMUEBLE” antes del término pactado por las '\n '“PARTES”, o incurra dentro de ése término en alguna causa de rescisión, se compromete a pagar '\n 'al “ARRENDADOR” el equivalente a las mensualidades restantes. Lo anterior no será aplicable '\n 'cuando la causa de rescisión sea imputable al “ARRENDADOR”.</p>'\n '<p>Las “PARTES” acuerdan que en caso de que al “ARRENDATARIO” se le impida el uso o goce '\n 'parcial del “INMUEBLE”, éste podrá pedir la reducción proporcional de la renta o la rescisión '\n 'del “CONTRATO”, si dicho impedimento durara más de 1 mes.',\n 'movable': True\n },\n {\n 'titulo': 'Buena fe',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” manifiestan que en la elaboración del “CONTRATO” no existe dolo, mala fe ni '\n 'ningún otro vicio del consentimiento que pudiera invalidar parcial o totalmente',\n 'movable': True\n },\n {\n 'titulo': 'Encabezados',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los encabezados de las cláusulas del “CONTRATO” se incluyen como referencia, por lo que la '\n 'interpretación del mismo se hará basado en el contenido de las cláusulas aquí pactadas y no '\n 'respecto a sus encabezados.',\n 'movable': True\n },\n {\n 'titulo': 'Jurisdicción aplicable',\n 'no': '<span class=\"num\">#</span>',\n 'desc': 'Las “PARTES” acuerdan en someterse a la jurisdicción de las leyes, tribunales y jueces del '\n 'estado en donde se encuentra localizado el “INMUEBLE”, para la interpretación y solución de '\n 'controversias que pudieran suscitarse respecto al “CONTRATO”, renunciando así al fuero que les'\n ' corresponda por su domicilio actual o futuro.',\n 'movable': False,\n 'end': True\n },\n {\n 'titulo': 'Mascotas',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Durante la totalidad de la vigencia del contrato, el “ARRENDATARIO” se obliga a no ingresar, '\n 'y/o mantener mascotas de cualquier tipo, raza, o tamaño. Cualquier acto en contravención de lo'\n ' dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a demandar la rescisión del \"CONTRATO\"',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'La cuota mensual de mantenimiento está incluida en el precio de la renta, siendo '\n 'responsabilidad del “ARRENDADOR” realizar este pago en tiempo y forma a la oficina necesaria.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Cuota de Mantenimiento No Incluida',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “ARRENDATARIO” se obliga a cubrir la cuota de mantenimiento que la administración del '\n 'Régimen de Condominio del edificio en donde se encuentra el \"INMUEBLE\", en los días '\n 'que el Consejo de Administración lo determine, debiendo de cubrir dicha cuota en forma mensual y en los '\n 'días establecidos. La falta de pago de más de una mensualidad de la cuota de mantenimiento, '\n 'dará lugar a la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Prohibición de Subarrendamiento',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Queda prohibido traspasar, subarrendar, ceder sus derechos u otorgar en comodato todo o parte '\n 'del \"INMUEBLE\", sin el previo consentimiento por escrito del \"ARRENDADOR\". Cualquier '\n 'acto en contravención de lo dispuesto por la presente cláusula dará derecho al \"ARRENDADOR\" a '\n 'demandar la rescisión del \"CONTRATO\".',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble CASA HABITACIÓN',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del INMUEBLE será exclusivamente el de CASA HABITACIÓN, por lo que si se le da un uso '\n 'distinto al aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Destino del Inmueble COMERCIAL',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El uso del \"INMUEBLE\" será exclusivamente COMERCIAL, por lo que si se le da un uso distinto al '\n 'aquí señalado será causa suficiente para rescindir el \"CONTRATO\".</p>'\n '<p>En el supuesto caso de que el “ARRENDATARIO” destine el \"INMUEBLE\" a otro fin que el '\n 'señalado, será responsable de defender e indemnizar al “ARRENDADOR” por la totalidad del '\n 'valor de los daños causados.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Seguro',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'En todo momento durante el término del “CONTRATO”, el “ARRENDATARIO” deberá mantener el seguro'\n ' que el “ARRENDADOR” razonablemente pueda exigir, incluidos, entre otros, los bienes '\n 'personales y de responsabilidad civil. Específicamente, el \"ARRENDATARIO\" obtendrá y mantendrá '\n 'durante el período, un seguro de responsabilidad general escrito sobre una base de ocurrencia,'\n ' asegurando su responsabilidad por la pérdida o daño de los bienes y lesiones o '\n 'muerte de terceros.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Aval',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Para garantizar el estricto y fiel cumplimiento de todas y cada una de las obligaciones a '\n 'cargo del “ARRENDATARIO” firma este contrato el(la) Señor(a) <input class=\"inpcont\" '\n 'name=\"nombaval\" id=\"nombaval\" size=\"1\" placeholder=\"Nombre del Aval\">, quien se '\n 'constituye como \"AVAL\" único y principal obligado solidario del “ARRENDATARIO”, por todas las'\n ' obligaciones contraídas responsabilidad que no cesará hasta que el “ARRENDATARIO” desocupe el'\n ' \"INMUEBLE\" y no exista obligación alguna por la entrega del \"INMUEBLE\" a '\n 'satisfacción del \"ARRENDADOR\", pudiendo el “AVAL” entregar el \"INMUEBLE\" a nombre del '\n '“ARRENDATARIO”.</p>'\n '<p>El \"AVAL\" señala como domicilio para cumplir sus obligaciones, el ubicado en <input '\n 'class=\"inpcont\" name=\"domaval\" id=\"domaval\" size=\"1\" placeholder=\"Domicilio del Aval\">'\n ', manifestando que es de su propiedad y lo acredita con la copia simple de la escritura '\n 'pública número <input class=\"inpcont\" name=\"noescaval\" id=\"noescaval\" size=\"1\" placeholder=\"No. de escritura'\n ' del aval\">, otorgada ante la fe del Notario Público número <input class=\"inpcont\" '\n 'name=\"nonotaval\" id=\"nonotaval\" size=\"1\" placeholder=\"Número de Notario del Aval\"> de <input class=\"inpcont\" '\n 'name=\"munnotaval\" id=\"munnotaval\" size=\"1\" placeholder=\"Municipio del Notario del Aval\">,'\n ' <input class=\"inpcont\" name=\"estnotaval\" id=\"estnotaval\" size=\"1\" placeholder=\"Estado del Notario del Aval\">, '\n 'con fecha del <input class=\"inpcont\" type=\"date\" name=\"fechaescaval\" id=\"fechaescaval\" size=\"1\" placeholder=\"Fecha de '\n 'escritura del Aval (dd/mm/aaaa)\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input class=\"inpcont\" type=\"date\" name=\"fecharegaval\" id=\"fecharegaval\" size=\"1\" '\n 'placeholder=\"Fecha de registro del Aval\">, bajo el folio '\n 'mercantil número <input class=\"inpcont\" type=\"number\" min=0 name=\"folmerc\" id=\"folmerc\" size=\"1\" '\n 'placeholder=\"Folio Mercantil de la escritura del Aval\">, del Registro Público de la Propiedad '\n 'y Comercio del estado de <input class=\"inpcont\" name=\"estregescaval\" id=\"estregescaval\" size=\"1\" '\n 'placeholder=\"Estado donde fue registrada la escritura del Aval\">'\n ', que se anexa al \"CONTRATO\", mismo que así lo mantendrá hasta que se haya dado '\n 'cumplimiento a todos los términos del \"CONTRATO\" y se haya entregado el \"INMUEBLE\" a '\n 'satisfacción del “ARRENDADOR”, siendo causa de rescisión del \"CONTRATO\", la '\n 'contravención a lo antes estipulado, renunciando a los beneficios de orden y exclusión '\n 'señalados en las leyes aplicables.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Pago Propio de Servicios',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'A partir del inicio de vigencia del “CONTRATO” pactada en la cláusula anterior el '\n '“ARRENDATARIO” se compromete a pagar los servicios de luz, gas, agua, teléfono, cable, '\n 'internet o cualquier otro servicio que llegara a contratar por su cuenta, siendo responsable '\n 'de la cancelación de los mismos al término de la vigencia del “CONTRATO”. Será necesario '\n 'entregar el último recibo pagado de cada uno de los servicios contratados por el “ARRENDATARIO'\n '” al término del “CONTRATO” para la devolución del depósito dejado en garantía.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Servicios Incluidos',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los costos de los servicios de luz, gas, agua, teléfono, cable e internet se verán reflejados'\n ' en el monto mensual de la renta pactado en la Cláusula de Precio. Será responsabilidad del '\n '“ARRENDADOR” mantener el pago actualizado y los servicios necesarios para el “ARRENDATARIO”. '\n 'La cancelación de los servicios por causas imputables al “ARRENDADOR” que duren más de 2 (dos)'\n ' meses, será causal de rescisión del contrato, sin responsabilidad adicional para el '\n '“ARRENDATARIO”.',\n 'movable': True,\n 'optional': True\n }\n ],\n 'donacion':\n [\n {\n 'titulo': 'Objeto',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “DONANTE” en este acto, dona de la forma establecida más adelante en este contrato al '\n '“DONATARIO”, <input class=\"inpcont\" name=\"bienocantdon\" id=\"bienocantdon\" size=\"1\" '\n 'placeholder=\"Bien Mueble, o Cantidad a Donar\">, con todo lo que por derecho corresponda, '\n 'quien acepta de forma expresa dicha donación a título de Donación.',\n 'movable': True\n },\n {\n 'titulo': 'Entrega',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El “DONANTE” por medio de éste acto dona el “BIEN MUEBLE” al “DONATARIO”, quien lo acepta '\n 'a su entera satisfacción a la fecha de firma del “CONTRATO”.',\n 'movable': True\n },\n {\n 'titulo': 'Caso fortuito y fuerza mayor',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que no habrá responsabilidad civil o penal para el “DONANTE” por '\n 'caso fortuito o fuerza mayor, entendiéndose pero no limitando a fenómenos naturales, '\n 'incendios, derrumbes, explosiones y demás que sufriere el “BIEN MUEBLE”, y que afectará '\n 'al “DONATARIO” en sus bienes, persona, familiares o visitantes.',\n 'movable': True\n },\n {\n 'titulo': 'Acuerdo Total',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'El presente “CONTRATO” constituye el acuerdo total entre las “PARTES”, por lo que éstas '\n 'expresamente manifiestan que cualquier otro acuerdo, previo a la firma del “CONTRATO”, '\n 'oral o escrito, tácito o expreso que directa o indirectamente se relacionen con el objeto '\n 'del “CONTRATO”, queda desde ahora terminado, siendo el “CONTRATO” el único documento legal'\n ' que rige las obligaciones existentes entre las “PARTES” respecto a lo aquí pactado.</p>'\n '<p>En caso de alguna controversia, judicial o extrajudicial, suscitada respecto de la '\n 'interpretación y cumplimiento del “CONTRATO”, el “DONATARIO” será responsable de los '\n 'gastos y honorarios que se generen.',\n 'movable': True\n },\n {\n 'titulo': 'Buena Fe',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” manifiestan que en la elaboración del “CONTRATO” no existe dolo, mala fe ni '\n 'ningún otro vicio del consentimiento que pudiera invalidarlo parcial o totalmente.',\n 'movable': True\n },\n {\n 'titulo': 'Encabezados',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Los encabezados de las cláusulas del “CONTRATO” se incluyen como referencia, por lo que la'\n ' interpretación del mismo se hará basado en el contenido de las cláusulas aquí pactadas y '\n 'no respecto a sus encabezados.',\n 'movable': True\n },\n {\n 'titulo': 'Jurisdicción Aplicable',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan en someterse a la jurisdicción de las leyes, tribunales y jueces del'\n ' estado de <input class=\"inpcont\" name=\"estadofirma\" id=\"estadofirma\" size=\"1\" placeholder'\n '=\"Estado donde se Firma el Contrato\">, para la interpretación y solución de controversias '\n 'que pudieran suscitarse respecto al “CONTRATO”, renunciando así al fuero que les '\n 'correspondiere por su domicilio actual o futuro.',\n 'movable': True\n },\n {\n 'titulo': 'Donación Pura',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que la donación es pura, por lo que el “DONANTE” la otorga en '\n 'términos absolutos.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Donación Condicional',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que la donación es condicional, por lo que se entiende que surtirá '\n 'efectos a partir de que <input class=\"inpcont\" name=\"condicion\" id=\"condicion\" size=\"1\"'\n 'placeholder=\"Condición impuesta por Donatario basada en Acontecimiento Incierto\">.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Donación Onerosa',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que la donación es onerosa, por lo que se entiende que para que '\n 'surta efectos el “DONATARIO” se obliga a pagar los gravámenes correspondientes y que '\n 'consisten en <input class=\"inpcont\" name=\"gravamenes\" id=\"gravamenes\" size=\"1\"'\n 'placeholder=\"Gravámenes impuestos por Donatario\">.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Donación Remuneratoria',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” acuerdan que la donación es remuneratoria, ya que se hace en atención a los '\n 'servicios otorgados al “DONANTE” por el “DONATARIO”, y los cuales consisten en '\n '<input class=\"inpcont\" name=\"serviciosprestados\" id=\"serviciosprestados\" size=\"1\"'\n 'placeholder=\"Servicios presatods por el Donatario al Donante\">.</p>'\n '<p>Las “PARTES” reconocen que no es obligación del “DONATARIO” el pago de los servicios '\n 'arriba mencionados, por lo que acuerdan celebrar el presente “CONTRATO”.',\n 'movable': True,\n 'optional': True\n },\n {\n 'titulo': 'Donación entre cónyugues',\n 'no': '<span class=\"numero\">#</span>',\n 'desc': 'Las “PARTES” reconocen que la celebración de éste “CONTRATO” no causa el Impuesto Sobre '\n 'la Renta (ISR) en virtud de tratarse de un acuerdo celebrado entre cónyuges.',\n 'movable': True,\n 'optional': True\n }\n ]\n }\n for key, clausulas in clausulas_dict.items():\n for clausula in clausulas:\n for i, value in ids_contratos.items():\n if i == key:\n clausula['id_contrato'] = value\n ccvb = Clausulas.query.filter_by(id_contrato=value, titulo=clausula['titulo']).first()\n if ccvb is None:\n ccvb = Clausulas(**clausula)\n db.session.add(ccvb)\n db.session.commit()\n else:\n if ccvb.desc != clausula['desc']:\n ccvb.desc = clausula['desc']\n db.session.commit()\n declaraciones_dict = {\n 'arrendamiento-inmueble': [\n {\n 'titulo': 'primera',\n 'desc': '<p id=\"bdec1\"> I. Declara el <b>\"ARRENDADOR\":</b></p>'\n '<p><ol id=\"bolist1\"><li>Ser una persona física, mayor de edad, con plena capacidad para realizar el '\n 'presente acto.</li><li>Ser propietario del inmueble localizado en <input size=\"1\" class=\"inpcont\" '\n 'name=\"direccioninmueble\" id=\"direccioninmueble\" placeholder=\"Dirección del Inmueble\">, tal como lo acredita mediante '\n 'escritura pública número <input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub\" id=\"noescpub\" placeholder=\"No. de escritura'\n ' Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" name=\"nonotario\" class=\"inpcont\" '\n 'id=\"nonotatrio\" placeholder=\"Número de Notario\"> de <input size=\"1\" name=\"dirnotario\" class=\"inpcont\" id=\"dirnotario\" '\n 'placeholder=\"Municipio y Estado del Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" '\n 'name=\"fechafirmaesc\" id=\"fechafirmaesc\" placeholder=\"Fecha de firma de la Escritura(dd/mm/aaaa)\">, misma que se encuentra debidamente '\n 'registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechareg\" id=\"fechareg\" placeholder=\"Fecha de registro(dd/mm/aaaa)\">'\n ', bajo el folio mercantil número <input size=\"1\" class=\"inpcont\" name=\"foliomerc\" id=\"foliomerc\" placeholder=\"Número de '\n 'Folio Mercantil\">, del Registro Público de la Propiedad y Comercio del estado de <input size=\"1\" '\n 'class=\"inpcont\" name=\"estadoreg\" id=\"estadoreg\" placeholder=\"Estado donde se Registró\">, en lo sucesivo el '\n '“INMUEBLE”.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener como domicilio para recibir todo tipo de notificaciones el '\n 'ubicado en <input size=\"1\" class=\"inpcont\" name=\"dirdomnot\" id=\"dirdomnot\" placeholder=\"Domicilio de Notificaciones del '\n 'Arrendador\">.</li></ol></p>'\n '<p id=\"bdec2\"> II. Declara el <b>\"ARRENDATARIO\":</b></p>'\n '<p><ol id=\"bolist2\"><li>Ser persona física, mayor de edad, con plena capacidad para realizar el presente '\n 'acto.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener el “INMUEBLE” como domicilio para recibir todo tipo de '\n 'notificaciones.</li></ol></p>'\n }\n ],\n 'arrendamientoin-mm': [\n {\n 'titulo': 'primera',\n 'desc': '<p id=\"bdec1\"> I. Declara el <b>\"ARRENDADOR\":</b></p>'\n '<p><ol id=\"bolist1\"><li>Ser una sociedad legalmente constituida y en operación conforme a las '\n 'leyes de los Estados Unidos Mexicanos, como lo acredita mediante escritura pública número '\n '<input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub\" id=\"noescpub\" placeholder=\"Número de Escritura Pública\">'\n ', otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot\" id=\"nonot\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot\" id=\"dirnot\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc\" id=\"'\n 'fechafirmesc\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop\" id=\"fecharegprop\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc\" '\n 'id=\"nofoliomerc\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop\" id=\"estadoregprop\" placeholder=\"Estado Donde se Registró\">.</li>'\n '<li>Su representante legal cuenta con las facultades necesarias para obligarla en los términos'\n ' del presente Contrato tal y como lo acredita mediante escritura pública número <input size=\"1\"'\n ' type=\"number\" min=0 class=\"inpcont\" name=\"noescpub2\" id=\"noescpub2\" placeholder=\"'\n 'Número de Escritura Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot2\" id=\"nonot2\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot2\" id=\"dirnot2\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc2\" id=\"'\n 'fechafirmesc2\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop2\" id=\"fecharegprop2\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc2\" '\n 'id=\"nofoliomerc2\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop2\" id=\"estadoregprop2\" placeholder=\"Estado Donde se Registró\">, facultades que no'\n ' les han sido limitadas, revocadas o modificadas de forma alguna a la fecha de este Contrato.'\n '</li>'\n '<li>Tiene como domicilio fiscal, y para recibir todo tipo de notificaciones el ubicado en '\n '<input size=\"1\" type=\"text\" class=\"inpcont\" name=\"dirinmu\" id=\"dirinmu\" placeholder=\"Dirección'\n ' del Inmueble\">, estando debidamente inscrita el Registro Federal de Contribuyentes bajo la '\n 'clave <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"RFC\" id=\"RFC\" placeholder=\"'\n 'Clave de RFC\">.</li>'\n '<li>Que su objeto social le permite la celebración del presente Contrato.</li>'\n '<li>Ser propietario del inmueble localizado en <input size=\"1\" class=\"inpcont\" '\n 'name=\"direccioninmueble3\" id=\"direccioninmueble3\" placeholder=\"Dirección del Inmueble\">, tal como lo acredita mediante '\n 'escritura pública número <input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub3\" id=\"noescpub3\" placeholder=\"No. de escritura'\n ' Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" name=\"nonotario3\" class=\"inpcont\" '\n 'id=\"nonotatrio3\" placeholder=\"Número de Notario\"> de <input size=\"1\" name=\"dirnotario3\" class=\"inpcont\" id=\"dirnotario3\" '\n 'placeholder=\"Municipio y Estado del Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" '\n 'name=\"fechafirmaesc3\" id=\"fechafirmaesc3\" placeholder=\"Fecha de firma de la Escritura(dd/mm/aaaa)\">, misma que se encuentra debidamente '\n 'registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechareg3\" id=\"fechareg3\" placeholder=\"Fecha de registro(dd/mm/aaaa)\">'\n ', bajo el folio mercantil número <input size=\"1\" class=\"inpcont\" name=\"foliomerc3\" id=\"foliomerc3\" placeholder=\"Número de '\n 'Folio Mercantil\">, del Registro Público de la Propiedad y Comercio del estado de <input size=\"1\" '\n 'class=\"inpcont\" name=\"estadoreg3\" id=\"estadoreg3\" placeholder=\"Estado donde se Registró\">, en lo sucesivo el '\n '“INMUEBLE”.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li></ol></p>'\n '<p id=\"bdec2\"> II. Declara el <b>\"ARRENDATARIO\":</b></p>'\n '<p><ol id=\"bolist2\"><li>Ser una sociedad legalmente constituida y en operación conforme a las '\n 'leyes de los Estados Unidos Mexicanos, como lo acredita mediante escritura pública número '\n '<input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub4\" id=\"noescpub4\" placeholder=\"Número de Escritura Pública\">'\n ', otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot4\" id=\"nonot4\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot4\" id=\"dirnot4\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc4\" id=\"'\n 'fechafirmesc4\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop4\" id=\"fecharegprop4\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc4\" '\n 'id=\"nofoliomerc4\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop4\" id=\"estadoregprop4\" placeholder=\"Estado Donde se Registró\">.</li>'\n '<li>Su representante legal cuenta con las facultades necesarias para obligarla en los términos'\n ' del presente Contrato tal y como lo acredita mediante escritura pública número <input size=\"1\"'\n ' type=\"number\" min=0 class=\"inpcont\" name=\"noescpub5\" id=\"noescpub5\" placeholder=\"'\n 'Número de Escritura Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot5\" id=\"nonot5\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot5\" id=\"dirnot5\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc5\" id=\"'\n 'fechafirmesc5\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop5\" id=\"fecharegprop5\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc5\" '\n 'id=\"nofoliomerc5\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop5\" id=\"estadoregprop5\" placeholder=\"Estado Donde se Registró\">, facultades que no'\n ' les han sido limitadas, revocadas o modificadas de forma alguna a la fecha de este Contrato.'\n '</li>'\n '<li>Tiene como domicilio fiscal el ubicado en '\n '<input size=\"1\" type=\"text\" class=\"inpcont\" name=\"dirarr5\" id=\"dirarr5\" placeholder=\"Dirección'\n ' del Inmueble\">, estando debidamente inscrita el Registro Federal de Contribuyentes bajo la '\n 'clave <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"RFC5\" id=\"RFC5\" placeholder=\"'\n 'Clave de RFC\">.</li>'\n '<li>Que su objeto social le permite la celebración del presente Contrato.</li>'\n '<li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '\"CONTRATO\".</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener el “INMUEBLE” como domicilio para recibir todo tipo de '\n 'notificaciones.</li></ol></p>'\n }\n ],\n 'arrendamientoin-fm': [\n {\n 'titulo': 'primera',\n 'desc': '<p id=\"bdec1\"> I. Declara el <b>\"ARRENDADOR\":</b></p>'\n '<p><ol id=\"bolist1\"><li>Ser una persona física, mayor de edad, con plena capacidad para realizar el '\n 'presente acto.</li><li>Ser propietario del inmueble localizado en <input size=\"1\" class=\"inpcont\" '\n 'name=\"direccioninmueble\" id=\"direccioninmueble\" placeholder=\"Dirección del Inmueble\">, tal como lo acredita mediante '\n 'escritura pública número <input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub\" id=\"noescpub\" placeholder=\"No. de escritura'\n ' Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" name=\"nonotario\" class=\"inpcont\" '\n 'id=\"nonotatrio\" placeholder=\"Número de Notario\"> de <input size=\"1\" name=\"dirnotario\" class=\"inpcont\" id=\"dirnotario\" '\n 'placeholder=\"Municipio y Estado del Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" '\n 'name=\"fechafirmaesc\" id=\"fechafirmaesc\" placeholder=\"Fecha de firma de la Escritura(dd/mm/aaaa)\">, misma que se encuentra debidamente '\n 'registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechareg\" id=\"fechareg\" placeholder=\"Fecha de registro(dd/mm/aaaa)\">'\n ', bajo el folio mercantil número <input size=\"1\" class=\"inpcont\" name=\"foliomerc\" id=\"foliomerc\" placeholder=\"Número de '\n 'Folio Mercantil\">, del Registro Público de la Propiedad y Comercio del estado de <input size=\"1\" '\n 'class=\"inpcont\" name=\"estadoreg\" id=\"estadoreg\" placeholder=\"Estado donde se Registró\">, en lo sucesivo el '\n '“INMUEBLE”.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener como domicilio para recibir todo tipo de notificaciones el '\n 'ubicado en <input size=\"1\" class=\"inpcont\" name=\"dirdomnot\" id=\"dirdomnot\" placeholder=\"Domicilio de Notificaciones del '\n 'Arrendador\">.</li></ol></p>'\n '<p id=\"bdec2\"> II. Declara el <b>\"ARRENDATARIO\":</b></p>'\n '<p><ol id=\"bolist2\"><li>Ser una sociedad legalmente constituida y en operación conforme a las '\n 'leyes de los Estados Unidos Mexicanos, como lo acredita mediante escritura pública número '\n '<input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub4\" id=\"noescpub4\" placeholder=\"Número de Escritura Pública\">'\n ', otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot4\" id=\"nonot4\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot4\" id=\"dirnot4\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc4\" id=\"'\n 'fechafirmesc4\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop4\" id=\"fecharegprop4\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc4\" '\n 'id=\"nofoliomerc4\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop4\" id=\"estadoregprop4\" placeholder=\"Estado Donde se Registró\">.</li>'\n '<li>Su representante legal cuenta con las facultades necesarias para obligarla en los términos'\n ' del presente Contrato tal y como lo acredita mediante escritura pública número <input size=\"1\"'\n ' type=\"number\" min=0 class=\"inpcont\" name=\"noescpub5\" id=\"noescpub5\" placeholder=\"'\n 'Número de Escritura Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot5\" id=\"nonot5\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot5\" id=\"dirnot5\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc5\" id=\"'\n 'fechafirmesc5\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop5\" id=\"fecharegprop5\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc5\" '\n 'id=\"nofoliomerc5\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop5\" id=\"estadoregprop5\" placeholder=\"Estado Donde se Registró\">, facultades que no'\n ' les han sido limitadas, revocadas o modificadas de forma alguna a la fecha de este Contrato.'\n '</li>'\n '<li>Tiene como domicilio fiscal el ubicado en '\n '<input size=\"1\" type=\"text\" class=\"inpcont\" name=\"dirarr5\" id=\"dirarr5\" placeholder=\"Dirección'\n ' del Inmueble\">, estando debidamente inscrita el Registro Federal de Contribuyentes bajo la '\n 'clave <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"RFC5\" id=\"RFC5\" placeholder=\"'\n 'Clave de RFC\">.</li>'\n '<li>Que su objeto social le permite la celebración del presente Contrato.</li>'\n '<li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '\"CONTRATO\".</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener el “INMUEBLE” como domicilio para recibir todo tipo de '\n 'notificaciones.</li></ol></p>'\n }\n ],\n 'arrendamientoin-mf': [\n {\n 'titulo': 'primera',\n 'desc': '<p id=\"bdec1\"> I. Declara el <b>\"ARRENDADOR\":</b></p>'\n '<p><ol id=\"bolist1\"><li>Ser una sociedad legalmente constituida y en operación conforme a las '\n 'leyes de los Estados Unidos Mexicanos, como lo acredita mediante escritura pública número '\n '<input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub\" id=\"noescpub\" placeholder=\"Número de Escritura Pública\">'\n ', otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot\" id=\"nonot\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot\" id=\"dirnot\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc\" id=\"'\n 'fechafirmesc\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop\" id=\"fecharegprop\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc\" '\n 'id=\"nofoliomerc\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop\" id=\"estadoregprop\" placeholder=\"Estado Donde se Registró\">.</li>'\n '<li>Su representante legal cuenta con las facultades necesarias para obligarla en los términos'\n ' del presente Contrato tal y como lo acredita mediante escritura pública número <input size=\"1\"'\n ' type=\"number\" min=0 class=\"inpcont\" name=\"noescpub2\" id=\"noescpub2\" placeholder=\"'\n 'Número de Escritura Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" type=\"number\" min=0 class=\"'\n 'inpcont\" name=\"nonot2\" id=\"nonot2\" placeholder=\"Número de Notario\"> de <input size=\"1\" type=\"'\n 'text\" class=\"inpcont\" name=\"dirnot2\" id=\"dirnot2\" placeholder=\"Municipio y estado del '\n 'Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechafrimesc2\" id=\"'\n 'fechafirmesc2\" placeholder=\"Fecha de Firma de Escritura MM-DD-AAAA\">, misma que se encuentra '\n 'debidamente registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"'\n 'fecharegprop2\" id=\"fecharegprop2\" placeholder=\"Fecha de Registro MM-DD-AAAA\">, bajo el folio '\n 'mercantil número <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"nofoliomerc2\" '\n 'id=\"nofoliomerc2\" placeholder=\"Número de Folio Mercantil\">, del Registro Público de la '\n 'Propiedad y Comercio del estado de <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"'\n 'estadoregprop2\" id=\"estadoregprop2\" placeholder=\"Estado Donde se Registró\">, facultades que no'\n ' les han sido limitadas, revocadas o modificadas de forma alguna a la fecha de este Contrato.'\n '</li>'\n '<li>Tiene como domicilio fiscal, y para recibir todo tipo de notificaciones el ubicado en '\n '<input size=\"1\" type=\"text\" class=\"inpcont\" name=\"dirinmu\" id=\"dirinmu\" placeholder=\"Dirección'\n ' del Inmueble\">, estando debidamente inscrita el Registro Federal de Contribuyentes bajo la '\n 'clave <input size=\"1\" type=\"text\" class=\"inpcont\" name=\"RFC\" id=\"RFC\" placeholder=\"'\n 'Clave de RFC\">.</li>'\n '<li>Que su objeto social le permite la celebración del presente Contrato.</li>'\n '<li>Ser propietario del inmueble localizado en <input size=\"1\" class=\"inpcont\" '\n 'name=\"direccioninmueble3\" id=\"direccioninmueble3\" placeholder=\"Dirección del Inmueble\">, tal como lo acredita mediante '\n 'escritura pública número <input size=\"1\" type=\"number\" min=0 class=\"inpcont\" name=\"noescpub3\" id=\"noescpub3\" placeholder=\"No. de escritura'\n ' Pública\">, otorgada ante la fe del Notario Público número <input size=\"1\" name=\"nonotario3\" class=\"inpcont\" '\n 'id=\"nonotatrio3\" placeholder=\"Número de Notario\"> de <input size=\"1\" name=\"dirnotario3\" class=\"inpcont\" id=\"dirnotario3\" '\n 'placeholder=\"Municipio y Estado del Notario\">, con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" '\n 'name=\"fechafirmaesc3\" id=\"fechafirmaesc3\" placeholder=\"Fecha de firma de la Escritura(dd/mm/aaaa)\">, misma que se encuentra debidamente '\n 'registrada con fecha del <input size=\"1\" type=\"date\" class=\"inpcont\" name=\"fechareg3\" id=\"fechareg3\" placeholder=\"Fecha de registro(dd/mm/aaaa)\">'\n ', bajo el folio mercantil número <input size=\"1\" class=\"inpcont\" name=\"foliomerc3\" id=\"foliomerc3\" placeholder=\"Número de '\n 'Folio Mercantil\">, del Registro Público de la Propiedad y Comercio del estado de <input size=\"1\" '\n 'class=\"inpcont\" name=\"estadoreg3\" id=\"estadoreg3\" placeholder=\"Estado donde se Registró\">, en lo sucesivo el '\n '“INMUEBLE”.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li></ol></p>'\n '<p id=\"bdec2\"> II. Declara el <b>\"ARRENDATARIO\":</b></p>'\n '<p><ol id=\"bolist2\"><li>Ser persona física, mayor de edad, con plena capacidad para realizar el presente '\n 'acto.</li><li>Que es su deseo arrendar el “INMUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”.</li><li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del '\n 'consentimiento.</li><li>Tener el “INMUEBLE” como domicilio para recibir todo tipo de '\n 'notificaciones.</li></ol></p>'\n }\n ],\n 'donacion': [\n {\n 'titulo': 'primera',\n 'desc': '<p id=\"bdec1\"> I. Declara el <b>\"DONANTE\":</b></p>'\n '<p><ol id=\"bolist1\"><li>Ser una persona física, mayor de edad, con plena capacidad para realizar el '\n 'presente acto.</li>'\n '<li>Que es su deseo donar en favor del DONATARIO de acuerdo a lo estipulado en '\n 'éste “CONTRATO”, por así convenir a sus intereses.</li>'\n '<li>Que se obliga al cumplimiento del presente “CONTRATO”, sin ningún vicio del consentimiento.'\n '</li>'\n '<li>Tener como domicilio para recibir todo tipo de notificaciones el ubicado en '\n '<input class=\"inpcont\" name=\"domnotdon\" id=\"domnotdon\" size=\"1\" placeholder=\"Domicilio de '\n 'notificaciones del Donante\">.</li></ol></p>'\n '<p id=\"bdec2\"> II. Declara el <b>\"DONATARIO\":</b></p>'\n '<p><ol id=\"bolist2\"><li>Ser persona física, mayor de edad, con plena capacidad para realizar el presente '\n 'acto.</li>'\n '<li>Que es su deseo recibir en donación el “BIEN MUEBLE” de acuerdo a lo estipulado en éste '\n '“CONTRATO”, por así convenir a sus intereses.</li>'\n '<li>Que se obliga al cumplimiento del presente CONTRATO, sin ningún vicio del consentimiento.</li>'\n '<li>Tener como domicilio para recibir todo tipo de notificaciones el ubicado en '\n '<input class=\"inpcont\" name=\"domnotdona\" id=\"domnotdona\" size=\"1\" placeholder=\"Domicilio de '\n 'notificaciones del Donatario\">.</li></ol></p>'\n }\n ],\n }\n for key, declaraciones in declaraciones_dict.items():\n for declaracion in declaraciones:\n for i, value in ids_contratos.items():\n if i == key:\n declaracion['id_contrato'] = value\n ccvb = Declaraciones.query.filter_by(id_contrato=value, titulo=declaracion['titulo']).first()\n if ccvb is None:\n ccvb = Declaraciones(**declaracion)\n db.session.add(ccvb)\n db.session.commit()\n else:\n if ccvb.desc != declaracion['desc']:\n ccvb.desc = declaracion['desc']\n db.session.commit()"
},
{
"alpha_fraction": 0.6333333253860474,
"alphanum_fraction": 0.6560137271881104,
"avg_line_length": 35.83544158935547,
"blob_id": "a555f134149fe4412c354add9ea8aefb1385d6fb",
"content_id": "159ec365de9b67e66f16b930cec76601a41f0404",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2910,
"license_type": "no_license",
"max_line_length": 69,
"num_lines": 79,
"path": "/migrations/versions/905b9ed4daca_.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "\"\"\"empty message\n\nRevision ID: 905b9ed4daca\nRevises: \nCreate Date: 2018-06-11 20:06:37.119313\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = '905b9ed4daca'\ndown_revision = None\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.create_table('contratos',\n sa.Column('id', sa.Integer(), nullable=False),\n sa.Column('contenido', sa.String(length=15000), nullable=True),\n sa.Column('fin', sa.String(length=15000), nullable=True),\n sa.Column('tipo', sa.String(length=500), nullable=True),\n sa.PrimaryKeyConstraint('id')\n )\n op.create_table('user',\n sa.Column('id', sa.Integer(), nullable=False),\n sa.Column('password_hash', sa.String(length=128), nullable=True),\n sa.Column('usuario', sa.String(length=64), nullable=True),\n sa.Column('correo', sa.String(length=120), nullable=True),\n sa.PrimaryKeyConstraint('id'),\n sa.UniqueConstraint('correo'),\n sa.UniqueConstraint('usuario')\n )\n op.create_table('clausulas',\n sa.Column('id', sa.Integer(), nullable=False),\n sa.Column('desc', sa.String(length=15000), nullable=True),\n sa.Column('no', sa.String(length=50), nullable=True),\n sa.Column('titulo', sa.String(length=80), nullable=True),\n sa.Column('id_contrato', sa.Integer(), nullable=True),\n sa.Column('movable', sa.Boolean(), nullable=True),\n sa.Column('optional', sa.Boolean(), nullable=True),\n sa.Column('end', sa.Boolean(), nullable=True),\n sa.ForeignKeyConstraint(['id_contrato'], ['contratos.id'], ),\n sa.PrimaryKeyConstraint('id')\n )\n op.create_table('cont_us',\n sa.Column('id', sa.Integer(), nullable=False),\n sa.Column('ort', sa.String(length=200), nullable=True),\n sa.Column('nombre', sa.String(length=200), nullable=True),\n sa.Column('id_usr', sa.Integer(), nullable=True),\n sa.ForeignKeyConstraint(['id_usr'], ['user.id'], ),\n sa.PrimaryKeyConstraint('id')\n )\n op.create_table('declaraciones',\n sa.Column('id', sa.Integer(), nullable=False),\n sa.Column('desc', sa.String(length=15000), nullable=True),\n sa.Column('no', sa.String(length=10), nullable=True),\n sa.Column('titulo', sa.String(length=80), nullable=True),\n sa.Column('id_contrato', sa.Integer(), nullable=True),\n sa.Column('movable', sa.Boolean(), nullable=True),\n sa.Column('optional', sa.Boolean(), nullable=True),\n sa.Column('end', sa.Boolean(), nullable=True),\n sa.ForeignKeyConstraint(['id_contrato'], ['contratos.id'], ),\n sa.PrimaryKeyConstraint('id')\n )\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_table('declaraciones')\n op.drop_table('cont_us')\n op.drop_table('clausulas')\n op.drop_table('user')\n op.drop_table('contratos')\n # ### end Alembic commands ###\n"
},
{
"alpha_fraction": 0.611657440662384,
"alphanum_fraction": 0.6141605377197266,
"avg_line_length": 42.703125,
"blob_id": "7f1a26c271631fe8a26e40c3b5e26d6de2d9f26f",
"content_id": "8bcf3364e2e5fea192a9264c40bb7926be0b0813",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5602,
"license_type": "no_license",
"max_line_length": 130,
"num_lines": 128,
"path": "/app/auth/routes.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from flask import render_template, redirect, url_for, flash, request, current_app\nfrom werkzeug.urls import url_parse\nfrom flask_login import login_user, logout_user, current_user, login_required\nfrom app import db\nfrom app.auth import bp\nfrom app.auth.forms import LoginForm, RegistrationForm, ResetPasswordRequestForm, ResetPasswordForm\nfrom app.models import User\nfrom app.email import send_password_reset_email, send_email\nfrom itsdangerous import SignatureExpired, URLSafeTimedSerializer, BadTimeSignature\n\n\ns = URLSafeTimedSerializer('QLbvEQyjZZMQlPswvldyYxVTZFDTpWsWStVrIGMNPfLjEqnCuvGagDRsYUKAMNoSWETunyNIaKaNDQURGkZXKUGdhvnvqMhKHonG')\n\n@bp.route('/login', methods=['GET', 'POST'])\ndef login():\n if current_user.is_authenticated:\n return redirect(url_for('main.index'))\n form = LoginForm()\n if form.validate_on_submit():\n user = User.query.filter_by(usuario=form.username.data).first()\n if user is None or not user.check_password(form.password.data):\n flash('Nombre de usuario o contraseña incorrectos', 'error')\n return redirect(url_for('auth.login'))\n login_user(user, remember=form.remember_me.data)\n flash('Login successful for user {}, Welcome!'.format(form.username.data), 'succ')\n next_page = request.args.get('next')\n if not next_page or url_parse(next_page).netloc != '':\n next_page = url_for('main.index')\n return redirect(next_page)\n return render_template('auth/login.html',\n title='Iniciar Sesión',\n form=form)\n\n\n@bp.route('/logout')\ndef logout():\n logout_user()\n return redirect(url_for('main.index'))\n\n\n@bp.route('/registro', methods=['GET', 'POST'])\ndef register():\n if current_user.is_authenticated:\n return redirect(url_for('main.index'))\n form = RegistrationForm()\n if form.validate_on_submit():\n user = User(usuario=form.username.data, correo=form.email.data, role_id=1)\n user.set_password(form.password.data)\n db.session.add(user)\n db.session.commit()\n token = s.dumps(user.correo, salt='email-confirm')\n send_email('Confirma tu correo', current_app.config['ADMINS'][0], [user.correo],\n html_body=render_template('email/confirm_email.html',\n user=user,\n token=token),\n text_body=render_template('email/confirm_email.txt',\n user=user,\n token=token))\n flash('Bienvenido, {}. Por favor verifica tu correo antes de continuar'.format(user.usuario), 'succ')\n return redirect(url_for('auth.login'))\n return render_template('auth/registro.html',\n title='Registro',\n form=form)\n\n\n@bp.route('/reset_password_request', methods=['GET', 'POST'])\ndef reset_password_request():\n if current_user.is_authenticated:\n return redirect(url_for('main.index'))\n form = ResetPasswordRequestForm()\n if form.validate_on_submit():\n user = User.query.filter_by(correo=form.email.data).first()\n if user:\n send_password_reset_email(user)\n flash('Revisa tu correo para completar el proceso de reestablecer tu contraseña', 'succ')\n return(redirect(url_for('auth.login')))\n return render_template('auth/reset_password.html',\n title='Reestablecer Contraseña',\n form=form)\n\n\n@bp.route('/reset_password/<token>', methods=['GET', 'POST'])\ndef reset_password(token):\n if current_user.is_authenticated:\n return redirect(url_for('main.index'))\n user = User.verify_reset_passwor_token(token)\n if not user:\n return redirect(url_for('main.index'))\n form = ResetPasswordForm()\n if form.validate_on_submit():\n user.set_password(form.password.data)\n db.session.commit()\n flash('Tu contraseña ha sido cambiada', 'succ')\n return redirect(url_for('auth.login'))\n return render_template('auth/reset_password_token.html', form=form)\n\n\n@bp.route('/validate_email')\n@login_required\ndef validate_email():\n user = User.query.filter_by(id=current_user.id).first()\n if user:\n token = s.dumps(user.correo, salt='email-confirm')\n send_email('Confirma tu correo', current_app.config['ADMINS'][0], [user.correo],\n html_body=render_template('email/confirm_email.html',\n user=user,\n token=token),\n text_body=render_template('email/confirm_email.txt',\n user=user,\n token=token))\n flash('Recibiras el link de validación en tu correo en un máximo de 30 minutos.', 'succ')\n return redirect(url_for('main.index'))\n\n\n@bp.route('/confirm_email/<token>')\ndef confirm_email(token):\n try:\n email = s.loads(token, salt='email-confirm', max_age=3600)\n user = User.query.filter_by(correo=email).first()\n user.validated = True\n user.role_id = 2\n db.session.commit()\n flash('Correo confirmado. Gracias!', 'succ')\n except SignatureExpired:\n return '<h1>El link caducó, por favor pide un nuevo link</h1>'\n except BadTimeSignature:\n return '<h1>El link es inválido, por favor verificalo nuevamente o pide un nuevo link</h1>'\n return redirect(url_for('main.index'))"
},
{
"alpha_fraction": 0.7117437720298767,
"alphanum_fraction": 0.7117437720298767,
"avg_line_length": 22.41666603088379,
"blob_id": "97b9e0245bcefd229814041f59be6c3aeab2652a",
"content_id": "351166f30f97e858dd973818e5709815555e7dd9",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 281,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 12,
"path": "/contratosexpress.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "#!/usr/bin/python\nfrom app import db, create_app\nfrom app.models import User, Contratos, Clausulas\n\n\napp = create_app()\n# cli.register(app)\n\n\n@app.shell_context_processor\ndef make_shell_context():\n return {'db': db, 'User': User, 'Contratos': Contratos, 'Clausulas': Clausulas}\n"
},
{
"alpha_fraction": 0.7707454562187195,
"alphanum_fraction": 0.7862166166305542,
"avg_line_length": 25.33333396911621,
"blob_id": "4a627a55422f920328ffe745d3ac2bfb093a055d",
"content_id": "208ba0890eb4b720cd803a838c648ba6a7d866d6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Dockerfile",
"length_bytes": 711,
"license_type": "no_license",
"max_line_length": 101,
"num_lines": 27,
"path": "/Dockerfile",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "FROM python:3.6-alpine\n\nRUN adduser -D contratosexpress\n\nWORKDIR /home/contratosexpress\n\nCOPY requirements.txt requirements.txt\nRUN pip install --upgrade pip setuptools \\\n && pip install --upgrade pypdf2\nRUN apk add --no-cache build-base linux-headers python3-dev zlib-dev jpeg-dev libffi-dev libressl-dev\nRUN python -m venv venv\nRUN venv/bin/pip install -r requirements.txt\nRUN venv/bin/pip install gunicorn\nRUN venv/bin/pip install -Iv pymysql==0.8.1\n\nCOPY app app\nCOPY migrations migrations\nCOPY contratosexpress.py config.py boot.sh ./\nRUN chmod a+x boot.sh\n\nENV FLASK_APP contratosexpress.py\n\nRUN chown -R contratosexpress:contratosexpress ./\nUSER contratosexpress\n\nEXPOSE 5000\nENTRYPOINT [\"./boot.sh\"]\n"
},
{
"alpha_fraction": 0.5465601086616516,
"alphanum_fraction": 0.5681028366088867,
"avg_line_length": 43.27692413330078,
"blob_id": "71214a5c736f2c1c6b82c443c58fb50ef75d20c4",
"content_id": "0cb588254bcda6bd2cece299c947219f952dd11f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5758,
"license_type": "no_license",
"max_line_length": 141,
"num_lines": 130,
"path": "/app/main/pdfgen.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, ListFlowable, ListItem, Table, TableStyle\nfrom reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle\nfrom reportlab.lib.pagesizes import letter\nfrom reportlab.lib.units import inch\nfrom reportlab.lib.pdfencrypt import StandardEncryption\nfrom reportlab.lib.enums import TA_CENTER, TA_JUSTIFY\nfrom .beautify import parsehtml\nimport os, datetime\nPAGE_WIDTH = letter[0]\nPAGE_HEIGHT = letter[1]\nstyles = getSampleStyleSheet()\n\nstyles.add(ParagraphStyle(name='NormalJ', alignment=TA_JUSTIFY))\nstyles.add(ParagraphStyle(name='NormalC', alignment=TA_CENTER))\nstyles.add(ParagraphStyle(name='List', alignmnet=TA_JUSTIFY, leftIndent=50))\n\npageinfo =\"Contratos Express\"\n# def firstPage(canvas, doc):\n# canvas.saveState()\n# canvas.setFont('Times-Bold', 16)\n# canvas.drawCentredString(PAGE_WIDTH/2,PAGE_HEIGHT-108, title)\n# canvas.setFont('Times-Roman', 9)\n# canvas.drawString(inch, 0.75*inch, \"Primera página / {}\".format(pageinfo))\n# canvas.restoreState()\n\ndef followingPages(canvas, doc):\n canvas.saveState()\n canvas.setFont('Times-Roman', 9)\n canvas.drawString(inch, 0.75*inch, \"Página {} {}\".format(doc.page, pageinfo))\n canvas.restoreState()\n\ndef go(callback_dict, soup):\n final_string = parsehtml(callback_dict, soup)\n basedir = os.path.abspath(os.path.dirname(__file__))\n pdftit = '{}/pdfs/{}-{}{}.pdf'.format(basedir, callback_dict['ud'], callback_dict['contrato'], datetime.datetime.now().strftime('%d-%m'))\n if os.path.isfile(pdftit):\n version = 2\n while True:\n new_pdf_tit = '{}/pdfs/{}-{}{}.pdf'.format(basedir, callback_dict['ud'], callback_dict['contrato'],\n datetime.datetime.now().strftime('%d-%m') +\n '-({})'.format(str(version)))\n if not os.path.isfile(new_pdf_tit):\n pdftit = new_pdf_tit\n break\n version += 1\n enc = StandardEncryption('', ownerPassword='m9kA52!lDbc%az', canPrint=1, canModify=0, canCopy=0, canAnnotate=0)\n doc = SimpleDocTemplate(pdftit, author='Contratos Express', title=callback_dict['contrato'], encrypt=enc)\n textbody = []\n cont = Paragraph(final_string['contract_top'], styles['NormalJ'])\n textbody.append(cont)\n textbody.append(Spacer(1, 0.2*inch))\n declaraciones = Paragraph(final_string['declaraciones'], styles['NormalC'])\n textbody.append(declaraciones)\n textbody.append(Spacer(1, 0.2*inch))\n dec1 = Paragraph(final_string['dec1'], styles['NormalJ'])\n textbody.append(dec1)\n textbody.append(Spacer(1, 0.2 * inch))\n dec1list = final_string['dec1list']\n dec1list_parragraphs = []\n for item in dec1list:\n dec1list_parragraphs.append(ListItem(Paragraph(item, styles['NormalJ'], bulletText=').'), leftIndent=35, spaceAfter=5))\n t = ListFlowable(\n dec1list_parragraphs,\n bulletType='a',\n leftIndent=7,\n bulletOffsetY=2\n )\n textbody.append(t)\n textbody.append(Spacer(1, 0.2*inch))\n dec2 = Paragraph(final_string['dec2'], styles['NormalJ'])\n textbody.append(dec2)\n textbody.append(Spacer(1, 0.2 * inch))\n dec2list = final_string['dec2list']\n dec2list_parragraphs = []\n for item in dec2list:\n dec2list_parragraphs.append(\n ListItem(Paragraph(item, styles['NormalJ'], bulletText=').'), leftIndent=35, spaceAfter=5))\n t = ListFlowable(\n dec2list_parragraphs,\n bulletType='a',\n leftIndent=7,\n bulletOffsetY=2,\n )\n textbody.append(t)\n textbody.append(Spacer(1, 0.2 * inch))\n clausulas = Paragraph(final_string['clausulas'], styles['NormalC'])\n textbody.append(clausulas)\n textbody.append(Spacer(1, 0.2 * inch))\n clausulas_dict = sorted(final_string['clausulas_dict'].items())\n for key, value in clausulas_dict:\n for para in value:\n if isinstance(para, dict):\n lines = []\n for items in para.values():\n for line in items:\n lines.append(\n ListItem(Paragraph(line, styles['NormalJ'], bulletText=').'), leftIndent=35, spaceAfter=5)\n )\n x = ListFlowable(\n lines,\n bulletType='a',\n leftIndent=7,\n bulletOffsetY=2\n )\n textbody.append(x)\n textbody.append(Spacer(1, 0.2 * inch))\n else:\n p = Paragraph(para, styles['NormalJ'])\n textbody.append(p)\n textbody.append(Spacer(1, 0.2 * inch))\n\n data = [[callback_dict['parte1'], callback_dict['parte2']],\n ['__________________________________', '__________________________________'],\n [callback_dict['parte1n'], callback_dict['parte2n']],\n ['TESTIGO', 'TESTIGO'],\n ['__________________________________', '__________________________________'],\n [callback_dict['test1'], callback_dict['test2']]]\n tab = Table(data, 2*[3.5*inch], 6*[0.35*inch])\n tab.setStyle(TableStyle([('ALIGN', (0,0), (-1,-1), 'CENTER'),\n ('VALIGN', (0,1), (-1,-2), 'BOTTOM'),\n ('VALIGN', (0,2), (-1, -4), 'TOP'),\n ('VALIGN', (0, 3), (-1, -3), 'BOTTOM'),\n ('VALIGN', (0, 4), (-1, -2), 'BOTTOM'),\n ('VALIGN', (0, 5), (-1, -1), 'TOP')\n ]))\n textbody.append(Spacer(1, 0.1*inch))\n textbody.append(tab)\n\n doc.build(textbody, followingPages, followingPages)\n return pdftit\n"
},
{
"alpha_fraction": 0.5138017535209656,
"alphanum_fraction": 0.520075261592865,
"avg_line_length": 36.97618865966797,
"blob_id": "2abe823654d423fd870ceb466a3d7f62f700d9d8",
"content_id": "282689a5a5900987069ce1cbb3aec996fb905757",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 1597,
"license_type": "no_license",
"max_line_length": 135,
"num_lines": 42,
"path": "/app/templates/auth/login.html",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "{% extends \"base.html\" %}\n\n{% block content %}\n<div class=\"container\">\n <h1 class=\"mt-5 text-center\">Bienvenido!</h1>\n <div class=\"container-fluid\">\n <form action=\"\" method=\"post\">\n {{ form.hidden_tag() }}\n <div class=\"row mt-5\">\n <div class=\"col form-group\">\n {{ form.username.label(class=\"bmd-label-floating\") }}\n {{ form.username(size=32, class=\"form-control\") }}\n {% for error in form.username.errors %}\n <div class=\"alert alert-danger\" role=\"alert\">\n {{ error }}\n </div>\n {% endfor %}\n </div>\n </div>\n <div class=\"row mt-5 mb-5\">\n <div class=\"col form-group\">\n {{ form.password.label(class=\"bmd-label-floating\") }}\n {{ form.password(size=32, class=\"form-control\") }}\n {% for error in form.password.errors %}\n <div class=\"alert alert-danger\" role=\"alert\">\n {{ error }}\n </div>\n {% endfor %}\n </div>\n </div>\n <div class=\"switch\"><label>{{ form.remember_me(type=\"checkbox\") }}Recuérdame!</label></div>\n <div class=\"row\">\n <div class=\"col\">\n {{ form.submit(class=\"btn btn-raised btn-lg btn-success\") }}\n </div>\n </div>\n </form>\n <p>Todavía no tienes cuenta? <a class=\"light-accent-txt\" href=\"{{ url_for('auth.register') }}\">Da Click para registrarte!</a></p>\n <p>Olvidaste tu contraseña? <a href=\"{{ url_for('auth.reset_password_request') }}\">Da Click para Reestablecer</a></p>\n </div>\n</div>\n{% endblock %}"
},
{
"alpha_fraction": 0.5394290089607239,
"alphanum_fraction": 0.5444703698158264,
"avg_line_length": 38.588233947753906,
"blob_id": "ade256a774cd5137d56de8529755ea8a2bdfa2e2",
"content_id": "0a4c7466cfc7a1790053e6dd0c3292efbb2426e7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 18847,
"license_type": "no_license",
"max_line_length": 119,
"num_lines": 476,
"path": "/app/main/routes.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from flask import render_template, flash, redirect, url_for, g, abort,\\\n session, request, make_response, jsonify, send_from_directory, send_file, current_app\nfrom app import db\nfrom app.main.forms import PdfForm, EditProfileForm, RenameContract, ContactForm\nfrom wtforms import StringField\nfrom wtforms.validators import DataRequired\nfrom app.models import User, Contratos, Clausulas, Declaraciones, ContUs, Roles\nfrom flask_login import current_user, login_required\nfrom app.main import bp\nfrom app.main.contratos import db_population\nfrom .pdfgen import go\nfrom app.email import send_email\nimport paypalrestsdk\n\n\n@bp.before_app_first_request\ndef initial_requests():\n roles = Roles.query.all()\n if not roles:\n role = Roles(name='Thrall')\n db.session.add(role)\n role2 = Roles(name='Karl')\n db.session.add(role2)\n role3 = Roles(name='Jarl')\n db.session.add(role3)\n role4 = Roles(name='Konnungar')\n db.session.add(role4)\n db.session.commit()\n db_population()\n\n\n@bp.route('/')\n@bp.route('/index')\n@bp.route('/inicio')\ndef index():\n return render_template('inicio.html',\n title='Inicio')\n\n\n@bp.route('/laboral')\n@login_required\ndef laboral():\n if check_role():\n return render_template('laboral.html',\n title='Contratos Laborales')\n\n\n@bp.route('/mercantil')\n@login_required\ndef mercantil():\n if check_role():\n return render_template('mercantil.html',\n title='Contratos Mercantiles')\n\n\n@bp.route('/civil')\n@login_required\ndef civil():\n if check_role():\n return render_template('civil.html',\n title='Contratos Civiles')\n\n\n@bp.route('/civil/compraventab')\n@login_required\ndef compraventab():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='compraventa-bienes').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n return render_template('compraventa.html',\n title='Contrato de Compra-Venta',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n@bp.route('/civil/arrendamientoinm', methods=['GET', 'POST'])\n@login_required\ndef arrendamientoinm():\n if check_role():\n return render_template('tiposarr.html',\n title='Tipos de Contrato de Arrendamiento')\n\n\n@bp.route('/civil/donacion', methods=['GET', 'POST'])\n@login_required\ndef donacion():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='donacion').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n\n if request.method == 'POST':\n callback_dict = {}\n for key, val in request.form.items():\n if val == '':\n break\n else:\n callback_dict[key] = val\n else:\n callback_dict.pop('csrf_token', None)\n callback_dict['donante'] = callback_dict['donante'].upper()\n callback_dict['donatario'] = callback_dict['donatario'].upper()\n callback_dict['test1'] = callback_dict['test1'].upper()\n callback_dict['test2'] = callback_dict['test2'].upper()\n callback_dict['parte1'] = 'DONANTE'\n callback_dict['parte2'] = 'DONATARIO'\n callback_dict['parte2n'] = callback_dict['donatario']\n callback_dict['parte1n'] = callback_dict['donante']\n callback_dict['contrato'] = 'Contrato de Donacion'\n callback_dict['un'] = current_user.usuario\n callback_dict['ud'] = current_user.id\n soup = str(callback_dict.pop('sopa', None))\n title = go(callback_dict, soup)\n last_ind = title.find('.pdf')\n first_ind = title.rfind('/')\n nombre = title[first_ind + 1:last_ind + 4]\n new_cont = ContUs(id_usr=current_user.id, ort=title, nombre=nombre)\n db.session.add(new_cont)\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('donacion.html',\n title='Contrato de Donación',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n@bp.route('/civil/arrendamientoinm/1', methods=['GET', 'POST'])\n@login_required\ndef arrendamientoinmff():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='arrendamiento-inmueble').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n\n if request.method == 'POST':\n callback_dict = {}\n for key, val in request.form.items():\n if val == '':\n break\n else:\n callback_dict[key] = val\n else:\n callback_dict.pop('csrf_token', None)\n callback_dict['arrendatario'] = callback_dict['arrendatario'].upper()\n callback_dict['arrendador'] = callback_dict['arrendador'].upper()\n callback_dict['test1'] = callback_dict['test1'].upper()\n callback_dict['test2'] = callback_dict['test2'].upper()\n callback_dict['parte1'] = 'ARRENDADOR'\n callback_dict['parte2'] = 'ARRENDATARIO'\n callback_dict['parte2n'] = callback_dict['arrendatario']\n callback_dict['parte1n'] = callback_dict['arrendador']\n callback_dict['contrato'] = 'Contrato de Arrendamiento Inmobiliario'\n callback_dict['un'] = current_user.usuario\n callback_dict['ud'] = current_user.id\n soup = str(callback_dict.pop('sopa', None))\n title = go(callback_dict, soup)\n last_ind = title.find('.pdf')\n first_ind = title.rfind('/')\n nombre = title[first_ind + 1:last_ind + 4]\n new_cont = ContUs(id_usr=current_user.id, ort=title, nombre=nombre)\n db.session.add(new_cont)\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('arrendamientoinm.html',\n title='Contrato de Arrendamiento',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n@bp.route('/civil/arrendamientoinm/2', methods=['GET', 'POST'])\n@login_required\ndef arrendamientoinmfm():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='arrendamientoin-fm').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n\n if request.method == 'POST':\n callback_dict = {}\n for key, val in request.form.items():\n if val == '':\n break\n else:\n callback_dict[key] = val\n else:\n callback_dict.pop('csrf_token', None)\n callback_dict['arrendatario'] = callback_dict['arrendatario'].upper()\n callback_dict['arrendador'] = callback_dict['arrendador'].upper()\n callback_dict['test1'] = callback_dict['test1'].upper()\n callback_dict['test2'] = callback_dict['test2'].upper()\n callback_dict['parte1'] = 'ARRENDADOR'\n callback_dict['parte2'] = 'ARRENDATARIO'\n callback_dict['parte2n'] = callback_dict['arrendatario']\n callback_dict['parte1n'] = callback_dict['arrendador']\n callback_dict['contrato'] = 'Contrato de Arrendamiento Inmobiliario'\n callback_dict['un'] = current_user.usuario\n callback_dict['ud'] = current_user.id\n soup = str(callback_dict.pop('sopa', None))\n title = go(callback_dict, soup)\n last_ind = title.find('.pdf')\n first_ind = title.rfind('/')\n nombre = title[first_ind + 1:last_ind + 4]\n new_cont = ContUs(id_usr=current_user.id, ort=title, nombre=nombre)\n db.session.add(new_cont)\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('arrendamientoinm.html',\n title='Contrato de Arrendamiento',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n@bp.route('/civil/arrendamientoinm/3', methods=['GET', 'POST'])\n@login_required\ndef arrendamientoinmmf():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='arrendamientoin-mf').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n\n if request.method == 'POST':\n callback_dict = {}\n for key, val in request.form.items():\n if val == '':\n break\n else:\n callback_dict[key] = val\n else:\n callback_dict.pop('csrf_token', None)\n callback_dict['arrendatario'] = callback_dict['arrendatario'].upper()\n callback_dict['arrendador'] = callback_dict['arrendador'].upper()\n callback_dict['test1'] = callback_dict['test1'].upper()\n callback_dict['test2'] = callback_dict['test2'].upper()\n callback_dict['parte1'] = 'ARRENDADOR'\n callback_dict['parte2'] = 'ARRENDATARIO'\n callback_dict['parte2n'] = callback_dict['arrendatario']\n callback_dict['parte1n'] = callback_dict['arrendador']\n callback_dict['contrato'] = 'Contrato de Arrendamiento Inmobiliario'\n callback_dict['un'] = current_user.usuario\n callback_dict['ud'] = current_user.id\n soup = str(callback_dict.pop('sopa', None))\n title = go(callback_dict, soup)\n last_ind = title.find('.pdf')\n first_ind = title.rfind('/')\n nombre = title[first_ind + 1:last_ind + 4]\n new_cont = ContUs(id_usr=current_user.id, ort=title, nombre=nombre)\n db.session.add(new_cont)\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('arrendamientoinm.html',\n title='Contrato de Arrendamiento',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n@bp.route('/civil/arrendamientoinm/4', methods=['GET', 'POST'])\n@login_required\ndef arrendamientoinmmm():\n if check_role():\n form = PdfForm()\n contrato = Contratos.query.filter_by(tipo='arrendamientoin-mm').first()\n clausulas = Clausulas.query.filter_by(id_contrato=contrato.id).all()\n declaraciones = Declaraciones.query.filter_by(id_contrato=contrato.id).all()\n\n if request.method == 'POST':\n callback_dict = {}\n for key, val in request.form.items():\n if val == '':\n break\n else:\n callback_dict[key] = val\n else:\n callback_dict.pop('csrf_token', None)\n callback_dict['arrendatario'] = callback_dict['arrendatario'].upper()\n callback_dict['arrendador'] = callback_dict['arrendador'].upper()\n callback_dict['test1'] = callback_dict['test1'].upper()\n callback_dict['test2'] = callback_dict['test2'].upper()\n callback_dict['parte1'] = 'ARRENDADOR'\n callback_dict['parte2'] = 'ARRENDATARIO'\n callback_dict['parte2n'] = callback_dict['arrendatario']\n callback_dict['parte1n'] = callback_dict['arrendador']\n callback_dict['contrato'] = 'Contrato de Arrendamiento Inmobiliario'\n callback_dict['un'] = current_user.usuario\n callback_dict['ud'] = current_user.id\n soup = str(callback_dict.pop('sopa', None))\n title = go(callback_dict, soup)\n last_ind = title.find('.pdf')\n first_ind = title.rfind('/')\n nombre = title[first_ind + 1:last_ind + 4]\n new_cont = ContUs(id_usr=current_user.id, ort=title, nombre=nombre)\n db.session.add(new_cont)\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('arrendamientoinm.html',\n title='Contrato de Arrendamiento',\n form=form,\n clausulas=clausulas,\n contrato=contrato,\n declaraciones=declaraciones)\n\n\n# @bp.route('/civil/arrendaminetoinm/imprimir/<callback_dict>/<soup>')\n# @login_required\n# def arrimprimir(callback_dict, soup):\n# go(callback_dict, soup)\n# return redirect(url_for('main.arrendamientoinm'))\n\n\n@bp.route('/test', methods=['GET', 'POST'])\n@login_required\ndef test():\n form = PdfForm()\n x = 7\n names_list = []\n for i in range(x):\n names_list.append(\"name\"+str(i))\n print(names_list)\n print(form.data)\n\n class OptionalFields(PdfForm):\n pass\n\n if x is not None:\n for i in range(x):\n setattr(OptionalFields, names_list[i], StringField(validators=[DataRequired()]))\n\n form = OptionalFields()\n print(form.data)\n\n if form.validate_on_submit():\n print(\"submitted data\", form.data)\n\n return render_template('pdfpreview.html',\n form=form)\n\n\n@bp.route('/perfil', methods=['GET', 'POST'])\n@login_required\ndef perfil():\n form = EditProfileForm(current_user.usuario)\n if form.validate_on_submit():\n usuario = User.query.filter_by(id=current_user.id).first()\n if usuario.check_password(form.contra.data):\n usuario.set_password(form.new_pass.data)\n db.session.commit()\n flash('Contraseña Cambiada', 'succ')\n return redirect(url_for('main.perfil'))\n else:\n flash('Contraseña incorrecta', 'error')\n return redirect(url_for('main.perfil'))\n return render_template('perfil.html',\n form=form)\n\n\n@bp.route('/perfil/contratos', methods=['GET', 'POST'])\n@login_required\ndef vcont():\n if check_role():\n form = RenameContract()\n if form.validate_on_submit():\n cont = ContUs.query.filter_by(id=request.form.get('subcont')).first()\n cont.nombre = form.nombre.data + '.pdf'\n db.session.commit()\n return redirect(url_for('main.vcont'))\n return render_template('vcont.html',\n form=form)\n\n\n@bp.route('/aviso-de-privacidad')\ndef aviso():\n return render_template('aviso.html')\n\n\n@bp.route('/dls/<path>')\n@login_required\ndef download(path):\n if check_role():\n cont = ContUs.query.filter_by(id=path).first()\n if current_user.id == cont.id_usr:\n last_ind = cont.ort.find('.pdf')\n first_ind = cont.ort.rfind('/')\n return send_from_directory(cont.ort[:first_ind], cont.ort[first_ind + 1: last_ind + 4], as_attachment=True)\n else:\n abort(404)\n # return redirect(url_for('main.perfil'))\n\n\n@bp.route('/contacto', methods=['GET', 'POST'])\n@login_required\ndef contacto():\n if check_role():\n form = ContactForm()\n if form.validate_on_submit():\n html_body = '<p>' + form.msg.data + '</p>'\n send_email(form.email.data + ' ' + form.name.data, current_app.config['ADMINS'][0],\n [current_app.config['ADMINS'][0]], form.msg.data, html_body)\n flash('Tu mensaje ha sido enviado, muchas gracias', 'succ')\n return redirect(url_for('main.contacto'))\n return render_template('contacto.html',\n title='Contacto',\n form=form)\n\n\n@bp.route('/prueba', methods=['GET', 'POST'])\n@login_required\ndef prueba():\n if check_role():\n roles = Roles.query.filter_by(name='Thrall').first()\n return render_template('pago_paypal.html',\n title='Pago')\n\n\n@bp.route('/pago', methods=['POST'])\ndef pago():\n payment = paypalrestsdk.Payment({\n \"intent\": \"sale\",\n \"payer\": {\n \"payment_method\": \"paypal\"},\n \"redirect_urls\": {\n \"return_url\": \"http://localhost:3000/payment/execute\",\n \"cancel_url\": \"http://localhost:3000/\"},\n \"transactions\": [{\n \"item_list\": {\n \"items\": [{\n \"name\": \"TESTING item\",\n \"sku\": \"12345\",\n \"price\": \"50.00\",\n \"currency\": \"USD\",\n \"quantity\": 1}]},\n \"amount\": {\n \"total\": \"50.00\",\n \"currency\": \"USD\"},\n \"description\": \"This is the payment transaction description.\"}]})\n\n if payment.create():\n print('Patment Success!')\n else:\n print(payment.error)\n\n return jsonify({'id': payment.id})\n\n\n@bp.route('/pagar', methods=['POST'])\ndef pagar():\n pago = paypalrestsdk.Payment.find(request.form['paymentID'])\n\n if pago.execute({'payer_id': request.form['payerID']}):\n print('Execute Success')\n else:\n print(pago.error)\n return ''\n\n\ndef check_role():\n if current_user.role_id == 1:\n return redirect(url_for('main.perfil'))\n elif current_user.role_id is None:\n abort(403)\n elif current_user.role_id != 1:\n return True\n"
},
{
"alpha_fraction": 0.6396685242652893,
"alphanum_fraction": 0.6583800911903381,
"avg_line_length": 32.40178680419922,
"blob_id": "73d742eb12f7678766a6cc44d25bf36eda778343",
"content_id": "3139f32aa7a594a1c5fd3cb11eb860f6f35c8a4a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3741,
"license_type": "no_license",
"max_line_length": 88,
"num_lines": 112,
"path": "/app/models.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "from flask_login import UserMixin\nfrom app import db, login\nfrom datetime import datetime\nfrom passlib.hash import pbkdf2_sha256\nfrom flask_security import RoleMixin\nfrom time import time\nimport jwt\nfrom flask import current_app\n\n\nroles_pplz = db.Table(\n 'roles_pplz',\n db.Column('user_id', db.Integer, db.ForeignKey('user.id')),\n db.Column('role_id', db.Integer, db.ForeignKey('role.id'))\n)\n\n\nclass Roles(db.Model):\n id = db.Column(db.Integer, primary_key=True)\n name = db.Column(db.String(80), unique=True)\n users = db.relationship('User', backref='users', lazy='dynamic')\n\n\nclass User(UserMixin, db.Model):\n id = db.Column(db.Integer, primary_key=True)\n password_hash = db.Column(db.String(128))\n usuario = db.Column(db.String(64), unique=True)\n correo = db.Column(db.String(120), unique=True)\n abo_stat = db.Column(db.DateTime)\n validated = db.Column(db.Boolean)\n role_id = db.Column(db.Integer, db.ForeignKey('roles.id'))\n contratos = db.relationship('ContUs', backref='usuario', lazy='dynamic')\n sub = db.relationship(\n 'Role', secondary=roles_pplz,\n primaryjoin=(roles_pplz.c.user_id == id),\n secondaryjoin=(roles_pplz.c.role_id == id),\n backref=db.backref('users', lazy='dynamic'), lazy='dynamic'\n )\n\n def set_password(self, password):\n self.password_hash = pbkdf2_sha256.hash(password)\n\n def check_password(self, password):\n return pbkdf2_sha256.verify(password, self.password_hash)\n\n def __repr__(self):\n return '<Usuario {}>'.format(self.usuario)\n\n def get_reset_password_token(self, expires_in=600):\n return jwt.encode(\n {'reset_password': self.id, 'exp': time() + expires_in},\n current_app.config['SECRET_KEY'], algorithm='HS256').decode('utf-8')\n\n @staticmethod\n def verify_reset_passwor_token(token):\n try:\n id = jwt.decode(token, current_app.config['SECRET_KEY'],\n algorithms=['HS256'])['reset_password']\n except:\n return\n return User.query.get(id)\n\n\nclass Contratos(db.Model):\n id = db.Column(db.Integer, primary_key=True)\n contenido = db.Column(db.String(15000))\n fin = db.Column(db.String(15000))\n tipo = db.Column(db.String(500))\n clausulas = db.relationship('Clausulas', backref='contrato', lazy='dynamic')\n declaraciones = db.relationship('Declaraciones', backref='contrato', lazy='dynamic')\n\n\nclass Role(db.Model, RoleMixin):\n id = db.Column(db.Integer, primary_key=True)\n tipo = db.Column(db.String(80), unique=True)\n\n def __str__(self):\n return self.tipo\n\n\nclass Clausulas(db.Model):\n id = db.Column(db.Integer, primary_key=True)\n desc = db.Column(db.String(15000))\n no = db.Column(db.String(50))\n titulo = db.Column(db.String(80))\n id_contrato = db.Column(db.Integer, db.ForeignKey('contratos.id'))\n movable = db.Column(db.Boolean, default=False)\n optional = db.Column(db.Boolean, default=False)\n end = db.Column(db.Boolean, default=False)\n\n\nclass Declaraciones(db.Model):\n id = db.Column(db.Integer, primary_key=True)\n desc = db.Column(db.String(15000))\n no = db.Column(db.String(10))\n titulo = db.Column(db.String(80))\n id_contrato = db.Column(db.Integer, db.ForeignKey('contratos.id'))\n movable = db.Column(db.Boolean, default=False)\n optional = db.Column(db.Boolean, default=False)\n end = db.Column(db.Boolean, default=False)\n\n\nclass ContUs(db.Model):\n id = db.Column(db.Integer, primary_key=True)\n ort = db.Column(db.String(200))\n nombre = db.Column(db.String(200))\n id_usr = db.Column(db.Integer, db.ForeignKey('user.id'))\n\n\n@login.user_loader\ndef load_user(id):\n return User.query.get(int(id))\n"
},
{
"alpha_fraction": 0.5293132066726685,
"alphanum_fraction": 0.7051926255226135,
"avg_line_length": 16.08571434020996,
"blob_id": "8ebea23c1d6bcf0b5f2d3c5c04110856986e518e",
"content_id": "83aca62dd56868b2aeb67a7ae70aa57a9833f57f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 597,
"license_type": "no_license",
"max_line_length": 25,
"num_lines": 35,
"path": "/requirements.txt",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "alembic==0.9.9\nBabel==2.5.3\nblinker==1.4\nclick==6.7\nFlask==1.0.2\nFlask-BabelEx==0.9.3\nFlask-Login==0.4.1\nFlask-Mail==0.9.1\nFlask-Migrate==2.1.1\nFlask-Principal==0.4.0\nFlask-Security==3.0.0\nFlask-SQLAlchemy==2.3.2\nFlask-WTF==0.14.2\nitsdangerous==0.24\nJinja2==2.10\nMako==1.0.7\nMarkupSafe==1.0\npasslib==1.7.1\npython-dateutil==2.7.3\npython-editor==1.0.3\npython-dotenv==0.8.2\npytz==2018.4\nsix==1.11.0\nspeaklater==1.3\nSQLAlchemy==1.2.7\nWerkzeug==0.14.1\nWTForms==2.1\nbeautifulsoup4==4.6.0\nreportlab==3.4.0\nPyJWT==1.5.3\npaypalrestsdk==1.13.1\n\n# requirements for Heroku\n# psycopg2==2.7.3.1\ngunicorn==19.7.1"
},
{
"alpha_fraction": 0.626153826713562,
"alphanum_fraction": 0.6753846406936646,
"avg_line_length": 22.214284896850586,
"blob_id": "9a9918e8e142095ce56477d8857cfbadb582e86c",
"content_id": "51ff4f68ae07dd10a924666045839123f2593fbd",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 650,
"license_type": "no_license",
"max_line_length": 78,
"num_lines": 28,
"path": "/migrations/versions/bb8d5b41a64c_.py",
"repo_name": "Baakel/contratosexpress",
"src_encoding": "UTF-8",
"text": "\"\"\"empty message\n\nRevision ID: bb8d5b41a64c\nRevises: b8ceddd90187\nCreate Date: 2018-08-28 16:19:07.518299\n\n\"\"\"\nfrom alembic import op\nimport sqlalchemy as sa\n\n\n# revision identifiers, used by Alembic.\nrevision = 'bb8d5b41a64c'\ndown_revision = 'b8ceddd90187'\nbranch_labels = None\ndepends_on = None\n\n\ndef upgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.add_column('user', sa.Column('validated', sa.Boolean(), nullable=True))\n # ### end Alembic commands ###\n\n\ndef downgrade():\n # ### commands auto generated by Alembic - please adjust! ###\n op.drop_column('user', 'validated')\n # ### end Alembic commands ###\n"
}
] | 16
|
vernwalrahul/Learning_Tensorflow
|
https://github.com/vernwalrahul/Learning_Tensorflow
|
9639f1f1796809d5985536c3556c1bd2a54d234f
|
38bd22e418c9cdd0f99b23b4cc9becdb2285cf13
|
013829c6beb3e5bb56ab88a1d4d71a42ada5acd7
|
refs/heads/master
| 2020-12-03T00:12:22.876261
| 2017-10-05T15:40:31
| 2017-10-05T15:40:31
| 95,999,696
| 0
| 2
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7180451154708862,
"alphanum_fraction": 0.7518796920776367,
"avg_line_length": 32.25,
"blob_id": "bf7668e925dacae627926a9896061e5a1d5fe08f",
"content_id": "8a4720bd89dab92aa6b186c8ac3f92f6e1956e50",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 266,
"license_type": "no_license",
"max_line_length": 61,
"num_lines": 8,
"path": "/CNN/testing_CNN.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "from tensorflow.examples.tutorials.mnist import input_data\nimport tensorflow as tf\nimport numpy as np\n\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\n\nx = tf.placeholder(tf.float32, shape=[None, 784])\ny_ = tf.placeholder(tf.float32, shape=[None, 10])\n"
},
{
"alpha_fraction": 0.5003484487533569,
"alphanum_fraction": 0.5435540080070496,
"avg_line_length": 24.625,
"blob_id": "b10001d7d135a76387ffcf62c387df1d3c317c9e",
"content_id": "69fa5f487cc5effb445746a828038344d3ec0c74",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1435,
"license_type": "no_license",
"max_line_length": 104,
"num_lines": 56,
"path": "/start.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "import tensorflow as tf\n\n#declaring constant\n\nn1=tf.constant(1.0, dtype=tf.float32)\nn2=tf.constant(2.0, dtype=tf.float32)\nprint(n1, n2) #will print their type, however on running the session one can get values\n\nsess=tf.Session()\n\nx=sess.run([n1,n2]) #values are assigned while running\nprint(x)\n\nn3=tf.subtract(n2,n1)\n\nsess=tf.Session()\n\nprint(sess.run(n3))\n\n\n#######################\n# Declaring placeholder (promising to provide value later)\n#######################\n\np1=tf.placeholder(tf.float32)\np2=tf.placeholder(tf.float32)\n\nsum=p1+p2 \n#or sum=tf.add(v1, v2)\n\n# sess=tf.Session()\nprint(sess.run(sum, {p1:1, p2:2}))\nprint(sess.run(sum, {p1:[1,2,3], p2:[1,1,1]}))\n\n\n######################\n# Variables\n######################\n\nv1=tf.Variable([0.3], dtype=tf.float32)\nv2=tf.Variable([-0.1], dtype=tf.float32)\ninit = tf.global_variables_initializer() \n\nsess.run(init) #to initialize all the variable you must explicitly call this\nprint(sess.run(v1+v2))\n\nass_v1=tf.assign(v1, [1])\nass_v2=tf.assign(v2, [2])\n\nsess.run([ass_v1, ass_v2])\nprint(sess.run(v1+v2))\n\n############################################################################################\n# Basically everything is an operation and you must put all that in sess.run() \n# *only takes single argument use list* to execute.\n############################################################################################\n"
},
{
"alpha_fraction": 0.6308671236038208,
"alphanum_fraction": 0.6770087480545044,
"avg_line_length": 24.612245559692383,
"blob_id": "c3aa46bef98c7838f9cf0c4d9b3e65bbe547e818",
"content_id": "b34c658ac6ffb152b39947f3b528e35e8e8e804c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1257,
"license_type": "no_license",
"max_line_length": 63,
"num_lines": 49,
"path": "/predict_digit.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "from tensorflow.examples.tutorials.mnist import input_data\nfrom scipy.misc import imshow\nimport tensorflow as tf\nimport numpy as np\n\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\nsess = tf.InteractiveSession()\n\nx = tf.placeholder(tf.float32, shape=[None, 784])\ny_ = tf.placeholder(tf.float32, shape=[None, 10])\n\nW = tf.Variable(tf.zeros([784,10]))\nb = tf.Variable(tf.zeros([10]))\n\nsess.run(tf.global_variables_initializer())\n\nweight=np.loadtxt('weights.txt')\nconst=np.loadtxt('const.txt')\nw_assign=tf.assign(W,np.reshape(weight,(784,10)))\nb_assign=tf.assign(b,np.reshape(const,(10)))\n\ntestim=mnist.test.next_batch(100)\n\ny = tf.matmul(x,W) + b\nsess.run([w_assign, b_assign])\nresult=sess.run([y], {x: testim[0]})\n\nindex=tf.argmax(result[0],1).eval()\n\n\nprint(\"\\n\\n predicted digit \\n\"+str(np.reshape(index,(10,10))))\n\ndef show_image(testim):\n image=np.reshape(testim[0],(28,28))\n\n for i in range(1,len(testim[:,1])):\n \tcurr=np.reshape(testim[i],(28,28))\n \timage=np.append(image, curr, axis=1)\n \n n_c=len(image[1,:])\n big_image=image[:,:(n_c/10)]\n for i in range(1,10):\n \ts_c=i*n_c/10\n \te_c=(i+1)*n_c/10\n \timage_temp=image[:,s_c:e_c]\n \tbig_image=np.append(big_image,image_temp , axis=0)\n imshow(big_image)\n \nshow_image(testim[0]) \t"
},
{
"alpha_fraction": 0.8552631735801697,
"alphanum_fraction": 0.8552631735801697,
"avg_line_length": 37,
"blob_id": "40611bb72a8998fa9cbff60258d273ae48e341e8",
"content_id": "e6dbe19c7b802c9b28ce0274b1520e25c50283b3",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 76,
"license_type": "no_license",
"max_line_length": 53,
"num_lines": 2,
"path": "/README.md",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "# Learning_Tensorflow\nimplementing ML concepts using tensorflow with python\n"
},
{
"alpha_fraction": 0.6970227956771851,
"alphanum_fraction": 0.7241681218147278,
"avg_line_length": 30.63888931274414,
"blob_id": "38047668c9fc4f8e26170113a674f1ef03f55d41",
"content_id": "6f540c32c6375fc00994a705c1140eeabbe58ff6",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1142,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 36,
"path": "/train_digit_recognition.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "from tensorflow.examples.tutorials.mnist import input_data\nimport tensorflow as tf\nimport numpy as np\n\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\nsess = tf.InteractiveSession()\n\nx = tf.placeholder(tf.float32, shape=[None, 784])\ny_ = tf.placeholder(tf.float32, shape=[None, 10])\n\nW = tf.Variable(tf.zeros([784,10]))\nb = tf.Variable(tf.zeros([10]))\n\nsess.run(tf.global_variables_initializer())\n\ny = tf.matmul(x,W) + b\n\ncross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))\n#sums up the cost and take average\ntrain_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)\n\nfor i in range(1000):\n batch = mnist.train.next_batch(100)\n train_step.run(feed_dict={x: batch[0], y_: batch[1]})\n\nweight=np.array(sess.run(W))\nconst=np.array(sess.run(b))\n\nnp.savetxt('weights.txt',weight)\nnp.savetxt('const.txt',const)\n\ncorrect_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))\naccuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n\nprint(\"\\n\\n\")\nprint(\"training completed with accuracy=\",accuracy.eval(feed_dict={x: mnist.test.images, y_: mnist.test.labels}))\n\n\n\n"
},
{
"alpha_fraction": 0.6261808276176453,
"alphanum_fraction": 0.6720647811889648,
"avg_line_length": 31.086956024169922,
"blob_id": "14fab81fefc72b82c0dfa850dcb6dc0405581ab4",
"content_id": "4c06551844a7a6800689bdb8227b8e6a905d4346",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 741,
"license_type": "no_license",
"max_line_length": 105,
"num_lines": 23,
"path": "/linear_regression.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "import tensorflow as tf\nx_train=tf.placeholder(tf.float32)\ny_train=tf.placeholder(tf.float32)\n\nW= tf.Variable([30], dtype=tf.float32)\nb=tf.Variable([-3 ], dtype=tf.float32)\n\nlin_func=W*x_train+b\n\ncost_arr=tf.square(lin_func- y_train)\ntotal_cost=tf.reduce_sum(cost_arr)\n\noptimizer=tf.train.GradientDescentOptimizer(0.01) #giving alpha value for gradient descent\ntrain=optimizer.minimize(total_cost)\n\ninit = tf.global_variables_initializer()\nsess = tf.Session()\nsess.run(init) \n\nfor i in range(1000):\n\tsess.run(train, {x_train: [1,2,3,4], y_train: [0, -1, -2, -3]})\n\tcurr_W, curr_b, curr_loss = sess.run([W, b, total_cost], {x_train: [1,2,3,4], y_train: [0, -1, -2, -3]})\n\tprint(\"W: %s b: %s loss: %s\"%(curr_W, curr_b, curr_loss))\n\n\n\n"
},
{
"alpha_fraction": 0.7000777125358582,
"alphanum_fraction": 0.7241647243499756,
"avg_line_length": 33.783782958984375,
"blob_id": "a6849f1db7c3d72d495b1673384f4b1568b5c0d9",
"content_id": "fcb6d85751656a4fee66296080a584f0e19fa3bc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1287,
"license_type": "no_license",
"max_line_length": 113,
"num_lines": 37,
"path": "/test.py",
"repo_name": "vernwalrahul/Learning_Tensorflow",
"src_encoding": "UTF-8",
"text": "from tensorflow.examples.tutorials.mnist import input_data\nfrom scipy.misc import imshow\nimport tensorflow as tf\nimport numpy as np\n\n\nnp.set_printoptions(threshold=np.inf)\nmnist = input_data.read_data_sets('MNIST_data', one_hot=True)\nsess = tf.InteractiveSession()\n\n\nx = tf.placeholder(tf.float32, shape=[None, 784])\ny_ = tf.placeholder(tf.float32, shape=[None, 10])\n\nW = tf.Variable(tf.zeros([784,10]))\nb = tf.Variable(tf.zeros([10]))\n\nsess.run(tf.global_variables_initializer())\n\ny = tf.matmul(x,W) + b\n\ncross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=y))\n#sums up the cost and take average\ntrain_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)\n\nbatch = mnist.train.next_batch(100)\n#print(\"Weight=\",np.array(sess.run(W)))\n\nfor i in range(10):\n\ttrain_step.run(feed_dict={x: batch[0], y_: batch[1]})\n\ttemp=np.array(sess.run(W))\n\t#print(\"After train_step \",temp)\n\tcorrect_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))\n\taccuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n\tprint(\"training completed with own accuracy=\",accuracy.eval(feed_dict={x: batch[0], y_: batch[1]}))\n\tprint(\"\\n\\n\")\nprint(\"training completed with accuracy=\",accuracy.eval(feed_dict={x: mnist.test.images, y_: mnist.test.labels}))\n"
}
] | 7
|
sunlightlabs/readthebill
|
https://github.com/sunlightlabs/readthebill
|
f490dddf33cba7d2f1d1e4835ff928847fab111a
|
6b5ce2bc68ceda3f24cbb555771029e839d8c704
|
bac3aba5a04e90e6e2ea0e33d51a87e90d1266d1
|
refs/heads/master
| 2021-01-12T14:18:26.149481
| 2016-10-04T22:10:06
| 2016-10-04T22:10:06
| 68,967,157
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6820015907287598,
"alphanum_fraction": 0.6916868686676025,
"avg_line_length": 27.159090042114258,
"blob_id": "53a5d87b4c0d30f2410f235d667aff57566de160",
"content_id": "1690dce5c30e4910b80b65a5898bb48279967b4f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3717,
"license_type": "no_license",
"max_line_length": 83,
"num_lines": 132,
"path": "/settings.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "# Django settings for readthebill project.\nimport os\nPROJECT_ROOT = os.path.abspath(os.path.dirname(__file__))\n\nDEBUG = True\nTEMPLATE_DEBUG = DEBUG\n\nADMINS = ()\n\nMANAGERS = ADMINS\n\n# Local time zone for this installation. Choices can be found here:\n# http://en.wikipedia.org/wiki/List_of_tz_zones_by_name\n# although not all choices may be available on all operating systems.\n# If running in a Windows environment this must be set to the same as your\n# system time zone.\nTIME_ZONE = 'America/New_York'\n\n# Language code for this installation. All choices can be found here:\n# http://www.i18nguy.com/unicode/language-identifiers.html\nLANGUAGE_CODE = 'en-us'\n\nSITE_ID = 1\n\n# If you set this to False, Django will make some optimizations so as not\n# to load the internationalization machinery.\nUSE_I18N = True\n\n# Absolute path to the directory that holds media.\n# Example: \"/home/media/media.lawrence.com/\"\nMEDIA_ROOT = os.path.join(PROJECT_ROOT, 'media')\n\n# URL that handles the media served from MEDIA_ROOT. Make sure to use a\n# trailing slash if there is a path component (optional in other cases).\n# Examples: \"http://media.lawrence.com\", \"http://example.com/media/\"\nMEDIA_URL = '/media/'\n\n# URL prefix for admin media -- CSS, JavaScript and images. Make sure to use a\n# trailing slash.\n# Examples: \"http://foo.com/media/\", \"/media/\".\nADMIN_MEDIA_PREFIX = 'http://assets.sunlightfoundation.com/admin/1.2.5/'\n\n# Make this unique, and don't share it with anybody.\nSECRET_KEY = ''\n\n# List of callables that know how to import templates from various sources.\nTEMPLATE_LOADERS = (\n 'django.template.loaders.filesystem.load_template_source',\n 'django.template.loaders.app_directories.load_template_source',\n)\n\nTEMPLATE_CONTEXT_PROCESSORS = (\n \"django.core.context_processors.request\",\n \"django.core.context_processors.auth\",\n \"django.core.context_processors.debug\",\n \"django.core.context_processors.i18n\",\n \"django.core.context_processors.media\",\n)\n\nMIDDLEWARE_CLASSES = (\n 'django.middleware.common.CommonMiddleware',\n 'django.contrib.sessions.middleware.SessionMiddleware',\n 'django.contrib.auth.middleware.AuthenticationMiddleware',\n 'gatekeeper.middleware.GatekeeperMiddleware',\n 'django.contrib.flatpages.middleware.FlatpageFallbackMiddleware',\n)\n\nROOT_URLCONF = 'readthebill.urls'\n\nTEMPLATE_DIRS = (\n os.path.join(PROJECT_ROOT, 'templates'),\n)\n\nINSTALLED_APPS = (\n 'django.contrib.admin',\n 'django.contrib.auth',\n 'django.contrib.comments',\n 'django.contrib.flatpages',\n 'django.contrib.contenttypes',\n 'django.contrib.markup',\n 'django.contrib.sessions',\n 'django.contrib.sites',\n 'mediasync',\n 'gatekeeper',\n 'failwhale',\n 'feedinator',\n 'morsels',\n 'contact_form',\n 'simplesurvey',\n 'uspolitics.politicians',\n #'callingtool',\n #'capcall', #temporary\n 'readthebill.rtb',\n 'tagging',\n 'blogdor',\n 'gunicorn',\n)\n\nGATEKEEPER_ENABLE_AUTOMODERATION = True\nGATEKEEPER_DEFAULT_STATUS = 0\n\nCONTACT_FORM_RECIPIENTS = ['']\n\nEMAIL_HOST = \"\"\nEMAIL_PORT = \"25\"\nEMAIL_HOST_USER = \"\"\nEMAIL_HOST_PASSWORD = \"\"\nEMAIL_USE_TLS = True\n\nMEDIASYNC = {\n 'BACKEND': '',\n 'AWS_KEY': '',\n 'AWS_SECRET': '',\n 'AWS_BUCKET': '',\n 'AWS_PREFIX': 'rtb/2.0',\n 'DOCTYPE': 'html5',\n 'CACHE_BUSTER': 201103181119,\n 'JOINED': {\n 'css/readthebill.css': ('css/screen.css','css/rtb.css'),\n 'js/readthebill.js': ('js/jquery-1.2.6.min.js','js/jquery.tablesorter.js'),\n },\n}\n\nimport re\nRTB_TAGS = [\"72[\\-\\s]hour\",\"read\\s?the\\s?bill\", \"h.\\s?res. 504\", \"[^\\w]?rtb[^\\w]?\"]\nRTB_REGEX = [re.compile(r) for r in RTB_TAGS]\nRTB_APPROVE_ALL = False\n\ntry:\n from local_settings import *\nexcept ImportError, exp:\n pass\n"
},
{
"alpha_fraction": 0.5926892757415771,
"alphanum_fraction": 0.5986571907997131,
"avg_line_length": 25.284313201904297,
"blob_id": "672f4d4068bc02ec649bf53e6103f6c77ebf24e1",
"content_id": "e8f4faaa4633e8b7913743f6b54055a9a6d968d4",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2681,
"license_type": "permissive",
"max_line_length": 81,
"num_lines": 102,
"path": "/morsels/templatetags/morsel_tags.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from morsels.models import Morsel\n\nfrom django.template import Library, Node\nfrom django.utils.safestring import mark_safe\nfrom django.conf import settings\n\ntypogrify = lambda a: a\ntry:\n if not getattr(settings, 'MORSELS_NO_TYPOGRIFY', False):\n settings.INSTALLED_APPS.index('typogrify')\n from typogrify import typogrify\nexcept ValueError:\n pass\n\nregister = Library()\n\nclass MorselNode(Node):\n\n def __init__(self, name, as_var, inherit):\n self.name = name\n self.as_var = as_var\n self.inherit = inherit\n\n def render(self, context):\n morsel = Morsel.objects.get_for_current(context, self.name, self.inherit)\n if morsel is None:\n return u''\n if self.as_var:\n context[self.as_var] = morsel\n return u''\n return mark_safe(typogrify(morsel.content))\n\n@register.tag\ndef morsel(parser, token):\n tokens = token.split_contents()\n\n try:\n as_tag = tokens.index(u'as')\n as_var = tokens[as_tag + 1]\n del tokens[as_tag]\n del tokens[as_tag]\n except (ValueError, IndexError):\n as_var = None\n\n try:\n tokens.remove(u'inherit')\n inherit = True\n except ValueError:\n inherit = False\n\n name = len(tokens) > 1 and tokens[1] or u''\n if name and name[0] in (u'\"', u\"'\") and name[-1] == name[0]:\n name = name[1:-1]\n\n return MorselNode(name, as_var, inherit)\n\nclass WithMorselNode(Node):\n def __init__(self, name, as_var, inherit, nodelist):\n self.name = name\n self.as_var = as_var\n self.inherit = inherit\n self.nodelist = nodelist\n\n def __repr__(self):\n return '<WithMorselNode>'\n\n def render(self, context):\n morsel = Morsel.objects.get_for_current(context, self.name, self.inherit)\n if morsel is None:\n return u''\n\n context.push()\n context[self.as_var] = morsel\n output = self.nodelist.render(context)\n context.pop()\n return output\n\n@register.tag\ndef withmorsel(parser, token):\n tokens = token.split_contents()\n\n try:\n as_tag = tokens.index(u'as')\n as_var = tokens[as_tag + 1]\n del tokens[as_tag]\n del tokens[as_tag]\n except (ValueError, IndexError):\n as_var = 'morsel'\n\n try:\n tokens.remove(u'inherit')\n inherit = True\n except ValueError:\n inherit = False\n\n name = len(tokens) > 1 and tokens[1] or u''\n if name and name[0] in (u'\"', u\"'\") and name[-1] == name[0]:\n name = name[1:-1]\n\n nodelist = parser.parse(('endwithmorsel',))\n parser.delete_first_token()\n return WithMorselNode(name, as_var, inherit, nodelist)\n"
},
{
"alpha_fraction": 0.6230106949806213,
"alphanum_fraction": 0.6407513618469238,
"avg_line_length": 27.183822631835938,
"blob_id": "ef4f02a18fee027fc1718d4c5be9e382b16034e9",
"content_id": "38198fc23600bacced9efce463094c084aa3d79d",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3833,
"license_type": "permissive",
"max_line_length": 122,
"num_lines": 136,
"path": "/morsels/tests.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "r\"\"\"\n>>> from morsels.models import Morsel\n\n# remove typogrify and sites apps for testing\n>>> from django.conf import settings\n>>> original_INSTALLED_APPS = settings.INSTALLED_APPS\n>>> if 'typogrify' in settings.INSTALLED_APPS: settings.INSTALLED_APPS.remove('typogrify')\n>>> if 'sites' in settings.INSTALLED_APPS: settings.INSTALLED_APPS.remove('sites')\n\n# test creating a morsel\n>>> m1 = Morsel.objects.create(url='/', title='M1', content='Morsel 1')\n>>> m1\n<Morsel: / -- M1>\n\n# create a few more morsels\n>>> m2 = Morsel.objects.create(url='/section1/info', title='M2', content='Morsel 2')\n>>> m3 = Morsel.objects.create(url='/section1/page1/info', title='M3', content='Morsel 3')\n>>> m4 = Morsel.objects.create(url='/section1/page1/', title='M4', content='Morsel 4')\n\n# morsel url must be unique\n>>> m5 = Morsel.objects.create(url='/section1/page1/info', content='Morsel 5')\nTraceback (most recent call last):\n ...\nIntegrityError: ...\n\n# create a locked morsel\n>>> m6 = Morsel.objects.create(url='/section1/page2/', locked=True)\n>>> m6.delete()\nTraceback (most recent call last):\n ...\nLockedError: Morsel \"/section1/page2/ -- \" cannot be deleted.\n\n>>> m6.locked = False\n>>> m6.save()\n>>> m6.delete()\n\n# set up a dummy request context, for rendering templates at specific url's\n>>> from django.template import Context\n>>> from django.template.loader import get_template_from_string\n>>> from django.http import HttpRequest\n>>> r = HttpRequest()\n>>> c = Context({'request': r})\n\n# the simplest morsel tag - find morsel by page url only\n>>> t = get_template_from_string('{% load morsel_tags %}{% morsel %}')\n>>> r.path = '/'\n>>> t.render(c)\nu'Morsel 1'\n\n>>> r.path = '/section1/'\n>>> t.render(c)\nu''\n\n>>> r.path = '/section1/page1/'\n>>> t.render(c)\nu'Morsel 4'\n\n# tag variation - find morsel with a custom name (url suffix)\n>>> t = get_template_from_string('{% load morsel_tags %}{% morsel info %}')\n>>> r.path = '/'\n>>> t.render(c)\nu''\n\n>>> r.path = '/section1/'\n>>> t.render(c)\nu'Morsel 2'\n\n>>> r.path = '/section1/page1/'\n>>> t.render(c)\nu'Morsel 3'\n\n# another variation - find morsel with inheritance\n>>> t = get_template_from_string('{% load morsel_tags %}{% morsel inherit %}')\n>>> r.path = '/section1/page1/'\n>>> t.render(c)\nu'Morsel 4'\n\n>>> r.path = '/section1/'\n>>> t.render(c)\nu'Morsel 1'\n\n>>> r.path = '/section1/page2/'\n>>> t.render(c)\nu'Morsel 1'\n\n>>> r.path = '/section1/page1/subpage/'\n>>> t.render(c)\nu'Morsel 4'\n\n# test inserting morsel into context\n>>> t = get_template_from_string('{% load morsel_tags %}{% morsel as var %}{{ var.title }}')\n>>> r.path = '/section1/page1/'\n>>> t.render(c)\nu'M4'\n\n>>> c\n[{u'var': <Morsel: /section1/page1/ -- M4>, ...\n...\n\n>>> r.path = '/section1/page2/'\n>>> c = Context({'request': r}) # new context to remove previous morsel\n>>> t.render(c)\nu''\n\n# test withmorsel tag\n>>> t = get_template_from_string('{% load morsel_tags %}{% withmorsel %}{{ morsel.content }}{% endwithmorsel %}')\n>>> r.path = '/section1/page1/'\n>>> c = Context({'request': r})\n>>> t.render(c)\nu'Morsel 4'\n\n# ... and with custom name and 'as'\n>>> t = get_template_from_string('{% load morsel_tags %}{% withmorsel info as var %}{{ var.content }}{% endwithmorsel %}')\n>>> r.path = '/section1/'\n>>> t.render(c)\nu'Morsel 2'\n\n# ... and with inheritance\n>>> t = get_template_from_string('{% load morsel_tags %}{% withmorsel inherit %}{{ morsel.content }}{% endwithmorsel %}')\n>>> r.path = '/section1/'\n>>> t.render(c)\nu'Morsel 1'\n\n# test morsel lookup with Sites enabled\n>>> from django.contrib.sites.models import Site\n>>> settings.INSTALLED_APPS.append('sites')\n>>> s = Site.objects.get_current()\n>>> m = Morsel.objects.create(url='/site/', title='AM', content='A Morsel')\n>>> m.sites.add(s)\n>>> r.path = '/site/'\n>>> t.render(c)\nu'A Morsel'\n\n# cleanup\n>>> settings.INSTALLED_APPS = original_INSTALLED_APPS\n\"\"\"\n"
},
{
"alpha_fraction": 0.6694831252098083,
"alphanum_fraction": 0.6873757243156433,
"avg_line_length": 28.58823585510254,
"blob_id": "57d0faf5f8c73b37ba0adf4ac514816bf91d856f",
"content_id": "365275e08346e07855a9fac1329590f12ab33926",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 2012,
"license_type": "no_license",
"max_line_length": 229,
"num_lines": 68,
"path": "/templates/callingtool/legislator_list_nojs.html",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "{% extends \"base_call.html\" %}\n\n{% block content %}\n\n<script type=\"text/javascript\">\n/* on ready */\n\n$(function() {\n $(\"table\").tablesorter();\n} );\n\nfunction checkZip(elmnt,content) {\n if (content.length==5) { \n\tdocument.getElementById('chosen_reps').style.display='block';\n\t$('#your_reps').load('/call/zip_rep/' + content + '/', null, function() { $('#your_reps').fadeIn(); });\n }\n} \n</script>\n\n\n{% if has_called %}\n<div id=\"thanks_box\"><h1 class=\"header thanks\">Thank you for taking the time to call your representative.</h1></div>\n{% else %}\n<!--<div id=\"header_box\">\n<h1 class=\"header\">The Senate is considering a bill S. 482 that would increase the disclosure of campaign contributions to Senate campaigns.</h1>\n</div>-->\n{% endif %}\n\n\n<div id=\"candidates_box\">\n<div id=\"candidates_explanation\">Reps. Baird and Culberson recently introduced a resolution (H. Res. 554) to require the U.S. House of Representatives to post online all non-emergency legislation 72 hours before debate begins.</div>\n</div>\n\n\n<div id=\"considering2\" style=\"font-size:18px; line-height:23px; height:100px;\"><img src=\"http://media.sunlightprojects.org/readthebill/images/v2/72_button_a.png\" border=\"0\" style=\"float:left; margin-right:5px;\">\n\t<span class=\"display:block; width:200px;\">This resolution will create more transparency of the legislative process by \ngiving lawmakers the time to debate bills with full knowledge and consideration of their implications, while giving citizens time to read \nlegislation and voice their concerns to their congressional delegation.\n</span>\n</div>\n\n<h2 class=\"fortunately\" style=\"clear:both;\">Legislative transparency is only a phone call away. Call now.</h2>\n<div id=\"steps\">\n\t<ul>\n <li>Determine your representative.</li>\n <li>Call his or her office.</li>\n <li>Ask if he or she will co-sponsor the 72 Hour Rule (H. Res. 554).</li>\n\n </ul>\n</div>\t\n\n\n\n\n <div id=\"your_reps\">\n {{ repblock }}\n </div>\n\n</div> <!-- ends senator box -->\n</div>\n\n\n\n\n\n\n\n{% endblock content %}\n"
},
{
"alpha_fraction": 0.6329571008682251,
"alphanum_fraction": 0.6343114972114563,
"avg_line_length": 29.76388931274414,
"blob_id": "7baf4a42d12e1f0aec426c40b1a0e61631ae8cc2",
"content_id": "7c606131c367e9af22b03acb8ff8499fabc63ea7",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2215,
"license_type": "no_license",
"max_line_length": 151,
"num_lines": 72,
"path": "/callingtool/models.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.contrib import admin\nfrom django.db import models\nfrom django.contrib.contenttypes.models import ContentType\nfrom django.contrib.contenttypes.generic import GenericRelation\nfrom simplesurvey.models import AnswerSet\nfrom uspolitics.politicians.models import Politician\n\nON_BILL_CHOICES = (\n ('U', 'Unknown'),\n ('C', 'Cosponsor'),\n ('S', 'Supports'),\n ('O', 'Opposes'))\n\nclass LegislatorDetailManager(models.Manager):\n def get_query_set(self):\n return super(LegislatorDetailManager, self).get_query_set().extra(\n select={'num_calls': 'SELECT COUNT(*) FROM simplesurvey_answerset WHERE content_type_id=%s AND object_id=callingtool_legislatordetail.id'},\n select_params=(ContentType.objects.get(app_label='callingtool', model='legislatordetail').id,)\n )\n\nclass LegislatorDetail(models.Model):\n\n objects = LegislatorDetailManager()\n\n legislator = models.OneToOneField(Politician)\n\n on_bill = models.CharField(max_length=1, choices=ON_BILL_CHOICES, default='U')\n on_amendment = models.NullBooleanField(default=None)\n call_goal = models.SmallIntegerField(default=10)\n\n calls = GenericRelation(AnswerSet)\n\n def __unicode__(self):\n return u' '.join([self.legislator.get_title_display(), \n self.good_fname(), self.legislator.lastname])\n\n def good_fname(self):\n return self.legislator.nickname or self.legislator.firstname\n\n def is_cosponsor(self):\n return self.on_bill == 'C'\n\n def supports_bill(self):\n if self.on_bill in ('C','S'):\n return True\n elif self.on_bill == 'O':\n return False\n else:\n return None\n\n def he_or_she(self):\n if self.legislator.gender == 'F':\n return 'she'\n else:\n return 'he'\n\n def his_or_her(self):\n if self.legislator.gender == 'F':\n return 'her'\n else:\n return 'his'\n\n def him_or_her(self):\n if self.legislator.gender == 'F':\n return 'her'\n else:\n return 'him'\n\n def needs_more_calls(self):\n return self.calls.count() < self.call_goal\n\nadmin.site.register(LegislatorDetail)\n"
},
{
"alpha_fraction": 0.6692041754722595,
"alphanum_fraction": 0.6730104088783264,
"avg_line_length": 42.712120056152344,
"blob_id": "4cb32a72f551644dbf9605b0d5e62ced4f6c74f6",
"content_id": "dfff1ca603e8bab6a8a4d3e1c19d4601d1f02215",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2890,
"license_type": "no_license",
"max_line_length": 208,
"num_lines": 66,
"path": "/rtb/views.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.conf import settings\nfrom django.http import HttpResponse, HttpResponseRedirect, Http404\nfrom django.shortcuts import render_to_response\nfrom django.template import RequestContext\nfrom feedinator.models import Feed, FeedEntry\nfrom readthebill.rtb.forms import SignupForm\nfrom readthebill.rtb.models import Organization\nimport gatekeeper\nimport urllib, urllib2\n\ndef index(request):\n \n is_thanks = (\"thanks\" in request.GET) and True or False\n \n if request.method == 'POST':\n \n form = SignupForm(request.POST)\n \n if form.is_valid():\n \n email = form.cleaned_data['email']\n zipcode = form.cleaned_data['zipcode']\n #affiliation = form.cleaned_data['affiliation']\n #message = form.cleaned_data.get('message', '')\n \n first_name = form.cleaned_data['first_name']\n last_name = form.cleaned_data['last_name']\n \n bsd_url = \"http://bsd.sunlightfoundation.com/page/s/rtbpetition\"\n #params = {\"email\": email, \"zip\": zipcode, \"custom-109\": affiliation, \"custom-108\": message}\n params = {\"email\": email, \"zip\": zipcode, \"firstname\": first_name, \"lastname\": last_name}\n response = urllib2.urlopen(bsd_url, urllib.urlencode(params)).read()\n\n return HttpResponseRedirect('/?thanks')\n #return HttpResponseRedirect('http://bsd.sunlightfoundation.com/page/invite/readthebill')\n \n else:\n form = SignupForm()\n \n #entries = FeedEntry.objects.all().approved()\n return render_to_response(\"index.html\", {\"form\": form, \"is_thanks\": is_thanks }, context_instance=RequestContext(request))\n\ndef petition(request):\n return render_to_response(\"petition.html\")\n\ndef photos(request):\n return render_to_response(\"photos.html\", {\"flickr_id\": settings.FLICKR_ID, \"flickr_tag\": settings.FLICKR_TAG})\n\ndef support(request):\n return render_to_response(\"support.html\", {\"task_key\": request.GET.get(\"task_key\"), \"username\": request.GET.get(\"username\"), \"tcorps_url\": settings.TCORPS_TASK_URL, \"message\": request.GET.get(\"message\")})\n\ndef partners(request):\n partners = Organization.objects.order_by('name')\n return render_to_response(\"partners.html\", {\"partners\": partners}, context_instance=RequestContext(request))\n\ndef partner_page(request, id):\n entry = FeedEntry.objects.get(pk=id)\n return render_to_response(\"partner_frame.html\", {\"entry\": entry}, context_instance=RequestContext(request))\n\ndef press(request):\n feed = Feed.objects.get(codename=\"press\")\n return render_to_response(\"press.html\", {\"feed\": feed}, context_instance=RequestContext(request))\n\ndef rushed_bills(request):\n feed = Feed.objects.get(codename=\"rushedbills\")\n return render_to_response(\"rushed_bills.html\", {\"feed\": feed}, context_instance=RequestContext(request))\n \n"
},
{
"alpha_fraction": 0.6329200863838196,
"alphanum_fraction": 0.6363636255264282,
"avg_line_length": 39.33333206176758,
"blob_id": "f457581b309e30eeb0458adac5adef338fc24511",
"content_id": "218568c9a543012196666148312956070ce4b49a",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1452,
"license_type": "permissive",
"max_line_length": 93,
"num_lines": 36,
"path": "/morsels/models.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from managers import MorselManager\nfrom exceptions import LockedError\n\nfrom django.db import models\nfrom django.utils.translation import ugettext_lazy as _\nfrom django.contrib.sites.models import Site\n\nclass Morsel(models.Model):\n url = models.CharField(_('url'), max_length=100, db_index=True, unique=True,\n help_text=_(\"\"\"\n The URL of the page in which this morsel should be shown, followed by an optional\n name. Examples: '/', '/contact/', '/contact/sidebar'.\n Make sure to have leading and trailing slashes for the page url, but no slash\n after the morsel name.\"\"\"))\n title = models.CharField(_('title'), max_length=80, blank=True)\n content = models.TextField(_('content'), blank=True)\n sites = models.ManyToManyField(Site, verbose_name=_('sites'))\n locked = models.BooleanField(_('locked'), default=False,\n help_text=_(\"\"\"\n Locked morsels cannot be deleted. Think twice before unlocking a morsel,\n as there is likely to be a good reason for it to be locked.\"\"\"))\n\n objects = MorselManager()\n\n class Meta:\n verbose_name = _('morsel')\n verbose_name_plural = _('morsels')\n ordering = ('url',)\n\n def __unicode__(self):\n return u'%s -- %s' % (self.url, self.title)\n\n def delete(self):\n if self.locked:\n raise LockedError('Morsel \"%s\" cannot be deleted.' % self)\n super(Morsel, self).delete()\n"
},
{
"alpha_fraction": 0.5120000243186951,
"alphanum_fraction": 0.5120000243186951,
"avg_line_length": 20,
"blob_id": "14b7db0cad9818e581e98b4578b05fb9697cb769",
"content_id": "b429c5bc215c2684be8ba694bd6d9f3de3c97639",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 125,
"license_type": "no_license",
"max_line_length": 43,
"num_lines": 6,
"path": "/failwhale/templates/failwhale/templatetags/summize.html",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "{% import failtags %}\n<ol>\n {% for result in results %}\n <li>{{ result|tweetile|safe }}</li>\n {% endfor %}\n</ol>"
},
{
"alpha_fraction": 0.5827650427818298,
"alphanum_fraction": 0.5881897211074829,
"avg_line_length": 33.13756561279297,
"blob_id": "bb0680eb7a6b3359a46ef514d0cbaa2271e9de2c",
"content_id": "1c7008bf9a8420434cb4107075c15e46eb3b9211",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6452,
"license_type": "no_license",
"max_line_length": 108,
"num_lines": 189,
"path": "/callingtool/views.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "import re\nfrom django.shortcuts import render_to_response, get_object_or_404\nfrom django.http import HttpResponseNotAllowed, HttpResponseRedirect\nfrom django.core.urlresolvers import reverse\nfrom django.conf import settings\nfrom django.core.cache import cache\nfrom django.utils.encoding import iri_to_uri\nfrom django.contrib.auth.decorators import login_required\n\nfrom simplesurvey.models import AnswerSet, Answer, Question, QuestionSet\nfrom callingtool.models import LegislatorDetail\n\nfrom sunlightapi import sunlight, SunlightApiError\nsunlight.apikey = '0b738e1dc83d9ac6d619537c7d48e088'\n\n\nSTATES = (\n ('AL', 'Alabama'),\n ('AK', 'Alaska'),\n ('AZ', 'Arizona'),\n ('AR', 'Arkansas'),\n ('CA', 'California'),\n ('CO', 'Colorado'),\n ('CT', 'Connecticut'),\n ('DE', 'Delaware'),\n ('DC', 'District of Columbia'),\n ('FL', 'Florida'),\n ('GA', 'Georgia'),\n ('HI', 'Hawaii'),\n ('ID', 'Idaho'),\n ('IL', 'Illinois'),\n ('IN', 'Indiana'),\n ('IA', 'Iowa'),\n ('KS', 'Kansas'),\n ('KY', 'Kentucky'),\n ('LA', 'Louisiana'),\n ('ME', 'Maine'),\n ('MD', 'Maryland'),\n ('MA', 'Massachusetts'),\n ('MI', 'Michigan'),\n ('MN', 'Minnesota'),\n ('MS', 'Mississippi'),\n ('MO', 'Missouri'),\n ('MT', 'Montana'),\n ('NE', 'Nebraska'),\n ('NV', 'Nevada'),\n ('NH', 'New Hampshire'),\n ('NJ', 'New Jersey'),\n ('NM', 'New Mexico'),\n ('NY', 'New York'),\n ('NC', 'North Carolina'),\n ('ND', 'North Dakota'),\n ('OH', 'Ohio'),\n ('OK', 'Oklahoma'),\n ('OR', 'Oregon'),\n ('PA', 'Pennsylvania'),\n ('RI', 'Rhode Island'),\n ('SC', 'South Carolina'),\n ('SD', 'South Dakota'),\n ('TN', 'Tennessee'),\n ('TX', 'Texas'),\n ('UT', 'Utah'),\n ('VT', 'Vermont'),\n ('VA', 'Virginia'),\n ('WA', 'Washington'),\n ('WV', 'West Virginia'),\n ('WI', 'Wisconsin'),\n ('WY', 'Wyoming'),\n)\n\nSTATE_DICT = dict(STATES)\n\ndef delete_url_cache(url):\n \"\"\" simple method to delete the cache for a particular URL \"\"\"\n key_prefix = settings.CACHE_MIDDLEWARE_KEY_PREFIX\n cache_key = 'views.decorators.cache.cache_header.%s.%s' % (key_prefix,\n iri_to_uri(url))\n cache.delete(cache_key)\n\ndef legislator_list(request):\n has_called = request.session.get('has_called', False)\n if has_called:\n del request.session['has_called']\n return render_to_response('callingtool/legislator_list.html',\n {'legislator_list': LegislatorDetail.objects.exclude(legislator__title='Sen'),\n 'states': STATES,\n 'has_called': has_called})\n\ndef call_legislator(request, id):\n legislator = get_object_or_404(LegislatorDetail, id=id)\n calls = []\n for call in legislator.calls.all():\n cdict = {'date':call.date}\n for q,a in call.q_and_a():\n if a:\n cdict[q.text] = a.text\n calls.append(cdict)\n\n return render_to_response('callingtool/legislator_call.html',\n {'legislator': legislator, 'calls': calls})\n\ndef state_reps(request, state):\n reps = LegislatorDetail.objects.filter(legislator__state=state).exclude(legislator__title='Sen')\n return render_to_response('callingtool/state_reps.html',\n {'state_name': STATE_DICT[state],\n 'reps': reps})\n\ndef zip_rep(request, zipcode):\n oreps = sunlight.legislators.allForZip(zipcode)\n reps = []\n for o in oreps:\n if o.title!='Sen':\n qs = LegislatorDetail.objects.get(legislator__crp_id=o.crp_id)\n reps.append( qs )\n return render_to_response('callingtool/zip_rep.html',\n {'zipcode':zipcode, 'reps': reps})\n\ndef zip_direct(request, zipcode):\n from django.template.loader import get_template\n from django.template import Context\n from django.http import HttpResponse\n\n if zipcode=='00000':\n if request.POST['zip']:\n zipcode = request.POST['zip']\n oreps = sunlight.legislators.allForZip(zipcode)\n reps = []\n for o in oreps:\n if o.title!='Sen':\n qs = LegislatorDetail.objects.get(legislator__crp_id=o.crp_id)\n reps.append( qs )\n t = get_template('callingtool/zip_rep.html')\n repblock = t.render(Context({'zipcode':zipcode, 'reps': reps}))\n\n return render_to_response('callingtool/legislator_list_nojs.html',\n {'repblock':repblock})\n\n\n\ndef submit_call(request, id):\n if request.method != 'POST':\n return HttpResponseNotAllowed(['POST'])\n\n # blank or zipcode\n zipcode = request.POST['zip']\n if not re.match('^(\\d{5}(\\-\\d{4})?)?$', zipcode):\n return HttpResponseRedirect(reverse('legislator_list'))\n\n call = AnswerSet.objects.create(question_set=QuestionSet.objects.get(slug=\"readthebill-call\"),\n related_object=LegislatorDetail.objects.get(id=id))\n\n for q in request.POST.iterkeys():\n Answer.objects.create(answer_set=call,\n question=Question.objects.get(text=q),\n text=request.POST.get(q))\n\n request.session['has_called'] = id\n\n # clear related cache keys\n delete_url_cache('/')\n delete_url_cache('/state_reps/%s/' % LegislatorDetail.objects.get(pk=id).legislator.state)\n delete_url_cache('/call/%s/' % id)\n delete_url_cache('/all_calls/')\n\n return HttpResponseRedirect(reverse('legislator_list'))\n\ndef all_calls(request):\n calls = []\n for call in AnswerSet.objects.all().order_by('-date'):\n cdict = {'date':call.date, 'rep':call.related_object, 'id': call.id}\n for q,a in call.q_and_a():\n if a:\n cdict[q.text] = a.text\n calls.append(cdict)\n num_calls = len(calls)\n num_unique = Answer.objects.filter(question__text='email').values_list('text').distinct().count()\n num_sens = AnswerSet.objects.values_list('object_id').distinct().count()\n\n return render_to_response('callingtool/all_calls.html', {'calls': calls,\n 'num_calls': num_calls, 'num_unique': num_unique, 'num_sens': num_sens})\n\n@login_required\ndef delete_call(request, id):\n ans = AnswerSet.objects.filter(id=id)[0]\n pol_id = ans.object_id\n ans.delete()\n delete_url_cache('/call/%s/' % pol_id)\n delete_url_cache('/all_calls/')\n return HttpResponseRedirect(reverse('all_calls'))\n"
},
{
"alpha_fraction": 0.5371819734573364,
"alphanum_fraction": 0.5420743823051453,
"avg_line_length": 28.200000762939453,
"blob_id": "f0c8d624f29c6d0d4f1939eabbf1a7cff30112a8",
"content_id": "f7292f1ecf2fa1cfd8d751503dd4fe9105fd2450",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1022,
"license_type": "permissive",
"max_line_length": 62,
"num_lines": 35,
"path": "/morsels/managers.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.db import models\nfrom django.conf import settings\n\nif 'sites' in settings.INSTALLED_APPS:\n SITES = True\n from django.contrib.flatpages.models import Site\nelse:\n SITES = False\n\nclass MorselManager(models.Manager):\n def get_for_current(self, context, name, inherit=False):\n\n if not context.has_key('request'):\n return None\n\n url = context['request'].path\n page = context.get('page', None)\n if page is not None:\n ix = url.rfind('%d/' % page)\n if ix != -1:\n url = url[:ix]\n \n path = url[:-1].split('/')\n urls = ['/'.join(path + [name])]\n while inherit is True and len(path) > 1:\n path = path[:-1]\n urls.append('/'.join(path + [name]))\n \n qs = self.get_query_set()\n if SITES:\n qs = qs.filter(sites=Site.objects.get_current())\n try:\n return qs.filter(url__in=urls).order_by('-url')[0]\n except IndexError:\n return None\n"
},
{
"alpha_fraction": 0.8608695864677429,
"alphanum_fraction": 0.8608695864677429,
"avg_line_length": 28,
"blob_id": "82cf2be61be7aee4694f1bf25c8da7dc4e85cccc",
"content_id": "6f1d71923b71094c1540fbe5366aa38cf897784c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 115,
"license_type": "no_license",
"max_line_length": 47,
"num_lines": 4,
"path": "/rtb/admin.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.contrib import admin\nfrom readthebill.rtb.models import Organization\n\nadmin.site.register(Organization)"
},
{
"alpha_fraction": 0.6653696298599243,
"alphanum_fraction": 0.6653696298599243,
"avg_line_length": 29.294116973876953,
"blob_id": "7cee9a1d1ca0a0f0c0197e918de16a6405620733",
"content_id": "c3cb00a04f3b95fdef85d4dcecfb727805b9c804",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 514,
"license_type": "no_license",
"max_line_length": 65,
"num_lines": 17,
"path": "/failwhale/management/commands/updatestatus.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.core.management.base import BaseCommand, CommandError\nfrom failwhale import util\nfrom failwhale.models import Account\n \nclass Command(BaseCommand):\n \n help = \"Update account statuses\"\n args = '([name])'\n \n requires_model_validation = False\n \n def handle(self, name=None, *args, **options):\n \n accounts = Account.objects.filter(passwd__isnull=False)\n for account in accounts:\n util.import_profile(account)\n util.import_statuses(account)"
},
{
"alpha_fraction": 0.7785365581512451,
"alphanum_fraction": 0.7814634442329407,
"avg_line_length": 50.29999923706055,
"blob_id": "449d1fdc27849043504d57d6fb888a6ca6e7c424",
"content_id": "2240554c74b7a6c19ec4f698d8263a31de5bc4ad",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Shell",
"length_bytes": 1025,
"license_type": "no_license",
"max_line_length": 114,
"num_lines": 20,
"path": "/dbinit.sh",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "#!/bin/bash\n\n./manage.py addfeed http://www.sunlightfoundation.com/feeds/latest/ sunlightfoundation\n./manage.py addfeed http://www.thenextright.com/fbfeed thenextright\n./manage.py addfeed http://www.cnewmark.com/rss.xml craignewmark\n./manage.py addfeed http://pogoblog.typepad.com/pogo/index.rdf pogo\n./manage.py addfeed http://personaldemocracy.com/node/feed pdf\n./manage.py addfeed http://www.ombwatch.org/blog/all/all/all/feed ombwatch\n./manage.py addfeed http://www.mediaaccess.org/rss/ mediaaccess\n./manage.py addfeed http://www.fas.org/blog/secrecy/feed secrecynews\n./manage.py addfeed http://www.eff.org/rss/updates.xml eff\n./manage.py addfeed http://www.opensecrets.org/news/rss.xml crp\n./manage.py addfeed http://blog.cdt.org/feed/ cdt\n\n./manage.py addfeed \"http://dev.opencongress.org/bill/readthebill.rss?sort=gpo&show_resolutions=false\" rushedbills\n./manage.py addfeed \"http://feeds.delicious.com/v2/rss/sunlight_foundation/readthebill?count=15\" press\n\n./manage.py updatefeeds\n\n./manage.py loaddata data/orgs.json"
},
{
"alpha_fraction": 0.6644737124443054,
"alphanum_fraction": 0.6644737124443054,
"avg_line_length": 27.5625,
"blob_id": "2ca91fb0bfd6dee5b448c33820ebc7d5d8db4c81",
"content_id": "423d0087e69e7935b30f332a08ee7fe900e4fbef",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 456,
"license_type": "no_license",
"max_line_length": 65,
"num_lines": 16,
"path": "/failwhale/management/commands/updatesummize.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.core.management.base import BaseCommand, CommandError\nfrom failwhale import util\nfrom failwhale.models import Summize\n \nclass Command(BaseCommand):\n \n help = \"Update summize searches\"\n args = '([name])'\n \n requires_model_validation = False\n \n def handle(self, name=None, *args, **options):\n \n summizes = Summize.objects.all()\n for summize in summizes:\n util.import_search_results(summize)"
},
{
"alpha_fraction": 0.6952953934669495,
"alphanum_fraction": 0.7051422595977783,
"avg_line_length": 59.766666412353516,
"blob_id": "16cba9f9d3322619650816486cbcf66ba02f101a",
"content_id": "6093cfff15849e525bfe49276ff3ddcd0d1a7c62",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 1828,
"license_type": "no_license",
"max_line_length": 185,
"num_lines": 30,
"path": "/templates/callingtool/roberts_script.html",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": " <p>I am also calling to find out if the senator will withdraw his amendment to S. 482.\n This amendment will decrease the chances that S.482 will pass and become law and it should be considered separately.</p>\n\n <p>Can you tell me if he plans to withdraw it? </p>\n\n <select name=\"oppose_amendment\" id=\"oppose_amendment\">\n <option value=\"n/a\">-- Report the Response --</option>\n <option value=\"yes\">Yes</option>\n <option value=\"unknown\">I Don't Know / Senator hasn't decided yet</option>\n <option value=\"no\">No</option>\n </select>\n\n <div class=\"script_item oppose_amendment_answer\" id=\"oppose_amendment_yes\">\n <h5 class=\"green\">If \"Yes\" on withdrawing amendment</h5>\n <p>Please thank Senator {{legislator.legislator.lastname}} for {{legislator.his_or_her}} support for a more transparent Congress.</p>\n {% include \"callingtool/end_call.html\" %}\n </div>\n\n <div class=\"script_item oppose_amendment_answer\" id=\"oppose_amendment_unknown\">\n <h5 class=\"orange\">If \"I Don't Know\" or \"Senator Hasn't Decided Yet\" on withdrawing amendment </h5>\n <p>Please let Senator {{legislator.legislator.lastname}} know that his Amendment will prevent groups from filing legitimate ethics complaints and should be considered separately.\n {% include \"callingtool/end_call.html\" %}\n </div>\n\n <div class=\"script_item oppose_amendment_answer\" id=\"oppose_amendment_no\">\n <h5 class=\"red\">If \"No\" on withdrawing amendment </h5>\n <p>Please let Senator {{legislator.legislator.lastname}} know that I hope {{legislator.he_or_she}} reconsiders. The amendment will hurt S. 482's chances of passing and becoming law.\n S. 482 is commonsense, uncontroversial legislation that will pass as long as the Roberts Amendment fails.</p>\n {% include \"callingtool/end_call.html\" %}\n </div>\n\n"
},
{
"alpha_fraction": 0.5811688303947449,
"alphanum_fraction": 0.5827922224998474,
"avg_line_length": 43,
"blob_id": "a304e104bb2587376664afd238e52f385f508f65",
"content_id": "b2548a028c80e50a1fe0f2708cea3f039500d468",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 616,
"license_type": "no_license",
"max_line_length": 79,
"num_lines": 14,
"path": "/callingtool/urls.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.conf.urls.defaults import *\n\nurlpatterns = patterns('callingtool.views',\n\n url(r'^zip_rep/(?P<zipcode>\\d+)/$', 'zip_rep'),\n url(r'^zip_direct/(?P<zipcode>\\d*)/$', 'zip_direct'),\n url(r'^$', 'legislator_list', name='legislator_list'),\n url(r'^(?P<id>\\d+)/$', 'call_legislator', name='call_legislator'),\n url(r'^state_reps/(?P<state>[A-Z]{2})/$', 'state_reps', name='state_reps'),\n url(r'^submit_call/(?P<id>\\d+)/$', 'submit_call', name='submit_call'),\n url(r'^all_calls/$', 'all_calls', name='all_calls'),\n url(r'^delete_call/(?P<id>\\d+)/$', 'delete_call', name='delete_call'),\n\n)\n"
},
{
"alpha_fraction": 0.6623563170433044,
"alphanum_fraction": 0.6767241358757019,
"avg_line_length": 40,
"blob_id": "81831b00e5cf4e1e1efb4eaa1ea1a3b6346fb9db",
"content_id": "becb5b55bc26ca57633a469f1a49a5c2a6e07fc0",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 696,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 17,
"path": "/rtb/forms.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django import forms\n\nAFFILIATION_CHOICES = (\n ('',''),\n ('c','Conservative'),\n ('i','Independent'),\n ('l','Liberal'),\n ('x','Private'),\n)\n\nclass SignupForm(forms.Form):\n first_name = forms.CharField(label=\"First name\", max_length=64)\n last_name = forms.CharField(label=\"Last name\", max_length=64)\n email = forms.CharField(label=\"Your email\", max_length=128)\n zipcode = forms.CharField(label=\"Your zipcode\", max_length=5, widget=forms.TextInput(attrs={'size':'5','maxlength':'5'}))\n #affiliation = forms.ChoiceField(label=\"Your affiliation\", choices=AFFILIATION_CHOICES)\n #message = forms.CharField(label=\"Your message\", widget=forms.Textarea, required=False)"
},
{
"alpha_fraction": 0.6727961301803589,
"alphanum_fraction": 0.6727961301803589,
"avg_line_length": 56.78125,
"blob_id": "17220caf3beb42ad275a0ffe76f62f9719d5f62c",
"content_id": "eac12e662fa4048edbb2acbd975195b9f6dd6fe2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1849,
"license_type": "no_license",
"max_line_length": 133,
"num_lines": 32,
"path": "/urls.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.conf.urls.defaults import *\nfrom django.contrib import admin\nfrom contact_form.forms import ContactForm\n\nadmin.autodiscover()\n\nclass RTBContactForm(ContactForm):\n from_email = \"bounce@sunlightfoundation.com\"\n recipient_list = ['jbrewer@sunlightfoundation.com']\n subject = \"[ReadTheBill.org] Contact\"\n\nurlpatterns = patterns('',\n url(r'^admin/gatekeeper/', include('gatekeeper.urls')),\n url(r'^admin/(.*)', admin.site.root),\n url(r'^action/callspeakerboehner/', 'django.views.generic.simple.direct_to_template', {'template': 'action/boehner.html'}),\n url(r'^blog/', include('blogdor.urls')),\n url(r'^contact/', include('contact_form.urls'), {\"form_class\": RTBContactForm, \"fail_silently\": False}),\n url(r'^partners/', 'readthebill.rtb.views.partners', name=\"partners\"),\n url(r'^partner/hat/', 'django.views.generic.simple.direct_to_template', {'template': 'partner_hat.html'}, name=\"partner_hat\"),\n url(r'^partner/(?P<id>\\d+)/', 'readthebill.rtb.views.partner_page', name=\"partner_page\"),\n url(r'^petition/', 'readthebill.rtb.views.petition', name=\"petition\"),\n url(r'^support/', 'readthebill.rtb.views.support', name=\"support\"),\n url(r'^photos/', 'readthebill.rtb.views.photos', name=\"photos\"),\n url(r'^press/', 'readthebill.rtb.views.press', name=\"press\"),\n url(r'^rushed/', 'readthebill.rtb.views.rushed_bills', name=\"rushed_bills\"),\n url(r'^endorsements/', 'django.views.generic.simple.direct_to_template', {'template': 'endorsements.html'}, name=\"endorsements\"),\n url(r'^invite/', 'django.views.generic.simple.direct_to_template', {'template': 'invite.html'}, name=\"invite\"),\n url(r'^call/(?P<id>\\d+)/$', 'callingtool.views.call_legislator', name='call_legislator'),\n url(r'^call/', include('callingtool.urls')),\n url(r'^', include('mediasync.urls')),\n url(r'^$', 'readthebill.rtb.views.index', name=\"index\"),\n)\n"
},
{
"alpha_fraction": 0.7255814075469971,
"alphanum_fraction": 0.7255814075469971,
"avg_line_length": 24.799999237060547,
"blob_id": "b440811426161ebd560cbcdf4f56fd4d3cce8150",
"content_id": "b7db9f371eae68ad8c501e2a1025c6df832a5f79",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 645,
"license_type": "no_license",
"max_line_length": 63,
"num_lines": 25,
"path": "/failwhale/admin.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django import forms\nfrom django.contrib import admin\nfrom failwhale.models import Account, Status, Summize, Timeline\n\n# account\n\nclass TimelineInline(admin.TabularInline):\n model = Timeline\n\nclass SummizeAdmin(admin.ModelAdmin):\n inlines = (TimelineInline,)\n \nclass AccountAdminForm(forms.ModelForm):\n class Meta:\n model = Account\n exclude = ['passwd']\n \nclass AccountAdmin(admin.ModelAdmin):\n form = AccountAdminForm\n list_display = ['username']\n list_display_links = ['username']\n search_fields = ['username']\n\nadmin.site.register(Account, AccountAdmin)\nadmin.site.register(Summize, SummizeAdmin)\n"
},
{
"alpha_fraction": 0.5526315569877625,
"alphanum_fraction": 0.5765550136566162,
"avg_line_length": 29.962963104248047,
"blob_id": "3bc38afba5e6b562dea27ddb731ae03edcb3bf7b",
"content_id": "7f583cf82d623ee115e504c9af992910665c117c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 836,
"license_type": "no_license",
"max_line_length": 147,
"num_lines": 27,
"path": "/templates/callingtool/all_calls.html",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "{% extends \"base_call.html\" %}\n\n{% block content %}\n\n<h1>{{num_calls}} calls | {{num_unique}} unique email addresses | {{num_sens}} Legislators called\n</h1>\n\n<table>\n<tr>\n<th>Caller</th><th>Senator</th><th>Email</th><th>Zip</th><th>Time</th><th>Comments / Notes</th><th>Supports S.482</th><th>Opposes Roberts</th></tr>\n<tbody>\n{% for call in calls %}\n<tr>\n <td width=\"10%\">{{call.name}}</td>\n <td width=\"10%\">{{call.senator}}</td>\n <td width=\"10%\">{{call.email}}</td>\n <td width=\"5%\">{{call.zip}}</td>\n <td width=\"10%\">{{call.date|date:\"m.d.y\"}} @ {{call.date|date:\"h:i A\"}}</td>\n <td width=\"35%\">{{call.comments}}</td>\n <td width=\"5%\">{{call.on_bill}}</td>\n <td width=\"10%\">{{call.on_amendment}}</td>\n <td width=\"5%\"><a href=\"{% url delete_call call.id %}\">delete?</a></td>\n</tr>\n{% endfor %}\n</tbody>\n</table>\n{% endblock %}\n"
},
{
"alpha_fraction": 0.7142857313156128,
"alphanum_fraction": 0.7142857313156128,
"avg_line_length": 24.33333396911621,
"blob_id": "c93304d781aaf095714ee787de1482a13f5ba2b4",
"content_id": "aa29e20cf69f1bc2f3e1956d0ea9703c5b463e2f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 455,
"license_type": "no_license",
"max_line_length": 72,
"num_lines": 18,
"path": "/local_settings.example.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "DATABASE_ENGINE = ''\nDATABASE_NAME = ''\nDATABASE_USER = ''\nDATABASE_PASSWORD = ''\nDATABASE_HOST = ''\nDATABASE_PORT = ''\n\nimport os.path\nTEMPLATE_DIRS = (os.path.join(os.path.dirname(__file__), 'templates'))\n\n# path to the receive URL for the TransparencyCorps photo-gathering task\nTCORPS_TASK_URL = ''\n\n# The flickr ID for the account you're using to show gathered photos\nFLICKR_ID = ''\n\n# the tag that gathered photos are using\nFLICKR_TAG = 'readthebill'"
},
{
"alpha_fraction": 0.5988258123397827,
"alphanum_fraction": 0.604207456111908,
"avg_line_length": 30.206106185913086,
"blob_id": "c6e3bec966864288665a9c5fb7db9dcf45fd6c70",
"content_id": "18f3659f6a93523d9a9893bfc31d7582380ced19",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4088,
"license_type": "no_license",
"max_line_length": 125,
"num_lines": 131,
"path": "/failwhale/util.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.utils import simplejson\nfrom failwhale.models import Account, Status, Summize, Timeline\nimport datetime\nimport rfc822\nimport failwhale\nimport time\nimport twitter\nimport urllib, urllib2\n\nSEARCH_URL = \"http://search.twitter.com/search.json\"\n\ndef load_account(username):\n try:\n return Account.objects.get(username=username)\n except Account.DoesNotExist:\n return create_account(username, check_if_exists=False)\n\ndef create_account(username, password=None, check_if_exists=True):\n if check_if_exists:\n assert Account.objects.filter(username=username).count() == 0\n accnt = Account()\n accnt.username = username\n accnt.password = password\n if password:\n import_profile(accnt)\n return accnt\n\ndef delete_account(username):\n try:\n Account.objects.get(username=username).delete()\n except Account.DoesNotExist:\n pass\n\n#\n# import methods\n#\n\ndef import_profile(accnt, save=True):\n client = twitter.Api(username=accnt.username, password=accnt.password)\n user = client.GetUser(accnt.username)\n accnt.twitter_id = user.id\n accnt.full_name = user.name\n accnt.location = user.location\n accnt.description = user.description\n accnt.avatar_url = user.profile_image_url\n accnt.url = user.url\n if save:\n accnt.save()\n\ndef import_statuses(accnt):\n \n client = twitter.Api(username=accnt.username, password=accnt.password)\n \n try:\n last_status = accnt.statuses()[0]\n since = rfc822.formatdate(time.mktime(last_status.timestamp.timetuple()))\n statuses = client.GetUserTimeline(user=accnt.username, since=since)\n except IndexError:\n statuses = client.GetUserTimeline(user=accnt.username)\n \n for status in statuses:\n \n if not accnt.avatar_url == status.user.profile_image_url:\n accnt.avatar_url = status.user.profile_image_url\n accnt.save()\n \n time_tuple = rfc822.parsedate(status.created_at)\n created_at = datetime.datetime(*time_tuple[0:7])\n \n try:\n s = Status.objects.get(pk=status.id)\n except Status.DoesNotExist:\n s = Status.objects.create(\n id=status.id,\n sender=accnt,\n message=status.text,\n timestamp=created_at,\n )\n \n if accnt.related_statuses.filter(timeline__status=s, timeline__discriminator=failwhale.STATUS).count() == 0:\n\n t = Timeline.objects.create(\n owner=accnt,\n status=s,\n discriminator=failwhale.STATUS,\n )\n\ndef import_search_results(summize, since_id=None):\n \n params = {'q': summize.query}\n if since_id:\n params['since_id'] = since_id\n url = \"%s?%s\" % (SEARCH_URL, urllib.urlencode(params))\n \n opener = urllib2.build_opener()\n opener.addheaders = [('User-agent', 'django-failwhale')]\n response = opener.open(url)\n content = response.read()\n response.close()\n \n json = simplejson.loads(content)\n results = json['results']\n \n for result in results:\n \n to_user = load_account(result['from_user'])\n \n if not to_user.avatar_url == result['profile_image_url']:\n to_user.avatar_url = result['profile_image_url']\n to_user.save()\n \n time_tuple = rfc822.parsedate(result['created_at'])\n created_at = datetime.datetime(*time_tuple[0:7])\n \n try:\n s = Status.objects.get(pk=result['id'])\n except Status.DoesNotExist:\n s = Status.objects.create(\n id=result['id'],\n sender=to_user,\n message=result['text'],\n timestamp=created_at,\n )\n \n if summize.related_statuses.filter(timeline__status=s, timeline__discriminator=failwhale.SEARCH_RESULT).count() == 0:\n \n t = Timeline.objects.create(\n owner=summize,\n status=s,\n discriminator=failwhale.SEARCH_RESULT,\n )\n"
},
{
"alpha_fraction": 0.7548262476921082,
"alphanum_fraction": 0.7548262476921082,
"avg_line_length": 27.77777862548828,
"blob_id": "d5e8e48f69b5ccbdcdb68e9f0e0e3ff37d9796b8",
"content_id": "d387cdde77b0c6f5e79057ce064671dd312793d5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 518,
"license_type": "no_license",
"max_line_length": 67,
"num_lines": 18,
"path": "/rtb/templatetags/rtb.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "\nfrom django import template\nfrom django.template.loader import render_to_string\nfrom readthebill.rtb.forms import SignupForm\nfrom readthebill.rtb.models import Organization\nimport random\n\nregister = template.Library()\n\n@register.simple_tag\ndef random_orgs(count):\n orgs = Organization.objects.filter(logo__isnull=False)\n orgs = random.sample(orgs, count)\n return render_to_string(\"rtb/random_orgs.html\", {\"orgs\": orgs})\n\n@register.simple_tag\ndef signup_form():\n form = SignupForm()\n return form.as_ul()"
},
{
"alpha_fraction": 0.6501035094261169,
"alphanum_fraction": 0.6501035094261169,
"avg_line_length": 29.25,
"blob_id": "ce428d264e474e829dd02032db86118040747532",
"content_id": "89903041c915e5fd6f19d31f58889979ef28732f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 483,
"license_type": "no_license",
"max_line_length": 71,
"num_lines": 16,
"path": "/failwhale/management/commands/addaccount.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.core.management.base import BaseCommand, CommandError\nimport failwhale\n \nclass Command(BaseCommand):\n \n help = \"Register a Twitter account\"\n args = '[username] ([password])'\n \n requires_model_validation = False\n \n def handle(self, username=None, password=None, *args, **options):\n \n if not username:\n raise CommandError('Usage is register_twit %s' % self.args)\n \n failwhale.create_account(username, password)"
},
{
"alpha_fraction": 0.5351089835166931,
"alphanum_fraction": 0.5351089835166931,
"avg_line_length": 23.294116973876953,
"blob_id": "da970f6581643b98fb0aebe7f161254f1eebab82",
"content_id": "b72b7ed000633c5a16a9a9d527664757e4258d84",
"detected_licenses": [
"BSD-3-Clause"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 413,
"license_type": "permissive",
"max_line_length": 58,
"num_lines": 17,
"path": "/morsels/admin.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from models import Morsel\n\nfrom django.contrib import admin\n\nclass MorselAdmin(admin.ModelAdmin):\n list_display = ('url', 'title', 'locked')\n fieldsets = (\n (None, {\n 'fields': ('url', 'title', 'content', 'sites')\n }),\n ('Advanced options', {\n 'classes': ('collapse',),\n 'fields': ('locked',)\n }),\n )\n\nadmin.site.register(Morsel, MorselAdmin)\n"
},
{
"alpha_fraction": 0.6519052386283875,
"alphanum_fraction": 0.656024694442749,
"avg_line_length": 28.303030014038086,
"blob_id": "707e88dc82576b5cb75223426231666ae23f9700",
"content_id": "ec87dd9197eef7d9205fb3445e230d360ef57c00",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 971,
"license_type": "no_license",
"max_line_length": 77,
"num_lines": 33,
"path": "/rtb/models.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.conf import settings\nfrom django.db import models\nfrom feedinator.models import Feed, FeedEntry\nimport gatekeeper\n\nAFFILIATION_CHOICES = (\n ('d', 'Democrat'),\n ('i', 'Independent'),\n ('n', 'Non-partisan'),\n ('r', 'Republican'),\n ('x', 'Does not disclose'),\n)\n\nclass Organization(models.Model):\n \n name = models.CharField(max_length=255)\n url = models.URLField(verify_exists=False)\n logo = models.URLField(verify_exists=False, blank=True, null=True)\n affiliation = models.CharField(max_length=1, choices=AFFILIATION_CHOICES)\n \n feed = models.OneToOneField(Feed)\n \n def __unicode__(self):\n return self.name\n\ndef mod(mo):\n entry = mo.content_object\n if not entry.feed.codename in [\"press\",\"rushedbills\"]:\n content = entry.content.lower()\n for regex in settings.RTB_REGEX:\n if regex.search(content):\n return True\ngatekeeper.register(FeedEntry, auto_moderator=mod) \n"
},
{
"alpha_fraction": 0.6692963242530823,
"alphanum_fraction": 0.6787630319595337,
"avg_line_length": 32.02083206176758,
"blob_id": "0558a421ac91e81906e5292c03986e26112c7b91",
"content_id": "91f0ba50c9913113db2005eac13a2848fe6b8b2e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 3169,
"license_type": "no_license",
"max_line_length": 94,
"num_lines": 96,
"path": "/failwhale/models.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django.db import models\nimport datetime\nimport failwhale\n\n# account and search models\n\nclass Syncable(models.Model):\n\n related_statuses = models.ManyToManyField('Status', through='Timeline')\n\n last_update = models.DateTimeField(auto_now_add=True, blank=True, null=True)\n next_update = models.DateTimeField(blank=True, null=True)\n ttl = models.IntegerField(default=5)\n\nclass Account(Syncable):\n \n username = models.CharField(max_length=32)\n passwd = models.CharField(max_length=32, blank=True, null=True)\n \n # profile\n twitter_id = models.IntegerField(blank=True, null=True)\n full_name = models.CharField(max_length=128, blank=True)\n location = models.CharField(max_length=128, blank=True)\n description = models.CharField(max_length=180, blank=True)\n url = models.URLField(verify_exists=False, blank=True, null=True)\n avatar_url = models.URLField(verify_exists=False, blank=True, null=True)\n is_protected = models.BooleanField(default=False)\n friend_count = models.IntegerField(default=-1)\n \n def __unicode__(self):\n return self.username\n \n def _get_password(self):\n return self.passwd\n \n def _set_password(self, password):\n self.passwd = password\n self.save()\n \n password = property(_get_password, _set_password)\n \n def statuses(self):\n return self.related_statuses.filter(timeline__discriminator=failwhale.STATUS)\n def friend_statuses(self):\n return self.related_statuses.filter(timeline__discriminator=failwhale.FRIEND_STATUS)\n def direct_messages(self):\n return self.related_statuses.filter(timeline__discriminator=failwhale.DIRECT_MESSAGE)\n\nclass Summize(Syncable):\n name = models.CharField(max_length=128, blank=True)\n query = models.CharField(max_length=255)\n \n def __unicode__(self):\n return self.name\n \n def save(self):\n if not self.name:\n self.name = self.query\n super(Summize, self).save()\n \n# tweet models\n\nclass Status(models.Model):\n sender = models.ForeignKey(Account, related_name=\"nigh_related_statuses\")\n recipient = models.ForeignKey(Account, related_name=\"received_dms\", blank=True, null=True)\n message = models.CharField(max_length=180)\n timestamp = models.DateTimeField()\n \n class Meta:\n ordering = ('-timestamp',)\n \n def __unicode__(self):\n return \"%s: %s\" % (self.sender.username, self.message)\n \n def is_dm(self):\n return not self.recipient == None\n \n def timestamp_est(self):\n return self.timestamp - datetime.timedelta(0, 60 * 60 * 5) # off five hours\n\n# timeline model\n\nTIMELINE_TYPES = (\n (failwhale.STATUS, 'status'),\n (failwhale.FRIEND_STATUS, 'friend status'),\n (failwhale.DIRECT_MESSAGE, 'direct message'),\n (failwhale.SEARCH_RESULT, 'search result'),\n)\n\nclass Timeline(models.Model):\n discriminator = models.IntegerField(choices=TIMELINE_TYPES)\n owner = models.ForeignKey(Syncable, related_name=\"timeline\")\n status = models.ForeignKey(Status, related_name=\"timeline\")\n \n class Meta:\n unique_together = ('discriminator','owner','status')"
},
{
"alpha_fraction": 0.6309427618980408,
"alphanum_fraction": 0.6333602070808411,
"avg_line_length": 30.846153259277344,
"blob_id": "0153ed86e2830818618d921d4c60ff96798aad18",
"content_id": "e1a37cb38c00ead19eafed15faf0edb13fd49692",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1241,
"license_type": "no_license",
"max_line_length": 93,
"num_lines": 39,
"path": "/failwhale/templatetags/failtags.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "from django import template\nfrom django.conf import settings\nfrom django.template.defaultfilters import stringfilter\nfrom django.template.loader import render_to_string\nfrom failwhale.models import Summize\nimport re\n\nregister = template.Library()\n\nAT_RE = re.compile(r'@(?P<screen_name>[\\w_]+)')\nHASH_RE = re.compile(r'#(?P<tag>[\\w_]+)')\nHTTP_RE = re.compile(r'(?P<url>http://[\\w_/\\.]+)')\n\n@register.simple_tag\ndef summize(name, count=5):\n results = Summize.objects.get(name=name).related_statuses.all()[:count]\n return render_to_string('failwhale/templatetags/summize.html', {\"results\": results})\n\n@register.filter\n@stringfilter\ndef tweetile(text):\n \n def repl_at(match):\n screen_name = match.group('screen_name')\n return '<a href=\"http://twitter.com/%s\">@%s</a>' % (screen_name, screen_name)\n \n def repl_hash(match):\n tag = match.group('tag')\n return '<a href=\"http://search.twitter.com/search?q=%s\">#%s</a>' % (\"%23\" + tag, tag)\n \n def repl_http(match):\n url = match.group('url')\n return '<a href=\"%s\">%s</a>' % (url, url)\n \n text = HTTP_RE.sub(repl_http, text)\n text = AT_RE.sub(repl_at, text)\n text = HASH_RE.sub(repl_hash, text)\n \n return text"
},
{
"alpha_fraction": 0.6615384817123413,
"alphanum_fraction": 0.7230769395828247,
"avg_line_length": 15.5,
"blob_id": "2bda08ad1e2f65ae2e82f0562f8e32d8ae3d69d2",
"content_id": "5c7f0b5cfb7535cda66b6c0dd940374077928add",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 65,
"license_type": "no_license",
"max_line_length": 18,
"num_lines": 4,
"path": "/failwhale/__init__.py",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "STATUS = 0\nFRIEND_STATUS = 1\nDIRECT_MESSAGE = 2\nSEARCH_RESULT = 3"
},
{
"alpha_fraction": 0.7871900796890259,
"alphanum_fraction": 0.8057851195335388,
"avg_line_length": 27.52941131591797,
"blob_id": "560a1e1cc3ebb341cfd56208271d2188db68ab4a",
"content_id": "b5c90ba3620a4a89ae7c45249b99b021d6238816",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Text",
"length_bytes": 484,
"license_type": "no_license",
"max_line_length": 73,
"num_lines": 17,
"path": "/requirements.txt",
"repo_name": "sunlightlabs/readthebill",
"src_encoding": "UTF-8",
"text": "Django==1.2.5\ndjango-gatekeeper==0.3.0\npython-sunlightapi\nfeedparser\n\nslimmer\ndjango-mediasync==2.0.0\n\n-e git://github.com/sunlightlabs/django-uspolitics.git#egg=uspolitics\n-e git://github.com/sunlightlabs/django-feedinator.git#egg=feedinator\n-e git://github.com/sunlightlabs/django-simplesurvey.git#egg=simplesurvey\n\n# blogdor\nmarkdown\ndjango-tagging\n-e git://github.com/jamesturk/django-markupfield.git#egg=markupfield\n-e git://github.com/sunlightlabs/django-blogdor.git#egg=blogdor"
}
] | 30
|
Nighthawkeye449/bang
|
https://github.com/Nighthawkeye449/bang
|
dc77cd6f2b781a19681c4b790f0f5ec536cee1f4
|
a249184d7d611def74847c8021d141eb11f0d761
|
570e446b60897a58e9b523d984bedd6dee1dad44
|
refs/heads/master
| 2023-02-03T17:12:08.914665
| 2020-12-19T22:46:55
| 2020-12-19T22:46:55
| null | 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.7016115188598633,
"alphanum_fraction": 0.7059435248374939,
"avg_line_length": 37.22516632080078,
"blob_id": "77a4788d8eb20b76b69ece352876d058a265dd6c",
"content_id": "96cefd777020dcffc3dc0a6b30cf207e87269f06",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 5771,
"license_type": "no_license",
"max_line_length": 198,
"num_lines": 151,
"path": "/static/library/playergame.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "from static.library import utils\nfrom static.library.constants import *\nimport random\n\nclass PlayerGame(dict):\n\tdef __init__(self, username=None, sid=None):\n\t\tself.username = username\n\t\tself.sid = sid\n\t\tself.lives = 0\n\t\tself.role = None\n\t\tself.character = None\n\t\tself.characterOptions = None\n\t\tself.lifeLimit = None\n\t\tself.jailStatus = 0 # 0 = not jailed, 1 = has the card but hasn't drawn for it yet\n\t\tself.cardsInHand = list()\n\t\tself.cardsInPlay = list()\n\t\tself.specialCards = list()\n\n\t\tdict.__init__(self)\n\n\tdef __repr__(self):\n\t\treturn self.__str__()\n\n\tdef __str__(self):\n\t\treturn str(self.username)\n\n\tdef __eq__(self, other):\n\t\tif not isinstance(other, PlayerGame):\n\t\t\treturn False\n\n\t\treturn self.username == other.username\n\n\tdef __ne__(self, other):\n\t\tif not isinstance(other, PlayerGame):\n\t\t\treturn True\n\n\t\treturn self.username != other.username\n\n\t# def __ne__(self, other):\n\t# \treturn (other is None) or self.username != other.username\n\n\tdef addCardToHand(self, card):\n\t\tutils.logPlayer(\"{} adding {} ({}) to hand.\".format(self.username, card.getDeterminerString(), card.uid))\n\t\tself.cardsInHand.append(card)\n\n\tdef addCardToInPlay(self, card):\n\t\tutils.logPlayer(\"{} putting {} ({}) in play.\".format(self.username, card.getDeterminerString(), card.uid))\n\t\tself.cardsInPlay.append(card)\n\n\tdef getRidOfCard(self, card):\n\t\tutils.logPlayer(\"{} attempting to discard card {}. cards in hand: {} cards in play: {} special cards: {}.\".format(self.username, card.uid, self.cardsInHand, self.cardsInPlay, self.specialCards))\n\n\t\tfor cardList in [self.cardsInHand, self.cardsInPlay, self.specialCards]:\n\t\t\tif card in cardList:\n\t\t\t\tcardList.remove(card)\n\t\t\t\tutils.logPlayer(\"Successfully discarded card {}. new cards in hand: {} new cards in play: {} new special cards: {}\".format(card.uid, self.cardsInHand, self.cardsInPlay, self.specialCards))\n\n\t\t\t\treturn\n\n\t\tutils.logError(\"Failed to discard card {} for {}.\".format(card.uid, self.username))\n\n\tdef getCardTypeFromHand(self, cardName):\n\t\tcards = [c for c in self.cardsInHand if c.name == cardName]\n\n\t\tif self.character.name == CALAMITY_JANET and cardName in [BANG, MANCATO]:\n\t\t\tcards += [c for c in self.cardsInHand if c.name == (MANCATO if cardName == BANG else BANG)]\n\n\t\tif self.character.name == ELENA_FUENTE and cardName == MANCATO:\n\t\t\tcards = list(self.cardsInHand)\n\n\t\treturn cards\n\n\tdef isAlive(self):\n\t\treturn self.lives > 0\n\n\tdef countBariles(self):\n\t\tamount = self.getBlueCardAmounts(BARILE, JOURDONNAIS)\n\t\tutils.logPlayer(\"{} has a barile amount of {}.\".format(self.username, amount))\n\t\treturn amount\n\n\tdef getMustangDistance(self): # Others view you at distance +1.\n\t\tamount = self.getBlueCardAmounts(MUSTANG, PAUL_REGRET)\n\t\tutils.logPlayer(\"{} has a mustang amount of {}.\".format(self.username, amount))\n\t\treturn amount\n\n\tdef getScopeDistance(self): # You view others at distance -1.\n\t\tamount = self.getBlueCardAmounts(SCOPE, ROSE_DOOLAN)\n\t\tutils.logPlayer(\"{} has a scope amount of {}.\".format(self.username, amount))\n\t\treturn amount\n\n\tdef hasBangLimit(self):\n\t\treturn self.character.name != WILLY_THE_KID and not any([c.name == VOLCANIC for c in self.cardsInPlay])\n\n\tdef getBlueCardAmounts(self, cardName, characterName):\n\t\treturn (1 if cardName in [c.name for c in self.cardsInPlay] else 0) + (1 if self.character.name == characterName else 0)\n\n\tdef getGunRange(self):\n\t\t# Assuming only 1 gun is allowed in play at a time.\n\t\tgun = utils.getUniqueItem(lambda card: card.cardtype == GUN_CARD, self.cardsInPlay)\n\t\t\n\t\tif gun == None:\n\t\t\tutils.logPlayer(\"{} has no gun, so range is 1.\".format(self.username))\n\t\t\treturn 1 # The default range is 1 for the Colt .45.\n\t\telse:\n\t\t\tutils.logPlayer(\"{} has {} in play, so range is {}.\".format(self.username, gun.getDeterminerString(), gun.range))\n\t\t\treturn gun.range\n\n\tdef gainOneLife(self):\n\t\tutils.logPlayer(\"{} going from {} to {} lives.\".format(self.username, self.lives, min(self.lives + 1, self.lifeLimit)))\n\t\tself.lives = min(self.lives + 1, self.lifeLimit)\n\n\tdef loseOneLife(self):\n\t\tutils.logPlayer(\"{} going from {} to {} lives.\".format(self.username, self.lives, self.lives - 1))\n\t\tself.lives -= 1\n\n\tdef getCardsOnTable(self):\n\t\treturn self.cardsInPlay + self.specialCards\n\n\tdef countExcessCards(self):\n\t\tcardLimit = self.lives if self.character.name != SEAN_MALLORY else 10\n\t\texcess = max(len(self.cardsInHand) - cardLimit, 0)\n\t\tutils.logPlayer(\"Counting excess cards for {} (cards: {}) (lives: {}): {}\".format(self.getLogString(), [c.name for c in self.cardsInHand], self.lives, excess))\n\t\treturn excess\n\n\tdef panico(self, card=None): # The card parameter would only be used if a specific card from in-play is being taken.\n\t\tif card == None:\n\t\t\tif len(self.cardsInHand) == 0:\n\t\t\t\tutils.logError(\"{} is getting Panico'd or Cat Balou'd with no card parameter given, but has no cards in hand.\".format(self.username))\n\t\t\t\treturn None\n\n\t\t\tcard = random.choice(self.cardsInHand)\n\t\t\tself.getRidOfCard(card)\n\t\t\tutils.logPlayer(\"{} randomly losing {} (UID: {}) from hand.\".format(self.getLogString(), card.getDeterminerString(), card.uid))\n\t\t\treturn card\n\t\t\n\t\telse:\n\t\t\tself.getRidOfCard(card)\n\t\t\tutils.logPlayer(\"{} lost on-the-table {} (UID: {}) because of a Panico/Cat Balou.\".format(self.getLogString(), card.getDeterminerString(), card.uid))\n\t\t\treturn card\n\n\tdef getLogString(self):\n\t\treturn \"{} ({})\".format(self.character.name, self.username)\n\n\tdef getPrigione(self):\n\t\treturn utils.getUniqueItem(lambda c: c.name == PRIGIONE, self.specialCards) # Will return None if the player isn't in jail.\n\n\tdef hasTheDynamite(self):\n\t\treturn any([c.name == DYNAMITE for c in self.specialCards])\n\n\tdef getCardInfo(self, isCurrentPlayer):\n\t\treturn [{'name': c.name, 'uid': c.uid, 'isCurrentPlayer': isCurrentPlayer} for c in sorted(self.cardsInHand, key=lambda c: c.uid)]"
},
{
"alpha_fraction": 0.4934944212436676,
"alphanum_fraction": 0.5037174820899963,
"avg_line_length": 52.849998474121094,
"blob_id": "a1cc2ab087b263925ba80064773e1b506603ea85",
"content_id": "a4fe1b129abb404192f0369a929a051b9ad219cc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 1076,
"license_type": "no_license",
"max_line_length": 131,
"num_lines": 20,
"path": "/templates/pick_lobby.html",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "{% extends \"skeleton.html\" %}\n{% block content %}\n <body>\n <div class=\"outer\">\n <h1 class=\"bang-title\" style=\"font-size: 150px;\">Bang!</h1>\n <form action=\"/lobby\" method=\"POST\" class=\"middle\">\n <div class=\"inner\" style=\"margin-top: 5%;\">\n <br><br><span style=\"font-size: 30px;\">Welcome, {{ username }}!</span><br><br>\n <input type=\"submit\" class=\"btn bang-button\" name=\"submit-button\" value=\"Create A New Lobby\">\n <input type=\"hidden\" name=\"username\" value=\"{{ username }}\" />\n </div>\n <div class=\"inner\" style=\"margin-top: 5%;\">\n <span style=\"font-size: 30px;\">Or, if you want to join an existing lobby, enter the number here:</span><br><br>\n <input type=\"text\" name=\"lobby_number\" placeholder=\"Lobby #\" class=\"text_input\">\n {% if warning_msg %}<p class=\"lobby-text\">{{ warning_msg }}</p>{% endif %}\n </div>\n </form>\n </div>\n </body>\n{% endblock %}"
},
{
"alpha_fraction": 0.6474226713180542,
"alphanum_fraction": 0.6474226713180542,
"avg_line_length": 18.440000534057617,
"blob_id": "dfa5e1f4e9cccc4c418ce21c88fe6340bf62c1fe",
"content_id": "887c98f27c5046174efe696d03b39ab3d6847fea",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 485,
"license_type": "no_license",
"max_line_length": 45,
"num_lines": 25,
"path": "/static/library/character.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "class Character(dict):\n\tdef __init__(self, name, numLives, ability):\n\t\tself.name = name\n\t\tself.numLives = numLives\n\t\tself.ability = ability\n\n\t\tdict.__init__(self)\n\n\tdef __repr__(self):\n\t\treturn self.__str__()\n\n\tdef __str__(self):\n\t\treturn str(vars(self))\n\n\tdef __eq__(self, other):\n\t\tif not isinstance(other, Character):\n\t\t\treturn False\n\n\t\treturn self.name == other.name\n\n\tdef __ne__(self, other):\n\t\tif not isinstance(other, Character):\n\t\t\treturn True\n\n\t\treturn self.name != other.name"
},
{
"alpha_fraction": 0.5933014154434204,
"alphanum_fraction": 0.5964912176132202,
"avg_line_length": 35.94117736816406,
"blob_id": "3cafc7b2dd55106e94663e13ed845fa8dd5f1913",
"content_id": "dbcfec7b3b396af496bb0ef7128e5db9589c548f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 627,
"license_type": "no_license",
"max_line_length": 104,
"num_lines": 17,
"path": "/templates/modals/cards_drawn.html",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "<div class=\"modal-dialog\">\n\n <div class=\"modal-content\">\n <div class=\"modal-header\">\n <button type=\"button\" class=\"close\" data-dismiss=\"modal\">×</button>\n <h4 class=\"modal-title\">{{ player.username + \", it's your turn!\" if startingTurn else \"\" }}</h4>\n </div>\n <div class=\"modal-body centered centered_text\">\n <p id=\"infoModalText\" class=\"centered_text\">{{ description }}</p>\n {{ cardsDrawnImagesTemplate }}\n </div>\n <div class=\"modal-footer\">\n <button type=\"button\" class=\"btn btn-default\" data-dismiss=\"modal\">Close</button>\n </div>\n </div>\n\n</div>"
},
{
"alpha_fraction": 0.7349397540092468,
"alphanum_fraction": 0.740963876247406,
"avg_line_length": 22.714284896850586,
"blob_id": "85f62829bb65c8a5ddbc86e442a3d9e258695fda",
"content_id": "f6889c5e3082a5e3d656eb507f612af26684516d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Markdown",
"length_bytes": 166,
"license_type": "no_license",
"max_line_length": 55,
"num_lines": 7,
"path": "/README.md",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "# Bang!\nA client-server implementation of the card game \"Bang!\"\n\n## Requirements\n* Python 3\n* Flask (pip install flask)\n* Flask SocketIO (pip install flask_socketio)\n"
},
{
"alpha_fraction": 0.7373611927032471,
"alphanum_fraction": 0.7411776185035706,
"avg_line_length": 37.43238067626953,
"blob_id": "35e0eb0bc6399b0c14229e80e127cdfb16762175",
"content_id": "a572ddb697c4b87f9a33e050c3372d490af88a89",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 20176,
"license_type": "no_license",
"max_line_length": 230,
"num_lines": 525,
"path": "/bang.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "import eventlet\neventlet.monkey_patch()\n\nfrom engineio.payload import Payload\nfrom flask import Flask, request, render_template, make_response, redirect, url_for, session, abort, send_from_directory, jsonify\nfrom flask_socketio import SocketIO, send, emit, join_room, leave_room\nfrom pathlib import Path\nfrom signal import signal, SIGINT\nfrom threading import Lock\nimport os\nimport random\nimport sys\nimport time\nimport traceback\n\n\n# Import local modules.\nfrom static.library import jinjafunctions\nfrom static.library import utils\nfrom static.library.constants import *\nfrom static.library.gameplay import Gameplay\nfrom static.library.playergame import PlayerGame\n\ndef handler(signal_received, frame):\n # Catch CTRL-C in order to separate sessions in the log.\n for func in [utils.logServer, utils.logPlayer, utils.logGameplay]:\n\t func(\"Exiting game with CTRL-C.\\n\\n\\n\")\n sys.exit(0)\n\ndef _default(self, obj):\n\treturn getattr(obj.__class__, \"to_json\", _default.default)(obj)\n\n# Validate whether enough time has passed since the previous socket message from a given user to consider a new one valid.\n# This is useful for avoiding things like accidental double-clicks.\ndef validResponse(username, responseInfo):\n\tglobal SOCKET_MESSAGE_TIMESTAMPS\n\n\twith lock:\n\t\tif username not in SOCKET_MESSAGE_TIMESTAMPS:\n\t\t\tSOCKET_MESSAGE_TIMESTAMPS[username] = time.time()\n\t\t\tSOCKET_MESSAGE_HISTORY[username] = responseInfo\n\t\t\treturn True\n\t\telse:\n\t\t\tpreviousTime, previousInfo = SOCKET_MESSAGE_TIMESTAMPS[username], SOCKET_MESSAGE_HISTORY[username]\n\n\t\t\tSOCKET_MESSAGE_TIMESTAMPS[username] = time.time()\n\t\t\tSOCKET_MESSAGE_HISTORY[username] = responseInfo\n\t\t\tminTimeDifference = 1 if responseInfo not in [ENDING_TURN, CANCEL_CURRENT_ACTION] else 2\n\n\t\t\tif responseInfo != previousInfo or time.time() - previousTime >= minTimeDifference:\n\t\t\t\treturn True\n\t\t\telse:\n\t\t\t\tutils.logServer(\"Not enough time has passed since {}'s last socket message ({}) for {}. Ignoring this one.\".format(username, time.time() - previousTime, responseInfo))\n\t\t\t\treturn False\n\ndef processGameSocketMessage(game, f):\n\tgameJson = utils.saveGameToJson(game)\n\n\ttry:\n\t\ttuples = f()\n\t\temitTuples(tuples)\n\n\texcept Exception as e:\n\t\tLOBBY_GAME_DICT[game.lobbyNumber] = utils.loadGameFromJson(gameJson) # Revert the game state so that it's not potentially stuck in limbo.\n\t\tutils.logError(traceback.format_exc())\n\t\tutils.logGameplay(\"Exception caught in gameplay processing. Reverting the game state.\")\n\ndef emit(emitString, args=None, recipient=None):\n\tif args != None and recipient != None:\n\t\tsocketio.emit(emitString, args, room=recipient.sid)\n\t\tif emitString != UPDATE_PLAYER_LIST:\n\t\t\tutils.logServer(\"Emitted socket message '{}' to {} with args {}.\".format(emitString, recipient.username, args))\n\t\n\telif args != None:\n\t\tsocketio.emit(emitString, args)\n\t\tutils.logServer(\"Emitted socket message '{}' to everybody with args {}.\".format(emitString, args))\n\t\n\telse:\n\t\tsocketio.emit(emitString)\n\t\tutils.logServer(\"Emitted socket message '{}' to everybody.\".format(emitString))\n\ndef emitTuples(tuples):\n\tfor (modalEmitString, args, recipient) in utils.consolidateTuples(tuples):\n\t\tif modalEmitString == SLEEP:\n\t\t\tutils.logServer(\"Sleeping for {} seconds while emitting tuples.\".format(args))\n\t\t\ttime.sleep(int(args))\n\t\t\n\t\telse:\n\t\t\temit(modalEmitString, args, recipient)\n\ndef getGameForPlayer(username):\n\tif username in USER_LOBBY_DICT:\n\t\tlobby = USER_LOBBY_DICT[username]\n\n\t\tif lobby not in LOBBY_GAME_DICT:\n\t\t\tLOBBY_GAME_DICT[lobby] = utils.loadGame(lobby)\n\t\t\n\t\treturn LOBBY_GAME_DICT[lobby]\n\n# Server setup\nPayload.max_decode_packets = 200\napp = Flask(__name__, static_url_path='/static', template_folder='templates')\napp.secret_key = 'secretkey1568486123168'\nsocketio = SocketIO(app, async_mode=\"eventlet\", async_handlers=False, cors_allowed_origins=\"*\", always_connect=True, ping_timeout=45, ping_interval=15)\n\nlock = Lock()\n\nUSER_LOBBY_DICT = dict()\nLOBBY_GAME_DICT = dict()\nLOBBIES_WAITING = set()\nSOCKET_MESSAGE_TIMESTAMPS = dict()\nSOCKET_MESSAGE_HISTORY = dict()\nCONNECTED_USERS = dict()\n\n#################### Socket IO functions ####################\n\n@socketio.on(CONNECTED)\ndef userConnected(username):\n\tif username not in CONNECTED_USERS:\n\t\tutils.logServer(\"Received socket message '{}' from {}.\".format(CONNECTED, username))\n\t\n\tCONNECTED_USERS[username] = request.sid\n\n\tif username in USER_LOBBY_DICT:\n\t\tgame = getGameForPlayer(username)\n\t\tgame.players[username].sid = request.sid\n\n\tsocketio.emit(KEEP_ALIVE, dict(), room=request.sid)\n\n@socketio.on(LEAVE_LOBBY)\ndef leaveLobby(username):\n\tgame = getGameForPlayer(username)\n\tsid = game.players[username].sid\n\tlobby = USER_LOBBY_DICT[username]\n\t\n\tif not game.started:\n\t\tgame.removePlayer(username)\n\t\tdel USER_LOBBY_DICT[username]\n\n\t# Delete this lobby entirely if all the players have left.\n\tif len([u for u in USER_LOBBY_DICT if USER_LOBBY_DICT[u] == lobby]) == 0:\n\t\tdel LOBBY_GAME_DICT[lobby]\n\n\telse:\n\t\tsorted_usernames = sorted(game.players.keys())\n\n\t\t# Broadcast the updated list of players to everybody else in this lobby.\n\t\ttuples = [(LOBBY_PLAYER_UPDATE, {'usernames': sorted_usernames}, p) for p in game.players.values()]\n\n\t\tif len(game.players) < 4 or (game.started and not all([name in USER_LOBBY_DICT for name in game.players])):\n\t\t\ttuples.append((HIDE_START_BUTTON, dict(), game.playerOrder[0]))\n\t\telse:\n\t\t\ttuples.append((SHOW_START_BUTTON, dict(), game.playerOrder[0]))\n\n\t\temitTuples(tuples)\n\n\t# Reload the pick lobby page for the player who left.\n\tsocketio.emit(RELOAD_LOBBY, {'html': render_template(\"pick_lobby.html\", username=username)}, room=sid)\n\n\n@socketio.on(START_BUTTON_CLICKED)\ndef startGame(username):\n\tlobby = USER_LOBBY_DICT[username]\n\ttuples = []\n\tutils.logServer(\"Received socket message '{}' from {}. Preparing game for setup in lobby {}.\".format(START_BUTTON_CLICKED, username, lobby))\n\n\tgame = LOBBY_GAME_DICT[lobby]\n\tif game.lobbyNumber in LOBBIES_WAITING:\n\t\tLOBBIES_WAITING.remove(game.lobbyNumber)\n\n\t# The game is starting for the first time, so players need to choose characters.\n\tif not game.started:\n\t\ttuples = game.prepareForSetup()\n\n\t# The game is being reloaded, so go straight to the play page.\n\telse:\n\t\ttuples = game.getStartGameTuples(reloadingGame=True)\n\n\tif tuples:\n\t\temitTuples(tuples)\n\n@socketio.on(SET_CHARACTER)\ndef setCharacter(username, character):\n\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(SET_CHARACTER, username, character))\n\ttuples = []\n\tgame = getGameForPlayer(username)\n\n\twith lock:\n\t\tgame.assignCharacter(username, character)\n\t\tunassigned_players_remaining = [u for u in game.players if game.players[u].character == None]\n\n\t\tif len(unassigned_players_remaining) > 0:\n\t\t\temit('character_was_set', {'players_remaining': unassigned_players_remaining})\n\n\t\telse:\n\t\t\t# Start the game for the players by loading their main play screens and info modals.\n\t\t\ttuples = game.getStartGameTuples()\n\n\tif tuples:\n\t\temitTuples(tuples)\n\n@socketio.on(INFO_MODAL_UNDEFINED)\ndef waitForInfoModal(username, html):\n\tutils.logServer(\"Info modal load failed for {}. Trying again.\".format(username))\n\t\n\tgame = getGameForPlayer(username)\n\ttup = (SHOW_INFO_MODAL, {'html': html}, game.players[username])\n\n\temit(*tup)\n\n@socketio.on(QUESTION_MODAL_UNDEFINED)\n# 7 options because the most for any question would be listing 6 other player's usernames + \"Never mind\".\ndef waitForQuestionModal(username, option1, option2, option3, option4, option5, option6, option7, html, question):\n\tutils.logServer(\"Question modal load failed for {}. Trying again.\".format(username))\n\n\tgame = getGameForPlayer(username)\n\ttup = (SHOW_QUESTION_MODAL, {'option1': option1, 'option2': option2, 'option3': option3, 'option4': option4, 'option5': option5, 'option6': option6, 'option7': option7, 'html': html, 'question': question}, game.players[username])\n\n\temit(*tup)\n\n@socketio.on(VALIDATE_CARD_CHOICE)\ndef cardWasPlayed(username, uid):\n\tif validResponse(username, (VALIDATE_CARD_CHOICE, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(VALIDATE_CARD_CHOICE, username, uid))\n\t\t\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.validateCardChoice(username, uid))\n\n@socketio.on(QUESTION_MODAL_ANSWERED)\ndef questionModalAnswered(username, question, answer):\n\tif validResponse(username, (QUESTION_MODAL_ANSWERED, question, answer)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {} -> {}.\".format(QUESTION_MODAL_ANSWERED, username, question, answer))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processQuestionResponse(username, question, answer))\n\n@socketio.on(BLUR_CARD_PLAYED)\ndef playBlurCard(username, uid):\n\tif validResponse(username, (BLUR_CARD_PLAYED, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(BLUR_CARD_PLAYED, username, uid))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processBlurCardSelection(username, int(uid)))\n\n@socketio.on(EMPORIO_CARD_PICKED)\ndef pickEmporioCard(username, uid):\n\tif validResponse(username, (EMPORIO_CARD_PICKED, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(EMPORIO_CARD_PICKED, username, uid))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processEmporioCardSelection(username, int(uid)))\n\n@socketio.on(CLAUS_THE_SAINT_CARD_PICKED)\ndef pickEmporioCard(username, uid):\n\tif validResponse(username, (CLAUS_THE_SAINT_CARD_PICKED, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(CLAUS_THE_SAINT_CARD_PICKED, username, uid))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processClausTheSaintCardSelection(username, int(uid)))\n\n@socketio.on(KIT_CARLSON_CARD_PICKED)\ndef pickKitCarlsonCard(username, uid):\n\tif validResponse(username, (KIT_CARLSON_CARD_PICKED, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(KIT_CARLSON_CARD_PICKED, username, uid))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processKitCarlsonCardSelection(username, int(uid)))\n\n@socketio.on(PLAYER_CLICKED_ON)\ndef playerClickedOn(username, targetName, clickType):\n\tif validResponse(username, (PLAYER_CLICKED_ON, targetName, clickType)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(PLAYER_CLICKED_ON, username, (targetName, clickType)))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processPlayerClickedOn(username, targetName, clickType))\n\n@socketio.on(ABILITY_CARD_CLICKED_ON)\ndef playerClickedOn(username, uid, clickType):\n\tif validResponse(username, (ABILITY_CARD_CLICKED_ON, uid, clickType)):\n\t\tutils.logServer(\"Received socket message '{}' from {}: {}.\".format(ABILITY_CARD_CLICKED_ON, username, (uid, clickType)))\n\n\t\tgame = getGameForPlayer(username)\n\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.processAbilityCardClickedOn(username, uid, clickType))\n\n@socketio.on(ENDING_TURN)\ndef endingTurn(username):\n\tif validResponse(username, ENDING_TURN):\n\t\tutils.logServer(\"Received socket message '{}' from {}.\".format(ENDING_TURN, username))\n\n\t\tgame = getGameForPlayer(username)\n\t\t\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.startNextTurn(username))\n\n@socketio.on(CANCEL_CURRENT_ACTION)\ndef cancelEndingTurn(username):\n\tif validResponse(username, CANCEL_CURRENT_ACTION):\n\t\tutils.logServer(\"Received socket message '{}' from {}.\".format(CANCEL_CURRENT_ACTION, username))\n\n\t\tgame = getGameForPlayer(username)\n\t\t\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.cancelCurrentAction(username))\n\n@socketio.on(DISCARDING_CARD)\ndef discardingCard(username, uid):\n\tif validResponse(username, (DISCARDING_CARD, uid)):\n\t\tutils.logServer(\"Received socket message '{}' from {} for {}.\".format(DISCARDING_CARD, username, uid))\n\n\t\tgame = getGameForPlayer(username)\n\t\t\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.playerDiscardingCard(username, int(uid)))\n\n@socketio.on(USE_SPECIAL_ABILITY)\ndef specialAbility(username):\n\tif validResponse(username, USE_SPECIAL_ABILITY):\n\t\tutils.logServer(\"Received socket message '{}' from {}.\".format(USE_SPECIAL_ABILITY, username))\n\t\t\n\t\tgame = getGameForPlayer(username)\n\t\t\n\t\twith lock:\n\t\t\tprocessGameSocketMessage(game, lambda: game.useSpecialAbility(username))\n\n@socketio.on(REQUEST_PLAYER_LIST)\ndef requestPlayerList(username):\n\tgame = getGameForPlayer(username)\n\t\n\twith lock:\n\t\ttuples = game.getPlayerList(username)\n\t\n\temitTuples(tuples)\n\n@socketio.on(DISCONNECT)\ndef playerDisconnect():\n\tsid = request.sid\n\tif sid in CONNECTED_USERS.values():\n\t\tusername = [u for u in CONNECTED_USERS if CONNECTED_USERS[u] == sid][0]\n\t\tutils.logServer(\"Received socket message '{}' from {} (SID {}).\".format(DISCONNECT, username, sid))\n\t\t\n\t\tdel CONNECTED_USERS[username]\n\n\t\t# If this is the last player disconnecting from his/her lobby and the game is over, just delete the lobby entirely.\n\t\tif username in USER_LOBBY_DICT and USER_LOBBY_DICT[username] in LOBBY_GAME_DICT:\n\t\t\tgame = getGameForPlayer(username)\n\t\t\tif game.started and game.lobbyNumber not in LOBBIES_WAITING and len([u for u in game.players if u in CONNECTED_USERS]) == 0:\n\t\t\t\tlobby = USER_LOBBY_DICT[username]\n\t\t\t\tutils.logServer(\"Last user in lobby {} was disconnected. Removing the game.\".format(lobby))\n\n\t\t\t\tfor u in game.players:\n\t\t\t\t\tif u in USER_LOBBY_DICT:\n\t\t\t\t\t\tdel USER_LOBBY_DICT[u]\n\n\t\t\t\t# Delete the game from the database if the game is over.\n\t\t\t\tif game.gameOver:\n\t\t\t\t\tdel LOBBY_GAME_DICT[lobby]\n\t\t\t\t\tutils.deleteGame(lobby)\n\t\t\t\telse:\n\t\t\t\t\tLOBBY_GAME_DICT[lobby] = utils.loadGame(lobby) # Reset the game to the save state.\n\n\telse:\n\t\tutils.logServer(\"SID {} didn't match any current users.\".format(sid))\n\n@socketio.on(RETURN_TO_LOBBY)\ndef returnToPickLobby(username):\n\tif username in USER_LOBBY_DICT and username in CONNECTED_USERS:\n\t\tgame = getGameForPlayer(username)\n\t\tdel USER_LOBBY_DICT[username]\n\t\temit(RELOAD_LOBBY, {'html': render_template(\"pick_lobby.html\", username=username)}, game.players[username])\n\n@socketio.on(REJOIN_GAME)\ndef rejoinGame(username):\n\tgame = getGameForPlayer(username)\n\twith lock:\n\t\ttuples = game.getPlayerReloadingTuples(username)\n\n\temitTuples(tuples)\n\n#################### App routes ####################\n\n@app.route(\"/\", methods = ['POST', 'GET'])\ndef homePage():\n\t# The method will be POST if the text box for username has been submitted.\n\tif request.method == 'POST':\n\t\tif 'name' not in request.form or utils.isEmptyOrNull(request.form['name']):\n\t\t\tutils.logServer(\"A player attempted to join with an invalid username. Reloading home page.\")\n\t\t\treturn render_template('home.html')\n\t\t\n\t\t# Add this new player if the username is valid.\n\t\tusername = utils.cleanUsernameInput(request.form['name'])\n\t\tvalidResult = checkUsernameValidity(username)\n\t\tif validResult != '':\n\t\t\treturn render_template('home.html', warning_msg=validResult)\n\t\telse:\n\t\t\tif username in USER_LOBBY_DICT and USER_LOBBY_DICT[username] in LOBBY_GAME_DICT and USER_LOBBY_DICT[username] not in LOBBIES_WAITING:\n\t\t\t\treturn render_template(\"rejoin_game.html\", username=username)\n\n\t\t\telse:\n\t\t\t\treturn render_template(\"pick_lobby.html\", username=username)\n\n\treturn render_template('home.html')\n\n@app.route(\"/lobby\", methods=['POST'])\ndef lobby():\n\n\tusername = request.form['username']\n\n\t# Player is joining an existing lobby.\n\tif not utils.isEmptyOrNull(request.form['lobby_number']):\n\t\tlobbyNumber = request.form['lobby_number']\n\n\t\tif not lobbyNumber.isdigit():\n\t\t\treturn render_template('pick_lobby.html', username=username, warning_msg=\"Sorry, that's in invalid lobby number.\")\n\t\telse:\n\t\t\tlobbyNumber = int(lobbyNumber)\n\t\t\n\t\tif lobbyNumber not in LOBBY_GAME_DICT:\n\t\t\treturn render_template('pick_lobby.html', username=username, warning_msg=\"Sorry, that lobby couldn't be found.\")\n\n\t\t# Don't allow players to join a lobby for a game that's already started.\n\t\telif LOBBY_GAME_DICT[lobbyNumber].started and username not in LOBBY_GAME_DICT[lobbyNumber].players:\n\t\t\treturn render_template('pick_lobby.html', username=username, warning_msg=\"Sorry, that game has already started.\")\n\n\t\t# Don't allow players to join a lobby if it's already full.\n\t\telif len(LOBBY_GAME_DICT[lobbyNumber].players) == 7:\n\t\t\treturn render_template('pick_lobby.html', username=username, warning_msg=\"Sorry, that lobby is already full.\")\n\n\t# Player is joining a new lobby.\n\telse:\n\t\tlobbyNumber = None\n\t\t\n\t\t# Generate new lobby numbers until an unused one is made.\n\t\twhile lobbyNumber == None or lobbyNumber in LOBBY_GAME_DICT:\n\t\t\tlobbyNumber = random.randint(1000, 9999)\n\t\t\n\t\t# Create a new game for this lobby.\n\t\tLOBBY_GAME_DICT[lobbyNumber] = Gameplay()\n\t\tLOBBY_GAME_DICT[lobbyNumber].lobbyNumber = lobbyNumber\n\t\n\tgame = LOBBY_GAME_DICT[lobbyNumber]\n\tUSER_LOBBY_DICT[username] = lobbyNumber\n\tLOBBIES_WAITING.add(lobbyNumber)\n\n\tif username not in game.players:\n\t\tgame.addPlayer(username, CONNECTED_USERS[username] if username in CONNECTED_USERS else 0)\n\t\tusername_order = [p.username for p in game.playerOrder]\n\t\ttuples = [(LOBBY_PLAYER_UPDATE, {'usernames': username_order}, p) for p in game.players.values()]\n\telse:\n\t\tgame.players[username].sid = CONNECTED_USERS[username]\n\t\tusername_order = [p.username for p in game.playerOrder if p.username in USER_LOBBY_DICT]\n\t\ttuples = [(LOBBY_PLAYER_UPDATE, {'usernames': username_order}, p) for p in game.players.values() if p.username in USER_LOBBY_DICT]\n\n\tif (not game.started and 4 <= len(game.players) <= 7) or (game.started and all([name in USER_LOBBY_DICT for name in game.players])):\n\t\ttuples.append((SHOW_START_BUTTON, dict(), game.playerOrder[0]))\n\n\t# Broadcast the updated list of players to everybody in this lobby.\n\temitTuples(tuples)\n\n\t# Render the lobby page with all usernames for the new player.\n\tutils.logServer(\"Rendering lobby for {}\".format(username))\n\treturn render_template('lobby.html', usernames=username_order, username=username, lobbyNumber=USER_LOBBY_DICT[username])\n\n@app.route(\"/setup\", methods = ['POST', 'GET'])\ndef setup():\n\tusername = request.json['username']\n\tutils.logServer(\"Received request for '/setup' from {}\".format(username))\n\n\tgame = getGameForPlayer(username)\n\t\n\tutils.logServer(\"Rendering setup page for {}.\".format(username))\n\treturn render_template('setup.html',\n\t\tplayerOrderString=\" -> \".join([\"{}{}\".format(p.username, \"\" if p != game.playerOrder[0] else \" (Sheriff) \") for p in game.playerOrder]),\n\t\trole=game.players[username].role,\n\t\toption1=game.players[username].characterOptions[0],\n\t\toption2=game.players[username].characterOptions[1],\n\t\tnumOtherPlayers=len(game.players) - 1)\n\ndef checkUsernameValidity(username):\n\tinvalidMsg = \"Sorry, that username is invalid! Try something else.\"\n\tusernameTakenMsg = \"Sorry, that username is taken! Try something else.\"\n\tif len(username) == 0:\n\t\tutils.logServer(\"A player's username was empty after filtering out characters. Rendering home page with warning message.\")\n\t\treturn invalidMsg\n\telif username.upper() in utils.getListOfConstants():\n\t\tutils.logServer(\"A player attempted to join with username {}, which matches a constant. Rendering home page with warning message.\".format(username))\n\t\treturn invalidMsg\n\telif all([c.isdigit() for c in username]):\n\t\tutils.logServer(\"A player attempted to join with a digit-only username. Rendering home page with warning message.\")\n\t\treturn invalidMsg\n\telif username in CONNECTED_USERS: # If the username is taken, just display an error message and let the user try again.\n\t\tutils.logServer(\"A player attempted to join with username {}, which is already taken. Rendering home page with warning message.\".format(username))\n\t\treturn usernameTakenMsg\n\n\treturn ''\n\n# Start Server\nif __name__ == '__main__':\n\n\tutils.resetLogs()\n\n\tsignal(SIGINT, handler)\n\n\tapp.jinja_env.filters['convertNameToPath'] = jinjafunctions.convertNameToPath\n\n\tLOBBY_GAME_DICT = utils.loadGames()\n\tLOBBIES_WAITING |= set(LOBBY_GAME_DICT.keys())\n\tutils.logServer(\"Successfully loaded {} games from the database.\".format(len(LOBBY_GAME_DICT)))\n\n\tsocketio.run(app, debug=False, host=\"0.0.0.0\", port=os.environ.get('PORT'))"
},
{
"alpha_fraction": 0.6479266285896301,
"alphanum_fraction": 0.6604803204536438,
"avg_line_length": 48.52153778076172,
"blob_id": "b026e4ba9f31d0afb97a79b281fb384505bb39a3",
"content_id": "1f05c7ee77141d040cc1e9c345f24c9db15a85af",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 180505,
"license_type": "no_license",
"max_line_length": 234,
"num_lines": 3645,
"path": "/test.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "import json\nimport unittest\n\nfrom flask import Flask, render_template\nfrom flask_testing import TestCase\nfrom html import unescape\n\nfrom static.library.character import Character\nfrom static.library.constants import *\nfrom static.library.gameplay import Gameplay\nfrom static.library import jinjafunctions\nfrom static.library.playergame import PlayerGame\nfrom static.library import utils\n\ngame = Gameplay()\nplayers = {'A': PlayerGame('A'), 'B': PlayerGame('B'), 'C': PlayerGame('C'), 'D': PlayerGame('D'), 'E': PlayerGame('E'), 'F': PlayerGame('F'), 'G': PlayerGame('G')}\nsortedPlayers = [players[username] for username in sorted(players)]\n\nCARD_PLAYED_TUPLES = {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION}\nWAITING_FOR_RESPONSE_TUPLES = {SHOW_QUESTION_MODAL, SHOW_WAITING_MODAL}\nBLUR_CARD_TUPLES = {SHOW_INFO_MODAL, BLUR_CARD_SELECTION}\nPLAYER_TOOK_DAMAGE_TUPLES = {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, UPDATE_ACTION}\nNEW_TURN_TUPLES = {SHOW_INFO_MODAL, UPDATE_ACTION, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_CARDS_IN_PLAY}\n\ndef setDefaults(uid=None, numPlayers=7):\n global game\n\n players['A'].role = SHERIFF\n players['A'].character = loadCharacter(SID_KETCHUM)\n players['A'].lives = players['A'].character.numLives + 1\n players['A'].lifeLimit = players['A'].character.numLives + 1\n\n players['B'].role = RENEGADE\n players['B'].character = loadCharacter(SID_KETCHUM)\n players['B'].lives = players['B'].character.numLives\n players['B'].lifeLimit = players['B'].character.numLives\n\n players['C'].role = OUTLAW\n players['C'].character = loadCharacter(SID_KETCHUM)\n players['C'].lives = players['C'].character.numLives\n players['C'].lifeLimit = players['C'].character.numLives\n\n players['D'].role = OUTLAW\n players['D'].character = loadCharacter(SID_KETCHUM)\n players['D'].lives = players['D'].character.numLives\n players['D'].lifeLimit = players['D'].character.numLives\n\n players['E'].role = VICE\n players['E'].character = loadCharacter(SID_KETCHUM)\n players['E'].lives = players['E'].character.numLives\n players['E'].lifeLimit = players['E'].character.numLives\n\n players['F'].role = OUTLAW\n players['F'].character = loadCharacter(SID_KETCHUM)\n players['F'].lives = players['F'].character.numLives\n players['F'].lifeLimit = players['F'].character.numLives\n\n players['G'].role = VICE\n players['G'].character = loadCharacter(SID_KETCHUM)\n players['G'].lives = players['G'].character.numLives\n players['G'].lifeLimit = players['G'].character.numLives\n\n for p in players.values():\n p.cardsInHand = list()\n p.cardsInPlay = list()\n p.specialCards = list()\n p.jailStatus = 0\n\n alivePlayers = list(sortedPlayers)[:numPlayers]\n\n game.started = True\n game.players = {p.username: p for p in alivePlayers}\n game.playerOrder = list(alivePlayers)\n game.currentTurn = 1\n game.sheriffUsername = 'A'\n game.drawingToStartTurn = False\n game.drawPile = list(game.allCards)\n game.discardPile = list()\n game.currentCard = None\n game.discardingCards = False\n game.bangedThisTurn = False\n game.emporioOptions = list()\n game.duelPair = list()\n game.unansweredQuestions = dict()\n game.playersWaitingFor = set()\n\n if uid != None: self.currentCard = self.getCardByUid(uid)\n\ndef loadCharacter(name):\n characterList = list()\n with open(utils.getLocalFilePath(\"./static/json/characters.json\")) as p:\n characterDict = json.load(p)\n characterList.extend([Character(**characterDict[c]) for c in characterDict])\n\n return utils.getUniqueItem(lambda c: c.name == name, characterList)\n\n'''\nUID mapping:\n 1-25 = bang\n 26-37 = mancato\n 38-41 = panico\n 42-47 = birra\n 48-49 = emporio\n 50-53 = cat balou\n 54 = gatling\n 55-57 = duello\n 58-59 = indians\n 60 = saloon\n 61-62 = diligenza\n 63 = wells fargo\n 64-65 = barile\n 66 = scope\n 67-68 = mustang\n 69-71 = prigione\n 72 = dynamite\n 73-74 = volcanic\n 75-77 = schofield\n 78 = remington\n 79 = rev carabine\n 80 = winchester\n'''\ndef setPlayerCardsInHand(playerCardDict):\n for username in playerCardDict:\n players[username].cardsInHand = [game.getCardByUid(uid) for uid in playerCardDict[username]]\n\ndef setPlayerCardsInPlay(playerCardDict):\n for username in playerCardDict:\n players[username].cardsInPlay = [game.getCardByUid(uid) for uid in playerCardDict[username]]\n\ndef setPlayerSpecialCards(playerCardDict):\n for username in playerCardDict:\n players[username].specialCards = [game.getCardByUid(uid) for uid in playerCardDict[username]]\n\ndef setPlayerLives(playerLifeDict):\n for username in playerLifeDict:\n players[username].lives = playerLifeDict[username]\n\ndef setPlayerCharacter(username, character):\n players[username].character = loadCharacter(character)\n\ndef getCardsOfASuit(suit, n):\n return [c for c in game.allCards if c.suit == suit][:n]\n\ndef getUsernameSet(players):\n return {p.username for p in players}\n\ndef getExplosionCard():\n return [c for c in game.allCards if c.suit == SPADE and '2' <= c.value <= '9'][0]\n\ndef getEmitTypes(tuples):\n return {t[0] for t in tuples if t[0] != SLEEP}\n\ndef countEmitTypes(tuples, countDict):\n for emitType in countDict:\n if len([t for t in tuples if t[0] == emitType]) != countDict[emitType]:\n return False\n\n return True\n\ndef countEmitTypeToRecipient(tuples, emitType, recipient):\n return len([t for t in tuples if t[0] == emitType and t[2] == recipient])\n\ndef playerGotInfo(username, info, tuples):\n return any([info in unescape(t[1]['html']) for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players[username]])\n\ndef playerGotQuestion(username, question, tuples):\n return any([question == t[1]['question'] for t in tuples if t[0] == SHOW_QUESTION_MODAL and t[2] == players[username]])\n\ndef playersGotUpdate(update, tuples):\n return update in [t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION]\n\ndef getQuestionTuple(username, tuples):\n return [t for t in tuples if t[0] == SHOW_QUESTION_MODAL and t[2] == players[username]][0]\n\nclass TestGameplay(TestCase):\n\n def create_app(self):\n app = Flask(__name__, template_folder=utils.getLocalFilePath('/templates'))\n app.config['TESTING'] = True\n\n # Set to 0 to have the OS pick the port.\n app.config['LIVESERVER_PORT'] = 0\n\n app.jinja_env.filters['convertNameToPath'] = jinjafunctions.convertNameToPath\n\n return app\n\n\n\n\n ''' Bang tests. '''\n\n # Bang against an in-range opponent who has no Mancatos given multiple opponents.\n def testBang1(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1]})\n \n self.assertEqual(game.validateCardChoice('A', 1)[0][0], SHOW_QUESTION_MODAL)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n self.assertTrue(countEmitTypes(tuples, {UPDATE_ACTION: 2}))\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Bang successfully against an in-range opponent who has a Mancato given multiple opponents.\n def testBang2(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1], 'B': [26]})\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_QUESTION_MODAL, SHOW_WAITING_MODAL})\n self.assertTrue(countEmitTypes(tuples, {SHOW_QUESTION_MODAL: 1, SHOW_WAITING_MODAL: 1, UPDATE_ACTION: 1}))\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_WAITING_MODAL, players['A']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST})\n self.assertTrue(countEmitTypes(tuples, {UPDATE_ACTION: 1}))\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Bang successfully against only alive opponent who has no Mancatos.\n def testBang3(self):\n setDefaults(numPlayers=3)\n setPlayerCardsInHand({'A': [1]})\n setPlayerLives({'B': 0}) # To also test shooting against someone who wasn't initally in range.\n \n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(getEmitTypes(tuples), CARD_PLAYED_TUPLES | PLAYER_TOOK_DAMAGE_TUPLES | {SHOW_WAITING_MODAL})\n self.assertTrue(countEmitTypes(tuples, {SHOW_INFO_MODAL: 2}))\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['C']), 1)\n\n self.assertEqual(players['C'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Bang successfully against only alive opponent who has 1 Mancato.\n def testBang4(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1], 'B': [26]})\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST})\n self.assertTrue(countEmitTypes(tuples, {UPDATE_ACTION: 1}))\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Bang successfully against only alive opponent who has multiple Mancatos.\n def testBang5(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27]})\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST})\n self.assertTrue(countEmitTypes(tuples, {UPDATE_ACTION: 1}))\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Try using Bang twice with the default limit of 1.\n def testBang6(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1, 2]})\n\n game.validateCardChoice('A', 1)\n \n tuples = game.validateCardChoice('A', 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"already played a Bang\" in tuples[0][1]['html'])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(2)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Try using Bang against an out-of-range opponent.\n def testBang7(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1]})\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'C')\n self.assertEqual(len(tuples), 1)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"C is out of range\" in tuples[0][1]['html'])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n # Try using Bang when there's nobody in range.\n def testBang8(self):\n setDefaults(numPlayers=3)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'B': [67],'C': [68]})\n\n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(len(tuples), 1)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"nobody in range\" in tuples[0][1]['html'])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Gatling and Indians tests. '''\n\n # Gatling and Indians where nobody can avoid it.\n def testGatlingIndiansWithNobodyAvoiding(self):\n for attackingUid in [54, 58]:\n setDefaults()\n setPlayerCardsInHand({'A': [attackingUid]})\n opponents = list(players.values())[1:]\n\n tuples = game.validateCardChoice('A', attackingUid)\n playerAInfoTexts = [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']]\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_PLAYER_LIST, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n for opponent in opponents:\n self.assertTrue(any([\"{} took the hit\".format(opponent.username) in infoText for infoText in playerAInfoTexts]))\n self.assertTrue(\"you've lost a life\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == opponent][0]))\n\n for opponent in opponents:\n self.assertEqual(opponent.lives, 3)\n\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid)])\n self.assertTrue(game.currentCard == None)\n\n # Gatling and Indians where all players can avoid it and all do.\n def testGatlingIndiansWithEverybodyAvoiding(self):\n for attackingUid in [54, 58]:\n setDefaults()\n setPlayerCardsInHand({'A': [attackingUid]})\n question = (QUESTION_GATLING_REACTION if attackingUid == 54 else QUESTION_INDIANS_REACTION).format('A')\n answer = PLAY_A_MANCATO if attackingUid == 54 else PLAY_A_BANG\n cardName = (MANCATO if attackingUid == 54 else BANG).capitalize()\n opponents = list(players.values())[1:]\n\n opponentCardUids = [c.uid for c in game.allCards if c.name == cardName.lower()][:len(players) - 1]\n for i, opponent in enumerate(opponents):\n setPlayerCardsInHand({opponent.username: [opponentCardUids[i]]})\n\n tuples = utils.consolidateTuples(game.validateCardChoice('A', attackingUid))\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, SHOW_QUESTION_MODAL, UPDATE_ACTION})\n\n for opponent in opponents:\n tuples = game.processQuestionResponse(opponent.username, question, answer)\n self.assertTrue(\"You automatically played your only {}\".format(cardName) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == opponent][0])\n self.assertTrue(\"{} played a {} to avoid\".format(opponent.username, cardName) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n\n for opponent in opponents:\n self.assertEqual(opponent.lives, 4)\n self.assertEqual(opponent.cardsInHand, [])\n\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid)] + [game.getCardByUid(uid) for uid in opponentCardUids])\n self.assertTrue(game.currentCard == None)\n\n # Gatling and Indians where all players can avoid it, but only some choose to.\n def testGatlingIndiansWithSomeAvoiding(self):\n for attackingUid in [54, 58]:\n setDefaults()\n setPlayerCardsInHand({'A': [attackingUid]})\n question = (QUESTION_GATLING_REACTION if attackingUid == 54 else QUESTION_INDIANS_REACTION).format('A')\n answer = PLAY_A_MANCATO if attackingUid == 54 else PLAY_A_BANG\n cardName = (GATLING if attackingUid == 54 else INDIANS).capitalize()\n opponents = list(players.values())[1:]\n numOpponentsAvoiding = 3\n\n opponentCardUids = [c.uid for c in game.allCards if c.name == (MANCATO if attackingUid == 54 else BANG)][:len(players) - 1]\n for i, opponent in enumerate(opponents):\n setPlayerCardsInHand({opponent.username: [opponentCardUids[i]]})\n\n game.validateCardChoice('A', attackingUid)\n\n for opponent in opponents[:numOpponentsAvoiding]:\n game.processQuestionResponse(opponent.username, question, answer)\n\n for opponent in opponents[numOpponentsAvoiding:]:\n tuples = game.processQuestionResponse(opponent.username, question, LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n self.assertTrue(\"You were hit by the {}\".format(cardName) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == opponent][0])\n self.assertTrue(\"{} took the hit\".format(opponent.username) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n\n for i, opponent in enumerate(opponents):\n if i < numOpponentsAvoiding:\n self.assertEqual(opponent.lives, 4)\n self.assertEqual(opponent.cardsInHand, [])\n else:\n self.assertEqual(opponent.lives, 3)\n self.assertEqual(opponent.cardsInHand, [game.getCardByUid(opponentCardUids[i])])\n\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid)] + [game.getCardByUid(uid) for uid in opponentCardUids[:numOpponentsAvoiding]])\n self.assertTrue(game.currentCard == None)\n\n # Gatling and Indians where the target has multiple of the required card and needs to pick one.\n def testGatlingIndiansWithMultipleRequiredCards(self):\n for attackingUid in [54, 58]:\n setDefaults(numPlayers=2)\n requiredCardUids = [26, 27] if attackingUid == 54 else [1, 2]\n setPlayerCardsInHand({'A': [attackingUid], 'B': requiredCardUids})\n question = (QUESTION_GATLING_REACTION if attackingUid == 54 else QUESTION_INDIANS_REACTION).format('A')\n answer = PLAY_A_MANCATO if attackingUid == 54 else PLAY_A_BANG\n cardName = (MANCATO if attackingUid == 54 else BANG).capitalize()\n\n game.validateCardChoice('A', attackingUid)\n\n tuples = game.processQuestionResponse('B', question, answer)\n self.assertEqual(getEmitTypes(tuples), BLUR_CARD_TUPLES)\n self.assertTrue(\"Click on the {} in your hand\".format(\"Bang\" if attackingUid == 58 else \"Mancato\") in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n self.assertTrue(all([t[2] == players['B'] for t in tuples]))\n\n tuples = game.processBlurCardSelection('B', requiredCardUids[1])\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, SHOW_INFO_MODAL, UPDATE_ACTION})\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n self.assertTrue(\"B played a {} to avoid\".format(cardName) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(requiredCardUids[0])])\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), game.getCardByUid(requiredCardUids[1])])\n self.assertEqual(game.currentCard, None)\n\n\n\n\n ''' Duello tests. '''\n\n # Duello where the target is picked from options and has no Bangs.\n def testDuelloNoBangs(self):\n setDefaults()\n setPlayerCardsInHand({'A': [55]})\n\n tuples = game.validateCardChoice('A', 55)\n self.assertEqual(getEmitTypes(tuples), {SHOW_QUESTION_MODAL})\n for opponent in [player for player in players.values() if player.username != 'A']:\n self.assertTrue(opponent.username in tuples[0][1].values())\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_DUEL, 'D')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE, UPDATE_ACTION, SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['D']), 1)\n\n self.assertEqual(players['D'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55)])\n self.assertEqual(game.currentCard, None)\n \n # Duello where the target is the only one left and has no Bangs.\n def testDuelloOneOpponentWithNoBangs(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [55]})\n\n tuples = game.validateCardChoice('A', 55)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE, UPDATE_ACTION, SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"B took the hit\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target could respond with a Bang but chooses not to play it.\n def testDuelloOneOpponentWithABang(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [55], 'B': [1]})\n\n tuples = game.validateCardChoice('A', 55)\n self.assertEqual(getEmitTypes(tuples), {SHOW_QUESTION_MODAL, SHOW_WAITING_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_WAITING_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, UPDATE_ACTION})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"B took the hit\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target has 1 Bang and plays it, and the player has none.\n def testDuelloWithBangAndOpponentWithoutBang(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [55], 'B': [1]})\n\n tuples = game.validateCardChoice('A', 55)\n self.assertEqual(getEmitTypes(tuples), {SHOW_QUESTION_MODAL, SHOW_WAITING_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, UPDATE_ACTION, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 2)\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(playerGotInfo('B', \"A took the hit\", tuples))\n\n self.assertEqual(players['A'].lives, 4)\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target has 1 Bang and plays it, and the player has 1 Bang but chooses not to play it.\n def testDuelloWithBangAndOpponentWithBang(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1, 55], 'B': [2]})\n\n game.validateCardChoice('A', 55)\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, SHOW_QUESTION_MODAL, SHOW_WAITING_MODAL, UPDATE_ACTION, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_WAITING_MODAL, players['B']), 1)\n self.assertTrue(playerGotQuestion('A', QUESTION_DUELLO_BANG_REACTION.format('B'), tuples))\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(playerGotInfo('B', \"A took the hit\", tuples))\n\n self.assertEqual(players['A'].lives, 4)\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(2)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target has 1 Bang and plays it, and the player has 1 Bang and plays it.\n def testDuelloWithBangAndOpponentWithBang2(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1, 55], 'B': [2]})\n\n game.validateCardChoice('A', 55)\n\n game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), PLAYER_TOOK_DAMAGE_TUPLES | CARD_PLAYED_TUPLES | {SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(playerGotInfo('A', \"B took the hit\", tuples))\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n\n self.assertEqual(players['A'].lives, 5)\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(2), game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target and player each have multiple Bangs and the opponent loses by running out first.\n def testDuelloWhereOpponentRunsOutFirst(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1, 2, 55], 'B': [3, 4]})\n\n game.validateCardChoice('A', 55)\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), BLUR_CARD_TUPLES)\n self.assertTrue(\"Click on the Bang in your hand\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n self.assertTrue(all([t[2] == players['B'] for t in tuples]))\n\n tuples = game.processBlurCardSelection('B', 3)\n self.assertEqual(getEmitTypes(tuples), WAITING_FOR_RESPONSE_TUPLES | CARD_PLAYED_TUPLES)\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), BLUR_CARD_TUPLES)\n self.assertTrue(\"Click on the Bang in your hand\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(all([t[2] == players['A'] for t in tuples]))\n\n tuples = game.processBlurCardSelection('A', 1)\n self.assertEqual(getEmitTypes(tuples), WAITING_FOR_RESPONSE_TUPLES | CARD_PLAYED_TUPLES)\n\n game.processQuestionResponse('B', QUESTION_DUELLO_BANG_REACTION.format('A'), PLAY_A_BANG)\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), PLAYER_TOOK_DAMAGE_TUPLES | CARD_PLAYED_TUPLES | {SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(playerGotInfo('A', \"B took the hit\", tuples))\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n\n self.assertEqual(players['A'].lives, 5)\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(3), game.getCardByUid(1), game.getCardByUid(4), game.getCardByUid(2)])\n self.assertEqual(game.currentCard, None)\n\n # Duello where the target and player each have multiple Bangs and the player loses by running out first.\n def testDuelloWherePlayerRunsOutFirst(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [1, 2, 55], 'B': [3, 4, 5]})\n\n game.validateCardChoice('A', 55)\n\n game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n game.processBlurCardSelection('B', 3)\n\n game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n game.processBlurCardSelection('A', 1)\n\n game.processQuestionResponse('B', QUESTION_DUELLO_BANG_REACTION.format('A'), PLAY_A_BANG)\n game.processBlurCardSelection('B', 4)\n\n game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n \n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_BANG_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(getEmitTypes(tuples), PLAYER_TOOK_DAMAGE_TUPLES | CARD_PLAYED_TUPLES | {SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 2)\n self.assertTrue(\"You were defeated in the Duello\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(playerGotInfo('B', \"A took the hit\", tuples))\n\n self.assertEqual(players['A'].lives, 4)\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(3), game.getCardByUid(1), game.getCardByUid(4), game.getCardByUid(2), game.getCardByUid(5)])\n self.assertEqual(game.currentCard, None)\n\n\n\n\n ''' Mancato tests. '''\n\n # Mancato successfully with only one in hand against a Bang and Gatling.\n def testMancato1(self):\n for (attackingUid, question) in [(1, QUESTION_BANG_REACTION), (54, QUESTION_GATLING_REACTION)]:\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [attackingUid], 'B': [26]})\n\n game.validateCardChoice('A', attackingUid)\n\n tuples = game.processQuestionResponse('B', question.format('A'), PLAY_A_MANCATO)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n\n self.assertEqual(players['B'].lives, 4)\n \n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), game.getCardByUid(26)])\n self.assertTrue(game.currentCard == None)\n\n # Mancato successfully with 2+ in hand against a Bang and Gatling.\n def testMancato2(self):\n for (attackingUid, question) in [(1, QUESTION_BANG_REACTION), (54, QUESTION_GATLING_REACTION)]:\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [attackingUid], 'B': [26, 27]})\n\n game.validateCardChoice('A', attackingUid)\n\n game.processQuestionResponse('B', question.format('A'), PLAY_A_MANCATO)\n\n tuples = game.processBlurCardSelection('B', 27)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE})\n \n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(26)])\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), game.getCardByUid(27)])\n self.assertTrue(game.currentCard == None)\n\n\n\n ''' Birra tests. '''\n\n # Try using Birra when already at the life limit.\n def testBirra1(self):\n setDefaults()\n setPlayerCardsInHand({'A': [42]})\n\n tuples = game.validateCardChoice('A', 42)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"already have your maximum\" in tuples[0][1]['html'])\n\n self.assertEqual(players['A'].lives, 5)\n \n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n # Successfully use 1 Birra.\n def testBirra2(self):\n setDefaults()\n setPlayerCardsInHand({'A': [42]})\n setPlayerLives({'A': 3})\n\n tuples = game.validateCardChoice('A', 42)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_ACTION, UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_PLAYER_LIST})\n self.assertTrue(\"A played a Birra\" in utils.getUniqueItem(lambda tup: tup[0] == UPDATE_ACTION, tuples)[1]['update'])\n \n self.assertEqual(players['A'].lives, 4)\n \n self.assertEqual(game.discardPile, [game.getCardByUid(42)])\n self.assertTrue(game.currentCard == None)\n\n # Successfully use multiple Birras.\n def testBirra3(self):\n setDefaults()\n setPlayerCardsInHand({'A': [42, 43]})\n setPlayerLives({'A': 2})\n\n game.validateCardChoice('A', 42)\n self.assertEqual(players['A'].lives, 3)\n\n game.validateCardChoice('A', 43)\n self.assertEqual(players['A'].lives, 4)\n\n self.assertEqual(game.discardPile, [game.getCardByUid(42), game.getCardByUid(43)])\n self.assertTrue(game.currentCard == None)\n\n # Use Birra when shot dead and only have 1 Birra left.\n def testBirra4(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1], 'B': [42]})\n setPlayerLives({'B': 1})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n\n self.assertEqual(players['B'].lives, 1)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(42)])\n self.assertTrue(game.currentCard == None)\n\n # Use Birra when shot dead and have multiple Birras left.\n def testBirra5(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1], 'B': [42, 43]})\n setPlayerLives({'B': 1})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n\n self.assertEqual(players['B'].lives, 1)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(43)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(42)])\n self.assertTrue(game.currentCard == None)\n\n # Use multiple Birras when killed by dynamite.\n def testBirra6(self):\n setDefaults()\n setPlayerCardsInHand({'A': [42, 43, 44]})\n setPlayerLives({'A': 1})\n game.currentCard = game.getDynamiteCard()\n\n tuples = game.processPlayerTakingDamage(players['A'], 3)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n\n self.assertEqual(players['A'].lives, 1)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getDynamiteCard(), game.getCardByUid(42), game.getCardByUid(43), game.getCardByUid(44)])\n self.assertTrue(game.currentCard == None)\n\n # Try to use Birra in a 1-on-1.\n def testBirra7(self):\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [42]})\n setPlayerLives({'A': 3})\n\n tuples = game.validateCardChoice('A', 42)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"can't use Birras when it's 1-v-1\" in unescape(tuples[0][1]['html']))\n\n self.assertEqual(players['A'].lives, 3)\n \n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(42)])\n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Saloon tests. '''\n\n # Everybody already has the maximum number of lives.\n def testSaloon1(self):\n setDefaults()\n setPlayerCardsInHand({'A': [60]})\n\n tuples = game.validateCardChoice('A', 60)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"no one would gain a life\" in tuples[0][1]['html'])\n\n self.assertTrue(all([p.lives == p.lifeLimit for p in players.values()]))\n \n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(60)])\n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n # Only the player can gain a life.\n def testSaloon2(self):\n setDefaults()\n setPlayerCardsInHand({'A': [60]})\n setPlayerLives({'A': 4})\n\n tuples = game.validateCardChoice('A', 60)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n\n self.assertTrue(players['A'].lives, 5)\n \n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(60)])\n self.assertTrue(game.currentCard == None)\n\n # Several players can gain a life, including the player.\n def testSaloon3(self):\n setDefaults()\n setPlayerCardsInHand({'A': [60]})\n setPlayerLives({'A': 4, 'C': 2, 'F': 1})\n\n tuples = game.validateCardChoice('A', 60)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n\n self.assertTrue(players['A'].lives, 5)\n self.assertTrue(players['C'].lives, 3)\n self.assertTrue(players['F'].lives, 2)\n \n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(60)])\n self.assertTrue(game.currentCard == None)\n\n # Several players can gain a life, excluding the player.\n def testSaloon4(self):\n setDefaults()\n setPlayerCardsInHand({'A': [60]})\n setPlayerLives({'B': 3, 'C': 2, 'F': 1})\n\n tuples = game.validateCardChoice('A', 60)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n\n self.assertTrue(players['A'].lives, 5)\n self.assertTrue(players['B'].lives, 4)\n self.assertTrue(players['C'].lives, 3)\n self.assertTrue(players['F'].lives, 2)\n \n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(60)])\n self.assertTrue(game.currentCard == None)\n\n # Everybody can gain a life.\n def testSaloon5(self):\n setDefaults()\n setPlayerCardsInHand({'A': [60]})\n setPlayerLives({p.username: p.lifeLimit - 1 for p in players.values()})\n\n tuples = game.validateCardChoice('A', 60)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_PLAYER_LIST})\n\n self.assertTrue(all([p.lives == p.lifeLimit for p in players.values()]))\n \n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(60)])\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Panico and Cat Balou tests. '''\n\n # Successful Panico and Cat Balou against a 1-away player who has 1 card in hand.\n def testStealInHand1(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid], 'B': [1]})\n\n game.validateCardChoice('A', cardUid)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].cardsInHand, [])\n if cardUid == 38:\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(1)])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico and Cat Balou against a 1-away player who has multiple cards in hand.\n def testStealInHand2(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid], 'B': [1, 2]})\n\n game.validateCardChoice('A', cardUid)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n cardStolen = game.getCardByUid(1) if players['B'].cardsInHand[0].uid == 2 else game.getCardByUid(2)\n cardNotStolen = game.getCardByUid(2) if players['B'].cardsInHand[0].uid == 2 else game.getCardByUid(1)\n\n self.assertEqual(players['B'].cardsInHand, [cardNotStolen])\n if cardUid == 38:\n self.assertTrue(players['A'].cardsInHand, [cardStolen])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), cardStolen])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico and Cat Balou against a 1-away player who has 1 card in play.\n def testStealInPlay1(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid]})\n setPlayerCardsInPlay({'B': [78]})\n\n game.validateCardChoice('A', cardUid)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].cardsInPlay, [])\n if cardUid == 38:\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(78)])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(78)])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico and Cat Balou against a 1-away player who has 2 cards in play.\n def testStealInPlay2(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid]})\n setPlayerCardsInPlay({'B': [65, 78]})\n\n game.validateCardChoice('A', cardUid)\n \n game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n\n discardSet = set() if cardUid == 38 else {UPDATE_DISCARD_PILE}\n tuples = game.processQuestionResponse('A', QUESTION_CARD_ON_TABLE.format('B', 'Panico' if cardUid == 38 else 'Cat Balou'), game.getCardByUid(65).getQuestionString())\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL} | discardSet)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].cardsInPlay, [game.getCardByUid(78)])\n if cardUid == 38:\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(65)])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(65)])\n\n self.assertTrue(game.currentCard == None)\n\n # Succesful Panico and Cat Balou against a 1-away player who has 2 cards in play and is in jail, taking the jail card.\n def testStealInPlayAndSpecialCard(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid]})\n setPlayerCardsInPlay({'B': [66, 78]})\n setPlayerSpecialCards({'B': [69]})\n players['B'].jailStatus = 1\n\n game.validateCardChoice('A', cardUid)\n \n game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n\n question = QUESTION_CARD_ON_TABLE.format('B', \"Panico\" if cardUid == 38 else \"Cat Balou\")\n discardSet = set() if cardUid == 38 else {UPDATE_DISCARD_PILE}\n\n tuples = game.processQuestionResponse('A', question, game.getCardByUid(69).getQuestionString())\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL} | discardSet)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].jailStatus, 0)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['B'].cardsInPlay, [game.getCardByUid(66), game.getCardByUid(78)])\n if cardUid == 38:\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(69)])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico and Cat Balou against 1-away player who has both a card in hand and in play, taking the card in hand.\n def testStealInHandAndInPlay1(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid], 'B': [1]})\n setPlayerCardsInPlay({'B': [78]})\n\n game.validateCardChoice('A', cardUid)\n \n game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n\n question = (QUESTION_PANICO_CARDS if cardUid == 38 else QUESTION_CAT_BALOU_CARDS).format('B')\n discardSet = set() if cardUid == 38 else {UPDATE_DISCARD_PILE}\n\n tuples = game.processQuestionResponse('A', question, FROM_THEIR_HAND)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL} | discardSet)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInPlay, [game.getCardByUid(78)])\n if cardUid == 38:\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(1)])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico and Cat Balou against 1-away player who has both a card in hand and in play, taking the card in play.\n def testStealInHandAndInPlay2(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid], 'B': [1]})\n setPlayerCardsInPlay({'B': [78]})\n\n game.validateCardChoice('A', cardUid)\n \n game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n\n question = (QUESTION_PANICO_CARDS if cardUid == 38 else QUESTION_CAT_BALOU_CARDS).format('B')\n discardSet = set() if cardUid == 38 else {UPDATE_DISCARD_PILE}\n\n tuples = game.processQuestionResponse('A', question, FROM_THE_TABLE)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL} | discardSet)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(players['B'].cardsInPlay, [])\n if cardUid == 38:\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(78)])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid)])\n else:\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(cardUid), game.getCardByUid(78)])\n\n self.assertTrue(game.currentCard == None)\n\n # Unsuccessful Panico against a 2-away player.\n def testPanicoNotInRange(self):\n setDefaults()\n setPlayerCardsInHand({'A': [38], 'B': [1], 'C': [2]})\n\n game.validateCardChoice('A', 38)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'C')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"is out of range\" in tuples[0][1]['html'])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Cat Balou against a 2-away player.\n def testCatBalouLongRange(self):\n setDefaults()\n setPlayerCardsInHand({'A': [50], 'C': [1]})\n\n game.validateCardChoice('A', 50)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'C')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['C']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['C']), 1)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['C'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(50), game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Unsuccessful Panico and Cat Balou when all opponents are card-less.\n def testStealNobodyInRange(self):\n for cardUid in [38, 50]:\n setDefaults()\n setPlayerCardsInHand({'A': [cardUid]})\n\n tuples = game.validateCardChoice('A', cardUid)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"nobody in range\" in tuples[0][1]['html'])\n\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Mustang and Scope tests. '''\n\n # Unsuccessful Bang and Panico against a 1-away player who has a Mustang equipped.\n def testMustang(self):\n for attackingUid in [1, 38]:\n setDefaults()\n setPlayerCardsInHand({'A': [attackingUid]})\n setPlayerCardsInPlay({'B': [67]})\n setPlayerCardsInPlay({'G': [2]}) # Needed so that Panico is considered valid.\n question = QUESTION_WHO_TO_SHOOT if attackingUid == 1 else QUESTION_WHOSE_CARDS\n\n game.validateCardChoice('A', attackingUid)\n \n tuples = game.processQuestionResponse('A', question, 'B')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"is out of range\" in tuples[0][1]['html'])\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Bang against a 2-away player by having a Scope equipped.\n def testScopeAgainstBang(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'A': [66]})\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'C')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico against a 2-away player by having a Scope equipped.\n def testScopeAgainstPanico(self):\n setDefaults()\n setPlayerCardsInHand({'A': [38], 'C': [2]})\n setPlayerCardsInPlay({'A': [66]})\n\n game.validateCardChoice('A', 38)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'C')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n\n self.assertTrue(game.currentCard == None)\n\n # Unsuccessful Bang and Pancico with a Scope equipped against a 2-away player who has a Mustang equipped.\n def testOutOfRangeScopeAgainstMustang(self):\n for attackingUid in [1, 38]:\n setDefaults()\n setPlayerCardsInHand({'A': [attackingUid]})\n setPlayerCardsInPlay({'A': [66], 'C': [67]})\n setPlayerCardsInPlay({'G': [2]}) # Needed so that Panico is considered valid.\n question = QUESTION_WHO_TO_SHOOT if attackingUid == 1 else QUESTION_WHOSE_CARDS\n\n game.validateCardChoice('A', attackingUid)\n tuples = game.processQuestionResponse('A', question, 'C')\n \n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"is out of range\" in tuples[0][1]['html'])\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Bang with a Scope equipped against a 1-away player who has a Mustang equipped.\n def testInRangeScopeAgainstMustangWithBang(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'A': [66], 'B': [67]})\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n\n self.assertTrue(game.currentCard == None)\n\n # Successful Panico with a Scope equipped against a 1-away player who has a Mustang equipped.\n def testInRangeScopeAgainstMustangWithPanico(self):\n setDefaults()\n setPlayerCardsInHand({'A': [38]})\n setPlayerCardsInPlay({'A': [66], 'B': [67]})\n\n game.validateCardChoice('A', 38)\n \n tuples = game.processQuestionResponse('A', QUESTION_WHOSE_CARDS, 'B')\n self.assertEqual(getEmitTypes(tuples), {UPDATE_DISCARD_PILE, UPDATE_CARD_HAND, UPDATE_ACTION, SHOW_INFO_MODAL})\n\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Barile tests. '''\n\n # Successfully draw a heart against a Bang and a Gatling.\n def testSuccessfulBariles(self):\n heartCard = getCardsOfASuit(HEART, 1)[0]\n for attackingUid in [1, 54]:\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [attackingUid]})\n setPlayerCardsInPlay({'B': [64]})\n game.drawPile.append(heartCard)\n\n tuples = game.validateCardChoice('A', attackingUid)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(\"B drew a heart for Barile and avoided your\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][-1])\n self.assertTrue(\"You drew a heart for Barile and avoided the\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), heartCard])\n self.assertTrue(game.currentCard == None)\n\n # Unsuccessfuly draw a heart against a Bang and a Gatling.\n def testUnsuccessfulBariles(self):\n nonHeartCard = getCardsOfASuit(SPADE, 1)[0]\n for attackingUid in [1, 54]:\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [attackingUid]})\n setPlayerCardsInPlay({'B': [64]})\n game.drawPile.append(nonHeartCard)\n\n tuples = game.validateCardChoice('A', attackingUid)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 2)\n self.assertTrue(\"B took the hit\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][-1])\n self.assertTrue(\"You didn't draw a heart\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0]))\n self.assertTrue(\"you've lost a life\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][1]))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), nonHeartCard])\n self.assertTrue(game.currentCard == None)\n\n # Have 2 players both successfully draw a Barile against a Gatling.\n def test2SuccessfulBariles(self):\n heartCards = getCardsOfASuit(HEART, 2)\n setDefaults(numPlayers=3)\n setPlayerCardsInHand({'A': [54]})\n setPlayerCardsInPlay({'B': [64], 'C': [65]})\n game.drawPile.extend(heartCards)\n\n tuples = game.validateCardChoice('A', 54)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['C']), 1)\n self.assertTrue(\"B drew a heart for Barile and avoided your\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(\"C drew a heart for Barile and avoided your\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][1])\n self.assertTrue(\"You drew a heart for Barile and avoided the\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n self.assertTrue(\"You drew a heart for Barile and avoided the\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['C']][0])\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(54)] + heartCards[::-1])\n self.assertTrue(game.currentCard == None)\n\n # Have 2 players successfully and unsuccessfuly draw a Barile against a Gatling.\n def testSuccessfulAndUnsuccessfulBariles(self):\n heartCard = getCardsOfASuit(HEART, 1)[0]\n nonHeartCard = getCardsOfASuit(SPADE, 1)[0]\n setDefaults(numPlayers=3)\n setPlayerCardsInHand({'A': [54]})\n setPlayerCardsInPlay({'B': [64], 'C': [65]})\n game.drawPile.extend([heartCard, nonHeartCard])\n\n tuples = game.validateCardChoice('A', 54)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['C']), 1)\n self.assertTrue(\"B took the hit\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n self.assertTrue(\"C drew a heart for Barile and avoided your\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][1])\n self.assertTrue(\"You didn't draw a heart\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0]))\n self.assertTrue(\"you've lost a life\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][1]))\n self.assertTrue(\"You drew a heart for Barile and avoided the\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['C']][0])\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(players['C'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(54), nonHeartCard, heartCard])\n self.assertTrue(game.currentCard == None)\n\n # Have a player unsuccessfully draw a Barile against a Bang and Gatling but still avoid it by using a Mancato.\n def testUnsuccessfulBarileWithMancato(self):\n for attackingUid in [1, 54]:\n setDefaults(numPlayers=2)\n setPlayerCardsInHand({'A': [attackingUid], 'B': [26]})\n setPlayerCardsInPlay({'B': [64]})\n nonHeartCard = getCardsOfASuit(SPADE, 1)[0]\n game.drawPile.append(nonHeartCard)\n\n game.validateCardChoice('A', attackingUid)\n\n game.processQuestionResponse('B', QUESTION_BARILE_MANCATO.format('A', game.getCardByUid(attackingUid).getDisplayName()), PLAY_A_MANCATO)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(game.discardPile, [game.getCardByUid(attackingUid), nonHeartCard, game.getCardByUid(26)])\n\n\n\n\n ''' Diligenza and Wells Fargo tests. '''\n\n def testDiligenzaAndWellsFargo(self):\n for uid in [61, 63]:\n setDefaults()\n setPlayerCardsInHand({'A': [uid]})\n game.drawPile = [game.getCardByUid(drawUid) for drawUid in [10, 20, 30, 40]]\n originalDrawPile = list(game.drawPile)\n numCards = 2 if uid == 61 else 3\n\n tuples = game.validateCardChoice('A', uid)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, SHOW_INFO_MODAL, UPDATE_ACTION})\n self.assertTrue(\"You drew {} cards\".format(numCards) in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL][0])\n\n self.assertEqual(players['A'].cardsInHand, originalDrawPile[::-1][:numCards])\n self.assertEqual(game.discardPile, [game.getCardByUid(uid)])\n self.assertEqual(game.drawPile, originalDrawPile[:4-numCards])\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Emporio tests. '''\n\n # Test Emporio with 7 different cards (i.e. no automatic selections).\n def testEmporioWithNoAutomaticSelections(self):\n setDefaults()\n setPlayerCardsInHand({'A': [48]})\n game.drawPile = [game.getCardByUid(uid) for uid in [1,2,30,40,50,60,70,80]]\n expectedEmporioOptions = game.drawPile[1:][::-1]\n expectedCardsInHand = list(expectedEmporioOptions)\n\n tuples = game.validateCardChoice('A', 48)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n\n self.assertEqual(game.drawPile, [game.getCardByUid(1)])\n self.assertEqual(game.emporioOptions, expectedEmporioOptions)\n\n for player in players.values():\n self.assertTrue(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, player), 1)\n\n for player in list(players.values())[:-1]:\n tuples = game.processEmporioCardSelection(player.username, expectedEmporioOptions.pop(0).uid)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, player), 1)\n\n self.assertTrue(\"You picked up the last Emporio card\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == list(players.values())[-1]][0])\n\n for i, player in enumerate(players.values()):\n self.assertEqual(player.cardsInHand, [expectedCardsInHand[i]])\n\n self.assertEqual(game.emporioOptions, [])\n self.assertTrue(game.currentCard == None)\n\n # Test Emporio with 7 of the same card (i.e. with all automatic selections).\n def testEmporioWithAllAutomaticSelections(self):\n setDefaults()\n setPlayerCardsInHand({'A': [48]})\n game.drawPile = [game.getCardByUid(uid) for uid in range(1, 2 + len(players))] # All Bangs.\n\n tuples = game.validateCardChoice('A', 48)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n\n self.assertEqual(game.drawPile, [game.getCardByUid(1)])\n self.assertEqual(game.emporioOptions, [])\n\n for player in players.values():\n self.assertTrue(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, player), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, player), 2 if player.username == 'A' else 1)\n self.assertTrue(\"You automatically picked up\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == player][0])\n \n self.assertEqual(len(player.cardsInHand), 1)\n self.assertEqual(player.cardsInHand[0].name, BANG)\n\n self.assertTrue(game.currentCard == None)\n\n # Test Emporio where the last few cards, but not all, are the same (i.e. with some automatic selections).\n def testEmporioWithSomeAutomaticSelections(self):\n setDefaults()\n setPlayerCardsInHand({'A': [48]})\n game.drawPile = [game.getCardByUid(uid) for uid in [1,2,3,4,50,60,70,80]]\n numUniqueCards = len([c for c in game.drawPile if c.name != BANG])\n expectedEmporioOptions = game.drawPile[1:][::-1]\n expectedCardsInHand = expectedEmporioOptions[:numUniqueCards] + expectedEmporioOptions[numUniqueCards:][::-1]\n\n tuples = game.validateCardChoice('A', 48)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n\n self.assertEqual(game.drawPile, [game.getCardByUid(1)])\n self.assertEqual(game.emporioOptions, expectedEmporioOptions)\n\n for player in list(players.values())[:numUniqueCards]:\n tuples = game.processEmporioCardSelection(player.username, expectedEmporioOptions.pop(0).uid)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, player), 1)\n\n for player in list(players.values())[numUniqueCards:]:\n self.assertTrue(\"You automatically picked up\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == player][0])\n\n for i, player in enumerate(players.values()):\n self.assertEqual(player.cardsInHand, [expectedCardsInHand[i]])\n\n self.assertEqual(game.emporioOptions, [])\n self.assertTrue(game.currentCard == None)\n\n\n\n\n ''' Gun tests. '''\n\n # Verifying valid targets for every gun.\n def testGunRanges(self):\n setDefaults()\n\n for (uid, expectedRange) in [(None, 1), (73, 1), (75, 2), (78, 3), (79, 4), (80, 5)]:\n if uid != None:\n setPlayerCardsInPlay({'A': [uid]})\n\n validTargets = game.getAllValidTargetsForCard(players['A'], BANG)\n expectedValidTargets = game.playerOrder[1:1+expectedRange] + game.playerOrder[1:][::-1][:expectedRange]\n\n self.assertEqual({p.username for p in validTargets}, {p.username for p in expectedValidTargets})\n\n # Bang twice with a Volcanic in play.\n def testVolcanicBangs(self):\n setDefaults(numPlayers=2)\n gunUids = [1, 2]\n setPlayerCardsInHand({'A': gunUids})\n setPlayerCardsInPlay({'A': [73]})\n\n expectedLives = 4\n expectedCardsInHand = [game.getCardByUid(uid) for uid in gunUids]\n expectedDiscard = []\n for uid in gunUids:\n expectedLives -= 1\n expectedDiscard.append(game.getCardByUid(uid))\n expectedCardsInHand.pop(0)\n\n tuples = game.validateCardChoice('A', uid)\n self.assertEqual(getEmitTypes(tuples), CARD_PLAYED_TUPLES | PLAYER_TOOK_DAMAGE_TUPLES | {SHOW_WAITING_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n\n self.assertEqual(players['B'].lives, expectedLives)\n\n self.assertEqual(players['A'].cardsInHand, expectedCardsInHand)\n self.assertEqual(game.discardPile, expectedDiscard)\n self.assertTrue(game.currentCard == None)\n\n\n ''' Prigione tests. '''\n\n # Successfully playing a Prigione against a non-jailed player.\n def testPrigioneAgainstNonJailedPlayer(self):\n setDefaults()\n setPlayerCardsInHand({'A': [69]})\n\n tuples = game.validateCardChoice('A', 69)\n self.assertEqual(getEmitTypes(tuples), {SHOW_QUESTION_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['A']), 1)\n self.assertEqual(tuples[0][1]['question'], QUESTION_WHO_TO_JAIL)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_JAIL, 'D')\n self.assertEqual(getEmitTypes(tuples), (CARD_PLAYED_TUPLES - {UPDATE_DISCARD_PILE}) | {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['D']), 1)\n self.assertTrue(\"A just put you in jail\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['D']][0])\n\n self.assertEqual(players['D'].jailStatus, 1)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['D'].specialCards, [game.getCardByUid(69)])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Unsuccessfully playing a Prigione against a jailed player.\n def testPrigioneAgainstJailedPlayer(self):\n setDefaults()\n setPlayerCardsInHand({'A': [69]})\n setPlayerSpecialCards({'D': [70]})\n players['D'].jailStatus = 1\n\n game.validateCardChoice('A', 69)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_JAIL, 'D')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['A']), 1)\n self.assertTrue(\"D is already in jail\" in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['A']][0])\n\n self.assertEqual(players['D'].jailStatus, 1)\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(69)])\n self.assertEqual(players['D'].specialCards, [game.getCardByUid(70)])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Unsuccessfully playing a Prigione against the Sheriff.\n def testPrigioneAgainstSheriff(self):\n setDefaults()\n game.rotatePlayerOrder()\n setPlayerCardsInHand({'B': [69]})\n\n game.validateCardChoice('B', 69)\n\n tuples = game.processQuestionResponse('B', QUESTION_WHO_TO_JAIL, 'A')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(\"You can't jail the sheriff\" in unescape([t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0]))\n\n self.assertEqual(players['A'].jailStatus, 0)\n \n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(69)])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n\n\n\n ''' Character special ability tests. '''\n\n # Bart Cassidy: Draw from the deck after taking damage.\n def testBartCassidy(self):\n setDefaults()\n setPlayerCharacter('B', BART_CASSIDY)\n setPlayerCardsInHand({'A': [54]})\n cardToDraw = game.drawPile[-1]\n\n tuples = game.validateCardChoice('A', 54)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n self.assertTrue(playerGotInfo('B', \"You drew a card because you lost a life\", tuples))\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(players['B'].cardsInHand, [cardToDraw])\n self.assertEqual(game.currentCard, None)\n\n # Black Jack: Draw a third card when the second one is a heart and diamond, with everyone seeing the second.\n def testBlackJack1(self):\n for suit in [HEART, DIAMOND]:\n setDefaults()\n setPlayerCharacter('B', BLACK_JACK)\n suitCard = getCardsOfASuit(suit, 1)[0]\n game.drawPile[-2] = suitCard\n expectedCardsDrawn = game.drawPile[-3:][::-1]\n expectedUpdate = \"B (Black Jack) drew 3 cards. The second card was {}.\".format(suitCard.getDeterminerString())\n expectedInfo = \"You drew {}, {}, and {} because the {} is a {}\".format(*[c.getDeterminerString() for c in expectedCardsDrawn], suitCard.getDisplayName(), suit)\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(expectedInfo in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(game.currentCard, None)\n\n # Black Jack: Draw two cards normally when the second one is a club or spade, with everyone seeing the second.\n def testBlackJack2(self):\n for suit in [CLUB, SPADE]:\n setDefaults()\n setPlayerCharacter('B', BLACK_JACK)\n suitCard = getCardsOfASuit(suit, 1)[0]\n game.drawPile[-2] = suitCard\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n expectedUpdate = \"B (Black Jack) drew 2 cards. The second card was {}.\".format(suitCard.getDeterminerString())\n expectedInfo = \"You drew {} and {}\".format(*[c.getDeterminerString() for c in expectedCardsDrawn])\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(expectedInfo in [t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL and t[2] == players['B']][0])\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Mancato as an attacking Bang.\n def testCalamityJanetMancato1(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [26]})\n expectedUpdate = \"A played a {} against B.\".format(MANCATO_AS_BANG)\n\n tuples = game.validateCardChoice('A', 26)\n self.assertEqual([t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION][0], expectedUpdate)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(26)])\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Mancato as an attacking Bang where the target chooses from one of several cards with which to respond.\n def testCalamityJanetMancato2(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [26], 'B': [27, 28]})\n expectedUpdate = \"B played a Mancato and avoided A's {}.\".format(MANCATO_AS_BANG)\n\n game.validateCardChoice('A', 26)\n\n game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), PLAY_A_BANG)\n\n tuples = game.processBlurCardSelection('B', 27)\n self.assertEqual([t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION][0], expectedUpdate)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(28)])\n self.assertEqual(game.discardPile, [game.getCardByUid(26), game.getCardByUid(27)])\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Mancato in response to an Indians.\n def testCalamityJanetMancato3(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [58], 'B': [26]})\n expectedUpdate = \"B played a {} and avoided A's Indians.\".format(MANCATO_AS_BANG)\n\n game.validateCardChoice('A', 58)\n \n tuples = game.processQuestionResponse('B', QUESTION_INDIANS_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual([t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION][0], expectedUpdate)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(58), game.getCardByUid(26)])\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Mancato in a Duello.\n def testCalamityJanetMancato4(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [55], 'B': [26]})\n expectedUpdate = \"B responded in the duel with A by playing a {}.\".format(MANCATO_AS_BANG)\n\n game.validateCardChoice('A', 55)\n \n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(26)])\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Bang as a Mancato in response to a Bang.\n def testCalamityJanetBang1(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [1], 'B': [2]})\n expectedUpdate = \"B played a {} and avoided A's Bang.\".format(BANG_AS_MANCATO)\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual([t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION][0], expectedUpdate)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(2)])\n self.assertEqual(game.currentCard, None)\n\n # Calamity Janet: Use a Bang as a Mancato in response to a Gatling.\n def testCalamityJanetBang2(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [54], 'B': [1]})\n expectedUpdate = \"B played a {} and avoided A's Gatling.\".format(BANG_AS_MANCATO)\n\n game.validateCardChoice('A', 54)\n \n tuples = game.processQuestionResponse('B', QUESTION_GATLING_REACTION.format('A'), PLAY_A_MANCATO)\n self.assertEqual([t[1]['update'] for t in tuples if t[0] == UPDATE_ACTION][0], expectedUpdate)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(54), game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # El Gringo: Steal from a player's hand after taking damage from his/her Bang.\n def testElGringoAgainstBang(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', EL_GRINGO)\n setPlayerCardsInHand({'A': [1, 2]})\n expectedAttackerInfo = \"B stole a Bang from your hand\"\n expectedElGringoInfo = \"You stole a Bang from A's hand\"\n expectedUpdate = \"B stole a card from A's hand using El Gringo's ability.\"\n\n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n self.assertTrue(playerGotInfo('A', expectedAttackerInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedElGringoInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(2)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # El Gringo: Steal from a player's hand after taking damage from his/her Gatling and Indians.\n def testElGringoAgainstGatlingIndians(self):\n for uid in [54, 58]:\n setDefaults()\n setPlayerCharacter('B', EL_GRINGO)\n setPlayerCardsInHand({'A': [1, uid]})\n expectedAttackerInfo = \"B stole a Bang from your hand\"\n expectedElGringoInfo = \"You stole a Bang from A's hand\"\n expectedUpdate = \"B stole a card from A's hand using El Gringo's ability.\"\n\n tuples = game.validateCardChoice('A', uid)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 1)\n self.assertTrue(playerGotInfo('A', expectedAttackerInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedElGringoInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [game.getCardByUid(uid)])\n self.assertEqual(game.currentCard, None)\n\n # El Gringo: Steal from a player's hand after taking damage from his/her Duello.\n def testElGringoAgainstDuello(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', EL_GRINGO)\n setPlayerCardsInHand({'A': [1, 55]})\n expectedAttackerInfo = \"B stole a Bang from your hand\"\n expectedElGringoInfo = \"You stole a Bang from A's hand\"\n expectedUpdate = \"B stole a card from A's hand using El Gringo's ability.\"\n\n\n tuples = game.validateCardChoice('A', 55)\n self.assertTrue(playerGotInfo('A', expectedAttackerInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedElGringoInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [game.getCardByUid(55)])\n self.assertEqual(game.currentCard, None)\n\n # El Gringo: Don't steal from a player's hand after taking damage in his/her own Duello.\n def testElGringoAgainstDuelloException(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', EL_GRINGO)\n setPlayerCardsInHand({'A': [55], 'B': [1, 30]})\n\n game.validateCardChoice('A', 55)\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n\n self.assertEqual(players['A'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(30)])\n self.assertEqual(game.discardPile, [game.getCardByUid(55), game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # El Gringo: Don't steal anything from a player's hand after taking damage if s/he has no cards to steal.\n def testElGringoUnsuccessful(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', EL_GRINGO)\n setPlayerCardsInHand({'A': [1]})\n expectedElGringoInfo = \"A has no cards, so you couldn't use El Gringo's ability to steal anything\"\n\n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['B']), 0)\n self.assertTrue(playerGotInfo('B', expectedElGringoInfo, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertEqual(game.currentCard, None)\n\n # Jesse Jones: Draw one card from a player's hand and one from the deck.\n def testJesseJonesUsingAbility(self):\n setDefaults()\n setPlayerCharacter('B', JESSE_JONES)\n setPlayerCardsInHand({'C': [1], 'D': [2]})\n expectedJesseJonesInfo = \"You drew a Bang from D's hand and {} from the deck\".format(game.drawPile[-1].getDeterminerString())\n expectedOpponentInfo = \"B drew a Bang from your hand using Jesse Jones's ability\"\n expectedUpdate = \"B drew a card from D's hand using Jesse Jones's ability.\"\n expectedCardsDrawn = [game.getCardByUid(2), game.drawPile[-1]]\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_JESSE_JONES, FROM_ANOTHER_PLAYER)\n self.assertEqual(getEmitTypes(tuples), {SHOW_QUESTION_MODAL})\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n self.assertEqual({val for val in tuples[0][1].values() if val in players}, {'C', 'D'})\n\n tuples = game.processQuestionResponse('B', QUESTION_WHOSE_HAND, 'D')\n self.assertTrue(playerGotInfo('B', expectedJesseJonesInfo, tuples))\n self.assertTrue(playerGotInfo('D', expectedOpponentInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['D'].cardsInHand, [])\n self.assertEqual(game.currentCard, None)\n\n # Jesse Jones: Draw one card from the hand of the only player with cards and one from the deck.\n def testJesseJonesUsingAbilityAutomaticOpponent(self):\n setDefaults()\n setPlayerCharacter('B', JESSE_JONES)\n setPlayerCardsInHand({'D': [2]})\n expectedJesseJonesInfo = \"You automatically drew a Bang from D's hand and {} from the deck\".format(game.drawPile[-1].getDeterminerString())\n expectedOpponentInfo = \"B drew a Bang from your hand using Jesse Jones's ability\"\n expectedUpdate = \"B drew a card from D's hand using Jesse Jones's ability.\"\n expectedCardsDrawn = [game.getCardByUid(2), game.drawPile[-1]]\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_JESSE_JONES, FROM_ANOTHER_PLAYER)\n self.assertTrue(playerGotInfo('B', expectedJesseJonesInfo, tuples))\n self.assertTrue(playerGotInfo('D', expectedOpponentInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['D'].cardsInHand, [])\n self.assertEqual(game.currentCard, None)\n\n # Jesse Jones: Draw both cards normally from the deck by choice.\n def testJesseJonesNotUsingAbilityByChoice(self):\n setDefaults()\n setPlayerCharacter('B', JESSE_JONES)\n setPlayerCardsInHand({'C': [1], 'D': [2]})\n expectedJesseJonesInfo = \"You drew {} and {} from the deck\".format(game.drawPile[-1].getDeterminerString(), game.drawPile[-2].getDeterminerString())\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_JESSE_JONES, FROM_THE_DECK)\n self.assertTrue(playerGotInfo('B', expectedJesseJonesInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(game.currentCard, None)\n\n # Jesse Jones: Draw both cards normally because nobody has a card to steal.\n def testJesseJonesNotUsingAbilityHavingNoChoice(self):\n setDefaults()\n setPlayerCharacter('B', JESSE_JONES)\n expectedJesseJonesInfo = \"nobody has cards to draw from\".format()\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n\n tuples = game.startNextTurn('A')\n self.assertEqual(getEmitTypes(tuples), NEW_TURN_TUPLES)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 0)\n self.assertTrue(playerGotInfo('B', expectedJesseJonesInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(game.currentCard, None)\n\n # Jourdonnais: Draw once against a Bang without having a Barile in play and get a heart.\n def testJourdonnaisWithoutBarileSuccess(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', JOURDONNAIS)\n setPlayerCardsInHand({'A': [1]})\n expectedAttackerInfo = \"B drew a heart for Barile and avoided your Bang\"\n expectedJourdonnaisInfo = \"You drew a heart for Barile\"\n expectedUpdate = \"B drew a heart for Barile and avoided A's Bang.\"\n cardToDraw = getCardsOfASuit(HEART, 1)[0]\n game.drawPile.append(cardToDraw)\n\n tuples = game.validateCardChoice('A', 1)\n self.assertTrue(playerGotInfo('A', expectedAttackerInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedJourdonnaisInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(game.currentCard, None)\n\n # Jourdonnais: Draw once against a Bang without having a Barile in play and don't get a heart.\n def testJourdonnaisWithoutBarileFailure(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', JOURDONNAIS)\n setPlayerCardsInHand({'A': [1]})\n expectedJourdonnaisInfo = \"You didn't draw a heart\"\n expectedUpdate = \"B tried to avoid the Bang with a Barile but didn't draw a heart.\"\n cardToDraw = getCardsOfASuit(SPADE, 1)[0]\n game.drawPile.append(cardToDraw)\n\n tuples = game.validateCardChoice('A', 1)\n self.assertTrue(playerGotInfo('B', expectedJourdonnaisInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(game.currentCard, None)\n\n # Jourdonnais: Draw twice against a Bang with a Barile in play when the first card isn't a heart, getting a heart on the second card.\n def testJourdonnaisWithBarileSuccess(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', JOURDONNAIS)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'B': [64]})\n expectedAttackerInfo = \"B drew a heart for Barile and avoided your Bang\"\n expectedJourdonnaisInfo = \"You drew a heart for Barile on your second card and avoided the Bang\"\n expectedUpdate = \"B drew a heart for Barile and avoided A's Bang.\"\n cardsToDraw = [getCardsOfASuit(HEART, 1)[0], getCardsOfASuit(CLUB, 1)[0]]\n game.drawPile.extend(cardsToDraw)\n\n tuples = game.validateCardChoice('A', 1)\n self.assertTrue(playerGotInfo('A', expectedAttackerInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedJourdonnaisInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(game.discardPile, [game.getCardByUid(1)] + cardsToDraw[::-1])\n self.assertEqual(game.currentCard, None)\n\n # Jourdonnais: Draw twice against a Bang with a Barile in play when the first card isn't a heart, failing both times.\n def testJourdonnaisWithBarileFailure(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', JOURDONNAIS)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'B': [64]})\n expectedUpdate = \"B tried to avoid the Bang with a Barile but didn't draw a heart either time.\"\n cardsToDraw = [getCardsOfASuit(DIAMOND, 1)[0], getCardsOfASuit(SPADE, 1)[0]]\n game.drawPile.extend(cardsToDraw)\n\n tuples = game.validateCardChoice('A', 1)\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(game.discardPile, [game.getCardByUid(1)] + cardsToDraw[::-1])\n self.assertEqual(game.currentCard, None)\n\n # Kit Carlson: Choose two of the first three cards and put the third back on the draw pile in every combination.\n def testKitCarlson(self):\n for cardIndex in range(0, 3):\n setDefaults()\n setPlayerCharacter('B', KIT_CARLSON)\n expectedOptions = game.drawPile[-3:][::-1]\n expectedKitCarlsonInfo = \"You drew {} and {} and put {} back on the draw pile\".format(*[c.getDeterminerString() for (i, c) in enumerate(expectedOptions) if i != cardIndex], expectedOptions[cardIndex].getDeterminerString())\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n self.assertTrue([c.getQuestionString() in [t[1].values() for t in tuples if t[0] == SHOW_QUESTION_MODAL and t[2] == players['B']] for c in expectedOptions])\n\n tuples = game.processQuestionResponse('B', QUESTION_KIT_CARLSON, expectedOptions[cardIndex].getQuestionString())\n self.assertTrue(playerGotInfo('B', expectedKitCarlsonInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, [c for (i, c) in enumerate(expectedOptions) if i != cardIndex])\n self.assertEqual(game.drawPile[-1], expectedOptions[cardIndex])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Lucky Duke: Successfully \"draw!\" by choosing the useful option.\n def testLuckyDukeSuccessful(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', LUCKY_DUKE)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'B': [64]})\n \n heartCard = getCardsOfASuit(HEART, 1)[0]\n clubCard = getCardsOfASuit(CLUB, 1)[0]\n game.drawPile.extend([heartCard, clubCard])\n\n tuples = game.validateCardChoice('A', 1)\n questionTuple = getQuestionTuple('B', tuples)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n self.assertEqual(questionTuple[1]['question'], QUESTION_LUCKY_DUKE.format('Bang'))\n self.assertEqual(questionTuple[1]['option1'], clubCard.getQuestionString())\n self.assertEqual(questionTuple[1]['option2'], heartCard.getQuestionString())\n\n tuples = game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Bang'), heartCard.getQuestionString())\n self.assertTrue(playerGotInfo('A', \"B drew a heart for Barile and avoided your Bang!\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a heart for Barile and avoided the Bang!\", tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(game.discardPile, [game.getCardByUid(1), clubCard, heartCard])\n self.assertEqual(game.currentCard, None)\n\n # Lucky Duke: Unsuccessfully \"draw!\" by not getting a useful choice.\n def testLuckyDukeUnsuccessful(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', LUCKY_DUKE)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'B': [64]})\n \n diamondCard = getCardsOfASuit(DIAMOND, 1)[0]\n clubCard = getCardsOfASuit(CLUB, 1)[0]\n game.drawPile.extend([diamondCard, clubCard])\n\n tuples = game.validateCardChoice('A', 1)\n questionTuple = getQuestionTuple('B', tuples)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n self.assertEqual(questionTuple[1]['question'], QUESTION_LUCKY_DUKE.format('Bang'))\n self.assertEqual(questionTuple[1]['option1'], clubCard.getQuestionString())\n self.assertEqual(questionTuple[1]['option2'], diamondCard.getQuestionString())\n\n tuples = game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Bang'), diamondCard.getQuestionString())\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_WAITING_MODAL, players['A']), 1)\n self.assertTrue(playerGotInfo('A', \"B took the hit\", tuples))\n self.assertTrue(playerGotInfo('B', \"You didn't draw a heart for Barile\", tuples))\n self.assertTrue(playerGotInfo('B', \"You were hit by the Bang\", tuples))\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(game.discardPile, [game.getCardByUid(1), clubCard, diamondCard])\n self.assertEqual(game.currentCard, None)\n\n # Lucky Duke: Draw successfuly for dynamite then draw normally at the start of the turn.\n def testLuckyDukeDynamite(self):\n setDefaults()\n setPlayerCharacter('B', LUCKY_DUKE)\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n heartCard = getCardsOfASuit(HEART, 1)[0]\n spadeCard = getCardsOfASuit(SPADE, 1)[0]\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n game.drawPile.extend([spadeCard, heartCard])\n\n game.startNextTurn('A')\n\n tuples = game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Dynamite'), heartCard.getQuestionString())\n self.assertTrue(playerGotInfo('B', \"The dynamite didn't explode on you\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew {}\".format(utils.convertCardsDrawnToString(expectedCardsDrawn)), tuples))\n self.assertTrue(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"The dynamite didn't explode on B, so now C has it.\", tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [game.getDynamiteCard()])\n\n self.assertEqual(game.dynamiteUsername, 'C')\n self.assertEqual(game.discardPile, [spadeCard, heartCard])\n self.assertEqual(game.currentCard, None)\n\n # Lucky Duke: Draw successfuly for jail then draw normally at the start of the turn.\n def testLuckyDukePrigione(self):\n setDefaults()\n setPlayerCharacter('B', LUCKY_DUKE)\n setPlayerSpecialCards({'B': [69]})\n players['B'].jailStatus = 1\n heartCard = getCardsOfASuit(HEART, 1)[0]\n clubCard = getCardsOfASuit(CLUB, 1)[0]\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n game.drawPile.extend([clubCard, heartCard])\n\n game.startNextTurn('A')\n\n tuples = game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Prigione'), heartCard.getQuestionString())\n self.assertTrue(playerGotInfo('B', \"You drew a heart, so you got out of jail!\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew {}\".format(utils.convertCardsDrawnToString(expectedCardsDrawn)), tuples))\n self.assertTrue(playersGotUpdate(\"B drew a heart, so they get to play this turn.\", tuples))\n self.assertFalse((END_YOUR_TURN, dict(), players['B']) in tuples)\n self.assertTrue(playersGotUpdate(DREW_2_CARDS.format('B'), tuples))\n\n self.assertEqual(players['B'].jailStatus, 0)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(game.playerOrder[0], players['B'])\n\n self.assertEqual(game.discardPile, [clubCard, heartCard, game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Lucky Duke: Draw successfuly for dynamite and jail together and then draw normally at the start of the turn.\n def testLuckyDukeDynamiteAndJail(self):\n setDefaults()\n setPlayerCharacter('B', LUCKY_DUKE)\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n heartCards = getCardsOfASuit(HEART, 2)\n diamondCards = getCardsOfASuit(DIAMOND, 2)\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n game.drawPile.extend(heartCards[:1] + diamondCards + heartCards[1:])\n\n game.startNextTurn('A')\n\n game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Dynamite'), heartCards[1].getQuestionString())\n \n game.processQuestionResponse('B', QUESTION_LUCKY_DUKE.format('Prigione'), heartCards[0].getQuestionString())\n\n self.assertEqual(players['B'].jailStatus, 0)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(game.playerOrder[0], players['B'])\n\n self.assertEqual(game.dynamiteUsername, 'C')\n self.assertEqual(game.discardPile, [diamondCards[1], heartCards[1], diamondCards[0], heartCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Paul Regret: Be out of range for a 1-range Bang without a Mustang in play.\n def testPaulRegretOutOfRange1(self):\n setDefaults()\n setPlayerCharacter('B', PAUL_REGRET)\n setPlayerCardsInHand({'A': [1]})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertTrue(playerGotInfo('A', \"B is out of range\", tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(game.currentCard, None)\n\n # Paul Regret: Be in range for a 2-range Bang without a Mustang in play.\n def testPaulRegretInRange(self):\n setDefaults()\n setPlayerCharacter('B', PAUL_REGRET)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'A': [75]})\n\n game.validateCardChoice('A', 1)\n game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n\n self.assertEqual(players['B'].lives, 3)\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertTrue(game.currentCard == None)\n\n # Paul Regret: Be out of range for a 2-range Bang with a Mustang in play.\n def testPaulRegretOutOfRange2(self):\n setDefaults()\n setPlayerCharacter('C', PAUL_REGRET)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'C': [67]})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'C')\n self.assertTrue(playerGotInfo('A', \"C is out of range\", tuples))\n\n self.assertEqual(players['C'].lives, 4)\n self.assertEqual(game.currentCard, None)\n\n # Pedro Ramirez: Draw one card from the discard pile and one from the deck.\n def testPedroRamirezSpecial(self):\n setDefaults()\n setPlayerCharacter('B', PEDRO_RAMIREZ)\n discardCard = game.drawPile.pop()\n game.discardPile.append(discardCard)\n drawCard = game.drawPile[-1]\n expectedPedroInfo = \"You drew {} from the discard pile and {} from the deck\".format(discardCard.getDeterminerString(), drawCard.getDeterminerString())\n expectedUpdate = \"B drew {} from the discard pile and 1 card from the deck.\".format(discardCard.getDeterminerString())\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_PEDRO_RAMIREZ, FROM_DISCARD)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_ACTION, UPDATE_DISCARD_PILE, UPDATE_CARD_HAND})\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n self.assertTrue(playerGotInfo('B', expectedPedroInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, [discardCard, drawCard])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Pedro Ramirez: Draw both cards from the deck by choice.\n def testPedroRamirezNormalByChoice(self):\n setDefaults()\n setPlayerCharacter('B', PEDRO_RAMIREZ)\n discardCard = game.drawPile.pop()\n game.discardPile.append(discardCard)\n drawnCards = game.drawPile[-2:][::-1]\n expectedPedroInfo = \"You drew {} from the deck\".format(utils.convertCardsDrawnToString(drawnCards))\n expectedUpdate = \"B drew 2 cards from the deck.\"\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n\n tuples = game.processQuestionResponse('B', QUESTION_PEDRO_RAMIREZ, FROM_THE_DECK)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_ACTION, UPDATE_CARD_HAND, UPDATE_DISCARD_PILE})\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n self.assertTrue(playerGotInfo('B', expectedPedroInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, drawnCards)\n self.assertEqual(game.discardPile, [discardCard])\n self.assertEqual(game.currentCard, None)\n\n # Pedro Ramirez: Draw both cards from the deck having no choice.\n def testPedroRamirezNormalNoChoice(self):\n setDefaults()\n setPlayerCharacter('B', PEDRO_RAMIREZ)\n drawnCards = game.drawPile[-2:][::-1]\n expectedPedroInfo = \"You drew {} from the deck (the discard pile is empty right now)\".format(utils.convertCardsDrawnToString(drawnCards))\n expectedUpdate = \"B drew 2 cards from the deck.\".format()\n\n tuples = game.startNextTurn('A')\n self.assertEqual(getEmitTypes(tuples), NEW_TURN_TUPLES)\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n self.assertTrue(playerGotInfo('B', expectedPedroInfo, tuples))\n\n self.assertEqual(players['B'].cardsInHand, drawnCards)\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Rose Doolan: Successfully Bang a 2-away player without a Scope in play.\n def testRoseDoolanSuccessful1(self):\n setDefaults()\n setPlayerCharacter('A', ROSE_DOOLAN)\n setPlayerCardsInHand({'A': [1]})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'C')\n\n self.assertEqual(players['C'].lives, 3)\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.currentCard, None)\n\n # Rose Doolan: Unsuccessfully Bang a 3-away player without a Scope in play.\n def testRoseDoolanUnsuccessful(self):\n setDefaults()\n setPlayerCharacter('A', ROSE_DOOLAN)\n setPlayerCardsInHand({'A': [1]})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'D')\n self.assertEqual(len(tuples), 1)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL})\n self.assertTrue(\"D is out of range\" in tuples[0][1]['html'])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n self.assertEqual(game.discardPile, [])\n self.assertTrue(game.currentCard == None)\n\n # Rose Doolan. Successfully Bang a 3-away player with a Scope in play.\n def testRoseDoolanSuccessful2(self):\n setDefaults()\n setPlayerCharacter('A', ROSE_DOOLAN)\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'A': [66]})\n\n game.validateCardChoice('A', 1)\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'D')\n\n self.assertEqual(players['D'].lives, 3)\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.currentCard, None)\n\n # Sid Ketchum: Successfully discard only two cards automatically to regain one life point.\n def testSidKetchumSuccessful1(self):\n setDefaults()\n setPlayerCharacter('A', SID_KETCHUM)\n setPlayerLives({'A': 4})\n setPlayerCardsInHand({'A': [20, 30]})\n expectedInfo = \"You've discarded 2 cards and gained a life.\"\n expectedUpdate = \"A used Sid Ketchum's ability to discard 2 cards and gain a life.\"\n\n tuples = game.useSpecialAbility('A')\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST} | CARD_PLAYED_TUPLES)\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].lives, 5)\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(game.specialAbilityCards[SID_KETCHUM], None)\n self.assertEqual(game.discardPile, [game.getCardByUid(20), game.getCardByUid(30)])\n self.assertEqual(game.currentCard, None)\n\n # Sid Ketchum: Successfully discard four cards to regain two life points.\n def testSidKetchumSuccessful2(self):\n setDefaults()\n setPlayerCharacter('A', SID_KETCHUM)\n setPlayerLives({'A': 2})\n setPlayerCardsInHand({'A': [20, 30, 40, 50, 60]})\n expectedInfo = \"You've discarded 2 cards and gained a life.\"\n expectedUpdate = \"A used Sid Ketchum's ability to discard 2 cards and gain a life.\"\n\n for uidPair in [(20, 30), (50, 60)]:\n tuples = game.useSpecialAbility('A')\n self.assertTrue(playerGotInfo('A', SID_KETCHUM_INFO, tuples))\n \n tuples = game.playerDiscardingCard('A', uidPair[0])\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, DISCARD_CLICK})\n \n tuples = game.playerDiscardingCard('A', uidPair[1])\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_PLAYER_LIST} | CARD_PLAYED_TUPLES)\n\n self.assertEqual(players['A'].lives, 4)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(40)])\n self.assertEqual(game.specialAbilityCards[SID_KETCHUM], None)\n self.assertEqual(game.discardPile, [game.getCardByUid(20), game.getCardByUid(30), game.getCardByUid(50), game.getCardByUid(60)])\n self.assertEqual(game.currentCard, None)\n\n # Sid Ketchum: Unsuccessfully try to discard two cards with none/one in hand.\n def testSidKetchumUnsuccessful1(self):\n setDefaults()\n setPlayerCharacter('A', SID_KETCHUM)\n setPlayerLives({'A': 4})\n\n for uids in [[], [20]]:\n setPlayerCardsInHand({'A': uids})\n expectedInfo = \"You don't have enough cards to use your special ability right now.\"\n\n tuples = game.useSpecialAbility('A')\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n\n self.assertEqual(players['A'].lives, 4)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(uid) for uid in uids])\n self.assertEqual(game.specialAbilityCards[SID_KETCHUM], None)\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Sid Ketchum: Unsuccessfully try to discard two cards when already at the life limit.\n def testSidKetchumUnsuccessful2(self):\n setDefaults()\n setPlayerCharacter('A', SID_KETCHUM)\n setPlayerLives({'A': 5})\n setPlayerCardsInHand({'A': [20, 30]})\n\n tuples = game.useSpecialAbility('A')\n self.assertTrue(playerGotInfo('A', ALREADY_MAX_LIVES, tuples))\n\n self.assertEqual(players['A'].lives, 5)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(20), game.getCardByUid(30)])\n self.assertEqual(game.specialAbilityCards[SID_KETCHUM], None)\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Successfully Bang against a target who only has one Mancato.\n def testSlabTheKillerSuccessful1(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26]})\n expectedSlabInfo = \"B took the hit\"\n expectedOpponentInfo = \"You were hit by the Bang\"\n\n tuples = game.validateCardChoice('A', 1)\n self.assertTrue(playerGotInfo('A', expectedSlabInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedOpponentInfo, tuples))\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(26)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n\n # Slab the Killer: Unsuccessfully Bang against a target who has two Mancatos and plays both.\n def testSlabTheKillerUnsuccessful1(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27]})\n expectedSlabInfo = \"B played 2 Mancatos to avoid your Bang!\"\n expectedOpponentInfo = \"You automatically played your only 2 Mancatos left\"\n expectedUpdate = \"B played 2 Mancatos and avoided A's Bang.\"\n\n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_WAITING_MODAL, players['A']), 1)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n \n questionTuple = getQuestionTuple('B', tuples)\n self.assertTrue(PLAY_A_MANCATO not in questionTuple[1].values())\n self.assertTrue(PLAY_TWO_MANCATOS in questionTuple[1].values())\n self.assertTrue(LOSE_A_LIFE in questionTuple[1].values())\n\n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), PLAY_TWO_MANCATOS)\n self.assertTrue(playerGotInfo('A', expectedSlabInfo, tuples))\n self.assertTrue(playerGotInfo('B', expectedOpponentInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(26), game.getCardByUid(27)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Unsuccessfully Bang against a target who has 3+ Mancatos and chooses two to play.\n def testSlabTheKillerUnsuccessful2(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27, 28]})\n expectedSlabInfo = \"B played 2 Mancatos to avoid your Bang!\"\n expectedUpdate = \"B played 2 Mancatos and avoided A's Bang.\"\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), PLAY_TWO_MANCATOS)\n self.assertEqual(countEmitTypeToRecipient(tuples, BLUR_CARD_SELECTION, players['B']), 1)\n self.assertTrue(playerGotInfo('B', \"Click on the first Mancato in your hand that you want to use\", tuples))\n \n tuples = game.processBlurCardSelection('B', 27)\n self.assertEqual(countEmitTypeToRecipient(tuples, BLUR_CARD_SELECTION, players['B']), 1)\n self.assertTrue(playerGotInfo('B', \"Click on the second Mancato in your hand that you want to use\", tuples))\n\n tuples = game.processBlurCardSelection('B', 28)\n self.assertTrue(playerGotInfo('A', expectedSlabInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(26)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(27), game.getCardByUid(28)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Unsuccessfuly Bang against Calamity Janet using 2 Bangs as Mancatos.\n def testSlabTheKillerAgainstCalamityJanet(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCharacter('B', CALAMITY_JANET)\n setPlayerCardsInHand({'A': [1], 'B': [2, 3, 4]})\n expectedSlabInfo = \"B played 2 Bangs (as Mancatos) to avoid your Bang!\"\n expectedUpdate = \"B played 2 Bangs (as Mancatos) and avoided A's Bang.\"\n\n game.validateCardChoice('A', 1)\n\n game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), PLAY_TWO_MANCATOS)\n\n game.processBlurCardSelection('B', 2)\n\n tuples = game.processBlurCardSelection('B', 4)\n self.assertTrue(playerGotInfo('A', expectedSlabInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(3)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), game.getCardByUid(2), game.getCardByUid(4)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Successfully Bang against a target who has two Mancatos but doesn't play them.\n def testSlabTheKillerSuccessful2(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27]})\n expectedSlabInfo = \"B played 2 Mancatos to avoid your Bang!\"\n expectedUpdate = \"B played 2 Mancatos and avoided A's Bang.\"\n\n game.validateCardChoice('A', 1)\n \n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), LOSE_A_LIFE)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(26), game.getCardByUid(27)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Successfully Bang against a target who draws a heart for \"draw!\" but doesn't choose to play a Mancato.\n def testSlabTheKillerSuccessfulAgainstBarile(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26]})\n setPlayerCardsInPlay({'B': [64]})\n heartCard = getCardsOfASuit(HEART, 1)[0]\n game.drawPile.append(heartCard)\n question = QUESTION_SLAB_BARILE_ONE.format('A')\n\n tuples = game.validateCardChoice('A', 1)\n questionTuple = getQuestionTuple('B', tuples)\n self.assertEqual(questionTuple[1]['question'], question)\n \n game.processQuestionResponse('B', question, LOSE_A_LIFE)\n\n self.assertEqual(players['B'].lives, 3)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(26)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), heartCard])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Unsuccessfully Bang against a target who both draws a heart for \"draw!\" and plays a Mancato.\n def testSlabTheKillerUnsuccessfulAgainstBarile1(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26]})\n setPlayerCardsInPlay({'B': [64]})\n heartCard = getCardsOfASuit(HEART, 1)[0]\n game.drawPile.append(heartCard)\n question = QUESTION_SLAB_BARILE_ONE.format('A')\n\n game.validateCardChoice('A', 1)\n \n game.processQuestionResponse('B', question, PLAY_A_MANCATO)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), heartCard, game.getCardByUid(26)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Unsuccessfully Bang against a target who doesn't draw a heart for \"draw!\" but plays two Mancatos.\n def testSlabTheKillerUnsuccessfulAgainstBarile2(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27]})\n setPlayerCardsInPlay({'B': [64]})\n diamondCard = getCardsOfASuit(DIAMOND, 1)[0]\n game.drawPile.append(diamondCard)\n\n game.validateCardChoice('A', 1)\n\n game.processQuestionResponse('B', QUESTION_SLAB_BARILE_TWO.format('A'), PLAY_TWO_MANCATOS)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), diamondCard, game.getCardByUid(26), game.getCardByUid(27)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Successfully avoid his Gatling using only 1 Mancato.\n def testSlabTheKillerGatling(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCardsInHand({'A': [54], 'B': [26]})\n question = QUESTION_GATLING_REACTION.format('A')\n\n tuples = game.validateCardChoice('A', 54)\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_QUESTION_MODAL, players['B']), 1)\n questionTuple = getQuestionTuple('B', tuples)\n self.assertEqual(questionTuple[1]['question'], question)\n\n game.processQuestionResponse('B', question, PLAY_A_MANCATO)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(game.discardPile, [game.getCardByUid(54), game.getCardByUid(26)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Slab the Killer: Use a Bang against Jourdonnais, who successfully draws a heart on the second card and then chooses a Mancato to play.\n def testSlabTheKillerAgainstJourdonnais(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SLAB_THE_KILLER)\n setPlayerCharacter('B', JOURDONNAIS)\n setPlayerCardsInHand({'A': [1], 'B': [26, 27]})\n setPlayerCardsInPlay({'B': [64]})\n heartCard = getCardsOfASuit(HEART, 1)[0]\n spadeCard = getCardsOfASuit(SPADE, 1)[0]\n game.drawPile.extend([heartCard, spadeCard])\n question = QUESTION_SLAB_BARILE_ONE.format('A')\n\n game.validateCardChoice('A', 1)\n \n game.processQuestionResponse('B', question, PLAY_A_MANCATO)\n\n game.processBlurCardSelection('B', 26)\n\n self.assertEqual(players['B'].lives, 4)\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['B'].cardsInHand, [game.getCardByUid(27)])\n self.assertEqual(game.discardPile, [game.getCardByUid(1), spadeCard, heartCard, game.getCardByUid(26)])\n self.assertEqual(game.specialAbilityCards[SLAB_THE_KILLER], None)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card as soon as last card was played in turn.\n def testSuzyLafayetteDrawingInTurn(self):\n setDefaults()\n setPlayerCharacter('A', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [66]})\n expectedCardDrawn = game.drawPile[-1]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"A drew a card using Suzy Lafayette's ability.\"\n\n tuples = game.validateCardChoice('A', 66)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_CARDS_IN_PLAY, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card after playing last card from hand in response to an attacking card.\n def testSuzyLafayetteDrawingAfterResponse(self):\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"B drew a card using Suzy Lafayette's ability.\"\n\n for (attackingUid, responseUid, question, answer) in \\\n [(1, 26, QUESTION_BANG_REACTION, PLAY_A_MANCATO),\n (54, 26, QUESTION_GATLING_REACTION, PLAY_A_MANCATO),\n (58, 1, QUESTION_INDIANS_REACTION, PLAY_A_BANG)]:\n \n\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [attackingUid], 'B': [responseUid]})\n expectedCardDrawn = game.drawPile[-1]\n\n game.validateCardChoice('A', attackingUid)\n\n tuples = game.processQuestionResponse('B', question.format('A'), answer)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('B', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Wait until after a Duello (winning by default) is finished to draw a new card.\n def testSuzyLafayetteDuelloWin(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [1, 55], 'B': [2]})\n expectedCardDrawn = game.drawPile[-1]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"A drew a card using Suzy Lafayette's ability.\"\n\n game.validateCardChoice('A', 55)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n\n game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), PLAY_A_BANG)\n\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_DISCARD_PILE, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Wait until after a Duello (winning by choice) is finished to draw a new card.\n def testSuzyLafayetteDuelloLoss(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [1, 55], 'B': [2]})\n expectedCardDrawn = game.drawPile[-1]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"B drew a card using Suzy Lafayette's ability.\"\n\n game.validateCardChoice('A', 55)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(1)])\n\n game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n\n tuples = game.processQuestionResponse('A', QUESTION_DUELLO_BANG_REACTION.format('B'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('B', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card after having the last one stolen by a Cat Balou / Panico.\n def testSuzyLafayetteCatBalouPanico(self):\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"B drew a card using Suzy Lafayette's ability.\"\n\n for uid in [38, 50]:\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [uid], 'B': [1]})\n expectedCardDrawn = game.drawPile[-1]\n\n tuples = game.validateCardChoice('A', uid)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('B', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card after playing a Birra to stay alive.\n def testSuzyLafayetteStayingAlive(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('B', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'A': [1], 'B': [42]})\n setPlayerLives({'B': 1})\n expectedCardDrawn = game.drawPile[-1]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"B drew a card using Suzy Lafayette's ability.\"\n\n tuples = game.validateCardChoice('A', 1)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_DISCARD_PILE, UPDATE_PLAYER_LIST, SHOW_WAITING_MODAL})\n self.assertTrue(playerGotInfo('B', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 1)\n\n self.assertEqual(players['B'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card after having the last one stolen by El Gringo.\n def testSuzyLafayetteElGringo(self):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', SUZY_LAFAYETTE)\n setPlayerCharacter('B', EL_GRINGO)\n setPlayerCardsInHand({'A': [1, 2], 'B': [26]})\n expectedCardDrawn = game.drawPile[-1]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"A drew a card using Suzy Lafayette's ability.\"\n\n game.validateCardChoice('A', 1)\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(2)])\n\n tuples = game.processQuestionResponse('B', QUESTION_BANG_REACTION.format('A'), LOSE_A_LIFE)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Suzy Lafayette: Draw a card after having the last one stolen by Jesse Jones.\n def testSuzyLafayetteJesseJones(self):\n setDefaults()\n setPlayerCharacter('B', JESSE_JONES)\n setPlayerCharacter('C', SUZY_LAFAYETTE)\n setPlayerCardsInHand({'C': [1]})\n expectedCardDrawn = game.drawPile[-2]\n expectedInfo = \"You drew a card using Suzy Lafayette's ability!\"\n expectedUpdate = \"C drew a card using Suzy Lafayette's ability.\"\n\n game.startNextTurn('A')\n\n tuples = game.processQuestionResponse('B', QUESTION_JESSE_JONES, FROM_ANOTHER_PLAYER)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('C', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['C'].cardsInHand, [expectedCardDrawn])\n self.assertTrue(expectedCardDrawn not in game.drawPile)\n self.assertEqual(game.currentCard, None)\n\n # Vulture Sam: Take all the cards from a player's hand and from in front of him/her when s/he gets eliminated.\n def testVultureSam(self):\n setDefaults()\n setPlayerCharacter('C', VULTURE_SAM)\n cardsInHand = [1, 50, 60]\n cardsInPlay = [66, 75]\n jailCard = [69]\n setPlayerCardsInHand({'A': [54], 'B': cardsInHand})\n setPlayerCardsInPlay({'B': cardsInPlay})\n setPlayerSpecialCards({'B': jailCard})\n setPlayerLives({'B': 1})\n expectedInfo = \"You got all of B's cards because they were eliminated\"\n expectedUpdate = \"C got all of B's cards using Vulture Sam's ability.\"\n\n tuples = game.validateCardChoice('A', 54)\n self.assertEqual(getEmitTypes(tuples), {SHOW_INFO_MODAL, UPDATE_CARD_HAND, UPDATE_ACTION, UPDATE_PLAYER_LIST, UPDATE_DISCARD_PILE})\n self.assertTrue(playerGotInfo('C', expectedInfo, tuples))\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['B'].lives, 0)\n\n self.assertEqual(players['B'].cardsInHand + players['B'].cardsInPlay + players['B'].specialCards, [])\n self.assertEqual(players['C'].cardsInHand, [game.getCardByUid(uid) for uid in cardsInHand + cardsInPlay + jailCard])\n self.assertEqual(game.currentCard, None)\n\n # Willy the Kid: Successfully play one, two, and even three Bangs in one turn.\n def testWillyTheKid(self):\n for bangAmount in range(1, 4):\n setDefaults(numPlayers=2)\n setPlayerCharacter('A', WILLY_THE_KID)\n bangUids = [b for b in range(1, 1 + bangAmount)]\n setPlayerCardsInHand({'A': bangUids})\n\n for bangUid in bangUids:\n self.assertNotEqual(game.validateCardChoice('A', bangUid), [])\n self.assertTrue(bangUid not in [c.uid for c in players['A'].cardsInHand])\n self.assertEqual(players['B'].lives, players['B'].lifeLimit - bangUid)\n self.assertEqual(game.currentCard, None)\n\n self.assertEqual(players['A'].cardsInHand, [])\n\n\n\n ''' Having cards in play tests. '''\n\n # Unsuccessfully putting down a duplicate card type.\n def testCardInPlayDuplicate(self):\n for (inHandUid, inPlayUid) in [[64, 65], [67, 68]]:\n setDefaults()\n setPlayerCardsInHand({'A': [inHandUid]})\n setPlayerCardsInPlay({'A': [inPlayUid]})\n inHandCard = game.getCardByUid(inHandUid)\n inPlayCard = game.getCardByUid(inPlayUid)\n expectedInfo = \"You already have {} in play\".format(inPlayCard.getDeterminerString())\n\n self.assertEqual(inHandCard.name, inPlayCard.name)\n\n tuples = game.validateCardChoice('A', inHandUid)\n self.assertTrue(playerGotInfo('A', expectedInfo, tuples))\n \n self.assertEqual(players['A'].cardsInHand, [inHandCard])\n self.assertEqual(players['A'].cardsInPlay, [inPlayCard])\n self.assertEqual(game.currentCard, None)\n\n # Choosing to replace one in-play card with another when 2 are down.\n def testInPlayReplacingACard(self):\n cardsInPlay = [66, 67]\n \n for i, cardInPlay in enumerate(map(game.getCardByUid, cardsInPlay)):\n setDefaults()\n setPlayerCardsInHand({'A': [64]})\n setPlayerCardsInPlay({'A': cardsInPlay})\n cardInHand = game.getCardByUid(64)\n remainingCardInPlay = game.getCardByUid(cardsInPlay[int(not bool(i))])\n expectedUpdate = \"A discarded {} and put {} in play.\".format(cardInPlay.getDeterminerString(), cardInHand.getDeterminerString())\n expectedCardsInHand = [cardInHand, remainingCardInPlay] if i == 0 else [remainingCardInPlay, cardInHand]\n\n tuples = game.validateCardChoice('A', 64)\n questionTuple = getQuestionTuple('A', tuples)\n self.assertEqual(questionTuple[1]['question'], QUESTION_IN_PLAY)\n \n answer = \"Replace the {}.\".format(cardInPlay.getQuestionString())\n tuples = game.processQuestionResponse('A', QUESTION_IN_PLAY, answer)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_CARDS_IN_PLAY, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['A'].cardsInPlay, expectedCardsInHand)\n self.assertEqual(game.discardPile, [cardInPlay])\n self.assertEqual(game.currentCard, None)\n\n # Choosing not to replace one in-play card with another when 2 are down.\n def testInPlayNotReplacingCard(self):\n setDefaults()\n setPlayerCardsInHand({'A': [64]})\n setPlayerCardsInPlay({'A': [66, 67]})\n\n game.validateCardChoice('A', 64)\n \n tuples = game.processQuestionResponse('A', QUESTION_IN_PLAY, KEEP_CURRENT_CARDS)\n self.assertEqual(tuples, [])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(64)])\n self.assertEqual(players['A'].cardsInPlay, [game.getCardByUid(66), game.getCardByUid(67)])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n # Choosing to replace an in-play gun with a new one given 1 or 2 in-play card(s).\n def testInPlayReplacingGun(self):\n for secondInPlayUid in [[], [67]]:\n setDefaults()\n setPlayerCardsInHand({'A': [75]})\n setPlayerCardsInPlay({'A': [78] + secondInPlayUid})\n newGun = game.getCardByUid(75)\n currentGun = game.getCardByUid(78)\n expectedUpdate = \"A discarded {} and put {} in play.\".format(currentGun.getDeterminerString(), newGun.getDeterminerString())\n\n tuples = game.validateCardChoice('A', 75)\n questionTuple = getQuestionTuple('A', tuples)\n self.assertEqual(questionTuple[1]['question'], QUESTION_REPLACE_GUN)\n \n answer = REPLACE_GUN.format(currentGun.getDisplayName(), newGun.getDisplayName())\n tuples = game.processQuestionResponse('A', QUESTION_REPLACE_GUN, answer)\n self.assertEqual(getEmitTypes(tuples), {UPDATE_CARD_HAND, UPDATE_CARDS_IN_PLAY, UPDATE_DISCARD_PILE, UPDATE_ACTION})\n self.assertTrue(playersGotUpdate(expectedUpdate, tuples))\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['A'].cardsInPlay, [newGun] + [game.getCardByUid(uid) for uid in secondInPlayUid])\n self.assertEqual(game.discardPile, [currentGun])\n self.assertEqual(game.currentCard, None)\n\n # Choosing to keep an in-play gun instead of playing a new one.\n def testInPlayNotReplacingGun(self):\n for secondInPlayUid in [[], [67]]:\n setDefaults()\n setPlayerCardsInHand({'A': [75]})\n setPlayerCardsInPlay({'A': [78] + secondInPlayUid})\n currentGun = game.getCardByUid(78)\n\n tuples = game.validateCardChoice('A', 75)\n questionTuple = getQuestionTuple('A', tuples)\n self.assertEqual(questionTuple[1]['question'], QUESTION_REPLACE_GUN)\n \n tuples = game.processQuestionResponse('A', QUESTION_REPLACE_GUN, KEEP_GUN)\n self.assertEqual(tuples, [])\n\n self.assertEqual(players['A'].cardsInHand, [game.getCardByUid(75)])\n self.assertEqual(players['A'].cardsInPlay, [currentGun] + [game.getCardByUid(uid) for uid in secondInPlayUid])\n self.assertEqual(game.discardPile, [])\n self.assertEqual(game.currentCard, None)\n\n\n\n\n ''' End of turn tests. '''\n\n # Over the card limit and discards enough at once.\n def testDiscardingCardsOverLimit(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1,2,3,4,5,6,7]})\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('A', \"You need to discard 2 cards! Click on cards in your hand to discard them\", tuples))\n \n tuples = game.playerDiscardingCard('A', 3)\n self.assertEqual(getEmitTypes(tuples), {DISCARD_CLICK, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n\n tuples = game.playerDiscardingCard('A', 5)\n self.assertEqual(getEmitTypes(tuples), {END_YOUR_TURN, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n\n self.assertEqual([c.uid for c in players['A'].cardsInHand], [1,2,4,6,7])\n self.assertEqual(game.discardPile, [game.getCardByUid(3), game.getCardByUid(5)])\n\n # Over the card limit but doesn't discard enough the first time.\n def testDiscardingCardsOverLimitTwice(self):\n setDefaults()\n setPlayerCardsInHand({'A': [1,2,3,4,5,6,7]})\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('A', \"You need to discard 2 cards! Click on cards in your hand to discard them\", tuples))\n \n tuples = game.playerDiscardingCard('A', 3)\n self.assertEqual(getEmitTypes(tuples), {DISCARD_CLICK, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('A', \"You need to discard 1 card! Click on a card in your hand to discard it\", tuples))\n\n tuples = game.playerDiscardingCard('A', 5)\n self.assertEqual(getEmitTypes(tuples), {END_YOUR_TURN, UPDATE_DISCARD_PILE, UPDATE_ACTION, UPDATE_CARD_HAND})\n\n self.assertEqual([c.uid for c in players['A'].cardsInHand], [1,2,4,6,7])\n self.assertEqual(game.discardPile, [game.getCardByUid(3), game.getCardByUid(5)])\n\n # At/below the card limit, so nothing gets discarded.\n def testNotDiscardingCardsAfterTurn(self):\n for lastCardUid in [[], [5]]:\n setDefaults()\n setPlayerCardsInHand({'A': [1,2,3,4] + lastCardUid})\n\n tuples = game.startNextTurn('A')\n self.assertEqual(getEmitTypes(tuples), NEW_TURN_TUPLES)\n\n self.assertEqual([c.uid for c in players['A'].cardsInHand], [1,2,3,4] + lastCardUid)\n self.assertEqual(game.discardPile, [])\n\n # New turn gets set up correctly for each player.\n def testNewTurnSetup(self):\n setDefaults()\n expectedTurn = game.currentTurn + 1\n\n game.startNextTurn('A')\n\n self.assertEqual(game.playerOrder[0], players['B'])\n self.assertEqual(game.playerOrder[-1], players['A'])\n self.assertEqual(game.currentTurn, expectedTurn)\n\n\n\n\n ''' Drawing cards to start the turn tests. '''\n \n # Drawing for dynamite and not taking damage.\n def testDynamiteNoDamage(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n drawnCard = [c for c in game.allCards if c.suit != SPADE][0]\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"The dynamite didn't explode on you\", tuples))\n self.assertTrue(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"The dynamite didn't explode on B, so now C has it.\", tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [game.getDynamiteCard()])\n\n self.assertEqual(game.dynamiteUsername, 'C')\n self.assertEqual(game.discardPile, [drawnCard])\n self.assertNotEqual(game.drawPile[-1], drawnCard)\n self.assertEqual(game.currentCard, None)\n\n # Drawing for dynamite and taking damage.\n def testDynamiteDamage(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n drawnCard = getExplosionCard()\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite, so you've lost 3 lives\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite and lost 3 lives.\", tuples))\n\n self.assertEqual(players['B'].lives, 1)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCard, game.getDynamiteCard()])\n self.assertNotEqual(game.drawPile[-1], drawnCard)\n self.assertEqual(game.currentCard, None)\n\n # Drawing for dynamite and getting eliminated.\n def testDynamiteElimination(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid]})\n setPlayerLives({'B': 2})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n drawnCard = getExplosionCard()\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite!! You've been eliminated!\", tuples))\n for p in game.players.values():\n if p != players['B']:\n self.assertTrue(playerGotInfo(p.username, \"B was hit by the exploding dynamite and has been eliminated! There are now 6 players left.\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite and has been eliminated.\", tuples))\n\n self.assertEqual(players['B'].lives, 0)\n self.assertEqual(players['B'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCard, game.getDynamiteCard()])\n self.assertNotEqual(game.drawPile[-1], drawnCard)\n self.assertEqual(game.currentCard, None)\n\n # Drawing for dynamite and surviving with 2 Birras.\n def testDynamiteExplosionWithBirra(self):\n setDefaults()\n setPlayerCardsInHand({'B': [42, 43]})\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid]})\n setPlayerLives({'B': 2})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n drawnCard = getExplosionCard()\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite and almost died, but were saved by 2 Birras\", tuples))\n self.assertFalse(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite but stayed alive by playing 2 Birras.\", tuples))\n self.assertFalse((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].lives, 1)\n self.assertTrue(game.getCardByUid(42) not in players['B'].cardsInHand)\n self.assertTrue(game.getCardByUid(43) not in players['B'].cardsInHand)\n self.assertEqual(players['B'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCard, game.getDynamiteCard(), game.getCardByUid(42), game.getCardByUid(43)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for jail and escaping.\n def testPrigioneEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [69]})\n players['B'].jailStatus = 1\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n drawnCard = getCardsOfASuit(HEART, 1)[0]\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You drew a heart, so you got out of jail!\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew {}\".format(utils.convertCardsDrawnToString(expectedCardsDrawn)), tuples))\n self.assertTrue(playersGotUpdate(\"B drew a heart, so they get to play this turn.\", tuples))\n self.assertFalse((END_YOUR_TURN, dict(), players['B']) in tuples)\n self.assertTrue(playersGotUpdate(DREW_2_CARDS.format('B'), tuples))\n\n self.assertEqual(players['B'].jailStatus, 0)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(game.playerOrder[0], players['B'])\n\n self.assertEqual(game.discardPile, [drawnCard, game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for jail and getting skipped.\n def testPrigioneNotEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [69]})\n players['B'].jailStatus = 1\n drawnCard = getCardsOfASuit(DIAMOND, 1)[0]\n game.drawPile.append(drawnCard)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You drew a {}, so you're stuck in jail for this turn\".format(drawnCard.suit), tuples))\n self.assertTrue(playersGotUpdate(\"B drew a {}, so they're stuck in jail for this turn.\".format(drawnCard.suit), tuples))\n self.assertTrue((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].jailStatus, 1)\n self.assertEqual(players['B'].specialCards, [])\n\n self.assertEqual(game.discardPile, [drawnCard, game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for both special cards: no explosion and escaping.\n def testDynamiteNotExplodingAndJailEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n drawnCards = getCardsOfASuit(HEART, 2)\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"The dynamite didn't explode on you\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a heart, so you got out of jail\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew {}\".format(utils.convertCardsDrawnToString(expectedCardsDrawn)), tuples))\n self.assertTrue(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"The dynamite didn't explode on B, so now C has it.\", tuples))\n self.assertTrue(playersGotUpdate(\"B drew a heart, so they get to play this turn.\", tuples))\n self.assertFalse((END_YOUR_TURN, dict(), players['B']) in tuples)\n self.assertTrue(playersGotUpdate(DREW_2_CARDS.format('B'), tuples))\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [game.getDynamiteCard()])\n\n self.assertEqual(game.dynamiteUsername, 'C')\n self.assertEqual(game.discardPile, [drawnCards[1], drawnCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for both special cards: no explosion and getting skipped.\n def testDynamiteNotExplodingAndJailNotEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n drawnCards = getCardsOfASuit(CLUB, 1) + getCardsOfASuit(HEART, 1)\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"The dynamite didn't explode on you\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a {}, so you're stuck in jail for this turn\".format(drawnCards[0].suit), tuples))\n self.assertTrue(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"The dynamite didn't explode on B, so now C has it.\", tuples))\n self.assertTrue(playersGotUpdate(\"B drew a {}, so they're stuck in jail for this turn.\".format(drawnCards[0].suit), tuples))\n self.assertTrue((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].lives, 4)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [game.getDynamiteCard()])\n\n self.assertEqual(game.dynamiteUsername, 'C')\n self.assertEqual(game.discardPile, [drawnCards[1], drawnCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for both special cards: explosion and getting skipped.\n def testDynamiteExplodingAndJailNotEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n drawnCards = getCardsOfASuit(SPADE, 1) + [getExplosionCard()]\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite, so you've lost 3 lives! You're down to 1 now.\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a {}, so you're stuck in jail for this turn\".format(drawnCards[0].suit), tuples))\n self.assertFalse(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite and lost 3 lives.\", tuples))\n self.assertTrue(playersGotUpdate(\"B drew a {}, so they're stuck in jail for this turn.\".format(drawnCards[0].suit), tuples))\n self.assertTrue((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].lives, 1)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCards[1], game.getDynamiteCard(), drawnCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for both special cards: explosion and escaping.\n def testDynamiteExplodingAndJailEscaping(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n expectedCardsDrawn = game.drawPile[-2:][::-1]\n drawnCards = getCardsOfASuit(HEART, 1) + [getExplosionCard()]\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite, so you've lost 3 lives! You're down to 1 now.\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a heart, so you got out of jail\", tuples))\n self.assertFalse(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite and lost 3 lives.\", tuples))\n self.assertTrue(playersGotUpdate(\"B drew a heart, so they get to play this turn.\", tuples))\n self.assertFalse((END_YOUR_TURN, dict(), players['B']) in tuples)\n self.assertTrue(playersGotUpdate(DREW_2_CARDS.format('B'), tuples))\n\n self.assertEqual(players['B'].lives, 1)\n self.assertEqual(players['B'].cardsInHand, expectedCardsDrawn)\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCards[1], game.getDynamiteCard(), drawnCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Drawing for both special cards: explosion, staying alive with a Birra, and still drawing for Prigione.\n def testDynamiteWithBirraAndJail(self):\n setDefaults()\n setPlayerCardsInHand({'B': [42]})\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n setPlayerLives({'B': 3})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n drawnCards = getCardsOfASuit(SPADE, 1) + [getExplosionCard()]\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertTrue(playerGotInfo('B', \"You were hit by the exploding dynamite and almost died, but were saved by a Birra\", tuples))\n self.assertTrue(playerGotInfo('B', \"You drew a {}, so you're stuck in jail for this turn\".format(drawnCards[0].suit), tuples))\n self.assertFalse(playerGotInfo('C', \"The dynamite didn't explode on B, so you'll have it next turn\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite but stayed alive by playing a Birra.\", tuples))\n self.assertTrue(playersGotUpdate(\"B drew a {}, so they're stuck in jail for this turn.\".format(drawnCards[0].suit), tuples))\n self.assertTrue((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].lives, 1)\n self.assertEqual(players['B'].cardsInHand, [])\n self.assertEqual(players['B'].specialCards, [])\n self.assertEqual(players['C'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCards[1], game.getDynamiteCard(), game.getCardByUid(42), drawnCards[0], game.getCardByUid(69)])\n self.assertEqual(game.currentCard, None)\n\n # Having both special cards: eliminated by explosion and not drawing for jail at all.\n def testDynamiteEliminationAndJail(self):\n setDefaults()\n setPlayerSpecialCards({'B': [game.getDynamiteCard().uid, 69]})\n setPlayerLives({'B': 3})\n game.dynamiteUsername = 'B'\n game.dynamiteStartTurn = 1\n players['B'].jailStatus = 1\n drawnCards = getCardsOfASuit(SPADE, 1) + [getExplosionCard()]\n game.drawPile.extend(drawnCards)\n\n tuples = game.startNextTurn('A')\n self.assertEqual(countEmitTypeToRecipient(tuples, SHOW_INFO_MODAL, players['B']), 1)\n self.assertTrue(playerGotInfo('B', \"You've been eliminated\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the exploding dynamite and has been eliminated.\".format(drawnCards[0].suit), tuples))\n self.assertTrue((END_YOUR_TURN, dict(), players['B']) in tuples)\n\n self.assertEqual(players['B'].lives, 0)\n self.assertEqual(players['B'].specialCards, [])\n\n self.assertEqual(game.dynamiteUsername, \"\")\n self.assertEqual(game.discardPile, [drawnCards[1], game.getDynamiteCard(), game.getCardByUid(69)])\n self.assertEqual(game.drawPile[-1], drawnCards[0])\n self.assertEqual(game.currentCard, None)\n\n\n\n\n ''' Players getting eliminated tests. '''\n\n # Player eliminated by a regular 1-point card.\n def testPlayerEliminated(self):\n setDefaults()\n setPlayerLives({'B': 1})\n setPlayerCardsInHand({'A': [1]})\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(getEmitTypes(tuples), (NEW_TURN_TUPLES - {UPDATE_CARDS_IN_PLAY}) | {SHOW_WAITING_MODAL})\n self.assertTrue(playerGotInfo('B', \"You were hit by the Bang!! You've been eliminated! Better luck next time\", tuples))\n for player in players.values():\n if player.username != 'B':\n self.assertTrue(playerGotInfo(player.username, \"B was hit by the Bang and has been eliminated! There are now 6 players left.\", tuples))\n self.assertTrue(playersGotUpdate(\"B was hit by the Bang and has been eliminated.\", tuples))\n\n self.assertFalse(players['B'].isAlive())\n self.assertEqual(players['B'].lives, 0)\n\n self.assertEqual(getUsernameSet(game.getAlivePlayers()), {'A', 'C', 'D', 'E', 'F', 'G'})\n self.assertEqual(game.currentCard, None)\n\n # Rotating player order skips eliminated players, including a player who was just eliminated.\n def testPlayerRotationWithEliminations(self):\n setDefaults()\n setPlayerLives({'B': 0, 'C': 0, 'D': 1})\n setPlayerCardsInHand({'A': [1]})\n setPlayerCardsInPlay({'A': [80]})\n\n game.validateCardChoice('A', 1)\n\n game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'D')\n\n tuples = game.startNextTurn('A')\n for player in players.values():\n if player != players['E']:\n self.assertTrue(playerGotInfo(player.username, \"It's now E's turn.\", tuples))\n\n self.assertEqual(game.playerOrder[0], players['E'])\n self.assertEqual(getUsernameSet(game.getAlivePlayers()), {'A', 'E', 'F', 'G'})\n\n # Valid targets properly account for eliminated players.\n def testValidTargetsWithEliminatedPlayers(self):\n setDefaults()\n setPlayerLives({'B': 0, 'C': 0, 'F': 0})\n\n targets = game.getAllValidTargetsForCard(players['A'], PRIGIONE)\n self.assertEqual(getUsernameSet(targets), {'D', 'E', 'G'})\n\n # Eliminated player's cards go to the discard pile.\n def testEliminatedPlayerDiscardingCards(self):\n setDefaults()\n setPlayerLives({'B': 1})\n cardsInHandUids = [2, 40, 55, 70]\n cardsInPlayUids = [79, 67]\n setPlayerCardsInHand({'A': [1], 'B': cardsInHandUids})\n setPlayerCardsInPlay({'A': [66], 'B': cardsInPlayUids})\n setPlayerSpecialCards({'B': [69, game.getDynamiteCard().uid]})\n\n game.validateCardChoice('A', 1)\n\n game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n\n self.assertEqual({c.uid for c in game.discardPile}, set(cardsInHandUids + cardsInPlayUids + [1, 69, game.getDynamiteCard().uid]))\n self.assertEqual(game.currentCard, None)\n\n # Whoever eliminates an Outlaw draws 3 cards.\n def testEliminatingOutlawReward(self):\n setDefaults()\n setPlayerLives({'B': 1})\n setPlayerCardsInHand({'A': [1]})\n expectedCardsDrawn = game.drawPile[-3:][::-1]\n\n players['B'].role = OUTLAW\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'B')\n self.assertEqual(countEmitTypeToRecipient(tuples, UPDATE_CARD_HAND, players['A']), 2)\n self.assertTrue(playerGotInfo('A', \"You eliminated an Outlaw, so you drew 3 cards!\", tuples))\n self.assertTrue(playersGotUpdate(\"A eliminated an Outlaw, so they drew 3 cards.\", tuples))\n\n self.assertEqual(players['A'].cardsInHand, expectedCardsDrawn)\n\n # When an Outlaw loses in a Duello s/he started himself/herself, the other player shouldn't draw anything.\n def testOutlawEliminationNoRewardInDuello(self):\n setDefaults()\n setPlayerLives({'A': 1})\n setPlayerCardsInHand({'A': [55], 'B': [1]})\n players['A'].role = OUTLAW\n game.sheriffUsername = 'F'\n players['F'].role = SHERIFF\n\n game.validateCardChoice('A', 55)\n\n game.processQuestionResponse('A', QUESTION_WHO_TO_DUEL, 'B')\n\n game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n\n self.assertEqual(players['B'].cardsInHand, [])\n\n # When the Sheriff eliminates a Vice, he loses all his cards.\n def testSheriffEliminatingVice(self):\n setDefaults()\n setPlayerLives({'E': 1})\n cardsInHandUids = [1,10,20,30,40]\n cardsInPlayUids = [66, 80]\n setPlayerCardsInHand({'A': cardsInHandUids})\n setPlayerCardsInPlay({'A': cardsInPlayUids})\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'E')\n self.assertTrue(playerGotInfo('A', \"You eliminated one of your Vices, so you have to discard all your cards\", tuples))\n self.assertTrue(playersGotUpdate(\"A is the Sheriff and eliminated a Vice, so they have to discard all their cards.\", tuples))\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['A'].cardsInPlay, [])\n self.assertTrue(all([game.getCardByUid(uid) in game.discardPile for uid in cardsInHandUids]))\n self.assertTrue(all([game.getCardByUid(uid) in game.discardPile for uid in cardsInPlayUids]))\n\n # If Vulture Sam is Sheriff and eliminates a Vice, both of their cards should be in the discard pile, not held by Vulture Sam.\n def testVultureSamSheriffAndVice(self):\n setDefaults()\n setPlayerLives({'E': 1})\n setPlayerCardsInHand({'A': [1], 'E': [10,20,40,50]})\n setPlayerCardsInPlay({'A': [80], 'E': [66]})\n setPlayerCharacter('A', VULTURE_SAM)\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'E')\n self.assertTrue(playerGotInfo('A', \"You eliminated one of your Vices, so you have to discard all your cards\", tuples))\n self.assertFalse(playerGotInfo('A', \"You got all of E's cards because they were eliminated\", tuples))\n self.assertTrue(playersGotUpdate(\"A is the Sheriff and eliminated a Vice, so they have to discard all their cards.\", tuples))\n\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['A'].cardsInPlay, [])\n self.assertEqual(players['A'].cardsInHand, [])\n self.assertEqual(players['E'].cardsInPlay, [])\n self.assertEqual(players['E'].cardsInPlay, [])\n self.assertEqual(players['E'].cardsInHand, [])\n\n\n\n\n ''' Game ending scenario tests. '''\n\n # Sheriff dies and outlaws win.\n def testOutlawsWinning(self):\n setDefaults()\n setPlayerLives({'A': 1, 'F': 0, 'G': 0})\n setPlayerCardsInHand({'A': [55], 'B': [1]})\n expectedResult = \"The Outlaws have won the game!\"\n\n game.validateCardChoice('A', 55)\n\n game.processQuestionResponse('A', QUESTION_WHO_TO_DUEL, 'B')\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(game.isGameOver(), expectedResult)\n self.assertTrue(any([expectedResult in t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL]))\n\n # Sheriff dies and the renegade wins.\n def testRenegadeWinning(self):\n setDefaults()\n setPlayerLives({'A': 1, 'C': 0, 'D': 0, 'E': 0, 'F': 0, 'G': 0})\n setPlayerCardsInHand({'A': [55], 'B': [1]})\n expectedResult = \"The Renegade has won the game!\"\n\n game.validateCardChoice('A', 55)\n\n game.processQuestionResponse('A', QUESTION_WHO_TO_DUEL, 'B')\n\n tuples = game.processQuestionResponse('B', QUESTION_DUELLO_REACTION.format('A'), PLAY_A_BANG)\n self.assertEqual(game.isGameOver(), expectedResult)\n self.assertTrue(any([expectedResult in t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL]))\n\n # Sheriff/vices win.\n def testSheriffVicesWinning(self):\n setDefaults()\n setPlayerLives({'B': 0, 'C': 1, 'D': 0, 'F': 0, 'G': 0})\n setPlayerCardsInHand({'A': [1]})\n expectedResult = \"The Sheriff and his Vices have won the game!\"\n\n game.validateCardChoice('A', 1)\n\n tuples = game.processQuestionResponse('A', QUESTION_WHO_TO_SHOOT, 'C')\n self.assertEqual(game.isGameOver(), expectedResult)\n self.assertTrue(any([expectedResult in t[1]['html'] for t in tuples if t[0] == SHOW_INFO_MODAL]))\n\n\n\n\n ''' Miscellaneous tests. '''\n\n # All character options are unique and roles are distributed correctly.\n def testRolesAndCharacterOptions(self):\n setDefaults()\n game.prepareForSetup()\n \n self.assertEqual(len(game.remainingCharacters), 16)\n\n for username in players:\n game.assignNewPlayer(username)\n\n self.assertEqual(len([p for p in players.values() if p.role == SHERIFF]), 1)\n self.assertEqual(len([p for p in players.values() if p.role == VICE]), 2)\n self.assertEqual(len([p for p in players.values() if p.role == OUTLAW]), 3)\n self.assertEqual(len([p for p in players.values() if p.role == RENEGADE]), 1)\n\n for p1 in players.values():\n for p2 in players.values():\n if p1 != p2:\n self.assertEqual({character.name for character in p1.characterOptions} & {character.name for character in p2.characterOptions}, set())\n\n # All players have the correct number of cards and lives to begin with.\n def testPlayerStartingLivesAndCards(self):\n setDefaults()\n game.sheriffUsername = ''\n game.prepareForSetup()\n \n self.assertEqual(len(game.remainingCharacters), 16)\n\n for username in players:\n game.assignNewPlayer(username)\n game.assignCharacter(username, players[username].characterOptions[0].name) # Just use the first character option.\n\n for player in players.values():\n expected = (player.character.numLives + 1) if player.role == SHERIFF else player.character.numLives\n self.assertEqual(player.lives, expected)\n self.assertEqual(len(player.cardsInHand), expected)\n\n # The deck gets reshuffled after the last card is drawn.\n def testDeckReshuffle(self):\n setDefaults()\n initialOrder = list(game.drawPile)\n\n for card in game.drawPile[1:]:\n game.discardPile.append(game.drawOneCard())\n\n self.assertEqual(len(game.discardPile), 79)\n self.assertEqual(len(game.drawPile), 1)\n\n game.discardPile.append(game.drawOneCard())\n\n self.assertEqual(len(game.discardPile), 0)\n self.assertEqual(len(game.drawPile), 80)\n self.assertNotEqual(initialOrder, game.drawPile)\n\n # Tuples get consolidated correctly.\n def testTupleConsolidation(self):\n consolidatedTuples = utils.consolidateTuples([\n (SLEEP, 1, None),\n (SLEEP, 1, None),\n (UPDATE_CARD_HAND, \"oldhand\", players['A']),\n (SLEEP, 1, None),\n (SHOW_INFO_MODAL, {'html': \"duplicate\"}, players['A']),\n (SHOW_INFO_MODAL, {'html': \"duplicate\"}, players['A']),\n (UPDATE_CARD_HAND, \"newhand\", players['A']),\n (SHOW_WAITING_MODAL, \"Waiting for C\", players['A']),\n (SLEEP, 1, None)\n ])\n\n expectedConsolidatedTuples = [\n (SLEEP, 1, None),\n (SHOW_INFO_MODAL, {'html': \"duplicate\"}, players['A']),\n (UPDATE_CARD_HAND, \"newhand\", players['A']),\n (SLEEP, 1, None),\n (SHOW_WAITING_MODAL, \"Waiting for C\", players['A'])\n ]\n\n self.assertEqual(consolidatedTuples, expectedConsolidatedTuples)\n\n\nif __name__ == '__main__':\n unittest.main()"
},
{
"alpha_fraction": 0.7377148270606995,
"alphanum_fraction": 0.7407764196395874,
"avg_line_length": 47.87694549560547,
"blob_id": "02aa73f05f33783c98bb797141f34b74dc251c2b",
"content_id": "4ad2303a3db0417bb9529c524418ced25887fdb2",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 128692,
"license_type": "no_license",
"max_line_length": 232,
"num_lines": 2633,
"path": "/static/library/gameplay.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "from static.library.card import Card\nfrom static.library.constants import *\nfrom static.library.playergame import PlayerGame\nfrom static.library import utils\nfrom flask import Markup, render_template\n\nimport copy\nimport random\nimport threading\n\nclass Gameplay(dict):\n\tdef __init__(self):\n\t\tself.lobbyNumber = None\n\t\tself.players = dict() # players[username] = PlayerGame()\n\t\tself.playerOrder = list() # Current player should always be at index 0.\n\t\tself.allCards = utils.loadCards()\n\t\tself.drawPile = list(self.allCards)\n\t\tself.discardPile = list()\n\t\tself.started = False\n\t\tself.gameOver = False\n\t\tself.remainingRoles = None\n\t\tself.characters = None\n\t\tself.includeExtraCharacters = True\n\t\tself.remainingCharacters = None\n\t\tself.currentTurn = 0\n\t\tself.currentCard = None\n\t\tself.sheriffUsername = None\n\t\tself.dynamiteStartTurn = None\n\t\tself.dynamiteUsername = None\n\t\tself.drawingToStartTurn = True\n\t\tself.discardingCards = False\n\t\tself.bangedThisTurn = False\n\t\tself.emporioOptions = list()\n\t\tself.duelPair = list()\n\t\tself.updatesList = list()\n\t\tself.infoTupleDict = dict()\n\t\tself.unansweredQuestions = dict()\n\t\tself.playersWaitingFor = list()\n\t\tself.clickingOnPlayerDict = dict()\n\t\tself.clickingOnCardSet = set()\n\t\tself.specialAbilityCards = {SID_KETCHUM: None, SLAB_THE_KILLER: None, KIT_CARLSON: None, DOC_HOLLYDAY: None, CLAUS_THE_SAINT: None}\n\t\tself.specialAbilityCounter = {DOC_HOLLYDAY: 0, JOSE_DELGADO: 0, MOLLY_STARK: 0, UNCLE_WILL: 0}\n\n\t\tdict.__init__(self)\n\n\tdef __repr__(self):\n\t\treturn self.__str__()\n\n\tdef __str__(self):\n\t\treturn str(vars(self))\n\n\tdef addPlayer(self, username, sid):\n\t\tp = PlayerGame(username, sid)\n\t\t\n\t\tself.players[username] = p\n\t\tself.playerOrder.append(p)\n\n\tdef removePlayer(self, username):\n\t\tself.playerOrder.remove(self.players[username])\n\t\tdel self.players[username]\n\n\tdef prepareForSetup(self):\n\t\tself.started = True\n\t\tnum_players = len(self.players)\n\n\t\tself.characters = utils.loadCharacters(self.includeExtraCharacters)\n\t\tself.remainingCharacters = list(self.characters)\n\n\t\tif num_players == 4: self.remainingRoles = [SHERIFF, OUTLAW, OUTLAW, RENEGADE]\n\t\telif num_players == 5: self.remainingRoles = [SHERIFF, VICE, OUTLAW, OUTLAW, RENEGADE]\n\t\telif num_players == 6: self.remainingRoles = [SHERIFF, VICE, OUTLAW, OUTLAW, OUTLAW, RENEGADE]\n\t\telse: self.remainingRoles = [SHERIFF, VICE, VICE, OUTLAW, OUTLAW, OUTLAW, RENEGADE]\n\n\t\trandom.shuffle(self.playerOrder)\n\t\trandom.shuffle(self.remainingCharacters)\n\t\trandom.shuffle(self.remainingRoles)\n\t\trandom.shuffle(self.drawPile)\n\n\t\tfor username in self.players:\n\t\t\tself.assignNewPlayer(username)\n\n\t\t# Make sure the sheriff starts the game.\n\t\tself.rotatePlayerOrder()\n\n\t\tutils.logGameplay(\"Successfully prepared for setup.\")\n\n\t\treturn [(START_GAME, dict(), p) for p in self.players.values()]\n\n\tdef assignNewPlayer(self, username):\n\t\tplayer = self.players[username]\n\n\t\tif len(self.remainingRoles) == 0 or len(self.remainingCharacters) < 2:\n\t\t\tutils.logError(\"Trying to pop element from empty list for {}.\".format(player.username))\n\t\telse:\n\t\t\tplayer.role = self.remainingRoles.pop()\n\t\t\tplayer.characterOptions = [self.remainingCharacters.pop(), self.remainingCharacters.pop()]\n\t\t\tutils.logGameplay(\"Assigned {} to a role of {} with character options of {}.\".format(player.username, player.role, [c.name for c in player.characterOptions]))\n\n\t\tif player.role == SHERIFF:\n\t\t\tself.sheriffUsername = player.username\n\n\tdef assignCharacter(self, username, c):\n\t\tcharacter = self.getCharacterByName(c)\n\t\tplayer = self.players[username]\n\t\tplayer.character = character\n\t\t\n\t\t# Assign the player's initial number of lives.\n\t\tplayer.lifeLimit = character.numLives + (1 if self.sheriffUsername == username else 0)\n\t\tplayer.lives = player.lifeLimit\n\n\t\t# Deal out however many cards the player should start with.\n\t\tself.drawCardsForPlayer(player, player.lives)\n\n\t\tutils.logGameplay(\"Assigned {} to a character of {} with an initial hand of {}.\".format(player.username, c, [card.name for card in player.cardsInHand]))\n\n\tdef getCharacterByName(self, c):\n\t\treturn utils.getUniqueItem(lambda character: character.name == c, self.characters)\n\n\tdef getStartGameTuples(self, reloadingGame=False):\n\t\tutils.logGameplay(\"Initial player order will be: {}. STARTING GAME.\".format([u.username for u in self.playerOrder]))\n\n\t\treturn [(RELOAD_PLAY_PAGE, {'html': self.renderPlayPageForPlayer(p.username), 'cardInfo': p.getCardInfo(p == self.playerOrder[0])}, p) for p in self.playerOrder] \\\n\t\t\t\t + [(SLEEP, 1, None)] + [t for t in self.startNextTurn(self.getCurrentPlayerName(), reloadingGame=reloadingGame) if t[0] != SLEEP]\n\n\tdef getPlayerReloadingTuples(self, username, gameOver=False):\n\t\tplayer = self.players[username]\n\t\temitTuples = []\n\n\t\temitTuples.append((RELOAD_PLAY_PAGE, {'html': self.renderPlayPageForPlayer(username), 'cardInfo': player.getCardInfo(player == self.playerOrder[0])}, player))\n\t\temitTuples.append((SLEEP, 1, None))\n\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\temitTuples.append(utils.createCardsInPlayTuple(player))\n\t\temitTuples += [utils.createUpdateTupleForPlayer(update, player) for update in self.updatesList]\n\n\t\tif not gameOver:\n\t\t\tif username in self.unansweredQuestions:\n\t\t\t\tquestionTup = self.unansweredQuestions[username]\n\t\t\t\temitTuples += [utils.createQuestionTuple(player, questionTup[0], questionTup[1], cardsDrawn=questionTup[2])]\n\t\t\telif username in self.clickingOnPlayerDict:\n\t\t\t\tclickType, lastCardUid = self.clickingOnPlayerDict[username]\n\t\t\t\temitTuples.append(utils.createClickOnPlayersTuple(player, clickType, lastCardUid=lastCardUid))\n\t\t\telif username in self.clickingOnCardSet:\n\t\t\t\tif player.character.name in [SID_KETCHUM, DOC_HOLLYDAY]:\n\t\t\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\t\t\t\telif player.character.name == JOSE_DELGADO:\n\t\t\t\t\temitTuples.extend(utils.createAbilityCardClickTuples(player, JOSE_DELGADO_CLICK))\n\t\t\t\telif player.character.name == UNCLE_WILL:\n\t\t\t\t\temitTuples.extend(utils.createAbilityCardClickTuples(player, UNCLE_WILL_CLICK))\n\t\t\telif username in self.infoTupleDict:\n\t\t\t\temitTuples.append(self.infoTupleDict[username])\n\n\t\treturn emitTuples\n\n\tdef rotatePlayerOrder(self):\n\t\tself.playerOrder = self.playerOrder[1:] + self.playerOrder[:1]\n\n\t\t# During game setup, rotate until the Sheriff starts.\n\t\tif self.currentTurn == 0:\n\t\t\tif self.playerOrder[0].role != SHERIFF:\n\t\t\t\tself.rotatePlayerOrder()\n\t\t# In-game, keep rotating until a non-eliminated player starts.\n\t\telse:\n\t\t\tif not self.playerOrder[0].isAlive():\n\t\t\t\tself.rotatePlayerOrder()\n\n\tdef getCurrentPlayerName(self):\n\t\treturn self.playerOrder[0].username\n\n\tdef getTopDiscardCard(self):\n\t\treturn self.discardPile[-1] if len(self.discardPile) > 0 else None\n\n\tdef advanceTurn(self):\n\t\tif self.currentTurn > 0:\n\t\t\tself.rotatePlayerOrder()\n\t\tself.currentTurn += 1\n\t\tself.bangedThisTurn = False\n\t\tself.drawingToStartTurn = True\n\n\tdef startNextTurn(self, username, reloadingGame=False):\n\t\tif not reloadingGame:\n\t\t\tif username == None or username not in self.players:\n\t\t\t\tutils.logError(\"Unrecognized username {} passed in for starting next turn.\".format(username, self.players.keys()))\n\t\t\t\treturn []\n\t\t\telif username != self.getCurrentPlayerName():\n\t\t\t\tutils.logError(\"{} shouldn't be able to end the current turn (the current player is {}).\".format(username, self.getCurrentPlayerName()))\n\t\t\t\treturn []\n\t\t\telif self.specialAbilityCards[SID_KETCHUM] != None:\n\t\t\t\tutils.logGameplay(\"{} tried to end their turn but Sid Ketchum needs to finish discarding cards for his special ability first.\".format(username))\n\t\t\t\tsidKetchumText = \"Sid Ketchum needs\" if self.players[username].character.name != SID_KETCHUM else \"You need\"\n\t\t\t\treturn [self.createInfoTuple(\"Hold on. {} to finish discarding cards for his ability first.\".format(sidKetchumText), self.players[username])]\n\t\t\telif self.specialAbilityCards[DOC_HOLLYDAY] != None:\n\t\t\t\tutils.logGameplay(\"{} tried to end their turn but s/he needs to finish using Doc Hollyday's special ability first.\".format(username))\n\t\t\t\treturn [self.createInfoTuple(\"Finish using your ability before ending your turn.\", self.players[username])]\n\t\t\telif self.currentCard != None or not self.currentCardCanBeReset():\n\t\t\t\tutils.logGameplay(\"{} tried to end their turn but something (current card? {}) is still being processed.\".format(username, self.currentCard))\n\t\t\t\tinfoText = \"You can't end your turn \" + (\"right now.\" if self.currentCard == None else \"while the {} is still being played!\".format(self.currentCard.getDisplayName()))\n\t\t\t\treturn [self.createInfoTuple(infoText, self.players[username])]\n\n\t\temitTuples = []\n\n\t\tplayer = self.playerOrder[0]\n\t\tcardsTooMany = 0 if player.jailStatus == 1 else player.countExcessCards()\n\t\t\n\t\t# self.discardingCards will be False if the player just triggered the end of his/her turn, so have him/her discard cards as required.\n\t\tif self.currentTurn > 0 and cardsTooMany > 0:\n\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\n\t\t\tif cardsTooMany > 0:\n\t\t\t\tclickString = \"Click on cards in your hand to discard them.\" if cardsTooMany > 1 else \"Click on a card in your hand to discard it.\"\n\n\t\t\t\tif not self.discardingCards:\n\t\t\t\t\tclickString += \" Press Shift-C to cancel.\"\n\n\t\t\t\ttext = \"You need to discard {} card{}! {}\".format(cardsTooMany, \"s\" if cardsTooMany > 1 else \"\", clickString)\n\t\t\t\temitTuples.append(self.createInfoTuple(text, player))\n\n\t\t\tself.discardingCards = True\n\n\t\t# The player doesn't need to discard or is done now, so move on to the next player.\n\t\telse:\n\t\t\t# If the game isn't being reloaded, save the game state here.\n\t\t\tif not reloadingGame:\n\t\t\t\tutils.logGameplay(\"Saving the game state (lobby {}).\".format(self.lobbyNumber))\n\t\t\t\tgameCopy = copy.deepcopy(self)\n\t\t\t\tthreading.Thread(target=utils.saveGame, args=(gameCopy,)).start()\n\n\t\t\t# Otherwise, this game state is no different from what's saved, so don't bother.\n\t\t\t# Instead, reload all the updates for every player's screen.\n\t\t\telse:\n\t\t\t\tfor updateString in self.updatesList:\n\t\t\t\t\temitTuples.extend(utils.createUpdateTuples(updateString, self.players.values()))\n\n\t\t\tself.discardingCards = False\n\t\t\tself.specialAbilityCounter = {k: 0 for k in self.specialAbilityCounter} # Reset the special ability counter after each turn.\n\n\t\t\tif self.currentTurn > 0 and self.playerOrder[0].jailStatus == 0:\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} ended their turn.\".format(self.getCurrentPlayerName())))\n\t\t\t\n\t\t\tself.playerOrder[0].jailStatus = 0 # A player should never end his/her turn in jail.\n\t\t\t\n\t\t\t# Rotate to the next alive player and set up for the new turn.\n\t\t\tself.advanceTurn()\n\t\t\tutils.logGameplay(\"Starting the next turn. The new current player is {}.\".format(self.getCurrentPlayerName()))\n\n\t\t\tplayer = self.playerOrder[0]\n\t\t\temitTuples.extend(self.createUpdates(\"{} started their turn.\".format(player.username)))\n\n\t\t\tdrawTuples = self.processSpecialCardDraw(player)\n\t\t\t# If the dynamite exploded, load the player info early so that the health animation shows up above the correct player.\n\t\t\tif any([t[0] == HEALTH_ANIMATION and t[1]['healthChange'] == -3 for t in drawTuples]):\n\t\t\t\temitTuples.extend([utils.createPlayerInfoListTuple(self.playerOrder, p) for p in self.playerOrder])\n\t\t\t\temitTuples.append((SLEEP, 0.2, None))\n\n\t\t\t# If the player is:\n\t\t\t# \t- Lucky Duke and did a \"draw!\" at the start of his turn\n\t\t\t# \t- still in jail\n\t\t\t#\t- eliminated\n\t\t\t# skip/end their turn and return here.\n\t\t\tif (player.character.name == LUCKY_DUKE and len(drawTuples) > 0) or player.jailStatus == 1 or not player.isAlive():\n\t\t\t\treturn emitTuples + drawTuples\n\n\t\t\temitTuples.extend(self.getTuplesForNewTurn(drawTuples=drawTuples))\n\n\t\tutils.logGameplay(\"Returning the following tuples for the start of a new turn: {}\".format(emitTuples))\n\n\t\treturn emitTuples\n\n\tdef getTuplesForNewTurn(self, drawTuples=[]):\n\t\temitTuples = []\n\n\t\t# Generate all the tuples to update every player's screen for the new turn.\n\t\tfor p in self.playerOrder:\n\t\t\temitTuples.append(utils.createCardsInHandTuple(p, p == self.playerOrder[0]))\n\t\t\temitTuples.append(utils.createCardsInPlayTuple(p))\n\n\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\n\t\t# If there was a \"draw!\" that didn't return yet, add those tuples in here.\n\t\tif len(drawTuples) > 0:\n\t\t\temitTuples.extend(drawTuples)\n\n\t\tfor p in self.playerOrder:\n\t\t\temitTuples.extend(self.makeCardDrawModalTuples(p))\n\n\t\temitTuples.extend([utils.createPlayerInfoListTuple(self.playerOrder, p) for p in self.playerOrder])\n\n\t\treturn emitTuples\n\n\tdef cancelCurrentAction(self, username):\n\t\temitTuples = []\n\t\tplayer = self.players[username]\n\n\t\tif player != self.playerOrder[0]:\n\t\t\treturn []\n\n\t\tif (username in self.playersWaitingFor or username in self.unansweredQuestions) and \\\n\t\t\t\t(player.character.name not in self.specialAbilityCards or self.specialAbilityCards[player.character.name] == None):\n\t\t\treturn []\n\n\t\tif self.discardingCards:\n\t\t\tif \"discarded\" not in self.updatesList[-1]:\n\t\t\t\tself.discardingCards = False\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You canceled discarding.\", player))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\telse:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You've already discarded, so you can't cancel anymore.\", player))\n\t\t\n\t\telif username in self.clickingOnCardSet:\n\t\t\tif player.character.name in [SID_KETCHUM, DOC_HOLLYDAY]:\n\t\t\t\tcanCancel = self.specialAbilityCards[player.character.name] == None or len(self.specialAbilityCards[player.character.name]) == 0\n\t\t\telif player.character.name in [JOSE_DELGADO, UNCLE_WILL]:\n\t\t\t\tcanCancel = True\n\t\t\telse:\n\t\t\t\tutils.logError(\"{} is in the clickingOnCardSet but isn't one of the expected characters.\".format(player.getLogString()))\n\t\t\t\treturn []\n\n\t\t\tif canCancel:\n\t\t\t\tself.clickingOnCardSet.remove(username)\n\n\t\t\t\tif player.character.name in self.specialAbilityCards:\n\t\t\t\t\tself.specialAbilityCards[player.character.name] = None\n\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You canceled your ability.\", player))\n\t\t\telse:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"Sorry, you can't cancel in the middle of using your ability.\", player))\n\t\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\t\t\n\t\telse:\n\t\t\tif self.currentCard == None:\n\t\t\t\tutils.logError(\"{} is canceling, but isn't discarding and the current card is set to None.\".format(player.getLogString()))\n\t\t\t\treturn []\n\t\t\telif self.currentCard.uid == -1:\n\t\t\t\temitTuples = [self.createInfoTuple(\"Sorry, you can't cancel in the middle of using your ability.\", player)]\n\n\t\t\t\tif player.character.name == DOC_HOLLYDAY:\n\t\t\t\t\temitTuples.append(self.createClickOnPlayersTuple(player, DOC_HOLLYDAY_CLICK))\n\n\t\t\t# Only tell the player s/he canceled if s/he only has 1 card in hand.\n\t\t\tif len(player.cardsInHand) == 1:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You canceled your {}.\".format(self.currentCard.getDisplayName()), player))\n\t\t\t\n\t\t\tif self.currentCard.uid != -1:\n\t\t\t\tself.currentCard = None\n\n\t\t\t\tif username in self.clickingOnPlayerDict:\n\t\t\t\t\tdel self.clickingOnPlayerDict[username]\n\n\t\treturn emitTuples\n\n\tdef createUpdates(self, updateString):\n\t\tself.updatesList.append(updateString)\n\t\treturn utils.createUpdateTuples(updateString, self.players.values())\n\n\tdef createInfoTuple(self, text, player, header=None, cards=None):\n\t\tself.infoTupleDict[player.username] = utils.createInfoTuple(text, player, header, cards)\n\t\treturn self.infoTupleDict[player.username]\n\n\tdef createCardsDrawnTuple(self, player, description, cardsDrawn, startingTurn=True):\n\t\tself.infoTupleDict[player.username] = utils.createCardsDrawnTuple(player, description, cardsDrawn, startingTurn=startingTurn)\n\t\treturn self.infoTupleDict[player.username]\n\n\tdef addQuestion(self, player, question, options, cardsDrawn=None):\n\t\tif player.username in self.unansweredQuestions:\n\t\t\tutils.logError(\"{} is getting asked \\\"{}\\\" before answering \\\"{}\\\".\".format(question, self.unansweredQuestions[player.username]))\n\t\t\treturn None\n\n\t\tself.unansweredQuestions[player.username] = (question, options, cardsDrawn)\n\t\tself.playersWaitingFor.append(player.username)\n\t\treturn utils.createQuestionTuple(player, question, options, cardsDrawn=cardsDrawn)\n\n\tdef getDynamiteCard(self):\n\t\treturn utils.getUniqueItem(lambda c: c.name == DYNAMITE, self.allCards)\n\n\tdef getCardByUid(self, uid):\n\t\treturn utils.getUniqueItem(lambda c: c.uid == int(uid), self.allCards)\n\n\tdef drawOneCard(self):\n\t\tcard = self.drawPile.pop()\n\n\t\t# Reshuffle the draw pile once it's empty.\n\t\tif len(self.drawPile) == 0:\n\t\t\tutils.logGameplay(\"Reshuffling the draw pile. It will now have {} cards.\".format(len(self.discardPile)))\n\t\t\tself.drawPile = list(self.discardPile)\n\t\t\tself.discardPile = list()\n\n\t\t\tmissingCards = [c for c in self.allCards if c not in self.drawPile and all([c not in (p.cardsInHand + p.getCardsOnTable()) for p in self.getAlivePlayers()])]\n\t\t\tif len(missingCards) > 0:\n\t\t\t\tutils.logError(\"There were missing cards while reshuffling: {}. Adding them back\".format(missingCards))\n\t\t\t\tself.drawPile += missingCards\n\n\t\t\trandom.shuffle(self.drawPile)\n\n\t\treturn card\n\n\t# Useful for \"draw!\", after which cards always need to be discarded.\n\tdef drawAndDiscardOneCard(self):\n\t\tcard = self.drawOneCard()\n\t\tself.discardPile.append(card)\n\t\treturn card\n\n\tdef drawCardsForPlayer(self, player, n=1):\n\t\tcard = self.drawOneCard()\n\t\tplayer.addCardToHand(card)\n\t\tutils.logGameplay(\"Drew {} (UID: {}) into the hand of {}. The draw pile has {} cards left.\".format(card.getDeterminerString(), card.uid, player.username, len(self.drawPile)))\n\n\t\tif n > 1:\n\t\t\tself.drawCardsForPlayer(player, n-1)\n\n\tdef drawCardsForPlayerTurn(self, player, extraInfo=None):\n\t\tif player.character.name == BLACK_JACK:\n\t\t\tself.drawCardsForPlayer(player, 2)\n\t\t\tif player.cardsInHand[-1].suit in [HEART, DIAMOND]: # Black Jack gets to draw one more if the second card is a heart or diamond.\n\t\t\t\tself.drawCardsForPlayer(player)\n\t\t\t\tresult = player.cardsInHand[-3:]\n\t\t\telse:\n\t\t\t\tresult = player.cardsInHand[-2:]\n\t\t\n\t\telif player.character.name == KIT_CARLSON:\n\t\t\tresult = []\n\t\t\tfor _ in range(3):\n\t\t\t\tresult.append(self.drawOneCard())\n\t\t\n\t\telif player.character.name == JESSE_JONES: # For Jesse Jones, extraInfo will either be empty or the username of the player to draw from.\n\t\t\tif extraInfo != None:\n\t\t\t\topponent = self.players[extraInfo]\n\t\t\t\tplayer.addCardToHand(opponent.panico())\n\t\t\t\tutils.logGameplay(\"{} drew {} ({}) from the hand of {}.\".format(player.getLogString(), player.cardsInHand[-1].getDeterminerString(), player.cardsInHand[-1].uid, opponent.username))\n\t\t\t\tself.drawCardsForPlayer(player)\n\t\t\telse:\n\t\t\t\tself.drawCardsForPlayer(player, 2)\n\t\t\t\n\t\t\tresult = player.cardsInHand[-2:]\n\t\t\n\t\telif player.character.name == PEDRO_RAMIREZ: # For Pedro Ramirez, extraInfo will be non-empty if the discard pile should be used for the first card.\n\t\t\tif extraInfo != None:\n\t\t\t\tplayer.addCardToHand(self.discardPile.pop())\n\t\t\t\tself.drawCardsForPlayer(player)\n\t\t\telse:\n\t\t\t\tself.drawCardsForPlayer(player, 2)\n\t\t\t\n\t\t\tresult = player.cardsInHand[-2:]\n\n\t\telif player.character.name == BILL_NOFACE:\n\t\t\tnumCardsToDraw = 1 + (player.lifeLimit - player.lives)\n\t\t\tself.drawCardsForPlayer(player, numCardsToDraw)\n\t\t\tresult = player.cardsInHand[-numCardsToDraw:]\n\n\t\telif player.character.name == PIXIE_PETE:\n\t\t\tself.drawCardsForPlayer(player, 3)\n\t\t\tresult = player.cardsInHand[-3:]\n\n\t\telse:\n\t\t\t# Default case.\n\t\t\tself.drawCardsForPlayer(player, 2)\n\t\t\tresult = player.cardsInHand[-2:]\n\n\t\tutils.logGameplay(\"Drew {} card(s) for {}.\".format(len(result), player.username))\n\t\treturn result\n\n\tdef getDiscardTuples(self, card):\n\t\treturn utils.createDiscardTuples(card, self.players.values())\n\n\tdef discardCard(self, player, card):\n\t\tif card.uid != -1:\n\t\t\tplayer.getRidOfCard(card)\n\t\t\tself.discardPile.append(card)\n\t\t\tutils.logGameplay(\"Adding {} (UID: {}) to the discard pile.\".format(card.getDeterminerString(), card.uid))\n\n\tdef playerDiscardingCard(self, username, uid):\n\t\tplayer = self.players[username]\n\t\tcard = self.getCardByUid(uid)\n\t\temitTuples = []\n\n\t\tif uid not in {c.uid for c in player.cardsInHand + player.getCardsOnTable()}:\n\t\t\tutils.logError(\"{} is trying to discard {} (UID: {}) but doesn't have it in their possession.\".format(player.getLogString(), card.name, uid))\n\t\t\treturn []\n\n\t\tif not self.playerIsDiscardingForAbility(player):\n\t\t\tif player.countExcessCards() == 0:\n\t\t\t\tutils.logError(\"{} tried to discard a card but is already at/under the limit.\".format(player.getLogString()))\n\t\t\t\treturn []\n\n\t\t\tself.discardCard(player, card)\n\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\temitTuples.extend(self.createUpdates(\"{} discarded {}.\".format(username, card.getDeterminerString())))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\n\t\t\texcessCards = player.countExcessCards()\n\t\t\tif excessCards == 0:\n\t\t\t\tutils.logGameplay(\"{} discarded a card and now has 0 excess cards. Ending their turn.\".format(player.getLogString()))\n\t\t\t\temitTuples.extend(self.startNextTurn(player.username))\n\t\t\telse:\n\t\t\t\tutils.logGameplay(\"{} discarded a card but still has {} excess card(s). Enabling discard click again.\".format(player.getLogString(), excessCards))\n\t\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\n\t\telse:\n\t\t\temitTuples.extend(self.processPlayerDiscardingForAbility(player, card))\n\n\t\treturn emitTuples\n\n\t# Check whether the user should even have the option of playing this card right now.\n\t# If it's a targeted card, also return question modal information listing all alive opponents as choices...\n\t# ...instead of filtering here; validate target choices separately so that that information can be shown in a modal too.\n\tdef validateCardChoice(self, username, uid):\n\t\tcard = self.getCardByUid(int(uid))\n\n\t\tif card == None:\n\t\t\tutils.logError(\"Received request to play card with UID {}. UID not recognized.\".format(uid))\n\t\t\treturn []\n\t\t\n\t\telif username != self.getCurrentPlayerName():\n\t\t\tutils.logError(\"Received request to play a card from {}, but it's currently {}'s turn.\".format(username, self.getCurrentPlayerName()))\n\t\t\treturn []\n\n\t\telif self.drawingToStartTurn:\n\t\t\tutils.logError(\"{} is trying to play a card but isn't done drawing cards yet.\".format(username))\n\t\t\treturn []\n\n\t\telif self.specialAbilityCards[SID_KETCHUM] != None:\n\t\t\tutils.logGameplay(\"{} tried to play a card but Sid Ketchum needs to finish discarding cards for his special ability first.\".format(username))\n\t\t\tsidKetchumText = \"Sid Ketchum needs\" if self.players[username].character.name != SID_KETCHUM else \"You need\"\n\t\t\treturn [self.createInfoTuple(\"Hold on. {} to finish discarding cards for his ability first.\".format(), self.players[username])]\n\n\t\telif self.specialAbilityCards[DOC_HOLLYDAY] != None:\n\t\t\tutils.logGameplay(\"{} tried to play a card but s/he needs to finish using Doc Hollyday's special ability first.\".format(username))\n\t\t\treturn []\n\t\t\n\t\tutils.logServer(\"Received socket message from {} to play {} (UID: {}) (current card: {}).\".format(username, card.getDisplayName(), uid, self.currentCard))\n\n\t\tplayer = self.players[username]\n\t\temitTuples = []\n\t\ttargetName = None\n\t\taliveOpponents = self.getAliveOpponents(username)\n\n\t\tif card not in player.cardsInHand:\n\t\t\tutils.logError(\"{} tried to play {} ({}) but doesn't have it in his/her hand.\".format(username, card.getDeterminerString(), uid))\n\t\t\treturn []\n\n\t\t# If the card clicking erroneously somehow allows the player to play a card while s/he's discarding, just discard from here.\n\t\telif self.discardingCards:\n\t\t\tutils.logError(\"{} is discarding but entered card validation anyway. Discarding card {} from here.\".format(player.getLogString(), uid))\n\t\t\treturn self.playerDiscardingCard(username, uid)\n\n\t\telif self.currentCard != None or not self.currentCardCanBeReset():\n\t\t\treturn [self.createInfoTuple(\"Slow down! We're still waiting for your {} to finish.\".format(self.currentCard.getDisplayName()), player)]\n\n\t\t\n\t\tif self.isEffectiveBang(player, card.name):\n\t\t\tif self.bangedThisTurn and player.hasBangLimit():\n\t\t\t\tresponse = \"You've already played a Bang this turn!\"\n\t\t\telse:\n\t\t\t\tvalidTargets = self.getAllValidTargetsForCard(player, BANG)\n\t\t\t\tif len(validTargets) == 0:\n\t\t\t\t\tresponse = \"There's nobody in range for a Bang right now!\"\n\t\t\t\telse:\n\t\t\t\t\tresponse = OK_MSG\n\t\t\t\t\tutils.logGameplay(\"Adding player clicks for {} for Bang.\".format(username))\n\t\t\t\t\temitTuples = [self.createClickOnPlayersTuple(player, TARGETED_CARD_PLAYER_CLICK, lastCardUid=uid)]\n\n\t\telif card.name == MANCATO:\n\t\t\tresponse = \"You can't play a Mancato right now!\"\n\n\t\telif card.name in [PANICO, CAT_BALOU]:\n\t\t\tvalidTargets = self.getAllValidTargetsForCard(player, card.name)\n\t\t\tif len(validTargets) == 0:\n\t\t\t\tresponse = \"There's nobody in range for {} right now!\".format(card.getDeterminerString())\n\t\t\telse:\n\t\t\t\tresponse = OK_MSG\n\t\t\t\temitTuples = [self.createClickOnPlayersTuple(player, TARGETED_CARD_PLAYER_CLICK, lastCardUid=uid)]\n\n\t\telif card.name == DUELLO:\n\t\t\tresponse = OK_MSG\n\n\t\t\tif len(aliveOpponents) == 1: # If there's only 1 alive opponent left, automatically play the Duello against him/her.\n\t\t\t\ttargetName = aliveOpponents[0].username\n\t\t\telse:\n\t\t\t\temitTuples = [self.createClickOnPlayersTuple(player, TARGETED_CARD_PLAYER_CLICK, lastCardUid=uid)]\n\n\t\telif card.name == BIRRA:\n\t\t\tif len(self.getAlivePlayers()) == 2:\n\t\t\t\tresponse = \"You can't use Birras when it's 1-v-1!\"\n\t\t\telif player.lives == player.lifeLimit:\n\t\t\t\tresponse = ALREADY_MAX_LIVES\n\t\t\telse:\n\t\t\t\tresponse = OK_MSG\n\n\t\telif card.name == SALOON:\n\t\t\tif all([p.lives == p.lifeLimit for p in self.getAlivePlayers()]):\n\t\t\t\tresponse = \"You can't play a Saloon right now because nobody would gain a life!\"\n\t\t\telse:\n\t\t\t\tresponse = OK_MSG\n\n\t\telif card.cardtype in [BLUE_CARD, GUN_CARD]:\n\t\t\tif card.name in [c.name for c in player.cardsInPlay]:\n\t\t\t\tresponse = \"You already have {} in play!\".format(card.getDeterminerString())\n\t\t\telif card.cardtype == GUN_CARD and GUN_CARD in [c.cardtype for c in player.cardsInPlay]:\n\t\t\t\tresponse = OK_MSG\n\t\t\t\tcurrentGun = utils.getUniqueItem(lambda c: c.cardtype == GUN_CARD, player.cardsInPlay)\n\t\t\t\temitTuples = [self.addQuestion(player, QUESTION_REPLACE_GUN, [REPLACE_GUN.format(currentGun.getDisplayName(), card.getDisplayName()), NEVER_MIND])]\n\t\t\telif len(player.cardsInPlay) == 2:\n\t\t\t\tresponse = OK_MSG\n\t\t\t\temitTuples = [self.addQuestion(player, QUESTION_IN_PLAY, [\"Replace the {}\".format(c.getQuestionString()) for c in player.cardsInPlay] + [NEVER_MIND])]\n\t\t\telse:\n\t\t\t\tresponse = OK_MSG\n\n\t\telif card.name == PRIGIONE:\n\t\t\tvalidTargets = self.getAllValidTargetsForCard(player, PRIGIONE)\n\t\t\tif len(validTargets) > 0:\n\t\t\t\tresponse = OK_MSG\n\t\t\t\temitTuples = [self.createClickOnPlayersTuple(player, TARGETED_CARD_PLAYER_CLICK, lastCardUid=uid)]\n\n\t\t\telse:\n\t\t\t\tresponse = \"You can't jail anyone right now!\"\n\n\t\telse: # Any cards not listed should always default to OK and with no question to ask.\n\t\t\tresponse = OK_MSG\n\t\t\n\t\tutils.logGameplay(\"Response for {} playing {} right now: \\\"{}\\\".\".format(username, card.getDeterminerString(), response))\n\n\t\tif response == OK_MSG:\n\t\t\tself.currentCard = card\n\n\t\t\tif len(emitTuples) == 0: # If there are no messages/questions to emit, the card can just be played without any more processing.\n\t\t\t\treturn self.playCurrentCard(player, targetName)\n\t\t\telse:\n\t\t\t\treturn emitTuples\n\n\t\telse:\n\t\t\treturn [self.createInfoTuple(response, player, header=\"Invalid Card\")]\n\n\t# Function to process what happens next when a card is actually put down and played (given a valid target, if applicable).\n\tdef playCurrentCard(self, player, targetName=None):\n\t\temitTuples = []\n\t\tcard = self.currentCard\n\n\t\tif self.currentCard == None:\n\t\t\tutils.logError(\"{} is trying to play the current card, but the current card is None.\".format(player.username))\n\t\t\treturn []\n\n\t\tutils.logGameplay(\"{} playing {}{}.\".format(player.username, card.getDeterminerString(), \" against {}\".format(targetName) if targetName else \"\"))\n\n\t\t# If the card isn't a blue card, it should go on top of the discard pile after being played.\n\t\tif card.cardtype == REGULAR_CARD:\n\t\t\tself.discardCard(player, card)\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\n\t\t# Otherwise, the player needs to get rid of it from their hand, but it won't go on the discard pile yet.\n\t\telse:\n\t\t\tplayer.getRidOfCard(card)\n\n\t\t# Make sure the card is removed from the player's hand in the UI.\n\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\n\t\t# Handle Suzy Lafayette's ability for when she's the current player.\n\t\t# The exception is a duel - in that case, the card shouldn't be drawn until after the duel ends.\n\t\tif card.name != DUELLO and player.character.name == SUZY_LAFAYETTE:\n\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(player))\n\n\t\t# Checking that these are valid moves has already been done in the validateCardChoice and validateTargetChoice methods.\n\t\tif targetName == None:\n\t\t\tif card.cardtype in [BLUE_CARD, GUN_CARD]:\n\t\t\t\tplayer.cardsInPlay.append(card)\n\t\t\t\temitTuples.append(utils.createCardsInPlayTuple(player))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} put {} in play.\".format(player.username, card.getDeterminerString())))\n\n\t\t\t\t# Take away all other cards of this type if the player is Johnny Kisch.\n\t\t\t\tif player.character.name == JOHNNY_KISCH:\n\t\t\t\t\temitTuples.extend(self.processJohnnyKischAbility(player, card))\n\n\t\t\telif card.name == DYNAMITE:\n\t\t\t\tplayer.specialCards.append(card)\n\t\t\t\tself.dynamiteUsername = player.username\n\t\t\t\tself.dynamiteStartTurn = self.currentTurn + 1\n\n\t\t\t\ttext = \"{} played the dynamite!\".format(player.username)\n\t\t\t\temitTuples.extend([self.createInfoTuple(text, p) for p in self.getAliveOpponents(player.username)])\n\t\t\t\temitTuples.extend(self.createUpdates(text))\n\n\t\t\telif card.name == BIRRA:\n\t\t\t\tplayer.gainOneLife()\n\t\t\t\tupdateString = \"{} played a Birra and now has {} lives.\".format(player.username, player.lives)\n\t\t\t\tlivesGained = 1\n\n\t\t\t\tif player.character.name == TEQUILA_JOE and player.lives < player.lifeLimit:\n\t\t\t\t\tplayer.gainOneLife()\n\t\t\t\t\tupdateString = \"{} played a Birra and gained 2 lives using Tequila Joe's ability.\".format(player.username)\n\t\t\t\t\tlivesGained = 2\n\n\t\t\t\temitTuples.extend(self.createUpdates(updateString))\n\t\t\t\temitTuples.extend(utils.createHealthAnimationTuples(player.username, livesGained, self.playerOrder))\n\n\t\t\tif card.name == SALOON:\n\t\t\t\tfor p in self.getAlivePlayers():\n\t\t\t\t\tif p.lives != p.lifeLimit:\n\t\t\t\t\t\temitTuples.extend(utils.createHealthAnimationTuples(p.username, 1, self.playerOrder))\n\t\t\t\t\t\n\t\t\t\t\tp.gainOneLife() # Will automatically limit the player to his/her maximum lives.\n\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played a Saloon.\".format(player.username)))\n\n\t\t\telif card.name in [DILIGENZA, WELLS_FARGO]:\n\t\t\t\tnumCards = 3 if card.name == WELLS_FARGO else 2\n\t\t\t\tself.drawCardsForPlayer(player, numCards)\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played {} and drew {} cards.\".format(player.username, card.getDeterminerString(), numCards)))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, \"You drew {} cards for {}:\".format(numCards, card.getDisplayName()), player.cardsInHand[-numCards:], startingTurn=False))\n\n\t\t\telif card.name == EMPORIO:\n\t\t\t\temitTuples.extend(self.setupEmporio(player))\n\n\t\t\telif card.name in [GATLING, INDIANS]:\n\t\t\t\temitTuples.extend(self.processBangGatlingIndians(player, card.name))\n\n\t\telse:\n\t\t\ttarget = self.players[targetName]\n\n\t\t\tif self.isEffectiveBang(player, card.name):\n\t\t\t\temitTuples.extend(self.processBangGatlingIndians(player, BANG, target))\n\n\t\t\telif card.name in [PANICO, CAT_BALOU]:\n\t\t\t\temitTuples.extend(self.processPanicoCatBalou(player, target, card.name))\n\n\t\t\telif card.name == DUELLO:\n\t\t\t\tself.duelPair = [player, target]\n\t\t\t\t\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played a Duello against {}.\".format(player.username, targetName)))\n\n\t\t\t\t# Only add the waiting tuple if the player has any cards in his/her hand.\n\t\t\t\tif len(target.cardsInHand) > 0:\n\t\t\t\t\temitTuples.append(utils.createWaitingModalTuple(player, WAITING_DUELLO_REACTION.format(target.username)))\n\n\t\t\t\t# Automatically count the Duello as a win if the target doesn't have any Bangs.\n\t\t\t\tif len(target.getCardTypeFromHand(BANG)) == 0:\n\t\t\t\t\tif len(target.cardsInHand) > 0:\n\t\t\t\t\t\temitTuples.append((SLEEP, AUTOMATIC_SLEEP_DURATION, None))\n\n\t\t\t\t\temitTuples.extend(self.processDuelloResponse(target, LOSE_A_LIFE))\n\t\t\t\t\n\t\t\t\t# Otherwise, ask how s/he wants to react.\n\t\t\t\telse:\n\t\t\t\t\temitTuples.append(self.addQuestion(target, QUESTION_DUELLO_REACTION.format(player.username), [PLAY_A_BANG, LOSE_A_LIFE]))\n\n\t\t\telif card.name == PRIGIONE:\n\t\t\t\ttarget.jailStatus = 1\n\t\t\t\ttarget.specialCards.append(card)\n\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} just put you in jail!\".format(player.username), target))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You've put {} in jail.\".format(target.username), player))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} put {} in jail.\".format(player.username, target.username)))\n\n\t\tif self.currentCardCanBeReset():\n\t\t\tself.currentCard = None\n\n\t\tif self.gameOver:\n\t\t\temitTuples = [t for t in emitTuples if t[0] != SLEEP] # Don't include any SLEEPs once the game is over.\n\n\t\treturn emitTuples\n\n\tdef getAllValidTargetsForCard(self, player, cardName):\n\t\tif self.isEffectiveBang(player, cardName):\n\t\t\tvalidTargets = [target for target in self.getAliveOpponents(player.username) if self.targetIsInRange(player, target)] \n\t\t\n\t\telif cardName == PANICO:\n\t\t\tvalidTargets = [target for target in self.getAliveOpponents(player.username) if self.targetIsInRange(player, target, bang=False) and len(target.cardsInHand + target.getCardsOnTable()) >= 1] \n\n\t\telif cardName == CAT_BALOU:\n\t\t\tvalidTargets = [target for target in self.getAliveOpponents(player.username) if len(target.cardsInHand) + len(target.getCardsOnTable()) >= 1] \n\n\t\telif cardName == PRIGIONE:\n\t\t\tvalidTargets = [target for target in self.getAliveOpponents(player.username) if target.role != SHERIFF and target.jailStatus == 0]\n\n\t\telse:\n\t\t\tutils.logError(\"Shouldn't be attempting to get valid targets for {}.\".format(cardName))\n\t\t\treturn []\n\n\t\tutils.logGameplay(\"The valid targets for {} for {} are {}\".format(player.username, cardName, [t.username for t in validTargets]))\n\t\treturn validTargets\n\n\tdef validateTargetChoice(self, player, target, card=None): # Check whether this specific target is valid for the given user.\n\t\tif card == None:\n\t\t\tcard = self.currentCard\n\n\t\tutils.logGameplay(\"Checking whether {} playing {}{} is valid.\".format(player.username, card.getDeterminerString(), \" against {}\".format(target.username) if target.username else \"\"))\n\n\t\tif not target.isAlive():\n\t\t\tutils.logGameplay(\"{} tried to play {} against {}, who is already eliminated.\".format(player.getLogString(), card.getDeterminerString(), target.getLogString()))\n\t\t\tresult = \"{} isn't in the game anymore!\".format(target.username)\n\n\t\telif card.suit == DIAMOND and target.character.name == APACHE_KID:\n\t\t\tresult = \"Cards of Diamonds have no effect against Apache Kid!\"\n\n\t\telif self.isEffectiveBang(player, card.name):\n\t\t\tresult = self.targetIsInRange(player, target)\n\t\t\tutils.logGameplay(\"Result for whether {} is in range of {} for a Bang: {}\".format(target.username, player.username, result))\n\t\t\tif result:\n\t\t\t\tresult = OK_MSG\n\t\t\telse:\n\t\t\t\tresult = \"{} is out of range for a Bang.\".format(target.username)\n\n\t\telif card.name == PANICO:\n\t\t\tutils.logGameplay(\"Result for whether {} is in range of {} for a Bang: {}\".format(target.username, player.username, self.targetIsInRange(player, target, bang=False)))\n\t\t\tif self.targetIsInRange(player, target, bang=False):\n\t\t\t\tif len(target.cardsInHand + target.getCardsOnTable()) == 0:\n\t\t\t\t\tresult = \"{} has no cards to steal!\".format(target.username)\n\t\t\t\telse:\n\t\t\t\t\tresult = OK_MSG\n\t\t\telse:\n\t\t\t\tresult = \"{} is out of range for a Panico.\".format(target.username)\n\n\t\telif card.name == CAT_BALOU:\n\t\t\tresult = OK_MSG if len(target.cardsInHand + target.getCardsOnTable()) > 0 else \"{} has no cards to discard!\".format(target.username)\n\n\t\telif card.name == PRIGIONE:\n\t\t\tif target in self.getAllValidTargetsForCard(player, PRIGIONE):\n\t\t\t\tresult = OK_MSG\n\t\t\telif target.role == SHERIFF:\n\t\t\t\tresult = \"You can't jail the sheriff!\"\n\t\t\telif target.jailStatus == 1:\n\t\t\t\tresult = \"{} is already in jail!\".format(target.username)\n\n\t\telse: # Any cards not listed should always default to OK.\n\t\t\tresult = OK_MSG\n\n\t\tutils.logGameplay(\"Return message for {} playing {}{}: \\\"{}\\\".\".format(player.username, card.getDeterminerString(), \" against {}\".format(target.username) if target.username else \"\", result))\n\t\t\n\t\treturn result\n\n\tdef targetIsInRange(self, player, target, bang=True):\n\t\teffectiveDistance = self.calculateEffectiveDistance(player, target)\n\t\treturn effectiveDistance <= (player.getGunRange() if bang else 1)\n\n\t# Get the effective distance between 2 players after factoring in eliminated opponents, scopes, and mustangs.\n\tdef calculateEffectiveDistance(self, player, target):\n\t\ttargetIndex = self.getAlivePlayers().index(target)\n\t\tbaseDistance = min(targetIndex, len(self.getAlivePlayers()) - targetIndex)\n\t\tresult = baseDistance - player.getScopeDistance() + (target.getMustangDistance() if player.character.name != BELLE_STAR else 0)\n\n\t\tutils.logGameplay(\"Calculated an effective distance of {} from {} to {}.\".format(result, player.username, target.username))\n\t\treturn result\n\n\tdef advanceDynamite(self):\n\t\tcurrentPlayer, nextPlayer = self.getAlivePlayers()[:2]\n\t\tutils.logGameplay(\"Advancing the dynamite from {} to {}.\".format(currentPlayer.username, nextPlayer.username))\n\n\t\tself.dynamiteUsername = self.getAlivePlayers()[1].username\n\t\tdynamiteCard = self.getDynamiteCard()\n\t\tcurrentPlayer.getRidOfCard(dynamiteCard)\n\t\tnextPlayer.specialCards.append(dynamiteCard)\n\n\t\treturn nextPlayer\n\n\tdef isEffectiveBang(self, player, cardName):\n\t\tisBang = cardName == BANG or (player != None and player.character.name == CALAMITY_JANET and cardName == MANCATO)\n\t\tutils.logGameplay(\"Checking effective Bang: {} and {} -> {}\".format(player, cardName, isBang))\n\t\treturn isBang\n\n\tdef makeCardDrawModalTuples(self, player):\n\t\topponents = [p for p in self.playerOrder[1:]]\n\t\temitTuples = []\n\n\t\t# For the player whose turn it currently is.\n\t\tif player == self.playerOrder[0]:\n\n\t\t\t# If the character isn't Jesse Jones/Kit Carlson/Pedro Ramirez, you can always just draw from the deck.\n\t\t\tif player.character.name not in [JESSE_JONES, KIT_CARLSON, PEDRO_RAMIREZ, PAT_BRENNAN, CLAUS_THE_SAINT]:\n\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\tdescription = \"You drew {}.\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\tself.drawingToStartTurn = False\n\n\t\t\t\tif player.character.name == BLACK_JACK:\n\t\t\t\t\tif len(cardsDrawn) == 3:\n\t\t\t\t\t\tdescription = \"You drew 3 cards because the 2nd one is a {}.\".format(cardsDrawn[1].suit)\n\t\t\t\t\tupdateString = \"{} drew {} cards. The second card was {}.\".format(player.username, len(cardsDrawn), cardsDrawn[1].getDeterminerString())\n\t\t\t\telif player.character.name == PIXIE_PETE:\n\t\t\t\t\tupdateString = \"{} drew 3 cards from the deck.\".format(player.username)\n\t\t\t\telif player.character.name != BILL_NOFACE:\n\t\t\t\t\tupdateString = DREW_2_CARDS.format(player.username)\n\t\t\t\telse:\n\t\t\t\t\tupdateString = DREW_2_CARDS.format(player.username)\n\t\t\t\t\tif len(cardsDrawn) == 1:\n\t\t\t\t\t\tupdateString = updateString.replace(\"2 cards\", \"1 card\")\n\t\t\t\t\telse:\n\t\t\t\t\t\tupdateString = updateString.replace(\"2 cards\", \"{} cards\".format(len(cardsDrawn)))\n\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\temitTuples.extend(self.createUpdates(updateString))\n\n\t\t\telse:\n\t\t\t\tif player.character.name == JESSE_JONES:\n\t\t\t\t\t# Jesse Jones can only use her special ability if anyone has cards to draw from.\n\t\t\t\t\tplayersToDrawFrom = self.getPlayersWithCardsInHand(player.username)\n\t\t\t\t\tif len(playersToDrawFrom) == 0:\n\t\t\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\t\t\tdescription = \"You drew {} from the deck (nobody has cards to draw from).\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\t\t\tself.drawingToStartTurn = False\n\n\t\t\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(player.username)))\n\n\t\t\t\t\telse:\n\t\t\t\t\t\treturn [self.addQuestion(player, QUESTION_JESSE_JONES, [FROM_ANOTHER_PLAYER, FROM_THE_DECK])]\n\n\t\t\t\telif player.character.name == KIT_CARLSON:\n\t\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\t\tself.specialAbilityCards[KIT_CARLSON] = list(cardsDrawn)\n\t\t\t\t\tkitTuple = utils.createKitCarlsonTuple(player, cardsDrawn)\n\t\t\t\t\tself.infoTupleDict[player.username] = kitTuple\n\t\t\t\t\treturn [kitTuple]\n\t\t\t\t\n\t\t\t\telif player.character.name == PEDRO_RAMIREZ:\n\t\t\t\t\t# Pedro Ramirez can only use his special ability if there are any cards in the discard pile.\n\t\t\t\t\tif len(self.discardPile) == 0:\n\t\t\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\t\t\tdescription = \"You drew {} from the deck (the discard pile is empty right now).\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\t\t\t\n\t\t\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(player.username)))\n\n\t\t\t\t\telse:\n\t\t\t\t\t\treturn [self.addQuestion(player, QUESTION_PEDRO_RAMIREZ, [FROM_DISCARD, FROM_THE_DECK])]\n\n\t\t\t\telif player.character.name == PAT_BRENNAN:\n\t\t\t\t\t# Pat Brennan can only use his special ability if anyone has any in-play cards.\n\t\t\t\t\tif len(self.getPlayersWithCardsInPlay(player.username)) == 0:\n\t\t\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\t\t\tdescription = \"You drew {} from the deck (no one has any in-play cards right now).\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\t\t\t\n\t\t\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(player.username)))\n\n\t\t\t\t\telse:\n\t\t\t\t\t\treturn [self.addQuestion(player, QUESTION_PAT_BRENNAN, [FROM_IN_PLAY, FROM_THE_DECK])]\n\n\t\t\t\telif player.character.name == CLAUS_THE_SAINT:\n\t\t\t\t\t# Get two card options for Claus The Saint and one for every other non-eliminated player.\n\t\t\t\t\tself.specialAbilityCards[CLAUS_THE_SAINT] = list()\n\t\t\t\t\tfor _ in range(len(self.getAlivePlayers()) + 1):\n\t\t\t\t\t\tself.specialAbilityCards[CLAUS_THE_SAINT].append(self.drawOneCard())\n\t\t\t\t\t\n\t\t\t\t\tif len({c.name for c in self.specialAbilityCards[CLAUS_THE_SAINT]}) > 1:\n\t\t\t\t\t\tutils.logGameplay(\"Initial options for Claus the Saint's ability: {}\".format([(c.name, c.uid) for c in self.specialAbilityCards[CLAUS_THE_SAINT]]))\n\t\t\t\t\t\tself.playersWaitingFor.append(player.username)\n\n\t\t\t\t\t\tclausTheSaintTuple = utils.createClausTheSaintTuple(player, \"Click on the first card you want to keep for yourself:\", self.specialAbilityCards[CLAUS_THE_SAINT])\n\t\t\t\t\t\tutils.logGameplay(\"Initial tuple for Claus the Saint: {}\".format(clausTheSaintTuple))\n\t\t\t\t\t\tself.infoTupleDict[player.username] = clausTheSaintTuple\n\t\t\t\t\t\temitTuples.append(clausTheSaintTuple)\n\n\t\t\t\t\telse:\n\t\t\t\t\t\tutils.logGameplay(\"All initial options for Claus The Saint's ability are the same. Distributing cards to players automatically.\")\n\t\t\t\t\t\temitTuples.extend(self.processClausTheSaintCardSelection(player.username, self.specialAbilityCards[CLAUS_THE_SAINT][-1].uid))\n\n\t\t\t\t\treturn emitTuples\n\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\treturn emitTuples\n\n\t\t# For players who aren't currently on their turn. It's only used once so there's no utils function for this.\n\t\telse:\n\t\t\treturn [(SHOW_INFO_MODAL, {'html': render_template('/modals/other_player_turn.html', turn=self.getCurrentPlayerName())}, player)]\n\n\tdef processQuestionResponse(self, username, question, answer):\n\t\tplayer = self.players[username]\n\t\tcurrentPlayer = self.playerOrder[0]\n\t\tutils.logGameplay(\"Received modal response \\\"{}\\\" from {}{}.\".format(answer, player.getLogString(), \"\" if self.currentCard == None else \" (card being played: {})\".format(self.currentCard.name)))\n\t\temitTuples = []\n\n\t\tif username not in self.unansweredQuestions:\n\t\t\tutils.logError(\"{} shouldn't be answering a question.\".format(username))\n\t\t\treturn []\n\t\t\n\t\tif question != self.unansweredQuestions[username][0]:\n\t\t\tutils.logError(\"Received a response from {} for \\\"{}\\\", but their saved question is \\\"{}\\\"\".format(username, question, self.unansweredQuestions[username]))\n\t\t\treturn [] \n\n\t\t# This player has answered his/her question, so s/he is no longer holding up the game.\n\t\tdel self.unansweredQuestions[username]\n\t\tself.playersWaitingFor.remove(player.username)\n\n\t\t# If the player said \"Never mind\", just cancel the current card.\n\t\tif answer == NEVER_MIND:\n\t\t\tself.currentCard = None\n\t\t\treturn []\n\n\t\t# Handle the responses for characters who have special start-of-turn draws. \n\t\tif self.drawingToStartTurn:\n\t\t\tif player.character.name in [JESSE_JONES, PEDRO_RAMIREZ, PAT_BRENNAN]:\n\t\t\t\temitTuples = self.processAbilityQuestionResponse(username, question, answer)\n\t\t\telse:\n\t\t\t\tutils.logError(\"{} shouldn't be answering a modal question while drawing for cards to start the turn.\".format(player.getLogString()))\n\n\t\telse:\n\t\t\t# # Handle a player answering which opponent to target for the current card.\n\t\t\t# if answer in self.players:\n\t\t\t# \ttarget = self.players[answer]\n\n\t\t\t# \tif player != currentPlayer:\n\t\t\t# \t\tutils.logError(\"{} answered a question targeting someone ({}), but the current player is {}.\".format(player.getLogString(), answer, currentPlayer.getLogString()))\n\t\t\t# \t\treturn []\n\t\t\t# \tif player.username == target.username:\n\t\t\t# \t\tutils.logError(\"{} is targeting himself/herself for {}.\".format(player.getLogString(), self.currentCard.name))\n\t\t\t# \t\treturn []\n\n\t\t\t# \tresponse = self.validateTargetChoice(player, target)\n\t\t\t# \tif response == OK_MSG:\n\t\t\t# \t\treturn self.playCurrentCard(player, targetName=target.username)\n\t\t\t# \telse:\n\t\t\t# \t\treturn [self.createInfoTuple(response, player, header=\"Invalid Target\")] # Don't re-open the question modal so that the player can play another card if s/he wants to.\n\n\t\t\t# Handle Lucky Duke choosing one of 2 cards for \"draw!\".\n\t\t\tif player.character.name == LUCKY_DUKE and question == QUESTION_LUCKY_DUKE.format(self.currentCard.getDisplayName()):\n\t\t\t\temitTuples = self.processAbilityQuestionResponse(username, question, answer)\n\n\t\t\t# Handle responses for players in a Duello.\n\t\t\telif any([utils.getReverseFormat(formatString, question) != None for formatString in [QUESTION_DUELLO_REACTION, QUESTION_DUELLO_BANG_REACTION]]):\n\t\t\t\temitTuples = self.processDuelloResponse(player, answer)\n\n\t\t\t# Handle responses for players playing a Cat Balou or Panico.\n\t\t\telif any([utils.getReverseFormat(formatString, question) != None for formatString in [QUESTION_PANICO_CARDS, QUESTION_CAT_BALOU_CARDS, QUESTION_CARD_ON_TABLE]]):\n\t\t\t\tif utils.getReverseFormat(QUESTION_PANICO_CARDS, question) != None:\n\t\t\t\t\ttarget = self.players[utils.getReverseFormat(QUESTION_PANICO_CARDS, question)[0]]\n\t\t\t\telif utils.getReverseFormat(QUESTION_CAT_BALOU_CARDS, question) != None:\n\t\t\t\t\ttarget = self.players[utils.getReverseFormat(QUESTION_CAT_BALOU_CARDS, question)[0]]\n\t\t\t\telse:\n\t\t\t\t\ttargetName, cardName = utils.getReverseFormat(QUESTION_CARD_ON_TABLE, question)\n\t\t\t\t\ttarget = self.players[targetName]\n\t\t\t\t\thasCardOnTableChosen = True\n\t\t\t\t\n\t\t\t\tif answer == FROM_THEIR_HAND:\n\t\t\t\t\tselectedCard = selectedCard = target.panico()\n\t\t\t\telse:\n\t\t\t\t\tname, value, suit = utils.getCardNameValueSuitFromAnswer(answer)\n\t\t\t\t\tcardChosen = utils.getUniqueItem(lambda card: (name, suit, value) == (card.name, card.suit, card.value), target.getCardsOnTable())\n\t\t\t\t\tselectedCard = target.panico(cardChosen)\n\n\t\t\t\treturn self.processPanicoCatBalou(player, target, self.currentCard.name, selectedCard=selectedCard, fromTheTable=(answer != FROM_THEIR_HAND))\n\t\t\t\t\n\t\t\t# Handle responses for how a player wants to react to Bang/Indians/Gatling.\n\t\t\telif question in [q.format(currentPlayer.username) for q in [QUESTION_BANG_REACTION, QUESTION_INDIANS_REACTION, QUESTION_GATLING_REACTION, QUESTION_SLAB_BARILE_ONE, QUESTION_SLAB_BARILE_TWO]] \\\n\t\t\t\t\tor utils.getReverseFormat(QUESTION_BARILE_MANCATO, question) != None:\n\t\t\t\tif answer == LOSE_A_LIFE:\n\t\t\t\t\temitTuples = self.processPlayerTakingDamage(player)\n\t\t\t\t\n\t\t\t\telif answer in [PLAY_A_MANCATO, PLAY_TWO_MANCATOS, PLAY_A_BANG]:\n\t\t\t\t\trequiredCardName = MANCATO if MANCATO in answer.lower() else BANG\n\t\t\t\t\trequiredCardsInHand = player.getCardTypeFromHand(requiredCardName)\n\n\t\t\t\t\tif answer == PLAY_TWO_MANCATOS:\n\t\t\t\t\t\temitTuples = self.processSlabTheKillerAbility(player)\n\n\t\t\t\t\telse:\n\t\t\t\t\t\tself.playersWaitingFor.append(player.username)\n\n\t\t\t\t\t\t# If the player can't choose, just automatically play the required cards.\n\t\t\t\t\t\tif not self.playerCanChooseResponseCard(player, requiredCardName, requiredCardsInHand):\n\t\t\t\t\t\t\tcard = requiredCardsInHand[0]\n\t\t\t\t\t\t\temitTuples.append((SLEEP, 0.5, None))\n\t\t\t\t\t\t\temitTuples.extend(self.processBlurCardSelection(player.username, card.uid))\n\n\t\t\t\t\t\t# Otherwise, blur any applicable cards and have the player choose which ones to use.\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\temitTuples = utils.createCardBlurTuples(player, requiredCardName)\n\n\t\t\t\telse:\n\t\t\t\t\tutils.logError(\"Answer by {} for reacting to an attacking card doesn't match any expected option: {}.\".format(username, answer))\n\n\t\t\t# Handle the case where a player wants to play a new blue card but already has 2 cards in play.\n\t\t\telif question == QUESTION_IN_PLAY:\n\t\t\t\tanswer = answer.replace(\"Replace the \", \"\")\n\t\t\t\tname, value, suit = utils.getCardNameValueSuitFromAnswer(answer)\n\t\t\t\tcardToDiscard = utils.getUniqueItem(lambda card: (name, suit, value) == (card.name, card.suit, card.value), player.cardsInPlay)\n\t\t\t\temitTuples.extend(self.replaceInPlayCard(player, cardToDiscard))\n\n\t\t\t# Handle player deciding what to do when a gun is already in play.\n\t\t\telif question == QUESTION_REPLACE_GUN:\n\t\t\t\tif utils.getReverseFormat(REPLACE_GUN, answer) != None: # Meaning to replace the current gun.\n\t\t\t\t\tinPlayGun = utils.getUniqueItem(lambda card: card.cardtype == GUN_CARD, player.cardsInPlay)\n\t\t\t\t\temitTuples.extend(self.replaceInPlayCard(player, inPlayGun))\n\t\t\t\telse:\n\t\t\t\t\tself.currentCard = None\n\n\t\treturn emitTuples\n\n\tdef processPanicoCatBalou(self, player, target, cardName, selectedCard=None, fromTheTable=False):\n\t\temitTuples = []\n\n\t\tif selectedCard != None:\n\t\t\tif selectedCard.name == DYNAMITE:\n\t\t\t\tself.dynamiteUsername = \"\"\n\t\t\t\tself.dynamiteStartTurn = self.currentTurn + 1\n\t\t\telif selectedCard.name == PRIGIONE:\n\t\t\t\ttarget.jailStatus = 0\n\n\t\t\tutils.logGameplay(\"{} played a {} to make {} lose {}.\".format(player.username, cardName, target.username, selectedCard.getDeterminerString()))\n\t\t\tif cardName == PANICO:\n\t\t\t\tplayer.addCardToHand(selectedCard)\n\t\t\t\t\n\t\t\t\tstolenCardString = selectedCard.getDisplayName() if not fromTheTable else \"your {}\".format(selectedCard.getDisplayName())\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} played a Panico and stole {} from you!\".format(player.username, selectedCard.getDeterminerString()), target, cards=[selectedCard]))\n\t\t\t\t\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You stole {} from {}!\".format(selectedCard.getDeterminerString(), target.username), player, cards=[selectedCard]))\n\t\t\t\t\n\t\t\t\tstolenCardString = \"a card\" if not fromTheTable else \"their {}\".format(selectedCard.getDisplayName())\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played a Panico on {} and stole {}.\".format(player.username, target.username, stolenCardString)))\n\t\t\telse:\n\t\t\t\tself.discardPile.append(selectedCard)\n\t\t\t\temitTuples.extend(self.getDiscardTuples(selectedCard))\n\n\t\t\t\tdiscardCardString = selectedCard.getDeterminerString() if not fromTheTable else \"your {}\".format(selectedCard.getDisplayName())\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} played a Cat Balou and made you discard {}!\".format(player.username, discardCardString), target, cards=[selectedCard]))\n\n\t\t\t\tdiscardCardString = selectedCard.getDeterminerString() if not fromTheTable else \"{} {}\".format(\"their\" if selectedCard.name != DYNAMITE else \"the\", selectedCard.getDisplayName())\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You forced {} to discard {}!\".format(target.username, discardCardString), player, cards=[selectedCard]))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played a Cat Balou on {}, who had to discard {}.\".format(player.username, target.username, discardCardString)))\n\t\t\t\n\t\t\tself.currentCard = None\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\temitTuples.append(utils.createCardsInPlayTuple(target))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(target, False))\n\n\t\t\tif target.character.name == SUZY_LAFAYETTE:\n\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(target))\n\n\t\telse:\n\t\t\tif len(target.cardsInHand) > 0 and len(target.getCardsOnTable()) == 0: # Have to steal from the hand.\n\t\t\t\tselectedCard = target.panico()\n\t\t\t\temitTuples = self.processPanicoCatBalou(player, target, cardName, selectedCard=selectedCard, fromTheTable=False)\n\t\t\telif len(target.getCardsOnTable()) == 1 and len(target.cardsInHand) == 0: # Have to steal the player's only card on the table.\n\t\t\t\tselectedCard = target.panico(target.getCardsOnTable()[0])\n\t\t\t\temitTuples = self.processPanicoCatBalou(player, target, cardName, selectedCard=selectedCard, fromTheTable=True)\n\t\t\telif len(target.getCardsOnTable()) >= 2 and len(target.cardsInHand) == 0: # Have to steal from what's on the table.\n\t\t\t\toptions = [c.getQuestionString() for c in target.getCardsOnTable()]\n\t\t\t\temitTuples = [self.addQuestion(player, QUESTION_CARD_ON_TABLE.format(target.username, utils.convertRawNameToDisplay(cardName)), options)]\n\t\t\telse:\n\t\t\t\tquestion = QUESTION_PANICO_CARDS if cardName == PANICO else QUESTION_CAT_BALOU_CARDS\n\t\t\t\toptions = [FROM_THEIR_HAND] + [c.getQuestionString() for c in target.getCardsOnTable()]\n\t\t\t\temitTuples = [self.addQuestion(player, question.format(target.username), options)]\n\n\t\treturn emitTuples\n\n\tdef processDuelloResponse(self, player, answer=None, card=None):\n\t\temitTuples = []\n\n\t\tattacker = [p for p in self.duelPair if p != player][0]\n\n\t\tif card != None: # A card will be passed in if we've already gotten a response about which card to play (or if there's only 1 option).\n\t\t\tself.discardCard(player, card)\n\t\t\teffectiveDisplayName = \"Bang\" if (player.character.name != CALAMITY_JANET or card.name != MANCATO) else MANCATO_AS_BANG\n\t\t\temitTuples = self.createUpdates(\"{} responded by playing a {}.\".format(player.username, effectiveDisplayName))\n\t\t\temitTuples.extend(self.getDiscardTuples(card))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\n\t\t\t# Only add the waiting tuple if the attacker has any cards in his/her hand.\n\t\t\tif len(attacker.cardsInHand) > 0:\n\t\t\t\temitTuples.append(utils.createWaitingModalTuple(player, WAITING_DUELLO_REACTION.format(attacker.username)))\n\n\t\t\tif len(attacker.getCardTypeFromHand(BANG)) > 0:\n\t\t\t\temitTuples.append(self.addQuestion(attacker, QUESTION_DUELLO_BANG_REACTION.format(player.username), [PLAY_A_BANG, LOSE_A_LIFE]))\n\t\t\t\n\t\t\t# Automatically take the hit if the next player doesn't have any Bangs to respond with.\n\t\t\telse:\n\t\t\t\tif len(attacker.cardsInHand) > 0:\n\t\t\t\t\temitTuples.append((SLEEP, AUTOMATIC_SLEEP_DURATION, None))\n\n\t\t\t\temitTuples.extend(self.processPlayerTakingDamage(attacker, attacker=player))\n\n\t\t\t\tfor dueller in self.duelPair:\n\t\t\t\t\tif dueller.isAlive() and dueller.character.name in [SUZY_LAFAYETTE, MOLLY_STARK]:\n\t\t\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(dueller)) # Now that the duel is over, Suzy Lafayette/Molly Stark can use her ability.\n\n\t\t\t\tself.duelPair = list()\n\n\t\telse:\n\t\t\tif answer == LOSE_A_LIFE:\n\t\t\t\temitTuples.extend(self.processPlayerTakingDamage(player, attacker=attacker))\n\n\t\t\t\tfor dueller in self.duelPair:\n\t\t\t\t\tif dueller.isAlive() and dueller.character.name in [SUZY_LAFAYETTE, MOLLY_STARK]:\n\t\t\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(dueller)) # Now that the duel is over, Suzy Lafayette/Molly Stark can use her ability.\n\n\t\t\t\tself.duelPair = list()\n\n\t\t\telif answer == PLAY_A_BANG:\n\t\t\t\tbangsInHand = player.getCardTypeFromHand(BANG)\n\t\t\t\tif player.character.name == MOLLY_STARK:\n\t\t\t\t\tself.specialAbilityCounter[MOLLY_STARK] += 1 # Count how many Bangs Molly Stark uses because she needs to draw that many cards once the duel ends.\n\n\t\t\t\t# If the player isn't Calamity Janet, or if Calamity only has 1 effective Bang, just automatically play the card(s) for him/her.\n\t\t\t\tif player.character.name != CALAMITY_JANET or len(set([c.name for c in bangsInHand])) == 1:\n\t\t\t\t\temitTuples.extend(self.processDuelloResponse(player, card=bangsInHand[0]))\n\t\t\t\t\n\t\t\t\t# Otherwise, blur the non-Bangs/Mancatos for Calamity and have him/her choose which one to use.\n\t\t\t\telse:\n\t\t\t\t\tself.playersWaitingFor.append(player.username)\n\t\t\t\t\temitTuples = utils.createCardBlurTuples(player, BANG)\n\n\t\t\telse:\n\t\t\t\tutils.logError(\"Answer by {} for reacting to a Duello doesn't match any expected option: {}.\".format(player.username, answer))\n\n\t\treturn emitTuples\n\n\t# Function to process the effects of a player taking damage once it's definitive that s/he will do so.\n\tdef processPlayerTakingDamage(self, player, damage=1, attacker=None):\n\t\temitTuples = []\n\t\topponents = self.getAliveOpponents(player.username)\n\t\trequiredBirras = 0\n\n\t\tif attacker != None and player.username == attacker.username:\n\t\t\tutils.logError(\"{} shouldn't be able to damage himself/herself.\".format(player.getLogString()))\n\t\t\treturn []\n\n\t\tutils.logGameplay(\"Processing {} taking {} damage{}.\".format(player.getLogString(), damage, \"\" if attacker == None else \" from {}\".format(attacker.username)))\n\t\t\n\t\tfor _ in range(damage):\n\t\t\tplayer.loseOneLife()\n\n\t\tlostLivesString = \"a life\" if damage == 1 else \"{} lives\".format(damage)\n\n\t\tif self.isEffectiveBang(attacker, self.currentCard.name): cardEffectString = \"hit by {}'s Bang\".format(self.getCurrentPlayerName())\n\t\telif self.currentCard.name == INDIANS: cardEffectString = \"hit by {}'s Indians\".format(self.getCurrentPlayerName())\n\t\telif self.currentCard.name == GATLING: cardEffectString = \"hit by {}'s Gatling\".format(self.getCurrentPlayerName())\n\t\telif self.currentCard.name == DUELLO: cardEffectString = \"defeated in the Duello\"\n\t\telif self.currentCard.name == DYNAMITE: cardEffectString = \"hit by the exploding dynamite\"\n\t\telse:\n\t\t\tutils.logError(\"{} shouldn't be able to lose a life to {} being played by {}.\".format(player.getLogString(), self.currentCard.name, attacker.username if attacker != None else 'None'))\n\t\t\treturn []\n\n\t\t# Meaning the player is taking damage from dynamite.\n\t\tif damage == 3:\n\t\t\tself.discardCard(player, self.getDynamiteCard()) # The dynamite always has to get discarded when it explodes.\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getDynamiteCard()))\n\n\t\t# Meaning the player is taking damage from an attacking card.\n\t\telse:\n\t\t\tattacker = attacker if attacker != None else self.playerOrder[0]\n\n\t\t# Handle the player potentially being eliminated.\n\t\tif not player.isAlive():\n\t\t\trequiredBirras = (abs(player.lives) + 1) if player.character.name != TEQUILA_JOE else ((abs(player.lives)) // 2) + 1\n\t\t\tbirrasInHand = player.getCardTypeFromHand(BIRRA)\n\t\t\tif len(birrasInHand) < requiredBirras or len(self.getAlivePlayers()) == 1: # Without enough Birras, or if it's 1-v-1, the player is eliminated.\n\t\t\t\tplayer.lives = 0\n\t\t\t\taliveCount = len(self.getAlivePlayers())\n\t\t\t\tisGameOverResult = self.checkGameOver()\n\t\t\t\t\n\t\t\t\tupdateText = \"{} was {} and has been eliminated.\".format(player.username, cardEffectString)\n\t\t\t\temitTuples.extend(self.createUpdates(updateText))\n\t\t\t\t\n\t\t\t\t# Process the game ending.\n\t\t\t\tif isGameOverResult != None:\n\t\t\t\t\t# \"Eliminate\" every player and remove all cards now that the game is over.\n\t\t\t\t\tfor p in self.playerOrder:\n\t\t\t\t\t\tp.lives = 0\n\t\t\t\t\t\tfor c in p.cardsInHand + p.getCardsOnTable():\n\t\t\t\t\t\t\tself.discardCard(p, c)\n\n\t\t\t\t\tself.drawPile += self.discardPile\n\t\t\t\t\tself.discardPile = []\n\n\t\t\t\t\temitTuples.extend(self.createUpdates(isGameOverResult))\n\t\t\t\t\temitTuples.extend([utils.createCardsInHandTuple(p, p == self.playerOrder[0]) for p in self.playerOrder])\n\t\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\t\temitTuples.extend([utils.createGameOverTuple(p, isGameOverResult) for p in self.playerOrder])\n\n\t\t\t\t\t# Save the game's final state.\n\t\t\t\t\tutils.saveGame(self)\n\n\t\t\t\t# Otherwise, emit to everybody that the player died.\n\t\t\t\telse:\n\t\t\t\t\tdeadPlayerText = \"You were {}! You've been eliminated! Better luck next time.\".format(cardEffectString)\n\t\t\t\t\totherPlayersText = \"{} was {} and has been eliminated!\".format(player.username, cardEffectString)\n\t\t\t\t\tattackerText = otherPlayersText.replace(self.getCurrentPlayerName() + \"'s\", \"your\") if attacker != None else None\n\n\t\t\t\t\temitTuples.append(self.createInfoTuple(deadPlayerText, player, header=\"Game Over!\"))\n\t\t\t\t\tif attacker != None:\n\t\t\t\t\t\temitTuples.extend([self.createInfoTuple(otherPlayersText, p) for p in self.playerOrder if p not in [player, attacker]])\n\t\t\t\t\t\temitTuples.append(self.createInfoTuple(attackerText, attacker))\n\t\t\t\t\telse:\n\t\t\t\t\t\temitTuples.extend([self.createInfoTuple(otherPlayersText, p) for p in self.playerOrder if p != player])\n\n\t\t\t\t\tif player == self.playerOrder[0]:\n\t\t\t\t\t\temitTuples.append((END_YOUR_TURN, dict(), player))\n\n\t\t\t\t\t# Discard Dynamite first if applicable.\n\t\t\t\t\tif self.getDynamiteCard() in player.specialCards:\n\t\t\t\t\t\tself.discardCard(player, self.getDynamiteCard())\n\n\t\t\t\t\temitTuples.extend(self.processPlayerEliminatedAbilities(attacker, player))\n\t\t\t\t\tself.discardPile.extend(player.cardsInHand + player.getCardsOnTable())\n\n\t\t\t\t\tplayer.cardsInHand = []\n\t\t\t\t\tplayer.cardsInPlay = []\n\t\t\t\t\tplayer.specialCards = []\n\t\t\t\t\tplayer.jailStatus = 0\n\n\t\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\t\t\t\temitTuples.append(utils.createCardsInPlayTuple(player))\n\n\t\t\t\t\t# Handle the cases where eliminating a player has a penalty or reward.\n\t\t\t\t\tduelloException = self.currentCard.name == DUELLO and player == self.playerOrder[0] # If the instigator is an Outlaw and loses a Duel, the other player shouldn't draw anything.\n\t\t\t\t\tsheriffEliminatedVice = attacker != None and attacker.role == SHERIFF and player.role == VICE\n\t\t\t\t\tattackerEliminatedOutlaw = attacker != None and player.role == OUTLAW\n\t\t\t\t\tif not duelloException and (sheriffEliminatedVice or attackerEliminatedOutlaw):\n\t\t\t\t\t\tif sheriffEliminatedVice:\n\t\t\t\t\t\t\tfor c in attacker.cardsInPlay + attacker.cardsInHand:\n\t\t\t\t\t\t\t\tself.discardCard(attacker, c)\n\n\t\t\t\t\t\t\tinfoText = \"You eliminated one of your Vices, so you had to discard all your cards!\"\n\t\t\t\t\t\t\tupdateText = \"{} discarded all their cards for eliminating a Vice as the Sheriff.\".format(attacker.username)\n\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\tself.drawCardsForPlayer(attacker, 3)\n\n\t\t\t\t\t\t\tinfoText = \"You drew 3 cards for eliminating an Outlaw!\"\n\t\t\t\t\t\t\tupdateText = \"{} drew 3 cards for eliminating an Outlaw.\".format(attacker.username)\n\n\t\t\t\t\t\temitTuples.append(self.createInfoTuple(infoText, attacker))\n\t\t\t\t\t\temitTuples.extend(self.createUpdates(updateText))\n\t\t\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\t\t\temitTuples.append(utils.createCardsInHandTuple(attacker, attacker == self.playerOrder[0]))\n\n\t\t\telse: # With enough Birras, the player stays in the game. Play as many as necessary to bring the player back to life.\n\t\t\t\tplayer.lives = player.lives + (requiredBirras * (1 if player.character.name != TEQUILA_JOE else 2))\n\n\t\t\t\tfor birra in birrasInHand[:requiredBirras]:\n\t\t\t\t\tself.discardCard(player, birra)\n\t\t\t\t\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\n\t\t\t\tif player.character.name in [SUZY_LAFAYETTE, MOLLY_STARK]:\n\t\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(player))\n\n\t\t\t\t# Update the player's info modal and update everyone else's action screen.\n\t\t\t\tbirraString = \"a Birra\" if requiredBirras == 1 else \"{} Birras\".format(requiredBirras)\n\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You were {} and almost died, but got saved by {}!\".format(cardEffectString, birraString), player))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} was {} but stayed alive by playing {}.\".format(player.username, cardEffectString, birraString)))\n\n\t\t\t\tif attacker != None:\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"{} took the hit but stayed alive by playing {}.\".format(player.username, birraString), attacker))\n\n\t\t\t\tutils.logGameplay(\"{} played {}\".format(player.username, birraString))\n\n\t\t# Otherwise, just take the player's lives and move on.\n\t\telse:\n\t\t\ttext = \"You were {}, so you've lost {}{} You're down to {} now.\".format(cardEffectString, lostLivesString, \"!\" if \"lives\" in lostLivesString else \".\", player.lives)\n\t\t\temitTuples.append(self.createInfoTuple(text, player))\n\n\t\t\tif attacker != None:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} took the hit and is down to {} now.\".format(player.username, \"{} {}\".format(player.lives, \"lives\" if player.lives > 1 else \"life\")), attacker))\n\n\t\t\tupdateText = \"{} was {}{}.\".format(player.username, cardEffectString, \"\" if damage == 1 else \" and lost {}\".format(lostLivesString))\n\t\t\temitTuples.extend(self.createUpdates(updateText))\n\n\n\t\t# If the player is still alive and has a character ability triggered by taking damage, process that here.\n\t\tif player.isAlive():\n\t\t\tif player.character.name == BART_CASSIDY: # Bart Cassidy draws a new card for every life point he's lost.\n\t\t\t\tself.drawCardsForPlayer(player, damage)\n\n\t\t\t\tcardString = player.cardsInHand[-1].getDeterminerString() if damage == 1 else \"{} cards\".format(damage)\n\t\t\t\tutils.logGameplay(\"{} drawing {} because they lost {}\".format(player.getLogString(), cardString, lostLivesString))\n\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You drew {} because you lost {}!\".format(cardString, lostLivesString), player, cards=player.cardsInHand[-damage:]))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew {} using Bart Cassidy's ability.\".format(player.username, \"a card\" if damage == 1 else \"{} cards\".format(damage))))\n\n\t\t\telif player.character.name == EL_GRINGO and self.playerOrder[0] != player and attacker != None: # El Gringo draws a card from the player's hand anytime a player deals him damage.\n\t\t\t\tif len(attacker.cardsInHand) > 0:\n\t\t\t\t\tstolenCard = attacker.panico()\n\n\t\t\t\t\tutils.logGameplay(\"{} stealing {} from the hand of {} for dealing him damage.\".format(player.getLogString(), stolenCard, attacker.getLogString()))\n\t\t\t\t\t\n\t\t\t\t\tplayer.addCardToHand(stolenCard)\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"You stole {} from {}'s hand because they made you lose a life!\".format(stolenCard.getDeterminerString(), attacker.username), player))\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"{} stole {} from your hand because you made them lose a life!\".format(player.username, stolenCard.getDeterminerString()), attacker))\n\t\t\t\t\temitTuples.extend(self.createUpdates(\"{} stole a card from {}'s hand using El Gringo's ability.\".format(player.username, attacker.username)))\n\t\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\t\t\t\temitTuples.append(utils.createCardsInHandTuple(attacker, attacker == self.playerOrder[0]))\n\n\t\t\t\t\tif attacker.character.name == SUZY_LAFAYETTE:\n\t\t\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(attacker))\n\n\t\t\t\telse:\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"{} has no cards, so you couldn't use El Gringo's ability to steal anything.\".format(attacker.username), player))\n\n\t\tif not self.gameOver:\n\t\t\temitTuples.extend(utils.createHealthAnimationTuples(player.username, -damage, self.playerOrder))\n\t\t\tif player.isAlive() and requiredBirras > 0:\n\t\t\t\temitTuples.append((SLEEP, 0.5, None))\n\t\t\t\temitTuples.extend(utils.createHealthAnimationTuples(player.username, requiredBirras * (1 if player.character.name != TEQUILA_JOE else 2), self.playerOrder))\n\n\t\t# Only reset the current card once its effects are finished, i.e. once every player has finished reacting to everything.\n\t\tif self.currentCardCanBeReset():\n\t\t\tself.currentCard = None\n\t\t\n\t\tutils.logGameplay(\"Processed {} losing {}. Will return the following emitTuples: {}.\".format(player.username, lostLivesString, [(t[0], t[2] if len(t)==3 else 'everybody') for t in emitTuples]))\n\t\treturn emitTuples\n\n\tdef checkGameOver(self):\n\t\talivePlayers = self.getAlivePlayers()\n\t\tsheriffIsAlive = self.players[self.sheriffUsername].isAlive()\n\t\trenegadeIsAlive = any([p.role == RENEGADE for p in alivePlayers])\n\t\tnumAliveOutlaws = len([p for p in alivePlayers if p.role == OUTLAW])\n\n\t\tif not sheriffIsAlive:\n\t\t\tself.gameOver = True\n\t\t\tif renegadeIsAlive and len(alivePlayers) == 1: return \"The Renegade has won the game!\"\n\t\t\telse: return \"The Outlaws have won the game!\"\n\t\telse:\n\t\t\tif not renegadeIsAlive and numAliveOutlaws == 0:\n\t\t\t\tself.gameOver = True\n\t\t\t\tif len(self.players) == 7:\n\t\t\t\t\treturn \"The Sheriff and his Vices have won the game!\"\n\t\t\t\telif 5 <= len(self.players) <= 6:\n\t\t\t\t\treturn \"The Sheriff and Vice have won the game!\"\n\t\t\t\telse:\n\t\t\t\t\treturn \"The Sheriff has won the game!\"\n\t\t\telse:\n\t\t\t\treturn None # Indicates the game is not over.\n\n\tdef currentCardCanBeReset(self):\n\t\tcanBeReset = len(self.unansweredQuestions) == 0 and len(self.playersWaitingFor) == 0\n\n\t\tif not canBeReset:\n\t\t\tutils.logGameplay(\"Card {} can't be reset yet. {} {}\".format(self.currentCard.uid if self.currentCard != None else None, self.unansweredQuestions, self.playersWaitingFor))\n\n\t\tif canBeReset:\n\t\t\tutils.logGameplay(\"Card {} CAN be reset.\".format(self.currentCard))\n\n\t\treturn canBeReset\n\n\t# Function to handle responses for the character abilities that require a question.\n\tdef processAbilityQuestionResponse(self, username, question, answer):\n\t\temitTuples = []\n\t\tplayer = self.players[username]\n\n\t\tutils.logGameplay(\"Beginning to process ability question response for {}.\".format(player.getLogString()))\n\n\t\tif player.character.name == JESSE_JONES: # Answering the question of whether to draw from a player or the deck.\n\t\t\tif answer == FROM_ANOTHER_PLAYER:\n\t\t\t\tplayersToDrawFrom = self.getPlayersWithCardsInHand(username)\n\t\t\t\tif len(playersToDrawFrom) > 1:\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"Click on the player whose hand you want to draw from.\", player))\n\t\t\t\t\temitTuples.append(self.createClickOnPlayersTuple(player, JESSE_JONES_CLICK))\n\t\t\t\t\n\t\t\t\t# There's only 1 player Jesse Jones can draw from, so automatically draw from that player's hand.\n\t\t\t\telse:\n\t\t\t\t\temitTuples.extend(self.processJesseJonesAbility(username, playersToDrawFrom[0].username, automatic=True))\n\n\t\t\telif answer == FROM_THE_DECK:\n\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\tdescription = \"You drew {} from the deck.\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\t\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(username)))\n\n\t\telif player.character.name == PEDRO_RAMIREZ:\n\t\t\tif answer in [FROM_DISCARD, FROM_THE_DECK]:\n\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player, extraInfo=(None if answer == FROM_THE_DECK else FROM_DISCARD))\n\t\t\t\tif answer == FROM_DISCARD:\n\t\t\t\t\tdescription = \"You drew {} from the discard pile and {} from the deck.\".format(cardsDrawn[-2].getDeterminerString(), cardsDrawn[-1].getDeterminerString())\n\t\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew {} from the discard pile and 1 card from the deck.\".format(username, cardsDrawn[-2].getDeterminerString())))\n\t\t\t\telse:\n\t\t\t\t\tdescription = \"You drew {} from the deck.\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(username)))\n\n\t\t\t\tself.drawingToStartTurn = False\n\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, player.cardsInHand[-2:]))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\n\t\t\telse:\n\t\t\t\tutils.logError(\"Option of \\\"{}\\\" was selected by {}, which doesn't match any expected options.\".format(answer, player.getLogString()))\n\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\treturn []\n\n\t\telif player.character.name == PAT_BRENNAN:\n\t\t\t# For deciding what type of draw he'll have.\n\t\t\tif question == QUESTION_PAT_BRENNAN:\n\t\t\t\tif answer == FROM_THE_DECK:\n\t\t\t\t\tcardsDrawn = self.drawCardsForPlayerTurn(player)\n\t\t\t\t\tdescription = \"You drew {} from the deck.\".format(utils.convertCardsDrawnToString(cardsDrawn))\n\t\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\t\t\n\t\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(username)))\n\t\t\t\t\n\t\t\t\telse:\n\t\t\t\t\tplayersToDrawFrom = self.getPlayersWithCardsInPlay(username)\n\t\t\t\t\tif len(playersToDrawFrom) > 1:\n\t\t\t\t\t\temitTuples.append(self.createInfoTuple(\"Click on the player whose in-play cards you want to draw from.\", player))\n\t\t\t\t\t\temitTuples.append(self.createClickOnPlayersTuple(player, PAT_BRENNAN_CLICK))\n\t\t\t\t\t\n\t\t\t\t\t# There's only 1 player Pat Brennan can draw from, so automatically draw from that player's in-play cards.\n\t\t\t\t\telse:\n\t\t\t\t\t\temitTuples.extend(self.processPatBrennanAbility(player, playersToDrawFrom[0]))\n\n\t\t\t# For deciding which card to take from the other player.\n\t\t\telse:\n\t\t\t\ttargetName = utils.getReverseFormat(QUESTION_PAT_BRENNAN_CARD, question)[0]\n\t\t\t\ttarget = self.players[targetName]\n\n\t\t\t\tcardName, value, suit = utils.getCardNameValueSuitFromAnswer(answer)\n\t\t\t\tcardChosen = utils.getUniqueItem(lambda card: (cardName, value, suit) == (card.name, card.value, card.suit), target.cardsInPlay)\n\t\t\t\temitTuples.extend(self.processPatBrennanAbility(player, target, card=cardChosen))\n\n\t\telif player.character.name == LUCKY_DUKE:\n\t\t\tself.playersWaitingFor.remove(player.username)\n\n\t\t\tcardName, value, suit = utils.getCardNameValueSuitFromAnswer(answer)\n\t\t\t\n\t\t\t# Both cards get discarded, but we force the one that Lucky Duke picked to get discarded second so it's on top.\n\t\t\tif (cardName, value, suit) in [(c.name, c.value, c.suit) for c in self.drawPile[-2:]]:\n\t\t\t\tif (cardName, value, suit) == (self.drawPile[-1].name, self.drawPile[-1].value, self.drawPile[-1].suit):\n\t\t\t\t\tcardDrawn = self.drawPile[-1]\n\t\t\t\t\tself.discardPile.append(self.drawPile.pop(-2))\n\t\t\t\telse:\n\t\t\t\t\tcardDrawn = self.drawPile[-2]\n\t\t\t\t\tself.discardPile.append(self.drawPile.pop(-1))\n\n\t\t\t\tif self.currentCard.name == DYNAMITE:\n\t\t\t\t\temitTuples.extend(self.processDynamiteDraw(player))\n\n\t\t\t\t\tif player.isAlive():\n\t\t\t\t\t\tif player.jailStatus == 1:\n\t\t\t\t\t\t\tself.currentCard = player.getPrigione()\n\t\t\t\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\t\t\t\temitTuples.append((SLEEP, 0.5, None))\n\t\t\t\t\t\t\temitTuples.append(self.createLuckyDukeTuple(player))\n\t\t\t\t\t\telse:\n\t\t\t\t\t\t\temitTuples.extend(self.getTuplesForNewTurn())\n\n\t\t\t\telif self.currentCard.name == PRIGIONE:\n\t\t\t\t\temitTuples.extend(self.processPrigioneDraw(player))\n\t\t\t\t\tif player.jailStatus == 0: # Meaning the player drew and got out of jail.\n\t\t\t\t\t\temitTuples.extend(self.getTuplesForNewTurn())\n\n\t\t\t\telif self.currentCard.name in [BANG, GATLING]:\n\t\t\t\t\temitTuples.extend(self.processBarileDraw(player))\n\n\t\t\t\telse:\n\t\t\t\t\tutils.logError(\"Lucky Duke ({}) shouldn't be doing \\\"draw!\\\" when the current card is {}.\".format(player.username, self.currentCard.name))\n\n\t\t\telse:\n\t\t\t\tutils.logError(\"Lucky Duke picked a card ({}, {}) for \\\"draw!\\\" that shouldn't be an option.\".format(cardName, suit))\n\n\t\tutils.logGameplay(\"processAbilityQuestionResponse() for ({}, {}, {}) tuples: {}\".format(username, question, answer, emitTuples))\n\t\treturn emitTuples\n\n\tdef processKitCarlsonCardSelection(self, username, uid):\n\t\temitTuples = []\n\t\tplayer = self.players[username]\n\n\t\tdiscardedCard = self.getCardByUid(uid)\n\t\tself.drawPile.append(discardedCard)\n\n\t\tfor c in self.specialAbilityCards[KIT_CARLSON]:\n\t\t\tif c != discardedCard:\n\t\t\t\tplayer.addCardToHand(c)\n\n\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\temitTuples.extend(self.createUpdates(DREW_2_CARDS.format(username)))\n\n\t\tself.specialAbilityCards[KIT_CARLSON] = None\n\t\tself.drawingToStartTurn = False\n\t\t\n\t\treturn emitTuples\n\n\t# Function to process a player's choice when s/he had to pick a card from his/her hand in response to the current card.\n\tdef processBlurCardSelection(self, username, uid):\n\t\tplayer = self.players[username]\n\t\tcurrentPlayer = self.playerOrder[0]\n\t\tselectedCard = self.getCardByUid(uid)\n\t\temitTuples = []\n\n\t\tif selectedCard not in player.cardsInHand:\n\t\t\tutils.logError(\"{} played {} ({}) but doesn't have that card in his/her hand.\".format(player.getLogString(), selectedCard.getDeterminerString(), uid))\n\t\t\treturn []\n\n\t\tif self.currentCard.name != DUELLO and username == self.getCurrentPlayerName():\n\t\t\tutils.logError(\"{} played a blurred card in a non-duel even though it's currently his/her turn.\".format(username))\n\t\t\treturn []\n\n\t\tif player.character.name != ELENA_FUENTE and selectedCard.name not in [BANG, MANCATO]:\n\t\t\tutils.logError(\"{} responded to the current card ({}) by playing {}.\".format(player.getLogString(), self.currentCard.name, selectedCard.name))\n\t\t\treturn []\n\n\t\tif player.username not in self.playersWaitingFor:\n\t\t\tutils.logError(\"{} selected a blurred card but isn't in the set of players being waited for ({})\".format(player.getLogString(), self.playersWaitingFor))\n\t\t\treturn []\n\n\t\tself.playersWaitingFor.remove(player.username)\n\n\t\tif self.currentCard.name == DUELLO:\n\t\t\temitTuples = self.processDuelloResponse(player, card=selectedCard)\n\n\t\telif self.currentCard.name in [BANG, GATLING] or (currentPlayer.character.name == CALAMITY_JANET and self.currentCard.name == MANCATO):\n\t\t\tself.discardCard(player, selectedCard)\n\n\t\t\tif player.character.name in [SUZY_LAFAYETTE, MOLLY_STARK]:\n\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(player))\n\t\t\t\n\t\t\teffectiveName = utils.convertRawNameToDisplay(GATLING if self.currentCard.name == GATLING else BANG)\n\t\t\tif (currentPlayer.character.name == CALAMITY_JANET and self.currentCard.name == MANCATO):\n\t\t\t\teffectiveName = MANCATO_AS_BANG\n\t\t\t\n\t\t\tif player.character.name in [CALAMITY_JANET, ELENA_FUENTE] and selectedCard.name != MANCATO:\n\t\t\t\teffectiveReactionDisplayName = \"{} as a Mancato\".format(selectedCard.getDeterminerString())\n\t\t\telse:\n\t\t\t\teffectiveReactionDisplayName = \"a Mancato\"\n\n\t\t\tif self.specialAbilityCards[SLAB_THE_KILLER] == None:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} played {} to avoid your {}!\".format(player.username, effectiveReactionDisplayName, effectiveName), currentPlayer))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} played {} and avoided {}'s {}.\".format(player.username, effectiveReactionDisplayName, currentPlayer.username, effectiveName)))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, False))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(selectedCard))\n\t\t\t\n\t\t\t# Handle a player discarding 1 of multiple Mancatos in response to Slab the Killer here.\n\t\t\telse:\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, False))\n\t\t\t\temitTuples.extend(self.getDiscardTuples(selectedCard))\n\n\t\t\t\tself.specialAbilityCards[SLAB_THE_KILLER].append(selectedCard)\n\n\t\t\t\t# Has only discarded 1 so far.\n\t\t\t\tif len(self.specialAbilityCards[SLAB_THE_KILLER]) == 1:\n\t\t\t\t\tself.playersWaitingFor.append(player.username)\n\t\t\t\t\temitTuples.extend(utils.createCardBlurTuples(player, MANCATO, msg=CLICK_ON_CARD.format(\"second Mancato\")))\n\t\t\t\t\n\t\t\t\t# Has discarded both, so the Bang is fully avoided.\n\t\t\t\telse:\n\t\t\t\t\tif len({c.name for c in self.specialAbilityCards[SLAB_THE_KILLER]}) == 1:\n\t\t\t\t\t\teffectiveReactionDisplayName = \"2 {}s\".format(self.specialAbilityCards[SLAB_THE_KILLER][0].getDisplayName())\n\n\t\t\t\t\t\tif self.specialAbilityCards[SLAB_THE_KILLER][0].name != MANCATO:\n\t\t\t\t\t\t\teffectiveReactionDisplayName += \" (as Mancatos)\"\n\n\t\t\t\t\telse:\n\t\t\t\t\t\teffectiveReactionDisplayNameList = []\n\t\t\t\t\t\tfor c in self.specialAbilityCards[SLAB_THE_KILLER]:\n\t\t\t\t\t\t\tif c.name == MANCATO:\n\t\t\t\t\t\t\t\teffectiveReactionDisplayNameList.append(\"a Mancato\")\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\teffectiveReactionDisplayNameList.append(c.getDeterminerString() + \" (as a Mancato)\")\n\n\t\t\t\t\t\teffectiveReactionDisplayName = \" and \".join(effectiveReactionDisplayNameList)\n\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"{} played {} to avoid your Bang!\".format(player.username, effectiveReactionDisplayName), currentPlayer))\n\t\t\t\t\temitTuples.extend(self.createUpdates(\"{} played {} and avoided {}'s Bang.\".format(player.username, effectiveReactionDisplayName, currentPlayer.username)))\n\n\t\t\t\t\tself.specialAbilityCards[SLAB_THE_KILLER] = None\n\n\t\t\tif self.currentCardCanBeReset() and self.specialAbilityCards[SLAB_THE_KILLER] == None:\n\t\t\t\tself.currentCard = None\n\n\t\telif self.currentCard.name == INDIANS:\n\t\t\tself.discardCard(player, selectedCard)\n\n\t\t\tif player.character.name in [SUZY_LAFAYETTE, MOLLY_STARK]:\n\t\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(player))\n\n\t\t\teffectiveReactionDisplayName = \"Bang\" if (player.character.name != CALAMITY_JANET or selectedCard.name != MANCATO) else MANCATO_AS_BANG\n\t\t\t\n\t\t\temitTuples.append(self.createInfoTuple(\"{} played a {} to avoid your Indians!\".format(player.username, effectiveReactionDisplayName), currentPlayer))\n\t\t\temitTuples.extend(self.createUpdates(\"{} played a {} and avoided {}'s Indians.\".format(player.username, effectiveReactionDisplayName, currentPlayer.username)))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, False))\n\t\t\temitTuples.extend(self.getDiscardTuples(selectedCard))\n\n\t\t\tif self.currentCardCanBeReset():\n\t\t\t\tself.currentCard = None\n\n\t\treturn emitTuples\n\n\tdef setupEmporio(self, player, uncleWillCard=None):\n\t\temitTuples = []\n\n\t\t# Get one card option for each non-eliminated player and show all players the choices.\n\t\tself.emporioOptions = list()\n\t\tfor _ in range(len(self.getAlivePlayers())):\n\t\t\tself.emporioOptions.append(self.drawOneCard())\n\n\t\tif uncleWillCard == None:\n\t\t\tupdateText = \"{} played an Emporio!\".format(player.username)\n\t\telse:\n\t\t\tupdateText = \"{} played {} as an Emporio using Uncle Will's ability!\".format(player.username, uncleWillCard.getDeterminerString())\n\t\t\n\t\temitTuples.extend(self.createUpdates(updateText))\n\n\t\tif len({c.name for c in self.emporioOptions}) > 1:\n\t\t\tutils.logGameplay(\"Initial options for Emporio for {}: {}\".format([p.username for p in self.getAlivePlayers()], [c.uid for c in self.emporioOptions]))\n\t\t\tself.playersWaitingFor.append(player.username)\n\n\t\t\temporioTuples = utils.createEmporioTuples(self.getAlivePlayers(), self.emporioOptions, player)\n\t\t\tfor t in emporioTuples:\n\t\t\t\tself.infoTupleDict[t[2].username] = t\n\t\t\t\temitTuples.extend(emporioTuples)\n\n\t\telse:\n\t\t\tutils.logGameplay(\"All initial options for Emporio are the same. Distributing 1 card to each player automatically.\")\n\t\t\temitTuples.extend(self.processEmporioClausTheSaintAutomatic(self.getAlivePlayers()[0]))\n\n\t\treturn emitTuples\n\n\tdef processEmporioCardSelection(self, username, uid):\n\t\tutils.logGameplay(\"Received request from {} to draw UID {} for Emporio.\".format(username, uid))\n\t\tplayer = self.players[username]\n\t\tcard = self.getCardByUid(uid)\n\t\temitTuples = []\n\n\t\tif card not in self.emporioOptions:\n\t\t\tutils.logError(\"{} was selected as {}'s choice for Emporio, but the options are {}\".format(uid, username, [c.uid for c in self.emporioOptions]))\n\t\t\treturn []\n\n\t\tif player.username not in self.playersWaitingFor:\n\t\t\tutils.logError(\"{} chose a card for Emporio but isn't in the set of players waiting for ({})\".format(player.getLogString(), self.playersWaitingFor))\n\t\t\treturn []\n\n\t\tself.playersWaitingFor.remove(player.username)\n\n\t\tself.emporioOptions.remove(card)\n\t\tplayer.addCardToHand(card)\n\n\t\temitTuples = self.createUpdates(PICKED_UP_FROM_EMPORIO.format(username, card.getDeterminerString()))\n\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\n\t\tnextPlayer = self.getAlivePlayers()[self.getAlivePlayers().index(player) + 1] # Should never be possible to get an index error here.\n\t\t\n\t\tif len(self.emporioOptions) == 1:\n\t\t\tcard = self.emporioOptions.pop()\n\t\t\tnextPlayer.addCardToHand(card)\n\t\t\temitTuples.append(utils.createCardsInHandTuple(nextPlayer, nextPlayer == self.playerOrder[0]))\n\t\t\temitTuples.extend(self.createUpdates(PICKED_UP_FROM_EMPORIO.format(nextPlayer.username, card.getDeterminerString())))\n\t\t\temitTuples.append(self.createInfoTuple(\"You picked up the last Emporio card:\", nextPlayer, cards=[card]))\n\t\t\temitTuples.extend([self.createInfoTuple(\"Everyone is done picking an Emporio card.\", p) for p in self.playerOrder if p != nextPlayer])\n\n\t\t\tself.currentCard = None\n\t\t\n\t\telif len({card.name for card in self.emporioOptions}) == 1: # Every remaining card is the same, so just distribute them automatically.\n\t\t\tautomaticPlayers = self.getAlivePlayers()[(self.getAlivePlayers().index(player) + 1):]\n\t\t\temitTuples.extend([self.createInfoTuple(\"Everyone is done picking an Emporio card.\", p) for p in self.playerOrder if p not in automaticPlayers])\n\t\t\temitTuples.extend(self.processEmporioClausTheSaintAutomatic(nextPlayer))\n\t\t\n\t\telse:\n\t\t\tself.playersWaitingFor.append(nextPlayer.username)\n\t\t\t\n\t\t\temporioTuples = utils.createEmporioTuples(self.playerOrder, self.emporioOptions, nextPlayer)\n\t\t\tfor t in emporioTuples:\n\t\t\t\tself.infoTupleDict[t[2].username] = t\n\t\t\temitTuples.extend(emporioTuples)\n\n\t\treturn emitTuples\n\n\tdef processClausTheSaintCardSelection(self, username, uid):\n\t\tutils.logGameplay(\"Received request from {} to select UID {} for Claus The Saint's ability.\".format(username, uid))\n\t\tplayer = self.players[username]\n\n\t\tif player.character.name != CLAUS_THE_SAINT:\n\t\t\tutils.logError(\"{} picked a card for Claus The Saint but his/her character is {}.\".format(username, player.character.name))\n\t\t\treturn []\n\t\telif self.playerOrder[0] != player:\n\t\t\tutils.logError(\"Received card selection from {} for Claus The Saint's ability but s/he is not the current player.\".format(username))\n\t\t\treturn []\n\t\t\n\t\tcard = self.getCardByUid(uid)\n\t\temitTuples = []\n\n\t\tif card not in self.specialAbilityCards[CLAUS_THE_SAINT]:\n\t\t\tutils.logError(\"{} was selected by {} for Claus The Saint's ability, but the options are {}\".format(uid, username, [c.uid for c in self.specialAbilityCards[CLAUS_THE_SAINT]]))\n\t\t\treturn []\n\n\t\tlenRemainingOptions = len(self.specialAbilityCards[CLAUS_THE_SAINT])\n\t\tnumAlivePlayers = len(self.getAlivePlayers())\n\n\t\t# Claus has picked the first card for himself/herself.\n\t\tif lenRemainingOptions == numAlivePlayers + 1:\n\t\t\tplayer.addCardToHand(card)\n\t\t\temitTuples.extend(self.createUpdates(\"{} picked his first card using his ability.\".format(username)))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\n\t\telse:\n\t\t\t# Claus has picked the second card for himself/herself.\n\t\t\tif lenRemainingOptions == numAlivePlayers:\n\t\t\t\tplayer.addCardToHand(card)\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} picked his second card using his ability.\".format(username)))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\n\t\t\t# Claus has picked a card for another player.\n\t\t\telse:\n\t\t\t\tplayerPickedFor = self.getAlivePlayers()[numAlivePlayers - lenRemainingOptions]\n\t\t\t\tplayerPickedFor.addCardToHand(card)\n\t\t\t\temitTuples.extend(self.createUpdates(PICKED_FOR_CLAUS_THE_SAINT.format(username, playerPickedFor.username)))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(playerPickedFor, False))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"Claus the Saint gave you {}:\".format(card.getDeterminerString()), playerPickedFor, cards=[card]))\n\n\t\tself.specialAbilityCards[CLAUS_THE_SAINT].remove(card)\n\t\tnextPlayerToPickFor = self.getAlivePlayers()[numAlivePlayers - lenRemainingOptions + 1]\n\t\tmodalText = \"Click on the second card you want to keep for yourself:\" if nextPlayerToPickFor == player else \"Click on the card you want to give to {}:\".format(nextPlayerToPickFor.username)\n\t\t\n\t\t# Every remaining card is the same, so just distribute them automatically.\n\t\tif len({card.name for card in self.specialAbilityCards[CLAUS_THE_SAINT]}) == 1:\n\t\t\tif nextPlayerToPickFor == player:\n\t\t\t\temitTuples.extend(self.processClausTheSaintCardSelection(player.username, self.specialAbilityCards[CLAUS_THE_SAINT][-1].uid))\n\n\t\t\telse:\n\t\t\t\temitTuples.extend(self.processEmporioClausTheSaintAutomatic(nextPlayerToPickFor, clausAbility=True))\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, \"You drew these 2 cards using your ability:\", player.cardsInHand[-2:]))\n\t\t\t\n\t\t\t\tself.currentCard = None\n\t\t\t\tself.playersWaitingFor.remove(player.username)\n\t\t\t\tself.specialAbilityCards[CLAUS_THE_SAINT] = None\n\t\t\n\t\t# Otherwise, have Claus choose the card for the next player.\n\t\telse:\n\t\t\tclausTheSaintTuple = utils.createClausTheSaintTuple(player, modalText, self.specialAbilityCards[CLAUS_THE_SAINT])\n\t\t\tself.infoTupleDict[player.username] = clausTheSaintTuple\n\t\t\temitTuples.append(clausTheSaintTuple)\n\t\t\tutils.logGameplay(\"Next Claus the Saint tuple: {}\".format(clausTheSaintTuple))\n\n\t\treturn emitTuples\n\n\tdef processEmporioClausTheSaintAutomatic(self, nextPlayer, clausAbility=False):\n\t\temitTuples = []\n\t\tplayerIndex = self.getAlivePlayers().index(nextPlayer)\n\t\tlistOfCards = self.emporioOptions if not clausAbility else self.specialAbilityCards[CLAUS_THE_SAINT]\n\n\t\twhile listOfCards:\n\t\t\tcard = listOfCards.pop()\n\t\t\tnextPlayer.addCardToHand(card)\n\n\t\t\tinfoTextFormat = \"You automatically picked up {} from Emporio.\" if not clausAbility else \"Claus the Saint gave you {}:\"\n\t\t\tupdateText = PICKED_UP_FROM_EMPORIO.format(nextPlayer.username, card.getDeterminerString()) if not clausAbility \\\n\t\t\t\t\t\t\telse PICKED_FOR_CLAUS_THE_SAINT.format(self.playerOrder[0].username, nextPlayer.username)\n\t\t\temitTuples.append(self.createInfoTuple(infoTextFormat.format(card.getDeterminerString()), nextPlayer, cards=[card]))\n\t\t\temitTuples.extend(self.createUpdates(updateText))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(nextPlayer, nextPlayer == self.playerOrder[0]))\n\n\t\t\tif listOfCards:\n\t\t\t\tplayerIndex += 1\n\t\t\t\tnextPlayer = self.getAlivePlayers()[playerIndex]\n\n\t\tself.currentCard = None\n\t\tif clausAbility:\n\t\t\tself.drawingToStartTurn = False\n\n\t\treturn emitTuples\n\n\tdef resetCardClickFunctions(self, username):\n\t\tplayer = self.players[username]\n\t\treturn ((RESET_CARD_CLICK_FUNCTIONS, { 'isCurrent': player == self.playerOrder[0] }, player))\n\n\tdef replaceInPlayCard(self, player, cardToReplace):\n\t\temitTuples = []\n\n\t\tcardIndex = player.cardsInPlay.index(cardToReplace)\n\t\tself.discardCard(player, cardToReplace)\n\t\tplayer.getRidOfCard(self.currentCard)\n\t\tplayer.cardsInPlay.append(self.currentCard)\n\n\t\tif player.character.name == SUZY_LAFAYETTE:\n\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(player))\n\n\t\tif cardIndex == 0 and len(player.cardsInPlay) == 2: # If need be, flip the order of the player's in-play cards to keep them in the same position.\n\t\t\tplayer.cardsInPlay = player.cardsInPlay[::-1]\n\t\t\n\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\temitTuples.append(utils.createCardsInPlayTuple(player))\n\t\temitTuples.extend(self.getDiscardTuples(cardToReplace))\n\t\temitTuples.extend(self.createUpdates(\"{} discarded {} and put {} in play.\".format(player.username, cardToReplace.getDeterminerString(), self.currentCard.getDeterminerString())))\n\n\t\tself.currentCard = None\n\n\t\treturn emitTuples\n\n\tdef getPlayersWithCardsInHand(self, usernameToExclude=''):\n\t\t# If usernameToExclude has the default empty value, this will just check everybody.\n\t\tplayers = [p for p in self.playerOrder if p.username != usernameToExclude and len(p.cardsInHand) > 0]\n\t\tutils.logGameplay(\"Players with cards in hand{}: {}\".format(\" (excluding {})\".format(usernameToExclude) if usernameToExclude else \"\", [p.username for p in players]))\n\t\treturn players\n\n\tdef getPlayersWithCardsInPlay(self, usernameToExclude=''):\n\t\t# If usernameToExclude has the default empty value, this will just check everybody.\n\t\tplayers = [p for p in self.playerOrder if p.username != usernameToExclude and len(p.cardsInPlay) > 0]\n\t\tutils.logGameplay(\"Players with cards in play{}: {}\".format(\" (excluding {})\".format(usernameToExclude) if usernameToExclude else \"\", [p.username for p in players]))\n\t\treturn players\n\n\tdef getQuestionModalWithOpponents(self, player, question, opponents=None):\n\t\tif opponents == None:\n\t\t\topponents = self.getAliveOpponents(player.username)\n\t\treturn self.addQuestion(player, question, [p.username for p in opponents] + [NEVER_MIND])\n\n\tdef getAlivePlayers(self):\n\t\tplayers = [p for p in self.playerOrder if p.isAlive()]\n\t\tutils.logGameplay(\"Alive players: {}\".format([p.username for p in players]))\n\t\treturn players\n\n\tdef getAliveOpponents(self, username):\n\t\topponents = [p for p in self.getAlivePlayers() if p.username != username]\n\t\tutils.logGameplay(\"Alive opponents of {}: {}\".format(username, [p.username for p in opponents]))\n\t\treturn opponents\n\n\tdef processSpecialCardDraw(self, player):\n\t\temitTuples = []\n\n\t\tif self.getDynamiteCard() in player.specialCards and self.dynamiteStartTurn <= self.currentTurn:\n\t\t\tself.currentCard = self.getDynamiteCard()\n\n\t\t\tif player.character.name != LUCKY_DUKE:\n\t\t\t\temitTuples.extend(self.processDynamiteDraw(player))\n\t\t\telse:\n\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\treturn [self.createLuckyDukeTuple(player)]\n\n\t\tif player.isAlive() and player.jailStatus == 1:\n\t\t\tself.currentCard = player.getPrigione()\n\n\t\t\tif player.character.name != LUCKY_DUKE:\n\t\t\t\temitTuples.extend(self.processPrigioneDraw(player))\n\t\t\telse:\n\t\t\t\tself.drawingToStartTurn = False\n\t\t\t\treturn [self.createLuckyDukeTuple(player)]\n\n\t\treturn emitTuples\n\n\tdef processDynamiteDraw(self, player):\n\t\tdrawnCard = self.drawAndDiscardOneCard()\n\t\temitTuples = self.getDiscardTuples(self.getTopDiscardCard())\n\n\t\tif drawnCard.suit == SPADE and '2' <= drawnCard.value <= '9': # Can't compare ints b/c of face-card values.\n\t\t\tutils.logGameplay(\"The dynamite exploded on {}.\".format(player.getLogString()))\n\t\t\tself.dynamiteUsername = \"\"\n\t\t\treturn emitTuples + self.processPlayerTakingDamage(player, 3)\n\t\telse:\n\t\t\tutils.logGameplay(\"The dynamite didn't explode on {}.\".format(player.getLogString()))\n\t\t\tnextPlayer = self.advanceDynamite()\n\t\t\temitTuples.append(self.createInfoTuple(\"Phew! The dynamite didn't explode on you!\", player))\n\t\t\temitTuples.append(self.createInfoTuple(\"The dynamite didn't explode on {}, so you'll have it next turn!\".format(player.username), nextPlayer))\n\t\t\temitTuples.extend(self.createUpdates(\"The dynamite didn't explode on {}, so now {} has it.\".format(player.username, nextPlayer.username)))\n\n\t\tself.currentCard = None\n\t\tself.drawingToStartTurn = True\n\n\t\treturn emitTuples\n\n\tdef processPrigioneDraw(self, player):\n\t\tdrawnCard = self.drawAndDiscardOneCard()\n\t\tself.discardCard(player, player.getPrigione())\n\t\temitTuples = self.getDiscardTuples(self.getTopDiscardCard())\n\n\t\tif drawnCard.suit == HEART:\n\t\t\tutils.logGameplay(\"{} drew a heart for Prigione, so s/he gets out of jail and will play this turn.\".format(player.getLogString()))\n\t\t\t\n\t\t\tself.drawingToStartTurn = True\n\t\t\tplayer.jailStatus = 0\n\t\t\temitTuples.append(self.createInfoTuple(\"You drew a heart, so you got out of jail!\", player))\n\t\t\temitTuples.extend(self.createUpdates(\"{} drew a heart, so they get to play this turn.\".format(player.username)))\n\t\t\n\t\telse:\n\t\t\tutils.logGameplay(\"{} didn't draw a heart for Prigione, so s/he stays in jail and will not play this turn.\".format(player.getLogString()))\n\t\t\t\n\t\t\temitTuples.append(self.createInfoTuple(\"You drew a {}, so you're stuck in jail for this turn!\".format(drawnCard.suit), player))\n\t\t\temitTuples.extend(self.createUpdates(\"{} drew a {}, so they're stuck in jail for this turn.\".format(player.username, drawnCard.suit)))\n\t\t\temitTuples.append((END_YOUR_TURN, dict(), player))\n\n\t\tself.currentCard = None\n\n\t\treturn emitTuples\n\n\t# Function to process \"draw!\" for Barile when a player is shot at.\n\tdef processBarileDraw(self, player):\n\t\tdrawnCard = self.drawAndDiscardOneCard()\n\t\tcurrentPlayer = self.playerOrder[0]\n\t\temitTuples = self.getDiscardTuples(self.getTopDiscardCard())\n\n\t\tutils.logGameplay(\"Processing barile draw for {} against {}: {}.\".format(player.getLogString(), self.currentCard.getDeterminerString(), drawnCard.suit))\n\n\t\t# If he needs it and can do so, draw a 2nd card for Jourdonnais.\n\t\tif player.character.name == JOURDONNAIS and player.countBariles() == 2 and drawnCard.suit != HEART:\n\t\t\tjourdonnaisTriedTwice = True\n\t\t\tdrawnCard = self.drawAndDiscardOneCard()\n\t\telse:\n\t\t\tjourdonnaisTriedTwice = False\n\n\t\teffectiveDisplayName = self.currentCard.getDisplayName()\n\t\tif player.character.name == CALAMITY_JANET and self.currentCard.name == MANCATO:\n\t\t\teffectiveDisplayName = MANCATO_AS_BANG\n\n\t\tif currentPlayer.character.name != SLAB_THE_KILLER or self.currentCard.name != BANG:\n\t\t\tif drawnCard.suit == HEART:\n\t\t\t\tutils.logGameplay(\"{} drew a heart and will avoid the {}\".format(player.getLogString(), effectiveDisplayName))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You drew a heart for Barile {}and avoided {}'s {}!\".format(\"on your second card \" if jourdonnaisTriedTwice else \"\", currentPlayer.username, effectiveDisplayName), player))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} drew a heart for Barile and avoided your {}!\".format(player.username, effectiveDisplayName), currentPlayer))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew a heart for Barile and avoided {}'s {}.\".format(player.username, currentPlayer.username, effectiveDisplayName)))\n\n\t\t\t\tif self.currentCard.name == BANG:\n\t\t\t\t\tself.currentCard = None\n\n\t\t\telse:\n\t\t\t\tutils.logGameplay(\"{} didn't draw a heart for Barile against the {}\".format(player.getLogString(), effectiveDisplayName))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} tried to avoid the {} with a Barile but didn't draw a heart{}.\".format(player.username, effectiveDisplayName, \" either time\" if jourdonnaisTriedTwice else \"\")))\n\t\t\t\t\n\t\t\t\t# Only show the waiting modal to the attacker on Bangs.\n\t\t\t\tif self.currentCard.name == BANG:\n\t\t\t\t\tdidntDrawString = \"{} didn't draw a heart for Barile.\".format(player.username)\n\t\t\t\t\tif len(player.cardsInHand) > 0:\n\t\t\t\t\t\temitTuples.append(utils.createWaitingModalTuple(currentPlayer, \"{} Waiting for them to react...\".format(didntDrawString)))\n\t\t\t\t\telse:\n\t\t\t\t\t\temitTuples.append(self.createInfoTuple(didntDrawString, currentPlayer))\n\t\t\t\t\n\t\t\t\t# The Barile wasn't a heart, so check if a Mancato can still be played to avoid the attack. Otherwise, automatically take the hit.\n\t\t\t\tif len(player.getCardTypeFromHand(MANCATO)) > 0:\n\t\t\t\t\temitTuples.append(self.addQuestion(player, QUESTION_BARILE_MANCATO.format(currentPlayer.username, effectiveDisplayName), [PLAY_A_MANCATO, LOSE_A_LIFE]))\n\t\t\t\t\n\t\t\t\telse:\n\t\t\t\t\temitTuples.append(self.createInfoTuple(\"You didn't draw a heart for Barile.\", player))\n\n\t\t\t\t\tif len(player.cardsInHand) > 0:\n\t\t\t\t\t\temitTuples.append((SLEEP, AUTOMATIC_SLEEP_DURATION, None))\n\t\t\t\t\t\n\t\t\t\t\temitTuples.extend(self.processPlayerTakingDamage(player, attacker=currentPlayer))\n\t\t\n\t\t# Handle the case where Slab the Killer used a Bang, so either 1 or 2 Mancatos still need to be played.\n\t\telse:\n\t\t\tmancatosInHand = player.getCardTypeFromHand(MANCATO)\n\n\t\t\temitTuples.append(utils.createWaitingModalTuple(currentPlayer, \"{} {} a Heart for Barile. Waiting for them to react...\".format(player.username, \"didn't draw\" if drawnCard.suit != HEART else \"drew\")))\n\n\t\t\tif drawnCard.suit == HEART:\n\t\t\t\tutils.logGameplay(\"{} drew a heart but still needs to play a Mancato to avoid the Bang\".format(player.getLogString()))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew a heart for Barile.\".format(player.username)))\n\t\t\t\trequiredMancatos = 1\n\t\t\telse:\n\t\t\t\tutils.logGameplay(\"{} didn't draw a heart, so they stil need to play 2 Mancatos to avoid the Bang\".format(player.getLogString()))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} didn't draw a heart{}.\".format(player.username, \" either time\" if jourdonnaisTriedTwice else \"\")))\n\t\t\t\trequiredMancatos = 2\n\t\t\t\n\t\t\tif len(mancatosInHand) >= requiredMancatos:\n\t\t\t\tquestion = (QUESTION_SLAB_BARILE_ONE if requiredMancatos == 1 else QUESTION_SLAB_BARILE_TWO).format(currentPlayer.username)\n\t\t\t\temitTuples.append(self.addQuestion(player, question, [PLAY_A_MANCATO if requiredMancatos == 1 else PLAY_TWO_MANCATOS, LOSE_A_LIFE]))\n\t\t\telse:\n\t\t\t\tif len(player.cardsInHand) > 0:\n\t\t\t\t\temitTuples.append((SLEEP, AUTOMATIC_SLEEP_DURATION, None))\n\t\t\t\temitTuples.extend(self.processPlayerTakingDamage(player, attacker=currentPlayer))\n\n\t\treturn emitTuples\n\n\t# Try Bariles first, then ask players who can avoid the card if they want to, then process taking damage.\n\t# The cardName will already have been converted to BANG from MANCATO for Calamity Janet.\n\tdef processBangGatlingIndians(self, player, cardName, target=None):\n\t\trequiredCard = MANCATO if cardName in [BANG, GATLING] else BANG\n\t\tquestion = {BANG: QUESTION_BANG_REACTION, INDIANS: QUESTION_INDIANS_REACTION, GATLING: QUESTION_GATLING_REACTION}[cardName].format(player.username)\n\t\toption = PLAY_A_MANCATO if cardName in [BANG, GATLING] else PLAY_A_BANG\n\t\t\n\t\teffectiveDisplayName = utils.getDeterminerString(cardName)\n\t\tif player.character.name == CALAMITY_JANET and self.currentCard.name == MANCATO:\n\t\t\teffectiveDisplayName = effectiveDisplayName.replace(\"Bang\", MANCATO_AS_BANG)\n\n\t\temitTuples = self.createUpdates(\"{} played {}{}.\".format(player.username, effectiveDisplayName, '' if cardName != BANG else ' against {}'.format(target.username)))\n\t\tcurrentCard = self.currentCard\n\n\t\tnumRequiredCards = 2 if cardName == BANG and player.character.name == SLAB_THE_KILLER else 1\n\t\t\n\t\t# The target will only not be None if the card is Bang.\n\t\tif target != None:\n\t\t\topponents = [target]\n\n\t\t# For Gatling or Indians, order the opponents so that players who will get a question modal get it before any automatic delays occur.\n\t\t# Randomize the order of the automatic opponents to also help make it seem like they responded normally.\n\t\telse:\n\t\t\topponents = [opp for opp in self.getAliveOpponents(player.username) if len(opp.getCardTypeFromHand(requiredCard)) >= numRequiredCards or\n\t\t\t\t\t\t\t(player.character.name != BELLE_STAR and opp.countBariles() > 0)]\n\t\t\tautomaticOpponents = [p for p in self.getAliveOpponents(player.username) if p not in opponents]\n\t\t\trandom.shuffle(automaticOpponents)\n\t\t\topponents += automaticOpponents\n\n\t\t\temitTuples.extend(utils.createSetPlayerOpacityTuples(self.getCurrentPlayerName(), self.playerOrder)) # Set player opacity for Gatling and Indians only.\n\n\t\tif cardName == BANG:\n\t\t\tself.bangedThisTurn = True\n\n\t\tfor opp in opponents:\n\t\t\tself.currentCard = currentCard # Resetting this is necessary for the case where more than 1 opponent takes damage.\n\n\t\t\t# Check for Apache Kid first.\n\t\t\tif opp.character.name == APACHE_KID and cardName in [GATLING, INDIANS] and currentCard.suit == DIAMOND: # Checking for a diamond Bang is done elsewhere.\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} avoided the {} using Apache Kid's ability.\".format(opp.username, currentCard.getDisplayName())))\n\n\t\t\t# Try Bariles next.\n\t\t\telif cardName in [BANG, GATLING] and player.character.name != BELLE_STAR and opp.countBariles() > 0:\n\t\t\t\tif opp.character.name == LUCKY_DUKE:\n\t\t\t\t\temitTuples.append(self.createLuckyDukeTuple(opp))\n\t\t\t\t\tif cardName == BANG: emitTuples.append(utils.createWaitingModalTuple(player, \"Waiting for {} (Lucky Duke) to choose a card for \\\"draw!\\\"...\".format(opp.username)))\n\t\t\t\telse:\n\t\t\t\t\temitTuples.extend(self.processBarileDraw(opp))\n\t\t\t\n\t\t\t# Then try giving the option of playing a Mancato/Bang in response.\n\t\t\telif len(opp.getCardTypeFromHand(requiredCard)) >= numRequiredCards:\n\t\t\t\tif cardName == BANG and player.character.name == SLAB_THE_KILLER:\n\t\t\t\t\toption = PLAY_TWO_MANCATOS\n\t\t\t\t\n\t\t\t\temitTuples.append(self.addQuestion(opp, question, [option, LOSE_A_LIFE]))\n\t\t\t\tif cardName == BANG: emitTuples.append(utils.createWaitingModalTuple(player, \"Waiting for {} to react to {}...\".format(opp.username, utils.convertRawNameToDisplay(cardName))))\n\t\t\t\n\t\t\t# Otherwise, there's no choice, so automatically take the damage.\n\t\t\telse:\n\t\t\t\tif len(opp.cardsInHand) > 0:\n\t\t\t\t\tif cardName == BANG:\n\t\t\t\t\t\temitTuples.append(utils.createWaitingModalTuple(player, \"Waiting for {} to react to {}...\".format(opp.username, utils.convertRawNameToDisplay(cardName))))\n\t\t\t\t\t\n\t\t\t\t\temitTuples.append((SLEEP, AUTOMATIC_SLEEP_DURATION, None))\n\t\t\t\t\n\t\t\t\temitTuples.extend(self.processPlayerTakingDamage(opp, attacker=player))\n\n\t\tself.currentCard = None if self.currentCardCanBeReset() else currentCard\n\n\t\tutils.logGameplay(\"Processed {} playing {}. Returning the following tuples: {}\".format(player.getLogString(), cardName, emitTuples))\n\t\treturn emitTuples\n\n\tdef createLuckyDukeTuple(self, player):\n\t\tself.playersWaitingFor.append(player.username)\n\t\toptions = [self.drawOneCard(), self.drawOneCard()]\n\t\tself.drawPile += options # Re-insert these cards into the draw pile because they'll get re-drawn and properly discarded after receiving Lucky Duke's selection.\n\t\treturn self.addQuestion(player, QUESTION_LUCKY_DUKE.format(self.currentCard.getDisplayName()), [c.getQuestionString() for c in options])\n\n\tdef processJesseJonesAbility(self, username, opponentName, automatic=False):\n\t\temitTuples = []\n\t\tplayer = self.players[username]\n\t\topponent = self.players[opponentName]\n\t\t\n\t\tif not opponent.isAlive():\n\t\t\treturn [self.createInfoTuple(\"{} isn't in the game anymore! Choose someone else.\".format(opponentName), player)]\n\t\telif len(opponent.cardsInHand) == 0:\n\t\t\treturn [self.createInfoTuple(\"{} doesn't have any cards to draw from! Choose someone else.\".format(opponentName), player)]\n\t\telif opponentName == username:\n\t\t\treturn []\n\n\t\tcardsDrawn = self.drawCardsForPlayerTurn(player, opponentName)\n\t\tstolenCard = cardsDrawn[0]\n\t\tdescription = \"You {}drew {} from {}'s hand and {} from the deck.\".format(\"automatically \" if automatic else \"\", stolenCard.getDeterminerString(), opponentName, cardsDrawn[1].getDeterminerString())\n\t\tself.drawingToStartTurn = False\n\n\t\tif opponent.character.name == SUZY_LAFAYETTE:\n\t\t\temitTuples.extend(self.processSuzyLafayetteMollyStarkAbility(opponent))\n\t\t\n\t\temitTuples.append(self.createCardsDrawnTuple(player, description, cardsDrawn))\n\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\temitTuples.append(utils.createCardsInHandTuple(opponent, False))\n\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\temitTuples.append(self.createInfoTuple(\"{} drew {} from your hand using Jesse Jones's ability!\".format(player.username, stolenCard.getDeterminerString()), opponent))\n\t\temitTuples.extend(self.createUpdates(\"{} drew a card from {}'s hand using Jesse Jones's ability.\".format(player.username, opponentName)))\n\n\t\treturn emitTuples\n\n\tdef renderPlayPageForPlayer(self, username):\n\t\tplayer = self.players[username]\n\t\tutils.logGameplay(\"Rendering playing page for {}.\".format(username))\n\t\treturn render_template('play.html',\n\t\t\tplayer=player,\n\t\t\tcardsInPlayTemplate=utils.getCardsInPlayTemplate(player),\n\t\t\tplayerInfoList=self.playerOrder,\n\t\t\tplayerInfoListTemplate=utils.getPlayerInfoListTemplate(self.playerOrder),\n\t\t\tdiscardUidString='' if len(self.discardPile) == 0 else str(self.getTopDiscardCard().uid))\n\n\tdef useSpecialAbility(self, username):\n\t\tplayer = self.players[username]\n\n\n\n\t\tif player.character.name == SID_KETCHUM or (player == self.playerOrder[0] and player.character.name == DOC_HOLLYDAY):\n\t\t\treturn self.processSidKetchumDocHollydayAbility(player)\n\n\t\telif player.character.name == CHUCK_WENGAM:\n\t\t\treturn self.processChuckWengamAbility(player)\n\n\t\telif player.character.name == JOSE_DELGADO:\n\t\t\treturn self.processJoseDelgadoAbility(player)\n\n\t\telif player.character.name == UNCLE_WILL:\n\t\t\treturn self.processUncleWillAbility(player)\n\t\t\t\n\t\telse:\n\t\t\tutils.logGameplay(\"Received request from {} to use special ability, but it's not applicable.\".format(player.getLogString()))\n\t\t\treturn []\n\n\tdef processSidKetchumDocHollydayAbility(self, player):\n\t\tutils.logGameplay(\"Processing {}'s ability for {}.\".format(player.character.name, player.getLogString()))\n\n\t\temitTuples = []\n\n\t\tif player.username in self.unansweredQuestions:\n\t\t\treturn []\n\n\t\telif player.character.name not in [SID_KETCHUM, DOC_HOLLYDAY]:\n\t\t\tutils.logError(\"{} is trying to discard cards for their special ability but shouldn't be able to.\".format(player.getLogString()))\n\t\t\treturn []\n\n\t\telif player == self.playerOrder[0] and self.discardingCards:\n\t\t\treturn [self.createInfoTuple(\"You can't use your ability right now.\", player)]\n\n\t\telif player.character.name == SID_KETCHUM and player.lives == player.lifeLimit:\n\t\t\treturn [self.createInfoTuple(ALREADY_MAX_LIVES, player)]\n\n\t\telif player.character.name == DOC_HOLLYDAY and self.specialAbilityCounter[DOC_HOLLYDAY] >= 1:\n\t\t\treturn [self.createInfoTuple(\"You've already used your ability this turn!\", player)]\n\t\t\n\t\telif len(player.cardsInHand) < 2:\n\t\t\treturn [self.createInfoTuple(\"You don't have enough cards to use your special ability right now.\", player)]\n\n\t\telif self.currentCard != None:\n\t\t\treturn [self.getWaitingForCurrentCardTuple(player)]\n\n\t\telif self.specialAbilityCards[player.character.name] != None or len(player.cardsInHand) == 2:\n\t\t\tif self.specialAbilityCards[player.character.name] != None:\n\t\t\t\tif len(self.specialAbilityCards[player.character.name]) != 2:\n\t\t\t\t\tutils.logError(\"An invalid number of cards ({}) was given for {} to use his special ability.\".format(self.specialAbilityCards[player.character.name], player.getLogString()))\n\t\t\t\t\treturn []\n\t\t\t\tif not all([c in player.cardsInHand for c in self.specialAbilityCards[player.character.name]]):\n\t\t\t\t\tutils.logError(\"The cards {} were given for {} to use his special ability, but at least 1 doesn't match his current hand ({}).\".format(self.specialAbilityCards[player.character.name], player.getLogString(), player.cardsInHand))\n\t\t\t\t\treturn []\n\n\t\t\tfor c in list(self.specialAbilityCards[player.character.name] if self.specialAbilityCards[player.character.name] != None else player.cardsInHand):\n\t\t\t\tself.discardCard(player, c)\n\n\t\t\tif player.username in self.clickingOnCardSet:\n\t\t\t\tself.clickingOnCardSet.remove(player.username)\n\t\t\tif player.username in self.playersWaitingFor:\n\t\t\t\tself.playersWaitingFor.remove(player.username)\n\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\n\t\t\tif player.character.name == SID_KETCHUM:\n\t\t\t\tself.specialAbilityCards[SID_KETCHUM] = None\n\t\t\t\tplayer.gainOneLife()\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You've discarded 2 cards and gained a life.\", player))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} used Sid Ketchum's ability to discard 2 cards and gain a life.\".format(player.username)))\n\t\t\t\temitTuples.extend(utils.createHealthAnimationTuples(player.username, 1, self.playerOrder))\n\n\t\t\telif player.character.name == DOC_HOLLYDAY:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"Click on the player you want to shoot.\", player))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} used Doc Hollyday's ability to discard 2 cards for a Bang.\".format(player.username)))\n\t\t\t\temitTuples.append(self.createClickOnPlayersTuple(player, DOC_HOLLYDAY_CLICK))\n\n\t\t\t\tself.currentCard = self.createFakeCard(BANG)\n\n\t\t# In this case, the player can discard 2 cards but needs to choose which 2 to discard.\n\t\telse:\n\t\t\tself.clickingOnCardSet.add(player.username)\n\t\t\tself.specialAbilityCards[player.character.name] = [] # Change this from None to indicate that the process of using the ability is ongoing.\n\t\t\tself.playersWaitingFor.append(player.username)\n\t\t\temitTuples.append(self.createInfoTuple(SID_KETCHUM_INFO if player.character.name == SID_KETCHUM else DOC_HOLLYDAY_INFO, player))\n\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\n\t\tutils.logGameplay(\"Returning the following the tuples for {} for Sid Ketchum's ability: {}\".format(player.getLogString(), emitTuples))\n\t\treturn emitTuples\n\n\tdef processSlabTheKillerAbility(self, player):\n\t\tutils.logGameplay(\"Processing Slab the Killer's ability for {}.\".format(player.getLogString()))\n\n\t\temitTuples = []\n\t\tself.specialAbilityCards[SLAB_THE_KILLER] = []\n\t\tmancatosInHand = player.getCardTypeFromHand(MANCATO)\n\n\t\tself.playersWaitingFor.append(player.username)\n\n\t\t# If the player can't choose, just automatically play the required cards.\n\t\tif not self.playerCanChooseResponseCard(player, MANCATO, mancatosInHand):\n\t\t\tself.processBlurCardSelection(player.username, mancatosInHand[0].uid) # Don't bother emitting the intermediate results.\n\t\t\temitTuples.extend(self.processBlurCardSelection(player.username, mancatosInHand[1].uid))\n\n\t\t# Otherwise, blur any applicable cards and have the player choose which ones to use.\n\t\telse:\n\t\t\temitTuples.extend(utils.createCardBlurTuples(player, MANCATO, msg=CLICK_ON_CARD.format(\"first Mancato\")))\n\n\t\tutils.logGameplay(\"Returning the following the tuples for {} for Slab the Killer's ability: {}\".format(player.getLogString(), emitTuples))\n\t\treturn emitTuples\n\n\tdef processSuzyLafayetteMollyStarkAbility(self, player):\n\t\temitTuples = []\n\n\t\tif player.character.name == SUZY_LAFAYETTE and len(player.cardsInHand) == 0:\n\t\t\tutils.logGameplay(\"Processing Suzy Lafayette's ability for {}.\".format(player.getLogString()))\n\t\t\tself.drawCardsForPlayer(player)\n\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\temitTuples.append(self.createInfoTuple(\"You drew a card using Suzy Lafayette's ability!\", player))\n\t\t\temitTuples.extend(self.createUpdates(\"{} drew a card using Suzy Lafayette's ability.\".format(player.username)))\n\n\t\t\tutils.logGameplay(\"Returning the following the tuples for {} for Suzy Lafayette's ability: {}\".format(player.getLogString(), emitTuples))\n\n\t\telif player.character.name == MOLLY_STARK:\n\t\t\tif player != self.playerOrder[0]: # Molly Stark's ability only applies out-of-turn.\n\t\t\t\tnumCardsToDraw = 1 if self.specialAbilityCounter[MOLLY_STARK] == 0 else self.specialAbilityCounter[MOLLY_STARK] # The counter will be used to track Bangs played in a Duel.\n\t\t\t\tcardsDrawnString = \"a card\" if numCardsToDraw == 1 else \"{} cards\".format(numCardsToDraw)\n\t\t\t\tself.drawCardsForPlayer(player, numCardsToDraw)\n\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, \"You drew {} using your ability:\".format(cardsDrawnString), player.cardsInHand[-numCardsToDraw:]))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, False))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew {} using Molly Stark's ability.\".format(player.username, cardsDrawnString)))\n\n\t\t\tself.specialAbilityCounter[MOLLY_STARK] = 0\n\t\t\n\t\treturn emitTuples\n\n\tdef processJohnnyKischAbility(self, player, card):\n\t\temitTuples = []\n\t\tforcedDiscard = False\n\t\t\n\t\tfor opp in self.getAliveOpponents(player.username):\n\t\t\topponentCard = utils.getUniqueItem(lambda c: c.name == card.name, opp.cardsInPlay)\n\t\t\tif opponentCard != None:\n\t\t\t\tforcedDiscard = True\n\t\t\t\tself.discardCard(opp, opponentCard)\n\n\t\t\t\temitTuples.append(utils.createCardsInPlayTuple(opp))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You had to discard your {} because {} put one in play.\".format(card.getDisplayName(), player.username), opp))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} was forced to discard their {}.\".format(opp.username, card.getDisplayName())))\n\n\t\tif forcedDiscard:\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\n\t\treturn emitTuples\n\n\tdef processChuckWengamAbility(self, player):\n\t\temitTuples = []\n\n\t\tif player != self.playerOrder[0]:\n\t\t\temitTuples.append(self.createInfoTuple(\"You can't use your ability unless it's your turn!\", player))\n\n\t\telif self.currentCard != None:\n\t\t\treturn [self.getWaitingForCurrentCardTuple(player)]\n\n\t\telif player.lives == 1:\n\t\t\temitTuples.append(self.createInfoTuple(\"You can't use your ability when you only have 1 life left!\", player))\n\n\t\telse:\n\t\t\tplayer.loseOneLife()\n\t\t\tself.drawCardsForPlayer(player, 2)\n\n\t\t\temitTuples.extend(utils.createHealthAnimationTuples(player.username, -1, self.playerOrder))\n\t\t\temitTuples.append(self.createCardsDrawnTuple(player, \"You drew 2 cards using your ability:\", player.cardsInHand[-2:]))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\temitTuples.extend(self.createUpdates(\"{} lost 1 life and drew 2 cards using Chuck Wengam's ability.\".format(player.username)))\n\n\t\treturn emitTuples\n\n\tdef processJoseDelgadoAbility(self, player, card=None):\n\t\tif player != self.playerOrder[0]:\n\t\t\treturn [self.createInfoTuple(\"You can't use your ability unless it's your turn!\", player)]\n\n\t\telif self.currentCard != None:\n\t\t\treturn [self.getWaitingForCurrentCardTuple(player)]\n\n\t\telif self.specialAbilityCounter[JOSE_DELGADO] == 2:\n\t\t\treturn [self.createInfoTuple(\"You've already used your ability twice this turn!\", player)]\n\n\t\temitTuples = []\n\t\tautomatic = False\n\t\tblueCardsInHand = [c for c in player.cardsInHand if c.cardtype in [BLUE_CARD, GUN_CARD, SPECIAL_CARD]]\n\n\t\tif card == None and len(blueCardsInHand) == 1:\n\t\t\tcard = blueCardsInHand[0]\n\t\t\tautomatic = True\n\n\t\tif card == None:\n\t\t\tif len(blueCardsInHand) == 0:\n\t\t\t\treturn [self.createInfoTuple(\"You don't have any blue cards in your hand!\", player)]\n\n\t\t\t# 2+ blue cards in hand.\n\t\t\telse:\n\t\t\t\tself.clickingOnCardSet.add(player.username)\n\t\t\t\treturn utils.createAbilityCardClickTuples(player, JOSE_DELGADO_CLICK)\n\n\t\telse:\n\t\t\tif card.cardtype not in [BLUE_CARD, GUN_CARD, SPECIAL_CARD]:\n\t\t\t\treturn [self.createInfoTuple(\"That's not a blue card!\", player)]\n\n\t\t\telse:\n\t\t\t\tif player.username in self.clickingOnCardSet:\t\t\t\t\t\t\n\t\t\t\t\tself.clickingOnCardSet.remove(player.username)\n\t\t\t\tself.specialAbilityCounter[JOSE_DELGADO] += 1\n\t\t\t\tself.discardCard(player, card)\n\t\t\t\tself.drawCardsForPlayer(player, 2)\n\n\t\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\t\temitTuples.append(self.createCardsDrawnTuple(player, \"You {}drew 2 cards using your ability:\".format(\"automatically \" if automatic else \"\"), player.cardsInHand[-2:]))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} drew 2 cards using Jose Delgado's ability.\".format(player.username)))\n\n\t\treturn emitTuples\n\n\tdef processUncleWillAbility(self, player, card=None):\n\t\tif player != self.playerOrder[0]:\n\t\t\treturn [self.createInfoTuple(\"You can't use your ability unless it's your turn!\", player)]\n\n\t\telif self.currentCard != None:\n\t\t\treturn [self.getWaitingForCurrentCardTuple(player)]\n\n\t\telif self.specialAbilityCounter[UNCLE_WILL] == 1:\n\t\t\treturn [self.createInfoTuple(\"You've already used your ability this turn!\", player)]\n\n\t\temitTuples = []\n\t\tautomatic = False\n\n\t\tif card == None and len(player.cardsInHand) == 1:\n\t\t\tcard = player.cardsInHand[0]\n\t\t\tautomatic = True\n\n\t\tif card == None:\n\t\t\tif len(player.cardsInHand) == 0:\n\t\t\t\treturn [self.createInfoTuple(\"You don't have any cards in your hand!\", player)]\n\n\t\t\telse:\n\t\t\t\tself.clickingOnCardSet.add(player.username)\n\t\t\t\treturn utils.createAbilityCardClickTuples(player, UNCLE_WILL_CLICK)\n\n\t\telse:\n\t\t\tif player.username in self.clickingOnCardSet:\t\t\t\n\t\t\t\tself.clickingOnCardSet.remove(player.username)\n\t\t\tself.specialAbilityCounter[UNCLE_WILL] = 1\n\t\t\tself.discardCard(player, card)\n\n\t\t\temitTuples.extend(self.getDiscardTuples(self.getTopDiscardCard()))\n\t\t\temitTuples.extend(self.setupEmporio(player, uncleWillCard=card))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\n\t\treturn emitTuples\n\n\tdef createClickOnPlayersTuple(self, player, clickType, lastCardUid=0):\n\t\tself.clickingOnPlayerDict[player.username] = (clickType, lastCardUid)\n\t\treturn utils.createClickOnPlayersTuple(player, clickType)\n\n\tdef processPlayerClickedOn(self, username, targetName, clickType):\n\t\tplayer = self.players[username]\n\t\ttarget = self.players[targetName]\n\n\t\tif player.username == target.username:\n\t\t\tutils.logError(\"{} is targeting himself/herself for {}.\".format(player.getLogString(), self.currentCard.name if self.currentCard != None else 'None'))\n\t\t\treturn []\n\t\telif player != self.playerOrder[0]:\n\t\t\tutils.logError(\"{} did an on-player click ({} against {}), but the current player is {}.\".format(player.getLogString(), clickType, targetName, self.playerOrder[0].getLogString()))\n\t\t\treturn []\n\n\t\t\n\t\tif clickType == JESSE_JONES_CLICK:\n\t\t\tdel self.clickingOnPlayerDict[player.username]\n\t\t\treturn self.processJesseJonesAbility(username, targetName)\n\t\t\n\t\telif clickType == DOC_HOLLYDAY_CLICK:\n\t\t\tresponse = self.validateTargetChoice(player, target)\n\t\t\tif response == OK_MSG:\n\t\t\t\tdel self.clickingOnPlayerDict[player.username]\n\t\t\t\tself.specialAbilityCards[player.character.name] = None\n\t\t\t\tself.specialAbilityCounter[DOC_HOLLYDAY] = 1\n\n\t\t\t\treturn self.processBangGatlingIndians(player, BANG, target)\n\t\t\t\n\t\t\telse:\n\t\t\t\treturn [self.createInfoTuple(response, player, header=\"Invalid Target\")]\n\t\t\n\t\telif clickType == PAT_BRENNAN_CLICK:\n\t\t\treturn self.processPatBrennanAbility(player, target)\n\t\t\n\t\telse:\n\t\t\tresponse = self.validateTargetChoice(player, target)\n\t\t\tif response == OK_MSG:\n\t\t\t\tdel self.clickingOnPlayerDict[player.username]\n\t\t\t\treturn self.playCurrentCard(player, targetName=target.username)\n\t\t\telse:\n\t\t\t\treturn [self.createInfoTuple(response, player, header=\"Invalid Target\")] # Don't re-open the question modal so that the player can play another card if s/he wants to.\n\n\tdef processAbilityCardClickedOn(self, username, uid, clickType):\n\t\temitTuples = []\n\t\tplayer = self.players[username]\n\t\tcard = self.getCardByUid(uid)\n\n\t\tif clickType == JOSE_DELGADO_CLICK:\n\t\t\temitTuples.extend(self.processJoseDelgadoAbility(player, card=card))\n\n\t\telif clickType == UNCLE_WILL_CLICK:\n\t\t\temitTuples.extend(self.processUncleWillAbility(player, card=card))\n\n\t\treturn emitTuples\n\n\tdef getPlayerList(self, username):\n\t\tplayer = self.players[username]\n\n\t\twaitingFor = self.playersWaitingFor if (self.currentCard != None and self.currentCard.name in [GATLING, INDIANS]) else list()\n\t\temitTuples = [utils.createPlayerInfoListTuple(self.playerOrder, player, playersWaitingFor=waitingFor)]\n\n\t\tif username in self.clickingOnPlayerDict:\n\t\t\tclickType, lastCardUid = self.clickingOnPlayerDict[username]\n\t\t\temitTuples.append(utils.createClickOnPlayersTuple(player, clickType, lastCardUid=lastCardUid))\n\n\t\treturn emitTuples\n\n\tdef playerIsDiscardingForAbility(self, player):\n\t\tif player.character.name in [SID_KETCHUM, DOC_HOLLYDAY]:\n\t\t\treturn self.specialAbilityCards[player.character.name] != None\n\t\t\n\t\treturn False\n\n\tdef processPlayerDiscardingForAbility(self, player, card):\n\t\temitTuples = []\n\n\t\tself.specialAbilityCards[player.character.name].append(card)\n\n\t\tif len(self.specialAbilityCards[player.character.name]) == 1:\n\t\t\t# Temporarily remove the card from the hand to show an updated hand in the UI.\n\t\t\tplayer.getRidOfCard(card)\n\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, player == self.playerOrder[0]))\n\n\t\t\tplayer.cardsInHand.append(card) # Re-insert the card because it properly gets discarded later.\n\n\t\t\temitTuples.extend(utils.createDiscardClickTuples(player))\n\n\t\telse: # Both cards have been selected, so actually discard them and gain the life.\n\t\t\temitTuples = self.processSidKetchumDocHollydayAbility(player)\n\n\t\treturn emitTuples\n\n\tdef playerCanChooseResponseCard(self, player, requiredCardName, requiredCardsInHand):\n\t\tif player.character.name == CALAMITY_JANET or (requiredCardName == MANCATO and player.character.name == ELENA_FUENTE):\n\t\t\treturn len(set([c.name for c in requiredCardsInHand])) > 1\n\n\t\treturn False\n\n\t# Check for Vulture Same, Greg Digger, and Herb Hunter among the alive players and use their abilities if applicable.\n\tdef processPlayerEliminatedAbilities(self, attacker, eliminatedPlayer):\n\t\temitTuples = []\n\n\t\tvultureSam = utils.getUniqueItem(lambda p: p.character.name == VULTURE_SAM, self.getAlivePlayers())\n\t\tvultureSamSheriffException = vultureSam != None and vultureSam == attacker and vultureSam.role == SHERIFF and eliminatedPlayer.role == VICE\n\t\tif not vultureSamSheriffException and vultureSam != None and vultureSam != eliminatedPlayer:\n\t\t\tif len(eliminatedPlayer.cardsInHand + eliminatedPlayer.getCardsOnTable()) > 0:\n\t\t\t\tvultureSam.cardsInHand.extend(eliminatedPlayer.cardsInHand + eliminatedPlayer.getCardsOnTable())\n\n\t\t\t\teliminatedPlayer.cardsInHand = []\n\t\t\t\teliminatedPlayer.cardsInPlay = []\n\t\t\t\teliminatedPlayer.specialCards = []\n\t\t\t\t\n\t\t\t\temitTuples.append((SLEEP, 0.5, None))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You got all of {}'s cards because they were eliminated!\".format(eliminatedPlayer.username), vultureSam))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} got all of {}'s cards using Vulture Sam's ability.\".format(vultureSam.username, eliminatedPlayer.username)))\n\t\t\t\temitTuples.append(utils.createCardsInHandTuple(vultureSam, vultureSam == self.playerOrder[0]))\n\n\t\t\telse:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You couldn't use Vulture Sam's ability because {} had no cards.\".format(eliminatedPlayer.username), vultureSam))\n\n\t\tgregDigger = utils.getUniqueItem(lambda p: p.character.name == GREG_DIGGER, self.getAlivePlayers())\n\t\tif gregDigger != None and gregDigger != eliminatedPlayer:\n\t\t\tlivesGained = min(gregDigger.lifeLimit - gregDigger.lives, 2)\n\n\t\t\tif livesGained > 0:\n\t\t\t\tlifeString = \"a life\" if livesGained == 1 else \"2 lives\"\n\t\t\t\tfor _ in range(livesGained):\n\t\t\t\t\tgregDigger.gainOneLife()\n\n\t\t\t\temitTuples.extend(utils.createHealthAnimationTuples(gregDigger.username, livesGained, self.playerOrder))\n\t\t\t\temitTuples.extend(self.createUpdates(\"{} gained {} using Greg Digger's ability.\".format(gregDigger.username, lifeString)))\n\t\t\t\temitTuples.append(self.createInfoTuple(\"You gained {} because {} was eliminated.\".format(lifeString, eliminatedPlayer.username), gregDigger))\n\n\t\therbHunter = utils.getUniqueItem(lambda p: p.character.name == HERB_HUNTER, self.getAlivePlayers())\n\t\tif herbHunter != None and herbHunter != eliminatedPlayer:\n\t\t\tself.drawCardsForPlayer(herbHunter, 2)\n\n\t\t\temitTuples.append(self.createCardsDrawnTuple(herbHunter, \"You drew 2 cards because {} was eliminated:\".format(eliminatedPlayer.username), herbHunter.cardsInHand[-2:]))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(herbHunter, herbHunter == self.playerOrder[0]))\n\t\t\temitTuples.extend(self.createUpdates(\"{} drew 2 cards using Herb Hunter's ability.\".format(herbHunter.username)))\n\n\t\treturn emitTuples\n\n\tdef processPatBrennanAbility(self, player, target, card=None):\n\t\temitTuples = []\n\t\tautomatic = False\n\n\t\tif card == None and len(target.cardsInPlay) == 1:\n\t\t\tcard = target.cardsInPlay[0]\n\t\t\tautomatic = True\n\t\t\tif player.username in self.clickingOnPlayerDict:\n\t\t\t\tdel self.clickingOnPlayerDict[player.username]\n\n\t\tif card == None:\n\t\t\tif not target.isAlive():\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} isn't in the game anymore! Choose someone else.\".format(target.username), player))\n\n\t\t\telif len(target.cardsInPlay) == 0:\n\t\t\t\temitTuples.append(self.createInfoTuple(\"{} doesn't have any in-play cards to draw from! Choose someone else.\".format(target.username), player))\n\t\t\t\n\t\t\t# If the target has 2 in-play cards.\n\t\t\telse:\n\t\t\t\tif player.username in self.clickingOnPlayerDict:\n\t\t\t\t\tdel self.clickingOnPlayerDict[player.username]\n\n\t\t\t\temitTuples.append(self.addQuestion(player, QUESTION_PAT_BRENNAN_CARD.format(target.username), [c.getQuestionString() for c in target.cardsInPlay]))\n\t\t\n\t\telse:\n\t\t\tplayer.cardsInHand.append(card)\n\t\t\ttarget.getRidOfCard(card)\n\t\t\tself.drawingToStartTurn = False\n\t\t\tdescription = \"You {}drew {}'s {}.\".format(\"automatically \" if automatic else \"\", target.username, card.getDisplayName())\n\n\t\t\temitTuples.append(self.createCardsDrawnTuple(player, description, [card]))\n\t\t\temitTuples.append(utils.createCardsInHandTuple(player, True))\n\t\t\temitTuples.append(utils.createCardsInPlayTuple(target))\n\t\t\temitTuples.append(self.createInfoTuple(\"{} took the {} from your in-play cards using Pat Brennan's ability!\".format(player.username, card.getDisplayName()), target))\n\t\t\temitTuples.extend(self.createUpdates(\"{} took the {} from {}'s in-play cards using Pat Brennan's ability.\".format(player.username, card.getDisplayName(), target.username)))\n\n\t\treturn emitTuples\n\n\tdef createFakeCard(self, cardName, value=\"A\", suit=CLUB):\n\t\texampleCard = [c for c in self.allCards if c.name == cardName][0]\n\t\treturn Card(cardName, -1, exampleCard.cardtype, exampleCard.requiresTarget, \"{} {}\".format(value, suit))\n\n\tdef getWaitingForCurrentCardTuple(self, player):\n\t\tusernameString = (self.playerOrder[0].username + \"'s\") if player != self.playerOrder[0] else \"your\"\n\t\treturn self.createInfoTuple(\"Wait until {} {} is finished before using your ability.\".format(usernameString, self.currentCard.getDisplayName()), player)"
},
{
"alpha_fraction": 0.7290918827056885,
"alphanum_fraction": 0.7337753176689148,
"avg_line_length": 38.90776824951172,
"blob_id": "090e36509e6f701d71096f7a42576304dfa0a422",
"content_id": "a65db6047e9fe03cc27dcad3a565452cfcc2152a",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 16441,
"license_type": "no_license",
"max_line_length": 219,
"num_lines": 412,
"path": "/static/library/utils.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "from static.library import constants\nfrom static.library.card import Card, GunCard\nfrom static.library.character import Character\nfrom flask import Markup, render_template\nfrom pathlib import Path\nimport datetime\nimport inspect\nimport json\nimport jsonpickle\nimport numbers\nimport os\nimport psycopg2\nimport random\nimport re\n\ndef saveGameToJson(game):\n\treturn jsonpickle.encode(game)\n\ndef loadGameFromJson(json):\n\treturn jsonpickle.decode(json)\n\ndef getDatabaseConnection():\n\ttry:\n\t\tdatabase_url = os.environ['DATABASE_URL']\n\texcept KeyError:\n\t\tdatabase_url = \"postgres://nnotnxproibrzj:e68985ec9425d74ea8537f086331b59e036a0a9ac557fe3c30da6de71baf4e48@ec2-54-165-36-134.compute-1.amazonaws.com:5432/d9smgukkf0nq7q\"\n\n\treturn psycopg2.connect(database_url, sslmode='require')\n\ndef saveGame(game):\n\tconn = getDatabaseConnection()\n\tcur = conn.cursor()\n\n\tgameJson = saveGameToJson(game)\n\n\tsql = \"INSERT INTO saved_games (lobbyNumber, gameJson, timestamp) VALUES (%s, %s, %s)\"\n\tcur.execute(sql, (game.lobbyNumber, gameJson, datetime.datetime.now()))\n\tconn.commit()\n\tcur.close()\n\tconn.close()\n\n\tlogServer(\"Saved game state for lobby {} to database.\".format(game.lobbyNumber))\n\ndef loadGame(lobbyNumber):\n\tconn = getDatabaseConnection()\n\tcur = conn.cursor()\n\n\tsql = \"SELECT gameJson FROM saved_games WHERE lobbyNumber = {} ORDER BY timestamp DESC LIMIT 1\".format(lobbyNumber)\n\tcur.execute(sql)\n\n\tresults = cur.fetchall()\n\tcur.close()\n\tconn.close()\n\n\tif len(results) == 0:\n\t\tlogError(\"Unable to get saved game data for lobby number {}. Returning null.\".format(lobbyNumber))\n\t\treturn None\n\n\treturn loadGameFromJson(results[0][0])\n\ndef loadGames():\n\tconn = getDatabaseConnection()\n\tcur = conn.cursor()\n\n\tsql = \"SELECT lobbyNumber, gameJson FROM saved_games WHERE lobbyNumber >= 1000 ORDER BY timestamp DESC\"\n\tcur.execute(sql)\n\n\tresults = cur.fetchall()\n\tcur.close()\n\tconn.close()\n\n\tlobbyDict = dict()\n\tfor result in results:\n\t\tlobbyNumber, gameJson = result\n\t\tif lobbyNumber not in lobbyDict:\n\t\t\tlobbyDict[lobbyNumber] = loadGameFromJson(gameJson)\n\n\treturn {lobbyNumber: lobbyDict[lobbyNumber] for lobbyNumber in lobbyDict if not lobbyDict[lobbyNumber].gameOver}\n\ndef deleteGame(lobbyNumber):\n\tconn = getDatabaseConnection()\n\tcur = conn.cursor()\n\n\tsql = \"DELETE FROM saved_games WHERE lobbyNumber = {}\".format(lobbyNumber)\n\tcur.execute(sql)\n\tconn.commit()\n\tcur.close()\n\tconn.close()\n\n\tlogServer(\"Saved game state for lobby {} to database.\".format(game.lobbyNumber))\n\ndef log(msg, file):\n\tif \"html\" not in msg:\n\t\tprint(\"{}: {}\".format(file.upper(), msg))\n\telse:\n\t\twith open(getLocalFilePath(\"./logs/{}.txt\".format(file)), 'a+') as f:\n\t\t\ttime = datetime.datetime.today().strftime(\"%d-%B-%Y %H:%M:%S\")\n\t\t\tstack = [s[3] for s in inspect.stack()[:6]]\n\n\t\t\tusefulStack = []\n\t\t\tfor s in stack:\n\t\t\t\tif '<' not in s and s[0].isalpha():\n\t\t\t\t\tusefulStack.append(s)\n\t\t\t\telse:\n\t\t\t\t\tbreak\n\n\t\t\tstackString = (\"{} -> \" * len(usefulStack)).format(*usefulStack[::-1]) # Show the last few methods on the stack to help debug.\n\t\t\t\n\t\t\tf.write(\"{}: {}\\n\\t\\t\\t\\t\\t\\t\\t\\t{}\\n\".format(time, stackString, msg))\n\ndef logServer(msg):\n\tlog(msg, \"server\")\n\ndef logPlayer(msg):\n\tlog(msg, \"player\")\n\ndef logGameplay(msg):\n\tlog(msg, \"gameplay\")\t\n\ndef logError(msg):\n\tlog(\"ERROR: {}\".format(msg), \"error\")\n\ndef resetLogs():\n\tfor file in [\"server\", \"player\", \"gameplay\", \"error\"]:\n\t\tpath = getLocalFilePath(\"./logs/{}.txt\".format(file))\n\t\twith open(path, \"w\") as f:\n\t\t\tf.truncate(0)\n\ndef loadCards():\n\tcardList = list()\n\twith open(getLocalFilePath(\"./static/json/cards.json\")) as p:\n\t\tcardDict = json.load(p)\n\t\tuid = 1\n\n\t\tfor cardName in cardDict:\n\t\t\tfor suitValue in cardDict[cardName]['suitValues']:\n\t\t\t\tt = cardDict[cardName]['cardtype']\n\t\t\t\tif t == constants.GUN_CARD:\n\t\t\t\t\tcardList.append(GunCard(cardName, uid, constants.GUN_CARD, cardDict[cardName]['requiresTarget'], cardDict[cardName]['range'], suitValue))\n\t\t\t\telse:\n\t\t\t\t\tcardList.append(Card(cardName, uid, t, cardDict[cardName]['requiresTarget'], suitValue))\n\t\t\t\t\n\t\t\t\tuid += 1\n\n\treturn cardList\n\ndef loadCharacters(includeExtras=False):\n\tfilePaths = [getLocalFilePath(\"static/json/characters.json\")]\n\tif includeExtras:\n\t\tfilePaths.append(getLocalFilePath(\"static/json/extra_characters.json\"))\n\n\tcharacterList = list()\n\tfor filePath in filePaths:\n\t\twith open(filePath) as p:\n\t\t\tcharacterDict = json.load(p)\n\t\t\tcharacterList.extend([Character(**characterDict[c]) for c in characterDict]) # Load the JSON directly into Character objects.\n\n\treturn characterList\n\ndef getListOfConstants():\n\treturn [item for item in dir(constants) if not item.startswith(\"__\")]\n\ndef isEmptyOrNull(obj):\n\treturn obj == None or str(obj).strip() == ''\n\ndef cleanUsernameInput(s):\n\t# If the username is already all letters, just capitalize the first letter.\n\tif s.isalpha():\n\t\treturn s[0].capitalize() + s[1:]\n\n\ts = s.replace('_', ' ') # Temporarily replace all underscores with regular spaces.\n\ts = \"\".join([c if not c.isspace() else ' ' for c in s.strip()]) # Replace all forms of whitespace with regular spaces.\n\ts = \"_\".join(capitalizeWords(s).split())\n\ts = \"\".join([char for char in s if char.isalpha() or char.isdigit() or char == '_']) # Remove all non-essential characters.\n\treturn s.strip(\"_\")[:40] # Limit usernames to 40 characters.\n\ndef getLocalFilePath(path=\"\"):\n\tpathToRoot = \"\\\\\".join(str(Path(__file__).parent.absolute()).split(\"\\\\\")[:-2])\n\treturn \"{}{}{}\".format(pathToRoot, \"/\" if len(pathToRoot) > 0 else \"\", path)\n\ndef getUniqueItem(function, l):\n\tfiltered = list(filter(function, l))\n\n\treturn None if len(filtered) != 1 else filtered[0]\n\ndef capitalizeWords(s):\n\treturn \" \".join([word.lower().capitalize() for word in s.split()])\n\ndef convertRawNameToDisplay(s):\n\treturn capitalizeWords(s.replace(\"_\", \" \"))\n\ndef convertDisplayNameToRaw(s):\n\treturn \"_\".join([word.lower() for word in s.split()])\n\ndef convertCardSuitResponseToRaw(answer):\n\tparenIndex = answer.index('(')\n\treturn (convertDisplayNameToRaw(answer[:parenIndex - 1]), answer[parenIndex+1:][:-1])\n\ndef convertCardsDrawnToString(cards):\n\tif len(cards) == 1:\n\t\treturn cards[0].getDeterminerString()\n\telif len(cards) == 2:\n\t\treturn \"{} and {}\".format(*[c.getDeterminerString() for c in cards])\n\telif len(cards) == 3:\n\t\treturn \"{}, {}, and {}\".format(*[c.getDeterminerString() for c in cards])\n\telse:\n\t\treturn \"{} cards\".format(len(cards))\n\ndef getDeterminerString(name):\n\treturn \"{} {}\".format(\"an\" if isVowel(name[0]) else \"a\", convertRawNameToDisplay(name))\n\ndef isVowel(c):\n\treturn c.lower() in ['a', 'e', 'i', 'o', 'u']\n\ndef getReverseFormat(formatString, s):\n\tformatString = formatString.replace(\"(\", \"\\(\").replace(\")\", \"\\)\").replace(\"?\", \"\\?\")\n\tr = formatString.replace(\"{}\", \"(.*)\")\n\tmatch = re.search(r, s)\n\tlogGameplay(\"Result for reverse format of {} using string \\\"{}: {}\\\"\".format(formatString, s, None if match == None else list(match.groups())))\n\treturn None if match == None else list(match.groups())\n\ndef getCardNameValueSuitFromAnswer(answer):\n\tname, value, suit = getReverseFormat(constants.QUESTION_CARD_FORMAT, answer)\n\treturn (convertDisplayNameToRaw(name), value, suit)\n\ndef getCardsInPlayTemplate(player):\n\treturn Markup(render_template('cards_in_play.html', player=player))\n\ndef getPlayerInfoListTemplate(playerInfoList, playersWaitingFor=list()):\n\treturn Markup(render_template('player_info_list.html', playerInfoList=playerInfoList, playersWaitingFor=playersWaitingFor))\n\ndef createClickOnPlayersTuple(player, clickType, lastCardUid=0):\n\treturn (constants.CREATE_CLICK_ON_PLAYERS, {'clickType': clickType, 'lastCardUid': lastCardUid}, player)\n\ndef createAbilityCardClickTuples(player, clickType):\n\treturn [createInfoTuple(\"Click on the card in your hand you want to use for your ability.\", player),\n\t\t\t(constants.SPECIAL_ABILITY_CARD_CLICK, {'clickType': clickType}, player)]\n\ndef createCardsDrawnTuple(player, description, cardsDrawn, startingTurn=True):\n\tcardsDrawnImagesTemplate = Markup(render_template('/modals/card_images.html', cards=cardsDrawn))\n\tdata = {'html': render_template('/modals/cards_drawn.html', player=player, startingTurn=startingTurn, cardsDrawnImagesTemplate=cardsDrawnImagesTemplate, description=Markup(description))}\n\n\treturn createEmitTuples(constants.SHOW_INFO_MODAL, data, [player])[0]\n\ndef createGameOverTuple(player, msg):\n\tdata = {'html': render_template('/modals/info.html', text=msg, header=\"Game Over!\")}\n\n\treturn createEmitTuples(constants.GAME_OVER, data, [player])[0]\n\n# Tuples to show information in players' information modals.\ndef createInfoTuple(text, player, header=None, cards=None):\n\tlogGameplay(\"Making info tuples for {} with text \\\"{}\\\"{}\".format(player.getLogString(), text, \" and cards {}\".format([c.name for c in cards]) if cards != None else \"\"))\n\tcardImagesTemplate = None if cards == None else Markup(render_template('/modals/card_images.html', cards=cards))\n\tdata = {'html': render_template('/modals/info.html', text=text, header=header, cardsTemplate=cardImagesTemplate)}\n\n\treturn createEmitTuples(constants.SHOW_INFO_MODAL, data, recipients=[player])[0]\n\n# Tuple to ask a player a question with the question modal.\ndef createQuestionTuple(player, question, options, cardsDrawn=None):\n\tlogGameplay(\"Making question tuple for {} with question \\\"{}\\\" and options {}\".format(player.username, question, options))\n\tcardsDrawnImagesTemplate = None if cardsDrawn == None else Markup(render_template('/modals/card_images.html', cards=cardsDrawn))\n\tdata = {'html': render_template('/modals/question.html', question=question, cardsDrawnImagesTemplate=cardsDrawnImagesTemplate), 'question': question}\n\tfor i, option in enumerate(options, start=1):\n\t\tdata['option{}'.format(i)] = option\n\n\treturn createEmitTuples(constants.SHOW_QUESTION_MODAL, data, [player])[0]\n\n# Tuple to show an unclosable waiting modal for a player.\ndef createWaitingModalTuple(player, text):\n\tdata = {'html': render_template('/modals/unclosable.html', text=text, playerIsDead=(not player.isAlive()))}\n\treturn createEmitTuples(constants.SHOW_WAITING_MODAL, data, [player])[0]\n\n# Tuples to update players' action screens.\ndef createUpdateTuples(updateString, gamePlayers):\n\treturn createEmitTuples(constants.UPDATE_ACTION, {'update': updateString}, [p for p in gamePlayers])\n\n# Tuple to update a single player's screen.\ndef createUpdateTupleForPlayer(updateString, player):\n\treturn createEmitTuples(constants.UPDATE_ACTION, {'update': updateString}, [player])[0]\n\n# Tuples to blur all but certain types of card in a player's hand.\ndef createCardBlurTuples(player, cardName, msg=None):\n\tif player.character.name == constants.CALAMITY_JANET and cardName in [constants.BANG, constants.MANCATO]:\n\t\tcardNames = [constants.BANG, constants.MANCATO]\n\telif player.character.name == constants.ELENA_FUENTE and cardName == constants.MANCATO:\n\t\tcardNames = [c.name for c in player.cardsInHand]\n\telse:\n\t\tcardNames = [cardName]\n\n\tmsg = constants.CLICK_ON_CARD.format(convertRawNameToDisplay(cardName) if len(cardNames) == 1 else \"card\") if msg == None else msg\n\n\treturn [createInfoTuple(msg, player)] + createEmitTuples(constants.BLUR_CARD_SELECTION, {'cardNames': cardNames}, recipients=[player])\n\n# Tuples to show Emporio options and let the next player up pick by clicking on the card.\ndef createEmporioTuples(alivePlayers, cardsLeft, playerPicking):\n\temitTuples = []\n\tdata = dict()\n\n\tfor p in alivePlayers:\n\t\tif p == playerPicking:\n\t\t\tcardImagesTemplate = Markup(render_template('/modals/card_images.html', cards=cardsLeft, clickFunction=constants.EMPORIO_CLICK))\n\t\t\ttext = \"Click on a card to choose it:\"\n\t\telse:\n\t\t\tcardImagesTemplate = Markup(render_template('/modals/card_images.html', cards=cardsLeft))\n\t\t\ttext = \"{} is choosing a card:\".format(playerPicking.username)\n\n\t\tdata = {'html': render_template('/modals/unclosable.html', text=text, header=\"Emporio\", cardsTemplate=cardImagesTemplate, playerIsDead=(not p.isAlive()))}\t\t\n\n\t\temitTuples.extend(createEmitTuples(constants.SHOW_INFO_MODAL, dict(data), recipients=[p]))\n\n\treturn emitTuples\n\ndef createClausTheSaintTuple(player, text, cardsLeft):\n\tcardImagesTemplate = Markup(render_template('/modals/card_images.html', cards=cardsLeft, clickFunction=constants.CLAUS_THE_SAINT_CLICK))\n\tdata = {'html': render_template('/modals/unclosable.html', text=text, header=\"Claus The Saint\", cardsTemplate=cardImagesTemplate, playerIsDead=False)}\t\t\n\n\treturn createEmitTuples(constants.SHOW_INFO_MODAL, dict(data), recipients=[player])[0]\n\ndef createKitCarlsonTuple(player, cardChoices):\n\tcardImagesTemplate = Markup(render_template('/modals/card_images.html', cards=cardChoices, clickFunction=\"pickKitCarlsonCard\"))\n\ttext = \"Kit Carlson, click the card you want to put back on the draw pile:\"\n\tdata = {'html': render_template('/modals/unclosable.html', text=text, header=\"Drawing Cards\", cardsTemplate=cardImagesTemplate, playerIsDead=False)}\t\t\n\n\treturn createEmitTuples(constants.SHOW_INFO_MODAL, dict(data), recipients=[player])[0]\n\n# Tuple to update a given player's cards-in-hand carousel.\ndef createCardsInHandTuple(player, isCurrentPlayer):\n\treturn createEmitTuples(constants.UPDATE_CARD_HAND, {'cardInfo': player.getCardInfo(isCurrentPlayer)}, recipients=[player])[0]\n\n# Tuple to update the images for a player's cards in play.\ndef createCardsInPlayTuple(player):\n\treturn createEmitTuples(constants.UPDATE_CARDS_IN_PLAY, {'html': getCardsInPlayTemplate(player)}, recipients=[player])[0]\n\n# Tuple to update the image of the top discard card for everybody.\ndef createDiscardTuples(discardTop, gamePlayers):\n\treturn createEmitTuples(constants.UPDATE_DISCARD_PILE, {'path': constants.CARD_IMAGES_PATH.format(discardTop.uid if discardTop != None else constants.FLIPPED_OVER)}, recipients=[p for p in gamePlayers])\n\n# Tuple to update the player order/lives/etc. for everybody.\ndef createPlayerInfoListTuple(playerInfoList, player, playersWaitingFor=list()):\n\treturn createEmitTuples(constants.UPDATE_PLAYER_LIST, {'html': getPlayerInfoListTemplate(playerInfoList, playersWaitingFor=playersWaitingFor)}, recipients=[p for p in playerInfoList] if player == None else [player])[0]\n\ndef createDiscardClickTuples(player):\n\treturn [(constants.SLEEP, 0.2, None)] + createEmitTuples(constants.DISCARD_CLICK, dict(), recipients=[player])\n\ndef createHealthAnimationTuples(playerUsername, healthChange, players):\n\treturn [(constants.HEALTH_ANIMATION, {'username': playerUsername, 'healthChange': healthChange}, p) for p in players]\n\ndef createSetPlayerOpacityTuples(currentUsername, players):\n\treturn [(constants.SET_PLAYER_OPACITY, {'currentUsername': currentUsername}, p) for p in players]\n\n# Returns tuples that are processed by the server and emitted via socket.\ndef createEmitTuples(emitString, data, recipients=[]):\n\temitTuples = []\n\n\tfor r in recipients:\n\t\temitTuples.append((emitString, data, r))\n\n\tlogServer(\"Created {} emit tuples for {}: {}\".format(emitString, [p.username for p in recipients], emitTuples))\n\n\treturn emitTuples\n\ndef consolidateTuples(tuples):\n\tif len(tuples) > 0:\n\t\tlogServer(\"Checking tuples for consolidation: {}\".format(tuples))\n\n\t\t# Remove any duplicates if there are any. Maintain the order and keep the newest versions.\n\t\tnonDuplicated = []\n\t\tfor t in tuples[::-1]:\n\t\t\tif t[0] == constants.SLEEP or t not in nonDuplicated:\n\t\t\t\tnonDuplicated.append(t)\n\n\t\tif len(nonDuplicated) < len(tuples):\n\t\t\tlogServer(\"Tuples after removing duplicates: {}\".format(tuples))\n\t\ttuples = nonDuplicated[::-1]\n\n\t\t# If there are SLEEPs in the tuples, remove any extra SLEEPs that are for the automatic duration.\n\t\tautomaticSleepTups = [t for t in tuples if t[0] == constants.SLEEP and t[1] == constants.AUTOMATIC_SLEEP_DURATION]\n\t\tif len(automaticSleepTups) > 0:\n\t\t\ttemp = []\n\t\t\taddedAutomaticSleep = False\n\t\t\tfor t in tuples:\n\t\t\t\tif t in automaticSleepTups:\n\t\t\t\t\tif not addedAutomaticSleep:\n\t\t\t\t\t\taddedAutomaticSleep = True\n\t\t\t\t\t\ttemp.append(t)\n\t\t\t\t\telse:\n\t\t\t\t\t\ttemp.append((constants.SLEEP, random.randint(10, 25) / 10, None)) # Add a random delay between 1 and 2.5 seconds so that the message timing seems more natural.\n\t\t\t\telse:\n\t\t\t\t\ttemp.append(t)\n\n\t\t\ttuples = list(temp)\n\t\t\tlogServer(\"Consolidated SLEEPS in the tuples: {}\".format(tuples))\n\n\t\t# Remove any tuples that come after the game over tuples.\n\t\ttemp = list(tuples)\n\t\ttuples = []\n\t\tgameIsOver = False\n\t\tfor t in temp:\n\t\t\ttuples.append(t)\n\t\t\t\n\t\t\tif t[0] == constants.GAME_OVER:\n\t\t\t\tgameIsOver = True\n\t\t\telse:\n\t\t\t\tif gameIsOver and t[0] != constants.GAME_OVER:\n\t\t\t\t\tbreak\n\n\t\tif gameIsOver:\n\t\t\ttuples = [t for t in tuples if t[0] != constants.SHOW_QUESTION_MODAL]\n\n\t\tlogServer(\"tuples after consolidating: {}\".format(tuples))\n\t\n\treturn tuples"
},
{
"alpha_fraction": 0.626472532749176,
"alphanum_fraction": 0.6346914172172546,
"avg_line_length": 30.8206729888916,
"blob_id": "96d39fbd5efee9f9c230089cc9e70afb1f4b9f19",
"content_id": "bb274340b537f1eef77057490944063d34a74b47",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "JavaScript",
"length_bytes": 25551,
"license_type": "no_license",
"max_line_length": 183,
"num_lines": 803,
"path": "/static/scripts/script.js",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "var socket;\nvar username;\n\nvar OK_MSG = \"OK\";\nvar INFO_MODAL = \"#info_modal\";\nvar INFO_MODAL_TEXT = \"#infoModalText\";\nvar INFO_MODAL_IMAGES = \"#infoModalImages\";\nvar QUESTION_MODAL = \"#question_modal\"\nvar TOP_HALF = \"#topHalfDiv\"\nvar BOTTOM_HALF = \"#bottomHalfDiv\"\nvar CARDS_IN_HAND_DIV = \"#cardsInHandDiv\"\nvar CARDS_IN_PLAY_DIV = \"#cardsInPlayDiv\";\nvar DISCARD_DIV = \"#discardCardDiv\";\nvar WAITING_FOR_SPAN = \"#waitingForSpan\";\nvar LOBBY_USERNAMES = \"#lobby_usernames\";\nvar PLAYER_COLUMN_IMAGE = \".player-column-image\";\nvar SOCKET_TIME_DIFFERENCE = 500; // Half a second.\nvar KEYCODES_LIST = [13, 16, 67, 69, 83]; // Enter, Shift, C, E, S\n\nvar cardsAreBlurred = false;\nvar clickingOnPlayer = false;\nvar keysPressed = {};\nvar healthAnimationCounter = 0;\nvar lastCardUid = -1;\nvar previousSocketTime = new Date().getTime();\nvar currentCardHandInfo = [];\n\n$(document).ready(function(){\n\n\tif (location.protocol !== 'http:') {\n\t location.replace(`http:${location.href.substring(location.protocol.length)}`);\n\t}\n\n\tusername = $(\"#username\").text();\n\twindow.history.pushState({}, '', '/');\n\n\t// Connect to the socket server.\n\tif (username.length > 0) {\n\t\tsocket = io.connect('http://' + document.domain + ':' + location.port + '/', { forceNew: true, transports: ['websocket'] });\n\t\tsocket.emit('connected', username);\n\n\t\tsetInterval(function() { socket.emit('connected', username); }, 10000);\n\n\t\tsocket.on('disconnect', function() {\n\t\t\tsocket.emit('connected', username);\n\t\t\tsetTimeout(function() {\n\t\t\t\tsocket.emit('rejoin_game', username);\n\t\t\t}, 250);\n\t\t});\n\n\t\tsocket.on('keep_alive', function() {})\n\n\t\t/* Socket functions for showing the modals. */\n\n\t\tsocket.on('show_info_modal', function(data) {\n\t\t\tif (isNullOrUndefined($(INFO_MODAL).html())) { // Undefined if the message was received before the page was rendered.\n\t\t\t\tsetTimeout(function() {\n\t\t\t\t\tvar html = data.html;\n\t\t\t\t\tsocket.emit('info_modal_undefined', username, html);\n\t\t\t\t}, 500);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tshowInfoModal(data.html);\n\t\t\t}\n\t\t});\n\n\t\tsocket.on('show_question_modal', function(data) {\n\t\t\t// Close the waiting modal if it's currently open, as it will block the question modal.\n\t\t\tif (waitingModalIsOpen()) {\n\t\t\t\tcloseInfoModal();\n\t\t\t}\n\n\t\t\tif (isNullOrUndefined($(QUESTION_MODAL).html())) { // Undefined if the message was received before the page was rendered.\n\t\t\t\tsetTimeout(function() {\n\t\t\t\t\tvar option1 = data.option1;\n\t\t\t\t\tvar option2 = data.option2;\n\t\t\t\t\tvar option3 = data.option3;\n\t\t\t\t\tvar option4 = data.option4;\n\t\t\t\t\tvar option5 = data.option5;\n\t\t\t\t\tvar option6 = data.option6;\n\t\t\t\t\tvar option7 = data.option7;\n\t\t\t\t\tvar html = data.html;\n\t\t\t\t\tvar question = data.question;\n\t\t\t\t\tsocket.emit('question_modal_undefined', username, option1, option2, option3, option4, option5, option6, option7, html, question);\n\t\t\t\t}, 500);\n\t\t\t}\n\t\t\telse\n\t\t\t{\n\t\t\t\t// Close the waiting modal if it's open.\n\t\t\t\tif ($(INFO_MODAL).is(':visible')) {\n\t\t\t\t\tif ($(INFO_MODAL_TEXT).text().indexOf('Waiting') > -1) {\n\t\t\t\t\t\t$(INFO_MODAL).modal('hide');\n\t\t\t\t\t\t$(INFO_MODAL).html('');\n\t\t\t\t\t}\n\t\t\t\t}\n\n\t\t\t\tvar question = data.question;\n\t\t\t\tvar d = {};\n\n\t\t\t\td[data.option1] = function() { socket.emit('question_modal_answered', username, question, data.option1); $( this ).dialog( \"close\" ); };\n\t\t\t\td[data.option2] = function() { socket.emit('question_modal_answered', username, question, data.option2); $( this ).dialog( \"close\" ); };\n\t\t\t\tif (!isNullOrUndefined(data.option3)) { d[data.option3] = function() { socket.emit('question_modal_answered', username, question, data.option3); $( this ).dialog( \"close\" ); }; }\n\t\t\t\tif (!isNullOrUndefined(data.option4)) { d[data.option4] = function() { socket.emit('question_modal_answered', username, question, data.option4); $( this ).dialog( \"close\" ); }; }\n\t\t\t\tif (!isNullOrUndefined(data.option5)) { d[data.option5] = function() { socket.emit('question_modal_answered', username, question, data.option5); $( this ).dialog( \"close\" ); }; }\n\t\t\t\tif (!isNullOrUndefined(data.option6)) { d[data.option6] = function() { socket.emit('question_modal_answered', username, question, data.option6); $( this ).dialog( \"close\" ); }; }\n\t\t\t\tif (!isNullOrUndefined(data.option7)) { d[data.option7] = function() { socket.emit('question_modal_answered', username, question, data.option7); $( this ).dialog( \"close\" ); }; }\n\n\t\t\t\t$(QUESTION_MODAL).css(\"display\", \"block\");\n\t\t\t\t$(QUESTION_MODAL).html(data.html)\n\t\t\t\t$(QUESTION_MODAL).dialog({\n\t\t\t\t\tdialogClass: \"no-close\",\n\t\t\t\t\tresizable: false,\n\t\t\t\t\tautoResize: true,\n\t\t\t\t\theight: \"auto\",\n\t\t\t\t\twidth: \"auto\",\n\t\t\t\t\tminHeight: 0,\n\t\t\t\t\tmodal: true,\n\t\t\t\t\tbuttons: d,\n\t\t\t\t\topen: function(event, ui) {\n\t\t\t\t\t\t$(this).dialog('widget').position({ my: \"center\", at: \"center\", of: window });\n\t\t\t\t\t}\n\t\t \t});\n\n\t\t \t$(\".ui-dialog-buttonset button\").each(function() {\n\t\t\t\t\t$(this).addClass(\"bang-button-question\");\n\t\t\t\t});\n\t\t\t}\n\t\t});\n\n\t\tsocket.on('show_waiting_modal', function(data) {\n\t\t\tshowInfoModal(data.html);\n\t\t});\n\n\t\t/* Socket functions for waiting in the lobby. */\n\n\t\tsocket.on('lobby_player_update', function(data) {\n\t\t\tvar players = data.usernames;\n\t\t\tvar lobby_players_list_string = '';\n\n\t\t\t// Update the list of players for people who are already in the lobby.\n\t\t\tvar listTag;\n\t\t\tfor (var i = 0; i < players.length; i++) {\n\t\t\t\tif (i == 0) {\n\t\t\t\t\tlistTag = \"<li style='color: red;'>\"\n\t\t\t\t}\n\t\t\t\telse {\n\t\t\t\t\tlistTag = \"<li>\"\n\t\t\t\t}\n\t\t\t\tlobby_players_list_string = lobby_players_list_string + listTag + players[i].toString() + '</li>';\n\t\t\t}\n\t\t\t$(LOBBY_USERNAMES).html(lobby_players_list_string);\n\t\t});\n\n\t\tsocket.on('show_start_button', function(data) {\n\t\t\t$(\"#start_button\").css(\"display\", \"block\");\n\t\t});\n\n\t\tsocket.on('hide_start_button', function(data) {\n\t\t\t$(\"#start_button\").css(\"display\", \"none\");\n\t\t});\n\n\t\tsocket.on('reload_lobby', function(data) {\n\t\t\tloadHtml(data.html);\n\t\t});\n\n\t\tsocket.on('start_game', function(data) {\n\t\t\tvar xhr = new XMLHttpRequest();\n\n\t\t\txhr.onreadystatechange = function() {\n\t\t\t\tif (xhr.readyState === 4) {\n\t\t\t\t\tloadHtml(xhr.response); // Force the new page to render because manually sending a POST request blocks it.\n\t\t\t\t}\n\t\t\t}\n\n\t\t\txhr.open(\"POST\", \"/setup\", true);\n\t\t\txhr.setRequestHeader('Content-Type', 'application/json');\n\t\t\txhr.send(JSON.stringify({\n\t\t\t\t'username': username\n\t\t\t}));\n\t\t});\n\n\t\t/* Socket functions for setup. */\n\n\t\tsocket.on('character_was_set', function(data) {\n\t\t\tif (data.players_remaining.includes(username)) {\n\t\t\t\tvar others_left = data.players_remaining.length - 1;\n\t\t\t\tif (others_left >= 0) {\n\t\t\t\t\tif (others_left == 0) {\n\t\t\t\t\t\t$(WAITING_FOR_SPAN).html(\"We're just waiting for you to pick a character now...\");\n\t\t\t\t\t}\n\t\t\t\t\telse if (others_left == 1) {\n\t\t\t\t\t\t$(WAITING_FOR_SPAN).html(\"Waiting for you and 1 other player to pick a character...\");\n\t\t\t\t\t}\n\t\t\t\t\telse {\n\t\t\t\t\t\t$(WAITING_FOR_SPAN).html(\"Waiting for you and \" + others_left.toString() + \" other players to pick a character...\");\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t\telse {\n\t\t\t\tvar others_left = data.players_remaining.length;\n\t\t\t\tif (others_left == 1) { $(WAITING_FOR_SPAN).html(\"We're still waiting for 1 more player...\"); }\n\t\t\t\telse { $(WAITING_FOR_SPAN).html(\"We're still waiting for \" + others_left.toString() + \" players...\"); }\n\t\t\t}\n\t\t});\n\n\t\t/* Socket functions for the play page. */\n\n\t\tsocket.on('reload_play_page', function(data) {\n\t\t\tloadPlayPage(data);\n\t\t});\n\n\t\tsocket.on('update_action', function(data) {\n\t\t\tvar usernameList = [];\n\t\t\t$(\".playerInfoColumn h2\").each(function(index, elem) {\n\t\t\t\tusernameList.push($(this).text());\n\t\t\t});\n\n\t\t\t// Indent updates that are during a turn.\n\t\t\tvar startTag = \"<li>\";\n\t\t\tif (!data.update.includes(\"started their turn\")) {\n\t\t\t\tstartTag = \"<li \" + \"style='margin-left: 25px;'\" + \">\"\n\t\t\t}\n\t\t\telse { // Add a line break between each player's turn.\n\t\t\t\tif ($(\"#updateActionList li\").length > 0) {\n\t\t\t\t\tstartTag = \"<br>\" + startTag;\n\t\t\t\t}\n\t\t\t}\n\n\t\t\t// If the update is about a player taking damage, remove the opacity on his/her image.\n\t\t\tif (data.update.split(' ').length > 3 && (data.update.split(' ')[1] + ' ' + data.update.split(' ')[2]) == \"was hit\") {\n\t\t\t\tvar playerHitUsername = data.update.split(' ')[0];\n\t\t\t\t$(\"#\" + playerHitUsername + \"PlayerImage\").css(\"opacity\", 1);\n\t\t\t}\n\n\t\t\t// Make player usernames red.\n\t\t\tvar redSpan = \"<span style='color: red;'>\";\n\n\t\t\tif (!data.update.includes(\"won the game\")) {\n\t\t\t\tvar wordsInUpdate = data.update.split(' ');\n\t\t\t\tvar updateHtml = startTag;\n\n\t\t\t\tfor (var i = 0; i < wordsInUpdate.length; i++) {\n\t\t\t\t\tif (usernameList.includes(wordsInUpdate[i])\n\t\t\t\t\t\t|| usernameList.includes(wordsInUpdate[i].replace(\"'s\", ''))\n\t\t\t\t\t\t|| usernameList.includes(wordsInUpdate[i].replace(\".\", ''))\n\t\t\t\t\t\t|| usernameList.includes(wordsInUpdate[i].replace(\",\", ''))) {\n\t\t\t\t\t\tupdateHtml += (redSpan + wordsInUpdate[i] + \"</span>\");\n\t\t\t\t\t}\n\t\t\t\t\telse {\n\t\t\t\t\t\tupdateHtml += wordsInUpdate[i];\n\t\t\t\t\t}\n\t\t\t\t\tupdateHtml += ' ';\n\t\t\t\t}\n\t\t\t\t$(\"#updateActionList\").append(updateHtml + \"</li>\");\n\t\t\t}\n\t\t\telse {\n\t\t\t\t$(\"#updateActionList\").append(startTag + redSpan + data.update + \"</span>\" + \"</li>\");\n\t\t\t}\n\t\t\t\n\t\t\t// Automatically keep the list of updates scrolled to the bottom.\n\t\t\tvar updateList = document.getElementById(\"updateActionList\");\n\t\t if (!isNullOrUndefined(updateList)) { updateList.scrollIntoView(false); }\n\n\t\t\tif ((/played a(n?) (Bang|Duello|Indians|Gatling)/.test(data.update) == false || (data.update.includes(\" avoid\"))) && !data.update.includes(\"won the game\")) {\n\t\t\t\tsocket.emit('request_player_list', username);\n\t\t\t}\n\t\t});\n\n\t\tsocket.on('blur_card_selection', function(data) {\n\t\t\taddBlurToCards(data.cardNames);\n\t\t});\n\n\t\tsocket.on('update_card_hand', function(data) {\n\t\t\tcurrentCardHandInfo = data.cardInfo;\n\t\t\tcreateCardHand(data.cardInfo);\n\t\t});\n\n\t\tsocket.on('update_cards_in_play', function(data) {\n\t\t\t$(\"#cardsInPlayDiv\").html(\"\");\n\t\t\t$(\"#cardsInPlayDiv\").html(data.html);\n\t\t});\n\n\t\tsocket.on('update_discard_pile', function(data) {\n\t\t\t$(\"#discardCardImage\").attr(\"src\", data.path);\n\t\t});\n\n\t\tsocket.on('end_your_turn', function(data) {\n\t\t\tsocket.emit('ending_turn', username);\n\t\t});\n\n\t\tsocket.on('update_player_list', function(data) {\n\t\t\t$(BOTTOM_HALF).html(\"\");\n\t\t\t$(BOTTOM_HALF).html(data.html);\n\n\t\t\t// Shrink any usernames that don't fit above the player's card.\n\t\t\t$(\".player-list-usernames\").each(function() {\n\t\t\t while ($(this).width() > $(this).parent().width() * 0.8) {\n\t\t\t $(this).css('font-size', (parseInt($(this).css('font-size')) - 1) + \"px\" );\n\t\t\t }\n\t\t\t});\n\n\t\t\tsetupTooltip();\n\t\t});\n\n\t\tsocket.on('health_animation', function(data) {\n\t\t\tsetTimeout(function() {\n\t\t\t\thealthAnimationCounter++;\n\t\t\t\tvar playerDiv = $('#player_div_' + data.username);\n\t\t\t\tvar divTop = playerDiv.offset().top;\n\t\t\t\tvar divPosTop = divTop - $(window).scrollTop();\n\t\t\t\tvar divLeft = playerDiv.offset().left;\n\t\t\t\tvar divPosLeft = divLeft - $(window).scrollLeft();\n\t\t\t\tvar animationColor = data.healthChange < 0 ? \"red\" : \"limegreen\";\n\n\t\t\t\t$(\"body\").append('<span id=\"player_damage_span_' + (data.username + healthAnimationCounter.toString()) + '\" style=\"font-size: 35px; font-style: italic; color: ' + animationColor +\n\t\t\t\t\t\t\t\t\t'; z-index: 200; position: absolute; top: ' + divPosTop.toString() + '; left: ' + (divPosLeft + (playerDiv.width() / 2)).toString() + ' \"></span>');\n\t\t\t\tvar playerDamageSpan = $(\"#player_damage_span_\" + (data.username + healthAnimationCounter.toString()));\n\t\t\t\tplayerDamageSpan.text((data.healthChange > 0 ? \"+\" : \"\") + data.healthChange.toString());\n\t\t\t\tplayerDamageSpan.animate({\n\t\t\t\t\ttop: \"-25px\",\n\t\t\t\t\topacity: 0.5\n\t\t\t }, 5000, function() { playerDamageSpan.remove()});\n\t\t\t}, 500); // Wait for half a second in case the player's position changes.\n\t\t});\n\n\t\tsocket.on('discard_click', function(data) {\n\t\t\taddDiscardClickFunctions();\n\t\t});\n\n\t\tsocket.on('game_over', function(data) {\n\t\t\tif (questionModalIsOpen()) { $(QUESTION_MODAL).dialog( \"close\" );\t}\n\t\t\tshowInfoModal(data.html);\n\n\t\t\t// Remove the click function for the player's cards if applicable.\n\t\t\t$(CARDS_IN_HAND_DIV).find(\"img\").each(function() {\n\t\t\t\t$(this).attr(\"onClick\", \"\"); \n\t\t\t});\n\n\t\t\t// Replace the question mark with a button for returning to the lobby.\n\t\t\t$(\"#questionmark\").hide();\n\t\t\t$(\"#return-to-lobby-button\").css(\"display\", \"block\");\n\t\t});\n\n\t\tsocket.on('create_click_on_players', function(data) {\n\t\t\tclickingOnPlayer = true;\n\n\t\t\t// Handle the player reloading the page.\n\t\t\tif (lastCardUid == 0 && data.lastCardUid != 0) {\n\t\t\t\tlastCardUid = data.lastCardUid;\n\t\t\t\tsetTimeout(function() {\n\t\t\t\t\tsetPlayerClicks(data.clickType);\n\t\t\t\t}, 500);\n\t\t\t}\n\t\t\telse {\n\t\t\t\tsetPlayerClicks(data.clickType);\n\t\t\t}\n\n\t\t\tif (data.clickType == \"targeted_card_player_click\") {\n\t\t\t\tsetCardOpacity(true, lastCardUid);\n\t\t\t}\n\t\t});\n\n\t\tsocket.on('set_player_opacity', function(data) {\n\t\t\tsetPlayerOpacity(data.currentUsername);\n\t\t});\n\n\t\tsocket.on('doc_hollyday_ability', function(data) {\n\t\t\tsetPlayerClicks(\"doc_hollyday_click\");\n\t\t});\n\n\t\tsocket.on('special_ability_card_click', function(data) {\n\t\t\tsetAbilityCardClicks(data.clickType);\n\t\t});\n\t}\n});\n\n/* General functions */\n\nfunction loadHtml(html) {\n\tdocument.body.innerHTML = \"\";\n\twindow.document.write(html);\n}\n\nfunction isNullOrUndefined(obj) {\n\treturn obj == null || obj == undefined;\n}\n\nfunction capitalizeWords(s) {\n\treturn s\n .toLowerCase()\n .split(' ')\n .map(word => word.charAt(0).toUpperCase() + word.slice(1))\n .join(' ');\n}\n\nfunction startButtonClick() {\n\tsocket.emit('start_button_clicked', username);\n}\n\nfunction leaveLobby() {\n\tsocket.emit('leave_lobby', username);\n}\n\nfunction chooseCharacter(character, isOption1) {\n\tif (confirm(\"Are you sure you want to play as \" + character + \"?\")) {\n\t\t$(\"#option1Card\").removeAttr(\"onClick\");\n\t\t$(\"#option2Card\").removeAttr(\"onClick\");\n\t\t\n\t\tif (isOption1) {\n\t\t\t$(\"#option2Card\").css(\"display\", \"none\");\n\t\t}\n\t\telse {\n\t\t\t$(\"#option1Card\").css(\"display\", \"none\");\n\t\t}\n\n\t\t$(\"#characterOptionsSpan\").html(\"Your character is \" + character + \".\");\n\t\tsocket.emit('set_character', username, character);\n\t}\n}\n\nfunction loadPlayPage(data) {\n\tloadHtml(data.html);\n\tcurrentCardHandInfo = data.cardInfo;\n\tcreateCardHand(data.cardInfo);\n\tsetupTooltip();\n\t$(\"body\").css(\"overflow\", \"hidden\");\n}\n\nfunction showInfoModal(html) {\n\t// Do nothing if the question modal is already open.\n\tif (questionModalIsOpen()) { return; }\n\n\t// If the incoming info modal is for Kit Carlson, the current info modal needs to be closed if it's open.\n\tif (html.includes(\"Drawing Cards\") && html.includes(\"Kit Carlson\")) {\n\t\tcloseInfoModal();\n\t}\n\n\t// If the modals can be combined, just combine them.\n\tvar eitherModalIsWaiting = waitingModalIsOpen() || html.includes(\"Waiting\");\n\tvar eitherModalIsEmporio = emporioModalIsOpen() || (html.includes(\"Emporio</h\"));\n\tif ($(INFO_MODAL).is(':visible') && !eitherModalIsWaiting && !eitherModalIsEmporio) {\n\t\tvar newModalElements = $(html);\n\t\tvar element = $(INFO_MODAL_TEXT, newModalElements);\n\t\tif (html.includes(\"<img\")) {\n\t\t\tvar imageDiv = $(INFO_MODAL_IMAGES, newModalElements);\n\t\t\t$(imageDiv[0]).appendTo(element);\n\t\t}\n\t\t$(INFO_MODAL_TEXT).prepend(element[0].innerHTML + '<br/><br/>');\n\t}\n\n\t// Otherwise, load the new HTML into the modal and display it.\n\telse {\n\t\tif ($(INFO_MODAL).is(':visible') && html.includes(\"Waiting\")) {\n\t\t\tvar element = $(INFO_MODAL_TEXT);\n\t\t\tvar textToAppend = \"<br/><br/>\" + element[0].innerHTML;\n\t\t\thtml = html.replace(\"</p>\", textToAppend + \"</p>\");\n\t\t}\n\n\t\tcloseInfoModal();\n\t\t$(INFO_MODAL).html(html);\n\t\t$(INFO_MODAL).modal('show');\n\n\t\t$(INFO_MODAL).draggable({\n\t\t handle: \".modal-header\"\n\t\t}); \n\n\t\t$(INFO_MODAL).css({top: \"20%\", left: 0});\n\t}\n\n\tif (cardsAreBlurred) {\n\t\tsetCardOpacity(true, lastCardUid);\n\t}\n}\n\nfunction playCard(uid) {\n\tconsole.log(\"playCard\", uid, cardsAreBlurred, clickingOnPlayer);\n\tif (!cardsAreBlurred && !clickingOnPlayer) {\n\t\tif (new Date().getTime() - previousSocketTime >= SOCKET_TIME_DIFFERENCE) {\n\t\t\tsocket.emit('validate_card_choice', username, uid);\n\t\t\tconsole.log(\"playCard emitted\");\n\t\t\tlastCardUid = uid;\n\t\t\tupdatePreviousSocketTime();\n\t\t}\n\t}\n}\n\nfunction playBlurCard(uid) {\n\tif (new Date().getTime() - previousSocketTime >= SOCKET_TIME_DIFFERENCE) {\n\t\tsocket.emit('blur_card_played', username, uid);\n\t\tcardsAreBlurred = false;\n\t\tupdatePreviousSocketTime();\n\t}\n}\n\nfunction discardCard(uid) {\n\tif (new Date().getTime() - previousSocketTime >= SOCKET_TIME_DIFFERENCE) {\n\t\tsocket.emit('discarding_card', username, uid);\n\t\tupdatePreviousSocketTime();\n\t}\n}\n\nfunction addBlurToCards(cardNames) {\n\t$(CARDS_IN_HAND_DIV).find(\"img\").each(function() {\n\t\tvar cardName = $(this).attr(\"alt\").split(' ')[0];\n\t\tvar uid = $(this).attr(\"alt\").split(' ')[1];\n\t\t\n\t\tif (!cardNames.includes(cardName)) {\n\t\t\t$(this).css(\"opacity\", 0.25);\n\t\t\t$(this).css(\"z-index\", 5);\n\t\t}\n\t\telse {\n\t\t\t$(this).attr(\"onClick\", \"playBlurCard(\" + uid + \")\" ); \n\t\t}\n\t});\n\t\n\tcardsAreBlurred = true;\n}\n\nfunction removeBlurFromCards() {\n\t$(CARDS_IN_HAND_DIV).find(\"img\").each(function() {\n\t\t$(this).css(\"opacity\", 1);\n\t\t$(this).removeAttr(\"onClick\"); // If the player is the current player, the click function will be reset by the new cards.\n\t});\n\t\n\tcardsAreBlurred = false;\n}\n\nfunction resetCardZIndeces() {\n\tvar counter = 0;\n\t$(CARDS_IN_HAND_DIV).find(\"img\").each(function() {\n\t\t$(this).css(\"z-index\", 10 + counter);\n\t\tcounter++;\n\t});\n}\n\nfunction pickEmporioCard(uid) {\n\tsocket.emit('emporio_card_picked', username, uid);\n}\n\nfunction pickClausTheSaintCard(uid) {\n\tsocket.emit('claus_the_saint_card_picked', username, uid);\n}\n\nfunction pickKitCarlsonCard(uid) {\n\tsocket.emit('kit_carlson_card_picked', username, uid);\n\tcloseInfoModal()\n}\n\nfunction setupTooltip() {\n\t$('a[data-toggle=\"tooltip\"]').tooltip({\n\t animated: 'fade',\n\t placement: 'top',\n\t html: true,\n\t});\n\n\t$('img[data-toggle=\"tooltip\"]').tooltip({\n\t animated: 'fade',\n\t placement: 'left',\n\t html: true,\n\t});\n}\n\nfunction addDiscardClickFunctions() {\n\t$(CARDS_IN_HAND_DIV).find(\"img\").each(function() {\n\t\tvar cardName = $(this).attr(\"alt\").split(' ')[0];\n\t\tvar uid = $(this).attr(\"alt\").split(' ')[1];\n\n\t\t$(this).attr(\"onClick\", \"discardCard(\" + uid + \")\" );\n\t});\n}\n\nfunction setPlayerClicks(clickType='') {\n\t$(\".playerInfoColumn\").each(function(index, elem) {\n\t\tvar opponentUsername = $(this).attr(\"id\").substring(\"player_div_\".length);\n\t\tif (opponentUsername != username) {\n\t\t\t$(this).attr(\"onClick\", clickType == '' ? '' : \"playerClickedOn('\" + opponentUsername + \"', '\" + clickType + \"')\");\n\t\t}\n\t});\n}\n\nfunction setAbilityCardClicks(clickType) {\n\t$(CARDS_IN_HAND_DIV + \" img\").each(function() {\n\t\tvar uid = $(this).attr(\"alt\").split(' ')[1];\n\t\t$(this).attr(\"onClick\", \"abilityCardClickedOn('\" + uid + \"', '\" + clickType + \"')\");\n\t});\n}\n\nfunction setCardOpacity(add, uid=-1) {\n\tvar cardId = '#hand_card_' + uid.toString();\n\tvar zindexDifference = 100;\n\n\tif (add && $(cardId).length) {\n\t\tcardsAreBlurred = true;\n\n\t\t$(cardId).css(\"zIndex\", (parseInt($(cardId).css(\"zIndex\")) + zindexDifference).toString());\n\n\t\t$(CARDS_IN_HAND_DIV + \" img\").each(function() {\n\t\t\tif ($(this).attr(\"id\") != cardId.substring(1) || $(CARDS_IN_HAND_DIV + \" img\").length == 1) {\n\t\t\t\t$(this).css(\"opacity\", 0.25);\n\t\t\t}\n\t\t});\n\t}\n\telse\n\t{\n\t\tcardsAreBlurred = false;\n\n\t\t$(cardId).css(\"zIndex\", (parseInt($(cardId).css(\"zIndex\")) - zindexDifference).toString());\n\t\t\n\t\t$(CARDS_IN_HAND_DIV + \" img\").each(function() {\n\t\t\t$(this).css(\"opacity\", 1);\n\t\t});\n\t}\n}\n\nfunction setPlayerOpacity(currentUsername, targetName) {\n\t$(PLAYER_COLUMN_IMAGE).each(function() {\n\t\tvar id = $(this).attr(\"id\");\n\t\tif (id != (currentUsername + \"PlayerImage\") && !($(this).attr(\"src\").includes(\"roles/\"))) {\n\t\t\t$(this).css(\"opacity\", 0.25);\n\t\t}\n\t});\n}\n\nfunction questionModalIsOpen() {\n\treturn !(isNullOrUndefined($(QUESTION_MODAL).html())) && $(QUESTION_MODAL).is(':visible');\n}\n\nfunction infoModalIsOpen() {\n\treturn !(isNullOrUndefined($(INFO_MODAL).html())) && $(INFO_MODAL).html() != '';\n}\n\nfunction waitingModalIsOpen() {\n\treturn !(isNullOrUndefined($(INFO_MODAL).html())) && $(INFO_MODAL).html().includes(\"Waiting\");\n}\n\nfunction emporioModalIsOpen() {\n\treturn !(isNullOrUndefined($(INFO_MODAL).html())) && \n\t\t\t(($(INFO_MODAL).html().includes(\"Emporio</h4>\") && !($(INFO_MODAL).html().includes(\"Everyone is done\") || $(INFO_MODAL).html().includes(\"You picked up\")))\n\t\t\t|| $(INFO_MODAL).html().includes(\"Claus The Saint</h4>\"));\n}\n\nfunction kitCarlsonModalIsOpen() {\n\treturn !(isNullOrUndefined($(INFO_MODAL).html())) && $(INFO_MODAL).html().includes(\"Kit Carlson\");\n}\n\nfunction closeInfoModal() {\n\t$(INFO_MODAL).modal('hide');\n\t$(INFO_MODAL).html('');\n}\n\nfunction createCardHand(cardInfo) {\n\tlastCardUid = 0;\n\tvar minimumCardsForOverlap = 4;\n\tvar numberOfCards = cardInfo.length;\n\n\tvar cardsInHandSpanId = \"cardsInHandSpan\";\n\t$(CARDS_IN_HAND_DIV).html(\"<span id='\" + cardsInHandSpanId + \"' class='centered centered_text'></span>\");\n\n\tif (numberOfCards > 0) {\n\t\tif (numberOfCards >= minimumCardsForOverlap) {\n\t\t\tvar cardWidth = Math.floor($(CARDS_IN_HAND_DIV).outerWidth() / numberOfCards);\n\t\t\tvar overlapWidth = Math.floor(cardWidth / 5);\n\t\t\tvar cardsWidth = (2 * (cardWidth - overlapWidth)) + ((numberOfCards - 2) * (cardWidth - overlapWidth - overlapWidth));\n\t\t}\n\t\telse {\n\t\t\tvar cardWidth = Math.floor($(CARDS_IN_HAND_DIV).outerWidth() / minimumCardsForOverlap);\n\t\t\tvar overlapWidth = -25;\n\t\t\tvar cardsWidth = (numberOfCards * cardWidth) + ((numberOfCards - 1) * Math.abs(overlapWidth));\n\t\t}\n\t\t\n\t\tvar bufferWidth = Math.floor(($(CARDS_IN_HAND_DIV).outerWidth() - cardsWidth) / (numberOfCards >= minimumCardsForOverlap ? 4 : 2));\n\t\tvar cardWidthPercent = (cardWidth * 100) / $(CARDS_IN_HAND_DIV).outerWidth();\n\t\tvar overlapWidthPercent = (overlapWidth * 100) / $(CARDS_IN_HAND_DIV).outerWidth();\n\t\tvar imageLeftXPercent = (bufferWidth * 100) / $(CARDS_IN_HAND_DIV).outerWidth();\n\n\t\tfor (var i = 0; i < numberOfCards; i++) {\n\t\t\tvar url = \"static/images/cards/actions/\" + cardInfo[i].uid.toString() + \".jpg\";\n\t\t\tvar zoom_size = numberOfCards >= minimumCardsForOverlap ? (numberOfCards >= minimumCardsForOverlap * 2 ? \"2\" : \"1_5\") : \"1_2\"\n\t\t\tvar img = $('<img id=\"hand_card_' + cardInfo[i].uid.toString() + '\" class=\"zoom_hover_' + zoom_size + '\">');\n\t\t\timg.attr('src', url);\n\t\t\timg.attr('alt', cardInfo[i].name + \" \" + cardInfo[i].uid.toString())\n\t\t\t\n\t\t\tif (cardInfo[i].isCurrentPlayer) {\n\t\t\t\timg.attr('onclick', \"playCard(\" + cardInfo[i].uid.toString() + \")\");\n\t\t\t}\n\n\t\t\timg.css({\"position\": \"absolute\", \"max-width\": cardWidthPercent.toString() + '%', \"margin-left\": imageLeftXPercent + \"%\"});\n\n\t\t\timg.appendTo(CARDS_IN_HAND_DIV);\n\t\t\tsetImageAfterLoading(img);\n\n\t\t\timageLeftXPercent += (cardWidthPercent - overlapWidthPercent);\n\t\t}\n\t}\n\n\tvar usernameText = \"<span style='color: red;'>\" + username + \"</span>, \";\n\tvar cardText = cardInfo.length > 0 ? \"your current hand is:\" : \"you have no cards in your hand.\"\n\t$(\"#\" + cardsInHandSpanId).html(usernameText + cardText);\n\t$(\"#\" + cardsInHandSpanId).css(\"margin-top\", \"3%\");\n\t$(\"#\" + cardsInHandSpanId).addClass(\"play-text-header\");\n\tresetCardZIndeces();\n}\n\nfunction setImageAfterLoading(img){\n\twindow.setTimeout(function() {\n\t if (img.outerHeight() != 0) {\n\t\t\tvar marginTop = Math.floor(($(CARDS_IN_HAND_DIV).outerHeight() - img.outerHeight()) / 4);\n\t\t\timg.css(\"bottom\", marginTop.toString() + \"px\");\n\t\t\timg.show();\n\t }\n\t else {\n\t \timg.hide();\n\t\t\tsetImageAfterLoading(img);\n\t }\n\t}, 100);\n}\n\nfunction returnToLobby() {\n\tsocket.emit('return_to_lobby', username);\n}\n\nfunction rejoinGame() {\n\tsocket.emit('rejoin_game', username);\n}\n\nfunction playerClickedOn(targetName, clickType) {\n\tconsole.log(\"player clicked on\");\n\tif (new Date().getTime() - previousSocketTime >= (SOCKET_TIME_DIFFERENCE / 2)) {\n\t\tsocket.emit('player_clicked_on', username, targetName, clickType);\n\t\tclickingOnPlayer = false;\n\t\tcardsAreBlurred = false;\n\t\tupdatePreviousSocketTime();\n\t}\n}\n\nfunction abilityCardClickedOn(uid, clickType) {\n\tconsole.log(\"ability card clicked on\");\n\tif (new Date().getTime() - previousSocketTime >= (SOCKET_TIME_DIFFERENCE / 2)) {\n\t\tsocket.emit('ability_card_clicked_on', username, uid, clickType);\n\t}\n}\n\nfunction updatePreviousSocketTime() {\n\tpreviousSocketTime = new Date().getTime();\n}\n\n/* Key press functions to enable players to send messages to the server using keyboard strokes. */\n\n$(document).keydown(function (e) {\n\tif (KEYCODES_LIST.includes(e.which))\n\t{\n\t\tvar isRepeating = !!keysPressed[e.which];\n\t\tconsole.log(\"keydown\", e.which, keysPressed);\n\n\t\tif (!isRepeating) {\n\t\t keysPressed[e.which] = true;\n\t\t var numKeys = Object.keys(keysPressed).length;\n\n\t\t if (numKeys == 2) {\n\t\t\t if (16 in keysPressed) {\n\t\t\t\t if (e.which == 69) { // Shift-E, to end the turn.\n\t\t\t\t \tsocket.emit('ending_turn', username);\n\t\t\t\t \tconsole.log(\"shift e\");\n\t\t\t\t }\n\n\t\t\t\t else if (e.which == 67) { // Shift-C, to cancel the current action.\n\t\t\t\t \tsocket.emit('cancel_current_action', username);\n\t\t\t\t \tconsole.log(\"shift c\");\n\n\t\t\t\t \tlastCardUid = 0;\n\t\t\t \t\tclickingOnPlayer = false;\n\t\t\t \t\tcardsAreBlurred = false;\n\t\t\t \t\tcreateCardHand(currentCardHandInfo);\n\t\t\t \t\tsetPlayerClicks();\n\t\t\t\t }\n\n\t\t\t\t else if (e.which == 83) { // Shift-S, to trigger a special ability when applicable.\n\t\t\t\t \tsocket.emit('use_special_ability', username);\n\t\t\t\t \tconsole.log(\"shift s\");\n\t\t\t\t }\n\t\t\t\t}\n\t\t\t}\n\n\t\t\tif (numKeys == 1) {\n\t\t\t\tif (13 in keysPressed) { // Enter, to close the info modal if it's open.\n\t\t\t\t\tif ($(QUESTION_MODAL).is(':visible')) {\n\t\t\t\t\t\te.preventDefault();\n\t\t\t\t\t}\n\n\t\t\t\t\tif (!waitingModalIsOpen() && !emporioModalIsOpen() && !kitCarlsonModalIsOpen()) {\n\t\t\t\t\t\tcloseInfoModal();\n\t\t\t\t\t}\n\t\t\t\t}\n\t\t\t}\n\t\t}\n\t}\n});\n\n$(document).keyup(function (e) {\n\tif (KEYCODES_LIST.includes(e.which)) {\n\t delete keysPressed[e.which];\n\t}\n});"
},
{
"alpha_fraction": 0.6520450711250305,
"alphanum_fraction": 0.69413161277771,
"avg_line_length": 20.367088317871094,
"blob_id": "7b03397046c9a195e957ac25aa5052868fcc9f47",
"content_id": "664541ff8c9dc0211f8427b178723255b28802f5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1687,
"license_type": "no_license",
"max_line_length": 82,
"num_lines": 79,
"path": "/static/library/card.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "from static.library import utils\nfrom static.library.constants import QUESTION_CARD_FORMAT, DYNAMITE\nimport json\n\n'''\nUID mapping:\n\t1-25 = bang\n\t26-37 = mancato\n\t38-41 = panico\n\t42-47 = birra\n\t48-49 = emporio\n\t50-53 = cat balou\n\t54 = gatling\n\t55-57 = duello\n\t58-59 = indians\n\t60 = saloon\n\t61-62 = diligenza\n\t63 = wells fargo\n\t64-65 = barile\n\t66 = scope\n\t67-68 = mustang\n\t69-71 = prigione\n\t72 = dynamite\n\t73-74 = volcanic\n\t75-77 = schofield\n\t78 = remington\n\t79 = rev carabine\n\t80 = winchester\n'''\nclass Card(dict):\n\tdef __init__(self, name, uid, cardtype, requiresTarget, suitValue):\n\t\tself.name = name\n\t\tself.uid = uid\n\t\tself.cardtype = cardtype\n\t\tself.requiresTarget = requiresTarget\n\t\tself.value, self.suit = suitValue.split()\n\n\t\tdict.__init__(self)\n\n\tdef __repr__(self):\n\t\treturn self.__str__()\n\n\tdef __str__(self):\n\t\treturn str(vars(self))\n\n\tdef __eq__(self, other):\n\t\tif not isinstance(other, Card):\n\t\t\treturn False\n\n\t\treturn self.uid == other.uid\n\n\tdef __ne__(self, other):\n\t\tif not isinstance(other, Card):\n\t\t\treturn True\n\n\t\treturn self.uid != other.uid\n\n\tdef getDisplayName(self):\n\t\treturn utils.convertRawNameToDisplay(self.name)\n\n\tdef getDeterminerString(self):\n\t\tif self.name == DYNAMITE:\n\t\t\treturn \"the Dynamite\"\n\t\telse:\n\t\t\treturn utils.getDeterminerString(self.name)\n\n\tdef getQuestionString(self):\n\t\treturn QUESTION_CARD_FORMAT.format(self.getDisplayName(), self.value, self.suit)\n\nclass GunCard(Card):\n\tdef __init__(self, name, uid, cardtype, requiresTarget, gunRange, suitValue):\n\t\tself.name = name\n\t\tself.uid = uid\n\t\tself.cardtype = cardtype\n\t\tself.requiresTarget = requiresTarget\n\t\tself.range = gunRange\n\t\tself.value, self.suit = suitValue.split()\n\n\t\tdict.__init__(self)"
},
{
"alpha_fraction": 0.688524603843689,
"alphanum_fraction": 0.688524603843689,
"avg_line_length": 30,
"blob_id": "739e5678c1f6ee6559d7829894e7c7a62e01aeaa",
"content_id": "d7c360b87f20b01ffbd9d773096170c573fc1e34",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 61,
"license_type": "no_license",
"max_line_length": 35,
"num_lines": 2,
"path": "/static/library/jinjafunctions.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "def convertNameToPath(s):\n\treturn \"_\".join(s.lower().split())"
},
{
"alpha_fraction": 0.719648540019989,
"alphanum_fraction": 0.7215122580528259,
"avg_line_length": 37.137054443359375,
"blob_id": "236c51bb753f364e241d8dfaf1b4b59bf4997ec8",
"content_id": "7cf1452766bd5215bd613f4de9943b61809b299c",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 7512,
"license_type": "no_license",
"max_line_length": 128,
"num_lines": 197,
"path": "/static/library/constants.py",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "# Roles.\nSHERIFF = \"Sheriff\"\nVICE = \"Vice\"\nOUTLAW = \"Outlaw\"\nRENEGADE = \"Renegade\"\n\n# Regular characters.\nBART_CASSIDY = \"Bart Cassidy\"\nBLACK_JACK = \"Black Jack\"\nCALAMITY_JANET = \"Calamity Janet\"\nEL_GRINGO = \"El Gringo\"\nJESSE_JONES = \"Jesse Jones\"\nJOURDONNAIS = \"Jourdonnais\"\nKIT_CARLSON = \"Kit Carlson\"\nLUCKY_DUKE = \"Lucky Duke\"\nPAUL_REGRET = \"Paul Regret\"\nPEDRO_RAMIREZ = \"Pedro Ramirez\"\nROSE_DOOLAN = \"Rose Doolan\"\nSID_KETCHUM = \"Sid Ketchum\"\nSLAB_THE_KILLER = \"Slab The Killer\"\nSUZY_LAFAYETTE = \"Suzy Lafayette\"\nVULTURE_SAM = \"Vulture Sam\"\nWILLY_THE_KID = \"Willy The Kid\"\n\n# Expansion characters.\nAPACHE_KID = \"Apache Kid\"\nBELLE_STAR = \"Belle Star\"\nBILL_NOFACE = \"Bill Noface\"\nCHUCK_WENGAM = \"Chuck Wengam\"\nCLAUS_THE_SAINT = \"Claus The Saint\"\nDOC_HOLLYDAY = \"Doc Hollyday\"\nELENA_FUENTE = \"Elena Fuente\"\nGREG_DIGGER = \"Greg Digger\"\nHERB_HUNTER = \"Herb Hunter\"\nJOHNNY_KISCH = \"Johnny Kisch\"\nJOSE_DELGADO = \"Jose Delgado\"\nMOLLY_STARK = \"Molly Stark\"\nPAT_BRENNAN = \"Pat Brennan\"\nPIXIE_PETE = \"Pixie Pete\"\nSEAN_MALLORY = \"Sean Mallory\"\nTEQUILA_JOE = \"Tequila Joe\"\nUNCLE_WILL = \"Uncle Will\"\nVERA_CUSTER = \"Vera Custer\"\n\n# Cards.\nBANG = \"bang\"\nMANCATO = \"mancato\"\nPANICO = \"panico\"\nBIRRA = \"birra\"\nEMPORIO = \"emporio\"\nCAT_BALOU = \"cat_balou\"\nGATLING = \"gatling\"\nDUELLO = \"duello\"\nINDIANS = \"indians\"\nSALOON = \"saloon\"\nDILIGENZA = \"diligenza\"\nWELLS_FARGO = \"wells_fargo\"\nBARILE = \"barile\"\nSCOPE = \"scope\"\nMUSTANG = \"mustang\"\nDYNAMITE = \"dynamite\"\nPRIGIONE = \"prigione\"\nSCHOFIELD = \"schofield\"\nVOLCANIC = \"volcanic\"\nWINCHESTER = \"winchester\"\nREV_CARABINE = \"rev_carabine\"\nREMINGTON = \"remington\"\n\n# Card types.\nREGULAR_CARD = \"regular\"\nBLUE_CARD = \"blue\"\nGUN_CARD = \"gun\"\nSPECIAL_CARD = \"special\"\n\n# Suits.\nHEART = \"heart\"\nDIAMOND = \"diamond\"\nSPADE = \"spade\"\nCLUB = \"club\"\n\n# Constants for questions asked in the question modal.\nQUESTION_JESSE_JONES = \"For your first card, do you want to draw randomly from the hand of another player or from the deck?\"\nQUESTION_KIT_CARLSON = \"Which of these 3 cards do you want to put back onto the top of the deck?\"\nQUESTION_PEDRO_RAMIREZ = \"For your first card, do you want to draw from the top of the discard pile or the deck?\"\nQUESTION_PAT_BRENNAN = \"Do you want to draw 1 card from someone's in-play cards, or draw 2 from the deck?\"\nQUESTION_PAT_BRENNAN_CARD = \"Which in-play card of {}'s do you want to take?\"\nQUESTION_LUCKY_DUKE = \"You need to \\\"draw!\\\" for {}. Which card do you choose? Both get discarded, but your choice goes on top.\"\nQUESTION_WHOSE_HAND = \"Whose hand do you want to draw from?\"\nQUESTION_WHOSE_CARDS = \"Whose cards do you want to target?\"\nQUESTION_BANG_REACTION = \"{} played a Bang against you! How do you want to react?\"\nQUESTION_INDIANS_REACTION = \"{} played an Indians! How do you want to react?\"\nQUESTION_GATLING_REACTION = \"{} played a Gatling! How do you want to react?\"\nQUESTION_DUELLO_REACTION = \"{} played a Duello against you! How do you want to react?\"\nQUESTION_DUELLO_BANG_REACTION = \"{} played a Bang in response! How do you want to react?\"\nQUESTION_PANICO_CARDS = \"You can either steal from {}'s hand, or select an in-play card of theirs to steal.\"\nQUESTION_CAT_BALOU_CARDS = \"You can force {} to discard a card from their hand, or select an in-play card for them to discard.\"\nQUESTION_CARD_ON_TABLE = \"Which one of {}'s cards on the table do you choose for {}?\"\nQUESTION_IN_PLAY = \"You already have 2 cards in play! What do you want to do?\"\nQUESTION_REPLACE_GUN = \"You already have a gun in play! Do you want to replace it?\"\nQUESTION_CARD_IN_PLAY = \"Which of your 2 cards in play do you want to replace?\"\nQUESTION_BARILE_MANCATO = \"You didn't draw a heart for Barile against {}'s {}, so you still need a Mancato.\"\nQUESTION_SLAB_BARILE_ONE = \"You drew a heart for Barile against {}'s Bang, but you still need one Mancato.\"\nQUESTION_SLAB_BARILE_TWO = \"You didn't draw a heart for Barile against {}'s Bang, so you still need two Mancatos.\"\n\n# Constants for possible responses to the above questions.\nFROM_THE_DECK = \"From the deck\"\nFROM_ANOTHER_PLAYER = \"From another player\"\nFROM_IN_PLAY = \"From someone's in-play cards\"\nFROM_DISCARD = \"From the discard pile\"\nFROM_THEIR_HAND = \"From their hand\"\nPLAY_A_BANG = \"Play a Bang\"\nPLAY_A_MANCATO = \"Play a Mancato\"\nPLAY_TWO_MANCATOS = \"Play 2 Mancatos\"\nLOSE_A_LIFE = \"Lose a life\"\nREPLACE_GUN = \"Yes, discard my {} and play the {}\"\nNEVER_MIND = \"Never mind\"\n\n# Constants for outgoing socket message names.\nLOBBY_PLAYER_UPDATE = \"lobby_player_update\"\nSHOW_START_BUTTON = \"show_start_button\"\nHIDE_START_BUTTON = \"hide_start_button\"\nRELOAD_LOBBY = \"reload_lobby\"\nSTART_GAME = \"start_game\"\nSHOW_INFO_MODAL = \"show_info_modal\"\nSHOW_QUESTION_MODAL = \"show_question_modal\"\nSHOW_WAITING_MODAL = \"show_waiting_modal\"\nUPDATE_ACTION = \"update_action\"\nHEALTH_ANIMATION = \"health_animation\"\nBLUR_CARD_SELECTION = \"blur_card_selection\"\nRESET_CARD_CLICK_FUNCTIONS = \"reset_card_click_functions\"\nUPDATE_CARD_HAND = \"update_card_hand\"\nUPDATE_CARDS_IN_PLAY = \"update_cards_in_play\"\nUPDATE_DISCARD_PILE = \"update_discard_pile\"\nUPDATE_PLAYER_LIST = \"update_player_list\"\nDISCARD_CLICK = \"discard_click\"\nEND_YOUR_TURN = \"end_your_turn\"\nRELOAD_PLAY_PAGE = \"reload_play_page\"\nCREATE_CLICK_ON_PLAYERS = \"create_click_on_players\"\nSET_PLAYER_OPACITY = \"set_player_opacity\"\nSLEEP = \"sleep\"\nGAME_OVER = \"game_over\"\n\n# Constants for incoming socket message names.\nKEEP_ALIVE = \"keep_alive\"\nCONNECTED = \"connected\"\nDISCONNECT = \"disconnect\"\nLEAVE_LOBBY = \"leave_lobby\"\nRETURN_TO_LOBBY = \"return_to_lobby\"\nREJOIN_GAME = \"rejoin_game\"\nSTART_BUTTON_CLICKED = \"start_button_clicked\"\nSET_CHARACTER = \"set_character\"\nVALIDATE_CARD_CHOICE = \"validate_card_choice\"\nINFO_MODAL_UNDEFINED = \"info_modal_undefined\"\nQUESTION_MODAL_UNDEFINED = \"question_modal_undefined\"\nQUESTION_MODAL_ANSWERED = \"question_modal_answered\"\nBLUR_CARD_PLAYED = \"blur_card_played\"\nEMPORIO_CARD_PICKED = \"emporio_card_picked\"\nENDING_TURN = \"ending_turn\"\nCANCEL_CURRENT_ACTION = \"cancel_current_action\"\nDISCARDING_CARD = \"discarding_card\"\nUSE_SPECIAL_ABILITY = \"use_special_ability\"\nREQUEST_PLAYER_LIST = \"request_player_list\"\nKIT_CARLSON_CARD_PICKED = \"kit_carlson_card_picked\"\nPLAYER_CLICKED_ON = \"player_clicked_on\"\nABILITY_CARD_CLICKED_ON = \"ability_card_clicked_on\"\nCLAUS_THE_SAINT_CARD_PICKED = \"claus_the_saint_card_picked\"\n\n# Constants for modals and the update screen.\nQUESTION_CARD_FORMAT = \"{} ({} of {}s)\"\nALREADY_MAX_LIVES = \"You're already at your life limit!\"\nCLICK_ON_CARD = \"Click on the {} in your hand that you want to use.\"\nDREW_2_CARDS = \"{} drew 2 cards from the deck.\"\nPICKED_UP_FROM_EMPORIO = \"{} picked up {} from Emporio.\"\nPICKED_FOR_CLAUS_THE_SAINT = \"{} picked a card to give to {}.\"\nWAITING_DUELLO_REACTION = \"Waiting for {} to decide how to react to Duello...\"\nBANG_AS_MANCATO = \"Bang (as a Mancato)\"\nMANCATO_AS_BANG = \"Mancato (as a Bang)\"\nSID_KETCHUM_INFO = \"Click on the 2 cards in your hand that you want to discard in order to gain a life.\"\nDOC_HOLLYDAY_INFO = \"Click on the 2 cards in your hand that you want to discard in order to use a Bang.\"\n\n# Constants for click types.\nEMPORIO_CLICK = \"pickEmporioCard\"\nTARGETED_CARD_PLAYER_CLICK = \"targeted_card_player_click\"\nSPECIAL_ABILITY_CARD_CLICK = \"special_ability_card_click\"\nJESSE_JONES_CLICK = \"jesse_jones_click\"\nDOC_HOLLYDAY_CLICK = \"doc_hollyday_click\"\nPAT_BRENNAN_CLICK = \"pat_brennan_click\"\nJOSE_DELGADO_CLICK = \"jose_delgado_click\"\nUNCLE_WILL_CLICK = \"uncle_will_click\"\nCLAUS_THE_SAINT_CLICK = \"pickClausTheSaintCard\"\n\nJSON_GAME_PATH = \"game_saves/{}.json\"\nOK_MSG = \"OK\"\nEMPTY_RESPONSE = ('', 204)\nFLIPPED_OVER = \"flipped_over\"\nCARD_IMAGES_PATH = \"static/images/cards/actions/{}.jpg\"\nAUTOMATIC_SLEEP_DURATION = 4"
},
{
"alpha_fraction": 0.5497835278511047,
"alphanum_fraction": 0.5497835278511047,
"avg_line_length": 28,
"blob_id": "0b887a0e8d5fb33e4aa67cbec6f9c621c33c0255",
"content_id": "ea18d4ac46a6a026e0f7b3f216f12ec49cd533cc",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 231,
"license_type": "no_license",
"max_line_length": 100,
"num_lines": 8,
"path": "/templates/game_started.html",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "{% extends \"skeleton.html\" %}\n{% block content %}\n <body>\n <div class=\"outer\">\n <p class=\"game_started_msg\">Sorry, you're out of luck! The game has already started.</p>\n </div>\n </body>\n{% endblock %}"
},
{
"alpha_fraction": 0.5043478012084961,
"alphanum_fraction": 0.519565224647522,
"avg_line_length": 37.41666793823242,
"blob_id": "6fa9690984aaae9481d16071bbe2683be45f6305",
"content_id": "5bc9f3cd3bf99e71a3f477726c9b237f26c35b6d",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "HTML",
"length_bytes": 460,
"license_type": "no_license",
"max_line_length": 110,
"num_lines": 12,
"path": "/templates/rejoin_game.html",
"repo_name": "Nighthawkeye449/bang",
"src_encoding": "UTF-8",
"text": "{% extends \"skeleton.html\" %}\n{% block content %}\n <body>\n <div class=\"outer\">\n <h1 class=\"bang-title\" style=\"font-size: 150px;\">Bang!</h1>\n <div class=\"middle\">\n <br><br><span style=\"font-size: 30px;\">Welcome, {{ username }}!</span><br><br>\n <button class=\"btn bang-button\" type=\"button\" onclick=\"rejoinGame()\">Rejoin Your Game</button>\n </div>\n </div>\n </body>\n{% endblock %}"
}
] | 15
|
kuenane/stunning-chainsaw
|
https://github.com/kuenane/stunning-chainsaw
|
190bf1ec71f8a67c5fd6fa71ddbba43e71b09c3d
|
613ea45184b209cf2b49a67a7fe5309e71376e37
|
83044b1d91ed0461c0f63d3575dfec76b185c4a3
|
refs/heads/main
| 2023-07-16T19:14:18.962580
| 2021-08-21T10:59:58
| 2021-08-21T10:59:58
| 398,524,202
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6606606841087341,
"alphanum_fraction": 0.6606606841087341,
"avg_line_length": 29.363636016845703,
"blob_id": "6fa78b47dc3b85be35e1c529441f8e20f1a62d34",
"content_id": "7e77963d1a87559a60e33516a054359372638100",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 333,
"license_type": "permissive",
"max_line_length": 53,
"num_lines": 11,
"path": "/api/urls.py",
"repo_name": "kuenane/stunning-chainsaw",
"src_encoding": "UTF-8",
"text": "from django.urls import path\nfrom .import views\n\nurlpatterns = [\n path('',views.getRoutes),\n path('notes/', views.getNotes),\n path('notes/create/', views.createNote),\n path('notes/<str:pk>/update/', views.updateNote),\n path('notes/<str:pk>/delete/', views.deleteNote),\n path('notes/<str:pk>/', views.getNoteById),\n]"
},
{
"alpha_fraction": 0.5755833387374878,
"alphanum_fraction": 0.5755833387374878,
"avg_line_length": 24.213674545288086,
"blob_id": "1c28d3f0e154291db18f66aea93fbe3b62e5b31b",
"content_id": "bce87191dab8987d41d79efc4445e7ea6a7204e3",
"detected_licenses": [
"Apache-2.0"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2957,
"license_type": "permissive",
"max_line_length": 83,
"num_lines": 117,
"path": "/api/views.py",
"repo_name": "kuenane/stunning-chainsaw",
"src_encoding": "UTF-8",
"text": "from rest_framework.decorators import api_view\nfrom rest_framework.response import Response\nfrom .serializers import NoteSerializer\nfrom .models import Note\n\ndef getRoutes(request):\n routes = [\n {\n 'Endpoint': '/notes',\n 'method': 'GET',\n 'body' : None,\n 'description': 'Returns an array of notes'\n\n },\n {\n 'Endpoint': '/notes/id',\n 'method': 'GET',\n 'body' : None,\n 'description': 'Returns a single note object'\n\n },\n {\n 'Endpoint': '/notes/create',\n 'method': 'POST',\n 'body' : {'body': \"\"},\n 'description': 'Creates new note with data sent in post request'\n\n },\n {\n 'Endpoint': '/notes/id/update/',\n 'method': 'PUT',\n 'body' : {'body': \"\"},\n 'description': 'Creates an existing note with data sent in put request'\n\n },\n {\n 'Endpoint': '/notes/id/delete/',\n 'method': 'DELETE',\n 'body' : None,\n 'description': 'Deletes an existing note'\n\n },\n {\n 'Endpoint': '/notes',\n 'method': 'GET',\n 'body' : None,\n 'description': 'Returns an array of notes'\n\n }\n ]\n\n return Response(routes)\n\n@api_view(['GET'])\ndef getNotes(request):\n #query the database\n notes = Note.objects.all()\n #Use NoteSerializer to serialize multiple data objects\n serializer = NoteSerializer(notes, many=True)\n return Response(serializer.data)\n\n@api_view(['GET'])\n#Serialize data\ndef getNoteById(request, pk):\n #query the database by primary key\n note = Note.objects.get(id=pk)\n #Use NoteSerializer to serialize a single data object\n serializer = NoteSerializer(note, many=False)\n return Response(serializer.data)\n\n@api_view(['POST'])\ndef createNote(request):\n data = request.data\n\n note = Note.objects.create(\n body = data['body']\n )\n serializer = NoteSerializer(note, many=False)\n return Response(serializer.data)\n\n@api_view(['POST'])\ndef createNote(request):\n data = request.data\n\n note = Note.objects.create(\n body = data['body']\n )\n serializer = NoteSerializer(note, many=False)\n return Response(serializer.data)\n\n\n@api_view(['POST'])\ndef createNote(request):\n data = request.data\n\n note = Note.objects.create(\n body = data['body']\n )\n serializer = NoteSerializer(note, many=False)\n return Response(serializer.data)\n\n@api_view(['PUT'])\ndef updateNote(request,pk):\n data = request.data\n \n note = Note.objects.get(id=pk)\n serializer = NoteSerializer(note, data=request.data)\n if serializer.is_valid():\n serializer.save()\n return Response(serializer.data)\n\n@api_view(['DELETE'])\ndef deleteNote(request,pk):\n \n note = Note.objects.get(id=pk)\n note.delete()\n return Response(\"Note deleted \")\n \n\n\n"
}
] | 2
|
puran1218/python-encode-decode
|
https://github.com/puran1218/python-encode-decode
|
66e377bc2025dab290f4361d81e4b723bce90455
|
ffd545aa5104f92b409d53516a684103b7ff82db
|
3ebe53befa3ca97eba1e3e841d22c6ebc6d53c61
|
refs/heads/master
| 2021-04-09T23:10:34.031494
| 2020-03-21T02:12:01
| 2020-03-21T02:12:01
| 248,890,728
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.6318864822387695,
"alphanum_fraction": 0.6519198417663574,
"avg_line_length": 29.743589401245117,
"blob_id": "a5cc6b08f5ee0d792283effbaa884551eb870bbe",
"content_id": "a3ffec271cde0721cee57442e5f2b48cc8997692",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1198,
"license_type": "no_license",
"max_line_length": 109,
"num_lines": 39,
"path": "/base64_encode_decode_file.py",
"repo_name": "puran1218/python-encode-decode",
"src_encoding": "UTF-8",
"text": "from __future__ import (absolute_import, division, print_function, unicode_literals)\nimport json\nimport base64\n\nfilepath = 'encoded.json'\n# filepath = 'raw_text.json'\nwith open(filepath, 'rb') as file:\n contents = json.load(file)\n\nfor items in contents:\n encoded = int(items['encode'])\n title = items['title']\n content = items['content']\n # print(\"encode is {}, title type is {}, content type is {}\".format(encoded, type(title), type(content)))\n\ndef encode_base64(data):\n encoded = base64.b64encode(data.encode())\n print(\"\\n---> Encoded message is: \" + encoded.decode())\n\n return encoded\n\ndef decode_base64(data):\n decoded = base64.b64decode(data.encode()).decode()\n print(\"\\n---> Decoded message is: \" + str(decoded))\n\n return decoded\n\nif encoded == 0:\n print(\"\\nOriginal Title: \" + title, end='')\n encode_base64(title)\n print(\"\\nOriginal Content: \" + content, end='')\n encode_base64(content)\nelif encoded == 1:\n print(\"\\nEncoded Title: \" + title, end='')\n decode_base64(title)\n print(\"\\nEncoded Content: \" + content, end='')\n decode_base64(content)\nelse:\n print(\"\\nThe format of your json file should be encode: ,title: ,content:, ***\")"
},
{
"alpha_fraction": 0.6752577424049377,
"alphanum_fraction": 0.7061855792999268,
"avg_line_length": 26.761905670166016,
"blob_id": "f40dc96be9da89281f609176b561e369778782a9",
"content_id": "56665a3f67cda925c5cb0bdf20b7fc0dc893ec4e",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 582,
"license_type": "no_license",
"max_line_length": 84,
"num_lines": 21,
"path": "/get_contents.py",
"repo_name": "puran1218/python-encode-decode",
"src_encoding": "UTF-8",
"text": "from __future__ import (absolute_import, division, print_function, unicode_literals)\nimport base64\n\ndef encode_base64(data):\n encoded = base64.b64encode(data.encode())\n print(\"\\n---> Encoded message is: \" + encoded.decode())\n\n return encoded\n\ndef decode_base64(data):\n decoded = base64.b64decode(data).decode()\n print(\"\\n---> Decoded message is: \" + str(decoded))\n\n return decoded\n\nfilepath = 'raw_text.txt'\nwith open(filepath) as file:\n contents = file.read()\n\nencoded_contents = encode_base64(contents)\ndecoded_again_contents = decode_base64(encoded_contents)"
},
{
"alpha_fraction": 0.617521345615387,
"alphanum_fraction": 0.6367521286010742,
"avg_line_length": 30.233333587646484,
"blob_id": "0089cde3a90c1e5632a99798a0906398e125efcd",
"content_id": "2df6444ea6058fc70f8508ad34df7cf6a6d6b842",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 936,
"license_type": "no_license",
"max_line_length": 124,
"num_lines": 30,
"path": "/base64_encode_decode.py",
"repo_name": "puran1218/python-encode-decode",
"src_encoding": "UTF-8",
"text": "import base64\n\ndef encode_base64(data):\n encoded = base64.b64encode(data.encode())\n print(\"\\n---> Encoded message is: \" + encoded.decode())\n\n return encoded\n\ndef decode_base64(data):\n decoded = base64.b64decode(data.encode()).decode()\n print(\"\\n---> Decoded message is: \" + str(decoded))\n\n return decoded\n\nprompt = \"\\nDo you want to encode or decode message? Or you can enter 'quit' to end the program. 'encode'/'decode'/'quit': \"\n\nactive = True\nwhile active:\n message = input(prompt)\n\n if message == 'encode':\n encode_message = input(\"\\nPlease input the message you want to encode: \")\n encode_base64(encode_message)\n elif message == 'decode':\n decode_message = input(\"\\nPlease input the message you want to decode: \")\n decode_base64(decode_message)\n elif message == 'quit':\n active = False\n else:\n print(\"\\n*** Please input 'encode', 'decode', or 'quit'. ***\")"
}
] | 3
|
thedewangan/binance_collector
|
https://github.com/thedewangan/binance_collector
|
2df28a5b4d370b341986481b1f471d6adfb28572
|
923ea5ebd304d071e8b5fbffaa65283505def018
|
b9869f1c4f4bd6973ddd4c493e0f0888ca19b5e3
|
refs/heads/main
| 2023-06-26T19:32:47.746211
| 2021-07-20T07:09:38
| 2021-07-20T07:09:38
| 386,755,691
| 0
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.47389885783195496,
"alphanum_fraction": 0.48409461975097656,
"avg_line_length": 38.5,
"blob_id": "5bb03f1bd13b67ee080f1ca2741775c209577ad1",
"content_id": "a3175a9c514918a8686249de17320bffbfef1e95",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2452,
"license_type": "no_license",
"max_line_length": 95,
"num_lines": 62,
"path": "/processor.py",
"repo_name": "thedewangan/binance_collector",
"src_encoding": "UTF-8",
"text": "from datetime import datetime\nimport logging\n\ndef set_processor_log_config(name):\n logging.basicConfig(filename=name, level=logging.INFO)\n\n#-------------------------------------------------------------------------------\n\ndef process(query_result, md):\n #inp is query result while md is a dict\n for row in query_result:\n market = row[1]\n if(md.__contains__(market) == False):\n md[market] = list(row)\n else:\n md[market][3] = max(md[market][3], row[3]) # high \n md[market][4] = min(md[market][4], row[4]) # low\n md[market][5] = row[5] # close\n md[market][6] += row[6] # volume\n\n#-------------------------------------------------------------------------------\n\ndef get_table_name(period):\n return {\n 5: (\"one_min\", \"five_min\"),\n 15: (\"five_min\", \"fifteen_min\"),\n 30: (\"fifteen_min\", \"thirty_min\"),\n 60: (\"thirty_min\", \"one_hour\")\n }.get(period)\n\n#-------------------------------------------------------------------------------\n\ndef data_processor(period, cur_min, conn):\n logging.info(\"DATA PROCESSOR: \" + str(period) + \" min\")\n\n (in_table, out_table) = get_table_name(period)\n start = datetime.utcfromtimestamp((cur_min-period)*60)\n end = datetime.utcfromtimestamp((cur_min-1)*60)\n\n query = \"SELECT * FROM \" + in_table + \" WHERE time BETWEEN %s AND %s order by time\"\n data = (start, end)\n try:\n cursor = conn.cursor()\n cursor.execute(query, data)\n result = cursor.fetchall()\n d = {}\n process(result, d)\n query = \"INSERT INTO \" + out_table + \" VALUES (%s, %s, %s, %s, %s, %s, %s)\"\n for market, row in d.items():\n # bug fix: do not take non border values as open time \n # happens in case of missing border values in input tables\n row[0] = min(row[0], start)\n try:\n cursor.execute(query, tuple(row))\n conn.commit()\n except Exception as e:\n conn.rollback()\n logging.error(\"Processor \" + str(period) + \" min\\t{}\".format(type(e).__name__))\n logging.error(\"Processor \" + str(period) + \" min\\t{}\".format(e))\n except Exception as e:\n logging.error(\"Processor \" + str(period) + \" min\\t{}\".format(type(e).__name__))\n logging.error(\"Processor \" + str(period) + \" min\\t{}\".format(e))\n\n\n\n"
},
{
"alpha_fraction": 0.5728487372398376,
"alphanum_fraction": 0.591332733631134,
"avg_line_length": 35.568180084228516,
"blob_id": "9128a821b1ddcd8da3f123043c4c321076b2f305",
"content_id": "1fad2001bb3195a523a8e4fddb21e08fb267cdd5",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 6438,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 176,
"path": "/reporter.py",
"repo_name": "thedewangan/binance_collector",
"src_encoding": "UTF-8",
"text": "import re\nimport smtplib, ssl\nfrom datetime import datetime\nfrom time import strftime\nimport json\nimport sys\nimport logging\nimport asyncio\nfrom util import *\nimport getpass\n\nconfig_file = \"config.test.json\" if(len(sys.argv)>1 and str(sys.argv[1]) == \"test\") else \"config.json\"\n\nwith open(config_file) as json_data_file:\n config = json.load(json_data_file)\n\nlogging.basicConfig(filename=config['reporter_log_file'], level=logging.INFO)\nINTERVAL_IN_SEC = config['reporter_interval_seconds']\n\n# start time in millis\nf = open(\"binance_collector_info\", \"r\")\nstart_time = int(f.readline()) \nmarket_total_count = int(f.readline()) \nf.close()\n\nmarket_limit = min(config['market_limit'], market_total_count)\nport = config['port']\n\ndbcon= config['mysql']\ndb_pass = getpass.getpass(\"Enter mysql password: \")\nmail_pass = getpass.getpass(\"Enter e-mail password: \")\n\nsmtp_server = config['smtp_server']\nsender = config['sender_email']\nreceivers = config['receiver_emails']\n\n#-------------------------------------------------------------------------------\n\ndef get_table_name(period):\n return {\n 5: \"five_min\",\n 15: \"fifteen_min\",\n 30: \"thirty_min\",\n 60: \"one_hour\"\n }.get(period)\n\n#-------------------------------------------------------------------------------\n\ndef get_count(period, params):\n\n end_time = params['end_time']\n start_time = end_time - INTERVAL_IN_SEC*1000\n end_time -= 60*1000\n # subtracting 1 min from end since SQL between is inclusive and we want exlusive\n\n end = datetime.utcfromtimestamp(end_time/1000)\n start = datetime.utcfromtimestamp(start_time/1000)\n \n start_str = ''.join(start.strftime(\"%Y-%m-%d %H:%M:%S\"))\n end_str = ''.join(end.strftime(\"%Y-%m-%d %H:%M:%S\"))\n\n # print(\"Period: \", period, \"\\tStart: \", start_str, \"\\tEnd: \", end_str)\n logging.info(\"Period: \" + str(period) + \"\\tStart: \" + start_str + \"\\tEnd: \" + end_str)\n\n table_name = get_table_name(period)\n query = \"SELECT COUNT(time) FROM \" + table_name + \" WHERE time BETWEEN %s AND %s \"\n data = (start, end)\n try:\n cursor = params['conn'].cursor()\n cursor.execute(query, data)\n result = cursor.fetchone()\n except Exception as e:\n logging.error(\"Reporter {}\".format(type(e).__name__))\n logging.error(\"Reporter {}\".format(e))\n return 0\n return result[0]\n\n#-------------------------------------------------------------------------------\n\ndef send_mails(receivers, message):\n context = ssl.create_default_context()\n with smtplib.SMTP_SSL(smtp_server, port, context=context) as server:\n for receiver in receivers:\n logging.info(\"Sending mail to: \" + receiver)\n try:\n server.login(sender, mail_pass)\n server.sendmail(sender, receiver, message)\n except Exception as e:\n logging.error(\"Reporter {}\".format(type(e).__name__))\n logging.error(\"Reporter {}\".format(e))\n\n#-------------------------------------------------------------------------------\n\nasync def send_report():\n\n min_in_millis = get_cur_min() \n min_in_millis = min_in_millis - (min_in_millis % (config['reporting_time_divisor']*1000))\n\n # uptime in millis\n uptime = min_in_millis - start_time\n \n # expected count per market\n expected = {}\n periods = [5, 15, 30, 60]\n for p in periods:\n expected[p] = INTERVAL_IN_SEC/(p*60) \n \n try:\n conn = create_connection(dbcon, db_pass)\n except Exception as e:\n logging.error(\"Collector\" + \"\\t{}\".format(type(e).__name__))\n logging.error(\"Collector\" + \"\\t{}\".format(e))\n return\n\n params = {\n 'conn': conn,\n 'end_time': min_in_millis\n }\n p1 = round(get_count(5, params)/(expected[5]*market_limit)*100, 2)\n p2 = round(get_count(15, params)/(expected[15]*market_limit)*100, 2)\n p3 = round(get_count(30, params)/(expected[30]*market_limit)*100, 2)\n p4 = round(get_count(60, params)/(expected[60]*market_limit)*100, 2)\n conn.close()\n\n data = {\n 'Number of markets present in exchange': market_total_count,\n 'Number of markets after limiting': market_limit,\n 'Number of data points expected in last one interval for 5 min': expected[5]*market_limit,\n 'Number of data points expected in last one interval for 15 min': expected[15]*market_limit,\n 'Number of data points expected in last one interval for 30 min': expected[30]*market_limit,\n 'Number of data points expected in last one interval for 1 hour': expected[60]*market_limit,\n 'Percentage of data points available for 5 min': p1,\n 'Percentage of data points available for 15 min': p2,\n 'Percentage of data points available for 30 min': p3,\n 'Percentage of data points available for 1 hour': p4\n }\n\n report_time = datetime.utcfromtimestamp(min_in_millis/1000).strftime(\"%Y-%m-%d %H:%M:%S\"),\n report_time = ''.join(report_time)\n subject = \"Binance Report UTC: \" + report_time\n body = json.dumps(data, indent=2)\n message = 'Subject: {}\\n\\n{}'.format(subject, body)\n\n logging.info(\"Report till: \" + report_time)\n try:\n send_mails(receivers, message)\n except Exception as e:\n logging.error(\"Reporter {}\".format(type(e).__name__))\n logging.error(\"Reporter {}\".format(e))\n\n#-------------------------------------------------------------------------------\n\nasync def time_manager():\n\n rem = get_cur_min() % (config['reporting_time_divisor']*1000)\n wait_time = INTERVAL_IN_SEC - rem/1000 + config['reporting_delay'] + config['initial_delay']\n # set intial delay eg 60 min to ensure atleast one 60 min processor was called before reporting\n # set reporting delay to >= 1 min to ensure processing was finished before reporting\n\n await asyncio.sleep(wait_time)\n while True:\n logging.info(\"Awaking reporter \" + get_cur_min_str())\n await asyncio.gather(asyncio.sleep(INTERVAL_IN_SEC), send_report())\n\n#-------------------------------------------------------------------------------\n\nlogging.info(\"Starting reporter \" + get_cur_min_str())\ntry:\n conn = create_connection(dbcon, db_pass)\n send_mails(receivers[:1], \"Starting Reporter\")\nexcept Exception as e:\n logging.error(\"Reporter {}\".format(type(e).__name__))\n logging.error(\"Reporter {}\".format(e))\n\nloop = asyncio.get_event_loop()\nloop.run_until_complete(time_manager())\n\n\n"
},
{
"alpha_fraction": 0.6786279678344727,
"alphanum_fraction": 0.6875989437103271,
"avg_line_length": 20.534090042114258,
"blob_id": "ddec00f7c36dbfbf7411597f16b5fc64082cb345",
"content_id": "24c028a4e194f4ee836540013c8cda378e0f5e0f",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1895,
"license_type": "no_license",
"max_line_length": 120,
"num_lines": 88,
"path": "/db.py",
"repo_name": "thedewangan/binance_collector",
"src_encoding": "UTF-8",
"text": "import mysql.connector\nimport json\nimport getpass\nimport sys\n\nconfig_file = \"config.test.json\" if(len(sys.argv)>1 and str(sys.argv[1]) == \"test\") else \"config.json\"\n\nwith open(config_file) as json_data_file:\n config = json.load(json_data_file)\n\ndbcon= config['mysql']\ndb_pass = getpass.getpass(\"Enter mysql password: \")\n\nconn = mysql.connector.connect(user=dbcon['user'], password=db_pass, host=dbcon['host'], database=dbcon['database'])\ncursor = conn.cursor()\n\ncursor.execute(\"DROP TABLE IF EXISTS one_min\")\ncursor.execute(\"DROP TABLE IF EXISTS five_min\")\ncursor.execute(\"DROP TABLE IF EXISTS fifteen_min\")\ncursor.execute(\"DROP TABLE IF EXISTS thirty_min\")\ncursor.execute(\"DROP TABLE IF EXISTS one_hour\")\n\n# ONE_MIN\nsql ='''CREATE TABLE one_min(\n time TIMESTAMP NOT NULL,\n market VARCHAR(255),\n open DOUBLE,\n high DOUBLE,\n low DOUBLE,\n close DOUBLE,\n volume DOUBLE,\n PRIMARY KEY (time, market)\n)'''\ncursor.execute(sql)\n\n# FIVE_MIN\nsql ='''CREATE TABLE five_min(\n time TIMESTAMP NOT NULL,\n market VARCHAR(255),\n open DOUBLE,\n high DOUBLE,\n low DOUBLE,\n close DOUBLE,\n volume DOUBLE,\n PRIMARY KEY (time, market)\n)'''\ncursor.execute(sql)\n\n# FIFTEEN_MIN\nsql ='''CREATE TABLE fifteen_min(\n time TIMESTAMP NOT NULL,\n market VARCHAR(255),\n open DOUBLE,\n high DOUBLE,\n low DOUBLE,\n close DOUBLE,\n volume DOUBLE,\n PRIMARY KEY (time, market)\n)'''\ncursor.execute(sql)\n\n# THIRTY_MIN\nsql ='''CREATE TABLE thirty_min(\n time TIMESTAMP NOT NULL,\n market VARCHAR(255),\n open DOUBLE,\n high DOUBLE,\n low DOUBLE,\n close DOUBLE,\n volume DOUBLE,\n PRIMARY KEY (time, market)\n)'''\ncursor.execute(sql)\n\n# ONE_HOUR\nsql ='''CREATE TABLE one_hour(\n time TIMESTAMP NOT NULL,\n market VARCHAR(255),\n open DOUBLE,\n high DOUBLE,\n low DOUBLE,\n close DOUBLE,\n volume DOUBLE,\n PRIMARY KEY (time, market)\n)'''\ncursor.execute(sql)\n\nconn.close()\n"
},
{
"alpha_fraction": 0.458450049161911,
"alphanum_fraction": 0.46965453028678894,
"avg_line_length": 32.46875,
"blob_id": "5d437cb2e3f1f0c81a1362de3913d162008ee5a8",
"content_id": "6e34ed39a4ef3d120fb0481f963ea25e7a0eeec8",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 1071,
"license_type": "no_license",
"max_line_length": 131,
"num_lines": 32,
"path": "/util.py",
"repo_name": "thedewangan/binance_collector",
"src_encoding": "UTF-8",
"text": "import mysql.connector, time\nfrom datetime import datetime\nimport pytz\nimport math\n\n#-------------------------------------------------------------------------------\n# returns latest minute since epoch in millis\ndef get_cur_min():\n s = math.floor(datetime.now(pytz.timezone('utc')).timestamp())\n s = s - s%60\n ms = s*1000\n return ms\n\n#-------------------------------------------------------------------------------\n\ndef get_cur_min_str():\n cur_time = datetime.utcfromtimestamp(get_cur_min()/1000).strftime(\"%Y-%m-%d %H:%M:%S\"),\n return ''.join(cur_time)\n\n#-------------------------------------------------------------------------------\n\ndef create_connection(dbcon, db_pass):\n retry_count = 0\n while True:\n try:\n conn = mysql.connector.connect(user=dbcon['user'], password=db_pass, host=dbcon['host'], database=dbcon['database'])\n return conn\n except Exception as e:\n retry_count += 1\n if(retry_count == dbcon['max_retry']):\n raise e\n time.sleep(dbcon['wait'])\n"
},
{
"alpha_fraction": 0.5556454658508301,
"alphanum_fraction": 0.5696074366569519,
"avg_line_length": 39.83470916748047,
"blob_id": "a7996448835029f3e8e792bdad80be4ba8d1c07e",
"content_id": "3ee66626b9e8ff894d95035983c8adfa17368aba",
"detected_licenses": [],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 4942,
"license_type": "no_license",
"max_line_length": 102,
"num_lines": 121,
"path": "/collector.py",
"repo_name": "thedewangan/binance_collector",
"src_encoding": "UTF-8",
"text": "import ccxt\nfrom datetime import datetime\nfrom pprint import pprint\nimport asyncio\nimport ccxt.async_support as ccxt\nfrom processor import data_processor, set_processor_log_config\nfrom util import *\nimport json\nimport sys\nimport logging\nimport getpass\n\nconfig_file = \"config.test.json\" if(len(sys.argv)>1 and str(sys.argv[1]) == \"test\") else \"config.json\"\n\nwith open(config_file) as json_data_file:\n config = json.load(json_data_file)\n\nlogging.basicConfig(filename=config['collector_log_file'], level=logging.INFO)\nset_processor_log_config(config['collector_log_file'])\n\nexchange = ccxt.binance()\nexchange.enableRateLimit = True\nexchange.rateLimit = config['exchange_ratelimit']\nexchange.timeout = config['exchange_timeout']\n\ndbcon = config['mysql']\ndb_pass = getpass.getpass(\"Enter mysql password: \")\nINTERVAL_IN_SEC = config['collector_interval_seconds']\n\n#-------------------------------------------------------------------------------\n\nasync def minute_collect_market(symbol, start, conn):\n try:\n cursor = conn.cursor()\n ans = await exchange.fetchOHLCV(symbol, timeframe='1m', since=start, limit=1)\n if(len(ans) and len(ans[0])==6):\n t = ans[0][0]\n timestamp = datetime.utcfromtimestamp(float(t)/1000)\n # print(timestamp)\n query = \"INSERT INTO one_min VALUES (%s, %s, %s, %s, %s, %s, %s)\"\n data = (timestamp, symbol, ans[0][1], ans[0][2], ans[0][3], ans[0][4], ans[0][5])\n try:\n cursor.execute(query, data)\n conn.commit()\n except Exception as e:\n conn.rollback()\n logging.error(\"Collector\\t\" + symbol + \"\\t{}\".format(type(e).__name__))\n logging.error(\"Collector\\t\" + symbol + \"\\t{}\".format(e))\n # print(symbol, end = \" \")\n # pprint(ans)\n # print()\n except Exception as e:\n logging.error(\"Collector\\t\" + symbol + \"\\t{}\".format(type(e).__name__))\n logging.error(\"Collector\\t\" + symbol + \"\\t{}\".format(e))\n\n#-------------------------------------------------------------------------------\n\nasync def minute_collect_all(start, conn):\n tasks = []\n market_limit = config['market_limit']\n for symbol in exchange.symbols[:market_limit]:\n tasks.append(minute_collect_market(symbol, start, conn))\n await asyncio.gather(*tasks)\n\n#-------------------------------------------------------------------------------\n\nasync def collector(params):\n min_in_millis = get_cur_min()\n if(params['running'] == False):\n await exchange.load_markets()\n params['running'] = True\n min_in_millis = get_cur_min()\n params['service_start_time'] = min_in_millis\n f = open(\"binance_collector_info\",\"w+\")\n f.write(str(min_in_millis)) # minute of first request / service start time\n f.write(\"\\n\"+str(len(exchange.symbols))) # number of markets present in exchange\n f.close()\n # actual number of markets was greater than request limit per second !?\n logging.info(\"Markets loaded\")\n \n start = min_in_millis - 60000\n uptime_in_min = (min_in_millis - params['service_start_time'])/60000\n minutes = min_in_millis/60000\n time_str = ''.join(datetime.utcfromtimestamp(min_in_millis/1000).strftime(\"%Y-%m-%d %H:%M:%S\"))\n logging.info(\"Starting collection: \" + time_str)\n\n try:\n conn = create_connection(dbcon, db_pass)\n except Exception as e:\n logging.error(\"Collector\" + \"\\t{}\".format(type(e).__name__))\n logging.error(\"Collector\" + \"\\t{}\".format(e))\n return\n\n # async support for databases ?\n await minute_collect_all(start, conn)\n\n if(minutes % 5 == 0 and uptime_in_min >= 5):\n data_processor(5, minutes, conn)\n if(minutes % 15 == 0 and uptime_in_min >= 15):\n data_processor(15, minutes, conn)\n if(minutes % 30 == 0 and uptime_in_min >= 30):\n data_processor(30, minutes, conn)\n if(minutes % 60 == 0 and uptime_in_min >= 60):\n data_processor(60, minutes, conn)\n if(minutes % 5 == 0 and uptime_in_min >= 5):\n logging.info(\"All processing finished \" + get_cur_min_str())\n conn.close()\n#-------------------------------------------------------------------------------\n\nasync def time_manager(params):\n while True:\n await asyncio.gather(asyncio.sleep(INTERVAL_IN_SEC), collector(params))\n # note that if collector takes more time than interval, actual wait would be more\n # so ensure that collector does work before interval\n # could not find something like setinterval\n # other options were maintaining end to start interval rather than start to start\n#-------------------------------------------------------------------------------\n\nparams = {'running': False} \nloop = asyncio.get_event_loop()\nloop.run_until_complete(time_manager(params))\n\n"
}
] | 5
|
tlinhart/pulumi-aws-lex-chatbot
|
https://github.com/tlinhart/pulumi-aws-lex-chatbot
|
3b50137cfb4f45130c492565d83895ab8e10ecf4
|
f53d694fb094d8c6b5ad28c0ed1388e5e582884e
|
cd8dbc609dd5c3d499a4843f97e37a84b8803cc7
|
refs/heads/main
| 2023-02-16T21:50:35.837020
| 2021-01-15T18:29:46
| 2021-01-15T18:29:46
| 329,991,984
| 1
| 0
| null | null | null | null | null |
[
{
"alpha_fraction": 0.699936032295227,
"alphanum_fraction": 0.7012156248092651,
"avg_line_length": 29.05769157409668,
"blob_id": "ffeb5f5726632446e06d0d38705b14de23b161ea",
"content_id": "d0ac73bd00d8618f0c99dbe708c473c61fe1950d",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "reStructuredText",
"length_bytes": 1563,
"license_type": "permissive",
"max_line_length": 138,
"num_lines": 52,
"path": "/README.rst",
"repo_name": "tlinhart/pulumi-aws-lex-chatbot",
"src_encoding": "UTF-8",
"text": "Amazon Lex chatbot\n------------------\n\nSample `Amazon Lex`_ chatbot based on `AWS Fundamentals: Building Serverless\nApplications`_ course exercise but using Pulumi to provision the AWS resources.\n\n.. _`Amazon Lex`: https://aws.amazon.com/lex/\n.. _`AWS Fundamentals: Building Serverless Applications`: https://www.coursera.org/learn/aws-fundamentals-building-serverless-applications\n\n.. image:: docs/bot-testing.png\n :alt: Bot testing\n\nCreate Pulumi project and stack\n-------------------------------\n\n.. code-block:: bash\n\n export AWS_PROFILE=pasmen\n pulumi login --cloud-url s3://pulumi.linhart.tech\n pulumi new aws-python --dir infra\n\nProvide these values:\n\n- *project name*: aws-lex-chatbot\n- *project description*: Sample chatbot using Amazon Lex\n- *stack name*: aws-lex-chatbot-prod\n- *passphrase*: <secret-passphrase>\n- *aws:region*: eu-central-1\n\n.. code-block:: bash\n\n export PULUMI_CONFIG_PASSPHRASE=<secret-passphrase>\n cd infra\n pulumi config set aws:profile pasmen\n\n vim __main__.py\n\nManage the stack\n----------------\n\n- ``pulumi up`` - Create or update the resources in a stack\n- ``pulumi stack output [<property-name>]`` - Show a stack's output properties\n- ``pulumi destroy`` - Destroy an existing stack and its resources\n- ``pulumi stack rm [<stack-name>]`` - Remove a stack and its configuration\n\nResources\n---------\n\n- https://www.coursera.org/learn/aws-fundamentals-building-serverless-applications\n- https://aws.amazon.com/lex/\n- https://www.pulumi.com/docs/get-started/aws/\n- https://www.pulumi.com/docs/reference/pkg/aws/lex/\n"
},
{
"alpha_fraction": 0.574970006942749,
"alphanum_fraction": 0.5777689218521118,
"avg_line_length": 29.876543045043945,
"blob_id": "38840f99dd20ef32baba2c4ab1447869756aacfe",
"content_id": "a1aee34619843742e73a0a604056c88dc7786b7f",
"detected_licenses": [
"MIT"
],
"is_generated": false,
"is_vendor": false,
"language": "Python",
"length_bytes": 2501,
"license_type": "permissive",
"max_line_length": 85,
"num_lines": 81,
"path": "/infra/__main__.py",
"repo_name": "tlinhart/pulumi-aws-lex-chatbot",
"src_encoding": "UTF-8",
"text": "import pulumi\nimport pulumi_aws as aws\n\n\ncat_weather_intent = aws.lex.Intent(\n 'CatWeatherIntent',\n description='Intent to determine if the weather is suitable for cat to go out',\n name='CatWeatherIntent',\n create_version=False,\n confirmation_prompt=aws.lex.IntentConfirmationPromptArgs(\n max_attempts=2,\n messages=[{\n 'content': 'So you want to know if your cat can go out today in {City}?',\n 'content_type': 'PlainText'\n }]\n ),\n rejection_statement=aws.lex.IntentRejectionStatementArgs(\n messages=[{\n 'content': 'Sorry, can you please repeat your initial question?',\n 'content_type': 'PlainText'\n }]\n ),\n fulfillment_activity=aws.lex.IntentFulfillmentActivityArgs(\n type='ReturnIntent'\n ),\n sample_utterances=[\n 'Can my cat go outside',\n 'Is it warm enough for my cat',\n 'Can I let my cat out in {City}',\n 'Should my cat wear booties in {City}',\n 'Will my cat stay dry in {City}'\n ],\n slots=[\n aws.lex.IntentSlotArgs(\n description='The city where the cat lives',\n name='City',\n priority=1,\n slot_constraint='Required',\n slot_type='AMAZON.US_CITY',\n value_elicitation_prompt=aws.lex.IntentSlotValueElicitationPromptArgs(\n max_attempts=2,\n messages=[{\n 'content': 'Which city?',\n 'content_type': 'PlainText'\n }]\n )\n )\n ]\n)\n\ncat_weather_bot = aws.lex.Bot(\n 'CatWeatherBot',\n description='Bot to determine if the cat can go out',\n name='CatWeatherBot',\n create_version=False,\n process_behavior='BUILD',\n enable_model_improvements=True,\n child_directed=False,\n idle_session_ttl_in_seconds=600,\n clarification_prompt=aws.lex.BotClarificationPromptArgs(\n max_attempts=2,\n messages=[{\n 'content': 'I did not understand you, what would you like to do?',\n 'content_type': 'PlainText'\n }]\n ),\n abort_statement=aws.lex.BotAbortStatementArgs(\n messages=[{\n 'content': 'Sorry, I am not able to assist at this time',\n 'content_type': 'PlainText'\n }]\n ),\n intents=[\n aws.lex.BotIntentArgs(\n intent_name=cat_weather_intent.name,\n intent_version=cat_weather_intent.version\n )\n ],\n locale='en-US',\n voice_id='Salli'\n)\n"
}
] | 2
|