Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

96b61046248a3e72e93e236aec968705b8d8a09c

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/testcase/common/basePage/basePage.py

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williamzxl/app_test_many_devices

c1806e54c17a84f18a04c3808604633c2deba052

dd5434018fadd11d5462903cafaafbb5b387c24a

refs/heads/master

2020-03-29T21:20:51.239295

2019-03-05T03:13:56

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from testcase.common.basePage.web_view import WebView from selenium.webdriver.support.wait import WebDriverWait from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.common.keys import Keys from utils.log import logger class BasePage(WebView): def __init__(self, page=None, browser_type=None): if page: self.driver = page.driver else: super(BasePage, self).__init__(browser_type=browser_type) def get_driver(self): return self.driver def open(self, appium_url, desired_caps): try: logger.info("Open appium_url: {}".format(appium_url)) logger.info("desired_caps:{}".format(desired_caps)) self.get(appium_url, desired_caps) except: logger.warning("Cant open appium url:{}".format(appium_url)) raise ValueError("Connect appium failed!") def find_element(self, *loc): try: WebDriverWait(self.driver, 30).until(EC.visibility_of_element_located(loc)) logger.info("Success return self.driver.find_element(*loc):{}".format(loc)) return self.driver.find_element(*loc) except TimeoutError: logger.error("In {} cant find {}".format(self, loc)) return False def find_elements(self, *loc): try: WebDriverWait(self.driver, 30).until(EC.visibility_of_element_located(loc)) logger.info("Success return self.driver.find_element(*loc):{}".format(loc)) return self.driver.find_elements(*loc) except TimeoutError: # print("In {} cant find {}".format(self, loc)) logger.error("In {} cant find {}".format(self, loc)) return False # def script(self, src): # self.driver.execute_script(src) def sendKeys(self, loc, value, clear_first=True, click_first=True): try: # loc = getattr(self, "_{}".format(loc)) if click_first: # self.find_element(*loc).click() loc.click() if clear_first: # self.find_element(*loc).clear() loc.clear() # self.find_element(*loc).send_keys(value) loc.send_keys(value) except AttributeError: logger.error("{} page cant find {} element".format(self, loc)) def get_url(self): return self.driver.current_url def getEleText(self,ele): return ele.text def getEleSize(self, ele): return ele.size def getEleLocation(self, ele): return ele.location def is_selected(self, element): element.is_selected() def is_enabled(self, element): element.is_enabled() def is_displayed(self, element): element.is_displayed() def enter(self, element): element.send_keys(Keys.RETURN) def click(self, element): element.click() def submit(self): pass def getEleAttribute(self, element, attribute): return element.get_attribute(attribute) # def getAttribute(self, ele, name): # return ele.get_attribute(name) def getText(self, element): try: return element.text except SyntaxError: logger.error("No such element TEXT") def getTitle(self): return self.driver.title def getCurrentUrl(self): return self.driver.current_url def get_contexts(self): return self.driver.contexts() def get_current_context(self): return self.driver.current_context() def get_context(self): return self.driver.context() def page_source(self): return self.driver.page_source def page_source_test(self): return self.driver.page_source if __name__ == "__main__": test = BasePage() test.open()

[ "1053418947@qq.com" ]

1053418947@qq.com

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/new_rule/ticket-rules/oracle/DML_SORT.py

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kk71/sqlaudit

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refs/heads/master

2023-02-04T18:38:46.125746

2020-06-05T09:49:46

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import re def code(rule, entries, **kwargs): single_sql: dict = kwargs.get("single_sql") sql_text: str = single_sql["sql_text_no_comment"] dml_sort = re.compile("(\\s)?((update )|(delete )).*order by") if dml_sort.search(sql_text): return -rule.weight, [] return None, [] code_hole.append(code)

[ "kai.fang@kirintech.cn" ]

kai.fang@kirintech.cn

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/setup.py

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[]

no_license

thatch45/archinator

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refs/heads/master

2020-06-01T03:52:43.793091

2013-06-24T05:24:04

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#!/usr/bin/env python from distutils.core import setup setup(name='archinator', version='0.5.0', description='Virtual machine generator for ArchLinux', author='Thomas S Hatch', author_email='thatch45@gmail.com', url='https://github.com/thatch45/archinator', packages=[ 'archinator', 'archinator.utils', ], scripts=['scripts/archinator'], )

[ "thatch45@gmail.com" ]

thatch45@gmail.com

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/2023/problems/millifaersla/submissions/partially_accepted/strings_0.py

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[]

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ForritunarkeppniFramhaldsskolanna/Keppnir

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refs/heads/master

2023-04-28T15:33:36.396225

2023-04-23T15:00:15

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#!/usr/bin/python3 a = input() b = input() c = input() if a < b and a < c: print("Monnei") elif b < a and b < c: print("Fjee") else: print("Dolladollabilljoll")

[ "bjarki.agust@gmail.com" ]

bjarki.agust@gmail.com

18939fdae293b7a96059b4ed05b61fab9a65a3e3

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/Solutions/0135_candy.py

af76e71034174d61806ca337a98996a7aa0af28e

[]

no_license

YoupengLi/leetcode-sorting

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refs/heads/master

2020-05-18T23:28:51.363862

2019-09-12T00:42:14

184,712,501

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# -*- coding: utf-8 -*- # @Time : 2019/7/18 0018 09:54 # @Author : Youpeng Li # @Site : # @File : 0135_candy.py # @Software: PyCharm ''' 135. Candy There are N children standing in a line. Each child is assigned a rating value. You are giving candies to these children subjected to the following requirements: Each child must have at least one candy. Children with a higher rating get more candies than their neighbors. What is the minimum candies you must give? Example 1: Input: [1,0,2] Output: 5 Explanation: You can allocate to the first, second and third child with 2, 1, 2 candies respectively. Example 2: Input: [1,2,2] Output: 4 Explanation: You can allocate to the first, second and third child with 1, 2, 1 candies respectively. The third child gets 1 candy because it satisfies the above two conditions. ''' class Solution: def candy(self, ratings: 'List[int]') -> 'int': if not ratings: return 0 res = [1] * len(ratings) lbase, rbase = 1, 1 for i in range(1, len(ratings)): # 从左向右扫描 lbase = lbase + 1 if ratings[i] > ratings[i - 1] else 1 res[i] = lbase for i in range(len(ratings) - 2, -1, -1): # 从右向左扫描 rbase = rbase + 1 if ratings[i] > ratings[i + 1] else 1 res[i] = max(rbase, res[i]) return sum(res) def candy_1(self, ratings: 'List[int]') -> 'int': peak = down = up = 0 res = 1 for i in range(1, len(ratings)): if ratings[i - 1] < ratings[i]: up += 1 down = 0 peak = up res += 1 + up elif ratings[i - 1] == ratings[i]: up = down = peak = 0 res += 1 else: up = 0 down += 1 res += 1 + down + ((-1) if peak >= down else 0) return res if __name__ == "__main__": a = Solution() ratings = [1, 0, 2] print(a.candy(ratings)) print(a.candy_1(ratings)) ratings = [1, 2, 2] print(a.candy(ratings)) print(a.candy_1(ratings)) ratings = [1, 2, 3, 2, 1, 0] print(a.candy(ratings)) print(a.candy_1(ratings))

[ "noreply@github.com" ]

YoupengLi.noreply@github.com

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/python3/212.Word Search II(单词搜索 II).py

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lishulongVI/leetcode

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refs/heads/master

2020-03-23T22:17:40.335970

2018-07-23T14:46:06

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""" Given a 2D board and a list of words from the dictionary, find all words in the board. Each word must be constructed from letters of sequentially adjacent cell, where "adjacent" cells are those horizontally or vertically neighboring. The same letter cell may not be used more than once in a word. Example: <pre> Input: words = <code>["oath","pea","eat","rain"]</code> and board = [ ['o','a','a','n'], ['e','t','a','e'], ['i','h','k','r'], ['i','f','l','v'] ] Output: <code>["eat","oath"]</code> </pre> Note: You may assume that all inputs are consist of lowercase letters <code>a-z</code>.给定一个二维网格 board 和一个字典中的单词列表 words，找出所有同时在二维网格和字典中出现的单词。 单词必须按照字母顺序，通过相邻的单元格内的字母构成，其中“相邻”单元格是那些水平相邻或垂直相邻的单元格。同一个单元格内的字母在一个单词中不允许被重复使用。 示例: <pre>输入: words = <code>["oath","pea","eat","rain"]</code> and board = [ ['o','a','a','n'], ['e','t','a','e'], ['i','h','k','r'], ['i','f','l','v'] ] 输出: <code>["eat","oath"]</code></pre> 说明: 你可以假设所有输入都由小写字母 <code>a-z</code> 组成。 提示: <ul> <li>你需要优化回溯算法以通过更大数据量的测试。你能否早点停止回溯？</li> <li>如果当前单词不存在于所有单词的前缀中，则可以立即停止回溯。什么样的数据结构可以有效地执行这样的操作？散列表是否可行？为什么？前缀树如何？如果你想学习如何实现一个基本的前缀树，请先查看这个问题： <a href="/problems/implement-trie-prefix-tree/description/">实现Trie（前缀树）</a>。</li> </ul> 给定一个二维网格 board 和一个字典中的单词列表 words，找出所有同时在二维网格和字典中出现的单词。 单词必须按照字母顺序，通过相邻的单元格内的字母构成，其中“相邻”单元格是那些水平相邻或垂直相邻的单元格。同一个单元格内的字母在一个单词中不允许被重复使用。 示例: <pre>输入: words = <code>["oath","pea","eat","rain"]</code> and board = [ ['o','a','a','n'], ['e','t','a','e'], ['i','h','k','r'], ['i','f','l','v'] ] 输出: <code>["eat","oath"]</code></pre> 说明: 你可以假设所有输入都由小写字母 <code>a-z</code> 组成。 提示: <ul> <li>你需要优化回溯算法以通过更大数据量的测试。你能否早点停止回溯？</li> <li>如果当前单词不存在于所有单词的前缀中，则可以立即停止回溯。什么样的数据结构可以有效地执行这样的操作？散列表是否可行？为什么？前缀树如何？如果你想学习如何实现一个基本的前缀树，请先查看这个问题： <a href="/problems/implement-trie-prefix-tree/description/">实现Trie（前缀树）</a>。</li> </ul> """ class Solution: def findWords(self, board, words): """ :type board: List[List[str]] :type words: List[str] :rtype: List[str] """

[ "lishulong@wecash.net" ]

lishulong@wecash.net

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/Users/M/mgrollins/eu_location_scraper.py

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BerilBBJ/scraperwiki-scraper-vault

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refs/heads/master

2021-12-02T23:55:58.481210

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import scraperwiki import lxml.html from lxml import etree html = scraperwiki.scrape("http://www.edd.ca.gov/jobs_and_training/Experience_Unlimited_Local_Information.htm") root = lxml.html.fromstring(html) locations = [] #for lel in root.cssselect("div.main_content"): print "in lel loop" for el in root.cssselect("div.content_left_column h2"): if el.text_content() != "More Information": locations.append(el.text_content()) print "in el loop" # for lel in el.cssselect("*"): # print lel.text_content() # break # place holder for loc in locations: print loc +",", # scraperwiki.sqlite.save(unique_keys = ['locations'], data = locations) # print lxml.html.tostring(el)import scraperwiki import lxml.html from lxml import etree html = scraperwiki.scrape("http://www.edd.ca.gov/jobs_and_training/Experience_Unlimited_Local_Information.htm") root = lxml.html.fromstring(html) locations = [] #for lel in root.cssselect("div.main_content"): print "in lel loop" for el in root.cssselect("div.content_left_column h2"): if el.text_content() != "More Information": locations.append(el.text_content()) print "in el loop" # for lel in el.cssselect("*"): # print lel.text_content() # break # place holder for loc in locations: print loc +",", # scraperwiki.sqlite.save(unique_keys = ['locations'], data = locations) # print lxml.html.tostring(el)

[ "pallih@kaninka.net" ]

pallih@kaninka.net

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/ec2_write_f/security-group-egres_revoke.py

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[]

no_license

lxtxl/aws_cli

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refs/heads/master

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#!/usr/bin/python # -*- codding: utf-8 -*- import os import sys sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__)))) from common.execute_command import write_parameter # url : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/ec2/describe-instances.html if __name__ == '__main__': """ authorize-security-group-egress : https://awscli.amazonaws.com/v2/documentation/api/latest/reference/ec2/authorize-security-group-egress.html """ write_parameter("ec2", "revoke-security-group-egress")

[ "hcseo77@gmail.com" ]

hcseo77@gmail.com

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/corehq/ex-submodules/dimagi/utils/tests/test_rate_limit.py

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from dimagi.utils.rate_limit import rate_limit, DomainRateLimiter from django.test import SimpleTestCase # import the datetime module and not datetime.datetime: # "datetime" has to be the datetime module since the tests/__init__.py file # just imports * from all test files and the json_format_datetime doctest # expects datetime to be the datetime module import datetime class RateLimitTestCase(SimpleTestCase): def test_rate_limit(self): start = datetime.datetime.utcnow() rate_limit_count = 0 iteration_count = 0 while (datetime.datetime.utcnow() - start) < datetime.timedelta(seconds=5): # Only allow 10 actions every 3 seconds in an 5 second period of time if rate_limit('rate-limit-test', actions_allowed=10, how_often=3): rate_limit_count += 1 iteration_count += 1 self.assertEqual(rate_limit_count, 20) self.assertGreater(iteration_count, 20) def test_domain_rate_limit(self): rate_limiter = DomainRateLimiter('rate-limit-domain-', 10, 3) domains = ('d1', 'd2') domain_counts = {domain: 0 for domain in domains} start = datetime.datetime.utcnow() iteration_count = 0 while (datetime.datetime.utcnow() - start) < datetime.timedelta(seconds=5): # Only allow 10 actions every 3 seconds in an 5 second period of time for domain in domains: if rate_limiter.can_perform_action(domain): domain_counts[domain] += 1 iteration_count += 1 for domain in domains: self.assertEqual(domain_counts[domain], 20) self.assertGreater(iteration_count, 20)

[ "gcapalbo@dimagi.com" ]

gcapalbo@dimagi.com

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/src/single_sided_node_v1.py

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goerz-research/trajoct

e6c22a591fea98c3e287d135265a532001423fa9

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refs/heads/master

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"""Description of nodes consisting of a single-sided cavity with an atom inside""" import sympy from sympy import symbols, sqrt from qnet.algebra.hilbert_space_algebra import LocalSpace from qnet.algebra.operator_algebra import Destroy, LocalSigma from qnet.algebra.circuit_algebra import SLH, identity_matrix def dagger(op): return op.adjoint() def syms_ops(node_index, n_cavity): """Define symbols and operators for a single node, required to write the SLH for a single node""" HilAtom = LocalSpace('q%d' % int(node_index), basis=('g', 'e'), order_index=(2*node_index)) HilCavity = LocalSpace('c%d' % int(node_index), dimension=n_cavity, order_index=(2*node_index+1)) Sym = {} Sym['Delta'] = symbols(r'Delta_%s' % node_index, real=True) Sym['g'] = symbols(r'g_%s' % node_index, positive=True) Sym['Omega'] = symbols(r'Omega_%s' % node_index) Sym['I'] = sympy.I Sym['kappa'] = symbols(r'kappa', positive=True) Op = {} Op['a'] = Destroy(hs=HilCavity) Op['|g><g|'] = LocalSigma('g', 'g', hs=HilAtom) Op['|e><e|'] = LocalSigma('e', 'e', hs=HilAtom) Op['|e><g|'] = LocalSigma('e', 'g', hs=HilAtom) return Sym, Op def node_hamiltonian(Sym, Op): """Symbolic Hamiltonian for a single node, in the RWA""" # Symbols Δ, g, Ω, I = (Sym['Delta'], Sym['g'], Sym['Omega'], Sym['I']) δ = g**2 / Δ # Cavity operators Op_a = Op['a']; Op_a_dag = dagger(Op_a); Op_n = Op_a_dag * Op_a # Qubit operators Op_gg = Op['|g><g|']; Op_eg = Op['|e><g|']; Op_ge = dagger(Op_eg) # Hamiltonian H = -δ * Op_n + (g**2/Δ) * Op_n * Op_gg \ -I * (g / (2*Δ)) * Ω * (Op_eg*Op_a - Op_ge*Op_a_dag) return H def node_slh(node_index, n_cavity): """SLH description for a single node with the given `node_index` (which will become the subscript in all symbols) and `n_cavity` number of levels for the cavity """ Sym, Op = syms_ops(node_index, n_cavity) S = identity_matrix(1) κ = Sym['kappa'] L = [sqrt(2 * κ) * Op['a'], ] H = node_hamiltonian(Sym, Op) return SLH(S, L, H)

[ "goerz@stanford.edu" ]

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/xcp2k/classes/_program_run_info48.py

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Roolthasiva/xcp2k

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2020-10-07T08:01:48

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from xcp2k.inputsection import InputSection from xcp2k.classes._each400 import _each400 class _program_run_info48(InputSection): def __init__(self): InputSection.__init__(self) self.Section_parameters = None self.Add_last = None self.Common_iteration_levels = None self.Filename = None self.Log_print_key = None self.EACH = _each400() self._name = "PROGRAM_RUN_INFO" self._keywords = {'Add_last': 'ADD_LAST', 'Common_iteration_levels': 'COMMON_ITERATION_LEVELS', 'Filename': 'FILENAME', 'Log_print_key': 'LOG_PRINT_KEY'} self._subsections = {'EACH': 'EACH'} self._attributes = ['Section_parameters']

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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bioCKO/lpp_Script

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refs/heads/master

2022-02-27T12:35:05.979231

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from falcon_polish.pypeflow import hgap import argparse import sys def main(argv=sys.argv): parser = argparse.ArgumentParser() parser.add_argument('--logging', help='.ini or .json config file for Python logging module') parser.add_argument('config', help='.ini or .json of HGAP config. Available sections: "general", "hgap", "falcon", "pbsmrtpipe", "blasr", "quiver", ...') args = parser.parse_args(argv[1:]) return hgap.run(args.config, args.logging) if __name__ == "__main__": main(sys.argv)

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409511038@qq.com

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/eval.py

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zhangwenhao123/Underwater-Color-Correction

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''' Evaluation File ''' import cPickle as pickle import tensorflow as tf from scipy import misc from tqdm import tqdm import numpy as np import argparse import random import ntpath import sys import os import time import time import glob import cPickle as pickle from tqdm import tqdm sys.path.insert(0, 'ops/') sys.path.insert(0, 'nets/') from tf_ops import * import data_ops if __name__ == '__main__': if len(sys.argv) < 2: print 'You must provide an info.pkl file' exit() pkl_file = open(sys.argv[1], 'rb') a = pickle.load(pkl_file) LEARNING_RATE = a['LEARNING_RATE'] LOSS_METHOD = a['LOSS_METHOD'] BATCH_SIZE = a['BATCH_SIZE'] L1_WEIGHT = a['L1_WEIGHT'] IG_WEIGHT = a['IG_WEIGHT'] NETWORK = a['NETWORK'] EPOCHS = a['EPOCHS'] DATA = a['DATA'] EXPERIMENT_DIR = 'checkpoints/LOSS_METHOD_'+LOSS_METHOD\ +'/NETWORK_'+NETWORK\ +'/L1_WEIGHT_'+str(L1_WEIGHT)\ +'/IG_WEIGHT_'+str(IG_WEIGHT)\ +'/DATA_'+DATA+'/'\ IMAGES_DIR = EXPERIMENT_DIR+'test_images/' print print 'Creating',IMAGES_DIR try: os.makedirs(IMAGES_DIR) except: pass print print 'LEARNING_RATE: ',LEARNING_RATE print 'LOSS_METHOD: ',LOSS_METHOD print 'BATCH_SIZE: ',BATCH_SIZE print 'L1_WEIGHT: ',L1_WEIGHT print 'IG_WEIGHT: ',IG_WEIGHT print 'NETWORK: ',NETWORK print 'EPOCHS: ',EPOCHS print 'DATA: ',DATA print if NETWORK == 'pix2pix': from pix2pix import * if NETWORK == 'resnet': from resnet import * # global step that is saved with a model to keep track of how many steps/epochs global_step = tf.Variable(0, name='global_step', trainable=False) # underwater image image_u = tf.placeholder(tf.float32, shape=(1, 256, 256, 3), name='image_u') # generated corrected colors gen_image = netG(image_u, LOSS_METHOD) saver = tf.train.Saver(max_to_keep=1) init = tf.group(tf.local_variables_initializer(), tf.global_variables_initializer()) sess = tf.Session() sess.run(init) ckpt = tf.train.get_checkpoint_state(EXPERIMENT_DIR) if ckpt and ckpt.model_checkpoint_path: print "Restoring previous model..." try: saver.restore(sess, ckpt.model_checkpoint_path) print "Model restored" except: print "Could not restore model" pass step = int(sess.run(global_step)) # testing paths ''' exts = ['*.jpg', '*.jpeg', '*.JPEG', '*.png'] test_paths = [] for ex in exts: test_paths.extend(glob.glob('datasets/'+DATA+'/test/'+ex)) test_paths = np.asarray(test_paths) ''' #test_paths = sorted(np.asarray(glob.glob('/mnt/data2/images/underwater/youtube/diving1/*.jpg'))) test_paths = sorted(np.asarray(glob.glob('/mnt/data1/videos/barbados/2018/images/*.png'))) IMAGES_DIR = '/mnt/data1/videos/barbados/2018/out_images/' #random.shuffle(test_paths) num_test = len(test_paths) print 'num test:',num_test print 'IMAGES_DIR:',IMAGES_DIR c = 0 times = [] for img_path in tqdm(test_paths): img_name = ntpath.basename(img_path) img_name = img_name.split('.')[0] batch_images = np.empty((1, 256, 256, 3), dtype=np.float32) a_img = misc.imread(img_path).astype('float32') a_img = misc.imresize(a_img, (256, 256, 3)) a_img = data_ops.preprocess(a_img) batch_images[0, ...] = a_img s = time.time() gen_images = np.asarray(sess.run(gen_image, feed_dict={image_u:batch_images})) tot = time.time()-s times.append(tot) for gen, real in zip(gen_images, batch_images): #misc.imsave(IMAGES_DIR+str(step)+'_'+str(c)+'_real.png', real) #misc.imsave(IMAGES_DIR+str(step)+'_'+str(c)+'_gen.png', gen) misc.imsave(IMAGES_DIR+img_name+'_real.png', real) misc.imsave(IMAGES_DIR+img_name+'_gen.png', gen) c += 1 print print 'average time:',np.mean(np.asarray(times)) print

[ "cameronfabbri@gmail.com" ]

cameronfabbri@gmail.com

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/BitManipulation/test_q136_single_number.py

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no_license

sevenhe716/LeetCode

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refs/heads/master

2020-03-16T16:12:27.461172

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import unittest from BitManipulation.q136_single_number import Solution class TestSingleNumber(unittest.TestCase): """Test q136_single_number.py""" def test_single_number(self): s = Solution() self.assertEqual(1, s.singleNumber([2, 2, 1])) self.assertEqual(4, s.singleNumber([4, 1, 2, 1, 2])) if __name__ == '__main__': unittest.main()

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429134862@qq.com

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/tests/integration/network/connect_nodes_test.py

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vishalbelsare/PySyft

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2023-08-21T21:56:37.319567

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# third party import pytest import requests # syft absolute import syft as sy NETWORK_PORT = 9081 NETWORK_PUBLIC_HOST = f"docker-host:{NETWORK_PORT}" DOMAIN1_PORT = 9082 DOMAIN2_PORT = 9083 NETWORK_VPN_IP = "100.64.0.1" DOMAIN1_VPN_IP = "100.64.0.2" DOMAIN2_VPN_IP = "100.64.0.3" TEST_ROOT_EMAIL = "info@openmined.org" TEST_ROOT_PASS = "changethis" def join_to_network_python( email: str, password: str, port: int, network_host: str ) -> None: root_client = sy.login(email=email, password=password, port=port) # test Syft API root_client.join_network(host_or_ip=network_host) response = root_client.vpn_status() return response def join_to_network_rest( email: str, password: str, port: int, network_host: str ) -> None: url = f"http://localhost:{port}/api/v1/login" auth_response = requests.post(url, json={"email": email, "password": password}) auth = auth_response.json() # test HTTP API url = f"http://localhost:{port}/api/v1/vpn/join/{network_host}" headers = {"Authorization": f"Bearer {auth['access_token']}"} response = requests.post(url, headers=headers) result = response.json() return result def run_network_tests(port: int, hostname: str, vpn_ip: str) -> None: response = join_to_network_python( email=TEST_ROOT_EMAIL, password=TEST_ROOT_PASS, port=port, network_host=NETWORK_PUBLIC_HOST, ) assert response["status"] == "ok" host = response["host"] assert host["ip"] == vpn_ip assert host["hostname"] == hostname assert host["os"] == "linux" response = join_to_network_rest( email=TEST_ROOT_EMAIL, password=TEST_ROOT_PASS, port=port, network_host=NETWORK_PUBLIC_HOST, ) assert response["status"] == "ok" @pytest.mark.network def test_connect_network_to_network() -> None: run_network_tests( port=NETWORK_PORT, hostname="test_network_1", vpn_ip=NETWORK_VPN_IP ) @pytest.mark.network def test_connect_domain1_to_network() -> None: run_network_tests( port=DOMAIN1_PORT, hostname="test_domain_1", vpn_ip=DOMAIN1_VPN_IP ) @pytest.mark.network def test_connect_domain2_to_network() -> None: run_network_tests( port=DOMAIN2_PORT, hostname="test_domain_2", vpn_ip=DOMAIN2_VPN_IP )

[ "me@madhavajay.com" ]

me@madhavajay.com

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/xai/brain/wordbase/nouns/_triptych.py

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cash2one/xai

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2021-01-19T12:33:54.964379

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#calss header class _TRIPTYCH(): def __init__(self,): self.name = "TRIPTYCH" self.definitions = [u'a piece of art made of three paintings connected to each other in a way that allows the two outer ones to fold in towards the larger central one: '] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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/travelport/models/universal_record_import_service_port_type_service_output.py

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tefra/xsdata-samples

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refs/heads/main

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from __future__ import annotations from dataclasses import dataclass, field from travelport.models.error_info_1 import ErrorInfo1 from travelport.models.universal_record_import_rsp import UniversalRecordImportRsp __NAMESPACE__ = "http://www.travelport.com/service/air_v52_0" @dataclass class UniversalRecordImportServicePortTypeServiceOutput: class Meta: name = "Envelope" namespace = "http://schemas.xmlsoap.org/soap/envelope/" body: None | UniversalRecordImportServicePortTypeServiceOutput.Body = field( default=None, metadata={ "name": "Body", "type": "Element", } ) @dataclass class Body: universal_record_import_rsp: None | UniversalRecordImportRsp = field( default=None, metadata={ "name": "UniversalRecordImportRsp", "type": "Element", "namespace": "http://www.travelport.com/schema/universal_v52_0", } ) fault: None | UniversalRecordImportServicePortTypeServiceOutput.Body.Fault = field( default=None, metadata={ "name": "Fault", "type": "Element", } ) @dataclass class Fault: faultcode: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) faultstring: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) faultactor: None | str = field( default=None, metadata={ "type": "Element", "namespace": "", } ) detail: None | UniversalRecordImportServicePortTypeServiceOutput.Body.Fault.Detail = field( default=None, metadata={ "type": "Element", "namespace": "", } ) @dataclass class Detail: error_info: None | ErrorInfo1 = field( default=None, metadata={ "name": "ErrorInfo", "type": "Element", "namespace": "http://www.travelport.com/schema/common_v52_0", } )

[ "chris@komposta.net" ]

chris@komposta.net

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/study/day3/使用list()函数将range()函数输出的值输出为列表.py

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yidaiweiren/Python

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refs/heads/master

2021-07-25T00:27:52.970745

2020-06-05T07:36:35

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#使用list()函数将range()函数输出的值输出为列表 #思路 #range()输出一组数字 #把range()函数输出的值作为参数传输值list()函数 num=list(range(1,9)) print (num) #结果 ''' [1, 2, 3, 4, 5, 6, 7, 8] '''

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2577110429@qq.com

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/app/events/regions.py

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from app.utilities.data import Prefab region_types = ['normal', 'status', 'event', 'formation'] class Region(Prefab): def __init__(self, nid): self.nid = nid self.region_type = 'normal' self.position = None self.size = [1, 1] self.sub_nid = None self.condition = 'True' self.only_once = False @property def area(self): return self.size[0] * self.size[1] @property def center(self) -> tuple: if self.position: x = int(self.position[0] + self.size[0] // 2) y = int(self.position[1] + self.size[1] // 2) return x, y else: return None def contains(self, pos: tuple) -> bool: x, y = pos if self.position: return self.position[0] <= x < self.position[0] + self.size[0] and \ self.position[1] <= y < self.position[1] + self.size[1] else: return False def fuzzy_contains(self, pos: tuple) -> bool: x, y = pos fuzz = 0.4 if self.position: return self.position[0] - fuzz <= x < self.position[0] + self.size[0] + fuzz and \ self.position[1] - fuzz <= y < self.position[1] + self.size[1] + fuzz else: return False def get_all_positions(self): if self.position: positions = [] for i in range(self.position[0], self.position[0] + self.size[0]): for j in range(self.position[1], self.position[1] + self.size[1]): positions.append((i, j)) return positions else: return [] @classmethod def default(cls): return cls('None')

[ "85828552+zerorock1312@users.noreply.github.com" ]

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/Django_test01/mysql_test2000.py

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ssk1987/FullStackExerciseLibrary

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2021-06-03T02:40:06.840380

2021-03-27T11:37:22

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import pymysql # 连接数据库 db = pymysql.connect(host='127.0.0.1', port=3306, user='root', password='12345678', database='country1', charset='utf8') # 获取游标 cur = db.cursor() # 插入数据 data_list = [] for x in range(200000): name = 'Py87_%s' % x data_list.append(name) # 插入语句 # 一个包最大 allowed_packet is 10586 # max_stmt_length = 1024000 ins sql语句的字符串长度 ins = 'insert into students(name) values(%s)' # 批量插入数据 # 每一次插入都是一次磁盘网络IO 提高单位频率上的效率 cur.executemany(ins, data_list) # 提交 db.commit() # 关闭 cur.close() db.close()

[ "10293665@qq.com" ]

10293665@qq.com

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/cifar10_cnn.py

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yaroslavvb/whitening

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refs/heads/master

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''' CIFAR-10 example from https://github.com/fchollet/keras/blob/master/examples/cifar10_cnn.py Now with weight normalization. Lines 64 and 69 contain the changes w.r.t. original. ''' from __future__ import print_function from keras.datasets import cifar10 from keras.preprocessing.image import ImageDataGenerator from keras.models import Sequential from keras.layers import Dense, Dropout, Activation, Flatten from keras.layers import Convolution2D, MaxPooling2D from keras.utils import np_utils from keras import optimizers import util as u import sys import numpy as np if len(sys.argv)<2: assert False if sys.argv[1]=='sgd': prefix='keras_sgd' optimizer='sgd' elif sys.argv[1]=='sgd_wn': prefix='keras_sgd_wn' optimizer='sgd_wn' elif sys.argv[1]=='adam': prefix='keras_adam' optimizer='adam' elif sys.argv[1]=='adam_wn': prefix='keras_adam_wn' optimizer='adam_wn' else: assert False batch_size = 5000 nb_classes = 10 nb_epoch = 10 data_augmentation = True # input image dimensions img_rows, img_cols = 32, 32 # the CIFAR10 images are RGB img_channels = 3 # the data, shuffled and split between train and test sets (X_train, y_train), (X_test, y_test) = cifar10.load_data() print('X_train shape:', X_train.shape) print(X_train.shape[0], 'train samples') print(X_test.shape[0], 'test samples') X_train = X_train.astype('float32') X_test = X_test.astype('float32') X_train /= 255 X_test /= 255 # convert class vectors to binary class matrices Y_train = np_utils.to_categorical(y_train, nb_classes) Y_test = np_utils.to_categorical(y_test, nb_classes) model = Sequential() model.add(Convolution2D(32, 3, 3, border_mode='same', input_shape=X_train.shape[1:])) model.add(Activation('relu')) model.add(Convolution2D(32, 3, 3)) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Convolution2D(64, 3, 3, border_mode='same')) model.add(Activation('relu')) model.add(Convolution2D(64, 3, 3)) model.add(Activation('relu')) model.add(MaxPooling2D(pool_size=(2, 2))) model.add(Dropout(0.25)) model.add(Flatten()) model.add(Dense(512)) model.add(Activation('relu')) model.add(Dropout(0.5)) model.add(Dense(nb_classes)) model.add(Activation('softmax')) # let's train the model using SGD + momentum (how original). EDIT: now with weight normalization, so slightly more original ;-) from weightnorm import SGDWithWeightnorm from weightnorm import AdamWithWeightnorm sgd_wn = SGDWithWeightnorm(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) sgd = optimizers.SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True) adam = optimizers.Adam() adam_wn = AdamWithWeightnorm() if optimizer == 'sgd': optimizer=sgd elif optimizer == 'sgd_wn': optimizer=sgd_wn elif optimizer == 'adam': optimizer=adam elif optimizer == 'adam_wn': optimizer=adam_wn else: assert False model.compile(loss='categorical_crossentropy',optimizer=optimizer, metrics=['accuracy']) # data based initialization of parameters from weightnorm import data_based_init data_based_init(model, X_train[:100]) if not data_augmentation: print('Not using data augmentation.') model.fit(X_train, Y_train, batch_size=batch_size, nb_epoch=nb_epoch, validation_data=(X_test, Y_test), shuffle=True) else: print('Using real-time data augmentation.') # this will do preprocessing and realtime data augmentation datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, # set each sample mean to 0 featurewise_std_normalization=False, # divide inputs by std of the dataset samplewise_std_normalization=False, # divide each input by its std zca_whitening=False, # apply ZCA whitening rotation_range=0, # randomly rotate images in the range (degrees, 0 to 180) width_shift_range=0.1, # randomly shift images horizontally (fraction of total width) height_shift_range=0.1, # randomly shift images vertically (fraction of total height) horizontal_flip=True, # randomly flip images vertical_flip=False) # randomly flip images # compute quantities required for featurewise normalization # (std, mean, and principal components if ZCA whitening is applied) datagen.fit(X_train) # fit the model on the batches generated by datagen.flow() result = model.fit_generator(datagen.flow(X_train, Y_train, batch_size=batch_size), samples_per_epoch=X_train.shape[0], nb_epoch=nb_epoch, validation_data=(X_test, Y_test)) acc_hist = np.asarray(result.history['acc']) u.dump(acc_hist, "%s_losses.csv"%(prefix,))

[ "yaroslavvb@gmail.com" ]

yaroslavvb@gmail.com

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/week1/single_process.py

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fywest/python

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import time def io_task(): time.sleep(1) def main(): start_time=time.time() for i in range(5): io_task() end_time=time.time() print('it takes: {:.2f}s'.format(end_time-start_time)) if __name__=='__main__': main()

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fywest2109@hotmail.com

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webclinic017/option_pdt

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from base.signal_base import SignalBase class Signal(SignalBase): def __init__(self, spot_instrument, future_instrument): super().__init__(spot_instrument, future_instrument) self.spot_instrument = spot_instrument self.future_instrument = future_instrument self.spot_price = float('nan') self.future_price = float('nan') self.subscription_list = [f'{_}|1s' for _ in [spot_instrument, future_instrument]] def on_market_data_1s_ready(self, data): instrument = '|'.join([data['exchange', 'symbol', 'contract_type']]) if instrument == self.spot_instrument: self.spot_price = data['metadata']['mid'] else: self.future_price = data['metadata']['mid'] self.value = self.future_price / self.spot_price - 1 def from_hist_data(self, mds): spot_orderbook = mds[self.subscription_list[0]] fut_orderbook = mds[self.subscription_list[1]] df = spot_orderbook[['local_timestamp']].copy() df['value'] = fut_orderbook['mid'] / spot_orderbook['mid'] - 1 return df

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# 使用requests，bs4库，爬取猫眼电影top10的电影名称、电影类型、上映时间，并以utf-8的字符集保存到csv文件中 import requests from bs4 import BeautifulSoup as bs maoyanUrl = "https://maoyan.com/board/4"; user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36' header = { 'Content-Type': 'text/plain; charset=UTF-8', 'Cookie' : '__mta=251934006.1593072991075.1593075273346.1593075275703.6; uuid_n_v=v1; uuid=2395D3F0B6BC11EA9F28E30FF5FFF73C9A16AE2FA53A448DA75AEAA9D715CB59; _csrf=8557626db9b655cf9050ae7e5b2aab69278c8061c21eca95e1c3cf2130b0b64c; _lxsdk_cuid=172ea8cb247c8-0a73066b1c0a8b-4353760-100200-172ea8cb248c8; _lxsdk=2395D3F0B6BC11EA9F28E30FF5FFF73C9A16AE2FA53A448DA75AEAA9D715CB59; mojo-uuid=c457eacb7c1eb59d3d2f6c1f8d75b9c9; Hm_lvt_703e94591e87be68cc8da0da7cbd0be2=1593072989,1593073002; _lx_utm=utm_source%3Dgoogle%26utm_medium%3Dorganic; mojo-session-id={"id":"dd5ec1780230b10b3b01a18882424620","time":1593078373432}; Hm_lpvt_703e94591e87be68cc8da0da7cbd0be2=1593078727; __mta=251934006.1593072991075.1593075275703.1593078726963.7; mojo-trace-id=3; _lxsdk_s=172eade6a22-b72-c5-308%7C%7C6', 'Origin': 'https://maoyan.com', 'Referer': 'https://maoyan.com/board/4', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36', } response = requests.get(maoyanUrl,headers=header) response.encoding = 'utf-8' bs_info = bs(response.text,"html.parser") # print(response.text) for tags in bs_info.find_all('div',altrs={'id':'container'}): print(tags) for tag in tags.find_all('a',): print(tag.get('href')) print(tag.get('title'))

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from .data_parser import DataParser class LogisticDataParser(DataParser): def __init__(self, max_len, cuda=True, quiet=True, remove_brackets=False): super(LogisticDataParser, self).__init__(max_len, cuda=cuda, quiet=quiet) self.remove_brackets = remove_brackets def normalize_string(self, s): if self.remove_brackets: s = [x for x in s if x not in ['(', ')', ',']] return s

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# coding: utf-8 """ SimScale API The version of the OpenAPI document: 0.0.0 Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six from simscale_sdk.configuration import Configuration class OneOfSolidSimulationControlPseudoTimeStepping(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'type': 'str', 'static_timesteps': 'DimensionalTime', 'simulation_intervals': 'DimensionalTime', 'timestep_length': 'RestrictedDimensionalFunctionTime' } attribute_map = { 'type': 'type', 'static_timesteps': 'staticTimesteps', 'simulation_intervals': 'simulationIntervals', 'timestep_length': 'timestepLength' } discriminator_value_class_map = { 'SINGLE_STEP': 'SingleStepPseudoTimeStepping', 'STEPPING_LIST_V18': 'SteppingListPseudoTimeStepping' } def __init__(self, type='STEPPING_LIST_V18', static_timesteps=None, simulation_intervals=None, timestep_length=None, local_vars_configuration=None): # noqa: E501 """OneOfSolidSimulationControlPseudoTimeStepping - a model defined in OpenAPI""" # noqa: E501 if local_vars_configuration is None: local_vars_configuration = Configuration() self.local_vars_configuration = local_vars_configuration self._type = None self._static_timesteps = None self._simulation_intervals = None self._timestep_length = None self.discriminator = 'type' self.type = type if static_timesteps is not None: self.static_timesteps = static_timesteps if simulation_intervals is not None: self.simulation_intervals = simulation_intervals if timestep_length is not None: self.timestep_length = timestep_length @property def type(self): """Gets the type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this OneOfSolidSimulationControlPseudoTimeStepping. :param type: The type of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: str """ if self.local_vars_configuration.client_side_validation and type is None: # noqa: E501 raise ValueError("Invalid value for `type`, must not be `None`") # noqa: E501 self._type = type @property def static_timesteps(self): """Gets the static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: DimensionalTime """ return self._static_timesteps @static_timesteps.setter def static_timesteps(self, static_timesteps): """Sets the static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. :param static_timesteps: The static_timesteps of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: DimensionalTime """ self._static_timesteps = static_timesteps @property def simulation_intervals(self): """Gets the simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: DimensionalTime """ return self._simulation_intervals @simulation_intervals.setter def simulation_intervals(self, simulation_intervals): """Sets the simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. :param simulation_intervals: The simulation_intervals of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: DimensionalTime """ self._simulation_intervals = simulation_intervals @property def timestep_length(self): """Gets the timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :return: The timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :rtype: RestrictedDimensionalFunctionTime """ return self._timestep_length @timestep_length.setter def timestep_length(self, timestep_length): """Sets the timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. :param timestep_length: The timestep_length of this OneOfSolidSimulationControlPseudoTimeStepping. # noqa: E501 :type: RestrictedDimensionalFunctionTime """ self._timestep_length = timestep_length def get_real_child_model(self, data): """Returns the real base class specified by the discriminator""" discriminator_key = self.attribute_map[self.discriminator] discriminator_value = data[discriminator_key] return self.discriminator_value_class_map.get(discriminator_value) def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, OneOfSolidSimulationControlPseudoTimeStepping): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, OneOfSolidSimulationControlPseudoTimeStepping): return True return self.to_dict() != other.to_dict()

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import time import torch import RLAgents import models.ppo_cnd_102_2.src.model_ppo as ModelPPO import models.ppo_cnd_102_2.src.model_cnd_target as ModelCNDTarget import models.ppo_cnd_102_2.src.model_cnd as ModelCND import models.ppo_cnd_102_2.src.config as Config #torch.cuda.set_device("cuda:0") #print("running on ", torch.cuda.get_device_name()) path = "models/ppo_cnd_102_2/" config = Config.Config() #config.envs_count = 1 envs = RLAgents.MultiEnvParallelOptimised("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezuma, config.envs_count) #envs = RLAgents.MultiEnvSeq("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezuma, config.envs_count) #envs = RLAgents.MultiEnvSeq("MontezumaRevengeNoFrameskip-v4", RLAgents.WrapperMontezumaVideo, config.envs_count) agent = RLAgents.AgentPPOCND(envs, ModelPPO, ModelCNDTarget, ModelCND, config) max_iterations = 500000 trainig = RLAgents.TrainingIterations(envs, agent, max_iterations, path, 128) trainig.run() ''' agent.load(path) agent.disable_training() while True: reward, done, _ = agent.main() envs.render(0) #time.sleep(0.01) '''

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""" Tio Booleano Álgebra Booleana, criada por George Boole 2 constantes: Verdadeiro ou Falso True -> Verdadeiro False -> Falso A primeira letra precisa ser maiúscula """ falso = False verdadeiro = True print(falso) print(verdadeiro) print(type(verdadeiro)) # Operações # Negação(not) : troca do valor atual para o seu contrário print(not falso) print(not verdadeiro) # Ou(or) : é uma operação binária onde um ou o outro precisa ser verdadeiro para retornar verdadeiro print(falso or verdadeiro) # E(and) : é uma operação binária onde ambos os valores devem ser verdadeiro para retornar verdadeiro print(falso and verdadeiro) print(not falso and verdadeiro) # Você pode comparar valores e variáveis para retornar um valor booleano print(5 < 6) print(3 > 4)

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# Generated by Django 2.1.5 on 2019-02-12 07:13 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('leasing', '0041_add_collateral'), ] operations = [ migrations.AddField( model_name='contract', name='first_call_sent', field=models.DateField(blank=True, null=True, verbose_name='First call sent'), ), migrations.AddField( model_name='contract', name='second_call_sent', field=models.DateField(blank=True, null=True, verbose_name='Second call sent'), ), migrations.AddField( model_name='contract', name='sign_by_date', field=models.DateField(blank=True, null=True, verbose_name='Sign by date'), ), migrations.AddField( model_name='contract', name='third_call_sent', field=models.DateField(blank=True, null=True, verbose_name='Third call sent'), ), ]

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import os import site from dj_scaffold.env import add_site_dir HERE = os.path.dirname(__file__) ROOT_PATH = os.path.abspath(os.path.join(HERE, '../')) ALLDIRS = [os.path.join(ROOT_PATH, 'env/lib/python2.7/site-packages'), os.path.join(ROOT_PATH, 'sites')] add_site_dir(ALLDIRS) os.environ['DJANGO_SETTINGS_MODULE'] = 'settings' import django.core.handlers.wsgi application = django.core.handlers.wsgi.WSGIHandler()

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#!/usr/bin/env python # -*- coding: utf-8 -*- """ Description: This is a project documents everything the author learned from a newbie becoming a Senior Python developer. This document is written mainly in Chinese, but I am trying to do the best to make it bilingual. Because I believe python3 is the future of python, so everything is tested in python33. 说明: pyrabbit-python-advance-guide-project 是一个将笔者从一个无任何计算机背景的菜鸟到成长为一个高级Python开发者 - 大数据科学家的路上, 所学到的所有Python的知识。经过笔者的思考, 和精心挑选的可执行的代码例子, 并将整个文档网站化, 可搜索化的一个项目。本项目基于Python33社区项目主要分为下面5大部分: - :mod:`cookbook <pyguide.cookbook>`: 一些有关Python的深入探讨 - :mod:`newbie <pyguide.newbie>`: 从零开始学Python - :mod:`ref <pyguide.ref>`: Python官方参考文档中的精华总结 - :mod:`stdlib <pyguide.stdlib>`: Python标准库的摘要 - :mod:`package <pyguide.package>`: 第三方库相关文档 """

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import os import re import numpy as np import tensorflow as tf from glob import glob from config import Config from ops import tf_fun class data_processing(object): def __init__(self): self.name = 'contours_gilbert_256_sparse_nonRandomShear' self.im_extension = '.png' self.images_dir = 'images' self.label_regex = r'(?<=length)\d+' self.config = Config() self.im_size = [256, 256, 3] # 600, 600 self.model_input_image_size = [256, 256, 3] # [107, 160, 3] self.max_ims = 0 self.output_size = [1] self.label_size = self.output_size self.default_loss_function = 'cce' self.score_metric = 'accuracy' self.store_z = False self.normalize_im = True self.shuffle = True self.input_normalization = 'zscore' self.preprocess = [''] # ['resize_nn'] self.folds = { 'train': 'train', 'val': 'val' } self.cv_split = 0.9 self.cv_balance = True self.targets = { 'image': tf_fun.bytes_feature, 'label': tf_fun.int64_feature } self.tf_dict = { 'image': tf_fun.fixed_len_feature(dtype='string'), 'label': tf_fun.fixed_len_feature(dtype='int64') } self.tf_reader = { 'image': { 'dtype': tf.float32, 'reshape': self.im_size }, 'label': { 'dtype': tf.int64, 'reshape': self.output_size } } def get_data(self): """Get the names of files.""" files = np.asarray( glob( os.path.join( self.config.data_root, self.name, '*%s' % self.im_extension))) labels = np.asarray( [int(re.search(self.label_regex, x).group()) for x in files]) labels = (labels > 1).astype(np.int32) ul, lc = np.unique(labels, return_counts=True) include_count = np.min(lc) if self.max_ims: include_count = np.min([include_count, lc]) # Trim files and labels to include_count pos_idx = np.where(labels == 1)[0][:include_count] neg_idx = np.where(labels == 0)[0][:include_count] # Create CV folds cv_files, cv_labels = {}, {} cv_files[self.folds['train']] = {} cv_files[self.folds['val']] = {} prev_cv = 0 for k, v in self.folds.iteritems(): if k == self.folds['train']: cv_split = int(include_count * self.cv_split) elif k == self.folds['val']: cv_split = int(include_count * (1 - self.cv_split)) else: raise NotImplementedError if prev_cv: cv_split += prev_cv cv_inds = np.arange(prev_cv, cv_split) it_files = np.concatenate(( files[pos_idx][cv_inds], files[neg_idx][cv_inds])) it_labels = np.concatenate(( labels[pos_idx][cv_inds], labels[neg_idx][cv_inds])) if self.shuffle: shuffle_idx = np.random.permutation(len(it_files)) it_files = it_files[shuffle_idx] it_labels = it_labels[shuffle_idx] cv_files[k] = it_files cv_labels[k] = it_labels prev_cv = cv_split return cv_files, cv_labels

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from typing import List, Optional import torch from torch import tensor import torch.nn as nn class ShortcutProjection(nn.Module): def __init__(self, in_channels: int, out_channels: int, stride: int): super().__init__() self.conv = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=stride) self.bn = nn.BatchNorm2d(out_channels) def forward(self, x: torch.Tensor): return self.bn(self.conv(x)) class ResidualBlock(nn.Module): def __init__(self, in_channels: int, out_channels: int, stride: int): super().__init__() self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=stride, padding=1) self.bn1 = nn.BatchNorm2d(out_channels) self.act1 = nn.ReLU() self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1) self.bn2 = nn.BatchNorm2d(out_channels) if stride != 1 or in_channels != out_channels: self.shortcut = ShortcutProjection(in_channels, out_channels, stride) else: self.shortcut = nn.Identity() self.act2 = nn.ReLU() def forward(self, x): shortcut = self.shortcut(x) x = self.act1(self.bn1(self.conv1(x))) x = self.bn2(self.conv2(x)) return self.act2(x + shortcut) class BottleneckResidualBlock(nn.Module): def __init__(self, in_channels: int, bottleneck_channels: int, out_channels: int, stride: int): super().__init__() self.conv1 = nn.Conv2d(in_channels, bottleneck_channels, kernel_size=1, stride=1) self.bn1 = nn.BatchNorm2d(bottleneck_channels) self.act1 = nn.ReLU() self.conv2 = nn.Conv2d(bottleneck_channels, bottleneck_channels, kernel_size=3, stride=stride, padding=1) self.bn2 = nn.BatchNorm2d(bottleneck_channels) self.act2 = nn.ReLU() self.conv3 = nn.Conv2d(bottleneck_channels, out_channels, kernel_size=1, stride=1) self.bn3 = nn.BatchNorm2d(out_channels) if stride != 1 or in_channels != out_channels: self.shortcut = ShortcutProjection(in_channels, out_channels, stride) else: self.shortcut = nn.Identity() self.act3 = nn.ReLU() def forward(self, x: torch.Tensor): shortcut = self.shortcut(x) x = self.act1(self.bn1(self.conv1(x))) x = self.act2(self.bn2(self.conv2(x))) x = self.bn3(self.conv3(x)) return self.act3(x + shortcut) class ResNetBase(nn.Module): def __init__(self, n_blocks: List[int], n_channels: List[int], bottlenecks: Optional[List[int]] = None, img_channels: int = 3, first_kernel_size: int = 7): super().__init__() assert len(n_blocks) == len(n_channels) assert bottlenecks is None or len(bottlenecks) == len(n_channels) self.conv = nn.Conv2d(img_channels, n_channels[0], kernel_size=first_kernel_size, stride=2, padding=first_kernel_size // 2) self.bn = nn.BatchNorm2d(n_channels[0]) blocks = [] prev_channel = n_channels[0] for i, channels in enumerate(n_channels): if len(blocks) == 0: stride = 2 else: stride = 1 if bottlenecks is None: blocks.append(ResidualBlock(prev_channel, channels, stride=stride)) else: blocks.append(BottleneckResidualBlock(prev_channel, bottlenecks[i], channels, stride=stride)) prev_channel = channels for _ in range(n_blocks[i] - 1): if bottlenecks is None: blocks.append(ResidualBlock(channels, channels, stride=1)) else: blocks.append(BottleneckResidualBlock(channels, bottlenecks[i], channels, stride=1)) self.blocks = nn.Sequential(*blocks) def forward(self, x: torch.Tensor): x = self.bn(self.conv(x)) x = self.blocks(x) x = x.view(x.shape[0], x.shape[1], -1) return x.mean(dim=-1)

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n=int(input()) stack=[] for i in range(n): command=input().split() if command[0]=='Add': stack.append(command) elif command[0]=='Del': ind=int(command[1]) if ind-1>=0 and ind-1<len(stack): stack[ind-1][0]='No' else: x=int(command[1]) res=0 for j in range(len(stack)): if stack[j][0]=="Add": tem=int(stack[j][1])*x+int(stack[j][2]) if tem>int(stack[j][3]): res+=1 print(res)

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def MinWindowSubstring(strArr): # code goes here containing_string = strArr[0] # first string search_string = ''.join(sorted(strArr[1])) # second string print(len(search_string)) min_chars_required = len(search_string) solution = '' solution_array = [] for x in containing_string: solution += x total_cnt = 0 print("",solution) for c in search_string: found_cnt = solution.count(c) needed_cnt = search_string.count(c) if found_cnt >= needed_cnt: total_cnt += 1 # print(total_cnt) if total_cnt == min_chars_required: solution_array.append(solution) # print(solution_array) # solution = '' # actual_solution_array = [] # for word in solution_array: # word = word [::-1] # for x in word: # solution += x # total_cnt = 0 # # print(solution) # for c in search_string: # found_cnt = solution.count(c) # needed_cnt = search_string.count(c) # if found_cnt >= needed_cnt: # total_cnt += 1 # # print(total_cnt) # if total_cnt == min_chars_required: # actual_solution_array.append(solution) # answer = min((word for word in actual_solution_array if word), key=len) # answer = answer [::-1] # return answer print(MinWindowSubstring(["sz","azjskfzts"]))

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''' Created on Mar 25, 2014 input: train, dev|test, para output: accuracy, label of required @author: cx ''' import site site.addsitedir('/bos/usr0/cx/PyCode/Geektools') site.addsitedir('/bos/usr0/cx/PyCode/QueryExpansion') site.addsitedir('/bos/usr0/cx/PyCode/cxPylib') site.addsitedir('/bos/usr0/cx/LibSVM/libsvm/python/') from LibSVMRelate.SVMBase import * from svmutil import * from cxBase.base import * from cxBase.ContingencyTable import * import json class SVMRunSingleParaC(object): def LoadData(self,InName): print "to be implemented by my inherited class" return [[],[]] def DumpPrediction(self,OutName,TestInName ,p_label,p_val): print "to be implemented by my inherited class" return False def Process(self,TrainInName,TestInName,ParaInName,OutName): lY,lX = self.LoadData(TrainInName) lSVMPara = ReadSVMParaSet(ParaInName) SVMPara = lSVMPara[0] #only use first one SVMModel = svm_train(lY,lX,SVMPara.dump()) lTestY,lTestX = self.LoadData(TestInName) p_label,p_acc,p_val = svm_predict(lTestY,lTestX,SVMModel,'-b 1') #add a contengency matrix output? lCTable = ContingencyTable(p_label,lTestY) print json.dumps(lCTable) out = open(OutName,'w') json.dump(lCTable,out) out.close() self.DumpPrediction(OutName + "_pre", TestInName, p_label, p_val) return True

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# ~/models/cells/modelPC2006Akemann.py import os pwd = os.getcwd() # record root directory path ~/cerebmodels path_to_files = pwd + os.sep + "models" + os.sep + "cells" + os.sep + \ "PC2006Akemann" + os.sep # record path to this model/folder from models.cells.PC2006Akemann.Purkinje import Purkinje from executive import ExecutiveControl from managers.simulation import SimulationManager as sm from managers.read import ReadManager as rm from managers.signalprocessing import SignalProcessingManager as spm import sciunit from cerebunit.capabilities.cells.response import ProducesElectricalResponse from cerebunit.capabilities.cells.measurements import ProducesSomaRestingVm, ProducesSomaSpikeHeight #from pdb import set_trace as breakpoint class PurkinjeCell( sciunit.Model, ProducesElectricalResponse, ProducesSomaRestingVm ): """USE CASE: """ # AFTER the model is in the HBP Validation Framework Model catalog, set the generated uuid #uuid = "22dc8fd3-c62b-4e07-9e47-f5829e038d6d" def __init__(self): ### ===================== Descriptive Attributes ====================== self.modelscale = "cells" self.modelname = "PC2006Akemann" # ------specify cell-regions from with response are recorded------- self.regions = {"soma": ["v"]} #"dend_sm": ["v"], "dend_sp": ["v"]} self.recordingunits = {"v": "mV"} # -----------attributed inheritance from sciunit.Model-------------- self.name = "Akemann and Knöpfel 2006 model of PurkinjeCell" self.description = "Akemann & Knöpfel 006 model of PurkinjeCell (PC) and published in 10.1523/JNEUROSCI.5204-05.2006 This is a single compartment model. This model is the SciUnit wrapped version of the NEURON model in modelDB accession # 80769." # ### =================== Instantiate cell template ==================== sm.lock_and_load_model_libraries(modelscale=self.modelscale, modelname=self.modelname) os.chdir(path_to_files) self.cell = Purkinje() os.chdir(pwd) ### =============================================================== self.fullfilename = "nil" self.prediction = "nil" # # ======================================================================= # +++++++++++++++++++++++ MODEL CAPABILITIES ++++++++++++++++++++++++++++ # ======================================================================= # --------------------- produce_voltage_response ------------------------ def produce_voltage_response(self, **kwargs): """generic/essential model response **Keyword Arguments:** kwargs = { "parameters": dictionary with keys, "stimparameters": None or dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ #ExecutiveControl.launch_model_raw("cells") print("Simulation produce_voltage_response starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], mode = "raw" ) print("File saving ...") fullfilename = ec.save_response() setattr(model, "fullfilename", fullfilename) print("File saved.") print("Simulation produce_voltage_response Done.") return model # ----------------------- produce_soma_restingVm ----------------------------- def produce_soma_restingVm(self, **kwargs): """ kwargs = { "parameters": dictionary with keys, "stimparameters": dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ print("Sim produce_soma v_restingVm starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], capabilities = {"model": "produce_voltage_response", "vtest": ProducesElectricalResponse}, mode="capability") nwbfile = rm.load_nwbfile(model.fullfilename) orderedepochs = rm.order_all_epochs_for_region(nwbfile=nwbfile, region="soma v") timestamps_over_epochs = [ rm.timestamps_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] data_over_epochs = [ rm.data_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] baseVms = spm.distill_baseVm_pre_epoch( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) setattr(model, "prediction", baseVms) print("Simulation produce_soma v_restingVm Done.") return model # ----------------------- produce_soma_spikeheight ------------------------ def produce_soma_spikeheight(self, **kwargs): """ kwargs = { "parameters": dictionary with keys, "stimparameters": dictionary with keys "type" and "stimlist", "onmodel": instantiated model } """ print("Sim produce_soma_spikeheight starting ...") ec = ExecutiveControl() # only works when in ~/cerebmodels model = ec.launch_model( parameters = kwargs["parameters"], stimparameters = kwargs["stimparameters"], stimloc = kwargs["stimloc"], onmodel = kwargs["onmodel"], capabilities = {"model": "produce_voltage_response", "vtest": ProducesElectricalResponse}, mode="capability" ) nwbfile = rm.load_nwbfile(model.fullfilename) orderedepochs = rm.order_all_epochs_for_region(nwbfile=nwbfile, region="soma v") timestamps_over_epochs = [ rm.timestamps_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] data_over_epochs = [ rm.data_for_epoch( orderedepochs[i] ) for i in range(len(orderedepochs)) ] baseVm = spm.distill_baseVm_pre_epoch( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) try: peakVms = spm.distill_peakVm_from_spikes( timestamps = timestamps_over_epochs, datavalues = data_over_epochs ) except: peakVms = baseVm setattr(model, "prediction", peakVms[0] - baseVm[0]) print("Simulation produce_soma_spikeheight Done.") return model # ----------------------- produce_spike_train --------------------------- def produce_spike_train(self, **kwargs): """ Use case: """ pass

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"""Support for the Nettigo Air Monitor service.""" from __future__ import annotations from datetime import timedelta import logging from typing import cast from homeassistant.components.sensor import ( DOMAIN as PLATFORM, SensorEntity, SensorEntityDescription, ) from homeassistant.config_entries import ConfigEntry from homeassistant.core import HomeAssistant from homeassistant.helpers import entity_registry from homeassistant.helpers.entity_platform import AddEntitiesCallback from homeassistant.helpers.typing import StateType from homeassistant.helpers.update_coordinator import CoordinatorEntity from homeassistant.util.dt import utcnow from . import NAMDataUpdateCoordinator from .const import ATTR_UPTIME, DOMAIN, MIGRATION_SENSORS, SENSORS PARALLEL_UPDATES = 1 _LOGGER = logging.getLogger(__name__) async def async_setup_entry( hass: HomeAssistant, entry: ConfigEntry, async_add_entities: AddEntitiesCallback ) -> None: """Add a Nettigo Air Monitor entities from a config_entry.""" coordinator: NAMDataUpdateCoordinator = hass.data[DOMAIN][entry.entry_id] # Due to the change of the attribute name of two sensors, it is necessary to migrate # the unique_ids to the new names. ent_reg = entity_registry.async_get(hass) for old_sensor, new_sensor in MIGRATION_SENSORS: old_unique_id = f"{coordinator.unique_id}-{old_sensor}" new_unique_id = f"{coordinator.unique_id}-{new_sensor}" if entity_id := ent_reg.async_get_entity_id(PLATFORM, DOMAIN, old_unique_id): _LOGGER.debug( "Migrating entity %s from old unique ID '%s' to new unique ID '%s'", entity_id, old_unique_id, new_unique_id, ) ent_reg.async_update_entity(entity_id, new_unique_id=new_unique_id) sensors: list[NAMSensor | NAMSensorUptime] = [] for description in SENSORS: if getattr(coordinator.data, description.key) is not None: if description.key == ATTR_UPTIME: sensors.append(NAMSensorUptime(coordinator, description)) else: sensors.append(NAMSensor(coordinator, description)) async_add_entities(sensors, False) class NAMSensor(CoordinatorEntity, SensorEntity): """Define an Nettigo Air Monitor sensor.""" coordinator: NAMDataUpdateCoordinator def __init__( self, coordinator: NAMDataUpdateCoordinator, description: SensorEntityDescription, ) -> None: """Initialize.""" super().__init__(coordinator) self._attr_device_info = coordinator.device_info self._attr_unique_id = f"{coordinator.unique_id}-{description.key}" self.entity_description = description @property def native_value(self) -> StateType: """Return the state.""" return cast( StateType, getattr(self.coordinator.data, self.entity_description.key) ) @property def available(self) -> bool: """Return if entity is available.""" available = super().available # For a short time after booting, the device does not return values for all # sensors. For this reason, we mark entities for which data is missing as # unavailable. return ( available and getattr(self.coordinator.data, self.entity_description.key) is not None ) class NAMSensorUptime(NAMSensor): """Define an Nettigo Air Monitor uptime sensor.""" @property def native_value(self) -> str: """Return the state.""" uptime_sec = getattr(self.coordinator.data, self.entity_description.key) return ( (utcnow() - timedelta(seconds=uptime_sec)) .replace(microsecond=0) .isoformat() )

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# -*- coding: utf-8 -*- # @File : 重定向.py # @Author: 一稚杨 # @Date : 2018/6/7/007 # @Desc : 重定向和404页面定义 # redirect实现重定向 from flask import Flask, redirect, render_template, flash app = Flask(__name__) app.secret_key = '123456' @app.route("/index1") def index1(): flash("登录成功", category="login") flash("hello",category="hello") return redirect("/index2/") @app.route("/index2/") def index2(): return render_template("flash.html") @app.errorhandler(404) def error(error): return render_template("404.html"),404 # form表单action为空时访问那个页面？结论：当action为空时，数据提交给发送数据的页面 @app.route("/action_none", methods=["GET", "POST"]) def action_none(): return render_template("action.html") app.run(debug=True)

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import time reps = 1000 repslist = range(reps) def timer(func,*pargs, **kargs): start = time.clock() for i in repslist: ret = func(*pargs,**kargs) elapsed = time.clock() - start return (elapsed, ret)

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# -*- coding: utf-8 -*- # デスクトップアプリケーションの作成2 # ファイル選択ダイアログ import tkinter.filedialog as fd path = fd.askopenfilename( title="ファイルを選択してください", filetypes=[("python", "py")] ) print(path)

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# MIT LICENSE # # Copyright 1997 - 2020 by IXIA Keysight # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. from ixnetwork_restpy.base import Base from ixnetwork_restpy.files import Files from typing import List, Any, Union class Delay(Base): """Delay each packet. The Delay class encapsulates a required delay resource which will be retrieved from the server every time the property is accessed. """ __slots__ = () _SDM_NAME = 'delay' _SDM_ATT_MAP = { 'Enabled': 'enabled', 'Units': 'units', 'Value': 'value', } _SDM_ENUM_MAP = { 'units': ['kilometers', 'kKilometers', 'kMicroseconds', 'kMilliseconds', 'kSeconds', 'microseconds', 'milliseconds', 'seconds'], } def __init__(self, parent, list_op=False): super(Delay, self).__init__(parent, list_op) @property def Enabled(self): # type: () -> bool """ Returns ------- - bool: If true, delay packets. """ return self._get_attribute(self._SDM_ATT_MAP['Enabled']) @Enabled.setter def Enabled(self, value): # type: (bool) -> None self._set_attribute(self._SDM_ATT_MAP['Enabled'], value) @property def Units(self): # type: () -> str """ Returns ------- - str(kilometers | kKilometers | kMicroseconds | kMilliseconds | kSeconds | microseconds | milliseconds | seconds): Specify the units for the delay value. """ return self._get_attribute(self._SDM_ATT_MAP['Units']) @Units.setter def Units(self, value): # type: (str) -> None self._set_attribute(self._SDM_ATT_MAP['Units'], value) @property def Value(self): # type: () -> int """ Returns ------- - number: Time to delay each packet. """ return self._get_attribute(self._SDM_ATT_MAP['Value']) @Value.setter def Value(self, value): # type: (int) -> None self._set_attribute(self._SDM_ATT_MAP['Value'], value) def update(self, Enabled=None, Units=None, Value=None): # type: (bool, str, int) -> Delay """Updates delay resource on the server. Args ---- - Enabled (bool): If true, delay packets. - Units (str(kilometers | kKilometers | kMicroseconds | kMilliseconds | kSeconds | microseconds | milliseconds | seconds)): Specify the units for the delay value. - Value (number): Time to delay each packet. Raises ------ - ServerError: The server has encountered an uncategorized error condition """ return self._update(self._map_locals(self._SDM_ATT_MAP, locals()))

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import numpy as np # pip install numpy arreglo1 = np.arange(1, 10, dtype=np.int32).reshape((3, 3)) print('Numpy Array 1:\n{}'.format(arreglo1)) arreglo2 = np.arange(3, 0, -1, dtype=np.int32).reshape((1, 3)) print('Numpy Array 2:\n{}'.format(arreglo2)) arreglo3 = np.arange(10, 40, 10, dtype=np.int32).reshape((3, 1)) print('Numpy Array 3:\n{}'.format(arreglo3)) print() # Binary Operations print('Numpy Addition (a1 + a2)') print(arreglo1 + arreglo2, end='\n\n') print('Numpy Addition (a1 + a3)') print(arreglo1 + arreglo3, end='\n\n') print('Numpy Addition (a1 + 5)') print(arreglo1 + 5, end='\n\n')

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# -*- coding: utf-8 -*- import sklearn as sk import pandas as pd import numpy as np import matplotlib.pyplot as plt """ We will look at data regarding coronary heart disease (CHD) in South Africa. The goal is to use different variables such as tobacco usage, family history, ldl cholesterol levels, alcohol usage, obesity and more. """ heart = pd.read_csv('Heart_Disease.csv', sep=',', header=0) heart.head() labels = heart.iloc[:,9].values features = heart.iloc[:,:9].values # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split features_train, features_test, labels_train, labels_test = train_test_split(features, labels, test_size = 0.25, random_state = 0) # Feature Scaling from sklearn.preprocessing import StandardScaler sc = StandardScaler() features_train = sc.fit_transform(features_train) features_test = sc.transform(features_test) # Fitting Logistic Regression to the Training set from sklearn.linear_model import LogisticRegression classifier = LogisticRegression() classifier.fit(features_train, labels_train) #Calculate Class Probabilities probability = classifier.predict_proba(features_test) # Predicting the class labels labels_pred = classifier.predict(features_test) # Making the Confusion Matrix from sklearn.metrics import confusion_matrix cm = confusion_matrix(labels_test, labels_pred)

[ "sharma1997lak@gmail.com" ]

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/PyTorch/LanguageModeling/BERT/triton/deployment_toolkit/warmup.py

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# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import logging import pathlib from distutils.version import LooseVersion from importlib.metadata import version from typing import List TRITON_CLIENT_VERSION = LooseVersion(version("tritonclient")) # method from PEP-366 to support relative import in executed modules if __package__ is None: __package__ = pathlib.Path(__file__).parent.name from .core import BatchingMode, EvaluationMode, MeasurementMode, OfflineMode from .perf_analyzer import PerfAnalyzer, PerfAnalyzerConfig from .utils import parse_server_url LOGGER = logging.getLogger("warmup") def performance_evaluation_warmup( server_url: str, model_name: str, batch_sizes: List[int], number_of_triton_instances: int, number_of_model_instances: int, input_data: str, input_shapes: List[str], measurement_mode: MeasurementMode, measurement_interval: int, measurement_request_count: int, batching_mode: BatchingMode, offline_mode: OfflineMode, evaluation_mode: EvaluationMode, output_shared_memory_size: int, ): protocol, host, port = parse_server_url(server_url) measurement_interval = 2 * measurement_interval measurement_request_count = 2 * measurement_request_count if batching_mode == BatchingMode.STATIC: batch_sizes = sorted({1, batch_sizes[-1]}) max_concurrency = 1 min_concurrency = 1 step = 1 elif batching_mode == BatchingMode.DYNAMIC: max_batch_size = max(batch_sizes) max_total_requests = 2 * max_batch_size * number_of_triton_instances * number_of_model_instances max_concurrency = min(256, max_total_requests) step = max(1, max_concurrency // 2) min_concurrency = step batch_sizes = [max(1, max_total_requests // 256)] else: raise ValueError(f"Unsupported batching mode: {batching_mode}") for batch_size in batch_sizes: for concurrency in range(min_concurrency, max_concurrency + step, step): params = { "model-name": model_name, "model-version": 1, "batch-size": batch_size, "url": f"{host}:{port}", "protocol": protocol, "input-data": input_data, "measurement-interval": measurement_interval, "concurrency-range": f"{concurrency}:{concurrency}:1", "output-shared-memory-size": output_shared_memory_size, } if TRITON_CLIENT_VERSION >= LooseVersion("2.11.0"): params["measurement-mode"] = measurement_mode.value params["measurement-request-count"] = measurement_request_count if evaluation_mode == EvaluationMode.OFFLINE: params["shared-memory"] = offline_mode.value params["output-shared-memory-size"] = output_shared_memory_size config = PerfAnalyzerConfig() for param, value in params.items(): config[param] = value for shape in input_shapes: config["shape"] = shape perf_analyzer = PerfAnalyzer(config=config) perf_analyzer.run()

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# # tests/test_http_response.py # import growler import asyncio import pytest from unittest import mock from collections import OrderedDict from growler.http.response import Headers from mock_classes import ( request_uri, ) @pytest.fixture def res(mock_protocol): return growler.http.HTTPResponse(mock_protocol) @pytest.fixture def mock_app(): return mock.Mock(spec=growler.App, ) @pytest.fixture def mock_protocol(mock_app, request_uri): from urllib.parse import (unquote, urlparse, parse_qs) parsed_url = urlparse(request_uri) protocol = mock.Mock(spec=growler.http.GrowlerHTTPProtocol, loop=mock.Mock(spec=asyncio.BaseEventLoop), http_application=mock_app, headers=None, path=unquote(parsed_url.path), query=parse_qs(parsed_url.query),) protocol.socket.getpeername.return_value = ['', ''] return protocol def test_constructor(res, mock_protocol): assert isinstance(res, growler.http.HTTPResponse) assert res.protocol is mock_protocol def test_construct_with_eol(mock_protocol): EOL = ':' res = growler.http.HTTPResponse(mock_protocol, EOL) assert isinstance(res, growler.http.HTTPResponse) assert res.protocol is mock_protocol assert res.EOL is EOL def test_default_headers(res): res._set_default_headers() # assert res.protocol is mock_protocol def test_send_headers(res): res.send_headers() def test_write(res): res.write() def test_write_eof(res): res.write_eof() def test_end(res): res.end() @pytest.mark.parametrize('url, status', [ ('/', 200), ]) def test_redirect(res, url, status): res.redirect(url, status) @pytest.mark.parametrize('obj, expect', [ ({'a': 'b'}, b'{"a": "b"}') ]) def test_json(res, mock_protocol, obj, expect): res.json(obj) assert res.headers['content-type'] == 'application/json' mock_protocol. transport.write.assert_called_with(expect) @pytest.mark.parametrize('obj, expect', [ ({'a': 'b'}, b'{"a": "b"}') ]) def test_headers(res, mock_protocol, obj, expect): res.json(obj) assert res.headers['content-type'] == 'application/json' mock_protocol.transport.write.assert_called_with(expect) def test_header_construct_with_dict(): headers = Headers({'a': 'b', 'c': 'D'}) s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_construct_with_keywords(): headers = Headers(a='b', c='D') s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_construct_mixed(): headers = Headers({'a': 'b'}, c='D') s = str(headers) assert s == 'a: b\r\nc: D\r\n\r\n' or s == 'c: D\r\na: b\r\n\r\n' def test_header_set(): headers = Headers() headers['foo'] = 'bar' assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_dict(): headers = Headers() d = {'foo': 'bar'} headers.update(d) assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_multiple_dicts(): headers = Headers() d_0 = OrderedDict([('foo', 'baz'), ('a', 'b')]) d_1 = {'foo': 'bar'} headers.update(d_0, d_1) assert str(headers) == 'foo: bar\r\na: b\r\n\r\n' def test_header_update_with_keyword(): headers = Headers() headers.update(foo='bar') assert str(headers) == 'foo: bar\r\n\r\n' def test_header_update_with_mixed(): headers = Headers() d = {'foo': 'bazz'} headers.update(d, foo='bar') assert str(headers) == 'foo: bar\r\n\r\n' def test_callable_header_value(): headers = Headers() headers['foo'] = lambda: 'bar' assert str(headers) == 'foo: bar\r\n\r\n'

[ "andrewkubera@gmail.com" ]

andrewkubera@gmail.com

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# BSD 3-Clause License; see https://github.com/scikit-hep/uproot5/blob/main/LICENSE """ This module is initially empty, a repository for dynamically adding new classes. The purpose of this namespace is to allow :doc:`uproot.model.VersionedModel` classes that were automatically generated from ROOT ``TStreamerInfo`` to be pickled, with the help of :doc:`uproot.model.DynamicModel`. In `Python 3.7 and later <https://www.python.org/dev/peps/pep-0562>`__, attempts to extract items from this namespace generate new :doc:`uproot.model.DynamicModel` classes, which are used as a container in which data from pickled :doc:`uproot.model.VersionedModel` instances are filled. """ def __getattr__(name): import uproot g = globals() if name not in g: g[name] = uproot._util.new_class(name, (uproot.model.DynamicModel,), {}) return g[name]

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ronit29/docprime

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# Generated by Django 2.0.5 on 2018-11-02 19:13 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('authentication', '0063_merge_20181025_1818'), ] operations = [ migrations.AddField( model_name='spocdetails', name='source', field=models.CharField(blank=True, max_length=2000), ), ]

[ "arunchaudhary@policybazaar.com" ]

arunchaudhary@policybazaar.com

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LuisGonzalezLopez/Luis-Gonzalez

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import tokenize from typing import ( Iterator, Tuple, ) BACKTICK_QUOTED_STRING: int def create_valid_python_identifier(name: str) -> str: ... def clean_backtick_quoted_toks(tok: Tuple[int, str]) -> Tuple[int, str]: ... def clean_column_name(name: str) -> str: ... def tokenize_backtick_quoted_string( token_generator: Iterator[tokenize.TokenInfo], source: str, string_start: int ) -> Tuple[int, str]: ... def tokenize_string(source: str) -> Iterator[Tuple[int, str]]: ...

[ "luxo237@gmail.com" ]

luxo237@gmail.com

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AdamZhouSE/pythonHomework

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n=int(input()) result=[] for i in range(0,n): arr=[int(n) for n in input().split(',')] for j in range(0,n): result.append(arr[j]) k=int(input()) result.sort() print(result[k-1])

[ "1069583789@qq.com" ]

1069583789@qq.com

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John-W-Stevens/algorithms_clrs

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# Import numpy to use Inf from numpy import Inf def find_max_crossing_subarray(arr,low,mid,high): """ From CLRS pgs. 70-74 "Takes as input an array and indices low,mid,high Returns a tuple containing the indicies demarcating a maximum sub-array that crosses the midpoint, along with the sum of the values in a maximum sub-array." Running time: linear """ # Look at the left left_sum = -Inf sm = 0 # sm for sum for i in range(mid,low-1,-1): sm += arr[i] if sm >= left_sum: left_sum = sm max_left = i # Look at the right right_sum = -Inf sm = 0 for j in range(mid+1,high+1): sm += arr[j] if sm >= right_sum: right_sum = sm max_right = j return (max_left,max_right,left_sum+right_sum) def find_maximum_subarray(arr,low,high): """ From CLSR pgs. 70-74 Input is an array, arr. low and high are index positions in arr that function as bounds for searching. Returns a tuple containing indicies for maximum sub-array along with the sum of sub-array. Running time: theta(n lg n) where 'lg n' stands for log2n """ # Base case if high == low: return (low,high,arr[low]) else: # find middle point of array mid = (low + high)//2 # find a max sub-array in left sub-array left_low,left_high,left_sum = find_maximum_subarray(arr,low,mid) # find a max sub-array in right sub-array right_low,right_high,right_sum = find_maximum_subarray(arr,mid+1,high) # find a max sub-array that crosses the mid-point cross_low,cross_high,cross_sum = find_max_crossing_subarray(arr,low,mid,high) # test if left sub-array contains a sub-array with the maximum sum if left_sum >= right_sum and left_sum >= cross_sum: return (left_low,left_high,left_sum) # test if right sub-array contains a sub-array with the maximum sum elif right_sum >= left_sum and right_sum >= cross_sum: return (right_low,right_high,right_sum) # if neither left nor right sub-arrays contain a sub-array with the maximum sum, # then a maximum sub-array must cross the mid-point else: return (cross_low,cross_high,cross_sum) test = [17, -25, 6, 18, -23, 8, 28, 6, 34, 31, -50, 3, 46, -33, -45, -26, 14, -23, 45, -24, 21, -31, 19, -41, 49, 47, 29, -11, 16, 12, -9, -14, 26, -46, -11, 39, -41, -13, -11, 8, -19, -13, -9, -25, -15, 27, 30, 8, 10] print(find_maximum_subarray(test,0,len(test)-1)) # Output: (24, 32, 145) the maximum subarray exists at test[24:33] and the sum of this subarray is 145

[ "john.william.stevens1@gmail.com" ]

john.william.stevens1@gmail.com

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fazi4888/APCSP-FreshmanYear

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#!/Users/rayaan_siddiqi23/untitled50/bin/python # -*- python -*- # Keep this script in sync with python-config.sh.in import getopt import os import sys import sysconfig valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags', 'ldflags', 'extension-suffix', 'help', 'abiflags', 'configdir'] def exit_with_usage(code=1): print("Usage: {0} [{1}]".format( sys.argv[0], '|'.join('--'+opt for opt in valid_opts)), file=sys.stderr) sys.exit(code) try: opts, args = getopt.getopt(sys.argv[1:], '', valid_opts) except getopt.error: exit_with_usage() if not opts: exit_with_usage() pyver = sysconfig.get_config_var('VERSION') getvar = sysconfig.get_config_var opt_flags = [flag for (flag, val) in opts] if '--help' in opt_flags: exit_with_usage(code=0) for opt in opt_flags: if opt == '--prefix': print(sysconfig.get_config_var('prefix')) elif opt == '--exec-prefix': print(sysconfig.get_config_var('exec_prefix')) elif opt in ('--includes', '--cflags'): flags = ['-I' + sysconfig.get_path('include'), '-I' + sysconfig.get_path('platinclude')] if opt == '--cflags': flags.extend(getvar('CFLAGS').split()) print(' '.join(flags)) elif opt in ('--libs', '--ldflags'): libs = ['-lpython' + pyver + sys.abiflags] libs += getvar('LIBS').split() libs += getvar('SYSLIBS').split() # add the prefix/lib/pythonX.Y/config dir, but only if there is no # shared library in prefix/lib/. if opt == '--ldflags': if not getvar('Py_ENABLE_SHARED'): libs.insert(0, '-L' + getvar('LIBPL')) if not getvar('PYTHONFRAMEWORK'): libs.extend(getvar('LINKFORSHARED').split()) print(' '.join(libs)) elif opt == '--extension-suffix': print(sysconfig.get_config_var('EXT_SUFFIX')) elif opt == '--abiflags': print(sys.abiflags) elif opt == '--configdir': print(sysconfig.get_config_var('LIBPL'))

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#Distribute_Candies for _ in range(int(input())): n = int(input()) a=list(map(int,input().split())) if(len(a)==0): print(a[0]) elif(len(a)==1): print(min(a)) else: a.sort(reverse=True) s=0 for i in range(2,len(a),3): s +=a [i] print(s)

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# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from ... import _utilities __all__ = [ 'GetJobCredentialResult', 'AwaitableGetJobCredentialResult', 'get_job_credential', ] @pulumi.output_type class GetJobCredentialResult: """ A stored credential that can be used by a job to connect to target databases. """ def __init__(__self__, id=None, name=None, type=None, username=None): if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if name and not isinstance(name, str): raise TypeError("Expected argument 'name' to be a str") pulumi.set(__self__, "name", name) if type and not isinstance(type, str): raise TypeError("Expected argument 'type' to be a str") pulumi.set(__self__, "type", type) if username and not isinstance(username, str): raise TypeError("Expected argument 'username' to be a str") pulumi.set(__self__, "username", username) @property @pulumi.getter def id(self) -> str: """ Resource ID. """ return pulumi.get(self, "id") @property @pulumi.getter def name(self) -> str: """ Resource name. """ return pulumi.get(self, "name") @property @pulumi.getter def type(self) -> str: """ Resource type. """ return pulumi.get(self, "type") @property @pulumi.getter def username(self) -> str: """ The credential user name. """ return pulumi.get(self, "username") class AwaitableGetJobCredentialResult(GetJobCredentialResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetJobCredentialResult( id=self.id, name=self.name, type=self.type, username=self.username) def get_job_credential(credential_name: Optional[str] = None, job_agent_name: Optional[str] = None, resource_group_name: Optional[str] = None, server_name: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetJobCredentialResult: """ A stored credential that can be used by a job to connect to target databases. :param str credential_name: The name of the credential. :param str job_agent_name: The name of the job agent. :param str resource_group_name: The name of the resource group that contains the resource. You can obtain this value from the Azure Resource Manager API or the portal. :param str server_name: The name of the server. """ __args__ = dict() __args__['credentialName'] = credential_name __args__['jobAgentName'] = job_agent_name __args__['resourceGroupName'] = resource_group_name __args__['serverName'] = server_name if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('azure-native:sql/v20201101preview:getJobCredential', __args__, opts=opts, typ=GetJobCredentialResult).value return AwaitableGetJobCredentialResult( id=__ret__.id, name=__ret__.name, type=__ret__.type, username=__ret__.username)

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# Functions to run a call from originating from pkcli # This is just a temporary setup. libEnsembleOptimizer shouldn't actually be tied to execution mode # It is instantiated because nlopt was requested # THe executor will be setup separately based off 'execution_type' in YAML and registered with libEnsembleOptimizer from rsopt.libe_tools.optimizer import libEnsembleOptimizer def serial(config): opt = libEnsembleOptimizer() opt.load_configuration(config) return opt #.run() # These names have to line up with accepted values for setup.execution_type # Another place where shared names are imported from common source run_modes = { 'serial': serial }

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temperatura = 14 frio = temperatura < 15 horas_acordado = 18 sono = horas_acordado > 16 ficar_casa = sono and frio print("Ficar em casa: ", ficar_casa)

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# coding: utf-8 from selenium.webdriver import Chrome from selenium.common.exceptions import WebDriverException import requests from retrying import retry import json import time import pprint import traceback def wait_for(fn, timeout=5): start_time = time.time() while time.time() - start_time < timeout: try: return fn() except WebDriverException: time.sleep(0.1) # one more try, which will raise any errors if they are outstanding return fn() def find_by_css(selector): def _find(): return driver.find_element_by_css_selector(selector) return wait_for(_find) def find_linkedin_url(term): params = { 'key': 'AIzaSyBs_qRMdd3UxIp6HQ9zMidKupXkRCtmZrQ', 'cx': '007098471526848933106:c_yqy7e87hi', 'q': term } r = requests.get( 'https://www.googleapis.com/customsearch/v1', params=params) r_json = r.json() for item in r_json['items']: if 'pagemap' in item and 'person' in item['pagemap']: return item['link'] @retry(stop_max_delay=6000) def get_contact_linkedin_html(name, company): term = u"{} {}".format(name, company) url = find_linkedin_url(term) if not url: raise ValueError(u"No result for {}".format(term)) driver.get(url) return find_by_css('#profile').get_attribute('innerHTML'), url driver = Chrome() driver.set_window_size(1280, 700) results = [] def main(): with open('attendees.json') as f: attendees_raw = json.load(f) attendees = [(a['name'], a['info2']) for a in attendees_raw if 'info2' in a] for name, company in attendees: try: html, link = get_contact_linkedin_html(name, company) except Exception: print traceback.print_exc() html = None link = None results.append({ 'name': name, 'company': company, 'html': html, 'link': link }) print len(results) with open('results.json', 'w+') as out: json.dump(results, out, indent=2) driver.quit() if __name__ == '__main__': start_time = time.time() main() print("--- ran in %s seconds ---" % (time.time() - start_time))

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# qubit number=4 # total number=11 import pyquil from pyquil.api import local_forest_runtime, QVMConnection from pyquil import Program, get_qc from pyquil.gates import * import numpy as np conn = QVMConnection() def make_circuit()-> Program: prog = Program() # circuit begin prog += H(0) # number=1 prog += H(1) # number=2 prog += H(2) # number=3 prog += X(1) # number=8 prog += H(3) # number=4 prog += Y(3) # number=5 prog += X(3) # number=7 prog += CNOT(3,0) # number=9 prog += CNOT(3,0) # number=10 # circuit end return prog def summrise_results(bitstrings) -> dict: d = {} for l in bitstrings: if d.get(l) is None: d[l] = 1 else: d[l] = d[l] + 1 return d if __name__ == '__main__': prog = make_circuit() qvm = get_qc('4q-qvm') results = qvm.run_and_measure(prog,1024) bitstrings = np.vstack([results[i] for i in qvm.qubits()]).T bitstrings = [''.join(map(str, l)) for l in bitstrings] writefile = open("../data/startPyquil415.csv","w") print(summrise_results(bitstrings),file=writefile) writefile.close()

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# -*- coding: utf-8 -*- # Copyright 2015 Donne Martin. All Rights Reserved. # # Creative Commons Attribution 4.0 International License (CC BY 4.0) # http://creativecommons.org/licenses/by/4.0/ import unittest from click.testing import CliRunner from awesome.awesome_cli import AwesomeCli class AwesomeCliTest(unittest.TestCase): def setUp(self): self.runner = CliRunner() self.awesome_cli = AwesomeCli()

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''' Created on Mar 23, 2017 @author: MT ''' _______ h__ c_ Solution(o.. ___ rearrangeString s, k hashmap # dict ___ c __ s: hashmap[c] hashmap.g.. c, 0)+1 heap # list ___ c, freq __ hashmap.i.. h__.heappush(heap, [-freq, c]) queue # list res # list w.... heap: freq, c h__.heappop(heap) res.a..(c) queue.a..([freq, c]) __ l..(queue) < k: _____ freq, c queue.p.. 0) freq -freq-1 __ freq > 0 h__.heappush(heap, [-freq, c]) r.. ''.j..(res) __ l..(res) __ l..(s) ____ '' ___ test testCases [ ('aabbcc', 3), ('aaabc', 3), ('aaadbbcc', 2), ] ___ s, k __ testCases: print('s: %s' % (s print('k: %s' % (k result rearrangeString(s, k) print('result: %s' % (result print('-='*20+'-') __ _____ __ _____ Solution().test()

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#!/usr/bin/env python # -*- coding: utf-8 -*- from unittest import TestCase,TestSuite from tree import Tree from mdsdata import * from mdsscalar import * from mdsarray import * import numpy as np import random import os import sys import tempfile _tmpdir=tempfile.mkdtemp() def setUpModule(): pass def tearDownModule(): import shutil shutil.rmtree(_tmpdir) class segmentsTests(TestCase): def setUp(self): os.environ["seg_tree_path"]=_tmpdir def tearDown(self): pass def arrayDimensionOrder(self): ptree=Tree('seg_tree',-1,'NEW') ptree.addNode('IMM') ptree.write() ptree=Tree('seg_tree',-1) ptree.createPulse(1) ptree=Tree('seg_tree',1) node=ptree.getNode('IMM') WIDTH = 640 HEIGHT =480; currFrame=np.zeros(WIDTH*HEIGHT, dtype = np.int16); currTime=float(0); for i in range(0,WIDTH): for j in range(0,HEIGHT): currFrame[i*HEIGHT+j]=random.randint(0,255) currTime = float(0) startTime = Float32(currTime) endTime = Float32(currTime) dim = Float32Array(currTime) segment = Int16Array(currFrame) segment.resize([1,HEIGHT,WIDTH]) shape = segment.getShape() node.makeSegment(startTime, endTime, dim, segment) retShape = node.getShape() self.assertEqual(shape[0],retShape[0]) self.assertEqual(shape[1],retShape[1]) self.assertEqual(shape[2],retShape[2]) def runTest(self): self.arrayDimensionOrder() def suite(): tests = ['arrayDimensionOrder'] return TestSuite(map(segmentsTests,tests))

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import numpy as np from matplotlib import pyplot as plt from matplotlib import animation fig, ax = plt.subplots() # 生成子图，相当于fig = plt.figure(), # ax = fig.add_subplot(),其中ax的函数参数表示把当前画布进行分割， # 例：fig.add_subplot(2,2,2).表示将画布分割为两行两列，ax在第2个子图中绘制，其中行优先。 x = np.arange(0, 2*np.pi, 0.01) # 表示从0~2*np.pi之间每隔0.01取一个点 line, = ax.plot(x, np.sin(x)) # 注意，这里line后面要加上逗号，表示一个具有一个元素的元组 # print(type(line)) # print(type((line,))) # <class 'matplotlib.lines.Line2D'> # <class 'tuple'> def animate(i): # 这里的i其实就是参数0-99，即时frames控制的参数，控制程序画图变换的次数 # print(i) # 0-99 line.set_ydata(np.sin(x + i/10.0)) # 改变线条y的坐标值 return line, def init(): # 初始化函数，图形开始显示的状态 line.set_ydata(np.sin(x)) return line, ani = animation.FuncAnimation(fig=fig, func=animate, frames=100, init_func=init, interval=100, blit=False) """frames设定帧数,总共执行100个update就会进行下一次循环，并且frames还会作为参数传入animate()函数，init_func设定初始函数图像, interval设置更新间隔此处设置为20毫秒，(仔细想想20毫秒其实是很小的一个间隔) blit如果是只有变化了的像素点才更新就设置为True,如果是整张图片所有像素点全部更新的话就设置为False """ plt.show()

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# coding=utf-8 # Copyright 2023 The Google Research Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Base class for tasks.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import abc import csv import os import tensorflow.compat.v1 as tf class Example(object): __metaclass__ = abc.ABCMeta def __init__(self, task_name): self.task_name = task_name class Task(object): """Override this class to add a new task.""" __metaclass__ = abc.ABCMeta def __init__(self, config, name, long_sequences=False): self.config = config self.name = name self.long_sequences = long_sequences def get_examples(self, split): return self.load_data(split + ".tsv", split) def get_test_splits(self): return ["test"] def load_data(self, fname, split): examples = self._create_examples( read_tsv(os.path.join(self.config.raw_data_dir(self.name), fname), max_lines=50 if self.config.debug else None), split) return examples @abc.abstractmethod def _create_examples(self, lines, split): pass @abc.abstractmethod def get_scorer(self): pass @abc.abstractmethod def get_feature_specs(self): pass @abc.abstractmethod def featurize(self, example, is_training): pass @abc.abstractmethod def get_prediction_module(self, bert_model, features, is_training, percent_done): pass def __repr__(self): return "Task(" + self.name + ")" def read_tsv(input_file, quotechar=None, max_lines=None): """Reads a tab separated value file.""" with tf.gfile.Open(input_file, "r") as f: reader = csv.reader(f, delimiter="\t", quotechar=quotechar) lines = [] for i, line in enumerate(reader): if max_lines and i >= max_lines: break lines.append(line) return lines

[ "copybara-worker@google.com" ]

copybara-worker@google.com

039644bfddd186986c491626e0b7127322ccbf58

f576f0ea3725d54bd2551883901b25b863fe6688

/sdk/identity/azure-identity/azure/identity/aio/_internal/get_token_mixin.py

162e6a51da5795a3b797f3692d41a13ade964552

[ "LicenseRef-scancode-generic-cla", "MIT", "LGPL-2.1-or-later" ]

permissive

Azure/azure-sdk-for-python

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c2ca191e736bb06bfbbbc9493e8325763ba990bb

refs/heads/main

2023-09-06T09:30:13.135012

2023-09-06T01:08:06

4,127,088

4,046

2,755

MIT

2023-09-14T21:48:49

2012-04-24T16:46:12

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UTF-8

Python

false

4,791

py

# ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ import abc import logging import time from typing import Any, Optional from azure.core.credentials import AccessToken from ..._constants import DEFAULT_REFRESH_OFFSET, DEFAULT_TOKEN_REFRESH_RETRY_DELAY from ..._internal import within_credential_chain _LOGGER = logging.getLogger(__name__) class GetTokenMixin(abc.ABC): def __init__(self, *args, **kwargs) -> None: self._last_request_time = 0 # https://github.com/python/mypy/issues/5887 super(GetTokenMixin, self).__init__(*args, **kwargs) # type: ignore @abc.abstractmethod async def _acquire_token_silently(self, *scopes: str, **kwargs) -> Optional[AccessToken]: """Attempt to acquire an access token from a cache or by redeeming a refresh token. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :return: An access token with the desired scopes if successful; otherwise, None. :rtype: ~azure.core.credentials.AccessToken or None """ @abc.abstractmethod async def _request_token(self, *scopes: str, **kwargs) -> AccessToken: """Request an access token from the STS. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :return: An access token with the desired scopes. :rtype: ~azure.core.credentials.AccessToken """ def _should_refresh(self, token: AccessToken) -> bool: now = int(time.time()) if token.expires_on - now > DEFAULT_REFRESH_OFFSET: return False if now - self._last_request_time < DEFAULT_TOKEN_REFRESH_RETRY_DELAY: return False return True async def get_token( self, *scopes: str, claims: Optional[str] = None, tenant_id: Optional[str] = None, **kwargs: Any ) -> AccessToken: """Request an access token for `scopes`. This method is called automatically by Azure SDK clients. :param str scopes: desired scopes for the access token. This method requires at least one scope. For more information about scopes, see https://learn.microsoft.com/azure/active-directory/develop/scopes-oidc. :keyword str claims: additional claims required in the token, such as those returned in a resource provider's claims challenge following an authorization failure. :keyword str tenant_id: optional tenant to include in the token request. :keyword bool enable_cae: indicates whether to enable Continuous Access Evaluation (CAE) for the requested token. Defaults to False. :return: An access token with the desired scopes. :rtype: ~azure.core.credentials.AccessToken :raises CredentialUnavailableError: the credential is unable to attempt authentication because it lacks required data, state, or platform support :raises ~azure.core.exceptions.ClientAuthenticationError: authentication failed. The error's ``message`` attribute gives a reason. """ if not scopes: raise ValueError('"get_token" requires at least one scope') try: token = await self._acquire_token_silently(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) if not token: self._last_request_time = int(time.time()) token = await self._request_token(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) elif self._should_refresh(token): try: self._last_request_time = int(time.time()) token = await self._request_token(*scopes, claims=claims, tenant_id=tenant_id, **kwargs) except Exception: # pylint:disable=broad-except pass _LOGGER.log( logging.DEBUG if within_credential_chain.get() else logging.INFO, "%s.get_token succeeded", self.__class__.__name__, ) return token except Exception as ex: _LOGGER.log( logging.DEBUG if within_credential_chain.get() else logging.WARNING, "%s.get_token failed: %s", self.__class__.__name__, ex, exc_info=_LOGGER.isEnabledFor(logging.DEBUG), ) raise

[ "noreply@github.com" ]

Azure.noreply@github.com

cb8a404a6028dd2e0c857ee4f7bbbaa73b7296c9

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03200/s271432048.py

bcd6a8482b6eb023426b8dd72faca95f03661394

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

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UTF-8

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176

py

S = list(input()) n = len(S) cnt_b = 0 cnt = 0 for i in range(n): if S[i] == 'B': cnt_b += 1 cnt += i ans = int((2*n - cnt_b -1)*cnt_b*0.5 - cnt) print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

59565e2453584531a21bcde645e428597918d80b

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/0x03-python-data_structures/10-divisible_by_2.py

2d808d5249e958464d33eb26dcdab22c4db79367

[]

no_license

MCavigli/holbertonschool-higher_level_programming_classic

2cea769dc1fd39e90f6ef74cdb3191e2472b0282

870548f964a3deac4a41918e9c3d0bad6cd732b4

refs/heads/master

2022-03-06T09:33:56.839118

2019-09-27T06:04:34

184,122,977

3

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UTF-8

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py

#!/usr/bin/python3 def divisible_by_2(my_list=[]): new = [] for num in my_list: new.append(True) if num % 2 == 0 else new.append(False) return new

[ "mcavigli@gmail.com" ]

mcavigli@gmail.com

3034898b4c6efff6c979aa9c058eaad3bdfe78e5

d51b4c766661af65b4ee6e7c30f8cb4bdd8603e3

/python/oop/method/iter.py

a612e99ce5f3e8c7cc0ed0aa897554f8d66889a4

[]

no_license

yanxurui/keepcoding

3e988c76b123d55b32cf7cc35fbffb12c4ccb095

d6b9f07e2d1437681fa77fee0687ea9b83cab135

refs/heads/master

2021-01-24T09:01:41.306597

2020-05-21T05:36:04

93,400,267

1

null

UTF-8

Python

false

698

py

class Spam(object): """[summary] >>> for i in Spam(1, 5): ... print(i) ... 1 4 9 16 >>> # iterate manully >>> X = Spam(1, 5) >>> I = iter(X) >>> next(I) 1 >>> next(I) 4 >>> next(I) 9 >>> next(I) 16 >>> next(I) Traceback (most recent call last): StopIteration """ def __init__(self, start, stop): self.value = start self.stop = stop def __iter__(self): return self # use `def __next__(self)` in python3 def next(self): if self.value == self.stop: raise StopIteration rv = self.value ** 2 self.value += 1 return rv

[ "617080352@qq.com" ]

617080352@qq.com

e85fdfeeaef3f45656935aec998ebc36b9928833

7f3a439c6ac921f07101759e932424792ee9e24e

/std_lib/asyncio/p01_coroutine_task/ch02_awaitables.py

9d984214e2480f5b6935010ec261bc2252865bb2

[]

no_license

multiscripter/python

03f6299af0ee2153e9e3b696aa591e460a3d6a52

eef7900b7a564e0850659fb59c1218be9c6829ea

refs/heads/master

2023-04-13T05:24:29.434394

2021-04-26T12:11:59

289,573,367

0

null

UTF-8

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false

1,553

py

import asyncio # Мы говорим, что объект является awaitable (ожидаемым) объектом, # если его можно использовать в выражении await. # Многие API-интерфейсы asyncio предназначены для приёма awaitable-объектов. # Есть три основных типа awaitable-объектов: Coroutine, Task и Future. # 1. Coroutine. # coroutines являются awaitable, и поэтому их можно "ожидать" из других coroutines: async def nested(): return 42 async def run_nested(): print(await nested()) asyncio.run(run_nested()) # 2. Task. # Tasks используются для планирования запуска coroutines одновременно. async def run_task_nested(): task = asyncio.create_task(nested()) print(await task) asyncio.run(run_task_nested()) # 3. Future. # Future - это специальный низкоуровневый ожидающий объект, # представляющий конечный результат асинхронной операции. # Когда ожидается объект Future, это означает, что coroutine будет ждать, # пока Future не будет разрешен (resolved) в каком-то другом месте. # Future-объекты в asyncio необходимы, чтобы разрешить использование кода # на основе callback с async/await.

[ "ILL-JAH@yandex.ru" ]

ILL-JAH@yandex.ru

53c448f8e4e441f92e2aec10e29d9ca24359595a

9e988c0dfbea15cd23a3de860cb0c88c3dcdbd97

/sdBs/AllRun/pg_1412+299/sdB_PG_1412+299_lc.py

1fc949095568bba26e541e43fa821db7addabfb7

[]

no_license

tboudreaux/SummerSTScICode

73b2e5839b10c0bf733808f4316d34be91c5a3bd

4dd1ffbb09e0a599257d21872f9d62b5420028b0

refs/heads/master

2021-01-20T18:07:44.723496

2016-08-08T16:49:53

65,221,159

0

null

UTF-8

Python

false

346

py

from gPhoton.gAperture import gAperture def main(): gAperture(band="NUV", skypos=[213.598708,29.684953], stepsz=30., csvfile="/data2/fleming/GPHOTON_OUTPU/LIGHTCURVES/sdBs/sdB_PG_1412+299 /sdB_PG_1412+299_lc.csv", maxgap=1000., overwrite=True, radius=0.00555556, annulus=[0.005972227,0.0103888972], verbose=3) if __name__ == "__main__": main()

[ "thomas@boudreauxmail.com" ]

thomas@boudreauxmail.com

91f7b1e95f64d31541ee7a3ad43d81110ac198fd

1d38c549c07f43cc26b7353ef95300b934eeed33

/GUI/Edit/Specy.py

fb03a7097cd0a7523d4349c7642606a3422113c2

[]

no_license

pooyagheyami/Adel3

a6354fbc5aa56a9c38a8b724c8d22bea689380a1

29e257e19fd6914de0e60c303871321e457a858b

refs/heads/master

2022-11-07T21:53:13.958369

2020-06-12T13:22:55

271,803,177

0

null

UTF-8

Python

false

4,690

py

# -*- coding: utf-8 -*- ########################################################################### ## Python code generated with wxFormBuilder (version Jun 17 2015) ## http://www.wxformbuilder.org/ ## ## PLEASE DO "NOT" EDIT THIS FILE! ########################################################################### import wx import wx.xrc import wx.grid import Database.MDataGet as DG ########################################################################### ## Class MyPanel2 ########################################################################### class MyPanel2 ( wx.Panel ): def __init__( self, parent , txts , ccod ,stit): wx.Panel.__init__ ( self, parent, id = wx.ID_ANY, pos = wx.DefaultPosition, size = wx.Size( 273,256 ), style = wx.TAB_TRAVERSAL ) self.SetLayoutDirection(2) self.ccod = ccod #print self.ccod #print stit self.iData = DG.GetData(u'',u'') self.itits = self.iData.gTitel(stit) self.ispec = self.iData.gSpcy(self.ccod) self.row = len(self.itits) Vsz1 = wx.BoxSizer( wx.VERTICAL ) Hsz1 = wx.BoxSizer( wx.HORIZONTAL ) self.txt1 = wx.StaticText( self, wx.ID_ANY, txts[0], wx.DefaultPosition, wx.DefaultSize, 0 ) self.txt1.Wrap( -1 ) Hsz1.Add( self.txt1, 0, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) self.fld1 = wx.TextCtrl( self, wx.ID_ANY, txts[1], wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz1.Add( self.fld1, 1, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) Vsz1.Add( Hsz1, 0, wx.EXPAND, 5 ) Hsz2 = wx.BoxSizer( wx.HORIZONTAL ) self.grid1 = wx.grid.Grid( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.STATIC_BORDER ) # Grid self.grid1.CreateGrid( self.row, 2 ) self.grid1.EnableEditing( True ) self.grid1.EnableGridLines( True ) self.grid1.EnableDragGridSize( False ) self.grid1.SetMargins( 0, 0 ) # Columns self.grid1.SetColSize( 0, 99 ) self.grid1.SetColSize( 1, 134 ) self.grid1.EnableDragColMove( False ) self.grid1.EnableDragColSize( True ) self.grid1.SetColLabelSize( 30 ) self.grid1.SetColLabelValue( 0, u"عنوان" ) self.grid1.SetColLabelValue( 1, u"مشخصه" ) self.grid1.SetColLabelAlignment( wx.ALIGN_CENTRE, wx.ALIGN_CENTRE ) # Rows self.grid1.EnableDragRowSize( True ) self.grid1.SetRowLabelSize( 19 ) self.grid1.SetRowLabelAlignment( wx.ALIGN_CENTRE, wx.ALIGN_CENTRE ) # Label Appearance # Cell Defaults self.grid1.SetDefaultCellAlignment( wx.ALIGN_LEFT, wx.ALIGN_TOP ) Hsz2.Add( self.grid1, 1, wx.ALL|wx.ALIGN_CENTER_VERTICAL|wx.EXPAND, 5 ) Vsz1.Add( Hsz2, 1, wx.EXPAND|wx.ALIGN_CENTER_HORIZONTAL, 5 ) Hsz3 = wx.BoxSizer( wx.HORIZONTAL ) self.btn1 = wx.Button( self, wx.ID_ANY, u"انصراف", wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz3.Add( self.btn1, 0, wx.ALL|wx.ALIGN_CENTER_VERTICAL, 5 ) self.btn2 = wx.Button( self, wx.ID_ANY, u"ثبت شود", wx.DefaultPosition, wx.DefaultSize, 0 ) Hsz3.Add( self.btn2, 0, wx.ALL, 5 ) Vsz1.Add( Hsz3, 0, wx.ALIGN_CENTER_HORIZONTAL, 5 ) #self.iData = DG.GetData(u'',u'') #self.itits = self.iData.gTitel(stit) #self.ispec = self.iData.gSpcy(self.ccod) self.lodtit() self.SetSizer( Vsz1 ) self.Layout() self.svit = False # Connect Events self.btn1.Bind( wx.EVT_BUTTON, self.cancl ) self.btn2.Bind( wx.EVT_BUTTON, self.aplyit ) def __del__( self ): pass # Virtual event handlers, overide them in your derived class def cancl( self, event ): self.svit = False q = self.GetParent() q.Close() def aplyit( self, event ): self.svit = True #self.sData = DG.SetData(u'',u'') #idata = self.gettit() #print idata #self.savtit(idata,self.sData) q = self.GetParent() q.Close() def lodtit(self): j = 0 for t in self.itits: self.grid1.SetCellValue(j,0,t[0]) for s in self.ispec: if s[1] in t: self.grid1.SetCellValue(j,1,s[0]) j = j + 1 def gettit(self): self.spcy = [] for i in range(len(self.itits)): ispc = self.grid1.GetCellValue(i,1) if ispc != '': self.spcy.append((self.ccod,self.itits[i][1],ispc)) #print self.itits[i][1] #print self.spcy return self.spcy def RetRev(self): return self.svit

[ "pooyagheyami@gmail.com" ]

pooyagheyami@gmail.com

41f673888cfffe4c1aa80b2a5a347f7f943800df

54ddb3f38cd09ac25213a7eb8743376fe778fee8

/topic_02_syntax/examples/isdigit_isnumeric_isdecimal.py

e1596f3051a547ad360699482c643e2c9d57e600

[]

no_license

ryndovaira/leveluppythonlevel1_300321

dbfd4ee41485870097ee490f652751776ccbd7ab

0877226e6fdb8945531775c42193a90ddb9c8a8b

refs/heads/master

2023-06-06T07:44:15.157913

2021-06-18T11:53:35

376,595,962

0

null

UTF-8

Python

false

621

py

def check_str(my_str): print(f"mystr: {my_str}") print(f"isnumeric: {str.isnumeric(my_str)}") print(f"isdigit: {str.isdigit(my_str)}") print(f"isdecimal: {str.isdecimal(my_str)}") print("-" * 50) # isdecimal() ⊆ isdigit() ⊆ isnumeric() if __name__ == '__main__': check_str('½') check_str('ⅠⅢⅧ') check_str('⑩⑬㊿') check_str('³') check_str('🄀⒊⒏') check_str('⓪③⑧') check_str('038') check_str('０３８') # FULLWIDTH DIGIT check_str('٠١٢٣٤') # ARABIC-INDIC DIGIT check_str('-38') check_str('+38') check_str('3_8')

[ "ryndovaira@gmail.com" ]

ryndovaira@gmail.com

2f3807cf8f62e47c63a60a47b092def214c58a97

524756e5e03465584dcb2d04b8092fbe8840448a

/users/signals.py

61f3f6acbaa87c5bbd5887d4336cc27d40a10557

[ "Apache-2.0" ]

permissive

areebbeigh/greenspace-demo

f9a241fb6c39a724b19094ccf21114647492dd81

0754f3b50e845bd5e50239361239f9b0b8aba42b

refs/heads/master

2022-10-11T05:45:05.036097

2020-06-11T11:04:12

2020-06-11T11:41:38

271,524,789

2

0

null

UTF-8

Python

false

300

py

import sys from django.conf import settings def create_groups(sender, **kwargs): from django.contrib.auth.models import Group group, created = Group.objects.get_or_create(name=settings.NURSERY_MGR_GROUP) print('Created new nursery group' if created else 'Nursery group already exists')

[ "areebbeigh@gmail.com" ]

areebbeigh@gmail.com

9ab1dae85e9196df975840e6c6d4551650fb7216

3adec884f06eabfe50d4ab3456123e04d02b02ff

/148. Sort List.py

a2e8d101bc501c111c899032f45427524ee85d4f

[]

no_license

windmzx/pyleetcode

c57ecb855c8e560dd32cf7cf14616be2f91ba50e

d0a1cb895e1604fcf70a73ea1c4b1e6b283e3400

refs/heads/master

2022-10-05T17:51:08.394112

2020-06-09T09:24:28

250,222,719

0

null

UTF-8

Python

false

1,486

py

# Definition for singly-linked list. class ListNode: def __init__(self, x): self.val = x self.next = None class Solution: def sortList(self, head: ListNode) -> ListNode: def split(head): if head.next == None: return head p =head q=head while q != None and q.next != None: temp=p p=p.next q=q.next.next temp.next = None l=split(head) r=split(p) return merge(l,r) def merge(l1,l2): head=ListNode(-1) cur=head while l1!=None and l2!=None: if l1.val<l2.val: cur.next=l1 l1=l1.next cur=cur.next else: cur.next=l2 l2=l2.next cur=cur.next if l1!=None: cur.next=l1 if l2!=None: cur.next=l2 return head.next if head is None: return None return split(head) if __name__ == "__main__": x=Solution() li=ListNode(3) p=li p.next=ListNode(1) p=p.next p.next=ListNode(4) p=p.next p.next=ListNode(0) p=p.next p.next=ListNode(2) p=p.next p.next=ListNode(5) p=p.next re=x.sortList(li) while re!=None: print(re.val) re=re.next

[ "2281927774@qq.com" ]

2281927774@qq.com

313e25acc001a41e971e137fbcf6bee9f8d3a909

8e69eee9b474587925e22413717eb82e4b024360

/v1.0.0.test/toontown/minigame/TwoDEnemyMgr.py

2b350c515aa1c976abc5e5490424ee267024aaa9

[ "MIT" ]

permissive

TTOFFLINE-LEAK/ttoffline

afaef613c36dc3b70514ccee7030ba73c3b5045b

bb0e91704a755d34983e94288d50288e46b68380

refs/heads/master

2020-06-12T15:41:59.411795

2020-04-17T08:22:55

194,348,185

5

4

null

UTF-8

Python

false

1,535

py

from panda3d.core import * from direct.directnotify import DirectNotifyGlobal from direct.showbase.DirectObject import DirectObject from toontown.minigame import ToonBlitzGlobals from toontown.minigame import TwoDEnemy class TwoDEnemyMgr(DirectObject): notify = DirectNotifyGlobal.directNotify.newCategory('TwoDEnemyMgr') def __init__(self, section, enemyList): self.section = section self.enemyList = enemyList self.load() def destroy(self): self.section = None while len(self.enemies): enemy = self.enemies[0] enemy.destroy() self.enemies.remove(enemy) self.enemies = None return def load(self): if len(self.enemyList): self.enemiesNP = NodePath('Enemies') self.enemiesNP.reparentTo(self.section.sectionNP) self.enemies = [] for index in xrange(len(self.enemyList)): enemyId = self.section.getSectionizedId(index) suitAttribs = self.enemyList[index] newEnemy = TwoDEnemy.TwoDEnemy(self, enemyId, suitAttribs) newEnemy.suit.reparentTo(self.enemiesNP) self.enemies.append(newEnemy) def enterPlay(self, elapsedTime): for enemy in self.enemies: enemy.start(elapsedTime) def exitPlay(self): pass def enterPause(self): for enemy in self.enemies: enemy.enterPause() def exitPause(self): for enemy in self.enemies: enemy.exitPause()

[ "s0mberdemise@protonmail.com" ]

s0mberdemise@protonmail.com

10e3f86ff0569d076876a2d1d0c9d815c172bf83

811bf15a5bad488284300b6016c8b77f1e2daf24

/rllib/core/testing/tf/bc_module.py

cca3a42f4eeb2f0f78c637b944e16f7057e4c21d

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permissive

justinwyang/ray

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import tensorflow as tf import tensorflow_probability as tfp from typing import Any, Mapping from ray.rllib.core.rl_module.rl_module import RLModule, RLModuleConfig from ray.rllib.core.rl_module.marl_module import ( MultiAgentRLModule, MultiAgentRLModuleConfig, ) from ray.rllib.core.rl_module.tf.tf_rl_module import TfRLModule from ray.rllib.core.models.specs.typing import SpecType from ray.rllib.policy.sample_batch import SampleBatch from ray.rllib.utils.annotations import override from ray.rllib.utils.nested_dict import NestedDict class DiscreteBCTFModule(TfRLModule): def __init__(self, config: RLModuleConfig) -> None: super().__init__(config) def setup(self): input_dim = self.config.observation_space.shape[0] hidden_dim = self.config.model_config_dict["fcnet_hiddens"][0] output_dim = self.config.action_space.n layers = [] layers.append(tf.keras.Input(shape=(input_dim,))) layers.append(tf.keras.layers.ReLU()) layers.append(tf.keras.layers.Dense(hidden_dim)) layers.append(tf.keras.layers.ReLU()) layers.append(tf.keras.layers.Dense(output_dim)) self.policy = tf.keras.Sequential(layers) self._input_dim = input_dim @override(RLModule) def output_specs_exploration(self) -> SpecType: return ["action_dist"] @override(RLModule) def output_specs_inference(self) -> SpecType: return ["action_dist"] @override(RLModule) def output_specs_train(self) -> SpecType: return ["action_dist"] @override(RLModule) def _forward_inference(self, batch: NestedDict) -> Mapping[str, Any]: obs = batch[SampleBatch.OBS] action_logits = self.policy(obs) action_logits_inference = tf.argmax(action_logits, axis=-1) action_dist = tfp.distributions.Deterministic(action_logits_inference) return {"action_dist": action_dist} @override(RLModule) def _forward_exploration(self, batch: NestedDict) -> Mapping[str, Any]: return self._forward_inference(batch) @override(RLModule) def _forward_train(self, batch: NestedDict) -> Mapping[str, Any]: obs = batch[SampleBatch.OBS] action_logits = self.policy(obs) action_dist = tfp.distributions.Categorical(logits=action_logits) return {"action_dist": action_dist} @override(RLModule) def get_state(self) -> Mapping[str, Any]: return {"policy": self.policy.get_weights()} @override(RLModule) def set_state(self, state: Mapping[str, Any]) -> None: self.policy.set_weights(state["policy"]) class BCTfRLModuleWithSharedGlobalEncoder(TfRLModule): def __init__(self, encoder, local_dim, hidden_dim, action_dim): super().__init__() self.encoder = encoder self.policy_head = tf.keras.Sequential( [ tf.keras.layers.Dense( hidden_dim + local_dim, input_shape=(hidden_dim + local_dim,), activation="relu", ), tf.keras.layers.Dense(hidden_dim, activation="relu"), tf.keras.layers.Dense(action_dim), ] ) @override(RLModule) def _default_input_specs(self): return [("obs", "global"), ("obs", "local")] @override(RLModule) def _forward_inference(self, batch): return self._common_forward(batch) @override(RLModule) def _forward_exploration(self, batch): return self._common_forward(batch) @override(RLModule) def _forward_train(self, batch): return self._common_forward(batch) def _common_forward(self, batch): obs = batch["obs"] global_enc = self.encoder(obs["global"]) policy_in = tf.concat([global_enc, obs["local"]], axis=-1) action_logits = self.policy_head(policy_in) return {"action_dist": tf.distributions.Categorical(logits=action_logits)} class BCTfMultiAgentModuleWithSharedEncoder(MultiAgentRLModule): def __init__(self, config: MultiAgentRLModuleConfig) -> None: super().__init__(config) def setup(self): # constructing the global encoder based on the observation_space of the first # module module_specs = self.config.modules module_spec = next(iter(module_specs.values())) global_dim = module_spec.observation_space["global"].shape[0] hidden_dim = module_spec.model_config_dict["fcnet_hiddens"][0] shared_encoder = tf.keras.Sequential( [ tf.keras.Input(shape=(global_dim,)), tf.keras.layers.ReLU(), tf.keras.layers.Dense(hidden_dim), ] ) for module_id, module_spec in module_specs.items(): self._rl_modules[module_id] = module_spec.module_class( encoder=shared_encoder, local_dim=module_spec.observation_space["local"].shape[0], hidden_dim=hidden_dim, action_dim=module_spec.action_space.n, ) def serialize(self): # TODO (Kourosh): Implement when needed. raise NotImplementedError def deserialize(self, data): # TODO (Kourosh): Implement when needed. raise NotImplementedError

[ "noreply@github.com" ]

justinwyang.noreply@github.com

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arineto/django-multi-tenant-example

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from django.contrib import admin from .models import Item from multi_tenant.models import Theme from multi_tenant.models import Tenant # Register your models here. admin.site.register(Item) admin.site.register(Theme) admin.site.register(Tenant)

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from django.contrib import admin from logger.models import Entry class EntryAdmin(admin.ModelAdmin): list_display = ('__unicode__', 'action', 'created_at',) list_filter = ('action', 'created_at',) admin.site.register(Entry, EntryAdmin)

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import logging import multiprocessing import multiprocessing.dummy from multiprocessing.reduction import reduce_connection import pickle import gobject gobject.threads_init() from mopidy import SettingsError logger = logging.getLogger('mopidy.utils.process') def pickle_connection(connection): return pickle.dumps(reduce_connection(connection)) def unpickle_connection(pickled_connection): # From http://stackoverflow.com/questions/1446004 (func, args) = pickle.loads(pickled_connection) return func(*args) class BaseProcess(multiprocessing.Process): def __init__(self, core_queue): super(BaseProcess, self).__init__() self.core_queue = core_queue def run(self): logger.debug(u'%s: Starting process', self.name) try: self.run_inside_try() except KeyboardInterrupt: logger.info(u'Interrupted by user') self.exit(0, u'Interrupted by user') except SettingsError as e: logger.error(e.message) self.exit(1, u'Settings error') except ImportError as e: logger.error(e) self.exit(2, u'Import error') except Exception as e: logger.exception(e) self.exit(3, u'Unknown error') def run_inside_try(self): raise NotImplementedError def destroy(self): self.terminate() def exit(self, status=0, reason=None): self.core_queue.put({'to': 'core', 'command': 'exit', 'status': status, 'reason': reason}) self.destroy() class BaseThread(multiprocessing.dummy.Process): def __init__(self, core_queue): super(BaseThread, self).__init__() self.core_queue = core_queue # No thread should block process from exiting self.daemon = True def run(self): logger.debug(u'%s: Starting thread', self.name) try: self.run_inside_try() except KeyboardInterrupt: logger.info(u'Interrupted by user') self.exit(0, u'Interrupted by user') except SettingsError as e: logger.error(e.message) self.exit(1, u'Settings error') except ImportError as e: logger.error(e) self.exit(2, u'Import error') except Exception as e: logger.exception(e) self.exit(3, u'Unknown error') def run_inside_try(self): raise NotImplementedError def destroy(self): pass def exit(self, status=0, reason=None): self.core_queue.put({'to': 'core', 'command': 'exit', 'status': status, 'reason': reason}) self.destroy() class GObjectEventThread(BaseThread): """ A GObject event loop which is shared by all Mopidy components that uses libraries that need a GObject event loop, like GStreamer and D-Bus. Should be started by Mopidy's core and used by :mod:`mopidy.output.gstreamer`, :mod:`mopidy.frontend.mpris`, etc. """ def __init__(self, core_queue): super(GObjectEventThread, self).__init__(core_queue) self.name = u'GObjectEventThread' self.loop = None def run_inside_try(self): self.loop = gobject.MainLoop().run() def destroy(self): self.loop.quit() super(GObjectEventThread, self).destroy()

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/OpenGLCffi/EGL/EXT/EXT/stream_consumer_egloutput.py

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from OpenGLCffi.EGL import params @params(api='egl', prms=['dpy', 'stream', 'layer']) def eglStreamConsumerOutputEXT(dpy, stream, layer): pass

[ "cdenizol@gmail.com" ]

cdenizol@gmail.com

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Code-Institute-Submissions/renanclothestore

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""" Django settings for carapp project. Generated by 'django-admin startproject' using Django 1.11.13. For more information on this file, see https://docs.djangoproject.com/en/1.11/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.11/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'rwl@k11m(xzyh+&^6=#k36hkev0)7s14n1mi7j6$!a9d7o$dh%' ALLOWED_HOSTS = ["renanclothestore.herokuapp.com", "127.0.0.1", "localhost"] SITE_ID = 4 # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django_forms_bootstrap', 'paypal.standard.ipn', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites', 'django.contrib.flatpages', 'carstore.apps.CarstoreConfig', 'accounts', 'paypal_store', 'products', ] AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'accounts.backends.EmailAuth', ) LOGIN_URL = '/login/' MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'django.middleware.security.SecurityMiddleware', 'django.contrib.flatpages.middleware.FlatpageFallbackMiddleware', ] ROOT_URLCONF = 'carapp.urls' AUTH_USER_MODEL = 'accounts.User' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'carapp.wsgi.application' # Password validation # https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/1.11/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.11/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles') STATICFILES_DIRS = ( os.path.join(BASE_DIR, "static"), ) MEDIA_ROOT = os.path.join(BASE_DIR, 'media') MEDIA_URL = '/media/'

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DayGitH/Python-Challenges

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""" [05/30/13] Challenge #126 [Intermediate] Perfect P'th Powers https://www.reddit.com/r/dailyprogrammer/comments/1fcpnx/053013_challenge_126_intermediate_perfect_pth/ # [](#IntermediateIcon) *(Intermediate)*: Perfect P'th Powers An integer X is a "perfect square power" if there is some integer Y such that Y^2 = X. An integer X is a "perfect cube power" if there is some integer Y such that Y^3 = X. We can extrapolate this where P is the power in question: an integer X is a "perfect p'th power" if there is some integer Y such that Y^P = X. Your goal is to find the highest value of P for a given X such that for some unknown integer Y, Y^P should equal X. You can expect the given input integer X to be within the range of an unsigned 32-bit integer (0 to 4,294,967,295). *Special thanks to the ACM collegiate programming challenges group for giving me the initial idea [here](http://uva.onlinejudge.org/index.php?option=onlinejudge&page=show_problem&problem=1563).* # Formal Inputs & Outputs ## Input Description You will be given a single integer on a single line of text through standard console input. This integer will range from 0 to 4,294,967,295 (the limits of a 32-bit unsigned integer). ## Output Description You must print out to standard console the highest value P that fits the above problem description's requirements. # Sample Inputs & Outputs ## Sample Input *Note:* These are all considered separate input examples. 17 1073741824 25 ## Sample Output *Note:* The string following the result are notes to help with understanding the example; it is NOT expected of you to write this out. 1 (17^1) 30 (2^30) 2 (5^2) """ def main(): pass if __name__ == "__main__": main()

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# http://www.pymcu.com/PlayingSounds.html # rttl.py version 1.0.1 (ported version to pyS60) # import e32 import pitchy # RTTL variable to hold RTTL song #RTTL = 'Bond:d=4,o=5,b=50:32p,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d#6,16d#6,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d6,16c#6,16c#7,c.7,16g#6,16f#6,g#.6' # A Dictionary that contains the frequencies for each note noteFreq = {'p':0,'a':3520,'a#':3729,'b':3951,'c':4186,'c#':4435,'d':4699,'d#':4978,'e':5274,'f':5588,'f#':5920,'g':6272,'g#':6645} # This function will return the default Duration, Octave, and BeatsPerMinute from the RTTL data def dob(dobData): dobVals = dobData.split(',') defaultDur = int(dobVals[0].split('=')[1]) defaultOct = int(dobVals[1].split('=')[1]) defaultBeats = int(dobVals[2].split('=')[1]) return defaultDur, defaultOct, defaultBeats # This function will return the duration per note from the RTTL note data def durSplit(noteData): for d in noteData: if ord(d) >= 97 and ord(d) <= 122: durSplit = noteData.split(d) if len(durSplit[0]) > 0: return int(durSplit[0]) return 0 # This function will return just the note for dictionary look up from the RTTL note data def noteSplit(noteData): note = '' hasDot = False for d in noteData: if ord(d) >= 97 and ord(d) <= 122: note += d if ord(d) == 35: note += d if ord(d) == 46: hasDot = True return note, hasDot # This function will return per note octave changes if specified in the RTTL note data def noteOctave(noteData): if noteData[len(noteData)-1] >= 53 and noteData[len(noteData)-1] <= 56: return 8 - int(noteData[len(noteData)-1]) else: return None def get_song_name(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts return rttlParts[0] # Song Name def get_duration(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultDur = int(dobVals[0].split('=')[1]) return defaultDur def get_octave(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultOct = iint(dobVals[1].split('=')[1]) return defaultOct def get_bpm(noktune): rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts dobVals = (rttlParts[1]).split(',') defaultBeats = int(dobVals[2].split('=')[1]) return defaultBeats def play_noktune(noktune,vol): global noteFreq tune=[] rttlParts = noktune.split(':') # Split the RTTL song data into it's 3 core parts defaultDur, defaultOct, defaultBeats = dob(rttlParts[1]) # Get default Duration, Octave, and Beats Per Minute rttlNotes = rttlParts[2].split(',') # Split all the note data into a list for note in rttlNotes: # Iterate through the note list note = note.strip() # Strip out any possible pre or post spaces in the note data durVal = durSplit(note) # Determine the per note duration if not default if durVal == 0: # If there is no per note duration then use default for that note durVal = defaultDur duration = 60000 / defaultBeats / durVal * 3 # Calculate the proper duration based on Beats Per Minute and Duration Value noteStr, hasDot = noteSplit(note) # Get note for dictionary lookup and check if the note has a dot nFreq = noteFreq[noteStr] # Look up note frequency from the dictionary if hasDot == True: # if it has a dot calculate the new duration duration *= 3 / 2 octave = noteOctave(note) # Determine if there is per note octave change if octave != None: # if so calculate the new octave frequency nFreq /= octave else: # else use the default octave frequency nFreq /= defaultOct if nFreq == 0: # if nFreq is 0 then it's a pause note so pause for the required time e32.ao_sleep(float(duration / 1000.0)) else: # else play the note from the song tune.append((nFreq,duration,vol)) pitchy.play_list(tune) #play_noktune('Bond:d=4,o=5,b=50:32p,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d#6,16d#6,16c#6,32d#6,32d#6,16d#6,8d#6,16c#6,16c#6,16c#6,16c#6,32e6,32e6,16e6,8e6,16d#6,16d6,16c#6,16c#7,c.7,16g#6,16f#6,g#.6',3)

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#coding=UTF-8 import MySQLdb,sys,string,time,datetime,uuid,pymongo,json # from django.contrib.auth.models import User from accounts.models import UserInfo from dbmanage.myapp.models import Db_name,Db_account,Db_instance from django.conf import settings from django.core.serializers.json import DjangoJSONEncoder from dbmanage.myapp.include.encrypt import prpcrypt public_user = settings.PUBLIC_USER export_limit = int(settings.EXPORT_LIMIT) def get_mongodb_list(username,tag='tag',search=''): dbtype='mongodb' host_list = [] if len(search) ==0: if (tag=='tag'): a = UserInfo.objects.get(username=username) #如果没有对应role='read'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.all().order_by("dbtag"): if row.db_account_set.all().filter(role__in=['read','all']): if row.instance.all().filter(role__in=['read','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif (tag=='log'): for row in Db_name.objects.values('dbtag').distinct().order_by("dbtag"): host_list.append(row['dbtag']) elif (tag=='exec'): a = UserInfo.objects.get(username=username) #如果没有对应role='write'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.all().order_by("dbtag"): if row.db_account_set.all().filter(role__in=['write','all']): #排除只读实例 if row.instance.all().filter(role__in=['write','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif len(search) > 0: if (tag=='tag'): a = UserInfo.objects.get(username=username) #如果没有对应role='read'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.filter(dbname__contains=search).order_by("dbtag"): if row.db_account_set.all().filter(role__in=['read','all']): if row.instance.all().filter(role__in=['read','all']).filter(db_type=dbtype): host_list.append(row.dbtag) elif (tag=='log'): for row in Db_name.objects.values('dbtag').distinct().order_by("dbtag"): host_list.append(row['dbtag']) elif (tag=='exec'): a = UserInfo.objects.get(username=username) #如果没有对应role='write'或者role='all'的account账号，则不显示在下拉菜单中 for row in a.db_name_set.filter(dbname__contains=search).order_by("dbtag"): if row.db_account_set.all().filter(role__in=['write','all']): #排除只读实例 if row.instance.all().filter(role__in=['write','all']).filter(db_type=dbtype): host_list.append(row.dbtag) return host_list def get_mongo_coninfo(hosttag,useraccount): a = Db_name.objects.filter(dbtag=hosttag)[0] # a = Db_name.objects.get(dbtag=hosttag) tar_dbname = a.dbname try: if a.instance.all().filter(role='read')[0]: tar_host = a.instance.all().filter(role='read')[0].ip tar_port = a.instance.all().filter(role='read')[0].port # 如果没有设置或没有role=read，则选择第一个读到的all实例读取 except Exception, e: tar_host = a.instance.filter(role='all')[0].ip tar_port = a.instance.filter(role='all')[0].port # tar_host = a.instance.all()[0].ip # tar_port = a.instance.all()[0].port for i in a.db_account_set.all(): if i.role != 'write' and i.role != 'admin': # find the specified account for the user if i.account.all().filter(username=useraccount): tar_username = i.user tar_passwd = i.passwd break # not find specified account for the user ,specified the public account to the user if not vars().has_key('tar_username'): for i in a.db_account_set.all(): if i.role != 'write' and i.role != 'admin': # find the specified account for the user if i.account.all().filter(username=public_user): tar_username = i.user tar_passwd = i.passwd break pc = prpcrypt() return tar_host,tar_port,tar_username,pc.decrypt(tar_passwd),tar_dbname def get_db_info(hosttag,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.command({'dbstats': 1}) return results def get_tb_info(hosttag,tbname,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.command({'collstats': tbname}) return results def get_tbindex_info(hosttag,tbname,useraccount): tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass collection = db[tbname] results = collection.index_information() return results def get_mongo_collection(hosttag,useraccount): try: tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) # 此处根据tablename获取其他信息 connect = pymongo.MongoClient(tar_host, int(tar_port)) db = connect[tar_dbname] try: db.authenticate(tar_username, tar_passwd) except Exception, e: pass results = db.collection_names() except Exception, e: results,col = ([str(e)],''),['error'] return results def get_mongo_data(b,hosttag,tbname,useraccount): try: num = int(UserInfo.objects.get(username=useraccount).user_profile.export_limit) except Exception, e: num = export_limit try: tar_host, tar_port, tar_username, tar_passwd, tar_dbname = get_mongo_coninfo(hosttag, useraccount) #此处根据tablename获取其他信息 connect = pymongo.MongoClient(tar_host,int(tar_port)) db=connect[tar_dbname] try: db.authenticate(tar_username,tar_passwd) except Exception,e: pass #tablename = tablename collection = db[tbname] #a = '''{'currTime': 1477371861706}''' resulta = collection.find(eval(b),{"_id":0}).limit(num) # resulta = collection.find().limit(20) #results = db.collection_names() #获取所有tables名字 results = [] for recordjson in resulta: #resultdict = {} #for k,v in recordjson: # resultdict[k] = v.encode('gb18030') #["ObjectId('580ee6e6f3de9821b20e57db') is not JSON serializable"] results.append(json.dumps(recordjson,ensure_ascii=False,cls=DjangoJSONEncoder)) #results.append(recordjson) except Exception, e: results = (['error'],'') return results if __name__ == '__main__': #x="insert /*sdfs*/into mysql.test ;truncate table mysql.db;rename mysql.db ;rename asdf;delete from `msql`.sa set ;delete ignore from t1 mysql.test values sdasdf;insert into ysql.user values()" # print x #x=" /*! */; select /**/ #asdfasdf; \nfrom mysql_replication_history;" #x = " insert into item_infor (id,name) values(7,'t\\'e\"st');drop t * from test;" print get_mongo_data('{"_class" : "com.mongodb.BasicDBObject"}','mongodb-easemob','message','root')

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/Ass/3/gameDemo/gd_fucks/alien.py

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zubairabid/ITWS2

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4703aba0ada3b0a0a165155ba1177420a110decf

refs/heads/master

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import globalset as gs class Alien: def __init__(self, x, y): self.txt = gs.alien self.x = x self.y = y self.life = gs.ALIEN_LIFE def update(self, sess): self.life -= gs.CLOCK_CYCLE if(self.life <= 0): self.remove(sess) def remove(self, sess): if(self in sess.alist): # c = 0 # for t in sess.alist: # if(self == t): # sess.alist.remove(c) # break # c += 1 sess.alist.remove(self) sess.screen[self.x][self.y] = None

[ "zubairabid1999+github@gmail.com" ]

zubairabid1999+github@gmail.com

a5a8886cd1b54a2f799c66975c4821c04172df57

6533c515c936d999c4bd8192d03d01c56172940c

/wlauto/commands/run.py

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[ "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

caogao/workload-automation

330558c1a51b42a6e9e3291333f7c0653975c617

44a49db04da3224003f16bf82db0dc309422b710

refs/heads/master

2021-01-15T11:07:01.869199

2016-04-15T15:39:24

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# Copyright 2014-2015 ARM Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import os import sys import shutil import wlauto from wlauto import Command, settings from wlauto.exceptions import ConfigError from wlauto.core.agenda import Agenda from wlauto.core.execution import Executor from wlauto.utils.log import add_log_file class RunCommand(Command): name = 'run' description = 'Execute automated workloads on a remote device and process the resulting output.' def initialize(self, context): self.parser.add_argument('agenda', metavar='AGENDA', help=""" Agenda for this workload automation run. This defines which workloads will be executed, how many times, with which tunables, etc. See example agendas in {} for an example of how this file should be structured. """.format(os.path.dirname(wlauto.__file__))) self.parser.add_argument('-d', '--output-directory', metavar='DIR', default=None, help=""" Specify a directory where the output will be generated. If the directory already exists, the script will abort unless -f option (see below) is used, in which case the contents of the directory will be overwritten. If this option is not specified, then {} will be used instead. """.format(settings.output_directory)) self.parser.add_argument('-f', '--force', action='store_true', help=""" Overwrite output directory if it exists. By default, the script will abort in this situation to prevent accidental data loss. """) self.parser.add_argument('-i', '--id', action='append', dest='only_run_ids', metavar='ID', help=""" Specify a workload spec ID from an agenda to run. If this is specified, only that particular spec will be run, and other workloads in the agenda will be ignored. This option may be used to specify multiple IDs. """) self.parser.add_argument('--disable', action='append', dest='instruments_to_disable', metavar='INSTRUMENT', help=""" Specify an instrument to disable from the command line. This equivalent to adding "~{metavar}" to the instrumentation list in the agenda. This can be used to temporarily disable a troublesome instrument for a particular run without introducing permanent change to the config (which one might then forget to revert). This option may be specified multiple times. """) def execute(self, args): # NOQA self.set_up_output_directory(args) add_log_file(settings.log_file) if os.path.isfile(args.agenda): agenda = Agenda(args.agenda) settings.agenda = args.agenda shutil.copy(args.agenda, settings.meta_directory) elif '.' in args.agenda or os.sep in args.agenda: raise ConfigError('Agenda "{}" does not exist.'.format(args.agenda)) else: self.logger.debug('{} is not a file; assuming workload name.'.format(args.agenda)) agenda = Agenda() agenda.add_workload_entry(args.agenda) if args.instruments_to_disable: if 'instrumentation' not in agenda.config: agenda.config['instrumentation'] = [] for itd in args.instruments_to_disable: self.logger.debug('Updating agenda to disable {}'.format(itd)) agenda.config['instrumentation'].append('~{}'.format(itd)) basename = 'config_' for file_number, path in enumerate(settings.get_config_paths(), 1): file_ext = os.path.splitext(path)[1] shutil.copy(path, os.path.join(settings.meta_directory, basename + str(file_number) + file_ext)) executor = Executor() executor.execute(agenda, selectors={'ids': args.only_run_ids}) def set_up_output_directory(self, args): if args.output_directory: settings.output_directory = args.output_directory self.logger.debug('Using output directory: {}'.format(settings.output_directory)) if os.path.exists(settings.output_directory): if args.force: self.logger.info('Removing existing output directory.') shutil.rmtree(settings.output_directory) else: self.logger.error('Output directory {} exists.'.format(settings.output_directory)) self.logger.error('Please specify another location, or use -f option to overwrite.\n') sys.exit(1) self.logger.info('Creating output directory.') os.makedirs(settings.output_directory) os.makedirs(settings.meta_directory)

[ "sergei.trofimov@arm.com" ]

sergei.trofimov@arm.com

c14936fab65953dbc7436882b80b1d347adc2081

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/backend/home/migrations/0001_load_initial_data.py

46847f2ef86805729f40bbd28060eabdfb9c3bef

[]

no_license

crowdbotics-apps/tester-app-31668

60413ed775d07c8f958bb30e5398b1941722a8bb

d3e5ba380ee2041c07e73b7e8b45dbe3c9955a03

refs/heads/master

2023-09-01T07:48:38.823415

2021-10-26T02:03:42

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from django.db import migrations def create_site(apps, schema_editor): Site = apps.get_model("sites", "Site") custom_domain = "tester-app-31668.botics.co" site_params = { "name": "Tester App", } if custom_domain: site_params["domain"] = custom_domain Site.objects.update_or_create(defaults=site_params, id=1) class Migration(migrations.Migration): dependencies = [ ("sites", "0002_alter_domain_unique"), ] operations = [ migrations.RunPython(create_site), ]

[ "team@crowdbotics.com" ]

team@crowdbotics.com

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/exps-gsn-edf/gsn-edf_ut=2.0_rd=0.8_rw=0.04_rn=4_u=0.075-0.35_p=harmonic-2/sched=RUN_trial=65/params.py

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[]

no_license

ricardobtxr/experiment-scripts

1e2abfcd94fb0ef5a56c5d7dffddfe814752eef1

7bcebff7ac2f2822423f211f1162cd017a18babb

refs/heads/master

2023-04-09T02:37:41.466794

2021-04-25T03:27:16

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{'cpus': 4, 'duration': 30, 'final_util': '2.016476', 'max_util': '2.0', 'periods': 'harmonic-2', 'release_master': False, 'res_distr': '0.8', 'res_nmb': '4', 'res_weight': '0.04', 'scheduler': 'GSN-EDF', 'trial': 65, 'utils': 'uni-medium-3'}

[ "ricardo.btxr@gmail.com" ]

ricardo.btxr@gmail.com

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9743d5fd24822f79c156ad112229e25adb9ed6f6

/xai/brain/wordbase/nouns/_joey.py

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permissive

cash2one/xai

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refs/heads/master

2021-01-19T12:33:54.964379

2017-01-28T02:00:50

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#calss header class _JOEY(): def __init__(self,): self.name = "JOEY" self.definitions = [u'a young kangaroo'] self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.specie = 'nouns' def run(self, obj1 = [], obj2 = []): return self.jsondata

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

0eef22e43e4999b7e13da85bee5a3719f09f6108

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/nn_ns/Bijection/BijectiveNumeration.py

d21afc99a4a5f19a282db7981ccf2d6d2a195f95

[]

no_license

edt-yxz-zzd/python3_src

43d6c2a8ef2a618f750b59e207a2806132076526

41f3a506feffb5f33d4559e5b69717d9bb6303c9

refs/heads/master

2023-05-12T01:46:28.198286

2023-05-01T13:46:32

143,530,977

2

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''' https://en.wikipedia.org/wiki/Bijective_numeration Radix <- PInt BiDigit = [1..Radix] # compare Digit = [0..Radix-1] # little-endian bidigitsLE2uint :: [BiDigit] -> UInt bidigitsLE2uint ds = f ds 1 where f [] weight = 0 f (h:ts) weight = h*weight + f ts (weight*Radix) bidigitsLE2uint = f where f [] = 0 f (h:ts) = h + (f ts) * Radix bidivmod :: UInt -> PInt -> (UInt, PInt) bidivmod n d = (q, r) where # q = ceil(n/d) - 1 = floor((n+d-1)/d) - 1 = floor((n-1)/d) q = (n-1)//d r = n - q*d uint2bidigitsLE :: UInt -> [BiDigit] uint2bidigitsLE = f where f 0 = [] f n = r : f q where (q, r) = bidivmod n Radix ''' __all__ = ''' bidigits2uint__little_endian uint2bidigits__little_endian '''.split() from .ArbitraryRadixNumber import \ number2iter_arbitrary_radix_reprLE, arbitrary_radix_reprBE2number def bidivmod(n, d): #ssert n >= 0 #ssert d >= 1 q, r = divmod(n-1, d) r += 1 return q, r q = (n-1)//d r = n - q*d def uint2iter_bidigitsLE(radix, u): assert u >= 0 assert radix >= 1 # need not 2 return number2iter_arbitrary_radix_reprLE(u, radix, 0, bidivmod) ''' bug: should comment below code to disable 'yield'!! while u > 0: u, r = bidivmod(u, radix) yield r ''' def uint2bidigitsLE(radix, u): return tuple(uint2iter_bidigitsLE(radix, u)) def bidigitsLE2uint(radix, bidigits): # little-endian assert all(1<=d<=radix for d in bidigits) return arbitrary_radix_reprBE2number(reversed(bidigits), radix, 0) u = 0 for d in reversed(bidigits): u *= radix u += d return u bidigits2uint__little_endian = bidigitsLE2uint uint2bidigits__little_endian = uint2bidigitsLE def test(): for radix in range(1, 5): for u in range(100): bs = uint2bidigitsLE(radix, u) u_ = bidigitsLE2uint(radix, bs) #rint(u, bs, u_) assert u == u_ from itertools import product for radix in range(1, 5): for L in range(5): for bs in product(range(1, radix+1), repeat=L): u = bidigitsLE2uint(radix, bs) bs_ = uint2bidigitsLE(radix, u) assert bs == bs_ if __name__ == '__main__': print('test BijectiveNumeration.py') test()

[ "wuming_zher@zoho.com.cn" ]

wuming_zher@zoho.com.cn

b10b08af4d84840fac55aead8c737624c5df79f2

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/postexp/module.py

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[]

no_license

krishpranav/postexp

9d4e1bf3be72ee27418449b4bc824ebdf9be1b44

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refs/heads/master

2023-04-20T04:33:32.173926

2021-05-06T05:23:02

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#!/usr/bin/env python3 # imports import os import pkg_resources from importlib import import_module INDEX_FILE = 'modindex.txt' client_commands = {} server_commands = {} def client_handler(cmd): def decorate(func): client_commands[cmd] = func return decorate def server_handler(cmd): def decorate(func): server_commands[cmd] = func return decorate def load_modules(): for fname in pkg_resources.resource_string(__name__, INDEX_FILE).split(): if fname.endswith('.py'): mod = os.path.splitext(fname)[0] if mod == '__init__': continue elif mod in server_commands.keys(): raise Exception('duplicate module detected: {}'.format(mod)) import_module('modules.' + mod)

[ "krisna.pranav@gmail.com" ]

krisna.pranav@gmail.com

85b2e627fa812d32731797a4a20c53bbac3ec85c

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/B站/twoWEB表单/Flask_WTF_demo2.py

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[]

no_license

lijianmin01/Flask_study

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refs/heads/main

2023-01-18T16:29:27.143408

2020-11-26T10:22:28

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from flask import Flask,render_template,request app = Flask(__name__) @app.route("/",methods=['POST','GET']) def index(): message = None if request.method == 'POST': username = request.form.get("username") password = request.form.get("password") password2 = request.form.get("password2") # 3、判断参数是否填写 & 密码是否相同 if not all([username,password,password2]): print("参数不完成") message = "参数不完整" elif password2!=password: message = "两次密码不一致" else: message = "success" return render_template('index.html',message=message) if __name__ == '__main__': app.run(debug=True)

[ "lijianmin01@126.com" ]

lijianmin01@126.com

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/.history/base/views_20210829091127.py

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[]

no_license

Justin-Panagos/todoList

95b1e97ff71af1b0be58e7f8937d726a687cea4d

10539219b59fcea00f8b19a406db3d4c3f4d289e

refs/heads/master

2023-08-04T13:27:13.309769

2021-08-29T14:06:43

400,827,602

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null

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from django.shortcuts import render from django.views.generic.list import ListView from django.views.generic.detail import DetailView from django.views.generic.edit import CreateView, UpdateView, DeleteView, FormView from django.urls import reverse_lazy from django.contrib.auth.views import LoginView from django.contrib.auth.mixins import LoginRequiredMixin from django.contrib.auth.forms import UserCreationForm from django.contrib.auth import login from .models import Task #login view class CustoomLoginView(LoginView): template_name = 'base/login.html' fields = '__all__' redirect_authenticated_user = True def get_success_url(self): return reverse_lazy('tasks') # class RegisterPage(FormView): template_name = 'base/register.html' form_class= UserCreationForm redirect_authenticated_user = True success_url = reverse_lazy('tasks') def form_validate(self,form): user= form.save() if user is not None: login(self.request, user) return super(RegisterPage, self).form_validate(form) class TaskList( LoginRequiredMixin, ListView): model = Task context_object_name = 'tasks' def get_context_data(self, **kwargs): context = super().get_context_data(**kwargs) context['tasks'] = context['tasks'].filter(user=self.request.user) context['count'] = context['tasks'].filter(complete=False).count() return context class TaskDetail(LoginRequiredMixin, DetailView): model = Task context_object_name = 'task' template_name = 'base/task.html' class TaskCreate(LoginRequiredMixin, CreateView): model = Task fields = ['title','description','complete'] success_url = reverse_lazy('tasks') def form_valid(self, form): form.instance.user = self.request.user return super(TaskCreate, self).form_valid(form) class TaskUpdate( LoginRequiredMixin, UpdateView): model = Task fields = ['title','description','complete'] success_url = reverse_lazy('tasks') class TaskDelete(LoginRequiredMixin, DeleteView): model = Task context_object_name = 'task' success_url = reverse_lazy('tasks')

[ "justpanagos@gmail.com" ]

justpanagos@gmail.com

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mindsdb/benchmarks

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from benchmarks.helpers.accuracy import balanced_accuracy_score, roc_auc from benchmarks.datasets.dataset import DatasetInterface class Dataset(DatasetInterface): tags = ['classification'] learn_kwargs = {} num_folds = 5 accuracy_functions = [balanced_accuracy_score, roc_auc] file = 'data.csv' active = True target = 'class' source = 'https://www.openml.org/d/41146' license = 'Public Domain Mark 1.0' is_open_license = True

[ "george@cerebralab.com" ]

george@cerebralab.com

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/page_counter/wsgi.py

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priyankaonly1/Page_Counter_project

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""" WSGI config for page_counter project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'page_counter.settings') application = get_wsgi_application()

[ "priyankabiswasonly1@gmail.com" ]

priyankabiswasonly1@gmail.com

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/leetcode/editor/en/[1827]Minimum Operations to Make the Array Increasing.py

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no_license

tainenko/Leetcode2019

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# You are given an integer array nums (0-indexed). In one operation, you can # choose an element of the array and increment it by 1. # # # For example, if nums = [1,2,3], you can choose to increment nums[1] to make # nums = [1,3,3]. # # # Return the minimum number of operations needed to make nums strictly # increasing. # # An array nums is strictly increasing if nums[i] < nums[i+1] for all 0 <= i < # nums.length - 1. An array of length 1 is trivially strictly increasing. # # # Example 1: # # # Input: nums = [1,1,1] # Output: 3 # Explanation: You can do the following operations: # 1) Increment nums[2], so nums becomes [1,1,2]. # 2) Increment nums[1], so nums becomes [1,2,2]. # 3) Increment nums[2], so nums becomes [1,2,3]. # # # Example 2: # # # Input: nums = [1,5,2,4,1] # Output: 14 # # # Example 3: # # # Input: nums = [8] # Output: 0 # # # # Constraints: # # # 1 <= nums.length <= 5000 # 1 <= nums[i] <= 10⁴ # # # Related Topics Array Greedy 👍 747 👎 34 # leetcode submit region begin(Prohibit modification and deletion) class Solution: def minOperations(self, nums: List[int]) -> int: if len(nums) <= 1: return 0 total = 0 prev = nums[0] for num in nums[1:]: if num <= prev: total += prev - num + 1 prev += 1 else: prev = num return total # leetcode submit region end(Prohibit modification and deletion)

[ "31752048+tainenko@users.noreply.github.com" ]

31752048+tainenko@users.noreply.github.com

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/capture/noworkflow/now/models/__init__.py

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[ "MIT" ]

permissive

hugobowne/noworkflow

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2021-01-17T20:27:16.524245

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# Copyright (c) 2015 Universidade Federal Fluminense (UFF) # Copyright (c) 2015 Polytechnic Institute of New York University. # This file is part of noWorkflow. # Please, consult the license terms in the LICENSE file. from __future__ import (absolute_import, print_function, division, unicode_literals) from .model import Model from .history import History from .trial import Trial from .diff import Diff from .trial_prolog import TrialProlog

[ "joaofelipenp@gmail.com" ]

joaofelipenp@gmail.com

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/scenarios/customer_create_debit/executable.py

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no_license

jess010/balanced-python

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refs/heads/master

2020-12-25T16:13:35.626111

2013-09-20T00:14:58

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import balanced balanced.configure('b5de51921b2d11e389c4026ba7cac9da') customer = balanced.Customer.find('/v1/customers/AC6M5tIyndBqrv4fEdubPUhg') customer.debit(amount=5000)

[ "ben@unfiniti.com" ]

ben@unfiniti.com

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/Python_Workbook/H01.py

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[]

no_license

cinxdy/Python_practice

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refs/heads/master

2022-05-09T00:10:15.849881

2022-04-03T09:38:53

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from random import * count = 0 answer = randint(1,100) while 1: number_try = int(input("Try guess number between 1 and 100 ")) count+=1 if number_try > answer : print("answer is smaller number") elif number_try < answer : print("answer is bigger number") else : print("You got it! try count : %d"%count) break

[ "cinxdys2@gmail.com" ]

cinxdys2@gmail.com