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

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/NAMS/download.py

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MiCurry/easy_plots

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refs/heads/master

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import os import sys import urllib from datetime import datetime, timedelta # TODO: Change arguments to a float?? """ download(north, south, east, west, height) north - north latitude value (string) south - south latitude value (string) east - east longitude value (string) west - west longitude value (string) height - height-above-ground (meters) returns filename as WIND_date_height.nc """ def download(north, south, east, west, height): #list of file ids created new_file_ids = [] current_time = datetime.now().date() end_time = datetime.now().date()+timedelta(days=1) begin = str(current_time) + 'T00%3A00%3A00Z' end = str(end_time) + 'T00%3A00%3A00Z' print "Downloading...." url = 'http://thredds.ucar.edu/thredds/ncss/grib/NCEP/NAM/CONUS_12km/conduit/Best?var=u-component_of_wind_height_above_ground&var=v-component_of_wind_height_above_ground&north='+north+'&west='+west+'&east='+east+'&south='+south+'&horizStride=1&time_start='+begin+'&time_end='+end+'&timeStride=1&addLatLon=true&accept=netcdf' fileName = "/home/data/{0}-{1}.nc".format("WIND", current_time) urllib.urlretrieve(url, fileName) print "Downloaded File: ", fileName return file north = "46.5"; south = "41.7"; east = "-116"; west = "-125"; height = "0"; download(north, south, east, west, height)

[ "currymiles@gmail.com" ]

currymiles@gmail.com

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/120_design_patterns/016_iterator/_exercises/templates/6-python-design-patterns-building-more-m6-exercise-files/BeforeIterator/__main1__.py

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syurskyi/Python_Topics

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from testdata import employees def main(): print("Employees:") for i in range(1, employees.headcount+1): employee = employees.get_employee(i) print('Employee Id: {}; Name: {}; Date of Hire: {}' .format(employee.empid, employee.name, employee.hiredate) ) if __name__ == '__main__': main()

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sergejyurskyj@yahoo.com

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/AISProject/ais_conv.py

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lzz5235/Code-Segment

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import os import xml.etree.ElementTree as ET import xml.dom.minidom as minidom import numpy as np NationDict = {307: 'Aruba', 401: 'Afghanistan', 601: 'South Africa (Rep. of)', 603: 'Angola (Rep. of)', 301: 'Anguilla', 201: 'Albania (Rep. of)', 605: 'Algeria (People\'s Democratic Rep. of)', 303: 'Alaska (State of)', 607: 'Saint Paul and Amsterdam Islands', 202: 'Andorra (Principality of)', 701: 'Argentine Rep.', 216: 'Armenia (Rep. of)', 403: 'Saudi Arabia (Kingdom of)', 608: 'Ascension Island', 304: 'Antigua and Barbuda', 305: 'Antigua and Barbuda', 306: 'Netherlands Caribbean', 503: 'Australia', 203: 'Austria', 423: 'Azerbaijani Rep.', 204: 'Azores', 710: 'Brazil (Federative Rep. of)', 308: 'Bahamas (Commonwealth of the)', 309: 'Bahamas (' 'Commonwealth of the)', 311: 'Bahamas (Commonwealth of the)', 609: 'Burundi (Rep. of)', 205: 'Belgium', 610: 'Benin (Rep. of)', 310: 'Bermuda', 633: 'Burkina Faso', 405: 'Bangladesh (People\'s Rep. of)', 408: 'Bahrain (Kingdom of)', 478: 'Bosnia and Herzegovina', 206: 'Belarus (Rep. of)', 312: 'Belize', 720: 'Bolivia (Plurinational State of)', 611: 'Botswana (Rep. of)', 314: 'Barbados', 506: 'Myanmar (Union of)', 508: 'Brunei Darussalam', 410: 'Bhutan (' 'Kingdom of)', 207: 'Bulgaria (Rep. of)', 612: 'Central African Rep', 316: 'Canada', 514: 'Cambodia (Kingdom of)', 515: 'Cambodia ' '(Kingdom of)', 725: 'Chile', 412: 'China (People\'s Rep. of)', 413: 'China (People\'s Rep. of)', 414: 'China (People\'s Rep. of)', 516: 'Christmas Island (Indian Ocean)', 518: 'Cook Islands', 730: 'Colombia (Rep. of)', 417: 'Sri Lanka (' 'Democratic ' 'Socialist Rep. of)', 613: 'Cameroon (Rep. of)', 676: 'Democratic Rep. of the Congo', 615: 'Congo (Rep. of the)', 616: 'Comoros (Union ' 'of the)', 617: 'Cape Verde (Rep. of)', 618: 'Crozet Archipelago', 619: 'Cote d\'Ivoire (Rep. of)', 321: 'Costa Rica', 323: 'Cuba', 208: 'Vatican City State', 319: 'Cayman Islands', 209: 'Cyprus (Rep. of)', 210: 'Cyprus (Rep. of)', 212: 'Cyprus (Rep. of)', 270: 'Czech Rep.', 211: 'Germany (Federal Rep. of)', 218: 'Germany (Federal Rep. of)', 621: 'Djibouti (Rep. of)', 325: 'Dominica (Commonwealth of)', 219: 'Denmark', 220: 'Denmark', 327: 'Dominican Rep.', 224: 'Spain', 225: 'Spain', 622: 'Egypt (Arab Rep. of)', 735: 'Ecuador', 625: 'Eritrea', 276: 'Estonia (Rep. of)', 624: 'Ethiopia (Federal Democratic Rep. of)', 226: 'France', 227: 'France', 228: 'France', 230: 'Finland', 520: 'Fiji (Rep. of)', 740: 'Falkland Islands (Malvinas)', 231: 'Faroe Islands', 510: 'Micronesia (Federated ' 'States of)', 232: 'United Kingdom of Great Britain and Northern Ireland', 233: 'United Kingdom of Great Britain and ' 'Northern Ireland', 234: 'United Kingdom of Great Britain and Northern Ireland', 235: 'United Kingdom of Great Britain and ' 'Northern Ireland', 626: 'Gabonese Rep.', 213: 'Georgia', 627: 'Ghana', 236: 'Gibraltar', 329: 'Gambia (Rep. of the)', 629: 'Guadeloupe (' 'French Department of)', 630: 'Guinea-Bissau (Rep. of)', 631: 'Equatorial Guinea (Rep. of)', 237: 'Greece', 239: 'Greece', 240: 'Greece', 241: 'Greece', 330: 'Grenada', 331: 'Greenland', 332: 'Guatemala (Rep. of)', 745: 'Guiana (French Department of)', 632: 'Guinea (Rep. of)', 750: 'Guyana', 477: 'Hong Kong (Special Administrative Region of China)', 334: 'Honduras (Rep. of)', 243: 'Hungary', 244: 'Netherlands (Kingdom of the)', 245: 'Netherlands (Kingdom of the)', 246: 'Netherlands (' 'Kingdom of the)', 238: 'Croatia (Rep. of)', 336: 'Haiti (Rep. of)', 247: 'Italy', 523: 'Cocos (Keeling) Islands', 419: 'India (Rep. ' 'of)', 525: 'Indonesia (Rep. of)', 250: 'Ireland', 422: 'Iran (Islamic Rep. of)', 425: 'Iraq (Rep. of)', 251: 'Iceland', 428: 'Israel (State of)', 431: 'Japan', 432: 'Japan', 339: 'Jamaica', 438: 'Jordan (Hashemite Kingdom of)', 436: 'Kazakhstan (Rep. of)', 634: 'Kenya (Rep. of)', 635: 'Kerguelen Islands', 451: 'Kyrgyz Rep.', 529: 'Kiribati (' 'Rep. of)', 341: 'Saint Kitts and Nevis (Federation of)', 440: 'Korea (Rep. of)', 441: 'Korea (Rep. of)', 445: 'Democratic ' 'People\'s ' 'Rep. of Korea', 447: 'Kuwait (State of)', 531: 'Lao People\'s Democratic Rep.', 450: 'Lebanon', 636: 'Liberia (Rep. of)', 637: 'Liberia (Rep. of)', 642: 'Libya', 343: 'Saint Lucia', 252: 'Liechtenstein (Principality of)', 644: 'Lesotho (' 'Kingdom of)', 277: 'Lithuania (Rep. of)', 253: 'Luxembourg', 275: 'Latvia (Rep. of)', 453: 'Macao (Special Administrative ' 'Region of China)', 645: 'Mauritius (Rep. of)', 254: 'Monaco (Principality of)', 214: 'Moldova (Rep. of)', 647: 'Madagascar (Rep. ' 'of)', 255: 'Madeira', 345: 'Mexico', 538: 'Marshall Islands (Rep. of the)', 274: 'The Former Yugoslav Rep. of Macedonia', 533: 'Malaysia', 455: 'Maldives (Rep. of)', 649: 'Mali (Rep. of)', 215: 'Malta', 229: 'Malta', 248: 'Malta', 249: 'Malta', 256: 'Malta', 262: 'Montenegro', 457: 'Mongolia', 650: 'Mozambique (Rep. of)', 536: 'Northern Mariana Islands (Commonwealth of ' 'the)', 242: 'Morocco (Kingdom of)', 347: 'Martinique (French Department of)', 248: 'Montserrat', 654: 'Mauritania (' 'Islamic Rep. of)', 655: 'Malawi', 350: 'Nicaragua', 540: 'New Caledonia', 656: 'Niger (Rep. of the)', 657: 'Nigeria (Federal Rep. of)', 542: 'Niue', 659: 'Namibia (Rep. of)', 257: 'Norway', 258: 'Norway', 259: 'Norway', 459: 'Nepal (Federal Democratic ' 'Rep. of)', 544: 'Nauru (Rep. of)', 512: 'New Zealand', 546: 'French Polynesia', 461: 'Oman (Sultanate of)', 463: 'Pakistan (' 'Islamic Rep. of)', 548: 'Philippines (Rep. of the)', 511: 'Palau (Rep. of)', 553: 'Papua New Guinea', 351: 'Panama (Rep. of)', 352: 'Panama (Rep. of)', 353: 'Panama (Rep. of)', 354: 'Panama (Rep. of)', 355: 'Panama (Rep. of)', 356: 'Panama (Rep. of)', 357: 'Panama (Rep. of)', 370: 'Panama (Rep. of)', 371: 'Panama (Rep. of)', 372: 'Panama (Rep. of)', 373: 'Panama (' 'Rep. of)', 261: 'Poland (Rep. of)', 263: 'Portugal', 755: 'Paraguay (Rep. of)', 760: 'Peru', 443: 'Palestine', 555: 'Pitcairn ' 'Island', 358: 'Puerto Rico', 466: 'Qatar (State of)', 660: 'Reunion (French Department of)', 264: 'Romania', 661: 'Rwanda (' 'Rep. of)', 273: 'Russian Federation', 265: 'Sweden', 266: 'Sweden', 662: 'Sudan (Rep. of the)', 663: 'Senegal (Rep. of)', 664: 'Seychelles (Rep. of)', 665: 'Saint Helena', 557: 'Solomon Islands', 359: 'El Salvador (Rep. of)', 559: 'American Samoa', 561: 'Samoa (Independent State of)', 268: 'San Marino (Rep. of)', 563: 'Singapore (Rep. of)', 564: 'Singapore (Rep. of)', 565: 'Singapore (Rep. of)', 566: 'Singapore (Rep. of)', 666: 'Somali Democratic Rep.', 361: 'Saint Pierre and Miquelon (Territorial Collectivity of)', 279: 'Serbia (Rep. of)', 667: 'Sierra Leone', 668: 'Sao Tome and Principe (Democratic Rep. of)', 269: 'Switzerland (Confederation of)', 765: 'Suriname (Rep. ' 'of)', 267: 'Slovak Rep.', 278: 'Slovenia (Rep. of)', 669: 'Swaziland (Kingdom of)', 468: 'Syrian Arab Rep.', 364: 'Turks ' 'and Caicos Islands', 670: 'Chad (Rep. of)', 671: 'Togolese Rep.', 567: 'Thailand', 472: 'Tajikistan (Rep. of)', 434: 'Turkmenistan', 570: 'Tonga (Kingdom of)', 362: 'Trinidad and Tobago', 672: 'Tunisia', 271: 'Turkey', 572: 'Tuvalu', 674: 'Tanzania (' 'United Rep. of)', 677: 'Tanzania (United Rep. of)', 470: 'United Arab Emirates', 675: 'Uganda (Rep. of)', 272: 'Ukraine', 770: 'Uruguay (Eastern Rep. of)', 338: 'United States of America', 366: 'United States of America', 367: 'United ' 'States of America', 368: 'United States of America', 369: 'United States of America', 437: 'Uzbekistan (Rep. of)', 375: 'Saint ' 'Vincent and the Grenadines', 376: 'Saint Vincent and the Grenadines', 377: 'Saint Vincent and the Grenadines', 775: 'Venezuela (Bolivarian ' 'Rep. of)', 379: 'United States Virgin Islands', 378: 'British Virgin Islands', 574: 'Viet Nam (Socialist Rep. of)', 576: 'Vanuatu (Rep. of)', 577: 'Vanuatu (Rep. of)', 578: 'Wallis and Futuna Islands', 416: 'Taiwan (Province of ' 'China)', 501: 'Adelie Land', 473: 'Yemen (Rep. of)', 475: 'Yemen (Rep. of)', 678: 'Zambia (Rep. of)', 679: 'Zimbabwe (Rep. of)' } ShipTypeDict = {5:'Navy',6:'Carrier',7:'Cargo',8:'Tanker'} def getNationFlag(MMSI): num = long(MMSI) num /=1000000 if num not in NationDict: return 'unknown' return NationDict[num] def getShipType(type): num = int(type) num /=10 if num not in ShipTypeDict: return 'unknown' return ShipTypeDict[num] def get_data_DY(input_path, all_MMSI): print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') for ship in element_Ships: mmsi = long(ship.find("MMSI").text) DynamicInfo = ship.find("DynamicInfo") LastTime = DynamicInfo.find("LastTime").text Latitude = float(DynamicInfo.find("Latitude").text) Longitude = float(DynamicInfo.find("Longitude").text) Speed = float(DynamicInfo.find("Speed").text) course = float(DynamicInfo.find("course").text) HeadCourse = float(DynamicInfo.find("HeadCourse").text) AngularRate = float(DynamicInfo.find("AngularRate").text) NaviStatus = float(DynamicInfo.find("NaviStatus").text) ShipData = {'MMSI':mmsi, 'DynamicInfo':[]} ShipData['DynamicInfo'].append({'LastTime':str(LastTime),'Latitude':Latitude,'Longitude':Longitude, 'Speed':Speed, 'course':course,'HeadCourse':HeadCourse,'AngularRate':AngularRate, 'NaviStatus':NaviStatus}) if mmsi < 100000000: continue write_data_DY(ShipData) # all_MMSI.append(ShipData) def get_data_ST(input_path,all_MMSI): print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') for ship in element_Ships: mmsi = long(ship.find("MMSI").text) StaticInfo = ship.find("StaticInfo") LastTime = StaticInfo.find("LastTime").text ShipType = int(StaticInfo.find("ShipType").text) Length = float(StaticInfo.find("Length").text) Width = float(StaticInfo.find("Width").text) Left = float(StaticInfo.find("Left").text) Trail = float(StaticInfo.find("Trail").text) Draught = float(StaticInfo.find("Draught").text) IMO = long(StaticInfo.find("IMO").text) CallSign = StaticInfo.find("CallSign").text ETA = StaticInfo.find("ETA").text Name = StaticInfo.find("Name").text Dest = StaticInfo.find("Dest").text ShipData = {'MMSI': mmsi, 'StaticInfo': []} ShipData['StaticInfo'].append({'LastTime': str(LastTime), 'ShipType': ShipType, 'Length': Length, 'Width': Width, 'Left': Left, 'Trail': Trail, 'Draught': Draught, 'IMO': IMO, 'CallSign': str(CallSign),'ETA':str(ETA),'Name':str(Name),'Dest':str(Dest)}) if mmsi < 100000000: continue write_data_ST(ShipData) # all_MMSI.append(ShipData) def write_data_DY(ShipData): MMSI = ShipData['MMSI'] string = str(MMSI) + ',' + ShipData['DynamicInfo'][0]['LastTime'] + ',' + str(ShipData['DynamicInfo'][0]['Latitude'])\ + ',' + str(ShipData['DynamicInfo'][0]['Longitude']) + ',' + str(ShipData['DynamicInfo'][0]['Speed']) + \ ',' + str(ShipData['DynamicInfo'][0]['course']) + ',' + str(ShipData['DynamicInfo'][0]['NaviStatus']) with open('./ShipLineTest/ais_dy.txt', 'a') as f: # DY f.write(string + '\n') def write_data_ST(ShipData): MMSI = ShipData['MMSI'] tmp = str(ShipData['StaticInfo'][0]['Length']) + ' x ' + str(ShipData['StaticInfo'][0]['Width']) + ' m|' string = str(MMSI) + '|' + ShipData['StaticInfo'][0]['Name'] + '|' + getNationFlag(MMSI) + '|' + getShipType( ShipData['StaticInfo'][0]['ShipType']) + '|N/A|N/A|N/A|' + str(MMSI) + '|' + ShipData['StaticInfo'][0][ 'CallSign'] + '|' + tmp + str(ShipData['StaticInfo'][0]['Draught']) + ' m|'+ str(ShipData['StaticInfo'][0][ 'IMO']) with open('./ShipLineTest/ais_st.txt', 'a') as f: # ST f.write(string + '\n') def Classfication_By_Nation(input_path,Nations): import shutil print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') for ship in element_Ships: mmsi = long(ship.find("MMSI").text) if getNationFlag(mmsi) != Nations: break shutil.copyfile(input_path, './Japan_Tanker/' + os.path.split(input_path)[1]) def Classfication_By_Draught(input_path,draught): import shutil print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') ship = element_Ships[0] mmsi = long(ship.find("MMSI").text) StaticInfo = ship.find("StaticInfo") Draught = float(StaticInfo.find("Draught").text) if draught.has_key(int(Draught)): draught[int(Draught)] += 1 else: draught[int(Draught)] = 1 def Classfication_By_Weight(input_path,weight): print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') ship = element_Ships[0] mmsi = long(ship.find("MMSI").text) StaticInfo = ship.find("StaticInfo") Draught = float(StaticInfo.find("Draught").text) if weight.has_key(int(Draught)): weight[int(Draught)] += 1 else: weight[int(Draught)] = 1 def Classfication_By_WS(input_path): print input_path if 0 == int(os.path.getsize(input_path)): return et = ET.parse(input_path) element = et.getroot() element_Ships = element.findall('Ship') ship = element_Ships[0] StaticInfo = ship.find("StaticInfo") Length = float(StaticInfo.find("Length").text) Width = float(StaticInfo.find("Width").text) Draught = float(StaticInfo.find("Draught").text) slist = [] for ship in element_Ships: DynamicInfo = ship.find("DynamicInfo") Speed = float(DynamicInfo.find("Speed").text) if int(Speed) != 0 : slist.append(Speed) slist = np.array(slist) Y = np.median(slist) X = int(Length*Width*Draught) return X,Y if __name__ == "__main__": all_MMSI_DY=[] all_MMSI_ST=[] data_paths_dy = [] data_paths_st = [] draught = {} from matplotlib import pyplot as plt from matplotlib.ticker import MultipleLocator from matplotlib import pyplot as plt from matplotlib.ticker import MultipleLocator speed_list = [] draught_list = [] for file in [os.path.join('/media/xxxx/xx/AISProject/Japan_Tanker', s) for s in os.listdir( '/media/xxxx/xx/AISProject/Japan_Tanker')]: X,Y = Classfication_By_WS(file) speed_list.append(X) draught_list.append(Y) speed_list = np.array(speed_list) draught_list = np.array(draught_list) plt.scatter(speed_list,draught_list,25,cmap=plt.cm.jet,marker='o',edgecolors='k',zorder=10,alpha=0.7) plt.xticks(np.arange(0,400000,20000)) plt.yticks(np.arange(6,25,2)) plt.xlabel("Ship Tanker Tonnage") plt.ylabel("Speed") plt.title("Japanese Ship Tanker Tonnage/Speed Scatter") plt.grid() plt.show()

[ "lzz5235@vip.qq.com" ]

lzz5235@vip.qq.com

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# Generated by Django 3.0.6 on 2020-07-09 21:24 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main_app', '0011_auto_20200709_1635'), ] operations = [ migrations.AddField( model_name='routine', name='activity_name', field=models.CharField(default='temp', max_length=50), preserve_default=False, ), ]

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edagotti689/PYTHON-7-REGULAR-EXPRESSIONS

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import re # Matches 1 or more occurencies of preceding expression. # name = 'sriram' # mo = re.match('\w+', name) # print(mo.group()) # Matches 0 or more occurrence of preceding expression. name = 'sriram123' mo = re.match('\d*', name) print(mo.group()) # Matches 0 or 1 occurrence of preceding expression. # name = 'sriram123' # mo = re.match('\d?', name) # print(mo.group())

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from flask import Flask,render_template,url_for,request, redirect, Response import numpy as np #import pickle import pickle5 as pickle import pandas as pd #import tensorflow as tf from tensorflow.keras.models import load_model #from tensorflow.keras.preprocessing.text import Tokenizer from tensorflow.keras.preprocessing.sequence import pad_sequences #from tensorflow.keras.models import model_from_json from numpy import array app=Flask(__name__) #model = tf.create_model() model = load_model("lstmModel.h5") model.load_weights("geaNlp_weight_model.h5") # with open(path_to_protocol5, "rb") as fh: # data = pickle.load(fh) with open('tokenizer2.pickle', 'rb') as handle: tokenizer = pickle.load(handle) @app.route('/') def table(): df = pd.read_csv('hasil_label.csv', index_col=0) positif1 = df.loc[df['nilai'] > 15].head() negatif1 = df.loc[df['nilai'] < -25].head() netral1 = df.loc[df['nilai'] == -1].head() headings = ("Tweet", "Nilai", "Sentimen") tuples1 = [tuple(x) for x in positif1.values] tuples2 = [tuple(x) for x in negatif1.values] tuples3 = [tuple(x) for x in netral1.values] senti_count = df['sentimen'].value_counts() senti_count2=list(zip(senti_count,senti_count.index)) senti_count2=tuple(zip(senti_count,senti_count.index)) senti_count2 = [tuple(str(x) for x in tup) for tup in senti_count2] senti_count2 = [(sub[1], sub[0]) for sub in senti_count2] return render_template('home.html', sentimen=senti_count, tabel=df, headings = headings, positif=tuples1, negatif=tuples2, netral=tuples3, sentimen2=senti_count2) def default(): return redirect('/home.html') @app.route('/home.html') def home(): df = pd.read_csv('hasil_label.csv', index_col=0) positif1 = df.loc[df['nilai'] > 15].head() negatif1 = df.loc[df['nilai'] < -25].head() netral1 = df.loc[df['nilai'] == -1].head() headings = ("Tweet", "Nilai", "Sentimen") tuples1 = [tuple(x) for x in positif1.values] tuples2 = [tuple(x) for x in negatif1.values] tuples3 = [tuple(x) for x in netral1.values] senti_count = df['sentimen'].value_counts() senti_count2=list(zip(senti_count,senti_count.index)) senti_count2=tuple(zip(senti_count,senti_count.index)) senti_count2 = [tuple(str(x) for x in tup) for tup in senti_count2] senti_count2 = [(sub[1], sub[0]) for sub in senti_count2] return render_template('home.html', sentimen=senti_count, tabel=df, headings = headings, positif=tuples1, negatif=tuples2, netral=tuples3, sentimen2=senti_count2) @app.route('/predict',methods=['POST']) def predict(): max_length = 200 if request.method == 'POST': review = request.form['review'] data = [review] #tokenizer.fit_on_texts(data) enc = tokenizer.texts_to_sequences(data) enc = pad_sequences(enc, maxlen=max_length, dtype='int32', value=0) my_prediction = model.predict(array([enc][0]))[0] #class1 = model.predict_classes(array([enc][0]))[0] sentiment = model.predict(enc)[0] #print(my_prediction) #print(review) #print(data) #neg = np.argmax(sentiment) print(sentiment) if (np.argmax(sentiment) == 0): sentimennya = 0 # neg = sentiment # sentiment = neg #print('Sentimen: Negatif') elif (np.argmax(sentiment) == 1): sentimennya = 1 # net = sentiment # sentiment = net #print('Sentimen: Netral') else: sentimennya = 2 # pos = sentiment # sentiment = pos #print('Sentimen: Positif') return render_template('result.html',prediction = sentimennya, teks=review) @app.route('/style.css',methods=['GET']) def stylecss(): read_file = open("static/style.css", "r") opens = read_file.read() return Response(opens, mimetype='text/css') if __name__ == '__main__': app.run(debug=True)

[ "ggeadalfa@gmail.com" ]

ggeadalfa@gmail.com

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/run_codegen.py

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takp/grpc-sample

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refs/heads/master

2020-04-04T00:57:44.023282

2018-11-04T05:24:11

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# Copyright 2015 gRPC 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. """Runs protoc with the gRPC plugin to generate messages and gRPC stubs.""" from grpc_tools import protoc protoc.main(( '', '-I./protos', '--python_out=.', '--grpc_python_out=.', './protos/helloworld.proto', ))

[ "takayoshi.nishida@gmail.com" ]

takayoshi.nishida@gmail.com

738181729eb2d9a6b0e3fd73dfae9eb50c4cf98c

d1bcd0150979532a9b6caa37a9b119b4203c1091

/PyBootCamp/print_and_string.py

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[]

no_license

svfarande/Python-Bootcamp

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0d7eb14b50fbe9bd8709422a51f34f1d6202c8e6

refs/heads/main

2023-03-11T19:29:37.574840

2021-03-07T18:12:19

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2

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Python

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796

py

mystr = "Shubham" print(len(mystr)) print(mystr[::-1]) print("Shubham"[::-1]) mystr = mystr[:3] + "B" + mystr[4:] print(mystr) letter = "S" print(letter * 5) mystr = "Shubham Farande" print(mystr.split("a")) print('%f' % (0.1 + 0.2 - 0.3)) print("Answer is {s:}".format(s=100 / 777)) # Answer is 0.1287001287001287 print("Answer is {s:.2}".format(s=100 / 777)) # Answer is 0.13 print("Answer is {s:10}".format(s=100 / 777)) # Answer is 0.1287001287001287 print("Answer is {s:10.0}".format(s=100 / 777)) # Answer is 0.1 print("Answer is {s:10.1}".format(s=100 / 777)) # Answer is 0.1 print("Answer is {s:10.2}".format(s=100 / 777)) # Answer is 0.13 print("Answer is {s:10.3}".format(s=100 / 777)) # Answer is 0.129 mystr = "aa" print(f"My name is {mystr}.")

[ "svfarande@gmail.com" ]

svfarande@gmail.com

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/tests/wallet/cc_wallet/test_cc_wallet.py

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permissive

Olive-blockchain/Olive-blockchain-CLI

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import asyncio from typing import List import pytest from olive.consensus.block_rewards import calculate_base_farmer_reward, calculate_pool_reward from olive.full_node.mempool_manager import MempoolManager from olive.simulator.simulator_protocol import FarmNewBlockProtocol from olive.types.blockchain_format.coin import Coin from olive.types.blockchain_format.sized_bytes import bytes32 from olive.types.peer_info import PeerInfo from olive.util.ints import uint16, uint32, uint64 from olive.wallet.cc_wallet.cc_utils import cc_puzzle_hash_for_inner_puzzle_hash from olive.wallet.cc_wallet.cc_wallet import CCWallet from olive.wallet.puzzles.cc_loader import CC_MOD from olive.wallet.transaction_record import TransactionRecord from olive.wallet.wallet_coin_record import WalletCoinRecord from tests.setup_nodes import setup_simulators_and_wallets from tests.time_out_assert import time_out_assert @pytest.fixture(scope="module") def event_loop(): loop = asyncio.get_event_loop() yield loop async def tx_in_pool(mempool: MempoolManager, tx_id: bytes32): tx = mempool.get_spendbundle(tx_id) if tx is None: return False return True class TestCCWallet: @pytest.fixture(scope="function") async def wallet_node(self): async for _ in setup_simulators_and_wallets(1, 1, {}): yield _ @pytest.fixture(scope="function") async def two_wallet_nodes(self): async for _ in setup_simulators_and_wallets(1, 2, {}): yield _ @pytest.fixture(scope="function") async def three_wallet_nodes(self): async for _ in setup_simulators_and_wallets(1, 3, {}): yield _ @pytest.mark.asyncio async def test_colour_creation(self, two_wallet_nodes): num_blocks = 3 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet = wallet_node.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100)) tx_queue: List[TransactionRecord] = await wallet_node.wallet_state_manager.get_send_queue() tx_record = tx_queue[0] await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet.get_confirmed_balance, 100) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 100) @pytest.mark.asyncio async def test_cc_spend(self, two_wallet_nodes): num_blocks = 3 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet_node_2, server_3 = wallets[1] wallet = wallet_node.wallet_state_manager.main_wallet wallet2 = wallet_node_2.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await server_3.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100)) tx_queue: List[TransactionRecord] = await wallet_node.wallet_state_manager.get_send_queue() tx_record = tx_queue[0] await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet.get_confirmed_balance, 100) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 100) assert cc_wallet.cc_info.my_genesis_checker is not None colour = cc_wallet.get_colour() cc_wallet_2: CCWallet = await CCWallet.create_wallet_for_cc(wallet_node_2.wallet_state_manager, wallet2, colour) assert cc_wallet.cc_info.my_genesis_checker == cc_wallet_2.cc_info.my_genesis_checker cc_2_hash = await cc_wallet_2.get_new_inner_hash() tx_record = await cc_wallet.generate_signed_transaction([uint64(60)], [cc_2_hash]) await wallet.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) await time_out_assert(15, cc_wallet.get_confirmed_balance, 40) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 40) await time_out_assert(30, cc_wallet_2.get_confirmed_balance, 60) await time_out_assert(30, cc_wallet_2.get_unconfirmed_balance, 60) cc_hash = await cc_wallet.get_new_inner_hash() tx_record = await cc_wallet_2.generate_signed_transaction([uint64(15)], [cc_hash]) await wallet.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) await time_out_assert(15, cc_wallet.get_confirmed_balance, 55) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 55) @pytest.mark.asyncio async def test_get_wallet_for_colour(self, two_wallet_nodes): num_blocks = 3 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet = wallet_node.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100)) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) colour = cc_wallet.get_colour() assert await wallet_node.wallet_state_manager.get_wallet_for_colour(colour) == cc_wallet @pytest.mark.asyncio async def test_generate_zero_val(self, two_wallet_nodes): num_blocks = 4 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet_node_2, server_3 = wallets[1] wallet = wallet_node.wallet_state_manager.main_wallet wallet2 = wallet_node_2.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await server_3.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100)) ph = await wallet2.get_new_puzzlehash() for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) await time_out_assert(15, cc_wallet.get_confirmed_balance, 100) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 100) assert cc_wallet.cc_info.my_genesis_checker is not None colour = cc_wallet.get_colour() cc_wallet_2: CCWallet = await CCWallet.create_wallet_for_cc(wallet_node_2.wallet_state_manager, wallet2, colour) assert cc_wallet.cc_info.my_genesis_checker == cc_wallet_2.cc_info.my_genesis_checker spend_bundle = await cc_wallet_2.generate_zero_val_coin() await time_out_assert(15, tx_in_pool, True, full_node_api.full_node.mempool_manager, spend_bundle.name()) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) async def unspent_count(): unspent: List[WalletCoinRecord] = list( await cc_wallet_2.wallet_state_manager.get_spendable_coins_for_wallet(cc_wallet_2.id()) ) return len(unspent) await time_out_assert(15, unspent_count, 1) unspent: List[WalletCoinRecord] = list( await cc_wallet_2.wallet_state_manager.get_spendable_coins_for_wallet(cc_wallet_2.id()) ) assert unspent.pop().coin.amount == 0 @pytest.mark.asyncio async def test_cc_spend_uncoloured(self, two_wallet_nodes): num_blocks = 3 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet_node_2, server_3 = wallets[1] wallet = wallet_node.wallet_state_manager.main_wallet wallet2 = wallet_node_2.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await server_3.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100)) tx_queue: List[TransactionRecord] = await wallet_node.wallet_state_manager.get_send_queue() tx_record = tx_queue[0] await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet.get_confirmed_balance, 100) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 100) assert cc_wallet.cc_info.my_genesis_checker is not None colour = cc_wallet.get_colour() cc_wallet_2: CCWallet = await CCWallet.create_wallet_for_cc(wallet_node_2.wallet_state_manager, wallet2, colour) assert cc_wallet.cc_info.my_genesis_checker == cc_wallet_2.cc_info.my_genesis_checker cc_2_hash = await cc_wallet_2.get_new_inner_hash() tx_record = await cc_wallet.generate_signed_transaction([uint64(60)], [cc_2_hash]) await wallet.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet.get_confirmed_balance, 40) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 40) await time_out_assert(15, cc_wallet_2.get_confirmed_balance, 60) await time_out_assert(15, cc_wallet_2.get_unconfirmed_balance, 60) cc2_ph = await cc_wallet_2.get_new_cc_puzzle_hash() tx_record = await wallet.wallet_state_manager.main_wallet.generate_signed_transaction(10, cc2_ph, 0) await wallet.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(0, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) id = cc_wallet_2.id() wsm = cc_wallet_2.wallet_state_manager await time_out_assert(15, wsm.get_confirmed_balance_for_wallet, 70, id) await time_out_assert(15, cc_wallet_2.get_confirmed_balance, 60) await time_out_assert(15, cc_wallet_2.get_unconfirmed_balance, 60) @pytest.mark.asyncio async def test_cc_spend_multiple(self, three_wallet_nodes): num_blocks = 3 full_nodes, wallets = three_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node_0, wallet_server_0 = wallets[0] wallet_node_1, wallet_server_1 = wallets[1] wallet_node_2, wallet_server_2 = wallets[2] wallet_0 = wallet_node_0.wallet_state_manager.main_wallet wallet_1 = wallet_node_1.wallet_state_manager.main_wallet wallet_2 = wallet_node_2.wallet_state_manager.main_wallet ph = await wallet_0.get_new_puzzlehash() await wallet_server_0.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await wallet_server_1.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await wallet_server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet_0.get_confirmed_balance, funds) cc_wallet_0: CCWallet = await CCWallet.create_new_cc(wallet_node_0.wallet_state_manager, wallet_0, uint64(100)) tx_queue: List[TransactionRecord] = await wallet_node_0.wallet_state_manager.get_send_queue() tx_record = tx_queue[0] await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet_0.get_confirmed_balance, 100) await time_out_assert(15, cc_wallet_0.get_unconfirmed_balance, 100) assert cc_wallet_0.cc_info.my_genesis_checker is not None colour = cc_wallet_0.get_colour() cc_wallet_1: CCWallet = await CCWallet.create_wallet_for_cc( wallet_node_1.wallet_state_manager, wallet_1, colour ) cc_wallet_2: CCWallet = await CCWallet.create_wallet_for_cc( wallet_node_2.wallet_state_manager, wallet_2, colour ) assert cc_wallet_0.cc_info.my_genesis_checker == cc_wallet_1.cc_info.my_genesis_checker assert cc_wallet_0.cc_info.my_genesis_checker == cc_wallet_2.cc_info.my_genesis_checker cc_1_hash = await cc_wallet_1.get_new_inner_hash() cc_2_hash = await cc_wallet_2.get_new_inner_hash() tx_record = await cc_wallet_0.generate_signed_transaction([uint64(60), uint64(20)], [cc_1_hash, cc_2_hash]) await wallet_0.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet_0.get_confirmed_balance, 20) await time_out_assert(15, cc_wallet_0.get_unconfirmed_balance, 20) await time_out_assert(30, cc_wallet_1.get_confirmed_balance, 60) await time_out_assert(30, cc_wallet_1.get_unconfirmed_balance, 60) await time_out_assert(30, cc_wallet_2.get_confirmed_balance, 20) await time_out_assert(30, cc_wallet_2.get_unconfirmed_balance, 20) cc_hash = await cc_wallet_0.get_new_inner_hash() tx_record = await cc_wallet_1.generate_signed_transaction([uint64(15)], [cc_hash]) await wallet_1.wallet_state_manager.add_pending_transaction(tx_record) tx_record_2 = await cc_wallet_2.generate_signed_transaction([uint64(20)], [cc_hash]) await wallet_2.wallet_state_manager.add_pending_transaction(tx_record_2) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record_2.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet_0.get_confirmed_balance, 55) await time_out_assert(15, cc_wallet_0.get_unconfirmed_balance, 55) await time_out_assert(30, cc_wallet_1.get_confirmed_balance, 45) await time_out_assert(30, cc_wallet_1.get_unconfirmed_balance, 45) await time_out_assert(30, cc_wallet_2.get_confirmed_balance, 0) await time_out_assert(30, cc_wallet_2.get_unconfirmed_balance, 0) @pytest.mark.asyncio async def test_cc_max_amount_send(self, two_wallet_nodes): num_blocks = 3 full_nodes, wallets = two_wallet_nodes full_node_api = full_nodes[0] full_node_server = full_node_api.server wallet_node, server_2 = wallets[0] wallet_node_2, server_3 = wallets[1] wallet = wallet_node.wallet_state_manager.main_wallet ph = await wallet.get_new_puzzlehash() await server_2.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) await server_3.start_client(PeerInfo("localhost", uint16(full_node_server._port)), None) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) funds = sum( [ calculate_pool_reward(uint32(i)) + calculate_base_farmer_reward(uint32(i)) for i in range(1, num_blocks - 1) ] ) await time_out_assert(15, wallet.get_confirmed_balance, funds) cc_wallet: CCWallet = await CCWallet.create_new_cc(wallet_node.wallet_state_manager, wallet, uint64(100000)) tx_queue: List[TransactionRecord] = await wallet_node.wallet_state_manager.get_send_queue() tx_record = tx_queue[0] await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(32 * b"0")) await time_out_assert(15, cc_wallet.get_confirmed_balance, 100000) await time_out_assert(15, cc_wallet.get_unconfirmed_balance, 100000) assert cc_wallet.cc_info.my_genesis_checker is not None cc_2_hash = await cc_wallet.get_new_inner_hash() amounts = [] puzzle_hashes = [] for i in range(1, 50): amounts.append(uint64(i)) puzzle_hashes.append(cc_2_hash) spent_coint = (await cc_wallet.get_cc_spendable_coins())[0].coin tx_record = await cc_wallet.generate_signed_transaction(amounts, puzzle_hashes, coins={spent_coint}) await wallet.wallet_state_manager.add_pending_transaction(tx_record) await time_out_assert( 15, tx_in_pool, True, full_node_api.full_node.mempool_manager, tx_record.spend_bundle.name() ) for i in range(1, num_blocks): await full_node_api.farm_new_transaction_block(FarmNewBlockProtocol(ph)) await asyncio.sleep(2) async def check_all_there(): spendable = await cc_wallet.get_cc_spendable_coins() spendable_name_set = set() for record in spendable: spendable_name_set.add(record.coin.name()) puzzle_hash = cc_puzzle_hash_for_inner_puzzle_hash(CC_MOD, cc_wallet.cc_info.my_genesis_checker, cc_2_hash) for i in range(1, 50): coin = Coin(spent_coint.name(), puzzle_hash, i) if coin.name() not in spendable_name_set: return False return True await time_out_assert(15, check_all_there, True) await asyncio.sleep(5) max_sent_amount = await cc_wallet.get_max_send_amount() # 1) Generate transaction that is under the limit under_limit_tx = None try: under_limit_tx = await cc_wallet.generate_signed_transaction( [max_sent_amount - 1], [ph], ) except ValueError: assert ValueError assert under_limit_tx is not None # 2) Generate transaction that is equal to limit at_limit_tx = None try: at_limit_tx = await cc_wallet.generate_signed_transaction( [max_sent_amount], [ph], ) except ValueError: assert ValueError assert at_limit_tx is not None # 3) Generate transaction that is greater than limit above_limit_tx = None try: above_limit_tx = await cc_wallet.generate_signed_transaction( [max_sent_amount + 1], [ph], ) except ValueError: pass assert above_limit_tx is None

[ "87711356+Olive-blockchain@users.noreply.github.com" ]

87711356+Olive-blockchain@users.noreply.github.com

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/music/apps.py

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[]

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gbip/djRDO

f9cae89a29560ed3f7f02b17824579cf67123c56

e2d6a0336c7934cae71f833cb34a1f5f21db2d02

refs/heads/master

2023-08-27T15:05:23.601486

2021-11-04T17:53:20

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from django.apps import AppConfig class MusicImporterConfig(AppConfig): name = "music"

[ "perso@florencepaul.com" ]

perso@florencepaul.com

8a3ea212efe2d9f38ce16796b86ef36e7e2d6b41

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/demisto_sdk/commands/common/content/objects/pack_objects/pack.py

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[ "MIT" ]

permissive

shubgwal-gif/demisto-sdk

fc80163b7a2c2fc00d5b664a47326a9dbebf6dd6

35b15113ff8488c7c9051da2c2cbcbc7c6915e8d

refs/heads/master

2023-01-29T11:31:36.928267

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from typing import Any, Iterator, Optional, Union from demisto_sdk.commands.common.constants import (CLASSIFIERS_DIR, CONNECTIONS_DIR, DASHBOARDS_DIR, DOC_FILES_DIR, INCIDENT_FIELDS_DIR, INCIDENT_TYPES_DIR, INDICATOR_FIELDS_DIR, INDICATOR_TYPES_DIR, INTEGRATIONS_DIR, LAYOUTS_DIR, PLAYBOOKS_DIR, RELEASE_NOTES_DIR, REPORTS_DIR, SCRIPTS_DIR, TEST_PLAYBOOKS_DIR, TOOLS_DIR, WIDGETS_DIR) from demisto_sdk.commands.common.content.objects.pack_objects import ( AgentTool, Classifier, ClassifierMapper, Connection, Dashboard, DocFile, IncidentField, IncidentType, IndicatorField, IndicatorType, Integration, Layout, OldClassifier, PackIgnore, PackMetaData, Playbook, Readme, ReleaseNote, Report, Script, SecretIgnore, Widget) from demisto_sdk.commands.common.content.objects_factory import \ path_to_pack_object from wcmatch.pathlib import Path class Pack: def __init__(self, path: Union[str, Path]): self._path = Path(path) def _content_files_list_generator_factory(self, dir_name: str, suffix: str) -> Iterator[Any]: """Generic content objcets iterable generator Args: dir_name: Directory name, for example: Integrations, Documentations etc. suffix: file suffix to search for, if not supplied then any suffix. Returns: object: Any valid content object found in the given directory. """ objects_path = (self._path / dir_name).glob(patterns=[f"*.{suffix}", f"*/*.{suffix}"]) for object_path in objects_path: yield path_to_pack_object(object_path) def _content_dirs_list_generator_factory(self, dir_name) -> Iterator[Any]: """Generic content objcets iterable generator Args: dir_name: Directory name, for example: Tools. Returns: object: Any valid content object found in the given directory. """ objects_path = (self._path / dir_name).glob(patterns=["*/"]) for object_path in objects_path: yield path_to_pack_object(object_path) @property def id(self) -> str: return self._path.parts[-1] @property def path(self) -> Path: return self._path @property def integrations(self) -> Iterator[Integration]: return self._content_files_list_generator_factory(dir_name=INTEGRATIONS_DIR, suffix="yml") @property def scripts(self) -> Iterator[Script]: return self._content_files_list_generator_factory(dir_name=SCRIPTS_DIR, suffix="yml") @property def playbooks(self) -> Iterator[Playbook]: return self._content_files_list_generator_factory(dir_name=PLAYBOOKS_DIR, suffix="yml") @property def reports(self) -> Iterator[Report]: return self._content_files_list_generator_factory(dir_name=REPORTS_DIR, suffix="json") @property def dashboards(self) -> Iterator[Dashboard]: return self._content_files_list_generator_factory(dir_name=DASHBOARDS_DIR, suffix="json") @property def incident_types(self) -> Iterator[IncidentType]: return self._content_files_list_generator_factory(dir_name=INCIDENT_TYPES_DIR, suffix="json") @property def incident_fields(self) -> Iterator[IncidentField]: return self._content_files_list_generator_factory(dir_name=INCIDENT_FIELDS_DIR, suffix="json") @property def layouts(self) -> Iterator[Layout]: return self._content_files_list_generator_factory(dir_name=LAYOUTS_DIR, suffix="json") @property def classifiers(self) -> Iterator[Union[Classifier, OldClassifier, ClassifierMapper]]: return self._content_files_list_generator_factory(dir_name=CLASSIFIERS_DIR, suffix="json") @property def indicator_types(self) -> Iterator[IndicatorType]: return self._content_files_list_generator_factory(dir_name=INDICATOR_TYPES_DIR, suffix="json") @property def indicator_fields(self) -> Iterator[IndicatorField]: return self._content_files_list_generator_factory(dir_name=INDICATOR_FIELDS_DIR, suffix="json") @property def connections(self) -> Iterator[Connection]: return self._content_files_list_generator_factory(dir_name=CONNECTIONS_DIR, suffix="json") @property def test_playbooks(self) -> Iterator[Union[Playbook, Script]]: return self._content_files_list_generator_factory(dir_name=TEST_PLAYBOOKS_DIR, suffix="yml") @property def widgets(self) -> Iterator[Widget]: return self._content_files_list_generator_factory(dir_name=WIDGETS_DIR, suffix="json") @property def release_notes(self) -> Iterator[ReleaseNote]: return self._content_files_list_generator_factory(dir_name=RELEASE_NOTES_DIR, suffix="md") @property def tools(self) -> Iterator[AgentTool]: return self._content_dirs_list_generator_factory(dir_name=TOOLS_DIR) @property def doc_files(self) -> Iterator[DocFile]: return self._content_files_list_generator_factory(dir_name=DOC_FILES_DIR, suffix="*") @property def pack_metadata(self) -> Optional[PackMetaData]: obj = None file = self._path / "pack_metadata.json" if file.exists(): obj = PackMetaData(file) return obj @property def secrets_ignore(self) -> Optional[SecretIgnore]: obj = None file = self._path / ".secrets-ignore" if file.exists(): obj = SecretIgnore(file) return obj @property def pack_ignore(self) -> Optional[PackIgnore]: obj = None file = self._path / ".pack-ignore" if file.exists(): obj = PackIgnore(file) return obj @property def readme(self) -> Optional[Readme]: obj = None file = self._path / "README.md" if file.exists(): obj = Readme(file) return obj

[ "noreply@github.com" ]

shubgwal-gif.noreply@github.com

266aa42a7d13fb27c4027899a7e959bbff0a81b6

935a3f949041bb43433bd02bb0988519f0fd8c4e

/ex2.py

0690e9624d92f0461f54cda7f1aff4db3d6a16f9

[]

no_license

damiankoper/iobLab

c5acae472be66b27f6c58d2453a8419129e33eb6

819f02e3aa8a8bbfbfab27362f2982fed12fb03a

refs/heads/master

2021-03-21T22:12:26.707722

2020-05-08T19:34:39

247,330,989

0

null

UTF-8

Python

false

3,584

py

#!/usr/bin/env python3 import numpy as np import urllib.request import cv2 import binascii import lorem import math import matplotlib.pyplot as plt def encode_as_binary_array(msg): """Encode a message as a binary string.""" msg = msg.encode("utf-8") msg = msg.hex() msg = [msg[i:i + 2] for i in range(0, len(msg), 2)] msg = [bin(int(el, base=16))[2:] for el in msg] msg = ["0" * (8 - len(el)) + el for el in msg] return "".join(msg) def decode_from_binary_array(array): """Decode a binary string to utf8.""" array = [array[i:i+8] for i in range(0, len(array), 8)] if len(array[-1]) != 8: array[-1] = array[-1] + "0" * (8 - len(array[-1])) array = [hex(int(el, 2))[2:].zfill(2) for el in array] array = "".join(array) result = binascii.unhexlify(array) return result.decode("utf-8", errors="replace") def hide_message(image, message, nbits=1): """Hide a message in an image (LSB). nbits: number of least significant bits """ nbits = clamp(nbits, 1, 8) shape = image.shape image = np.copy(image).flatten() if len(message) > len(image) * nbits: raise ValueError("Message is to long :(") chunks = [message[i:i + nbits] for i in range(0, len(message), nbits)] for i, chunk in enumerate(chunks): byte = str(bin(image[i]))[2:].zfill(8) new_byte = byte[:-nbits] + chunk image[i] = int(new_byte, 2) return image.reshape(shape) def clamp(n, minn, maxn): """Clamp the n value to be in range (minn, maxn).""" return max(min(maxn, n), minn) def reveal_message(image, nbits=1, length=0): """Reveal the hidden message. nbits: number of least significant bits length: length of the message in bits. """ nbits = clamp(nbits, 1, 8) shape = image.shape image = np.copy(image).flatten() length_in_pixels = math.ceil(length/nbits) if len(image) < length_in_pixels or length_in_pixels <= 0: length_in_pixels = len(image) message = "" i = 0 while i < length_in_pixels: byte = str(bin(image[i]))[2:].zfill(8) message += byte[-nbits:] i += 1 mod = length % -nbits if mod != 0: message = message[:mod] return message print("Downloading image!") path = 'https://picsum.photos/500/500' resp = urllib.request.urlopen(path) image = np.asarray(bytearray(resp.read()), dtype="uint8") image = cv2.imdecode(image, cv2.IMREAD_COLOR) print("Image downloaded!") message = lorem.text()*1000 secret = encode_as_binary_array(message) resultImageRow1 = None resultImageRow2 = None nbitsList = range(1, 9) nbitsMSE = [] for nbits in nbitsList: print(nbits) imageSecret = hide_message(image, secret[:int(image.size*0.8)], nbits) mse = ((imageSecret - image)**2).mean() nbitsMSE.append(mse) if nbits <= 4: resultImageRow1 = imageSecret if resultImageRow1 is None else np.hstack( [resultImageRow1, imageSecret]) else: resultImageRow2 = imageSecret if resultImageRow2 is None else np.hstack( [resultImageRow2, imageSecret]) plt.plot(nbitsList, nbitsMSE) plt.xlabel('nbits') plt.ylabel('MSE') cv2.namedWindow("Result", cv2.WINDOW_NORMAL) cv2.imshow('Result', np.vstack([resultImageRow1, resultImageRow2])) cv2.imwrite('ex2_encoded.png', np.vstack([resultImageRow1, resultImageRow2])) cv2.waitKey(1) plt.savefig('ex2_plot.png') plt.show() cv2.waitKey() # Dla nbits=7,8 MSE zmalał, ponieważ widoczna jest większa część bazowego obrazu # - wiadomość zapisano na mniejszej liczbie plkseli

[ "kopernickk@gmail.com" ]

kopernickk@gmail.com

1e89fbf40a207c845671b836a424fd324fc46b79

30834d127caf5044959ae7e17fdf0cf03b1db4d0

/41. First Missing Positive.py

cce102c99c3c7dc206eb0ff957e525b0b7a3676a

[]

no_license

xigaoli/lc-challenges

9c4dfe866340b42a2780994719e12c3a5a513af2

eb06aab20129fca8239717842582c0dc2bb69d53

refs/heads/main

2023-02-11T09:00:51.777126

2021-01-13T23:27:46

308,232,532

0

null

UTF-8

Python

false

431

py

from collections import defaultdict class Solution: def firstMissingPositive(self, nums: List[int]) -> int: numdict = defaultdict(int) for n in nums: #print(n) numdict[n]+=1 for i in range(1,len(nums)+1): if(numdict[i]==0): return i #if nums is [1,2,...k] then len(nums)+1==k+1 is answer return len(nums)+1

[ "lxgfrom2009@gmail.com" ]

lxgfrom2009@gmail.com

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# Definition for singly-linked list. # class ListNode: # def __init__(self, val=0, next=None): # self.val = val # self.next = next class Solution: def reorderList(self, head: ListNode) -> None: """ Do not return anything, modify head in-place instead. """ #Time Complexity: O(n) #Space Complexity: O(1) if not head: return None slow_pointer = head fast_pointer = head while fast_pointer.next and fast_pointer.next.next: #finding mid-point slow_pointer = slow_pointer.next fast_pointer = fast_pointer.next.next fast_pointer = self.reverse(slow_pointer.next) #reversing second half slow_pointer.next = None #severing two lists slow_pointer = head while fast_pointer: #merging two lists temp = slow_pointer.next slow_pointer.next = fast_pointer fast_pointer = fast_pointer.next slow_pointer.next.next = temp slow_pointer = temp def reverse(self, root): prev = None curr = root while curr: temp = curr.next curr.next = prev prev = curr curr = temp return prev

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# Generated by Django 2.0.1 on 2018-03-19 13:17 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('posts', '0008_auto_20180316_1109'), ] operations = [ migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('timestamp', models.DateTimeField(auto_now=True)), ('text', models.CharField(max_length=500)), ('post', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='posts.Post')), ('user', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)), ], ), ]

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#!/usr/bin/python3 """Docstring because reasons""" class BaseGeometry: """ A mostly empty class with a few error conditions """ def area(self): """ Just an error for this one """ raise Exception("area() is not implemented") def integer_validator(self, name, value): """ Just meant to raise errors for now parameters - name: a string much like key in dict value: (int) much like value in a dict """ if type(value) is not int: raise TypeError("{} must be an integer".format(name)) elif value <= 0: raise ValueError("{} must be greater than 0".format(name)) class Rectangle(BaseGeometry): """ Inheriets from the class BaseGeometry which is mostly full or errors """ def __init__(self, width, height): """ initializes with a validity check for ints parameters - width (int): the width height (int): the height """ self.integer_validator("width", width) self.__width = width self.integer_validator("height", height) self.__height = height def area(self): """ calcualtes the area of our rectangle """ return (self.__height * self.__width) def __str__(self): """ returns a string representation of the object """ return("[Rectangle] {}/{}".format(self.__width, self.__height)) class Square(Rectangle): """ Inheriets from class rectangle """ def __init__(self, size): """ Initializes a square of size size after validating size to be an int parameter - size (int): the size """ self.integer_validator("size", size) self.__size = size def area(self): """ Returns the area of the square """ return (self.__size ** 2) def __str__(self): """ returns a string representation of the object """ return("[Square] {}/{}".format(self.__size, self.__size))

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from django.apps import AppConfig class SapAppConfig(AppConfig): name = 'Sap_app'

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import numpy as np from megskull.network import Network from megskull.opr.all import ( Conv2D, Pooling2D, FullyConnected, Softmax, CrossEntropyLoss, Dropout, ElementwiseAffine, Concat, Floor, Ceil, ones, Cumsum, Min, Max, AdvancedIndexing, Astype, Linspace, IndexingRemap, Equal, ZeroGrad, ) from megskull.opr.helper.elemwise_trans import ReLU, Identity from megskull.graph.query import GroupNode from megskull.opr.netsrc import DataProvider, ConstProvider import megskull.opr.helper.param_init as pinit from megskull.opr.helper.param_init import AutoGaussianParamInitializer as G from megskull.opr.helper.param_init import ConstantParamInitializer as C from megskull.opr.regularizer import BatchNormalization as BN import megskull.opr.arith as arith global idx idx = 0 def conv_bn(inp, ker_shape, stride, padding, out_chl, isrelu): global idx idx += 1 l1 = Conv2D( "conv{}".format(idx), inp, kernel_shape = ker_shape, stride = stride, padding = padding, output_nr_channel = out_chl, W = G(mean = 0, std = ((1 + int(isrelu)) / (ker_shape**2 * inp.partial_shape[1]))**0.5), nonlinearity = Identity() ) l2 = BN("bn{}".format(idx), l1, eps = 1e-9) l2 = ElementwiseAffine("bnaff{}".format(idx), l2, shared_in_channels = False, k = C(1), b = C(0)) if isrelu: l2 = arith.ReLU(l2) return l2, l1 def dfconv(inp, chl, isrelu, ker_shape = 3, stride = 1, padding = 1, dx = [-1, 0, 1], dy = [-1, 0, 1]): inp = Conv2D( name + "conv", inp, kernel_shape = 3, stride = 1, padding = 1, output_nr_channel = ker_shape**2, W = G(mean = 0, std = ((1) / (ker_shape**2 * inp.partial_shape[1]))**0.5), nonlinearity = Identity() ) inp = BN(name + "BN", inp, eps = 1e-9) global idx #idx += 1 gamma = 0.001 offsetx = inp.partial_shape[2] * Conv2D( "conv{}_offsetx".format(idx + 1), inp, kernel_shape = ker_shape, stride = stride, padding = padding, output_nr_channel = ker_shape**2, W = G(mean = 0, std = gamma / (ker_shape**2 * inp.partial_shape[2])), nonlinearity = Identity() ) offsety = inp.partial_shape[3] * Conv2D( "conv{}_offsety".format(idx + 1), inp, kernel_shape = ker_shape, stride = stride, padding = padding, output_nr_channel = ker_shape**2, W = G(mean = 0, std = gamma / (ker_shape**2 * inp.partial_shape[3])), nonlinearity = Identity() ) outputs = [] for sx in range(2): for sy in range(2): if sx == 0: ofx = Floor(offsetx) bilx = offsetx - ofx else: ofx = Ceil(offsetx) bilx = ofx - offsetx if sy == 0: ofy = Floor(offsety) bily = offsety - ofy else: ofy = Ceil(offsety) bily = ofy - offsety """ No padding padding1 = ConstProvider(np.zeros((inp.partial_shape[0], inp.partial_shape[1], 1, inp.partial_shape[3]))) padding2 = ConstProvider(np.zeros((inp.partial_shape[0], inp.partial_shape[1], inp.partial_shape[2] + 2, 1))) arg_fea = Concat([padding1, inp, padding1], axis = 2) arg_fea = Concat([padding2, arg_fea, padding2], axis = 3) """ arg_fea = inp #one_mat = ConstProvider(np.ones((inp.partial_shape[2], inp.partial_shape[3])), dtype = np.int32) one_mat = ConstProvider(1, dtype = np.int32).add_axis(0).broadcast((ofx.partial_shape[2], ofx.partial_shape[3])) affx = (Cumsum(one_mat, axis = 0) - 1) * stride affy = (Cumsum(one_mat, axis = 1) - 1) * stride ofx = ofx + affx.dimshuffle('x', 'x', 0, 1) ofy = ofy + affy.dimshuffle('x', 'x', 0, 1) one_mat = ConstProvider(np.ones((ker_shape, ofx.partial_shape[2], ofx.partial_shape[3]))) #ofx[:, :ker_shape, :, :] -= 1 #ofx[:, ker_shape*2:, :, :] += 1 ofx += Concat([one_mat * i for i in dx], axis = 0).dimshuffle('x', 0, 1, 2) #ofy[:, ::3, :, :] -= 1 #ofy[:, 2::3, :, :] += 1 one_mat = ones((1, ofx.partial_shape[2], ofx.partial_shape[3])) one_mat = Concat([one_mat * i for i in dy], axis = 0) one_mat = Concat([one_mat] * ker_shape, axis = 0) ofy += one_mat.dimshuffle('x', 0, 1, 2) ofx = Max(Min(ofx, arg_fea.partial_shape[2] - 1), 0) ofy = Max(Min(ofy, arg_fea.partial_shape[3] - 1), 0) def DeformReshape(inp, ker_shape): inp = inp.reshape(inp.shape[0], ker_shape, ker_shape, inp.shape[2], inp.shape[3]) inp = inp.dimshuffle(0, 3, 1, 4, 2) inp = inp.reshape(inp.shape[0], inp.shape[1] * inp.shape[2], inp.shape[3] * inp.shape[4]) return inp ofx = DeformReshape(ofx, ker_shape) ofy = DeformReshape(ofy, ker_shape) bilx = DeformReshape(bilx, ker_shape) bily = DeformReshape(bily, ker_shape) of = ofx * arg_fea.shape[2] + ofy arg_fea = arg_fea.reshape(arg_fea.shape[0], arg_fea.shape[1], -1) of = of.reshape(ofx.shape[0], -1) of = of.dimshuffle(0, 'x', 1) #of = Concat([of] * arg_fea.partial_shape[1], axis = 1) of = of.broadcast((of.shape[0], arg_fea.shape[1], of.shape[2])) arx = Linspace(0, arg_fea.shape[0], arg_fea.shape[0], endpoint = False) arx = arx.add_axis(1).add_axis(2).broadcast(of.shape) ary = Linspace(0, arg_fea.shape[1], arg_fea.shape[1], endpoint = False) ary = ary.add_axis(0).add_axis(2).broadcast(of.shape) of = of.add_axis(3) arx = arx.add_axis(3) ary = ary.add_axis(3) idxmap = Astype(Concat([arx, ary, of], axis = 3), np.int32) """ sample = [] for i in range(arg_fea.partial_shape[0]): for j in range(arg_fea.partial_shape[1]): sample.append(arg_fea[i][j].ai[of[i][j]].dimshuffle('x', 0)) sample = Concat(sample, axis = 0) """ sample = IndexingRemap(arg_fea, idxmap).reshape(inp.shape[0], inp.shape[1], bilx.shape[1], -1) bilx = bilx.dimshuffle(0, 'x', 1, 2).broadcast(sample.shape) bily = bily.dimshuffle(0, 'x', 1, 2).broadcast(sample.shape) sample *= bilx * bily outputs.append(sample) output = outputs[0] for i in outputs[1:]: output += i return conv_bn(output, ker_shape, 3, 0, chl, isrelu) def dfpooling(name, inp, window = 2, padding = 0, dx = [0, 1], dy = [0, 1]): #inp = ConstProvider([[[[1, 2], [3, 4]]]], dtype = np.float32) """ Add a new conv&bn to insure that the scale of the feature map is variance 1. """ ker_shape = window stride = window offsetlay = Conv2D( name + "conv", inp, kernel_shape = 3, stride = 1, padding = 1, output_nr_channel = ker_shape**2, W = G(mean = 0, std = ((1) / (3**2 * inp.partial_shape[1]))**0.5), nonlinearity = Identity() ) #offsetlay = BN(name + "BN", offsetlay, eps = 1e-9) offsetx = Conv2D( name + "conv1x", offsetlay, kernel_shape = ker_shape, stride = stride, padding = padding, output_nr_channel = ker_shape**2, W = G(mean = 0, std = (1 / (ker_shape**2 * inp.partial_shape[2]))**0.5), nonlinearity = Identity() ) offsety = Conv2D( name + "conv1y", offsetlay, kernel_shape = ker_shape, stride = stride, padding = padding, output_nr_channel = ker_shape**2, W = G(mean = 0, std = (1 / (ker_shape**2 * inp.partial_shape[3]))**0.5), nonlinearity = Identity() ) offset = Concat([offsetx, offsety], axis = 1) ndim = ker_shape**2 * offsetx.partial_shape[2] * offsetx.partial_shape[3] * 2 offset = FullyConnected( name + "offset", offsetx, output_dim = ndim, W = G(mean = 0, std = (1 / ndim)**2), #W = C(0), b = C(0), nonlinearity = Identity() ) offsetx = offset[:, :ndim // 2].reshape(offsetx.shape) offsety = offset[:, ndim // 2:].reshape(offsety.shape) """ offsetx = FullyConnected( name + "offsetx", offsetx, output_dim = ndim, W = G(mean = 0, std = gamma / ndim), b = C(0), nonlinearity = Identity() ) offsetx = offsetx.reshape(offsety.shape) offsety = FullyConnected( name + "offsety", offsety, output_dim = ndim, W = G(mean = 0, std = gamma / ndim), b = C(0), nonlinearity = Identity() ) offsety = offsety.reshape(offsetx.shape) print(offsety.partial_shape) """ #offsetx = ZeroGrad(offsetx) #offsety = ZeroGrad(offsety) outputs = [] for sx in range(2): for sy in range(2): if sx == 0: ofx = Floor(offsetx) bilx = 1 - (offsetx - ofx) else: ofx = Ceil(offsetx) bilx = 1 - (ofx - offsetx) if sy == 0: ofy = Floor(offsety) bily = 1 - (offsety - ofy) else: ofy = Ceil(offsety) bily = 1 - (ofy - offsety) """ No padding padding1 = ConstProvider(np.zeros((inp.partial_shape[0], inp.partial_shape[1], 1, inp.partial_shape[3]))) padding2 = ConstProvider(np.zeros((inp.partial_shape[0], inp.partial_shape[1], inp.partial_shape[2] + 2, 1))) arg_fea = Concat([padding1, inp, padding1], axis = 2) arg_fea = Concat([padding2, arg_fea, padding2], axis = 3) """ arg_fea = inp #one_mat = ConstProvider(np.ones((inp.partial_shape[2], inp.partial_shape[3])), dtype = np.int32) one_mat = ConstProvider(1, dtype = np.int32).add_axis(0).broadcast((ofx.shape[2], ofx.shape[3])) affx = (Cumsum(one_mat, axis = 0) - 1) * stride affy = (Cumsum(one_mat, axis = 1) - 1) * stride ofx = ofx + affx.dimshuffle('x', 'x', 0, 1) ofy = ofy + affy.dimshuffle('x', 'x', 0, 1) one_mat = ConstProvider(np.ones((ker_shape, ofx.partial_shape[2], ofx.partial_shape[3]))) #ofx[:, :ker_shape, :, :] -= 1 #ofx[:, ker_shape*2:, :, :] += 1 ofx += Concat([one_mat * i for i in dx], axis = 0).dimshuffle('x', 0, 1, 2) #ofy[:, ::3, :, :] -= 1 #ofy[:, 2::3, :, :] += 1 one_mat = ones((1, ofx.partial_shape[2], ofx.partial_shape[3])) one_mat = Concat([one_mat * i for i in dy], axis = 0) one_mat = Concat([one_mat] * ker_shape, axis = 0) ofy += one_mat.dimshuffle('x', 0, 1, 2) ofx = Max(Min(ofx, arg_fea.partial_shape[2] - 1), 0) ofy = Max(Min(ofy, arg_fea.partial_shape[3] - 1), 0) def DeformReshape(inp, ker_shape): inp = inp.reshape(inp.shape[0], ker_shape, ker_shape, inp.shape[2], inp.partial_shape[3]) inp = inp.dimshuffle(0, 3, 1, 4, 2) inp = inp.reshape(inp.shape[0], inp.shape[1] * inp.shape[2], inp.shape[3] * inp.shape[4]) return inp ofx = DeformReshape(ofx, ker_shape) ofy = DeformReshape(ofy, ker_shape) bilx = DeformReshape(bilx, ker_shape) bily = DeformReshape(bily, ker_shape) of = ofx * arg_fea.partial_shape[2] + ofy arg_fea = arg_fea.reshape(arg_fea.shape[0], arg_fea.shape[1], -1) of = of.reshape(ofx.shape[0], -1) of = of.dimshuffle(0, 'x', 1) #of = Concat([of] * arg_fea.partial_shape[1], axis = 1) of = of.broadcast((of.shape[0], arg_fea.shape[1], of.shape[2])) arx = Linspace(0, arg_fea.shape[0], arg_fea.shape[0], endpoint = False) arx = arx.add_axis(1).add_axis(2).broadcast(of.shape) ary = Linspace(0, arg_fea.shape[1], arg_fea.shape[1], endpoint = False) ary = ary.add_axis(0).add_axis(2).broadcast(of.shape) of = of.add_axis(3) arx = arx.add_axis(3) ary = ary.add_axis(3) idxmap = Astype(Concat([arx, ary, of], axis = 3), np.int32) """ sample = [] for i in range(arg_fea.partial_shape[0]): for j in range(arg_fea.partial_shape[1]): sample.append(arg_fea[i][j].ai[of[i][j]].dimshuffle('x', 0)) sample = Concat(sample, axis = 0) """ sample = IndexingRemap(arg_fea, idxmap).reshape(inp.shape[0], inp.shape[1], bilx.shape[1], -1) bilx = bilx.dimshuffle(0, 'x', 1, 2).broadcast(sample.shape) bily = bily.dimshuffle(0, 'x', 1, 2).broadcast(sample.shape) sample *= bilx * bily outputs.append(sample) output = outputs[0] for i in outputs[1:]: output += i return Pooling2D(name, output, window = 2, mode = "AVERAGE") def make_network(minibatch_size = 128): patch_size = 32 inp = DataProvider("data", shape = (minibatch_size, 3, patch_size, patch_size)) label = DataProvider("label", shape = (minibatch_size, )) #lay = bn_relu_conv(inp, 3, 1, 1, 16, False, False) lay, conv = conv_bn(inp, 3, 1, 1, 16, True) out = [conv] for chl in [32, 64, 128]: for i in range(10): lay, conv = conv_bn(lay, 3, 1, 1, chl, True) out.append(conv) if chl != 128: lay = dfpooling("pooling{}".format(chl), lay) #global average pooling print(lay.partial_shape) feature = lay.mean(axis = 2).mean(axis = 2) #feature = Pooling2D("glbpoling", lay, window = 8, stride = 8, mode = "AVERAGE") pred = Softmax("pred", FullyConnected( "fc0", feature, output_dim = 10, W = G(mean = 0, std = (1 / feature.partial_shape[1])**0.5), b = C(0), nonlinearity = Identity() )) network = Network(outputs = [pred] + out) network.loss_var = CrossEntropyLoss(pred, label) return network if __name__ == '__main__': make_network()

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#!/usr/bin/env python import os import sys import argparse import numpy as np import astropy.io.fits as pyfits import astropy.units as units import matplotlib.pyplot as plt from desispec.io import read_frame from desispec.interpolation import resample_flux from desispec.io.filters import load_legacy_survey_filter band="R" fluxunits = 1e-17 * units.erg / units.s / units.cm**2 / units.Angstrom parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="Display spectra, looping over targets if targetid not set, and optionally show best fit from redrock" ) parser.add_argument('--cframes', type = str, default = None, required = True, nargs="*", help = 'path to cframe fits files') parser.add_argument('--stdstars', type = str, default = None, required = True, help = 'path to stdstars fits files') args = parser.parse_args() stars_filename = args.stdstars #"stdstars-0-00051001.fits" frame_filenames = args.cframes #["cframe-r0-00051001.fits","cframe-b0-00051001.fits","cframe-z0-00051001.fits"] h=pyfits.open(stars_filename) h.info() fibers=h["FIBERS"].data table=h["METADATA"].data print("std stars fibers=",fibers) model_wave = h["WAVELENGTH"].data model_flux = h["FLUX"].data frames=[] for frame_filename in frame_filenames : frame = read_frame(frame_filename) selection=np.intersect1d(frame.fibermap["FIBER"],fibers) frame = frame[selection] frames.append(frame) for i,fiber in enumerate(fibers) : j=np.where(frame.fibermap['FIBER']==fiber)[0][0] print("fiber={}, i={}, j={}".format(fiber,i,j)) photsys = frame.fibermap['PHOTSYS'][j] filter_response=load_legacy_survey_filter("R",photsys) model_mag=filter_response.get_ab_magnitude(model_flux[i]*fluxunits,model_wave) fiber_mag=-2.5*np.log10(frame.fibermap['FLUX_R'][j])+22.5 print("model mag={:4.2f} fiber mag={:4.2f}".format(model_mag,fiber_mag)) a=0 for frame in frames : mflux = resample_flux(frame.wave,model_wave,model_flux[i]) rflux = frame.R[j].dot(mflux) plt.plot(frame.wave,frame.flux[j]) plt.plot(frame.wave,rflux,c="k",alpha=0.6) if a==0 : a=np.sum(frame.flux[j]*rflux)/np.sum(rflux**2) print("scale a={}".format(a)) plt.plot(frame.wave,rflux*a,c="gray",alpha=0.6) plt.show()

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2021-01-19T07:13:32.147420

2015-04-11T05:18:22

2015-04-11T05:20:01

33,696,924

0

null

UTF-8

Python

false

295

py

#!/usr/bin/env python3 MAX_VALUE = 4000000 # iterative fibonacci # this sequence starts with 1, 2, 3, 5... fib1 = 1 fib2 = 2 runningTotal = 0 while fib1 < MAX_VALUE: if fib1 % 2 == 0: runningTotal += fib1 fib3 = fib1 + fib2 fib1 = fib2 fib2 = fib3 print(runningTotal)

[ "BrianKlinect@gmail.com" ]

BrianKlinect@gmail.com

39cdc6f248a4a68259c53e7807d24f3070950075

788e202b4a9d33b419e0b32dc1aaf1325e5cc3db

/Lib/site-packages/pybitbucket/build.py

33ad6bf82c6deb3d5fe9ebcf3c6753465338addc

[]

no_license

DShaw14/supportal-web

a8de71042d5c277e7702fbfaf116070022e3aac7

152c8f8030a673791de2af50f92106c4752af6ed

refs/heads/master

2022-10-15T07:21:54.517723

2021-01-27T04:58:10

74,401,106

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2022-10-05T13:19:43

2016-11-21T20:03:15

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Python

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# -*- coding: utf-8 -*- """ Defines the BuildStatus resource and registers the type with the Client. Classes: - BuildStatusStates: enumerates the possible states of a build status - BuildStatus: represents the result of a build """ from uritemplate import expand from pybitbucket.bitbucket import Bitbucket, BitbucketBase, Client, enum BuildStatusStates = enum( 'BuildStatusStates', INPROGRESS='INPROGRESS', SUCCESSFUL='SUCCESSFUL', FAILED='FAILED') class BuildStatus(BitbucketBase): id_attribute = 'key' resource_type = 'build' @staticmethod def is_type(data): return (BuildStatus.has_v2_self_url(data)) @staticmethod def make_payload( key, state, url, name=None, description=None): BuildStatusStates.expect_valid_value(state) payload = { 'key': key, 'state': state, 'url': url, } # Since server defaults may change, method defaults are None. # If the parameters are not provided, then don't send them # so the server can decide what defaults to use. if name is not None: payload.update({'name': name}) if description is not None: payload.update({'description': description}) return payload @staticmethod def create_buildstatus( owner, repository_name, revision, key, state, url, name=None, description=None, client=Client()): template = ( '{+bitbucket_url}' + '/2.0/repositories{/owner,repository_name}' + '/commit{/revision}/statuses/build') # owner, repository_name, and revision are required api_url = expand( template, { 'bitbucket_url': client.get_bitbucket_url(), 'owner': owner, 'repository_name': repository_name, 'revision': revision }) payload = BuildStatus.make_payload( key=key, state=state, url=url, name=name, description=description) return BuildStatus.post(api_url, json=payload, client=client) """ A convenience method for changing the current build status. """ def modify( self, key=None, state=None, url=None, name=None, description=None): if (state is None): state = self.state if (key is None): key = self.key if (url is None): url = self.url if (name is None): name = self.name if (description is None): description = self.description payload = self.make_payload( state=state, key=key, name=name, url=url, description=description) return self.put(json=payload) """ A convenience method for finding a specific build status. In contrast to the pure hypermedia driven method on the Bitbucket class, this method returns a BuildStatus object, instead of the generator. """ @staticmethod def find_buildstatus_for_repository_commit_by_key( repository_name, revision, key, owner=None, client=Client()): if (owner is None): owner = client.get_username() return next( Bitbucket(client=client).repositoryCommitBuildStatusByKey( owner=owner, repository_name=repository_name, revision=revision, key=key)) """ A convenience method for finding build statuses for a repository's commit. The method is a generator BuildStatus objects. """ @staticmethod def find_buildstatuses_for_repository_commit( repository_name, revision, owner=None, client=Client()): if (owner is None): owner = client.get_username() return Bitbucket(client=client).repositoryCommitBuildStatuses( owner=owner, repository_name=repository_name, revision=revision) Client.bitbucket_types.add(BuildStatus)

[ "david14shaw@gmail.com" ]

david14shaw@gmail.com

0cbd04b6ef65ee08c9dc3e2028930c50f679cbb3

c800cba645625b24ff9b2e5fd75812f950f3aa2d

/main/migrations/0001_initial.py

33c4d1498022ccb09c506d1454b26d526450c953

[]

no_license

ZICCORP/booknow

0d68592b8604a89432da6b1d0c9733da72d967b4

7815471c03d503cdebeee5ba9e96cff2f62a4add

refs/heads/master

2022-12-13T05:21:25.688799

2020-09-12T01:24:26

290,068,154

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py

# Generated by Django 2.2 on 2020-09-03 15:30 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Product', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=32)), ('description', models.TextField(blank=True)), ('price', models.DecimalField(decimal_places=2, max_digits=6)), ('slug', models.SlugField(max_length=48)), ('active', models.BooleanField(default=True)), ('in_stock', models.BooleanField(default=True)), ('date_updated', models.DateTimeField(auto_now=True)), ], ), ]

[ "frankchuka250@gmail.com" ]

frankchuka250@gmail.com

4002df1f037029048dc4fdc1f9909bf1a602c0d6

4c0707c00eb437fe80cbae46ebcf90ae28690430

/experts/migrations/0027_auto__del_field_langue_nom__add_field_langue_nomlangue.py

a51fa413e427f4c5b84a94f66c553534a52537dd

[]

no_license

matnode/lesexpertsauf

4d2ea8c9a7348a825eeb648df6c11385425a608b

106b1982ac4b35015b91e4b9487c402a334ddae3

refs/heads/master

2021-01-02T22:32:34.014121

2015-09-29T11:34:03

42,111,156

0

null

UTF-8

Python

false

11,688

py

# -*- coding: utf-8 -*- from south.utils import datetime_utils as datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Deleting field 'Langue.nom' db.delete_column('experts_langue', 'nom') # Adding field 'Langue.nomlangue' db.add_column('experts_langue', 'nomlangue', self.gf('django.db.models.fields.CharField')(default=0, max_length=255), keep_default=False) def backwards(self, orm): # Adding field 'Langue.nom' db.add_column('experts_langue', 'nom', self.gf('django.db.models.fields.CharField')(default=0, max_length=255), keep_default=False) # Deleting field 'Langue.nomlangue' db.delete_column('experts_langue', 'nomlangue') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'experts.competence': { 'Meta': {'object_name': 'Competence'}, 'description': ('django.db.models.fields.TextField', [], {}), 'human': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Human']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'nom': ('django.db.models.fields.TextField', [], {}) }, 'experts.entreprise': { 'Meta': {'object_name': 'Entreprise'}, 'activite': ('django.db.models.fields.TextField', [], {}), 'adresse': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'codepostale': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'datedefondation': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'description': ('django.db.models.fields.TextField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'nom': ('django.db.models.fields.TextField', [], {}), 'photo': ('django.db.models.fields.files.ImageField', [], {'max_length': '100'}), 'siteweb': ('django.db.models.fields.TextField', [], {}), 'taille': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'telephone': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'}), 'ville': ('django.db.models.fields.CharField', [], {'max_length': '200'}) }, 'experts.formation': { 'Meta': {'object_name': 'Formation'}, 'datedebut': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'datefin': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'description': ('django.db.models.fields.TextField', [], {}), 'diplome': ('django.db.models.fields.TextField', [], {}), 'ecole': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'human': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Human']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'intitule': ('django.db.models.fields.TextField', [], {}), 'lieu': ('django.db.models.fields.CharField', [], {'max_length': '255'}) }, 'experts.human': { 'Meta': {'object_name': 'Human'}, 'adresse': ('django.db.models.fields.TextField', [], {}), 'civilite': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'codepostale': ('django.db.models.fields.TextField', [], {}), 'datecreation': ('django.db.models.fields.DateTimeField', [], {}), 'datenaissance': ('django.db.models.fields.TextField', [], {}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'niveauetude': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'nom': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'online': ('django.db.models.fields.IntegerField', [], {}), 'pays': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'photo': ('django.db.models.fields.files.ImageField', [], {'max_length': '100'}), 'prenom': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'signature': ('django.db.models.fields.TextField', [], {}), 'siteweb': ('django.db.models.fields.TextField', [], {}), 'telephone': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'}), 'ville': ('django.db.models.fields.CharField', [], {'max_length': '255'}) }, 'experts.langue': { 'Meta': {'object_name': 'Langue'}, 'human': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Human']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'niveau': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'nomlangue': ('django.db.models.fields.CharField', [], {'max_length': '255'}) }, 'experts.loisir': { 'Meta': {'object_name': 'Loisir'}, 'description': ('django.db.models.fields.TextField', [], {}), 'human': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Human']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'titre': ('django.db.models.fields.TextField', [], {}) }, 'experts.mission': { 'Meta': {'object_name': 'Mission'}, 'competence': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['experts.Competence']", 'symmetrical': 'False'}), 'competenceutilisee': ('django.db.models.fields.TextField', [], {}), 'datedebut': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'datefin': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'description': ('django.db.models.fields.TextField', [], {}), 'entreprise': ('django.db.models.fields.CharField', [], {'max_length': '255'}), 'fonction': ('django.db.models.fields.TextField', [], {}), 'human': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Human']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'titre': ('django.db.models.fields.TextField', [], {}) }, 'experts.offre': { 'Meta': {'object_name': 'Offre'}, 'contactoffre': ('django.db.models.fields.TextField', [], {}), 'datedebut': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'datefin': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'description': ('django.db.models.fields.TextField', [], {}), 'entreprise': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['experts.Entreprise']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'intitule': ('django.db.models.fields.TextField', [], {}), 'mission': ('django.db.models.fields.TextField', [], {}), 'reference': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'region': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'salairemax': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'salairemin': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'secteuractivite': ('django.db.models.fields.TextField', [], {}), 'typeoffre': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'ville': ('django.db.models.fields.CharField', [], {'max_length': '200'}) }, 'experts.typecompte': { 'Meta': {'object_name': 'Typecompte'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'typedecompte': ('django.db.models.fields.CharField', [], {'max_length': '200'}), 'user': ('django.db.models.fields.related.OneToOneField', [], {'to': "orm['auth.User']", 'unique': 'True'}) } } complete_apps = ['experts']

[ "martial.nodem@auf.org" ]

martial.nodem@auf.org

97fd972b1c27f2217820fd2196cd6048b8d568eb

abb3daa870fc818980af90893e197517b95467af

/DataCollection/eventbriteData.py

cec994bb110bd8558443457374bd3db244f47938

[]

no_license

souless94/main-1

9ecc19954ba7caa1e083f812faee8d2ce3219c21

2b95ab940c0f618e67087d80a7215d46800fe1ef

refs/heads/master

2020-05-07T12:25:23.815342

2019-06-04T04:00:25

179,941,599

0

null

2019-04-07T09:08:34

null

UTF-8

Python

false

3,283

py

# file to collect data from eventbrite from requests import get import os from datetime import datetime class EventbriteData: def __init__(self): # f = open(r"C:\Users\wen kai\Downloads\y4s2\event-advisor\DataCollection\token.txt","r") # credentials = f.read() # f.close() # txt_arr = credentials.split("\n") # self._token = txt_arr[0] self._token = os.environ.get('event-token') self._url = "https://www.eventbriteapi.com/v3/events/search" self.category_dict = {"Arts": "Performing & Visual Arts", "Business": "Business & Professional", "Charity": "Charity & Causes", "Culture": "Community & Culture", "Education": "Family & Education", "Family": "Family & Education", "Fashion": "Fashion & Beauty", "Film": "Film, Media & Entertainment", "Food": "Food & Drink", "Health": "Health & Wellness", "Hobbies": "Hobbies & Special Interest", "Music": "Music", "Outdoors": "Travel & Outdoor", "Religion": "Religion & Spirituality", "Tech": "Science & Technology", "Sports": "Sports & Fitness"} def getData(self,page,searchtxt): eventsearchtxt = self.category_dict.get(searchtxt) if (eventsearchtxt is not None): searchtxt = eventsearchtxt payload = {"q":searchtxt, "location.address":"singapore", "page":page, "sort_by": "date", "expand":"venue", "token":self._token} response = get(self._url,params=payload).json()["events"] return response def getEventName(self,items): names = [] for i in range(len(items)): name = "Eventbrite " + items[i].get("name").get("text") names.append(name) return names def getEventUrl(self,items): urls = [] for i in range(len(items)): url = items[i].get("url") urls.append(url) return urls def getEventlocation(self,items): eventLocations=[] for i in range(len(items)): eventLocation = items[i].get('venue').get('address') eventAddress = eventLocation.get('localized_address_display') eventLocations.append(eventAddress) return eventLocations def getEventTime(self,items): eventTimes=[] for i in range(len(items)): # Date & Start Time date_time = items[i].get("start")["local"].split("T") starttime = datetime.strptime(date_time[1],"%H:%M:%S") eventTimes.append(str(starttime)) return eventTimes def getEventDate(self,items): eventDates=[] for i in range(len(items)): # Date & Start Time date_time = items[i].get("start")["local"].split("T") date = datetime.strptime(date_time[0], "%Y-%m-%d") date = datetime.strftime(date,"%Y-%m-%d") eventDates.append(str(date)) return eventDates

[ "cl.wk@hotmail.com" ]

cl.wk@hotmail.com

cdefd2ad395a69ada95e1118b6ce8f7617d09066

acfab9011d276323ce4aa24075aee35f470c17b8

/13. Exceptions/99.2.IndexError.py

f2da757e4c9c5d3013194297b85368b872a98dc8

[]

no_license

Engi20/Python-Programming-for-Beginners

ad84d66a5ce9dd4e6ab23acde13f74607b87ead1

fa02fcd265f8d7145e554267435c7e73ed562e36

refs/heads/master

2022-06-07T05:56:17.326070

2020-05-02T17:41:20

null

0

null

UTF-8

Python

false

126

py

l = [10,20,30,40] #print(l[10]) #print(l) try: print(l[10]) except IndexError as e: print(e) print(l)

[ "noreply@github.com" ]

Engi20.noreply@github.com

6ad3be5505734d9c10992339771c730efc9c9099

3fbd28e72606e5358328bfe4b99eb0349ca6a54f

/.history/a_Young_Physicist_20210607192618.py

36507965512f61ea782fbecec4eb9fd7112b6c47

[]

no_license

Tarun1001/codeforces

f0a2ef618fbd45e3cdda3fa961e249248ca56fdb

576b505d4b8b8652a3f116f32d8d7cda4a6644a1

refs/heads/master

2023-05-13T04:50:01.780931

2021-06-07T21:35:26

374,399,423

0

null

UTF-8

Python

false

75

py

n= int(input()) x=[] for i in range(n): p=list(map(int,input().split())

[ "tarunsivasai8@gmail.com" ]

tarunsivasai8@gmail.com

abcbf44cdf9d64ce61f4ab61659e75a0b56b5847

83fe081b5ab66e63116774858bebd32a8e5f50ce

/resolution/harmonic.py

daf618fc0c9d0f8e0a1c603472afdcddae85006c

[]

no_license

dborzov/Light-in-Flight

d0ff638f0ea9aaade242d84d2d1c02d2898e3597

798627e4d98d5d5b66ecbc68bd665bc1263b98d9

refs/heads/master

2020-06-09T02:34:30.702774

2013-07-15T00:50:05

null

0

null

UTF-8

Python

false

899

py

import numpy as np import matplotlib.pyplot as plt def component(m): flips = [x/float(m) + 1./float(2.*m) for x in range(m)] flips.append(1.) return flips def l2(interval,m): sign = (-1.)**len([x for x in component(m) if interval[0] >= x]) inside = [x for x in component(m) if interval[0] < x and interval[1] > x] array = [interval[0]] + inside + [interval[1]] l2 = sign * sum([(-1)**i*(array[i+1]-x) for i,x in enumerate(array[:-1])]) return l2 INTERVAL = [0.07,0.3] fourier = [l2(INTERVAL,n) for n in range(1,100)] norma = np.abs(fourier[0]) significant = [i for i,x in enumerate(fourier) if np.abs(x) > 0.05*norma] threshold = max(significant) print threshold xx = [x for x, _ in enumerate(fourier)] print fourier plt.axhline(0, color='black', lw=2) plt.vlines(xx,[0],fourier) plt.vlines(threshold,-norma,norma,color='r') plt.savefig('fourier.png') plt.clf()

[ "tihoutrom@gmail.com" ]

tihoutrom@gmail.com

532e2122130f05f313aa1e7cd3a9aed542525cf1

f3d5a903c4dfb87b0a53d46c047a1cd39e147577

/colorplor.py

a153d33e0a57f2969cf4816f3b5d57d2b11517e1

[]

no_license

vishalgolcha/Computational-Physics

60b40272cb5265822bc4717adee1f0ddd0070217

dd9c97bc160cb4860cf63bb2fc078d66ac374713

refs/heads/master

2021-06-10T17:09:36.634995

2017-01-19T04:10:20

null

0

null

UTF-8

Python

false

641

py

import numpy as np import matplotlib # import matplotlib matplotlib.use('QT4Agg') import matplotlib.pyplot as plt H = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]) # added some commas and array creation code fig = plt.figure(figsize=(6, 3.2)) ax = fig.add_subplot(111) ax.set_title('colorMap') plt.imshow(H) ax.set_aspect('equal') cax = fig.add_axes([0.12, 0.1, 0.78, 0.8]) cax.get_xaxis().set_visible(False) cax.get_yaxis().set_visible(False) cax.patch.set_alpha(0) cax.set_frame_on(False) plt.colorbar(orientation='vertical') plt.show() plt.savefig("colorplot.png")

[ "vishalgolcha@hotmail.com" ]

vishalgolcha@hotmail.com

78b88ce44a1b69163f787739f2f16b29b7c3a456

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p02400/s247086956.py

5fa80293019ffc5a8ea215926eec8e94cb127c10

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

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import math r = float(input()) s = r * r * math.pi l = r * 2.0 * math.pi print("{:f} {:f}".format(s, l))

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

66529651+Aastha2104@users.noreply.github.com

9167ad416df88889048241c2117b86f525de23fb

f27d87c7039a978824251a2f8bbef7c3524f5e7b

/whole/lat.py

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[]

no_license

tonyre4/CSPmio

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4a037973bce2694f247914e872a51bf088a8472c

refs/heads/master

2022-05-20T02:26:40.817934

2020-03-19T00:40:23

242,209,893

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from pylatex import (Document, TikZ, TikZNode, TikZDraw, TikZCoordinate, NoEscape,TikZUserPath, TikZOptions) import pylatex as pl def cutReport(num_part,data): space = 0.8 s = "" s+= """\\begin{center}Reporte de cortes\\end{center}\\newline\\newline\bNumero de parte: %s\\hline\\hline\\newline\\newline""" %(num_part) for cut in data: s+= "x %d" % cut[0] for c in cut[1]: cc = c*space s+= """\\begin{tikzpicture} \\draw (0,0) rectangle (%f\\linewidth,1) node[pos=0.5] {Test}; \\end{tikzpicture}""" % cc s+="\\hline\\newline" doc = Document() doc.append(TikZ()) doc.append(pl.utils.NoEscape(s)) doc.generate_pdf('PDFexit', clean_tex=False) print (s) cutReport("6050",[[20,[0.5,0.1,0.1,0.2,0.15,0.15],[0.0,0.0]],[21,[0.1,0.1,0.1],[0.1,17.0]]])

[ "tonyre4@gmail.com" ]

tonyre4@gmail.com

e3f5ce740dabae5d2ac3f96257e4f3b50c6647a7

e7a88984a771e34f125fa9ba550bfd5ba47f2c13

/test/test.py

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[]

no_license

ljljlj23/flask

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refs/heads/master

2022-12-10T17:09:54.243851

2019-10-15T12:55:11

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2022-11-23T03:33:10

2019-10-13T07:37:39

CSS

UTF-8

Python

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py

def test(**kwargs): print(kwargs) def newfunc(**kwargs): test(**kwargs) newfunc(name='zhangsan',age=90)

[ "1074819863@qq.com" ]

1074819863@qq.com

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/2task5.py

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[]

no_license

LinJiaB00755804/inwk6312fall

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b3e8cd6f8f9e591227c506a51f5aa212474acf0a

refs/heads/master

2021-07-06T21:02:31.268074

2017-10-03T20:47:23

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import turtle def lt(t,s): t.lt(s) def polygon(t,l,n): for i in range(n): t.fd(l) lt(t,360/n) bob = turtle.Turtle() print(bob) polygon(bob,100,6) turtle.mainloop()

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LinJiaB00755804.noreply@github.com

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/binary_tree.py

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ryenumu2/Python-Database

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2022-11-30T15:32:57.011820

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from logic import LogicBase class BinaryTree(LogicBase): #the binary search tree implementation: child nodes to the left are smaller than their parent nodes and child nodes to the right are larger than their parent nodes #def __init__(self, node): # self._pathTo(node) = None def _get(self,node,key): #iterate through the binary search tree by comparing the passed in key with the node that the BST is currently on. while node != None: if key < node.key: node = self._pathTo(node.left_ref) elif node.key < key: node = self._pathTo(node.right_ref) else: return self._pathTo(node.value_ref) raise KeyError def _insert(self, node, key, value_ref): #recursively run this function definition to add a new node to the binary search tree if node == None: newest_node = BinaryNode()

[ "ryenumu2@ncsu.edu" ]

ryenumu2@ncsu.edu

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/deals/models.py

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no_license

Difroz/test

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refs/heads/main

2023-07-09T01:22:56.206728

2020-12-17T04:16:07

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from django.db import models, transaction import csv import io class Deal(models.Model): customer = models.CharField(max_length=200) item = models.CharField(max_length=200) total = models.DecimalField(max_digits=7, decimal_places=2) quantity = models.PositiveIntegerField() date = models.DateTimeField() def __str__(self): return self.customer @classmethod def upload_data(cls, csv_file): """ Загружает информацию из csv файла в БД """ file = csv_file.read().decode('utf-8') reader = csv.DictReader(io.StringIO(file)) data = [line for line in reader] with transaction.atomic(): for row in data: Deal.objects.get_or_create(**row) return data @classmethod def data_processing(cls, start_date=None, end_date=None): """ Обрабатывае загруженные в БД данные """ result_list = [] if start_date and end_date: data = Deal.objects.filter(models.Q(date__gte=start_date) & models.Q(date__lte=end_date)) else: data = Deal.objects.all() users = data.values('customer').annotate(spend_money=models.Sum('total')).order_by('-spend_money')[:5] gems_list = Deal.objects.values('item', 'customer').filter( customer__in=users.values_list('customer', flat=True)) gems = gems_list.values('item').annotate(unique_usr=models.Count('customer', distinct=True)).filter( unique_usr__gte=2) for i in users: user_dict = {} user_dict['username'] = i['customer'] user_dict['spend_money'] = i['spend_money'] gem = gems_list.values('item').filter(models.Q(item__in=gems.values('item')) & models.Q(customer=i['customer'])).distinct() user_dict['gems'] = list(gem.values_list('item', flat=True)) result_list.append(user_dict) return result_list

[ "proger@company.com" ]

proger@company.com

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xxbeam/leetcode-python

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refs/heads/master

2023-07-17T23:33:08.783011

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# 236. 二叉树的最近公共祖先 # Definition for a binary tree node. class TreeNode: def __init__(self, x): self.val = x self.left = None self.right = None class Solution: def lowestCommonAncestor(self, root: 'TreeNode', p: 'TreeNode', q: 'TreeNode') -> 'TreeNode': if p == q: return p node_map = {} queue = [root] p_flag = False q_flag = False while queue: temp = [] for node in queue: if node == p: p_flag = True if node == q: q_flag = True if p_flag and q_flag: break if node.left: node_map[node.left] = node temp.append(node.left) if node.right: node_map[node.right] = node temp.append(node.right) queue = temp visit = set() while q: visit.add(q) if q in node_map: q = node_map[q] else: q = None while p: if p in visit: return p if p in node_map: p = node_map[p] else: p = None return None

[ "xiongxin@songxiaocai.com" ]

xiongxin@songxiaocai.com

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pablo14simon/pablo-simon-P0

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2023-07-17T23:12:40.652225

2021-09-03T23:40:54

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import matplotlib.pyplot as plt arch1 = open("Caso B.1 con float64 (double).txt", "r") arch2 = open("Caso B.2 con float64 (double).txt", "r") arch3 = open("Caso B.3 con float64 (double).txt", "r") arch4 = open("Caso B.4 con float64 (double).txt", "r") arch5 = open("Caso B.5 con float64 (double).txt", "r") arch6 = open("Caso B.6 con float64 (double).txt", "r") arch6 = open("Caso B.6 con float64 (double).txt", "r") arch7 = open("Caso B.7 con float64 (double).txt", "r") arch8 = open("Caso B.8 con float64 (double).txt", "r") arch9 = open("Caso B.9 con float64 (double).txt", "r") mat1 = arch1.read() mat1 = mat1.split("\n") mat1.pop(0) mat1.pop(-1) x=0 uno=0 un=0 e=0 tiempo1 = [] tamaño1 = [] prom1 =[] M = int(len(mat1)/2) for d in mat1: l=d.split() tiempo1.append(float(l[0])) tamaño1.append(float(l[1])) x+=1 while uno<len(tiempo1): while e<len(mat1): un+=tiempo1[e] e+=M prom1.append(un/10) e+=1 uno+=10 arch1.close() mat2 = arch2.read() mat2 = mat2.split("\n") mat2.pop(0) mat2.pop(-1) x=0 tiempo2 = [] tamaño2 = [] prom=[] M = int(len(mat2)/2) for d in mat2: l=d.split() tiempo2.append(float(l[0])) tamaño2.append(float(l[1])) prom.append((float(l[0]))/10) x+=1 arch2.close() mat3 = arch3.read() mat3 = mat3.split("\n") mat3.pop(0) mat3.pop(-1) x=0 tiempo3 = [] tamaño3 = [] prom3=[] M = int(len(mat3)/2) for d in mat2: l=d.split() tiempo3.append(float(l[0])) tamaño3.append(float(l[1])) prom3.append((float(l[0]))/10) x+=1 arch3.close() mat4 = arch4.read() mat4 = mat4.split("\n") mat4.pop(0) mat4.pop(-1) x=0 uno=0 un=0 e=0 tiempo4 = [] tamaño4 = [] prom4 =[] M = int(len(mat4)/2) for d in mat4: l=d.split() tiempo1.append(float(l[0])) tamaño1.append(float(l[1])) x+=1 while uno<len(tiempo4): while e<len(mat4): un+=tiempo4[e] e+=M prom4.append(un/10) e+=1 uno+=10 arch4.close() mat5 = arch5.read() mat5 = mat5.split("\n") mat5.pop(0) mat5.pop(-1) x=0 uno=0 un=0 e=0 tiempo5 = [] tamaño5 = [] prom5 =[] M = int(len(mat5)/2) for d in mat5: l=d.split() tiempo5.append(float(l[0])) tamaño5.append(float(l[1])) x+=1 while uno<len(tiempo5): while e<len(mat5): un+=tiempo5[e] e+=M prom5.append(un/10) e+=1 uno+=10 arch5.close() mat6 = arch6.read() mat6 = mat6.split("\n") mat6.pop(0) mat6.pop(-1) x=0 uno=0 un=0 e=0 tiempo6 = [] tamaño6 = [] prom6 =[] M = int(len(mat6)/2) for d in mat6: l=d.split() tiempo6.append(float(l[0])) tamaño6.append(float(l[1])) x+=1 while uno<len(tiempo6): while e<len(mat6): un+=tiempo6[e] e+=M prom6.append(un/10) e+=1 uno+=10 arch6.close() mat7 = arch7.read() mat7 = mat7.split("\n") mat7.pop(0) mat7.pop(-1) x=0 uno=0 un=0 e=0 tiempo7 = [] tamaño7 = [] prom7 =[] M = int(len(mat7)/2) for d in mat7: l=d.split() tiempo7.append(float(l[0])) tamaño7.append(float(l[1])) x+=1 while uno<len(tiempo7): while e<len(mat7): un+=tiempo1[e] e+=M prom7.append(un/10) e+=1 uno+=10 arch7.close() mat8 = arch8.read() mat8 = mat8.split("\n") mat8.pop(0) mat8.pop(-1) x=0 uno=0 un=0 e=0 tiempo8 = [] tamaño8 = [] prom8 =[] M = int(len(mat8)/2) for d in mat8: l=d.split() tiempo8.append(float(l[0])) tamaño8.append(float(l[1])) x+=1 while uno<len(tiempo8): while e<len(mat8): un+=tiempo1[e] e+=M prom8.append(un/10) e+=1 uno+=10 arch8.close() mat9 = arch9.read() mat9 = mat9.split("\n") mat9.pop(0) mat9.pop(-1) x=0 uno=0 un=0 e=0 tiempo9 = [] tamaño9 = [] prom9 =[] M = int(len(mat9)/2) for d in mat9: l=d.split() tiempo9.append(float(l[0])) tamaño9.append(float(l[1])) x+=1 while uno<len(tiempo9): while e<len(mat9): un+=tiempo1[e] e+=M prom9.append(un/10) e+=1 uno+=10 arch9.close() x1 = ["10","20","50","100","200","500","1000","2000","5000","10000","20000"] T1 = [10,20,50,100,200,500,1000,2000,5000,10000,20000] y1 = ["0.1 ms", "1 ms", "10 ms","0.1 s", "1 s", "10 s", "1 min", "10 min"] dt1 = [0.1/1000,1/1000,10/1000,0.1,1,10,60,60*10] y2 = ["1 KB", "10KB", "100 KB", "1 MB", "10 MB", "100 MB", "1 GB", "10 GB"] m1 = [1*10**3,10*10**3,100*10**3,1*10**6,10*10**6,100*10**6,1*10**9,10*10**9] plt.figure(1) plt.subplot(2,1,1) plt.title("Rendimiento B todos los casos double") i=0 j=0 while i < 10: while j < len(mat1): plt.loglog(tamaño1[j:j+22],tiempo1[0:22], "o-") plt.loglog(tamaño2[0:22],tiempo2[0:22], "o-") plt.loglog(tamaño3[0:22],tiempo3[0:22], "o-") plt.loglog(tamaño4[j:j+22],tiempo4[0:22], "o-") plt.loglog(tamaño5[0:22],tiempo5[0:22], "o-") plt.loglog(tamaño6[0:22],tiempo6[0:22], "o-") plt.loglog(tamaño7[0:22],tiempo7[0:22], "o-") plt.loglog(tamaño8[0:22],tiempo8[0:22], "o-") plt.loglog(tamaño9[0:22],tiempo9[0:22], "o-") j+=M i+=1 plt.yticks(dt1, y1) plt.xticks(T1, x1, rotation=45) plt.xticks(T1, ["","","","","","","","","",""]) plt.xlim(right=20000) plt.grid() plt.ylabel("Tiempo transcurrido (s)") plt.xlabel("Tamaño matriz M") plt.savefig("Redimiento de inversion") plt.show()

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PaddlePaddle/PaddleTest

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#!/bin/env python # -*- coding: utf-8 -*- # encoding=utf-8 vi:ts=4:sw=4:expandtab:ft=python """ test jit cases """ import os import sys sys.path.append(os.path.abspath(os.path.dirname(os.getcwd()))) sys.path.append(os.path.join(os.path.abspath(os.path.dirname(os.getcwd())), "utils")) from utils.yaml_loader import YamlLoader from jittrans import JitTrans yaml_path = os.path.join(os.path.abspath(os.path.dirname(os.getcwd())), "yaml", "nn.yml") yml = YamlLoader(yaml_path) def test_Linear_base(): """test Linear_base""" jit_case = JitTrans(case=yml.get_case_info("Linear_base")) jit_case.jit_run()

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knosk/knosk-core

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refs/heads/master

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py

from knosk.choosers import * from knosk.core import * from knosk.fields import * from knosk.matchers import * from knosk.suggesters import *

[ "makcimkos@gmail.com" ]

makcimkos@gmail.com

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backwardn/dvc

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2020-09-13T16:50:22.918981

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import getpass import os from subprocess import CalledProcessError, check_output import pytest from funcy import cached_property from dvc.utils import env2bool from .base import Base from .local import Local TEST_SSH_USER = "user" TEST_SSH_KEY_PATH = os.path.join( os.path.abspath(os.path.dirname(__file__)), f"{TEST_SSH_USER}.key" ) class SSH: @staticmethod def should_test(): do_test = env2bool("DVC_TEST_SSH", undefined=None) if do_test is not None: return do_test # FIXME: enable on windows if os.name == "nt": return False try: check_output(["ssh", "-o", "BatchMode=yes", "127.0.0.1", "ls"]) except (CalledProcessError, OSError): return False return True @staticmethod def get_url(): return "ssh://{}@127.0.0.1:22{}".format( getpass.getuser(), Local.get_storagepath() ) class SSHMocked(Base): @staticmethod def get_url(user, port): path = Local.get_storagepath() if os.name == "nt": # NOTE: On Windows Local.get_storagepath() will return an # ntpath that looks something like `C:\some\path`, which is not # compatible with SFTP paths [1], so we need to convert it to # a proper posixpath. # To do that, we should construct a posixpath that would be # relative to the server's root. # In our case our ssh server is running with `c:/` as a root, # and our URL format requires absolute paths, so the # resulting path would look like `/some/path`. # # [1]https://tools.ietf.org/html/draft-ietf-secsh-filexfer-13#section-6 drive, path = os.path.splitdrive(path) assert drive.lower() == "c:" path = path.replace("\\", "/") url = f"ssh://{user}@127.0.0.1:{port}{path}" return url def __init__(self, server): self.server = server @cached_property def url(self): return self.get_url(TEST_SSH_USER, self.server.port) @cached_property def config(self): return { "url": self.url, "keyfile": TEST_SSH_KEY_PATH, } @pytest.fixture def ssh_server(): import mockssh users = {TEST_SSH_USER: TEST_SSH_KEY_PATH} with mockssh.Server(users) as s: yield s @pytest.fixture def ssh_connection(ssh_server): from dvc.remote.ssh.connection import SSHConnection yield SSHConnection( host=ssh_server.host, port=ssh_server.port, username=TEST_SSH_USER, key_filename=TEST_SSH_KEY_PATH, ) @pytest.fixture def ssh(ssh_server, monkeypatch): from dvc.remote.ssh import SSHRemoteTree # NOTE: see http://github.com/iterative/dvc/pull/3501 monkeypatch.setattr(SSHRemoteTree, "CAN_TRAVERSE", False) return SSHMocked(ssh_server) @pytest.fixture def ssh_remote(tmp_dir, dvc, ssh): tmp_dir.add_remote(config=ssh.config) yield ssh

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backwardn.noreply@github.com

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balasaajay/python_ops_automation

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#! /usr/bin/env python # -*- coding: utf-8 -*- # syntax check for an ansible yaml import yaml import sys try: playbook = yaml.load(open('/path/to/playbook.yml','r')) # Update with path to your playbook except: print "Error loading the ansible-playbook, must be a yaml syntax problem" sys.exit(1) else: print "YAML syntax looks good."

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ajaybre1987@gmail.com

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no_license

ssandylin/JerryHW

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py

from django.db import models class person(models.Model): name = models.CharField(max_length=10) birthday = models.CharField(max_length=10) is_girl = models.BooleanField(default=0) def __str__(self): return self.name # Create your models here.

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/DC/main.py

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refs/heads/master

2021-05-11T11:33:55.246035

2018-01-16T06:20:28

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# -*- coding:utf-8 -*- import os import urlparse from methods import google_ from methods import see_page import sys reload(sys) sys.setdefaultencoding("utf-8" ) class DC_Main(object): def __init__(self, url): self.url = url self.keyword = [] self.google = ['inurl:', 'site:'] def get_Keyword(self): file = open('keyword.txt', 'r') key = file.readlines() for k in key: k = k.replace('\n', '') if k == '': continue self.keyword.append(k) def run(self): self.get_Keyword() e_main = '' print u'====== 检测网站 ======' print 'url: %s' % self.url try: obj = see_page.See_MainPage(self.url, self.keyword) reason = obj.run() except IOError, e: e_main = e.message print '_______________________' try: obj = google_.Google(self.url, self.google, self.keyword) print u'== google搜索暗链地址 ==' dc = obj.run() if e_main == '': if len(dc) == 0 and reason == False: file = open('output/no.txt', 'a+') file.write(self.url + '\n') file.close() elif len(dc) !=0 and reason == False: file = open('output/' + urlparse.urlparse(self.url).netloc + '.txt', 'a+') file.write(u"主页未发现暗链" + '\n') file.write("________________________________" + '\n') for x in dc: file.write(x + '\n') file.close() else: file = open('output/' + urlparse.urlparse(self.url).netloc + '.txt', 'a+') file.write("________________________________" + '\n') for x in dc: file.write(x + '\n') file.close() else: if len(dc) != 0: file = open('output/' + urlparse.urlparse(self.url).netloc + '.txt', 'a+') file.write(u"主页连接失败, 原因: %s" % e_main + '\n') file.write("________________________________" + '\n') for x in dc: file.write(x + '\n') file.close() else: file = open('output/no.txt', 'a+') file.write(self.url + '\n') file.close() print '_______________________' except IOError, e: e_google = e.message print e_google if __name__ == "__main__": file = open('url.txt', 'r') for url in file.readlines(): url = url.replace('\n', '') if url == '': continue url_parser = urlparse.urlparse(url) if url_parser.scheme != '': url = url_parser.netloc if os.path.exists('output/' + url + '.txt'): file = open('output/' + url + '.txt', 'w') file.write('') file.close() url_parser = urlparse.urlparse(url) if url_parser.scheme == '': url = 'http://' + url DC_Main(url).run() file.close()

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/scripts/speech_recognition/confidence/benchmark_asr_confidence.py

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[ "Apache-2.0" ]

permissive

NVIDIA/NeMo

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refs/heads/main

2023-08-21T15:28:04.447838

2023-08-21T00:49:36

200,722,670

7,957

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Apache-2.0

2023-09-14T18:49:54

2019-08-05T20:16:42

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# Copyright (c) 2022, 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 json import os from dataclasses import dataclass, is_dataclass from pathlib import Path from typing import Optional import pytorch_lightning as pl import torch from omegaconf import MISSING, OmegaConf from sklearn.model_selection import ParameterGrid from nemo.collections.asr.metrics.rnnt_wer import RNNTDecodingConfig from nemo.collections.asr.metrics.wer import CTCDecodingConfig from nemo.collections.asr.models import ASRModel, EncDecRNNTModel from nemo.collections.asr.parts.utils.asr_confidence_benchmarking_utils import ( apply_confidence_parameters, run_confidence_benchmark, ) from nemo.collections.asr.parts.utils.asr_confidence_utils import ConfidenceConfig from nemo.core.config import hydra_runner from nemo.utils import logging """ Get confidence metrics and curve plots for a given model, dataset, and confidence parameters. # Arguments model_path: Path to .nemo ASR checkpoint pretrained_name: Name of pretrained ASR model (from NGC registry) dataset_manifest: Path to dataset JSON manifest file (in NeMo format) output_dir: Output directory to store a report and curve plot directories batch_size: batch size during inference num_workers: number of workers during inference cuda: Optional int to enable or disable execution of model on certain CUDA device amp: Bool to decide if Automatic Mixed Precision should be used during inference audio_type: Str filetype of the audio. Supported = wav, flac, mp3 target_level: Word- or token-level confidence. Supported = word, token, auto (for computing both word and token) confidence_cfg: Config with confidence parameters grid_params: Dictionary with lists of parameters to iteratively benchmark on # Usage ASR model can be specified by either "model_path" or "pretrained_name". Data for transcription are defined with "dataset_manifest". Results are returned as a benchmark report and curve plots. python benchmark_asr_confidence.py \ model_path=null \ pretrained_name=null \ dataset_manifest="" \ output_dir="" \ batch_size=64 \ num_workers=8 \ cuda=0 \ amp=True \ target_level="word" \ confidence_cfg.exclude_blank=False \ 'grid_params="{\"aggregation\": [\"min\", \"prod\"], \"alpha\": [0.33, 0.5]}"' """ def get_experiment_params(cfg): """Get experiment parameters from a confidence config and generate the experiment name. Returns: List of experiment parameters. String with the experiment name. """ blank = "no_blank" if cfg.exclude_blank else "blank" aggregation = cfg.aggregation method_name = cfg.measure_cfg.name alpha = cfg.measure_cfg.alpha if method_name == "entropy": entropy_type = cfg.measure_cfg.entropy_type entropy_norm = cfg.measure_cfg.entropy_norm experiment_param_list = [ aggregation, str(cfg.exclude_blank), method_name, entropy_type, entropy_norm, str(alpha), ] experiment_str = "-".join([aggregation, blank, method_name, entropy_type, entropy_norm, str(alpha)]) else: experiment_param_list = [aggregation, str(cfg.exclude_blank), method_name, "-", "-", str(alpha)] experiment_str = "-".join([aggregation, blank, method_name, str(alpha)]) return experiment_param_list, experiment_str @dataclass class ConfidenceBenchmarkingConfig: # Required configs model_path: Optional[str] = None # Path to a .nemo file pretrained_name: Optional[str] = None # Name of a pretrained model dataset_manifest: str = MISSING output_dir: str = MISSING # General configs batch_size: int = 32 num_workers: int = 4 # Set `cuda` to int to define CUDA device. If 'None', will look for CUDA # device anyway, and do inference on CPU only if CUDA device is not found. # If `cuda` is a negative number, inference will be on CPU only. cuda: Optional[int] = None amp: bool = False audio_type: str = "wav" # Confidence configs target_level: str = "auto" # Choices: "word", "token", "auto" (for both word- and token-level confidence) confidence_cfg: ConfidenceConfig = ConfidenceConfig(preserve_word_confidence=True, preserve_token_confidence=True) grid_params: Optional[str] = None # a dictionary with lists of parameters to iteratively benchmark on @hydra_runner(config_name="ConfidenceBenchmarkingConfig", schema=ConfidenceBenchmarkingConfig) def main(cfg: ConfidenceBenchmarkingConfig): torch.set_grad_enabled(False) logging.info(f'Hydra config: {OmegaConf.to_yaml(cfg)}') if is_dataclass(cfg): cfg = OmegaConf.structured(cfg) if cfg.model_path is None and cfg.pretrained_name is None: raise ValueError("Both cfg.model_path and cfg.pretrained_name cannot be None!") # setup GPU if cfg.cuda is None: if torch.cuda.is_available(): device = [0] # use 0th CUDA device accelerator = 'gpu' else: device = 1 accelerator = 'cpu' else: device = [cfg.cuda] accelerator = 'gpu' map_location = torch.device('cuda:{}'.format(device[0]) if accelerator == 'gpu' else 'cpu') # setup model if cfg.model_path is not None: # restore model from .nemo file path model_cfg = ASRModel.restore_from(restore_path=cfg.model_path, return_config=True) classpath = model_cfg.target # original class path imported_class = model_utils.import_class_by_path(classpath) # type: ASRModel logging.info(f"Restoring model : {imported_class.__name__}") asr_model = imported_class.restore_from( restore_path=cfg.model_path, map_location=map_location ) # type: ASRModel else: # restore model by name asr_model = ASRModel.from_pretrained( model_name=cfg.pretrained_name, map_location=map_location ) # type: ASRModel trainer = pl.Trainer(devices=device, accelerator=accelerator) asr_model.set_trainer(trainer) asr_model = asr_model.eval() # Check if ctc or rnnt model is_rnnt = isinstance(asr_model, EncDecRNNTModel) # Check that the model has the `change_decoding_strategy` method if not hasattr(asr_model, 'change_decoding_strategy'): raise RuntimeError("The asr_model you are using must have the `change_decoding_strategy` method.") # get filenames and reference texts from manifest filepaths = [] reference_texts = [] if os.stat(cfg.dataset_manifest).st_size == 0: logging.error(f"The input dataset_manifest {cfg.dataset_manifest} is empty. Exiting!") return None manifest_dir = Path(cfg.dataset_manifest).parent with open(cfg.dataset_manifest, 'r') as f: for line in f: item = json.loads(line) audio_file = Path(item['audio_filepath']) if not audio_file.is_file() and not audio_file.is_absolute(): audio_file = manifest_dir / audio_file filepaths.append(str(audio_file.absolute())) reference_texts.append(item['text']) # setup AMP (optional) autocast = None if cfg.amp and torch.cuda.is_available() and hasattr(torch.cuda, 'amp') and hasattr(torch.cuda.amp, 'autocast'): logging.info("AMP enabled!\n") autocast = torch.cuda.amp.autocast # do grid-based benchmarking if grid_params is provided, otherwise a regular one work_dir = Path(cfg.output_dir) os.makedirs(work_dir, exist_ok=True) report_legend = ( ",".join( [ "model_type", "aggregation", "blank", "method_name", "entropy_type", "entropy_norm", "alpha", "target_level", "auc_roc", "auc_pr", "auc_nt", "nce", "ece", "auc_yc", "std_yc", "max_yc", ] ) + "\n" ) model_typename = "RNNT" if is_rnnt else "CTC" report_file = work_dir / Path("report.csv") if cfg.grid_params: asr_model.change_decoding_strategy( RNNTDecodingConfig(fused_batch_size=-1, strategy="greedy_batch", confidence_cfg=cfg.confidence_cfg) if is_rnnt else CTCDecodingConfig(confidence_cfg=cfg.confidence_cfg) ) params = json.loads(cfg.grid_params) hp_grid = ParameterGrid(params) hp_grid = list(hp_grid) logging.info(f"==============================Running a benchmarking with grid search=========================") logging.info(f"Grid search size: {len(hp_grid)}") logging.info(f"Results will be written to:\nreport file `{report_file}`\nand plot directories near the file") logging.info(f"==============================================================================================") with open(report_file, "tw", encoding="utf-8") as f: f.write(report_legend) f.flush() for i, hp in enumerate(hp_grid): logging.info(f"Run # {i + 1}, grid: `{hp}`") asr_model.change_decoding_strategy(apply_confidence_parameters(asr_model.cfg.decoding, hp)) param_list, experiment_name = get_experiment_params(asr_model.cfg.decoding.confidence_cfg) plot_dir = work_dir / Path(experiment_name) results = run_confidence_benchmark( asr_model, cfg.target_level, filepaths, reference_texts, cfg.batch_size, cfg.num_workers, plot_dir, autocast, ) for level, result in results.items(): f.write(f"{model_typename},{','.join(param_list)},{level},{','.join([str(r) for r in result])}\n") f.flush() else: asr_model.change_decoding_strategy( RNNTDecodingConfig(fused_batch_size=-1, strategy="greedy_batch", confidence_cfg=cfg.confidence_cfg) if is_rnnt else CTCDecodingConfig(confidence_cfg=cfg.confidence_cfg) ) param_list, experiment_name = get_experiment_params(asr_model.cfg.decoding.confidence_cfg) plot_dir = work_dir / Path(experiment_name) logging.info(f"==============================Running a single benchmarking===================================") logging.info(f"Results will be written to:\nreport file `{report_file}`\nand plot directory `{plot_dir}`") with open(report_file, "tw", encoding="utf-8") as f: f.write(report_legend) f.flush() results = run_confidence_benchmark( asr_model, cfg.batch_size, cfg.num_workers, cfg.target_level, filepaths, reference_texts, plot_dir, autocast, ) for level, result in results.items(): f.write(f"{model_typename},{','.join(param_list)},{level},{','.join([str(r) for r in result])}\n") logging.info(f"===========================================Done===============================================") if __name__ == '__main__': main()

[ "noreply@github.com" ]

NVIDIA.noreply@github.com

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/python_fundemental/80_Consecutive_Numbers_Sum.py

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[]

no_license

Deanwinger/python_project

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8c0c2a8bcd51825e6902e4d03dabbaf6f303ba83

refs/heads/master

2022-07-10T16:41:56.853165

2019-07-21T13:08:48

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0

null

UTF-8

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false

39

py

# leetcode 829. Consecutive Numbers Sum

[ "a541203951@163.com" ]

a541203951@163.com

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/data_pre-processing.py

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[]

no_license

anondo1969/baseline-emotion-recognizer

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f53acdc5b5c79a3b989a9ebfbb27fe83b8df87a8

refs/heads/master

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#===================================================================================== #this script will eliminate the unwanted portions of feature file- #generated by OpenSmile and store them in Numpy array formatted text files. # Written by Mahbub Ul Alam #===================================================================================== #!/usr/bin/python import os import sys #location of the feature file generated from openSmile. #if you are using newer version of python then please use "input" instead of "raw_input" . file_path = raw_input("Enter OpenSmile generated Feature containing CSV File location: ") #if K-fold cross-validation is needed to be performed on data #then please select All (A). data_type = raw_input("Enter output Data Type, T for Training, D for Development, A for All: ") # processed data will be saved in text files. if(data_type=="T"): output_file_name = open("training_data.txt",'w') print("Data will be generated shortly, please check training_data.txt") elif(data_type=="D"): output_file_name = open("development_data.txt",'w') print("Data will be generated shortly, please check development_data.txt file") else: output_file_name = open("processed_data.txt",'w') print("Data will be generated shortly, please check processed_data.txt file") sys.stdout = output_file_name #data will be saved in Numpy array format input_file = open(file_path) count=-1 token=-1 for line in input_file.read().split('\n'): count=-1 token=-1 if(line!='') : if(line[0]!='@'): for value in line.split(","): count+=1 if(count==0): for word in value.split("_"): token+=1 if(token==0): break break; line = line.replace(value,word) line = line.replace('\'','') line = line.replace(",?",'') print (line)

[ "alammb@ims.uni-stuttgart.de" ]

alammb@ims.uni-stuttgart.de

ace9b59b193f5bf5eee08edf92be7370d22caaa6

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/Practice/Interview/6.从尾到头打印链表.py

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[]

no_license

ICESDHR/Bear-and-Pig

c1153345c13ec52f0b000acccede773ad2421ad4

2fb98240258de285b43eae92c187bf36372c9668

refs/heads/master

2022-03-06T09:35:35.164032

2022-02-24T08:49:23

127,283,094

1

null

UTF-8

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py

# -*- coding:utf-8 -*- class ListNode: def __init__(self, x): self.val = x self.next = None def PrintListFromTailToHead(listNode): if listNode != None: temp = [listNode.val] nodes = listNode else: return [] while nodes.next != None: temp.append(nodes.next.val) nodes = nodes.next return temp[::-1] # 使用递归 def PrintListFromTailToHead2(listNode): if listNode != None: return PrintListFromTailToHead2(listNode.next)+[listNode.val] else: return [] if __name__ == '__main__': listNode = ListNode(5) listNode.next = ListNode(7) ans = PrintListFromTailToHead2(listNode) print(ans)

[ "smilewangyizhe@163.com" ]

smilewangyizhe@163.com

bdad26231a915897f8611a7c72d2e4aad1eaed8a

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/App.py + csvfiles/app.py

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[]

no_license

cageofan21/sqlalchemy-challenge

6c4a9c764d589a52278d77f59dc45a9f2b9190f7

f3313f8055d2fdd909b48a9c1f87ff776d387ace

refs/heads/master

2020-12-28T13:57:28.520671

2020-04-09T07:59:49

238,359,600

0

null

UTF-8

Python

false

4,109

py

import numpy as np import pandas as pd import datetime as dt import sqlalchemy from sqlalchemy.ext.automap import automap_base from sqlalchemy.orm import Session from sqlalchemy import create_engine, func from flask import Flask, jsonify ################################################# # Database Setup ################################################# engine = create_engine("sqlite:///Hawaii.sqlite") # reflect an existing database into a new model Base = automap_base() # reflect the tables Base.prepare(engine, reflect=True) # Save reference to the table station = Base.classes.station measurement = Base.classes.measurement ########################################## # Flask Setup ########################################## session = Session(engine) app = Flask(__name__) ########################################## # Flask Routes ########################################## @app.route("/") def welcome(): """List all available api routes.""" return ( f"Available Routes: " f"/api/v1.0/precipitation " f"/api/v1.0/stations " f"/api/v1.0/tobs " f"/api/v1.0/start " f"/api/v1.0/start-end" ) @app.route("/api/v1.0/precipitation") def precipitation(): # Create our session (link) from Python to the DB session = Session(engine) last_12months = (dt.date(2017, 8, 23)) - (dt.timedelta(days=365)) lastyr_precip = session.query(measurement.date, func.avg(measurement.prcp)).\ filter(measurement.date >= last_12months).\ group_by(measurement.date).all() all_precip = [] for date, prcp in lastyr_precip: rain_dict = {} rain_dict["date"] = date rain_dict["prcp"] = prcp all_precip.append(rain_dict) return jsonify(all_precip) @app.route("/api/v1.0/stations") def stations(): station = Base.classes.station # Create our session (link) from Python to the DB session = Session(engine) results = session.query(station.station, station.name).all() stations_list = [] for station, name in results: stations_dict = {} stations_dict["station"] = station stations_dict["name"] = name stations_list.append(stations_dict) return jsonify(stations_list) @app.route("/api/v1.0/tobs") def tobs(): # Create our session (link) from Python to the DB session = Session(engine) last_12months = (dt.date(2017, 8, 23)) - (dt.timedelta(days=365)) tobs_observ = session.query(measurement.date, measurement.tobs).\ filter(measurement.date >= last_12months).\ group_by(measurement.date).all() tobs_list = [] for date, tobs in tobs_observ: tobs_dict = {} tobs_dict["date"] = date tobs_dict["tobs"] = tobs tobs_list.append(tobs_dict) return jsonify(tobs_list) @app.route("/api/v1.0/start") def temp (start = "2016-08-23"): # Create our session (link) from Python to the DB session = Session(engine) # Given start date, to calculate all dates greater than and equal to the start date. start = "2016-08-23" temp_start = session.query(measurement.date, func.min(measurement.tobs), func.avg(measurement.tobs), func.max(measurement.tobs)).\ filter(measurement.date >= start).group_by(measurement.date).all() tempstart_list=list(temp_start) return jsonify(tempstart_list) @app.route("/api/v1.0/start-end") def tempend(start = "2016-08-23", end = "2017-08-23"): # Create our session (link) from Python to the DB session = Session(engine) # Given start date, to calculate for dates between the start and end date inclusive. start = "2016-08-23" end = "2017-08-23" temp_start1 = session.query(measurement.date, func.min(measurement.tobs), func.avg(measurement.tobs), func.max(measurement.tobs)).\ filter(measurement.date >= start).filter(measurement.date <= end).group_by(measurement.date).all() tempstart_list1=list(temp_start1) return jsonify(tempstart_list1) if __name__ == '__main__': app.run(debug=True)

[ "adib.cena@gmail.com" ]

adib.cena@gmail.com

093b920439e7837b4a8f668ec9e2bfda1feeb331

12ce225916bbee1c4fc83104478a695a9afc8b4f

/user/migrations/0001_initial.py

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[]

no_license

suman-kr/prism

4985711edbd7f178663e7de8034c13f378777034

7b731304bd1a441c29d87edb0944e95026e125a1

refs/heads/master

2022-12-21T21:37:56.697211

2020-09-25T08:58:28

298,069,027

1

0

null

UTF-8

Python

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1,724

py

# Generated by Django 3.1.1 on 2020-09-21 15:15 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('email', models.EmailField(max_length=255, unique=True, verbose_name='email address')), ('first_name', models.CharField(max_length=50)), ('last_name', models.CharField(max_length=50)), ('contact', models.CharField(max_length=50, verbose_name='Phone Number')), ('h_no', models.CharField(max_length=50, verbose_name='House/Flat No')), ('street_one', models.CharField(blank=True, max_length=50, null=True)), ('street_two', models.CharField(blank=True, max_length=50, null=True)), ('city', models.CharField(max_length=50)), ('state', models.CharField(max_length=50)), ('pin', models.CharField(max_length=50, verbose_name='Pincode')), ('roles', models.CharField(choices=[('ADV', 'Advertiser'), ('PTR', 'Partner')], max_length=3)), ('is_active', models.BooleanField(default=True)), ('is_admin', models.BooleanField(default=False)), ], options={ 'abstract': False, }, ), ]

[ "skcool.123bgp@gmail.com" ]

skcool.123bgp@gmail.com

acb4d49de13e8c5b8f71ab3a8a6a31918cebbe30

191969ffc6f6cd164964129f2a986c9f3a3c045e

/05day/07-变量.py

a635c8e36ead4c3308e5ed749fbe5468dd1d8aa5

[]

no_license

2001128/p1805

72844bde17b23de85a60308253da8a39750659fb

65538d83229639c237ea6de56dc2105bd3ca06a2

refs/heads/master

2020-03-19T11:32:06.878033

2018-06-28T02:50:36

136,460,761

0

null

UTF-8

Python

false

135

py

# = 赋值运算符 a=2 b=5 c=a+b print(c) d=a-b print(d) e=a*b print(e) f=a/b print(f) g=a//b print(g) h=a%b print(h) i=a**b print(i)

[ "335775879@qq.com" ]

335775879@qq.com

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/videos/migrations/0003_video_share_message.py

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[]

no_license

mathbeal/videomembership-django

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refs/heads/master

2021-06-04T20:13:38.457946

2016-09-13T13:37:05

null

0

null

UTF-8

Python

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475

py

# -*- coding: utf-8 -*- # Generated by Django 1.9.2 on 2016-02-22 13:47 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('videos', '0002_auto_20160219_1433'), ] operations = [ migrations.AddField( model_name='video', name='share_message', field=models.TextField(default='\nCheck out this video!\n'), ), ]

[ "leo.maltrait@gmail.com" ]

leo.maltrait@gmail.com

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/Dhein_Elegans_Projects/Code/draw_plots.py

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[]

no_license

SES591/C.-elegans

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08f0ef49f7002dd4847b27c7dc9afac8e75da989

refs/heads/master

2016-08-12T13:39:38.032623

2016-05-05T23:26:30

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#!/usr/bin/python #bionetworks.py #last update : 14 Aug 2014 __author__ = '''Hyunju Kim''' import networkx as nx import os import sys import random as ran from math import log from optparse import OptionParser, OptionGroup from scipy import * from collections import defaultdict import matplotlib.pyplot as plt #from info_measure import * import itertools from pylab import * from matplotlib.offsetbox import AnchoredOffsetbox, TextArea, HPacker import operator import copy def a_line(xlist, ylist, axis_labels, file_name): plt.figure(figsize=(12,8)) plt.plot(xlist, ylist, '-o') plt.xticks(xlist, axis_labels, rotation='vertical') plt.grid() plt.margins(0.2) # Tweak spacing to prevent clipping of tick-labels plt.subplots_adjust(bottom=0.25) plt.savefig(file_name) plt.show() def plot_AI_scale(dictO, result_file_name, viz_file_name): dictA = copy.deepcopy(dictO) #print "DDDDDDD" xlist = [x for x in range(len(dictA.keys()))] #list_node_names = list(dicA.keys()) dictA_values = list(dictA.values()) sorted_dicA_values = sorted(dictA_values) sorted_dicA_values.reverse() ylist = sorted_dicA_values axis_labels = [] for u in ylist: for i, j in dictA.iteritems(): if j == u: axis_labels.append(i) del dictA[i] break result_file = open(result_file_name, 'w') for i in range(len(xlist)): result_file.write('%s\t%f\n'%(axis_labels[i], ylist[i])) plt.figure(figsize=(12,8)) plt.plot(xlist, ylist, '-o') plt.xticks(xlist, axis_labels, rotation='vertical') plt.grid() plt.margins(0.2) # Tweak spacing to prevent clipping of tick-labels plt.subplots_adjust(bottom=0.25) plt.savefig(viz_file_name) #plt.show() def plot_TE_scale(dictO, result_file_name, viz_file_name): dictA = copy.deepcopy(dictO) #print "DDDDDDD" xlist = [x for x in range(len(dictA.keys()))] #list_node_names = list(dicA.keys()) dictA_values = list(dictA.values()) sorted_dicA_values = sorted(dictA_values) sorted_dicA_values.reverse() ylist = sorted_dicA_values axis_labels = [] for u in ylist: for i, j in dictA.iteritems(): if j == u: axis_labels.append(i) del dictA[i] break result_file = open(result_file_name, 'w') for i in range(len(xlist)): result_file.write('%s\t%f\n'%(axis_labels[i], ylist[i])) plt.figure(figsize=(12,8)) plt.plot(xlist, ylist, '-o') #plt.xticks(xlist, axis_labels, rotation='vertical') plt.grid() plt.margins(0.2) # Tweak spacing to prevent clipping of tick-labels plt.subplots_adjust(bottom=0.25) plt.savefig(viz_file_name) #plt.show() def a_line_nolabel(xlist, ylist, file_name): plt.figure(figsize=(12,8)) plt.plot(xlist, ylist, '-o') plt.grid() plt.margins(0.2) # Tweak spacing to prevent clipping of tick-labels plt.subplots_adjust(bottom=0.25) plt.savefig(file_name) #plt.show() def heatmap(nodes_list, hpcell, output_file_name): xlabels = list(nodes_list) # hpcell = {} # print input_file_name # input_file = open(input_file_name, 'r') # for line in input_file: # items = [x.strip() for x in line.rstrip().split('\t')] # ynode = items[0] # xnode = items[1] # hpcell[(ynode, xnode)] = float(items[2]) M = [] for ynode in xlabels: rM = [] for xnode in xlabels: rM.append(hpcell[(ynode, xnode)]) M.append(rM) M = np.array(M) fig1 = plt.figure(figsize=(10,8)) plt.yticks(np.arange(len(xlabels))+0.5, xlabels, size = 15, rotation=0, va="center", ha="right") plt.xticks(np.arange(len(xlabels))+0.5, xlabels, size = 15, rotation=90, va="top", ha="center") ax1 = fig1.add_subplot(111) cax1=ax1.pcolor(M, cmap=plt.cm.OrRd) plt.gca().set_aspect('equal') #ax1.set_title('Jaccard index of 27 pathways (edges)', size = 30) fig1.colorbar(cax1) plt.subplots_adjust(bottom=0.3) plt.savefig(output_file_name) #plt.show()

[ "Kelle Dhein" ]

Kelle Dhein

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c2640725115d0d62fd815539b9f3d33006586b81

/VertexCover.py

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[]

no_license

GiridharaSPK/Advanced-Analysis-and-Design-of-Algorithms

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f189d4c99d48b1dd71dd00b9b896c3e0cafbc348

refs/heads/master

2021-10-29T02:16:43.225151

2021-10-19T07:42:30

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from pulp import * A= [[0,1,1,0,0,0,0], [1,0,1,1,0,0,0], [1,1,0,0,1,0,1], [0,1,0,0,0,1,0], [0,0,1,0,0,1,0], [0,0,0,1,1,0,1], [0,0,0,0,0,1,0] ] prob = LpProblem("VertexCover",LpMinimize) variables=[] for i in range(len(A[0])): variables.append(LpVariable("A_{}".format(i),0,1)) for i in range(len(A[0])): prob+=lpSum(variables) #constraints for i in range(len(A[0])): for j in range(len(A[0])): if A[i][j]==1: prob+=variables[i]+variables[j]>=1 prob.writeLP("VertexCover.lp") prob.solve() print("Status:", LpStatus[prob.status]) for v in prob.variables(): print(v.name," : ", v.varValue) print("objective=", value(prob.objective))

[ "noreply@github.com" ]

GiridharaSPK.noreply@github.com

7649769d02263db44beb3e9dabb1074a73afe3bd

76a3099faad6720ad1d3f7595cb7fbe660c640cc

/reverse.py

c0aac686a9a199e07d69b63bab55deabea0b3bf1

[]

no_license

AcidPenguin/learning-python

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refs/heads/master

2021-07-10T12:22:25.533284

2020-07-22T22:25:36

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# print what ever results from the brackets # print(" ".join(input().split()[::-1]))

[ "addictedpenguins@icloud.com" ]

addictedpenguins@icloud.com

7e47cc01ebb88fb90a91148d4b000cd84c660f05

47b6ca131212a3e434b701d5e67d1d2e49ab21b2

/Exercise 5.py

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[]

no_license

ZarkoHDS/MuhammadYusuf_ITP2017_Exercise5

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refs/heads/master

2021-07-10T12:06:53.856432

2017-10-08T11:09:47

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py

#exercise 5 x=0 def calculator(num1,num2,operator,x): if operator == "+": x=num1 + num2 elif operator == "-": x=num1 - num2 elif operator == "*": x=num1 * num2 elif operator == "/": x=num1 / num2 else: x = num1+num2 if format == "integer": print(int(x)) elif format == "float": print(float(x)) operator=input("Insert Your symbols of math :") num1=int(input("Insert First Number :")) num2=int(input("Insert Second Number :")) format=input("Format :") calculator(num1,num2,operator,x)

[ "muhammad.andiyusuf@ymail.com" ]

muhammad.andiyusuf@ymail.com

d7263ad2898835a25b3012e0164c9c1abf279507

4c9bfaa5f83d76b00db63f14e5c8484a58ed7d99

/ll_env/bin/django-admin

f8372abe329761312875b9b51ea2a766734fff95

[]

no_license

davidthurman/My-Website

0fb14ed4aa45ea905f259c5091fef41f5c2bea2e

55bd5aa2e72e2d811da3f01f5a97b2715ad16c1b

refs/heads/master

2020-12-01T05:27:25.521149

2016-10-01T15:27:52

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#!/Users/davidthurman/Desktop/Python/Django/My-Website/ll_env/bin/python3 # -*- coding: utf-8 -*- import re import sys from django.core.management import execute_from_command_line if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(execute_from_command_line())

[ "davidthurmanwork@gmail.com" ]

davidthurmanwork@gmail.com

a702e97955980bf12bf92cfbc414efd0e9a8c369

35d1b6ba84ffcc682e361e929bfb3b81caf0402f

/invenio_records/systemfields/model.py

efc74c3cf19daa7ce1f4a3d4d60900de4ba83da4

[ "MIT", "LicenseRef-scancode-unknown-license-reference" ]

permissive

ppanero/invenio-records

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b189ce21d89f2e186d51a368931d5ab3e721ffae

refs/heads/master

2022-09-14T19:34:26.877056

2022-03-17T09:13:43

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0

MIT

2019-04-03T07:28:48

2019-04-03T07:28:47

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# -*- coding: utf-8 -*- # # This file is part of Invenio. # Copyright (C) 2020 CERN. # # Invenio is free software; you can redistribute it and/or modify it # under the terms of the MIT License; see LICENSE file for more details. """Constant system field.""" from ..dictutils import dict_lookup from .base import SystemField class ModelField(SystemField): """Model field for providing get and set access on a model field.""" def __init__(self, model_field_name=None, dump=True, dump_key=None, dump_type=None): """Initialize the field. :param model_field_name: Name of field on the database model. :param dump: Set to false to not dump the field. :param dump_key: The dictionary key to use in dumps. :param dump_type: The data type used to determine how to serialize the model field. """ self._model_field_name = model_field_name self.dump = dump self._dump_key = dump_key self._dump_type = dump_type # # Helpers # @property def model_field_name(self): """The name of the SQLAlchemy field on the model. Defaults to the attribute name used on the class. """ return self._model_field_name or self.attr_name @property def dump_key(self): """The dictionary key to use in dump output. Note, it's up to the dumper to choose if it respects this name. The name defaults to the model field name. """ return self._dump_key or self.model_field_name @property def dump_type(self): """The data type used to determine how to serialize the model field. Defaults to none, meaning the dumper will determine how to dump it. """ return self._dump_type def _set(self, model, value): """Internal method to set value on the model's field.""" setattr(model, self.model_field_name, value) # # Data descriptor # def __get__(self, record, owner=None): """Accessing the attribute.""" # Class access if record is None: return self # Instance access try: return getattr(record.model, self.model_field_name) except AttributeError: return None def __set__(self, instance, value): """Accessing the attribute.""" self._set(instance.model, value) # # Record extension # def post_init(self, record, data, model=None, field_data=None): """Initialise the model field.""" if field_data is not None: self._set(model, field_data)

[ "lars.holm.nielsen@cern.ch" ]

lars.holm.nielsen@cern.ch

2d99be2947ed06a48d470ebeae9181f5060181a0

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/SPrEader.py

c036387ed9cb0f59a8a10fa604f75d61df0cc79b

[]

no_license

Alirezabln/RubyRead-3

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e37cf2469dc995c2dd0ae81c575d0cbc43641824

refs/heads/master

2023-04-24T18:59:37.297387

2021-05-19T18:20:44

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''' winspec.py - read SPE files created by WinSpec with Princeton Instruments' cameras. ''' import ctypes, os import struct import numpy as np import logging __all__ = ['SpeFile', 'print_offsets'] __author__ = "Anton Loukianov" __email__ = "anton.loukianov@gmail.com" __license__ = "BSD" __version__ = "0.2.1" log = logging.getLogger('winspec') # Definitions of types spe_byte = ctypes.c_ubyte spe_word = ctypes.c_ushort spe_dword = ctypes.c_uint spe_char = ctypes.c_char # 1 byte spe_short = ctypes.c_short # 2 bytes # long is 4 bytes in the manual. It is 8 bytes on my machine spe_long = ctypes.c_int # 4 bytes spe_float = ctypes.c_float # 4 bytes spe_double = ctypes.c_double # 8 bytes class ROIinfo(ctypes.Structure): pass class AxisCalibration(ctypes.Structure): pass class Header(ctypes.Structure): pass def print_offsets(): ''' Print the attribute names, sizes and offsets in the C structure Assuming that the sizes are correct and add up to an offset of 4100 bytes, everything should add up correctly. This information was taken from the WinSpec 2.6 Spectroscopy Software User Manual version 2.6B, page 251. If this table doesn't add up, something changed in the definitions of the datatype widths. Fix this in winspec.structs file and let me know! ''' import inspect, re A = Header() for i in [Header, AxisCalibration, ROIinfo]: fields = [] print('\n{:30s}[{:4s}]\tsize'.format(repr(i), 'offs')) for name,obj in inspect.getmembers(i): if inspect.isdatadescriptor(obj) and not inspect.ismemberdescriptor(obj) \ and not inspect.isgetsetdescriptor(obj): fields.append((name, obj)) fields = sorted(fields, key=lambda x: x[1].offset) for name, obj in fields: print('{:30s}[{:4d}]\t{:4d}'.format(name, obj.size, obj.offset)) class SpeFile(object): ''' A file that represents the SPE file. All details written in the file are contained in the `header` structure. Data is accessed by using the `data` property. Once the object is created and data accessed, the file is NOT read again. Create a new object if you want to reread the file. ''' # Map between header datatype field and numpy datatype _datatype_map = {0 : np.float32, 1 : np.int32, 2 : np.int16, 3 : np.uint16} def __init__(self, name): ''' Open file `name` to read the header.''' with open(name, mode='rb') as f: self.header = Header() self.path = os.path.realpath(name) self._data = None self._xaxis = None self._yaxis = None # Deprecated method, but FileIO apparently can't be used with numpy f.readinto(self.header) # set some useful properties self.reversed = True if self.header.geometric == 2 else False self.gain = self.header.gain if self.header.ADCtype == 8: self.adc = 'Low Noise' elif self.header.ADCtype == 9: self.adc = 'High Capacity' else: self.adc = 'Unknown' if self.header.ADCrate == 12: self.adc_rate = '2 MHz' elif self.header.ADCrate == 6: self.adc_rate = '100 KHz' else: self.adc_rate = 'Unknown' self.readout_time = self.header.ReadoutTime def _read(self): ''' Read the data segment of the file and create an appropriately-shaped numpy array Based on the header, the right datatype is selected and returned as a numpy array. I took the convention that the frame index is the first, followed by the x,y coordinates. ''' if self._data is not None: log.debug('using cached data') return self._data # In python 2.7, apparently file and FileIO cannot be used interchangably with open(self.path, mode='rb') as f: f.seek(4100) # Skip header (4100 bytes) _count = self.header.xdim * self.header.ydim * self.header.NumFrames self._data = np.fromfile(f, dtype=SpeFile._datatype_map[self.header.datatype], count=_count) # Also, apparently the ordering of the data corresponds to how it is stored by the shift register # Thus, it appears a little backwards... self._data = self._data.reshape((self.header.NumFrames, self.header.ydim, self.header.xdim)) # Orient the structure so that it is indexed like [NumFrames][x, y] self._data = np.rollaxis(self._data, 2, 1) # flip data if all([self.reversed == True, self.adc == '100 KHz']): pass elif any([self.reversed == True, self.adc == '100 KHz']): self._data = self._data[:, ::-1, :] log.debug('flipped data because of nonstandard ADC setting ' + \ 'or reversed setting') return self._data @property def xaxis(self): if self._xaxis is not None: log.debug('using cached xaxis') return self._xaxis px, py = self._make_axes() return px @property def yaxis(self): if self._yaxis is not None: log.debug('using cached yaxis') return self._yaxis px, py = self._make_axes() return py @property def xaxis_label(self): '''Read the x axis label ''' return self.header.xcalibration.string.decode('ascii') @property def yaxis_label(self): '''Read the y axis label ''' return self.header.ycalibration.string.decode('ascii') def _make_axes(self): '''Construct axes from calibration fields in header file ''' xcalib = self.header.xcalibration ycalib = self.header.ycalibration xcalib_valid = struct.unpack('?', xcalib.calib_valid) if xcalib_valid: xcalib_order, = struct.unpack('>B', xcalib.polynom_order) # polynomial order px = xcalib.polynom_coeff[:xcalib_order+1] px = np.array(px[::-1]) # reverse coefficients to use numpy polyval pixels = np.arange(1, self.header.xdim + 1) px = np.polyval(px, pixels) else: px = np.arange(1, self.header.xdim + 1) ycalib_valid = struct.unpack('?', ycalib.calib_valid) if ycalib_valid: ycalib_order, = struct.unpack('>B', ycalib.polynom_order) # polynomial order py = ycalib.polynom_coeff[:ycalib_order+1] py = np.array(py[::-1]) # reverse coefficients to use numpy polyval pixels = np.arange(1, self.header.ydim + 1) py = np.polyval(py, pixels) else: py = np.arange(1, self.header.ydim + 1) self._xaxis = px self._yaxis = py return px, py ''' Data recorded in the file, returned as a numpy array. The convention for indexes is that the first index is the frame index, followed by x,y region of interest. ''' data = property(fget=_read) def __str__(self): return 'SPE File \n\t{:d}x{:d} area, {:d} frames\n\tTaken on {:s}' \ .format(self.header.xdim, self.header.ydim, self.header.NumFrames, self.header.date.decode()) def __repr__(self): return str(self) # Lengths of arrays used in header HDRNAMEMAX = 120 USERINFOMAX = 1000 COMMENTMAX = 80 LABELMAX = 16 FILEVERMAX = 16 DATEMAX = 10 ROIMAX = 10 TIMEMAX = 7 # Definitions of WinSpec structures # Region of interest defs ROIinfo._pack_ = 1 ROIinfo._fields_ = [ ('startx', spe_word), ('endx', spe_word), ('groupx', spe_word), ('starty', spe_word), ('endy', spe_word), ('groupy', spe_word)] # Calibration structure for X and Y axes AxisCalibration._pack_ = 1 AxisCalibration._fields_ = [ ('offset', spe_double), ('factor', spe_double), ('current_unit', spe_char), ('reserved1', spe_char), ('string', spe_char * 40), ('reserved2', spe_char * 40), ('calib_valid', spe_char), ('input_unit', spe_char), ('polynom_unit', spe_char), ('polynom_order', spe_char), ('calib_count', spe_char), ('pixel_position', spe_double * 10), ('calib_value', spe_double * 10), ('polynom_coeff', spe_double * 6), ('laser_position', spe_double), ('reserved3', spe_char), ('new_calib_flag', spe_byte), ('calib_label', spe_char * 81), ('expansion', spe_char * 87)] # Full header definition Header._pack_ = 1 Header._fields_ = [ ('ControllerVersion', spe_short), ('LogicOutput', spe_short), ('AmpHiCapLowNoise', spe_word), ('xDimDet', spe_word), ('mode', spe_short), ('exp_sec', spe_float), ('VChipXdim', spe_short), ('VChipYdim', spe_short), ('yDimDet', spe_word), ('date', spe_char * DATEMAX), ('VirtualChipFlag', spe_short), ('Spare_1', spe_char * 2), # Unused data ('noscan', spe_short), ('DetTemperature', spe_float), ('DetType', spe_short), ('xdim', spe_word), ('stdiode', spe_short), ('DelayTime', spe_float), ('ShutterControl', spe_word), ('AbsorbLive', spe_short), ('AbsorbMode', spe_word), ('CanDoVirtualChipFlag', spe_short), ('ThresholdMinLive', spe_short), ('ThresholdMinVal', spe_float), ('ThresholdMaxLive', spe_short), ('ThresholdMaxVal', spe_float), ('SpecAutoSpectroMode', spe_short), ('SpecCenterWlNm', spe_float), ('SpecGlueFlag', spe_short), ('SpecGlueStartWlNm', spe_float), ('SpecGlueEndWlNm', spe_float), ('SpecGlueMinOvrlpNm', spe_float), ('SpecGlueFinalResNm', spe_float), ('PulserType', spe_short), ('CustomChipFlag', spe_short), ('XPrePixels', spe_short), ('XPostPixels', spe_short), ('YPrePixels', spe_short), ('YPostPixels', spe_short), ('asynen', spe_short), ('datatype', spe_short), # 0 - float, 1 - long, 2 - short, 3 - ushort ('PulserMode', spe_short), ('PulserOnChipAccums', spe_word), ('PulserRepeatExp', spe_dword), ('PulseRepWidth', spe_float), ('PulseRepDelay', spe_float), ('PulseSeqStartWidth', spe_float), ('PulseSeqEndWidth', spe_float), ('PulseSeqStartDelay', spe_float), ('PulseSeqEndDelay', spe_float), ('PulseSeqIncMode', spe_short), ('PImaxUsed', spe_short), ('PImaxMode', spe_short), ('PImaxGain', spe_short), ('BackGrndApplied', spe_short), ('PImax2nsBrdUsed', spe_short), ('minblk', spe_word), ('numminblk', spe_word), ('SpecMirrorLocation', spe_short * 2), ('SpecSlitLocation', spe_short * 4), ('CustomTimingFlag', spe_short), ('ExperimentTimeLocal', spe_char * TIMEMAX), ('ExperimentTimeUTC', spe_char * TIMEMAX), ('ExposUnits', spe_short), ('ADCoffset', spe_word), ('ADCrate', spe_word), ('ADCtype', spe_word), ('ADCresolution', spe_word), ('ADCbitAdjust', spe_word), ('gain', spe_word), ('Comments', spe_char * 5 * COMMENTMAX), ('geometric', spe_word), # x01 - rotate, x02 - reverse, x04 flip ('xlabel', spe_char * LABELMAX), ('cleans', spe_word), ('NumSkpPerCln', spe_word), ('SpecMirrorPos', spe_short * 2), ('SpecSlitPos', spe_float * 4), ('AutoCleansActive', spe_short), ('UseContCleansInst', spe_short), ('AbsorbStripNum', spe_short), ('SpecSlipPosUnits', spe_short), ('SpecGrooves', spe_float), ('srccmp', spe_short), ('ydim', spe_word), ('scramble', spe_short), ('ContinuousCleansFlag', spe_short), ('ExternalTriggerFlag', spe_short), ('lnoscan', spe_long), # Longs are 4 bytes ('lavgexp', spe_long), # 4 bytes ('ReadoutTime', spe_float), ('TriggeredModeFlag', spe_short), ('Spare_2', spe_char * 10), ('sw_version', spe_char * FILEVERMAX), ('type', spe_short), ('flatFieldApplied', spe_short), ('Spare_3', spe_char * 16), ('kin_trig_mode', spe_short), ('dlabel', spe_char * LABELMAX), ('Spare_4', spe_char * 436), ('PulseFileName', spe_char * HDRNAMEMAX), ('AbsorbFileName', spe_char * HDRNAMEMAX), ('NumExpRepeats', spe_dword), ('NumExpAccums', spe_dword), ('YT_Flag', spe_short), ('clkspd_us', spe_float), ('HWaccumFlag', spe_short), ('StoreSync', spe_short), ('BlemishApplied', spe_short), ('CosmicApplied', spe_short), ('CosmicType', spe_short), ('CosmicThreshold', spe_float), ('NumFrames', spe_long), ('MaxIntensity', spe_float), ('MinIntensity', spe_float), ('ylabel', spe_char * LABELMAX), ('ShutterType', spe_word), ('shutterComp', spe_float), ('readoutMode', spe_word), ('WindowSize', spe_word), ('clkspd', spe_word), ('interface_type', spe_word), ('NumROIsInExperiment', spe_short), ('Spare_5', spe_char * 16), ('controllerNum', spe_word), ('SWmade', spe_word), ('NumROI', spe_short), ('ROIinfblk', ROIinfo * ROIMAX), ('FlatField', spe_char * HDRNAMEMAX), ('background', spe_char * HDRNAMEMAX), ('blemish', spe_char * HDRNAMEMAX), ('file_header_ver', spe_float), ('YT_Info', spe_char * 1000), ('WinView_id', spe_long), ('xcalibration', AxisCalibration), ('ycalibration', AxisCalibration), ('Istring', spe_char * 40), ('Spare_6', spe_char * 25), ('SpecType', spe_byte), ('SpecModel', spe_byte), ('PulseBurstUsed', spe_byte), ('PulseBurstCount', spe_dword), ('PulseBurstPeriod', spe_double), ('PulseBracketUsed', spe_byte), ('PulseBracketType', spe_byte), ('PulseTimeConstFast', spe_double), ('PulseAmplitudeFast', spe_double), ('PulseTimeConstSlow', spe_double), ('PulseAmplitudeSlow', spe_double), ('AnalogGain', spe_short), ('AvGainUsed', spe_short), ('AvGain', spe_short), ('lastvalue', spe_short)] # ###test = SpeFile('Bi-cell4-ruby7.SPE') # ###print(test) # ###print(test.header.ExperimentTimeUTC) # ### # ###print(test.data.shape) # ###print(test.data[0].shape) # ###print(print(test.header))

[ "jssmith@anl.gov" ]

jssmith@anl.gov

67ee694b86cd7dc3c2c0e4b65be8f0f59bff7f81

3a343e05afa4a3b2485aa6bba8386011ade0f32c

/gohappyserver/authviews.py

368e431fb4e8eb9d5e4644f7a7ad4b6c81bedf9b

[]

no_license

kazemnejad/gohappy-filemanager-server

21c3cc5ede3dadafb3f898513098eb3ad209f2cc

e9ca82cb567da62cf3cf48cf1bdeb4dbb0058095

refs/heads/master

2021-01-10T08:48:41.119086

2016-03-27T09:53:15

54,634,274

0

null

UTF-8

Python

false

1,995

py

from flask import abort from flask import request, jsonify, render_template from gohappyserver.database import db_session from gohappyserver.models import User from gohappyserver.server import app class AuthResponceCode: SUCCESS = 10 FAIL = 11 USER_EXISTS = 12 INVALID_CREDENTIALS = 13 @app.route("/") def main_page(): return render_template("index.html") @app.route("/auth/login", methods=['POST']) def login(): username = request.form['username'] password = request.form['password'] response = {} user = User.query.filter_by(username=username).first() if not user or not user.verify_password(password): response["result"] = AuthResponceCode.FAIL response["message"] = AuthResponceCode.INVALID_CREDENTIALS else: response["result"] = AuthResponceCode.SUCCESS response["token"] = user.generate_auth_token().decode('ascii') return jsonify(response), 200, @app.route("/auth/register", methods=["POST"]) def register(): username = request.form['username'] password = request.form['password'] if len(username) == 0 or len(password) == 0: abort(400) response = {} if User.query.filter_by(username=username).first() is not None: response["result"] = AuthResponceCode.FAIL response["message"] = AuthResponceCode.USER_EXISTS else: user = User(username=username, password=password) db_session.add(user) db_session.commit() response["result"] = AuthResponceCode.SUCCESS response["id"] = user.id response["token"] = user.generate_auth_token().decode('ascii') print response return jsonify(response), 200, @app.route("/users/online", methods=["GET"]) def list_users(): token = str(request.headers.get("Authorization")).split(" ")[1] if not User.verify_auth_token(token): abort(403) online_users = User.query.filter(User.socket_id != None) return jsonify(online_users), 200,

[ "ub.maka@gmail.com" ]

ub.maka@gmail.com

4d0112a32f6eca81ffc2fdd40fa60162f829a9b4

07d01fa4ec60b5a6cb0d157e97b4352847f8ef36

/.venv/Lib/site-packages/pathspec/tests/test_pathspec.py

a76ec0701f627ac13736aeddc56178808c7bd9eb

[]

no_license

freddieaviator/simple_python_pipeline

9b833df352a3310e10929313d46bc76b23ae9490

34c11a04d028906aa8de73d5b8a6a6f143c94de0

refs/heads/main

2023-06-30T04:41:13.738241

2021-08-05T14:25:30

392,977,835

0

null

UTF-8

Python

false

7,416

py

# encoding: utf-8 """ This script tests ``PathSpec``. """ import unittest import pathspec class PathSpecTest(unittest.TestCase): """ The ``PathSpecTest`` class tests the ``PathSpec`` class. """ def test_01_absolute_dir_paths_1(self): """ Tests that absolute paths will be properly normalized and matched. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "foo", ], ) results = set( spec.match_files( [ "/a.py", "/foo/a.py", "/x/a.py", "/x/foo/a.py", "a.py", "foo/a.py", "x/a.py", "x/foo/a.py", ] ) ) self.assertEqual( results, { "/foo/a.py", "/x/foo/a.py", "foo/a.py", "x/foo/a.py", }, ) def test_01_absolute_dir_paths_2(self): """ Tests that absolute paths will be properly normalized and matched. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "/foo", ], ) results = set( spec.match_files( [ "/a.py", "/foo/a.py", "/x/a.py", "/x/foo/a.py", "a.py", "foo/a.py", "x/a.py", "x/foo/a.py", ] ) ) self.assertEqual( results, { "/foo/a.py", "foo/a.py", }, ) def test_01_current_dir_paths(self): """ Tests that paths referencing the current directory will be properly normalized and matched. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) results = set( spec.match_files( [ "./src/test1/a.txt", "./src/test1/b.txt", "./src/test1/c/c.txt", "./src/test2/a.txt", "./src/test2/b.txt", "./src/test2/c/c.txt", ] ) ) self.assertEqual( results, { "./src/test2/a.txt", "./src/test2/b.txt", "./src/test2/c/c.txt", }, ) def test_01_match_files(self): """ Tests that matching files one at a time yields the same results as matching multiples files at once. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) test_files = [ "src/test1/a.txt", "src/test1/b.txt", "src/test1/c/c.txt", "src/test2/a.txt", "src/test2/b.txt", "src/test2/c/c.txt", ] single_results = set(filter(spec.match_file, test_files)) multi_results = set(spec.match_files(test_files)) self.assertEqual(single_results, multi_results) def test_01_windows_current_dir_paths(self): """ Tests that paths referencing the current directory will be properly normalized and matched. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) results = set( spec.match_files( [ ".\\src\\test1\\a.txt", ".\\src\\test1\\b.txt", ".\\src\\test1\\c\\c.txt", ".\\src\\test2\\a.txt", ".\\src\\test2\\b.txt", ".\\src\\test2\\c\\c.txt", ], separators=("\\",), ) ) self.assertEqual( results, { ".\\src\\test2\\a.txt", ".\\src\\test2\\b.txt", ".\\src\\test2\\c\\c.txt", }, ) def test_01_windows_paths(self): """ Tests that Windows paths will be properly normalized and matched. """ spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) results = set( spec.match_files( [ "src\\test1\\a.txt", "src\\test1\\b.txt", "src\\test1\\c\\c.txt", "src\\test2\\a.txt", "src\\test2\\b.txt", "src\\test2\\c\\c.txt", ], separators=("\\",), ) ) self.assertEqual( results, { "src\\test2\\a.txt", "src\\test2\\b.txt", "src\\test2\\c\\c.txt", }, ) def test_02_eq(self): """ Tests equality. """ first_spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) second_spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", "!test1/", ], ) self.assertEqual(first_spec, second_spec) def test_02_ne(self): """ Tests equality. """ first_spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "*.txt", ], ) second_spec = pathspec.PathSpec.from_lines( "gitwildmatch", [ "!*.txt", ], ) self.assertNotEqual(first_spec, second_spec) def test_01_addition(self): """ Test pattern addition using + operator """ first_spec = pathspec.PathSpec.from_lines( "gitwildmatch", ["test.txt", "test.png"] ) second_spec = pathspec.PathSpec.from_lines( "gitwildmatch", ["test.html", "test.jpg"] ) combined_spec = first_spec + second_spec results = set( combined_spec.match_files( ["test.txt", "test.png", "test.html", "test.jpg"], separators=("\\",) ) ) self.assertEqual(results, {"test.txt", "test.png", "test.html", "test.jpg"}) def test_02_addition(self): """ Test pattern addition using += operator """ spec = pathspec.PathSpec.from_lines("gitwildmatch", ["test.txt", "test.png"]) spec += pathspec.PathSpec.from_lines("gitwildmatch", ["test.html", "test.jpg"]) results = set( spec.match_files( ["test.txt", "test.png", "test.html", "test.jpg"], separators=("\\",) ) ) self.assertEqual(results, {"test.txt", "test.png", "test.html", "test.jpg"})

[ "harberg@kth.se" ]

harberg@kth.se

79b993423382b3e092e440f39a6078aea418e1fc

5ac5440db74b41e46ca5ac4de10430251a3076f9

/Copia de velocidades.py

948249c5881035ff6713195c642cc8e24b44fcf9

[]

no_license

JMicrobium/progra

f75663cfe18b39367fb218919b190aad51581c62

47c24c27b1cde1401bde10a760244ee7a21041c7

refs/heads/master

2020-08-08T06:16:47.236430

2019-11-07T03:41:35

213,751,394

0

null

UTF-8

Python

false

992

py

"""# division of lists # using zip() + list comprehension res = [i / j for i, j in zip(test_list1, test_list2)]""" deltasA=[50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110] tiemposA=[0.0116, 0.0113, 0.0115, 0.0113, 0.0113, 0.0112, 0.0111, 0.0109, 0.0103, 0.0098, 0.0094, 0.0089, 0.0085, 0.0087, 0.0086, 0.0085, 0.0083, 0.0085, 0.0085, 0.0090, 0.0085 ,0.0086, 0.0088, 0.0089, 0.0080, 0.0080, 0.0082, 0.0081, 0.0081, 0.0083, 0.0076, 0.0074, 0.0073, 0.0072, 0.0071, 0.0071, 0.0071, 0.0072, 0.0070, 0.0071, 0.0070, 0.0069, 0.0068, 0.0067, 0.0067, 0.0067, 0.0066, 0.0066, 0.0066, 0.0066, 0.0065, 0.0066, 0.0065, 0.0064, 0.0064, 0.0062, 0.0062, 0.0061, 0.0060, 0.0060, 0.0060] A=[(i-20) for i in deltasA] velocidadesA=[k/j for k,j in zip(A,tiemposA)] print("'velocidadesA':",velocidadesA)

[ "54874211+JMicrobium@users.noreply.github.com" ]

54874211+JMicrobium@users.noreply.github.com

32ed04f60ded1e497874c903fcb12015b3432175

af217fb6a724a0450917dc365a0dff3c38fbe94f

/grocy/model/inline_object7.py

33a02074e26fb3493103c6992b18b2322518fd35

[]

no_license

fipwmaqzufheoxq92ebc/grocy-python-openapi

b8f7ab5eba96ff28d6845ada22493bf233ac1900

014c7b3ef88c9a2e11d6a59c4ef2f8037c623bc6

refs/heads/main

2023-06-02T16:59:20.253117

2021-06-24T13:23:02

379,931,022

0

null

UTF-8

Python

false

12,177

py

""" grocy REST API Authentication is done via API keys (header *GROCY-API-KEY* or same named query parameter), which you can manage [here](http://localhost:8111/manageapikeys). Additionally requests from within the frontend are also valid (via session cookie). # noqa: E501 The version of the OpenAPI document: 3.0.1 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from grocy.model_utils import ( # noqa: F401 ApiTypeError, ModelComposed, ModelNormal, ModelSimple, cached_property, change_keys_js_to_python, convert_js_args_to_python_args, date, datetime, file_type, none_type, validate_get_composed_info, ) from ..model_utils import OpenApiModel from grocy.exceptions import ApiAttributeError class InlineObject7(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } validations = { } @cached_property def additional_properties_type(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded """ return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501 _nullable = False @cached_property def openapi_types(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded Returns openapi_types (dict): The key is attribute name and the value is attribute type. """ return { 'amount': (float,), # noqa: E501 'stock_entry_id': (str,), # noqa: E501 'allow_subproduct_substitution': (bool,), # noqa: E501 } @cached_property def discriminator(): return None attribute_map = { 'amount': 'amount', # noqa: E501 'stock_entry_id': 'stock_entry_id', # noqa: E501 'allow_subproduct_substitution': 'allow_subproduct_substitution', # noqa: E501 } read_only_vars = { } _composed_schemas = {} @classmethod @convert_js_args_to_python_args def _from_openapi_data(cls, *args, **kwargs): # noqa: E501 """InlineObject7 - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) amount (float): The amount to mark as opened. [optional] # noqa: E501 stock_entry_id (str): A specific stock entry id to open, if used, the amount has to be 1. [optional] # noqa: E501 allow_subproduct_substitution (bool): `True` when any in-stock sub product should be used when the given product is a parent product and currently not in-stock. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) self = super(OpenApiModel, cls).__new__(cls) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) return self required_properties = set([ '_data_store', '_check_type', '_spec_property_naming', '_path_to_item', '_configuration', '_visited_composed_classes', ]) @convert_js_args_to_python_args def __init__(self, *args, **kwargs): # noqa: E501 """InlineObject7 - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) amount (float): The amount to mark as opened. [optional] # noqa: E501 stock_entry_id (str): A specific stock entry id to open, if used, the amount has to be 1. [optional] # noqa: E501 allow_subproduct_substitution (bool): `True` when any in-stock sub product should be used when the given product is a parent product and currently not in-stock. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) if var_name in self.read_only_vars: raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate " f"class with read only attributes.")

[ "29818044+fipwmaqzufheoxq92ebc@users.noreply.github.com" ]

29818044+fipwmaqzufheoxq92ebc@users.noreply.github.com

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e593273909dd6b5148357c775bb3acb15fad3779

/b2/part.py

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[ "MIT" ]

permissive

Python3pkg/B2_Command_Line_Tool

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refs/heads/master

2021-01-21T09:23:43.104569

2017-05-18T08:45:35

91,653,925

1

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2017-05-18T05:50:33

2017-05-18T05:50:32

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UTF-8

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###################################################################### # # File: b2/part.py # # Copyright 2016 Backblaze Inc. All Rights Reserved. # # License https://www.backblaze.com/using_b2_code.html # ###################################################################### class PartFactory(object): @classmethod def from_list_parts_dict(cls, part_dict): return Part( part_dict['fileId'], part_dict['partNumber'], part_dict['contentLength'], part_dict['contentSha1'] ) class Part(object): def __init__(self, file_id, part_number, content_length, content_sha1): self.file_id = file_id self.part_number = part_number self.content_length = content_length self.content_sha1 = content_sha1 def __repr__(self): return '<%s %s %s %s %s>' % ( self.__class__.__name__, self.file_id, self.part_number, self.content_length, self.content_sha1 ) def __eq__(self, other): return isinstance(other, self.__class__) and self.__dict__ == other.__dict__ def __ne__(self, other): return not (self == other)

[ "coder@beachfamily.net" ]

coder@beachfamily.net

71967d56f56ea90ba5abb1691448706e5b956b69

e7881505ecc7e993b1d87be5bf604448fa2a3e2d

/server/taxi/taxi/urls.py

a8e995c75829d2cc0fbf6ee7d3e0090012af6d15

[]

no_license

pmaturure3/React_Django_Taxi_App

8bf7e78174dd6eab6e4cdb1da70aa58af4d2ae05

1e69d4120b83be2bb430decea3fbc16d74a77b31

refs/heads/master

2023-02-11T02:33:18.081483

2020-07-26T21:58:46

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from django.contrib import admin from django.urls import include, path from rest_framework_simplejwt.views import TokenRefreshView from trips.views import SignUpView, LogInView urlpatterns = [ path('admin/', admin.site.urls), path('api/sign_up/', SignUpView.as_view(), name='sign_up'), path('api/log_in/', LogInView.as_view(), name='log_in'), path('api/token/refresh/', TokenRefreshView.as_view(), name='token_refresh'), path('api/trip/', include('trips.urls', 'trip',)), ]

[ "sjogleka@uncc.edu" ]

sjogleka@uncc.edu

c55d8ac50017b3cbc3399ad4b902e24e61709f95

e30aa4cbaecf14398ca72eac996e7dfda55d85cd

/setup.py

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[ "MIT" ]

permissive

DanielLSM/crypto-insider

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f668f184e5d748e82918f4ec4b57f8ae9b417804

refs/heads/master

2021-04-28T18:44:54.614934

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from setuptools import setup, find_packages import sys if sys.version_info.major != 3: print('This Python is only compatible with Python 3, but you are running ' 'Python {}. The installation will likely fail.'.format(sys.version_info.major)) setup(name='baselines', packages=[package for package in find_packages() if package.startswith('crypto-insider')], install_requires=[ 'lxml', 'requests', ], description='A library to scrap popular crypto currencies websites ', author='Marta. Daniel Luis', url='https://github.com/DanielLSM/crypto-insider', author_email='daniellsmarta@gmail.com', version='0.0.1')

[ "daniellsmarta@gmail.com" ]

daniellsmarta@gmail.com

8a43744f7e3df08e09834cfc54ecc99bb72ea18f

c63bf01b632c52dcfb19e78b47c36fb5efcab507

/src/components/enemy.py

ca6b6fdbea24c7d86a63f385b3af1085c8dd35c9

[]

no_license

Grimmys/BubbleTanks2

3292173eb6abd66d40aa5306e65af381a47867bd

a015ece36b4bea80b92656ffc37e947b0919a536

refs/heads/main

2023-06-26T12:27:15.150425

2021-07-29T19:47:51

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from random import uniform from math import pi, cos, sin, hypot import pygame as pg from assets.paths import * from data.constants import * from data.enemies import ENEMIES from components.utils import * from components.base_mob import BaseMob from components.enemy_body import EnemyBody from components.enemy_weapons import EnemyWeapons from components.enemy_event import EnemyEvent from components.special_effects import infection_surfaces sticky_w = H(108.391) sticky_h = H(99.248) sticky_image = pg.image.load(STICKY_IMAGE).convert_alpha() sticky_image = pg.transform.smoothscale(sticky_image, (sticky_w, sticky_h)) class Enemy(BaseMob): def __init__(self, game, name): self.name = name data = ENEMIES[name] super().__init__(*self.start_pos(), data["max health"], data["max health"], data["radius"], EnemyBody(self, game.rect, data), EnemyWeapons(self, game, data)) self.game = game self.death_award = data["death award"] self.screen_rect = game.rect self.rect = pg.Rect(0, 0, data["rect size"], data["rect size"]) self.rect.center = self.x, self.y self.update_component_states() self.events = [EnemyEvent(self, game, event_data) for event_data in data["events"]] self.velocity = data["velocity"] self.vel_x = 0 self.vel_y = 0 self.body.angle = uniform(0, 2*pi) if self.velocity != 0 else 0 self.set_velocity() self.angle_to_turn = 0 self.last_angle = 0 self.safety_turn = False self.time_to_turn = 0 self.time_to_hold_turning = 0 self.spawners_data = data["spawners"] self.killed = False self.chasing_infectors = set() self.infected = False self.infection_time = 0 self.infection_cooldown = 170 self.infection_effect_time = 0 @property def is_on_screen(self): return self.rect.colliderect(self.screen_rect) @property def about_to_exit(self): if self.velocity == 0: return False distance = self.rect.w/2 + HF(132) x = self.x + distance * self.vel_x / self.velocity y = self.y + distance * self.vel_y / self.velocity return hypot(x - SCR_W2, y - SCR_H2) > ROOM_RADIUS @staticmethod def start_pos(): distance = uniform(0, ROOM_RADIUS * 0.7) angle = uniform(0, 2*pi) x = SCR_W2 + distance * cos(angle) y = SCR_H2 - distance * sin(angle) return x, y def update_health(self, delta_health: int): self.health = min(self.max_health, self.health + delta_health) self.update_component_states() if self.health <= 0: self.killed = True def become_infected(self): if not self.infected: self.infected = True self.body.become_infected() self.weapons.become_infected() def update_infected_state(self, dt): if self.infected: self.infection_time += dt if self.infection_time >= self.infection_cooldown: self.receive_damage(-1, play_sound=False) self.infection_time = 0 def get_angle_pos(self): return calculate_angle(SCR_W2, SCR_H2, self.x, self.y) def set_velocity(self): self.vel_x = self.velocity * cos(self.body.angle) self.vel_y = -self.velocity * sin(self.body.angle) def set_pos(self, x, y): self.x = x self.y = y self.rect.center = x, y def move_by_time(self, dt): self.move(self.vel_x * dt, self.vel_y * dt) def update_angle(self, delta_angle): self.body.angle += delta_angle self.set_velocity() def update_pos(self, dt): if self.stunned or self.sticky or self.velocity == 0: self.rect.center = self.x, self.y self.weapons.update_pos() return last_angle_pos = self.get_angle_pos() self.move_by_time(dt) about_to_exit = self.about_to_exit if self.time_to_turn == 0 or (about_to_exit and not self.safety_turn): if about_to_exit: angle_pos = self.get_angle_pos() angle_to_turn = uniform(-pi, -pi/2) if angle_pos > last_angle_pos: angle_to_turn *= -1 k = HF(2.4 * 180 / pi) self.time_to_turn = abs(angle_to_turn) / self.velocity * k self.angle_to_turn = self.velocity * sign(angle_to_turn) / k self.time_to_hold_turning = 1800 self.safety_turn = True else: self.time_to_turn = max(0, self.time_to_turn - dt) self.update_angle(self.angle_to_turn * dt) if self.time_to_hold_turning > 0: self.time_to_hold_turning -= dt elif self.time_to_turn == 0: if dt != 0 and uniform(0, 1000/dt) < 1: distance = uniform(-100, 100) k = HF(2.4) self.time_to_turn = abs(distance) / self.velocity * k self.angle_to_turn = self.velocity * sign(distance) / k * pi/180 self.safety_turn = False self.weapons.update_pos() def update_shape(self, dt): if self.is_on_screen: self.body.update_shape(dt) self.weapons.update_shape(dt) self.infection_effect_time = (self.infection_effect_time + dt) % 320 def update_shooting(self, dt): if not self.stunned: self.weapons.update_shooting(dt) def receive_damage(self, damage, play_sound=True): super().receive_damage(damage) for event in self.events: if self.health <= event.trigger_value and not event.hit or event.trigger_value == -1: event.hit = True event.action() if self.killed: self.game.sound_player.play_sound(ENEMY_DEATH) self.game.pause_menu.update_counter(0, 1) if play_sound: self.game.sound_player.play_sound(ENEMY_HIT) def update(self, dt): self.update_sticky_state(dt) self.update_stunned_state(dt) self.update_infected_state(dt) self.update_pos(dt) self.update_shape(dt) self.update_shooting(dt) def draw_sticky(self, screen, dx, dy): x = self.x - dx - sticky_w/2 y = self.y - dy - sticky_h/2 screen.blit(sticky_image, (x, y)) def draw_infected(self, screen, dx, dy): index = int(17 * self.infection_effect_time/320) if 9 <= index <= 15: surface = infection_surfaces[index - 9] x = self.x - dx - surface.get_width()/2 y = self.y - dy - surface.get_height()/2 screen.blit(surface, (x, y)) def draw(self, screen, dx=0, dy=0): if self.is_on_screen: self.body.draw(screen, dx, dy) self.weapons.draw(screen, dx, dy) if self.sticky: self.draw_sticky(screen, dx, dy) if self.infected: self.draw_infected(screen, dx, dy) class BossHead(Enemy): def __init__(self, game, name): super().__init__(game, name) self.body.angle = -0.5 * pi self.delta_angle = 0 self.target = game.player self.rect_offset = HF(192.575) @staticmethod def start_pos(): return SCR_W2, -HF(480) def collide_bullet(self, bullet) -> bool: return (self.rect.colliderect(bullet.rect) and circle_collidepoint(*self.rect.center, self.radius + bullet.radius, bullet.x, bullet.y)) def move(self, dx, dy): self.x += dx self.y += dy self.rect.centerx = self.x + self.rect_offset * cos(self.body.angle) self.rect.centery = self.y - self.rect_offset * sin(self.body.angle) def update_pos(self, dt): if self.sticky or self.stunned: self.weapons.update_pos() return angle = calculate_angle(self.x, self.y, self.target.x, self.target.y) + 0.5 * pi if angle > pi: angle = -angle + 0.5 * pi if angle > self.delta_angle: self.delta_angle = min(angle, self.delta_angle + 0.00072 * dt, 0.23 * pi) else: self.delta_angle = max(angle, self.delta_angle - 0.00072 * dt, -0.23 * pi) self.body.angle = -0.5 * pi + self.delta_angle self.rect.centerx = self.x + self.rect_offset * cos(self.body.angle) self.rect.centery = self.y - self.rect_offset * sin(self.body.angle) self.weapons.update_pos() class BossLeg(Enemy): def __init__(self, game, name): super().__init__(game, name) self.body.angle = 0.5 * pi self.rect_offset = HF(124.374) self.rect.centerx = self.x + self.rect_offset * cos(self.body.angle) self.rect.centery = self.y - self.rect_offset * sin(self.body.angle) @staticmethod def start_pos(): return SCR_W2, HF(1280) def collide_bullet(self, bullet) -> bool: return (self.rect.colliderect(bullet.rect) and circle_collidepoint(*self.rect.center, self.radius + bullet.radius, bullet.x, bullet.y)) def move(self, dx, dy): self.x += dx self.y += dy self.rect.centerx = self.x + self.rect_offset * cos(self.body.angle) self.rect.centery = self.y - self.rect_offset * sin(self.body.angle) def update_pos(self, dt): self.weapons.update_pos() class BossHand(Enemy): def __init__(self, game, name): super().__init__(game, name) if self.name == "BossLeftHand": self.body.angle = -0.2 * pi else: self.body.angle = -0.8 * pi def start_pos(self): if self.name == "BossLeftHand": return SCR_W2 - HF(600), -HF(80) return SCR_W2 + HF(600), -HF(80) def update_pos(self, dt): self.weapons.update_pos() def make_enemy(game, name): if name == "BossHead": return BossHead(game, name) if name == "BossLeg": return BossLeg(game, name) if name in ("BossLeftHand", "BossRightHand"): return BossHand(game, name) return Enemy(game, name) __all__ = ["Enemy", "make_enemy"]

[ "ildar.239@mail.ru" ]

ildar.239@mail.ru

c8dcd6449bc4e03816534630d254503edabffe65

f42431fa2dd76706ebf694bd421e8416b9ba83a5

/training/train_with_action_masking_3/callbacks.py

6067e2a9855f116eb7ffc5acdced23c3cc65c800

[]

no_license

Woitoxx/bomberman-rl

95e633bc711ebd6f42914c68a7f7565199d58fba

6071bfcb5a8d4d5398e5c9e43221d83361932209

refs/heads/master

2023-03-26T13:10:52.269182

2021-03-29T13:34:44

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import copy import random from typing import Dict import numpy as np from ray.rllib import RolloutWorker, BaseEnv, Policy, SampleBatch from ray.rllib.agents.callbacks import DefaultCallbacks from ray.rllib.evaluation import MultiAgentEpisode class MyCallbacks(DefaultCallbacks): def __init__(self): super().__init__() self.policies = [] self.player_scores = [] self.opponent_scores = [] def on_episode_start(self, worker: RolloutWorker, base_env: BaseEnv, policies: Dict[str, Policy], episode: MultiAgentEpisode, **kwargs): pass def on_episode_step(self, worker: RolloutWorker, base_env: BaseEnv, episode: MultiAgentEpisode, **kwargs): pass def on_episode_end(self, worker: RolloutWorker, base_env: BaseEnv, policies: Dict[str, Policy], episode: MultiAgentEpisode, **kwargs): self.player_scores.append(episode.last_info_for(f'agent_0')) for i in range(1,4): self.opponent_scores.append(episode.last_info_for(f'agent_{i}')) def on_sample_end(self, worker: RolloutWorker, samples: SampleBatch, **kwargs): print(f'Player max score: {np.max(self.player_scores)}') print(f'Player avg score: {np.average(self.player_scores)}') print(f'Opp max score: {np.max(self.opponent_scores)}') print(f'Opp avg score: {np.average(self.opponent_scores)}') self.player_scores.clear() self.opponent_scores.clear() pass @staticmethod # probably no longer required def copy_weights(src_policy, dest_policy): P0key_P1val = {} # temp storage with "policy_0" keys & "policy_1" values for (k, v), (k2, v2) in zip(dest_policy.get_weights().items(), src_policy.items()): P0key_P1val[k] = v2 # set weights dest_policy.set_weights(P0key_P1val) def on_train_result(self, trainer, result: dict, **kwargs): print("trainer.train() result: {} -> {} episodes".format( trainer, result["episodes_this_iter"])) # Add current policy to the menagerie current_policy = trainer.get_policy('policy_01').get_weights() if result["policy_reward_mean"]["policy_01"] > 0.02 or len(self.policies) == 0: self.policies.append(current_policy) # Maintain only the latest 100 previous policies if len(self.policies) > 100: self.policies.pop(0) #self.copy_weights(current_policy if np.random.rand() > 0.2 else np.random.choice(self.policies), trainer.get_policy('policy_02')) # Choose either current policy (80%) or random previous policy (20%) for our opponents #new_policy = current_policy if np.random.rand() > 0.2 else random.choice(self.policies) #trainer.workers.foreach_worker(lambda w: w.get_policy('policy_02').set_weights(new_policy)) trainer.workers.foreach_worker(lambda w: self.copy_weights(current_policy if np.random.rand() > 0.2 else np.random.choice(self.policies), w.get_policy('policy_02'))) # Checkpoint if result["iterations_since_restore"] % 10 == 0: print(f'Checkpoint saved at iter {result["iterations_since_restore"]}') trainer.save() def on_postprocess_trajectory( self, worker: RolloutWorker, episode: MultiAgentEpisode, agent_id: str, policy_id: str, policies: Dict[str, Policy], postprocessed_batch: SampleBatch, original_batches: Dict[str, SampleBatch], **kwargs): pass

[ "15731141+Woitoxx@users.noreply.github.com" ]

15731141+Woitoxx@users.noreply.github.com

6fde26ec65ad1921499ea7fa51e39286788804c3

b21a81b7f8ad98c87321b735487c10069e6fc72a

/attendance/urls.py

08a5e7f46a8c08376ca3c2f4d83d6381095701d0

[]

no_license

cabilangan112/Attendace

2bf809a1ce6db849cc9dcf7f311600e453f52f9c

bfb4aa86293f4321cd2f121a5cdc957d61ea704a

refs/heads/master

2021-08-24T11:29:53.448940

2017-11-21T05:52:28

111,504,407

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UTF-8

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py

"""attendace URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.11/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import url from django.contrib import admin urlpatterns = [ url(r'^admin/', admin.site.urls), ]

[ "jassencabilangan@gmail.com" ]

jassencabilangan@gmail.com

c533d73f97e5d29a1450cb193a09ef1e06419fc7

bf01f2ee9dc903810dfaba3bff6dda56d31f41b9

/ctpnsource/lib/fast_rcnn/train.py

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[ "MIT" ]

permissive

cwxcode/OCR_caption_recognition

e978741ccae2889ceb9cda055e9694dad40b80b0

b2c5641e37e0d98b52e659ff42f549eb33840ea2

refs/heads/master

2020-04-07T01:31:35.243289

2018-11-17T03:42:45

157,943,881

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import numpy as np import os import tensorflow as tf from lib.roi_data_layer.layer import RoIDataLayer from lib.utils.timer import Timer from lib.roi_data_layer import roidb as rdl_roidb from lib.fast_rcnn.config import cfg _DEBUG = False class SolverWrapper(object): def __init__(self, sess, network, imdb, roidb, output_dir, logdir, pretrained_model=None): """Initialize the SolverWrapper.""" self.net = network self.imdb = imdb self.roidb = roidb self.output_dir = output_dir self.pretrained_model = pretrained_model print('Computing bounding-box regression targets...') if cfg.TRAIN.BBOX_REG: self.bbox_means, self.bbox_stds = rdl_roidb.add_bbox_regression_targets(roidb) print('done') # For checkpoint self.saver = tf.train.Saver(max_to_keep=100,write_version=tf.train.SaverDef.V2) self.writer = tf.summary.FileWriter(logdir=logdir, graph=tf.get_default_graph(), flush_secs=5) def snapshot(self, sess, iter): net = self.net if cfg.TRAIN.BBOX_REG and 'bbox_pred' in net.layers and cfg.TRAIN.BBOX_NORMALIZE_TARGETS: # save original values with tf.variable_scope('bbox_pred', reuse=True): weights = tf.get_variable("weights") biases = tf.get_variable("biases") orig_0 = weights.eval() orig_1 = biases.eval() # scale and shift with bbox reg unnormalization; then save snapshot weights_shape = weights.get_shape().as_list() sess.run(weights.assign(orig_0 * np.tile(self.bbox_stds, (weights_shape[0],1)))) sess.run(biases.assign(orig_1 * self.bbox_stds + self.bbox_means)) if not os.path.exists(self.output_dir): os.makedirs(self.output_dir) infix = ('_' + cfg.TRAIN.SNAPSHOT_INFIX if cfg.TRAIN.SNAPSHOT_INFIX != '' else '') filename = (cfg.TRAIN.SNAPSHOT_PREFIX + infix + '_iter_{:d}'.format(iter+1) + '.ckpt') filename = os.path.join(self.output_dir, filename) self.saver.save(sess, filename) print('Wrote snapshot to: {:s}'.format(filename)) if cfg.TRAIN.BBOX_REG and 'bbox_pred' in net.layers: # restore net to original state sess.run(weights.assign(orig_0)) sess.run(biases.assign(orig_1)) def build_image_summary(self): # A simple graph for write image summary log_image_data = tf.placeholder(tf.uint8, [None, None, 3]) log_image_name = tf.placeholder(tf.string) # import tensorflow.python.ops.gen_logging_ops as logging_ops from tensorflow.python.ops import gen_logging_ops from tensorflow.python.framework import ops as _ops log_image = gen_logging_ops._image_summary(log_image_name, tf.expand_dims(log_image_data, 0), max_images=1) _ops.add_to_collection(_ops.GraphKeys.SUMMARIES, log_image) # log_image = tf.summary.image(log_image_name, tf.expand_dims(log_image_data, 0), max_outputs=1) return log_image, log_image_data, log_image_name def train_model(self, sess, max_iters, restore=False): """Network training loop.""" data_layer = get_data_layer(self.roidb, self.imdb.num_classes) total_loss,model_loss, rpn_cross_entropy, rpn_loss_box=self.net.build_loss(ohem=cfg.TRAIN.OHEM) # scalar summary tf.summary.scalar('rpn_reg_loss', rpn_loss_box) tf.summary.scalar('rpn_cls_loss', rpn_cross_entropy) tf.summary.scalar('model_loss', model_loss) tf.summary.scalar('total_loss',total_loss) summary_op = tf.summary.merge_all() log_image, log_image_data, log_image_name =\ self.build_image_summary() # optimizer lr = tf.Variable(cfg.TRAIN.LEARNING_RATE, trainable=False) if cfg.TRAIN.SOLVER == 'Adam': opt = tf.train.AdamOptimizer(cfg.TRAIN.LEARNING_RATE) elif cfg.TRAIN.SOLVER == 'RMS': opt = tf.train.RMSPropOptimizer(cfg.TRAIN.LEARNING_RATE) else: # lr = tf.Variable(0.0, trainable=False) momentum = cfg.TRAIN.MOMENTUM opt = tf.train.MomentumOptimizer(lr, momentum) global_step = tf.Variable(0, trainable=False) with_clip = True if with_clip: tvars = tf.trainable_variables() grads, norm = tf.clip_by_global_norm(tf.gradients(total_loss, tvars), 10.0) train_op = opt.apply_gradients(list(zip(grads, tvars)), global_step=global_step) else: train_op = opt.minimize(total_loss, global_step=global_step) # intialize variables sess.run(tf.global_variables_initializer()) restore_iter = 0 # load vgg16 if self.pretrained_model is not None and not restore: try: print(('Loading pretrained model ' 'weights from {:s}').format(self.pretrained_model)) self.net.load(self.pretrained_model, sess, True) except: raise Exception('Check your pretrained model {:s}'.format(self.pretrained_model)) # resuming a trainer if restore: try: ckpt = tf.train.get_checkpoint_state(self.output_dir) print('Restoring from {}...'.format(ckpt.model_checkpoint_path), end=' ') self.saver.restore(sess, ckpt.model_checkpoint_path) stem = os.path.splitext(os.path.basename(ckpt.model_checkpoint_path))[0] restore_iter = int(stem.split('_')[-1]) sess.run(global_step.assign(restore_iter)) print('done') except: raise 'Check your pretrained {:s}'.format(ckpt.model_checkpoint_path) last_snapshot_iter = -1 timer = Timer() for iter in range(restore_iter, max_iters): timer.tic() # learning rate if iter != 0 and iter % cfg.TRAIN.STEPSIZE == 0: sess.run(tf.assign(lr, lr.eval() * cfg.TRAIN.GAMMA)) print(lr) # get one batch blobs = data_layer.forward() feed_dict={ self.net.data: blobs['data'], self.net.im_info: blobs['im_info'], self.net.keep_prob: 0.5, self.net.gt_boxes: blobs['gt_boxes'], self.net.gt_ishard: blobs['gt_ishard'], self.net.dontcare_areas: blobs['dontcare_areas'] } res_fetches=[] fetch_list = [total_loss,model_loss, rpn_cross_entropy, rpn_loss_box, summary_op, train_op] + res_fetches total_loss_val,model_loss_val, rpn_loss_cls_val, rpn_loss_box_val, \ summary_str, _ = sess.run(fetches=fetch_list, feed_dict=feed_dict) self.writer.add_summary(summary=summary_str, global_step=global_step.eval()) _diff_time = timer.toc(average=False) if (iter) % (cfg.TRAIN.DISPLAY) == 0: print('iter: %d / %d, total loss: %.4f, model loss: %.4f, rpn_loss_cls: %.4f, rpn_loss_box: %.4f, lr: %f'%\ (iter, max_iters, total_loss_val,model_loss_val,rpn_loss_cls_val,rpn_loss_box_val,lr.eval())) print('speed: {:.3f}s / iter'.format(_diff_time)) if (iter+1) % cfg.TRAIN.SNAPSHOT_ITERS == 0: last_snapshot_iter = iter self.snapshot(sess, iter) if last_snapshot_iter != iter: self.snapshot(sess, iter) def get_training_roidb(imdb): """Returns a roidb (Region of Interest database) for use in training.""" if cfg.TRAIN.USE_FLIPPED: print('Appending horizontally-flipped training examples...') imdb.append_flipped_images() print('done') print('Preparing training data...') if cfg.TRAIN.HAS_RPN: rdl_roidb.prepare_roidb(imdb) else: rdl_roidb.prepare_roidb(imdb) print('done') return imdb.roidb def get_data_layer(roidb, num_classes): """return a data layer.""" if cfg.TRAIN.HAS_RPN: if cfg.IS_MULTISCALE: # obsolete # layer = GtDataLayer(roidb) raise "Calling caffe modules..." else: layer = RoIDataLayer(roidb, num_classes) else: layer = RoIDataLayer(roidb, num_classes) return layer def train_net(network, imdb, roidb, output_dir, log_dir, pretrained_model=None, max_iters=40000, restore=False): """Train a Fast R-CNN network.""" config = tf.ConfigProto(allow_soft_placement=True) config.gpu_options.allocator_type = 'BFC' config.gpu_options.per_process_gpu_memory_fraction = 0.75 with tf.Session(config=config) as sess: sw = SolverWrapper(sess, network, imdb, roidb, output_dir, logdir= log_dir, pretrained_model=pretrained_model) print('Solving...') sw.train_model(sess, max_iters, restore=restore) print('done solving')

[ "kl1411@126.com" ]

kl1411@126.com

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/13/part1.py

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[]

no_license

zacharyliu/advent-of-code-2020

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''' Your ferry can make it safely to a nearby port, but it won't get much further. When you call to book another ship, you discover that no ships embark from that port to your vacation island. You'll need to get from the port to the nearest airport. Fortunately, a shuttle bus service is available to bring you from the sea port to the airport! Each bus has an ID number that also indicates how often the bus leaves for the airport. Bus schedules are defined based on a timestamp that measures the number of minutes since some fixed reference point in the past. At timestamp 0, every bus simultaneously departed from the sea port. After that, each bus travels to the airport, then various other locations, and finally returns to the sea port to repeat its journey forever. The time this loop takes a particular bus is also its ID number: the bus with ID 5 departs from the sea port at timestamps 0, 5, 10, 15, and so on. The bus with ID 11 departs at 0, 11, 22, 33, and so on. If you are there when the bus departs, you can ride that bus to the airport! Your notes (your puzzle input) consist of two lines. The first line is your estimate of the earliest timestamp you could depart on a bus. The second line lists the bus IDs that are in service according to the shuttle company; entries that show x must be out of service, so you decide to ignore them. To save time once you arrive, your goal is to figure out the earliest bus you can take to the airport. (There will be exactly one such bus.) For example, suppose you have the following notes: 939 7,13,x,x,59,x,31,19 Here, the earliest timestamp you could depart is 939, and the bus IDs in service are 7, 13, 59, 31, and 19. Near timestamp 939, these bus IDs depart at the times marked D: time bus 7 bus 13 bus 59 bus 31 bus 19 929 . . . . . 930 . . . D . 931 D . . . D 932 . . . . . 933 . . . . . 934 . . . . . 935 . . . . . 936 . D . . . 937 . . . . . 938 D . . . . 939 . . . . . 940 . . . . . 941 . . . . . 942 . . . . . 943 . . . . . 944 . . D . . 945 D . . . . 946 . . . . . 947 . . . . . 948 . . . . . 949 . D . . . The earliest bus you could take is bus ID 59. It doesn't depart until timestamp 944, so you would need to wait 944 - 939 = 5 minutes before it departs. Multiplying the bus ID by the number of minutes you'd need to wait gives 295. What is the ID of the earliest bus you can take to the airport multiplied by the number of minutes you'll need to wait for that bus? ''' def run(): cmds = [] earliest = {} with open('./input.txt') as f: time = int(f.readline().strip()) for t in f.readline().strip().split(','): if t == 'x': continue t = int(t) cur = 0 while cur < time: cur += t earliest[t] = cur best_id = None best = None for bus, t in earliest.items(): if best == None or t < best: best_id = bus best = t return best_id * (best - time) print(run())

[ "zach@zliu.io" ]

zach@zliu.io

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/project/app/models/tortoiseORM.py

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[]

no_license

AimVoma/fastapi-tdd-docker

87a4217bba5156dfb099ed46ab96530dbe177dd4

2046bda82d25a6fb824508a348eb829c7feb82e5

refs/heads/master

2023-05-09T05:20:37.985464

2021-05-29T17:04:10

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2021-06-06T19:08:03

2021-05-16T20:24:42

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py

# project/app/models/tortoise.py from tortoise import fields, models from tortoise.contrib.pydantic import pydantic_model_creator # new class TextSummary(models.Model): url = fields.TextField() summary = fields.TextField() created_at = fields.DatetimeField(auto_now_add=True) def __str__(self): return self.url SummarySchema = pydantic_model_creator(TextSummary) # new

[ "aim.voma@outlook.com" ]

aim.voma@outlook.com

aea11a35bba0d061397f5bdd20233c0cf6b90b7c

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/python/autscore/app/__init__.py

e9add9e0e15d85c5218949b4ee9361ae4a70d7df

[]

no_license

sunyinggang/w_project

e61619922a4ea2c27ac8f40242a211ecaf9fb7a3

2c65457e91d84fc39cd96d3e2e8010af03b1ddd0

refs/heads/master

2022-12-14T20:10:22.552572

2020-09-05T11:09:47

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2022-12-08T04:22:17

2020-01-15T01:01:52

HTML

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from flask import Flask from flask_sqlalchemy import SQLAlchemy app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = "mysql+pymysql://root:123456@localhost/wautscore" app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = True app.config['SECRET_KEY'] = '8906ced739ec4d3a80c0bcecfb15fb8c' app.debug = True db = SQLAlchemy(app) from app.home import home as home_blueprint from app.admin import admin as admin_blueprint from app.teacher import teacher as teacher_blueprint from app.student import student as student_blueprint app.register_blueprint(home_blueprint) app.register_blueprint(admin_blueprint, url_prefix="/admin") app.register_blueprint(teacher_blueprint, url_prefix="/teacher") app.register_blueprint(student_blueprint, url_prefix="/student")

[ "136080416@qq.com" ]

136080416@qq.com

b984ec0ae65ac9b2c3d218e69774959c6ec17e79

ed70c80a4dcd8438fd5873ad9f0166c49e51fb1d

/datasets/Vessels.py

4003140289681cb8eb281d4266f9060d74ae28af

[ "MIT" ]

permissive

texsmv/point_cloud_reconstruction

65ae96aee53c2eef4ee79947adba91c75de899cc

ef348b0884245c818674d2bb5e3ba05cc832a639

refs/heads/master

2021-11-30T20:55:30.757450

2021-11-20T06:07:14

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from os import listdir, makedirs, remove from os.path import exists, join import os import pickle import pandas as pd import numpy as np import itertools from torch.utils.data import Dataset from utils.data import load_obj, load_obj_features, basis_point_set_random, load_HKS_features class VesselDataset(Dataset): def __init__(self, root_dir = "D/3D Models", split = 'train'): self.root_dir = root_dir self.pc_names = [] self.categories = listdir(root_dir) #todo: some of the objets in these categories are corrupted self.categories.remove("Amphora") self.categories.remove("All Models") self.categories.remove("Modern-Glass") self.split = split self.get_names() def get_names(self): self.pc_names = [ [file for file in listdir(join(self.root_dir, category))] for category in self.categories] for i in range(len(self.categories)): for j in range(len(self.pc_names[i])): self.pc_names[i][j] = join(self.categories[i], self.pc_names[i][j]) if(self.split == 'train'): self.pc_names = [ pc[:int(0.85 * len(pc))] for pc in self.pc_names ] elif(self.split == 'test'): self.pc_names = [ pc[int(0.85 * len(pc)):] for pc in self.pc_names ] self.pc_names = list(itertools.chain.from_iterable(self.pc_names)) self.pc_names = np.array(self.pc_names) self.pc_names = self.pc_names.flatten() def __len__(self): return len(self.pc_names) def __getitem__(self, idx): pc_filename = self.pc_names[idx] pc_filepath = join(self.root_dir, pc_filename) sample = load_obj(pc_filepath) return sample, 0 class VesselDataset2(Dataset): def __init__(self, root_dir = "/media/D/Datasets/Tesis/SimplifiedManifolds"): # def __init__(self, root_dir = "/media/data/Datasets/Tesis/3D Models/Abstract"): self.root_dir = root_dir self.pc_names = [] self.get_names() def get_names(self): self.pc_names = np.array(listdir(self.root_dir)) self.pc_names.sort() def __len__(self): return len(self.pc_names) def __getitem__(self, idx): pc_filename = self.pc_names[idx] pc_filepath = join(self.root_dir, pc_filename) sample = load_obj(pc_filepath) return sample, 0 class VesselDataset_Pset(Dataset): def __init__(self, root_dir = "/home/texs/Documents/Repositorios/point_cloud_reconstruction/data/SimplifiedManifolds"): self.root_dir = root_dir self.pc_names = [] self.get_names() self.basis_pset = [] if os.path.exists("basis_pytorch.pkl"): self.basis_pset = pickle.load( open( "basis_pytorch.pkl", "rb" ) ) else: self.basis_pset = basis_point_set_random(1.0, 1000) pickle.dump( self.basis_pset, open( "basis_pytorch.pkl", "wb" ) ) def get_names(self): self.pc_names = np.array(listdir(self.root_dir)) self.pc_names.sort() def __len__(self): return len(self.pc_names) def __getitem__(self, idx): pc_filename = self.pc_names[idx] pc_filepath = join(self.root_dir, pc_filename) features, points = load_obj_features(pc_filepath, self.basis_pset) return features, points class VesselDataset_HKS1(Dataset): def __init__(self, root_dir_hks = "/home/texs/Documents/Repositorios/point_cloud_reconstruction/data/150", root_dir_pc = "/home/texs/Documents/Repositorios/point_cloud_reconstruction/data/SimplifiedManifolds"): self.root_dir_hks = root_dir_hks self.root_dir_pc = root_dir_pc self.pc_names = [] self.get_names() def get_names(self): self.pc_names = np.array(listdir(self.root_dir_pc)) self.pc_names.sort() self.pc_names_hks = np.array(listdir(self.root_dir_hks)) self.pc_names_hks.sort() def __len__(self): return len(self.pc_names) def __getitem__(self, idx): pc_filename = self.pc_names[idx] pc_filepath = join(self.root_dir_pc, pc_filename) pc_filename_hks = self.pc_names_hks[idx] pc_filepath_hks = join(self.root_dir_hks, pc_filename_hks) features, points = load_HKS_features(pc_filepath, pc_filepath_hks) return features, points class VesselDataset4(Dataset): def __init__(self, root_dir = "/home/texs/Documents/Repositorios/point_cloud_reconstruction/data/SimplifiedManifolds"): self.root_dir = root_dir self.pc_names = [] self.get_names() self.basis_pset = basis_point_set_random(1.0, 1000) def get_names(self): self.pc_names = np.array(listdir(self.root_dir)) self.pc_names.sort() def __len__(self): return len(self.pc_names) def __getitem__(self, idx): pc_filename = self.pc_names[idx] pc_filepath = join(self.root_dir, pc_filename) features, points = load_obj_features(pc_filepath, self.basis_pset) return features, points def get_noise(batch_size, n_points): return np.random.normal(size=(batch_size, n_points, 3))

[ "texs.mv@gmail.com" ]

texs.mv@gmail.com

9dd531a45b01bb96b38f0b077553e091a9191659

6daab8f7776ef1f7dcfa656e7caefe2c100d214a

/part05/if elif else.py

dff6bacbbc29328652a27175e3ce5fcfaf821d4d

[]

no_license

yoga-nugroho129/python-dasar-kelasterbuka

5b46bf20eb6fa5dfe4e58aa703c67c66bca83366

33dd66a01f048fea69d8e7775150905f55552eca

refs/heads/master

2022-07-16T16:42:45.768305

2020-05-21T04:00:03

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UTF-8

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py

### PENGKONDISIAN/PENGKONDISIAN nilai = 80 ### syntax if dalam python : ### if ..kondisi.. : ### ..aksi.. ### cara 1) dengan 'sama dengan' (==) if nilai == 75: print("Nilai anda", nilai) ### cara 2) dengan 'is' if nilai is 75: print("Nilai anda", nilai) ### NEGASI bisa dengan menggunakan '!=' atau 'is not' if nilai != 75: print("Nilai anda bukan 75") if 80 <= nilai <=100: print("Nilai anda A") elif 70 <= nilai <80: print("Nilai anda B") elif 60 <= nilai <70: print("Nilai anda C") elif 50 <= nilai <60: print("Nilai anda D") else: print("Anda Tidak Lulus, Nilai anda E") print(100*"-") ### pengkondisian dalam logika list/array ### cara 1 menu = ["pecel", "semur", "sate", "gule", "rendang"] beli = "soto" if beli in menu: print("Baik,", beli ,"akan segera kami antar") else: print("Maaf,",beli,"tidak ada pada menu") ### cara 2 beli2 = "sate" if beli2 not in menu: print("Maaf,",beli2,"tidak ada pada menu") else: print("Baik,", beli2, "akan segera kami proses") ### pengkondisian diatas bisa juga untuk memeriksa karakter dalam string maupun tipe data lain

[ "yoga.nugroho129@gmail.com" ]

yoga.nugroho129@gmail.com

af907f12b024fb1fc96229918c602bc5b99accf1

5f85a871faaffecf55f766cdd58d1ea6b48ad679

/natlas-server/app/auth/__init__.py

8695e60d1ef501afb4cb16063fe656b7e9f9d362

[ "Apache-2.0" ]

permissive

fdcarl/natlas

859bbd56cf08d1cfb7e7a9d40c80e690d8c231f9

551038f3b7100546721a9185e194107521abbfc5

refs/heads/main

2022-10-22T04:01:43.747947

2020-05-12T03:58:26

null

0

null

UTF-8

Python

false

114

py

from flask import Blueprint bp = Blueprint('auth', __name__) from app.auth import routes, wrappers # noqa: F401

[ "0xdade@users.noreply.github.com" ]

0xdade@users.noreply.github.com

626d43a51f20589955b459724b2c27d00796debf

43b50da74e752bc20bb3f71f04ad4b0d6b9d4d67

/6pro.py

0f5a2f7dc58a286421631edbb5fc357732f5d4a6

[]

no_license

abinayavarshini/python

a547b35b0790a863267a218bec7d052bfd397555

1f2a5298ff1dea92fa503e8ff9623cae0a18d558

refs/heads/master

2020-06-12T07:50:46.982132

2019-08-12T16:33:58

194,237,394

0

3

null

UTF-8

Python

false

244

py

gh1=int(input()) gh2=list(map(int,input().split())) ant=0 for j in range(len(gh2)-2): for k in range(j+1,len(gh2)-1): for l in range(k+1,len(gh2)): if gh2[j]<gh2[k]<gh2[l] and j<k<l: ant=ant+1 print(ant)

[ "noreply@github.com" ]

abinayavarshini.noreply@github.com

a3724821f4d69568eb22265b90af7dd176e3a666

e72f1268c4f2737ae24f27f250c6b36e795dd94b

/lesson5/hashtable_add.py

5f63c16200baf2435e9ee891a9c336548f4de74f

[]

no_license

maykjony90/intro_to_cs

33201aaf93114f5fb60cd22b58020d97b8fdd30c

39b52c566c7403163f99d8e18bdb5f2cf7e8228b

refs/heads/master

2021-01-20T13:10:47.726371

2017-10-09T20:56:05

90,456,852

0

null

UTF-8

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false

1,263

py

# Define a procedure, # # hashtable_add(htable,key,value) # # that adds the key to the hashtable (in # the correct bucket), with the correct # value and returns the new hashtable. # # (Note that the video question and answer # do not return the hashtable, but your code # should do this to pass the test cases.) def hashtable_add(htable,keyword,value): htable[hash_string(keyword, len(htable))].append([keyword, value]) return htable def hashtable_get_bucket(htable,keyword): return htable[hash_string(keyword,len(htable))] def hash_string(keyword,buckets): out = 0 for s in keyword: out = (out + ord(s)) % buckets return out def make_hashtable(nbuckets): table = [] for unused in range(0,nbuckets): table.append([]) return table #table = make_hashtable(5) #hashtable_add(table,'Bill', 17) #hashtable_add(table,'Coach', 4) #hashtable_add(table,'Ellis', 11) #hashtable_add(table,'Francis', 13) #hashtable_add(table,'Louis', 29) #hashtable_add(table,'Nick', 2) #hashtable_add(table,'Rochelle', 4) #hashtable_add(table,'Zoe', 14) #print table #>>> [[['Ellis', 11], ['Francis', 13]], [], [['Bill', 17], ['Zoe', 14]], #>>> [['Coach', 4]], [['Louis', 29], ['Nick', 2], ['Rochelle', 4]]]

[ "aykilkilic@gmail.com" ]

aykilkilic@gmail.com

79c1df71b44a8417307bb340d793675fc6e22870

5d42cfb9340f2b8bb3eae2de4fe459d16c1aba28

/Python_Challenge/PyBank/Main.py

66514060a866e3d41285372b3460c4a4442a6191

[]

no_license

saniyasule/Python-Challenge

c699e951c030867cbd242c0ed536e0161831bf99

948c948f784c209e957726fc7b04141a90ad979c

refs/heads/master

2020-09-23T13:25:21.501095

2020-03-10T14:59:08

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null

UTF-8

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2,101

py

import os import csv os.chdir(os.path.dirname(os.path.abspath(__file__))) csvpath = os.path.join('Resources', 'budget_data.csv') with open(csvpath) as csvfile: csvreader = (csv.reader(csvfile, delimiter=",")) csv_header = next(csvreader) sheet_row = [] sheet_column = [] maxandmin = [] for row in csvreader: date = row[0] profit_loss = row[1] sheet_row.append(date) sheet_column.append(profit_loss) row_count = len(sheet_column) #print (row_count) with open(csvpath) as csvfile: csvreader = (csv.reader(csvfile, delimiter=",")) csv_header = next(csvreader) total = sum(int(r[1]) for r in csv.reader(csvfile)) #print ("total: $" + str(total)) percent = sheet_column[0] #print (percent) percent1 = sheet_column[-1] #print (percent1) change = (int(percent1) - int(percent))/(int(row_count) -1) #print (change) i = 1 for i in range (1,len(sheet_column)): maxandmin.append(int(sheet_column[i]) - int(sheet_column[i-1])) max_change = max(maxandmin) min_change = min(maxandmin) #print (max_change) #print (min_change) max_date = str(sheet_row[maxandmin.index(max(maxandmin))+1]) min_date = str(sheet_row[maxandmin.index(min(maxandmin))+1]) #print (max_date) #print (min_date) os.chdir(os.path.dirname(os.path.abspath(__file__))) output_path = os.path.join("Resources", "pybanktxt.txt") with open(output_path, 'w', newline='') as txt_file: txt_file.write("Financial Analysis \n") txt_file.write("---------------------------------\n") txt_file.write(f"Total Months : {(row_count)} \n") txt_file.write(f"total: $ {(total)} \n") txt_file.write(f"Average Change: ${round(change, 2)} \n") txt_file.write(f"Greatest Increase in Profits: {(max_date)},(${(max_change)})\n") txt_file.write(f"Greatest Decrease in Profits: {(min_date)},(${(min_change)})\n")

[ "noreply@github.com" ]

saniyasule.noreply@github.com

1ae7156d2599d5a3a932e57176a82951011e5f59

4acabcefbdb4ddb8289bced532dc18adc4257558

/PA3/simple_de_bruijn.py

9208f5e47bbb120e0f43d25400a870ec34ea124e

[]

no_license

insomnolent/CM122-projects

29f59f5770900a32899edbd2d91da388cf4bed4e

67e3baaaaeafe6ed9f4d19bcd526db424c9237d9

refs/heads/master

2021-01-20T09:21:21.970979

2017-03-24T07:32:48

82,614,599

0

2

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UTF-8

Python

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3,502

py

from os.path import join import sys import time from collections import defaultdict, Counter import sys import os sys.path.insert(0, os.path.abspath("..")) sys.path.insert(0, os.path.abspath("../..")) from BIOINFO_M260B.helpers import read_reads def read_assembly_reads(read_fn): return read_reads(read_fn) def simple_de_bruijn(sequence_reads, k): """ Creates A simple DeBruijn Graph with nodes that correspond to k-mers of size k. :param sequence_reads: A list of reads from the genome :param k: The length of the k-mers that are used as nodes of the DeBruijn graph :return: A DeBruijn graph where the keys are k-mers and the values are the set of k-mers that """ de_bruijn_counter = defaultdict(Counter) # You may also want to check the in-degree and out-degree of each node # to help you find the beginnning and end of the sequence. for read in sequence_reads: # Cut the read into k-mers kmers = [read[i: i + k] for i in range(len(read) - k)] for i in range(len(kmers) - 1): pvs_kmer = kmers[i] next_kmer = kmers[i + 1] de_bruijn_counter[pvs_kmer].update([next_kmer]) # This line removes the nodes from the DeBruijn Graph that we have not seen enough. de_bruijn_graph = {key: {val for val in de_bruijn_counter[key] if de_bruijn_counter[key][val] > 2} for key in de_bruijn_counter} # This line removes the empty nodes from the DeBruijn graph de_bruijn_graph = {key: de_bruijn_graph[key] for key in de_bruijn_graph if de_bruijn_graph[key]} return de_bruijn_graph def de_bruijn_reassemble(de_bruijn_graph): """ Traverses the DeBruijn Graph created by simple_de_bruijn and returns contigs that come from it. :param de_bruijn_graph: A De Bruijn Graph :return: a list of the """ assembled_strings = [] while True: n_values = sum([len(de_bruijn_graph[k]) for k in de_bruijn_graph]) if n_values == 0: break good_starts = [k for k in de_bruijn_graph if de_bruijn_graph[k]] # You may want to find a better start # position by looking at in and out-degrees, # but this will work okay. current_point = good_starts[0] assembled_string = current_point while True: try: next_values = de_bruijn_graph[current_point] next_edge = next_values.pop() assembled_string += next_edge[-1] de_bruijn_graph[current_point] = next_values current_point = next_edge except KeyError: assembled_strings.append(assembled_string) break return assembled_strings if __name__ == "__main__": chr_name = 'hw3all_A_3_chr_1' input_folder = './{}'.format(chr_name) reads_fn = join(input_folder, 'reads_{}.txt'.format(chr_name)) reads = read_assembly_reads(reads_fn) db_graph = simple_de_bruijn(reads, 25) for k in db_graph.keys()[:40]: print k, db_graph[k] output = de_bruijn_reassemble(db_graph) output_fn_end = 'assembled_{}.txt'.format(chr_name) output_fn = join(input_folder, output_fn_end) with open(output_fn, 'w') as output_file: output_file.write('>' + chr_name + '\n') output_file.write('>ASSEMBLY\n') output_file.write('\n'.join(output))

[ "jbcccsun@gmail.com" ]

jbcccsun@gmail.com

c6f5ac6fea9aff3e441cf19f8b673b69c380f927

9cabe395035e3e344dcf0d83baa20bcdefec969e

/LibreriasFallidas/pippi-master/pippi/wavetables.py

13c3e839f624d7a92b869a91c0fd4cf27453e374

[]

no_license

dagomankle/LukeBox

11703ab6ea0079e98649f41e23b5f780e33d3611

2b86167f2c3f6717194751f2e6ee605fb48858a2

refs/heads/master

2020-03-12T17:50:11.556813

2018-04-23T19:29:52

130,737,144

0

null

UTF-8

Python

false

3,321

py

import collections import random import numpy as np from . import interpolation SINEWAVE_NAMES = set(('sin', 'sine', 'sinewave')) COSINE_NAMES = set(('cos', 'cosine')) TRIANGLE_NAMES = set(('tri', 'triangle')) SAWTOOTH_NAMES = set(('saw', 'sawtooth', 'ramp', 'line', 'lin')) RSAWTOOTH_NAMES = set(('isaw', 'rsaw', 'isawtooth', 'rsawtooth', 'reversesaw', 'phasor')) HANNING_NAMES = set(('hanning', 'hann', 'han')) HAMMING_NAMES = set(('hamming', 'hamm', 'ham')) BLACKMAN_NAMES = set(('blackman', 'black', 'bla')) BARTLETT_NAMES = set(('bartlett', 'bar')) KAISER_NAMES = set(('kaiser', 'kai')) SQUARE_NAMES = set(('square', 'sq')) ALL_WINDOWS = SINEWAVE_NAMES | TRIANGLE_NAMES | \ SAWTOOTH_NAMES | RSAWTOOTH_NAMES | \ HANNING_NAMES | HAMMING_NAMES | \ BLACKMAN_NAMES | BARTLETT_NAMES | \ KAISER_NAMES ALL_WAVETABLES = SINEWAVE_NAMES | COSINE_NAMES | \ TRIANGLE_NAMES | SAWTOOTH_NAMES | \ RSAWTOOTH_NAMES | SQUARE_NAMES def window(window_type=None, length=None, data=None): if data is not None: return interpolation.linear(data, length) wt = None if window_type == 'random': window_type = random.choice(list(ALL_WINDOWS)) if window_type in SINEWAVE_NAMES: wt = np.linspace(0, np.pi, length, dtype='d') wt = np.sin(wt) if window_type in TRIANGLE_NAMES: wt = np.linspace(0, 2, length, dtype='d') wt = np.abs(np.abs(wt - 1) - 1) if window_type in SAWTOOTH_NAMES: wt = np.linspace(0, 1, length, dtype='d') if window_type in RSAWTOOTH_NAMES: wt = np.linspace(1, 0, length, dtype='d') if window_type in HANNING_NAMES: wt = np.hanning(length) if window_type in HAMMING_NAMES: wt = np.hamming(length) if window_type in BARTLETT_NAMES: wt = np.bartlett(length) if window_type in BLACKMAN_NAMES: wt = np.blackman(length) if window_type in KAISER_NAMES: wt = np.kaiser(length, 0) if wt is None: return window('sine', length) return wt def wavetable(wavetable_type=None, length=None, duty=0.5, data=None): if data is not None: return interpolation.linear(data, length) wt = None if wavetable_type is None: wavetable_type = 'sine' elif wavetable_type == 'random': wavetable_type = random.choice(list(ALL_WAVETABLES)) if wavetable_type in SINEWAVE_NAMES: wt = np.linspace(-np.pi, np.pi, length, dtype='d', endpoint=False) wt = np.sin(wt) if wavetable_type in COSINE_NAMES: wt = np.linspace(-np.pi, np.pi, length, dtype='d', endpoint=False) wt = np.cos(wt) if wavetable_type in TRIANGLE_NAMES: wt = np.linspace(-1, 1, length, dtype='d', endpoint=False) wt = np.abs(wt) wt = (wt - wt.mean()) * 2 if wavetable_type in SAWTOOTH_NAMES: wt = np.linspace(-1, 1, length, dtype='d', endpoint=False) if wavetable_type in RSAWTOOTH_NAMES: wt = np.linspace(1, -1, length, dtype='d', endpoint=False) if wavetable_type in SQUARE_NAMES: wt = np.zeros(length) duty = int(length * duty) wt[:duty] = 1 wt[duty:] = -1 if wt is None: return wavetable('sine', length) return wt

[ "dagomankle@hotmail.com" ]

dagomankle@hotmail.com

61e355d3284db96cc11f987258d161aa7254a7af

5b2c920946732fb2c03f37a83220491230e39aff

/testlyt.py

19b2fc038a1b8a2d92b7195cdb0cbaccf461aabc

[]

no_license

gloriaiaiaiaia/test_123

2a4bb46f6b740696424d5a1b0bd23f86d3013267

2115b507bbe0403dc52c96115bc01fc3356b07e3

refs/heads/master

2021-07-05T14:53:40.310527

2017-09-29T17:31:11

105,297,462

0

null

2017-09-29T17:04:58

null

UTF-8

Python

false

52

py

ddddddddddddd jjkslaksl;ajodhqocdqwe jjkk kklklklll

[ "noreply@github.com" ]

gloriaiaiaiaia.noreply@github.com

09af47de6a19917c807d1f56ea540c3629f06085

02a680759a50f523a42d274d844b9a3b13d8b98e

/local_settings-example.py

37e2ad76384a6786467c1b9c69320b9298474dbe

[]

no_license

JuliFed/board_v2

86261772ac662e3347d757776eda3d728b8f653d

f15157633e0311ce21072941418bbcfb88f59ec9

refs/heads/master

2020-03-19T08:52:37.123119

2018-06-12T13:45:32

136,241,831

0

null

UTF-8

Python

false

244

py

import os basedir = os.path.abspath(os.path.dirname(__file__)) SQLALCHEMY_TRACK_MODIFICATIONS = False # SQLALCHEMY_DATABASE_URI = 'sqlite:///' + os.path.join(basedir,'app.db') # SQLALCHEMY_MIGRATE_REPO = os.path.join(basedir, 'db_repository')

[ "fedorchenkojuli@gmail.com" ]

fedorchenkojuli@gmail.com

54cc2229676d7ba820006f56c595adce01319a33

07e1f102993454350d0daaa8d61a11d4c018ca2f

/test4.py

f2341f6962b2cfc362321b945335e1bcccb1600a

[]

no_license

ravinkece/Selenium-WebDriver-Python-

cc117ae804e1306f4986fdb3138699394e752461

2d19cef2abf082578552544fc9934d85dc293edc

refs/heads/master

2020-04-01T19:57:51.323785

2020-01-14T04:23:55

153,580,711

0

1

null

2019-08-19T11:20:06

2018-10-18T07:21:53

Python

UTF-8

Python

false

282

py

import time from selenium import webdriver from selenium.common.exceptions import TimeoutException from selenium.webdriver.support.ui import Select from selenium.webdriver.common.keys import Keys driver = webdriver.Chrome() driver.get("http://google.com") print ("Ada")

[ "noreply@github.com" ]

ravinkece.noreply@github.com

3c71cf23f566faaac769fd3eb5aa1b028593dd60

bc9f66258575dd5c8f36f5ad3d9dfdcb3670897d

/lib/googlecloudsdk/command_lib/compute/scope.py

3d89de4a7553e92bbf964aee1d1f46b7782b7ab6

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

permissive

google-cloud-sdk-unofficial/google-cloud-sdk

05fbb473d629195f25887fc5bfaa712f2cbc0a24

392abf004b16203030e6efd2f0af24db7c8d669e

refs/heads/master

2023-08-31T05:40:41.317697

2023-08-23T18:23:16

335,182,594

9

2

NOASSERTION

2022-10-29T20:49:13

2021-02-02T05:47:30

Python

UTF-8

Python

false

1,976

py

# -*- coding: utf-8 -*- # # Copyright 2016 Google LLC. 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. """Definitiones compute scopes (locations).""" from __future__ import absolute_import from __future__ import division from __future__ import unicode_literals import enum from googlecloudsdk.core import exceptions from googlecloudsdk.core import properties class ScopeEnum(enum.Enum): """Enum representing GCE scope.""" ZONE = ('zone', 'a ', properties.VALUES.compute.zone.Get) REGION = ('region', 'a ', properties.VALUES.compute.region.Get) GLOBAL = ('global', '', lambda: None) def __init__(self, flag_name, prefix, property_func): # Collection parameter name matches command line file in this case. self.param_name = flag_name self.flag_name = flag_name self.prefix = prefix self.property_func = property_func @classmethod def CollectionForScope(cls, scope): if scope == cls.ZONE: return 'compute.zones' if scope == cls.REGION: return 'compute.regions' raise exceptions.Error( 'Expected scope to be ZONE or REGION, got {0!r}'.format(scope)) def IsSpecifiedForFlag(args, flag_name): """Returns True if the scope is specified for the flag. Args: args: The command-line flags. flag_name: The name of the flag. """ return (getattr(args, '{}_region'.format(flag_name), None) is not None or getattr(args, 'global_{}'.format(flag_name), None) is not None)

[ "cloudsdk.mirror@gmail.com" ]

cloudsdk.mirror@gmail.com

f687eba6bdacdff5305d1244a95c34500656513f

f43ef4a4291d65087407c1f1fd4bb0a532bf152d

/MoviesHub/views.py

b243e1ffc5e41b20cb76285222b56c3493add83a

[]

no_license

dheerajiiitv/Spoon

807f1d03e0fbadeaa4d2bd10794ddaeb72345752

4f1e99a3d860c0ba7b9ac63eea1fa96912d0ab00

refs/heads/master

2022-12-21T12:03:11.263825

2018-12-07T00:32:07

160,619,616

0

null

UTF-8

Python

false

4,197

py

from django.http import HttpResponse from django.shortcuts import render, redirect from django.contrib import messages import requests from threading import Thread from Spoon.settings import TMDB_KEY import queue import time # Create your views here. def index(request): # Function to show home page. if request.method == 'POST': # If user submitted a query query = request.POST.get('query') page = request.POST.get('page', 1) if query: link = "https://api.themoviedb.org/3/search/movie?api_key=" + TMDB_KEY + "&include_adult=true&query=" \ + query + "&page=" + str(page) response = requests.get(link) if response.status_code == 200: json_data = response.json() results = json_data['results'] page_no = json_data['page'] total_pages = json_data['total_pages'] return render(request, 'MoviesHub/movies_list.html', {'movies': results, 'query': query, 'page_no': page_no, 'total_pages': total_pages}) else: messages.error(request, "TMDB API not working") return redirect('MoviesHub:index') return render(request, 'MoviesHub/index.html') else: try: messages.error(request, "No query provided") except: print("error") return redirect('MoviesHub:index') # Call API else: return render(request, 'MoviesHub/index.html') def get_movie_details(request, movie_id): if movie_id: primary_info_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'?api_key='+TMDB_KEY alternative_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/alternative_titles?api_key='+TMDB_KEY cast_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/credits?api_key='+TMDB_KEY images_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/images?api_key='+TMDB_KEY plot_keywords_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/keywords?api_key='+TMDB_KEY release_info_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/release_dates?api_key='+TMDB_KEY videos_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/videos?api_key='+TMDB_KEY reviews_link = 'https://api.themoviedb.org/3/movie/'+str(movie_id)+'/reviews?api_key='+TMDB_KEY # Taking too much time (calling multiple API) Using threads # Queue is used to store all data data = queue.Queue() primary_info_data = GetData(primary_info_link,data,'primary_info_data') alternative_data = GetData(alternative_link,data,'alternative_data') cast_data = GetData(cast_link,data,'cast_data') images_data = GetData(images_link,data,'images_data') plot_keywords_data = GetData(plot_keywords_link,data,'plot_keywords_data') release_info_data = GetData(release_info_link,data,'release_info_data') videos_data = GetData(videos_link,data,'videos_data') reviews_data = GetData(reviews_link,data,'reviews_data') primary_info_data.start() alternative_data.start() cast_data.start() images_data.start() plot_keywords_data.start() release_info_data.start() videos_data.start() reviews_data.start() real_data = {} for d in range(8): temp = data.get() real_data[temp[0]] = temp[1] # Data Format return render(request, 'MoviesHub/movie_details.html', {'real_data':real_data}) else: redirect('MoviesHub:index') class GetData(Thread): def __init__(self, link,q, field): super(GetData, self).__init__() self.link = link self.q = q self.field = field def run(self): response = requests.get(self.link) if response.status_code == 200: temp = [] temp.append(self.field) temp.append(response.json()) self.q.put(temp) else: print('Error!', self.link) return {}

[ "dheeraj.agarwal@monoxor.com" ]

dheeraj.agarwal@monoxor.com

bf6b1db427afcec7a6112db1436fba53c06a09b2

ab3a53ef9f39e7124afa49a3de7c28359f036aff

/exemples/langue-bois.py

f02d7bb5c81b16701a90426544fe4df223c17379

[]

no_license

marcyves/Python-Pratique

19ae70525b9ef399ee76f1d6ae7297f411352fc2

d1104252eab688778e31b1cc7f5e4cdb178847e0

refs/heads/master

2021-08-16T21:36:54.580105

2018-10-13T10:34:54

134,450,855

1

0

null

UTF-8

Python

false

3,290

py

from random import randint fragment = [] fragment.append( [ "Mesdames, messieurs, ", "Je reste profondement persuadé que ", "Dès lors, sachez que je me battrai pour faire admettre que ", "Par ailleurs, c'est en toute connaissance de cause que je peux affirmer aujourd'hui que ", "Je tiens à vous dire ici ma détermination sans faille pour clamer haut et fort que ", "J'ai depuis longtemps (ai-je besoin de le rappeler ?), défendue l'idée que ", "Et c'est en toute conscience que je déclare avec conviction que ", "Et ce n'est certainement pas vous, mes chers compatriotes, qui me contredirez si je vous dis que ", ] ) fragment.append( [ "la conjoncture actuelle ", "la situation d'exclusion que certains d'entre vous connaissez ", "l'acuité des problèmes de la vie quotidienne ", "la volonté farouche de sortir notre pays de la crise ", "l'effort prioritaire en faveur du statut précaire des exclus ", "le particularisme dû à notre histoire unique ", "l'aspiration plus que légitime de chacun au progrès social ", "la nécessité de répondre à votre inquiétude journalière, que vous soyez jeune ou âgés ", ] ) fragment.append( [ "doit s'intégrer à la finalisation globale ", "oblige à la prise en compte encore plus effective ", "interpelle le citoyen que je suis et nous oblige tous à aller de l'avant dans la voie ", "a pour conséquence obligatoire l'urgente nécessité ", "conforte mon désir incontestable d'aller dans le sens ", "doit nous amener au choix réellement impératif ", "doit prendre en compte les préoccupations de la population de base dans l'élaboration ", "entraine une mission somme toute des plus exaltantes pour moi : l'élaboration ", ] ) fragment.append( [ "d'un processus allant vers plus d'égalité.", "d'un avenir s'orientant vers plus de progrès et plus de justice.", "d'une restructuration dans laquelle chacun pourra enfin retrouver sa dignité.", "d'une valorisation sans concession de nos caractères spécifiques.", "d'un plan coorespondant véritablement aux exigences légitimes de chacun.", "de solutions rapides correspondant aux grands axes sociaux prioritaires.", "d'un programme plus humain, plus fraternel et plus juste.", "d'un projet porteur de véritables espoirs, notamment pour les plus démunis.", ] ) # Welcome message print("\t- - - - - - - - - - - - - - - - - - - - - - - - -") print("\t Discours type ENA garanti avec langue de bois!!") print("\t- - - - - - - - - - - - - - - - - - - - - - - - -") # Loop on speeches loop = True while loop: print("\n\t- - - - - - - - - - - - - - - - - - - - - - - - -") print("\t Voici mon discours Pythonesque !") print("\t- - - - - - - - - - - - - - - - - - - - - - - - -") for col in range(4): i = randint(0, 7) print(fragment[col][i], end=" ") reponse = input("\n\nUn autre discours ? (o/n): ") if (reponse == "n") or (reponse == "N"): loop = False print("Merci d'utiliser notre générateur de discours Python")

[ "m.augier@me.com" ]

m.augier@me.com

f34f7b206662ef49703b1ecbd2f758bb64d2328f

8a090cf9d8d27f62a0024774792783f751599db8

/array-string/max-product-subarray.py

5ee822653017dd7268992a8a1f58634936552089

[]

no_license

kcaebe/interview-practice

1809964351fc7f81cc281cade18c2a1d85568b2b

a00847f49de646205ccb29f0619a8b6dead47cd0

refs/heads/master

2020-06-26T18:56:46.112861

2019-10-29T06:11:58

199,721,816

0

null

UTF-8

Python

false

435

py

def maxProd(nums): max_here = min_here = nums[0] tot_max = tot_min = nums[0] for i in range(1, len(nums)): num = nums[i] print(max_here, min_here ,num) max_here = max(num, max_here * num, min_here * num) min_here = min(num, max_here * num, min_here * num) tot_max = max(tot_max, max_here) tot_min = min(tot_min, min_here) return tot_max print(maxProd([2, 3, -2, 4]))

[ "kcaebe@gmail.com" ]

kcaebe@gmail.com

8b2e3aea484729669fff0e7f931cf7252b691257

e6c442ed80d147d53759985b8b34abe1af47ec8a

/blog/migrations/0001_initial.py

892a40b9013c1c2aa117c941a247abf7cc82db4a

[]

no_license

ConjureETS/site-2015

178db4b2693f2e4a6ae268eed40e3886dadc8f83

119fbd2b8215908b2ace9d4e03c2d594f0c8f124

refs/heads/master

2021-06-11T14:41:16.432678

2015-11-12T04:01:14

38,846,537

1

0

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# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ] operations = [ migrations.CreateModel( name='Article', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('title', models.CharField(max_length=50)), ('text', models.TextField()), ('author', models.CharField(max_length=20)), ('photo', models.ImageField(upload_to=b'article_photos')), ], options={ }, bases=(models.Model,), ), ]

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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 from ... import _utilities, _tables from . import outputs __all__ = ['Replication'] class Replication(pulumi.CustomResource): def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, location: Optional[pulumi.Input[str]] = None, registry_name: Optional[pulumi.Input[str]] = None, replication_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None, __name__=None, __opts__=None): """ An object that represents a replication for a container registry. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] location: The location of the resource. This cannot be changed after the resource is created. :param pulumi.Input[str] registry_name: The name of the container registry. :param pulumi.Input[str] replication_name: The name of the replication. :param pulumi.Input[str] resource_group_name: The name of the resource group to which the container registry belongs. :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: The tags of the resource. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() if location is None: raise TypeError("Missing required property 'location'") __props__['location'] = location if registry_name is None: raise TypeError("Missing required property 'registry_name'") __props__['registry_name'] = registry_name if replication_name is None: raise TypeError("Missing required property 'replication_name'") __props__['replication_name'] = replication_name if resource_group_name is None: raise TypeError("Missing required property 'resource_group_name'") __props__['resource_group_name'] = resource_group_name __props__['tags'] = tags __props__['name'] = None __props__['provisioning_state'] = None __props__['status'] = None __props__['type'] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:containerregistry/v20170601preview:Replication"), pulumi.Alias(type_="azure-nextgen:containerregistry/v20171001:Replication"), pulumi.Alias(type_="azure-nextgen:containerregistry/v20190501:Replication"), pulumi.Alias(type_="azure-nextgen:containerregistry/v20191201preview:Replication")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(Replication, __self__).__init__( 'azure-nextgen:containerregistry/latest:Replication', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'Replication': """ Get an existing Replication resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() return Replication(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter def location(self) -> pulumi.Output[str]: """ The location of the resource. This cannot be changed after the resource is created. """ return pulumi.get(self, "location") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the resource. """ return pulumi.get(self, "name") @property @pulumi.getter(name="provisioningState") def provisioning_state(self) -> pulumi.Output[str]: """ The provisioning state of the replication at the time the operation was called. """ return pulumi.get(self, "provisioning_state") @property @pulumi.getter def status(self) -> pulumi.Output['outputs.StatusResponse']: """ The status of the replication at the time the operation was called. """ return pulumi.get(self, "status") @property @pulumi.getter def tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ The tags of the resource. """ return pulumi.get(self, "tags") @property @pulumi.getter def type(self) -> pulumi.Output[str]: """ The type of the resource. """ return pulumi.get(self, "type") def translate_output_property(self, prop): return _tables.CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return _tables.SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

[ "public@paulstack.co.uk" ]

public@paulstack.co.uk

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/vmware_nsx/services/qos/common/utils.py

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yfauser/vmware-nsx

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refs/heads/master

2021-01-18T17:41:40.411620

2016-06-02T21:13:43

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2016-06-03T09:42:43

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# Copyright 2016 VMware, Inc. # # 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. from neutron.objects.qos import policy as qos_policy def update_network_policy_binding(context, net_id, new_policy_id): # detach the old policy (if exists) from the network old_policy = qos_policy.QosPolicy.get_network_policy( context, net_id) if old_policy: if old_policy.id == new_policy_id: return old_policy.detach_network(net_id) # attach the new policy (if exists) to the network if new_policy_id is not None: new_policy = qos_policy.QosPolicy.get_object( context, id=new_policy_id) if new_policy: new_policy.attach_network(net_id) def update_port_policy_binding(context, port_id, new_policy_id): # detach the old policy (if exists) from the port old_policy = qos_policy.QosPolicy.get_port_policy( context, port_id) if old_policy: if old_policy.id == new_policy_id: return old_policy.detach_port(port_id) # attach the new policy (if exists) to the port if new_policy_id is not None: new_policy = qos_policy.QosPolicy.get_object( context, id=new_policy_id) if new_policy: new_policy.attach_port(port_id)

[ "asarfaty@vmware.com" ]

asarfaty@vmware.com

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/scripts/sofi.py

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[]

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lifewinning/blackbox.finance

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2021-01-21T13:48:34.935530

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#!/usr/bin/python # MUST BE RUN AS ROOT (due to GPIO access) # # Required software includes Adafruit_Thermal, Python Imaging and PySerial # libraries. Other libraries used are part of stock Python install. # # Resources: # http://www.adafruit.com/products/597 Mini Thermal Receipt Printer # http://www.adafruit.com/products/600 Printer starter pack from __future__ import print_function import RPi.GPIO as GPIO import random, time, Image, socket from Adafruit_Thermal import * fanPin = 23 ledPin = 18 buttonPin = 25 printer = Adafruit_Thermal("/dev/ttyAMA0", 19200, timeout=5) def sofi(): GPIO.output(fanPin, True) x = random.randint(300,850) value = ["totally great","not great at all","great enough","not especially great"] v = random.choice(value) printer.doubleHeightOn() printer.setSize('L') printer.justify('C') printer.boldOn() printer.feed(5) printer.print(x) printer.feed(3) printer.print(v) printer.feed(5) def hold(): GPIO.output(ledPin, GPIO.HIGH) sofi() # Initialization # Use Broadcom pin numbers (not Raspberry Pi pin numbers) for GPIO GPIO.setmode(GPIO.BCM) # Enable LED and button (w/pull-up on latter) GPIO.setup(ledPin, GPIO.OUT) GPIO.setup(fanPin, GPIO.OUT) GPIO.output(fanPin, False) GPIO.setup(buttonPin, GPIO.IN, pull_up_down=GPIO.PUD_UP) # LED on while working GPIO.output(ledPin, GPIO.HIGH) # Processor load is heavy at startup; wait a moment to avoid # stalling during greeting. time.sleep(5) printer.feed(5) while True: if ( GPIO.input(buttonPin) == False ): print("Printing") sofi() GPIO.output(fanPin, False) print("Printed") time.sleep(.1) if KeyboardInterrupt: GPIO.cleanup()

[ "lifewinning@gmail.com" ]

lifewinning@gmail.com

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/instagramy/__init__.py

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2023-04-01T22:28:48.208118

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# -*- coding: utf-8 -*- """ Instagramy ~~~~~~~~~~ A python package for Instagram. It scarpe the Instagram contents. :license: MIT License """ __package__ = "instagramy" __description__ = "A python package for Instagram. It scarpe the Instagram contents." __url__ = "https://github.com/yogeshwaran01/instagramy" __version__ = "4.3" __author__ = "YOGESHWARAN R <yogeshin247@gmail.com>" __license__ = "MIT License" __copyright__ = "Copyright 2021 Yogeshwaran R" __all__ = ["InstagramUser", "InstagramHashTag", "InstagramPost"] from .InstagramUser import InstagramUser from .InstagramPost import InstagramPost from .InstagramHashTag import InstagramHashTag

[ "yogeshin247@gmail.com" ]

yogeshin247@gmail.com

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2022-12-27T04:12:43.470749

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import logging import azure.functions as func from ..common.response import make_response from pymongo import MongoClient def main(req: func.HttpRequest) -> func.HttpResponse: logging.info("Python HTTP trigger function processed a request.") email = req.params.get("email") if not email: return make_response({"msg": "Email not sent."}, 400) client = MongoClient( "mongodb://admin:admin@cluster0-shard-00-00-cty3m.azure.mongodb.net:27017,cluster0-shard-00-01-cty3m.azure.mongodb.net:27017,cluster0-shard-00-02-cty3m.azure.mongodb.net:27017/test?ssl=true&replicaSet=Cluster0-shard-0&authSource=admin&retryWrites=true&w=majority" ) db = client["inscribble"] prescriptions = db["prescriptions"] result = list( prescriptions.aggregate( [ {"$match": {"patientEmail": email}}, { "$lookup": { "from": "users", "localField": "doctorEmail", "foreignField": "email", "as": "member", } }, { "$project": { "_id": 1, "name": "$member.name", "createdOn": 1, } }, {"$unwind": "$name"}, ] ) ) for doc in result: doc["id"] = str(doc.pop("_id")) doc["createdOn"] = int(doc["createdOn"].timestamp() * 1000) return make_response({"data": result}, 200)

[ "shrey.batra@innovaccer.com" ]

shrey.batra@innovaccer.com

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/PythonImageAnalysis/GeometricalAnalysisForSUN/FullGeometricalFeaturesAnalysisForSUN.py

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manf1984/RemotePythonImageAnalysis

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2022-11-20T13:04:43.269068

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''' Created on 5 Jul 2020 @author: Andrea Manfrin ''' #Import of necessary Modules and Packages: import os import re from pathlib import Path import numpy as np import matplotlib.pyplot as plt import seaborn as sns import skimage from skimage.measure import label, regionprops import skimage.filters as skf import skimage.morphology as skm from skimage.measure._regionprops import RegionProperties from cellpose.models import Cellpose import math from scipy import stats from tifffile import TiffFile from tifffile import TiffWriter from scipy.ndimage.morphology import binary_fill_holes as fillHoles import timeit import pandas as pd #This is the folder that contains all the folders with the files of the extracted microwells and segmented aggregates: path = "/path/to/your/folder" #Calculate the conversion factor pixel/micrometers: pixelLength = 9723.41/13442 #Length in micrometers of a pixel (along one dimension). Total width in micrometers/total width in pixels pixelArea = pixelLength**2 #Area, in square micrometers, of a pixel. #This function takes a "mask" file path and returns the geometrical properties (only if the mask is composed of #exactly 1 particle, otherwise it returns a None type object). It returns a tuple containing the file name (e.g "01") #as first element and a "skimage.measure._regionprops.RegionProperties" object as second element of the tuple! def extractGeometryFromFile(file : str = ""): myFile = file mask = None with TiffFile(myFile) as tif: mask = tif.asarray() fileName = None listOfParticleProps = [] sepPatt = re.compile(os.sep) tifPatt = re.compile(r".tif+$") mo1 = re.split(sepPatt, myFile) mo2 = re.split(tifPatt, mo1[-1]) fileName = mo2[0] maskParticles = label(mask) props = regionprops(maskParticles) if len(props) == 1: return (fileName, props[0]) else: return None #This functions takes the path to a "/Mask" folder and applies the function "extractGeometryFromFile" to all the #"mask" files contained in it. It then returns a list of "skimage.measure._regionprops.RegionProperties" objects, #one per file. def processAWellFolder(folder : str = "") -> list: myFolder = Path(folder) filePatt = re.compile(r"^.*\.tif+$") fileList = [file.as_posix() for file in myFolder.iterdir() if file.is_file() and re.search(filePatt, file.as_posix())] fileList.sort() listOfParticles = [] for file in fileList: result = extractGeometryFromFile(file) if result != None: listOfParticles.append(result) else: pass return listOfParticles #This function takes the path of the folder containing all the folders of each well. It makes use of the function #"processAWellFolder" to process all the files contained in each folder (remeber that you have to add "/Mask" #to the path for "processAWellFolder"). It returns a dictionary where the "key" is a string corresponding to the #“folder/well name“ and it cotains as unique value (for each key) a list of all the "RegionProperties" objects associated #with that folder/well: def processAllFolders(path : str = "") -> dict: mainPath = Path(path) folderList = [folder.as_posix() for folder in mainPath.iterdir() if folder.is_dir()] folderList.sort() dictionaryAllWells = dict() for folder in folderList: maskPath = folder + "/Masks" separator = re.compile(os.sep) mo = re.split(separator, folder) wellName = mo[-1] regionsList = processAWellFolder(maskPath) dictionaryAllWells[wellName] = regionsList return dictionaryAllWells #It will be cool now to have a function that takes the dictionary, and build out of it a Pandas.DataFrame with the #value of all the geometrical parameters I want to analyze and a label corresponding to the name of the well/folder #in which the original file was stored. The function return this DataFrame. def createDataFrame(dictionary : dict = dict()): myDict = dictionary tempDict = {"Sample" : [], "Date" : [], "File_name" : [], "Area" : [], "Eccentricity" : [], "Major_Axis" : [], "Minor_Axis" : [], "Perimeter" : [], "Solidity" : [], "Plate_format" : [], "Treatment" : [], "Microwell_type" : [], "Microwell_diameter" : [], "Staining" : [], "Diameter_Of_Circle" : [], "Repetition" : []} for label in myDict: sepPatt = re.compile(r"_") mo = re.split(sepPatt, label) Date = mo[0] Plate_format = mo[1] Microwell_type = mo[2] Microwell_diameter = mo[3] Staining = mo[4] Treatment = mo[5] Repetition = mo[6] for elems in myDict[label]: tempDict["Sample"].append(label) tempDict["Date"].append(Date) tempDict["Plate_format"].append(Plate_format) tempDict["Microwell_type"].append(Microwell_type) tempDict["Microwell_diameter"].append(Microwell_diameter) tempDict["Staining"].append(Staining) tempDict["Treatment"].append(Treatment) tempDict["Repetition"].append(Repetition) #Extract from the tuple created by "extractGeometryFromFile" function the file name (= first element #of the tuple): tempDict["File_name"].append(elems[0]) #Extract all the geometrical parameters that are part of the "RegionProperties" object, which is the #second element of the tuple: tempDict["Area"].append(elems[1].area) tempDict["Eccentricity"].append(elems[1].eccentricity) tempDict["Major_Axis"].append(elems[1].major_axis_length) tempDict["Minor_Axis"].append(elems[1].minor_axis_length) tempDict["Perimeter"].append(elems[1].perimeter) tempDict["Solidity"].append(elems[1].solidity) tempDict["Diameter_Of_Circle"].append(elems[1].equivalent_diameter) #Create the Pandas.DataFrame from "tempDict": myData = pd.DataFrame(tempDict) #Process the values in "myData" DataFrame: #Calculate the "Circularity" parameter ((4*pi*Area)/(Perimeter^2)): myData["Circularity"] = (4*math.pi*myData["Area"]) / (myData["Perimeter"]**2) #Calculate the "Proper_Roundness", the one defined by this formula ( (4*Area)/(pi*Major_Axis^2) ): myData["Roundness"] = (4*myData["Area"]) / (math.pi*(myData["Major_Axis"]**2)) #Convert all the values that are in pixel-dimensions to micrometer-dimensions: myData["Area"] = myData["Area"]*pixelArea myData["Major_Axis"] = myData["Major_Axis"]*pixelLength myData["Minor_Axis"] = myData["Minor_Axis"]*pixelLength myData["Perimeter"] = myData["Perimeter"]*pixelLength myData["Diameter_Of_Circle"] = myData["Diameter_Of_Circle"]*pixelLength myData = myData[["Sample", "File_name", "Date", "Plate_format", "Microwell_type", "Microwell_diameter", "Staining", "Treatment", "Repetition", "Area", "Perimeter", "Diameter_Of_Circle", "Roundness", "Major_Axis", "Minor_Axis", "Circularity", "Eccentricity", "Solidity"]] return myData #EXECUTE THE CODE: #Create the DataFrame: myDictionary = processAllFolders(path) myData = createDataFrame(myDictionary) print(myData) #This functions takes a proper Pandas.DataFrame and represent the data in it in form of Seaborn violinplots: def violinPlotGeometry(df, xName : str = "Sample", yName : str = "", hueStr : str = None, fileName : str = "ViolinPlot"): fig, ax = plt.subplots(1) fig.suptitle(yName) sns.violinplot(x = xName, y = yName, data = df, ax = ax, hue = hueStr) ax.set_xticklabels(ax.get_xticklabels(), rotation = 45, horizontalalignment = "right") fig.set_size_inches(12, 6) plt.show(); fig.savefig(path + os.sep + fileName + ".pdf", dpi = 300, format = "pdf", bbox_inches = "tight") return fig, ax #This functions takes a proper Pandas.DataFrame and represent the data in it in form of Seaborn barplots #(average as height of bars and standard deviation reported as a line): def barPlotGeometry(df, xName : str = "Sample", yName : str = "", hueStr : str = None, fileName : str = "BarPlot"): fig, ax = plt.subplots(1) fig.suptitle(yName) sns.barplot(x = xName, y = yName, data = df, ci = "sd", hue = hueStr) ax.set_xticklabels(ax.get_xticklabels(), rotation = 45, horizontalalignment = "right") ax.set_ylabel(ax.get_ylabel() + " (Mean and SD)") fig.set_size_inches(12, 6) plt.show(); fig.savefig(path + os.sep + fileName + ".pdf", dpi = 300, format = "pdf", bbox_inches = "tight") return fig, ax #Strip plot function: def stripPlotGeometry(df, xName : str = "Sample", yName : str = "", hueStr : str = None, fileName : str = "StripPlot"): fig, ax = plt.subplots(1) fig.suptitle(yName) sns.stripplot(x = xName, y = yName, hue = hueStr, data = df, jitter = True, ax = ax) ax.set_xticklabels(ax.get_xticklabels(), rotation = 45, horizontalalignment = "right") fig.set_size_inches(12, 6) plt.show(); fig.savefig(path + os.sep + fileName + ".pdf", dpi = 300, format = "pdf", bbox_inches = "tight") return fig, ax #Swarm plot function: def swarmPlotGeometry(df, xName : str = "Sample", yName : str = "", hueStr : str = None, fileName : str = "SwarmPlot"): fig, ax = plt.subplots(1) fig.suptitle(yName) sns.swarmplot(x = xName, y = yName, hue = hueStr, data = df, ax = ax) ax.set_xticklabels(ax.get_xticklabels(), rotation = 45, horizontalalignment = "right") fig.set_size_inches(12, 6) plt.show(); fig.savefig(path + os.sep + fileName + ".pdf", dpi = 300, format = "pdf", bbox_inches = "tight") return fig, ax def boxPlotGeometry(df, xName : str = "Sample", yName : str = "", hueStr : str = None, fileName : str = "BoxPlot"): fig, ax = plt.subplots(1) fig.suptitle(yName) sns.boxplot(x = xName, y = yName, hue = hueStr, data = df, ax = ax) ax.set_xticklabels(ax.get_xticklabels(), rotation = 45, horizontalalignment = "right") fig.set_size_inches(12, 6) plt.show(); fig.savefig(path + os.sep + fileName + ".pdf", dpi = 300, format = "pdf", bbox_inches = "tight") return fig, ax #CREATE THE PLOTS: #Violin plot: violinPlotGeometry(myData, yName = "Area") #Various Bar plots: barPlotGeometry(myData, yName = "Area") barPlotGeometry(myData, yName = "Area", hueStr = "Plate_format", fileName = "BarPlotByPlateFormat") barPlotGeometry(myData, xName = "Microwell_diameter", yName = "Area", hueStr = "Plate_format", fileName = "BarPlotByPlateFormatAndMicrowellDiameter") #Strip plot: stripPlotGeometry(myData, yName = "Area") #Swarm plot: swarmPlotGeometry(myData, yName = "Area") #Box plot: boxPlotGeometry(myData, yName = "Area") #Here you can calculate various parameters from "myData" DataFrame: #Average Area per Sample: sampleGroup = myData.groupby("Sample") sampleGroup.agg(["mean", "std"]) summary = sampleGroup.agg(["mean", "std"]) myData.to_csv(path + os.sep + "Data.csv", index = False) summary.to_csv(path + os.sep + "DataSummary.csv", index = True)

[ "andrea@localhost" ]

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[]

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geegatomar/Django-DBMS

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from django import forms from .models import Items, ItemsCart class ItemsForm(forms.ModelForm): class Meta: model = Items fields = [ "item_name", "item_type", "item_details", "item_price", ] class ItemsCartForm(forms.ModelForm): class Meta: model = ItemsCart fields = [ ]

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""" WSGI config for Proba 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/2.1/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Proba.settings') application = get_wsgi_application()

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class Person(object): def __init__(self,name): self.name = name def getName(self): return self.name def isEmployee(self): return False #Inherited class class Employee(Person): # Here we return true def isEmployee(self): return True emp = Person("anyone") # An Object of Person print(emp.getName(), emp.isEmployee()) emp = Employee("karmanya") # An Object of Employee print(emp.getName(), emp.isEmployee())

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__author__ = "Adam Najman" #__sources__ == "CLRS" """ Adam Najman Python implementation of top-down (recursive) Matrix-chain Multiplication Adapted from CLRS """ import re import sys def print_best(s, i, j): if i == j: sys.stdout.write("A%i" % i) else: sys.stdout.write("(") print_best(s, i, s[i][j]) print_best(s, s[i][j]+1, j) sys.stdout.write(")") def rec_matrix_order(p): n = len(p) - 1 m = [[float("inf") for y in xrange(n + 1)] \ for x in xrange(n + 1)] #print m return lookup(m, p, 1, n) def lookup(m, p, i, j): if m[i][j] < float("inf"): return m[i][j] elif i == j: m[i][j] = 0 else: for k in xrange(i, j): q = ( lookup(m, p, i, k) + \ lookup(m, p, k + 1, j) + \ ( p[i-1]*p[k]*p[j] ) ) if q < m[i][j]: m[i][j] = q return m[i][j] f = sys.stdin#open('input.txt', 'rb') times = int(f.readline()) delim = " ", "x", "\n" patern = '|'.join(map(re.escape, delim)) #print "patern is: ", patern for x in f: foo = re.split(patern, x) foo = foo[:-1] #print foo matrix = [] for y in xrange(len(foo)): if y % 2 == 0: bar = (int(foo[y]), int(foo[y+1])) matrix.append(bar) print "matrix is: " print matrix param = [] for e in matrix: param.append(e[0]) if e == matrix[-1]: param.append(e[1]) print "\n" print "rec: " print rec_matrix_order(param)

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automobiles = ['lexus', 'bmw', 'tesla', 'acura'] print(f"I would like to own a {automobiles[0].title()} automobile.") print(f"I would like to own a {automobiles[1].title()} automobile.") print(f"I would like to own a {automobiles[2].title()} automobile.") print(f"I would like to own a {automobiles[3].title()} automobile.")

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import logging from ..service import Agent LOG = logging.getLogger(__name__) def match_agent(agents=None, any_agent=False): def match(item): if isinstance(item, Agent) and (any_agent or item in agents): return item elif isinstance(item, str): matches = {agent for agent in agents if agent.name.lower().startswith(item.lower()) or agent.real_name.lower().startswith(item.lower())} LOG.debug("matching agents for %s amongst %r", item, agents) if len(matches) == 1: return matches.pop() return match class BaseCommand: def welcome(self, srv=None, game=None, role=None): """Send an introductory message, if appropriate""" pass def on_message(self, srv=None, game=None, role=None, channel=None, text=None): """When a message is received by a player in a particular channel, handle it Text turns up as already split ready for matching.""" pass def ready(self, srv=None, game=None): """As a phase starts, these steps are called in order They should ready the scratchpad if required.""" def resolve(self, srv=None, game=None): """As a phase exits, these resolution phases are called in order They should update the scratchpad if required. Then they should make any reports required. Return None if there is no winner; otherwise, return the winner's side. The first resolution mechanism to declare a winner will be the value taken.""" return None def is_relevant(self, game=None): return game.current_phase['handler'].action_relevant(game=game, command=self) def notice(self, game=None, running=True): """Return any text to add to the day's notice `running` will be True if this phase is still going, or False if the phase is concluded. Return None - or Text to be appended to the game notice.""" return None

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from .video2events import DiffStream

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