def main(parsed_args): pp_args(parsed_args) if 'key' in parsed_args.keys(): set_key_globals(int(parsed_args['key'])) else: set_key_globals(26) if 'old' in parsed_args.keys(): set_global_command(parsed_args['old']) else: set_global_command('ax64') runs, actions, passalong = genruns(parsed_args) comment(total_runs=len(runs), actions=actions, passalong=passalong) fname = 'runs.txt' comment('W {} runs to {}'.format(len(runs), fname)) pretty_print('W {} runs to {}'.format(len(runs), fname)) write_runs_to_file(runs, actions, passalong, fname) comment('=' * 16, 'running...') runs_output, vectors = do_runs(runs, actions, passalong) comment('=' * 16, 'done!') write_csv('times.csv', 'NO.,TIME', runs_output) write_csv('vectors.csv', 'IP,OP,KEY,ROUNDS,IV,LZS', vectors) comment('W {} runtimes to times.csv'.format(len(runs_output))) pretty_print('W {} runtimes to times.csv'.format(len(runs_output))) comment('W {} test vectors written vectors.csv'.format(len(vectors))) pretty_print('W {} test vectors written vectors.csv'.format(len(vectors)))
def drop_nones(): rows, header = helpers.load_csv(dirs.dirs_dict["discoveries"]["instagram"]) new_rows = list() for row in rows: if row["username"] and row["user_id"]: new_rows.append(row) helpers.write_csv(dirs.dirs_dict["discoveries"]["instagram"], new_rows, header) return
def write_ranks(rks_dict): discovery_list, discovery_header = helpers.load_csv(dirs.dirs_dict["discoveries"]["instagram"]) # fixes bug where some influencers are reported as None discovery_list = filter(lambda infl: bool(infl['username']), discovery_list) for i, el in enumerate(discovery_list): discovery_list[i]["pagerank"] = rks_dict[el["user_id"]] discovery_header.append("pagerank") discovery_list.sort(key=lambda k: k["pagerank"], reverse=True) helpers.write_csv(dirs.dirs_dict["discoveries"]["instagram"]+"-pageranked", discovery_list, discovery_header) return None
def drop_nones(): rows, header = helpers.load_csv(dirs.dirs_dict["discoveries"]["instagram"]) new_rows = list() for row in rows: if row['username'] and row['user_id']: new_rows.append(row) helpers.write_csv(dirs.dirs_dict["discoveries"]["instagram"], new_rows, header) return
def flush_info(self, subdir="profiles"): filename = dirs.dirs_dict[subdir][self.network] header = ["time_pulled"] + configs.profile_attributes to_write = {a: helpers.format_attr(getattr(self, a), a) for a in header} if not (to_write['user_id'] and to_write['username']): return helpers.write_csv(filename, [to_write,], header, write_type='a+') return to_write
def dedup(folder, network, on_keys): rows, header = helpers.load_csv(dirs.dirs_dict[folder][network]) if not rows: return stored_keys = set() new_rows = list() for row in rows: row_key = tuple(row[on_key] for on_key in on_keys) if row_key not in stored_keys: new_rows.append(row) stored_keys.add(row_key) helpers.write_csv(dirs.dirs_dict[folder][network], new_rows, header) return
def flush_follows(self): header = ["follower_id", "follows_id", "time_written"] if not self.follows: return None filename = dirs.dirs_dict["relationships"][self.network] all_follow_rows = self.get_follows() helpers.write_csv(filename, all_follow_rows, header, write_type='a+') # with open(filename, "a+") as f: # writer = csv.writer(f) # if (not os.path.isfile(filename)) or os.path.getsize(filename) == 0: # writer.writerow(header) # for follows_dict in all_follow_rows: # writer.writerow([follows_dict[h] for h in header]) return None
def write_ranks(rks_dict): discovery_list, discovery_header = helpers.load_csv( dirs.dirs_dict["discoveries"]["instagram"]) # fixes bug where some influencers are reported as None discovery_list = filter(lambda infl: bool(infl['username']), discovery_list) for i, el in enumerate(discovery_list): discovery_list[i]["pagerank"] = rks_dict[el["user_id"]] discovery_header.append("pagerank") discovery_list.sort(key=lambda k: k["pagerank"], reverse=True) helpers.write_csv( dirs.dirs_dict["discoveries"]["instagram"] + "-pageranked", discovery_list, discovery_header) return None
def main(rolls, write_csv, write_chart, plot_chart): """The main entrypoint.""" print(f"Running dice mode with {rolls} rolls.\n") data = run(rolls) df = helpers.get_df(data) print(df.to_string(index=False)) if write_csv: helpers.write_csv(df, 'dice', rolls) if write_chart: helpers.write_chart(df, 'dice', rolls) if plot_chart: helpers.plot_chart(df)
def flush_info(self, subdir="profiles"): filename = dirs.dirs_dict[subdir][self.network] header = ["time_pulled"] + configs.profile_attributes to_write = { a: helpers.format_attr(getattr(self, a), a) for a in header } if not (to_write['user_id'] and to_write['username']): return helpers.write_csv(filename, [ to_write, ], header, write_type='a+') return to_write
def run(): if args.tag != 0: db.edit_tag(args.tag, 1) elif len(args.diff) == 2: if args.reg: out = db.regressed_matches(args.diff[0], args.diff[1], args.modules) print(out) else: out = db.calc_diffs(args.diff[0], args.diff[1], args.modules) print(out) write_csv(out, diffs_columns, output=args.output, sort=False, delim=args.csvdelimiter) elif args.target: write_csv(db.regressed_matches_for_project(args.target[0], args.target[1], args.target[2], args.modules), diffs_columns, output=args.output, sort=False, delim=args.csvdelimiter) elif args.measures != 0: dbm = DatabaseMeasure(db, args.measures, args.modules) print("Precision for run " + str(args.measures) + ": " + str(dbm.precision())) print("Recall for run " + str(args.measures) + ": " + str(dbm.recall())) print("F1score for run " + str(args.measures) + ": " + str(dbm.f1score())) else: write_csv(db.calc_latest_diff(), diffs_columns, output=args.output, sort=False, delim=args.csvdelimiter) db.close()
continue score = score.split('\n') homescore = 0 awayscore = 0 if len(score) == 2: homescore = 2 elif len(score) == 3: homescore = 2 awayscore = 1 elif len(score) == 4: homescore = 3 awayscore = 1 elif len(score) == 5: homescore = 3 awayscore = 2 home_names.append(player1) away_names.append(player2) home_scores.append(homescore) away_scores.append(awayscore) tournaments.append(tournament) years.append(year) cities.append(city) countries.append(country) cols_name = ['Home', 'Away', 'Home Score', 'Away Score', 'Tournament', 'Year', 'City', 'Country'] cols = [home_names, away_names, home_scores, away_scores, tournaments, years, cities, countries] write_csv('1984-2005_tennis_matches.csv', cols_name, cols)
makedirs(download_dir, exist_ok=True) url = 'http://books.toscrape.com/' print('getting categories') categories = get_categories(url) for category in categories: print('\n' + 'getting books from ' + category['title'] + ':') books = get_books_from_category(category['url']) books_data = [] for book in books: books_data.append(get_book_data(book, category['title'])) print(' ' + books_data[-1]['title']) print('\n' + 'writing ' + category['title'] + '.csv') write_csv(download_dir + category['title'] + '.csv', books_data) print('') images_dir = download_dir + category['title'] + '/' makedirs(images_dir, exist_ok=True) for data in books_data: file_name = data['title'].replace("/", " - ") + ' - ' + \ data['universal product code (upc)'] + '.jpg' print('downloading ' + file_name) download_image(data['image url'], images_dir + file_name)
import random from helpers import write_csv cities_list = [] with open('cities.txt', 'r') as f: for line in f.readlines(): cities_list.append(line.strip()) ids = [] names = [] cities = [] lives_in_campus = [] i = 0 with open('students.txt', 'r') as f: for line in f.readlines(): if len(line.strip()) > 20: continue i += 1 ids.append(i) names.append(line.strip()) cities.append(random.choice(cities_list)) lives_in_campus.append(random.choice([True, False])) write_csv('students.csv', ['Id', 'Name', 'City', 'Lives in campus'], [ids, names, cities, lives_in_campus])
try: champion = winners.find_all( 'div', class_='tourney-detail-winner')[0].find('a').text.strip() except: continue details = tournament.find_all('td', class_='tourney-details') surface = details[1].find('span').text.strip() url = details[4].find('a')['href'] names.append(name) cities.append(city) countries.append(country) start_dates.append(start_date) prizes.append(prize) champions.append(champion) surfaces.append(surface) urls.append(url) years.append(year) cols_name = [ 'Tournament', 'City', 'Country', 'Start Date', 'Prize', 'Champion', 'Surface', 'URL', 'Year' ] cols = [ names, cities, countries, start_dates, prizes, champions, surfaces, urls, years ] write_csv('1975_2005_tennis_tournaments.csv', cols_name, cols)
transfer_end_date.append("-") else: transfer_end_date.append( transfer_join_date[-len(transfers) + i - 1]) cols_name = [ 'ManagerName', 'Nationality', 'WorkedInClub', 'Country', 'FromDate', 'ToDate', 'Position' ] cols = [ coaches_name, coaches_nationality, coaches_trained_teams, coaches_team_country, coaches_from_date, coaches_end_date, coaches_position ] write_csv('2_retired_managers_history.csv', cols_name, cols) cols_name = [ 'PlayerName', 'Nationality', 'Season', 'JoinDate', 'EndDate', 'LeftTeam', 'CountryLeftTeam', 'JoinedTeam', 'CountryJoinedTeam', 'Value' ] cols = [ transfer_player_name, transfer_player_nationality, transfer_season, transfer_join_date, transfer_end_date, transfer_left_team, transfer_left_team_country, transfer_joined_team, transfer_joined_team_country, transfer_value_or_type ] write_csv('2_retired_players_history.csv', cols_name, cols) print("Am salvat pentru link-ul: ", link)
import random from helpers import write_csv spec = ['Robotics', 'Algorithms', 'Semantics', 'Distributed Systems', 'Computer Graphics', 'Computer Architecture', 'Computer Systems'] ids = [] names = [] specializations = [] office_rooms = [] i = 0 with open('professors.txt', 'r') as f: for line in f.readlines(): if len(line.strip()) > 20: continue i += 1 ids.append(i) names.append(line.strip()) specializations.append(random.choice(spec)) dig1 = random.choice([i for i in range(1, 7)]) dig2 = random.choice([i for i in range(1, 9)]) office_rooms.append('PR' + str(dig1) + '0' + str(dig2)) write_csv('professors.csv', ['Id', 'Name', 'Specialization', 'Office'], [ids, names, specializations, office_rooms])
===== pentru verificare ===== print (player_name) for i in range(len(transfers)): print (transfer_join_date[-len(transfers) + i], " ", transfer_end_date[-len(transfers) + i]) print (transfer_season[-len(transfers) + i]) print (transfer_left_team[-len(transfers) + i]) print (transfer_joined_team[-len(transfers) + i]) print (transfer_value_or_type[-len(transfers) + i]) cols_name = ['TeamName', 'Country', 'NoPlayers', 'AvgAge', 'NoForeigners', 'TotalPlayersValue', 'Coach', 'AgeCouch', 'Stadium', 'StadiumCapacity'] cols = [team_names, countries, squads_no, avg_ages, no_foreigners, players_total_values, coaches, age_coaches, stadiums, stadiums_capacity] write_csv('teams.csv', cols_name, cols) cols_name = ['ManagerName', 'Nationality', 'WorkedInClub', 'CountryClub', 'FromDate', 'ToDate', 'Position'] cols = [coaches_name, coaches_nationality, coaches_trained_teams, coaches_team_country, coaches_from_date, coaches_end_date, coaches_position] write_csv('active_managers_history.csv', cols_name, cols) cols_name = ['PlayerName', 'Age', 'Birthdate', 'Nationality', 'Position', 'Club', 'TShirtNumber', 'Value', 'Captain'] cols = [player_names, player_ages, player_birth_dates, player_nationalities, players_positions, player_team_names, player_tshirt_numbers, player_values, captains] write_csv('players.csv', cols_name, cols) cols_name = ['PlayerName', 'Season','JoinDate', 'EndDate',
for row in rows[1:]: cols = row.find_all('td') if len(cols) == 1: championship = cols[0].find('img')['title'].strip() continue season = cols[0].findNext('a').text.strip() season = get_season(season) seasons.append(season) team = cols[2].text.strip() team_names.append(team) coach = cols[3].text.strip() if coach == "": coach = "-" coaches.append(coach) countries.append(country) championships.append(championship.replace(" ", "") + "_" + season) # cols_name = ['ChampionshipWinner', 'Season', 'Championship', 'Country', 'CoachWinner'] # cols = [team_names, seasons, championships, countries, coaches] # write_csv('championship_winner.csv', cols_name, cols) cols_name = ['ChampionshipWinner', 'Season', 'Championship', 'CoachWinner'] cols = [team_names, seasons, championships, coaches] write_csv('championsLeague_winners.csv', cols_name, cols) # cols_name = ['ChampionshipWinner', 'Season', 'Championship', 'CoachWinner'] # cols = [team_names, seasons, championships, coaches] # write_csv('europaLeague_winners.csv', cols_name, cols)
for i in range(0, len(dates)): print(dates[i]) for nr_page in range(14): current_url = f"{root_url}{dates[i]}&countryCode=all&rankPage={nr_page * 100 + 1}-{(nr_page + 1) * 100}" page = requests.get(current_url) soup = BeautifulSoup(page.content, "html.parser") players_table = soup.find('table', class_='mega-table') for player_row in players_table.find('tbody').find_all('tr'): player_name = player_row.find( 'td', class_='player-cell').find('a').text.strip() player_url = player_row.find( 'td', class_='player-cell').find('a')['href'] player_age = player_row.find('td', class_='age-cell').text.strip() player_rank = player_row.find('td', class_='rank-cell').text.strip() if player_name in already_saved_players or player_name in players_names: continue players_names.append(player_name) players_urls.append(player_url) players_age.append(player_age) players_rank.append(player_rank) cols_name = ['Name', 'URL', 'Age', 'Rank'] cols = [players_names, players_urls, players_age, players_rank] write_csv('new_tennis_players.csv', cols_name, cols)
tokens = cols[4].find('a').text.strip().split(":") if tokens[0] == '-' or len(tokens) == 1: continue home_teams.append(cols[3].find('img')['alt'].strip()) away_teams.append(cols[5].find('img')['alt'].strip()) home_scores.append(tokens[0]) if 'AET' in tokens[1]: tokens[1] = tokens[1][:tokens[1].index('AET') - 1] away_scores.append(tokens[1]) if int(tokens[0]) > int(tokens[1]): winners.append("HomeTeam") elif int(tokens[0]) < int(tokens[1]): winners.append("AwayTeam") else: winners.append("Draw") dates.append(date) stages.append(stage) filename = "Campionate/" + championship_name + "_" + year + "!" + str( int(year) + 1) + '.csv' cols_name = [ 'HomeTeam', 'AwayTeam', 'HomeScore', 'AwayScore', 'Winner', 'Stage', "Date" ] cols = [ home_teams, away_teams, home_scores, away_scores, winners, stages, dates ] write_csv(filename, cols_name, cols)
def sell_trade(etoro_instance): try: detail = "" # etoro_instance.login() logger.info( f"Going to get last Ordered Trades (For Opening Selling Position ) ..." ) lastOrderedTrades = helpers.lastOrderedTrade(isBuy=True) if not lastOrderedTrades: logger.info( f"No Last Ordered Trades found to open a selling position.") for t1, lastOrderedTrade in enumerate(lastOrderedTrades): instrumentID = lastOrderedTrade['InstrumentID'] instrumentData = helpers.find_instrument_by_id(instrumentID) lastOrderedTrade.update({ k: v for k, v in instrumentData.items() if k in ( "InstrumentDisplayName", "SymbolFull", ) }) instrumentSymbol = instrumentData["SymbolFull"] instrumentDisplayName = instrumentData["InstrumentDisplayName"] instrumentTitle = f"{instrumentSymbol} - {instrumentDisplayName}" positionID = lastOrderedTrade['PositionID'] logger.info( f"\n[{t1+1}/{len(lastOrderedTrades)}] :\n{lastOrderedTrade}\n") logger.info(f"Going to get User Trade History ...") tradeHistory = etoro_instance.get_trade_history closedOrder = helpers.isOrderClosed( positionID, data_list=tradeHistory, path=config.closed_trade_history_file) if not closedOrder: logger.info(f"<[{instrumentTitle}]: postionID->" f"{positionID} instrumentID->{instrumentID}>" " is not closed yet. skipping this...") continue # here opens a selling postion for this trade logger.info( f"Going to open Selling Trade for: {instrumentTitle}\n") sell_trade, sell_trade_res = etoro_instance.trade(ins=instrumentID, IsBuy=False) if sell_trade is False: detail = ( f"Couldnot open selling position for: '{instrumentTitle}'" f" reason :\n{sell_trade_res}\n") logger.warning(detail) else: detail = (f"Opened selling position for: '{instrumentTitle}'" f" response :\n{sell_trade_res}\n") logger.info(detail) logger.info(f"\nGoing to update User Date ...") user_data = etoro_instance.get_login_info logger.info(f"\nGot User Data :\n{user_data}\n") logger.info(f"\nGoing to update User Trade History ...") user_trade_history = etoro_instance.get_trade_history logger.info(f"\nGot User Trade History :\n{user_trade_history}\n") msg = "<sell_trade> finished ..." print('+' * len(msg)) print(msg) print('+' * len(msg)) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] err_detail = e, fname, exc_tb.tb_lineno detail = f"Following Error occured in sell_trade ::\n{err_detail}\n" logger.error(detail) #write trade logs helpers.write_csv("Selling", detail)
import csv import sys import json import os import glob import pandas as pd sys.path.append('../../helpers') from helpers import write_csv root_url = "http://ontheworldmap.com/all/cities/" page = requests.get(root_url) soup = BeautifulSoup(page.content, "html.parser") cities_cols = soup.find_all('div', class_='col-3') paranthesis = re.compile(r'\([^)]*\)') cities = set() for cities_col in cities_cols[:3]: for city_row in cities_col.find_all('li'): city_name = city_row.find('a').text city_name = re.sub(paranthesis, '', city_name).strip() cities.add(city_name) cols_name = ['City'] cols = [cities] write_csv('cities.csv', cols_name, cols)
def buy_trade(etoro_instance): try: detail = "" # etoro_instance.login() #checking current balance clientCredit = helpers.clientCredit( login_data=etoro_instance.get_login_info) open_markets_only = config.analyze_open_markets_only logger.info( f"Analyzing Today Stocks For {'opened' if open_markets_only else 'all'} markets ..." ) analyzer = AnalyzeStocks() top_markets = analyzer.today_price_analysis( stocks_sort_by=config.stocks_sort_by, time_slots_count=24, open_markets_only=open_markets_only, time_slots_pick=2) # top_markets = analyzer.trade_insights( # etoro_instance.get_insights(), # open_markets_only=open_markets_only, sort_by="growth") for t1, top_market in enumerate(top_markets): logger.info(f"\nGoing to open Buying Trade for :\n{top_market}\n") buy_trade, buy_trade_res = etoro_instance.trade( ins=top_market.get("InstrumentId"), IsBuy=True) if buy_trade is False: detail = ( f"Couldnot open buying position for: '{top_market.get('SymbolFull')}'" f" reason :\n{buy_trade_res}\n") logger.warning(detail) else: detail = ( f"Opened buying position for: '{top_market.get('SymbolFull')}'" f" response :\n{buy_trade_res}\n") logger.info(detail) break logger.info(f"\nGoing to update User Date ...") user_data = etoro_instance.get_login_info logger.info(f"\nGot User Data :\n{user_data}\n") logger.info(f"\nGoing to update User Trade History ...") user_trade_history = etoro_instance.get_trade_history logger.info(f"\nGot User Trade History :\n{user_trade_history}\n") msg = '<buy_trade> finished ...' print('+' * len(msg)) print(msg) print('+' * len(msg)) except Exception as e: exc_type, exc_obj, exc_tb = sys.exc_info() fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] err_detail = e, fname, exc_tb.tb_lineno detail = f"Following Error occured in buy_trade ::\n{err_detail}\n" logger.error(detail) #write trade logs helpers.write_csv("Buying", detail)
def run(): rootdir = os.path.dirname(os.path.dirname(__file__)) parser = argparse.ArgumentParser() parser.add_argument("target", help="project to work with (e.g. OpenFOAM, SU2)") parser.add_argument("-i", "--install", help="Install the project instead of running?", dest='install', default=False, action="store_true") parser.add_argument("-c", "--gencommands", help="Generate compile commands manually?", dest='gencommands', default=False, action="store_true") parser.add_argument( "--version", help= "Project version appendix (e.g. 6 for OpenFOAM-6, releases for SU2 7.0.0)", default="") parser.add_argument("-o", "--output", help="Name of output csv file", default="") parser.add_argument("-d", "--csvdelimiter", help="Delimiter for csv output", default=";") parser.add_argument( "--config", help="Name of config file or directory (default = project name + conf)", default="") parser.add_argument( "--oolint", help="Directory of OO-Lint(if automatic finding fails)", default="") parser.add_argument("--db", help="Database to interact with", default="") parser.add_argument("--diff", help="Differences of runs to show(list of 2 ids)", type=int, nargs=2, default=[]) args = parser.parse_args() if args.oolint == "": args.oolint = find_opovlint() if args.target == "OpenFOAM": pr = project.openFOAM elif args.target == "SU2": pr = project.su2 if args.config == "": config = args.target + "conf.json" else: config = args.config simple_columns = ["MatchType", "File", "Line", "Column", "Code", "Files"] pName = args.target if args.version != "": pName = pName + "-" + args.version elif args.target == "SU2": args.version = "6.2.0" if args.install or args.gencommands: if args.install: pr.setup(args.version) pr.environ(pName) if args.install: pr.preconfigure(args.version) pr.comgen(pName) else: if not os.path.exists(pName + "/compile_commands.json"): if not os.path.exists("compile_commands/" + pName + ".json"): print( "No pre-generated compile command database available, generate manually with --gencommands" ) else: replace_with("compile_commands/" + pName + ".json", pName + "/compile_commands.json", "[root]", os.getcwd()) if args.db != "": db = Database(args.db) target_list = extract_list(pName) conf_path = os.path.join(rootdir, "config/" + config) #support multiple configs if os.path.isdir(conf_path): accList = [] for conf in os.listdir(conf_path): accList += execute_find_type(target_list, pName, args.oolint, delim=args.csvdelimiter, config=conf_path + "/" + conf) if args.db != "": db.add_run(args.target, args.version, args.oolint, config=conf_path + "/" + conf) db.add_matches(accList, args.csvdelimiter) if args.output != "": write_csv(accList, simple_columns, output=args.output, delim=args.csvdelimiter) else: tList = execute_find_type(target_list, pName, args.oolint, delim=args.csvdelimiter, config=conf_path) if args.db != "": db.add_run(args.target, args.version, args.oolint, config=conf_path) db.add_matches(tList, args.csvdelimiter) if args.output != "": write_csv(tList, simple_columns, output=args.output, delim=args.csvdelimiter) if args.db != "": db.close()
def test_write_csv(self): convertfunc = lambda x: 0 if b'b' in x else 1 # convertfucntion for Prediction column to 0 if bg, and 1 if signal converters = {"Prediction": convertfunc} data = load_csv(self.path, converters=converters) write_csv(data, "test/test_write.csv")
#!/usr/bin/env python # coding: utf-8 import sys import argparse from helpers import load_input, anonymize_cols, write_csv if __name__ == '__main__': parser = argparse.ArgumentParser(description='Script para anonimizar clumnas en un CSV.') parser.add_argument('-c', '--columns' help='Columns to anonymize', required=True, nargs='*') parser.add_argument('-i', '--input', help='CSV que se desea anonimizar', required=True) parser.add_argument('-o', '--output', help='Nombre del Archivo de salida', required=True) args = parser.parse_args() # Load resource input_data = load_input(args.input) anonymized_data = anonymize_cols(input_data, args.columns) status = write_csv(anonymized_data, args.output) if status: print ('Se genero correctamente "%s".' % status) else: print ('Ocurrio un fallo a procesar el archivo: "%s".' % args.input)
print('Done dump') texts_list = [] titles_list = [] categories_list = [] url_list = [] source_list = [] date_list = [] for key in categories.keys(): if not texts[key] or not titles[key]: continue texts_list.append(texts[key]) titles_list.append(titles[key]) categories_list.append(categories[key]) url_list.append(url[key]) source_list.append(source[key]) date_list.append(date[key]) print('Writing csv') write_csv( "category_news.csv", ["Titles", "Texts", "Categories", "Url", "Source", "Date"], [ titles_list, texts_list, categories_list, url_list, source_list, date_list ], )
['Unity Games', 'Modelling', 'Animation'], ['CPU Analysis', 'Memory Analysis'], ['Operating Systems', 'Security', 'Compilers', 'Drivers']] ids = [] student_ids = [] professor_ids = [] thesis_areas = [] thesis_title = [] professors = pandas.read_csv('professors.csv') for i in range(1, 10000): ids.append(i) student_ids.append(i) prof = random.choice([i for i in range(1, 201)]) professor_ids.append(prof) specialization = professors.loc[prof - 1, 'Specialization'] specialization = spec.index(specialization) area = random.choice(areas[specialization]) thesis_areas.append(area) thesis_title.append(area + ' ' + str(random.choice([i for i in range(1, 101)]))) student_ids = random.sample(student_ids, len(student_ids)) write_csv('thesis.csv', ['Id', 'Student_id', 'Professor_id', 'Area', 'Title'], [ids, student_ids, professor_ids, thesis_areas, thesis_title])
tournaments.append('EuropaLeague_2014/2015') stadiums.append('PGE Narodowy') cities.append('Warsaw') countries.append('Poland') tournaments.append('EuropaLeague_2015/2016') stadiums.append('St. Jakob-Park') cities.append('Basel') countries.append('Switzerland') tournaments.append('EuropaLeague_2016/2017') stadiums.append('Friends Arena') cities.append('Stockholm') countries.append('Sweden') tournaments.append('EuropaLeague_2017/2018') stadiums.append('Groupama Stadium') cities.append('Lyon') countries.append('France') tournaments.append('EuropaLeague_2018/2019') stadiums.append('Baku Olympic Stadium') cities.append('Baku') countries.append('Azerbaijan') cols_name = ['Tournament', 'Stadium', 'City', 'Country'] cols = [tournaments, stadiums, cities, countries] write_csv('finals_stadiums.csv', cols_name, cols)
# Iterate through each covenant in a facility # If there is an invalid covenant then break and invalidate current facility for covenant in facility.covenants: if not covenant.valid_loan(loan): valid_facility = False break # If facility is valid check if it is cheaper than the current facility # If None assign automatically if valid_facility: if cheapest_facility is None: cheapest_facility = facility else: if cheapest_facility.interest_rate > facility.interest_rate: cheapest_facility = facility # Update the expected_yield and amount for the facility once a loan has been assigned # if the facility is not None if cheapest_facility is not None: cheapest_facility.update_expected_yield_and_amount(loan) facilities_loans_assignment[loan_id] = cheapest_facility.facility_id facility_yields = {} for bank_id, bank in banks.iteritems(): for facility_id, facility in bank.facilities.iteritems(): facility_yields[facility_id] = round(facility.expected_yield) write_csv('assignment.csv', ['load_id', 'facility_id'], facilities_loans_assignment) write_csv('yields.csv', ['facility_id', 'expected_yield'], facility_yields)