def analyze_results(file_name, directory): mutants_list = os.path.join(directory, 'mutants') with open(mutants_list, 'rb') as handle: mutants = json.load(handle) for m in mutants: index = 0 print 'Processing mutants %d' % m['id'] instrumented_image = os.path.join(directory, '%s_%d.apk_%d.png' % (file_name, m['id'], index)) # print instrumented_image while(os.path.exists(instrumented_image)): original_image = os.path.join(directory, '%s.apk_%d.png' % (file_name, index)) # print original_image, instrumented_image similar, crashed = checkSimilarPictures(original_image, instrumented_image) m['crashed'] = crashed if not similar: m['killed'] = True break index += 1 instrumented_image = os.path.join(directory, '%s_%d.apk_%d.png' % (file_name, m['id'], index)) with open(mutants_list, 'wb') as handle: json.dump(mutants, handle) ReportGenerator.generateReport(mutants, directory)
def main(): print( 'Select an action: \n [1] Generate user report(default) \n [2] Generate library report \n [3] Send message \n [4] Use apt-get' ) action_type = input() rg = ReportGenerator() helper = InstalHelpers() if action_type == '1': pid = os.getpid() print('Select time period: \n [1] Week (default) \n [2] Month') time_period = input() if time_period == '2': rg.perform(helper.owner(pid), helper.get_ts_month_ago()) else: rg.perform(helper.owner(pid), helper.get_ts_week_ago()) elif action_type == '2': print('Select time period: \n [1] Week (default) \n [2] Month') time_period = input() print('Enter lib name:') lib = input() if time_period == '2': rg.get_db_lib_changes(helper.get_ts_month_ago(), lib) else: rg.get_db_lib_changes(helper.get_ts_week_ago(), lib) elif action_type == '3': print( 'Select addressee: \n [1] All online \n [2] All users \n [3] Concrete user(default)' ) addressee = input() if addressee == '1': print('Enter your message') msg = input() send_message_all_online(msg) elif addressee == '2': print('Enter your message') msg = input() send_message_all(msg) else: print('Enter user name') usr = input() print('Enter your message') msg = input() send_message_to_user(usr, msg) else: print( 'Select action: \n [1] Install(default) \n [2] Delete \n [3] Update' ) action = input() if action == '2': print('Enter lib name:') lib = input() subprocess.Popen(f"curl http://127.0.0.1:8000/delete?lib={lib}", shell=True) elif action == '3': subprocess.Popen(f"curl http://127.0.0.1:8000/update", shell=True) else: print('Enter lib name:') lib = input() subprocess.Popen(f"curl http://127.0.0.1:8000/add?lib={lib}", shell=True)
#from file_reader import FileReader #data = FileReader().read_power_stations_coordinates("testData.txt") #print(data) from report_generator import ReportGenerator report = ReportGenerator('graf') report.add_graph_points([2, 3, 7, 16]) report.set_params(333, 333, 333, 333, 333, 333) report.generate_graph()
('eu não consigo mais aguentar tudo isso', True), ('eu não pertenço mais a este mundo', True), ('a vida não tem mais graça', True), ('me sinto muito sozinho', True), ('eu choro todo o dia pois minha vida é horrível', True), ( 'vou te matar', False ), # intenção dessa frase é mostrar o tratamento feito na ordem das palavras ('me sinto muito bem', False), ('estou planejando viajar para o nordeste', False), ('a economia do brasil vai mal', False), ('o neymar é muito cai cai', False), ('me ferrei na prova porque estudei pouco, espero que sirva de lição para mim mesmo no futuro', False), ('amanhã eu vou jogar futebol com meus amigos, nunca mais joguei com eles', False), ('no dia do lixo eu me entupi de hamburguer coca cola', False), ('sexta-feira é dia de tomar uma gelada', False), ('adoro ficar no meu quarto olhando televisão', False), ('quero viver', False), ('eu te amo muito, quero viver com você pra sempre', False), ('pombos gostam de se alimentar na sombra das arvores', False), ('raposas são criaturas assustadoras', False), ('tenho medo de levantar sozinho pra tomar água no meio da noite', False) ] print('\nResultado\n===================================') report_generator = ReportGenerator(classifier) report = report_generator.generate(TEST_DATABASE) print(report)
from work_items_service import WorkItemsService from report_generator import ReportGenerator if __name__ == "__main__": service = WorkItemsService() work_items = service.get_my_work_items() generator = ReportGenerator() generator.create_monthly_report('.', work_items)
from report_generator import ReportGenerator from standard_output import StandardOutput from employee_dao import EmployeeDao if __name__ == '__main__': dao = EmployeeDao() output = StandardOutput() ReportGenerator(dao, output).print_employee_names()
def main(): args = readArgs() filename = args.file try: file = open(filename, 'r') file.close() except FileNotFoundError: print('=== ERROR ===', file=sys.stderr) print('Input file does not exist, check filename or path:', filename, file=sys.stderr) exit(1) outlier_label = args.outlier output_dir = args.output index = args.index if index < 0: index = None verbose = args.verbose file_type = filename.split('.')[-1] if verbose > 0: print() print('File:', filename) print('Type:', file_type) print('Outlier label:', outlier_label) print('Verbose level:', verbose) print('Index column:', index) print('Sheet:', args.sheet) print('JSON:', args.json) print() if file_type.lower() == 'csv': lp = log_parser.CSVLogParser(filename, index, outlier_label, verbose) elif file_type.lower() == 'json': lp = log_parser.JSONLogParser(filename, args.json, outlier_label, verbose) elif file_type.lower().startswith('xls'): lp = log_parser.ExcelLogParser(filename, args.sheet, index, outlier_label, verbose) else: print('=== ERROR ===', file=sys.stderr) print('Unknown file type:', file_type, file=sys.stderr) exit(1) try: parsed_dataset, original = lp.parse() except KeyError: print('=== ERROR ===', file=sys.stderr) print('Invalid outlier label:', outlier_label, file=sys.stderr) exit(1) if verbose > 0: print(parsed_dataset) global run run = True show_mem_usage = parsed_dataset.index.size > 25000 if show_mem_usage and verbose > 0: process = psutil.Process(os.getpid()) t = threading.Thread(target=memoryCounterFunc, args=(process, ), daemon=True) t.start() try: stats = dict() benchmarkAllAlgorithms(parsed_dataset, original, outlier_label, stats, verbose) except pd.core.indexing.IndexingError: print('=== ERROR ===', file=sys.stderr) print('Incorrect index column provided', file=sys.stderr) print( 'If no index is specified in the dataset pass -i -1 as a parameter to this benchmark', file=sys.stderr) exit(1) finally: if show_mem_usage: run = False t.join() rg = ReportGenerator(output_dir, verbose) rg.benchmarkReport(stats) print() print( '============================================================================' ) print( '| END OF BENCHMARK |' ) print( '============================================================================' ) print() return
def run_report_generator(view): report_generator = ReportGenerator(view) report_generator.run()
if to_empty_db: plyvel.destroy_db(db_connection_name) return plyvel.DB(db_connection_name, create_if_missing=True) db_connection = db_setup() location_generator = LocationGenerator() entity_report_factory = EntityReportFactory(DetectionIdGeneratorUUID(), location_generator) entity_report_update = EntityReportUpdate(location_generator) kafka_reporter = KafkaReporter(_kafka_broker_ip=broker_list, _topic=source_name + "-raw-data", _sync_action=(settings.to_only_create or settings.kafka_sync)) entities_manager = EntitiesManager(db_connection, entity_report_factory, entity_report_update, source_name) reporter = ReportGenerator(_entity_manager=entities_manager, _report_freq=entity_reporting_freq, _reporter=kafka_reporter, _number_of_reports=number_of_entities) if settings.to_only_create: reporter.single_generation() while True: import time time.sleep(1) else: reporter.generate()
def launchStrategyTester(self): print("Strategy Tester Running") # Open and read all test cases f = open(self.strategyTests, "r") strategyTests= (f.read()).splitlines() count =1 # Loop theough each test case and generate configuration files for i in strategyTests: platform = (i.split("|")[0]).lower() account = "Account:"+platform+"_demo" expert = "Expert:"+i.split("|")[1] period = "Period:"+i.split("|")[2] symbol = "Symbol:"+i.split("|")[3] mode = "StrategyTester:-" # Source of input must be in .txt format. # Destination must be in .set format if(platform=="mt4"): # Get all inputs for current Expert custom_inputs=glob.glob(os.path.join(self.mt4_custom_inputs_folder,i.split("|")[1],"*.set")) # input file for testing test_input = os.path.join(self.mt4_inputs,i.split("|")[1]+".set") elif(platform=="mt5"): # Get all inputs for current Expert custom_inputs=glob.glob(os.path.join(self.mt5_custom_inputs_folder,i.split("|")[1],"*.set")) # input file for testing test_input = os.path.join(self.mt5_inputs,i.split("|")[1]+".set") if(self.currentExpertName != i.split("|")[1]): self.currentExpertName=i.split("|")[1] #Save the report if(self.reportGenerator!=None): self.reportGenerator.saveReport() # Generate new report self.reportGenerator=ReportGenerator(i.split("|")[3],self.currentExpertName,custom_inputs,platform) for j in custom_inputs: shutil.copy(j,test_input) _input="Input: "+i.split("|")[1] print(_input) # Generate configuration file for current account, symbol, period and expert configGenerator = ConfigGenerator() configGenerator.generateConfigFile(account, period, expert, symbol,mode,_input,platform) # Now launch MT4 or MT5 if(platform=="mt4"): self.mtLauncher.launchMT4(account,1) # Launch MT4 elif(platform=="mt5"): self.mtLauncher.launchMT5(account,1) # Launch MT5 # TODO: Update report self.reportGenerator.updateReport(i.split("|")[3],i.split("|")[2],j) print("Test "+str(count)+" of "+str(len(strategyTests))+" completed") count+=1 # Move this out to save report only once. self.reportGenerator.saveReport() print("All tests complete...") repeated_list = self.reportGenerator.visualization_data["currency_pairs"] self.reportGenerator.visualization_data["currency_pairs"] = repeated_list[0:int(len(repeated_list)/2)] with open(self.reportGenerator.json_report, 'w') as outfile: json.dump(self.reportGenerator.visualization_data, outfile)