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)