def wait_for_task_done_or_error(self, initial_task: 'Task'):
"""
Wait until the given task is DONE or ERROR
:param initial_task:
:return: The last state of the Task
"""
# Initialize web-socket connection
websocket = self.__init_ws_connection()
current_task = initial_task
bar = ChargingBar(current_task.type(), max=current_task.total_step())
bar.next(0)
if current_task.current_step_description() is not None:
bar.message = current_task.current_step_description()
while current_task.status() != Status.DONE and current_task.status(
) != Status.ERROR:
current_task = self.__wait_for_task_message(
websocket, initial_task)
bar.next()
bar.message = current_task.current_step_description()
bar.finish()
# Closing web-socket
websocket.close()
return current_task
def tag_dir(dir_path):
'''
Takes a directory at <dir_path>
Tags its content (audio files only) with metadata retrieved through the AcoustID API
'''
lth = 0
for _file in listdir(dir_path):
if is_audio_file(dir_path + '/' + _file):
lth += 1
bar = ChargingBar(max=lth, suffix='[%(index)d/%(max)d]')
for _file in listdir(dir_path):
song_path = dir_path + '/' + _file
if is_audio_file(song_path):
bar.message = INDENT + cyan_fg(_file) + '\n'
tag(song_path)
bar.next()
def process_default(out_file, algorithm):
global CONFIG
csv_file = open(out_file, 'w', newline='')
csv_writer = csv.writer(csv_file,
delimiter=' ',
quotechar='|',
quoting=csv.QUOTE_MINIMAL)
engine = create_engine(CONFIG['mysql'])
print(f'Processing with {algorithm} algorithm...')
stores = CONFIG['stores']
barcodes = CONFIG['barcodes']
periods = CONFIG['periods']
iter_cnt = len(stores) * len(barcodes) * len(periods)
bar = ChargingBar('Waiting...', max=iter_cnt)
bar.start()
for store_id in stores:
for barcode in barcodes:
bar.message = f'[Store: {store_id}] {str(barcode).ljust(13, " ")}'
bar.update()
df_barcode = get_barcode_daily_sales(engine, store_id, barcode)
for period in periods:
forecast_from_date = arrow.get(period['date'], 'DD.MM.YYYY')
forecast_before_date = forecast_from_date.shift(
days=period['days'])
forecast = do_forecast(algorithm, df_barcode,
forecast_from_date,
forecast_before_date)
csv_writer.writerow([
store_id, barcode, period['date'], period['days'], forecast
])
bar.next()
bar.finish()
csv_file.close()
print(f'\nDone. Result was written to {args.output}')
def create_dir_metadata(dir_path, sample_dir_path):
# Getting the number of audio files in <dir_path>
lth = 0
for _file in listdir(dir_path):
if is_audio_file(dir_path + '/' + _file):
lth += 1
# Retrieving metadata for audio files in <dir_path> while creating samples
metadata_tab = []
bar = ChargingBar(max=lth, suffix='[%(index)d/%(max)d]')
for _file in listdir(dir_path):
if is_audio_file(dir_path + '/' + _file):
bar.message = INDENT + cyan_fg(_file) + '\n'
start_time = time()
metadata_tab.append(
create_metadata(dir_path + '/' + _file, sample_dir_path))
end_time = time()
elapsed_time = end_time - start_time
print("\nSong exportation time : " + dim('{:02d}s:{:02d}cs'.format(
int(elapsed_time), int((elapsed_time % 1) * 100))))
bar.next()
return metadata_tab
def process_short(out_file, in_file, algorithm):
global CONFIG
beg_date = arrow.get('2019-10-01', 'YYYY-MM-DD')
end_date = arrow.get('2020-01-31', 'YYYY-MM-DD')
write_stdout(f'Forecast from {beg_date} to {end_date}\n') # 123 days
lines_count = 0
if wc and sed:
write_stdout(f'Counting {in_file} non-blank lines... ')
lines_count = int(wc(sed(r'/^\s*$/d', in_file), '-l'))
print(lines_count)
ops_count = lines_count * 123
out_csv_file = open(out_file, 'w', newline='')
in_csv_file = open(in_file, 'r', newline='\n')
csv_writer = csv.writer(out_csv_file,
delimiter=' ',
quotechar='|',
quoting=csv.QUOTE_MINIMAL)
csv_reader = csv.reader(in_csv_file, delimiter=',')
engine = create_engine(CONFIG['mysql'])
print(f'Processing short output with {algorithm} algorithm...')
bar = None
if ops_count > 0:
bar = ChargingBar('Waiting...', max=ops_count)
bar.start()
i = 0
dfs = {}
for row in csv_reader:
if row is not None and len(row):
store_id = int(row[0])
barcode = int(row[1])
key = f'{store_id}-{barcode}'
try:
df_barcode = dfs[key]
except KeyError:
df_barcode = get_barcode_daily_sales(engine, store_id, barcode)
dfs[key] = df_barcode
for j, d in enumerate(arrow.Arrow.range('day', beg_date,
end_date)):
forecast_from_date = d
forecast_before_date = forecast_from_date.shift(days=5)
forecast = do_forecast(algorithm, df_barcode,
forecast_from_date,
forecast_before_date)
csv_writer.writerow([int(round(forecast))])
if bar:
curr_op = i * 123 + j
if curr_op % 5 == 0:
bar.message = f'{curr_op} of {ops_count}'
bar.update()
bar.next()
i += 1
bar.message = 'Done'
bar.update()
out_csv_file.close()
in_csv_file.close()
engine = create_engine(config['mysql'])
print(f'Processing...')
stores = config['stores']
barcodes = config['barcodes']
periods = config['periods']
iter_cnt = len(stores) * len(barcodes) * len(periods)
bar = ChargingBar('Waiting...', max=iter_cnt)
bar.start()
for s in range(len(stores)):
store_id = stores[s]
for b in range(len(barcodes)):
barcode = barcodes[b]
bar.message = f'[Store: {store_id}] {str(barcode).ljust(13, " ")}'
bar.update()
df_barcode = get_barcode_daily_sales(engine, store_id, barcode)
for plot in range(len(periods)):
period = periods[plot]
today = arrow.get(period['date'], 'DD.MM.YYYY')
beg = today.shift(days=1)
end = beg.shift(days=period['days'])
sales = df_barcode.loc[beg.date():end.date()]
sales_sum = sales['quantity'].sum()
csv_writer.writerow([
store_id,