def metrics_initializer(m_data: dict, period='2y'):
"""Metrics Initializer
Keyword Arguments:
period {str} -- (default: {'2y'})
Returns:
list -- downloaded_data, sector_list, index, metrics_file data
"""
sectors = m_data['Components']
tickers = " ".join(sectors)
tickers = index_appender(tickers)
all_tickers = tickers.split(' ')
if isinstance(period, (list)):
period = period[0]
# tickers = index_appender(tickers)
print(" ")
print(f'Fetching Type Composite Index funds for {period}...')
data, _ = download_data_indexes(indexes=sectors,
tickers=all_tickers,
period=period,
interval='1d')
print(" ")
return data, sectors
def metrics_initializer(duration: str = 'short') -> list:
"""Metrics Initializer
Keyword Arguments:
duration {str} -- duration of view (default: {'short'})
Returns:
list -- data downloaded and sector list
"""
metrics_file = os.path.join("resources", "sectors.json")
if not os.path.exists(metrics_file):
return None, []
with open(metrics_file) as m_file:
m_data = json.load(m_file)
m_file.close()
m_data = m_data.get("Correlation")
sectors = m_data['tickers']
tickers = " ".join(m_data['tickers'])
START = m_data['start']
tickers = index_appender(tickers)
all_tickers = tickers.split(' ')
date = datetime.now().strftime('%Y-%m-%d')
print(" ")
print('Fetching Correlation Composite Index funds...')
if duration == 'short':
START = datetime.today() - timedelta(days=900)
START = START.strftime('%Y-%m-%d')
data, _ = download_data_indexes(indexes=all_tickers,
tickers=tickers,
start=START,
end=date,
interval='1d')
print(" ")
return data, sectors
def metrics_initializer(period='5y', name='Market Composite Index'):
"""Metrics Initializer
Keyword Arguments:
period {str/list} -- duration of view (default: {'5y'})
name {str} -- (default: {'Market Composite Index'})
Returns:
list -- data downloaded, sector list
"""
metrics_file = os.path.join("resources", "sectors.json")
if not os.path.exists(metrics_file):
print(f"{WARNING}WARNING: '{metrics_file}' not found for " +
f"'metrics_initializer'. Failed.{NORMAL_COLOR}")
return None, []
with open(metrics_file) as m_file:
m_data = json.load(m_file)
m_file.close()
m_data = m_data.get("Market_Composite")
sectors = m_data['tickers']
tickers = " ".join(m_data['tickers'])
tickers = index_appender(tickers)
all_tickers = tickers.split(' ')
if isinstance(period, (list)):
period = period[0]
print(" ")
print(f'Fetching {name} funds for {period}...')
data, _ = download_data_indexes(indexes=all_tickers,
tickers=tickers,
period=period,
interval='1d')
print(" ")
return data, sectors
def init_script(config: dict, **kwargs) -> list:
"""Init Script
Arguments:
config {dict} -- startup config object to control application
Optional Args:
release {str} -- 'dev' or 'prod' (default: {'prod'})
Returns:
list -- script: dataset, funds, periods, config
"""
release = kwargs.get('release', 'prod')
if release == 'dev':
config['process_steps'] = PROCESS_STEPS_DEV
elif release == 'prod':
config['process_steps'] = PROCESS_STEPS_PROD
if config['release'] == True:
# Use only after release!
print(" ")
if release == 'dev':
message = f"{HEADER_COLOR}~~~~ DEVELOPMENT VERSION ~~~~ "
message += f"[latest functionality, 'unclean' version]{NORMAL_COLOR}"
print(message)
config = start_header(update_release=_DATE_REVISION_DEV_,
version=_DEV_VERSION_,
options=True)
config['process_steps'] = PROCESS_STEPS_DEV
else:
if release == 'prod':
print(
f"{PROD_COLOR}~~~~ PRODUCTION ENVIRONMENT ~~~~{NORMAL_COLOR}")
print(" ")
if config['state'] == 'halt':
return
if 'function' in config['state']:
# If only simple functions are desired, they go into this handler
only_functions_handler(config)
return
if 'no_index' not in config['state']:
config['tickers'] = index_appender(config['tickers'])
config['process_steps'] = config['process_steps'] + 2
if 'debug' in config['state']:
print(f"{HEADER_COLOR}~~~~ DEBUG MODE ENABLED ~~~~ {NORMAL_COLOR}")
# Temporary directories to save graphs as images, etc.
remove_temp_dir()
configure_temp_dir()
dataset, funds, periods, config = download_data_all(config=config)
for period in dataset:
e_check = {'tickers': config['tickers']}
if has_critical_error(dataset[period], 'download_data', misc=e_check):
return None
return dataset, funds, periods, config