def debug_msg(label, datafeed_type, msg_format, date_str, df):
"""debug_msg
Debug helper for debugging scrubbing handlers
:param label: log label
:param datafeed_type: fetch type
:param msg_format: message to include
:param date_str: date string
:param df: ``pandas DataFrame`` or ``None``
"""
msg = msg_format.format('_', date_str)
dft_msg = ''
if (datafeed_type == yahoo_consts.DATAFEED_PRICING_YAHOO
or datafeed_type == yahoo_consts.DATAFEED_OPTIONS_YAHOO
or datafeed_type == yahoo_consts.DATAFEED_NEWS_YAHOO):
dft_msg = yahoo_consts.get_datafeed_str_yahoo(df_type=datafeed_type)
elif (datafeed_type == td_consts.DATAFEED_TD_CALLS
or datafeed_type == td_consts.DATAFEED_TD_PUTS):
dft_msg = td_consts.get_datafeed_str_td(df_type=datafeed_type)
else:
dft_msg = iex_consts.get_datafeed_str(df_type=datafeed_type)
if ae_consts.ev('DEBUG_FETCH', '0') == '1':
if 'START' in msg:
log.info('{} - {} -------------------------'
'------------------------------------'.format(
label, dft_msg))
msg = msg_format.format(df, date_str),
if hasattr(df, 'empty'):
log.info('{} - {} - {} found df={} '
'columns={}'.format(label, dft_msg, msg, df,
df.columns.values))
else:
log.info('{} - {} - {} not df={}'.format(label, dft_msg, msg, df))
if 'END' in msg:
log.info('{} - {} -------------------------'
'------------------------------------'.format(
label, dft_msg))
else:
log.info('{} - {} - {}'.format(label, dft_msg, msg))
def extract_option_calls_dataset(
work_dict,
scrub_mode='sort-by-date'):
"""extract_option_calls_dataset
Extract the TD options calls for a ticker and
return it as a ``pandas.Dataframe``
:param work_dict: dictionary of args
:param scrub_mode: type of scrubbing handler to run
"""
label = '{}'.format(work_dict.get('label', 'extract'))
ds_id = work_dict.get('ticker')
df_type = td_consts.DATAFEED_TD_CALLS
df_str = td_consts.get_datafeed_str_td(df_type=df_type)
redis_key = work_dict.get(
'redis_key',
work_dict.get('tdcalls', 'missing-redis-key'))
s3_key = work_dict.get(
's3_key',
work_dict.get('tdcalls', 'missing-s3-key'))
redis_host = work_dict.get(
'redis_host',
None)
redis_port = work_dict.get(
'redis_port',
None)
redis_db = work_dict.get(
'redis_db',
ae_consts.REDIS_DB)
verbose = work_dict.get(
'verbose_td',
False)
if verbose:
log.info(
'{} - {} - start - redis_key={} s3_key={}'.format(
label,
df_str,
redis_key,
s3_key))
if not redis_host and not redis_port:
redis_host = ae_consts.REDIS_ADDRESS.split(':')[0]
redis_port = ae_consts.REDIS_ADDRESS.split(':')[1]
exp_date_str = None
calls_df = None
status = ae_consts.NOT_RUN
try:
redis_rec = redis_get.get_data_from_redis_key(
label=label,
host=redis_host,
port=redis_port,
db=redis_db,
password=work_dict.get('password', None),
key=redis_key,
decompress_df=True)
status = redis_rec['status']
if verbose:
log.info(
'{} - {} redis get data key={} status={}'.format(
label,
df_str,
redis_key,
ae_consts.get_status(status=status)))
if status == ae_consts.SUCCESS:
calls_json = None
if 'calls' in redis_rec['rec']['data']:
calls_json = redis_rec['rec']['data']['calls']
else:
calls_json = redis_rec['rec']['data']
if verbose:
log.info(
'{} - {} redis convert calls to df'.format(
label,
df_str))
exp_date_str = None
try:
calls_df = pd.read_json(
calls_json,
orient='records')
if len(calls_df.index) == 0:
return ae_consts.SUCCESS, None
if 'date' not in calls_df:
log.debug(
'failed to find date column in TD calls '
'df={}'.format(
calls_df,
len(calls_df.index)))
return ae_consts.SUCCESS, None
calls_df.sort_values(
by=[
'date',
'strike'
])
"""
for i, r in calls_df.iterrows():
print(r['date'])
convert_epochs = [
'ask_date',
'bid_date',
'trade_date'
]
for c in convert_epochs:
if c in calls_df:
calls_df[c] = pd.DatetimeIndex(pd.to_datetime(
calls_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT
)).tz_localize(
'UTC').tz_convert(
'US/Eastern')
# dates converted
"""
exp_date_str = (
calls_df['exp_date'].iloc[-1])
calls_df['date'] = calls_df['date'].dt.strftime(
ae_consts.COMMON_TICK_DATE_FORMAT)
except Exception as f:
log.error(
'{} - {} redis_key={} '
'no calls df found or ex={}'.format(
label,
df_str,
redis_key,
f))
return ae_consts.EMPTY, None
# end of try/ex to convert to df
if verbose:
log.info(
'{} - {} redis_key={} calls={} exp_date={}'.format(
label,
df_str,
redis_key,
len(calls_df.index),
exp_date_str))
else:
if verbose:
log.info(
'{} - {} did not find valid redis option calls '
'in redis_key={} status={}'.format(
label,
df_str,
redis_key,
ae_consts.get_status(status=status)))
except Exception as e:
log.debug(
'{} - {} - ds_id={} failed getting option calls from '
'redis={}:{}@{} key={} ex={}'.format(
label,
df_str,
ds_id,
redis_host,
redis_port,
redis_db,
redis_key,
e))
return ae_consts.ERR, None
# end of try/ex extract from redis
if verbose:
log.info(
'{} - {} ds_id={} extract scrub={}'.format(
label,
df_str,
ds_id,
scrub_mode))
scrubbed_df = scrub_utils.extract_scrub_dataset(
label=label,
scrub_mode=scrub_mode,
datafeed_type=df_type,
msg_format='df={} date_str={}',
ds_id=ds_id,
df=calls_df)
status = ae_consts.SUCCESS
return status, scrubbed_df
def extract_option_calls_dataset(ticker=None,
date=None,
work_dict=None,
scrub_mode='sort-by-date',
verbose=False):
"""extract_option_calls_dataset
Extract the TD options calls for a ticker and
return a tuple (status, ``pandas.Dataframe``)
.. code-block:: python
import analysis_engine.td.extract_df_from_redis as td_extract
# extract by historical date is also supported as an arg
# date='2019-02-15'
calls_status, calls_df = td_extract.extract_option_calls_dataset(
ticker='SPY')
print(calls_df)
:param ticker: string ticker to extract
:param date: optional - string date to extract
formatted ``YYYY-MM-DD``
:param work_dict: dictionary of args
:param scrub_mode: optional - string type of
scrubbing handler to run
:param verbose: optional - boolean for turning on logging
"""
label = 'extract_td_calls'
latest_close_date = ae_utils.get_last_close_str()
use_date = date
if work_dict:
if not ticker:
ticker = work_dict.get('ticker', None)
label = f'{work_dict.get("label", label)}'
if not use_date:
use_date = latest_close_date
ds_id = ticker
df_type = td_consts.DATAFEED_TD_CALLS
df_str = td_consts.get_datafeed_str_td(df_type=df_type)
redis_db = ae_consts.REDIS_DB
redis_key = f'{ticker}_{use_date}_tdcalls'
redis_host, redis_port = ae_consts.get_redis_host_and_port(req=work_dict)
redis_password = ae_consts.REDIS_PASSWORD
s3_key = redis_key
if work_dict:
redis_db = work_dict.get('redis_db', redis_db)
redis_password = work_dict.get('redis_password', redis_password)
verbose = work_dict.get('verbose_td', verbose)
if verbose:
log.info(f'{label} - {df_str} - start - redis_key={redis_key} '
f's3_key={s3_key}')
exp_date_str = None
calls_df = None
status = ae_consts.NOT_RUN
try:
redis_rec = redis_get.get_data_from_redis_key(label=label,
host=redis_host,
port=redis_port,
db=redis_db,
password=redis_password,
key=redis_key,
decompress_df=True)
status = redis_rec['status']
if verbose:
log.info(f'{label} - {df_str} redis get data key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
if status == ae_consts.SUCCESS:
calls_json = None
if 'tdcalls' in redis_rec['rec']['data']:
calls_json = redis_rec['rec']['data']['tdcalls']
elif 'calls' in redis_rec['rec']['data']:
calls_json = redis_rec['rec']['data']['calls']
else:
calls_json = redis_rec['rec']['data']
if not calls_json:
return ae_consts.SUCCESS, pd.DataFrame([])
if verbose:
log.info(f'{label} - {df_str} redis convert calls to df')
exp_date_str = None
try:
calls_df = pd.read_json(calls_json, orient='records')
if len(calls_df.index) == 0:
return ae_consts.SUCCESS, pd.DataFrame([])
if 'date' not in calls_df:
if verbose:
log.error(
'failed to find date column in TD calls '
f'df={calls_df} from lens={len(calls_df.index)}')
return ae_consts.SUCCESS, pd.DataFrame([])
calls_df.sort_values(by=['date', 'strike'])
"""
for i, r in calls_df.iterrows():
print(r['date'])
convert_epochs = [
'ask_date',
'bid_date',
'trade_date'
]
for c in convert_epochs:
if c in calls_df:
calls_df[c] = pd.DatetimeIndex(pd.to_datetime(
calls_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT
)).tz_localize(
'UTC').tz_convert(
'US/Eastern')
# dates converted
"""
exp_date_str = (calls_df['exp_date'].iloc[-1])
calls_df['date'] = calls_df['date'].dt.strftime(
ae_consts.COMMON_TICK_DATE_FORMAT)
except Exception as f:
not_fixed = True
if ('Can only use .dt accessor with '
'datetimelike values') in str(f):
try:
log.critical(f'fixing dates in {redis_key}')
# remove epoch second data and
# use only the millisecond date values
bad_date = ae_consts.EPOCH_MINIMUM_DATE
calls_df['date'][calls_df['date'] < bad_date] = None
calls_df = calls_df.dropna(axis=0, how='any')
fmt = ae_consts.COMMON_TICK_DATE_FORMAT
calls_df['date'] = pd.to_datetime(
calls_df['date'], unit='ms').dt.strftime(fmt)
not_fixed = False
except Exception as g:
log.critical(
f'failed to parse date column {calls_df["date"]} '
f'with dt.strftime ex={f} and EPOCH EX={g}')
return ae_consts.SUCCESS, pd.DataFrame([])
# if able to fix error or not
if not_fixed:
log.debug(f'{label} - {df_str} redis_key={redis_key} '
f'no calls df found or ex={f}')
return ae_consts.SUCCESS, pd.DataFrame([])
# if unable to fix - return out
log.error(f'{label} - {df_str} redis_key={redis_key} '
f'no calls df found or ex={f}')
return ae_consts.SUCCESS, pd.DataFrame([])
# end of try/ex to convert to df
if verbose:
log.info(
f'{label} - {df_str} redis_key={redis_key} '
f'calls={len(calls_df.index)} exp_date={exp_date_str}')
else:
if verbose:
log.info(f'{label} - {df_str} did not find valid redis '
f'option calls in redis_key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
except Exception as e:
if verbose:
log.error(
f'{label} - {df_str} - ds_id={ds_id} failed getting option '
f'calls from redis={redis_host}:{redis_port}@{redis_db} '
f'key={redis_key} ex={e}')
return ae_consts.ERR, pd.DataFrame([])
# end of try/ex extract from redis
if verbose:
log.info(
f'{label} - {df_str} ds_id={ds_id} extract scrub={scrub_mode}')
scrubbed_df = scrub_utils.extract_scrub_dataset(
label=label,
scrub_mode=scrub_mode,
datafeed_type=df_type,
msg_format='df={} date_str={}',
ds_id=ds_id,
df=calls_df)
status = ae_consts.SUCCESS
return status, scrubbed_df
def extract_option_puts_dataset(work_dict, scrub_mode='sort-by-date'):
"""extract_option_puts_dataset
Extract the TD options puts for a ticker and
return it as a ``pandas.Dataframe``
:param work_dict: dictionary of args
:param scrub_mode: type of scrubbing handler to run
"""
label = f'{work_dict.get("label", "extract")}'
ds_id = work_dict.get('ticker')
df_type = td_consts.DATAFEED_TD_PUTS
df_str = td_consts.get_datafeed_str_td(df_type=df_type)
redis_key = work_dict.get('redis_key',
work_dict.get('tdputs', 'missing-redis-key'))
s3_key = work_dict.get('s3_key', work_dict.get('tdputs', 'missing-s3-key'))
redis_host = work_dict.get('redis_host', None)
redis_port = work_dict.get('redis_port', None)
redis_db = work_dict.get('redis_db', ae_consts.REDIS_DB)
verbose = work_dict.get('verbose_td', False)
if verbose:
log.info(f'{label} - {df_str} - start - redis_key={redis_key} '
f's3_key={s3_key}')
if not redis_host and not redis_port:
redis_host = ae_consts.REDIS_ADDRESS.split(':')[0]
redis_port = ae_consts.REDIS_ADDRESS.split(':')[1]
exp_date_str = None
puts_df = None
status = ae_consts.NOT_RUN
try:
redis_rec = redis_get.get_data_from_redis_key(label=label,
host=redis_host,
port=redis_port,
db=redis_db,
password=work_dict.get(
'password', None),
key=redis_key,
decompress_df=True)
status = redis_rec['status']
if verbose:
log.info(f'{label} - {df_str} redis get data key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
if status == ae_consts.SUCCESS:
puts_json = None
if 'puts' in redis_rec['rec']['data']:
puts_json = redis_rec['rec']['data']['puts']
else:
puts_json = redis_rec['rec']['data']
if verbose:
log.info(f'{label} - {df_str} redis convert puts to df')
try:
puts_df = pd.read_json(puts_json, orient='records')
if len(puts_df.index) == 0:
return ae_consts.SUCCESS, None
if 'date' not in puts_df:
log.debug('failed to find date column in TD puts '
f'df={puts_df} len={len(puts_df.index)}')
return ae_consts.SUCCESS, None
puts_df.sort_values(by=['date', 'strike'])
"""
for i, r in calls_df.iterrows():
print(r['date'])
convert_epochs = [
'ask_date',
'bid_date',
'trade_date'
]
for c in convert_epochs:
if c in puts_df:
puts_df[c] = pd.DatetimeIndex(pd.to_datetime(
puts_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT
)).tz_localize(
'UTC').tz_convert(
'US/Eastern')
# dates converted
"""
exp_date_str = (puts_df['exp_date'].iloc[-1])
puts_df['date'] = puts_df['date'].dt.strftime(
ae_consts.COMMON_TICK_DATE_FORMAT)
except Exception:
log.debug(f'{label} - {df_str} redis_key={redis_key} '
'no puts df found')
return ae_consts.EMPTY, None
# end of try/ex to convert to df
if verbose:
log.info(f'{label} - {df_str} redis_key={redis_key} '
f'puts={len(puts_df.index)} exp_date={exp_date_str}')
else:
if verbose:
log.info(f'{label} - {df_str} did not find valid redis '
f'option puts in redis_key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
except Exception as e:
log.debug(f'{label} - {df_str} - ds_id={ds_id} failed getting option '
f'puts from redis={redis_host}:{redis_port}@{redis_db} '
f'key={redis_key} ex={e}')
return ae_consts.ERR, None
# end of try/ex extract from redis
if verbose:
log.info(
f'{label} - {df_str} ds_id={ds_id} extract scrub={scrub_mode}')
scrubbed_df = scrub_utils.extract_scrub_dataset(
label=label,
scrub_mode=scrub_mode,
datafeed_type=df_type,
msg_format='df={} date_str={}',
ds_id=ds_id,
df=puts_df)
status = ae_consts.SUCCESS
return status, scrubbed_df
def extract_option_puts_dataset(ticker=None,
date=None,
work_dict=None,
scrub_mode='sort-by-date',
verbose=False):
"""extract_option_puts_dataset
Extract the TD options puts for a ticker and
return a tuple (status, ``pandas.Dataframe``)
.. code-block:: python
import analysis_engine.td.extract_df_from_redis as td_extract
# extract by historical date is also supported as an arg
# date='2019-02-15'
puts_status, puts_df = td_extract.extract_option_puts_dataset(
ticker='SPY')
print(puts_df)
:param ticker: string ticker to extract
:param date: optional - string date to extract
formatted ``YYYY-MM-DD``
:param work_dict: dictionary of args
:param scrub_mode: optional - string type of
scrubbing handler to run
:param verbose: optional - boolean for turning on logging
"""
label = 'extract_td_puts'
latest_close_date = ae_utils.get_last_close_str()
use_date = date
if work_dict:
if not ticker:
ticker = work_dict.get('ticker', None)
label = f'{work_dict.get("label", label)}'
if not use_date:
use_date = latest_close_date
ds_id = ticker
df_type = td_consts.DATAFEED_TD_PUTS
df_str = td_consts.get_datafeed_str_td(df_type=df_type)
redis_db = ae_consts.REDIS_DB
redis_key = f'{ticker}_{use_date}_tdputs'
redis_host, redis_port = ae_consts.get_redis_host_and_port(req=work_dict)
redis_password = ae_consts.REDIS_PASSWORD
s3_key = redis_key
if work_dict:
redis_db = work_dict.get('redis_db', redis_db)
redis_password = work_dict.get('redis_password', redis_password)
verbose = work_dict.get('verbose_td', verbose)
if verbose:
log.info(f'{label} - {df_str} - start - redis_key={redis_key} '
f's3_key={s3_key}')
exp_date_str = None
puts_df = None
status = ae_consts.NOT_RUN
try:
redis_rec = redis_get.get_data_from_redis_key(label=label,
host=redis_host,
port=redis_port,
db=redis_db,
password=redis_password,
key=redis_key,
decompress_df=True)
status = redis_rec['status']
if verbose:
log.info(f'{label} - {df_str} redis get data key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
if status == ae_consts.SUCCESS:
puts_json = None
if 'tdputs' in redis_rec['rec']['data']:
puts_json = redis_rec['rec']['data']['tdputs']
if 'puts' in redis_rec['rec']['data']:
puts_json = redis_rec['rec']['data']['puts']
else:
puts_json = redis_rec['rec']['data']
if not puts_json:
return ae_consts.SUCCESS, pd.DataFrame([])
if verbose:
log.info(f'{label} - {df_str} redis convert puts to df')
try:
puts_df = pd.read_json(puts_json, orient='records')
if len(puts_df.index) == 0:
return ae_consts.SUCCESS, pd.DataFrame([])
if 'date' not in puts_df:
log.debug('failed to find date column in TD puts '
f'df={puts_df} len={len(puts_df.index)}')
return ae_consts.SUCCESS, pd.DataFrame([])
puts_df.sort_values(by=['date', 'strike'])
"""
for i, r in calls_df.iterrows():
print(r['date'])
convert_epochs = [
'ask_date',
'bid_date',
'trade_date'
]
for c in convert_epochs:
if c in puts_df:
puts_df[c] = pd.DatetimeIndex(pd.to_datetime(
puts_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT
)).tz_localize(
'UTC').tz_convert(
'US/Eastern')
# dates converted
"""
exp_date_str = (puts_df['exp_date'].iloc[-1])
puts_df['date'] = puts_df['date'].dt.strftime(
ae_consts.COMMON_TICK_DATE_FORMAT)
except Exception:
log.debug(f'{label} - {df_str} redis_key={redis_key} '
'no puts df found')
return ae_consts.SUCCESS, pd.DataFrame([])
# end of try/ex to convert to df
if verbose:
log.info(f'{label} - {df_str} redis_key={redis_key} '
f'puts={len(puts_df.index)} exp_date={exp_date_str}')
else:
if verbose:
log.info(f'{label} - {df_str} did not find valid redis '
f'option puts in redis_key={redis_key} '
f'status={ae_consts.get_status(status=status)}')
except Exception as e:
if verbose:
log.error(
f'{label} - {df_str} - ds_id={ds_id} failed getting option '
f'puts from redis={redis_host}:{redis_port}@{redis_db} '
f'key={redis_key} ex={e}')
return ae_consts.ERR, pd.DataFrame([])
# end of try/ex extract from redis
if verbose:
log.info(
f'{label} - {df_str} ds_id={ds_id} extract scrub={scrub_mode}')
scrubbed_df = scrub_utils.extract_scrub_dataset(
label=label,
scrub_mode=scrub_mode,
datafeed_type=df_type,
msg_format='df={} date_str={}',
ds_id=ds_id,
df=puts_df)
status = ae_consts.SUCCESS
return status, scrubbed_df