def test_integration_extract_earnings_dataset(self):
"""test_integration_extract_earnings_dataset"""
if ev('INT_TESTS', '0') == '0':
return
ticker = 'NFLX'
label = 'IEX earnings dataset'
# build dataset cache dictionary
work = get_ds_dict(ticker=ticker, label=label)
status, df = extract_earnings_dataset(work_dict=work)
self._check(df=df, status=status, label=label, work=work)
def test_integration_extract_earnings_dataset(self):
"""test_integration_extract_earnings_dataset"""
if ev('INT_TESTS', '0') == '0':
return
ticker = 'NFLX'
label = 'IEX earnings dataset'
# build dataset cache dictionary
work = get_ds_dict(ticker=ticker, label=label)
status, df = extract_earnings_dataset(work_dict=work)
if status == SUCCESS:
self.assertIsNotNone(df)
self.debug_df(df=df)
else:
log.critical('{} is missing in redis '
'for ticker={} status={}'.format(
label, work['ticker'], get_status(status=status)))
def run_algo(
ticker=None,
tickers=None,
algo=None, # optional derived ``analysis_engine.algo.Algo`` instance
balance=None, # float starting base capital
commission=None, # float for single trade commission for buy or sell
start_date=None, # string YYYY-MM-DD HH:MM:SS
end_date=None, # string YYYY-MM-DD HH:MM:SS
datasets=None, # string list of identifiers
num_owned_dict=None, # not supported
cache_freq='daily', # 'minute' not supported
auto_fill=True,
load_config=None,
report_config=None,
history_config=None,
extract_config=None,
use_key=None,
extract_mode='all',
iex_datasets=None,
redis_enabled=True,
redis_address=None,
redis_db=None,
redis_password=None,
redis_expire=None,
redis_key=None,
s3_enabled=True,
s3_address=None,
s3_bucket=None,
s3_access_key=None,
s3_secret_key=None,
s3_region_name=None,
s3_secure=False,
s3_key=None,
celery_disabled=True,
broker_url=None,
result_backend=None,
label=None,
name=None,
timeseries=None,
trade_strategy=None,
verbose=False,
publish_to_slack=True,
publish_to_s3=True,
publish_to_redis=True,
extract_datasets=None,
config_file=None,
config_dict=None,
version=1,
raise_on_err=True,
**kwargs):
"""run_algo
Run an algorithm with steps:
1) Extract redis keys between dates
2) Compile a data pipeline dictionary (call it ``data``)
3) Call algorithm's ``myalgo.handle_data(data=data)``
.. note:: If no ``algo`` is set, the
``analysis_engine.algo.BaseAlgo`` algorithm
is used.
.. note:: Please ensure Redis and Minio are running
before trying to extract tickers
**Stock tickers to extract**
:param ticker: single stock ticker/symbol/ETF to extract
:param tickers: optional - list of tickers to extract
:param use_key: optional - extract historical key from Redis
**Algo Configuration**
:param algo: derived instance of ``analysis_engine.algo.Algo`` object
:param balance: optional - float balance parameter
can also be set on the ``algo`` object if not
set on the args
:param commission: float for single trade commission for
buy or sell. can also be set on the ``algo`` objet
:param start_date: string ``YYYY-MM-DD_HH:MM:SS`` cache value
:param end_date: string ``YYYY-MM-DD_HH:MM:SS`` cache value
:param dataset_types: list of strings that are ``iex`` or ``yahoo``
datasets that are cached.
:param cache_freq: optional - depending on if you are running data feeds
on a ``daily`` cron (default) vs every ``minute`` (or faster)
:param num_owned_dict: not supported yet
:param auto_fill: optional - boolean for auto filling
buy/sell orders for backtesting (default is
``True``)
:param trading_calendar: ``trading_calendar.TradingCalendar``
object, by default ``analysis_engine.calendars.
always_open.AlwaysOpen`` trading calendar
# TradingCalendar by ``TFSExchangeCalendar``
:param config_file: path to a json file
containing custom algorithm object
member values (like indicator configuration and
predict future date units ahead for a backtest)
:param config_dict: optional - dictionary that
can be passed to derived class implementations
of: ``def load_from_config(config_dict=config_dict)``
**Timeseries**
:param timeseries: optional - string to
set ``day`` or ``minute`` backtesting
or live trading
(default is ``minute``)
**Trading Strategy**
:param trade_strategy: optional - string to
set the type of ``Trading Strategy``
for backtesting or live trading
(default is ``count``)
**Algorithm Dataset Loading, Extracting, Reporting
and Trading History arguments**
:param load_config: optional - dictionary
for setting member variables to load an
agorithm-ready dataset from
a file, s3 or redis
:param report_config: optional - dictionary
for setting member variables to publish
an algo ``trading performance report`` to s3,
redis, a file or slack
:param history_config: optional - dictionary
for setting member variables to publish
an algo ``trade history`` to s3, redis, a file
or slack
:param extract_config: optional - dictionary
for setting member variables to publish
an algo ``trading performance report`` to s3,
redis, a file or slack
**(Optional) Data sources, datafeeds and datasets to gather**
:param iex_datasets: list of strings for gathering specific `IEX
datasets <https://iextrading.com/developer/docs/#stocks>`__
which are set as consts: ``analysis_engine.iex.consts.FETCH_*``.
**(Optional) Redis connectivity arguments**
:param redis_enabled: bool - toggle for auto-caching all
datasets in Redis
(default is ``True``)
:param redis_address: Redis connection string format: ``host:port``
(default is ``localhost:6379``)
:param redis_db: Redis db to use
(default is ``0``)
:param redis_password: optional - Redis password
(default is ``None``)
:param redis_expire: optional - Redis expire value
(default is ``None``)
:param redis_key: optional - redis key not used
(default is ``None``)
**(Optional) Minio (S3) connectivity arguments**
:param s3_enabled: bool - toggle for auto-archiving on Minio (S3)
(default is ``True``)
:param s3_address: Minio S3 connection string format: ``host:port``
(default is ``localhost:9000``)
:param s3_bucket: S3 Bucket for storing the artifacts
(default is ``dev``) which should be viewable on a browser:
http://localhost:9000/minio/dev/
:param s3_access_key: S3 Access key
(default is ``trexaccesskey``)
:param s3_secret_key: S3 Secret key
(default is ``trex123321``)
:param s3_region_name: S3 region name
(default is ``us-east-1``)
:param s3_secure: Transmit using tls encryption
(default is ``False``)
:param s3_key: optional s3 key not used
(default is ``None``)
**(Optional) Celery worker broker connectivity arguments**
:param celery_disabled: bool - toggle synchronous mode or publish
to an engine connected to the `Celery broker and backend
<https://github.com/celery/celery#transports-and-backends>`__
(default is ``True`` - synchronous mode without an engine
or need for a broker or backend for Celery)
:param broker_url: Celery broker url
(default is ``redis://0.0.0.0:6379/13``)
:param result_backend: Celery backend url
(default is ``redis://0.0.0.0:6379/14``)
:param label: tracking log label
:param publish_to_slack: optional - boolean for
publishing to slack (coming soon)
:param publish_to_s3: optional - boolean for
publishing to s3 (coming soon)
:param publish_to_redis: optional - boolean for
publishing to redis (coming soon)
**(Optional) Debugging**
:param verbose: bool - show extract warnings
and other debug logging (default is False)
:param raise_on_err: optional - boolean for
unittests and developing algorithms with the
``analysis_engine.run_algo.run_algo`` helper.
When set to ``True`` exceptions will
are raised to the calling functions
:param kwargs: keyword arguments dictionary
"""
# dictionary structure with a list sorted on: ascending dates
# algo_data_req[ticker][list][dataset] = pd.DataFrame
algo_data_req = {}
extract_requests = []
return_algo = False # return created algo objects for use by caller
rec = {}
msg = None
use_tickers = tickers
use_balance = balance
use_commission = commission
if ticker:
use_tickers = [ticker]
else:
if not use_tickers:
use_tickers = []
# if these are not set as args, but the algo object
# has them, use them instead:
if algo:
if len(use_tickers) == 0:
use_tickers = algo.get_tickers()
if not use_balance:
use_balance = algo.get_balance()
if not use_commission:
use_commission = algo.get_commission()
default_iex_datasets = [
'daily', 'minute', 'quote', 'stats', 'peers', 'news', 'financials',
'earnings', 'dividends', 'company'
]
if not iex_datasets:
iex_datasets = default_iex_datasets
if redis_enabled:
if not redis_address:
redis_address = os.getenv('REDIS_ADDRESS', 'localhost:6379')
if not redis_password:
redis_password = os.getenv('REDIS_PASSWORD', None)
if not redis_db:
redis_db = int(os.getenv('REDIS_DB', '0'))
if not redis_expire:
redis_expire = os.getenv('REDIS_EXPIRE', None)
if s3_enabled:
if not s3_address:
s3_address = os.getenv('S3_ADDRESS', 'localhost:9000')
if not s3_access_key:
s3_access_key = os.getenv('AWS_ACCESS_KEY_ID', 'trexaccesskey')
if not s3_secret_key:
s3_secret_key = os.getenv('AWS_SECRET_ACCESS_KEY', 'trex123321')
if not s3_region_name:
s3_region_name = os.getenv('AWS_DEFAULT_REGION', 'us-east-1')
if not s3_secure:
s3_secure = os.getenv('S3_SECURE', '0') == '1'
if not s3_bucket:
s3_bucket = os.getenv('S3_BUCKET', 'dev')
if not broker_url:
broker_url = os.getenv('WORKER_BROKER_URL', 'redis://0.0.0.0:6379/11')
if not result_backend:
result_backend = os.getenv('WORKER_BACKEND_URL',
'redis://0.0.0.0:6379/12')
if not label:
label = 'run-algo'
num_tickers = len(use_tickers)
last_close_str = ae_utils.get_last_close_str()
if iex_datasets:
if verbose:
log.info('{} - tickers={} '
'iex={}'.format(label, num_tickers,
json.dumps(iex_datasets)))
else:
if verbose:
log.info('{} - tickers={}'.format(label, num_tickers))
ticker_key = use_key
if not ticker_key:
ticker_key = '{}_{}'.format(ticker, last_close_str)
if not algo:
algo = base_algo.BaseAlgo(ticker=None,
tickers=use_tickers,
balance=use_balance,
commission=use_commission,
config_dict=config_dict,
name=label,
auto_fill=auto_fill,
timeseries=timeseries,
trade_strategy=trade_strategy,
publish_to_slack=publish_to_slack,
publish_to_s3=publish_to_s3,
publish_to_redis=publish_to_redis,
raise_on_err=raise_on_err)
return_algo = True
# the algo object is stored
# in the result at: res['rec']['algo']
if not algo:
msg = ('{} - missing algo object'.format(label))
log.error(msg)
return build_result.build_result(status=ae_consts.EMPTY,
err=msg,
rec=rec)
if raise_on_err:
log.debug('{} - enabling algo exception raises'.format(label))
algo.raise_on_err = True
common_vals = {}
common_vals['base_key'] = ticker_key
common_vals['celery_disabled'] = celery_disabled
common_vals['ticker'] = ticker
common_vals['label'] = label
common_vals['iex_datasets'] = iex_datasets
common_vals['s3_enabled'] = s3_enabled
common_vals['s3_bucket'] = s3_bucket
common_vals['s3_address'] = s3_address
common_vals['s3_secure'] = s3_secure
common_vals['s3_region_name'] = s3_region_name
common_vals['s3_access_key'] = s3_access_key
common_vals['s3_secret_key'] = s3_secret_key
common_vals['s3_key'] = ticker_key
common_vals['redis_enabled'] = redis_enabled
common_vals['redis_address'] = redis_address
common_vals['redis_password'] = redis_password
common_vals['redis_db'] = redis_db
common_vals['redis_key'] = ticker_key
common_vals['redis_expire'] = redis_expire
"""
Extract Datasets
"""
iex_daily_status = ae_consts.FAILED
iex_minute_status = ae_consts.FAILED
iex_quote_status = ae_consts.FAILED
iex_stats_status = ae_consts.FAILED
iex_peers_status = ae_consts.FAILED
iex_news_status = ae_consts.FAILED
iex_financials_status = ae_consts.FAILED
iex_earnings_status = ae_consts.FAILED
iex_dividends_status = ae_consts.FAILED
iex_company_status = ae_consts.FAILED
yahoo_news_status = ae_consts.FAILED
yahoo_options_status = ae_consts.FAILED
yahoo_pricing_status = ae_consts.FAILED
td_calls_status = ae_consts.FAILED
td_puts_status = ae_consts.FAILED
iex_daily_df = None
iex_minute_df = None
iex_quote_df = None
iex_stats_df = None
iex_peers_df = None
iex_news_df = None
iex_financials_df = None
iex_earnings_df = None
iex_dividends_df = None
iex_company_df = None
yahoo_option_calls_df = None
yahoo_option_puts_df = None
yahoo_pricing_df = None
yahoo_news_df = None
td_calls_df = None
td_puts_df = None
use_start_date_str = start_date
use_end_date_str = end_date
last_close_date = ae_utils.last_close()
end_date_val = None
cache_freq_fmt = ae_consts.COMMON_TICK_DATE_FORMAT
if not use_end_date_str:
use_end_date_str = last_close_date.strftime(cache_freq_fmt)
end_date_val = ae_utils.get_date_from_str(date_str=use_end_date_str,
fmt=cache_freq_fmt)
start_date_val = None
if not use_start_date_str:
start_date_val = end_date_val - datetime.timedelta(days=60)
use_start_date_str = start_date_val.strftime(cache_freq_fmt)
else:
start_date_val = datetime.datetime.strptime(
use_start_date_str, ae_consts.COMMON_TICK_DATE_FORMAT)
total_dates = (end_date_val - start_date_val).days
if end_date_val < start_date_val:
msg = ('{} - invalid dates - start_date={} is after '
'end_date={}'.format(label, start_date_val, end_date_val))
raise Exception(msg)
log.debug('{} - days={} start={} end={} datatset={}'.format(
label, total_dates, use_start_date_str, use_end_date_str, datasets))
for ticker in use_tickers:
req = algo_utils.build_algo_request(ticker=ticker,
use_key=use_key,
start_date=use_start_date_str,
end_date=use_end_date_str,
datasets=datasets,
balance=use_balance,
cache_freq=cache_freq,
timeseries=timeseries,
trade_strategy=trade_strategy,
label=label)
ticker_key = '{}_{}'.format(ticker, last_close_str)
common_vals['ticker'] = ticker
common_vals['base_key'] = ticker_key
common_vals['redis_key'] = ticker_key
common_vals['s3_key'] = ticker_key
for date_key in req['extract_datasets']:
date_req = api_requests.get_ds_dict(ticker=ticker,
base_key=date_key,
ds_id=label,
service_dict=common_vals)
node_date_key = date_key.replace('{}_'.format(ticker), '')
extract_requests.append({
'id': date_key,
'ticker': ticker,
'date_key': date_key,
'date': node_date_key,
'req': date_req
})
# end of for all ticker in use_tickers
extract_iex = True
if extract_mode not in ['all', 'iex']:
extract_iex = False
extract_yahoo = True
if extract_mode not in ['all', 'yahoo']:
extract_yahoo = False
extract_td = True
if extract_mode not in ['all', 'td']:
extract_td = False
first_extract_date = None
last_extract_date = None
total_extract_requests = len(extract_requests)
cur_idx = 1
for idx, extract_node in enumerate(extract_requests):
iex_daily_df = None
iex_minute_df = None
iex_quote_df = None
iex_stats_df = None
iex_peers_df = None
iex_news_df = None
iex_financials_df = None
iex_earnings_df = None
iex_dividends_df = None
iex_company_df = None
yahoo_option_calls_df = None
yahoo_option_puts_df = None
yahoo_pricing_df = None
yahoo_news_df = None
td_calls_df = None
td_puts_df = None
extract_ticker = extract_node['ticker']
extract_date = extract_node['date']
extract_req = extract_node['req']
dataset_node_id = extract_node['id']
if not first_extract_date:
first_extract_date = extract_date
last_extract_date = extract_date
dataset_id = dataset_node_id
percent_label = ('{} ticker={} date={} {} {}/{}'.format(
label, extract_ticker, extract_date,
ae_consts.get_percent_done(progress=cur_idx,
total=total_extract_requests), idx,
total_extract_requests))
log.debug('{} - extract - start'.format(percent_label))
if 'daily' in iex_datasets or extract_iex:
iex_daily_status, iex_daily_df = \
iex_extract_utils.extract_daily_dataset(
extract_req)
if iex_daily_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_daily={}'.format(ticker))
if 'minute' in iex_datasets or extract_iex:
iex_minute_status, iex_minute_df = \
iex_extract_utils.extract_minute_dataset(
extract_req)
if iex_minute_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_minute={}'.format(ticker))
if 'quote' in iex_datasets or extract_iex:
iex_quote_status, iex_quote_df = \
iex_extract_utils.extract_quote_dataset(
extract_req)
if iex_quote_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_quote={}'.format(ticker))
if 'stats' in iex_datasets or extract_iex:
iex_stats_df, iex_stats_df = \
iex_extract_utils.extract_stats_dataset(
extract_req)
if iex_stats_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_stats={}'.format(ticker))
if 'peers' in iex_datasets or extract_iex:
iex_peers_df, iex_peers_df = \
iex_extract_utils.extract_peers_dataset(
extract_req)
if iex_peers_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_peers={}'.format(ticker))
if 'news' in iex_datasets or extract_iex:
iex_news_status, iex_news_df = \
iex_extract_utils.extract_news_dataset(
extract_req)
if iex_news_status != ae_consts.SUCCESS:
if verbose:
log.warning('unable to extract iex_news={}'.format(ticker))
if 'financials' in iex_datasets or extract_iex:
iex_financials_status, iex_financials_df = \
iex_extract_utils.extract_financials_dataset(
extract_req)
if iex_financials_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_financials={}'.format(ticker))
if 'earnings' in iex_datasets or extract_iex:
iex_earnings_status, iex_earnings_df = \
iex_extract_utils.extract_earnings_dataset(
extract_req)
if iex_earnings_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_earnings={}'.format(ticker))
if 'dividends' in iex_datasets or extract_iex:
iex_dividends_status, iex_dividends_df = \
iex_extract_utils.extract_dividends_dataset(
extract_req)
if iex_dividends_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_dividends={}'.format(ticker))
if 'company' in iex_datasets or extract_iex:
iex_company_status, iex_company_df = \
iex_extract_utils.extract_company_dataset(
extract_req)
if iex_company_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract iex_company={}'.format(ticker))
# end of iex extracts
if extract_yahoo:
yahoo_options_status, yahoo_option_calls_df = \
yahoo_extract_utils.extract_option_calls_dataset(
extract_req)
yahoo_options_status, yahoo_option_puts_df = \
yahoo_extract_utils.extract_option_puts_dataset(
extract_req)
if yahoo_options_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_options={}'.format(ticker))
yahoo_pricing_status, yahoo_pricing_df = \
yahoo_extract_utils.extract_pricing_dataset(
extract_req)
if yahoo_pricing_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_pricing={}'.format(ticker))
yahoo_news_status, yahoo_news_df = \
yahoo_extract_utils.extract_yahoo_news_dataset(
extract_req)
if yahoo_news_status != ae_consts.SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_news={}'.format(ticker))
# end of yahoo extracts
if extract_td:
"""
Debug by setting:
extract_req['verbose_td'] = True
"""
td_calls_status, td_calls_df = \
td_extract_utils.extract_option_calls_dataset(
extract_req)
if td_calls_status != ae_consts.SUCCESS:
if verbose:
log.warning('unable to extract tdcalls={}'.format(ticker))
td_puts_status, td_puts_df = \
td_extract_utils.extract_option_puts_dataset(
extract_req)
if td_puts_status != ae_consts.SUCCESS:
if verbose:
log.warning('unable to extract tdputs={}'.format(ticker))
# td extracts
# map extracted data to DEFAULT_SERIALIZED_DATASETS
ticker_data = {}
ticker_data['daily'] = iex_daily_df
ticker_data['minute'] = iex_minute_df
ticker_data['quote'] = iex_quote_df
ticker_data['stats'] = iex_stats_df
ticker_data['peers'] = iex_peers_df
ticker_data['news1'] = iex_news_df
ticker_data['financials'] = iex_financials_df
ticker_data['earnings'] = iex_earnings_df
ticker_data['dividends'] = iex_dividends_df
ticker_data['company'] = iex_company_df
ticker_data['calls'] = yahoo_option_calls_df
ticker_data['puts'] = yahoo_option_puts_df
ticker_data['pricing'] = yahoo_pricing_df
ticker_data['news'] = yahoo_news_df
ticker_data['tdcalls'] = td_calls_df
ticker_data['tdputs'] = td_puts_df
if ticker not in algo_data_req:
algo_data_req[ticker] = []
algo_data_req[ticker].append({
'id': dataset_id, # id is currently the cache key in redis
'date': extract_date, # used to confirm dates in asc order
'data': ticker_data
})
if verbose:
log.info('extract - {} dataset={}'.format(
percent_label, len(algo_data_req[ticker])))
cur_idx += 1
# end of for service_dict in extract_requests
# this could be a separate celery task
status = ae_consts.NOT_RUN
if len(algo_data_req) == 0:
msg = ('{} - nothing to test - no data found for tickers={} '
'between {} and {}'.format(label, use_tickers,
first_extract_date,
last_extract_date))
log.info(msg)
return build_result.build_result(status=ae_consts.EMPTY,
err=msg,
rec=rec)
# this could be a separate celery task
try:
if verbose:
log.info('handle_data START - {} from {} to {}'.format(
percent_label, first_extract_date, last_extract_date))
algo.handle_data(data=algo_data_req)
if verbose:
log.info('handle_data END - {} from {} to {}'.format(
percent_label, first_extract_date, last_extract_date))
except Exception as e:
msg = ('{} - algo={} encountered exception in handle_data '
'tickers={} from '
'{} to {} ex={}'.format(percent_label, algo.get_name(),
use_tickers, first_extract_date,
last_extract_date, e))
if raise_on_err:
if algo:
log.error('algo failure report: algo={} handle_data() '
'{} and config={}'.format(
algo.get_name(), algo.get_debug_msg(),
ae_consts.ppj(algo.config_dict)))
try:
ind_obj = \
algo.get_indicator_process_last_indicator()
if ind_obj:
found_error_hint = False
if hasattr(ind_obj.use_df, 'to_json'):
if len(ind_obj.use_df.index) == 0:
log.critical(
'indicator failure report for '
'last module: '
'{} indicator={} config={} dataset={} '
'name_of_dataset={}'.format(
ind_obj.get_path_to_module(),
ind_obj.get_name(),
ae_consts.ppj(ind_obj.get_config()),
ind_obj.use_df, ind_obj.uses_data))
log.critical(
'--------------------------------------'
'--------------------------------------')
log.critical(
'Please check if this indicator: '
'{} '
'supports Empty Dataframes: {}'.format(
ind_obj.get_path_to_module(),
ind_obj.use_df))
log.critical(
'--------------------------------------'
'--------------------------------------')
found_error_hint = True
# indicator error hints
if not found_error_hint:
log.critical(
'indicator failure report for last module: '
'{} indicator={} config={} dataset={} '
'name_of_dataset={}'.format(
ind_obj.get_path_to_module(),
ind_obj.get_name(),
ae_consts.ppj(ind_obj.get_config()),
ind_obj.use_df, ind_obj.uses_data))
except Exception as f:
log.critical('failed to pull indicator processor '
'last indicator for debugging '
'from ex={} with parsing ex={}'
''.format(e, f))
# end of ignoring non-supported ways of creating
# indicator processors
log.error(msg)
raise e
else:
log.error(msg)
return build_result.build_result(status=ae_consts.ERR,
err=msg,
rec=rec)
# end of try/ex
# this could be a separate celery task
try:
if verbose:
log.info('get_result START - {} from {} to {}'.format(
percent_label, first_extract_date, last_extract_date))
rec = algo.get_result()
status = ae_consts.SUCCESS
if verbose:
log.info('get_result END - {} from {} to {}'.format(
percent_label, first_extract_date, last_extract_date))
except Exception as e:
msg = ('{} - algo={} encountered exception in get_result '
'tickers={} from '
'{} to {} ex={}'.format(percent_label, algo.get_name(),
use_tickers, first_extract_date,
last_extract_date, e))
if raise_on_err:
if algo:
log.error('algo={} failed in get_result with debug_msg'
'={}'.format(algo.get_name(), algo.get_debug_msg()))
log.error(msg)
raise e
else:
log.error(msg)
return build_result.build_result(status=ae_consts.ERR,
err=msg,
rec=rec)
# end of try/ex
if return_algo:
rec['algo'] = algo
return build_result.build_result(status=status, err=msg, rec=rec)
def extract(ticker=None,
tickers=None,
use_key=None,
extract_mode='all',
iex_datasets=None,
redis_enabled=True,
redis_address=None,
redis_db=None,
redis_password=None,
redis_expire=None,
s3_enabled=True,
s3_address=None,
s3_bucket=None,
s3_access_key=None,
s3_secret_key=None,
s3_region_name=None,
s3_secure=False,
celery_disabled=True,
broker_url=None,
result_backend=None,
label=None,
verbose=False):
"""extract
Extract all cached datasets for a stock ``ticker`` or
a list of ``tickers`` and returns a dictionary. Please
make sure the datasets are already cached in Redis
before running this method. If not please refer to
the ``analysis_engine.fetch.fetch`` function
to prepare the datasets on your environment.
Python example:
.. code-block:: python
from analysis_engine.extract import extract
d = extract(ticker='NFLX')
print(d)
for k in d['NFLX']:
print('dataset key: {}'.format(k))
This was created for reducing the amount of typying in
Jupyter notebooks. It can be set up for use with a
distributed engine as well with the optional arguments
depending on your connectitivty requirements.
.. note:: Please ensure Redis and Minio are running
before trying to extract tickers
**Stock tickers to extract**
:param ticker: single stock ticker/symbol/ETF to extract
:param tickers: optional - list of tickers to extract
:param use_key: optional - extract historical key from Redis
usually formatted ``<TICKER>_<date formatted YYYY-MM-DD>``
**(Optional) Data sources, datafeeds and datasets to gather**
:param iex_datasets: list of strings for gathering specific `IEX
datasets <https://iextrading.com/developer/docs/#stocks>`__
which are set as consts: ``analysis_engine.iex.consts.FETCH_*``.
**(Optional) Redis connectivity arguments**
:param redis_enabled: bool - toggle for auto-caching all
datasets in Redis
(default is ``True``)
:param redis_address: Redis connection string format: ``host:port``
(default is ``localhost:6379``)
:param redis_db: Redis db to use
(default is ``0``)
:param redis_password: optional - Redis password
(default is ``None``)
:param redis_expire: optional - Redis expire value
(default is ``None``)
**(Optional) Minio (S3) connectivity arguments**
:param s3_enabled: bool - toggle for auto-archiving on Minio (S3)
(default is ``True``)
:param s3_address: Minio S3 connection string format: ``host:port``
(default is ``localhost:9000``)
:param s3_bucket: S3 Bucket for storing the artifacts
(default is ``dev``) which should be viewable on a browser:
http://localhost:9000/minio/dev/
:param s3_access_key: S3 Access key
(default is ``trexaccesskey``)
:param s3_secret_key: S3 Secret key
(default is ``trex123321``)
:param s3_region_name: S3 region name
(default is ``us-east-1``)
:param s3_secure: Transmit using tls encryption
(default is ``False``)
**(Optional) Celery worker broker connectivity arguments**
:param celery_disabled: bool - toggle synchronous mode or publish
to an engine connected to the `Celery broker and backend
<https://github.com/celery/celery#transports-and-backends>`__
(default is ``True`` - synchronous mode without an engine
or need for a broker or backend for Celery)
:param broker_url: Celery broker url
(default is ``redis://0.0.0.0:6379/13``)
:param result_backend: Celery backend url
(default is ``redis://0.0.0.0:6379/14``)
:param label: tracking log label
**(Optional) Debugging**
:param verbose: bool - show extract warnings
and other debug logging (default is False)
**Supported environment variables**
::
export REDIS_ADDRESS="localhost:6379"
export REDIS_DB="0"
export S3_ADDRESS="localhost:9000"
export S3_BUCKET="dev"
export AWS_ACCESS_KEY_ID="trexaccesskey"
export AWS_SECRET_ACCESS_KEY="trex123321"
export AWS_DEFAULT_REGION="us-east-1"
export S3_SECURE="0"
export WORKER_BROKER_URL="redis://0.0.0.0:6379/13"
export WORKER_BACKEND_URL="redis://0.0.0.0:6379/14"
"""
rec = {}
extract_requests = []
use_tickers = tickers
if ticker:
use_tickers = [ticker]
else:
if not use_tickers:
use_tickers = []
default_iex_datasets = [
'daily', 'minute', 'quote', 'stats', 'peers', 'news', 'financials',
'earnings', 'dividends', 'company'
]
if not iex_datasets:
iex_datasets = default_iex_datasets
if redis_enabled:
if not redis_address:
redis_address = os.getenv('REDIS_ADDRESS', 'localhost:6379')
if not redis_password:
redis_password = os.getenv('REDIS_PASSWORD', None)
if not redis_db:
redis_db = int(os.getenv('REDIS_DB', '0'))
if not redis_expire:
redis_expire = os.getenv('REDIS_EXPIRE', None)
if s3_enabled:
if not s3_address:
s3_address = os.getenv('S3_ADDRESS', 'localhost:9000')
if not s3_access_key:
s3_access_key = os.getenv('AWS_ACCESS_KEY_ID', 'trexaccesskey')
if not s3_secret_key:
s3_secret_key = os.getenv('AWS_SECRET_ACCESS_KEY', 'trex123321')
if not s3_region_name:
s3_region_name = os.getenv('AWS_DEFAULT_REGION', 'us-east-1')
if not s3_secure:
s3_secure = os.getenv('S3_SECURE', '0') == '1'
if not s3_bucket:
s3_bucket = os.getenv('S3_BUCKET', 'dev')
if not broker_url:
broker_url = os.getenv('WORKER_BROKER_URL', 'redis://0.0.0.0:6379/13')
if not result_backend:
result_backend = os.getenv('WORKER_BACKEND_URL',
'redis://0.0.0.0:6379/14')
if not label:
label = 'get-latest'
num_tickers = len(use_tickers)
last_close_str = get_last_close_str()
if iex_datasets:
log.info('{} - getting latest for tickers={} '
'iex={}'.format(label, num_tickers, json.dumps(iex_datasets)))
else:
log.info('{} - getting latest for tickers={}'.format(
label, num_tickers))
ticker_key = use_key
if not ticker_key:
ticker_key = '{}_{}'.format(ticker, last_close_str)
common_vals = {}
common_vals['base_key'] = ticker_key
common_vals['celery_disabled'] = celery_disabled
common_vals['ticker'] = ticker
common_vals['label'] = label
common_vals['iex_datasets'] = iex_datasets
common_vals['s3_enabled'] = s3_enabled
common_vals['s3_bucket'] = s3_bucket
common_vals['s3_address'] = s3_address
common_vals['s3_secure'] = s3_secure
common_vals['s3_region_name'] = s3_region_name
common_vals['s3_access_key'] = s3_access_key
common_vals['s3_secret_key'] = s3_secret_key
common_vals['s3_key'] = ticker_key
common_vals['redis_enabled'] = redis_enabled
common_vals['redis_address'] = redis_address
common_vals['redis_password'] = redis_password
common_vals['redis_db'] = redis_db
common_vals['redis_key'] = ticker_key
common_vals['redis_expire'] = redis_expire
common_vals['redis_address'] = redis_address
common_vals['s3_address'] = s3_address
log.info('{} - extract ticker={} last_close={} base_key={} '
'redis_address={} s3_address={}'.format(
label, ticker, last_close_str, common_vals['base_key'],
common_vals['redis_address'], common_vals['s3_address']))
"""
Extract Datasets
"""
iex_daily_status = FAILED
iex_minute_status = FAILED
iex_quote_status = FAILED
iex_stats_status = FAILED
iex_peers_status = FAILED
iex_news_status = FAILED
iex_financials_status = FAILED
iex_earnings_status = FAILED
iex_dividends_status = FAILED
iex_company_status = FAILED
yahoo_news_status = FAILED
yahoo_options_status = FAILED
yahoo_pricing_status = FAILED
iex_daily_df = None
iex_minute_df = None
iex_quote_df = None
iex_stats_df = None
iex_peers_df = None
iex_news_df = None
iex_financials_df = None
iex_earnings_df = None
iex_dividends_df = None
iex_company_df = None
yahoo_option_calls_df = None
yahoo_option_puts_df = None
yahoo_pricing_df = None
yahoo_news_df = None
for ticker in use_tickers:
req = get_ds_dict(ticker=ticker,
base_key=common_vals['base_key'],
ds_id=label,
service_dict=common_vals)
extract_requests.append(req)
# end of for all ticker in use_tickers
extract_iex = True
if extract_mode not in ['all', 'iex']:
extract_iex = False
extract_yahoo = True
if extract_mode not in ['all', 'yahoo']:
extract_yahoo = False
for extract_req in extract_requests:
if 'daily' in iex_datasets or extract_iex:
iex_daily_status, iex_daily_df = \
iex_extract_utils.extract_daily_dataset(
extract_req)
if iex_daily_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_daily={}'.format(ticker))
if 'minute' in iex_datasets or extract_iex:
iex_minute_status, iex_minute_df = \
iex_extract_utils.extract_minute_dataset(
extract_req)
if iex_minute_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_minute={}'.format(ticker))
if 'quote' in iex_datasets or extract_iex:
iex_quote_status, iex_quote_df = \
iex_extract_utils.extract_quote_dataset(
extract_req)
if iex_quote_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_quote={}'.format(ticker))
if 'stats' in iex_datasets or extract_iex:
iex_stats_df, iex_stats_df = \
iex_extract_utils.extract_stats_dataset(
extract_req)
if iex_stats_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_stats={}'.format(ticker))
if 'peers' in iex_datasets or extract_iex:
iex_peers_df, iex_peers_df = \
iex_extract_utils.extract_peers_dataset(
extract_req)
if iex_peers_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_peers={}'.format(ticker))
if 'news' in iex_datasets or extract_iex:
iex_news_status, iex_news_df = \
iex_extract_utils.extract_news_dataset(
extract_req)
if iex_news_status != SUCCESS:
if verbose:
log.warning('unable to extract iex_news={}'.format(ticker))
if 'financials' in iex_datasets or extract_iex:
iex_financials_status, iex_financials_df = \
iex_extract_utils.extract_financials_dataset(
extract_req)
if iex_financials_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_financials={}'.format(ticker))
if 'earnings' in iex_datasets or extract_iex:
iex_earnings_status, iex_earnings_df = \
iex_extract_utils.extract_earnings_dataset(
extract_req)
if iex_earnings_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_earnings={}'.format(ticker))
if 'dividends' in iex_datasets or extract_iex:
iex_dividends_status, iex_dividends_df = \
iex_extract_utils.extract_dividends_dataset(
extract_req)
if iex_dividends_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_dividends={}'.format(ticker))
if 'company' in iex_datasets or extract_iex:
iex_company_status, iex_company_df = \
iex_extract_utils.extract_company_dataset(
extract_req)
if iex_company_status != SUCCESS:
if verbose:
log.warning(
'unable to extract iex_company={}'.format(ticker))
# end of iex extracts
if extract_yahoo:
yahoo_options_status, yahoo_option_calls_df = \
yahoo_extract_utils.extract_option_calls_dataset(
extract_req)
yahoo_options_status, yahoo_option_puts_df = \
yahoo_extract_utils.extract_option_puts_dataset(
extract_req)
if yahoo_options_status != SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_options={}'.format(ticker))
yahoo_pricing_status, yahoo_pricing_df = \
yahoo_extract_utils.extract_pricing_dataset(
extract_req)
if yahoo_pricing_status != SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_pricing={}'.format(ticker))
yahoo_news_status, yahoo_news_df = \
yahoo_extract_utils.extract_yahoo_news_dataset(
extract_req)
if yahoo_news_status != SUCCESS:
if verbose:
log.warning(
'unable to extract yahoo_news={}'.format(ticker))
# end of yahoo extracts
ticker_data = {}
ticker_data['daily'] = iex_daily_df
ticker_data['minute'] = iex_minute_df
ticker_data['quote'] = iex_quote_df
ticker_data['stats'] = iex_stats_df
ticker_data['peers'] = iex_peers_df
ticker_data['news1'] = iex_news_df
ticker_data['financials'] = iex_financials_df
ticker_data['earnings'] = iex_earnings_df
ticker_data['dividends'] = iex_dividends_df
ticker_data['company'] = iex_company_df
ticker_data['calls'] = yahoo_option_calls_df
ticker_data['puts'] = yahoo_option_puts_df
ticker_data['pricing'] = yahoo_pricing_df
ticker_data['news'] = yahoo_news_df
rec[ticker] = ticker_data
# end of for service_dict in extract_requests
return rec
def build_dataset_node(ticker,
datasets,
date=None,
service_dict=None,
log_label=None,
redis_enabled=True,
redis_address=None,
redis_db=None,
redis_password=None,
redis_expire=None,
redis_key=None,
s3_enabled=True,
s3_address=None,
s3_bucket=None,
s3_access_key=None,
s3_secret_key=None,
s3_region_name=None,
s3_secure=False,
s3_key=None,
verbose=False):
"""build_dataset_node
Helper for building a dictionary that of
cached datasets from redis.
The datasets should be built from
off the algorithm's config indicators
``uses_data`` fields which if not
set will default to ``minute`` data
:param ticker: string ticker
:param datasets: list of string dataset names
to extract from redis
:param date: optional - string datetime formatted
``YYYY-MM-DD``
(default is last trading close date)
:param service_dict: optional - dictionary for all
service connectivity to Redis and Minio if not
set the arguments for all ``s3_*`` and ``redis_*``
will be used to lookup data in Redis and Minio
**(Optional) Redis connectivity arguments**
:param redis_enabled: bool - toggle for auto-caching all
datasets in Redis
(default is ``True``)
:param redis_address: Redis connection string
format is ``host:port``
(default is ``localhost:6379``)
:param redis_db: Redis db to use
(default is ``0``)
:param redis_password: optional - Redis password
(default is ``None``)
:param redis_expire: optional - Redis expire value
(default is ``None``)
:param redis_key: optional - redis key not used
(default is ``None``)
:param s3_enabled: bool - toggle for turning on/off
Minio or AWS S3
(default is ``True``)
:param s3_address: Minio S3 connection string address
format is ``host:port``
(default is ``localhost:9000``)
:param s3_bucket: S3 Bucket for storing the artifacts
(default is ``dev``) which should be viewable on a browser:
http://localhost:9000/minio/dev/
:param s3_access_key: S3 Access key
(default is ``trexaccesskey``)
:param s3_secret_key: S3 Secret key
(default is ``trex123321``)
:param s3_region_name: S3 region name
(default is ``us-east-1``)
:param s3_secure: Transmit using tls encryption
(default is ``False``)
:param s3_key: optional s3 key not used
(default is ``None``)
**Debugging**
:param log_label: optional - log label string
:param verbose: optional - flag for debugging
(default to ``False``)
"""
label = log_label
if not label:
label = 'build_bt'
if not date:
date = ae_utils.get_last_close_str()
td_convert_to_datetime = (ae_consts.TRADIER_CONVERT_TO_DATETIME)
date_key = f'{ticker}_{date}'
base_req = api_requests.get_ds_dict(ticker=ticker,
base_key=date_key,
ds_id=label,
service_dict=service_dict)
if not service_dict:
base_req['redis_enabled'] = redis_enabled
base_req['redis_address'] = redis_address
base_req['redis_password'] = redis_password
base_req['redis_db'] = redis_db
base_req['redis_key'] = date_key
base_req['redis_expire'] = redis_expire
base_req['s3_enabled'] = s3_enabled
base_req['s3_bucket'] = s3_bucket
base_req['s3_address'] = s3_address
base_req['s3_secure'] = s3_secure
base_req['s3_region_name'] = s3_region_name
base_req['s3_access_key'] = s3_access_key
base_req['s3_secret_key'] = s3_secret_key
base_req['s3_key'] = date_key
if verbose:
log.info(f'extracting {date_key}')
"""
for showing connectivity args in the logs
log.debug(
f'bt {date_key} {ae_consts.ppj(base_req)}')
"""
iex_daily_status = ae_consts.FAILED
iex_minute_status = ae_consts.FAILED
iex_quote_status = ae_consts.FAILED
iex_stats_status = ae_consts.FAILED
iex_peers_status = ae_consts.FAILED
iex_news_status = ae_consts.FAILED
iex_financials_status = ae_consts.FAILED
iex_earnings_status = ae_consts.FAILED
iex_dividends_status = ae_consts.FAILED
iex_company_status = ae_consts.FAILED
td_calls_status = ae_consts.FAILED
td_puts_status = ae_consts.FAILED
iex_daily_df = None
iex_minute_df = None
iex_quote_df = None
iex_stats_df = None
iex_peers_df = None
iex_news_df = None
iex_financials_df = None
iex_earnings_df = None
iex_dividends_df = None
iex_company_df = None
td_calls_df = None
td_puts_df = None
if 'daily' in datasets:
iex_daily_status, iex_daily_df = \
iex_extract_utils.extract_daily_dataset(
base_req)
if iex_daily_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_daily={ticker}')
if 'minute' in datasets:
iex_minute_status, iex_minute_df = \
iex_extract_utils.extract_minute_dataset(
base_req)
if iex_minute_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_minute={ticker}')
if 'quote' in datasets:
iex_quote_status, iex_quote_df = \
iex_extract_utils.extract_quote_dataset(
base_req)
if iex_quote_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_quote={ticker}')
if 'stats' in datasets:
iex_stats_df, iex_stats_df = \
iex_extract_utils.extract_stats_dataset(
base_req)
if iex_stats_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_stats={ticker}')
if 'peers' in datasets:
iex_peers_df, iex_peers_df = \
iex_extract_utils.extract_peers_dataset(
base_req)
if iex_peers_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_peers={ticker}')
if 'news' in datasets:
iex_news_status, iex_news_df = \
iex_extract_utils.extract_news_dataset(
base_req)
if iex_news_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_news={ticker}')
if 'financials' in datasets:
iex_financials_status, iex_financials_df = \
iex_extract_utils.extract_financials_dataset(
base_req)
if iex_financials_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_financials={ticker}')
if 'earnings' in datasets:
iex_earnings_status, iex_earnings_df = \
iex_extract_utils.extract_earnings_dataset(
base_req)
if iex_earnings_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_earnings={ticker}')
if 'dividends' in datasets:
iex_dividends_status, iex_dividends_df = \
iex_extract_utils.extract_dividends_dataset(
base_req)
if iex_dividends_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_dividends={ticker}')
if 'company' in datasets:
iex_company_status, iex_company_df = \
iex_extract_utils.extract_company_dataset(
base_req)
if iex_company_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract iex_company={ticker}')
# end of iex extracts
"""
Yahoo disabled on Jan 2019
yahoo_news_status = ae_consts.FAILED
yahoo_options_status = ae_consts.FAILED
yahoo_pricing_status = ae_consts.FAILED
yahoo_option_calls_df = None
yahoo_option_puts_df = None
yahoo_pricing_df = None
yahoo_news_df = None
if 'options' in datasets:
yahoo_options_status, yahoo_option_calls_df = \
yahoo_extract_utils.extract_option_calls_dataset(
base_req)
yahoo_options_status, yahoo_option_puts_df = \
yahoo_extract_utils.extract_option_puts_dataset(
base_req)
if yahoo_options_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract yahoo_options={ticker}')
if 'pricing' in datasets:
yahoo_pricing_status, yahoo_pricing_df = \
yahoo_extract_utils.extract_pricing_dataset(
base_req)
if yahoo_pricing_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract yahoo_pricing={ticker}')
if 'news' in datasets:
yahoo_news_status, yahoo_news_df = \
yahoo_extract_utils.extract_yahoo_news_dataset(
base_req)
if yahoo_news_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract yahoo_news={ticker}')
# end of yahoo extracts
"""
"""
Tradier Extraction
Debug by setting:
base_req['verbose_td'] = True
"""
if ('calls' in datasets or 'tdcalls' in datasets):
td_calls_status, td_calls_df = \
td_extract_utils.extract_option_calls_dataset(
base_req)
if td_calls_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract tdcalls={ticker}')
else:
if ae_consts.is_df(df=td_calls_df):
for c in td_convert_to_datetime:
if c in td_calls_df:
td_calls_df[c] = pd.to_datetime(
td_calls_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT)
if 'date' in td_calls_df:
td_calls_df.sort_values('date', ascending=True)
# end of converting dates
# end of Tradier calls extraction
if ('puts' in datasets or 'tdputs' in datasets):
td_puts_status, td_puts_df = \
td_extract_utils.extract_option_puts_dataset(
base_req)
if td_puts_status != ae_consts.SUCCESS:
if verbose:
log.warn(f'unable to extract tdputs={ticker}')
else:
if ae_consts.is_df(df=td_puts_df):
for c in td_convert_to_datetime:
if c in td_puts_df:
td_puts_df[c] = pd.to_datetime(
td_puts_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT)
if 'date' in td_puts_df:
td_puts_df.sort_values('date', ascending=True)
# end of converting dates
# end of Tradier puts extraction
ticker_data = {
'daily': iex_daily_df,
'minute': iex_minute_df,
'quote': iex_quote_df,
'stats': iex_stats_df,
'peers': iex_peers_df,
'news1': iex_news_df,
'financials': iex_financials_df,
'earnings': iex_earnings_df,
'dividends': iex_dividends_df,
'company': iex_company_df,
'tdcalls': td_calls_df,
'tdputs': td_puts_df,
'calls': None, # yahoo - here for legacy
'news': None, # yahoo - here for legacy
'pricing': None, # yahoo - here for legacy
'puts': None # yahoo - here for legacy
}
return ticker_data
def latest(self,
date_str=None,
start_row=-200,
extract_iex=True,
extract_yahoo=False,
extract_td=True,
verbose=False,
**kwargs):
"""latest
Run the algorithm with the latest pricing data. Also
supports running a backtest for a historical date in
the pricing history (format ``YYYY-MM-DD``)
:param date_str: optional - string start date ``YYYY-MM-DD``
default is the latest close date
:param start_row: negative number of rows back
from the end of the list in the data
default is ``-200`` where this means the algorithm
will process the latest 200 rows in the minute
dataset
:param extract_iex: bool flag for extracting from ``IEX``
:param extract_yahoo: bool flag for extracting from ``Yahoo``
which is disabled as of 1/2019
:param extract_td: bool flag for extracting from ``Tradier``
:param verbose: bool flag for logs
:param kwargs: keyword arg dict
"""
use_date_str = date_str
if not use_date_str:
use_date_str = ae_utils.get_last_close_str()
log.info(f'creating algo')
self.algo_obj = base_algo.BaseAlgo(
ticker=self.config_dict['ticker'],
balance=self.config_dict['balance'],
commission=self.config_dict['commission'],
name=self.use_name,
start_date=self.use_start_date,
end_date=self.use_end_date,
auto_fill=self.auto_fill,
config_dict=self.config_dict,
load_from_s3_bucket=self.load_from_s3_bucket,
load_from_s3_key=self.load_from_s3_key,
load_from_redis_key=self.load_from_redis_key,
load_from_file=self.load_from_file,
load_compress=self.load_compress,
load_publish=self.load_publish,
load_config=self.load_config,
report_redis_key=self.report_redis_key,
report_s3_bucket=self.report_s3_bucket,
report_s3_key=self.report_s3_key,
report_file=self.report_file,
report_compress=self.report_compress,
report_publish=self.report_publish,
report_config=self.report_config,
history_redis_key=self.history_redis_key,
history_s3_bucket=self.history_s3_bucket,
history_s3_key=self.history_s3_key,
history_file=self.history_file,
history_compress=self.history_compress,
history_publish=self.history_publish,
history_config=self.history_config,
extract_redis_key=self.extract_redis_key,
extract_s3_bucket=self.extract_s3_bucket,
extract_s3_key=self.extract_s3_key,
extract_file=self.extract_file,
extract_save_dir=self.extract_save_dir,
extract_compress=self.extract_compress,
extract_publish=self.extract_publish,
extract_config=self.extract_config,
publish_to_slack=self.publish_to_slack,
publish_to_s3=self.publish_to_s3,
publish_to_redis=self.publish_to_redis,
dataset_type=self.dataset_type,
serialize_datasets=self.serialize_datasets,
compress=self.compress,
encoding=self.encoding,
redis_enabled=self.redis_enabled,
redis_key=self.redis_key,
redis_address=self.redis_address,
redis_db=self.redis_db,
redis_password=self.redis_password,
redis_expire=self.redis_expire,
redis_serializer=self.redis_serializer,
redis_encoding=self.redis_encoding,
s3_enabled=self.s3_enabled,
s3_key=self.s3_key,
s3_address=self.s3_address,
s3_bucket=self.s3_bucket,
s3_access_key=self.s3_access_key,
s3_secret_key=self.s3_secret_key,
s3_region_name=self.s3_region_name,
s3_secure=self.s3_secure,
slack_enabled=self.slack_enabled,
slack_code_block=self.slack_code_block,
slack_full_width=self.slack_full_width,
dataset_publish_extract=self.extract_publish,
dataset_publish_history=self.history_publish,
dataset_publish_report=self.report_publish,
run_on_engine=self.run_on_engine,
auth_url=self.broker_url,
backend_url=self.backend_url,
include_tasks=self.include_tasks,
ssl_options=self.ssl_options,
transport_options=self.transport_options,
path_to_config_module=self.path_to_config_module,
timeseries=self.timeseries,
trade_strategy=self.trade_strategy,
verbose=False,
raise_on_err=self.raise_on_err)
log.info(f'run latest - start')
ticker = self.config_dict['ticker']
self.common_fetch_vals['base_key'] = f'{ticker}_{use_date_str}'
extract_req = api_requests.get_ds_dict(
ticker=ticker,
base_key=self.common_fetch_vals['base_key'],
ds_id=ticker,
service_dict=self.common_fetch_vals)
node_date_key = use_date_str.replace(f'{ticker}_', '')
req = {
'id': use_date_str,
'ticker': ticker,
'date_key': self.common_fetch_vals['base_key'],
'date': node_date_key,
'req': extract_req
}
# fetch
iex_daily_df = None
iex_minute_df = None
iex_quote_df = None
iex_stats_df = None
iex_peers_df = None
iex_news_df = None
iex_financials_df = None
iex_earnings_df = None
iex_dividends_df = None
iex_company_df = None
yahoo_option_calls_df = None
yahoo_option_puts_df = None
yahoo_pricing_df = None
yahoo_news_df = None
td_calls_df = None
td_puts_df = None
node_date_key = req['date']
dataset_node_id = req['id']
dataset_id = dataset_node_id
label = (f'ticker={ticker} ' f'date={node_date_key}')
if verbose:
log.info(f'{label} - extract - start')
if 'daily' in self.iex_datasets or extract_iex:
iex_daily_status, iex_daily_df = \
iex_extract_utils.extract_daily_dataset(
extract_req)
if iex_daily_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_daily={ticker}')
if 'minute' in self.iex_datasets or extract_iex:
iex_minute_status, iex_minute_df = \
iex_extract_utils.extract_minute_dataset(
extract_req)
if iex_minute_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_minute={ticker}')
if 'quote' in self.iex_datasets or extract_iex:
iex_quote_status, iex_quote_df = \
iex_extract_utils.extract_quote_dataset(
extract_req)
if iex_quote_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_quote={ticker}')
if 'stats' in self.iex_datasets or extract_iex:
iex_stats_status, iex_stats_df = \
iex_extract_utils.extract_stats_dataset(
extract_req)
if iex_stats_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_stats={ticker}')
if 'peers' in self.iex_datasets or extract_iex:
iex_peers_status, iex_peers_df = \
iex_extract_utils.extract_peers_dataset(
extract_req)
if iex_peers_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_peers={ticker}')
if 'news' in self.iex_datasets or extract_iex:
iex_news_status, iex_news_df = \
iex_extract_utils.extract_news_dataset(
extract_req)
if iex_news_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_news={ticker}')
if 'financials' in self.iex_datasets or extract_iex:
iex_financials_status, iex_financials_df = \
iex_extract_utils.extract_financials_dataset(
extract_req)
if iex_financials_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_financials={ticker}')
if 'earnings' in self.iex_datasets or extract_iex:
iex_earnings_status, iex_earnings_df = \
iex_extract_utils.extract_earnings_dataset(
extract_req)
if iex_earnings_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_earnings={ticker}')
if 'dividends' in self.iex_datasets or extract_iex:
iex_dividends_status, iex_dividends_df = \
iex_extract_utils.extract_dividends_dataset(
extract_req)
if iex_dividends_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_dividends={ticker}')
if 'company' in self.iex_datasets or extract_iex:
iex_company_status, iex_company_df = \
iex_extract_utils.extract_company_dataset(
extract_req)
if iex_company_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract iex_company={ticker}')
# end of iex extracts
if extract_yahoo:
yahoo_options_status, yahoo_option_calls_df = \
yahoo_extract_utils.extract_option_calls_dataset(
extract_req)
yahoo_options_status, yahoo_option_puts_df = \
yahoo_extract_utils.extract_option_puts_dataset(
extract_req)
if yahoo_options_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract yahoo_options={ticker}')
yahoo_pricing_status, yahoo_pricing_df = \
yahoo_extract_utils.extract_pricing_dataset(
extract_req)
if yahoo_pricing_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract yahoo_pricing={ticker}')
yahoo_news_status, yahoo_news_df = \
yahoo_extract_utils.extract_yahoo_news_dataset(
extract_req)
if yahoo_news_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract yahoo_news={ticker}')
# end of yahoo extracts
if extract_td:
"""
Debug by setting:
extract_req['verbose_td'] = True
"""
convert_to_datetime = [
'date', 'created', 'ask_date', 'bid_date', 'trade_date'
]
td_calls_status, td_calls_df = \
td_extract_utils.extract_option_calls_dataset(
extract_req)
if td_calls_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract tdcalls={ticker}')
else:
if ae_consts.is_df(df=td_calls_df):
for c in convert_to_datetime:
if c in td_calls_df:
td_calls_df[c] = pd.to_datetime(
td_calls_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT)
if 'date' in td_calls_df:
td_calls_df.sort_values('date', ascending=True)
# end of converting dates
td_puts_status, td_puts_df = \
td_extract_utils.extract_option_puts_dataset(
extract_req)
if td_puts_status != ae_consts.SUCCESS:
if verbose:
log.warning(f'unable to extract tdputs={ticker}')
else:
if ae_consts.is_df(df=td_puts_df):
for c in convert_to_datetime:
if c in td_puts_df:
td_puts_df[c] = pd.to_datetime(
td_puts_df[c],
format=ae_consts.COMMON_TICK_DATE_FORMAT)
if 'date' in td_puts_df:
td_puts_df.sort_values('date', ascending=True)
# end of converting dates
# td extracts
# map extracted data to DEFAULT_SERIALIZED_DATASETS
ticker_data = {}
ticker_data['daily'] = iex_daily_df
ticker_data['minute'] = iex_minute_df
ticker_data['quote'] = iex_quote_df
ticker_data['stats'] = iex_stats_df
ticker_data['peers'] = iex_peers_df
ticker_data['news1'] = iex_news_df
ticker_data['financials'] = iex_financials_df
ticker_data['earnings'] = iex_earnings_df
ticker_data['dividends'] = iex_dividends_df
ticker_data['company'] = iex_company_df
ticker_data['calls'] = yahoo_option_calls_df
ticker_data['puts'] = yahoo_option_puts_df
ticker_data['pricing'] = yahoo_pricing_df
ticker_data['news'] = yahoo_news_df
ticker_data['tdcalls'] = td_calls_df
ticker_data['tdputs'] = td_puts_df
algo_data_req = {
ticker: [{
'id': dataset_id, # id is currently the cache key in redis
'date': use_date_str, # used to confirm dates in asc order
'data': ticker_data,
'start_row': start_row
}]
}
if verbose:
log.info(f'extract - {label} '
f'dataset={len(algo_data_req[ticker])}')
# this could be a separate celery task
try:
if verbose:
log.info(f'handle_data START - {label} from '
f'{node_date_key}')
self.algo_obj.handle_data(data=algo_data_req)
if verbose:
log.info(f'handle_data END - {label} from ' f'{node_date_key}')
except Exception as e:
a_name = self.algo_obj.get_name()
a_debug_msg = self.algo_obj.get_debug_msg()
if not a_debug_msg:
a_debug_msg = 'debug message not set'
# a_config_dict = ae_consts.ppj(self.algo_obj.config_dict)
msg = (f'{label} - algo={a_name} '
f'encountered exception in handle_data tickers={ticker} '
f'from {node_date_key} ex={e} '
f'and failed during operation: {a_debug_msg}')
log.critical(f'{msg}')
# end try/ex
log.info(f'run latest - create history')
history_ds = self.algo_obj.create_history_dataset()
self.history_df = pd.DataFrame(history_ds[ticker])
self.determine_latest_times_in_history()
self.num_rows = len(self.history_df.index)
if verbose:
log.info(self.history_df[['minute', 'close']].tail(5))
log.info(f'run latest minute={self.end_date} - '
f'rows={self.num_rows} - done')
return self.get_history()