def run_distributed_algorithm(self, algo_req):
"""run_distributed_algorithm
Process an Algorithm using a Celery task that is
processed by a Celery worker
:param algo_req: dictionary for key/values for
running an algorithm using Celery workers
"""
label = algo_req.get('name', 'ae-algo')
verbose = algo_req.get('verbose_task', False)
debug = algo_req.get('debug', False)
# please be careful logging prod passwords:
if debug:
log.info(f'task - {label} - start algo_req={algo_req}')
elif verbose:
log.info(f'task - {label} - start ')
# end of start log
rec = {}
res = build_result.build_result(status=ae_consts.NOT_RUN,
err=None,
rec=rec)
created_algo_object = None
custom_algo_module = None
new_algo_object = None
use_custom_algo = False
found_algo_module = True # assume the BaseAlgo
should_publish_extract_dataset = False
should_publish_history_dataset = False
should_publish_report_dataset = False
ticker = algo_req.get('ticker', 'SPY')
num_days_back = algo_req.get('num_days_back', 75)
name = algo_req.get('name', 'ae-algo')
algo_module_path = algo_req.get('mod_path', None)
module_name = algo_req.get('module_name', 'BaseAlgo')
custom_algo_module = algo_req.get('custom_algo_module', None)
new_algo_object = algo_req.get('new_algo_object', None)
use_custom_algo = algo_req.get('use_custom_algo', False)
should_publish_extract_dataset = algo_req.get(
'should_publish_extract_dataset', False)
should_publish_history_dataset = algo_req.get(
'should_publish_history_dataset', False)
should_publish_report_dataset = algo_req.get(
'should_publish_report_dataset', False)
start_date = algo_req.get('start_date', None)
end_date = algo_req.get('end_date', None)
raise_on_err = algo_req.get('raise_on_err', True)
report_config = algo_req.get('report_config', None)
history_config = algo_req.get('history_config', None)
extract_config = algo_req.get('extract_config', None)
err = None
if algo_module_path:
found_algo_module = False
module_name = algo_module_path.split('/')[-1]
loader = importlib.machinery.SourceFileLoader(module_name,
algo_module_path)
custom_algo_module = types.ModuleType(loader.name)
loader.exec_module(custom_algo_module)
use_custom_algo = True
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
found_algo_module = True
break
# for all members in this custom module file
# if loading a custom algorithm module from a file on disk
if not found_algo_module:
err = (f'{label} - unable to find custom algorithm '
f'module={custom_algo_module} module_path={algo_module_path}')
if algo_module_path:
err = (
f'{label} - analysis_engine.'
'work_tasks.run_distributed_algorithm was unable '
f'to find custom algorithm module={custom_algo_module} with '
f'provided path to \n file: {algo_module_path} \n'
'\n'
'Please confirm '
'that the class inherits from the BaseAlgo class like:\n'
'\n'
'import analysis_engine.algo\n'
'class MyAlgo(analysis_engine.algo.BaseAlgo):\n '
'\n'
'If it is then please file an issue on github:\n '
'https://github.com/AlgoTraders/stock-analysis-engine/'
'issues/new \n\nFor now this error results in a shutdown'
'\n')
# if algo_module_path set
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# if not found_algo_module
use_start_date = start_date
use_end_date = end_date
if not use_end_date:
end_date = datetime.datetime.utcnow()
use_end_date = end_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
if not use_start_date:
start_date = end_date - datetime.timedelta(days=num_days_back)
use_start_date = start_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
dataset_publish_extract = algo_req.get('dataset_publish_extract', False)
dataset_publish_history = algo_req.get('dataset_publish_history', False)
dataset_publish_report = algo_req.get('dataset_publish_report', False)
try:
if use_custom_algo:
if verbose:
log.info(
f'inspecting {custom_algo_module} for class {module_name}')
use_class_member_object = None
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
if verbose:
log.info(f'start {name} with {member[1]}')
use_class_member_object = member
break
# end of looking over the class definition but did not find it
if use_class_member_object:
if algo_req.get('backtest', False):
new_algo_object = member[1](ticker=algo_req['ticker'],
config_dict=algo_req)
else:
new_algo_object = member[1](**algo_req)
else:
err = (f'{label} - did not find a derived '
'analysis_engine.algo.BaseAlgo '
f'class in the module file={algo_module_path} '
f'for ticker={ticker} algo_name={name}')
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of finding a valid algorithm object
else:
new_algo_object = ae_algo.BaseAlgo(**algo_req)
# if using a custom module path or the BaseAlgo
if new_algo_object:
# heads up - logging this might have passwords in the algo_req
# log.debug(f'{name} algorithm request: {algo_req}')
if verbose:
log.info(f'{name} - run START ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
if algo_req.get('backtest', False):
algo_res = run_algo.run_algo(algo=new_algo_object,
config_dict=algo_req)
created_algo_object = new_algo_object
else:
algo_res = run_algo.run_algo(algo=new_algo_object, **algo_req)
created_algo_object = new_algo_object
if verbose:
log.info(f'{name} - run DONE ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
if debug:
if custom_algo_module:
log.info(f'{name} - done run_algo '
f'custom_algo_module={custom_algo_module} '
f'module_name={module_name} ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
else:
log.info(
f'{name} - done run_algo BaseAlgo ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
else:
err = (
f'{label} - missing a derived analysis_engine.algo.BaseAlgo '
f'class in the module file={algo_module_path} for '
f'ticker={ticker} algo_name={name}')
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of finding a valid algorithm object
if not created_algo_object:
err = (f'{label} - failed creating algorithm object - '
f'ticker={ticker} '
f'status={ae_consts.get_status(status=algo_res["status"])} '
f'error={algo_res["err"]} algo name={name} '
f'custom_algo_module={custom_algo_module} '
f'module_name={module_name} '
f'from {use_start_date} to {use_end_date}')
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of stop early
if should_publish_extract_dataset or dataset_publish_extract:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (extract_config['redis_address'] and extract_config['redis_db']
and extract_config['redis_key']):
redis_log = (f'redis://{extract_config["redis_address"]}'
f'@{extract_config["redis_db"]}'
f'/{extract_config["redis_key"]}')
use_log += f' {redis_log}'
else:
extract_config['redis_enabled'] = False
if (extract_config['s3_address'] and extract_config['s3_bucket']
and extract_config['s3_key']):
s3_log = (f's3://{extract_config["s3_address"]}'
f'/{extract_config["s3_bucket"]}'
f'/{extract_config["s3_key"]}')
use_log += f' {s3_log}'
else:
extract_config['s3_enabled'] = False
if extract_config['output_file']:
file_log = f'file:{extract_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(f'{name} - publish - start ticker={ticker} '
f'algorithm-ready {use_log}')
publish_status = created_algo_object.publish_input_dataset(
**extract_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish algorithm-ready datasets with '
f'status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of stop early
if verbose:
log.info(f'{name} - publish - done ticker={ticker} '
f'algorithm-ready {use_log}')
# if publish the algorithm-ready dataset
if should_publish_history_dataset or dataset_publish_history:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (history_config['redis_address'] and history_config['redis_db']
and history_config['redis_key']):
redis_log = (f'redis://{history_config["redis_address"]}'
f'@{history_config["redis_db"]}'
f'/{history_config["redis_key"]}')
use_log += f' {redis_log}'
if (history_config['s3_address'] and history_config['s3_bucket']
and history_config['s3_key']):
s3_log = (f's3://{history_config["s3_address"]}'
f'/{history_config["s3_bucket"]}'
f'/{history_config["s3_key"]}')
use_log += f' {s3_log}'
if history_config['output_file']:
file_log = f'file:{history_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(f'{name} - publish - start ticker={ticker} trading '
f'history {use_log}')
publish_status = \
created_algo_object.publish_trade_history_dataset(
**history_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish trading history datasets with '
f'status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of stop early
if verbose:
log.info(f'{name} - publish - done ticker={ticker} trading '
f'history {use_log}')
# if publish an trading history dataset
if should_publish_report_dataset or dataset_publish_report:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (report_config['redis_address'] and report_config['redis_db']
and report_config['redis_key']):
redis_log = (f'redis://{report_config["redis_address"]}'
f'@{report_config["redis_db"]}'
f'/{report_config["redis_key"]}')
use_log += f' {redis_log}'
if (report_config['s3_address'] and report_config['s3_bucket']
and report_config['s3_key']):
s3_log = (f's3://{report_config["s3_address"]}'
f'/{report_config["s3_bucket"]}'
f'/{report_config["s3_key"]}')
use_log += f' {s3_log}'
if report_config['output_file']:
file_log = f' file:{report_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(
f'{name} - publishing ticker={ticker} trading performance '
f'report {use_log}')
publish_status = created_algo_object.publish_report_dataset(
**report_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish trading performance '
'report datasets with '
f'status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
# end of stop early
if verbose:
log.info(f'{name} - publish - done ticker={ticker} trading '
f'performance report {use_log}')
# if publish an trading performance report dataset
if verbose:
log.info(f'{name} - done publishing datasets for ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
rec['history_config'] = history_config
rec['report_config'] = report_config
res = build_result.build_result(status=ae_consts.SUCCESS,
err=None,
rec=rec)
except Exception as e:
res = build_result.build_result(
status=ae_consts.ERR,
err=('failed - run_distributed_algorithm '
f'dict={algo_req} with ex={e}'),
rec=rec)
if raise_on_err:
raise e
else:
log.error(f'{label} - {res["err"]}')
# end of try/ex
if verbose:
log.info('task - run_distributed_algorithm done - '
f'{label} - status={ae_consts.get_status(res["status"])}')
task_result = {
'status': res['status'],
'err': res['err'],
'algo_req': algo_req,
'rec': rec
}
return task_result
def run_backtest_and_plot_history(config_dict):
"""run_backtest_and_plot_history
Run a derived algorithm with an algorithm config dictionary
:param config_dict: algorithm config dictionary
"""
log.debug('start - sa')
parser = argparse.ArgumentParser(description=('stock analysis tool'))
parser.add_argument('-t', help=('ticker'), required=True, dest='ticker')
parser.add_argument('-e',
help=('file path to extract an '
'algorithm-ready datasets from redis'),
required=False,
dest='algo_extract_loc')
parser.add_argument('-l',
help=('show dataset in this file'),
required=False,
dest='show_from_file')
parser.add_argument('-H',
help=('show trading history dataset in this file'),
required=False,
dest='show_history_from_file')
parser.add_argument(
'-E',
help=('show trading performance report dataset in this file'),
required=False,
dest='show_report_from_file')
parser.add_argument(
'-L',
help=('restore an algorithm-ready dataset file back into redis'),
required=False,
dest='restore_algo_file')
parser.add_argument('-f',
help=('save the trading history dataframe '
'to this file'),
required=False,
dest='history_json_file')
parser.add_argument(
'-J',
help=('plot action - after preparing you can use: '
'-J show to open the image (good for debugging)'),
required=False,
dest='plot_action')
parser.add_argument(
'-b',
help=('run a backtest using the dataset in '
'a file path/s3 key/redis key formats: '
'file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
's3://algoready/SPY-latest.json or '
'redis:SPY-latest'),
required=False,
dest='backtest_loc')
parser.add_argument('-B',
help=('optional - broker url for Celery'),
required=False,
dest='broker_url')
parser.add_argument('-C',
help=('optional - broker url for Celery'),
required=False,
dest='backend_url')
parser.add_argument(
'-w',
help=('optional - flag for publishing an algorithm job '
'using Celery to the ae workers'),
required=False,
dest='run_on_engine',
action='store_true')
parser.add_argument('-k',
help=('optional - s3 access key'),
required=False,
dest='s3_access_key')
parser.add_argument('-K',
help=('optional - s3 secret key'),
required=False,
dest='s3_secret_key')
parser.add_argument('-a',
help=('optional - s3 address format: <host:port>'),
required=False,
dest='s3_address')
parser.add_argument('-Z',
help=('optional - s3 secure: default False'),
required=False,
dest='s3_secure')
parser.add_argument('-s',
help=('optional - start date: YYYY-MM-DD'),
required=False,
dest='start_date')
parser.add_argument('-n',
help=('optional - end date: YYYY-MM-DD'),
required=False,
dest='end_date')
parser.add_argument('-u',
help=('optional - s3 bucket name'),
required=False,
dest='s3_bucket_name')
parser.add_argument('-G',
help=('optional - s3 region name'),
required=False,
dest='s3_region_name')
parser.add_argument(
'-g',
help=('Path to a custom algorithm module file '
'on disk. This module must have a single '
'class that inherits from: '
'https://github.com/AlgoTraders/stock-analysis-engine/'
'blob/master/'
'analysis_engine/algo.py Additionally you '
'can find the Example-Minute-Algorithm here: '
'https://github.com/AlgoTraders/stock-analysis-engine/'
'blob/master/analysis_engine/mocks/'
'example_algo_minute.py'),
required=False,
dest='run_algo_in_file')
parser.add_argument('-p',
help=('optional - s3 bucket/file for trading history'),
required=False,
dest='algo_history_loc')
parser.add_argument(
'-o',
help=('optional - s3 bucket/file for trading performance report'),
required=False,
dest='algo_report_loc')
parser.add_argument('-r',
help=('optional - redis_address format: <host:port>'),
required=False,
dest='redis_address')
parser.add_argument('-R',
help=('optional - redis and s3 key name'),
required=False,
dest='keyname')
parser.add_argument(
'-m',
help=('optional - redis database number (0 by default)'),
required=False,
dest='redis_db')
parser.add_argument('-x',
help=('optional - redis expiration in seconds'),
required=False,
dest='redis_expire')
parser.add_argument(
'-c',
help=('optional - algorithm config_file path for setting '
'up internal algorithm trading strategies and '
'indicators'),
required=False,
dest='config_file')
parser.add_argument('-v',
help=('set the Algorithm to verbose logging'),
required=False,
dest='verbose_algo',
action='store_true')
parser.add_argument(
'-P',
help=('set the Algorithm\'s IndicatorProcessor to verbose logging'),
required=False,
dest='verbose_processor',
action='store_true')
parser.add_argument(
'-I',
help=('set all Algorithm\'s Indicators to verbose logging '
'(note indivdual indicators support a \'verbose\' key '
'that can be set to True to debug just one '
'indicator)'),
required=False,
dest='verbose_indicators',
action='store_true')
parser.add_argument(
'-V',
help=('inspect the datasets an algorithm is processing - this'
'will slow down processing to show debugging'),
required=False,
dest='inspect_datasets',
action='store_true')
parser.add_argument(
'-j',
help=('run the algorithm on just this specific date in the datasets '
'- specify the date in a format: YYYY-MM-DD like: 2018-11-29'),
required=False,
dest='run_this_date')
parser.add_argument('-d',
help=('debug'),
required=False,
dest='debug',
action='store_true')
args = parser.parse_args()
ticker = ae_consts.TICKER
use_balance = 10000.0
use_commission = 6.0
use_start_date = None
use_end_date = None
use_config_file = None
debug = False
verbose_algo = None
verbose_processor = None
verbose_indicators = None
inspect_datasets = None
history_json_file = None
run_this_date = None
s3_access_key = ae_consts.S3_ACCESS_KEY
s3_secret_key = ae_consts.S3_SECRET_KEY
s3_region_name = ae_consts.S3_REGION_NAME
s3_address = ae_consts.S3_ADDRESS
s3_secure = ae_consts.S3_SECURE
redis_address = ae_consts.REDIS_ADDRESS
redis_password = ae_consts.REDIS_PASSWORD
redis_db = ae_consts.REDIS_DB
redis_expire = ae_consts.REDIS_EXPIRE
if args.s3_access_key:
s3_access_key = args.s3_access_key
if args.s3_secret_key:
s3_secret_key = args.s3_secret_key
if args.s3_region_name:
s3_region_name = args.s3_region_name
if args.s3_address:
s3_address = args.s3_address
if args.s3_secure:
s3_secure = args.s3_secure
if args.redis_address:
redis_address = args.redis_address
if args.redis_db:
redis_db = args.redis_db
if args.redis_expire:
redis_expire = args.redis_expire
if args.history_json_file:
history_json_file = args.history_json_file
if args.ticker:
ticker = args.ticker.upper()
if args.debug:
debug = True
if args.verbose_algo:
verbose_algo = True
if args.verbose_processor:
verbose_processor = True
if args.verbose_indicators:
verbose_indicators = True
if args.inspect_datasets:
inspect_datasets = True
if args.run_this_date:
run_this_date = args.run_this_date
if args.start_date:
try:
use_start_date = f'{str(args.start_date)} 00:00:00'
datetime.datetime.strptime(args.start_date,
ae_consts.COMMON_DATE_FORMAT)
except Exception as e:
msg = ('please use a start date formatted as: '
f'{ae_consts.COMMON_DATE_FORMAT}\nerror was: {e}')
log.error(msg)
sys.exit(1)
# end of testing for a valid date
# end of args.start_date
if args.end_date:
try:
use_end_date = f'{str(args.end_date)} 00:00:00'
datetime.datetime.strptime(args.end_date,
ae_consts.COMMON_DATE_FORMAT)
except Exception as e:
msg = ('please use an end date formatted as: '
f'{ae_consts.COMMON_DATE_FORMAT}\nerror was: {e}')
log.error(msg)
sys.exit(1)
# end of testing for a valid date
# end of args.end_date
if args.config_file:
use_config_file = args.config_file
if not os.path.exists(use_config_file):
log.error(
f'Failed: unable to find config file: -c {use_config_file}')
sys.exit(1)
if args.backtest_loc:
backtest_loc = args.backtest_loc
if ('file:/' not in backtest_loc and 's3://' not in backtest_loc
and 'redis://' not in backtest_loc):
log.error('invalid -b <backtest dataset file> specified. '
f'{backtest_loc} '
'please use either: '
'-b file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-b s3://algoready/SPY-latest.json or '
'-b redis://SPY-latest')
sys.exit(1)
load_from_s3_bucket = None
load_from_s3_key = None
load_from_redis_key = None
load_from_file = None
if 's3://' in backtest_loc:
load_from_s3_bucket = backtest_loc.split('/')[-2]
load_from_s3_key = backtest_loc.split('/')[-1]
elif 'redis://' in backtest_loc:
load_from_redis_key = backtest_loc.split('/')[-1]
elif 'file:/' in backtest_loc:
load_from_file = backtest_loc.split(':')[-1]
# end of parsing supported transport - loading an algo-ready
load_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=load_from_file,
s3_bucket=load_from_s3_bucket,
s3_key=load_from_s3_key,
redis_key=load_from_redis_key,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
verbose=debug,
label=f'load-{backtest_loc}')
if load_from_file:
load_config['output_file'] = load_from_file
if load_from_redis_key:
load_config['redis_key'] = load_from_redis_key
load_config['redis_enabled'] = True
if load_from_s3_bucket and load_from_s3_key:
load_config['s3_bucket'] = load_from_s3_bucket
load_config['s3_key'] = load_from_s3_key
load_config['s3_enabled'] = True
if debug:
log.info('starting algo')
config_dict['ticker'] = ticker
config_dict['balance'] = use_balance
config_dict['commission'] = use_commission
if verbose_algo:
config_dict['verbose'] = verbose_algo
if verbose_processor:
config_dict['verbose_processor'] = verbose_processor
if verbose_indicators:
config_dict['verbose_indicators'] = verbose_indicators
if inspect_datasets:
config_dict['inspect_datasets'] = inspect_datasets
if run_this_date:
config_dict['run_this_date'] = run_this_date
algo_obj = ExampleCustomAlgo(ticker=config_dict['ticker'],
config_dict=config_dict)
algo_res = run_algo.run_algo(ticker=ticker,
algo=algo_obj,
start_date=use_start_date,
end_date=use_end_date,
raise_on_err=True)
if algo_res['status'] != ae_consts.SUCCESS:
log.error('failed running algo backtest '
f'{algo_obj.get_name()} hit status: '
f'{ae_consts.get_status(status=algo_res["status"])} '
f'error: {algo_res["err"]}')
return
# if not successful
log.info(f'backtest: {algo_obj.get_name()} '
f'{ae_consts.get_status(status=algo_res["status"])}')
trading_history_dict = algo_obj.get_history_dataset()
history_df = trading_history_dict[ticker]
if not hasattr(history_df, 'to_json'):
return
if history_json_file:
log.info(f'saving history to: {history_json_file}')
history_df.to_json(history_json_file,
orient='records',
date_format='iso')
log.info('plotting history')
use_xcol = 'date'
use_as_date_format = '%d\n%b'
xlabel = f'Dates vs {trading_history_dict["algo_name"]} values'
ylabel = f'Algo {trading_history_dict["algo_name"]}\nvalues'
df_filter = (history_df['close'] > 0.01)
first_date = history_df[df_filter]['date'].iloc[0]
end_date = history_df[df_filter]['date'].iloc[-1]
if config_dict['timeseries'] == 'minute':
use_xcol = 'minute'
use_as_date_format = '%d %H:%M:%S\n%b'
first_date = history_df[df_filter]['minute'].iloc[0]
end_date = history_df[df_filter]['minute'].iloc[-1]
title = (f'Trading History {ticker} for Algo '
f'{trading_history_dict["algo_name"]}\n'
f'Backtest dates from {first_date} to {end_date}')
# set default hloc columns:
blue = None
green = None
orange = None
red = 'close'
blue = 'balance'
if debug:
for i, r in history_df.iterrows():
log.debug(f'{r["minute"]} - {r["close"]}')
plot_trading_history.plot_trading_history(title=title,
df=history_df,
red=red,
blue=blue,
green=green,
orange=orange,
date_col=use_xcol,
date_format=use_as_date_format,
xlabel=xlabel,
ylabel=ylabel,
df_filter=df_filter,
show_plot=True,
dropna_for_all=True)
def run_custom_algo(
mod_path,
ticker='SPY',
balance=50000,
commission=6.0,
start_date=None,
end_date=None,
name='myalgo',
auto_fill=True,
config_file=None,
config_dict=None,
load_from_s3_bucket=None,
load_from_s3_key=None,
load_from_redis_key=None,
load_from_file=None,
load_compress=False,
load_publish=True,
load_config=None,
report_redis_key=None,
report_s3_bucket=None,
report_s3_key=None,
report_file=None,
report_compress=False,
report_publish=True,
report_config=None,
history_redis_key=None,
history_s3_bucket=None,
history_s3_key=None,
history_file=None,
history_compress=False,
history_publish=True,
history_config=None,
extract_redis_key=None,
extract_s3_bucket=None,
extract_s3_key=None,
extract_file=None,
extract_save_dir=None,
extract_compress=False,
extract_publish=True,
extract_config=None,
publish_to_s3=True,
publish_to_redis=True,
publish_to_slack=True,
dataset_type=ae_consts.SA_DATASET_TYPE_ALGO_READY,
serialize_datasets=ae_consts.DEFAULT_SERIALIZED_DATASETS,
compress=False,
encoding='utf-8',
redis_enabled=True,
redis_key=None,
redis_address=None,
redis_db=None,
redis_password=None,
redis_expire=None,
redis_serializer='json',
redis_encoding='utf-8',
s3_enabled=True,
s3_key=None,
s3_address=None,
s3_bucket=None,
s3_access_key=None,
s3_secret_key=None,
s3_region_name=None,
s3_secure=False,
slack_enabled=False,
slack_code_block=False,
slack_full_width=False,
timeseries=None,
trade_strategy=None,
verbose=False,
debug=False,
dataset_publish_extract=False,
dataset_publish_history=False,
dataset_publish_report=False,
run_on_engine=False,
auth_url=ae_consts.WORKER_BROKER_URL,
backend_url=ae_consts.WORKER_BACKEND_URL,
include_tasks=ae_consts.INCLUDE_TASKS,
ssl_options=ae_consts.SSL_OPTIONS,
transport_options=ae_consts.TRANSPORT_OPTIONS,
path_to_config_module=ae_consts.WORKER_CELERY_CONFIG_MODULE,
raise_on_err=True):
"""run_custom_algo
Run a custom algorithm that derives the
``analysis_engine.algo.BaseAlgo`` class
.. note:: Make sure to only have **1**
class defined in an algo module. Imports from
other modules should work just fine.
**Algorithm arguments**
:param mod_path: file path to custom
algorithm class module
:param ticker: ticker symbol
:param balance: float - starting balance capital
for creating buys and sells
:param commission: float - cost pet buy or sell
:param name: string - name for tracking algorithm
in the logs
:param start_date: string - start date for backtest with
format ``YYYY-MM-DD HH:MM:SS``
:param end_date: end date for backtest with
format ``YYYY-MM-DD HH:MM:SS``
:param auto_fill: optional - boolean for auto filling
buy and sell orders for backtesting
(default is ``True``)
: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``)
**Running Distributed Algorithms on the Engine Workers**
:param run_on_engine: optional - boolean
flag for publishing custom algorithms
to Celery ae workers for distributing
algorithm workloads
(default is ``False`` which will run algos locally)
this is required for distributing algorithms
:param auth_url: Celery broker address
(default is ``redis://localhost:6379/11``
or ``analysis_engine.consts.WORKER_BROKER_URL``
environment variable)
this is required for distributing algorithms
:param backend_url: Celery backend address
(default is ``redis://localhost:6379/12``
or ``analysis_engine.consts.WORKER_BACKEND_URL``
environment variable)
this is required for distributing algorithms
:param include_tasks: list of modules containing tasks to add
(default is ``analysis_engine.consts.INCLUDE_TASKS``)
:param ssl_options: security options dictionary
(default is ``analysis_engine.consts.SSL_OPTIONS``)
:param trasport_options: transport options dictionary
(default is ``analysis_engine.consts.TRANSPORT_OPTIONS``)
:param path_to_config_module: config module for advanced
Celery worker connectivity requirements
(default is ``analysis_engine.work_tasks.celery_config``
or ``analysis_engine.consts.WORKER_CELERY_CONFIG_MODULE``)
**Load Algorithm-Ready Dataset From Source**
Use these arguments to load algorithm-ready datasets
from supported sources (file, s3 or redis)
:param load_from_s3_bucket: optional - string load the algo from an
a previously-created s3 bucket holding an s3 key with an
algorithm-ready dataset for use with:
``handle_data``
:param load_from_s3_key: optional - string load the algo from an
a previously-created s3 key holding an
algorithm-ready dataset for use with:
``handle_data``
:param load_from_redis_key: optional - string load the algo from a
a previously-created redis key holding an
algorithm-ready dataset for use with:
``handle_data``
:param load_from_file: optional - string path to
a previously-created local file holding an
algorithm-ready dataset for use with:
``handle_data``
:param load_compress: optional - boolean
flag for toggling to decompress
or not when loading an algorithm-ready
dataset (``True`` means the dataset
must be decompressed to load correctly inside
an algorithm to run a backtest)
:param load_publish: boolean - toggle publishing
the load progress to slack, s3, redis or a file
(default is ``True``)
:param load_config: optional - dictionary
for setting member variables to load an
agorithm-ready dataset from
a file, s3 or redis
**Publishing Control Bool Flags**
:param publish_to_s3: optional - boolean for
toggling publishing to s3 on/off
(default is ``True``)
:param publish_to_redis: optional - boolean for
publishing to redis on/off
(default is ``True``)
:param publish_to_slack: optional - boolean for
publishing to slack
(default is ``True``)
**Algorithm Trade History Arguments**
:param history_redis_key: optional - string
where the algorithm trading history will be stored in
an redis key
:param history_s3_bucket: optional - string
where the algorithm trading history will be stored in
an s3 bucket
:param history_s3_key: optional - string
where the algorithm trading history will be stored in
an s3 key
:param history_file: optional - string key
where the algorithm trading history will be stored in
a file serialized as a json-string
:param history_compress: optional - boolean
flag for toggling to decompress
or not when loading an algorithm-ready
dataset (``True`` means the dataset
will be compressed on publish)
:param history_publish: boolean - toggle publishing
the history to s3, redis or a file
(default is ``True``)
:param history_config: optional - dictionary
for setting member variables to publish
an algo ``trade history`` to s3, redis, a file
or slack
**Algorithm Trade Performance Report Arguments (Output Dataset)**
:param report_redis_key: optional - string
where the algorithm ``trading performance report`` (report)
will be stored in an redis key
:param report_s3_bucket: optional - string
where the algorithm report will be stored in
an s3 bucket
:param report_s3_key: optional - string
where the algorithm report will be stored in
an s3 key
:param report_file: optional - string key
where the algorithm report will be stored in
a file serialized as a json-string
:param report_compress: optional - boolean
flag for toggling to decompress
or not when loading an algorithm-ready
dataset (``True`` means the dataset
will be compressed on publish)
:param report_publish: boolean - toggle publishing
the ``trading performance report`` s3, redis or a file
(default is ``True``)
:param report_config: optional - dictionary
for setting member variables to publish
an algo ``trading performance report`` to s3,
redis, a file or slack
**Extract an Algorithm-Ready Dataset Arguments**
:param extract_redis_key: optional - string
where the algorithm report will be stored in
an redis key
:param extract_s3_bucket: optional - string
where the algorithm report will be stored in
an s3 bucket
:param extract_s3_key: optional - string
where the algorithm report will be stored in
an s3 key
:param extract_file: optional - string key
where the algorithm report will be stored in
a file serialized as a json-string
:param extract_save_dir: optional - string path to
auto-generated files from the algo
:param extract_compress: optional - boolean
flag for toggling to decompress
or not when loading an algorithm-ready
dataset (``True`` means the dataset
will be compressed on publish)
:param extract_publish: boolean - toggle publishing
the used ``algorithm-ready dataset`` to s3, redis or a file
(default is ``True``)
:param extract_config: optional - dictionary
for setting member variables to publish
an algo ``trading performance report`` to s3,
redis, a file or slack
**Dataset Arguments**
:param dataset_type: optional - dataset type
(default is ``SA_DATASET_TYPE_ALGO_READY``)
:param serialize_datasets: optional - list of dataset names to
deserialize in the dataset
(default is ``DEFAULT_SERIALIZED_DATASETS``)
:param encoding: optional - string for data encoding
**Publish Algorithm Datasets to S3, Redis or a File**
:param dataset_publish_extract: optional - bool
for publishing the algorithm's
``algorithm-ready``
dataset to: s3, redis or file
:param dataset_publish_history: optional - bool
for publishing the algorithm's
``trading history``
dataset to: s3, redis or file
:param dataset_publish_report: optional - bool
for publishing the algorithm's
``trading performance report``
dataset to: s3, redis or file
**Redis connectivity arguments**
:param redis_enabled: bool - toggle for auto-caching all
datasets in Redis
(default is ``True``)
:param redis_key: string - key to save the data in redis
(default is ``None``)
: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_serializer: not used yet - support for future
pickle objects in redis
:param redis_encoding: format of the encoded key in redis
**Minio (S3) connectivity arguments**
:param s3_enabled: bool - toggle for auto-archiving on Minio (S3)
(default is ``True``)
:param s3_key: string - key to save the data in redis
(default is ``None``)
: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``)
**Slack arguments**
:param slack_enabled: optional - boolean for
publishing to slack
:param slack_code_block: optional - boolean for
publishing as a code black in slack
:param slack_full_width: optional - boolean for
publishing as a to slack using the full
width allowed
**Debugging arguments**
:param debug: optional - bool for debug tracking
:param verbose: optional - bool for increasing
logging
:param raise_on_err: boolean - set this to ``False`` on prod
to ensure exceptions do not interrupt services.
With the default (``True``) any exceptions from the library
and your own algorithm are sent back out immediately exiting
the backtest.
"""
module_name = 'BaseAlgo'
custom_algo_module = None
new_algo_object = None
use_custom_algo = False
found_algo_module = True
should_publish_extract_dataset = False
should_publish_history_dataset = False
should_publish_report_dataset = False
use_config_file = None
use_config_dict = config_dict
if config_file:
if os.path.exists(config_file):
use_config_file = config_file
if not config_dict:
try:
use_config_dict = json.loads(open(config_file, 'r').read())
except Exception as e:
msg = (f'failed parsing json config_file={config_file} '
f'with ex={e}')
log.error(msg)
raise Exception(msg)
# end of loading the config_file
err = None
if mod_path:
module_name = mod_path.split('/')[-1]
loader = importlib.machinery.SourceFileLoader(module_name, mod_path)
custom_algo_module = types.ModuleType(loader.name)
loader.exec_module(custom_algo_module)
use_custom_algo = True
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
found_algo_module = True
break
# for all members in this custom module file
# if loading a custom algorithm module from a file on disk
if not found_algo_module:
err = (f'unable to find custom algorithm module={custom_algo_module}')
if mod_path:
err = (
'analysis_engine.run_custom_algo.run_custom_algo was unable '
f'to find custom algorithm module={custom_algo_module} with '
f'provided path to \n file: {mod_path} \n'
'\n'
'Please confirm '
'that the class inherits from the BaseAlgo class like:\n'
'\n'
'import analysis_engine.algo\n'
'class MyAlgo(analysis_engine.algo.BaseAlgo):\n '
'\n'
'If it is then please file an issue on github:\n '
'https://github.com/AlgoTraders/stock-analysis-engine/'
'issues/new \n\nFor now this error results in a shutdown'
'\n')
# if mod_path set
if verbose or debug:
log.error(err)
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
# if not found_algo_module
use_start_date = start_date
use_end_date = end_date
if not use_end_date:
end_date = datetime.datetime.utcnow()
use_end_date = end_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
if not use_start_date:
start_date = end_date - datetime.timedelta(days=75)
use_start_date = start_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
if verbose:
log.info(
f'{name} {ticker} setting default start_date={use_start_date}')
# Load an algorithm-ready dataset from:
# file, s3, or redis
if not load_config:
load_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=None,
s3_bucket=None,
s3_key=None,
redis_key=None,
compress=load_compress,
redis_enabled=publish_to_redis,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
redis_serializer=redis_serializer,
redis_encoding=redis_encoding,
s3_enabled=publish_to_s3,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
slack_enabled=publish_to_slack,
slack_code_block=slack_code_block,
slack_full_width=slack_full_width,
verbose=verbose,
label=f'load-{name}')
if load_from_file:
load_config['output_file'] = load_from_file
if load_from_redis_key:
load_config['redis_key'] = load_from_redis_key
load_config['redis_enabled'] = True
if load_from_s3_bucket and load_from_s3_key:
load_config['s3_bucket'] = load_from_s3_bucket
load_config['s3_key'] = load_from_s3_key
load_config['s3_enabled'] = True
# end of building load_config dictionary if not already set
# Automatically save all datasets to an algorithm-ready:
# file, s3, or redis
if not extract_config:
extract_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=None,
s3_bucket=None,
s3_key=None,
redis_key=None,
compress=extract_compress,
redis_enabled=publish_to_redis,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
redis_serializer=redis_serializer,
redis_encoding=redis_encoding,
s3_enabled=publish_to_s3,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
slack_enabled=publish_to_slack,
slack_code_block=slack_code_block,
slack_full_width=slack_full_width,
verbose=verbose,
label=f'extract-{name}')
should_publish_extract_dataset = False
if extract_file:
extract_config['output_file'] = extract_file
should_publish_extract_dataset = True
if extract_redis_key and publish_to_redis:
extract_config['redis_key'] = extract_redis_key
extract_config['redis_enabled'] = True
should_publish_extract_dataset = True
if extract_s3_bucket and extract_s3_key and publish_to_s3:
extract_config['s3_bucket'] = extract_s3_bucket
extract_config['s3_key'] = extract_s3_key
extract_config['s3_enabled'] = True
should_publish_extract_dataset = True
else:
extract_config['s3_enabled'] = False
# end of building extract_config dictionary if not already set
# Automatically save the trading performance report:
# file, s3, or redis
if not report_config:
report_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=None,
s3_bucket=None,
s3_key=None,
redis_key=None,
compress=report_compress,
redis_enabled=publish_to_redis,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
redis_serializer=redis_serializer,
redis_encoding=redis_encoding,
s3_enabled=publish_to_s3,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
slack_enabled=publish_to_slack,
slack_code_block=slack_code_block,
slack_full_width=slack_full_width,
verbose=verbose,
label=f'report-{name}')
should_publish_report_dataset = False
if report_file:
report_config['output_file'] = report_file
should_publish_report_dataset = True
if report_redis_key and publish_to_redis:
report_config['redis_key'] = report_redis_key
report_config['redis_enabled'] = True
should_publish_report_dataset = True
if report_s3_bucket and report_s3_key and publish_to_s3:
report_config['s3_bucket'] = report_s3_bucket
report_config['s3_key'] = report_s3_key
report_config['s3_enabled'] = True
should_publish_report_dataset = True
# end of building report_config dictionary if not already set
# Automatically save the trade history:
# file, s3, or redis
if not history_config:
history_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=None,
s3_bucket=None,
s3_key=None,
redis_key=None,
compress=report_compress,
redis_enabled=publish_to_redis,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
redis_serializer=redis_serializer,
redis_encoding=redis_encoding,
s3_enabled=publish_to_s3,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
slack_enabled=publish_to_slack,
slack_code_block=slack_code_block,
slack_full_width=slack_full_width,
verbose=verbose,
label=f'history-{name}')
should_publish_history_dataset = False
if history_file:
history_config['output_file'] = history_file
should_publish_history_dataset = True
if history_redis_key and publish_to_redis:
history_config['redis_key'] = history_redis_key
history_config['redis_enabled'] = True
should_publish_history_dataset = True
if history_s3_bucket and history_s3_key and publish_to_s3:
history_config['s3_bucket'] = history_s3_bucket
history_config['s3_key'] = history_s3_key
history_config['s3_enabled'] = True
should_publish_history_dataset = True
# end of building history_config dictionary if not already set
if verbose:
remove_vals = ['s3_access_key', 's3_secret_key', 'redis_password']
debug_extract_config = {}
for k in extract_config:
if k not in remove_vals:
debug_extract_config[k] = extract_config[k]
debug_report_config = {}
for k in report_config:
if k not in remove_vals:
debug_report_config[k] = report_config[k]
debug_history_config = {}
for k in history_config:
if k not in remove_vals:
debug_history_config[k] = history_config[k]
debug_load_config = {}
for k in load_config:
if k not in remove_vals:
debug_load_config[k] = load_config[k]
log.info(f'{name} {ticker} using extract config '
f'{ae_consts.ppj(debug_extract_config)}')
log.info(f'{name} {ticker} using report config '
f'{ae_consts.ppj(debug_report_config)}')
log.info(f'{name} {ticker} using trade history config '
f'{ae_consts.ppj(debug_history_config)}')
log.info(f'{name} {ticker} using load config '
f'{ae_consts.ppj(debug_load_config)}')
log.info(f'{name} {ticker} - building algo request')
# end of verbose
algo_req = build_algo_request.build_algo_request(
ticker=ticker,
balance=balance,
commission=commission,
start_date=use_start_date,
end_date=use_end_date,
timeseries=timeseries,
trade_strategy=trade_strategy,
config_file=use_config_file,
config_dict=use_config_dict,
load_config=load_config,
history_config=history_config,
report_config=report_config,
extract_config=extract_config,
label=name)
algo_req['name'] = name
algo_req['should_publish_extract_dataset'] = should_publish_extract_dataset
algo_req['should_publish_history_dataset'] = should_publish_history_dataset
algo_req['should_publish_report_dataset'] = should_publish_report_dataset
algo_res = build_result.build_result(status=ae_consts.NOT_RUN,
err=None,
rec=None)
if run_on_engine:
rec = {'algo_req': algo_req, 'task_id': None}
task_name = ('analysis_engine.work_tasks.'
'task_run_algo.task_run_algo')
if verbose:
log.info(f'starting distributed algo task={task_name}')
elif debug:
log.info(
'starting distributed algo by publishing to '
f'task={task_name} broker={auth_url} backend={backend_url}')
# Get the Celery app
app = get_celery_app.get_celery_app(
name=__name__,
auth_url=auth_url,
backend_url=backend_url,
path_to_config_module=path_to_config_module,
ssl_options=ssl_options,
transport_options=transport_options,
include_tasks=include_tasks)
if debug:
log.info(f'calling distributed algo task={task_name} '
f'request={ae_consts.ppj(algo_req)}')
elif verbose:
log.info(f'calling distributed algo task={task_name}')
job_id = app.send_task(task_name, (algo_req, ))
if verbose:
log.info(f'calling task={task_name} - success job_id={job_id}')
rec['task_id'] = job_id
algo_res = build_result.build_result(status=ae_consts.SUCCESS,
err=None,
rec=rec)
return algo_res
# end of run_on_engine
if use_custom_algo:
if verbose:
log.info(
f'inspecting {custom_algo_module} for class {module_name}')
use_class_member_object = None
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
if verbose:
log.info(f'start {name} with {member[1]}')
use_class_member_object = member
break
# end of looking over the class definition but did not find it
if use_class_member_object:
new_algo_object = member[1](**algo_req)
else:
err = ('did not find a derived analysis_engine.algo.BaseAlgo '
f'class in the module file={mod_path} '
f'for ticker={ticker} algo_name={name}')
if verbose or debug:
log.error(err)
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
# end of finding a valid algorithm object
else:
new_algo_object = ae_algo.BaseAlgo(**algo_req)
# if using a custom module path or the BaseAlgo
if new_algo_object:
# heads up - logging this might have passwords in the algo_req
# log.debug(
# f'{name} algorithm request: {algo_req}')
if verbose:
log.info(f'{name} - run ticker={ticker} from {use_start_date} '
f'to {use_end_date}')
algo_res = run_algo.run_algo(algo=new_algo_object,
raise_on_err=raise_on_err,
**algo_req)
algo_res['algo'] = new_algo_object
if verbose:
log.info(f'{name} - run ticker={ticker} from {use_start_date} '
f'to {use_end_date}')
if custom_algo_module:
if verbose:
log.info(f'{name} - done run_algo '
f'custom_algo_module={custom_algo_module} '
f'module_name={module_name} ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
else:
if verbose:
log.info(f'{name} - done run_algo BaseAlgo ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
else:
err = ('missing a derived analysis_engine.algo.BaseAlgo '
f'class in the module file={mod_path} for ticker={ticker} '
f'algo_name={name}')
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
# end of finding a valid algorithm object
algo = algo_res.get('algo', None)
if not algo:
err = (f'failed creating algorithm object - ticker={ticker} '
f'status={ae_consts.get_status(status=algo_res["status"])} '
f'error={algo_res["err"]} algo name={name} '
f'custom_algo_module={custom_algo_module} '
f'module_name={module_name} '
f'from {use_start_date} to {use_end_date}')
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
if should_publish_extract_dataset or dataset_publish_extract:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (extract_config['redis_address'] and extract_config['redis_db'] >= 0
and extract_config['redis_key']):
redis_log = (
f'redis://{extract_config["redis_address"]}'
f'@{extract_config["redis_db"]}/{extract_config["redis_key"]}')
use_log += f' {redis_log}'
else:
extract_config['redis_enabled'] = False
if (extract_config['s3_address'] and extract_config['s3_bucket']
and extract_config['s3_key']):
s3_log = (
f's3://{extract_config["s3_address"]}'
f'/{extract_config["s3_bucket"]}/{extract_config["s3_key"]}')
use_log += f' {s3_log}'
else:
extract_config['s3_enabled'] = False
if extract_config['output_file']:
file_log = f'file:{extract_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(f'{name} - publish - start ticker={ticker} '
f'algorithm-ready {use_log}')
publish_status = algo.publish_input_dataset(**extract_config)
if publish_status != ae_consts.SUCCESS:
msg = (
'failed to publish algorithm-ready datasets '
f'with status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
if verbose:
log.info(f'{name} - publish - done ticker={ticker} '
f'algorithm-ready {use_log}')
# if publish the algorithm-ready dataset
if should_publish_history_dataset or dataset_publish_history:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (history_config['redis_address'] and history_config['redis_db'] >= 0
and history_config['redis_key']):
redis_log = (
f'redis://{history_config["redis_address"]}'
f'@{history_config["redis_db"]}/{history_config["redis_key"]}')
use_log += f' {redis_log}'
else:
history_config['redis_enabled'] = False
if (history_config['s3_address'] and history_config['s3_bucket']
and history_config['s3_key']):
s3_log = (
f's3://{history_config["s3_address"]}'
f'/{history_config["s3_bucket"]}/{history_config["s3_key"]}')
use_log += f' {s3_log}'
else:
history_config['s3_enabled'] = False
if history_config['output_file']:
file_log = f'file:{history_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(f'{name} - publish - start ticker={ticker} trading '
f'history {use_log}')
publish_status = algo.publish_trade_history_dataset(**history_config)
if publish_status != ae_consts.SUCCESS:
msg = (
'failed to publish trading history datasets '
f'with status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
if verbose:
log.info(f'{name} - publish - done ticker={ticker} trading '
f'history {use_log}')
# if publish an trading history dataset
if should_publish_report_dataset or dataset_publish_report:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (report_config['redis_address'] and report_config['redis_db'] >= 0
and report_config['redis_key']):
redis_log = (
f'redis://{report_config["redis_address"]}'
f'@{report_config["redis_db"]}/{report_config["redis_key"]}')
use_log += f' {redis_log}'
else:
report_config['redis_enabled'] = False
if (report_config['s3_address'] and report_config['s3_bucket']
and report_config['s3_key']):
s3_log = (
f's3://{report_config["s3_address"]}'
f'/{report_config["s3_bucket"]}/{report_config["s3_key"]}')
use_log += f' {s3_log}'
else:
report_config['s3_enabled'] = False
if report_config['output_file']:
file_log = f'file:{report_config["output_file"]}'
use_log += f' {file_log}'
if verbose:
log.info(
f'{name} - publishing ticker={ticker} trading performance '
f'report {use_log}')
publish_status = algo.publish_report_dataset(**report_config)
if publish_status != ae_consts.SUCCESS:
msg = (
'failed to publish trading performance report datasets '
f'with status {ae_consts.get_status(status=publish_status)} '
f'attempted to {use_log}')
log.error(msg)
return build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
if verbose:
log.info(
f'{name} - publish - done ticker={ticker} trading performance '
f'report {use_log}')
# if publish an trading performance report dataset
if verbose:
log.info(f'{name} - done publishing datasets for ticker={ticker} '
f'from {use_start_date} to {use_end_date}')
return algo_res
def run_distributed_algorithm(self, algo_req):
"""run_distributed_algorithm
Process a distributed Algorithm
:param algo_req: dictionary for key/values for
running an algorithm using Celery workers
"""
label = algo_req.get('name', 'ae-algo')
verbose = algo_req.get('verbose', False)
debug = algo_req.get('debug', False)
# please be careful logging prod passwords:
if verbose or debug:
log.info('task - {} - start ' 'algo_req={}'.format(label, algo_req))
else:
log.info('task - {} - start '.format(label))
# end of start log
rec = {}
res = build_result.build_result(status=ae_consts.NOT_RUN,
err=None,
rec=rec)
created_algo_object = None
custom_algo_module = None
new_algo_object = None
use_custom_algo = False
found_algo_module = True # assume the BaseAlgo
should_publish_extract_dataset = False
should_publish_history_dataset = False
should_publish_report_dataset = False
ticker = algo_req.get('ticker', 'SPY')
num_days_back = algo_req.get('num_days_back', 75)
name = algo_req.get('name', 'ae-algo')
algo_module_path = algo_req.get('mod_path', None)
module_name = algo_req.get('module_name', 'BaseAlgo')
custom_algo_module = algo_req.get('custom_algo_module', None)
new_algo_object = algo_req.get('new_algo_object', None)
use_custom_algo = algo_req.get('use_custom_algo', False)
should_publish_extract_dataset = algo_req.get(
'should_publish_extract_dataset', False)
should_publish_history_dataset = algo_req.get(
'should_publish_history_dataset', False)
should_publish_report_dataset = algo_req.get(
'should_publish_report_dataset', False)
start_date = algo_req.get('start_date', None)
end_date = algo_req.get('end_date', None)
raise_on_err = algo_req.get('raise_on_err', False)
report_config = algo_req.get('report_config', None)
history_config = algo_req.get('history_config', None)
extract_config = algo_req.get('extract_config', None)
err = None
if algo_module_path:
found_algo_module = False
module_name = algo_module_path.split('/')[-1]
loader = importlib.machinery.SourceFileLoader(module_name,
algo_module_path)
custom_algo_module = types.ModuleType(loader.name)
loader.exec_module(custom_algo_module)
use_custom_algo = True
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
found_algo_module = True
break
# for all members in this custom module file
# if loading a custom algorithm module from a file on disk
if not found_algo_module:
err = ('{} - unable to find custom algorithm module={} '
'module_path={}'.format(label, custom_algo_module,
algo_module_path))
if algo_module_path:
err = (
'{} - analysis_engine.work_tasks.run_distributed_algorithm '
'was unable '
'to find custom algorithm module={} with provided path to \n '
'file: {} \n'
'\n'
'Please confirm '
'that the class inherits from the BaseAlgo class like:\n'
'\n'
'import analysis_engine.algo\n'
'class MyAlgo(analysis_engine.algo.BaseAlgo):\n '
'\n'
'If it is then please file an issue on github:\n '
'https://github.com/AlgoTraders/stock-analysis-engine/'
'issues/new \n\nFor now this error results in a shutdown'
'\n'.format(label, custom_algo_module, algo_module_path))
# if algo_module_path set
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# if not found_algo_module
use_start_date = start_date
use_end_date = end_date
if not use_end_date:
end_date = datetime.datetime.utcnow()
use_end_date = end_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
if not use_start_date:
start_date = end_date - datetime.timedelta(days=num_days_back)
use_start_date = start_date.strftime(ae_consts.COMMON_TICK_DATE_FORMAT)
dataset_publish_extract = algo_req.get('dataset_publish_extract', False)
dataset_publish_history = algo_req.get('dataset_publish_history', False)
dataset_publish_report = algo_req.get('dataset_publish_report', False)
try:
if use_custom_algo:
log.info('inspecting {} for class {}'.format(
custom_algo_module, module_name))
use_class_member_object = None
for member in inspect.getmembers(custom_algo_module):
if module_name in str(member):
log.info('start {} with {}'.format(name, member[1]))
use_class_member_object = member
break
# end of looking over the class definition but did not find it
if use_class_member_object:
new_algo_object = member[1](**algo_req)
else:
err = ('{} - did not find a derived '
'analysis_engine.algo.BaseAlgo '
'class in the module file={} '
'for ticker={} algo_name={}'.format(
label, algo_module_path, ticker, name))
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of finding a valid algorithm object
else:
new_algo_object = ae_algo.BaseAlgo(**algo_req)
# if using a custom module path or the BaseAlgo
if new_algo_object:
# heads up - logging this might have passwords in the algo_req
# log.debug(
# '{} algorithm request: {}'.format(
# name,
# algo_req))
log.info('{} - run ticker={} from {} to {}'.format(
name, ticker, use_start_date, use_end_date))
algo_res = run_algo.run_algo(algo=new_algo_object,
raise_on_err=raise_on_err,
**algo_req)
created_algo_object = new_algo_object
log.info('{} - run ticker={} from {} to {}'.format(
name, ticker, use_start_date, use_end_date))
if custom_algo_module:
log.info(
'{} - done run_algo custom_algo_module={} module_name={} '
'ticker={} from {} to {}'.format(name, custom_algo_module,
module_name, ticker,
use_start_date,
use_end_date))
else:
log.info('{} - done run_algo BaseAlgo ticker={} from {} '
'to {}'.format(name, ticker, use_start_date,
use_end_date))
else:
err = ('{} - missing a derived analysis_engine.algo.BaseAlgo '
'class in the module file={} for '
'ticker={} algo_name={}'.format(label, algo_module_path,
ticker, name))
log.error(err)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of finding a valid algorithm object
if not created_algo_object:
err = ('{} - failed creating algorithm object - '
'ticker={} status={} error={}'
'algo name={} custom_algo_module={} module_name={} '
'from {} to {}'.format(
label, ticker,
ae_consts.get_status(status=algo_res['status']),
algo_res['err'], name, custom_algo_module, module_name,
use_start_date, use_end_date))
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of stop early
if should_publish_extract_dataset or dataset_publish_extract:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (extract_config['redis_address'] and extract_config['redis_db']
and extract_config['redis_key']):
redis_log = 'redis://{}@{}/{}'.format(
extract_config['redis_address'],
extract_config['redis_db'], extract_config['redis_key'])
use_log += ' {}'.format(redis_log)
else:
extract_config['redis_enabled'] = False
if (extract_config['s3_address'] and extract_config['s3_bucket']
and extract_config['s3_key']):
s3_log = 's3://{}/{}/{}'.format(extract_config['s3_address'],
extract_config['s3_bucket'],
extract_config['s3_key'])
use_log += ' {}'.format(s3_log)
else:
extract_config['s3_enabled'] = False
if extract_config['output_file']:
file_log = 'file:{}'.format(extract_config['output_file'])
use_log += ' {}'.format(file_log)
log.info('{} - publish - start ticker={} algorithm-ready {}'
''.format(name, ticker, use_log))
publish_status = created_algo_object.publish_input_dataset(
**extract_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish algorithm-ready datasets '
'with status {} attempted to {}'.format(
ae_consts.get_status(status=publish_status),
use_log))
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of stop early
log.info('{} - publish - done ticker={} algorithm-ready {}'
''.format(name, ticker, use_log))
# if publish the algorithm-ready dataset
if should_publish_history_dataset or dataset_publish_history:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (history_config['redis_address'] and history_config['redis_db']
and history_config['redis_key']):
redis_log = 'redis://{}@{}/{}'.format(
history_config['redis_address'],
history_config['redis_db'], history_config['redis_key'])
use_log += ' {}'.format(redis_log)
if (history_config['s3_address'] and history_config['s3_bucket']
and history_config['s3_key']):
s3_log = 's3://{}/{}/{}'.format(history_config['s3_address'],
history_config['s3_bucket'],
history_config['s3_key'])
use_log += ' {}'.format(s3_log)
if history_config['output_file']:
file_log = 'file:{}'.format(history_config['output_file'])
use_log += ' {}'.format(file_log)
log.info('{} - publish - start ticker={} trading history {}'
''.format(name, ticker, use_log))
publish_status = \
created_algo_object.publish_trade_history_dataset(
**history_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish trading history datasets '
'with status {} attempted to {}'.format(
ae_consts.get_status(status=publish_status),
use_log))
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of stop early
log.info('{} - publish - done ticker={} trading history {}'
''.format(name, ticker, use_log))
# if publish an trading history dataset
if should_publish_report_dataset or dataset_publish_report:
s3_log = ''
redis_log = ''
file_log = ''
use_log = 'publish'
if (report_config['redis_address'] and report_config['redis_db']
and report_config['redis_key']):
redis_log = 'redis://{}@{}/{}'.format(
report_config['redis_address'], report_config['redis_db'],
report_config['redis_key'])
use_log += ' {}'.format(redis_log)
if (report_config['s3_address'] and report_config['s3_bucket']
and report_config['s3_key']):
s3_log = 's3://{}/{}/{}'.format(report_config['s3_address'],
report_config['s3_bucket'],
report_config['s3_key'])
use_log += ' {}'.format(s3_log)
if report_config['output_file']:
file_log = ' file:{}'.format(report_config['output_file'])
use_log += ' {}'.format(file_log)
log.info('{} - publishing ticker={} trading performance report {}'
''.format(name, ticker, use_log))
publish_status = created_algo_object.publish_report_dataset(
**report_config)
if publish_status != ae_consts.SUCCESS:
msg = ('failed to publish trading performance report datasets '
'with status {} attempted to {}'.format(
ae_consts.get_status(status=publish_status),
use_log))
log.error(msg)
res = build_result.build_result(status=ae_consts.ERR,
err=err,
rec=None)
return get_task_results.get_task_results(work_dict=algo_req,
result=res)
# end of stop early
log.info(
'{} - publish - done ticker={} trading performance report {}'
''.format(name, ticker, use_log))
# if publish an trading performance report dataset
log.info(
'{} - done publishing datasets for ticker={} from {} to {}'.format(
name, ticker, use_start_date, use_end_date))
res = build_result.build_result(status=ae_consts.SUCCESS,
err=None,
rec=rec)
except Exception as e:
res = build_result.build_result(
status=ae_consts.ERR,
err=('failed - run_distributed_algorithm '
'dict={} with ex={}').format(algo_req, e),
rec=rec)
log.error('{} - {}'.format(label, res['err']))
# end of try/ex
log.info('task - run_distributed_algorithm done - '
'{} - status={}'.format(label,
ae_consts.get_status(res['status'])))
return get_task_results.get_task_results(work_dict=algo_req, result=res)
def run_backtest_and_plot_history(config_dict):
"""run_backtest_and_plot_history
Run a derived algorithm with an algorithm config dictionary
:param config_dict: algorithm config dictionary
"""
log.debug('start - sa')
parser = argparse.ArgumentParser(description=('stock analysis tool'))
parser.add_argument('-t', help=('ticker'), required=False, dest='ticker')
parser.add_argument('-e',
help=('file path to extract an '
'algorithm-ready datasets from redis'),
required=False,
dest='algo_extract_loc')
parser.add_argument('-l',
help=('show dataset in this file'),
required=False,
dest='show_from_file')
parser.add_argument('-H',
help=('show trading history dataset in this file'),
required=False,
dest='show_history_from_file')
parser.add_argument(
'-E',
help=('show trading performance report dataset in this file'),
required=False,
dest='show_report_from_file')
parser.add_argument(
'-L',
help=('restore an algorithm-ready dataset file back into redis'),
required=False,
dest='restore_algo_file')
parser.add_argument('-f',
help=('save the trading history dataframe '
'to this file'),
required=False,
dest='history_json_file')
parser.add_argument(
'-J',
help=('plot action - after preparing you can use: '
'-J show to open the image (good for debugging)'),
required=False,
dest='plot_action')
parser.add_argument(
'-b',
help=('run a backtest using the dataset in '
'a file path/s3 key/redis key formats: '
'file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
's3://algoready/SPY-latest.json or '
'redis:SPY-latest'),
required=False,
dest='backtest_loc')
parser.add_argument('-B',
help=('optional - broker url for Celery'),
required=False,
dest='broker_url')
parser.add_argument('-C',
help=('optional - broker url for Celery'),
required=False,
dest='backend_url')
parser.add_argument(
'-w',
help=('optional - flag for publishing an algorithm job '
'using Celery to the analysis_engine workers'),
required=False,
dest='run_on_engine',
action='store_true')
parser.add_argument('-k',
help=('optional - s3 access key'),
required=False,
dest='s3_access_key')
parser.add_argument('-K',
help=('optional - s3 secret key'),
required=False,
dest='s3_secret_key')
parser.add_argument('-a',
help=('optional - s3 address format: <host:port>'),
required=False,
dest='s3_address')
parser.add_argument('-Z',
help=('optional - s3 secure: default False'),
required=False,
dest='s3_secure')
parser.add_argument('-s',
help=('optional - start date: YYYY-MM-DD'),
required=False,
dest='start_date')
parser.add_argument('-n',
help=('optional - end date: YYYY-MM-DD'),
required=False,
dest='end_date')
parser.add_argument('-u',
help=('optional - s3 bucket name'),
required=False,
dest='s3_bucket_name')
parser.add_argument('-G',
help=('optional - s3 region name'),
required=False,
dest='s3_region_name')
parser.add_argument('-g',
help=('Path to a custom algorithm module file '
'on disk. This module must have a single '
'class that inherits from: '
'https://github.com/AlgoTraders/stock-ana'
'lysis-engine/blob/master/'
'analysis_engine/algo.py Additionally you '
'can find the Example-Minute-Algorithm here: '
'https://github.com/AlgoTraders/stock-anal'
'ysis-engine/blob/master/analysis_engine/mocks/'
'example_algo_minute.py'),
required=False,
dest='run_algo_in_file')
parser.add_argument('-p',
help=('optional - s3 bucket/file for trading history'),
required=False,
dest='algo_history_loc')
parser.add_argument(
'-o',
help=('optional - s3 bucket/file for trading performance report'),
required=False,
dest='algo_report_loc')
parser.add_argument('-r',
help=('optional - redis_address format: <host:port>'),
required=False,
dest='redis_address')
parser.add_argument('-R',
help=('optional - redis and s3 key name'),
required=False,
dest='keyname')
parser.add_argument(
'-m',
help=('optional - redis database number (0 by default)'),
required=False,
dest='redis_db')
parser.add_argument('-x',
help=('optional - redis expiration in seconds'),
required=False,
dest='redis_expire')
parser.add_argument(
'-c',
help=('optional - algorithm config_file path for setting '
'up internal algorithm trading strategies and '
'indicators'),
required=False,
dest='config_file')
parser.add_argument('-v',
help=('set the Algorithm to verbose logging'),
required=False,
dest='verbose_algo',
action='store_true')
parser.add_argument(
'-P',
help=('set the Algorithm\'s IndicatorProcessor to verbose logging'),
required=False,
dest='verbose_processor',
action='store_true')
parser.add_argument(
'-I',
help=('set all Algorithm\'s Indicators to verbose logging '
'(note indivdual indicators support a \'verbose\' key '
'that can be set to True to debug just one '
'indicator)'),
required=False,
dest='verbose_indicators',
action='store_true')
parser.add_argument(
'-V',
help=('inspect the datasets an algorithm is processing - this'
'will slow down processing to show debugging'),
required=False,
dest='inspect_datasets',
action='store_true')
parser.add_argument(
'-j',
help=('run the algorithm on just this specific date in the datasets '
'- specify the date in a format: YYYY-MM-DD like: 2018-11-29'),
required=False,
dest='run_this_date')
parser.add_argument('-d',
help=('debug'),
required=False,
dest='debug',
action='store_true')
args = parser.parse_args()
ticker = None
use_balance = 10000.0
use_commission = 6.0
use_start_date = None
use_end_date = None
use_config_file = None
debug = False
verbose_algo = None
verbose_processor = None
verbose_indicators = None
inspect_datasets = None
history_json_file = None
run_this_date = None
algo_obj = None
algo_history_loc = 's3://algohistory'
algo_report_loc = 's3://algoreport'
algo_extract_loc = 's3://algoready'
backtest_loc = None
ssl_options = ae_consts.SSL_OPTIONS
transport_options = ae_consts.TRANSPORT_OPTIONS
broker_url = ae_consts.WORKER_BROKER_URL
backend_url = ae_consts.WORKER_BACKEND_URL
path_to_config_module = ae_consts.WORKER_CELERY_CONFIG_MODULE
include_tasks = ae_consts.INCLUDE_TASKS
load_from_s3_bucket = None
load_from_s3_key = None
load_from_redis_key = None
load_from_file = None
load_compress = False
load_publish = True
load_config = None
report_redis_key = None
report_s3_bucket = None
report_s3_key = None
report_file = None
report_compress = False
report_publish = True
report_config = None
history_redis_key = None
history_s3_bucket = None
history_s3_key = None
history_file = None
history_compress = False
history_publish = True
history_config = None
extract_redis_key = None
extract_s3_bucket = None
extract_s3_key = None
extract_file = None
extract_save_dir = None
extract_compress = False
extract_publish = True
extract_config = None
s3_enabled = True
s3_access_key = ae_consts.S3_ACCESS_KEY
s3_secret_key = ae_consts.S3_SECRET_KEY
s3_region_name = ae_consts.S3_REGION_NAME
s3_address = ae_consts.S3_ADDRESS
s3_bucket_name = ae_consts.S3_BUCKET
s3_key = None
s3_secure = ae_consts.S3_SECURE
redis_enabled = True
redis_address = ae_consts.REDIS_ADDRESS
redis_key = None
redis_password = ae_consts.REDIS_PASSWORD
redis_db = ae_consts.REDIS_DB
redis_expire = ae_consts.REDIS_EXPIRE
redis_serializer = 'json'
redis_encoding = 'utf-8'
publish_to_s3 = True
publish_to_redis = True
publish_to_slack = True
slack_enabled = False
slack_code_block = False
slack_full_width = False
dataset_type = ae_consts.SA_DATASET_TYPE_ALGO_READY
serialize_datasets = ae_consts.DEFAULT_SERIALIZED_DATASETS
compress = False
encoding = 'utf-8'
debug = False
run_on_engine = False
auto_fill = True
timeseries = 'minute'
trade_strategy = 'count'
if args.s3_access_key:
s3_access_key = args.s3_access_key
if args.s3_secret_key:
s3_secret_key = args.s3_secret_key
if args.s3_region_name:
s3_region_name = args.s3_region_name
if args.s3_address:
s3_address = args.s3_address
if args.s3_secure:
s3_secure = args.s3_secure
if args.redis_address:
redis_address = args.redis_address
if args.redis_db:
redis_db = args.redis_db
if args.redis_expire:
redis_expire = args.redis_expire
if args.history_json_file:
history_json_file = args.history_json_file
if args.ticker:
ticker = args.ticker.upper()
if args.debug:
debug = True
if args.verbose_algo:
verbose_algo = True
if args.verbose_processor:
verbose_processor = True
if args.verbose_indicators:
verbose_indicators = True
if args.inspect_datasets:
inspect_datasets = True
if args.run_this_date:
run_this_date = args.run_this_date
if args.start_date:
try:
use_start_date = '{} 00:00:00'.format(str(args.start_date))
datetime.datetime.strptime(args.start_date,
ae_consts.COMMON_DATE_FORMAT)
except Exception as e:
msg = ('please use a start date formatted as: {}'
'\n'
'error was: {}'.format(ae_consts.COMMON_DATE_FORMAT, e))
log.error(msg)
sys.exit(1)
# end of testing for a valid date
# end of args.start_date
if args.end_date:
try:
use_end_date = '{} 00:00:00'.format(str(args.end_date))
datetime.datetime.strptime(args.end_date,
ae_consts.COMMON_DATE_FORMAT)
except Exception as e:
msg = ('please use an end date formatted as: {}'
'\n'
'error was: {}'.format(ae_consts.COMMON_DATE_FORMAT, e))
log.error(msg)
sys.exit(1)
# end of testing for a valid date
# end of args.end_date
algo_mod_path = None
if args.run_algo_in_file:
if not os.path.exists(args.run_algo_in_file):
log.error('missing algorithm module file: {}'.format(
args.run_algo_in_file))
sys.exit(1)
algo_mod_path = args.run_algo_in_file
if args.config_file:
use_config_file = args.config_file
if not os.path.exists(use_config_file):
log.error('Failed: unable to find config file: -c {}'.format(
use_config_file))
sys.exit(1)
config_dict = json.loads(open(use_config_file).read())
algo_mod_path = config_dict.get('algo_path', algo_mod_path)
if not os.path.exists(algo_mod_path):
log.error('missing algorithm module file from config: {}'.format(
algo_mod_path))
sys.exit(1)
"""
Finalize the algo config
"""
if config_dict:
use_balance = float(config_dict.get('balance', use_balance))
use_commission = float(config_dict.get('commission', use_commission))
ticker = str(config_dict.get('ticker', ticker)).upper()
config_dict['ticker'] = ticker
config_dict['balance'] = use_balance
config_dict['commission'] = use_commission
else:
if not ticker:
ticker = str(config_dict.get('ticker', ae_consts.TICKER)).upper()
if not ticker:
log.error('usage error: please set a ticker with -t <TICKER>')
sys.exit(1)
if verbose_algo:
config_dict['verbose'] = verbose_algo
if verbose_processor:
config_dict['verbose_processor'] = verbose_processor
if verbose_indicators:
config_dict['verbose_indicators'] = verbose_indicators
if inspect_datasets:
config_dict['inspect_datasets'] = inspect_datasets
if run_this_date:
config_dict['run_this_date'] = run_this_date
"""
Run a custom algo module from disk
"""
if algo_mod_path:
if args.backtest_loc:
backtest_loc = args.backtest_loc
if ('file:/' not in backtest_loc and 's3://' not in backtest_loc
and 'redis://' not in backtest_loc):
log.error(
'invalid -b <backtest dataset file> specified. '
'{} '
'please use either: '
'-b file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-b s3://algoready/SPY-latest.json or '
'-b redis://SPY-latest'.format(backtest_loc))
sys.exit(1)
if 's3://' in backtest_loc:
load_from_s3_bucket = backtest_loc.split('/')[-2]
load_from_s3_key = backtest_loc.split('/')[-1]
elif 'redis://' in backtest_loc:
load_from_redis_key = backtest_loc.split('/')[-1]
elif 'file:/' in backtest_loc:
load_from_file = backtest_loc.split(':')[-1]
load_publish = True
# end of parsing supported transport - loading an algo-ready
if args.algo_history_loc:
algo_history_loc = args.algo_history_loc
if ('file:/' not in algo_history_loc
and 's3://' not in algo_history_loc
and 'redis://' not in algo_history_loc):
log.error(
'invalid -b <backtest dataset file> specified. '
'{} '
'please use either: '
'-p file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-p s3://algoready/SPY-latest.json or '
'-p redis://SPY-latest'.format(algo_history_loc))
sys.exit(1)
if 's3://' in algo_history_loc:
history_s3_bucket = algo_history_loc.split('/')[-2]
history_s3_key = algo_history_loc.split('/')[-1]
elif 'redis://' in algo_history_loc:
history_redis_key = algo_history_loc.split('/')[-1]
elif 'file:/' in algo_history_loc:
history_file = algo_history_loc.split(':')[-1]
history_publish = True
# end of parsing supported transport - trading history
if args.algo_report_loc:
algo_report_loc = args.algo_report_loc
if ('file:/' not in algo_report_loc
and 's3://' not in algo_report_loc
and 'redis://' not in algo_report_loc):
log.error(
'invalid -b <backtest dataset file> specified. '
'{} '
'please use either: '
'-o file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-o s3://algoready/SPY-latest.json or '
'-o redis://SPY-latest'.format(algo_report_loc))
sys.exit(1)
if 's3://' in algo_report_loc:
report_s3_bucket = algo_report_loc.split('/')[-2]
report_s3_key = algo_report_loc.split('/')[-1]
elif 'redis://' in algo_report_loc:
report_redis_key = algo_report_loc.split('/')[-1]
elif 'file:/' in algo_report_loc:
report_file = algo_report_loc.split(':')[-1]
report_publish = True
# end of parsing supported transport - trading performance report
if args.algo_extract_loc:
algo_extract_loc = args.algo_extract_loc
if ('file:/' not in algo_extract_loc
and 's3://' not in algo_extract_loc
and 'redis://' not in algo_extract_loc):
log.error(
'invalid -b <backtest dataset file> specified. '
'{} '
'please use either: '
'-e file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-e s3://algoready/SPY-latest.json or '
'-e redis://SPY-latest'.format(algo_extract_loc))
sys.exit(1)
if 's3://' in algo_extract_loc:
extract_s3_bucket = algo_extract_loc.split('/')[-2]
extract_s3_key = algo_extract_loc.split('/')[-1]
elif 'redis://' in algo_extract_loc:
extract_redis_key = algo_extract_loc.split('/')[-1]
elif 'file:/' in algo_extract_loc:
extract_file = algo_extract_loc.split(':')[-1]
extract_publish = True
# end of parsing supported transport - extract algorithm-ready
if args.run_on_engine:
run_on_engine = True
if verbose_algo:
log.info('starting algo on the engine')
use_name = config_dict.get('name', 'missing-algo-name')
auto_fill = config_dict.get('auto_fill', auto_fill)
timeseries = config_dict.get('timeseries', timeseries)
trade_strategy = config_dict.get('trade_strategy', trade_strategy)
algo_res = run_custom_algo.run_custom_algo(
mod_path=algo_mod_path,
ticker=config_dict['ticker'],
balance=config_dict['balance'],
commission=config_dict['commission'],
name=use_name,
start_date=use_start_date,
end_date=use_end_date,
auto_fill=auto_fill,
config_dict=config_dict,
load_from_s3_bucket=load_from_s3_bucket,
load_from_s3_key=load_from_s3_key,
load_from_redis_key=load_from_redis_key,
load_from_file=load_from_file,
load_compress=load_compress,
load_publish=load_publish,
load_config=load_config,
report_redis_key=report_redis_key,
report_s3_bucket=report_s3_bucket,
report_s3_key=report_s3_key,
report_file=report_file,
report_compress=report_compress,
report_publish=report_publish,
report_config=report_config,
history_redis_key=history_redis_key,
history_s3_bucket=history_s3_bucket,
history_s3_key=history_s3_key,
history_file=history_file,
history_compress=history_compress,
history_publish=history_publish,
history_config=history_config,
extract_redis_key=extract_redis_key,
extract_s3_bucket=extract_s3_bucket,
extract_s3_key=extract_s3_key,
extract_file=extract_file,
extract_save_dir=extract_save_dir,
extract_compress=extract_compress,
extract_publish=extract_publish,
extract_config=extract_config,
publish_to_slack=publish_to_slack,
publish_to_s3=publish_to_s3,
publish_to_redis=publish_to_redis,
dataset_type=dataset_type,
serialize_datasets=serialize_datasets,
compress=compress,
encoding=encoding,
redis_enabled=redis_enabled,
redis_key=redis_key,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
redis_serializer=redis_serializer,
redis_encoding=redis_encoding,
s3_enabled=s3_enabled,
s3_key=s3_key,
s3_address=s3_address,
s3_bucket=s3_bucket_name,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
slack_enabled=slack_enabled,
slack_code_block=slack_code_block,
slack_full_width=slack_full_width,
dataset_publish_extract=extract_publish,
dataset_publish_history=history_publish,
dataset_publish_report=report_publish,
run_on_engine=run_on_engine,
auth_url=broker_url,
backend_url=backend_url,
include_tasks=include_tasks,
ssl_options=ssl_options,
transport_options=transport_options,
path_to_config_module=path_to_config_module,
timeseries=timeseries,
trade_strategy=trade_strategy,
verbose=verbose_algo)
show_label = 'algo.name={}'.format(use_name)
show_extract = '{}'.format(algo_extract_loc)
show_history = '{}'.format(algo_history_loc)
show_report = '{}'.format(algo_report_loc)
base_label = ('load={} '
'extract={} '
'history={} '
'report={}'.format(args.run_algo_in_file, show_extract,
show_history, show_report))
algo_obj = algo_res.get('algo', None)
if not algo_obj:
log.error(
'{} - failed creating algorithm object'.format(show_label))
sys.exit(1)
if not run_on_engine:
algo_trade_history_recs = algo_res['rec'].get('history', [])
show_label = ('{} algo.name={} {} trade_history_len={}'.format(
ticker, use_name, base_label, len(algo_trade_history_recs)))
if args.debug:
log.info('algo_res={}'.format(algo_res))
if algo_res['status'] == ae_consts.SUCCESS:
log.info('{} - done running {}'.format(
ae_consts.get_status(status=algo_res['status']),
show_label))
else:
log.error('{} - done running {}'.format(
ae_consts.get_status(status=algo_res['status']),
show_label))
else:
if algo_res['status'] == ae_consts.SUCCESS:
log.info('{} - done running {}'.format(
ae_consts.get_status(status=algo_res['status']),
show_label))
else:
log.error('run_custom_algo returned error: {}'.format(
algo_res['err']))
sys.exit(1)
# end of running the custom algo handler
# end if running a custom algorithm module
else:
if args.backtest_loc:
backtest_loc = args.backtest_loc
if ('file:/' not in backtest_loc and 's3://' not in backtest_loc
and 'redis://' not in backtest_loc):
log.error(
'invalid -b <backtest dataset file> specified. '
'{} '
'please use either: '
'-b file:/opt/sa/tests/datasets/algo/SPY-latest.json or '
'-b s3://algoready/SPY-latest.json or '
'-b redis://SPY-latest'.format(backtest_loc))
sys.exit(1)
load_from_s3_bucket = None
load_from_s3_key = None
load_from_redis_key = None
load_from_file = None
if 's3://' in backtest_loc:
load_from_s3_bucket = backtest_loc.split('/')[-2]
load_from_s3_key = backtest_loc.split('/')[-1]
elif 'redis://' in backtest_loc:
load_from_redis_key = backtest_loc.split('/')[-1]
elif 'file:/' in backtest_loc:
load_from_file = backtest_loc.split(':')[-1]
# end of parsing supported transport - loading an algo-ready
# end of backtest_loc
load_config = build_publish_request.build_publish_request(
ticker=ticker,
output_file=load_from_file,
s3_bucket=load_from_s3_bucket,
s3_key=load_from_s3_key,
redis_key=load_from_redis_key,
redis_address=redis_address,
redis_db=redis_db,
redis_password=redis_password,
redis_expire=redis_expire,
s3_address=s3_address,
s3_access_key=s3_access_key,
s3_secret_key=s3_secret_key,
s3_region_name=s3_region_name,
s3_secure=s3_secure,
verbose=debug,
label='load-{}'.format(backtest_loc))
if load_from_file:
load_config['output_file'] = load_from_file
if load_from_redis_key:
load_config['redis_key'] = load_from_redis_key
load_config['redis_enabled'] = True
if load_from_s3_bucket and load_from_s3_key:
load_config['s3_bucket'] = load_from_s3_bucket
load_config['s3_key'] = load_from_s3_key
load_config['s3_enabled'] = True
log.info('starting algo')
algo_obj = ExampleCustomAlgo(ticker=config_dict['ticker'],
config_dict=config_dict)
algo_res = run_algo.run_algo(ticker=ticker,
algo=algo_obj,
start_date=use_start_date,
end_date=use_end_date,
raise_on_err=True)
if algo_res['status'] != ae_consts.SUCCESS:
log.error('failed running algo backtest '
'{} hit status: {} error: {}'.format(
algo_obj.get_name(),
ae_consts.get_status(status=algo_res['status']),
algo_res['err']))
return
# if not successful
log.info('backtest: {} {}'.format(
algo_obj.get_name(),
ae_consts.get_status(status=algo_res['status'])))
# end of use custom algo or not
if algo_obj:
trading_history_dict = algo_obj.get_history_dataset()
history_df = trading_history_dict[ticker]
if not hasattr(history_df, 'to_json'):
return
if history_json_file:
log.info('saving history to: {}'.format(history_json_file))
history_df.to_json(history_json_file,
orient='records',
date_format='iso')
log.info('plotting history')
first_date = history_df['date'].iloc[0]
end_date = history_df['date'].iloc[-1]
title = ('Trading History {} for Algo {}\n'
'Backtest dates from {} to {}'.format(
ticker, trading_history_dict['algo_name'], first_date,
end_date))
use_xcol = 'date'
use_as_date_format = '%d\n%b'
if config_dict['timeseries'] == 'minute':
use_xcol = 'minute'
use_as_date_format = '%d %H:%M:%S\n%b'
xlabel = 'Dates vs {} values'.format(trading_history_dict['algo_name'])
ylabel = 'Algo {}\nvalues'.format(trading_history_dict['algo_name'])
df_filter = (history_df['close'] > 0.01)
# set default hloc columns:
blue = None
green = None
orange = None
red = 'close'
blue = 'balance'
if debug:
for i, r in history_df.iterrows():
log.debug('{} - {}'.format(r['minute'], r['close']))
plot_trading_history.plot_trading_history(
title=title,
df=history_df,
red=red,
blue=blue,
green=green,
orange=orange,
date_col=use_xcol,
date_format=use_as_date_format,
xlabel=xlabel,
ylabel=ylabel,
df_filter=df_filter,
show_plot=True,
dropna_for_all=True)