mirror of
https://github.com/wassname/options_backtester.git
synced 2026-06-27 20:05:56 +08:00
Catalina Syddall
91 lines
3.0 KiB
Python
91 lines
3.0 KiB
Python
import logging
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import hashlib
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import pandas as pd
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import pandas_market_calendars as mcal
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from . import cboe
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from .notifications import slack_notification
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logger = logging.getLogger(__name__)
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def file_hash_matches_data(file_path, data):
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file_hash = file_md5(file_path)
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data_md5 = hashlib.md5(data.encode()).hexdigest()
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return file_hash == data_md5
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def file_md5(file, chunk_size=4096):
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md5 = hashlib.md5()
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with open(file, "rb") as f:
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for chunk in iter(lambda: f.read(chunk_size), b""):
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md5.update(chunk)
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return md5.hexdigest()
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def validate_dates_in_month(symbol, date_range):
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"""Compares `date_range` (month) with NYSE trading calendar.
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Returns `True` if there are no missing days.
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"""
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# NYSE and CBOE have the same trading calendar
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# https://www.nyse.com/markets/hours-calendars
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# http://cfe.cboe.com/about-cfe/holiday-calendar
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nyse = mcal.get_calendar("NYSE")
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first_date = date_range[0]
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period = pd.Period(year=first_date.year, month=first_date.month, freq="M")
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trading_days = nyse.valid_days(start_date=period.start_time,
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end_date=period.end_time)
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# Remove timezone info
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trading_days = trading_days.tz_convert(tz=None)
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missing_days = trading_days.difference(date_range)
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if not missing_days.empty:
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logger.error("Error validating monthly dates. Missing: %s",
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missing_days)
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return missing_days.empty
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def validate_historical_dates(symbol, date_range):
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"""Compares `date_range` (any time range) with trading calendar.
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Returns `True` if there are no missing days.
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"""
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nyse = mcal.get_calendar("NYSE")
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start_date = date_range.min()
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end_date = date_range.max()
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trading_days = nyse.valid_days(start_date=start_date, end_date=end_date)
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# Remove timezone info
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trading_days = trading_days.tz_convert(tz=None)
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date_range = date_range.dt.tz_convert(tz=None)
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missing_days = trading_days.difference(date_range)
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if not missing_days.empty:
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logger.error("Error validating historical dates. Missing: %s",
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missing_days)
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return missing_days.empty
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def validate_columns(expected, received):
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"""Verify that the `received` columns scraped are equal to `expected`"""
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expected = sorted(expected)
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received = sorted(received)
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valid = expected == received
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if not valid:
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expected_cols = ", ".join(expected)
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received_cols = ", ".join(received)
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msg = """Columns expected differ from those received.
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Expected: {}
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Received: {}""".format(expected_cols, received_cols)
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logger.error(msg)
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slack_notification(msg, __name__)
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return valid
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def validate_aggregate_file(aggregate_file, daily_files):
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"""Compares `aggregate_file` with the data from `daily_files`."""
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aggregate_df = pd.read_csv(aggregate_file)
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recreated_df = cboe.concatenate_files(daily_files)
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return aggregate_df.equals(recreated_df) |