mirror of
https://github.com/wassname/catalyst.git
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fredfortier
143 lines
3.8 KiB
Python
143 lines
3.8 KiB
Python
import os
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import tempfile
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import pandas as pd
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import six
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from catalyst.assets._assets import TradingPair, get_calendar
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from logbook import Logger
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from pandas.util.testing import assert_frame_equal
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from catalyst.constants import LOG_LEVEL
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from catalyst.exchange.asset_finder_exchange import AssetFinderExchange
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from catalyst.exchange.exchange_data_portal import DataPortalExchangeBacktest
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from catalyst.exchange.factory import get_exchanges
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from catalyst.utils.paths import ensure_directory
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log = Logger('Validator', level=LOG_LEVEL)
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def output_df(df, assets, name=None):
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"""
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Outputs a price DataFrame to a temp folder.
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Parameters
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----------
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df: pd.DataFrame
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assets
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name
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Returns
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-------
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"""
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if isinstance(assets, TradingPair):
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exchange_folder = assets.exchange
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asset_folder = assets.symbol
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else:
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exchange_folder = ','.join([asset.exchange for asset in assets])
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asset_folder = ','.join([asset.symbol for asset in assets])
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folder = os.path.join(
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tempfile.gettempdir(), 'catalyst', exchange_folder, asset_folder
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)
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ensure_directory(folder)
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if name is None:
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name = 'output'
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path = os.path.join(folder, '{}.csv'.format(name))
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df.to_csv(path)
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return path
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class Validator(object):
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def __init__(self, data_portal):
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self.data_portal = data_portal
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def compare_bundle_with_exchange(self, exchange, assets, end_dt, bar_count,
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sample_minutes):
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"""
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Creates DataFrames from the bundle and exchange for the specified
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data set.
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Parameters
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----------
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exchange: Exchange
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assets
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end_dt
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bar_count
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sample_minutes
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Returns
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-------
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"""
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freq = '{}T'.format(sample_minutes)
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log.info('creating data sample from bundle')
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df1 = self.data_portal.get_history_window(
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assets=assets,
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end_dt=end_dt,
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bar_count=bar_count,
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frequency=freq,
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field='close',
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data_frequency='minute'
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)
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path = output_df(df1, assets, '{}_resampled'.format(freq))
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log.info('saved resampled bundle candles: {}\n{}'.format(
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path, df1.tail(10))
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)
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log.info('creating data sample from exchange api')
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candles = exchange.get_candles(
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end_dt=end_dt,
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freq='{}T'.format(sample_minutes),
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assets=assets,
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bar_count=bar_count
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)
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series = dict()
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for asset in assets:
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series[asset] = pd.Series(
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data=[candle['close'] for candle in candles[asset]],
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index=[candle['last_traded'] for candle in candles[asset]]
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)
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df2 = pd.DataFrame(series)
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path = output_df(df2, assets, '{}_api'.format(freq))
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log.info('saved exchange api candles: {}\n{}'.format(
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path, df2.tail(10))
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)
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try:
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assert_frame_equal(df1, df2)
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return True
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except:
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log.warn('differences found in dataframes')
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return False
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if __name__ == '__main__':
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exchanges = get_exchanges(['poloniex'])
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exchange = six.next(six.itervalues(exchanges))
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assets = exchange.get_assets(symbols=['eth_btc'])
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open_calendar = get_calendar('OPEN')
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asset_finder = AssetFinderExchange()
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data_portal = DataPortalExchangeBacktest(
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exchanges=exchanges,
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asset_finder=asset_finder,
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trading_calendar=open_calendar,
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first_trading_day=None # will set dynamically based on assets
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)
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validator = Validator(data_portal=data_portal)
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validator.compare_bundle_with_exchange(
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exchange=exchange,
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assets=assets,
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end_dt=pd.to_datetime('2017-11-10 1:00', utc=True),
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bar_count=200,
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sample_minutes=30
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)
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