Exemple #1
0
    def test_ingest_candles(self):
        exchange_name = 'bitfinex'
        data_frequency = 'minute'

        exchange = get_exchange(exchange_name)
        bundle = ExchangeBundle(exchange)
        assets = [exchange.get_asset('iot_btc')]

        end_dt = pd.to_datetime('2017-10-20', utc=True)
        bar_count = 100

        start_dt = get_start_dt(end_dt, bar_count, data_frequency)
        candles = exchange.get_candles(
            assets=assets,
            start_dt=start_dt,
            end_dt=end_dt,
            bar_count=bar_count,
            freq='1T'
        )

        writer = bundle.get_writer(start_dt, end_dt, data_frequency)
        for asset in assets:
            dates = [candle['last_traded'] for candle in candles[asset]]

            values = dict()
            for field in ['open', 'high', 'low', 'close', 'volume']:
                values[field] = [candle[field] for candle in candles[asset]]

            periods = bundle.get_calendar_periods_range(
                start_dt, end_dt, data_frequency
            )
            df = pd.DataFrame(values, index=dates)
            df = df.loc[periods].fillna(method='ffill')

            # TODO: why do I get an extra bar?
            bundle.ingest_df(
                ohlcv_df=df,
                data_frequency=data_frequency,
                asset=asset,
                writer=writer,
                empty_rows_behavior='raise',
                duplicates_behavior='raise'
            )

        bundle_series = bundle.get_history_window_series(
            assets=assets,
            end_dt=end_dt,
            bar_count=bar_count,
            field='close',
            data_frequency=data_frequency,
            reset_reader=True
        )
        df = pd.DataFrame(bundle_series)
        print('\n' + df_to_string(df))
        pass
Exemple #2
0
    def test_validate_data(self):
        exchange_name = 'bitfinex'
        data_frequency = 'minute'

        exchange = get_exchange(exchange_name)
        exchange_bundle = ExchangeBundle(exchange)
        assets = [exchange.get_asset('iot_btc')]

        end_dt = pd.to_datetime('2017-9-2 1:00', utc=True)
        bar_count = 60

        bundle_series = exchange_bundle.get_history_window_series(
            assets=assets,
            end_dt=end_dt,
            bar_count=bar_count * 5,
            field='close',
            data_frequency='minute',
        )
        candles = exchange.get_candles(
            assets=assets,
            end_dt=end_dt,
            bar_count=bar_count,
            data_frequency='minute'
        )
        start_dt = get_start_dt(end_dt, bar_count, data_frequency)

        frames = []
        for asset in assets:
            bundle_df = pd.DataFrame(
                data=dict(bundle_price=bundle_series[asset]),
                index=bundle_series[asset].index
            )
            exchange_series = exchange.get_series_from_candles(
                candles=candles[asset],
                start_dt=start_dt,
                end_dt=end_dt,
                data_frequency=data_frequency,
                field='close'
            )
            exchange_df = pd.DataFrame(
                data=dict(exchange_price=exchange_series),
                index=exchange_series.index
            )

            df = exchange_df.join(bundle_df, how='left')
            df['last_traded'] = df.index
            df['asset'] = asset.symbol
            df.set_index(['asset', 'last_traded'], inplace=True)

            frames.append(df)

        df = pd.concat(frames)
        print('\n' + df_to_string(df))
        pass