Function resample_apply

backtesting/lib.py:207–335

Apply `func` (such as an indicator) to `series`, resampled to a time frame specified by `rule`. When called from inside `backtesting.backtesting.Strategy.init`, the result (returned) series will be automatically wrapped in `backtesting.backtesting.Strategy.I` wrapper method.

(rule: str,
                   func: Optional[Callable[..., Sequence]],
                   series: Union[pd.Series, pd.DataFrame, _Array],
                   *args,
                   agg: Optional[Union[str, dict]] = None,
                   **kwargs)

def resample_apply(rule: str,
                   func: Optional[Callable[..., Sequence]],
                   series: Union[pd.Series, pd.DataFrame, _Array],
                   *args,
                   agg: Optional[Union[str, dict]] = None,
                   **kwargs):
    """
    Apply `func` (such as an indicator) to `series`, resampled to
    a time frame specified by `rule`. When called from inside
    `backtesting.backtesting.Strategy.init`,
    the result (returned) series will be automatically wrapped in
    `backtesting.backtesting.Strategy.I`
    wrapper method.

    `rule` is a valid [Pandas offset string] indicating
    a time frame to resample `series` to.

    [Pandas offset string]: \
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases

    `func` is the indicator function to apply on the resampled series.

    `series` is a data series (or array), such as any of the
    `backtesting.backtesting.Strategy.data` series. Due to pandas
    resampling limitations, this only works when input series
    has a datetime index.

    `agg` is the aggregation function to use on resampled groups of data.
    Valid values are anything accepted by `pandas/resample/.agg()`.
    Default value for dataframe input is `OHLCV_AGG` dictionary.
    Default value for series input is the appropriate entry from `OHLCV_AGG`
    if series has a matching name, or otherwise the value `"last"`,
    which is suitable for closing prices,
    but you might prefer another (e.g. `"max"` for peaks, or similar).

    Finally, any `*args` and `**kwargs` that are not already eaten by
    implicit `backtesting.backtesting.Strategy.I` call
    are passed to `func`.

    For example, if we have a typical moving average function
    `SMA(values, lookback_period)`, _hourly_ data source, and need to
    apply the moving average MA(10) on a _daily_ time frame,
    but don't want to plot the resulting indicator, we can do:

        class System(Strategy):
            def init(self):
                self.sma = resample_apply(
                    'D', SMA, self.data.Close, 10, plot=False)

    The above short snippet is roughly equivalent to:

        class System(Strategy):
            def init(self):
                # Strategy exposes `self.data` as raw NumPy arrays.
                # Let's convert closing prices back to pandas Series.
                close = self.data.Close.s

                # Resample to daily resolution. Aggregate groups