zipline.pipeline.engine_from_files()

Complexity

Conditions

4

Size

Total Lines

36

Duplication

Lines	0
Ratio	0 %

from __future__ import print_function
def engine_from_files(daily_bar_path,
                      adjustments_path,
                      asset_db_path,
                      calendar,
                      warmup_assets=False):
    """
    Construct a SimplePipelineEngine from local filesystem resources.

    Parameters
    ----------
    daily_bar_path : str
        Path to pass to `BcolzDailyBarReader`.
    adjustments_path : str
        Path to pass to SQLiteAdjustmentReader.
    asset_db_path : str
        Path to pass to `AssetFinder`.
    calendar : pd.DatetimeIndex
        Calendar to use for the loader.
    warmup_assets : bool
        Whether or not to populate AssetFinder caches.  This can speed up
        initial latency on subsequent pipeline runs, at the cost of extra
        memory consumption.
    """
    loader = USEquityPricingLoader.from_files(daily_bar_path, adjustments_path)

    if not asset_db_path.startswith("sqlite:"):
        asset_db_path = "sqlite:///" + asset_db_path
    asset_finder = AssetFinder(asset_db_path)
    if warmup_assets:
        results = asset_finder.retrieve_all(asset_finder.sids)
        print("Warmed up %d assets." % len(results))

    return SimplePipelineEngine(
        lambda _: loader,
        calendar,
        asset_finder,
    )