mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-10 18:05:16 +08:00
Richard Frank
64 lines
1.8 KiB
Python
64 lines
1.8 KiB
Python
from __future__ import print_function
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from zipline.assets import AssetFinder
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from .classifiers import Classifier, CustomClassifier
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from .engine import SimplePipelineEngine
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from .factors import Factor, CustomFactor
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from .filters import Filter, CustomFilter
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from .term import Term
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from .graph import ExecutionPlan, TermGraph
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from .pipeline import Pipeline
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from .loaders import USEquityPricingLoader
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def engine_from_files(daily_bar_path,
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adjustments_path,
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asset_db_path,
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calendar,
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warmup_assets=False):
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"""
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Construct a SimplePipelineEngine from local filesystem resources.
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Parameters
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----------
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daily_bar_path : str
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Path to pass to `BcolzDailyBarReader`.
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adjustments_path : str
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Path to pass to SQLiteAdjustmentReader.
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asset_db_path : str
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Path to pass to `AssetFinder`.
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calendar : pd.DatetimeIndex
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Calendar to use for the loader.
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warmup_assets : bool, optional
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Whether or not to populate AssetFinder caches. This can speed up
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initial latency on subsequent pipeline runs, at the cost of extra
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memory consumption. Default is False
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"""
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loader = USEquityPricingLoader.from_files(daily_bar_path, adjustments_path)
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asset_finder = AssetFinder(asset_db_path)
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if warmup_assets:
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results = asset_finder.retrieve_all(asset_finder.sids)
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print("Warmed up %d assets." % len(results))
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return SimplePipelineEngine(
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lambda _: loader,
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calendar,
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asset_finder,
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)
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__all__ = (
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'Classifier',
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'CustomFactor',
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'CustomFilter',
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'CustomClassifier',
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'engine_from_files',
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'ExecutionPlan',
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'Factor',
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'Filter',
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'Pipeline',
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'SimplePipelineEngine',
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'Term',
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'TermGraph',
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)
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