mirror of
https://github.com/wassname/catalyst.git
synced 2026-06-29 03:02:36 +08:00
Joe Jevnik
59c8e371a2
Adds the data bundle concept which makes it easy for users to register loading functions to build out minute and daily data along with an assets db and adjustments db. By default we have provided a `quandl` bundle which pulls from the public domain WIKI dataset. Users may register new bundles by decorating an ingest function with `zipline.data.bundles.register(<name>)`. This also provides a `yahoo_equities` function for creating an ingestion function that will load a static set of assets from yahoo. The cli is now structured as a couple of subcommands and has been changed to `python -m zipline`. The old behavior of `run_algo.py` has been moved to the `run` subcommand. This is almost entirely the same except that it now takes the name of the data bundle to use, defaulting to `quandl`. The next subcommand is `ingest` which takes the name of a data bundle to ingest. This will run the loading machinery and write the data to a specified location that `run` can find. There is also a `clean` subcommand which deletes the data that was written with `ingest`. Extensions have also been added to zipline. This is an experimental feature where users can provide an extra set of python files to run at the start of the process. These can be used to configure aspects of zipline. Right now the only thing that is supported in an extension file is the registration of a new data bundle.
119 lines
3.1 KiB
Python
119 lines
3.1 KiB
Python
import click
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import pandas as pd
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from .context_tricks import CallbackManager
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def maybe_show_progress(it, show_progress, **kwargs):
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"""Optionally show a progress bar for the given iterator.
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Parameters
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----------
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it : iterable
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The underlying iterator.
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show_progress : bool
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Should progress be shown.
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**kwargs
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Forwarded to the click progress bar.
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Returns
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-------
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itercontext : context manager
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A context manager whose enter is the actual iterator to use.
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Examples
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--------
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.. code-block:: python
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with maybe_show_progress([1, 2, 3], True) as ns:
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for n in ns:
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...
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"""
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if show_progress:
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return click.progressbar(it, **kwargs)
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# context manager that just return `it` when we enter it
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return CallbackManager(lambda it=it: it)
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class _DatetimeParam(click.ParamType):
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def __init__(self, tz=None):
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self.tz = tz
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def parser(self, value):
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return pd.Timestamp(value, tz=self.tz)
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@property
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def name(self):
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return type(self).__name__.upper()
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def convert(self, value, param, ctx):
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try:
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return self.parser(value)
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except ValueError:
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self.fail(
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'%s is not a valid %s' % (value, self.name.lower()),
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param,
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ctx,
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)
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class Timestamp(_DatetimeParam):
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"""A click parameter that parses the value into pandas.Timestamp objects.
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Parameters
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----------
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tz : timezone-coercable, optional
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The timezone to parse the string as.
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By default the timezone will be infered from the string or naiive.
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"""
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class Date(_DatetimeParam):
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"""A click parameter that parses the value into datetime.date objects.
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Parameters
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----------
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tz : timezone-coercable, optional
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The timezone to parse the string as.
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By default the timezone will be infered from the string or naiive.
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as_timestamp : bool, optional
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If True, return the value as a pd.Timestamp object normalized to
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midnight.
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"""
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def __init__(self, tz=None, as_timestamp=False):
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super(Date, self).__init__(tz=tz)
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self.as_timestamp = as_timestamp
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def parser(self, value):
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ts = super(Date, self).parser(value)
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return ts.normalize() if self.as_timestamp else ts.date()
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class Time(_DatetimeParam):
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"""A click parameter that parses the value into timetime.time objects.
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Parameters
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----------
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tz : timezone-coercable, optional
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The timezone to parse the string as.
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By default the timezone will be infered from the string or naiive.
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"""
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def parser(self, value):
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return super(Time, self).parser(value).time()
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class Timedelta(_DatetimeParam):
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"""A click parameter that parses values into pd.Timedelta objects.
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Parameters
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----------
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unit : {'D', 'h', 'm', 's', 'ms', 'us', 'ns'}, optional
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Denotes the unit of the input if the input is an integer.
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"""
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def __init__(self, unit='ns'):
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self.unit = unit
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def parser(self, value):
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return pd.Timedelta(value, unit=self.unit)
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