mirror of
https://github.com/saymrwulf/zipline.git
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e491ebef53
This commit adds initial support for international markets in the Pipeline API
via addition of the concept of "domains".
Significant changes on this branch include:
- Added `zipline.pipeline.domain` and the `Domain` interface.
- Added several canonical domain definitions:
- GENERIC
- US_EQUITIES
- CA_EQUITIES
- GB_EQUITIES
- Added `zipline.country` as a place to define canonical country code names.
- Made `PipelineLoader` an interface and added new `domain` parameter to
signature of `load_adjusted_array`.
- Added a new system for "generic" and "specialized" DataSet and BoundColumn
objects.
- Added a new system for inferring a domain from a pipeline that contains a mix
of generic and non-generic terms.
- Reworked the built-in pricing dataset. USEquityPricing dataset is now a
specialized version of a generic EquityPricing dataset, and most built-in
factors are now implemented in terms of EquityPricing rather than
USEquityPricing.
- Removed `zipline.data.us_equity_pricing`.
- Moved BcolzDailyBar{Reader,Writer} to `zipline.data.bcolz_daily_bars`.
- Moved SQLiteAdjustment{Reader,Writer} to `zipline.data.adjustments`.
New dependencies added as part of this work:
- iso3166 (for canonical country code definitions)
- python-interface (for strict interface definitions).
See https://github.com/quantopian/zipline/issues/2265 for a full description of
the design for domains.
65 lines
1.6 KiB
Python
65 lines
1.6 KiB
Python
from nose.tools import nottest
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import numpy as np
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from zipline.testing.predicates import assert_equal
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from zipline.pipeline import Classifier, Factor, Filter
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from zipline.utils.numpy_utils import float64_dtype, int64_dtype
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from .base import BaseUSEquityPipelineTestCase
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@nottest
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class BaseAliasTestCase(BaseUSEquityPipelineTestCase):
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def test_alias(self):
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f = self.Term()
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alias = f.alias('ayy lmao')
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f_values = np.random.RandomState(5).randn(5, 5)
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self.check_terms(
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terms={
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'f_alias': alias,
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},
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expected={
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'f_alias': f_values,
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},
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initial_workspace={f: f_values},
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mask=self.build_mask(np.ones((5, 5))),
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)
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def test_repr(self):
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assert_equal(
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repr(self.Term().alias('ayy lmao')),
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"Aliased%s(Term(...), name='ayy lmao')" % (
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self.Term.__base__.__name__,
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),
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)
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def test_graph_repr(self):
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for name in ('a', 'b'):
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assert_equal(
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self.Term().alias(name).graph_repr(),
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name,
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)
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class TestFactorAlias(BaseAliasTestCase):
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class Term(Factor):
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dtype = float64_dtype
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inputs = ()
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window_length = 0
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class TestFilterAlias(BaseAliasTestCase):
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class Term(Filter):
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inputs = ()
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window_length = 0
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class TestClassifierAlias(BaseAliasTestCase):
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class Term(Classifier):
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dtype = int64_dtype
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inputs = ()
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window_length = 0
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missing_value = -1
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