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catalyst/tests/test_assets.py
T
Scott Sanderson ef4f642e62 ENH: Compute engine architecture for FFC API. 
This patch lays the groundwork for a compute engine designed to
facilitate construction of factor-based universe screening and portfolio
allocation.  It contains:

A new module, `zipline.modelling`, containing entities that can be used
to express computations as dependency graphs.  Each node in such a graph
is an instance of the base `Term` class, defined in
`zipline.modelling.term`.  Dependency graphs are executed by instances
of `FFCEngine`, defined in `zipline.modelling.engine`.

A new module, `zipline.data.ffc`, containing loaders and dataset
definitions for inputs to the modelling API.

New `TradingAlgorithm` api methods: `add_factor`, and `add_filter`.
These methods can only be called from `initialize`, and are used to
inform the algorithm that each day it should compute the given terms.
Computed factor results are made available through a new attribute of
the `data` object in `before_trading_start` and `handle_data`.  Computed
filter results control which assets are available in the factor matrix
on each day.
2015-07-29 12:30:46 -04:00

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#
# Copyright 2015 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Tests for the zipline.assets package
"""
import sys
from unittest import TestCase
from datetime import datetime, timedelta
import pickle
import uuid
import warnings
import pandas as pd
from pandas.tseries.tools import normalize_date
from pandas.util.testing import assert_frame_equal
from nose_parameterized import parameterized
from numpy import full
from zipline.assets import Asset, Equity, Future, AssetFinder
from zipline.assets.futures import FutureChain
from zipline.errors import (
SymbolNotFound,
MultipleSymbolsFound,
SidAssignmentError,
RootSymbolNotFound,
)
from zipline.finance.trading import with_environment
from zipline.utils.test_utils import (
all_subindices,
make_rotating_asset_info,
)
def build_lookup_generic_cases():
"""
Generate test cases for AssetFinder test_lookup_generic.
"""
unique_start = pd.Timestamp('2013-01-01', tz='UTC')
unique_end = pd.Timestamp('2014-01-01', tz='UTC')
dupe_0_start = pd.Timestamp('2013-01-01', tz='UTC')
dupe_0_end = dupe_0_start + timedelta(days=1)
dupe_1_start = pd.Timestamp('2013-01-03', tz='UTC')
dupe_1_end = dupe_1_start + timedelta(days=1)
frame = pd.DataFrame.from_records(
[
{
'sid': 0,
'file_name': 'duplicated',
'company_name': 'duplicated_0',
'start_date_nano': dupe_0_start.value,
'end_date_nano': dupe_0_end.value,
'exchange': '',
},
{
'sid': 1,
'file_name': 'duplicated',
'company_name': 'duplicated_1',
'start_date_nano': dupe_1_start.value,
'end_date_nano': dupe_1_end.value,
'exchange': '',
},
{
'sid': 2,
'file_name': 'unique',
'company_name': 'unique',
'start_date_nano': unique_start.value,
'end_date_nano': unique_end.value,
'exchange': '',
},
],
)
finder = AssetFinder(metadata=frame)
dupe_0, dupe_1, unique = assets = [
finder.retrieve_asset(i)
for i in range(3)
]
dupe_0_start = dupe_0.start_date
dupe_1_start = dupe_1.start_date
cases = [
##
# Scalars
# Asset object
(finder, assets[0], None, assets[0]),
(finder, assets[1], None, assets[1]),
(finder, assets[2], None, assets[2]),
# int
(finder, 0, None, assets[0]),
(finder, 1, None, assets[1]),
(finder, 2, None, assets[2]),
# Duplicated symbol with resolution date
(finder, 'duplicated', dupe_0_start, dupe_0),
(finder, 'duplicated', dupe_1_start, dupe_1),
# Unique symbol, with or without resolution date.
(finder, 'unique', unique_start, unique),
(finder, 'unique', None, unique),
##
# Iterables
# Iterables of Asset objects.
(finder, assets, None, assets),
(finder, iter(assets), None, assets),
# Iterables of ints
(finder, (0, 1), None, assets[:-1]),
(finder, iter((0, 1)), None, assets[:-1]),
# Iterables of symbols.
(finder, ('duplicated', 'unique'), dupe_0_start, [dupe_0, unique]),
(finder, ('duplicated', 'unique'), dupe_1_start, [dupe_1, unique]),
# Mixed types
(finder,
('duplicated', 2, 'unique', 1, dupe_1),
dupe_0_start,
[dupe_0, assets[2], unique, assets[1], dupe_1]),
]
return cases
class AssetTestCase(TestCase):
def test_asset_object(self):
self.assertEquals({5061: 'foo'}[Asset(5061)], 'foo')
self.assertEquals(Asset(5061), 5061)
self.assertEquals(5061, Asset(5061))
self.assertEquals(Asset(5061), Asset(5061))
self.assertEquals(int(Asset(5061)), 5061)
self.assertEquals(str(Asset(5061)), 'Asset(5061)')
def test_asset_is_pickleable(self):
# Very wow
s = Asset(
1337,
symbol="DOGE",
asset_name="DOGECOIN",
start_date=pd.Timestamp('2013-12-08 9:31AM', tz='UTC'),
end_date=pd.Timestamp('2014-06-25 11:21AM', tz='UTC'),
first_traded=pd.Timestamp('2013-12-08 9:31AM', tz='UTC'),
exchange='THE MOON',
)
s_unpickled = pickle.loads(pickle.dumps(s))
attrs_to_check = ['end_date',
'exchange',
'first_traded',
'end_date',
'asset_name',
'start_date',
'sid',
'start_date',
'symbol']
for attr in attrs_to_check:
self.assertEqual(getattr(s, attr), getattr(s_unpickled, attr))
def test_asset_comparisons(self):
s_23 = Asset(23)
s_24 = Asset(24)
self.assertEqual(s_23, s_23)
self.assertEqual(s_23, 23)
self.assertEqual(23, s_23)
self.assertNotEqual(s_23, s_24)
self.assertNotEqual(s_23, 24)
self.assertNotEqual(s_23, "23")
self.assertNotEqual(s_23, 23.5)
self.assertNotEqual(s_23, [])
self.assertNotEqual(s_23, None)
self.assertLess(s_23, s_24)
self.assertLess(s_23, 24)
self.assertGreater(24, s_23)
self.assertGreater(s_24, s_23)
def test_lt(self):
self.assertTrue(Asset(3) < Asset(4))
self.assertFalse(Asset(4) < Asset(4))
self.assertFalse(Asset(5) < Asset(4))
def test_le(self):
self.assertTrue(Asset(3) <= Asset(4))
self.assertTrue(Asset(4) <= Asset(4))
self.assertFalse(Asset(5) <= Asset(4))
def test_eq(self):
self.assertFalse(Asset(3) == Asset(4))
self.assertTrue(Asset(4) == Asset(4))
self.assertFalse(Asset(5) == Asset(4))
def test_ge(self):
self.assertFalse(Asset(3) >= Asset(4))
self.assertTrue(Asset(4) >= Asset(4))
self.assertTrue(Asset(5) >= Asset(4))
def test_gt(self):
self.assertFalse(Asset(3) > Asset(4))
self.assertFalse(Asset(4) > Asset(4))
self.assertTrue(Asset(5) > Asset(4))
def test_type_mismatch(self):
if sys.version_info.major < 3:
self.assertIsNotNone(Asset(3) < 'a')
self.assertIsNotNone('a' < Asset(3))
else:
with self.assertRaises(TypeError):
Asset(3) < 'a'
with self.assertRaises(TypeError):
'a' < Asset(3)
class TestFuture(TestCase):
future = Future(
2468,
symbol='OMH15',
root_symbol='OM',
notice_date=pd.Timestamp('2014-01-20', tz='UTC'),
expiration_date=pd.Timestamp('2014-02-20', tz='UTC'),
contract_multiplier=500
)
def test_str(self):
strd = self.future.__str__()
self.assertEqual("Future(2468 [OMH15])", strd)
def test_repr(self):
reprd = self.future.__repr__()
self.assertTrue("Future" in reprd)
self.assertTrue("2468" in reprd)
self.assertTrue("OMH15" in reprd)
self.assertTrue("root_symbol='OM'" in reprd)
self.assertTrue(("notice_date=Timestamp('2014-01-20 00:00:00+0000', "
"tz='UTC')") in reprd)
self.assertTrue("expiration_date=Timestamp('2014-02-20 00:00:00+0000'"
in reprd)
self.assertTrue("contract_multiplier=500" in reprd)
def test_reduce(self):
reduced = self.future.__reduce__()
self.assertEqual(Future, reduced[0])
def test_to_and_from_dict(self):
dictd = self.future.to_dict()
self.assertTrue('root_symbol' in dictd)
self.assertTrue('notice_date' in dictd)
self.assertTrue('expiration_date' in dictd)
self.assertTrue('contract_multiplier' in dictd)
from_dict = Future.from_dict(dictd)
self.assertTrue(isinstance(from_dict, Future))
self.assertEqual(self.future, from_dict)
def test_root_symbol(self):
self.assertEqual('OM', self.future.root_symbol)
class AssetFinderTestCase(TestCase):
def test_lookup_symbol_fuzzy(self):
as_of = pd.Timestamp('2013-01-01', tz='UTC')
frame = pd.DataFrame.from_records(
[
{
'sid': i,
'file_name': 'TEST@%d' % i,
'company_name': "company%d" % i,
'start_date_nano': as_of.value,
'end_date_nano': as_of.value,
'exchange': uuid.uuid4().hex,
}
for i in range(3)
]
)
finder = AssetFinder(frame, fuzzy_char='@')
asset_0, asset_1, asset_2 = (
finder.retrieve_asset(i) for i in range(3)
)
for i in range(2): # we do it twice to test for caching bugs
self.assertIsNone(finder.lookup_symbol('test', as_of))
self.assertEqual(
asset_1,
finder.lookup_symbol('test@1', as_of)
)
# Adding an unnecessary fuzzy shouldn't matter.
self.assertEqual(
asset_1,
finder.lookup_symbol('test@1', as_of, fuzzy=True)
)
# Shouldn't find this with no fuzzy_str passed.
self.assertIsNone(finder.lookup_symbol('test1', as_of))
# Should find exact match.
self.assertEqual(
asset_1,
finder.lookup_symbol('test1', as_of, fuzzy=True),
)
def test_lookup_symbol_resolve_multiple(self):
# Incrementing by two so that start and end dates for each
# generated Asset don't overlap (each Asset's end_date is the
# day after its start date.)
dates = pd.date_range('2013-01-01', freq='2D', periods=5, tz='UTC')
df = pd.DataFrame.from_records(
[
{
'sid': i,
'file_name': 'existing',
'company_name': 'existing',
'start_date_nano': date.value,
'end_date_nano': (date + timedelta(days=1)).value,
'exchange': 'NYSE',
}
for i, date in enumerate(dates)
]
)
finder = AssetFinder(df)
for _ in range(2): # Run checks twice to test for caching bugs.
with self.assertRaises(SymbolNotFound):
finder.lookup_symbol_resolve_multiple('non_existing', dates[0])
with self.assertRaises(MultipleSymbolsFound):
finder.lookup_symbol_resolve_multiple('existing', None)
for i, date in enumerate(dates):
# Verify that we correctly resolve multiple symbols using
# the supplied date
result = finder.lookup_symbol_resolve_multiple(
'existing',
date,
)
self.assertEqual(result.symbol, 'existing')
self.assertEqual(result.sid, i)
@parameterized.expand(
build_lookup_generic_cases()
)
def test_lookup_generic(self, finder, symbols, reference_date, expected):
"""
Ensure that lookup_generic works with various permutations of inputs.
"""
results, missing = finder.lookup_generic(symbols, reference_date)
self.assertEqual(results, expected)
self.assertEqual(missing, [])
def test_lookup_generic_handle_missing(self):
data = pd.DataFrame.from_records(
[
# Sids that will be found when we do lookups.
{
'sid': 0,
'file_name': 'real',
'company_name': 'real',
'start_date_nano': pd.Timestamp('2013-1-1', tz='UTC'),
'end_date_nano': pd.Timestamp('2014-1-1', tz='UTC'),
'exchange': '',
},
{
'sid': 1,
'file_name': 'also_real',
'company_name': 'also_real',
'start_date_nano': pd.Timestamp('2013-1-1', tz='UTC'),
'end_date_nano': pd.Timestamp('2014-1-1', tz='UTC'),
'exchange': '',
},
# Sid whose end date is before our query date. We should
# still correctly find it.
{
'sid': 2,
'file_name': 'real_but_old',
'company_name': 'real_but_old',
'start_date_nano': pd.Timestamp('2002-1-1', tz='UTC'),
'end_date_nano': pd.Timestamp('2003-1-1', tz='UTC'),
'exchange': '',
},
# Sid whose end date is before our query date. We should
# still correctly find it.
{
'sid': 3,
'file_name': 'real_but_in_the_future',
'company_name': 'real_but_in_the_future',
'start_date_nano': pd.Timestamp('2014-1-1', tz='UTC'),
'end_date_nano': pd.Timestamp('2020-1-1', tz='UTC'),
'exchange': 'THE FUTURE',
},
]
)
finder = AssetFinder(data)
results, missing = finder.lookup_generic(
['real', 1, 'fake', 'real_but_old', 'real_but_in_the_future'],
pd.Timestamp('2013-02-01', tz='UTC'),
)
self.assertEqual(len(results), 3)
self.assertEqual(results[0].symbol, 'real')
self.assertEqual(results[0].sid, 0)
self.assertEqual(results[1].symbol, 'also_real')
self.assertEqual(results[1].sid, 1)
self.assertEqual(len(missing), 2)
self.assertEqual(missing[0], 'fake')
self.assertEqual(missing[1], 'real_but_in_the_future')
def test_insert_metadata(self):
finder = AssetFinder()
finder.insert_metadata(0,
asset_type='equity',
start_date='2014-01-01',
end_date='2015-01-01',
symbol="PLAY",
foo_data="FOO",)
# Test proper insertion
equity = finder.retrieve_asset(0)
self.assertIsInstance(equity, Equity)
self.assertEqual('PLAY', equity.symbol)
self.assertEqual(pd.Timestamp('2015-01-01', tz='UTC'),
equity.end_date)
# Test invalid field
self.assertFalse('foo_data' in finder.metadata_cache[0])
def test_consume_metadata(self):
# Test dict consumption
finder = AssetFinder()
dict_to_consume = {0: {'symbol': 'PLAY'},
1: {'symbol': 'MSFT'}}
finder.consume_metadata(dict_to_consume)
equity = finder.retrieve_asset(0)
self.assertIsInstance(equity, Equity)
self.assertEqual('PLAY', equity.symbol)
finder = AssetFinder()
# Test dataframe consumption
df = pd.DataFrame(columns=['asset_name', 'exchange'], index=[0, 1])
df['asset_name'][0] = "Dave'N'Busters"
df['exchange'][0] = "NASDAQ"
df['asset_name'][1] = "Microsoft"
df['exchange'][1] = "NYSE"
finder.consume_metadata(df)
self.assertEqual('NASDAQ', finder.metadata_cache[0]['exchange'])
self.assertEqual('Microsoft', finder.metadata_cache[1]['asset_name'])
def test_consume_asset_as_identifier(self):
# Build some end dates
eq_end = pd.Timestamp('2012-01-01', tz='UTC')
fut_end = pd.Timestamp('2008-01-01', tz='UTC')
# Build some simple Assets
equity_asset = Equity(1, symbol="TESTEQ", end_date=eq_end)
future_asset = Future(200, symbol="TESTFUT", end_date=fut_end)
# Consume the Assets
finder = AssetFinder()
finder.consume_identifiers([equity_asset, future_asset])
# Test equality with newly built Assets
self.assertEqual(equity_asset, finder.retrieve_asset(1))
self.assertEqual(future_asset, finder.retrieve_asset(200))
self.assertEqual(eq_end, finder.retrieve_asset(1).end_date)
self.assertEqual(fut_end, finder.retrieve_asset(200).end_date)
def test_sid_assignment(self):
# This metadata does not contain SIDs
metadata = {'PLAY': {'symbol': 'PLAY'},
'MSFT': {'symbol': 'MSFT'}}
today = normalize_date(pd.Timestamp('2015-07-09', tz='UTC'))
# Build a finder that is allowed to assign sids
finder = AssetFinder(metadata=metadata,
allow_sid_assignment=True)
# Verify that Assets were built and different sids were assigned
play = finder.lookup_symbol('PLAY', today)
msft = finder.lookup_symbol('MSFT', today)
self.assertEqual('PLAY', play.symbol)
self.assertIsNotNone(play.sid)
self.assertNotEqual(play.sid, msft.sid)
def test_sid_assignment_failure(self):
# This metadata does not contain SIDs
metadata = {'PLAY': {'symbol': 'PLAY'},
'MSFT': {'symbol': 'MSFT'}}
# Build a finder that is not allowed to assign sids, asserting failure
with self.assertRaises(SidAssignmentError):
AssetFinder(metadata=metadata, allow_sid_assignment=False)
def test_security_dates_warning(self):
# Build an asset with an end_date
eq_end = pd.Timestamp('2012-01-01', tz='UTC')
equity_asset = Equity(1, symbol="TESTEQ", end_date=eq_end)
# Catch all warnings
with warnings.catch_warnings(record=True) as w:
# Cause all warnings to always be triggered
warnings.simplefilter("always")
equity_asset.security_start_date
equity_asset.security_end_date
equity_asset.security_name
# Verify the warning
self.assertEqual(3, len(w))
for warning in w:
self.assertTrue(issubclass(warning.category,
DeprecationWarning))
def test_lookup_future_chain(self):
metadata = {
# Notice day is today, so not valid
2: {
'symbol': 'ADN15',
'root_symbol': 'AD',
'asset_type': 'future',
'notice_date': pd.Timestamp('2015-05-14', tz='UTC'),
'start_date': pd.Timestamp('2015-01-01', tz='UTC')
},
1: {
'symbol': 'ADV15',
'root_symbol': 'AD',
'asset_type': 'future',
'notice_date': pd.Timestamp('2015-08-14', tz='UTC'),
'start_date': pd.Timestamp('2015-01-01', tz='UTC')
},
# Starts trading today, so should be valid.
0: {
'symbol': 'ADF16',
'root_symbol': 'AD',
'asset_type': 'future',
'notice_date': pd.Timestamp('2015-11-16', tz='UTC'),
'start_date': pd.Timestamp('2015-05-14', tz='UTC')
},
# Copy of the above future, but starts trading in August,
# so it isn't valid.
3: {
'symbol': 'ADF16',
'root_symbol': 'AD',
'asset_type': 'future',
'notice_date': pd.Timestamp('2015-11-16', tz='UTC'),
'start_date': pd.Timestamp('2015-08-01', tz='UTC')
},
}
finder = AssetFinder(metadata=metadata)
dt = pd.Timestamp('2015-05-14', tz='UTC')
last_year = pd.Timestamp('2014-01-01', tz='UTC')
first_day = pd.Timestamp('2015-01-01', tz='UTC')
# Check that we get the expected number of contracts, in the
# right order
ad_contracts = finder.lookup_future_chain('AD', dt, dt)
self.assertEqual(len(ad_contracts), 2)
self.assertEqual(ad_contracts[0].sid, 1)
self.assertEqual(ad_contracts[1].sid, 0)
# Check that we get nothing if our knowledge date is last year
ad_contracts = finder.lookup_future_chain('AD', dt, last_year)
self.assertEqual(len(ad_contracts), 0)
# Check that we get things that start on the knowledge date
ad_contracts = finder.lookup_future_chain('AD', dt, first_day)
self.assertEqual(len(ad_contracts), 1)
def test_map_identifier_index_to_sids(self):
# Build an empty finder and some Assets
dt = pd.Timestamp('2014-01-01', tz='UTC')
finder = AssetFinder()
asset1 = Equity(1, symbol="AAPL")
asset2 = Equity(2, symbol="GOOG")
asset200 = Future(200, symbol="CLK15")
asset201 = Future(201, symbol="CLM15")
# Check for correct mapping and types
pre_map = [asset1, asset2, asset200, asset201]
post_map = finder.map_identifier_index_to_sids(pre_map, dt)
self.assertListEqual([1, 2, 200, 201], post_map)
for sid in post_map:
self.assertIsInstance(sid, int)
# Change order and check mapping again
pre_map = [asset201, asset2, asset200, asset1]
post_map = finder.map_identifier_index_to_sids(pre_map, dt)
self.assertListEqual([201, 2, 200, 1], post_map)
@with_environment()
def test_compute_lifetimes(self, env=None):
num_assets = 4
trading_day = env.trading_day
first_start = pd.Timestamp('2015-04-01', tz='UTC')
frame = make_rotating_asset_info(
num_assets=num_assets,
first_start=first_start,
frequency=env.trading_day,
periods_between_starts=3,
asset_lifetime=5
)
finder = AssetFinder(frame)
all_dates = pd.date_range(
start=first_start,
end=frame.end_date.max(),
freq=trading_day,
)
for dates in all_subindices(all_dates):
expected_mask = full(
shape=(len(dates), num_assets),
fill_value=False,
dtype=bool,
)
for i, date in enumerate(dates):
it = frame[['start_date', 'end_date']].itertuples()
for j, start, end in it:
if start <= date <= end:
expected_mask[i, j] = True
# Filter out columns with all-empty columns.
expected_result = pd.DataFrame(
data=expected_mask,
index=dates,
columns=frame.sid.values,
)
actual_result = finder.lifetimes(dates)
assert_frame_equal(actual_result, expected_result)
class TestFutureChain(TestCase):
metadata = {
0: {
'symbol': 'CLG06',
'root_symbol': 'CL',
'asset_type': 'future',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2005-12-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-01-20', tz='UTC')},
1: {
'root_symbol': 'CL',
'symbol': 'CLK06',
'asset_type': 'future',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-03-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-04-20', tz='UTC')},
2: {
'symbol': 'CLQ06',
'root_symbol': 'CL',
'asset_type': 'future',
'start_date': pd.Timestamp('2005-12-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-06-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-07-20', tz='UTC')},
3: {
'symbol': 'CLX06',
'root_symbol': 'CL',
'asset_type': 'future',
'start_date': pd.Timestamp('2006-02-01', tz='UTC'),
'notice_date': pd.Timestamp('2006-09-20', tz='UTC'),
'expiration_date': pd.Timestamp('2006-10-20', tz='UTC')}
}
asset_finder = AssetFinder(metadata=metadata)
def test_len(self):
""" Test the __len__ method of FutureChain.
"""
# None of the contracts have started yet.
cl = FutureChain(self.asset_finder, lambda: '2005-11-30', 'CL')
self.assertEqual(len(cl), 0)
# Sids 0, 1, & 2 have started, 3 has not yet started.
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
self.assertEqual(len(cl), 3)
# Sid 0 is still valid the day before its notice date.
cl = FutureChain(self.asset_finder, lambda: '2005-12-19', 'CL')
self.assertEqual(len(cl), 3)
# Sid 0 is now invalid, leaving only Sids 1 & 2 valid.
cl = FutureChain(self.asset_finder, lambda: '2005-12-20', 'CL')
self.assertEqual(len(cl), 2)
# Sid 3 has started, so 1, 2, & 3 are now valid.
cl = FutureChain(self.asset_finder, lambda: '2006-02-01', 'CL')
self.assertEqual(len(cl), 3)
# All contracts are no longer valid.
cl = FutureChain(self.asset_finder, lambda: '2006-09-20', 'CL')
self.assertEqual(len(cl), 0)
def test_getitem(self):
""" Test the __getitem__ method of FutureChain.
"""
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
self.assertEqual(cl[0], 0)
self.assertEqual(cl[1], 1)
self.assertEqual(cl[2], 2)
with self.assertRaises(IndexError):
cl[3]
cl = FutureChain(self.asset_finder, lambda: '2005-12-19', 'CL')
self.assertEqual(cl[0], 0)
cl = FutureChain(self.asset_finder, lambda: '2005-12-20', 'CL')
self.assertEqual(cl[0], 1)
cl = FutureChain(self.asset_finder, lambda: '2006-02-01', 'CL')
self.assertEqual(cl[-1], 3)
def test_root_symbols(self):
""" Test that different variations on root symbols are handled
as expected.
"""
# Make sure this successfully gets the chain for CL.
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
self.assertEqual(cl.root_symbol, 'CL')
# These root symbols don't exist, so RootSymbolNotFound should
# be raised immediately.
with self.assertRaises(RootSymbolNotFound):
FutureChain(self.asset_finder, lambda: '2005-12-01', 'CLZ')
with self.assertRaises(RootSymbolNotFound):
FutureChain(self.asset_finder, lambda: '2005-12-01', '')
def test_repr(self):
""" Test the __repr__ method of FutureChain.
"""
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
cl_feb = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL',
as_of_date='2006-02-01')
# The default chain should not include the as of date.
self.assertEqual(repr(cl), "FutureChain(root_symbol='CL')")
# An explicit as of date should show up in the repr.
self.assertEqual(
repr(cl_feb),
("FutureChain(root_symbol='CL', "
"as_of_date='2006-02-01 00:00:00+00:00')")
)
def test_as_of(self):
""" Test the as_of method of FutureChain.
"""
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
# Test that the as_of_date is set correctly to the future
feb = '2006-02-01'
cl_feb = cl.as_of(feb)
self.assertEqual(
cl_feb.as_of_date,
pd.Timestamp(feb, tz='UTC')
)
# Test that the as_of_date is set correctly to the past, with
# args of str, datetime.datetime, and pd.Timestamp.
feb_prev = '2005-02-01'
cl_feb_prev = cl.as_of(feb_prev)
self.assertEqual(
cl_feb_prev.as_of_date,
pd.Timestamp(feb_prev, tz='UTC')
)
feb_prev = datetime(year=2005, month=2, day=1)
cl_feb_prev = cl.as_of(feb_prev)
self.assertEqual(
cl_feb_prev.as_of_date,
pd.Timestamp(feb_prev, tz='UTC')
)
feb_prev = pd.Timestamp('2005-02-01')
cl_feb_prev = cl.as_of(feb_prev)
self.assertEqual(
cl_feb_prev.as_of_date,
pd.Timestamp(feb_prev, tz='UTC')
)
# The chain as of the current dt should always be the same as
# the defualt chain. Tests date as str, pd.Timestamp, and
# datetime.datetime.
self.assertEqual(cl[0], cl.as_of('2005-12-01')[0])
self.assertEqual(cl[0], cl.as_of(pd.Timestamp('2005-12-01'))[0])
self.assertEqual(
cl[0],
cl.as_of(datetime(year=2005, month=12, day=1))[0]
)
def test_offset(self):
""" Test the offset method of FutureChain.
"""
cl = FutureChain(self.asset_finder, lambda: '2005-12-01', 'CL')
# Test that an offset forward sets as_of_date as expected
self.assertEqual(
cl.offset('3 days').as_of_date,
cl.as_of_date + pd.Timedelta(days=3)
)
# Test that an offset backward sets as_of_date as expected, with
# time delta given as str, datetime.timedelta, and pd.Timedelta.
self.assertEqual(
cl.offset('-1000 days').as_of_date,
cl.as_of_date + pd.Timedelta(days=-1000)
)
self.assertEqual(
cl.offset(timedelta(days=-1000)).as_of_date,
cl.as_of_date + pd.Timedelta(days=-1000)
)
self.assertEqual(
cl.offset(pd.Timedelta('-1000 days')).as_of_date,
cl.as_of_date + pd.Timedelta(days=-1000)
)
# An offset of zero should give the original chain.
self.assertEqual(cl[0], cl.offset(0)[0])
self.assertEqual(cl[0], cl.offset("0 days")[0])
# A string that doesn't represent a time delta should raise a
# ValueError.
with self.assertRaises(ValueError):
cl.offset("blah")
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