wehub-resource-sync
77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from AlgorithmImports import *
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from QuantConnect.Tests import *
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from QuantConnect.Tests.Python import *
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from PandasMapper import PandasColumn
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# TODO: Rename to PandasResearchTests and keep this class for QB related tests; rename py module to PandasTests
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class PandasIndexingTests():
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def __init__(self):
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self.qb = QuantBook()
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self.qb.SetStartDate(2020, 1, 1)
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self.qb.SetEndDate(2020, 1, 4)
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self.symbol = self.qb.AddEquity("SPY", Resolution.Daily).Symbol
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def test_indexing_dataframe_with_list(self):
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symbols = [self.symbol]
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self.history = self.qb.History(symbols, 30)
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self.history = self.history['close'].unstack(level=0).dropna()
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test = self.history[[self.symbol]]
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return True
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# Test class that sets up two dataframes to test on
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class PandasDataFrameTests():
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def __init__(self):
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self.spy = Symbols.SPY
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self.aapl = Symbols.AAPL
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# Set our symbol cache
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SymbolCache.Set("SPY", self.spy)
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SymbolCache.Set("AAPL", self.aapl)
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pdConverter = PandasConverter()
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# Create our dataframes
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self.spydf = pdConverter.GetDataFrame(PythonTestingUtils.GetSlices(self.spy))
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def test_contains_user_mapped_ticker(self):
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# Create a new DF that has a plain ticker, test that our mapper doesn't break
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# searching for it.
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df = pd.DataFrame({'spy': [2, 5, 8, 10]})
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return 'spy' in df
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def test_expected_exception(self):
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# Try indexing a ticker that doesn't exist in this frame, but is still in our cache
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try:
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self.spydf['aapl']
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except KeyError as e:
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return str(e)
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def test_contains_user_defined_columns_with_spaces(self, column_name):
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# Adds a column, then try accessing it.
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# If the colums has white spaces, it should not fail
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df = self.spydf.copy()
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df[column_name] = 1
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try:
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x = df[column_name]
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return True
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except:
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return False
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def test_column_equals_only_matching_string(self):
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# A column label should only equal a matching string, never None/ints/floats
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column = PandasColumn("shares")
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return (not (column == None)) and (not (column == 0)) and (not (column == 123)) and (column == "shares")
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