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pep8 conversion of python algos #1-25 (#7926)

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* pep8 conversion of python algos

* address peer-review

* PEP8 updates/fixes

* More fixes

---------

Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
This commit is contained in:
Louis Szeto
2024-04-18 05:02:32 +08:00
committed by GitHub
parent 784e497691
commit ed7f3ebbbf
35 changed files with 735 additions and 727 deletions
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Algorithm.Python/FundamentalRegressionAlgorithm.py
+53 -53
View File
@@ -22,34 +22,34 @@ from AlgorithmImports import *
### <meta name="tag" content="regression test" />
class FundamentalRegressionAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2014, 3, 26)
self.SetEndDate(2014, 4, 7)
def initialize(self):
self.set_start_date(2014, 3, 26)
self.set_end_date(2014, 4, 7)
self.UniverseSettings.Resolution = Resolution.Daily
self.universe_settings.resolution = Resolution.DAILY
self._universe = self.AddUniverse(self.SelectionFunction)
self._universe = self.add_universe(self.selection_function)
# before we add any symbol
self.AssertFundamentalUniverseData()
self.assert_fundamental_universe_data()
self.AddEquity("SPY")
self.AddEquity("AAPL")
self.add_equity("SPY")
self.add_equity("AAPL")
# Request fundamental data for symbols at current algorithm time
ibm = Symbol.Create("IBM", SecurityType.Equity, Market.USA)
ibmFundamental = self.Fundamentals(ibm)
if self.Time != self.StartDate or self.Time != ibmFundamental.EndTime:
raise ValueError(f"Unexpected Fundamental time {ibmFundamental.EndTime}")
if ibmFundamental.Price == 0:
ibm = Symbol.create("IBM", SecurityType.EQUITY, Market.USA)
ibm_fundamental = self.fundamentals(ibm)
if self.time != self.start_date or self.time != ibm_fundamental.end_time:
raise ValueError(f"Unexpected Fundamental time {ibm_fundamental.end_time}")
if ibm_fundamental.price == 0:
raise ValueError(f"Unexpected Fundamental IBM price!")
nb = Symbol.Create("NB", SecurityType.Equity, Market.USA)
fundamentals = self.Fundamentals([ nb, ibm ])
nb = Symbol.create("NB", SecurityType.EQUITY, Market.USA)
fundamentals = self.fundamentals([ nb, ibm ])
if len(fundamentals) != 2:
raise ValueError(f"Unexpected Fundamental count {len(fundamentals)}! Expected 2")
# Request historical fundamental data for symbols
history = self.History(Fundamental, TimeSpan(2, 0, 0, 0))
history = self.history(Fundamental, TimeSpan(2, 0, 0, 0))
if len(history) != 4:
raise ValueError(f"Unexpected Fundamental history count {len(history)}! Expected 4")
@@ -57,75 +57,75 @@ class FundamentalRegressionAlgorithm(QCAlgorithm):
data = history.loc[ticker]
if data["value"][0] == 0:
raise ValueError(f"Unexpected {data} fundamental data")
if Object.ReferenceEquals(data.earningreports.iloc[0], data.earningreports.iloc[1]):
if Object.reference_equals(data.earningreports.iloc[0], data.earningreports.iloc[1]):
raise ValueError(f"Unexpected fundamental data instance duplication")
if data.earningreports.iloc[0]._timeProvider.GetUtcNow() == data.earningreports.iloc[1]._timeProvider.GetUtcNow():
if data.earningreports.iloc[0]._time_provider.get_utc_now() == data.earningreports.iloc[1]._time_provider.get_utc_now():
raise ValueError(f"Unexpected fundamental data instance duplication")
self.AssertFundamentalUniverseData()
self.assert_fundamental_universe_data()
self.changes = None
self.numberOfSymbolsFundamental = 2
self.number_of_symbols_fundamental = 2
def AssertFundamentalUniverseData(self):
def assert_fundamental_universe_data(self):
# Case A
universeDataPerTime = self.History(self._universe.DataType, [self._universe.Symbol], TimeSpan(2, 0, 0, 0))
if len(universeDataPerTime) != 2:
raise ValueError(f"Unexpected Fundamentals history count {len(universeDataPerTime)}! Expected 2")
universe_data_per_time = self.history(self._universe.data_type, [self._universe.symbol], TimeSpan(2, 0, 0, 0))
if len(universe_data_per_time) != 2:
raise ValueError(f"Unexpected Fundamentals history count {len(universe_data_per_time)}! Expected 2")
for universeDataCollection in universeDataPerTime:
self.AssertFundamentalEnumerator(universeDataCollection, "A")
for universe_data_collection in universe_data_per_time:
self.assert_fundamental_enumerator(universe_data_collection, "A")
# Case B (sugar on A)
universeDataPerTime = self.History(self._universe, TimeSpan(2, 0, 0, 0))
if len(universeDataPerTime) != 2:
raise ValueError(f"Unexpected Fundamentals history count {len(universeDataPerTime)}! Expected 2")
universe_data_per_time = self.history(self._universe, TimeSpan(2, 0, 0, 0))
if len(universe_data_per_time) != 2:
raise ValueError(f"Unexpected Fundamentals history count {len(universe_data_per_time)}! Expected 2")
for universeDataCollection in universeDataPerTime:
self.AssertFundamentalEnumerator(universeDataCollection, "B")
for universe_data_collection in universe_data_per_time:
self.assert_fundamental_enumerator(universe_data_collection, "B")
# Case C: Passing through the unvierse type and symbol
enumerableOfDataDictionary = self.History[self._universe.DataType]([self._universe.Symbol], 100)
for selectionCollectionForADay in enumerableOfDataDictionary:
self.AssertFundamentalEnumerator(selectionCollectionForADay[self._universe.Symbol], "C")
enumerable_of_data_dictionary = self.history[self._universe.data_type]([self._universe.symbol], 100)
for selection_collection_for_a_day in enumerable_of_data_dictionary:
self.assert_fundamental_enumerator(selection_collection_for_a_day[self._universe.symbol], "C")
def AssertFundamentalEnumerator(self, enumerable, caseName):
dataPointCount = 0
def assert_fundamental_enumerator(self, enumerable, case_name):
data_point_count = 0
for fundamental in enumerable:
dataPointCount += 1
data_point_count += 1
if type(fundamental) is not Fundamental:
raise ValueError(f"Unexpected Fundamentals data type {type(fundamental)} case {caseName}! {str(fundamental)}")
if dataPointCount < 7000:
raise ValueError(f"Unexpected historical Fundamentals data count {dataPointCount} case {caseName}! Expected > 7000")
raise ValueError(f"Unexpected Fundamentals data type {type(fundamental)} case {case_name}! {str(fundamental)}")
if data_point_count < 7000:
raise ValueError(f"Unexpected historical Fundamentals data count {data_point_count} case {case_name}! Expected > 7000")
# return a list of three fixed symbol objects
def SelectionFunction(self, fundamental):
def selection_function(self, fundamental):
# sort descending by daily dollar volume
sortedByDollarVolume = sorted([x for x in fundamental if x.Price > 1],
key=lambda x: x.DollarVolume, reverse=True)
sorted_by_dollar_volume = sorted([x for x in fundamental if x.price > 1],
key=lambda x: x.dollar_volume, reverse=True)
# sort descending by P/E ratio
sortedByPeRatio = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.PERatio, reverse=True)
sorted_by_pe_ratio = sorted(sorted_by_dollar_volume, key=lambda x: x.valuation_ratios.pe_ratio, reverse=True)
# take the top entries from our sorted collection
return [ x.Symbol for x in sortedByPeRatio[:self.numberOfSymbolsFundamental] ]
return [ x.symbol for x in sorted_by_pe_ratio[:self.number_of_symbols_fundamental] ]
def OnData(self, data):
def on_data(self, data):
# if we have no changes, do nothing
if self.changes is None: return
# liquidate removed securities
for security in self.changes.RemovedSecurities:
if security.Invested:
self.Liquidate(security.Symbol)
self.Debug("Liquidated Stock: " + str(security.Symbol.Value))
for security in self.changes.removed_securities:
if security.invested:
self.liquidate(security.symbol)
self.debug("Liquidated Stock: " + str(security.symbol.value))
# we want 50% allocation in each security in our universe
for security in self.changes.AddedSecurities:
self.SetHoldings(security.Symbol, 0.02)
for security in self.changes.added_securities:
self.set_holdings(security.symbol, 0.02)
self.changes = None
# this event fires whenever we have changes to our universe
def OnSecuritiesChanged(self, changes):
def on_securities_changed(self, changes):
self.changes = changes