chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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+# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
+# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
+#
+# 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.
+
+from AlgorithmImports import *
+
+### <summary>
+### Regression test illustrating how history from custom data sources can be requested. The <see cref="QCAlgorithm.history"/> method used in this
+### example also allows to specify other parameters than just the resolution, such as the data normalization mode, the data mapping mode, etc.
+### </summary>
+class HistoryWithCustomDataSourceRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2014, 6, 5)
+        self.set_end_date(2014, 6, 6)
+
+        self.aapl = self.add_data(CustomData, "AAPL", Resolution.MINUTE).symbol
+        self.spy = self.add_data(CustomData, "SPY", Resolution.MINUTE).symbol
+
+    def on_end_of_algorithm(self):
+        aapl_history = self.history(CustomData, self.aapl, self.start_date, self.end_date, Resolution.MINUTE,
+            fill_forward=False, extended_market_hours=False, data_normalization_mode=DataNormalizationMode.RAW).droplevel(0, axis=0)
+        spy_history = self.history(CustomData, self.spy, self.start_date, self.end_date, Resolution.MINUTE,
+            fill_forward=False, extended_market_hours=False, data_normalization_mode=DataNormalizationMode.RAW).droplevel(0, axis=0)
+
+        if aapl_history.size == 0 or spy_history.size == 0:
+            raise AssertionError("At least one of the history results is empty")
+
+        # Check that both resutls contain the same data, since CustomData fetches APPL data regardless of the symbol
+        if not aapl_history.equals(spy_history):
+            raise AssertionError("Histories are not equal")
+
+class CustomData(PythonData):
+    '''Custom data source for the regression test algorithm, which returns AAPL equity data regardless of the symbol requested.'''
+
+    def get_source(self, config, date, is_live_mode):
+        return TradeBar().get_source(
+            SubscriptionDataConfig(
+                config,
+                CustomData,
+                # Create a new symbol as equity so we find the existing data files
+                # Symbol.create(config.mapped_symbol, SecurityType.EQUITY, config.market)),
+                Symbol.create("AAPL", SecurityType.EQUITY, config.market)),
+            date,
+            is_live_mode)
+
+    def reader(self, config, line, date, is_live_mode):
+        trade_bar = TradeBar.parse_equity(config, line, date)
+        data = CustomData()
+        data.Symbol = config.symbol
+        data.time = trade_bar.time
+        data.value = trade_bar.value
+        data.close = trade_bar.close
+        data.open = trade_bar.open
+        data.high = trade_bar.high
+        data.low = trade_bar.low
+        data.volume = trade_bar.volume
+
+        return data