chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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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>
+### This algorithm tests the functionality of the CompositeIndicator
+### using either a lambda expression or a method reference.
+### </summary>
+class CompositeIndicatorWorksAsExpectedRegressionAlgorithm(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2013, 10, 4)
+        self.set_end_date(2013, 10, 5)
+        self.add_equity("SPY", Resolution.MINUTE)
+        close  = self.identity("SPY", Resolution.MINUTE, Field.CLOSE)
+        low = self.min("SPY", 420, Resolution.MINUTE, Field.LOW)
+        self.composite_min_direct = CompositeIndicator("CompositeMinDirect", close, low, lambda l, r: IndicatorResult(min(l.current.value, r.current.value)))
+        self.composite_min_method = CompositeIndicator("CompositeMinMethod", close, low, self.composer)
+
+        self.data_received = False
+
+    def composer(self, l, r):
+        return IndicatorResult(min(l.current.value, r.current.value))
+
+    def on_data(self, data):
+        self.data_received = True
+        if self.composite_min_direct.current.value != self.composite_min_method.current.value:
+            raise AssertionError(f"Values of indicators differ: {self.composite_min_direct.current.value} | {self.composite_min_method.current.value}")
+        
+    def on_end_of_algorithm(self):
+        if not self.data_received:
+            raise AssertionError("No data was processed during the algorithm execution.")