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>
+### Demonstration algorithm of indicators history window usage
+### </summary>
+class IndicatorHistoryAlgorithm(QCAlgorithm):
+    '''Demonstration algorithm of indicators history window usage.'''
+
+    def initialize(self):
+        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
+        self.set_start_date(2013, 1, 1)
+        self.set_end_date(2014, 12, 31)
+        self.set_cash(25000)
+
+        self._symbol = self.add_equity("SPY", Resolution.DAILY).symbol
+
+        self.bollinger_bands = self.bb(self._symbol, 20, 2.0, resolution=Resolution.DAILY)
+        # Let's keep BB values for a 20 day period
+        self.bollinger_bands.window.size = 20
+        # Also keep the same period of data for the middle band
+        self.bollinger_bands.middle_band.window.size = 20
+
+    def on_data(self, slice: Slice):
+        # Let's wait for our indicator to fully initialize and have a full window of history data
+        if not self.bollinger_bands.window.is_ready: return
+
+        # We can access the current and oldest (in our period) values of the indicator
+        self.log(f"Current BB value: {self.bollinger_bands[0].end_time} - {self.bollinger_bands[0].value}")
+        self.log(f"Oldest BB value: {self.bollinger_bands[self.bollinger_bands.window.count - 1].end_time} - "
+                 f"{self.bollinger_bands[self.bollinger_bands.window.count - 1].value}")
+
+        # Let's log the BB values for the last 20 days, for demonstration purposes on how it can be enumerated
+        for data_point in self.bollinger_bands:
+            self.log(f"BB @{data_point.end_time}: {data_point.value}")
+
+        # We can also do the same for internal indicators:
+        middle_band = self.bollinger_bands.middle_band
+        self.log(f"Current BB Middle Band value: {middle_band[0].end_time} - {middle_band[0].value}")
+        self.log(f"Oldest BB Middle Band value: {middle_band[middle_band.window.count - 1].end_time} - "
+                 f"{middle_band[middle_band.window.count - 1].value}")
+        for data_point in middle_band:
+            self.log(f"BB Middle Band @{data_point.end_time}: {data_point.value}")
+
+        # We are done now!
+        self.quit()