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 *
+from queue import Queue
+
+class ScheduledQueuingAlgorithm(QCAlgorithm):
+
+    def initialize(self) -> None:
+        self.set_start_date(2020, 9, 1)
+        self.set_end_date(2020, 9, 2)
+        self.set_cash(100000)
+
+        self.__number_of_symbols = 2000
+        self.__number_of_symbols_fine = 1000
+        self.set_universe_selection(FineFundamentalUniverseSelectionModel(self.coarse_selection_function, self.fine_selection_function, None))
+
+        self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())
+
+        self.set_execution(ImmediateExecutionModel())
+
+        self._queue = Queue()
+        self._dequeue_size = 100
+
+        self.add_equity("SPY", Resolution.MINUTE)
+        self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.at(0, 0), self.fill_queue)
+        self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.every(timedelta(minutes=60)), self.take_from_queue)
+
+    def coarse_selection_function(self, coarse: list[CoarseFundamental]) -> list[Symbol]:
+        has_fundamentals = [security for security in coarse if security.has_fundamental_data]
+        sorted_by_dollar_volume = sorted(has_fundamentals, key=lambda x: x.dollar_volume, reverse=True)
+        return [ x.symbol for x in sorted_by_dollar_volume[:self.__number_of_symbols] ]
+
+    def fine_selection_function(self, fine: list[FineFundamental]) -> list[Symbol]:
+        sorted_by_pe_ratio = sorted(fine, key=lambda x: x.valuation_ratios.pe_ratio, reverse=True)
+        return [ x.symbol for x in sorted_by_pe_ratio[:self.__number_of_symbols_fine] ]
+
+    def fill_queue(self) -> None:
+        securities = [security for security in self.active_securities.values() if security.fundamentals]
+
+        # Fill queue with symbols sorted by PE ratio (decreasing order)
+        self._queue.queue.clear()
+        sorted_by_pe_ratio = sorted(securities, key=lambda x: x.fundamentals.valuation_ratios.pe_ratio, reverse=True)
+        for security in sorted_by_pe_ratio:
+            self._queue.put(security.symbol)
+
+    def take_from_queue(self) -> None:
+        symbols = [self._queue.get() for _ in range(min(self._dequeue_size, self._queue.qsize()))]
+        self.history(symbols, 10, Resolution.DAILY)
+
+        self.log(f"Symbols at {self.time}: {[str(symbol) for symbol in symbols]}")