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>
+### In this algorithm we show how you can easily use the universe selection feature to fetch symbols
+### to be traded using the BaseData custom data system in combination with the AddUniverse{T} method.
+### AddUniverse{T} requires a function that will return the symbols to be traded.
+### </summary>
+### <meta name="tag" content="using data" />
+### <meta name="tag" content="universes" />
+### <meta name="tag" content="custom universes" />
+class DropboxBaseDataUniverseSelectionAlgorithm(QCAlgorithm):
+
+    def initialize(self) -> None:
+        self.universe_settings.resolution = Resolution.DAILY
+
+        # Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
+        # Commented so regression algorithm is more sensitive
+        #self.settings.minimum_order_margin_portfolio_percentage = 0.005
+
+        self.set_start_date(2017, 7, 6)
+        self.set_end_date(2018, 7, 4)
+
+        universe = self.add_universe(StockDataSource, self.stock_data_source)
+
+        historical_selection_data = self.history(universe, 3)
+        if len(historical_selection_data) != 3:
+            raise ValueError(f"Unexpected universe data count {len(historical_selection_data)}")
+
+        for universe_data in historical_selection_data["symbols"]:
+            if len(universe_data) != 5:
+                raise ValueError(f"Unexpected universe data receieved")
+
+        self._changes = None
+
+    def stock_data_source(self, data: list[DynamicData]) -> list[Symbol]:
+        list = []
+        for item in data:
+            for symbol in item["Symbols"]:
+                list.append(symbol)
+        return list
+
+    def on_data(self, slice: Slice) -> None:
+        if slice.bars.count == 0:
+           return
+        if not self._changes:
+           return
+
+        # start fresh
+        self.liquidate()
+
+        percentage = 1 / slice.bars.count
+        for trade_bar in slice.bars.values():
+            self.set_holdings(trade_bar.symbol, percentage)
+
+        # reset changes
+        self._changes = None
+
+    def on_securities_changed(self, changes: SecurityChanges) -> None:
+        self._changes = changes
+
+class StockDataSource(PythonData):
+
+    def get_source(self, config: SubscriptionDataConfig, date: datetime, is_live_mode: bool) -> SubscriptionDataSource:
+        url = "https://www.dropbox.com/s/2l73mu97gcehmh7/daily-stock-picker-live.csv?dl=1" if is_live_mode else \
+            "https://www.dropbox.com/s/ae1couew5ir3z9y/daily-stock-picker-backtest.csv?dl=1"
+        return SubscriptionDataSource(url, SubscriptionTransportMedium.REMOTE_FILE)
+
+    def reader(self, config: SubscriptionDataConfig, line: str, date: datetime, is_live_mode: bool) -> DynamicData:
+        if not (line.strip() and line[0].isdigit()):
+            return None
+
+        stocks = StockDataSource()
+        stocks.symbol = config.symbol
+
+        csv = line.split(',')
+        if is_live_mode:
+            stocks.time = date
+            stocks["Symbols"] = csv
+        else:
+            stocks.time = datetime.strptime(csv[0], "%Y%m%d")
+            stocks["Symbols"] = csv[1:]
+        return stocks