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"message": "Cannot assign to attribute \"train_env\" for class \"ReforceXY*\"\n Expression of type \"VecEnv\" cannot be assigned to attribute \"train_env\" of class \"ReforceXY\"\n Type \"VecEnv\" is not assignable to type \"VecMonitor | SubprocVecEnv | Env[Any, Any]\"\n \"VecEnv\" is not assignable to \"VecMonitor\"\n \"VecEnv\" is not assignable to \"SubprocVecEnv\"\n \"VecEnv\" is not assignable to \"Env[Any, Any]\"",
"rule": "reportAttributeAccessIssue",
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"rule": "reportAttributeAccessIssue",
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"rule": "reportArgumentType",
"severity": "error",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"obj\" of type \"Sized\" in function \"len\"\n Type \"Any | None\" is not assignable to type \"Sized\"\n \"None\" is incompatible with protocol \"Sized\"\n \"__len__\" is not present",
"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"obj\" of type \"Sized\" in function \"len\"\n Type \"Any | None\" is not assignable to type \"Sized\"\n \"None\" is incompatible with protocol \"Sized\"\n \"__len__\" is not present",
"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"steps_to_days\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
"rule": "reportArgumentType",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"steps_to_days\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
"rule": "reportArgumentType",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"steps_to_days\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
"rule": "reportArgumentType",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"VecMonitor | SubprocVecEnv | Env[Any, Any]\" cannot be assigned to parameter \"eval_env\" of type \"VecEnv | None\" in function \"get_callbacks\"\n Type \"VecMonitor | SubprocVecEnv | Env[Any, Any]\" is not assignable to type \"VecEnv | None\"\n Type \"Env[Any, Any]\" is not assignable to type \"VecEnv | None\"\n \"Env[Any, Any]\" is not assignable to \"VecEnv\"\n \"Env[Any, Any]\" is not assignable to \"None\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 43,
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},
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | list[float]\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | list[float]\" is not assignable to type \"ConvertibleToFloat\"\n Type \"list[float]\" is not assignable to type \"ConvertibleToFloat\"\n \"list[float]\" is not assignable to \"str\"\n \"list[float]\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsIndex\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 67,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | list[float]\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | list[float]\" is not assignable to type \"ConvertibleToFloat\"\n Type \"list[float]\" is not assignable to type \"ConvertibleToFloat\"\n \"list[float]\" is not assignable to \"str\"\n \"list[float]\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
"severity": "error",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"best_trial_params\" is possibly unbound",
"rule": "reportPossiblyUnboundVariable",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Parameter declaration \"seed\" is obscured by a declaration of the same name",
"rule": "reportRedeclaration",
"severity": "error",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Parameter declaration \"env_info\" is obscured by a declaration of the same name",
"rule": "reportRedeclaration",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"list[() -> BaseEnvironment]\" cannot be assigned to parameter \"env_fns\" of type \"list[() -> Env[Any, Any]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Any, Any]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Any, Any]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
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},
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"list[() -> BaseEnvironment]\" cannot be assigned to parameter \"env_fns\" of type \"list[() -> Env[Any, Any]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Any, Any]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Any, Any]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
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},
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"message": "Operator \"*\" not supported for \"None\"",
"rule": "reportOptionalOperand",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Operator \"*\" not supported for \"None\"",
"rule": "reportOptionalOperand",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Operator \"*\" not supported for \"None\"",
"rule": "reportOptionalOperand",
"severity": "error",
"startCharacter": 16,
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"message": "Operator \"*\" not supported for \"None\"",
"rule": "reportOptionalOperand",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Operator \"*\" not supported for types \"Any | None\" and \"Any | int | None\"\n Operator \"*\" not supported for types \"None\" and \"None\"\n Operator \"*\" not supported for types \"None\" and \"int\"",
"rule": "reportOperatorIssue",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Operator \"*\" not supported for types \"Any | None\" and \"Any | int | None\"\n Operator \"*\" not supported for types \"None\" and \"None\"\n Operator \"*\" not supported for types \"None\" and \"int\"",
"rule": "reportOperatorIssue",
"severity": "error",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Operator \">\" not supported for \"None\"",
"rule": "reportOptionalOperand",
"severity": "error",
"startCharacter": 15,
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"is_pruned\" is not a known attribute of \"None\"",
"rule": "reportOptionalMemberAccess",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"use_masking\" is not a known attribute of \"None\"",
"rule": "reportOptionalMemberAccess",
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"startCharacter": 56,
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"update_best_reward\" is not a known attribute of \"None\"",
"rule": "reportOptionalMemberAccess",
"severity": "error",
"startCharacter": 42,
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | list[float]\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | list[float]\" is not assignable to type \"ConvertibleToFloat\"\n Type \"list[float]\" is not assignable to type \"ConvertibleToFloat\"\n \"list[float]\" is not assignable to \"str\"\n \"list[float]\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsIndex\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 67,
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | list[float]\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | list[float]\" is not assignable to type \"ConvertibleToFloat\"\n Type \"list[float]\" is not assignable to type \"ConvertibleToFloat\"\n \"list[float]\" is not assignable to \"str\"\n \"list[float]\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"list[float]\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 67,
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},
{
"endCharacter": 46,
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"is_pruned\" is not a known attribute of \"None\"",
"rule": "reportOptionalMemberAccess",
"severity": "error",
"startCharacter": 37,
- "startLine": 3101
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"best_mean_reward\" is not a known attribute of \"None\"",
"rule": "reportOptionalMemberAccess",
"severity": "error",
"startCharacter": 41,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Cannot assign to attribute \"train_env\" for class \"ReforceXY*\"\n Type \"None\" is not assignable to type \"VecMonitor | SubprocVecEnv | Env[Any, Any]\"\n \"None\" is not assignable to \"VecMonitor\"\n \"None\" is not assignable to \"SubprocVecEnv\"\n \"None\" is not assignable to \"Env[Any, Any]\"",
"rule": "reportAttributeAccessIssue",
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},
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Cannot assign to attribute \"eval_env\" for class \"ReforceXY*\"\n Type \"None\" is not assignable to type \"VecMonitor | SubprocVecEnv | Env[Any, Any]\"\n \"None\" is not assignable to \"VecMonitor\"\n \"None\" is not assignable to \"SubprocVecEnv\"\n \"None\" is not assignable to \"Env[Any, Any]\"",
"rule": "reportAttributeAccessIssue",
"severity": "error",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Declaration \"MyRLEnv\" is obscured by a declaration of the same name",
"rule": "reportRedeclaration",
"severity": "error",
"startCharacter": 0,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Declaration \"_last_closed_trade_tick\" is obscured by a declaration of the same name",
"rule": "reportRedeclaration",
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Method \"reset\" overrides class \"BaseEnvironment\" in an incompatible manner\n Return type mismatch: base method returns type \"tuple[DataFrame, dict[Unknown, Unknown]]\", override returns type \"tuple[NDArray[float32], dict[str, Any]]\"\n \"tuple[NDArray[float32], dict[str, Any]]\" is not assignable to \"tuple[DataFrame, dict[Unknown, Unknown]]\"\n Tuple entry 1 is incorrect type\n \"ndarray[_AnyShape, dtype[float32]]\" is not assignable to \"DataFrame\"",
"rule": "reportIncompatibleMethodOverride",
"severity": "error",
"startCharacter": 8,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Type \"tuple[DataFrame, dict[Unknown, Unknown]]\" is not assignable to return type \"tuple[NDArray[float32], dict[str, Any]]\"\n \"DataFrame\" is not assignable to \"ndarray[_AnyShape, dtype[float32]]\"",
"rule": "reportReturnType",
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | None\" is not assignable to type \"ConvertibleToFloat\"\n Type \"None\" is not assignable to type \"ConvertibleToFloat\"\n \"None\" is not assignable to \"str\"\n \"None\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"None\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 44,
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},
{
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- "endLine": 4094,
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | None\" is not assignable to type \"ConvertibleToFloat\"\n Type \"None\" is not assignable to type \"ConvertibleToFloat\"\n \"None\" is not assignable to \"str\"\n \"None\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"None\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 44,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | None\" is not assignable to type \"ConvertibleToFloat\"\n Type \"None\" is not assignable to type \"ConvertibleToFloat\"\n \"None\" is not assignable to \"str\"\n \"None\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"None\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"",
"rule": "reportArgumentType",
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"float | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | None\" is not assignable to type \"ConvertibleToFloat\"\n Type \"None\" is not assignable to type \"ConvertibleToFloat\"\n \"None\" is not assignable to \"str\"\n \"None\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"None\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Method \"_get_observation\" overrides class \"BaseEnvironment\" in an incompatible manner\n Return type mismatch: base method returns type \"DataFrame\", override returns type \"NDArray[float32]\"\n \"ndarray[_AnyShape, dtype[float32]]\" is not assignable to \"DataFrame\"",
"rule": "reportIncompatibleMethodOverride",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Method \"step\" overrides class \"Base5ActionRLEnv\" in an incompatible manner\n Return type mismatch: base method returns type \"tuple[DataFrame, float, bool, Literal[False], dict[str, Unknown]]\", override returns type \"tuple[NDArray[float32], float, bool, bool, dict[str, Any]]\"\n \"tuple[NDArray[float32], float, bool, bool, dict[str, Any]]\" is not assignable to \"tuple[DataFrame, float, bool, Literal[False], dict[str, Unknown]]\"\n Tuple entry 1 is incorrect type\n \"ndarray[_AnyShape, dtype[float32]]\" is not assignable to \"DataFrame\"",
"rule": "reportIncompatibleMethodOverride",
"severity": "error",
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Method \"action_masks\" overrides class \"BaseEnvironment\" in an incompatible manner\n Return type mismatch: base method returns type \"list[bool]\", override returns type \"NDArray[bool_]\"\n \"ndarray[_AnyShape, dtype[bool_]]\" is not assignable to \"list[bool]\"",
"rule": "reportIncompatibleMethodOverride",
"severity": "error",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"Figure\" is not exported from module \"matplotlib.pyplot\"",
"rule": "reportPrivateImportUsage",
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splits; training disables `shuffle_after_split`, and the native RL base
disables row-removing SVM/DBSCAN/DI outlier removal to preserve trajectories.
+Archived strategy charts require the extracted `RLAgentStrategy` source, not a
+fallback to the current strategy. They still use the current server's FreqAI
+model and configuration; see [archived strategy charts](../docs/evaluation.md#archived-strategy-charts).
+
## Configuration reference
The implementation and runtime validation are in
--- /dev/null
+"""Native archived replay must not train against a substituted current strategy."""
+
+import re
+import unittest
+from pathlib import Path
+
+import pandas as pd
+from freqtrade.data.dataprovider import DataProvider
+from freqtrade.enums import TradingMode
+from freqtrade.resolvers import StrategyResolver
+from qa_support import QaTestCase, model_config, temporary_directory
+
+from ReforceXY.user_data.freqaimodels.ReforceXY import ReforceXY
+from scripts.archive_replay_contract import HAS_ARCHIVED_STRATEGY_REPLAY, archived_strategy
+
+STRATEGY_SOURCE = Path(__file__).resolve().parents[1] / "user_data/strategies/RLAgentStrategy.py"
+
+
+@unittest.skipUnless(HAS_ARCHIVED_STRATEGY_REPLAY, "Native archived replay is unavailable")
+class ArchiveReplayTest(QaTestCase):
+ def test_current_strategy_fallback_cannot_start_training(self):
+ with temporary_directory() as directory:
+ current = directory / "strategies"
+ current.mkdir()
+ (current / STRATEGY_SOURCE.name).write_bytes(STRATEGY_SOURCE.read_bytes())
+ broken = directory / STRATEGY_SOURCE.name
+ broken.write_text("import missing_archived_dependency\n" + STRATEGY_SOURCE.read_text())
+ config = model_config(
+ directory, strategy="RLAgentStrategy", trading_mode=TradingMode.SPOT
+ )
+ with archived_strategy(config, broken) as (replay, source):
+ strategy = StrategyResolver.load_strategy(replay)
+ self.assertEqual(
+ Path(strategy.__file__).resolve(), (current / STRATEGY_SOURCE.name).resolve()
+ )
+ strategy.dp = DataProvider(replay, exchange=None)
+ model = ReforceXY(config=replay)
+ with self.assertRaisesRegex(ValueError, re.escape(source.name)):
+ model.start(
+ pd.DataFrame(
+ {
+ "date": pd.date_range(
+ "2026-01-01", periods=8, freq="5min", tz="UTC"
+ ),
+ "open": 100.0,
+ "high": 101.0,
+ "low": 99.0,
+ "close": 100.0,
+ "volume": 1.0,
+ }
+ ),
+ {"pair": "BTC/USDT"},
+ strategy,
+ )
import rapidjson
import torch as th
from datasieve.pipeline import Pipeline
+from freqtrade.enums import RunMode
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import timeframe_to_seconds
from freqtrade.freqai.data_drawer import (
_PRODUCED_COLUMN = "_freqai_strategies_produced"
+def _get_native_archive_strategy_file(config: dict[str, Any]) -> Path | None:
+ """Recognize Freqtrade 2026.10's extracted archive, not a general strategy path.
+
+ The webserver uses an ft_bt_strategy temporary directory containing one
+ <archive>_<strategy>.py file. Recheck this private SDK contract on upgrades.
+ Keep both model copies identical.
+ """
+ if config.get("runmode") != RunMode.WEBSERVER:
+ return None
+ strategy_path = config.get("strategy_path")
+ strategy_name = config.get("strategy")
+ if not strategy_path or not strategy_name:
+ return None
+ directory = Path(strategy_path)
+ if not directory.name.startswith("ft_bt_strategy"):
+ return None
+ source = next(directory.glob(f"*_{strategy_name}.py"), None)
+ return source.resolve() if source is not None else None
+
+
+def _validate_archived_strategy_source(strategy: Any) -> None:
+ """Refuse native archive replay that silently resolved the current strategy."""
+ archived = _get_native_archive_strategy_file(strategy.config)
+ if archived is None:
+ return
+ actual = getattr(strategy, "__file__", None)
+ if actual is None or Path(actual).resolve() != archived:
+ raise ValueError(
+ f"Backtest replay [{strategy.config['strategy']}]: could not load archived "
+ f"strategy {archived.name!r}; refusing current strategy fallback"
+ )
+
+
def _legacy_produced_prediction_mask(frame: pd.DataFrame) -> NDArray[np.bool_]:
"""Bootstrap has status 0; only nonzero, nonexpired statuses prove legacy production."""
if "do_predict" not in frame:
self._install_replay_persistence()
self._install_prediction_provenance()
+ def start(self, dataframe: pd.DataFrame, metadata: dict, strategy: Any) -> pd.DataFrame:
+ _validate_archived_strategy_source(strategy)
+ return super().start(dataframe, metadata, strategy)
+
def _ensure_history_schema(self, dk: FreqaiDataKitchen, pair: str) -> None:
"""Extend restored history without inventing past observations or metadata."""
if pair not in self.dd.historic_predictions:
deployment refit, not later rolling predictions. `timeseries_split` does not
accept zero.
+### Archived strategy charts
+
+Freqtrade 2026.10 can reanalyse the strategy source stored in a backtest ZIP
+for charts. This is separate from running a backtest or reusing its prediction
+cache. With the supplied models, replay refuses a fallback to the current
+strategy when the archived source cannot load.
+
+QuickAdapter rejects this archived chart replay: native archives omit its local
+helper modules, and already imported current helpers are not historical copies.
+Use current-strategy charts with the intended project revision, or rerun the
+backtest from that revision. Self-contained `RLAgentStrategy` archives may replay
+when the extracted source loads, but the current server still supplies the
+FreqAI model and runtime configuration; this does not reproduce a saved policy
+or freeze the historical environment.
+
+These checks run in `QuickAdapterRegressorV3` and `ReforceXY`, not in other
+FreqAI models. Reserve `ft_bt_strategy*` directories containing
+`<archive>_<strategy>.py` for native archive extraction; do not configure that
+layout as an ordinary `strategy_path`.
+
## Design the comparison
1. **Fix the question before inspecting results.** Specify the incumbent,
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"rule": "reportOptionalMemberAccess",
"severity": "error",
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"rule": "reportOptionalMemberAccess",
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columns. `freqai_backtest_live_models=true` is a separate Freqtrade mode: it
replays stored live predictions without training models.
+Archived strategy chart replay is unsupported because native backtest archives
+omit QuickAdapter's helper modules. This does not disable normal backtesting or
+prediction-cache reuse; see [archived strategy charts](../docs/evaluation.md#archived-strategy-charts).
+
## Prediction warmup and restarts
### When thresholds become available
--- /dev/null
+"""Reject native archive replay rather than borrow deployed QuickAdapter helpers."""
+
+import re
+import unittest
+from pathlib import Path
+
+from freqtrade.enums import TradingMode
+from freqtrade.resolvers import StrategyResolver
+from qa_support import QaTestCase, model_config, temporary_directory
+
+from scripts.archive_replay_contract import HAS_ARCHIVED_STRATEGY_REPLAY, archived_strategy
+
+STRATEGY_SOURCE = Path(__file__).resolve().parents[1] / "user_data/strategies/QuickAdapterV3.py"
+MODEL_DIRECTORY = STRATEGY_SOURCE.parent.parent / "freqaimodels"
+
+
+@unittest.skipUnless(HAS_ARCHIVED_STRATEGY_REPLAY, "Native archived replay is unavailable")
+class ArchiveReplayTest(QaTestCase):
+ def test_archived_source_with_cached_helpers_cannot_start_the_model(self):
+ with temporary_directory() as directory:
+ config = model_config(
+ directory,
+ strategy="QuickAdapterV3",
+ trading_mode=TradingMode.SPOT,
+ freqaimodel="QuickAdapterRegressorV3",
+ freqaimodel_path=str(MODEL_DIRECTORY),
+ freqai={"optuna_hyperopt": {"enabled": False}},
+ )
+ with archived_strategy(config, STRATEGY_SOURCE) as (replay, source):
+ strategy = StrategyResolver.load_strategy(replay)
+ self.assertEqual(Path(strategy.__file__).resolve(), source.resolve())
+ with self.assertRaisesRegex(ValueError, re.escape(source.name)):
+ strategy.ft_bot_start()
+ self.assertFalse((directory / "models").exists())
+
+ def test_current_strategy_fallback_cannot_start_the_model(self):
+ with temporary_directory() as directory:
+ current = directory / "strategies"
+ current.mkdir()
+ (current / STRATEGY_SOURCE.name).write_bytes(STRATEGY_SOURCE.read_bytes())
+ broken = directory / STRATEGY_SOURCE.name
+ broken.write_text("import missing_archived_dependency\n" + STRATEGY_SOURCE.read_text())
+ config = model_config(
+ directory,
+ strategy="QuickAdapterV3",
+ trading_mode=TradingMode.SPOT,
+ freqaimodel="QuickAdapterRegressorV3",
+ freqaimodel_path=str(MODEL_DIRECTORY),
+ freqai={"optuna_hyperopt": {"enabled": False}},
+ )
+ with archived_strategy(config, broken) as (replay, source):
+ strategy = StrategyResolver.load_strategy(replay)
+ self.assertEqual(
+ Path(strategy.__file__).resolve(), (current / STRATEGY_SOURCE.name).resolve()
+ )
+ with self.assertRaisesRegex(ValueError, re.escape(source.name)):
+ strategy.ft_bot_start()
+ self.assertFalse((directory / "models").exists())
import sklearn
from datasieve.pipeline import Pipeline
from datasieve.transforms import SKLearnWrapper
-from freqtrade.enums import TRADE_MODES
+from freqtrade.enums import TRADE_MODES, RunMode
from freqtrade.exceptions import DependencyException
from freqtrade.exchange import timeframe_to_seconds
from freqtrade.freqai.base_models.BaseRegressionModel import BaseRegressionModel
_PRODUCED_PREDICTION_COLUMN = "_freqai_strategies_produced"
+def _get_native_archive_strategy_file(config: dict[str, Any]) -> Path | None:
+ """Recognize Freqtrade 2026.10's extracted archive, not a general strategy path.
+
+ The webserver uses an ft_bt_strategy temporary directory containing one
+ <archive>_<strategy>.py file. Recheck this private SDK contract on upgrades.
+ Keep both model copies identical.
+ """
+ if config.get("runmode") != RunMode.WEBSERVER:
+ return None
+ strategy_path = config.get("strategy_path")
+ strategy_name = config.get("strategy")
+ if not strategy_path or not strategy_name:
+ return None
+ directory = Path(strategy_path)
+ if not directory.name.startswith("ft_bt_strategy"):
+ return None
+ source = next(directory.glob(f"*_{strategy_name}.py"), None)
+ return source.resolve() if source is not None else None
+
+
+def _validate_archived_strategy_source(strategy: Any) -> None:
+ """Refuse native archive replay that silently resolved the current strategy."""
+ archived = _get_native_archive_strategy_file(strategy.config)
+ if archived is None:
+ return
+ actual = getattr(strategy, "__file__", None)
+ if actual is None or Path(actual).resolve() != archived:
+ raise ValueError(
+ f"Backtest replay [{strategy.config['strategy']}]: could not load archived "
+ f"strategy {archived.name!r}; refusing current strategy fallback"
+ )
+
+
def _legacy_produced_prediction_mask(frame: pd.DataFrame) -> NDArray[np.bool_]:
"""Bootstrap has status 0; only nonzero, nonexpired statuses prove legacy production."""
if "do_predict" not in frame:
return copy.deepcopy(self._optuna_label_candle_pool_full_cache[cache_key])
def __init__(self, config: dict[str, Any], *args, **kwargs):
+ if archived := _get_native_archive_strategy_file(config):
+ raise ValueError(
+ f"Backtest replay [{config['strategy']}]: {archived.name!r} does not preserve "
+ "QuickAdapter helper modules; archived replay is unsupported. "
+ "Use current-strategy charts with the intended project revision instead"
+ )
migrate_config(config, logger)
normalize_fit_live_predictions_config(config, logger)
super().__init__(config, *args, **kwargs)
drawer.__dict__["return_null_values_to_strategy"] = MethodType(null, drawer)
def start(self, dataframe: pd.DataFrame, metadata: dict, strategy: Any) -> pd.DataFrame:
+ _validate_archived_strategy_source(strategy)
result = super().start(dataframe, metadata, strategy)
if "prediction_available" not in result:
result = self._normalise_prediction_returns(result)
--- /dev/null
+"""Real Freqtrade archives shared by the strategy replay regressions."""
+
+from collections.abc import Iterator
+from contextlib import contextmanager
+from copy import deepcopy
+from pathlib import Path
+from typing import Any
+
+from freqtrade.data import btanalysis
+from freqtrade.enums import RunMode
+from freqtrade.optimize.optimize_reports import store_backtest_results
+
+HAS_ARCHIVED_STRATEGY_REPLAY = hasattr(btanalysis, "backtest_strategy_dir")
+
+
+@contextmanager
+def archived_strategy(
+ config: dict[str, Any], source: Path
+) -> Iterator[tuple[dict[str, Any], Path]]:
+ """Export and extract the main source exactly as native backtesting does."""
+ name = config["strategy"]
+ output = config["user_data_dir"] / "backtest_results"
+ output.mkdir(parents=True, exist_ok=True)
+ metadata = {
+ "run_id": "archive-replay-regression",
+ "backtest_start_time": 1761955200,
+ "backtest_start_ts": 1761955200,
+ "backtest_end_ts": 1762041600,
+ "timeframe": config["timeframe"],
+ }
+ archive = store_backtest_results(
+ {"exportdirectory": output, "original_config": config},
+ {"metadata": {name: metadata}, "strategy": {}, "strategy_comparison": []},
+ "2026-10-31_00-00-00",
+ strategy_files={name: str(source)},
+ )
+ with btanalysis.backtest_strategy_dir(archive, name) as directory:
+ replay = deepcopy(config)
+ replay["runmode"] = RunMode.WEBSERVER
+ replay["strategy_path"] = str(directory)
+ replay["timerange"] = f"{metadata['backtest_start_ts']}-{metadata['backtest_end_ts']}"
+ yield replay, directory / f"{archive.stem}_{name}.py"
repositories / freqai-strategies.git / commitdiff
