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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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": 26,
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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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"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[Unknown, Unknown]\"\n \"VecEnv\" is not assignable to \"VecMonitor\"\n \"VecEnv\" is not assignable to \"SubprocVecEnv\"\n \"VecEnv\" is not assignable to \"Env[Unknown, Unknown]\"",
"rule": "reportAttributeAccessIssue",
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"message": "Cannot assign to attribute \"eval_env\" for class \"ReforceXY*\"\n Expression of type \"VecEnv\" cannot be assigned to attribute \"eval_env\" of class \"ReforceXY\"\n Type \"VecEnv\" is not assignable to type \"VecMonitor | SubprocVecEnv | Env[Unknown, Unknown]\"\n \"VecEnv\" is not assignable to \"VecMonitor\"\n \"VecEnv\" is not assignable to \"SubprocVecEnv\"\n \"VecEnv\" is not assignable to \"Env[Unknown, Unknown]\"",
"rule": "reportAttributeAccessIssue",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"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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"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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"startCharacter": 52,
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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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"startCharacter": 50,
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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",
"severity": "error",
"startCharacter": 52,
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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",
"severity": "error",
"startCharacter": 55,
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},
{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"VecMonitor | SubprocVecEnv | Env[Unknown, Unknown]\" cannot be assigned to parameter \"eval_env\" of type \"BaseEnvironment\" in function \"get_callbacks\"\n Type \"VecMonitor | SubprocVecEnv | Env[Unknown, Unknown]\" is not assignable to type \"BaseEnvironment\"\n \"SubprocVecEnv\" is not assignable to \"BaseEnvironment\"",
"rule": "reportArgumentType",
"severity": "error",
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"NDArray[float32]\" cannot be assigned to parameter \"x\" of type \"float32\" in function \"append\"\n \"ndarray[_AnyShape, dtype[float32]]\" is not assignable to \"floating[_32Bit]\"",
"rule": "reportArgumentType",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"best_trial_params\" is possibly unbound",
"rule": "reportPossiblyUnboundVariable",
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"startCharacter": 15,
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{
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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",
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{
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"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[Unknown, Unknown]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Unknown, Unknown]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Unknown, Unknown]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 38,
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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[Unknown, Unknown]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Unknown, Unknown]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Unknown, Unknown]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 36,
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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[Unknown, Unknown]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Unknown, Unknown]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Unknown, Unknown]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 37,
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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[Unknown, Unknown]]\" in function \"__init__\"\n \"list[() -> BaseEnvironment]\" is not assignable to \"list[() -> Env[Unknown, Unknown]]\"\n Type parameter \"_T@list\" is invariant, but \"() -> BaseEnvironment\" is not the same as \"() -> Env[Unknown, Unknown]\"\n Consider switching from \"list\" to \"Sequence\" which is covariant",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 35,
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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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{
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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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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"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",
"severity": "error",
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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",
"severity": "error",
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{
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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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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Argument of type \"VecEnv\" cannot be assigned to parameter \"eval_env\" of type \"BaseEnvironment\" in function \"get_callbacks\"\n \"VecEnv\" is not assignable to \"BaseEnvironment\"",
"rule": "reportArgumentType",
"severity": "error",
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{
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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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"startCharacter": 37,
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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",
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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[Unknown, Unknown]\"\n \"None\" is not assignable to \"VecMonitor\"\n \"None\" is not assignable to \"SubprocVecEnv\"\n \"None\" is not assignable to \"Env[Unknown, Unknown]\"",
"rule": "reportAttributeAccessIssue",
"severity": "error",
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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[Unknown, Unknown]\"\n \"None\" is not assignable to \"VecMonitor\"\n \"None\" is not assignable to \"SubprocVecEnv\"\n \"None\" is not assignable to \"Env[Unknown, Unknown]\"",
"rule": "reportAttributeAccessIssue",
"severity": "error",
"startCharacter": 32,
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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",
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"startCharacter": 0,
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "Declaration \"_last_closed_position\" is obscured by a declaration of the same name",
"rule": "reportRedeclaration",
"severity": "error",
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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
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"rule": "reportRedeclaration",
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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",
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},
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"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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"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",
"severity": "error",
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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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{
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"file": "ReforceXY/user_data/freqaimodels/ReforceXY.py",
"message": "\"name\" is not a known attribute of \"None\"",
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"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"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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"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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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"message": "Argument of type \"Mapping[Unknown, Unknown]\" cannot be assigned to parameter \"src\" of type \"dict[str, Any]\" in function \"deepmerge\"\n \"Mapping[Unknown, Unknown]\" is not assignable to \"dict[str, Any]\"",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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 ...",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToInt\" in function \"__new__\"\n Type \"Any | None\" is not assignable to type \"ConvertibleToInt\"\n Type \"None\" is not assignable to type \"ConvertibleToInt\"\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 \"SupportsInt\"\n \"__int__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToInt\" in function \"__new__\"\n Type \"Any | None\" is not assignable to type \"ConvertibleToInt\"\n Type \"None\" is not assignable to type \"ConvertibleToInt\"\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 \"SupportsInt\"\n \"__int__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"",
"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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 ...",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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 ...",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToInt\" in function \"__new__\"\n Type \"Any | None\" is not assignable to type \"ConvertibleToInt\"\n Type \"None\" is not assignable to type \"ConvertibleToInt\"\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 \"SupportsInt\"\n \"__int__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"\n ...",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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 ...",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"Any | 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 ...",
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from collections.abc import Callable, Iterator, Mapping
from contextlib import contextmanager, suppress
from datetime import datetime, timezone
+from functools import wraps
+from inspect import iscoroutinefunction, unwrap
from pathlib import Path
from typing import (
Any,
VecMonitor,
)
-_DATE_PRED_DEDUP_SENTINEL = "_quickadapter_date_pred_dedup_patched"
+_DATE_PRED_DEDUP_SENTINEL = "_freqai_strategies_date_pred_repair_patched"
def _dedupe_historic_predictions_on_date_pred(frame: pd.DataFrame) -> pd.DataFrame:
- """Return ``frame`` with a unique, chronologically ordered ``date_pred``,
- keeping the most informative row per timestamp (a real prediction outranks a
- zero/NaN placeholder). ``NaT`` ``date_pred`` rows are dropped: they match no
- candle, and two or more of them break the ``validate="m:1"`` merge in
- ``attach_return_values_to_return_dataframe`` (data_drawer.py:429-431) since
- pandas treats repeated null keys as non-unique.
+ """Normalize dates and retain the latest recorded row per candle, in date order.
+
+ Freqtrade fills downtime rows with zeros/NaNs, without a candle close or a
+ prediction status. Those rows must not replace recorded predictions, including
+ zero predictions and rejected predictions (do_predict == 0 with a candle close).
+ Indistinguishable legacy rows use last-write-wins; label magnitudes never rank rows.
+ Invalid dates cannot match a candle and are discarded.
"""
- date_pred = pd.to_datetime(frame["date_pred"], utc=True, errors="coerce")
+ date_pred = pd.to_datetime(frame["date_pred"], utc=True, errors="coerce", format="mixed")
valid = date_pred.notna()
- if valid.all() and not date_pred[valid].duplicated().any():
- return frame
- work = frame.reset_index(drop=True)
- content = [column for column in work.columns if column not in ("date_pred", "date")]
- block = work[content]
- numeric = block.apply(pd.to_numeric, errors="coerce")
- is_numeric = numeric.notna()
- informative = (block.notna() & is_numeric & numeric.ne(0)) | (block.notna() & ~is_numeric)
- work = work.assign(
- _dp=date_pred.to_numpy(),
- _score=informative.sum(axis=1).to_numpy(),
- _nonnull=block.notna().sum(axis=1).to_numpy(),
- _order=work.index.to_numpy(),
+ if valid.all() and date_pred.is_monotonic_increasing and date_pred.is_unique:
+ if date_pred.dtype == frame["date_pred"].dtype:
+ return frame
+ result = frame.copy()
+ result["date_pred"] = date_pred
+ return result
+
+ recorded = np.zeros(len(frame), dtype=bool)
+ if "close_price" in frame:
+ close = pd.to_numeric(frame["close_price"], errors="coerce")
+ recorded |= (close.gt(0) & close.lt(np.inf)).fillna(False).to_numpy(dtype=bool)
+ if "do_predict" in frame:
+ status = pd.to_numeric(frame["do_predict"], errors="coerce")
+ recorded |= (status.notna() & status.ne(0)).to_numpy(dtype=bool)
+ # Rank only metadata, without copying or coercing all prediction columns.
+ order = pd.DataFrame(
+ {"date_pred": date_pred.array, "recorded": recorded, "position": np.arange(len(frame))}
)
- contested = work[valid.to_numpy()].sort_values(
- ["_dp", "_score", "_nonnull", "_order"], kind="stable"
+ kept = (
+ order.loc[valid.to_numpy()]
+ .sort_values(["date_pred", "recorded", "position"])
+ .drop_duplicates("date_pred", keep="last")
)
- kept = contested.drop_duplicates("_dp", keep="last")
- return kept.drop(columns=["_dp", "_score", "_nonnull", "_order"]).reset_index(drop=True)
+ result = frame.iloc[kept.index].copy()
+ result["date_pred"] = date_pred.iloc[kept.index].array
+ return result.reset_index(drop=True)
def _install_date_pred_dedup_patch() -> None:
- """Keep ``FreqaiDataDrawer``'s per-pair prediction store free of duplicate
- ``date_pred`` rows, which freqtrade 2026.7 does not deduplicate and its
- ``validate="m:1"`` merge (data_drawer.py:429-431) then rejects with a
- ``MergeError``. Duplicates persist across a crash or are re-created by the
- positional trim in ``set_initial_return_values`` (data_drawer.py:319-321).
-
- Re-verify the three wrapped signatures against ``data_drawer.py`` on every
- freqtrade bump.
+ """Repair persisted history and duplicates produced by older Freqtrade writers.
+
+ Normalize before upstream positional writes and after legacy duplicate writes.
+ Normalize before upstream disk repair can discard a recorded duplicate.
+ Already-clean upstream results are preserved. Recheck these synchronous
+ method contracts on Freqtrade upgrades.
"""
- if getattr(FreqaiDataDrawer, _DATE_PRED_DEDUP_SENTINEL, False):
+ names = (
+ "set_initial_return_values",
+ "append_model_predictions",
+ "attach_return_values_to_return_dataframe",
+ )
+ # Freqtrade 2026.7 has no per-frame disk-repair hook.
+ original_repair = getattr(FreqaiDataDrawer, "_repair_historic_predictions", None)
+ if original_repair is not None:
+ names += ("_repair_historic_predictions",)
+ originals = tuple(getattr(FreqaiDataDrawer, name) for name in names)
+ pending = []
+ for original in originals:
+ current = unwrap(
+ original, stop=lambda method: bool(getattr(method, _DATE_PRED_DEDUP_SENTINEL, False))
+ )
+ pending.append(not getattr(current, _DATE_PRED_DEDUP_SENTINEL, False))
+ if iscoroutinefunction(original) or iscoroutinefunction(current):
+ raise RuntimeError("FreqAI prediction repair requires synchronous drawer methods")
+ if not any(pending):
return
- original_set_initial = FreqaiDataDrawer.set_initial_return_values
- original_append = FreqaiDataDrawer.append_model_predictions
- original_attach = FreqaiDataDrawer.attach_return_values_to_return_dataframe
+ original_set_initial, original_append, original_attach = originals[:3]
+ @wraps(original_set_initial)
def set_initial_return_values(
self, pair: str, pred_df: pd.DataFrame, dataframe: pd.DataFrame
) -> None:
+ self.historic_predictions[pair] = _dedupe_historic_predictions_on_date_pred(
+ self.historic_predictions[pair]
+ )
original_set_initial(self, pair, pred_df, dataframe)
- frame = _dedupe_historic_predictions_on_date_pred(self.historic_predictions[pair])
- self.historic_predictions[pair] = frame
- self.model_return_values[pair] = frame.tail(len(dataframe.index)).reset_index(drop=True)
+ history = self.historic_predictions[pair]
+ repaired = _dedupe_historic_predictions_on_date_pred(history)
+ if repaired is not history:
+ self.historic_predictions[pair] = repaired
+ self.model_return_values[pair] = repaired.tail(len(dataframe.index)).reset_index(
+ drop=True
+ )
+ @wraps(original_append)
def append_model_predictions(
self,
pair: str,
dk: FreqaiDataKitchen,
strat_df: pd.DataFrame,
) -> None:
+ self.historic_predictions[pair] = _dedupe_historic_predictions_on_date_pred(
+ self.historic_predictions[pair]
+ )
+ if self.historic_predictions[pair].empty and not strat_df.empty:
+ # Legacy append requires an initialized row; let upstream construct it.
+ original_set_initial(self, pair, pd.DataFrame(index=pd.RangeIndex(1)), strat_df.tail(1))
original_append(self, pair, predictions, do_preds, dk, strat_df)
- frame = _dedupe_historic_predictions_on_date_pred(self.historic_predictions[pair])
- self.historic_predictions[pair] = frame
- self.model_return_values[pair] = frame.tail(len(strat_df.index)).reset_index(drop=True)
+ history = self.historic_predictions[pair]
+ repaired = _dedupe_historic_predictions_on_date_pred(history)
+ if repaired is not history:
+ self.historic_predictions[pair] = repaired
+ self.model_return_values[pair] = repaired.tail(len(strat_df.index)).reset_index(
+ drop=True
+ )
+ @wraps(original_attach)
def attach_return_values_to_return_dataframe(
self, pair: str, dataframe: pd.DataFrame
) -> pd.DataFrame:
)
return original_attach(self, pair, dataframe)
- FreqaiDataDrawer.set_initial_return_values = set_initial_return_values
- FreqaiDataDrawer.append_model_predictions = append_model_predictions
- FreqaiDataDrawer.attach_return_values_to_return_dataframe = (
- attach_return_values_to_return_dataframe
+ replacements = (
+ set_initial_return_values,
+ append_model_predictions,
+ attach_return_values_to_return_dataframe,
)
- setattr(FreqaiDataDrawer, _DATE_PRED_DEDUP_SENTINEL, True)
+ if original_repair is not None:
+
+ @wraps(original_repair)
+ def repair_historic_predictions(self, pair: str, pair_df: pd.DataFrame) -> pd.DataFrame:
+ if "date_pred" in pair_df:
+ pair_df = _dedupe_historic_predictions_on_date_pred(pair_df)
+ return original_repair(self, pair, pair_df)
+
+ replacements += (repair_historic_predictions,)
+ for name, replacement, needed in zip(names, replacements, pending, strict=True):
+ if needed:
+ setattr(replacement, _DATE_PRED_DEDUP_SENTINEL, True)
+ setattr(FreqaiDataDrawer, name, replacement)
_install_date_pred_dedup_patch()
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"severity": "error",
"startCharacter": 23,
- "startLine": 3679
+ "startLine": 3692
},
{
"endCharacter": 9,
- "endLine": 3790,
+ "endLine": 3803,
"file": "quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py",
"message": "No overloads for \"pdist\" match the provided arguments",
"rule": "reportCallIssue",
"severity": "error",
"startCharacter": 36,
- "startLine": 3788
+ "startLine": 3801
},
{
"endCharacter": 42,
- "endLine": 3789,
+ "endLine": 3802,
"file": "quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py",
"message": "Argument of type \"str\" cannot be assigned to parameter \"metric\" of type \"_MetricFunc\" in function \"pdist\"\n Type \"str\" is not assignable to type \"_MetricFunc\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 27,
- "startLine": 3789
+ "startLine": 3802
},
{
"endCharacter": 9,
- "endLine": 3887,
+ "endLine": 3900,
"file": "quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py",
"message": "No overloads for \"cdist\" match the provided arguments",
"rule": "reportCallIssue",
"severity": "error",
"startCharacter": 15,
- "startLine": 3882
+ "startLine": 3895
},
{
"endCharacter": 34,
- "endLine": 3885,
+ "endLine": 3898,
"file": "quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py",
"message": "Argument of type \"str\" cannot be assigned to parameter \"metric\" of type \"_MetricFunc\" in function \"cdist\"\n Type \"str\" is not assignable to type \"_MetricFunc\"",
"rule": "reportArgumentType",
"severity": "error",
"startCharacter": 19,
- "startLine": 3885
+ "startLine": 3898
},
{
"endCharacter": 55,
zigzag,
)
-_DATE_PRED_DEDUP_SENTINEL = "_quickadapter_date_pred_dedup_patched"
+_DATE_PRED_DEDUP_SENTINEL = "_freqai_strategies_date_pred_repair_patched"
def _dedupe_historic_predictions_on_date_pred(frame: pd.DataFrame) -> pd.DataFrame:
Indistinguishable legacy rows use last-write-wins; label magnitudes never rank rows.
Invalid dates cannot match a candle and are discarded.
"""
- date_pred = pd.to_datetime(frame["date_pred"], utc=True, errors="coerce")
+ date_pred = pd.to_datetime(frame["date_pred"], utc=True, errors="coerce", format="mixed")
valid = date_pred.notna()
if valid.all() and date_pred.is_monotonic_increasing and date_pred.is_unique:
if date_pred.dtype == frame["date_pred"].dtype:
"""Repair persisted history and duplicates produced by older Freqtrade writers.
Normalize before upstream positional writes and after legacy duplicate writes.
- Already-clean upstream results are preserved. Recheck the three synchronous
+ Normalize before upstream disk repair can discard a recorded duplicate.
+ Already-clean upstream results are preserved. Recheck these synchronous
method contracts on Freqtrade upgrades.
"""
- originals = (
- FreqaiDataDrawer.set_initial_return_values,
- FreqaiDataDrawer.append_model_predictions,
- FreqaiDataDrawer.attach_return_values_to_return_dataframe,
+ names = (
+ "set_initial_return_values",
+ "append_model_predictions",
+ "attach_return_values_to_return_dataframe",
)
+ # Freqtrade 2026.7 has no per-frame disk-repair hook.
+ original_repair = getattr(FreqaiDataDrawer, "_repair_historic_predictions", None)
+ if original_repair is not None:
+ names += ("_repair_historic_predictions",)
+ originals = tuple(getattr(FreqaiDataDrawer, name) for name in names)
pending = []
for original in originals:
current = unwrap(
original, stop=lambda method: bool(getattr(method, _DATE_PRED_DEDUP_SENTINEL, False))
)
pending.append(not getattr(current, _DATE_PRED_DEDUP_SENTINEL, False))
- if iscoroutinefunction(current):
- raise RuntimeError("QuickAdapter prediction repair requires synchronous drawer methods")
+ if iscoroutinefunction(original) or iscoroutinefunction(current):
+ raise RuntimeError("FreqAI prediction repair requires synchronous drawer methods")
if not any(pending):
return
- original_set_initial, original_append, original_attach = originals
+ original_set_initial, original_append, original_attach = originals[:3]
@wraps(original_set_initial)
def set_initial_return_values(
self.historic_predictions[pair] = _dedupe_historic_predictions_on_date_pred(
self.historic_predictions[pair]
)
+ if self.historic_predictions[pair].empty and not strat_df.empty:
+ # Legacy append requires an initialized row; let upstream construct it.
+ original_set_initial(self, pair, pd.DataFrame(index=pd.RangeIndex(1)), strat_df.tail(1))
original_append(self, pair, predictions, do_preds, dk, strat_df)
history = self.historic_predictions[pair]
repaired = _dedupe_historic_predictions_on_date_pred(history)
append_model_predictions,
attach_return_values_to_return_dataframe,
)
- names = (
- "set_initial_return_values",
- "append_model_predictions",
- "attach_return_values_to_return_dataframe",
- )
+ if original_repair is not None:
+
+ @wraps(original_repair)
+ def repair_historic_predictions(self, pair: str, pair_df: pd.DataFrame) -> pd.DataFrame:
+ if "date_pred" in pair_df:
+ pair_df = _dedupe_historic_predictions_on_date_pred(pair_df)
+ return original_repair(self, pair, pair_df)
+
+ replacements += (repair_historic_predictions,)
for name, replacement, needed in zip(names, replacements, pending, strict=True):
if needed:
setattr(replacement, _DATE_PRED_DEDUP_SENTINEL, True)
current = unwrap(
original, stop=lambda method: bool(getattr(method, _RPC_CUSTOM_DATA_SENTINEL, False))
)
+ if iscoroutinefunction(original) or iscoroutinefunction(current):
+ raise RuntimeError("QuickAdapter RPC cleanup requires a synchronous annotation RPC")
if getattr(current, _RPC_CUSTOM_DATA_SENTINEL, False):
return
- if iscoroutinefunction(current):
- raise RuntimeError("QuickAdapter RPC cleanup requires a synchronous annotation RPC")
@wraps(original)
def analysed_dataframe(self, *args, **kwargs):
repositories / freqai-strategies.git / commitdiff
