core: Add ruff rules for PIE (langchain-ai#26939)

All auto-fixes.

libs/core/langchain_core/callbacks/streaming_stdout.py

@@ -112,7 +112,6 @@ def on_agent_action(self, action: AgentAction, **kwargs: Any) -> Any:
             action (AgentAction): The agent action.
             **kwargs (Any): Additional keyword arguments.
         """
-        pass
 
     def on_tool_end(self, output: Any, **kwargs: Any) -> None:
         """Run when tool ends running.

libs/core/langchain_core/language_models/chat_models.py

@@ -357,7 +357,7 @@ def stream(
         stop: Optional[list[str]] = None,
         **kwargs: Any,
     ) -> Iterator[BaseMessageChunk]:
-        if not self._should_stream(async_api=False, **{**kwargs, **{"stream": True}}):
+        if not self._should_stream(async_api=False, **{**kwargs, "stream": True}):
             # model doesn't implement streaming, so use default implementation
             yield cast(
                 BaseMessageChunk, self.invoke(input, config=config, stop=stop, **kwargs)
@@ -427,7 +427,7 @@ async def astream(
         stop: Optional[list[str]] = None,
         **kwargs: Any,
     ) -> AsyncIterator[BaseMessageChunk]:
-        if not self._should_stream(async_api=True, **{**kwargs, **{"stream": True}}):
+        if not self._should_stream(async_api=True, **{**kwargs, "stream": True}):
             # No async or sync stream is implemented, so fall back to ainvoke
             yield cast(
                 BaseMessageChunk,
@@ -550,7 +550,7 @@ def _get_ls_params(
 
     def _get_llm_string(self, stop: Optional[list[str]] = None, **kwargs: Any) -> str:
         if self.is_lc_serializable():
-            params = {**kwargs, **{"stop": stop}}
+            params = {**kwargs, "stop": stop}
             param_string = str(sorted(params.items()))
             # This code is not super efficient as it goes back and forth between
             # json and dict.

libs/core/langchain_core/prompts/chat.py

@@ -1007,11 +1007,9 @@ def __init__(
                 input_vars.update(_message.input_variables)
 
         kwargs = {
-            **{
-                "input_variables": sorted(input_vars),
-                "optional_variables": sorted(optional_variables),
-                "partial_variables": partial_vars,
-            },
+            "input_variables": sorted(input_vars),
+            "optional_variables": sorted(optional_variables),
+            "partial_variables": partial_vars,
             **kwargs,
         }
         cast(type[ChatPromptTemplate], super()).__init__(messages=_messages, **kwargs)

libs/core/langchain_core/runnables/config.py

@@ -36,8 +36,6 @@
 class EmptyDict(TypedDict, total=False):
     """Empty dict type."""
 
-    pass
-
 
 class RunnableConfig(TypedDict, total=False):
     """Configuration for a Runnable."""

libs/core/langchain_core/runnables/configurable.py

@@ -457,8 +457,6 @@ def _prepare(
 class StrEnum(str, enum.Enum):
     """String enum."""
 
-    pass
-
 
 _enums_for_spec: WeakValueDictionary[
     Union[

libs/core/langchain_core/runnables/fallbacks.py

@@ -619,7 +619,8 @@ def wrapped(*args: Any, **kwargs: Any) -> Any:
                 return self.__class__(
                     **{
                         **self.model_dump(),
-                        **{"runnable": new_runnable, "fallbacks": new_fallbacks},
+                        "runnable": new_runnable,
+                        "fallbacks": new_fallbacks,
                     }
                 )
 

libs/core/langchain_core/tools/base.py

@@ -320,8 +320,6 @@ class ToolException(Exception):  # noqa: N818
     to the agent as observation, and printed in red on the console.
     """
 
-    pass
-
 
 class BaseTool(RunnableSerializable[Union[str, dict, ToolCall], Any]):
     """Interface LangChain tools must implement."""

libs/core/langchain_core/tracers/base.py

@@ -850,7 +850,6 @@ async def on_retriever_end(
 
     async def _on_run_create(self, run: Run) -> None:
         """Process a run upon creation."""
-        pass
 
     async def _on_run_update(self, run: Run) -> None:
         """Process a run upon update."""

libs/core/langchain_core/tracers/event_stream.py

@@ -829,7 +829,6 @@ async def _astream_events_implementation_v1(
                 inputs = log_entry["inputs"]
                 if inputs is not None:
                     data["input"] = inputs
-                pass
 
             if event_type == "end":
                 inputs = log_entry["inputs"]

libs/core/langchain_core/utils/function_calling.py

@@ -561,7 +561,7 @@ def _parse_google_docstring(
             if block.startswith("Args:"):
                 args_block = block
                 break
-            elif block.startswith("Returns:") or block.startswith("Example:"):
+            elif block.startswith(("Returns:", "Example:")):
                 # Don't break in case Args come after
                 past_descriptors = True
             elif not past_descriptors:

libs/core/langchain_core/utils/mustache.py

@@ -32,8 +32,6 @@
 class ChevronError(SyntaxError):
     """Custom exception for Chevron errors."""
 
-    pass
-
 
 #
 # Helper functions

libs/core/langchain_core/utils/utils.py

@@ -268,8 +268,6 @@ def convert_to_secret_str(value: Union[SecretStr, str]) -> SecretStr:
 class _NoDefaultType:
     """Type to indicate no default value is provided."""
 
-    pass
-
 
 _NoDefault = _NoDefaultType()
 

libs/core/pyproject.toml

@@ -44,7 +44,7 @@ python = ">=3.12.4"
 [tool.poetry.extras]
 
 [tool.ruff.lint]
-select = [ "B", "C4", "E", "F", "I", "N", "T201", "UP",]
+select = [ "B", "C4", "E", "F", "I", "N", "PIE", "T201", "UP",]
 ignore = [ "UP007",]
 
 [tool.coverage.run]

libs/core/tests/integration_tests/test_compile.py

@@ -4,4 +4,3 @@
 @pytest.mark.compile
 def test_placeholder() -> None:
     """Used for compiling integration tests without running any real tests."""
-    pass

libs/core/tests/unit_tests/_api/test_beta_decorator.py

@@ -68,7 +68,6 @@ async def beta_async_function() -> str:
 class ClassWithBetaMethods:
     def __init__(self) -> None:
         """original doc"""
-        pass
 
     @beta()
     def beta_method(self) -> str:
@@ -244,7 +243,6 @@ def test_whole_class_beta() -> None:
     class BetaClass:
         def __init__(self) -> None:
             """original doc"""
-            pass
 
         @beta()
         def beta_method(self) -> str:

libs/core/tests/unit_tests/_api/test_deprecation.py

@@ -88,7 +88,6 @@ async def deprecated_async_function() -> str:
 class ClassWithDeprecatedMethods:
     def __init__(self) -> None:
         """original doc"""
-        pass
 
     @deprecated(since="2.0.0", removal="3.0.0")
     def deprecated_method(self) -> str:
@@ -268,7 +267,6 @@ def test_whole_class_deprecation() -> None:
     class DeprecatedClass:
         def __init__(self) -> None:
             """original doc"""
-            pass
 
         @deprecated(since="2.0.0", removal="3.0.0")
         def deprecated_method(self) -> str:
@@ -311,7 +309,6 @@ def test_whole_class_inherited_deprecation() -> None:
     class DeprecatedClass:
         def __init__(self) -> None:
             """original doc"""
-            pass
 
         @deprecated(since="2.0.0", removal="3.0.0")
         def deprecated_method(self) -> str:
@@ -324,7 +321,6 @@ class InheritedDeprecatedClass(DeprecatedClass):
 
         def __init__(self) -> None:
             """original doc"""
-            pass
 
         @deprecated(since="2.2.0", removal="3.2.0")
         def deprecated_method(self) -> str:

libs/core/tests/unit_tests/language_models/chat_models/test_base.py

@@ -107,7 +107,7 @@ def eval_response(callback: BaseFakeCallbackHandler, i: int) -> None:
         else:
             assert llm_result.generations[0][0].text == message[:i]
 
-    for i in range(0, 2):
+    for i in range(2):
         llm = FakeListChatModel(
             responses=[message],
             error_on_chunk_number=i,

libs/core/tests/unit_tests/language_models/llms/test_base.py

@@ -105,7 +105,7 @@ def eval_response(callback: BaseFakeCallbackHandler, i: int) -> None:
         else:
             assert llm_result.generations[0][0].text == message[:i]
 
-    for i in range(0, 2):
+    for i in range(2):
         llm = FakeStreamingListLLM(
             responses=[message],
             error_on_chunk_number=i,

libs/core/tests/unit_tests/test_messages.py

@@ -429,16 +429,12 @@ def test_message_chunk_to_message() -> None:
     expected = AIMessage(
         content="I am",
         tool_calls=[
-            create_tool_call(**{"name": "tool1", "args": {"a": 1}, "id": "1"}),  # type: ignore[arg-type]
-            create_tool_call(**{"name": "tool2", "args": {}, "id": "2"}),  # type: ignore[arg-type]
+            create_tool_call(name="tool1", args={"a": 1}, id="1"),  # type: ignore[arg-type]
+            create_tool_call(name="tool2", args={}, id="2"),  # type: ignore[arg-type]
         ],
         invalid_tool_calls=[
-            create_invalid_tool_call(
-                **{"name": "tool3", "args": None, "id": "3", "error": None}
-            ),
-            create_invalid_tool_call(
-                **{"name": "tool4", "args": "abc", "id": "4", "error": None}
-            ),
+            create_invalid_tool_call(name="tool3", args=None, id="3", error=None),
+            create_invalid_tool_call(name="tool4", args="abc", id="4", error=None),
         ],
     )
     assert message_chunk_to_message(chunk) == expected

libs/core/tests/unit_tests/test_tools.py

@@ -357,7 +357,6 @@ def structured_tool(
             some_base_model: SomeBaseModel, another_base_model: AnotherBaseModel
         ) -> None:
             """Return the arguments directly."""
-            pass
 
 
 def test_base_tool_inheritance_base_schema() -> None:

libs/core/tests/unit_tests/utils/test_function_calling.py

@@ -54,7 +54,6 @@ def dummy_function(
         arg2: ExtensionsAnnotated[Literal["bar", "baz"], "one of 'bar', 'baz'"],
     ) -> None:
         """dummy function"""
-        pass
 
     return dummy_function
 
@@ -68,7 +67,6 @@ def dummy_function(arg1: int, arg2: Literal["bar", "baz"]) -> None:
             arg1: foo
             arg2: one of 'bar', 'baz'
         """
-        pass
 
     return dummy_function
 
@@ -220,7 +218,6 @@ def dummy_function(self, arg1: int, arg2: Literal["bar", "baz"]) -> None:
             arg1: foo
             arg2: one of 'bar', 'baz'
         """
-        pass
 
 
 class DummyWithClassMethod:
@@ -232,7 +229,6 @@ def dummy_function(cls, arg1: int, arg2: Literal["bar", "baz"]) -> None:
             arg1: foo
             arg2: one of 'bar', 'baz'
         """
-        pass
 
 
 def test_convert_to_openai_function(
@@ -334,7 +330,6 @@ class NestedV2(BaseModelV2Maybe):
 
     def my_function(arg1: NestedV2) -> None:
         """dummy function"""
-        pass
 
     convert_to_openai_function(my_function)
 
@@ -348,7 +343,6 @@ class Nested(BaseModel):
 
     def my_function(arg1: Nested) -> None:
         """dummy function"""
-        pass
 
     expected = {
         "name": "my_function",
@@ -386,7 +380,6 @@ class Nested(BaseModel):
 
     def my_function(arg1: Nested) -> None:
         """dummy function"""
-        pass
 
     expected = {
         "name": "my_function",
@@ -429,7 +422,6 @@ def func5(
         c: Optional[list[Optional[str]]],
     ) -> None:
         """A test function"""
-        pass
 
     func = convert_to_openai_function(func5)
     req = func["parameters"]["required"]
@@ -439,7 +431,6 @@ def func5(
 def test_function_no_params() -> None:
     def nullary_function() -> None:
         """nullary function"""
-        pass
 
     func = convert_to_openai_function(nullary_function)
     req = func["parameters"].get("required")
@@ -781,7 +772,6 @@ def test_convert_union_type_py_39() -> None:
     @tool
     def magic_function(input: int | float) -> str:
         """Compute a magic function."""
-        pass
 
     result = convert_to_openai_function(magic_function)
     assert result["parameters"]["properties"]["input"] == {