Report unnecessary pragma: no cover comments (#1666)

samuelcolvin · web-flow · commit 7364f0074ab6 · 2025-05-09T15:39:36.000+02:00
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -223,6 +223,7 @@ jobs:
 
       - run: uv run coverage report --fail-under 95
       - run: uv run diff-cover coverage.xml --fail-under 100
+      - run: uv run tests/wrong_coverage.py
 
   test-mcp-run-python:
     runs-on: ubuntu-latest
diff --git a/pydantic_ai_slim/pydantic_ai/exceptions.py b/pydantic_ai_slim/pydantic_ai/exceptions.py
@@ -3,9 +3,9 @@
 import json
 import sys
 
-if sys.version_info < (3, 11):  # pragma: no cover
+if sys.version_info < (3, 11):
     from exceptiongroup import ExceptionGroup
-else:  # pragma: no cover
+else:
     ExceptionGroup = ExceptionGroup
 
 __all__ = (
diff --git a/pydantic_ai_slim/pydantic_ai/messages.py b/pydantic_ai_slim/pydantic_ai/messages.py
@@ -81,7 +81,7 @@ class VideoUrl:
     """Type identifier, this is available on all parts as a discriminator."""
 
     @property
-    def media_type(self) -> VideoMediaType:  # pragma: no cover
+    def media_type(self) -> VideoMediaType:  # pragma: lax no cover
         """Return the media type of the video, based on the url."""
         if self.url.endswith('.mkv'):
             return 'video/x-matroska'
diff --git a/pydantic_ai_slim/pydantic_ai/models/_json_schema.py b/pydantic_ai_slim/pydantic_ai/models/_json_schema.py
@@ -99,7 +99,7 @@ def _handle_object(self, schema: JsonSchema) -> JsonSchema:
         if (additional_properties := schema.get('additionalProperties')) is not None:
             if isinstance(additional_properties, bool):
                 schema['additionalProperties'] = additional_properties
-            else:  # pragma: no cover
+            else:
                 schema['additionalProperties'] = self._handle(additional_properties)
 
         if (pattern_properties := schema.get('patternProperties')) is not None:
diff --git a/pydantic_ai_slim/pydantic_ai/models/function.py b/pydantic_ai_slim/pydantic_ai/models/function.py
@@ -282,7 +282,7 @@ def _estimate_string_tokens(content: str | Sequence[UserContent]) -> int:
         return 0
     if isinstance(content, str):
         return len(re.split(r'[\s",.:]+', content.strip()))
-    else:  # pragma: no cover
+    else:
         tokens = 0
         for part in content:
             if isinstance(part, str):
diff --git a/pydantic_ai_slim/pydantic_ai/models/gemini.py b/pydantic_ai_slim/pydantic_ai/models/gemini.py
@@ -805,7 +805,7 @@ def transform(self, schema: JsonSchema) -> JsonSchema:
         additional_properties = schema.pop(
             'additionalProperties', None
         )  # don't pop yet so it's included in the warning
-        if additional_properties:  # pragma: no cover
+        if additional_properties:
             original_schema = {**schema, 'additionalProperties': additional_properties}
             warnings.warn(
                 '`additionalProperties` is not supported by Gemini; it will be removed from the tool JSON schema.'
diff --git a/pydantic_ai_slim/pydantic_ai/models/openai.py b/pydantic_ai_slim/pydantic_ai/models/openai.py
@@ -770,7 +770,7 @@ async def _map_user_prompt(part: UserPromptPart) -> responses.EasyInputMessagePa
                             file_data=f'data:{item.media_type};base64,{base64_encoded}',
                         )
                     )
-                elif isinstance(item, DocumentUrl):  # pragma: no cover
+                elif isinstance(item, DocumentUrl):
                     client = cached_async_http_client()
                     response = await client.get(item.url)
                     response.raise_for_status()
diff --git a/pydantic_ai_slim/pydantic_ai/providers/__init__.py b/pydantic_ai_slim/pydantic_ai/providers/__init__.py
@@ -65,7 +65,7 @@ def infer_provider(provider: str) -> Provider[Any]:
 
         return GoogleGLAProvider()
     # NOTE: We don't test because there are many ways the `boto3.client` can retrieve the credentials.
-    elif provider == 'bedrock':  # pragma: no cover
+    elif provider == 'bedrock':
         from .bedrock import BedrockProvider
 
         return BedrockProvider()
diff --git a/pydantic_ai_slim/pydantic_ai/providers/azure.py b/pydantic_ai_slim/pydantic_ai/providers/azure.py
@@ -82,7 +82,7 @@ def __init__(
             self._client = openai_client
         else:
             azure_endpoint = azure_endpoint or os.getenv('AZURE_OPENAI_ENDPOINT')
-            if not azure_endpoint:  # pragma: no cover
+            if not azure_endpoint:
                 raise UserError(
                     'Must provide one of the `azure_endpoint` argument or the `AZURE_OPENAI_ENDPOINT` environment variable'
                 )
diff --git a/pydantic_evals/pydantic_evals/dataset.py b/pydantic_evals/pydantic_evals/dataset.py
@@ -42,15 +42,15 @@
 from .otel._context_subtree import context_subtree
 from .reporting import EvaluationReport, ReportCase
 
-if sys.version_info < (3, 11):  # pragma: no cover
+if sys.version_info < (3, 11):
     from exceptiongroup import ExceptionGroup
 else:
     ExceptionGroup = ExceptionGroup
 
 # while waiting for https://github.com/pydantic/logfire/issues/745
 try:
     import logfire._internal.stack_info
-except ImportError:  # pragma: no cover
+except ImportError:
     pass
 else:
     from pathlib import Path
@@ -296,7 +296,7 @@ async def _handle_case(case: Case[InputsT, OutputT, MetadataT], report_case_name
 
     def evaluate_sync(
         self, task: Callable[[InputsT], Awaitable[OutputT]], name: str | None = None, max_concurrency: int | None = None
-    ) -> EvaluationReport:  # pragma: no cover
+    ) -> EvaluationReport:
         """Evaluates the test cases in the dataset using the given task.
 
         This is a synchronous wrapper around [`evaluate`][pydantic_evals.Dataset.evaluate] provided for convenience.
diff --git a/pydantic_evals/pydantic_evals/generation.py b/pydantic_evals/pydantic_evals/generation.py
@@ -37,7 +37,7 @@ async def generate_dataset(
     model: models.Model | models.KnownModelName = 'openai:gpt-4o',
     n_examples: int = 3,
     extra_instructions: str | None = None,
-) -> Dataset[InputsT, OutputT, MetadataT]:  # pragma: no cover
+) -> Dataset[InputsT, OutputT, MetadataT]:
     """Use an LLM to generate a dataset of test cases, each consisting of input, expected output, and metadata.
 
     This function creates a properly structured dataset with the specified input, output, and metadata types.
diff --git a/pydantic_evals/pydantic_evals/otel/_context_subtree.py b/pydantic_evals/pydantic_evals/otel/_context_subtree.py
@@ -8,7 +8,7 @@
 
 try:
     from ._context_in_memory_span_exporter import context_subtree
-except ImportError as e:  # pragma: no cover
+except ImportError as e:
     _IMPORT_ERROR = e
 
     @contextmanager
diff --git a/pyproject.toml b/pyproject.toml
@@ -215,7 +215,10 @@ show_missing = true
 ignore_errors = true
 precision = 2
 exclude_lines = [
+    # `# pragma: no cover` si standard marker for code that's not covered, this will error if code is covered
     'pragma: no cover',
+    # use `# pragma: lax no cover` if you want to ignore covered and ignore cases where (some of) the code is covered
+    'pragma: lax no cover',
     'raise NotImplementedError',
     'if TYPE_CHECKING:',
     'if typing.TYPE_CHECKING:',
diff --git a/tests/conftest.py b/tests/conftest.py
@@ -59,7 +59,7 @@ def set(self, name: str, value: str) -> None:
     def remove(self, name: str) -> None:
         self.envars[name] = os.environ.pop(name, None)
 
-    def reset(self) -> None:  # pragma: no cover
+    def reset(self) -> None:
         for name, value in self.envars.items():
             if value is None:
                 os.environ.pop(name, None)
@@ -100,7 +100,7 @@ def create_client(handler: Callable[[httpx.Request], httpx.Response]) -> httpx.A
     try:
         yield create_client
     finally:
-        if client:  # pragma: no cover
+        if client:
             await client.aclose()
 
 
@@ -155,7 +155,7 @@ def run(
 
 
 @contextmanager
-def try_import() -> Iterator[Callable[[], bool]]:  # pragma: no cover
+def try_import() -> Iterator[Callable[[], bool]]:
     import_success = False
 
     def check_import() -> bool:
@@ -276,7 +276,7 @@ def mistral_api_key() -> str:
 
 
 @pytest.fixture(scope='session')
-def bedrock_provider():  # pragma: no cover
+def bedrock_provider():
     try:
         import boto3
 
@@ -304,7 +304,7 @@ def model(
     co_api_key: str,
     gemini_api_key: str,
     bedrock_provider: BedrockProvider,
-) -> Model:  # pragma: no cover
+) -> Model:  # pragma: lax no cover
     try:
         if request.param == 'openai':
             from pydantic_ai.models.openai import OpenAIModel
diff --git a/tests/evals/test_evaluator_common.py b/tests/evals/test_evaluator_common.py
@@ -40,7 +40,7 @@ def __init__(self, output: Any = None, expected_output: Any = None, inputs: Any
             self.expected_output = expected_output
             self.inputs = inputs
             self.duration = duration
-else:  # pragma: no cover
+else:
     MockContext = object
 
 
diff --git a/tests/evals/test_otel.py b/tests/evals/test_otel.py
@@ -879,7 +879,7 @@ async def test_context_subtree_invalid_tracer_provider(mocker: MockerFixture):
 
     mocker.patch('pydantic_evals.otel._context_in_memory_span_exporter.get_tracer_provider', return_value=None)
     with pytest.raises(TypeError) as exc_info:
-        with context_subtree():  # pragma: no cover
+        with context_subtree():
             pass
     assert str(exc_info.value) == snapshot(
         "Expected `tracer_provider` to have an `add_span_processor` method; got an instance of <class 'NoneType'>. For help resolving this, please create an issue at https://github.com/pydantic/pydantic-ai/issues."
diff --git a/tests/graph/test_mermaid.py b/tests/graph/test_mermaid.py
@@ -259,7 +259,7 @@ def create_client(handler: Callable[[httpx.Request], httpx.Response]) -> httpx.C
     try:
         yield create_client
     finally:
-        if client:  # pragma: no cover
+        if client:
             client.close()
 
 
diff --git a/tests/models/test_bedrock.py b/tests/models/test_bedrock.py
@@ -358,7 +358,7 @@ async def get_temperature(city: str) -> str:
         Args:
             city: The city name.
         """
-        return '30°C'  # pragma: no cover
+        return '30°C'
 
     event_parts: list[Any] = []
     async with agent.iter(user_prompt='What is the temperature of the capital of France?') as agent_run:
diff --git a/tests/models/test_cohere.py b/tests/models/test_cohere.py
@@ -66,9 +66,7 @@ class MockAsyncClientV2:
     def create_mock(cls, completions: MockChatResponse | Sequence[MockChatResponse]) -> AsyncClientV2:
         return cast(AsyncClientV2, cls(completions=completions))
 
-    async def chat(  # pragma: no cover
-        self, *_args: Any, **_kwargs: Any
-    ) -> ChatResponse:
+    async def chat(self, *_args: Any, **_kwargs: Any) -> ChatResponse:
         assert self.completions is not None
         if isinstance(self.completions, Sequence):
             raise_if_exception(self.completions[self.index])
diff --git a/tests/models/test_gemini.py b/tests/models/test_gemini.py
@@ -420,7 +420,7 @@ def handler(request: httpx.Request) -> httpx.Response:
 
 def gemini_response(content: _GeminiContent, finish_reason: Literal['STOP'] | None = 'STOP') -> _GeminiResponse:
     candidate = _GeminiCandidates(content=content, index=0, safety_ratings=[])
-    if finish_reason:  # pragma: no cover
+    if finish_reason:
         candidate['finish_reason'] = finish_reason
     return _GeminiResponse(candidates=[candidate], usage_metadata=example_usage(), model_version='gemini-1.5-flash-123')
 
diff --git a/tests/models/test_groq.py b/tests/models/test_groq.py
@@ -489,7 +489,7 @@ async def test_no_content(allow_model_requests: None):
 
     with pytest.raises(UnexpectedModelBehavior, match='Received empty model response'):
         async with agent.run_stream(''):
-            pass  # pragma: no cover
+            pass
 
 
 async def test_no_delta(allow_model_requests: None):
diff --git a/tests/models/test_mistral.py b/tests/models/test_mistral.py
@@ -92,7 +92,7 @@ def create_stream_mock(
     ) -> Mistral:
         return cast(Mistral, cls(stream=completions_streams))
 
-    async def chat_completions_create(  # pragma: no cover
+    async def chat_completions_create(  # pragma: lax no cover
         self, *_args: Any, stream: bool = False, **_kwargs: Any
     ) -> MistralChatCompletionResponse | MockAsyncStream[MockCompletionEvent]:
         if stream or self.stream:
diff --git a/tests/models/test_model_function.py b/tests/models/test_model_function.py
@@ -92,7 +92,7 @@ def test_simple():
     )
 
 
-async def weather_model(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:  # pragma: no cover
+async def weather_model(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:  # pragma: lax no cover
     assert info.allow_text_output
     assert {t.name for t in info.function_tools} == {'get_location', 'get_weather'}
     last = messages[-1].parts[-1]
@@ -194,7 +194,7 @@ def test_weather():
     assert result.output == 'Sunny in Ipswich'
 
 
-async def call_function_model(messages: list[ModelMessage], _: AgentInfo) -> ModelResponse:  # pragma: no cover
+async def call_function_model(messages: list[ModelMessage], _: AgentInfo) -> ModelResponse:  # pragma: lax no cover
     last = messages[-1].parts[-1]
     if isinstance(last, UserPromptPart):
         if isinstance(last.content, str) and last.content.startswith('{'):
diff --git a/tests/models/test_openai.py b/tests/models/test_openai.py
@@ -99,7 +99,7 @@ def create_mock_stream(
     ) -> AsyncOpenAI:
         return cast(AsyncOpenAI, cls(stream=stream))
 
-    async def chat_completions_create(  # pragma: no cover
+    async def chat_completions_create(  # pragma: lax no cover
         self, *_args: Any, stream: bool = False, **kwargs: Any
     ) -> chat.ChatCompletion | MockAsyncStream[MockChatCompletionChunk]:
         self.chat_completion_kwargs.append({k: v for k, v in kwargs.items() if v is not NOT_GIVEN})
@@ -519,7 +519,7 @@ async def test_no_content(allow_model_requests: None):
 
     with pytest.raises(UnexpectedModelBehavior, match='Received empty model response'):
         async with agent.run_stream(''):
-            pass  # pragma: no cover
+            pass
 
 
 async def test_no_delta(allow_model_requests: None):
diff --git a/tests/models/test_openai_responses.py b/tests/models/test_openai_responses.py
@@ -68,7 +68,7 @@ class MyOutput(TypedDict):
 
     agent = Agent(model=model, output_type=MyOutput)
     result = await agent.run('Give me the name and age of Brazil, Argentina, and Chile.')
-    assert result.output == snapshot({'name': 'Brazil', 'age': 2023})  # pragma: no cover
+    assert result.output == snapshot({'name': 'Brazil', 'age': 2023})
 
 
 async def test_openai_responses_reasoning_effort(allow_model_requests: None, openai_api_key: str):
diff --git a/tests/providers/test_google_vertex.py b/tests/providers/test_google_vertex.py
@@ -147,7 +147,7 @@ def save_service_account(service_account_path: Path, project_id: str) -> None:
 def vertex_provider_auth(mocker: MockerFixture) -> None:
     # Locally, we authenticate via `gcloud` CLI, so we don't need to patch anything.
     if not os.getenv('CI'):
-        return  # pragma: no cover
+        return  # pragma: lax no cover
 
     @dataclass
     class NoOpCredentials:
diff --git a/tests/providers/test_provider_names.py b/tests/providers/test_provider_names.py
@@ -37,7 +37,7 @@
     ]
 
 if not imports_successful():
-    test_infer_provider_params = []  # pragma: no cover
+    test_infer_provider_params = []
 
 pytestmark = pytest.mark.skipif(not imports_successful(), reason='need to install all extra packages')
 
diff --git a/tests/test_examples.py b/tests/test_examples.py
@@ -107,7 +107,7 @@ def test_docs_examples(  # noqa: C901
 
     class CustomEvaluationReport(EvaluationReport):
         def print(self, *args: Any, **kwargs: Any) -> None:
-            if 'width' in kwargs:  # pragma: no cover
+            if 'width' in kwargs:  # pragma: lax no cover
                 raise ValueError('width should not be passed to CustomEvaluationReport')
             table = self.console_table(*args, **kwargs)
             io_file = StringIO()
@@ -181,7 +181,7 @@ def print(self, *args: Any, **kwargs: Any) -> None:
 
     if not opt_lint.startswith('skip'):
         # ruff and seem to black disagree here, not sure if that's easily fixable
-        if eval_example.update_examples:  # pragma: no cover
+        if eval_example.update_examples:  # pragma: lax no cover
             eval_example.format_ruff(example)
         else:
             eval_example.lint_ruff(example)
@@ -192,7 +192,7 @@ def print(self, *args: Any, **kwargs: Any) -> None:
         test_globals: dict[str, str] = {}
         if opt_title == 'mcp_client.py':
             test_globals['__name__'] = '__test__'
-        if eval_example.update_examples:  # pragma: no cover
+        if eval_example.update_examples:  # pragma: lax no cover
             module_dict = eval_example.run_print_update(example, call=call_name, module_globals=test_globals)
         else:
             module_dict = eval_example.run_print_check(example, call=call_name, module_globals=test_globals)
@@ -241,7 +241,7 @@ def rich_prompt_ask(prompt: str, *_args: Any, **_kwargs: Any) -> str:
         return 'Vichy'
     elif prompt == 'what is 1 + 1?':
         return '2'
-    else:  # pragma: no cover
+    else:
         raise ValueError(f'Unexpected prompt: {prompt}')
 
 
@@ -404,7 +404,9 @@ async def list_tools() -> list[None]:
 }
 
 
-async def model_logic(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:  # pragma: no cover  # noqa: C901
+async def model_logic(  # noqa: C901
+    messages: list[ModelMessage], info: AgentInfo
+) -> ModelResponse:  # pragma: lax no cover
     m = messages[-1].parts[-1]
     if isinstance(m, UserPromptPart):
         if isinstance(m.content, list) and m.content[0] == 'This is file d9a13f:':
@@ -580,7 +582,7 @@ async def model_logic(messages: list[ModelMessage], info: AgentInfo) -> ModelRes
 
 async def stream_model_logic(  # noqa C901
     messages: list[ModelMessage], info: AgentInfo
-) -> AsyncIterator[str | DeltaToolCalls]:  # pragma: no cover
+) -> AsyncIterator[str | DeltaToolCalls]:  # pragma: lax no cover
     async def stream_text_response(r: str) -> AsyncIterator[str]:
         if isinstance(r, str):
             words = r.split(' ')
@@ -638,7 +640,7 @@ def mock_infer_model(model: Model | KnownModelName) -> Model:
     if isinstance(model, FallbackModel):
         # When a fallback model is encountered, replace any OpenAIModel with a model that will raise a ModelHTTPError.
         # Otherwise, do the usual inference.
-        def raise_http_error(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:  # pragma: no cover
+        def raise_http_error(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
             raise ModelHTTPError(401, 'Invalid API Key')
 
         mock_fallback_models: list[Model] = []
diff --git a/tests/test_streaming.py b/tests/test_streaming.py
diff --git a/tests/wrong_coverage.py b/tests/wrong_coverage.py

Original file line number	Diff line number	Diff line change
`@@ -770,7 +770,7 @@ async def _map_user_prompt(part: UserPromptPart) -> responses.EasyInputMessagePa`
`770`	`770`	`file_data=f'data:{item.media_type};base64,{base64_encoded}',`
`771`	`771`	`)`
`772`	`772`	`)`
`773`		`- elif isinstance(item, DocumentUrl): # pragma: no cover`
	`773`	`+ elif isinstance(item, DocumentUrl):`
`774`	`774`	`client = cached_async_http_client()`
`775`	`775`	`response = await client.get(item.url)`
`776`	`776`	`response.raise_for_status()`
Original file line number	Diff line number	Diff line change
`@@ -82,7 +82,7 @@ def __init__(`
`82`	`82`	`self._client = openai_client`
`83`	`83`	`else:`
`84`	`84`	`azure_endpoint = azure_endpoint or os.getenv('AZURE_OPENAI_ENDPOINT')`
`85`		`- if not azure_endpoint: # pragma: no cover`
	`85`	`+ if not azure_endpoint:`
`86`	`86`	`raise UserError(`
`87`	`87`	'Must provide one of the `azure_endpoint` argument or the `AZURE_OPENAI_ENDPOINT` environment variable'
`88`	`88`	`)`