🔧 Add FastAPI Agents Skill

[skip ci]

.github/workflows/test.yml

@@ -208,4 +208,4 @@ jobs:
         uses: re-actors/alls-green@release/v1
         with:
           jobs: ${{ toJSON(needs) }}
-          allowed-skips: coverage-combine,test
+          allowed-skips: coverage-combine,test,benchmark

docs/en/docs/release-notes.md

@@ -7,6 +7,11 @@ hide:
 
 ## Latest Changes
 
+### Internal
+
+* 👥 Update FastAPI People - Experts. PR [#14972](https://github.com/fastapi/fastapi/pull/14972) by [@tiangolo](https://github.com/tiangolo).
+* 👷 Allow skipping `benchmark` job in `test` workflow. PR [#14974](https://github.com/fastapi/fastapi/pull/14974) by [@YuriiMotov](https://github.com/YuriiMotov).
+
 ## 0.132.0
 
 ### Breaking Changes

fastapi/.agents/skills/fastapi/SKILL.md

@@ -0,0 +1,640 @@
+---
+name: fastapi
+description: FastAPI best practices and conventions. Use when working with FastAPI APIs and Pydantic models for them. Keeps FastAPI code clean and up to date with the latest features and patterns, updated with new versions. Write new code or refactor and update old code.
+---
+
+# FastAPI
+
+Official FastAPI skill to write code with best practices, keeping up to date with new versions and features.
+
+## Use the `fastapi` CLI
+
+To run the development server, in localhost, with reload:
+
+```bash
+fastapi dev
+```
+
+
+And to run the production server:
+
+```bash
+fastapi run
+```
+
+### Add an entrypoint in `pyproject.toml`
+
+FastAPI CLI will read the entrypoint in `pyproject.toml` to know where the FastAPI app is declared.
+
+```toml
+[tool.fastapi]
+entrypoint = "my_app.main:app"
+```
+
+This way the same command can be used without having to pass a path every time.
+
+### Use `fastapi` with a path
+
+When adding the entrypoint to `pyproject.toml` is not possible, or the user explicitly asks not to, or it's running an independent small app, you can pass the path to the file to the `fastapi` command:
+
+```bash
+fastapi dev my_app/main.py
+```
+
+## Use `Annotated`
+
+Always prefer the `Annotated` style for parameter and dependency declarations.
+
+It keeps the function signatures working in other contexts, respects the types, allows reusability.
+
+### In Parameter Declarations
+
+Use `Annotated` for parameter declarations, including `Path`, `Query`, `Header`, etc.:
+
+```python
+from typing import Annotated
+
+from fastapi import FastAPI, Path, Query
+
+app = FastAPI()
+
+
+@app.get("/items/{item_id}")
+async def read_item(
+    item_id: Annotated[int, Path(ge=1, description="The item ID")],
+    q: Annotated[str | None, Query(max_length=50)] = None,
+):
+    return {"message": "Hello World"}
+```
+
+instead of:
+
+```python
+# DO NOT DO THIS
+from fastapi import FastAPI, Path, Query
+
+app = FastAPI()
+
+
+@app.get("/items/{item_id}")
+async def read_item(
+    item_id: int = Path(ge=1, description="The item ID"),
+    q: str | None = Query(default=None, max_length=50),
+):
+    return {"message": "Hello World"}
+```
+
+### For Dependencies
+
+Use `Annotated` for dependencies with `Depends()`.
+
+Unless asked not to, create a new type alias for the dependency to allow re-using it.
+
+```python
+from typing import Annotated
+
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+def get_current_user():
+    return {"username": "johndoe"}
+
+
+CurrentUserDep = Annotated[dict, Depends(get_current_user)]
+
+
+@app.get("/items/")
+async def read_item(current_user: CurrentUserDep):
+    return {"message": "Hello World"}
+```
+
+instead of:
+
+```python
+# DO NOT DO THIS
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+def get_current_user():
+    return {"username": "johndoe"}
+
+
+@app.get("/items/")
+async def read_item(current_user: dict = Depends(get_current_user)):
+    return {"message": "Hello World"}
+```
+
+## Do not use Ellipsis for *path operations*
+
+Do not use `...` as a default value for required parameters.
+
+Do this, without Ellipsis (`...`):
+
+```python
+from typing import Annotated
+
+from fastapi import FastAPI, Query
+
+app = FastAPI()
+
+
+@app.get("/items/")
+async def read_item(project_id: Annotated[int, Query()]):
+    return {"message": "Hello World"}
+```
+
+instead of this:
+
+```python
+# DO NOT DO THIS
+from fastapi import FastAPI, Query
+
+app = FastAPI()
+
+
+@app.get("/items/")
+async def read_item(project_id: int = Query(...)):
+    return {"message": "Hello World"}
+```
+
+## Do not use Ellipsis for Pydantic models
+
+Do this, without Ellipsis (`...`):
+
+```python
+from fastapi import FastAPI
+from pydantic import BaseModel, Field
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str
+    description: str | None = None
+    price: float = Field(gt=0)
+
+
+@app.post("/items/")
+async def create_item(item: Item):
+    return {"message": "Hello World"}
+```
+
+instead of this:
+
+```python
+# DO NOT DO THIS
+from fastapi import FastAPI
+from pydantic import BaseModel, Field
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str = ...
+    description: str | None = None
+    price: float = Field(..., gt=0)
+
+
+@app.post("/items/")
+async def create_item(item: Item):
+    return {"message": "Hello World"}
+```
+
+## Return Type or Response Model
+
+When possible, include a return type. It will be used to validate, filter, document, and serialize the response.
+
+```python
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str
+    description: str | None = None
+
+
+@app.get("/items/me")
+async def get_item() -> Item:
+    return Item(name="Plumbus", description="All-purpose home device")
+```
+
+**Important**: Return types or response models are what filter data ensuring no sensitive information is exposed. And they are used to serialize data with Pydantic, this is the main idea that can increase response performance.
+
+The return type doesn't have to be a Pydantic model, it could be a different type, like a list of Pydantic models, or a dict, etc.
+
+### When to use `response_model` instead
+
+If the return type is not the same as the type that you want to use to validate, filter, serialize, use the `response_model` parameter on the decorator instead.
+
+```python
+from typing import Any
+
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str
+    description: str | None = None
+
+
+@app.get("/items/me", response_model=Item)
+async def get_item() -> Any:
+    return {"name": "Foo", "description": "A very nice Item"}
+```
+
+This can be in particular useful when filtering data to expose only the public fields, and avoid exposing sensitive information.
+
+```python
+from typing import Any
+
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+app = FastAPI()
+
+
+class InternalItem(BaseModel):
+    name: str
+    description: str | None = None
+    secret_key: str
+
+
+class Item(BaseModel):
+    name: str
+    description: str | None = None
+
+
+@app.get("/items/me", response_model=Item)
+async def get_item() -> Any:
+    item = InternalItem(
+        name="Foo", description="A very nice Item", secret_key="supersecret"
+    )
+    return item
+```
+
+## Performance
+
+Do not use `ORJSONResponse` or `UJSONResponse`, they are deprecated.
+
+Instead declare a return type or response model. Pydantic will handle the data serialization in the Rust side.
+
+### Including Routers
+
+When declaring routers, prefer to add router level parameters like prefix, tags, etc. to the router itself, instead of in `include_router()`.
+
+Do this:
+
+```python
+from fastapi import APIRouter, FastAPI
+
+app = FastAPI()
+
+router = APIRouter(prefix="/items", tags=["items"])
+
+
+@router.get("/")
+async def list_items():
+    return []
+
+
+# In main.py
+app.include_router(router)
+```
+
+instead of this:
+
+```python
+# DO NOT DO THIS
+from fastapi import APIRouter, FastAPI
+
+app = FastAPI()
+
+router = APIRouter()
+
+
+@router.get("/")
+async def list_items():
+    return []
+
+
+# In main.py
+app.include_router(router, prefix="/items", tags=["items"])
+```
+
+There could be exceptions but try to follow this convention.
+
+Apply shared dependencies at the router level via `dependencies=[Depends(...)]`.
+
+## Dependency Injection
+
+Use dependencies when:
+
+* They can't be declared in Pydantic validation and require additional logic
+* The logic depends on external resources or could block in any other way
+* Other dependencies need their results (it's a sub-dependency)
+* The logic can be shared by multiple endpoints to do things like error early, authentication, etc.
+* They need to handle cleanup (e.g., DB sessions, file handles), using dependencies with `yield`
+* Their logic needs request input data, like headers, query parameters, etc.
+
+### Dependencies with `yield` and `scope`
+
+When the using dependencies with `yield`, they can have a `scope` that defines when the exit code is run.
+
+Use the default scope `"request"` to run the exit code after the response is sent back.
+
+```python
+from typing import Annotated
+
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+def get_db():
+    db = DBSession()
+    try:
+        yield db
+    finally:
+        db.close()
+
+
+DBDep = Annotated[DBSession, Depends(get_db)]
+
+
+@app.get("/items/")
+async def read_items(db: DBDep):
+    return db.query(Item).all()
+```
+
+Use the scope `"function"` when they should run the exit code after the response data is generated but before the response is sent back to the client.
+
+```python
+from typing import Annotated
+
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+def get_username():
+    try:
+        yield "Rick"
+    finally:
+        print("Cleanup up before response is sent")
+
+UserNameDep = Annotated[str, Depends(get_username, scope="function")]
+
+@app.get("/users/me")
+def get_user_me(username: UserNameDep):
+    return username
+```
+
+### Class Dependencies
+
+Avoid creating class dependencies when possible.
+
+If a class is needed, instead create a regular function dependency that return a class instance.
+
+Do this:
+
+```python
+from dataclasses import dataclass
+from typing import Annotated
+
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+@dataclass
+class CommonQueryParams:
+    q: str | None = None
+    skip: int = 0
+    limit: int = 100
+
+
+def get_common_params(
+    q: str | None = None, skip: int = 0, limit: int = 100
+) -> CommonQueryParams:
+    return CommonQueryParams(q=q, skip=skip, limit=limit)
+
+
+CommonsDep = Annotated[CommonQueryParams, Depends(get_common_params)]
+
+
+@app.get("/items/")
+async def read_items(commons: CommonsDep):
+    return {"q": commons.q, "skip": commons.skip, "limit": commons.limit}
+```
+
+instead of this:
+
+```python
+# DO NOT DO THIS
+from typing import Annotated
+
+from fastapi import Depends, FastAPI
+
+app = FastAPI()
+
+
+class CommonQueryParams:
+    def __init__(self, q: str | None = None, skip: int = 0, limit: int = 100):
+        self.q = q
+        self.skip = skip
+        self.limit = limit
+
+
+@app.get("/items/")
+async def read_items(commons: Annotated[CommonQueryParams, Depends()]):
+    return {"q": commons.q, "skip": commons.skip, "limit": commons.limit}
+```
+
+## Async vs Sync *path operations*
+
+Use `async` *path operations* only when fully certain that the logic called inside is compatible with async and await (it's called with `await`) or doesn't block.
+
+```python
+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+# Use async def when calling async code
+@app.get("/async-items/")
+async def read_async_items():
+    data = await some_async_library.fetch_items()
+    return data
+
+
+# Use plain def when calling blocking/sync code or when in doubt
+@app.get("/items/")
+def read_items():
+    data = some_blocking_library.fetch_items()
+    return data
+```
+
+In case of doubt, or by default, use regular `def` functions, those will be run in a threadpool so they don't block the event loop.
+
+The same rules apply to dependencies.
+
+Make sure blocking code is not run inside of `async` functions. The logic will work, but will damage heavily the performance.
+
+### Asyncer
+
+When needing to run blocking code inside of async functions, or async code inside of blocking functions, suggest using Asyncer.
+
+Install:
+
+```bash
+uv add asyncer
+```
+
+Run blocking sync code inside of async with `asyncify()`:
+
+```python
+from asyncer import asyncify
+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+def do_blocking_work(name: str) -> str:
+    # Some blocking I/O operation
+    return f"Hello {name}"
+
+
+@app.get("/items/")
+async def read_items():
+    result = await asyncify(do_blocking_work)(name="World")
+    return {"message": result}
+```
+
+And run async code inside of blocking sync code with `syncify()`:
+
+```python
+from asyncer import syncify
+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+async def do_async_work(name: str) -> str:
+    return f"Hello {name}"
+
+
+@app.get("/items/")
+def read_items():
+    result = syncify(do_async_work)(name="World")
+    return {"message": result}
+```
+
+## Use uv
+
+If uv is available, use it to manage dependencies.
+
+## SQLModel for SQL databases
+
+When working with SQL databases, prefer using SQLModel as it is integrated with Pydantic and will allow declaring data validation with the same models.
+
+## Do not use Pydantic RootModels
+
+Do not use Pydantic `RootModel`, instead use regular type annotations with `Annotated` and Pydantic validation utilities.
+
+For example for a list with validations you could do:
+
+```python
+from typing import Annotated
+
+from fastapi import Body, FastAPI
+from pydantic import Field
+
+app = FastAPI()
+
+
+@app.post("/items/")
+async def create_items(items: Annotated[list[int], Field(min_length=1), Body()]):
+    return items
+```
+
+instead of:
+
+```python
+# DO NOT DO THIS
+from typing import Annotated
+
+from fastapi import FastAPI
+from pydantic import Field, RootModel
+
+app = FastAPI()
+
+
+class ItemList(RootModel[Annotated[list[int], Field(min_length=1)]]):
+    pass
+
+
+@app.post("/items/")
+async def create_items(items: ItemList):
+    return items
+
+```
+
+FastAPI supports these type annotations and will create a Pydantic `TypeAdapter` for them, so that types can work as normally.
+
+## Use one HTTP operation per function
+
+Don't mix HTTP operations in a single function, having one function per HTTP operation helps separate concerns and organize the code.
+
+Do this:
+
+```python
+from fastapi import FastAPI
+from pydantic import BaseModel
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str
+
+
+@app.get("/items/")
+async def list_items():
+    return []
+
+
+@app.post("/items/")
+async def create_item(item: Item):
+    return item
+```
+
+instead of this:
+
+```python
+# DO NOT DO THIS
+from fastapi import FastAPI, Request
+from pydantic import BaseModel
+
+app = FastAPI()
+
+
+class Item(BaseModel):
+    name: str
+
+
+@app.api_route("/items/", methods=["GET", "POST"])
+async def handle_items(request: Request):
+    if request.method == "GET":
+        return []
+    # ...
+```