271 lines
9.6 KiB
Markdown
271 lines
9.6 KiB
Markdown
## WIP: FastAPI Best Practices
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### 1. Project Structure. Group files by module domain, not file types.
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I didn't like the project structure presented by @tiangolo,
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where we separate files by their type (e.g. api, crud, models, schemas).
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Structure that I find more scalable and evolvable is inspired by Netflix's [Dispatch](https://github.com/Netflix/dispatch) with some little modifications.
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```
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fastapi-project
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├── alembic/
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├── src
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│ ├── auth
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│ │ ├── router.py
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│ │ ├── schemas.py # pydantic models
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│ │ ├── models.py # db models
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│ │ ├── dependencies.py
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│ │ ├── config.py # local configs
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│ │ ├── constants.py
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│ │ ├── exceptions.py
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│ │ ├── service.py
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│ │ └── utils.py
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│ ├── aws
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│ │ ├── client.py # client model for external service communication
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│ │ ├── schemas.py
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│ │ ├── config.py
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│ │ ├── constants.py
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│ │ ├── exceptions.py
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│ │ └── utils.py
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│ └── posts
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│ │ ├── router.py
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│ │ ├── schemas.py
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│ │ ├── models.py
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│ │ ├── dependencies.py
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│ │ ├── constants.py
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│ │ ├── exceptions.py
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│ │ ├── service.py
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│ │ └── utils.py
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│ ├── config.py # global configs
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│ ├── models.py # global models
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│ ├── exceptions.py # global exceptions
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│ ├── pagination.py # global module e.g. pagination
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│ ├── database.py # db connection related stuff
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│ └── main.py
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├── tests/
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│ ├── auth
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│ ├── aws
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│ └── posts
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├── templates/
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│ └── index.html
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├── requirements
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│ ├── base.txt
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│ ├── dev.txt
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│ └── prod.txt
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├── .env
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├── .gitignore
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├── logging.ini
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└── alembic.ini
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```
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1. Store all the module directories inside src folder
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1. `src/` - highest level of an app, contains common models, configs, and constants, etc.
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2. `src/main.py` - root of the project, which inits the FastAPI app
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2. Each module has its own router, schemas, models, etc.
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1. `router.py` - is a core of each module with all the endpoints
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2. `schemas.py` - for pydantic models
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3. `models.py` - for db models
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4. `service.py` - module specific business logic
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5. `dependencies.py` - router dependencies
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6. `constants.py` - module specific constants and error codes
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7. `config.py` - e.g. env vars
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8. `utils.py` - non-business logic functions, e.g. response normalization, data enrichment, etc.
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9. `exceptions` - module specific exceptions, e.g. `PostNotFound`, `InvalidUserData`
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### 2. Excessively use Pydantic
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Pydantic has a rich set of features to validate and transform data.
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In addition to regular features like required, non-required fields and default data,
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it has built-in comprehensive data processing params like regex, enums for limited allowed options, length validation, email validation, etc.
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```python3
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from enum import Enum
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from pydantic import BaseModel, constr, EmailStr, Field, AnyUrl
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class MusicBand(str, Enum):
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AEROSMITH = "AEROSMITH"
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QUEEN = "QUEEN"
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ACDC = "AC/DC"
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class UserBase(BaseModel):
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first_name: str = Field(min_length=1, max_length=128)
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username: constr(regex="^[A-Za-z0-9-_]+$", to_lower=True, strip_whitespace=True)
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email: EmailStr
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age: int = Field(ge=18, default=None) # must be greater or equal to 18
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favorite_band: MusicBand = None. # only "AEROSMITH", "QUEEN", "AC/DC" values are allowed to be inputted
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website: AnyUrl = None
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```
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### 3. Use dependencies for data validation vs DB
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Pydantic can only validate the values of client input.
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Use dependencies to validate data against database requirements like email already exists, user not found, etc.
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```python3
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# dependencies.py
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async def valid_post_id(post_id: UUID4) -> Mapping:
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post = await service.get_by_id(post_id)
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if not post:
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raise PostNotFound()
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return post
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# router.py
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@router.get("/posts/{post_id}", response_model=PostResponse)
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async def get_post(post: Mapping = Depends(valid_post_id)):
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return post
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@router.put("/posts/{post_id}", response_model=PostResponse)
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async def get_post(
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update_data: PostUpdate,
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post: Mapping = Depends(valid_post_id),
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):
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updated_post: Mapping = await service.update(id=post["id"], data=update_data)
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return updated_post
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@router.get("/posts/{post_id}/reviews", response_model=list[ReviewsResponse])
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async def get_post(post: Mapping = Depends(valid_post_id)):
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post_reviews: list[Mapping] = await reviews_service.get_by_post_id(post["id"])
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return post_reviews
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```
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If we didn't put data validation to dependency, we would have to add post_id validation
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for every endpoint and write the same tests for each of them.
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### 5. Chain dependencies
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Dependencies can use other dependencies and avoid code repetition for similar logic.
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```python3
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# dependencies.py
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from fastapi.security import OAuth2PasswordBearer
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from jose import JWTError, jwt
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async def valid_post_id(post_id: UUID4) -> Mapping:
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post = await service.get_by_id(post_id)
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if not post:
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raise PostNotFound()
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return post
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async def parse_jwt_data(
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token: str = Depends(OAuth2PasswordBearer(tokenUrl="/auth/token"))
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) -> dict:
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try:
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payload = jwt.decode(token, "JWT_SECRET", algorithms=["HS256"])
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except JWTError:
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raise InvalidCredentials()
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return {"user_id": payload["id"]}
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async def valid_owned_post(
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post: Mapping = Depends(valid_post_id),
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token_data: dict = Depends(parse_jwt_data),
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) -> Mapping:
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if post["creator_id"] != token_data["user_id"]:
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raise UserNotOwner()
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return post
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# router.py
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@router.get("/users/{user_id}/posts/{post_id}", response_model=PostResponse)
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async def get_user_post(post: Mapping = Depends(valid_owned_post)):
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"""Get post that belong the user."""
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return post
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```
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### 6. Decouple & Reuse dependencies. Dependency calls are cached.
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Depdencies can be reused multiple times and they won't be recalculated - FastAPI caches their result by default,
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i.e. if we have dependency which calls service `get_post_by_id`,
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we won't be visiting DB each time we call this dependency - only the first time.
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1. If attr is better to be validated through several dependencies - do it, don't make monster dependencies
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```python3
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# dependencies.py
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from fastapi.security import OAuth2PasswordBearer
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from jose import JWTError, jwt
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async def valid_post_id(post_id: UUID4) -> Mapping:
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post = await service.get_by_id(post_id)
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if not post:
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raise PostNotFound()
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return post
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async def parse_jwt_data(
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token: str = Depends(OAuth2PasswordBearer(tokenUrl="/auth/token"))
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) -> dict:
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try:
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payload = jwt.decode(token, "JWT_SECRET", algorithms=["HS256"])
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except JWTError:
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raise InvalidCredentials()
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return {"user_id": payload["id"]}
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async def valid_owned_post(
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post: Mapping = Depends(valid_post_id),
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token_data: dict = Depends(parse_jwt_data),
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) -> Mapping:
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if post["creator_id"] != token_data["user_id"]:
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raise UserNotOwner()
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return post
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async def valid_active_creator(
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token_data: dict = Depends(parse_jwt_data),
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):
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user = await users_service.get_by_id(token_data["user_id"])
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if not user["is_active"]:
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raise UserIsBanned()
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return user
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# router.py
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@router.get("/users/{user_id}/posts/{post_id}", response_model=PostResponse)
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async def get_user_post(
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post: Mapping = Depends(valid_owned_post),
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user: Mapping = Depends(valid_active_creator),
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):
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"""Get post that belong the active user."""
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return post
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```
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### 7. Follow REST
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1. Developing RESTfull API makes it easier to reuse dependencies e.g. /users/:user_id, /users/:user_id/posts/:post_id
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2. Add /me endpoint for users own posts
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1. No need to validate that user id exists - it's already checked via auth
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2. No need to check user id belongs to the requester
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### 8. DON'T MAKE YOUR ROUTE ASYNC IF YOU CONNECT TO DB OR MAKE EXTERNAL REQUESTS SYNC
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### 9. Custom base model model from day 0,
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convert datetime to common standard
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### 10. Hide docs by default. Show it explicitly on the selected envs
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### 11. Use Starlette's Config object, instead of 3rd party ones - it's decent enough
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### 12. Set DB keys naming convention immediately, from day 0
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### 13. Set DB table naming convention immediately, from day 0
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### 14. Set uuids within the app
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it's easier to test
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### 15. Set tests client async from day 0
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1. Unless you aren't planning to add integrational tests with db
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2. If you do, then do it. Problems with event loop will appear once you want to prepare objects
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### 16. Set postgres identity from day 0
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### 17. take use of background workers - they are stable enough
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good for both async and sync routes
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### 18. take use of response model, response status, responses
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### 19. typing is important - use it everywhere
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### 20. save files in chunk
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### 21. use smart union or add explicit invalidation
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### 22. do a lot of logic in db, use pydantic to parse it (show the way we evolved creator field)
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### 23. validate file formats
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### 24. validate url source (if users are able to send files)
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### 25. root_validator if multiple columns
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### 26. pre if data need to be pre-handled before validation
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### 27. you can just raise a ValueError in pydantic schemas, if that's it faces user request.
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it will return a nice response
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### 28. don't forget that fastapi converts response Model to Dict then to Model then to JSON
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### 29. if no async lib, and poor documentation, then use asgiref
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### 30. use linters (black, isort, autoflake)
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### 31. set logs from day 0
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