To enable JWT-based authentication, we need to generate JWTs as well as decode them to get user credentials. If not verify_password(password, user.hashed_password): Return pwd_context.verify(plain_password, hashed_password)ĭef authenticate_user(db, email: str, password: str): Pwd_context = CryptContext(schemes=, deprecated="auto")ĭef verify_password(plain_password, hashed_password): #Flask app builder with mongodb tutorial passwordLet’s define functions that handle password hashing and checking if a password is correct. We want the following security features in our app:įor password hashing, we can use Passlib. The method defines another parameter for getting a handle on the database-this is dependency injection in action and is discussed later in this tutorial. In order to ensure that the user has submitted the right data, we have typed hint the request body with an earlier defined UserCreate schema. We have used a decorator to specify the HTTP verb, the URI, and the schema of successful responses. There’s a lot going on in this short piece of code. Signedup_user = crud.create_user(db, user_data) User = crud.get_user_by_email(db, user_data.email) response_model=schemas.User)ĭef signup(user_data: schemas.UserCreate, db: Session = Depends(get_db)): We write our first request handler using the UserCreate and UserBase schema defined above. Let Users Sign Upįirst, let’s allow users to sign up, as all of our services need to be accessed by an authenticated user. We now turn our attention to request handlers where these schemas will be used to do all the heavy lifting of data conversion and validation for free. With this, we are done with defining schemas for all data exchanges. #Flask app builder with mongodb tutorial updateTo support the update of an existing TODO item, we define another schema: class TODOUpdate(TODOCreate): To support the creation and listing of TODO items, we define the following schema: class TODOCreate(BaseModel): Here, we marked last name, first name, and password as a string, but it can be further tightened by using pydantic constrained strings that enable checks such as min length, max length, and regexes. We just need to define a UserCreate schema here to specify data that will flow into our signup endpoint and a UserBase schema to return as a response in case the signup process is successful. In our TODO app, however, we will leverage the built-in OAuth2 support in FastAPI for a JSON Web Tokens (JWT)-based login flow. This means we need two pydantic models to express these two different shapes of User info. We need more information from users during signup and minimal (only email and password) when logging in. Both of these interactions deal with User information, but the shape of data will be different. Traditionally, a new user will sign up for our TODO service and an existing user will log in. To write pydantic models, think about all the ways the User and TODO information will flow in and out. Please note these models are not related to our database workflow and only specify the shape of data that’s flowing in and out of our REST interface. #Flask app builder with mongodb tutorial freeWith FastAPI, we express the schema of our incoming/outgoing data using pydantic models and then use these pydantic models to type hint and enjoy free data validation and conversion. Let’s tackle it up front before we go to writing request handlers. SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)Ī sizable part of any API project concerns the routine stuff like data validation and conversion. #Flask app builder with mongodb tutorial how toOnce our models are ready, let’s write the configuration file for SQLAlchemy so that it knows how to establish a connection with the database. Owner = relationship("User", back_populates="todos") Owner_id = Column(Integer, ForeignKey("users.id")) Todos = relationship("TODO", back_populates="owner", cascade="all, delete-orphan")Ĭompleted = Column(Boolean, default=False) Id = Column(Integer, primary_key=True, index=True)Įmail = Column(String, unique=True, index=True) With the help of SQLAlchemy, the database toolkit for Python, we can express our models like this: class User(Base): Our app has just two models: User and TODO. Our tiny app will provide the following features: To explore the big ideas behind FastAPI, let’s build a TODO app, which sets up to-do lists for its users.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |