How to Use Flask-RESTful to Create a REST API in Flask

This blog teaches you how to use Flask-RESTful, a Flask extension for building REST APIs, to create a simple API that returns JSON data from your database. You will learn how to install and configure Flask-RESTful, how to define and test your API resources, and how to use HTTP methods and status codes to interact with your API.

Table of Contents

1. Introduction

In this tutorial, you will learn how to use Flask-RESTful, a Flask extension for building REST APIs, to create a simple API that returns JSON data from your database. A REST API is an application programming interface that follows the principles of REST (Representational State Transfer), a software architectural style that defines how web services should communicate with each other. A REST API allows clients to access and manipulate data on a server using HTTP methods, such as GET, POST, PUT, and DELETE.

Flask-RESTful is a Flask extension that simplifies the process of creating REST APIs in Flask. It provides a Resource class that you can inherit from to define your API resources, a Api class that you can use to register your resources with your Flask app, and a reqparse module that you can use to parse and validate incoming requests. Flask-RESTful also handles the serialization and deserialization of JSON data, so you don’t have to worry about that.

By the end of this tutorial, you will be able to:

Create a Flask app and install Flask-RESTful
Create a database model using SQLAlchemy
Define your API resources using Flask-RESTful
Test your API using Postman
Add authentication and authorization using Flask-JWT
Handle errors and exceptions using Flask-RESTful

To follow along with this tutorial, you will need:

Python 3.6 or higher
Flask 1.1.2 or higher
Flask-RESTful 0.3.8 or higher
SQLAlchemy 1.3.23 or higher
Flask-JWT 0.3.2 or higher
Postman or any other API testing tool

Ready to create your first REST API in Flask? Let’s get started!

2. What is Flask-RESTful and Why Use It?

Flask-RESTful is a Flask extension that makes it easy to create REST APIs in Flask. But what is a REST API and why do you need one?

A REST API is an application programming interface that follows the principles of REST (Representational State Transfer), a software architectural style that defines how web services should communicate with each other. A REST API allows clients to access and manipulate data on a server using HTTP methods, such as GET, POST, PUT, and DELETE.

For example, suppose you have a database of books and you want to create a web service that allows users to search, view, add, update, and delete books. You can use a REST API to expose the data in your database as resources that can be accessed and modified by clients using HTTP requests. Each resource has a unique identifier, usually a URL, that specifies its location and how to access it. For example, you can have a resource for a single book, identified by its ID, such as https://example.com/api/books/1, or a resource for a collection of books, such as https://example.com/api/books.

Each HTTP request to a resource can specify an HTTP method that indicates the action to be performed on the resource. For example, you can use a GET request to retrieve the data of a resource, a POST request to create a new resource, a PUT request to update an existing resource, or a DELETE request to delete a resource. Each HTTP response from the server can also include a status code that indicates the outcome of the request, such as 200 for success, 404 for not found, or 500 for internal server error. Additionally, each request and response can include a body that contains the data of the resource, usually in JSON format.

Using a REST API has many benefits, such as:

It is simple and intuitive, as it uses the standard HTTP protocol and methods that are familiar to most developers.
It is flexible and scalable, as it can handle different types of data and clients without requiring changes to the server.
It is stateless and cacheable, as it does not store any information about the client or the session on the server, and it allows the client to cache the responses to improve performance.
It is interoperable and portable, as it can work with any platform, language, or framework that supports HTTP and JSON.

However, creating a REST API in Flask can also be challenging, as you have to deal with many details, such as:

Defining the URL routes and methods for your resources
Parsing and validating the incoming requests and their parameters
Serializing and deserializing the data to and from JSON format
Handling the errors and exceptions that may occur
Adding security features, such as authentication and authorization
Documenting and testing your API

This is where Flask-RESTful comes in handy. Flask-RESTful is a Flask extension that simplifies the process of creating REST APIs in Flask. It provides a Resource class that you can inherit from to define your API resources, an Api class that you can use to register your resources with your Flask app, and a reqparse module that you can use to parse and validate incoming requests. Flask-RESTful also handles the serialization and deserialization of JSON data, so you don’t have to worry about that.

Some of the features of Flask-RESTful are:

It supports multiple HTTP methods for each resource, such as GET, POST, PUT, and DELETE
It automatically converts Python objects to JSON and vice versa
It provides a consistent and uniform response format, including status codes and error messages
It allows you to define custom fields and marshalers to control how your data is serialized
It integrates with Flask-JWT to add authentication and authorization to your API
It provides a Swagger documentation generator to document your API

In the next section, you will learn how to set up your project and install Flask-RESTful.

3. Setting Up the Project

Before you can start creating your REST API, you need to set up your project and install Flask-RESTful. In this section, you will learn how to do that.

First, you need to create a virtual environment for your project. A virtual environment is a isolated Python environment that allows you to install and use specific packages and dependencies for your project without affecting the global Python installation. This way, you can avoid conflicts and errors that may arise from different versions of the same package.

To create a virtual environment, you can use the venv module that comes with Python 3. To do that, open a terminal and navigate to the folder where you want to create your project. Then, run the following command:

python -m venv venv

This will create a folder called venv that contains the virtual environment. To activate the virtual environment, run the following command:

source venv/bin/activate

You should see a (venv) prefix in your terminal prompt, indicating that you are in the virtual environment. To deactivate the virtual environment, run the following command:

deactivate

Next, you need to install Flask and Flask-RESTful. Flask is a lightweight web framework that allows you to create web applications in Python. Flask-RESTful is a Flask extension that simplifies the process of creating REST APIs in Flask. To install them, run the following command:

pip install flask flask-restful

This will install the latest versions of Flask and Flask-RESTful and their dependencies. You can check the installed packages and their versions by running the following command:

pip freeze

Finally, you need to create a Python file that will contain your Flask app and your API code. You can name it anything you want, but for this tutorial, we will name it app.py. To create it, run the following command:

touch app.py

This will create an empty file called app.py in your project folder. You can open it with your favorite code editor and start writing your code.

Congratulations, you have successfully set up your project and installed Flask-RESTful. In the next section, you will learn how to create a database model using SQLAlchemy.

4. Creating the Database Model

In this section, you will learn how to create a database model using SQLAlchemy. A database model is a representation of the data and the relationships in your database. It defines the tables, columns, and constraints that store and validate your data. SQLAlchemy is a Python library that provides an object-relational mapper (ORM) that allows you to interact with your database using Python objects and expressions.

To create a database model using SQLAlchemy, you need to follow these steps:

Import SQLAlchemy and create a database engine
Create a base class for your model classes
Create your model classes and define their attributes and relationships
Create the database tables from your model classes

Let’s go through each step in detail.

1. Import SQLAlchemy and create a database engine

The first step is to import SQLAlchemy and create a database engine. A database engine is an object that connects to your database and executes SQL statements. To create a database engine, you need to specify the database URI, which is a string that contains the information about the database type, name, location, and credentials. For example, if you want to use SQLite, which is a lightweight and embedded database that stores the data in a single file, you can use a URI like this:

sqlite:///books.db

This means that you want to use SQLite and store the data in a file called books.db in the same folder as your app. To import SQLAlchemy and create a database engine, you can write the following code in your app.py file:

from flask import Flask
from flask_restful import Api, Resource, reqparse, fields, marshal_with
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
api = Api(app)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///books.db'
db = SQLAlchemy(app)

This code imports the Flask, Flask-RESTful, and Flask-SQLAlchemy modules, creates a Flask app and an Api object, sets the database URI to use SQLite, and creates a SQLAlchemy object called db that represents the database engine.

2. Create a base class for your model classes

The next step is to create a base class for your model classes. A model class is a Python class that represents a table in your database. It defines the columns, types, and constraints of the table, as well as the relationships with other tables. A base class is a common class that inherits from the db.Model class provided by SQLAlchemy and provides some common attributes and methods for your model classes. To create a base class, you can write the following code:

class Base(db.Model):
    __abstract__ = True
    id = db.Column(db.Integer, primary_key=True)
    created_at = db.Column(db.DateTime, default=db.func.current_timestamp())
    updated_at = db.Column(db.DateTime, default=db.func.current_timestamp(), onupdate=db.func.current_timestamp())

This code creates a class called Base that inherits from db.Model and sets the __abstract__ attribute to True, which means that this class will not create a table in the database, but only serve as a parent class for other model classes. The class also defines three common columns for all model classes: id, which is an integer column that serves as the primary key, created_at, which is a datetime column that stores the timestamp of when the record was created, and updated_at, which is a datetime column that stores the timestamp of when the record was updated. The default and onupdate arguments specify the default values and the update values for these columns, using the db.func.current_timestamp() function that returns the current timestamp.

3. Create your model classes and define their attributes and relationships

The third step is to create your model classes and define their attributes and relationships. For this tutorial, we will create two model classes: Book and Author. A Book class represents a book in the database, and an Author class represents an author in the database. A book can have one or more authors, and an author can have one or more books. This is a many-to-many relationship, which means that we need to create a third table to store the association between books and authors. To create your model classes, you can write the following code:

# Create a table for the association between books and authors
books_authors = db.Table('books_authors',
    db.Column('book_id', db.Integer, db.ForeignKey('book.id'), primary_key=True),
    db.Column('author_id', db.Integer, db.ForeignKey('author.id'), primary_key=True)
)

# Create a model class for books
class Book(Base):
    __tablename__ = 'book'
    title = db.Column(db.String(100), nullable=False)
    genre = db.Column(db.String(50), nullable=False)
    price = db.Column(db.Float, nullable=False)
    authors = db.relationship('Author', secondary=books_authors, lazy='subquery', backref=db.backref('books', lazy=True))

    def __repr__(self):
        return f''

# Create a model class for authors
class Author(Base):
    __tablename__ = 'author'
    name = db.Column(db.String(100), nullable=False)
    email = db.Column(db.String(100), nullable=False, unique=True)

    def __repr__(self):
        return f''

This code creates two model classes: Book and Author, that inherit from the Base class and define their table names and columns. The Book class has four columns: title, which is a string column that stores the title of the book, genre, which is a string column that stores the genre of the book, price, which is a float column that stores the price of the book, and authors, which is a relationship column that defines the association with the Author class. The Author class has three columns: name, which is a string column that stores the name of the author, email, which is a string column that stores the email of the author, and books, which is a backref column that defines the reverse association with the Book class.

The code also creates a table called books_authors that stores the many-to-many relationship between books and authors. It has two columns: book_id and author_id, which are foreign keys that reference the primary keys of the book and author tables, respectively. The db.Table function creates a table object that can be used as the secondary argument for the relationship column. The lazy argument specifies how the related objects are loaded, and the backref argument specifies the name of the reverse relationship.

The code also defines a __repr__ method for each model class, which returns a string representation of the object. This is useful for debugging and testing purposes.

4. Create the database tables from your model classes

The final step is to create the database tables from your model classes. To do that, you need to use the db.create_all() method, which creates all the tables that are defined by the model classes that inherit from db.Model. To create the database tables, you can write the following code at the end of your app.py file:

if __name__ == '__main__':
    db.create_all()
    app.run(debug=True)

This code checks if the file is run as the main program, and if so, it creates the database tables and runs the Flask app in debug mode. Debug mode allows you to see the errors and stack traces in the browser, and also reloads the app automatically when you make changes to the code.

To run the file, you can use the following command:

python app.py

This will create a file called books.db in your project folder, which contains the database tables for your model classes. You can use a SQLite browser, such as DB Browser for SQLite, to view and manipulate the data in your database.

Congratulations, you have successfully

5. Defining the API Resources

In this section, you will learn how to define the API resources using Flask-RESTful. An API resource is a class that inherits from the Resource class provided by Flask-RESTful and defines the methods and logic for handling the requests to a specific URL. For example, you can have a resource for a single book, identified by its ID, such as https://example.com/api/books/1, or a resource for a collection of books, such as https://example.com/api/books.

To define the API resources using Flask-RESTful, you need to follow these steps:

Create a resource class and inherit from the Resource class
Define the methods and logic for each HTTP method that you want to support
Use the reqparse module to parse and validate the incoming requests and their parameters
Use the fields and marshal_with modules to serialize and deserialize the data to and from JSON format
Register the resource class with the Api object and specify the URL route and endpoint

Let’s go through each step in detail.

1. Create a resource class and inherit from the `Resource` class

The first step is to create a resource class and inherit from the Resource class. A resource class is a Python class that represents a specific URL that can handle different HTTP methods, such as GET, POST, PUT, and DELETE. To create a resource class, you need to inherit from the Resource class provided by Flask-RESTful and give it a name that reflects the resource that it represents. For example, to create a resource class for a single book, you can write the following code:

class BookResource(Resource):
    pass

This code creates a class called BookResource that inherits from the Resource class and does nothing for now. You will add the methods and logic for the resource class in the next step.

2. Define the methods and logic for each HTTP method that you want to support

The second step is to define the methods and logic for each HTTP method that you want to support. A HTTP method is a verb that indicates the action to be performed on the resource, such as GET, POST, PUT, and DELETE. To define the methods and logic for each HTTP method, you need to write a method with the same name as the HTTP method in lowercase and add the logic for handling the request and returning the response. For example, to define the method and logic for the GET method, which retrieves the data of a single book, you can write the following code:

class BookResource(Resource):
    def get(self, book_id):
        # Get the book from the database by its ID
        book = Book.query.get_or_404(book_id)
        # Return the book data as JSON
        return book

This code defines a get method that takes a book_id parameter, which is the ID of the book to be retrieved. The method uses the query attribute of the Book model class to query the database and get the book object by its ID. If the book is not found, the method raises a 404 error using the get_or_404 method. The method then returns the book object as the response. Flask-RESTful automatically converts the book object to JSON format using the default serializer.

You can define the methods and logic for other HTTP methods in a similar way. For example, to define the method and logic for the POST method, which creates a new book, you can write the following code:

class BookResource(Resource):
    def get(self, book_id):
        # Get the book from the database by its ID
        book = Book.query.get_or_404(book_id)
        # Return the book data as JSON
        return book

    def post(self):
        # Parse and validate the incoming request and its parameters
        parser = reqparse.RequestParser()
        parser.add_argument('title', type=str, required=True, help='Title is required')
        parser.add_argument('genre', type=str, required=True, help='Genre is required')
        parser.add_argument('price', type=float, required=True, help='Price is required')
        parser.add_argument('author_ids', type=int, action='append', required=True, help='At least one author ID is required')
        args = parser.parse_args()
        # Create a new book object with the parsed arguments
        book = Book(title=args['title'], genre=args['genre'], price=args['price'])
        # Add the authors to the book object using the author IDs
        for author_id in args['author_ids']:
            author = Author.query.get_or_404(author_id)
            book.authors.append(author)
        # Add the book object to the database and commit the changes
        db.session.add(book)
        db.session.commit()
        # Return the book data as JSON with a 201 status code
        return book, 201

This code defines a post method that takes no parameters, but expects some parameters in the request body. The method uses the reqparse module to parse and validate the incoming request and its parameters. The reqparse module provides a RequestParser class that allows you to define the arguments that you expect in the request and their types, requirements, and help messages. The parse_args method parses the request and returns a dictionary of the arguments and their values. If any argument is missing or invalid, the method raises a 400 error with the help message.

The method then creates a new book object with the parsed arguments using the Book model class. The method also adds the authors to the book object using the author_ids argument, which is a list of author IDs. The method uses the query attribute of the Author model class to get the author objects by their IDs, and the append method of the authors relationship column to add them to the book object. The method then adds the book object to the database session and commits the changes using the db.session object. The method then returns the book object as the response, along with a 201 status code, which indicates that a new resource has been created.

You can define the methods and logic for the PUT and DELETE methods in a similar way. The PUT method updates an existing book, and the DELETE method deletes an existing book. For the sake of brevity, we will not show the code for these methods here, but you can find them in the GitHub repository for this tutorial.

3. Use the `reqparse` module to parse and validate the incoming requests and their parameters

The third step is to use the reqparse module to parse and validate the incoming requests and their parameters. The reqparse module is a Flask-RESTful module that provides a RequestParser class that allows you to define the arguments that you expect in the request and their types, requirements, and help messages. The parse_args method parses the request and returns a dictionary of the arguments and their values. If any argument is missing or invalid, the method raises a 400 error with the help message.

We have already seen an example of how to use the reqparse module in the previous step, when we defined the method and logic for the POST method. Here is the code snippet again:

def post(self):
        # Parse and validate the incoming request and its parameters
        parser = reqparse.RequestParser()
        parser.add_argument('title', type=str, required=True, help='Title is required')
        parser.add_argument('genre', type=str, required=True, help='Genre is required')
        parser.add_argument('price', type=float, required=True, help='Price is required')
        parser.add_argument('author_ids', type=int, action='append', required=True, help='At least one author ID is required')
        args = parser.parse_args()

This code creates a RequestParser object and adds four arguments to it: title, genre, price, and author_ids. Each argument has a type, a requirement, and a help message. The type argument specifies the data type of the argument, such as str, int, or float</

6. Testing the API with Postman

Now that you have defined your API resources, you can test them using Postman, a popular tool for testing and debugging APIs. Postman allows you to send HTTP requests to your API endpoints and inspect the responses, as well as save, organize, and share your requests and responses.

To test your API with Postman, you will need to:

Download and install Postman from https://www.postman.com/downloads/
Run your Flask app on your local machine
Create a new collection in Postman to store your requests
Create and send requests for each of your API resources and methods
Verify that the responses match your expectations

Let’s see how to do each of these steps in detail.

Downloading and Installing Postman

To download and install Postman, you can follow the instructions on the official website: https://learning.postman.com/docs/getting-started/installation-and-updates/

Once you have installed Postman, you can launch it and create a free account or sign in with an existing one. You will see the main Postman window, which consists of several sections, such as the sidebar, the workspace, the request builder, and the response viewer.

Running Your Flask App

To run your Flask app on your local machine, you can use the same command that you used before:

python app.py

This will start your Flask app on the default port 5000. You should see a message like this in your terminal:

* Serving Flask app "app" (lazy loading)
* Environment: production
  WARNING: This is a development server. Do not use it in a production deployment.
  Use a production WSGI server instead.
* Debug mode: on
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
* Restarting with stat
* Debugger is active!
* Debugger PIN: 123-456-789

This means that your Flask app is running and listening for requests on the URL http://127.0.0.1:5000/, which is also known as http://localhost:5000/. You can use this URL as the base URL for your API requests in Postman.

Creating a New Collection in Postman

A collection in Postman is a group of related requests that you can save, organize, and share. To create a new collection for your API requests, you can follow these steps:

Click on the New button on the top left corner of the Postman window.
Select Collection from the options.
Enter a name for your collection, such as Flask-RESTful API.
Optionally, you can add a description, choose a color, and add some metadata for your collection.
Click on Create to create your collection.

You should see your collection appear in the sidebar under the Collections tab. You can expand or collapse your collection by clicking on the arrow next to its name. You can also edit, delete, or share your collection by clicking on the three dots next to its name.

Creating and Sending Requests for Each of Your API Resources and Methods

Now that you have created your collection, you can start adding requests for each of your API resources and methods. To create a new request, you can follow these steps:

Click on the Add Request button under your collection name in the sidebar.
Enter a name for your request, such as Get All Books.
Optionally, you can add a description and some metadata for your request.
Click on Save to Flask-RESTful API to save your request to your collection.

You should see your request appear under your collection name in the sidebar. You can also edit, delete, or duplicate your request by clicking on the three dots next to its name.

Creating a new request in Postman

To send your request, you need to specify the following information in the request builder:

The HTTP method, such as GET, POST, PUT, or DELETE.
The URL of the resource, such as http://localhost:5000/api/books or http://localhost:5000/api/books/1.
The headers, such as Content-Type: application/json or Authorization: Bearer token.
The body, such as a JSON object with the data of the resource.

For example, to send a GET request to get all the books from your API, you can enter the following information in the request builder:

Method: GET
URL: http://localhost:5000/api/books
Headers: None
Body: None

Then, you can click on the Send button to send your request to your API endpoint. You should see the response from the server in the response viewer below the request builder. You can inspect the status code, the headers, the body, and the time of the response.

You can repeat this process for each of your API resources and methods, changing the method, the URL, the headers, and the body as needed. For example, to send a POST request to create a new book in your API, you can enter the following information in the request builder:

Method: POST
URL: http://localhost:5000/api/books
Headers: Content-Type: application/json
Body: A JSON object with the data of the new book, such as {"title": "The Hitchhiker's Guide to the Galaxy", "author": "Douglas Adams", "genre": "Science Fiction"}

Verifying That the Responses Match Your Expectations

As you test your API with Postman, you should verify that the responses match your expectations. You can use the following criteria to check the quality of your API responses:

The status code should indicate the outcome of the request, such as 200 for success, 201 for created, 400 for bad request, 401 for unauthorized, 404 for not found, or 500 for internal server error.
The headers should include the relevant information, such as the content type, the content length, the date, and the authorization token.
The body should contain the data of the resource in JSON format, or an error message if the request failed.
The time should be reasonable, depending on the complexity of the request and the size of the data.

If the responses do not match your expectations, you should debug your API and find the source of the error. You can use the following techniques to debug your API:

Check the terminal where you are running your Flask app for any error messages or stack traces.
Use the Debugger tab in Postman to see the details of your request and response, such as the headers, the cookies, the variables, and the console logs.
Use the Tests tab in Postman to write and run tests for your API, such as checking the status code, the headers, the body,

7. Adding Authentication and Authorization

One of the important features of any API is security. You want to make sure that only authorized users can access and modify your data, and that your data is protected from unauthorized or malicious requests. In this section, you will learn how to add authentication and authorization to your API using Flask-JWT, a Flask extension that integrates JSON Web Tokens (JWT) with Flask.

JWT is a standard for securely transmitting information between parties as a JSON object. JWT can be used to authenticate users, as well as to pass information such as roles, permissions, and preferences. A JWT consists of three parts: a header, a payload, and a signature. The header contains metadata about the token, such as the algorithm and the type. The payload contains the claims, or the information that the token carries, such as the user ID, the expiration time, and the roles. The signature is a hash of the header and the payload, encrypted with a secret key, that verifies the integrity of the token.

To use JWT for authentication and authorization, you need to implement the following steps:

Create a secret key that will be used to encrypt and decrypt the tokens.
Create an endpoint for generating and returning a token when a user provides valid credentials, such as a username and a password.
Create an endpoint for verifying and refreshing a token when a user provides an expired token.
Add a decorator to your API resources that requires a valid token to access them.
Add a decorator to your API resources that checks the roles or permissions of the user before allowing them to perform certain actions.

Let’s see how to do each of these steps in detail.

Creating a Secret Key

To create a secret key, you can use any random string that is hard to guess. You can also use a tool like https://passwordsgenerator.net/ to generate a strong and secure key. For example, you can use something like this:

SECRET_KEY = "fjw8fjw9fjw9fjw9fjw9fjw9fjw9fjw9"

You can store your secret key in your app configuration, like this:

app.config["SECRET_KEY"] = SECRET_KEY

You can also use environment variables to store your secret key, which is a more secure and recommended way. To do that, you can use the os module to get the value of the environment variable, like this:

import os

SECRET_KEY = os.environ.get("SECRET_KEY")
app.config["SECRET_KEY"] = SECRET_KEY

Then, you can set the value of the environment variable in your terminal, like this:

export SECRET_KEY="fjw8fjw9fjw9fjw9fjw9fjw9fjw9fjw9"

Make sure to keep your secret key private and do not share it with anyone.

Creating an Endpoint for Generating and Returning a Token

To create an endpoint for generating and returning a token, you need to use the flask_jwt module, which provides the functionality for integrating JWT with Flask. You can import the module and initialize it with your app, like this:

from flask_jwt import JWT, jwt_required, current_identity

jwt = JWT(app, authenticate, identity)

The JWT class takes three arguments: the app, a function for authenticating the user, and a function for identifying the user. The authenticate function takes the username and password as parameters and returns the user object if the credentials are valid, or None if they are not. The identity function takes the payload of the token as a parameter and returns the user object based on the user ID in the payload.

For example, you can define the authenticate and identity functions as follows:

def authenticate(username, password):
    user = User.query.filter_by(username=username).first()
    if user and user.check_password(password):
        return user

def identity(payload):
    user_id = payload["identity"]
    user = User.query.get(user_id)
    return user

These functions assume that you have a User model that represents the users in your database, and that it has a check_password method that verifies the password. You can use SQLAlchemy to create and manage your database models, as you did in the previous sections.

Once you have defined and initialized the JWT class, it will automatically create an endpoint for generating and returning a token at /auth. You can send a POST request to this endpoint with the username and password in the JSON body, and it will return a token in the JSON response, like this:

Request:
POST /auth
Content-Type: application/json

{
    "username": "alice",
    "password": "password123"
}

Response:
200 OK
Content-Type: application/json

{
    "access_token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpZGVudGl0eSI6MSwiZXhwIjoxNjE5MjQwMjg0LCJuYmYiOjE2MTkyMzk5ODQsImlhdCI6MTYxOTIzOTk4NH0.3y7QZLZnXQfW8lZnXQfW8lZnXQfW8lZnXQfW8lZnXQfW8lZn"
}

The token is a long string that consists of three parts separated by dots: the header, the payload, and the signature. You can decode the token using a tool like https://jwt.io/ and see the information it contains. For example, the payload of the token above contains the following information:

{
  "identity": 1,
  "exp": 1619240284,
  "nbf": 1619239984,
  "iat": 1619239984
}

The identity field is the user ID, the exp field is the expiration time, the nbf field is the not before time, and the iat field is the issued at time. By default, the token expires in 5 minutes, but you can change that by setting the JWT_EXPIRATION_DELTA configuration in your app, like this:

from datetime import timedelta

app.config["JWT_EXPIRATION_DELTA"] = timedelta(minutes=15)

This will set the token expiration time to 15 minutes. You can also set other configurations for the JWT, such as the algorithm, the header name, and the response key. You can see the full list of configurations here: https://pythonhosted.org/Flask-JWT/#configuration-options

Creating an Endpoint for Verifying and Refreshing a Token

If your token expires, you can create an endpoint for verifying and refreshing it. To do that, you need to use the jwt_refresh_token_required decorator, which requires a valid refresh token to access the endpoint. A refresh token is a special type of token that can only be used to refresh an expired access token. You can enable the refresh token feature by setting the JWT_REFRESH_TOKEN_VALIDITY configuration in your app, like this:

app.config["JWT_REFRESH_TOKEN_VALIDITY"] = True

This will make the /auth endpoint return both an access token and a refresh token in the response, like this:

Response:
200 OK
Content-Type: application/json

{
    "access_token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpZGVudGl0eSI6MSwiZXhwIjoxNjE5MjQwMjg0LCJuYmYiOjE2MTkyMzk5ODQsImlhdCI6MTYxOTIzOTk4NH0.3y7QZLZnXQfW8lZnXQfW

8. Handling Errors and Exceptions

One of the important aspects of any API is how it handles errors and exceptions that may occur during the execution of the requests. Errors and exceptions are inevitable in any software application, and they can be caused by various factors, such as invalid input, network issues, database errors, or internal bugs. You want to make sure that your API responds to errors and exceptions in a consistent and informative way, so that the clients can understand what went wrong and how to fix it.

In this section, you will learn how to handle errors and exceptions in your API using Flask-RESTful, a Flask extension that simplifies the process of creating REST APIs in Flask. Flask-RESTful provides a way to define custom error handlers for different types of errors and exceptions, and to return a uniform response format that includes the status code, the message, and the data of the error.

To handle errors and exceptions in your API using Flask-RESTful, you need to implement the following steps:

Create a dictionary that maps the error codes and names to the corresponding messages and data.
Register the dictionary with the Api class using the errors keyword argument.
Raise the appropriate error or exception in your API resources using the abort or raise_for_status methods.
Optionally, you can define custom error classes that inherit from the Exception class and register them with the Api class using the error_handlers keyword argument.

Let’s see how to do each of these steps in detail.

Creating a Dictionary of Error Codes and Messages

To create a dictionary of error codes and messages, you can use the following syntax:

errors = {
    "ErrorCode": {
        "message": "Error message",
        "status": status_code,
        "data": error_data
    },
    ...
}

For example, you can define the following dictionary of errors for your API:

errors = {
    "BookNotFound": {
        "message": "The book with the given ID was not found",
        "status": 404,
        "data": None
    },
    "BookAlreadyExists": {
        "message": "A book with the same title and author already exists",
        "status": 409,
        "data": None
    },
    "InvalidInput": {
        "message": "The input data is not valid",
        "status": 400,
        "data": None
    },
    "Unauthorized": {
        "message": "You are not authorized to access this resource",
        "status": 401,
        "data": None
    },
    "InternalServerError": {
        "message": "Something went wrong on the server side",
        "status": 500,
        "data": None
    }
}

The message field is the error message that will be returned to the client. The status field is the status code that will be returned to the client. The data field is any additional data that you want to return to the client, such as the validation errors or the stack trace. You can set the data field to None if you don’t have any additional data to return.

Registering the Dictionary with the Api Class

To register the dictionary with the Api class, you can use the errors keyword argument when you initialize the Api class, like this:

api = Api(app, errors=errors)

This will tell the Api class to use the dictionary of errors that you defined to handle the errors and exceptions that may occur in your API. The Api class will automatically return a JSON response with the appropriate status code, message, and data for each error or exception.

Raising the Appropriate Error or Exception in Your API Resources

To raise the appropriate error or exception in your API resources, you can use the abort or raise_for_status methods that are provided by the Flask-RESTful module. The abort method takes the status code and the error name as arguments and raises the corresponding error or exception. The raise_for_status method takes the response object as an argument and raises the corresponding error or exception if the response status code is not 200.

For example, you can use the abort method in your API resources to raise the BookNotFound error if the book with the given ID does not exist in the database, like this:

class Book(Resource):
    def get(self, book_id):
        book = BookModel.query.get(book_id)
        if book is None:
            abort(404, "BookNotFound")
        return book.json()

You can also use the raise_for_status method in your API resources to raise the appropriate error or exception if the response status code is not 200, like this:

class BookList(Resource):
    def get(self):
        response = requests.get("https://example.com/api/books")
        response.raise_for_status()
        return response.json()

This will raise the corresponding error or exception if the response status code is not 200, such as 400 for bad request, 401 for unauthorized, 404 for not found, or 500 for internal server error.

Defining Custom Error Classes

Optionally, you can define custom error classes that inherit from the Exception class and register them with the Api class using the error_handlers keyword argument. This can be useful if you want to have more control over the error handling logic, such as adding custom attributes or methods to your error classes.

For example, you can define a custom error class for the BookNotFound error, like this:

class BookNotFound(Exception):
    def __init__(self, book_id):
        self.book_id = book_id
        self.message = f"The book with the ID {book_id} was not found"
        self.status = 404
        self.data = None

    def __str__(self):
        return self.message

This custom error class inherits from the Exception class and adds a book_id attribute to store the book ID that caused the error. It also overrides the __init__ and __str__ methods to set and return the message, status, and data of the error.

To register the custom error class with the Api class, you can use the error_handlers keyword argument when you initialize the Api class, like this:

api = Api(app, error_handlers={BookNotFound: handle_book_not_found})

This will tell the Api class to use the handle_book_not_found function to handle the BookNotFound error. The handle_book_not_found function takes the error object as an argument and returns a JSON response with the appropriate status code, message, and data, like this:

def handle_book_not_found(error):
    return {"message": error.message, "status": error.status, "data": error.data}, error.status

You can repeat this process for any other custom error classes that you want to define and register with the Api class.

In the next and final section, you will learn how to conclude your tutorial and provide some additional resources for the readers.

9. Conclusion

Congratulations! You have successfully created a REST API in Flask using Flask-RESTful, a Flask extension that simplifies the process of creating REST APIs in Flask. You have learned how to:

Set up your project and install Flask-RESTful
Create a database model using SQLAlchemy
Define your API resources using Flask-RESTful
Test your API using Postman
Add authentication and authorization using Flask-JWT
Handle errors and exceptions using Flask-RESTful

You have also learned some of the benefits and challenges of creating a REST API in Flask, as well as some of the features and functionalities of Flask-RESTful, such as the Resource, Api, and reqparse classes, the JWT integration, and the error handling mechanism.

By creating a REST API in Flask, you have gained a valuable skill that can help you build web services that can communicate with different types of clients and platforms, such as web browsers, mobile apps, or other servers. You have also gained a deeper understanding of the principles and practices of REST, such as the use of HTTP methods, status codes, and JSON data.

However, this is not the end of your learning journey. There are still many topics and concepts that you can explore and learn more about, such as:

How to document your API using tools like Swagger or Postman
How to test your API using tools like pytest or unittest
How to deploy your API to a production server using tools like Heroku or AWS
How to optimize your API performance using tools like caching or pagination
How to secure your API using tools like HTTPS or CORS
How to extend your API functionality using other Flask extensions or libraries

To help you continue your learning journey, here are some additional resources that you may find useful:

We hope you enjoyed this tutorial and learned something new and useful. Thank you for reading and happy coding!

1. Introduction

2. What is Flask-RESTful and Why Use It?

3. Setting Up the Project

4. Creating the Database Model

1. Import SQLAlchemy and create a database engine

2. Create a base class for your model classes

3. Create your model classes and define their attributes and relationships

4. Create the database tables from your model classes

5. Defining the API Resources

1. Create a resource class and inherit from the Resource class

2. Define the methods and logic for each HTTP method that you want to support

3. Use the reqparse module to parse and validate the incoming requests and their parameters

6. Testing the API with Postman

Downloading and Installing Postman

Running Your Flask App

Creating a New Collection in Postman

Creating and Sending Requests for Each of Your API Resources and Methods

Verifying That the Responses Match Your Expectations

7. Adding Authentication and Authorization

Creating a Secret Key

Creating an Endpoint for Generating and Returning a Token

Creating an Endpoint for Verifying and Refreshing a Token

8. Handling Errors and Exceptions

Creating a Dictionary of Error Codes and Messages

Registering the Dictionary with the Api Class

Raising the Appropriate Error or Exception in Your API Resources

Defining Custom Error Classes

9. Conclusion

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1. Create a resource class and inherit from the `Resource` class

3. Use the `reqparse` module to parse and validate the incoming requests and their parameters