Adventures in Machine Learning

Building a REST API with Flask and SQLite: A Comprehensive Guide

Building a REST API with Flask

Flask is a popular Python web framework that makes building web applications a breeze. A REST API is a web service that follows the principles of REST (Representational State Transfer) and allows clients to interact with a server using standard HTTP requests.

In this article, we will outline the basic steps for building a REST API with Flask.

Basic Flask Project Setup

To start a new Flask project, you need to install Flask using pip. Once installed, you can create a new Flask application by creating a Python file and importing the Flask class from the flask module.

You can then create a new instance of the Flask class and define the routes for your application.

Creating CRUD Operations with Connexion

Connexion is a Python library that makes it easy to build REST APIs with Flask. It handles the mapping of HTTP requests to Python functions and provides validation and documentation for your API.

To use Connexion, you need to install it using pip and create a YAML file that defines your API specification. You can then create a new instance of the Flask class and use the make_api() method provided by Connexion to create your API endpoints.

Adding a SQLite Database to Flask App

A SQL database is used to store data in a structured manner. The SQLite database is a lightweight and portable database that can be easily integrated into a Flask application.

To use SQLite with Flask, you need to install the SQLite3 module and create a new database file. You can then use the sqlite3 module in Python to execute SQL commands and interact with the database.

Initializing and Interacting with the Database

To initialize the database, you create a function that creates the database tables if they do not already exist. You can then use this function in your Flask app to ensure that the database is set up correctly before you start using it.

To interact with the database, you can use the SQLite3 module to execute SQL commands such as SELECT, INSERT, UPDATE, and DELETE. You can also use ORM libraries such as SQLAlchemy to interact with the database in a more object-oriented manner.

Creating a Database Table

A database table is a two-dimensional array that consists of columns and records. Each column represents a specific type of data, and each record represents a unique instance of that data.

To create a database table, you need to define the column names and data types, as well as a primary key that uniquely identifies each record in the table.

Constructing the Person Table for the Application

For our REST API, we will create a person table that stores information about people. The table will have five columns: id (the primary key), fname (the person’s first name), lname (the person’s last name), email (the person’s email address), and phone (the person’s phone number).

We will use the SQLite3 module to create the table and insert some initial data.

In Conclusion

Building a REST API with Flask and SQLite is a straightforward process that requires some basic knowledge of Python and databases. By following the steps outlined in this article, you can create a functional API that can be used to interact with your application’s data.

Whether you are building a small prototype or a large-scale application, Flask and SQLite are powerful tools that can help you achieve your goals.

Working with the Configuration and Models

When building a web application with Flask, it’s important to properly configure the various tools you are using, such as Connexion, SQLAlchemy, and Marshmallow. These tools all have their own configuration requirements, which can be set in the file.

Additionally, defining your SQLAlchemy and Marshmallow classes is key to working with models in your Flask app. Configuring Flask, Connexion, SQLAlchemy, and Marshmallow

To configure Flask, you can set various options in the file.

These might include things like the secret key, database URI, and debug mode. To use Connexion with your Flask app, you will need to configure it to use your API specification file and any other necessary settings.

Similarly, to use SQLAlchemy and Marshmallow, you will need to specify the database URI and other settings in the file. You may also need to set up your database models and schemas in separate files.

Defining the SQLAlchemy and Marshmallow Classes

In your file, you can define your SQLAlchemy database classes and Marshmallow schema classes. SQLAlchemy classes represent your database tables, while Marshmallow schema classes define the structure and validation of your data.

To define a SQLAlchemy class, you will need to inherit from the SQLAlchemy base class and define your table columns as class attributes. For example:


from flask_sqlalchemy import SQLAlchemy

db = SQLAlchemy()

class Person(db.Model):

id = db.Column(db.Integer, primary_key=True)

fname = db.Column(db.String(50))

lname = db.Column(db.String(50))

email = db.Column(db.String(100))

phone = db.Column(db.String(20))


To define a Marshmallow schema class, you will need to inherit from the Marshmallow Schema class and define your fields as class attributes. For example:


from marshmallow import Schema, fields

class PersonSchema(Schema):

id = fields.Integer(dump_only=True)

fname = fields.String(required=True)

lname = fields.String(required=True)

email = fields.Email(required=True)

phone = fields.String(required=True)


Retrieving and Working with Models

To retrieve models from your database, you can use either pure SQL commands or SQLAlchemy’s ORM (Object-Relational Mapping) system. Retrieving data with pure SQL can be a bit more verbose, but it can be useful when you need to execute complex queries or operations that are not supported by SQLAlchemy.

For example, to get all the people in our Person database table using pure SQL, we could execute the following command:


SELECT * FROM person;


To retrieve data with SQLAlchemy’s ORM, you can query your database using the query() method of your SQLAlchemy database model. For example:


people = Person.query.all()


This would return a list of all the Person objects in the database.

Once you have retrieved your models from the database, you may need to work with them in some way, such as updating their data or serializing them for output. To update a model with SQLAlchemy, you can simply modify its attributes and then call the commit() method of your SQLAlchemy database session.

For example:


person = Person.query.get(1) = ‘[email protected]



To serialize a model with Marshmallow, you can call the dump() method of your Marshmallow schema object. For example:


person = Person.query.get(1)

person_schema = PersonSchema()

person_data = person_schema.dump(person)


This would create a dictionary representation of the Person object that could be returned as JSON (or otherwise serialized).

In Conclusion

Working with configuration and models is an essential part of building a Flask web application. It’s important to properly configure each tool you are using and define your database models and schema classes in order to retrieve and work with your data.

By using tools like SQLAlchemy and Marshmallow, you can make this process more efficient and less error-prone, allowing you to focus on building your application’s features and functionality. Conclusion:

In this tutorial series, we have covered the basics of building a REST API using Flask and a SQLite database.

We have explored how to configure Connexion, SQLAlchemy, and Marshmallow, and how to define database models and schema classes. We have discussed how to retrieve and work with models using SQL and SQLAlchemy, and how to serialize data using Marshmallow.

Next Steps:

Now that you have a basic understanding of how to build a REST API with Flask and SQLite, you can start to explore different features and extensions that can make your application more robust and feature-rich. Here are some next steps you might consider:


Adding authentication and authorization: This can involve adding user management features to your application and protecting certain endpoints with authentication and authorization checks. 2.

Implementing pagination: If your API returns a large amount of data, implementing pagination can make it more usable and efficient. 3.

Documenting your API: Using tools like Swagger UI or ReDoc, you can auto-generate a documentation page for your API that makes it easy for clients to understand how to use it. 4.

Versioning your API: If you need to make breaking changes to your API, versioning can help you maintain compatibility with existing clients. 5.

Testing your API: Writing automated tests for your API can help you catch bugs and ensure that it works as expected. By continuing to learn and experiment, you can build powerful and effective REST APIs that meet the needs of your application and users.

Remember to keep your code organized, well-documented, and easy to maintain, and to test thoroughly before deploying to production. Good luck!

In this tutorial series, we have covered the essential steps for building a REST API with Flask and a SQLite database.

We discussed configuring Flask, Connexion, SQLAlchemy, and Marshmallow, defining SQLAlchemy and Marshmallow classes, and querying the database with SQL and SQLAlchemy. We also delved into how to serialize data and work with models using Marshmallow.

Building a REST API with Flask and SQLite will help you create a scalable and robust web application that can handle CRUD operations. The key takeaway is that with these fundamental steps, you can build a solid foundation for your application, and continuing to explore features and extensions can make your REST API more powerful.

Remember to keep your code well-organized and test it before deploying to production, and you will be on track to creating a successful web application.

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