Querying Tables and Paginating Data in Flask SQLAlchemy

Flask SQLAlchemy is a powerful ORM (Object-Relational Mapping) tool that allows developers to interact with databases using Python objects. In this article, we will learn how to query tables and paginate data using Flask SQLAlchemy.

Querying Tables

To query a table in Flask SQLAlchemy, we first need to define a model for that table. Here’s an example of how to define a simple User model:

    
from flask_sqlalchemy import SQLAlchemy

db = SQLAlchemy()

class User(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    username = db.Column(db.String(80), unique=True, nullable=False)
    email = db.Column(db.String(120), unique=True, nullable=False)
    created_at = db.Column(db.DateTime, default=datetime.utcnow)

    def __repr__(self):
        return f''
    
  

Once we have defined our model, we can query the table using Flask SQLAlchemy’s query method. Here’s an example of how to query all users:

    
users = User.query.all()

for user in users:
    print(user.username)
    
  

Paginating Data

When dealing with large datasets, it is common to use pagination to limit the number of results returned per page. Flask SQLAlchemy provides a paginate method to easily paginate data. Here’s an example of how to paginate users:

    
page = request.args.get('page', 1, type=int)
per_page = 10

users = User.query.paginate(page, per_page, False)

for user in users.items:
    print(user.username)
    
  

In the above example, we are paginating users with 10 results per page. The paginate method returns a Paginate object that contains the paginated data as well as information about the current page and total number of pages.

By following these simple steps, you can easily query tables and paginate data in Flask SQLAlchemy. This can be useful when working with large datasets or when building web applications that require displaying data in a paginated format.