ORM in Python: A Beginner’s Guide
Introduction to ORM
Object-relational mapping (ORM) is a technique that allows you to access data in a relational database using an object-oriented programming (OOP) language. ORMs provide a layer of abstraction between your code and the database, which makes it easier to work with data.
ORMs work by mapping database tables to objects in your code. For example, if you have a database table called customers, you could create a class called Customer in your code. The ORM would then map the columns in the customers table to the properties of the Customer class.
Once you have mapped your database tables to objects, you can use the ORM to access data in your database. For example, you could use the following code to get all of the customers in your database:
Python
customers = orm.GetCustomers()
The ORM would then query the customers table and return a list of Customer objects.
Why use ORMs?
ORMs can make working with data in a relational database much more manageable. They can also help improve your code’s performance, as they can avoid the need to write complex SQL queries.
Here are some of the benefits of using ORMs:
- Easier to use: ORMs make working with data in a relational database easier by providing a layer of abstraction between your code and the database. This means that you can focus on your application logic and not worry about the details of how to access the database.
- Improved performance: ORMs can enhance the performance of your code by avoiding the need to write complex SQL queries. ORMs can also cache data in memory, which can further improve performance.
- Reduced code complexity: ORMs can reduce the code you need to write by providing a high-level API for accessing data in a relational database. This can make your code easier to maintain and understand.
Types of ORMs
Several different ORMs are available, each with its strengths and weaknesses. Some popular ORMs include:
- SQLAlchemy: SQLAlchemy is a popular and well-supported ORM for Python. It is very flexible and can be used with a variety of databases.
- Django ORM: The Django ORM is the ORM that is included with the Django web framework. It is easy to use and integrates well with Django’s other features.
- Peewee ORM: Peewee ORM is a lightweight ORM that is easy to learn and use. It is well-suited for small projects.
When to use ORMs
ORMs can be a valuable tool for developers needing to access relational database data. They can make it easier to work with data, improve the performance of your code, and reduce the amount of code you need to write.
However, ORMs are not always the best solution. If you need complete control over accessing your data, you may want to avoid using an ORM.
Using ORMs in Python
You will first need to install the ORM library to use an ORM in Python. Once you have installed the library, you can create a new object for the ORM class. Then, you can use the object to map database tables to objects in your code.
For example, the following code shows how to use the SQLAlchemy ORM to map a database table called customers to a class called Customer:
Python
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
engine = create_engine('mysql://user:password@localhost/database')
Session = sessionmaker(bind=engine)
session = Session()
class Customer(object):
__tablename__ = 'customers'
id = Column(Integer, primary_key=True)
name = Column(String(255))
email = Column(String(255))
def __init__(self, id, name, email):
self.id = id
self.name = name
self.email = email
for customer in session.query(Customer):