How to use ORM framework in Python server programming?

With the widespread use of Python in server-side programming, the ORM (Object Relational Mapping) framework has become an important part of Python server programming. The ORM framework simplifies database operations by mapping data in the database to Python objects and abstracts common interfaces, allowing developers to focus more on the implementation of business logic rather than underlying database operations. This article will introduce how to use the ORM framework in Python server programming.

Advantages of ORM framework

In traditional database operations, we need to use SQL statements to add, delete, modify, and query the database. Such operations require understanding of database structure, data table structure and SQL syntax, and are difficult to maintain and expand. The use of the ORM framework can map data tables to Python classes, abstracting the operations of adding, deleting, modifying, and querying, thus simplifying development. The advantages of the ORM framework are as follows:

1. Abstract data table

The data table is the most basic storage unit in the database. Using the ORM framework, we can map a data table into a Python class, and the attributes in the class correspond to the column names in the data table, thus realizing the abstraction of the data table. In this way, operating on the data table is equivalent to operating on the Python class.

2. Simplify operations

Using the ORM framework, we can use simple Python functions and methods to operate the database. We can encapsulate the underlying SQL operations and only need to call methods. You can perform add, delete, modify and check operations.

3. Reduce maintenance difficulty

Using the ORM framework can abstract the underlying details of database operations and reduce the coupling between the database and the code, thereby reducing maintenance and expansion. The difficulty allows developers to focus more on implementing business logic.

Choose the appropriate ORM framework

There are many ORM frameworks in Python, including Django ORM, SQLAlchemy, Peewee, etc. When choosing a suitable ORM framework, you need to consider the following aspects:

1. Is it compatible with your own development framework

If you are using a Python web framework, such as Flask or Django , you need to ensure that the ORM framework you choose is compatible with the framework.

2. Database support

Different ORM frameworks support different databases. For example, Django ORM only supports PostgreSQL, MySQL and SQLite, while SQLAlchemy supports more databases. Such as Oracle, SQL Server, MySQL, etc. Therefore, you need to choose an ORM framework suitable for your own use.

3. Function support

Different ORM frameworks provide different functional support for different application scenarios. You need to choose the ORM framework that meets your needs based on your own needs.

Using SQLAlchemy to implement ORM

In Python server programming, SQLAlchemy is one of the most popular ORM frameworks. It is a full-featured SQL toolkit and ORM library that can work with most databases. to interact. Below, we will introduce how to use SQLAlchemy to implement ORM.

Install SQLAlchemy

Before you start, you need to install SQLAlchemy first. You can use the pip command to install it.

pip install sqlalchemy

Connecting to the database

To use SQLAlchemy for ORM operations, you first need to establish a connection with the database. In SQLAlchemy, you can use create_engine()

from sqlalchemy import create_engine

DB_URI = 'postgresql://username:password@host:port/database'
engine = create_engine(DB_URI)

to connect to the database. Among them, DB_URI is the database connection string in the format of "{dialect}://{user}:{password}@{host}:{port }/{database}", for example, the connection string in PostgreSQL format is:

postgresql://myuser:mypassword@localhost:5432/mydatabase

Create data table and Python class

To use SQLAlchemy for database operations, you need to map the data table to a Python class. The Python class corresponds to the data table of the database, and the attributes of the class correspond to the column names in the table. Before creating a Python class, you first need to create a data table. Data tables in SQLAlchemy are represented as Table. You can use the declarative_base() function to create a base class, and then use the base class to define the mapping relationship between Python classes and database tables.

from sqlalchemy import Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'

    id = Column(Integer, primary_key=True)
    name = Column(String)
    age = Column(Integer)
    email = Column(String)

In the above code, the User class inherits from the Base class, the __tablename__ attribute specifies the corresponding data table name, and then each attribute corresponds to the column in the data table.

Implementing ORM operations

Now that we have established a database connection and created a mapping relationship between Python classes and data tables, we can now operate the database.

Insert data

To insert data, you can use the session.add() method, and to commit a transaction, use the session.commit() method.

from sqlalchemy.orm import sessionmaker

Session = sessionmaker(bind=engine)
session = Session()

user = User(name='Tom', age=20, email='tom@example.com')
session.add(user)
session.commit()

Query data

Using SQLAlchemy to perform query operations is mainly divided into two steps:

1. Create the query data table Object, and use Session to create a Query object .
2. Use methods such as filter() and order_by() in the Query object to query.

users = session.query(User).filter(User.age > 18).order_by(User.age.desc()).all()
for user in users:
    print(user.name, user.age, user.email)

Update data

Update data can be updated using the session.add() method.

user = session.query(User).filter_by(name='Tom').first()
user.age = 21
session.add(user)
session.commit()

Delete data

To delete data from the database, you can use the session.delete() method to perform the deletion operation.

user = session.query(User).filter_by(name='Tom').first()
session.delete(user)
session.commit()

总结

在Python服务器编程中，ORM框架可以提供数据抽象、简化操作和降低维护难度的优势，能够加快开发速度。在选择ORM框架时，需要考虑自己的技术栈以及需求，选择相应的ORM框架。本文以SQLAlchemy为例，介绍了如何使用SQLAlchemy实现ORM操作，包括连接数据库、创建数据表和Python类以及实现增删改查操作。

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