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SQLAlchemy is an open sourcepython tool package that uses an object-oriented approach to operate relational database, provides an intuitive and convenient api, simplifying the development work of the relational database . The core idea of SQLAlchemy is object-relational mapping (ORM), which maps tables in relational databases to Python classes and maps rows in the database to Python objects to implement database operations. flexibility and code readability.
In SQLAlchemy, the entity refers to the table or view in the database, and the model refers to the Python class corresponding to the entity. There is a one-to-one correspondence between entities and models, and columns in entities are mapped to attributes in the model.
Session is the bridge between SQLAlchemy and the database. It encapsulates the database connection and operations on the database. A transaction is a logical unit of database operations, which ensures that a series of operations either all execute successfully or all fail to be rolled back.
SQLAlchemy provides rich query and filter functions, allowing developers to use Python code to construct complex query statements. Queries can be composed using chained operations, and filters can be used to limit the scope of query results.
SQLAlchemy supports multiple relationship types, including one-to-one, one-to-many, many-to-many, etc. Relationships can be defined using relationship attributes, which allow models to reference each other.
SQLAlchemy supports inheritance, allowing models to inherit from other models, thereby enabling code reuse and extension. Inheritance can be used to create abstract models and concrete models. The concrete model can inherit the properties and methods of the abstract model.
SQLAlchemy provides event and hook mechanisms that allow developers to execute custom code when specific events occur. Events and hooks can be used in model definition or session management, and can be used to implement logging recording, data verification and other functions.
ORM mode is the core idea of SQLAlchemy, which can significantly improve the readability and maintainability of code. The ORM mode allows developers to use Python code to operate the database without writing complex SQL statements.
Sessions and transactions are important mechanisms for SQLAlchemy to manage database connections and operations. Sessions can be used to perform a series of database operations, and transactions can ensure that these operations either all execute successfully or all fail to be rolled back.
Queries and filters are powerful tools for SQLAlchemy to obtain database data. Queries can be composed using chained operations, and filters can be used to limit the scope of query results.
Python SQLAlchemy ProgrammingThe art is a subtle knowledge that can significantly improve the reliability, readability, and maintainability of relational database applications. This article details the basic concepts, advanced usage, and best practices of SQLAlchemy to help you conquer the challenges of relational databases.
Sample code:
from sqlalchemy import Column, Integer, String, create_engine from sqlalchemy.orm import sessionmaker # 创建数据库引擎 engine = create_engine("postgresql://scott:tiger@localhost:5432/test") # 创建会话工厂 Session = sessionmaker(bind=engine) # 创建会话 session = Session() # 创建一个实体类 class User(object): id = Column(Integer, primary_key=True) name = Column(String(50), unique=True) email = Column(String(120), unique=True) # 创建一个用户对象 user = User(name="admin", email="admin@example.com") # 将用户对象添加到会话 session.add(user) # 提交会话 session.commit() # 查询所有用户 users = session.query(User).all() # 打印所有用户 for user in users: print(user.name, user.email) # 关闭会话 session.close()
This code demonstrates how to use SQLAlchemy to create a relational database model, insert data, query data and close the session. You can modify and extend it to suit your needs.
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