Table of Contents
Install SQLAlchemy
Create database engine
Create session
adding data
submit data
Query data
update data
delete data
Summarize" >Summarize
Home Backend Development Python Tutorial Use Python SQLAlchemy skillfully to easily conquer the world of relational databases

Use Python SQLAlchemy skillfully to easily conquer the world of relational databases

Feb 25, 2024 am 08:01 AM

巧用 Python SQLAlchemy,轻松征服关系数据库世界

python sqlAlchemy is a powerful object-relational mapping tool library that allows development Personnel use Python objects to manipulate relational databases . This allows developers to easily create, query, and update data in the database without having to write complex SQL code.

Install SQLAlchemy

To use SQLAlchemy, you first need to install it. You can use the pip command to install:

from sqlalchemy import Column, Integer, String

class User(Base):
__tablename__ = "users"
id = Column(Integer, primary_key=True)
name = Column(String(50), unique=True)
email = Column(String(120), unique=True)
Copy after login

In this class, the __tablename__ attribute specifies the name of the table in the database. The id, name, and email attributes are respectively columns in the database. id is the primary key and is automatically incremented. name and email are columns of string type and are unique.

Create database engine

To map the ORM model to the database, you need to create a database engine. The database engine is an object that is responsible for interacting with the database.

For example, to create a database engine that connects to a SQLite database, you can write the following code:

from sqlalchemy import create_engine

engine = create_engine("sqlite:///database.sqlite")
Copy after login

In this code, "sqlite:///database.sqlite" is the connection string of the database.

Create session

To operate the data in the database, you need to create a session. A session is an object that represents an interaction with the database.

For example, to create a session, you can write the following code:

from sqlalchemy.orm import sessionmaker

Session = sessionmaker(bind=engine)
session = Session()
Copy after login

In this code, Session is a session class, which is bound to engine. session is a session object, which can use methods such as add(), delete() and commit() to operate in the database The data.

adding data

To add data to the database, you can use the add() method. For example, to add a piece of data to the users table, you can write the following code:

user = User(name="John Doe", email="johndoe@example.com")
session.add(user)
Copy after login

In this code, user is a User object that contains the data to be added. session.add(user) Adds the user object to the session.

submit data

To submit data to the database, you can use the commit() method. For example, to submit data, you can write the following code:

session.commit()
Copy after login

In this code, session.commit() commits the data in the session to the database.

Query data

To query data in the database, you can use the query() method. For example, to query all User objects, you can write the following code:

users = session.query(User).all()
Copy after login

In this code, session.query(User).all() queries all User objects and stores them in the users variable.

update data

To update data in the database, you can use the update() method. For example, to update the email address of John Doe, you would write the following code:

session.query(User).filter_by(name="John Doe").update({User.email: "johndoe@example.com"})
Copy after login

In this code, session.query(User).filter_by(name="John Doe") queries the user named John Doe and updates the email address for johndoe@example.com.

delete data

To delete data in the database, you can use the delete() method. For example, to delete a user named John Doe, you would write the following code:

session.query(User).filter_by(name="John Doe").delete()
Copy after login

In this code, session.query(User).filter_by(name="John Doe") queries users named John Doe and deletes them.

SQLAlchemy is a powerful ORM tool library that helps developers easily operate relational databases. Using SQLAlchemy, developers can quickly create, query, and update data in a database without writing complex SQL code.

The above is the detailed content of Use Python SQLAlchemy skillfully to easily conquer the world of relational databases. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. How to Fix Audio if You Can't Hear Anyone
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

How to solve the permissions problem encountered when viewing Python version in Linux terminal? How to solve the permissions problem encountered when viewing Python version in Linux terminal? Apr 01, 2025 pm 05:09 PM

Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

How Do I Use Beautiful Soup to Parse HTML? How Do I Use Beautiful Soup to Parse HTML? Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Serialization and Deserialization of Python Objects: Part 1 Serialization and Deserialization of Python Objects: Part 1 Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

How to Perform Deep Learning with TensorFlow or PyTorch? How to Perform Deep Learning with TensorFlow or PyTorch? Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Mathematical Modules in Python: Statistics Mathematical Modules in Python: Statistics Mar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Scraping Webpages in Python With Beautiful Soup: Search and DOM Modification Scraping Webpages in Python With Beautiful Soup: Search and DOM Modification Mar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

What are some popular Python libraries and their uses? What are some popular Python libraries and their uses? Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

How to Create Command-Line Interfaces (CLIs) with Python? How to Create Command-Line Interfaces (CLIs) with Python? Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

See all articles