Home Backend Development Python Tutorial Django vs. Flask: A comparative analysis of Python web frameworks

Django vs. Flask: A comparative analysis of Python web frameworks

Jan 19, 2024 am 08:36 AM
python flask django

Django vs. Flask:Python Web框架的对比分析

Django and Flask are both leaders in Python web frameworks. They both have their own advantages and applicable scenarios. This article will conduct a comparative analysis of these two frameworks and provide specific code examples.

  1. Development Introduction

Django is a full-featured Web framework, its main purpose is to quickly develop complex Web applications. Django provides many built-in functions, such as ORM (Object Relational Mapping), forms, authentication, management backend, etc. These features make Django very advantageous in handling large-scale web applications.

Flask is a lightweight web framework, its main purpose is to provide an easy way to quickly build web applications. Unlike Django, the core of Flask only contains the simplest functions, such as routing, request context, sessions, templates, etc. This allows developers to customize their own frameworks.

  1. Framework structure

Most of Django’s functions are composed of various built-in applications. The functions of these applications vary, but they are all composed according to Django's rules. For example, Django's ORM application is provided by Django itself, the template application is provided by Django itself, and Django's form application is provided by a third party. Through the combination of these applications, we can quickly complete the construction of Web applications.

Flask's framework structure is relatively free, and we can organize our own application structure as needed. For example, we can create a directory named "main", place all routes, templates, and static files in this directory, and then initialize it through an instance of Flask. You can also create different Blueprints, place different functional modules in different Blueprints, and then use Flask instances to combine them.

  1. Routes

In Django, routes are defined by urlconf, which is a mapping of discovery URLs and corresponding views. For a given URL, Django will sequentially find its matching URL in the urlconf and map it to the corresponding view, while passing the relevant parameters.

In Flask, routes are defined by decorators. A decorator contains a URL path and its corresponding function. For example, the following is a route definition in a Flask application:

from flask import Flask
app = Flask(__name__)

@app.route('/hello')
def hello():
    return 'Hello, World!'
Copy after login

This code defines a route that, when accessing the /hello path, will call the hello function and return the "Hello, World!" string .

  1. Database

Django has a built-in ORM (Object Relational Mapping), which provides support for a variety of databases. Based on ORM, we can use Python code to define the data model, and can easily perform addition, deletion, modification and query operations.

Flask does not have a built-in ORM, but it works well with several excellent ORMs. For example, we can use SQLAlchemy as an ORM to perform database operations. The following is a Flask sample code that uses SQLAlchemy for database query:

from flask import Flask
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql://user:password@localhost/test'
db = SQLAlchemy(app)

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)

    def __repr__(self):
        return '<User %r>' % self.username

@app.route('/user')
def user_detail():
    user = User.query.filter_by(username='john').first()
    return 'User email is ' + user.email
Copy after login

In this code, we define a User object, which inherits from db.Model. Then we use SQLAlchemy's query language to query user data that meets the conditions through User.query.filter_by.

  1. Template engine

Django provides a built-in template engine, which makes it very convenient for us to design templates. The Django template engine provides many built-in tags and filters for efficient template rendering.

Flask does not have a built-in template engine. Developers can use excellent template engines such as Jinja2 to process templates. The following is a Flask sample code that uses Jinja2 template rendering:

from flask import Flask, render_template

app = Flask(__name__)

@app.route('/hello')
@app.route('/hello/<name>')
def hello(name=None):
    return render_template('hello.html', name=name)
Copy after login

In this code, we use the render_template function to render the hello.html template. Jinja2 template tags can be used in hello.html to render dynamic content.

  1. Summary

Django and Flask are both excellent frameworks among Python web frameworks. They each have their own advantages and applicable scenarios. If we need to develop a complex web application, Django may be more suitable. And if we just need to quickly build a small web application, Flask may be better. In actual development, we can choose the appropriate framework according to our needs.

In the code examples, we use keywords such as ORM and template engine. Their specific implementation requires code writing, and the article needs to show the differences through specific example codes. Through specific code samples, readers can better understand the differences between Django and Flask.

The above is the detailed content of Django vs. Flask: A comparative analysis of Python web frameworks. 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
WWE 2K25: How To Unlock Everything In MyRise
1 months 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)

Do mysql need to pay Do mysql need to pay Apr 08, 2025 pm 05:36 PM

MySQL has a free community version and a paid enterprise version. The community version can be used and modified for free, but the support is limited and is suitable for applications with low stability requirements and strong technical capabilities. The Enterprise Edition provides comprehensive commercial support for applications that require a stable, reliable, high-performance database and willing to pay for support. Factors considered when choosing a version include application criticality, budgeting, and technical skills. There is no perfect option, only the most suitable option, and you need to choose carefully according to the specific situation.

HadiDB: A lightweight, horizontally scalable database in Python HadiDB: A lightweight, horizontally scalable database in Python Apr 08, 2025 pm 06:12 PM

HadiDB: A lightweight, high-level scalable Python database HadiDB (hadidb) is a lightweight database written in Python, with a high level of scalability. Install HadiDB using pip installation: pipinstallhadidb User Management Create user: createuser() method to create a new user. The authentication() method authenticates the user's identity. fromhadidb.operationimportuseruser_obj=user("admin","admin")user_obj.

Navicat's method to view MongoDB database password Navicat's method to view MongoDB database password Apr 08, 2025 pm 09:39 PM

It is impossible to view MongoDB password directly through Navicat because it is stored as hash values. How to retrieve lost passwords: 1. Reset passwords; 2. Check configuration files (may contain hash values); 3. Check codes (may hardcode passwords).

How to optimize MySQL performance for high-load applications? How to optimize MySQL performance for high-load applications? Apr 08, 2025 pm 06:03 PM

MySQL database performance optimization guide In resource-intensive applications, MySQL database plays a crucial role and is responsible for managing massive transactions. However, as the scale of application expands, database performance bottlenecks often become a constraint. This article will explore a series of effective MySQL performance optimization strategies to ensure that your application remains efficient and responsive under high loads. We will combine actual cases to explain in-depth key technologies such as indexing, query optimization, database design and caching. 1. Database architecture design and optimized database architecture is the cornerstone of MySQL performance optimization. Here are some core principles: Selecting the right data type and selecting the smallest data type that meets the needs can not only save storage space, but also improve data processing speed.

How to use AWS Glue crawler with Amazon Athena How to use AWS Glue crawler with Amazon Athena Apr 09, 2025 pm 03:09 PM

As a data professional, you need to process large amounts of data from various sources. This can pose challenges to data management and analysis. Fortunately, two AWS services can help: AWS Glue and Amazon Athena.

Python: Exploring Its Primary Applications Python: Exploring Its Primary Applications Apr 10, 2025 am 09:41 AM

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

The 2-Hour Python Plan: A Realistic Approach The 2-Hour Python Plan: A Realistic Approach Apr 11, 2025 am 12:04 AM

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Can mysql connect to the sql server Can mysql connect to the sql server Apr 08, 2025 pm 05:54 PM

No, MySQL cannot connect directly to SQL Server. But you can use the following methods to implement data interaction: Use middleware: Export data from MySQL to intermediate format, and then import it to SQL Server through middleware. Using Database Linker: Business tools provide a more friendly interface and advanced features, essentially still implemented through middleware.

See all articles