Python

Common Ways to Create Web Applications in Python

The following article describes some Common Ways to Create Web Applications in Python.

Basically, there are several common ways to create web applications in Python, each with its own strengths and use cases. For instance, the following are some of the most popular approaches and frameworks.

Django

Django is a high-level, full-stack web framework for building robust and scalable web applications quickly. It includes an ORM (Object-Relational Mapping) for database interaction, an authentication system, and a templating engine. Django follows the “batteries-included” philosophy, providing many built-in features, including admin panels, security features, and more. It’s an excellent choice for building complex, data-driven web applications.

Official Website: https://www.djangoproject.com/

Flask

Flask is a lightweight and flexible micro-framework for building web applications. It provides essential components like routing, request handling, and templating, allowing developers to choose additional libraries or extensions as needed. Flask is known for its simplicity and minimalism, making it a great choice for small to medium-sized projects and RESTful APIs.

Official Website: https://flask.palletsprojects.com/

FastAPI

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It provides automatic interactive documentation and validation of request and response data, making it an excellent choice for creating RESTful APIs with minimal boilerplate code. It’s particularly popular for building microservices.

Official Website: https://fastapi.tiangolo.com/

Tornado

Tornado is a non-blocking, asynchronous web framework and networking library. It is well-suited for building real-time applications like chat servers, long polling, and WebSockets. Tornado’s asynchronous nature makes it highly efficient for handling a large number of concurrent connections.

Official Website: https://www.tornadoweb.org/en/stable/

Bottle

Bottle is a simple and lightweight micro-framework for building small web applications. It is designed to be easy to use and has no external dependencies. Bottle is often used for small projects or prototyping.

Official Website: https://bottlepy.org/docs/dev/

Pyramid

Pyramid is a flexible and modular web framework that allows developers to choose and integrate various components to build web applications. It’s suitable for both small and large projects, and it provides great flexibility in terms of database, templating, and authentication choices.

Official Website: https://trypyramid.com/

CherryPy

CherryPy is an object-oriented web framework that allows developers to build web applications in a manner similar to writing Python programs. It is lightweight and has a minimal learning curve. CherryPy’s simplicity makes it suitable for smaller projects.

Official Website: https://cherrypy.org/

Web2py

Web2py is a full-stack web framework with a focus on ease of use and deployment. It includes a built-in IDE for web application development, a web-based administrative interface, and support for various databases. Web2py aims to simplify the entire web development process.

Official Website: http://www.web2py.com/

Dash (for Data Visualization):Dash is a Python framework for building interactive, web-based data visualization applications. It’s often used with libraries like Plotly to create data dashboards and interactive charts.

Official Website: https://dash.plotly.com/introduction

Turbogears:TurboGears is a full-stack web framework that integrates multiple components like SQLAlchemy, Genshi, and more. It aims to provide a complete solution for web application development while remaining flexible.

Official Website: https://turbogears.org/

Your choice of web framework depends on your project’s requirements, your familiarity with the framework, and your specific use case. Each of these frameworks has its own strengths and trade-offs, so it’s essential to evaluate them based on your project’s needs and your development team’s expertise.


Further Reading

How to Perform Dataset Preprocessing in Python?

10 Unique Project Ideas Using Streamlit

Spring Framework Practice Problems and Their Solutions

How to Implement Linear Regression from Scratch?

Java Practice Exercise

How to Use Generators in Python?

10 Unique Project Ideas on AWS EC2

Getting Started with Data Analysis in Python

10 Unique Project Ideas That You Can Apply With React Only

The Benefits of Using Data Science in the Mortgage Industry: Better Outcomes for Borrowers and Lenders

Wake Up to Better Performance with Hibernate

Data Science in Insurance: Better Decisions, Better Outcomes

10 Unique Project Ideas on DevOps

Most Popular Trading Software

10 Unique Project Ideas on Blockchain

How to Use Decorators in Python?

10 Unique Project Ideas on Data Visualization

Breaking the Mold: Innovative Ways for College Students to Improve Software Development Skills

programmingempire

Princites

You may also like...

Leave a Reply

Your email address will not be published. Required fields are marked *