Popular Python Web Frameworks to Use in 2025

As we enter 2025, Python web frameworks are becoming more advanced and diverse than ever. They are empowering developers to create everything from simple sites to complex web applications. Finding the best Python framework for web development is key to building efficient and scalable solutions. In this article, we’ll walk through a comprehensive list of Python web frameworks, showcasing the best ones developers can use in 2025. We’ll also compare these frameworks based on their speed, reliability, features, and more.

Table of Contents

• What Are Web Frameworks?
• Types of Web Development Frameworks
• Difference between Front-End Frameworks and Back-End Frameworks
• Top Python Web Frameworks to Learn in 2025
  • Django
  • Flask
  • FastAPI
  • Tornado
  • Pyramid
  • CherryPy
  • Dash
  • PyScript
  • TurboGears
  • Sanic
• Comparison of Python Web Frameworks
• Why is Python Becoming the First Choice for Developers?
• Benefits of Using Web Development Frameworks
• Conclusion
• Frequently Asked Questions

What Are Web Frameworks?

Web frameworks are pre-existing software packages which make the development and maintenance of web applications simpler. They offer a framework and guidelines that help developers work through common tasks such as routing, database interaction, and user authentication more easily.

By employing a web framework, the developer no longer needs to keep re-inventing the wheel with each project. Most frameworks come bundled with built-in libraries and utilities that make the development process faster. The better-known instances include Django with Python, Rails with Ruby, and Express with Node.js. Using these frameworks ensures that developers spend less time on building functions from scratch and addressing lower-level matters.

Also Read: Python 3.14 Update – What’s New in This Sweet Slice of π?

Types of Web Development Frameworks

Python provides a variety of web development frameworks to meet various project requirements and developer tastes:

• Full-Stack Frameworks: These frameworks manage database interactions, URL routing, authentication, and frontend templating in one complete package. Django tops this list, offering everything developers require straight out of the box.
• Microframeworks: They provide core functionality while allowing developers to choose their own components for tasks like database access or form validation. This flexibility is perfect for smaller projects or specialized applications. Flask and Bottle represent this lightweight approach.
• Asynchronous Frameworks: These frameworks take advantage of Python’s async feature to provide stunning speed and performance for new web services. Frameworks like Sanic and FastAPI are meant for high-performance applications that require dealing with numerous concurrent connections.
• Backend Frameworks: They efficiently handle requests, process data, and provide secure endpoints for frontend applications to consume. Backend frameworks like FastAPI, Django REST, and Tornado hence focus on server-side operations, database management, and business logic implementation.
• Frontend Frameworks: While Python is primarily backend-focused, frameworks like Django with Hotwire, HTMX support, and Dash enable developers to create interactive user interfaces. These tools help bridge Python backend code with frontend functionality without extensive JavaScript.

The richness of Python web frameworks guarantees that developers can choose the appropriate tool depending on project needs, team skills, and performance requirements. From lean solutions to full-fledged solutions, Python’s ecosystem has everything in between web development and data science requirements.

Difference between Front-End Frameworks and Back-End Frameworks

Front-end and back-end frameworks play distinct roles in web development, each catering to different aspects of a web application. Below are key differences between the two:

Feature	Front-End Frameworks (Python)	Back-End Frameworks (Python)
Focus	Client-side (User Interface & Experience)	Server-side (Logic, Database, Authentication)
Primary Role	Building interactive and responsive interfaces	Handling requests, processing data, and managing databases
Common Technologies	HTML, CSS, JavaScript, and Python (via frameworks like Anvil, PyScript, Streamlit, JustPy)	Python
Tasks Handled	UI rendering, user interaction, and state management	Authentication, database integration, server-side security
Tooling Provided	Widgets, event handling, layout rendering, interactivity	Routing, middleware, ORM, API development
Examples (Python only)	Anvil, PyScript, Streamlit, JustPy	Django, Flask, FastAPI
Execution Environment	Runs in the browser or via frontend-specific servers	Runs on the server

Top Python Web Frameworks to Learn in 2025

With web development rapidly advancing in 2025, Python stands out for its clean syntax and powerful ecosystem. In this section, we’ll explore 10 popular Python web frameworks, offering a brief look at their strengths and weaknesses.

1. Django

Django is a Python web framework based on the Model-View-Template (MVT) architecture. Used by leading companies such as Google, YouTube, and Instagram, Django has increased in popularity with Python’s swift growth. It supports the Convention Over Configuration and DRY (Don’t Repeat Yourself) principles, simplifying web development.

Django is built with security considerations, providing protection in the form of blocking code execution in templates. Its strong set of features sets it apart from other back-end frameworks.

For further information about Django, please visit here.

Advantages of Django:

• High-Quality Documentation: Known for its extensive and continuously developing resources in many languages.
• SEO-Highlightable URL Handling: Supports human-readable URLs rather than server IPs, which makes SEO integration easy.
• Beginner-Friendly: No in-depth back-end experience required to create fully featured websites. It manages multiple files and database queries with ease.
• Extensible Architecture: Inbuilt support for pluggable apps makes adding third-party components an easy task.
• Built-in Security: Deals with common security vulnerabilities by default, saving developers from undue effort.

Disadvantages of Django:

• Limited Scalability: Unsuitable for apps that need ultra-scalability.
• Steep Learning Curve: Inexperienced developers might find it complicated initially.
• Monolithic Design: Its tightly coupled design might restrict flexibility and customization.

Also Read: Deploying Django App on Google Compute Engine

2. Flask

Flask is a lightweight Python microframework that is flexible and easy to use. First released in 2010, Flask only sends bare essentials by default, and the programmer can pick their own elements for database and authentication-like features. Based on Werkzeug and Jinja2, Flask is best suited for small-to-medium-sized applications, APIs, and projects that demand direct control.

In contrast to Django, Flask does not impose structure or include built-in features, offering greater liberty in app development. While light, it’s used by production-grade services of industry leaders like Netflix, Reddit, and Airbnb.

For further information about Flask, please visit here.

Advantages of Flask:

• Simplicity & Flexibility: Provides a clean, easy-to-read appearance that is simple to understand and can be personalized for every project.
• Lightweight & Quick: Runs with minimal overhead, making it ideal for microservices, APIs, or lightweight web apps.
• Extensible Ecosystem: Robust third-party extension support like Flask-SQLAlchemy, Flask-Login, and Flask-RESTful.
• Modular Design: Facilitates a plug-and-play structure and gets along well with other libraries and tools.
• Documentation & Community: Supported by excellent documentation and an ever-expanding developer community.
• WSGI Compliant: 100% WSGI 1.0 compliant for seamless deployment and integration.

Disadvantages of Flask:

• Bring-Your-Own Tools: Does not include integrated solutions for ORM, form validation, and admin interfaces; developers must implement or integrate them themselves.
• Security & Maintenance: There is little security present, but more advanced protections (e.g., CSRF, authentication) need third-party solutions.
• Scalability Complexity: Scalable, but requires careful planning and skilled developers to build big applications.
• Limited Defaults: Newcomers may find it challenging with the absence of out-of-the-box features and reliance on add-ons.

Also Read: Which is Better for Machine Learning: Flask vs Django?

3. FastAPI

FastAPI is a new, high-performance Python framework that is aimed at building APIs. It leverages Python type hints for automatic validation and documentation of data, with exceptional performance due to asynchronous programming. It is built on Starlette and Pydantic and is optimized for developers looking to create fast, efficient, and scalable API services.

FastAPI differentiates itself in the world of API development by adopting OpenAPI standards and including auto-generated interactive documentation. Its usage has increased immensely since its release in 2018, and now leads Django by monthly downloads on PyPI.

For further information about FastAPI, please visit here.

Advantages of FastAPI:

• Asynchronous Support & Performance: Native support for async and fast request processing through ASGI and Uvicorn.
• Automatic Docs: Auto-generates Swagger UI and ReDoc documentation by default.
• Type-Driven Development: Leverages Python 3.6+ type hints for validation, serialization, and auto-completion.
• Modular & Scalable: Lightweight micro-framework, ideal for containerization and production deployments.
• Secure by Design: Implements OAuth2, JWT, and other authentication schemes.
• Developer Productivity: Provides quick debugging, clean syntax, and robust IDE/editor support.

Disadvantages of FastAPI:

• Younger Ecosystem: Less mature than Django or Flask, with a smaller community and fewer plugins.
• Limited Full-stack Capability: Only backend APIs, with additional frontend solutions needed.
• Learning Curve: Type-hinting, dependency injection, and async patterns can be difficult for newbies.

4. Tornado

Tornado is an open-source, high-performance Python web application framework and asynchronous networking library created originally by FriendFeed. It is optimized for making thousands of connections concurrently. This makes it a very good choice for real-time apps, such as live data feeds, chat platforms, and long-poll WebSocket connections.

Based on non-blocking I/O and Python’s asyncio integration, Tornado shines in applications with high concurrency and low latency requirements. It also comes with features such as built-in authentication of users, support for custom templates, third-party auth, and internationalization.

For further information about Tornado, please visit here.

Advantages of Tornado:

• Asynchronous & Non-blocking: Optimized to handle thousands of connections at the same time.
• Real-time Communication: Native support for WebSockets and long-polling makes it suitable for dynamic, live applications.
• Scalable & Lightweight: Low overhead and scalable architecture support high-performance deployments.
• Built-in Utilities: Supports user auth, templating, and making the app work in multiple languages without needing extra setup.

Disadvantages of Tornado:

• Steeper Learning Curve: Async programming and event loops can be challenging for newbies.
• Specific Use Cases: Better for real-time or I/O-bound apps than standard web development.
• Smaller Ecosystem: Fewer third-party extensions than more popular frameworks such as Flask or Django.

Also Read: Top 10 Open Source Python Libraries for Building Voice Agents

5. Pyramid

Pyramid is an open-source Python web framework. It is as simple as microframeworks like Flask, yet scalable as full-stack choices like Django. Aiming for the middle ground between small prototype apps and big business enterprise apps, it is both flexible and solid. Popular with major businesses such as Dropbox, Mozilla, and SurveyMonkey, Pyramid has a modular structure, testability features, and an elegant design.

It supports several templating engines, routing frameworks, and authentication methods, which makes it very customizable according to project requirements. Pyramid is also WSGI-compliant and plays nicely with libraries such as SQLAlchemy, but can use other database tools if you want.

For further information about Pyramid, please visit here.

Advantages of Pyramid:

• Flexible & Scalable: Suitable for both simple apps and intricate enterprise systems.
• Modular & Flexible: Allows developers to choose only the parts they require.
• Strong Testing Support: Integrated testing and debugging tools.
• Flexible Auth: Seamlessly supports authentication and authorization mechanisms.
• Templating & Routing: Facilitates Mako, Chameleon, and Jinja2 with flexible routing through URL dispatch or traversal.

Disadvantages of Pyramid:

• Steep Learning Curve: Ideal for developers who have experience with Python web development.
• Overhead for Small Apps: May be more than necessary for extremely simple applications.
• Manual Setup: Needs configuring tools such as ORM, form validation, and templating to be done explicitly.

6. CherryPy

CherryPy is a lightweight, object-oriented web framework for Python that allows developers to write web applications rapidly and effectively. Being one of the oldest Python web frameworks (first published in 2002), it’s fast, secure, and minimalist.

CherryPy enables developers to code web apps like any other Python application using OOP concepts. Although it doesn’t have built-in templating or ORM systems, it’s very extensible and plays well with external libraries and tools. Netflix, Hulu, and Indigo Domotics are some of the companies that use CherryPy in their tech stack.

For further information about CherryPy, please visit here.

Advantages of CherryPy:

• Production-Ready: Includes a stable, multithreaded WSGI web server.
• Minimal & Lightweight: Simple to set up, use, and extend.
• OOP Design: Promotes writing modular, sustainable code.
• Cross-Compatible: Supports Python 2.7+, Python 3.5+, PyPy, Jython, and even Android.
• Customizable: Includes a solid config system and plugin system.
• Integrated Tools: Direct support for sessions, caching, encoding, static files, and testing.

Disadvantages of CherryPy:

• Lacks Full-Stack Features: Does not have built-in support for database access or templating.
• Documentation Gaps: It can be hard for new developers because of weak documentation.
• Backend-Oriented: Manages mostly the HTTP logic; front-end integration should be treated independently.

7. Dash

Dash framework are based on a component-based structure with interactive widgets such as sliders, dropdowns, and graphs. It is well-optimized for building analytical dashboards, real-time monitoring dashboards for web applications, and responsive, mobile-friendly interfaces. Based on Flask, Plotly.js, and React.js, Dash is flexible and powerful yet easy to use for Python programmers.

For further information about Dash, please visit here.

Advantages of Dash:

• Python-Only Development: Build the entire application using Python only, no need to write in frontend code..
• Rich Visualizations: Interactive, high-fidelity charts and graphs with effortless integration into Plotly.
• Component-Based UI: Construct responsive UIs using pre-built components such as sliders, dropdowns, and tabs.
• Mobile-Friendly: Responsive designs by default mean usability across platforms.
• Real-Time Interactivity: Python callbacks between UI inputs and outputs, perfect for live dashboards.
• Deployment-Ready: Deploy with ease on local servers, cloud infrastructure, or Dash Enterprise.
• Fantastic for Data Science: Designed with users who have analytical minds and little web programming background.
• Strong Ecosystem: Works well with the Python science stack (NumPy, Pandas, etc.).

Disadvantages of Dash:

• Limited Custom UI: Advanced front-end customization can need React or CSS expertise.
• Performance Limitations: Can be slow with extremely big data or intricate interactivity unless tuned.
• Not a Full-Stack Framework: Though excellent for front-end visualizing, it lacks inherent database support or authentication, which you’ll have to add yourself.
• Callback Complexity: State management and callbacks can become difficult to debug and handle in big applications.

8. PyScript

PyScript is an open-source framework developed by Anaconda in 2022 to let developers create interactive web apps in Python within the browser. It embeds Python code inside HTML, making it possible to build rich, client-side apps without requiring conventional JavaScript programming. It takes advantage of technologies such as Pyodide and WebAssembly to run Python code in the browser environment.​

For further information about Pyscript, please visit here.

Advantages of PyScript:

• Lower Barrier to Entry: Enables Python programmers to develop web applications without having to learn JavaScript, thus making web development easier.
• Rapid Prototyping: Enables rapid development and testing of ideas in the browser itself.
• Improved Privacy: Handles data on the client side, minimizing the need to send sensitive information to servers.
• Learning Resource: Acts as a rich learning resource for education in programming by enabling students to observe instantaneous feedback of their code in the browser

Disadvantages of PyScript:

• Performance Limitations: Executing Python in the browser through WebAssembly might result in decreased performance compared to native JavaScript programs.
• Limited Cross-Browser Support: Does not work uniformly on every browser, with best performance on newer browsers such as Chrome and Firefox.
• Dependence on JavaScript: Even though PyScript employs Python syntax, it depends on the underlying JavaScript and browser technologies, which can require some knowledge of JavaScript for sophisticated operations.
• Early Development Phase: Being a new framework, PyScript is still in the process of development, and developers might find bugs or sparse documentation.

Also Read: All About Python 3.13.0

9. TurboGears

TurboGears is a robust, full-stack web application framework built for rapid data-driven application extensibility and scalability using Python. It leverages a group of best-in-class Python packages into a homogeneous framework with optimal developer productivity, requiring minimal setup. Initially implemented to fill in the gap between microframeworks and full-stack frameworks, TurboGears empowers developers with the ability to begin with an easy app that can be transformed into a rich solution when desired.

For further information about TurboGears, please visit here.

Advantages of TurboGears:

• Flexible and Modular: Begin small with low setup and scale to full-stack when necessary.
• Perfect for Data-Driven Applications: Built expressly to make it easy to build data-heavy web apps.
• Rich Frontend Features: Smooth JavaScript and AJAX integration with ToscaWidgets and other libraries.
• Suited for Beginners and Experts: Open-source and documented, ideal for new developers and seasoned teams alike.
• Multi-Version Python Support: Supports prominent Python versions such as 2.7, 3.4 up to 3.8.
• Strong Community and Ecosystem: Regularly updated with a set of community plugins and extensions.

Disadvantages of TurboGears:

• Scalability Complexity: Though extensible, scaling the framework for large-scale, enterprise-class apps might demand meticulous planning and experience.
• Learning Curve: Although beginner-friendly, becoming an expert in its full-stack features might take time owing to the incorporation of multiple technologies.

10. Sanic

Sanic is a Python web framework for high-performance, asynchronous Python, optimized for speed and scalability. It’s built on Python 3.9+ and uses asyncio with uvloop, allowing non-blocking requests to be handled. This makes it perfect for applications that need high concurrency and real-time data processing.

The API of Sanic is designed similar to Flask, making an easy learning experience for developers who already know Flask

For further information about Sanic, please visit here.

Advantages of Sanic:

• Speed and Efficiency: Built to process a high volume of requests per second, making it among the fastest Python web frameworks.
• Scalability: Ideal for developing scalable applications, ranging from simple APIs to intricate web services. ​
• Flask-like API: Provides a familiar API for Flask developers, making it easy to transition and minimizing the learning curve. ​
• Community Driven: Actively maintained and supported by an increasing community of developers. ​

Disadvantages of Sanic:

• Small Ecosystem: In contrast to more mature frameworks such as Django or Flask, Sanic has a relatively limited set of third-party plugins and extensions.​
• Complexity for Newbies: Asynchronous coding can be complex for developers who are new to the idea, which can even drive up the learning curve.​
• Limited Windows Support: Sanic might be limited while running on Windows environments because of uvloop dependencies.

Comparison of Python Web Frameworks

Python has a diverse ecosystem of web frameworks, each designed for particular development requirements varying from rapid prototyping to production-level and scalable applications. The table below compares the popular Python web frameworks listed above, on the basis of their architecture, performance, simplicity, best use cases, important features, and limitations.

Framework	Type	Async Support	Performance	Learning Curve	Ideal For	Notable Features	Limitations
Django	Full-stack	Limited	Moderate	Moderate	Large-scale apps, Admin panels	ORM, Admin interface, Authentication, Batteries-included	Heavyweight, less flexible for microservices
FastAPI	Microframework	Native	Very High	Easy-Moderate	APIs, async apps, modern web	Automatic docs (Swagger), async/await, type hints	Newer ecosystem, async learning curve
Flask	Microframework	Via plugins	Moderate	Very Easy	Simple web apps, MVPs, microservices	Minimalist, Jinja templating, Extensions for ORM, Auth	Not async-native, lacks built-in tools
Tornado	Asynchronous framework	Native	High	Moderate-Hard	Real-time apps, long-lived connections	Non-blocking I/O, WebSockets, Coroutine-based	Complex syntax, limited community
Pyramid	Hybrid (flexible size)	Via plugins	High	Moderate	Scalable apps, testing-intensive dev	Minimalism + flexibility, HTML form support, routing system	Requires deeper setup for simple apps
CherryPy	Minimalist	Threaded	High	Easy	Portable apps, embedded systems	Built-in WSGI server, multithreaded, object-oriented	Sparse docs, no built-in templating or DB access
Dash	Analytics/Dashboard	No (sync)	Moderate	Easy	Data viz, dashboards	Interactive graphs, Plotly support, mobile-friendly UI	Limited to data apps, not for general web dev
PyScript	Front-end framework	N/A	Depends on browser	Easy	Embedding Python in HTML	Run Python in browser, JS interoperability, UI components	Limited browser support, not for full backend
TurboGears	Full-stack	Partial	High	Moderate	Scalable full-stack apps	ORM, templating, hybrid MVC/micro support	Less popular, requires configuration
Sanic	Micro/Async framework	Full	Very High	Easy-Moderate	High-performance async apps	Async/await support, uvloop, Flask-like syntax, WSGI/ASGI compatible	Smaller community, async-only

Why is Python Becoming the First Choice for Developers?

Globally, Python is quickly becoming programmers’ first choice of programming language. Its simple syntax lowers the learning barrier considerably, allowing beginners to learn the fundamentals and start developing applications with little frustration. Its flexibility differentiates Python from competitors. Python succeeds in web application development, data analysis, applications of AI, and task automation. With such a spectrum of applications, it is easy for developers to change specialties without neglecting their central language knowledge.

Also, Python’s extensive ecosystem is the biggest contributor to its adoption level. Web frameworks such as Django and Flask remove the hassle of writing the same common functions over and over again. Such pre-built configurations tackle common problems, greatly reducing development cycles.

The community strength of Python is particularly noteworthy. Rich documentation, active forums, and plenty of learning resources ensure that troubleshooting is easy. Developers hardly get stuck for long when help is so easily accessible.

Benefits of Using Web Development Frameworks

Using Python web frameworks can offer several advantages to your development cycle, including:

• Speed and Efficiency: Django and Flask enable developers to create applications in a faster time with less code using Python’s minimal syntax and efficient libraries.
• Consistency and Modularity: Python frameworks deliver well-organized structure that makes applications easier to keep and extend with time.
• Security: Frameworks such as Django feature robust integrated security components that safeguard against usual web weaknesses and threats.
• Community Support: Python web frameworks boast huge, vigorous communities offering rich documentation, add-ons, and active help forums.
• Scalability: Ranging from Flask’s minimalism to Django’s rich framework, Python frameworks accommodate applications from small projects to enterprise applications.
• Testing and Debugging: Python’s testing system integrates well with frameworks, supporting strong testing tools such as pytest and unit test for stable applications.

Conclusion

Python web frameworks offer a great balance between developer productivity and application performance. They take advantage of Python’s readability and large library ecosystem and add specialized tools for the difficulties of web development. From developing a straightforward API using Flask to creating a sophisticated application using Django, these frameworks simplify development without losing Python’s friendly feel.

Choosing the best Python web framework completely depends on your project’s particular requirements, size, and development objectives. Whether you’re developing lightweight APIs, data-driven dashboards, or enterprise-scale applications. Python has a vibrant ecosystem of frameworks each with its own strengths.

Finally, the better option depends on your team’s skill, performance needs, and scalability in the future. With a grasp of the fundamental traits and limitations of each framework, you can make a confident selection of the one that works best for your development plan.

Frequently Asked Questions

Q1. Which Python web framework is best for beginners?

A. Flask is often recommended for beginners due to its simplicity, minimal setup, and clear documentation. It provides enough flexibility for small projects and is easy to learn.

Q2. What is the most scalable Python web framework?

A. Django and FastAPI are highly scalable. Django offers a full-stack solution with built-in components, while FastAPI’s async support makes it suitable for modern, high-performance APIs.

Q3. When should I choose Dash or PyScript?

A. Dash is ideal for building interactive data dashboards, especially for data scientists. PyScript is great when you want to embed Python directly into frontend applications and enable Python-JS interaction.

Q4. Is FastAPI better than Flask?

A. FastAPI is newer and offers modern features like asynchronous support and automatic documentation. Flask is more mature and has a larger ecosystem. The choice depends on project needs.

Q5. Can I use CherryPy or Pyramid for large applications?

A. Yes, both CherryPy and Pyramid are capable of handling large-scale applications. CherryPy is known for its minimalism and performance, while Pyramid offers flexibility with a robust feature set.

Q6. Which frameworks support asynchronous programming?

A. FastAPI, Sanic, and Tornado support asynchronous programming out of the box. These are ideal when handling concurrent requests or building real-time applications.

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