Python Frameworks: Top 10 Python Frameworks To Learn in 2025

Python frameworks will be essential for developers in 2025, offering pre-built modules and libraries to simplify web development, data science, machine learning, and automation. With growing demand for faster deployment cycles and scalable applications, these frameworks now support advanced asynchronous processing, modular design, and built-in AI capabilities. They are well-suited for building efficient and adaptable software across industries.

These frameworks save valuable time by reducing repetitive coding tasks, allowing developers to focus on building robust applications. 

In this blog, we'll explore the Python frameworks list you should learn in 2025. It covers versatile web frameworks like Django and Flask, as well as powerful data science tools like PyTorch. 

Python Frameworks: Top 10 Python Frameworks To Learn in 2025

To stay competitive in 2025, you need to know what is a framework in Python is and which ones drive real impact. Modern development trends like async-first design, real-time data processing, and AI integration are redefining Python frameworks. Whether you're building real-time dashboards, ML-driven pipelines, or scalable APIs for fintech and SaaS platforms, choosing the right framework is key. 

Based on speed, scalability, community backing, and adaptability, here are 10 Python frameworks developers should prioritize this year.

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Types of Frameworks in Python

Python frameworks fall into categories like full stack, microframeworks, and asynchronous frameworks, each designed for different development needs. Understanding these types helps you pick the right tool based on project scope, performance requirements, and scalability. 

The following table addresses some of the prominent types of Python frameworks, such as full-stack frameworks, along with their benefits, descriptions, and use cases. 

Also Read: Python Developer Salary in India in 2025 [For Freshers & Experienced]

Now that you understand the importance of selecting the right framework, let's explore the top 10 Python frameworks you should consider learning in 2025.

Top 10 Frameworks of Python to Consider in 2025

When choosing a Python framework in 2025, it’s important to consider your project’s purpose and the specific benefits and limitations of each option. You should also stay updated on current trends, including the rise of async-first designs, growing enterprise AI APIs, and evolving standards like compatibility with Python 3.13.

Depending on your project's needs, frameworks can simplify development by offering built-in tools and features, or they can provide flexibility for more custom solutions. 

Next, we'll cover the top 10 Python frameworks list, detailing their applications, use cases, and the specific tools they offer for different types of projects. 

Here’s a quick comparison of the top 10 Python frameworks in 2025, highlighting their core features and the types of projects they’re best suited for.

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Let's discuss each one of the above in detail.

1. Django

Django is a high-level Python web framework for fast development and clean, pragmatic design. It's known for its scalability and robustness, making it one of the most widely used frameworks in the industry.

Django’s built-in components like its ORM, URL routing, and database schema migration provide reliability and scalability, though it is not optimized for lightweight or async-first applications 

Django powers high-traffic platforms such as Instagram and Pinterest, demonstrating its ability to support scalable and high-performance web applications.

Features of Django:

• Authentication: Django has a built-in authentication system, including login, logout, and password management, which ensures secure user access.
• URL Routing: Provides a clean and flexible URL routing mechanism that allows for the creation of user-friendly URLs.
• ORM (Object-Relational Mapping): Simplifies database queries by mapping Python objects to database tables, reducing the need for raw SQL.
• Template Engine: Offers a simple, efficient, and secure templating engine for rendering HTML.
• Database Migrations: Automatically handles database schema changes, allowing developers to evolve their database structure without manual intervention.

Advantages of Django:

• Rapid Development: The built-in components and features allow for faster project completion without having to build common functionality from scratch.
• Security: Django protects against common web security vulnerabilities, such as SQL injection, cross-site scripting, and cross-site request forgery.
• Scalability: Django's modular approach and robust ORM make it easy to scale applications as traffic grows.
• Community and Support: A large, active community provides extensive documentation and third-party packages to extend functionality.

Companies Using Django:

Instagram, Mozilla, Pinterest, National Geographic, and more.

Also Read: Top 16 Django Project GitHub for Beginners and Experienced Professionals [2025]

2. Pyramid

Pyramid is a flexible and minimalistic Python framework known for its simplicity and scalability. It's designed for both small applications and large, complex systems, making it a popular choice for developers who require flexibility. 

Pyramid's routing system and HTML form validation allow for quick and efficient web application development. With the option to extend or replace its core components, Pyramid is perfect for building high-performance applications.

Features of Pyramid:

• Routing: Pyramid's flexible URL routing system supports dynamic routes and complex path matching, which is ideal for RESTful APIs.
• HTML Form Validation: It includes built-in support for form validation, reducing errors during form processing.
• Extensibility: Pyramid allows developers to choose their authentication systems, templating engines, and more, making it highly customizable.
• Security: Comes with robust security features such as built-in CSRF protection and a flexible authorization system.

Advantages of Pyramid:

• Customizability: Pyramid allows users to choose different libraries for different components, allowing it to be tailored to the project's needs.
• Ease of Learning: With a well-organized structure and clear documentation, Pyramid is easy for beginners to pick up while also offering advanced features for experienced developers.
• Scalability: Pyramid is perfect for projects of any size, from simple applications to large-scale systems with complex needs.

Companies Using Pyramid:

Reddit, Mozilla, and Yelp.

3. Turbo Gears

Turbo Gears is a Python framework that integrates various components, such as Genshi, SQLAlchemy, and WebOb, to streamline the development process. It's well-suited for building scalable, database-driven applications.

 With Turbo Gears, developers can easily manage complex data models and enhance their application's performance. It's a great choice if you're looking to work on projects with demanding database interaction and need flexibility.

Features of Turbo Gears:

• Component-Based: Turbo Gears integrates several libraries, such as Genshi for templating and SQLAlchemy for ORM, offering a modular approach.
• SQLAlchemy Integration: A powerful ORM that makes it easier to interact with databases by abstracting SQL queries into Python code.
• Genshi: An XML-based templating system that is both powerful and flexible for creating dynamic web content.
• WebOb: A utility for working with HTTP requests and responses, streamlining web application development.

Advantages of Turbo Gears:

• Rapid Development: Combines a robust set of components for developers to quickly build applications without starting from scratch.
• Flexibility: Developers can mix and match components based on their project's specific needs, offering a highly customizable development environment.
• Database Efficiency: Its built-in ORM makes working with databases seamless, helping manage large-scale data-driven applications.

Companies Using Turbo Gears:

The Washington Post, CNET.

4. Web2py

Web2py is a full-stack Python framework with an integrated web-based IDE that offers code editing, debugging, and one-click deployment. It's designed for rapid application development, especially when working on projects that require quick turnarounds.

 The self-contained environment makes it easy to develop, deploy, and maintain web apps. It's particularly useful for those who want an all-in-one solution without relying on external tools.

Features of Web2py:

• Built-In IDE: Web2py comes with an integrated development environment (IDE) that includes a code editor, debugger, and deployment system, reducing setup time.
• Built-In Security Features: Includes secure authentication, role-based access control, and protection against common security vulnerabilities.
• Database Management: Web2py includes a powerful database abstraction layer, enabling easy database migrations and access.
• Deployment: Offers one-click deployment for hosting applications on cloud platforms or local servers.

Advantages of Web2py:

• All-in-One Solution: By combining an IDE, database management, and deployment tools in one platform, Web2py streamlines development and simplifies developers' workflows.
• Fast to Learn: The integrated IDE and low-code setup reduce onboarding time, making it easier for developers unfamiliar with full-stack frameworks to get started quickly.
• Security and Scalability: Web2py is equipped with security features out of the box, and its modular structure allows for scalability as projects grow.

Companies Using Web2py:

Express Technologies, Betfair, and Computaris.

5. CherryPy

CherryPy follows a minimalistic approach, offering a lightweight framework for building web applications. It is designed for extensibility, allowing developers to add new features without modifying the core framework. CherryPy's simple yet powerful architecture makes it a great choice for smaller projects or for developers who want fine control over their application's design.

Features of CherryPy:

• Minimalistic Design: CherryPy follows a minimalist approach with a small core, allowing developers to add only the components they need.
• Built-In Web Server: Includes a multi-threaded server that makes it easy to get started with minimal configuration.
• Extensibility: It's designed to be extended, offering great flexibility for developers who need to build custom functionality.
• Multi-Threading: Allows handling multiple simultaneous requests, making it suitable for applications that require concurrency.

Advantages of CherryPy:

• Flexibility: Its minimalistic design gives developers full control over how they want to structure their applications.
• Performance: Ideal for lightweight applications that require concurrency, CherryPy uses built-in multi-threading to handle multiple requests efficiently. 
• Simplicity: With a clean, Pythonic API, it's easy for developers to use CherryPy for both simple and complex applications.

Companies Using CherryPy:

Netflix, OpenStack, and Red Hat.

6. Flask

Flask is a lightweight micro-framework for Python that's perfect for small applications or APIs. With minimal built-in functionality, Flask gives developers complete flexibility to choose their tools and libraries. It's designed to be simple yet extendable, making it an ideal choice for projects that don't require a heavy framework.

Features of Flask:

• Jinja2 Templating: Flask uses Jinja2, a powerful templating engine that allows developers to create dynamic HTML pages.
• Werkzeug WSGI Toolkit: This toolkit provides a comprehensive set of utilities for building web applications, such as session handling and request processing.
• Minimal Setup: Flask requires minimal boilerplate code, making it an ideal choice for projects where simplicity and flexibility are key.
• Extensibility: It supports a wide range of extensions for adding features like authentication, database support, and form validation.

Advantages of Flask:

• Lightweight: It's an excellent choice for smaller projects, providing just the essentials for building web applications.
• Flexible: Developers can pick and choose their libraries and tools, making it ideal for projects that don't require a full-stack framework.
• Community Support: Flask has a large, active community that provides a wealth of plugins, tutorials, and support.

Companies Using Flask:

Netflix, Airbnb, and LinkedIn.

7. Sanic

Sanic is an asynchronous Python framework designed for high-performance web applications. It supports asynchronous request handlers and is built to handle large numbers of concurrent requests. With native support for Python 3.5's 'async' and 'await’ syntax, Sanic is ideal for building fast, scalable APIs and services.

Features of Sanic:

• Asynchronous Request Handlers: Fully supports asynchronous request handling, making it ideal for applications that need to process numerous requests concurrently.
• Fast Performance: Built for speed, Sanic allows for handling thousands of concurrent requests with minimal latency.
• Async/Await: Leverages async/await syntax supported in modern Python versions (3.7+) to simplify asynchronous programming and efficiently handle I/O-bound tasks.
• WebSockets Support: Sanic has built-in support for WebSockets, making it ideal for real-time applications.

Advantages of Sanic:

• High Performance: Ideal for high-throughput applications that need to handle large numbers of simultaneous requests.
• Asynchronous: Perfect for applications that rely on asynchronous processing, such as real-time chat or notifications.
• Scalable: Sanic's design allows it to scale horizontally with minimal effort, making it a great choice for growing applications.

Companies Using Sanic:

Cigna, Darktrace, and Uber.

8. FastAPI

FastAPI is an asynchronous Python framework designed for high performance and ease of use. It leverages Python's type hints for automatic validation and documentation, making it incredibly productive for developers. FastAPI is well-suited for building modern, scalable APIs and backend services, particularly when speed and performance are critical.

Features of FastAPI:

• Automatic Documentation: Uses Python’s type hints to automatically generate OpenAPI specifications and JSON Schema for seamless API documentation.
• High Performance: Built on Starlette and Pydantic, FastAPI provides fast performance, on par with Node.js and Go.
• Asynchronous Support: FastAPI's async capabilities ensure fast processing for I/O-bound tasks, making it suitable for APIs that require speed.
• Security and Validation: Built-in support for OAuth2, JWT tokens, and automatic data validation using Python type hints.

Advantages of FastAPI:

• Speed: One of the fastest frameworks for building APIs, offering both high performance and rapid development.
• Developer Productivity: Automatic documentation and validation make development faster and more efficient.
• Scalable: Handles large-scale applications effortlessly with async features and optimized code structure.

Companies Using FastAPI:

Microsoft, Uber, and Netflix.

9. Bottle

Bottle is a minimalist micro-framework ideal for small applications and rapid prototyping. With a single-file design, it's extremely lightweight and easy to use. Despite its simplicity, Bottle supports essential features like routing, templating, and request handling, making it perfect for projects with minimal complexity.

Features of the Bottle:

• Single-File Framework: Everything you need fits in a single file, making it easy to deploy and manage.
• Routing: Includes simple URL routing for clean, easy-to-understand paths.
• Minimal Dependencies: Bottle has very few dependencies, making it a lightweight choice for small projects.
• Integrated Templating: Supports simple templating for rendering HTML without requiring external tools.

Advantages of Bottle:

• Simple: Bottle is perfect for rapid prototyping or small-scale applications where you need a minimalistic framework.
• Lightweight: With minimal dependencies, it's fast and easy to deploy, making it ideal for small projects.
• Easy to Learn: Its simplicity means there's a small learning curve, even for beginners.

Companies Using Bottles:

Hootsuite, GitHub, and Dropbox.

10. Dash

Dash is a specialized framework for creating analytical web applications and dashboards using Python. Its integration with Plotly allows developers to easily create interactive visualizations and data apps. Dash is especially popular in the data science and business intelligence sectors, where data-driven insights are key.

Features of Dash:

• Plotly Integration: Dash integrates with Plotly, enabling rich and interactive data visualizations directly in web apps.
• Component-Based: Uses reusable components to build interactive UI elements, making it easy to design complex dashboards.
• No JavaScript: Allows developers to build interactive web applications without needing to write JavaScript.
• Real-Time Data: Supports live updates of data visualizations, making it ideal for real-time dashboards.

Advantages of Dash:

• Ideal for Data Apps: Perfect for building data-driven applications without needing frontend knowledge.
• Simple Setup: Rapidly build interactive dashboards without deep knowledge of web development frameworks.
• Pythonic: Since it's entirely written in Python, it fits seamlessly into the data science ecosystem.

Companies Using Dash:

NASA, Google, and Deloitte use Dash to create sophisticated dashboards. NASA utilizes it for telemetry visualizations, Google for real-time metrics interfaces, and Deloitte for business intelligence dashboards, integrating SQL and machine learning models. 

Also Read: Top 70 Python Interview Questions & Answers: Ultimate Guide 2025 

It's important to distinguish between libraries and frameworks before selecting a framework. This understanding will shape how you approach your project's architecture and development.

Key Difference between Library and Frameworks in Python

The key difference between libraries and frameworks in Python lies in control and structure. A library offers a set of functions and tools that you call as needed to perform specific tasks, giving you control over the flow. In contrast, a framework defines the overall structure and flow of your application, calling your code at predefined points. 

For example, using the Requests library, you decide when to make HTTP calls in your script, while using Django, the framework manages requests, routing, and responses to build a full backend stack. In the next section, we'll explore how to choose between them based on your project needs.

Choosing between a library and a framework of Python affects everything from your application's architecture to how your team collaborates and maintains the code. Here's a detailed comparison to help you understand their key differences:

Key Insights:

• Control Flow: Libraries allow you to decide when and how the functionality is called. Frameworks, however, invert this control by calling your code in specific places according to its structure.
• Purpose and Flexibility: Libraries offer more flexibility as you can pick and choose the functionalities you need, whereas frameworks enforce a set structure, reducing flexibility but speeding up development for larger projects.
• Integration: Libraries integrate seamlessly into existing projects, while frameworks might require a shift in how your application is structured.
• Learning Curve: Learning how to use a library is often quicker than learning a framework of Python because libraries are smaller, more focused, and generally simpler.
• Examples: Libraries like NumPy or Pandas are best for specific tasks, while Django or Flask provide a complete system for developing applications.

Now that we've clarified the distinction between libraries and frameworks, let's explore how to choose the right Python framework for your project. 

How to Choose the Right Python Framework? Key Considerations

What is a framework in Python? The bigger question than this is choosing the right Python framework; it depends on multiple factors beyond just project size. 

Here's a clearer way to compare popular frameworks based on key criteria that affect real-world development:

• Project Complexity & Use Case:
  Lightweight frameworks like Flask or FastAPI work well for a small, quick MVP or simple API. For complex systems needing a full feature set, Django offers built-in tools that reduce development time. 

Example Scenario:

A startup building a social media MVP might start with Flask for speed, while a company developing an enterprise CRM would benefit from Django's structure.

• Scalability & Performance:
  High-concurrency projects such as chat apps or live streaming services demand asynchronous handling. FastAPI and Sanic excel here by efficiently managing many simultaneous connections. Django scales too, but may require additional setup for async workloads.

Example Scenario:

A real-time analytics dashboard is a good example where FastAPI’s speed can be critical.

• Security Needs:
  Applications handling sensitive data, like healthcare portals or fintech platforms, benefit from Django's robust built-in security features, including protection against CSRF, SQL injection, and secure authentication. 

Example Scenario:

For projects where compliance and data protection are paramount, Django's framework helps ensure safety by default.

• Team Expertise & Learning Curve:
  Flask is ideal if your team prefers flexibility and minimal learning overhead, letting developers add only what’s needed. Django’s comprehensive approach has a steeper learning curve but offers a consistent development environment that can simplify long-term maintenance. 

Example Scenario:

Teams new to Python web development might start with Flask before scaling up.

• Tooling & Deployment:
  Consider how easily a framework integrates with your deployment pipeline. Django’s extensive admin interface and plugins simplify backend management, while Flask's modularity fits well with containerized environments like Docker and cloud platforms such as AWS. 

Example Scenario:

FastAPI supports modern DevOps workflows with its lightweight footprint and automatic documentation.

Also Read: Top 50 Python Project Ideas with Source Code in 2025

Understanding how to choose the right Python framework sets the foundation. Now, upGrad can help you build advanced skills to put that knowledge into practice.

Advance Your Skills in Python Frameworks with upGrad!

Choosing the right Python framework depends on your project needs, such as scalability, ease of use, and community support. Frameworks like Django offer full-featured solutions, while Flask and FastAPI provide lightweight, flexible options. Understanding these differences helps you pick the best fit for your development goals.

Many learners find it challenging to gain hands-on experience and practical knowledge in these frameworks. upGrad offers structured programs with real-world projects and expert mentorship to help you master frameworks like Django, Flask, and FastAPI. Explore these courses to accelerate your learning and advance your Python development career.

While the course covered in the tutorial can significantly improve your knowledge, here are some free courses to facilitate your continued learning:

• AI-Powered Full Stack Development Course by IIITB
• Analyzing Patterns in Data and Storytelling
• Basics of Inferential Statistics
• Introduction to Tableau
• Case Study using Tableau, Python and SQL

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References:
https://docs.python.org/3/whatsnew/3.13.html