Best Development Frameworks for Python
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Compare the Top Development Frameworks that integrate with Python as of June 2025
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This a list of Development Frameworks that integrate with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.
What are Development Frameworks for Python?
Development frameworks are code libraries and development tools that streamline the development process for developers that build applications. Development frameworks simplify the process of programming in different languages. There are a variety of different types of development frameworks including web development frameworks, mobile app development frameworks, frontend and backend frameworks, and more. Compare and read user reviews of the best Development Frameworks for Python currently available using the table below. This list is updated regularly.
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1
Django
Django
Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of web development, so you can focus on writing your app without needing to reinvent the wheel. Django was designed to help developers take applications from concept to completion as quickly as possible. Django takes security seriously and helps developers avoid many common security mistakes. Some of the busiest sites on the web leverage Django’s ability to quickly and flexibly scale. Django includes dozens of extras you can use to handle common web development tasks. Django takes care of user authentication, content administration, site maps, RSS feeds, and many more tasks — right out of the box.Starting Price: Free -
2
Flask
Flask
Flask is a lightweight WSGI web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications. It began as a simple wrapper around Werkzeug and Jinja and has become one of the most popular Python web application frameworks. Flask offers suggestions, but doesn't enforce any dependencies or project layout. It is up to the developer to choose the tools and libraries they want to use. There are many extensions provided by the community that make adding new functionality easy.Starting Price: Free -
3
LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
4
Streamlit
Streamlit
Streamlit. The fastest way to build and share data apps. Turn data scripts into sharable web apps in minutes. All in Python. All for free. No front-end experience required. Streamlit combines three simple ideas. Embrace Python scripting. Build an app in a few lines of code with our magically simple API. Then see it automatically update as you save the source file. Weave in interaction. Adding a widget is the same as declaring a variable. No need to write a backend, define routes, handle HTTP requests, etc. Deploy instantly. Use Streamlit’s sharing platform to effortlessly share, manage, and collaborate on your apps. A minimal framework for powerful apps. Face-GAN explorer. App that uses Shaobo Guan’s TL-GAN project from Insight Data Science, TensorFlow, and NVIDIA's PG-GAN to generate faces that match selected attributes. Real time object detection. An image browser for the Udacity self-driving-car dataset with real-time object detection. -
5
GraalVM
GraalVM
Discover libraries and frameworks that work out-of-the-box with Native Image. Apply Graal, an advanced optimizing compiler, that generates faster and leaner code requiring fewer compute resources. Compile Java applications ahead of time to native binaries that start up instantly and deliver peak performance with no warmup time. Leverage the best features and libraries of popular languages in a single app with no overhead. Debug, monitor, profile, and optimize resource consumption in Java and across multiple languages. GraalVM’s high-performance JIT compiler generates optimized native machine code that runs faster, produces less garbage, and uses less CPU thanks to a battery of advanced compiler optimizations and aggressive and sophisticated inlining techniques. The end results are applications that run faster and consume fewer resources, reducing cloud and infrastructure costs.Starting Price: Free -
6
Atri Framework
Atri Labs
Atri framework is a full-stack web development framework to build Progressive Web Apps. Use our visual editor to increase your productivity. You can also add your custom React code. Currently, we support Python for backend development. We are planning to add support for NodeJS soon. Our CLI provides rich support for easy deployment at your platform of choice such as GitHub Pages, AWS, etc. Atri framework comes with a suite of productivity tools such as a visual editor, asset management tools, etc. that significantly reduce development time from months to hours. Atri framework is extending the definition of full-stack to include non-web developers in the development and maintenance of an app.Starting Price: $100 per user per month -
7
NiceGUI
NiceGUI
NiceGUI is an open source Python library that enables developers to create web-based graphical user interfaces (GUIs) using only Python code. It provides a gentle learning curve while still offering the option for advanced customizations. NiceGUI follows a backend-first philosophy: it handles all the web development details, allowing developers to focus on writing Python code. This makes it ideal for a wide range of projects, including short scripts, dashboards, robotics projects, IoT solutions, smart home automation, and machine learning. The framework is built on FastAPI for backend operations, Vue.js for frontend interaction, and Tailwind CSS for styling. Developers can create buttons, dialogs, Markdown, 3D scenes, plots, and more, all within a Python environment. NiceGUI supports real-time interactivity through WebSocket connections, enabling instant updates in the browser without page reloads. It offers a variety of components and layout options, such as rows, columns, etc.Starting Price: Free -
8
Rio
Rio
Rio is an open source Python framework that enables developers to build modern web and desktop applications entirely in Python. Inspired by frameworks like React and Flutter, Rio introduces a declarative UI model where components are defined as Python data classes with a build() method, allowing for reactive state management and seamless UI updates. It includes over 50 built-in components adhering to Google's Material Design, facilitating the creation of professional-grade interfaces. Rio's layout system is Pythonic and intuitive, calculating each component's natural size before distributing available space, eliminating the need for traditional CSS. Developers can run applications locally or in the browser with the backend powered by FastAPI and communication handled via WebSockets.Starting Price: Free -
9
Tornado Web Server
Tornado
Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed. By using non-blocking network I/O, Tornado can scale to tens of thousands of open connections, making it ideal for long polling, WebSockets, and other applications that require a long-lived connection to each user. Tornado is different from most Python web frameworks. It is not based on WSGI, and it is typically run with only one thread per process. While some support of WSGI is available in the tornado.wsgi module, it is not a focus of development and most applications should be written to use Tornado’s own interfaces (such as tornado.web) directly instead of using WSGI. In general, Tornado code is not thread-safe. Tornado is integrated with the standard library asyncio module and shares the same event loop (by default since Tornado 5.0). In general, libraries designed for use with asyncio can be mixed freely with Tornado. -
10
Jinja
Jinja
Jinja is a fast, expressive, extensible templating engine. Special placeholders in the template allow writing code similar to Python syntax. Then the template is passed data to render the final document.Starting Price: Free -
11
Horovod
Horovod
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.Starting Price: Free -
12
Enhance
Enhance
Enhance ships with everything you need to build a production-ready app. Organize your pages as easily as a desktop folder. Access and store data with simple JavaScript functions. Build reusable components with HTML and scoped CSS. Add client-side interaction just where you need it. Build server-rendered custom elements that seamlessly upgrade to interactive web components. Enhance makes the right way the easy way. Start with a version that works everywhere for everyone. Incrementally upgrade interactive elements from there. The web platform has what you need and never goes out of fashion. Ditch throbbers and loading screens by removing framework bloat and authoring only the code you need. When you learn Enhance, you’re learning development approaches that will last as long as the web does. Enhance apps are designed with deployment in mind. When you're ready to launch, we've got you covered with Begin. -
13
FastAPI
FastAPI
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). One of the fastest Python frameworks available. Minimize code duplication, multiple features from each parameter declaration. -
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Litestar
Litestar
Everything that's needed to build modern APIs, from data serialization and validation to websockets, ORM integration, session management, authentication and more. Litestar puts great emphasis on developer experience and performance: It's one of the fastest ASGI frameworks and developing with it is just as fast. Asynchronous at heart, but with synchronous execution not as a second class citizen: Synchronous applications run without performance penalties. Interfaces for various key/value stores that seamlessly integrate with your application and third party extensions. Response caching with minimal configuration and overhead to speed up response times. Response caching with minimal configuration and overhead to speed up response times. Session and JWT based authentication and utilities at your disposal to start building your authentication layer with ease. -
15
Sanic
Sanic
Intuitive API with smart defaults and no bloat allows you to get straight to work building your app. Build the way you want to build without letting your tooling constrain you. Built from the ground up with speed and scalability as a main concern. It is ready to power web applications big and small. Out of the box, it comes bundled with a web server ready to power your web applications. Sanic is one of the overall most popular frameworks on PyPI, and the top async enabled framework. The project is maintained and run by the community for the community. -
16
Giotto
Giotto
It is based on the concept of Model, View and Controllers. The framework is designed to enforce a clean style that results in code that is maintainable over a long period. Other popular web frameworks are built with a mindset of launching fast. This results in code that will deploy quickly, but falls under it’s own complexity after many iterations. An example of a controller process is Apache, or gunicorn. A manifest is given to the controller process when it is started. All incoming requests to the controller process will be routed to a program contained within the manifest. A manifest is just a collection of programs. A user makes a request to the controller process. This can be a web request, or a command line invocation, or any other action that is handled by a controller process. -
17
Growler
Growler
Growler is a web framework built atop asyncio, the asynchronous library described in PEP 3156 and added to the standard library in python 3.4. It takes a cue from the Connect & Express frameworks in the nodejs ecosystem, using a single application object and series of middleware to process HTTP requests. The custom chain of middleware provides an easy way to implement complex applications. The pip utility allows packages to provide optional requirements, so features may be installed only upon request. This meshes well with the minimal nature of the Growler project: don't install anything the user doesn't need. That being said, there are (will be) community packages that are blessed by the growler developers (after ensuring they work as expected and are well tested with each version of growler) that will be available as extras directly from the growler package. -
18
hug
hug
Drastically simplify API development over multiple interfaces. With hug, design and develop your API once, then expose it however your clients need to consume it. Be it locally, over HTTP, or through the command line - hug is the fastest and most modern way to create APIs on Python3. hug has been built from the ground up with performance in mind. It is built to consume resources only when necessary and is then compiled with Cython to achieve amazing performance. As a result, hug consistently benchmarks as one of the fastest Python frameworks and without question takes the crown as the fastest high-level framework for Python 3. hug makes it easy to expose multiple versions of your API. With hug you can simply specify what version or range of versions an endpoint supports and then automatically have that enforced and communicated to your API's users. -
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Starlette
Starlette
Starlette includes an application class Starlette that nicely ties together all of its other functionality. A list of middleware to run for every request. A starlette application will always automatically include two middleware classes. ServerErrorMiddleware is added as the very outermost middleware, to handle any uncaught errors occurring anywhere in the entire stack. ExceptionMiddleware is added as the very innermost middleware, to deal with handled exception cases occurring in the routing or endpoints. Startup handler callables do not take any arguments and may be either standard functions or async functions. Shutdown handler callables do not take any arguments and may be either standard functions or async functions. -
20
AIOHTTP
AIOHTTP
Supports both client and server side of HTTP protocol, both client and server web-sockets out-of-the-box, and avoids callback hell and web-server with middlewares and pluggable routing. -
21
asyncio
asyncio
asyncio is used as a foundation for multiple Python asynchronous frameworks that provide high-performance network and web-servers, database connection libraries, distributed task queues, etc. asyncio is often a perfect fit for IO-bound and high-level structured network code. -
22
Falcon
Falcon
Falcon is a blazing fast, minimalist Python web API framework for building robust app backends and microservices. The framework works great with both asyncio (ASGI) and gevent/meinheld (WSGI). The Falcon web framework encourages the REST architectural style. Resource classes implement HTTP method handlers that resolve requests and perform state transitions. Falcon complements more general Python web frameworks by providing extra reliability, flexibility, and performance wherever you need it. A number of Falcon add-ons, templates, and complementary packages are available for use in your projects. We've listed several of these on the Falcon wiki as a starting point, but you may also wish to search PyPI for additional resources. -
23
CherryPy
CherryPy
CherryPy allows developers to build web applications in much the same way they would build any other object-oriented Python program. This results in smaller source code developed in less time. CherryPy is now more than ten years old, and it has proven to be fast and reliable. It is being used in production by many sites, from the simplest to the most demanding. In order to make the most of CherryPy, you should start with the tutorials that will lead you through the most common aspects of the framework. Once done, you will probably want to browse through the basics and advanced sections that will demonstrate how to implement certain operations. Finally, you will want to carefully read the configuration and extend sections that go in-depth regarding the powerful features provided by the framework. -
24
Bottle
Bottle
Bottle is a fast, simple and lightweight WSGI micro web-framework for Python. It is distributed as a single file module and has no dependencies other than the Python Standard Library. Requests to function-call mapping with support for clean and dynamic URLs. Fast and pythonic built-in template engine and support for mako, jinja2 and cheetah templates. Convenient access to form data, file uploads, cookies, headers and other HTTP-related metadata. Built-in HTTP development server and support for paste, bjoern, gae, cherrypy or any other WSGI capable HTTP server. -
25
UnionML
Union
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. -
26
CubicWeb
CubicWeb
Modeling your data is the first step, as it always should be because applications fade away but data is here to stay. Once your model is implemented, your CubicWeb application runs and you can incrementally add high-value functionalities for your users. Based on the application model, RQL is a compact language focused on the attributes and relationships of the data. It is similar to SPARQL but is more readable by human beings. After a RQL request has selected a graph of data, several views can be applied to display the information in the most relevant way. All CubicWeb architecture is designed along this pattern. Permissions are directly defined in the data model with limitless precision. Security checks are automatically added to any RQL request submitted to the engine. CubicWeb relies on a standard SQL database for storing and managing data. PostgreSQL is the preferred database of CubicWeb. -
27
Solara
Widgetti BV
Many Python frameworks can handle basic dashboards but falter with complex ones, often leading teams to split into frontend and backend roles, causing various challenges. Solara is a new web framework that integrates ReactJS principles with Python simplicity. It offers a flexible API for various UI complexities and efficient state management. Solara supports a range of applications, from prototypes to intricate dashboards, and is compatible with platforms like Jupyter, Voilà, and various web servers. It emphasizes code quality, developer accessibility, and robust testing.
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