Open Source Python Frameworks
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Python Frameworks
View 168 business solutionsBrowse free open source Python Frameworks and projects below. Use the toggles on the left to filter open source Python Frameworks by OS, license, language, programming language, and project status.
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1
AIOHTTP
Asynchronous HTTP client/server framework for asyncio and Python
Asynchronous HTTP Client/Server for asyncio and Python. AIOHTTP supports both client and server side of HTTP protocol. A long awaited new feature is tracing client request life cycle to figure out when and why client request spends a time waiting for connection establishment, getting server response headers etc. Now it is possible by registering special signal handlers on every request processing stage. The main change is dropping yield from support and using async/await everywhere. Farewell, Python 3.4. You often want to send some sort of data in the URL’s query string. If you were constructing the URL by hand, this data would be given as key/value pairs in the URL after a question mark, e.g. httpbin.org/get?key=val. Requests allows you to provide these arguments as a dict, using the params keyword argument. aiohttp internally performs URL canonicalization before sending request. -
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Flask
The Python micro framework for building web applications
Flask is a lightweight WSGI web application framework designed to help developers get started with their web applications quickly and easily with the ability to scale up to complex applications. Being a “micro” framework does not mean that your whole web application must fit into a single Python file (although it can) or that it be limited; rather it means that Flask aims to keep the core simple but extensible. Flask offers suggestions, but it won’t make any decisions for you such as what database to use or what dependencies or project layout to choose. You get to choose the tools and libraries you want to use, so Flask can be everything you need and nothing you don’t. Flask has become one of the most popular Python web application frameworks, and has amassed a great number of extensions provided by the community that make adding new functionality easy. -
3
Volatility
An advanced memory forensics framework
Volatility is a widely used open-source framework for analyzing memory captures (RAM dumps) from Windows, Linux, and macOS systems. It enables investigators and malware analysts to extract process lists, network connections, DLLs, strings, artifacts, and more. Volatility supports many plugins for detecting hidden processes, malware, rootkits, and event tracing. It’s essential in digital forensics and incident response workflows. -
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wxWidgets
A cross-platform GUI library
wxWidgets is a C++ library that lets developers create applications for Windows, Mac OS X, Linux and other platforms with a single code base. It has popular language bindings for Python, Perl, Ruby and many other languages, and unlike other cross-platform toolkits, wxWidgets gives applications a truly native look and feel because it uses the platform's native API rather than emulating the GUI. It's also extensive, free, open-source and mature. -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. It also supports differentiable programming, enabling gradients to be computed through simulation pipelines, which is particularly valuable for machine learning integration. -
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Dagster
An orchestration platform for the development, production
Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant, multi-tool engine that scales technically and organizationally. Dagster as a unified control plane: The ‘single plane of glass’ data teams love to use. Rein in the chaos and maintain control over your data as the complexity scales. Centralize your metadata in one tool with built-in observability, diagnostics, cataloging, and lineage. Spot any issues and identify performance improvement opportunities. -
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CadQuery
A python parametric CAD scripting framework based on OCCT
CadQuery is an intuitive, easy-to-use Python library for building parametric 3D CAD models. It has several goals. Build models with scripts that are as close as possible to how you’d describe the object to a human, using a standard, already established programming language. Create parametric models that can be very easily customized by end users. Output high-quality CAD formats like STEP and AMF in addition to traditional STL. Provide a non-proprietary, plain text model format that can be edited and executed with only a web browser. The scripts use a standard programming language, Python, and thus can benefit from the associated infrastructure. This includes many standard libraries and IDEs. CadQuery's CAD kernel Open CASCADE Technology (OCCT) is much more powerful than the CGAL used by OpenSCAD. Features supported natively by OCCT include NURBS, splines, surface sewing, STL repair, STEP import/export, and other complex operations. -
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Django
The Web framework for perfectionists with deadlines
Django is a high-level, free and open-source Python web framework founded on the Model–Template–View (MTV) pattern, designed to facilitate rapid development of secure, maintainable, and scalable database-driven websites. First, read docs/intro/install.txt for instructions on installing Django. Next, work through the tutorials in order (docs/intro/tutorial01.txt, docs/intro/tutorial02.txt, etc.). If you want to set up an actual deployment server, read docs/howto/deployment/index.txt for instructions. You'll probably want to read through the topical guides (in docs/topics) next; from there you can jump to the HOWTOs (in docs/howto) for specific problems, and check out the reference (docs/ref) for gory details. -
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wxPython
A wrapper for the cross-platform, GUI API toolkit wxWidgets
A set of Python extension modules that wrap the cross-platform GUI classes from wxWidgets. -
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Kivy
Innovative user interfaces made easy
Kivy is an open source, cross-platform UI framework that lets you develop applications that make use of innovative, multi-touch user interfaces. Written in Python with a graphics engine built over OpenGL ES 2, Kivy supports various input devices and protocols, and gives you access to over 20 widgets that are all highly extensible and have built-in multi-touch support. You can run the same codebase on Mac, Windows, Linux, Android and iOS. Kivy is 100% free and open source with a professionally developed and used toolkit, as well as a stable framework and well-documented API, so you can be confident in using it in a commercial product. -
11
FastAPI
FastAPI framework, high performance, easy to learn, fast to code
FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. Great editor support. Completion everywhere. Less time debugging. Designed to be easy to use and learn. Less time reading docs. Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. Get production-ready code. With automatic interactive documentation. Based on (and fully compatible with) the open standards for APIs: OpenAPI (previously known as Swagger) and JSON Schema. If you are building a CLI app to be used in the terminal instead of a web API, check out Typer. Typer is FastAPI's little sibling. And it's intended to be the FastAPI of CLIs. In summary, you declare once the types of parameters, body, etc. as function parameters. You do that with standard modern Python types. You don't have to learn a new syntax, the methods or classes of a specific library, etc. -
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Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. It also provides PS 3.15 certificates and password based mecanism to anonymize and de-identify DICOM datasets. -
13
AIOGram
Framework for Telegram Bot API written in Python 3.7 with asyncio
aiogram is modern and fully asynchronous framework for Telegram Bot API written in Python with asyncio and aiohttp. It helps you to make your bots faster and simpler. Is a pretty simple and fully asynchronous framework for Telegram Bot API written in Python 3.7 with asyncio and aiohttp. -
14
Rekall
Rekall Memory Forensic Framework
Rekall is a powerful memory forensics framework that turns raw RAM captures—or live system state—into structured artifacts investigators can query and script. It ships with a large collection of plugins that parse OS internals to recover processes, modules, sockets, registry hives, and file objects, even when rootkits try to hide them. The design emphasizes repeatability: investigators run well-defined analyses that produce timelines, indicators, and reports suitable for case work or automation. Rekall supports profile-free operation for many targets, reducing setup friction and making it easier to handle varied images in the field. Extensibility is a core theme, with a plugin API and notebook-friendly workflows for custom hunts and triage. Used well, it compresses what would be hours of manual sleuthing into scripted passes over a consistent object model. -
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Anthropic Cybersecurity Skills
754 structured cybersecurity skills for AI agents
Anthropic Cybersecurity Skills is a collection of structured prompts, tools, and workflows designed to enhance the cybersecurity capabilities of AI systems. It focuses on defining reusable “skills” that guide AI models in performing tasks such as vulnerability analysis, threat detection, and security auditing. The project is intended for experimentation and development of AI-assisted cybersecurity workflows, providing templates that can be adapted to different environments. It emphasizes structured interaction patterns, ensuring that outputs are consistent and actionable. The repository also encourages modularity, allowing individual skills to be combined into larger security pipelines. It is particularly useful for developers exploring how AI can augment traditional cybersecurity practices. Overall, the project serves as a foundation for building AI-driven security tools and workflows. -
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Celery
Distributed task queue (development branch)
Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via messages, usually using a broker to mediate between clients and workers. To initiate a task the client adds a message to the queue, the broker then delivers that message to a worker. A Celery system can consist of multiple workers and brokers, giving way to high availability and horizontal scaling. Celery is written in Python, but the protocol can be implemented in any language. -
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Starlette
The little ASGI framework that shines
Starlette is a lightweight ASGI framework/toolkit, which is ideal for building async web services in Python. It is production-ready and gives you a lightweight, low-complexity HTTP web framework. WebSocket support. In-process background tasks. Startup and shutdown events. Test client built on httpx. CORS, GZip, Static Files, streaming responses. Session and Cookie support. 100% test coverage. 100% type annotated codebase. Few hard dependencies. Compatible with asyncio and trio backends. -
18
AWS Serverless Application Model
An open-source framework for building serverless applications
The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based applications, use the AWS SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, and debug applications defined by SAM templates or through the AWS Cloud Development Kit (CDK). You can also use the SAM CLI to deploy your applications to AWS. SAM and SAM CLI are open-sourced under the Apache 2.0 license. You can contribute new features and enhancements to SAM on GitHub or SAM CLI on GitHub. -
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Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
Powered by Cookiecutter, Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly. Cookiecutter Django works with Python 3.9 and renders Django projects with 100% starting test coverage. It has 12-Factor based settings via django-environment. Secure by default, beacuse we believe in SSL. Optimized development and production settings. Registration is handled via django-allauth. It comes with custom user model ready to go. Provides an optional basic ASGI setup for Websockets and an optional custom static build using Gulp and livereload. Send emails via Anymail (using Mailgun by default or Amazon SES if AWS is selected cloud provider, but switchable). Media storage using Amazon S3 or Google Cloud Storage. Docker support using docker-compose for development and production (using Traefik with LetsEncrypt support). Procfile for deploying to Heroku. Provides instructions for deploying to PythonAnywhere. You can run tests with unittest or pytest. -
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The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
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21
BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads to scale separately from the serving logic. Adaptive batching dynamically groups inference requests for optimal performance. Orchestrate distributed inference graph with multiple models via Yatai on Kubernetes. Easily configure CUDA dependencies for running inference with GPU. Automatically generate docker images for production deployment. -
22
Manim
A community-maintained Python framework for creating animations
A community-maintained Python library for creating mathematical animations. Manim is a free and open-source project originally written by Grant Sanderson. It is now maintained by the Manim Community and permissively released under the MIT license. Manim was originally created by Grant Sanderson as a personal project and for use in his YouTube channel, 3Blue1Brown. As his channel gained popularity, many grew to like the style of his animations and wanted to use manim for their own projects. However, as manim was only intended for personal use, it was very difficult for other users to install and use it. Manim, or ManimCE refers to the community-maintained version of the library. This is the version documented on this website; the package name on PyPI is manim. ManimGL is the latest released version of the library developed by Grant “3b1b” Sanderson. It has more experimental features and breaking changes between versions are not documented. -
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Robot Framework
Generic automation framework for acceptance testing and RPA
Robot Framework is a generic open source automation framework. It can be used for test automation and robotic process automation (RPA). Robot Framework is supported by Robot Framework Foundation. Many industry-leading companies use the tool in their software development. Robot Framework is open and extensible. Robot Framework can be integrated with virtually any other tool to create powerful and flexible automation solutions. Robot Framework is free to use without licensing costs. Robot Framework has an easy syntax, utilizing human-readable keywords. Its capabilities can be extended by libraries implemented with Python, Java or many other programming languages. Robot Framework has a rich ecosystem around it, consisting of libraries and tools that are developed as separate projects. -
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django-helpdesk
A Django application to manage tickets for an internal helpdesk
A Django application to manage tickets for an internal helpdesk. Formerly known as Jutda Helpdesk. django-helpdesk was formerly known as Jutda Helpdesk, named after the company which originally created it. As of January 2011 the name has been changed to reflect what it really is: a Django-powered ticket tracker with contributors reaching far beyond Jutda. django-helpdesk includes a basic demo Django project so that you may easily get started with testing or developing django-helpdesk. The demo project resides in the demo/ top-level folder. The demo project uses sqlite as its database. Sqlite does not allow case-insensitive searches and so the search function may not work as effectively as it would on another database such as PostgreSQL or MySQL that does support case-insensitive searches. For more information, see this note in the Django documentation. -
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Arianne RPG
Arianne is an engine to develop multiplayer online games like Stendhal
Arianne is a multiplayer online engine to develop turn based and real time games, providing a simple way of creating the game server rules and clients like our MORPG Stendhal. Our engine Marauroa uses Java and SQL for hosting hundreds of players on a solo host. Stendhal is a fun friendly and free multiplayer online adventure game with a huge and rich world. With hundreds of NPCs and different quests, features like the Travel log and achievement system keep track of progress. Thousands of creatures are ready to fight, above and below ground, and as players level up they can compare themselves on a detailed stats website. The engine Marauroa provides a simple way of creating games on a portable and robust server architecture. Marauroa manages the client server communication and provides an object orientated view of the world for game developers. It handles database access in a transparent way to store player accounts, character progress and the state of the world
