Browse 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.

  • MongoDB Atlas runs apps anywhere Icon
    MongoDB Atlas runs apps anywhere

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  • 1
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu backend is selected by default, so the above command is equivalent to if a compatible GPU resource is found on the system. The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores.
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  • 2
    InterPython (stands Python InterOperability) is a .NET library that allows a python interpreter to be "embedded" in your .NET programs, and gives you (almost) transparent access to python libraries and services in .NET programs. Great for GUIs, etc.
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  • 3
    Intronet is a light weighted framework which allows user to work with remote Linux system and to do some administration tasks using web browser. It's fully usable in browsers at mobile devices such pda, modern cell phones, etc.
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  • 4
    IrcPy is a communication framework based on the syntax of the IRC protocol.
    Downloads: 0 This Week
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  • Streamline Azure Security with Palo Alto Networks VM-Series Icon
    Streamline Azure Security with Palo Alto Networks VM-Series

    Centrally manage physical and virtualized firewalls with Panorama

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  • 5
    JARVIS on Messenger

    JARVIS on Messenger

    Community-driven python bot that aims to be as simple as possible

    A community-driven python bot that aims to be as simple as possible to serve humans with their everyday tasks. Messenger is now used by 1.2 billion people every month. With the launch of Send/Receive API, bots are about to take over. It should have a lot of useful features (both fun and commonly used). Anyone can contribute to this project. (As this is module-based, anybody with a decent knowledge of Python can contribute.) One of the prime goals of this project is to lower the entry barrier into the world of open source.
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  • 6
    A high level Python Web framework. The project is under active development and is not ready for production use.
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  • 7
    Jeffy

    Jeffy

    Serverless Application Framework for Python AWS Lambda

    Jeffy is a Serverless "Application" Framework for Python consisting of a suite of Utilities for Lambda functions that make developing serverless applications easy. There are three main things that Jeffy is focused on: 1. Logging - Jeffy provides easy to see JSON format logging. All events, responses and errors are captured and you can make configurations for any additional attributes you'd like to see on the logs. 2. Decorators - Jeffy has an extensive range of decorators/ event handlers for implementing common things for Lambda functions. 3. Tracing - Events are traceable within related functions and AWS services with generating and passing correlation_id.
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  • 8
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype.
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  • 9

    Joe SDK

    Web. Desktop. Best of both worlds.

    Joe SDK is an easy to learn and adapt python software development kit for excellent GUI desktop applications. You can create a desktop application using python, html, css, javascript or jquery in minutes! The SDK allows you to: - Run python code, on any javascript event. - Render result of python function dynamically - Create HTML User Interfaces, using standard HTML. The SDK is powered by: - Google Chrome apps - Python anywhere - Cherrypy Web Framework Though it is a desktop application sdk, it is purely web hosted locally. This makes it extremely easy to deploy these applications to web.
    Downloads: 0 This Week
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  • 10
    JyConsole is an advanced Java graphic console for Jython. JyConsole provides an object-oriented completion on Java and Python objects and allows the direct manipulation of objects. JyConsole includes command history, script loading and GUI preference.
    Downloads: 0 This Week
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  • 11
    Python web development framework with a focus on efficiency/speed and extensibility, with a large library of functions to aid in the development of modern web applications.
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  • 12
    Kopf

    Kopf

    A Python framework to write Kubernetes operators

    Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic).
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  • 13
    Kubernetes Operator Pythonic Framework

    Kubernetes Operator Pythonic Framework

    A Python framework to write Kubernetes operators in just a few lines

    Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). The project was originally started as zalando-incubator/kopf in March 2019, and then forked as nolar/kopf in August 2020: but it is the same codebase, the same packages, the same developer(s). A full-featured operator in just 2 files: a Dockerfile + a Python file (*). Handling functions registered via decorators with a declarative approach. No infrastructure boilerplate code with K8s API communication. Both sync and async handlers, with sync ones being threaded under the hood. Detailed documentation with examples.
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  • 14
    LINE Messaging API SDK for Python

    LINE Messaging API SDK for Python

    LINE Messaging API SDK for Python

    The LINE Messaging API SDK for Python makes it easy to develop bots using LINE Messaging API, and you can create a sample bot within minutes. You must upload a rich menu image and link the rich menu to a user for the rich menu to be displayed. You can create up to 1000 rich menus for one LINE Official Account with the Messaging API. The LINE Messaging API SDK for Python includes experimental asyncio support. (API may change without notice in a future version). Send push messages to multiple users at any time. Messages cannot be sent to groups or rooms. Get progress status of narrowcast messages sent. Gets the user IDs of the members of a room that the bot is in. This includes the user IDs of users who have not added the bot as a friend or has blocked the bot. Get the number of users who have added the bot on or before a specified date.
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  • 15
    Python port of Platform LSF API using swig. Access is provided directly to the API call in addition to server Object classes.
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  • 16
    LangChain Apps on Production with Jina

    LangChain Apps on Production with Jina

    Langchain Apps on Production with Jina & FastAPI

    Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own infrastructure to ensure data privacy. With long chain-serve, you can craft REST/WebSocket APIs, spin up LLM-powered conversational Slack bots, or wrap your LangChain apps into FastAPI packages on the cloud or on-premises.
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  • 17
    Leilany is a framework to build GUI applications with Python and GTK, using de MVC pattern design. Interested in build the gadgets for invoicing and the necessary requirements. The main goal is make applications with low memory.
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  • 18
    Linderdaum Engine
    Linderdaum Engine is an open source purely object-oriented 3D gaming engine written in C++. It is designed to be an integrated solution for the development of interactive 3D applications, for game, industrial and scientific visualization.
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  • 19
    Lino is a suite of Python packages for IT professionals who offer business applications for small and medium-sized enterprises.
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  • 20
    Lioness (Languages Interop Framework)
    Framework for making Windows applications that are one .exe file in AutoHotKey_L,C++,C#, VB.NET,Java,Groovy,Common Lisp,Nemerle,Ruby,Python,PHP,Lua,Tcl,Perl,Jint,S#,WSH VBScript,HTML/JavaScript/CSS,COM, PowerShell without compiling . For .NET 4.
    Downloads: 0 This Week
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  • 21
    The LisBON Framework is an adaptable framework for developing new parallel Memetic Algorithms (hybrid search algorithms for efficiently solving optimisation problems).
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  • 22
    LocalStack

    LocalStack

    Develop and test your cloud apps offline

    LocalStack is a fully functional local AWS cloud stack that enables you to develop and test your cloud and serverless apps offline. It spins up an easy-to-use testing environment on your local machine that has the same APIs and works the same way as the real AWS cloud environment. It can spin up a number of different core Cloud APIs on your local machine, including API Gateway, Kinesis, DynamoDB, Firehose, Lambda and many others. LocalStack was built on some of today’s best-of-breed mocking/testing tools, combining them and making them interoperable, and adding important functionality such as error injection and pluggable services. All this happening locally, without ever talking to the cloud.
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  • 23
    Lusca is a test-framework for testing network applications under unix-like operating systems. Provides remote equipment control, automated script execution, event logging and more.
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  • 24
    MITK Workbench
    The MITK Workbench is a free, open-source application for medical image visualization, segmentation, registration, and much more. Beyond the Workbench application, MITK is a comprehensive C++ framework for medical image computing. It provides a modular foundation for extending the MITK Workbench with custom plugins or developing your own medical imaging applications and research prototypes.
    Downloads: 0 This Week
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  • 25
    MMF

    MMF

    A modular framework for vision & language multimodal research

    MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. Through our modular design, you can use specific components from MMF that you care about. Our configuration system allows MMF to easily adapt to your needs.
    Downloads: 0 This Week
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