Top 10 Python Packages With Most Contributors on GitHub in 2024
GitHub is a global platform for developers who contribute to open-source projects. Within GitHub, Python open-source community is a group of maintainers and developers who work on software packages that rely on Python language. According to a recent report by GitHub, there are 361,832 fellow developers and contributors in the community supporting 266,966 packages of Python. We have compiled the top ten packages of Python with the most contributors in descending order. 1| TensorFlow (tensorflow/tensorflow) Stars: 152k About: TensorFlow is a popular open-source machine learning framework for developers. It is an end-to-end open-source platform with a comprehensive, flexible ecosystem of tools, libraries, and community resources. Researchers originally developed TensorFlow at Google Brain to do machine learning and deep neural networks research. The framework provides stable Python and C++ APIs and non-guaranteed backward compatible API for other languages. Know more here. 2| Home Assistant (home-assistant/core) Stars: 39.2k About: Home Assistant package is an open-source home automation tool that puts local control and privacy first. Home Assistant allows users to control all the devices without storing any of the data in the cloud and set up advanced rules to control devices. Users need Raspberry Pi 4 Model B, micro SD sard, SD card reader, ethernet cable etc. to install Home Assistant. Know more here. 3| PyTorch Stars: 45.5k About: PyTorch is a popular Python package used mostly by the machine learning developers and data scientists. The package provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on a tape-based autograd system. It consists of various components, such as a Tensor library like NumPy, with strong GPU support, a compilation stack (TorchScript) to create serializable and optimizable models from PyTorch code, a neural networks library deeply integrated with autograd designed for maximum flexibility, and more. Know more here. 4| Ansible (ansible/ansible) Stars: 46.6k About: Ansible is an open-source IT automation system that handles configuration management, application deployment, cloud provisioning, ad-hoc task execution, network automation, and multi-node orchestration. The system also makes complex changes like zero-downtime rolling updates with load balancers easy. Ansible includes several design principles, such as managing new machines without bootstrapping any software, allowing module development in a dynamic language, including python. Know more here. 5| YouTube-DL (ytdl-org/youtube-dl) Stars: 87.6k About: YouTube-DL is a command-line program to download videos from YouTube.com and a few more sites. It requires the Python interpreter with versions 2.6, 2.7, or 3.2+. One can also configure youtube-DL by placing any supported command line option to a configuration file. Know more here. 6| Transformers (huggingface/transformers) Stars: 39.2k About: Transformers provides thousands of pre-trained models to perform tasks on texts including classification, information extraction, question answering, summarisation, translation, text generation, etc across languages. The package provides APIs to download and use those pre-trained models on a given text, fine-tune them on any dataset and then share them with the community. Know more here. 7| Microsoft Azure CLI (Azure/azure-cli) Stars: 2.2k About: Microsoft Azure CLI or Azure Command-Line Interface is a next-generation multi-platform command line experience for Azure. It is a set of commands that are used to create and manage Azure resources. The Azure CLI is available across Azure services and is designed to work quickly with Azure, with an emphasis on automation. The Azure CLI capabilities make it easy to work with different programming languages and software environments. It supports long-running operations, offers command-line flexibility when managing an Azure solution, allows for querying of command-line results with query output returned in your format of choice, and more. Know more here. 8| pandas (pandas-dev/pandas) Stars: 28k About: pandas is a popular library among data scientists used for data analysis and data manipulation. The library is in Python language and provides labelled data structures similar to R data.frame objects, statistical functions, etc. The features include- easy handling of missing data, easy to convert ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects, automatic and explicit data alignment, and more. Know more here. 9| Font-Awesome Stars: 64.8k About: Font Awesome, claimed to be the most popular font and icon toolkit, has been redesigned and built from scratch by the developers. Notable features include- icon font ligatures, an SVG framework, official NPM packages for popular frontend libraries like React, and access to a new CDN. Know more here. 10| TensorFlow Model Garden (tensorflow/models) Stars: 68.3k About: The TensorFlow Model Garden is a repository with many different implementations of state-of-the-art models and modelling solutions for TensorFlow users. This repo aims to demonstrate the best practices for modelling so the users can take full advantage of TensorFlow for their research and product development. The repo is a collection of example implementations for SOTA models using the latest TensorFlow 2’s high-level APIs. Know more here.
GitHub is a global platform for developers who contribute to open-source projects. Within GitHub, Python open-source community is a group of maintainers and developers who work on software packages that rely on Python language. According to a recent report by GitHub, there are 361,832 fellow developers and contributors in the community supporting 266,966 packages of […]
According to a recent report by GitHub, there are 361,832 fellow developers and contributors in the community supporting 266,966 packages of Python.
["Python", "Pytorch", "Tensorflow"]
["Pytorch", "NumPy", "machine learning", "AI", "neural network", "PyTorch", "Transformers", "RAG", "Python", "Aim", "TensorFlow", "Pandas", "Tensorflow"]
["AI", "machine learning", "neural network", "Aim", "TensorFlow", "PyTorch", "Transformers", "Pandas", "NumPy", "RAG"]
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.