6796 repositories for Python

All Algorithms implemented in Python

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

🏡 Open source home automation that puts local control and privacy first.

Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.

A list of useful payloads and bypass for Web Application Security and Pentest/CTF

Scrapy, a fast high-level web crawling & scraping framework for Python.

🔎 Hunt down social media accounts by username across social networks

Developer-first error tracking and performance monitoring

The uncompromising Python code formatter

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

Full reference of LinkedIn answers 2023 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers

Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.

We have made you a wrapper you can't refuse

⛅ The right way to check the weather

Python sample codes for robotics algorithms.

Saleor Core: the high performance, composable, headless commerce API.

matplotlib: plotting with Python

MindsDB is a Server for Artificial Intelligence Logic. Enabling developers to ship AI powered projects to production in a fast and scalable way.

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch