PyYAML - The next generation YAML parser and emitter for Python. To install, type 'python setup.py install'. By default, the setup.py script checks

Usefulpy Check out the Usefulpy site Usefulpy site is not always up to date Download and Import download and install with with pip download usefulpyth

mkdocs-git-revision-date-plugin MkDocs plugin that displays the last revision date of the current page of the documentation based on Git. The revision

time-series-kafka-demo Mock stream producer for time series data using Kafka. I walk through this tutorial and others here on GitHub and on my Medium

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Pachyderm: The Data Foundation for Machine Learning Pachyderm provides the data layer that allows machine learning teams to productionize and scale th

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30 Days of Cloud Leaderboard This is a leaderboard for the students of Thapar, Patiala who are participating in the 2021 30 days of Google Cloud Platf

Introduction Swagger UI allows anyone — be it your development team or your end consumers — to visualize and interact with the API’s resources without

meiga 🧙 A simple, typed and monad-based Result type for Python. Table of Contents Installation 💻 Getting Started 📈 Example Features Result Function

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Launch X - On Boarding Assignments from Launch X's Python Introduction Course Explore the docs » Report Bug · Request Feature Table of Contents About

hjson-py Hjson, a user interface for JSON Hjson works with Python 2.5+ and Python 3.3+ The Python implementation of Hjson is based on simplejson. For

Revengeshogi My attempt at creating a USI Shogi Engine in python using python-shogi. Current State of Engine Currently only generating random moves us

Read the Docs Sphinx Theme This Sphinx theme was designed to provide a great reader experience for documentation users on both desktop and mobile devi

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An intro to hikari This repo provides some simple examples to get you started with hikari. Contained in this repo are bots designed with both the hika

Overview Feast is an open source feature store for machine learning. Feast is the fastest path to productionizing analytic data for model training and

nvim-snippets This was originally included in my personal Neovim setup, but I didn't like having all the snippets there so I decided to have them sepa