Open Source Python Code Review Software for Mac

Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. When you need to scale up things like BERT and self-supervised learning, Lightning responds accordingly by automatically exporting to ONNX or TorchScript. PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more!

Sentry is a cross-platform, self-hosted error monitoring solution that helps software teams discover, monitor and fix errors in real-time. The most users and logs will have to provide are the clues, and Sentry provides the answers. Sentry offers enhanced application performance monitoring through information-laden stack traces. It lets you build better software faster and more efficiently by showing you all issues in one place and providing the trail of events that lead to errors. It also provides real-time monitoring and data visualization through dashboards. Sentry’s server is in Python, but its API enables for sending events from any language, in any application. More than fifty-thousand companies already ship better software faster thanks to Sentry; let yours be one of them!

Test project with a 2D platform game developing in Godot 3.1, reusable mechanics for: State Machine, basics AI, Android Games.

This project provide a framework for general coding style checker's process: 1, Support different adapter plugin for different programming language syntax 2, Support incremental scanning 3, Support customize criteria rules. 4, Generate report for scanning result. A C/C++ adapter was also implemented based on clang library as example.

This project aims to assist developers by allowing them to create documentation on their projects. Document can work with a number of languages, and allows you to document any portion of your source code.

Patchwork automates development gruntwork like PR reviews, bug fixing, security patching, and more using a self-hosted CLI agent and your preferred LLMs.

The Fuck is an app that corrects errors in previous console commands. It works by matching these previous commands with a rule. When it finds a match, it creates a new command based on the matched rule and executes this command. It has numerous rules enabled by default, including ones for fixing misspelled commands, fixing wrong commands, spell checking and correcting failed commands, and many, many others. You can also create your own rules and set certain parameters.

Simplify Todo management with Todo Notifier - a versatile Python library that generates automated summaries and sends reminders via email, SNS, SES & more. Integrate easily with other project management tools. The package is available on PyPi: https://pypi.org/project/todonotifier/ For more information, please check out the GitHub repository: https://github.com/ashu-tosh-kumar/todo_notifier Detailed code documentation on GitHub Pages: https://ashu-tosh-kumar.github.io/todo_notifier/todonotifier.html Medium Article on how to use: https://at-k.medium.com/streamline-your-todos-with-todo-notifier-for-python-projects-6f95c03a2d34

Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to review! Fewer code revisions - strict linting ensures that you don't have to re-write the codebase again and again. Reduce code redundancy - Sometimes we write complex code as we are thinking in a certain way about a problem. The linter offers suggestions that can help simplify the code and eliminate redundant statements. The ultimate goal of this project is to make all people write exactly the same Python code.