Distributed Libraries

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments. HandyRL focuses on a practicable algorithm and …

You can run this with: And, yes, there's a built-in crash handling mode B) We're hoping to add a respawn-from-repl system soon! Yes, you saw it here first; we provide 2-way streams with reliable, tra…

Here's a short overview of the project. A few months ago I got into the crypto market. It was all new and fascinating to me. The idea of this project originally came from a script I used to automate…

Exploratory data analysis (EDA) is a prerequisite for all data science, as illustrated by the ubiquity of Jupyter notebooks, the preferred interface for EDA among data scientists. The operations invo…

Heat is a distributed tensor framework for high performance data analytics. With Heat you can: If you need a functionality that is not yet supported: It should print something like this: In order to …

Includes ready implementations to support handlers built for HTTP requests, websockets, AWS SNS+SQS and RabbitMQ / AMQP for 🚀 event based messaging, 🔗 intra-service communication and 🐶 watchdog handl…

A good Bond reference is always due. The data is collected for both the safe and risky classes with 7000 sequences each. Each Sequence consist of 8 images before the collision. The collected images w…

GeoMX is a MXNet-based two-layer parameter server framework, aiming at integrating data knowledge that owned by multiple independent parties in a privacy-preserving way (i.e. no need to transfer raw …

A HTML page with curated list of Python frameworks! That's it! Add a Bootstrap card element, like this: If you need a new category for Python frameworks, try this: And, update the nav grid links,

A HTML page with curated list of Python frameworks! Fork and clone this repository, and run Add a Bootstrap card element, like this: If you need a new category for a Python framework, try this:

To Wrapify a class, simply add the decorators describing the publisher and listener parameters. Wrapify imposes an object-orientedrequirement on your coding style: All wrapify compatible functions ne…