Showing 3 open source projects for "static analysis tools for python"

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    Safety Compliance Made Easy

    SiteDocs is a digital safety management software used to support work site compliance.

    Ideally designed for business that deals with Construction, Oil & Gas, Mining, Manufacturing, Mechanical, Electrical, Plumbing, Heating, and Excavating, SiteDocs is a perfect solution for any size business looking to modernize the way Safety Compliance is organized.
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  • Component Content Management System for Software Documentation Icon
    Component Content Management System for Software Documentation

    Great tool for serious technical writers

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  • 1
    SLM Lab

    SLM Lab

    Modular Deep Reinforcement Learning framework in PyTorch

    SLM Lab is a modular and extensible deep reinforcement learning framework designed for research and practical applications. It provides implementations of various state-of-the-art RL algorithms and emphasizes reproducibility, scalability, and detailed experiment tracking. SLM Lab is structured around a flexible experiment management system, allowing users to define, run, and analyze RL experiments efficiently.
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  • 2
    Atropos

    Atropos

    Language Model Reinforcement Learning Environments frameworks

    Atropos is a comprehensive open-source framework for reinforcement learning (RL) environments tailored specifically to work with large language models (LLMs). Designed as a scalable ecosystem of environment microservices, Atropos allows researchers and developers to collect, evaluate, and manage trajectories (sequences of actions and outcomes) generated by LLMs across a variety of tasks—from static dataset benchmarks to dynamic interactive games and real-world scenario environments. It...
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  • 3
    gym-pybullet-drones

    gym-pybullet-drones

    PyBullet Gymnasium environments for multi-agent reinforcement

    Gym-PyBullet-Drones is an open-source Gym-compatible environment for training and evaluating reinforcement learning agents on drone control and swarm robotics tasks. It leverages the PyBullet physics engine to simulate quadrotors and provides a platform for studying control, navigation, and coordination of single and multiple drones in 3D space.
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