Tianshou is a comprehensive deep reinforcement learning framework built on PyTorch that implements a wide range of RL algorithms including policy gradient methods, actor-critic algorithms, and value-based approaches. It supports training agents in diverse environments from Atari games to continuous control tasks using Mujoco physics simulator. The library separates algorithm logic from policy abstractions, providing modular components for constructing and experimenting with RL pipelines.