This repository is the companion code and documentation for the JoyRL Book, a Chinese-language reinforcement learning textbook. It contains over 30 self-contained Jupyter notebooks implementing classic and modern RL algorithms (DQN, Double DQN, Dueling DQN, Noisy DQN, PER DQN, Categorical DQN, Rainbow DQN, REINFORCE, A2C, PPO, DDPG, TD3, SAC, TRPO, ACER, CQL, etc.) on Gymnasium environments like CartPole-v1, Pendulum-v1, and Acrobot-v1. The site is built with Docusaurus and includes interactive playgrounds (e.g., DQN Playground), visitor tracking via a Cloudflare Worker, and extensive pseudocode in LaTeX. The code is educational: each notebook is self-contained with model, replay buffer, policy, training loop, and plotting utilities. There is heavy code duplication across notebooks, no shared library, and no unit tests, but the implementations are correct and well-documented for learning purposes. The repository also includes documentation on offline RL and LLM+RL (placeholders).