This repository provides a minimal implementation of PPO with clipped objective for reinforcement learning. It supports both discrete and continuous action spaces and includes utilities for training, testing, logging rewards to CSV, plotting graphs, and generating gifs from pretrained networks. The code is designed primarily for beginners learning reinforcement learning but can be adapted for more complex environments with hyperparameter tuning.