semvec/pypi-packages huggingface dataset:
or-gym-inventory 1.0.0
Gymnasium-compatible implementations of classic inventory management environments (Newsvendor, Multi-Echelon, Network) based on OR-Gym.
Requires Python: >=3.8
Keywords: reinforcement learning, operations research, inventory management, gymnasium, rl

# Gymnasium-Compatible Inventory Management Environments & Benchmarks (or-gym-inventory)

This repository provides `or_gym_inventory`, an installable Python package containing implementations of classic inventory management environments. These environments are adapted from the original [OR-Gym library](https://github.com/hubbs5/or-gym) and updated for compatibility with the [Gymnasium](https://gymnasium.farama.org/) API (the successor to OpenAI Gym).

The package also includes comprehensive benchmarking scripts (located in the `examples/` directory of the source repository) to compare various heuristic, optimization-inspired, and Reinforcement Learning (RL) policies on these environments.

**Environments Included:**
1.  **Newsvendor (`or_gym_inventory.newsvendor`):** Multi-period newsvendor problem with lead times and stochastic Poisson demand (based on Zipkin (2000, 2008), and Balaji et al. 2019, https://arxiv.org/abs/1911.10641). Class: `NewsvendorEnv`.
2.  **Inventory Management (`or_gym_inventory.inventory_management`):** Multi-period, multi-echelon inventory system for a single product (based on Paul Glasserman and Sridhar Tayur (1995) and D. Hubbs (2020)). Includes `InvManagementBacklogEnv` and `InvManagementLostSalesEnv`. 
3.  **Network Inventory Management (`or_gym_inventory.network_management`):** Multi-period, multi-node inventory system with a network structure (factories, distributors, retailers, markets). Includes `NetInvMgmtBacklogEnv` and `NetInvMgmtLostSalesEnv` (based on Paul Glasserman and Sridhar Tayur (1995) and Perez et al. (2021)).

## Features

*   **Installable Package:** Easily install using pip (`pip install or_gym_inventory`).
*   **Gymnasium Compatible:** Environments adhere to the modern Gymnasium API standard (`reset` returns `obs, info`, `step` returns `obs, reward, terminated, truncated, info`).
*   **Three Core Environments:** Covers single-item, multi-echelon, and network inventory problems.
*   **Backlog & Lost Sales Variants:** Specific environment classes (`*BacklogEnv`, `*LostSalesEnv`) implement these dynamics.
*   **Comprehensive Benchmarking Examples:** Includes dedicated scripts (`examples/benchmark_*.py` in the source repo) comparing various agents:
    *   **Baselines:** Random Agent.
    *   **Heuristics:** Relevant heuristics adapted for each environment type (e.g., Order-Up-To, Classic Newsvendor, (s,S) for Newsvendor; Base Stock, Constant Order for multi-echelon/network).
    *   **Stable Baselines3 Agents:** PPO, SAC, TD3, A2C, DDPG examples.
    *   **Ray RLlib Agents:** PPO, SAC examples.
*   **Detailed Reporting (from Benchmarks):** Benchmark examples generate:
    *   Summary tables (CSV).
    *   Raw results per episode (CSV).
    *   Detailed step-by-step data (optional, JSON Lines).
    *   Comparison plots (PNG).

## Installation

You can install the core package using pip:

```bash
pip install or_gym_inventory
pycmt 0.1.0
Fast git add/commit/push via one CLI command

# pycmt

**pycmt** is a simple CLI tool for instantly running `git add .`, `git commit -m "message"`, and `git push` with a single command.

---

## 🚀 Usage

From any git repository, simply run:

```bash
gp "your commit message"
```

The tool will:
- Stage all changes (`git add .`)
- Commit with your message
- Push to the current branch

---

## 🛠️ Installation

Clone this repository and install locally:

```bash
pip install .
```

Or, if published on PyPI:

```bash
pip install pycmt
```

---

## 💡 Why?

Typing `git add . && git commit -m "" && git push` every time is boring!  
Use `pycmt` for one-shot commits to speed up your workflow.

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## 📝 License

MIT — see [LICENSE](https://github.com/froas-dev/pico/blob/master/LICENCE) for details.

---

**Author:** [Froas](https://github.com/Froas)
pyops-cli 1.0.0
PyOps CLI Toolkit: System Monitoring, Git Automation, Linux Commands, API Tools
Requires Python: >=3.6

# PyOps CLI Toolkit

A Python CLI tool for:
âœ… System Monitoring (CPU, Memory, Disk)
âœ… Git Automation (clone, status)
âœ… External API Consumption
âœ… Centralized Logging

## Installation