argonctl 0.1.1

Argon CLI brings Git-style branching to MongoDB, streamlining AI, ML, and data science project management.

🚀 Argon: Serverless, Branchable MongoDB Platform 🚀

Transform your MongoDB workflows with Git-style branching, stateless compute, and S3-powered time-travel!

🤔 Why Argon? • ✨ Features • ⚙️ How it Works • 🚀 Quickstart • 📚 Dive Deeper (Wiki) • 🤝 Contributing

🚀 Installation

Via pip (Recommended)

pip install argonctl

From source

git clone https://github.com/argon-lab/argon.git
cd argon
pip install -e .

---

🤔 Why Argon?

Ever wished you could manage your databases with the same flexibility as your code? Traditional MongoDB setups can be rigid and resource-intensive, making it challenging to:

• 🧪 Experiment Freely: Quickly spin up isolated environments for testing new features or data models without impacting production.
• 🌳 Branch & Version Data: Create independent "branches" of your database for different development tasks, just like Git.
• ⏪ Rollback Easily: "Time-travel" to previous data states effortlessly if something goes wrong.
• 💰 Optimize Costs: Avoid paying for idle, full-scale database clones.

Argon addresses these pain points by bringing the power of Git-like branching, stateless compute, and S3-backed versioning to MongoDB. It empowers developers and data teams to work more agilely, collaborate effectively, and innovate faster.

👉 Discover the full motivation (Wiki)

✨ Features

Argon is packed with features to supercharge your database workflows:

• 🌿 Git-style Branching: Create, suspend, resume, and delete database branches.
• 💨 Stateless Compute: MongoDB runs in lightweight Docker containers, decoupled from persistent storage.
• 💾 S3-Powered Storage: Durable, versioned snapshots of your data are stored efficiently in AWS S3.
• ⏳ Time-Travel: Restore or create new branches from any historical snapshot.
• ⌨️ Powerful CLI: A comprehensive command-line interface to manage all aspects of Argon.
• 🖥️ Web Dashboard (Experimental): Visualize and manage branches, with an optional auto-suspend feature for idle instances.

👉 Explore all features in detail (Wiki)

⚙️ How it Works

Argon cleverly combines Docker for containerization, AWS S3 for persistent, versioned storage, and a local metadata database to manage your branches:

1. Branch Creation: When you create a branch, Argon can start from a base snapshot (e.g., a clean database or a production dump) stored in S3. It pulls this snapshot and launches a new, isolated MongoDB instance in a Docker container.
2. Making Changes: You connect to this containerized MongoDB as usual and make your changes.
3. Suspending a Branch: When you suspend a branch, Argon takes a snapshot (dump) of the container's current data, uploads it to S3 (creating a new version), and then stops and removes the Docker container, freeing up local resources.
4. Resuming a Branch: To resume, Argon pulls the latest (or a specified) snapshot for that branch from S3 and starts a fresh Docker container with that data.
5. Time-Travel: You can create a new branch from any historical snapshot of an existing branch, effectively rolling back to or inspecting a previous data state in an isolated environment.

This architecture ensures that your MongoDB instances are stateless (compute is separate from storage), cost-effective (only pay for S3 storage for suspended branches and compute when running), and highly flexible.

+-----------------+      +---------------------+      +-----------------+
|      User       |----->|      Argon CLI      |<---->| Metadata (SQLite)|
+-----------------+      +---------------------+      +-----------------+
                             |          ^
                             |          | (Snapshot/Restore)
                             V          |
                       +---------------------+      +-----------------+
                       | Docker (MongoDB     |----->|  AWS S3 Bucket  |
                       |       Containers)   |      | (Snapshots)     |
                       +---------------------+      +-----------------+

👉 Get the deep dive on architecture and state flows (Wiki)

🚀 Quickstart

Ready to jump in? Get Argon running in minutes!

1. ✅ Prerequisites: Docker, AWS CLI (configured), Python 3.8+.
2. 🛠️ Install: pip install argonctl
3. 🔑 Configure: Create a .env file and add your AWS S3 bucket name and other settings.
4. 📦 Base Snapshot: Ensure base/dump.archive is in your S3 bucket (see wiki for details).
5. 🏁 Initialize: argonctl init (first run initializes local DB).

👉 View the full Quickstart Guide (Wiki)

🧪 Demo Scenario

See Argon in action! Follow our step-by-step demo to create, branch, modify, and time-travel your first Argon-powered MongoDB.

👉 Walk through the Demo Scenario (Wiki)

📚 Dive Deeper (Wiki)

Want to understand the nuts and bolts? Our wiki has you covered:

• 🤔 Introduction & Motivation
• ✨ Features
• ⚙️ How Argon Works & High-Level Design
• 🚀 Quickstart Guide
• 🧪 Demo Scenario
• 🔑 Environment Variables
• 📁 Folder Structure
• 📊 Project Status
• 🤝 Contributing to Argon

📈 Status

Argon is currently in its initial launch phase. Key features are operational, and we're actively working on improvements and new capabilities.

👉 Check the current Project Status (Wiki)

🤝 Contributing

Contributions are highly welcome! Whether it's bug reports, feature ideas, or code, let's make Argon better together.

👉 Learn how to Contribute (Wiki)

(Further details in CONTRIBUTING.md)

📜 License

Argon is open-source software licensed under the MIT License.