chenetdb 0.0.1

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ChenetDB

A Pythonic driver for managing graph data topology on top of MongoDB.

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🚧 Project Status: Pre-Alpha

ChenetDB is currently under active development. The API is subject to change. We are building the core driver to allow seamless graph operations (Nodes, Edges, Traversals) using MongoDB as the persistent storage engine.

Current Stage: 🏗️ Architecture & Skeleton Implementation Expected Alpha Release: Q3 2026

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💡 The Vision

MongoDB is an incredible document store, but handling complex relationships often requires rigid schemas or expensive aggregations. ChenetDB bridges the gap.

It provides a strictly typed graph layer that abstracts the complexity of storing networks in a document database.

Key Features (Planned)

• 3-Collection Architecture: Automatically manages separate collections for _nodes, _edges, and _logs for every graph.
• Rich Properties: Nodes and Edges are fully compliant MongoDB documents (store JSON of any complexity).
• ACID Graph Operations: Atomic node/edge creation.
• Audit Logging: Built-in history tracking for graph mutations.
• Pythonic API: Feels like NetworkX, scales like MongoDB.

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🛠️ Installation

Coming soon to PyPI.

Currently, you can install the development version via uv or pip from source:

Using uv (Recommended for contributors)

uv sync

Or standard pip

pip install git+[https://github.com/Pont-Vision/ChenetDB.git](https://github.com/Pont-Vision/ChenetDB.git)# ChenetDB 

A Pythonic driver for managing graph data topology on top of MongoDB.

---

🚧 Project Status: Pre-Alpha

ChenetDB is currently under active development. The API is subject to change. We are building the core driver to allow seamless graph operations (Nodes, Edges, Traversals) using MongoDB as the persistent storage engine.

Current Stage: 🏗️ Architecture & Skeleton Implementation Expected Alpha Release: Q3 2026

---

💡 The Vision

MongoDB is an incredible document store, but handling complex relationships often requires rigid schemas or expensive aggregations. ChenetDB bridges the gap.

It provides a strictly typed graph layer that abstracts the complexity of storing networks in a document database.

Key Features (Planned)

• 3-Collection Architecture: Automatically manages separate collections for _nodes, _edges, and _logs for every graph.
• Rich Properties: Nodes and Edges are fully compliant MongoDB documents (store JSON of any complexity).
• ACID Graph Operations: Atomic node/edge creation.
• Audit Logging: Built-in history tracking for graph mutations.
• Pythonic API: Feels like NetworkX, scales like MongoDB.