🎉 Announcing py-ipfs-lite v0.1.1: An Embeddable IPFS Peer for Python!

[sumanjeet0012]

Hey everyone! 👋

We are incredibly excited to announce the release of py-ipfs-lite v0.1.1 over at the IPFS-Meshkit organization.

If you've ever wanted to integrate decentralized storage directly into your Python backend without the heavy overhead of running and maintaining a separate Kubo daemon, this is exactly what you've been looking for.

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🤔 What is py-ipfs-lite?

py-ipfs-lite is a lightweight, embeddable IPFS node built natively in Python using py-libp2p.

Instead of wrapping a command-line utility or talking to an external API over HTTP, py-ipfs-lite boots a genuine IPFS peer directly inside your Python process. It speaks the native libp2p protocols (Bitswap, DHT, Swarm) and integrates directly into your trio async event loops.

This means your Python applications can pin data, serve blocks, publish IPNS records, and swarm with the global IPFS network natively!

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✨ Features Implemented in this Release

We've packed this release with robust, production-ready features and squashed a host of edge-case bugs to make the SDK extremely reliable:

• Native py-libp2p Integration: Full support for Bitswap exchanges, Kademlia DHT Routing (tiered and delegated), and Swarm connectivity.
• Kubo-Compatible HTTP API: We ship with a built-in FastAPI server that implements the standard Kubo /api/v0/ endpoints, allowing seamless integration with existing IPFS tooling.
• CAR File Support: Fast import and export of Content Addressable aRchives with strict cryptographic hash verification. Malformed payloads are rejected natively.
• IPNS Support: Seamlessly publish and resolve mutable pointers.
• Advanced Garbage Collection & Pinning: Exception-safe, concurrent memory management via read/write locks, supporting both direct and recursive pinning logic.
• Production Telemetry: Out-of-the-box Prometheus /debug/metrics/prometheus endpoints tracking swarm connections, blockstore sizes, and bitswap bandwidth.
• Pythonic SDK: Designed around clean async with context managers for guaranteed exception-safe lifecycles.

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🚀 Example: Try it yourself!

The SDK is designed to be incredibly easy to use. Here is a quick example of how you can boot an ephemeral in-memory peer, add some data, and pull it back out:

import trio
from py_ipfs_lite.config import Config
from py_ipfs_lite.peer import Peer

async def main():
    # Configure an ephemeral, offline memory store
    config = Config(offline=True, blockstore_type="memory")
    
    # Safely boot the peer inside an async context manager
    async with Peer(config, listen_addrs=["/ip4/127.0.0.1/tcp/0"]) as peer:
        print("✅ Peer started!")
        
        # 1. Add some raw data natively
        cid = await peer.add_file(b"Hello from py-ipfs-lite!")
        print(f"📦 Added data with CID: {cid}")
        
        # 2. Pin the block to prevent Garbage Collection
        await peer.add_pin(cid)
        print("📌 Pinned CID successfully.")
        
        # 3. Retrieve the data from the blockstore
        data = await peer.get_file(cid)
        print(f"📥 Retrieved data: {data.decode('utf-8')}")

# py-ipfs-lite uses the trio async runtime (not asyncio)
trio.run(main)

👉 Explore More Examples — CAR import/export, IPNS, daemon API, and more!

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🎥 Video Screencast & Demos

Want to see py-ipfs-lite in action before you install it? We've recorded a full video screencast walking through the architecture, the daemon API, and live code execution!

👉 Watch the Screencast Demo Here

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🤝 Get Involved!

We would absolutely love for you to take py-ipfs-lite for a spin! Whether you are building decentralized apps, scraping data, or just experimenting with Python and IPFS:

• Star the repo: IPFS-Meshkit/py-ipfs-lite
• Install via pip: pip install py-ipfs-lite
• Feedback: Found a bug or have a feature request? Drop an issue or reply right here in the discussions!

Happy coding! 🚀