data-anchor-py 0.0.23

A way to create shared dataclasses in python for multiprocessing and multi threading real time applications

DataAnchor

DataAnchor is a Python library that enables seamless shared memory synchronization for Python dataclasses.

It provides a thread-safe and process-safe mechanism to share data between processes and threads, making it ideal for lightweight Inter-Process Communication (IPC) scenarios. It's built to be simple to use: just inherit the DataAnchor class into your dataclass, and its attributes will automatically be shared across processes.

You can also customize how your data is serialized and deserialized—just ensure the deserialization results in a dictionary matching the class's attributes.

This library was born out of a personal need to solve the critical problem of sharing data between processes and threads in a way that minimizes complexity and avoids common headaches. I hope it can help you too!

While I'm currently using DataAnchor for distributed systems within the same program, I'm actively working on extending its capabilities to support communication across different programs and even networks.

The larger vision is to create a simple PubSub system using shared_memory as the transport for sharing data seamlessly across programs and machines.

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Key Features

• Lightweight Shared Memory: Use Python's multiprocessing.shared_memory to share data across processes with minimal overhead.

• Thread and Process Safety: Prevent race conditions with semaphores, ensuring synchronized reads and writes.

• Dataclass Integration: Enhance Python dataclasses with shared memory capabilities by inheriting from DataAnchor.

• Custom Serialization: Customize how your data is serialized and deserialized for flexible and efficient IPC.

• Singleton Design: Each shared dataclass instance uses a single shared memory region, ensuring consistent and synchronized access.

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Installation

Install the library using pip:

pip install data-anchor