🗄️ redis-memory

This repository is no longer maintained

Development continues at synced-memory, which supports multiple backends, currently both Redis and DragonflyDB.

• PyPI: https://pypi.org/project/synced-memory/
• GitHub: https://github.com/sinan-ozel/synced-memory
• Docs: https://sinan-ozel.github.io/synced-memory/latest/

Please migrate to synced-memory for continued updates and support.

A production-ready Python class for seamless, multiprocessing-safe, persistent key-value storage using Redis as a backend. If Redis is unavailable, values are cached locally and queued for syncing when Redis comes back online. All values are serialized as JSON, and you interact with it using natural Python attribute access.

Purpose

The intention is to use this with agentic workflows deployed as microservices, allowing for multiple instances of the same pod to share their state.

✨ Features

• 🔄 Multiprocessing-safe: All processes share the same state via Redis.
• 🧠 Pythonic API: Set and get attributes as if they were regular object properties.
• 🕰️ Persistence: Values survive process restarts and context blocks.
• 🚦 Resilient: If Redis is down, changes are queued and flushed when it returns.
• 🧩 Customizable: Prefixes and conversation IDs for namespacing.
• 🧵 Background sync: Queued changes are flushed automatically in the background.

Quick Example

from redis_memory import Memory

mem = Memory()
mem.answer = 42
print(mem.answer)  # 42

# Across processes or instances:
mem2 = Memory()
print(mem2.answer)  # 42

mem.settings = {"theme": "dark", "volume": 0.75}
print(mem.settings)  # {'theme': 'dark', 'volume': 0.75}

Getting Started

Check out the Installation Guide and Quickstart Tutorial to get up and running.

License

MIT - Made with ❤️ and Redis.