redis-memory 0.2.2

An object that persists in Redis. Works across instances and works seamlessly through magic functions.

🗄️ redis-memory

A 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.

The intention is to use this with agentic workflows deployed as microservices, allowing for multiple instances of the same pod. (Hence the name ``memory'') That said, this is probably a good alternative for state management in microservice architecture where multiple pods are deployed in parallel.

✨ 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.

🚀 Quickstart

pip install redis-memory

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}

🧑‍💻 Context Management

You can use Memory as a context manager for automatic resource handling:

with Memory() as memory:
    memory.session = "active"
    print(memory.session)  # "active"

# Later, in a new context:
with Memory() as memory:
    print(memory.session)  # "active"

🗂️ Namespacing with ConversationMemory

For chatbots or multi-user apps, use ConversationMemory to isolate keys:

from redis_memory import ConversationMemory

conv_mem = ConversationMemory(conversation_id="user123")
conv_mem.state = {"step": 1}
print(conv_mem.state)  # {'step': 1}

⚙️ Environment Variables

• REDIS_HOST: Redis server hostname (default: redis)
• REDIS_PORT: Redis server port (default: 6379)
• REDIS_PREFIX: Key prefix (default: memory:)

🛠️ Development

🐳 Docker/Devcontainer

• Clone the repo.
• You can use VS Code Dev Containers for an instant dev environment.
• Or, just run tests in Docker—no setup needed!

🧪 Running Tests

• With Devcontainer: Open in VS Code, and use the built-in test tasks.

• With Docker directly:

  docker compose up -d redis
  docker run --rm -it -v $PWD:/workspace -w /workspace python:3.11 bash
  # Inside container:
  pip install -e .
  pytest
  

• Or use the tasks in .vscode/tasks.json for one-click testing.

🤝 Contributing

• PRs are welcome! No special permissions required.
• All you need is Docker (or a devcontainer).
• Please ensure all tests pass before submitting your PR.

📚 License

MIT

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Made with ❤️ and Redis.