livedict 1.0.4

Encrypted TTL-based key-value store with sandboxed hooks and optional persistence backends (SQLite/File/Redis).

LiveDict (Release v1.0.4)

Encrypted, TTL-based, Persistent Python Dictionary with Hook Callbacks

LiveDict is a secure, extensible, and ephemeral key-value store designed for applications that need in-memory caching with optional persistence and encryption.

License

MIT License. © 2025 LiveDict. All rights reserved.

Highlights

• AES-GCM encryption (via cryptography) with a deterministic fallback for test environments.
• TTL expiry driven by a heap-based monitor thread for efficient scheduling.
• Optional persistence backends:
  • SQLite (file-backed DB)
  • File-backed object store (per-bucket files)
  • Redis (thin wrapper; requires redis package)
• Hook callbacks (on_access, on_expire) executed safely (sandboxing recommended).
• Pydantic-backed configuration models for clarity and validation.
• Bucket policies and limits to control memory usage and namespaces.

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Installation

Minimum supported Python: 3.8+

Install with:

pip install livedict

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Quick Start

from livedict import LiveDict, LiveDictConfig, SQLiteBackend, CipherAdapter

# Create a sqlite backend and pass to LiveDict for persistence
db = SQLiteBackend(dsn="sqlite:///livedict.db")
cfg = LiveDictConfig()

store = LiveDict(config=cfg, cipher=CipherAdapter(), backends={"sqlite": db})

store.set("username", "alice", ttl=60)
print(store.get("username"))  # -> 'alice'

store.stop()  # stop the monitor thread cleanly

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Features & Notes

Encryption

• Uses AES-GCM when cryptography is available.
• Fallback deterministic XOR + base64 if cryptography absent (useful for tests).
• Keep the same CipherAdapter (or same keys) across restarts to decrypt persisted blobs.

Persistence Backends

• SQLiteBackend uses short-lived connections and has an any-bucket fallback lookup.
• FileBackend stores entries as per-bucket small files with JSON metadata.
• RedisBackend is a thin wrapper — redis-py required for full functionality.

Configuration & Limits

• Use pydantic LiveDictConfig to tune defaults, monitor behavior, and backend settings.
• Memory limits and heap rebuild thresholds help avoid large memory usage.

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Documentation

See

• Documentation/s.
• Documentation/s and more on Website