advanced-caching 0.1.5

Production-ready composable caching with TTL, SWR, and background refresh patterns for Python.

advanced-caching

Production-ready caching library for Python with TTL, stale-while-revalidate (SWR), and background refresh.
Type-safe, fast, thread-safe, async-friendly, and framework-agnostic.

Issues & feature requests: new issue

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Table of Contents

• Installation
• Quick Start
• Key Templates
• Storage Backends
  • InMemCache
  • RedisCache & Serializers
  • HybridCache (L1 + L2)
  • Custom Storage
• API Reference
• Testing & Benchmarks
• Use Cases
• Comparison
• Contributing
• License

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Installation

uv pip install advanced-caching            # core
uv pip install "advanced-caching[redis]"  # Redis support
# pip works too

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Quick Start

from advanced_caching import TTLCache, SWRCache, BGCache

@TTLCache.cached("user:{}", ttl=300)
def get_user(user_id: int) -> dict:
    return db.fetch(user_id)

@SWRCache.cached("product:{}", ttl=60, stale_ttl=30)
def get_product(product_id: int) -> dict:
    return api.fetch_product(product_id)

# Background refresh
@BGCache.register_loader("inventory", interval_seconds=300)
def load_inventory() -> list[dict]:
    return warehouse_api.get_all_items()

# Async works too
@TTLCache.cached("user:{}", ttl=300)
async def get_user_async(user_id: int) -> dict:
    return await db.fetch(user_id)

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Key Templates

• "user:{}" → first positional argument
• "user:{user_id}" → named argument
• Custom:

key=lambda *a, **k: f"user:{k.get('user_id', a[0])}"

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Storage Backends

InMemCache

Thread-safe in-memory cache with TTL.

from advanced_caching import InMemCache

cache = InMemCache()
cache.set("key", "value", ttl=60)
cache.get("key")
cache.delete("key")
cache.exists("key")
cache.set_if_not_exists("key", "value", ttl=60)
cache.cleanup_expired()

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RedisCache & Serializers

import redis
from advanced_caching import RedisCache, JsonSerializer

client = redis.Redis(host="localhost", port=6379)

cache = RedisCache(client, prefix="app:")
json_cache = RedisCache(client, prefix="app:json:", serializer="json")
custom_json = RedisCache(client, prefix="app:json2:", serializer=JsonSerializer())

Custom Serializer Example (msgpack)

import msgpack

class MsgpackSerializer:
    handles_entries = False

    @staticmethod
    def dumps(obj):
        return msgpack.packb(obj, use_bin_type=True)

    @staticmethod
    def loads(data):
        return msgpack.unpackb(data, raw=False)

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HybridCache (L1 + L2)

Two-level cache:

• L1: In-memory
• L2: Redis

Simple setup

import redis
from advanced_caching import HybridCache, TTLCache

client = redis.Redis()
hybrid = HybridCache.from_redis(client, prefix="app:", l1_ttl=60)

@TTLCache.cached("user:{}", ttl=300, cache=hybrid)
def get_user(user_id: int):
    return {"id": user_id}

Manual wiring

from advanced_caching import HybridCache, InMemCache, RedisCache

l1 = InMemCache()
l2 = RedisCache(client, prefix="app:")
# l2_ttl defaults to l1_ttl * 2 if not specified
hybrid = HybridCache(l1_cache=l1, l2_cache=l2, l1_ttl=60)

# Explicit l2_ttl for longer L2 persistence
hybrid_long_l2 = HybridCache(l1_cache=l1, l2_cache=l2, l1_ttl=60, l2_ttl=3600)

TTL behavior:

• l1_ttl: How long data stays in fast L1 memory cache
• l2_ttl: How long data persists in L2 (Redis). Defaults to l1_ttl * 2
• When data expires from L1 but exists in L2, it's automatically repopulated to L1

With BGCache using lambda factory

For lazy initialization (e.g., deferred Redis connection):

from advanced_caching import BGCache, HybridCache, InMemCache, RedisCache

def get_redis_cache():
    """Lazy Redis connection factory."""
    import redis
    client = redis.Redis(host="localhost", port=6379)
    return RedisCache(client, prefix="app:")

@BGCache.register_loader(
    "config_map",
    interval_seconds=3600,
    run_immediately=True,
    cache=lambda: HybridCache(
        l1_cache=InMemCache(),
        l2_cache=get_redis_cache(),
        l1_ttl=3600,
        l2_ttl=86400  # L2 persists longer than L1
    )
)
def load_config_map() -> dict[str, dict]:
    return {"db": {"host": "localhost"}, "cache": {"ttl": 300}}

# Access nested data
db_host = load_config_map().get("db", {}).get("host")

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Custom Storage

Implement the CacheStorage protocol.

File-based example

import json, time
from pathlib import Path
from advanced_caching import CacheEntry, CacheStorage, TTLCache, validate_cache_storage

class FileCache(CacheStorage):
    def __init__(self, directory="/tmp/cache"):
        self.dir = Path(directory)
        self.dir.mkdir(parents=True, exist_ok=True)

    def _path(self, key: str) -> Path:
        return self.dir / f"{key.replace(':','_')}.json"

    def get_entry(self, key):
        p = self._path(key)
        if not p.exists():
            return None
        data = json.loads(p.read_text())
        return CacheEntry(**data)

    def set_entry(self, key, entry, ttl=None):
        self._path(key).write_text(json.dumps(entry.__dict__))

    def get(self, key):
        e = self.get_entry(key)
        return e.value if e and e.is_fresh() else None

    def set(self, key, value, ttl=0):
        now = time.time()
        self.set_entry(key, CacheEntry(value, now + ttl, now))

    def delete(self, key):
        self._path(key).unlink(missing_ok=True)

    def exists(self, key):
        return self.get(key) is not None

    def set_if_not_exists(self, key, value, ttl):
        if self.exists(key):
            return False
        self.set(key, value, ttl)
        return True

cache = FileCache()
assert validate_cache_storage(cache)

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API Reference

• TTLCache.cached(key, ttl, cache=None)

• SWRCache.cached(key, ttl, stale_ttl=0, cache=None)

• BGCache.register_loader(key, interval_seconds, ttl=None, run_immediately=True)

• Storages:

  • InMemCache()
  • RedisCache(redis_client, prefix="", serializer="pickle"|"json"|custom)
  • HybridCache(l1_cache, l2_cache, l1_ttl=60, l2_ttl=None) - l2_ttl defaults to l1_ttl * 2

• Utilities:

  • CacheEntry
  • CacheStorage
  • validate_cache_storage()

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Testing & Benchmarks

uv run pytest -q
uv run python tests/benchmark.py

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Use Cases

• Web & API caching (FastAPI, Flask, Django)
• Database query caching
• SWR for upstream APIs
• Background refresh for configs & datasets
• Distributed caching with Redis
• Hybrid L1/L2 hot-path optimization

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Comparison

Feature	advanced-caching	lru_cache	cachetools	Redis	Memcached
TTL	✅	❌	✅	✅	✅
SWR	✅	❌	❌	Manual	Manual
Background refresh	✅	❌	❌	Manual	Manual
Custom backends	✅	❌	❌	N/A	N/A
Distributed	✅	❌	❌	✅	✅
Async support	✅	❌	❌	✅	✅
Type hints	✅	✅	✅	❌	❌

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Contributing

1. Fork the repo
2. Create a feature branch
3. Add tests
4. Run uv run pytest
5. Open a pull request

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License

MIT License – see LICENSE.