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recall

Smart caching for any function — simple as requests.

from recall import cache

@cache(ttl="1h")
def get_user(user_id):
    return db.query(user_id)

Features

  • Simple API — just @cache(ttl="1h") on any function
  • Multiple backends — Memory, Disk, Redis
  • TTL shorthand — "30m", "1h", "7d" instead of raw seconds
  • LRU eviction — automatic cleanup when maxsize is reached
  • Thread-safe — works in concurrent environments
  • Async support — full async/await compatibility
  • Cache statistics — track hit/miss rates
  • Stampede protection — prevent cache stampede
  • Background refresh — auto-refresh before expiry
  • Compression — zlib compression for large values
  • Bulk operations — get_many, set_many, delete_many
  • Serialization — pickle, JSON, msgpack
  • Namespacing — key prefix and versioning
  • Cache warming — pre-populate cache
  • Sliding TTL — reset TTL on each access
  • Zero dependencies — Redis backend optional

Install

pip install recall
# With Redis support:
pip install recall[redis]

Quick Start

from recall import cache
import time

@cache(ttl="1h", maxsize=1000)
def expensive_func(x):
    time.sleep(2)
    return x * 2

# First call: computes
result = expensive_func(5)  # takes 2 seconds

# Second call: instant (from cache)
result = expensive_func(5)  # returns immediately

Backends

Memory (default)

@cache(ttl="1h", maxsize=1000)
def func(x):
    return x * 2

Disk (persistent)

from recall import DiskBackend

@cache(ttl="1h", backend=DiskBackend("/tmp/my_cache"))
def func(x):
    return x * 2

Redis

from recall import RedisBackend

@cache(ttl="1h", backend=RedisBackend("redis://localhost:6379"))
def func(x):
    return x * 2

Cache Management

# Clear all cached values
expensive_func.cache_clear()

# Delete specific key
expensive_func.cache_delete(42)

# Get without computing
result = expensive_func.cache_get(42)

# Set manually
expensive_func.cache_set(99, 42)

# Pre-populate cache
expensive_func.cache_warm([(1,), (2,), (3,)])

# Get cache statistics
stats = expensive_func.cache_stats
print(stats.hits, stats.misses, stats.hit_rate)

# Get all keys
keys = expensive_func.cache_keys()

# Backend health check
health = expensive_func.cache_health()

Bulk Operations

# Get multiple keys
results = expensive_func.cache_get_many(["key1", "key2"])

# Set multiple keys
expensive_func.cache_set_many({"key1": 1, "key2": 2})

# Delete multiple keys
expensive_func.cache_delete_many(["key1", "key2"])

Advanced Features

Sliding TTL (reset on access)

@cache(ttl="5m", sliding=True)
def get_session(session_id):
    return db.query(session_id)

Cache Versioning

@cache(ttl="1h", version="2")  # Change to invalidate all
def get_data(key):
    return fetch(key)

Stampede Protection

@cache(ttl="1h", stampede_protection=True)
def expensive_computation(x):
    return x ** x

Background Refresh

@cache(ttl="1h", background_refresh=300)  # Refresh 5min before expiry
def get_config():
    return fetch_config()

Compression

@cache(ttl="1h", compression=True)
def get_large_data():
    return list(range(100000))

Custom Key Function

@cache(ttl="1h", key_fn=lambda f, a, k: f"{a[0]}_{k.get('mode', '')}")
def process(data, mode="default"):
    return f"{data}_{mode}"

Key Prefix (Namespacing)

@cache(ttl="1h", prefix="myapp")
def get_user(user_id):
    return db.query(user_id)

Serialization Format

@cache(ttl="1h", serializer="json")  # pickle, json, msgpack
def get_data():
    return {"key": "value"}

Async Support

@cache(ttl="1h")
async def get_user_async(user_id):
    return await db.query(user_id)

# Works with async functions
result = await get_user_async(1)

# Cache warming in async
await get_user_async.cache_warm([(1,), (2,)])

TTL Formats

Shorthand Meaning
"30s" 30 seconds
"5m" 5 minutes
"1h" 1 hour
"1d" 1 day
"1w" 1 week
3600 raw seconds (int/float)

Why recall?

Tool Issue
functools.lru_cache No TTL, no persistence
cachetools Complex API, no disk/Redis
redis alone Manual key management
dogpile.cache Overkill for simple use

recall = simple API + real backends + TTL done right.

License

MIT

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