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
• 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)

# Custom key function
@cache(ttl="1h", key_fn=lambda f, a, k: f"{a}_{k.get('mode', '')}")
def custom(data, mode):
    return f"{data}_{mode}"

TTL Formats

Why recall?

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

License

MIT

trigger

trigger

trigger

trigger

trigger