persistent decorators mirroring functools.lru_cache
Project description
PicoCache
Persistent, datastore‑backed lru_cache for Python.
PicoCache gives you the ergonomics of functools.lru_cache while keeping your
cached values safe across process restarts and even across machines.
Two back‑ends are provided out of the box:
- SQLAlchemyCache – persists to any RDBMS supported by SQLAlchemy (SQLite, Postgres, MySQL, …).
- RedisCache – stores values in Redis, perfect for distributed deployments.
Why PicoCache?
- Familiar API – decorators feel identical to
functools.lru_cache. - Durable – survive restarts, scale horizontally.
- Introspectable –
cache_info()andcache_clear()just like the standard library. - Zero boilerplate – pass a connection URL and start decorating.
Installation
pip install picocache
Quick‑start
1. SQL (SQLite example)
from picocache import SQLAlchemyCache
# Create the decorator bound to an SQLite file
sql_cache = SQLAlchemyCache("sqlite:///cache.db")
@sql_cache(maxsize=256) # feels just like functools.lru_cache
def fib(n: int) -> int:
return n if n < 2 else fib(n - 1) + fib(n - 2)
2. Redis
from picocache import RedisCache
redis_cache = RedisCache("redis://localhost:6379/0")
@redis_cache(maxsize=128, typed=True)
def slow_add(a: int, b: int) -> int:
print("Executing body…")
return a + b
On the second call with the same arguments, slow_add() returns instantly and
“Executing body…” is not printed – the result came from Redis.
API
Each decorator object is initialised with connection details and called with
the same signature as functools.lru_cache:
SQLAlchemyCache(url_or_engine, *, key_serializer=None, value_serializer=None, ...)
RedisCache(url_or_params, *, key_serializer=None, value_serializer=None, ...)
__call__(maxsize=128, typed=False)
Returns a decorator that memoises the target function.
| Param | Type | Default | Meaning |
|---|---|---|---|
maxsize |
int/None |
128 |
Per‑function entry limit (None → no limit). |
typed |
bool |
False |
Treat arguments with different types as distinct (same as stdlib). |
The wrapped function gains:
.cache_info()→namedtuple(hits, misses, currsize, maxsize).cache_clear()→ empties the persistent store for that function.
Running the tests
uv sync
just test
- SQL tests run against an in‑memory SQLite DB (no external services).
- Redis tests are skipped automatically unless a Redis server is available on
localhost:6379.
License
MIT – see LICENSE for details.
Project details
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