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functools.lru_cache with TTL support and async compatibility.

Project description

ttlru

functools.lru_cache with TTL support and async compatibility — a single decorator for both sync and async functions.

Install

pip install ttlru

Usage

from ttlru import ttl_cache

# Works for both sync and async — TTL=-1 means never expire (default)
@ttl_cache(ttlru_ttl=60, ttlru_maxsize=256)
def fetch_user(user_id: int):
    ...

@ttl_cache(ttlru_ttl=30)
async def fetch_remote(url: str):
    ...

# No parens — uses defaults (no expiry, maxsize=128)
@ttl_cache
def compute(x):
    ...

# Cache management (mirrors functools.lru_cache)
fetch_user.cache_clear()
fetch_user.cache_info()  # CacheInfo(hits=…, misses=…, maxsize=…, currsize=…)

Parameters

All decorator keyword arguments use the ttlru_ prefix so they never clash with parameters of the decorated function (e.g. a function that has its own ttl or config parameter).

Parameter Default Description
ttlru_ttl -1 Seconds before entry expires. -1 = never expire.
ttlru_maxsize 128 Max entries. None = unlimited, 0 = no caching.
ttlru_typed False Cache f(3) and f(3.0) separately when True.
ttlru_config global CacheConfig instance for enabled flag and telemetry.

Telemetry

from ttlru import set_telemetry_provider, MetricsTelemetryProvider

set_telemetry_provider(MetricsTelemetryProvider(my_otel_counter))

Built-in providers: LoggingTelemetryProvider (default, DEBUG level), MetricsTelemetryProvider, NoOpTelemetryProvider.

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