cachetiny 0.1.2

A tiny decorator-based TTL cache for Python

cachetiny

A tiny, dependency‑free, in‑memory caching decorator for Python with TTL support and optional logging.

cachetiny is designed to be extremely small, easy to understand, and useful for scripts, CLIs, APIs, and lightweight applications that need fast caching without external services or disk storage.

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Features

• Decorator-based API
• In-memory cache (no files written to disk)
• Configurable TTL (time-to-live)
• Optional logging for cache hits vs computations
• Thread-safe implementation
• Zero dependencies
• Extremely small and fast

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Quick Example

import time
from cachetiny import cachetiny


@cachetiny(ttl=5, log=True)
def slow_add(a, b):
    print("Doing expensive work...")
    time.sleep(2)
    return a + b


print(slow_add(1, 2))
print(slow_add(1, 2))
print(slow_add(1, 2))

time.sleep(6)

print(slow_add(1, 2))

Example output:

[cachetiny] COMPUTING -> slow_add(1, 2){}
Doing expensive work...
3

[cachetiny] USING CACHE -> slow_add(1, 2){}
3

[cachetiny] USING CACHE -> slow_add(1, 2){}
3

[cachetiny] COMPUTING -> slow_add(1, 2){}
Doing expensive work...
3

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API

Decorator

@cachetiny(ttl=60, log=False)

Parameters

Parameter Type Description

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ttl int Time in seconds before cache expires log bool Print when retrieving cache or computing value

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Logging

When logging is enabled:

@cachetiny(ttl=30, log=True)

You will see messages indicating whether the value was retrieved from cache or computed again.

Example:

[cachetiny] USING CACHE -> fetch_data(123){}
[cachetiny] COMPUTING -> fetch_data(456){}

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Important Behavior

Cache is stored in memory

cachetiny does NOT write anything to disk.

This means:

✔ Extremely fast lookups
✔ No file management
✔ No external dependencies

But also:

⚠ Cache is cleared when the Python process exits.

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Thread Safety

cachetiny uses a thread lock internally to protect the cache dictionary.

This ensures safe behavior when multiple threads access cached functions.

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