cachey

library0.2.1pypiunverified

Cachey is a Python library from Dask designed for caching in analytic computations where the costs of recomputation and storage can vary significantly. Unlike traditional caching policies (e.g., LRU), Cachey is mindful of these varying costs. The latest PyPI version is 0.2.1, released in March 2020. The project README states it is 'new and not robust'.

data workflow

Install & Compatibility

Where this runs

tested against v0.2.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 17.9MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 1.6s · import 0.000s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

from cachey import Cache

This example demonstrates how to initialize `Cachey` with a memory limit and use the `@cache.memoize` decorator to cache the results of an expensive function. The `key` and `cost` parameters help Cachey manage its eviction policy effectively.

from cachey import Cache from time import sleep # Initialize a cache with a 2 GB limit cache = Cache(2 * 10**9) @cache.memoize(key='my-expensive-function', cost=100) # Define key and estimated cost def my_expensive_function(x): print(f"Computing for {x}...") sleep(0.1) # Simulate expensive computation return x + 1 # First call will compute and cache result1 = my_expensive_function(1) print(f"Result 1: {result1}") # Second call with same arguments will retrieve from cache result2 = my_expensive_function(1) print(f"Result 2: {result2}") # Call with different arguments will compute and cache separately result3 = my_expensive_function(2) print(f"Result 3: {result3}")

Debug

Known footguns

gotchaThe official GitHub README for Cachey explicitly states: 'Cachey is new and not robust.' Users should be aware that the library might have unaddressed issues or lack full stability, and it may not be suitable for critical production systems without thorough testing.

deprecatedThe last release of Cachey (v0.2.1) was on March 11, 2020. This indicates a lack of active development and maintenance, which may lead to unpatched bugs, security vulnerabilities, or incompatibility with newer Python versions or related libraries.

Upgrade

Version history

Breaking-change detection hasn't run for this library yet.

Audit

Security & dependencies

CVE tracking and dependency tree are planned for a later release.

Agent activity

18 hits · last 30 days

gptbot

ahrefsbot

dotbot

script

Resources

No resource links recorded.