AI-generated analysisPublished automatically and not human-verified. Validated context appears in community notes below.
← Watch feed
Informational 15 Bitcoin

add "lrucache" module, extracted from the 3rd-party tkem/cachetools library

Public commit record

What the developer wrote

Authored by SomberNight

81/100 · Strong
add "lrucache" module, extracted from the 3rd-party tkem/cachetools library

functools.lru_cache in the stdlib is not generic enough. That can be used to cache the results of a single pure function,
however I have usecases where one function is supposed to populate the cache, while another function consumes it.
https://docs.python.org/3/library/functools.html#functools.lru_cache

This is stripped down and extracts just the LRUCache from tkem/cachetools. It is relatively short, and very mature code.
I don't expect that we have to "follow" upstream, etc. There likely won't be relevant changes upstream.
Effectively, we are forking and bundling this code.

similar to https://github.com/spesmilo/electrumx/commit/04582cc353b45721e2461176cfce1768003dd5ae
✓ Specific, descriptive subject✓ Names a concrete action or component✓ Provides detailed explanatory context✓ Links an issue, advisory, or supporting reference
The short version

What changed, and why it matters

This commit adds a new internal helper module that provides a simple least-recently-used (LRU) cache. It is a copy of well-known, mature third-party code with no user-facing behavior changes. There is no indication this introduces a security problem.

Recommended action

No security action required. Treat as routine dependency/code vendoring. If this module is later used for caching security-relevant data (e.g., signatures, keys, authentication tokens), ensure maxsize and getsizeof are configured safely and that cached entries are not exposed to untrusted code paths.

Security signals we found

No strong security signals were identified.

Risk score

Why this scored 15/100

Our methodology →
Potential impact 0/30
Exploitability 0/25
Stealth signal 0/15
Affected reach 0/15
Confidence 10/10
Evidence quality 5/5
Human-validated context

Community notes

Notes can correct, qualify, or add evidence to the AI analysis. Every note shown here has been validated by a human moderator.

No validated notes yet.

The AI analysis stands alone for now. Submit a note if you can add evidence or important context.