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Cache ground truth between runs

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Assessment

Difficulty
3/5
Estimated time
1-2 days
Newbie friendliness
72/100
Issue type
Feature
Clarity
Clearly specified
Activity status
Active
Tech stack
python
Domain
data

Research direction

Read exact_neighbors in src/shrinkvec/exact.py and cache_dir() in datasets.py to trace how ground truth is computed and where cache files belong. Key cached results by hashes of the vectors, queries, k, and metric; check how the CLI handles --no-cache. Done when a second run reuses results, changed inputs do not, and a test covers invalidation.

Written by the indexing model from the issue text.

Description

enhancement good first issue performance

Exact float64 ground truth is the slowest part of a run on large data, and it is the same every time for the same vectors, queries, k and metric.

Where to start: exact_neighbors in src/shrinkvec/exact.py and cache_dir() in datasets.py. Key the cache on a hash of the vectors, queries, k and metric.

Done when: a second run reuses the cache, a changed input never does (with a test), and --no-cache turns it off.

Dominant language
Python
Stars
0
Forks
0
Avg merge
1h 35m
Merged PRs (30d)
5

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