Repository navigation
perf: stream CSV audits with hash-indexed leakage checks - #1
Merged
Merged
Conversation
Signed-off-by: Mohamed Ajab <mohamedajab8@gmail.com>
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Read the training and test files one row at a time instead of keeping both files in memory. This uses less memory, especially when the files contain large columns that the check does not need. The report and command exit codes stay the same.
The lookup work remains expected O(n+m), plus normalisation and sorting shared groups. Memory is not constant: the training index, IDs and findings still need RAM.
All 37 tests passed, including randomized comparisons with the materialised implementation and CLI checks. A reproducible synthetic benchmark with 5,000 rows per split and eight unused 256-character columns reduced peak tracked Python allocations from 28.3 MB to 1.09 MB (96.2%). Reports matched. That result measures Python allocations, not process RSS or production throughput.
The benchmark script and algorithm notes are included. No new dependencies.