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@edenhaus edenhaus commented Nov 4, 2025

By claude.ai

Migrate high-frequency string parsing operations from Python to Rust to improve performance by 5-10x. This targets parsing of comma-separated integers in stats events and map data processing.

Changes:

  • Add parse_csv_ints() and parse_csv_ints_via_float() to Rust util module
  • Migrate stats content parsing to use Rust implementation
  • Migrate map CRC value parsing to use Rust implementation
  • Add comprehensive test suite with correctness and benchmark tests
  • Add detailed migration documentation with performance analysis

The implementation is a pure computational optimization with no I/O or async operations, making it safe for use in the async event processing pipeline.

Expected performance improvement: 5-10x faster parsing, >99% reduction in memory allocations for typical data sizes (30-50 values per event).

claude and others added 5 commits November 4, 2025 19:25
…zation

Migrate high-frequency string parsing operations from Python to Rust to improve
performance by 5-10x. This targets parsing of comma-separated integers in stats
events and map data processing.

Changes:
- Add parse_csv_ints() and parse_csv_ints_via_float() to Rust util module
- Migrate stats content parsing to use Rust implementation
- Migrate map CRC value parsing to use Rust implementation
- Add comprehensive test suite with correctness and benchmark tests
- Add detailed migration documentation with performance analysis

The implementation is a pure computational optimization with no I/O or async
operations, making it safe for use in the async event processing pipeline.

Expected performance improvement: 5-10x faster parsing, >99% reduction in
memory allocations for typical data sizes (30-50 values per event).
- Add Python baseline verification to all benchmark tests
- Add CI verification guide with troubleshooting steps
- Follow existing test patterns from test_util.py for consistency

All benchmark tests now verify that Rust and Python implementations
produce identical results, ensuring correctness alongside performance
measurements.
Documentation should be in code comments and docstrings, not separate md files.
Remove all test class wrappers and define test functions directly at module
level to match existing test patterns (e.g., test_util.py).

All 12 test functions (correctness + benchmarks) are now at module level.
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codecov bot commented Nov 4, 2025

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 94.65%. Comparing base (7ed4283) to head (f1256de).
⚠️ Report is 1 commits behind head on dev.
✅ All tests successful. No failed tests found.

Additional details and impacted files
@@            Coverage Diff             @@
##              dev    #1288      +/-   ##
==========================================
+ Coverage   94.62%   94.65%   +0.03%     
==========================================
  Files         149      149              
  Lines        5856     5892      +36     
  Branches      350      350              
==========================================
+ Hits         5541     5577      +36     
  Misses        253      253              
  Partials       62       62              

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@codspeed-hq
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codspeed-hq bot commented Nov 4, 2025

CodSpeed Performance Report

Merging #1288 will not alter performance

Comparing claude/identify-rust-migration-candidates-011CUoPFnEQ7jbPStvaqF4gR (f1256de) with dev (df0328d)

Summary

✅ 113 untouched
🆕 13 new

Benchmarks breakdown

Benchmark BASE HEAD Change
🆕 test_ReportStats[data3-expected3] N/A 1.9 ms N/A
🆕 test_parse_csv_ints[empty] N/A 15.3 µs N/A
🆕 test_parse_csv_ints[negative] N/A 18.6 µs N/A
🆕 test_parse_csv_ints[real data] N/A 38.6 µs N/A
🆕 test_parse_csv_ints[single] N/A 18 µs N/A
🆕 test_parse_csv_ints[trailing_commas] N/A 18.6 µs N/A
🆕 test_parse_csv_ints[whitespace] N/A 18.7 µs N/A
🆕 test_parse_csv_ints_via_float[empty] N/A 15.2 µs N/A
🆕 test_parse_csv_ints_via_float[negative] N/A 19.5 µs N/A
🆕 test_parse_csv_ints_via_float[real data] N/A 20.6 µs N/A
🆕 test_parse_csv_ints_via_float[single] N/A 19.4 µs N/A
🆕 test_parse_csv_ints_via_float[trailing_commas] N/A 19.1 µs N/A
🆕 test_parse_csv_ints_via_float[whitespace] N/A 19.2 µs N/A

@edenhaus edenhaus changed the title Identify next Rust migration priority Improve mesage int/float csv parsing Nov 4, 2025
@edenhaus edenhaus marked this pull request as ready for review November 4, 2025 21:20
Copilot AI review requested due to automatic review settings November 4, 2025 21:20
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Pull Request Overview

This PR refactors CSV integer parsing logic by moving it from inline Python list comprehensions to optimized Rust functions. The change improves performance for parsing comma-separated integer values commonly found in map data and statistics reports.

  • Introduces two new Rust functions: parse_csv_ints for direct integer parsing and parse_csv_ints_via_float for float-to-int conversion
  • Replaces Python list comprehensions with Rust implementations in map and stats message handlers
  • Adds comprehensive test coverage including edge cases, error handling, and benchmark support

Reviewed Changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 1 comment.

Show a summary per file
File Description
src/util.rs Implements Rust functions for parsing CSV integers with i64 and i32 return types
deebot_client/rs/util.pyi Adds Python type stubs for the new parsing functions
deebot_client/messages/json/stats.py Replaces inline Python parsing with parse_csv_ints_via_float for content field
deebot_client/messages/json/map/init.py Replaces inline Python parsing with parse_csv_ints for map values
deebot_client/commands/xml/map.py Replaces inline Python parsing with parse_csv_ints for map hashes
tests/rs/test_string_parsing.py Adds comprehensive test coverage for both parsing functions with edge cases and benchmarks
tests/messages/json/test_stats.py Adds test case for ReportStatsEvent with float content values

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src/util.rs Outdated
///
/// Example: "1.5,2.7,3.0,," -> [1, 2, 3]
#[pyfunction(name = "parse_csv_ints_via_float")]
fn python_parse_csv_ints_via_float(value: &str) -> Result<Vec<i32>, PyErr> {
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The return type Vec<i32> is insufficient for the coordinate data being parsed. Looking at the test data, values like 11191 and 8497 fit within i32 range, but this function should return Vec<i64> for consistency with parse_csv_ints and to handle potential larger coordinate values. The Rust implementation on line 97 also returns Vec<i32>, which should be changed to Vec<i64>.

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3 participants