197 add per step barcode timing statistics

[noamteyssier]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @noamteyssier, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the observability of the CRISPR and GEX mapping workflows by integrating a robust timing mechanism. It captures the execution duration of each processing step, from initial mapping and sorting to barcode correction, UMI correction, counting, and H5AD conversion. The collected timing data is then serialized and written to a dedicated TSV file, offering valuable performance metrics for analysis and future optimizations. This change provides a clearer understanding of where computational resources are being spent within the workflow.

Highlights

• Per-Step Timing Statistics: Introduced detailed timing collection for individual steps within the CRISPR and GEX mapping workflows, providing insights into the execution duration of each module.
• New Timing Module: Added a new timing module (crates/cyto-workflow/src/timing.rs) which defines ModuleTiming (to store module name, type, and elapsed time) and Module enum (listing various workflow stages).
• Timing Data Output: Implemented functionality to write the collected timing statistics to a .timings.tsv file in the output directory, using the csv crate.
• Dependency Management Refinement: Standardized the csv dependency across multiple crates to use workspace inheritance, and added parking_lot and serde as workspace dependencies to cyto-workflow to support the new timing features.
• Minor Code Optimization: Refactored string handling in crates/cyto-ibu-count/src/lib.rs from to_string() to clone() for slight performance improvement.

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[gemini-code-assist]

Code Review

This pull request successfully adds timing statistics for each step of the workflow. The timing data is collected for various modules and written to a TSV file. The changes are spread across several crates, including dependency updates to use the csv crate from the workspace.

My review focuses on improving maintainability. I've identified two areas with significant code duplication that could be refactored to make the code easier to manage in the future:

• The main run functions in crispr.rs and gex.rs are nearly identical.
• The timing logic within the ibu_steps function in utils.rs is highly repetitive.

Addressing these points would make the new timing feature more robust and the overall codebase cleaner.