
Worked on the astronomy-commons/lsdb repository to deliver support for the npix_suffix property in HATS catalogs, enabling flexible file organization through custom suffixes or directory structures for pixel data. Updated the read_hats function to propagate the suffix parameter to the file reading utility, ensuring end-to-end compatibility across the data pipeline. Developed comprehensive tests and data generation scripts to validate the new functionality, focusing on robust file I/O and data loading processes. Utilized Python and Jupyter Notebook to implement and verify these changes, emphasizing configuration management and testing to improve data ingest reliability and pipeline efficiency for HATS catalog workflows.
March 2025: Delivered a feature for HATS catalogs in lsdb to support npix_suffix, enabling flexible file organization (custom suffixes or directory structures) for pixel data. Updated read_hats to pass the suffix through to the file reading utility, with accompanying tests and data generation scripts to validate functionality. Implemented via commit 92a77a8f135b1397e13d2e9f6e46b8b73c97e681. No major bugs fixed within this scope this month. Business impact: Enables scalable, customizable data organization for HATS catalogs, improving data ingest reliability, discoverability, and pipeline efficiency. Demonstrates strong Python development, testing, and data-generation skills, with robust validation coverage for file I/O and data layout changes.
March 2025: Delivered a feature for HATS catalogs in lsdb to support npix_suffix, enabling flexible file organization (custom suffixes or directory structures) for pixel data. Updated read_hats to pass the suffix through to the file reading utility, with accompanying tests and data generation scripts to validate functionality. Implemented via commit 92a77a8f135b1397e13d2e9f6e46b8b73c97e681. No major bugs fixed within this scope this month. Business impact: Enables scalable, customizable data organization for HATS catalogs, improving data ingest reliability, discoverability, and pipeline efficiency. Demonstrates strong Python development, testing, and data-generation skills, with robust validation coverage for file I/O and data layout changes.

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