Open Source

Contributing upstream, learning in public.

I contribute targeted fixes, regression tests, and implementation work to open-source data systems while learning from maintainers and the engineering decisions behind mature projects.

Current contributions

OPEN · PR #3810

PyIceberg — nested field statistics

PyIceberg previously restricted full statistics collection for nested primitive fields, preventing lower and upper bounds from being collected for those fields.

My contribution adds support for nested-field statistics and implementswrite.metadata.metrics.max-inferred-column-defaults, following the behavior of the Apache Iceberg Java implementation.

The change includes regression coverage for nested structs, lists, maps, inferred limits, explicit column overrides, and edge cases.

Issue #2699·View PR #3810 →

OPEN · PR #705

dlt verified-sources — PostgreSQL replication

The PostgreSQL replication source defined optional dictionary fields with tuple defaults, allowing (None,) to flow into code expecting dictionary-like values.

My contribution corrects those defaults to None and adds a focused regression test that captures the original failure condition.

Issue #700·View PR #705 →

How I contribute

I try to begin with a concrete failure mode or missing behavior, understand the existing implementation and project conventions, and keep the resulting change as focused as possible.

I prefer contributions that include regression tests and explain the intended semantics clearly enough that a future contributor can understand why the behavior exists.

When a project has implementations in multiple languages or an existing specification, I also look for established behavior before introducing a new interpretation.

GitHub

You can follow my current contributions, pull requests, and engineering work on GitHub →