Dear Yi Hu and Apache Beam Development Team, My name is Sarath Ra, and I am writing to express my strong interest in the *"Python SDK native streaming transforms"* project for GSoC 2026. I am currently a working professional with over 1.7 years of experience focused on Python-based automation and ML experiment execution.
Having reviewed the project requirements, I believe my background aligns well with the task of porting streaming transforms from Java to Python. My professional experience involves writing Python wrapper scripts and managing ML workflows, which directly relates to the goal of creating a functional wrapper API for UnboundedSource built on Splittable DoFn. *Why I am a strong fit for this project:* - *Professional Python Experience:* I have spent the last 20 months developing automation scripts and fixing issues within existing ML codebases, giving me a solid grasp of Python's ecosystem. - *Java & Spring Proficiency:* I possess a strong foundation in Java and a functional understanding of the Spring framework, which will be instrumental in interpreting the existing Java SDK implementation for porting to Python. I have already begun familiarizing myself with the Apache Beam programming model and the specific GitHub issues (#19137 and #21521) mentioned in the project description. I am eager to contribute to the community and am ready to begin working on "Good First Issues" to demonstrate my technical capabilities. I have attached my resume for your reference and would welcome any guidance on the initial steps I should take to better align my proposal with the project goals. Thank you for your time and for this opportunity. Best regards, Sarath Ra [email protected] GitHub Profile <https://github.com/Sarath-Ra> LinkedIn Profile <https://www.google.com/search?q=https://linkedin.com/in/sarath-ra-b32100231>
sarath_ra.pdf
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