ONSdigital/rdsa-utils
Jan 2025 – Jan 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
Code RefactoringData EngineeringDependency ManagementPySparkPythonUnit Testing
shipsi98
PROFILE
Shipsi98
Isaac Shipsey developed a comprehensive DataFrame Utilities and Timing Decorator Enhancement for the ONSdigital/rdsa-utils repository, focusing on improving data manipulation and performance monitoring in Python and PySpark environments. He introduced helper functions for tasks such as caching DataFrames, counting nulls, aggregating columns, and managing unique values, streamlining common data engineering workflows. Isaac refactored the existing time_it decorator to leverage the codetiming package, standardizing performance timing and simplifying benchmarking across analytics pipelines. His work emphasized code refactoring, dependency management, and unit testing, resulting in more efficient, observable, and maintainable data transformation processes without addressing major bug fixes during the period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,898
Activity Months1
Your Network
35 peopleShared Repositories
1
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for the ONSdigital/rdsa-utils repo. Delivered a major feature enhancement: DataFrame Utilities and Timing Decorator Enhancement, introducing Python & PySpark helpers for data manipulation and performance timing, with a refactor of time_it to rely on codetiming and added as a dependency. No major bugs fixed this month. The work accelerates data processing, reduces boilerplate, improves observability, and strengthens data transformation capabilities across analytics pipelines.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for the ONSdigital/rdsa-utils repo. Delivered a major feature enhancement: DataFrame Utilities and Timing Decorator Enhancement, introducing Python & PySpark helpers for data manipulation and performance timing, with a refactor of time_it to rely on codetiming and added as a dependency. No major bugs fixed this month. The work accelerates data processing, reduces boilerplate, improves observability, and strengthens data transformation capabilities across analytics pipelines.
January 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Code RefactoringData EngineeringDependency ManagementPySparkPythonUnit Testing
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