ONSdigital/rdsa-utils
Jan 2025 – Jan 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
Code RefactoringData EngineeringDependency ManagementPySparkPythonUnit Testing
shipsi98
PROFILE
Shipsi98
During January 2025, work focused on enhancing the ONSdigital/rdsa-utils repository by delivering a comprehensive DataFrame Utilities and Timing Decorator Enhancement. This involved developing new Python and PySpark helper functions to streamline data manipulation, including features for caching DataFrames, counting nulls, aggregating columns, and managing unique values. The time_it decorator was refactored to leverage the codetiming package, introducing standardized performance timing and improved benchmarking across analytics pipelines. Emphasis was placed on code refactoring, dependency management, and unit testing, resulting in accelerated data processing, reduced boilerplate, and strengthened data transformation capabilities for data engineering workflows within the project.
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
36 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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