Feat/data pipeline#4
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Pull request overview
This PR introduces a data pipeline feature that enables combining multiple data sources and applying transformations to time-series data. The implementation follows a clean architecture pattern with abstract base classes and concrete implementations.
Key Changes:
- Implements a
DataPipelineclass with a fluent builder pattern for composing data sources and transformers - Adds a
Transformerabstract base class andTimezoneTransformerconcrete implementation for timezone conversions - Provides comprehensive test coverage with unit tests for both pipeline operations and transformers
Reviewed changes
Copilot reviewed 7 out of 7 changed files in this pull request and generated 3 comments.
Show a summary per file
| File | Description |
|---|---|
epftoolbox2/data/transformers/base.py |
Defines abstract base class for data transformers |
epftoolbox2/data/transformers/timezone.py |
Implements timezone conversion transformer with validation |
epftoolbox2/data/transformers/__init__.py |
Exports transformer classes for public API |
epftoolbox2/pipelines/data_pipeline.py |
Core pipeline implementation with source merging and transformation chaining |
epftoolbox2/pipelines/__init__.py |
Exports DataPipeline class for public API |
tests/data/transformers/test_transformers.py |
Comprehensive tests for transformer initialization, transformation logic, and edge cases |
tests/pipelines/test_pipeline.py |
Extensive tests covering pipeline initialization, builder pattern, data merging, and transformation application |
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Pull request overview
Copilot reviewed 7 out of 7 changed files in this pull request and generated no new comments.
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