[Roadmap Pull Request] Add Optional Narwhals Backend-Agnostic strict_temporal_ordering for TimeFrame (#49) #50
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…namespaces - Established consistent namespace structure for partitioning workflows. - Added static and dynamic directories with clear documentation. - Removed redundant files and organized padding functionality into single_target namespace.
…oner - Added reusable utility functions in `utils.py` for single-target partitioning workflows. - Implemented `SlidingWindowPartitioner` with dynamic validation and verbose configuration. - Included validation for train, test, and validation percentages and cardinality checks. - Prepared for seamless integration with future algorithms like `ExpandingWindowPartitioner` and similar implementations.
…core_utils with 100% coverage - implemented strict temporal ordering logic in core_utils.py and integrated it into temporal_data_loader.py - refactored `validate_dataframe_column_types` to ensure `time_col` supports numeric or datetime types and all other columns are numeric - updated unit tests in `test_core_utils.py` to align with the updated validation function - removed redundant `nw.from_native` in tests, ensuring Narwhals API handles conversions natively - improved code coverage in `temporal_data_loader.py` and adjusted unit tests for partition utilities - resolved regex mismatches in tests for error validation messages - maintained a clean modular design by centralizing validation in core_utils.py, facilitating reuse and ensuring consistency across the codebase
…o be at 100% refactoring some bugs in previous sorting logic when given an id_col - Fixed logic for sorting validation
…alidation feat(core): add optional strict temporal ordering and enhance validation - Introduced `strict_temporal_ordering` functionality for backend-agnostic validation of global or group-specific temporal ordering and uniqueness. - Extended the `TimeFrame` class with the `strict_temporal_order` parameter to optionally enforce rigorous temporal validation. - Updated `core_utils` with utility functions supporting strict temporal ordering and group-level uniqueness checks. - Enhanced test coverage to 100%, covering all edge cases for new and existing features. - Updated tutorials and integration tests to reflect the new functionality. - Removed outdated tests and ensured full compliance with modern Narwhals backend compatibility. This enhancement bridges the gap between flexible mixed-frequency workflows and scenarios requiring strict temporal guarantees, aligning with the library's core philosophy.
…dated tutorial to show output for new end-users
philip-ndikum
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philip-ndikum
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Pull Request
PR Type
Description
This PR introduces the optional
strict_temporal_orderingfunctionality for the TemporalScope library, addressing the need for backend-agnostic strict temporal validation. Key enhancements include:strict_temporal_orderingfunction incore_utils.py:TimeFrameclass:strict_temporal_orderparameter for optional strict validation.These changes align with the roadmap, ensuring TemporalScope supports modern ML/DL workflows while remaining flexible for exploratory/scientific research and mixed-frequency use cases.
Related Issues
strict_temporal_orderingforTimeFrame#49Testing
Added/Updated Tests
How Has This Been Tested?
This feature has been validated through:
TimeFrameclass and partitioning functions.Test Configuration
Checklist
Additional Notes
This enhancement bridges the gap between flexible mixed-frequency workflows and scenarios requiring rigorous temporal guarantees. It ensures backward compatibility, with strict validation being entirely opt-in.