- Updated the `_parse_float_auto` function in `type_converter.py` to better handle various decimal and thousand separators, particularly for cases with long decimal parts from sources like Apple Health.
- Enhanced the logic for splitting and processing numeric strings to ensure correct interpretation of values, including edge cases with multiple separators.
- Added handling for cases where numeric strings may contain both commas and periods, improving overall robustness in float parsing.
These changes enhance the accuracy of numeric conversions, ensuring more reliable data processing across the application.
- Updated the `validate_csv_template` function to normalize both the column signature and field mappings for accurate comparison, preventing false warnings about mismatches.
- Enhanced warning messages to provide clearer guidance on the relationship between normalized signatures and raw field mappings.
- Added a new test to ensure that normalized signatures do not trigger false warnings when compared to raw mappings.
- Introduced a new endpoint for validating CSV templates without saving, allowing users to check field mappings and type conversions.
- Updated the `create_system_template` and `update_system_template` functions to include validation reports in responses.
- Enhanced error handling in CSV import processes by integrating `enrich_row_error` for more informative error messages.
- Improved the AdminCsvTemplateEditorPage to support format checking and display validation results, enhancing user experience.
- Incremented version numbers for `csv_import` and `admin_csv_templates` to reflect these updates.
- Increased precision for `kcal_active`, `kcal_resting`, `hr_avg`, and `hr_max` fields in the activity log schema.
- Added a new function `_activity_hr_bpm` to validate heart rate values during CSV import, ensuring they fall within plausible ranges.
- Updated the CSV parser to utilize the new heart rate validation function for improved data integrity.
- Enhanced the type converter to accommodate additional aliases for energy fields in CSV imports.
- Added a test to verify conversion of active energy from kJ to kcal, ensuring accurate data handling.
- Added SAVEPOINT management to the `_import_activity` function to improve error handling during CSV imports.
- Moved the training type resolution logic to occur within a transaction block, ensuring that errors can be rolled back without affecting the entire import process.
- Enhanced error logging to capture evaluation failures, providing better insights during CSV import operations.
- Modified `_resolve_training_type_for_activity` to accept a database cursor, improving efficiency and avoiding potential deadlocks during CSV imports.
- Introduced `get_training_type_for_activity_with_cursor` to handle training type resolution with an existing cursor, streamlining database interactions.
- Updated related calls in the activity import logic to utilize the new function, ensuring consistent behavior across the application.
- Introduced `diagnose_blood_pressure_row` and `diagnose_activity_row` functions to validate and analyze blood pressure and activity data from CSV imports.
- Updated the CSV import logic to handle combined datetime columns for blood pressure and activity, improving data integrity during import.
- Enhanced type conversion specifications to include `start_time` for blood pressure and activity, ensuring accurate data mapping.
- Added tests to validate the new diagnosis functions and their integration with existing import processes, ensuring robustness and reliability.
- Updated frontend messages to provide clearer guidance on blood pressure and activity data handling during CSV imports.
- Implemented a new endpoint for diagnosing CSV imports without writing to the database, allowing users to validate mappings and type conversions.
- Introduced the `diagnose_vitals_row` function to analyze vital metrics and provide detailed feedback on data validity.
- Enhanced the CSV import logic to include alias handling for vital fields, improving compatibility with different CSV formats.
- Updated the frontend to support the new diagnosis feature, including UI elements for displaying diagnosis results and error details.
- Added tests to ensure the correctness of the new diagnosis functionality and its integration with existing import processes.
- Updated the CSV import logic to include SAVEPOINT management, allowing for better error handling during the vitals baseline import process.
- Enhanced the SQL migration script to drop existing CHECK constraints related to the 'source' field, ensuring compatibility with the new universal CSV import.
- Incremented DB_SCHEMA_VERSION to "20260409c" to reflect these changes and improve the import process reliability.
- Updated the aggregate_mapped_rows function to support multiple row policies, allowing for flexible handling of duplicate keys during CSV imports.
- Introduced deduplication of identical rows before aggregation, improving data integrity.
- Enhanced validation for multi_row_policy and dedupe_identical_rows in import_row_processing specifications.
- Updated the AdminCsvTemplateEditorPage to include options for multi-row policies and deduplication settings, improving user experience in template management.
- Added comprehensive tests to validate new aggregation behaviors and ensure correct error handling for multiple rows.
- Updated the CSV import logic to support new row processing specifications for weight and vitals baseline, allowing for better data aggregation and validation.
- Implemented handling for multiple rows on the same day, enabling aggregation of values such as averages for vitals and last values for weight.
- Enhanced test coverage for the new import functionalities, ensuring correct behavior during data processing and validation.
- Refactored the module registry to include default import row processing options for better flexibility in handling CSV data.
- Updated the nutrition import logic to utilize a new row processing specification, improving data aggregation and validation.
- Refactored the template rendering process in the workflow executor to use Jinja2's Environment with ChainableUndefined for better handling of missing attributes.
- Added backward-compatible shortcuts for accessing decision signals in node contexts, enhancing flexibility in template usage.
- Introduced import row processing options in CSV templates, allowing for more customizable data handling during imports.
- Updated the source_unit_choices_for_field function to include a custom option for user-defined conversion factors, improving flexibility in unit conversions.
- Modified the AdminCsvTemplateEditorPage to support custom conversion factors, allowing users to input specific scaling factors for their data.
- Added tests to ensure the custom option is correctly included in the source unit choices and functions as expected in the template editor.
- Added workflow_run triggers for "Deploy Development" and "Deploy Production" to ensure tests run only after successful deployments.
- Updated Python version in CI from 3.12 to 3.11 for better compatibility with the Debian 12 ARM64 runner.
- Enhanced job conditions to skip tests on failed workflow runs.
- Improved frontend build process by updating Node.js setup and ensuring correct directory navigation.
- Refined CSV parsing logic to handle custom and unknown source units, enhancing conversion flexibility.
- Added new tests for custom source unit handling in CSV conversions, ensuring accurate processing.
- Updated the CSV import architecture to clarify the distinction between import and data layer responsibilities, as outlined in the new section of ARCHITECTURE.md.
- Enhanced the build_row_after_mapping function to include module-specific context for improved data processing.
- Introduced source unit options in the admin CSV template editor to facilitate user-defined conversions, improving flexibility in handling various data formats.
- Added new tests to validate the handling of source units and ensure accurate conversions during CSV imports.
- Updated module definitions to include unit specifications for nutritional and activity data fields, enhancing data integrity.
- Integrated date parsing improvements using dateutil for better handling of various date formats in sleep data.
- Added total sleep hours to the nights dictionary for comprehensive sleep analysis.
- Updated the import logic to handle cases where sleep duration is zero, providing appropriate warnings.
- Enhanced the CSV import interface to detect Apple sleep CSV format and provide user feedback on template selection.
- Improved the admin CSV template editor to accommodate new sleep import requirements and clarify usage instructions.
- Added support for new CSV import modules: sleep and vitals_baseline, expanding the import capabilities.
- Implemented backend logic for handling CSV imports related to sleep and vitals baseline, including error handling and data processing.
- Updated frontend components to include new modules in the CSV import interface, improving user experience.
- Introduced unit tests for the new import functionalities to ensure reliability and correctness.
- Enhanced existing CSV analysis features to accommodate the new modules, ensuring consistent behavior across the application.
- Added new functions for calculating header signature recall and ranking metrics, improving the analysis of CSV templates.
- Updated existing CSV analysis endpoints to utilize the new ranking metrics, enhancing the accuracy of template matching.
- Refactored related code to replace Jaccard score calculations with the new metrics, providing a more comprehensive evaluation of CSV structure.
- Improved documentation for new functions to clarify their purpose and usage in the context of CSV template analysis.
- Added a new endpoint for analyzing uploaded CSV files, providing suggestions for field mappings and type conversions.
- Implemented validation for required field targets to ensure all mandatory fields are mapped correctly.
- Enhanced the admin CSV templates interface with new routes and navigation options in the frontend.
- Updated API utility functions to support the new CSV analysis functionality.
- Improved error handling for CSV uploads, including file size and row count checks.
- Added a new function to strip header keys of unwanted characters, improving CSV import consistency.
- Updated CSV row iteration to utilize the new header normalization function, ensuring cleaner data processing.
- Enhanced date parsing capabilities to support flexible formats, accommodating various date representations in CSV files.
- Introduced additional tests to validate the new header normalization and date parsing functionalities.
- Updated version for csv_import to 0.2.0, reflecting new features.
- Implemented a new POST endpoint for universal CSV import, supporting nutrition, weight, and blood pressure modules.
- Added CSV parsing function to yield rows as dictionaries for easier data handling.
- Enhanced error handling and logging for import operations.
- Introduced tests for the new CSV parsing functionality to ensure reliability.
- Added permissions for editing and deleting CSV field mappings.
- Created type converter for CSV cells to handle various data types.
- Implemented database migrations for CSV field mappings and import logs.
- Seeded initial system templates for nutrition and activity data imports.
- Developed admin endpoints for managing system CSV templates.
- Introduced user endpoints for CSV import analysis and mapping retrieval.
- Added tests for core CSV parser functionalities, including delimiter detection and value conversion.
