Changelog
All notable changes to the Tabular-Enhancement-Tool will be documented in this file.
v0.2.2 (2026-03-05)
Fixed Sphinx build error [myst.xref_missing] on GitHub Actions.
Updated CONTRIBUTING.md and README.md to use absolute URLs for the LICENSE file.
Updated docs/conf.py to pull project metadata from pyproject.toml.
v0.2.1 (2026-03-05)
Unified TabularDataHandler and TabularEnhancer into a single class for a more streamlined Python API.
Added read(), enhance(), and save() methods to TabularEnhancer to support full-lifecycle processing.
Removed deprecated standalone functions (read_tabular_file, save_tabular_file) and TabularDataHandler class.
Added support for nested dictionaries and lists in API mapping for both POST and GET methods.
Updated documentation and README with the new unified API and nested mapping examples.
Achieved 100% test coverage for all core modules.
v0.2.0 (2026-03-05)
Removed ODBC/SQLAlchemy-based enhancement method.
Focused the package exclusively on REST-based POST and GET methods.
Updated documentation and CLI to remove all database-related references.
Removed sqlalchemy dependency.
Removed setup.py in favor of pyproject.toml.
v0.1.5 (2026-03-04)
Internal development and maintenance.
v0.1.4 (2026-03-04)
Added detailed “Contributing”, “Changelog”, and “FAQ” pages to the documentation.
Improved documentation structure and content for better user guidance.
v0.1.3 (2026-03-04)
Enhanced documentation with more narrative and explanation of classes and parameters.
Added comprehensive documentation for TabularEnhancer, ODBCEnhancer, and utility functions.
v0.1.2 (2026-03-04)
Integrated MyST-Parser to use README.md as the main Sphinx documentation index page.
Updated documentation requirements to include myst-parser.
v0.1.1 (2026-03-04)
Added initial Sphinx documentation including landing page, usage, and examples.
Added support for installation instructions via PyPI.
v0.1.0 (2026-03-04)
Initial release of the Tabular-Enhancement-Tool.
Core functionality for REST API and SQLAlchemy database enhancement.
Support for CSV, Excel, TSV, TXT, and Parquet file formats.
High-performance asynchronous processing using thread pools.
Data type preservation by reading all inputs as strings.
Response flattening and append-only enhancement.
Flexible field mapping and various authentication schemes.