tlg-indices 1.3.0

Browse TLG indices

About

This Python package facilitates the browsing of the indices of the old TLG CD-ROMs. It expects that texts have been processed by the tlgu package (tlgu homepage, rehosted code), which offers a variety of ways to convert the Beta Code of the original files into Unicode text files.

Install

Install from PyPI with:

pip install tlg-indices

Disclaimer

This repository makes no claim to ownership of the contents of the original TLG CD-ROM, which are owned by the University of California, Irvine. It is an independent effort to facilitate study of texts and does not represent or imply endorsement by the University of California, Irvine or the TLG project.

Usage overview

The main entry point is the utility functions in src/tlg_indices/utils.py, which expose prebuilt indices and convenience lookups. The quickest way to see how to call these helpers is in tlg_index_examples.py, which demonstrates:

• Reading index data (epithets, geographies, dates, and author/work mappings).
• Looking up authors by epithet or geography, and reversing those lookups.
• Looking up works by author and retrieving a single work title.
• Sorting and querying date ranges using ParsedDate and get_dates_in_range().

For a runnable walkthrough, open tlg_index_examples.py and follow the patterns there.

PHI5 index helpers live in src/tlg_indices/phi5_index_utils.py, with a runnable tour in phi5_examples.py. These cover:

• Author id/name lookups and reverse lookups for PHI5.
• Author-to-work id mappings for PHI5.
• Resolving author ids from work ids.

File access utilities live in src/tlg_indices/file_utils.py. Use file_access_examples.py for runnable examples of:

• assemble_tlg_author_filepaths() and assemble_tlg_works_filepaths().
• assemble_phi5_author_filepaths() and assemble_phi5_works_filepaths().

Converting Beta Code with tlgu

If you have Beta Code files from the original TLG/PHI distributions, you can convert them using the tlgu wrapper in this package. See tlgu_examples.py for runnable examples of:

• Converting a single file into an author-level file (grouping="author").
• Splitting a single file into work-level files (grouping="work").
• Converting an entire corpus for either grouping.

Open tlgu_examples.py and adjust the file paths for your local setup.

Development

Type checking

% uv run mypy *.py src/

Packaging

% uv build --no-sources
% uv publish --token "pypi-xxxxxxxxxxxxxxxx"