jqueguiner / words2num2 / 29606311227

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refactor: thin Python binder — delete the 120-file Python conversion layer

words2num2/ is now a thin binder over the Rust core, matching num2words2/. All
locale resolution, en-grammar parsing, reverse-table lookup and mode dispatch
live in words2num2-core; the Python package only binds _rust and surfaces the
exception/result types.

- words2num2-core: add top-level `words2num(text, lang, to)` (resolve_lang +
  CONVERTER_TYPES check + en-vs-reverse-table dispatch) so no dispatch remains
  in Python. Bump to 0.1.1.
- binder: expose `#[pyfunction] words2num`.
- words2num2/__init__.py: thin pass-throughs to _rust (words2num,
  words2num_sentence, auto_parse, auto_parse_sentence, parse_number_string,
  normalize, supported_langs) + Words2NumError / Quantity surface.
- Delete 122 files: all 118 lang_*.py, formats.py, utils.py, compat.py,
  converters/sentence.py. base.py keeps only Words2NumError; converters/auto.py
  keeps only Quantity + pluralize (the names _rust imports).
- tests: drop the 2 dispatch tests referencing the removed CONVERTER_CLASSES.

Verified: cargo test green, clippy clean, words2num2-core 0.1.1 published;
pytest 114 passed / 1 skipped (was 116/1 — the 2 removed are the deleted-layer
dispatch tests).

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