Finalfusion in Python

This release marks a major change to finalfusion-python: the entire package has been rewritten in Python and is no longer a wrapper around finalfusion-rust.

The API is now almost on par with finalfusion-rust and in some places even goes beyond that.

• Vocab, Storage, Metadata and Norms are now accessible as properties on Embeddings
• Any of the chunks above can be loaded by themselves from a finalfusion file
• All chunks can be constructed from within Python
  • It's possible to add, remove or change embeddings
• Storage types integrate directly with numpy arrays
• Reading and writing to all common Embedding formats (word2vec, GloVe, fastText) is supported
• The API for vocabularies and subword indexers has been made mor ergonomic:
  • vocab words and the word -> index mapping are accessible as properties
  • SubwordVocabs expose the subword indexer through vocab.subword_indexer

In addition to the overhauled API, finalfusion-python now comes with executables:

• ffp-convert to convert between embedding formats
• ffp-similar and ffp-analogy for similarity and analogy queries
• ffp-bucket-to-explicit to convert from bucket subword to explicit subword embeddings

Check out the documentation at https://finalfusion-python.readthedocs.io for more information!