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Changelog

kwx tries to follow semantic versioning, a MAJOR.MINOR.PATCH version where increments are made of the:

  • MAJOR version when we make incompatible API changes
  • MINOR version when we add functionality in a backwards compatible manner
  • PATCH version when we make backwards compatible bug fixes

kwx 1.0.0 (December 28th, 2021)

kwx 0.1.8 (April 29th, 2021)

Changes include:

  • Support has been added for gensim 3.8.x and 4.x
  • Dependencies in requirement and environment files are now condensed
  • An alert for users when the corpus size is to small for the number of topics was added
  • An import error for pyLDAvis was fixed

kwx 0.1.7.3 (March 30th, 2021)

Changes include:

  • Switching over to an src structure
  • Removing the lda_bert method because its dependencies were causing breaks
  • Code quality is now checked with Codacy
  • Extensive code formatting to improve quality and style
  • Bug fixes and a more explicit use of exceptions
  • More extensive contributing guidelines
  • Tests now use random seeds and are thus more robust

kwx 0.1.5 (March 15th, 2021)

Changes include:

  • Keyword extraction and selection are now disjointed so that modeling doesn't occur again to get new keywords
  • Keyword extraction and cleaning are now fully disjointed processes
  • kwargs for sentence-transformers BERT, LDA, and TFIDF can now be passed
  • The cleaning process is verbose and uses multiprocessing
  • The user has greater control over the cleaning process
  • Reformatting of the code to make the process more clear

kwx 0.1.0 (Feb 17th, 2021)

First stable release of kwx

Changes include:

  • Full documentation of the package
  • Virtual environment files
  • Bug fixes
  • Extensive testing of all modules with GH Actions and Codecov
  • Code of conduct and contribution guidelines

kwx 0.0.2.2 (Jan 31st, 2021)

The minimum viable product of kwx:

  • Users are able to extract keywords using the following methods
    • Most frequent words
    • TFIDF words unique to one corpus when compared to others
    • Latent Dirichlet Allocation
    • Bidirectional Encoder Representations from Transformers
    • An autoencoder application of LDA and BERT combined
  • Users are able to tell the model to remove certain words to fine tune results
  • Support is offered for a universal cleaning process in all major languages
  • Visualization techniques to display keywords and topics are included
  • Outputs can be cleanly organized in a directory or zip file
  • Runtimes for topic number comparisons are estimated using tqdm