#250: skorch your scikit-learn together with PyTorch

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About the show

Sponsored by us:

• Check out the courses over at Talk Python
• And Brian’s book too!

Special guest: Prayson Daniel

Brian #1: Exciting New Ways To Be Told That Your Python Code is Bad

• Two new pylint errors
  • consider-ternary-expression

        if condition():
            x = 4
        else:
            x = 5
    

    x = 4 if condition() else 5

• while-used
  • it unconditionally flags every use of while expressions.
  • generally, while should be avoided.

Michael #2: GitHub Readme Stats

• via Роман Великий
• Dynamically generated stats for your github readmes
• This are for your repo or your stats (others too I suppose) posted somewhere outside of github
• Card for a project: https://github-readme-stats.vercel.app/api/pin/?username=mikeckennedy&repo=python-switch
• Card for a user: https://github-readme-stats.vercel.app/api?username=mikeckennedy&show_icons=true&theme=radical
• Card for your languages: https://github-readme-stats.vercel.app/api/top-langs/?username=mikeckennedy&repo=python-switch

Prayson #3: Nox

• Nox appeared as “footnotes” in Episodes 182 and 248 (Hypermodern Python …)
• It does tox what invoke did (substituting GNU Make)

Brian #4: Two tools for dealing with text

• python-easyfrontmatter - a small package to load and parse files (or just text) with YAML (or JSON, TOML or other) front matter.

      >>> post = frontmatter.load('tests/yaml/hello-world.txt')
      >>> print(post['title'])
      Hello, world!
  

• Tried it with a helper script I’m using with Hugo, and it parses Hugo metadata in blog posts like a dream.
• ftfy - fixes text for you
• “Take in bad Unicode and output good Unicode”

      >>> import ftfy
      >>> ftfy.fix_text('✔ No problems')
      '✔ No problems'
  

Michael #5: MPIRE (MultiProcessing Is Really Easy)

• A Python package for easy multiprocessing, but faster than multiprocessing
• It combines the
• convenience of map like functions of multiprocessing.Pool
• with the benefits of using copy-on-write shared objects of multiprocessing.Process,
• together with easy-to-use worker state, worker insights, and progress bar functionality.
• Many features
• Requisite shoutout to unsync too.

Prayson #6: skorch

• Going deep learning with scikit-learn pipelines (Breaking limits of multi-layer perceptron (MLP))
• Using PyTorch, skorch provides an API to extend neural networks models in scikit-learn.
• Example: Penguins Classification shameless Gist

Extras

Michael

• vim + jupyter, via Marco Gorelli
• PyBay talk

Prayson

• python-decouple

Joke: Adoption