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#65: Speed of your import statements affecting performance?

Published Wed, Feb 14, 2018, recorded Wed, Feb 7, 2018

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Brian #1: pygal : Simple Python Charting

  • Output SVG or PNG
  • Example Flask App (also django response) part of documentation.
  • Enough other bits of doc to get you a chart in a web page super fast.

Michael #2: Thoughts on becoming a self-taught programming

  • Basic format:
  • I'm 31 days into self-studying Python and am loving every minute of it!
  • A few questions:
    • What were you doing before you began self-studying programming?
    • What made you want to study programming on your own?
    • How did you start (which resources and language)?
    • How long did it take for you to feel confident enough in your skills and knowledge to know you could be employed as a programmer?
    • What else did you do besides self-study that helped you in your journey to becoming a programmer?
    • What's next for you?

Brian #3: How to speed up Python application startup time (timing imports in 3.7)

  • Python 3.7 includes -X importtime option that allows you to profile the time it takes to do all the imports.
  • Way cool tool to help optimize the startup time of an application.

Michael #4: AnPyLar - The Python web front-end framework

  • Create web applications with elegance, simplicity and yet full power with Python and components
  • MISSION: Empower all Python programmers to work not only on the back-end but also on the front-end with the same language of choice
  • Features
    • Reactive programming and Promises
    • Python standard formatting as templates
    • reusable components
    • Scoped styling for component
    • Integrated routing engine

Brian #5: Migrating to Python 3 with pleasure

  • “A short guide on features of Python 3 for data scientists”
  • Quick tutorial through examples of pathlib.
  • Type hinting and how cool it works with editors (PyCharm example shown)
  • Adding runtime type enforcement for specific methods using enforce
  • Using function annotations for units, as done in astropy.
  • Matrix multiplication with @.
  • Globbing with **.
    • found_images = glob.glob('/path/**/*.jpg', recursive=True)
  • Also … underscores in numeric literals, f-strings, true division with /, integer division with //, and lots of more fun goodies.

Michael #6: Moving to Python 3

  • Many of these issues were corrected just by running 2to3, which not only fixed many of the compatibility issues
    • Outdated external libraries which needed to be updated to newer versions featuring Python 3 compatibility basestring to str, urlparse to urllib.urlparse and similar major changes
    • Dictionary change like iteritems() to items(), or .items() now returning a view.
    • Things that weren't needed anymore, like Django's force_unicode or __future__ library tools.
  • Once we finished working on the "low-hanging fruits", the next step was to run Aphrodite's test suite and achieve zero errors.
  • Lessons learned
    • Code coverage was originally around 70%,
    • Keeping the Python 3 branch up to date with master
    • A non-trivial feature was delivered during the migration (via feature branch)
    • The pickle protocol version in python 3 can be higher than the highest available in Python 2.7. So we needed to add versioning to our Django caches
    • Each modified file had to comply with flake8 linting rules
  • Afrodita is currently running on Google App Engine Flexible, and one of the features our team loves with is traffic splitting
  • With this feature, we can do canary releases with ease: We just deploy our new version of the service, and start redirecting small amounts of traffic traffic while we monitor for unexpected errors.
  • After some minor bugfixes, we could bring the traffic of the Python 3.6 version to 100% with confidence. We also had the old version available for instant rollback, thanks to how parallel versions and traffic splitting work in GAE flexible.

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