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#90: A Django Async Roadmap

Published Tue, Aug 7, 2018, recorded Thu, Aug 2, 2018

Sponsored by Digital Ocean:

Brian #1: Reproducible Data Analysis in Jupyter

  • Amazing series of videos by Jake Vanderplas
  • Exploring a data set through visualization in a Jupyter notebook
  • There’s a lot of dense material there, from saving datasets to files, plotting in the notebook as opposed to outside in a separate window, using resampling, …

Michael #2: PySimpleGUI - For simple Python GUIs

  • Via Mike Barnett
  • Looking to take your Python code from the world of command lines and into the convenience of a GUI?
  • Have a Raspberry Pi with a touchscreen that's going to waste because you don't have the time to learn a GUI SDK?
  • Look no further, you've found your GUI package.
  • Based on tkinter
  • No dependencies (outside of Python itself): pip install PySimpleGUI
  • Python3 is required to run PySimpleGUI. It takes advantage of some Python3 features that do not translate well into Python2.
  • Looking to help? → Port to other graphic engines. Hook up the front-end interface to a backend other than tkinter. Qt, WxPython, etc.

Brian #3: Useful tricks you might not know about Git stash

  • git stash save - Stash the changes in a dirty working directory away
  • git stash apply - re-applies your changes after you do whatever you need to to your directory, like perhaps pull.
  • Lots of neat things to do with stash
    • you can add a message so the stashed content has a nice label
    • -u will include untracked files when saving.
    • git stash branch [HTML_REMOVED] stash@{1} will create a new branch with the latest stash, and then deletes the latest stash
    • Lots of other nice tricks in the article
  • See also: git-stash in git-scm book

Michael #4: A Django Async Roadmap

  • via Andrew Godwin, from Django Channels
  • Thinks that the time has come to start talking seriously about bringing async functionality into Django itself
  • Open for public feedback
  • The goal is to make Django a world-class example of what async can enable for HTTP requests, such as:
    • Doing ORM queries in parallel
    • Allowing views to query external APIs without blocking threads
    • Running slow-response/long-poll endpoints alongside each other efficiently
    • Bringing easy performance improvements to any project that spends a majority of time blocking on databases or sockets (which is most projects!)
  • Imperative that we keep Django backwards-compatible with existing code
  • Why now? Django 2.1 will be the first release that only supports Python 3.5 and up, and so this provides us the perfect place to start working on async-native code

Brian #5: pydub

  • “Manipulate audio with a simple and easy high level interface”
  • Really clean use of operators.

        from pydub import AudioSegment 
        # also handles lots of other formats 
        song = AudioSegment.from_mp3("never_gonna_give_you_up.mp3") 
        # pydub does things in milliseconds 
        ten_seconds = 10 * 1000 
        first_10_seconds = song[:ten_seconds] 
        last_5_seconds = song[-5000:] 
        # boost volume by 6dB 
        beginning = first_10_seconds + 6 
        # reduce volume by 3dB 
        end = last_5_seconds - 3 
        # Concatenate audio (add one file to the end of another) 
        without_the_middle = beginning + end
  • also:

    • crossfade
    • repeat
    • fade
    • switch formats
    • add metadata tags
    • save with a specific bitrate

Michael #6: Molten: Modern API framework

  • molten is a minimal, extensible, fast and productive framework for building HTTP APIs with Python.
  • Heavy use of type annotations
  • Officially supports Python 3.6 and later
  • Request Validation: molten can automatically validate requests according to predefined schemas, ensuring that your handlers only ever run if given valid input
  • Dependency Injection: Write clean, decoupled code by leveraging DI.
  • Still experimental at this stage.

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