#90: A Django Async Roadmap

Sponsored by Digital Ocean: pythonbytes.fm/digitalocean

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.