#26 How have you automated your life, or CLI, with Python?

Python Bytes - Podcast tekijän mukaan Michael Kennedy and Brian Okken - Maanantaisin

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Sponsored by rollbar: rollbar.com/pythonbytes

Brian #1: Two part series on interactive terminal applications

Part 1: 4 terminal applications with great command-line UIs

  • For Comparison: both ok but could be better
    • MySQL REPL
    • Python REPL
  • bpython adds autocompletion and other goodies
    • also check out ptpython as a REPL replacement
  • mycli adds context aware completion to MySQL mycli - pgcli for postgress that adds fuzzy search
  • fish : like bash, but has better search history

Part 2: 4 Python libraries for building great cli's

  • prompt_toolkit - for building a REPL like interface
    • includes command history, auto-suggestion, auto-completion
  • click
    • includes pager and ability to launch an editor
  • fuzzyfinder - make suggestions
    • article shows how to combine that with prompt_toolkit
  • pygments - syntax highlighting

Michael #2: How have you automated your life with python?

  • There is something magical about writing code that interacts with the physical world.
  • I have a script which runs every 5 minutes between 17:00 and 17:30 which scrapes the train times website and sends me desktop notifications saying whether or not my trains home are delayed / cancelled.
  • I recently wrote a quick python script that tells me when my girlfriend comes home: It sniffs the network for DHCP traffic, when her phone joins the wifi network outside it uses the say command to let me know.
  • Wrote a script to check if nearby ice cream shops are stocking my favourite (rare) flavour by scanning their menu page for keywords.
  • A script to check the drive time too/from work using a route with tolls or without tolls.. to try and save some money when the times aren't too different. Using google maps API and a flask site.
  • I have a script that generates weekly status update emails based off my git commit messages and pull requests. It also creates timesheets in Harvest based on the projects I'm assigned.
  • I have thrown together some python that automatically controls my reverse-cycle AC system so that it makes optimal use of my solar panels on my roof.

Brian #3: Building a Simple Birthday App with Flask-SQLAlchemy

  • Nice simple application with a clear need.
    • Keep track of upcoming birthdays
    • Avoid Faceboook
    • Build a simple Flask app
    • Try SQLAlchemy

Sponsored by Rollbar, try them at rollbar.com/pythonbytes and don't forget to visit their booth at PyCon!

Michael #4: Spelling with Elemental Symbols

  • How does it work?
    • Input: "Amputations"
    • Output: "AmPuTaTiONS", "AmPUTaTiONS"
  • Generating Character Groupings:
    • 'AmPuTaTiONS' (2,2,2,2,1,1,1)
    • 'AmPUTaTiONS' (2,1,1,2,2,1,1,1)
    • How many are there in general for a given word? fib(n + 1)!
  • Addressing Performance Issues: A few attempts don’t add much but
  • Memoization: The technique of saving a function's output and returning it if the function is called again with the same inputs. A memoized function only needs to generate output once for a given input. This can be very helpful with expensive functions that are called many times with the same few inputs, but only works for pure functions. → 30% faster
  • Algorithms: Switch to directed graphs and recursion, changes O(2^n) to O(n) and time from 16min to 10 sec.
  • Learned a great deal along the way. This project introduced:
    • Combinatorics
    • Performance profiling
    • Time complexity
    • Memoization
    • Recursion
    • Graphs and trees

Brian #5: IDE's for beginners

  • Recent discussion on Reddit about Thonny
  • I have mixed feelings about encouraging beginner IDE's.
    • Mostly negative feelings.
    • And yet there is IDLE, there is Thonny, ...
  • Are these useful? Anti-useful?
  • Isn't learning a decent editor part of learning to program?

Michael #6: PDF Plumber

  • Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.
  • Visual debugging with .to_image()
  • Extracting tables
    • pdfplumber's approach to table detection borrows heavily from Anssi Nurminen's master's thesis, and is inspired by Tabula. It works like this:
    • For any given PDF page, find the lines that are (a) explicitly defined and/or (b) implied by the alignment of words on the page.
    • Merge overlapping, or nearly-overlapping, lines.
    • Find the intersections of all those lines.
    • Find the most granular set of rectangles (i.e., cells) that use these intersections as their vertices.
    • Group contiguous cells into tables.
    • Check out the demonstrations section.

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