Lecture 15: Introduction to the Policy context

Aidan Feldman

Computing in Context (SIPA)

Structure for today¶

1. Intro

2. Going over course info like the syllabus, tools, etc.

3. IDEs

4. Command line

5. Packages

About me¶

• Coding since 2005 🖥

• Government since 2014 🦅

• Teaching since 2011 🎓

• Also a modern dancer 💃 and cyclist 🚲

Day jobs¶

Currently freelancing with:

• Colorado Behavioral Health Administration

• Reinvent Albany

In the past, have worked for...

Government¶

• NYC Office of Technology & Innovation (OTI)

• California Department of Transportation (CalTrans)

• General Services Administration (GSA)

  • 18F

  • TTS

• Census xD

• NYC Planning Labs

Non-profits¶

• Upsolve

• VoteAmerica

Tech companies¶

• GitHub

• Artsy

Access the course site¶

computing-in-context.afeld.me

You can also get there through CourseWorks.

Class materials¶

New context-specific stuff:

• Syllabus

• Office hours

• Files

• CourseWorks

• Ed

Disclaimers¶

Me¶

• Here to teach you to:

  • Do a lot with just a little code

  • Troubleshoot

  • Google stuff

• Terrible memory

  • Names

• Not a statistician

You¶

• Are not going to understand everything the first time

• Will want to throw your computer out a window at one or many points in the class

  • Celebrate the little victories

• Will get out of it what you put into it

Politics/protests/war¶

⏪ Rewind¶

These next two lectures, we’ll be revisiting topics from the first half.

Python¶

• Language

• Interpretor

• Language

• Interpretor

• Editor (VSCode)

• Largely live demo and installation

  • If everything works, it will be a miracle.

  • Thanks for your patience.

• Showing the recommended+supported path

  • If you’re comfortable with alternatives, can use those.

• May feel like a whirlwind, just skimming the surface of these tools

• Keeping the information in the slides minimal

  • There are links to more info

Editors¶

• Spectrum: Minimalist editors to integrated development environments (IDEs)

• Like Notepad/TextEdit/Notes vs. Word / Google Docs

  • Pros/cons?

• Getting even more powerful with generative AI integrations

Visual Studio Code (VSCode)¶

Note to self: Switch to Computing in Context demo Profile.

Set up project¶

1. Go to open a folder/workspace

2. If you don’t have a class folder already:

   1. Navigate to where you want it.

   2. Click New Folder.

   3. Name it something like computing-in-context.

Extensions¶

Install extensions, if they aren’t already:

• Python

• Ruff

Configuration¶

1. Open your User Settings JSON.

2. Add the following. You may already have some settings — if you want to keep them, you’ll need to combine.

   {
     // https://marketplace.visualstudio.com/items?itemName=charliermarsh.ruff#configuring-vs-code
     "editor.formatOnSave": true,
     "[python]": {
       "editor.defaultFormatter": "charliermarsh.ruff",
       "editor.codeActionsOnSave": {
         "source.organizeImports": "explicit"
       }
     },
     "notebook.formatOnSave.enabled": true,
     "notebook.codeActionsOnSave": {
       "notebook.source.organizeImports": "explicit"
     }
   }

Confirm it works¶

1. Put some ill-formatted code (like 1 + 1) in test.py.

2. Save the file.

3. Confirm the extra spaces were automatically removed.

Create Python file¶

1. Create test.py

2. Add code

   • print() something

3. Confirm it’s using Python through the venv.

   • Can have multiple Pythons

4. Run script

5. Show:

   1. Syntax issue

   2. Unused import

   3. Auto import

Command line¶

• Can use from within VSCode, or standalone

  • We’ll do the former, to stay in one place.

• UNIX vs. Windows

  • Git BASH

• We’re learning as little as necessary

  • We get into more detail in Advanced Computing for Policy.

Quick tips¶

• You can press the up arrow on your keyboard to get to previously-run commands, rather than having to re-type it each time.

• You can press control-R then type something to search through your command history. Press control-R again to see the next result.

Packages¶

• a.k.a. “libraries”

• Developers have create them to make code/functionality reusable and easily sharable

• Software plugins that you import

• Main packages we’ll use:

  • jupyter-book

  • pandas

  • plotly

A module is a file containing Python definitions and statements.

https://docs.python.org/3/tutorial/modules.html

Your code, part of the standard library, or part of a package.