Instructions for Introduction to Scientific Python

Author

Joseph C. Slater

Address

201 Clement Hall 1010 N. Peachtree Avenue Tennessee Tech University Cookeville, TN 38505

Contact

joseph.c.slater@gmail.com

date

Date: 2019-08-25 19:23:53 +0000 (Sunday, 25 August 2019)

status

This is a "work in progress"

version

1

copyright

This document has been placed in the public domain. You may do with it as you wish. You may copy, modify, redistribute, reattribute, sell, buy, rent, lease, destroy, or improve it, quote it at length, excerpt, incorporate, collate, fold, staple, or mutilate it, or do anything else to it that your or anyone else's heart desires.

If you can't get this to work, you can do much of this class in mybinder.org.

To be able to execute all of the code I will demonstrate during the class, and to be able to write your own, please come prepared by installing Anaconda Python and the Github app per the instructionsin the sections below.

Table of Contents

What will be covered? The rest will happen in class! (See that link, those are the actual class notes).

Installing Python

• Students should have Anaconda Python, Python version 3.5, 3.6, 3.7, or 3.8, installed (64 bit is correct for any reasonably recent machine). There won't be time to do this at the start of the short class!!!

I may have an alternative live during the course, but it won't get your machine working!

• When doing this also install Visual Studio Code. It is an option near the end.
• Just install anything it asks you about.
• Users should install locally (not for all users) to keep things simple.
• All platforms (Mac, Windows, Linux) will be covered.

Platform Differences

Windows Users

• Find the Anaconda Prompt application and run it. Answer yes to all prompts.
• Type conda update --all
• Type conda install cython
• Type conda install numba

Mac Users

• Find the Terminal.app. It is located in your /Applications/Utilities folder. Answer yes to all prompts.
  • Quick tip- command-key space-bar, then type 'Terminal' may launch it if Spotlight is set up correctly.
• Type conda update --all
• Type conda install cython
• Type conda install numba

Linux Users

• Open your favorite terminal and type conda update --all. Answer yes to all prompts.
• Type conda install cython
• Type conda install numba

Installing GitHub Desktop

I will want you to get things during the course from GitHub.

• Download GitHub Desktop and install it. You may need to create an account on GitHub.

  Linux Users:

  You will need to use GitKraken.

  • Good News: It's much more powerful.
  • Bad News: It's much more complicated.
  • I need to leave it to you to read up on how to use it. I'll try to add instructions later.
• Go to the repository for this class in your web browser.
• You should be able to see a green button that says Clone or Download. Clone is much better. This will allow you to update it in the future. Download means you reorganize each time. I suggest you create a folder GitHub in your Documents folder.

Loading and running my course locally

Mac Users

• Open your terminal application.
  • For Mac, look inside your Applications folder, inside Utilities and run Terminal
  • On Linux, you likely already know which one you like.
• Move into the appropriate directory
  • Method 1. (Useful to learn, not necessary today)
    • Move into the appropriate directory.
      • This is done using the cd command. In the Finder go inside the folder with the cloned repository.
      • You know you are in the right place when you see Calc_Review.ipynb.
      • Hold the Command key and click on the folder icon at the top of the window. It's to the left of Introduction_to_Python.
      • This is your path. It will look something like /MyComputer/Users/Myname/GitHub/Introduction_to_Python. It depends on a lot of decisions you've made in the past and presently.
      • Get the right names and type cd /MyComputer/Users/Myname/GitHub/Introduction_to_Python.
      • There may be something like Documents or such embedded. You need to figure this path out.
      • Typing ls should provide a list of files that include Calc_Review.ipynb
  • Method 2. (Quick way but lacking power)
    • In the GitHub Desktop (app), select the repository Introduction_to_Python.
    • On the right it will provide options, one of which is open in terminal.
    • This, plus the pwd command (present working directory) can tell you where everything is.
• Type jupyter notebook Introduction_to_Python.ipynb

Linux Users

• Read the Mac instructions and tweak the names for linux. Unfortunately there is no GitHub Desktop for linux

Windows Users

• Open Anaconda Terminal
• Move into the appropriate directory
  • Method 1. (Useful to learn, maybe not necessary today)
  • This is done using the cd command. In the File Explorer go inside the folder with the cloned repository.
  • You know you are in the right place when you see Calc_Review.ipynb.
  • Near the top of the window you can see the entire path.
  • This is your path. It will look something like C:\MyComputer\Users\Myname\GitHub\Introduction_to_Python. It depends on a lot of decisions you've made in the past and presently. This is called your path.
  • Get the right names and type cd path from above. This is all one line. The path from above is exactly what you read off the top of your window two bullets above.
  • There may be something like Documents or such embedded. You need to figure this path out.
  • Typing dir should provide a list of files that include Calc_Review.ipynb
• Method 2. (Quick way but lacking power)
• In the GitHub Desktop (app), select the repository Introduction_to_Python.
• On the right it will (may- I haven't checked) provide options, one of which is open in Anaconda Terminal.
• This, plus the cd command (cd both changes directory when there is a directory after it, or tells you the directory if there is not.) can tell you where everything is.
• Type jupyter notebook Introduction_to_Python.ipynb

If we have time, we will learn a little Bokeh

These are notes to myself... you might figure them out, you need to know how to hunt paths, though.

bokeh serve /Users/jslater/Documents/python-dev/bokeh/examples/app/taylor.py

jupyter notebook /Users/jslater/Documents/python-dev/bokeh-notebooks/quickstart

Other Educational Resources

• Python Plotting With Matplotlib
• Lorena Barba's Numerical Python Mooc
• SciPy Lecture Notes
• Generic Python Introduction
• SciPy Cookbook

Recommended Books

• Learning Scientific Programming with Python - Christian Hill
• A Primer on Scientific Programming with Python - Hans Petter Langtangen (4th Edition)