Monday, July 6 from 9:00 AM - 1:00 PM CDT (With tutorial setup help from 8:00 AM - 9:00 AM CDT.)
This tutorial is a gentle introduction to Python for folks who are completely new to it and may not have much experience programming. We’ll work in a Jupyter Notebook, one of the most popular tools in scientific Python. You’ll learn how to write beautiful Python while practicing loops, if’s, functions, and usage of Python’s built-in features in a series of fun, interactive exercises. By the end of the tutorial we think you’ll be ready to write your own basic Python -- but most importantly, we want you to learn the form and vocabulary of Python so that you can understand Python documentation and interpret code written by others.
See the tutorial description on the conference website here.
Please do at least the download and install of Anaconda before coming to the tutorial! We can help with further setup at the tutorial.
If you don't already have Anaconda installed, download and install Anaconda for Python 3 (not Python 2): https://www.anaconda.com/products/individual.
If you're prompted to install VS Code we recommend you do install it unless you already have a code editor you prefer.
After installing Anaconda you can test your installation using these instructions.
If you'd like to do your own setup, we'll be using the following Python libraries:
If you're not able to get Anaconda installed/working you can still follow along in class by going to this URL and launching the notebooks: https://mybinder.org/v2/gh/jiffyclub/scipy-2020-intro-to-python/main. However, note that Binder will not persist your work and will "forget" about it after a period of idleness. Make sure to download your work as soon as you finish a lesson so you can keep a record.
While this tutorial serves as an introduction to Python, you may want to consider reading about some concepts in more detail on your own time. Below are some useful references to help you get more acquainted with Python and other programming fundamentals.
- Official Python (3) Documentation
- Software Carpentry
- SciPy Lecture Notes - Commonly Used Packages
- How to Think Like a Computer Scientist Tutorial
After reading the links in the above section, you may consider learning about more advanced topics: