In this class session we'll review some of the features of Python that you will be using this semester in class, in your assignments, and in your term project.

To prepare for class, you should review the first three topics in the Python tutorial and briefly skim the rest of the tutorial. Note that we'll be using Python 3 (not Python 2). You should also review the Getting Started page of Google Colab Notebooks. As always, don't forget to bring a laptop to class!

In class we'll use a combination of lecture, discussion, and a Colab notebook to take a whirlwind tour of some of the Python capabilities that we'll be using this semester. Our goal is not to teach programming -- you need to already have some experience doing Python programming to take this class -- but rather to focus on specific Python capabilities that we'll be using extensively, that is, working with text for search.

If you need to knock some of the rust off your Python knowledge, or do some preparation for later sessions and assignments, this class can also help to identify where you should invest your time.

We'll use the following files in class. And this will be the Colab notebook to run together in the class.

We'll walk through these slides in the class.

Recording is available in Panopto (2 files to be merged, for quick viewing - slides at 00:02:24 aligns with the audio).

Readings recommended after class:

Python basics and numpy: Stanford CS224n Python review session: https://web.stanford.edu/class/cs224n/readings/cs224n-python-review.pdf
Getting started with text files: Language processing: Gutenberg Corpus https://www.pythonstudio.us/language-processing/gutenberg-corpus.html
Getting started with text files: NLTK book, Accessing Text Corpora and Lexical Resources (Ch.2) https://www.nltk.org/book/ch02.html
Visualizing word count: A sample project: Zipf’s law https://goodresearch.dev/zipf.html
More generally: The Python Tutorial https://docs.python.org/3/tutorial/