This repository contains the slides for Computer Science 102 Fall 2020. To learn more about the course for which these slides were created, please visit the Computer Science 102 Fall 2020 GitHub Organization.

Since this repository primarily contains LaTeX source code, the GitHub Actions configuration for it will compile the source code and automatically release a PDF of the source code whenever the last commit is associated with a Git Tag. As such, this will cause PDF files to become available in the listing of the Releases for this repository. All release numbers in this repository adhere to the Semantic Versioning standard.

The slides contain the source code of segments of Python programs that a student can run in order to learn more about the connection between discrete structures and Python programming. Here is an outline of the commands that you can type if you want to change into the directory that contains these Python programs and then run them on your own laptop. Importantly, these commands assume that you have already cloned this repository to your laptop.

• Change into the directory that contains the Python source code: cd src
• Run the program that computes the absolute value: python abs-compute.py
• Run the program that computes the factorial sequence: python factorial-function.py
• Run the program that computes the mean of a list of numbers: python mean-compute.py
• Run the program that uses a Newton's method function to compute a square root: python newtons-method-function.py
• Run the program that uses a Newton's method segment to compute a square root: python newtons-method.py
• Run the program that displays a range of integer numbers: python range-display.py
• Run the program that uses higher-order functions to compute a number's square: python square-function.py
• Run the program that performs string multiple types of concatenation: python string-concatenation.py
• Run the program that performs sums and products of lists: python number-sums-products.py
• Run the program that demonstrates the map function: python map-function.py
• Run the program that demonstrates the filter function: python filter-function.py
• Run the program that demonstrates the reduce function: python reduce-function.py
• Run the program that demonstrates a generator expression: python generate-even-squares.py
• Run the program that demonstrates a generator function for the Fibonacci sequence: python fibonacci-generator.py
• Run the program that demonstrates a list function for the Fibonacci sequence: python fibonacci-list.py
• Run the program that demonstrates a tuple function for the Fibonacci sequence: python fibonacci-tuple.py
• Run the program that generates and endless stream of integers: python endless-stream.py
• Run the program that demonstrates how to create sets: python set-creation-examples.py
• Run the program that demonstrates how to create sets with different elements: python set-element-types.py
• Run the program that uses the different set operations: python set-operations.py
• Run the program that demonstrates the use of set comprehensions: python set-comprehension.py
• Run the program that demonstrates the use of set comprehensions and Boolean logic: python set-comprehension-logical.py
• Run the program that shows how to create a finite set using Sympy: python finiteset-creation.py
• Run the program that shows how to perform operations on a finite set using Sympy: python finiteset-operations.py
• Run the program that demonstrates that a finite set in Sympy removes repeated elements: python finiteset-repeats.py
• Run the program that shows how to perform subsets with the finite set in Sympy: python finiteset-subsets.py
• Run the program that shows to how calculate logical-and-probability with finite set in Sympy: python probability-event-and.py
• Run the program that shows to how calculate logical-or-probability with finite set in Sympy: python probability-event-or.py
• Run the program that demonstrates a basic probably calculation in Python: python probability-example.py
• Run the program that shows how to create a dictionary discrete structure: python dictionary-example.py
• Run the program that shows some differences in the dictionary discrete structure: python dictionary-differences.py
• Run the program that shows how to represent an object in Python using a list: python dog-list.py
• Run the program that shows how to represent an object in Python using a dictionary: python dog-dictionary.py
• Run the program that shows how to represent an object in Python using object-oriented programming : python dog-object.py

Please note that these are what I would call "Python program segments" in that they do not leverage a framework, like Poetry, for building Python applications. While these programs will execute and produce output in your terminal window, they do not provide either a command-line or a web-based interface. Unless stated otherwise, these programs also do not assume that you have any additional Python packages installed on your laptop. With that said, the programs that use the FiniteSet package assume that you have installed the sympy package by typing pip install sympy. Finally, these programs contain debugging output not listed on the slides, thereby better ensuring that you can understand how the program accepts input and produces output. Here is an example from running the command python mean-compute.py program:

Called compute_mean with numbers = [5, 10, 5, 10, 5]
Sum of numbers = 35
Length of numbers = 5
Calculated mean = 7.0
7.0
Called compute_mean with numbers = [5, 1, 7, 99, 4]
Sum of numbers = 116
Length of numbers = 5
Calculated mean = 23.2
23.2
5.0

The version of the Python function that contains the debugging output statements that produced this output is as follows:

def compute_mean(numbers):
    print(f"Called compute_mean with numbers = {numbers}")
    s = sum(numbers)
    print(f"Sum of numbers = {s}")
    N = len(numbers)
    print(f"Length of numbers = {N}")
    mean = s / N
    print(f"Calculated mean = {mean}")
    return mean

If you have any problems with compiling the slides, then please create an issue in this repository using the "Issues" link at the top of this site. Please note that this slides has been developed and tested on an Arch Linux workstation running TexLive 2020. It is also worth noting that you can also compile the slides using LaTeX development tools such as latexmk. If you are unable to compile the slides with your development tools and your execution environment, then please open a new issue and I will attempt to resolve your concerns.