Using a temperature dataset of four locations in Austin 2016-2017, this code calculates the best date to go for a customization temperature and the best path to visit 3 out of the 4 locations. My code is written in python since it is the only programming I know. Here my goal was to use some of the computer science concepts I recently learned, data structures and algorithms. I was able to implement a greedy algoorithm to calculate a path to take to the 3 locaitons using the data struccture called graphs. Although, my greedy algorithm is inefficient I still wanted to use to apply my newly learned knowledge.
I split the python code into 4 files. Graphs.py holds the data structure of Graphs and nodes. shortest_path.py holds the functions that calculate the best order to visit each of the 3 locations the person is going to visit in Austin. The function to calculate the path is a solution to the variation called Travelling Salesman Problem called the Hamiltonian path problem. I changed this function so that all the nodes on the graph are visited at least once and the ends at the target nodes. Dates.py is used to output all the available dates that have a certain temperatures in the 3 locations we are visiting. Finally, script.py uses all the other files to compose the program.
A link to the the code on GitHub is below:
https://github.com/froglegs1/Austin-visit
I would appreciate any feedback on how to format my code, any problems in my code, general advice, etc.
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