Time complexity tracking for python lists
This project is useful for people exploring time complexity for algorithms in Python. Starting out it only works with python lists, but I plan to extending it to numpy arrays and dictionaries eventually.
It works by tracking __getitem__ calls. After you run your algorithm, call .show().
This plots the number of times that each element of the array was accessed, as well as lines showing several different time complexities.
Comparing time complexity of sorting algorithms is a common application of this sort of analysis. For instance if we wanted to compare the efficency of selection sort and quick sort, you could use the following code:
test = Array(np.random.rand(9))
selectionSort(test)
test.show()
test = Array(np.random.rand(9))
quickSort(test)
test.show()