Intro to CS: Lecture 22 - Big Oh and Theta

Mon 19 January 2026 in Intro to CS using Python

#computer-science #python

Topics: Complexity: Big-Oh notation, Big-Theta notation, complexity relations and classes, calc-complexity

Getting introduced to the python time.perf_counter() function. This is new to me. I guess its a more accurate version of time.time(). We compare the runtime of a few different functions. The plots of input size vs. runtime turn out to be linear, logarithmic, and quadratic.

Timing is a critical tool to assess the performance of programs. But we will see another complementary tool (asymptotic complexity) that has other advantages. A.k.a. Big Oh notation. Express runtime as an order-of instead of exact growth. Focus on the largest factors in runtime.