In this chapter, you learned many techniques that help cut down the application's runtime. We started by improving the speed of the Gold Hunt application. The total time taken to run this application was improved by more than 50%—we accomplished this by changing the algorithm so that it does not need to compute the square root for distance comparison. Two more changes knocked off a few more seconds from the total execution time. We avoided the function re-evaluation (skipped the "dots") and preferred local scope for the variables over global scope. This was the end of part one of the performance improvement for the Gold Hunt program.
Moving on, the chapter taught you a number of ways that help speed up the code. It illustrated how a list comprehension does a better job compared to an equivalent for loop. We also saw how the choice of data structure affects the performance. The chapter further introduced us to the generator expressions that offer memory advantage over the list comprehensions...
