CSC 101 Principles in Information Technology and Computation

For example, to count the number of items in a list, we would write the following for loop:

We set the variable count to zero before the loop starts, then we write a for loop to run through the list of numbers. Our iteration variable is named itervar and while we do not use itervar in the loop, it does control the loop and cause the loop body to be executed once for each of the values in the list.

count = 0
for itervar in [3, 41, 12, 9, 74, 15]:
  count = count + 1
print('Count: ', count)

In the body of the loop, we add 1 to the current value of count for each of the values in the list. While the loop is executing, the value of count is the number of values we have seen “so far”.

Once the loop completes, the value of count is the total number of items. The total number “falls in our lap” at the end of the loop. We construct the loop so that we have what we want when the loop finishes.

Another similar loop that computes the total of a set of numbers is as follows:

In this loop we do use the iteration variable. Instead of simply adding one to the count as in the previous loop, we add the actual number (3, 41, 12, etc.) to the running total during each loop iteration. If you think about the variable total, it contains the “running total of the values so far”. So before the loop starts total is zero because we have not yet seen any values, during the loop total is the running total, and at the end of the loop total is the overall total of all the values in the list.

As the loop executes, total accumulates the sum of the elements; a variable used this way is sometimes called an accumulator.

Neither the counting loop nor the summing loop are particularly useful in practice because there are built-in functions len() and sum() that compute the number of items in a list and the total of the items in the list respectively.

To find the largest value in a list or sequence, we construct the following loop:

When the program executes, the output is as follows:

Before: None
Loop: 3 3
Loop: 41 41
Loop: 12 41
Loop: 9 41
Loop: 74 74
Loop: 15 74
Largest: 74

The variable largest is best thought of as “the largest value we have seen so far.” Before the loop, we set largest to the constant None. None is a special constant value which we can store in a variable to mark the variable as “empty”.

Before the loop starts, the largest value we have seen so far is None since we have not yet seen any values. While the loop is executing, if largest is None then we take the first value we see as the largest so far. You can see in the first iteration when the value of itervar is 3, since largest is None, we immediately set largest to be 3.

After the first iteration, largest is no longer None, so the second part of the compound logical expression that checks itervar > largest triggers only when we see a value that is larger than the “largest so far”. When we see a new “even larger” value we take that new value for largest. You can see in the program output that largest progresses from 3 to 41 to 74.

At the end of the loop, we have scanned all of the values and the variable largest now does contain the largest value in the list.

To compute the smallest number, the code is very similar with one small change:

Again, smallest is the “smallest so far” before, during, and after the loop executes. When the loop has completed, smallest contains the minimum value in the list.

Again as in counting and summing, the built-in functions max() and min() make writing these exact loops unnecessary.

The following is a simple version of the Python built-in min() function:

In the function version of the “smallest” code, we removed all of the print statements so as to be equivalent to the min function which is already built in to Python.