We have seen that functions allow us to organize and re-use parts of our code. We have also seen that functions can be defined in terms of other functions. In this lesson we learn that a function can be defined in terms of itself! This very useful approach is called recursion. Legend has it that "to understand recursion, you must first understand recursion."
In our lesson on loops, we used a
while loop to create the following output.
5 4 3 2 1 Blastoff!Here is a program that uses recursion to achieve the same effect.
Let's add some extra print statements to help us understand how the program works. This version of the program also reads the time limit from input.
If you like, use Enter input with the above program to try other input values. Try
0 first and see what happens, and then
When the input is
5, the program first calls a copy of the
countdown function with
n=5, which prints
5 and calls
countdown(4). This continues until
countdown(0), which prints
"Blastoff!" and does not call
countdown any more. When Python finishes executing the
n=0 call of the
countdown function, Python returned to the function that called it, which is the
n=1 call of the
countdown. Then we return to the
n=2 call, and so on.
Now it's your turn to write some code. Modify the
countdown function so that it counts up instead of down.
Next, let's modify our
countdown program to count in increments of 2. The output should be 5, 3, 1, Blastoff! We will change the function argument from
n-2. Is there anything else that we need to change?
You can see that this program did not work as we intended. It printed
5, 3, 1, like we wanted, but instead of stopping it continued with
-1, -3, -5 and ran forever. (More precisely, it runs out of time and also memory, because each recursive call takes up a little more working memory.)
When designing a recursive function, we must be careful that its sequence of calls does not continue forever! Modify the
countdownBy2 program above so that it correctly stops at 1 (or 2, if
n is even) and prints 'Blastoff!'.
Designing recursive functions
A recursive function just means a function that calls itself. But there must be some occasions when the function does not call itself, or else the program will run forever, like we saw above. A base case is the part of a recursive function where it doesn't call itself. In the example above, the base case was
n<=0. Designing a recursive function requires that you carefully choose a base case and make sure that every sequence of function calls eventually reaches a base case.
In the next exercise, the base case has been programmed for you, but you will write the rest of the recursive function.
Now you will write a recursive function that calls
digitalSum as a subroutine.
def gcd(a, b):
if b == 0: return a
return gcd(b, a % b)
Mathematicians believe that every hailstone sequence reaches
1 eventually, no matter what value of
n we start with. However, no one has been able to prove this yet.
Here is an interesting natural application of recursion. A nested list is one where you put some lists inside of others, possibly multiple times. For example, some nested lists of integers are
[[1, 2], [9, 10]] as well as
[, 2] and
x = [, 2, [3, []]]. The last nested list example is a list with three elements:
x== to begin, then
x==[3, []]. (So
x, viewed as a list, has length 3). Note that a list like
[1, 2, 3] also counts as a nested list. Can we write a function to find the total sum of any nested list of integers? For example, on input
[, 2, [10, 8, []]] it should return the value
This task is difficult for a
while loop or a
for loop, since we want a function that works on nested lists with any shape/format. However, nested lists have a naturally recursive structure: a nested list is a list each of whose items is either (a) an integer or (b) a nested list. And, once we compute the sum of each subpart of the main list, the total of those values is the overall sum. We can express this with the following code; it uses
isinstance(x, int) which gives a boolean value telling us whether
x has integer type (as opposed to a list).
Do you see how recursion is used to break down each nested list into smaller parts? For example,
nestedListSum([1, [3, 4], 5]) makes a total of 6 recursive calls: the initial one, then on
1, then on
[3, 4], then on
4, (after which the
[3, 4] total is returned as
7) and finally on
5 (after which the overall total
13 is obtained).
Recursion is also related to fractals — images which contain multiple smaller copies of themselves. The banner at the top of this webpage is one example. The next exercise creates a simple repeating pattern using recursion.
Congratulations! You are ready to move to the next lesson.