Recursion: Python
Lesson 1 of 2
1. 1
The best way to understand recursion is with lots of practice! At first, this method of solving a problem can seem unfamiliar but by the end of this lesson, we’ll have implemented a variety of algo…
2. 2
In the previous exercise, we used an iterative function to implement how a call stack accumulates execution contexts during recursive function calls. We’ll now address the conclusion of this funct…
3. 3
Now that we’ve built a mental model for how recursion is handled by Python, let’s implement the same function and make it truly recursive. To recap: We want a function that takes an integer as an …
4. 4
Excellent job writing your first recursive function. Our next task may seem familiar so there won’t be as much guidance. We’d like a function factorial that, given a positive integer as input, re…
5. 5
The previous exercise ended with a stack overflow, which is a reminder that recursion has costs that iteration doesn’t. We saw in the first exercise that **every recursive call spends time on th…
6. 6
Let’s use recursion to solve another problem involving lists: flatten(). We want to write a function that removes nested lists within a list but keeps the values contained. nested_planets = […
7. 7
So far our recursive functions have all included a single recursive call within the function definition. Let’s explore a problem which pushes us to use multiple recursive calls within the fun…
8. 8
Data structures can also be recursive. Trees are a recursive data structure because their definition is self-referential. A tree is a data structure which contains a piece of data **and reference…
1. 1
This lesson will provide a series of algorithms and an iterative or recursive implementation. Anything we write iteratively, we can also write recursively, and vice versa. Often, the difference i…
2. 2
Nice work! We’ll demonstrate another classic recursive function: fibonacci(). fibonacci() should return the Nth Fibonacci number, where N is the number given as input. The first two numbers of a F…
3. 3
Fantastic! Now we’ll switch gears and show you an iterative algorithm to sum the digits of a number. This function, sum_digits(), produces the sum of all the digits in a positive number as if the…
4. 4
We’ll use an iterative solution to the following problem: find the minimum value in a list. def find_min(my_list): min = None for element in my_list: if not min or (element < min): m…
5. 5
Palindromes are words which read the same forward and backward. Here’s an iterative function that checks whether a given string is a palindrome: def is_palindrome(my_string): while len(my_string…
6. 6
All programming languages you’re likely to use will include arithmetic operators like +, -, and . Let’s pretend Python left out the multiplication, , operator. How could we implement it oursel…
7. 7
Binary trees , trees which have at most two children per node, are a useful data structure for organizing hierarchical data. It’s helpful to know the depth of a tree, or how many levels make up t…

## How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory 