Practice Python

Beginner Python exercises

11 November 2014

Element Search

Exercise 20 (and Solution)

Write a function that takes an ordered list of numbers (a list where the elements are in order from smallest to largest) and another number. The function decides whether or not the given number is inside the list and returns (then prints) an appropriate boolean.




  1. Booleans - True and False
  2. Equality testing
  3. Binary search


When you are writing programs, there is often a time when you need to make a decision about something based on the truthfulness of something else. Basically, you need to make a decision based on whether something is TRUE or something is FALSE.

An obvious example is when using conditionals:

  michele_age = 22
  truth_value = michele_age > 17
  if (truth_value):
    print("Michele can see a rated R movie")

(We talked about this idea of conditionals in a previous post.)

But what is happening behind the scenes is that the statement michele_age > 17 is being evaluated into a type that is either True or False. This is then getting stored inside the variable truth_value, and then the decision is being made inside the conditional.

Here is another example:

  while True:
    age = input("How old are you? ")
    if age >= 17: 
      print("can see a rated R movie")
    elif age < 17 and age > 12:
      print("can see a rated PG-13 movie")
      print("can only see rated PG movies")

What the while True statement does at the beginning of the code segment is continue asking for an age and printing a response - it never stops. (To stop it, press CTRL-C in a terminal or in the Python shell).

These types - True and False are called boolean types or boolean variables. They can only take on two values, either True or False.

For more extensive reading on Python booleans, take a look at these resources.

Equality testing on strings

Scenarios come up where you need to test if things are equal to each other - numbers or strings or something else. We covered this idea in a previous post, but it is worth returning to again, this time for strings.

Good thing it’s easy!

Remember, comparing numbers for equality is done with an == sign, like so:

  age = 21
  if age == 21:
    print("You are 21!")
  elif age > 21:
    print("You're old.")
    print("Young one!")

Turns out, comparing strings is equally (hehe..) simple, using a == to check for equality and != to check for inequality.

  password = "unsafepassword"
  if password == "unsafepassword":
    print("You may enter.")
    print("Try again!")

Or, a more practical password-checking piece of code:

  real_password = "unsafepassword"
  user_password = input("Enter the password: ")
  while user_password != real_password:
    user_password = input("Enter the password: ")
  print("You may enter!")

There are a number of ways to search for elements in a list, and there is no one correct way to do so. The point of this exercise is to get you thinking about possible ways to search for elements in the list, in an entire sequence of exercises about lists, searching, and sorting. This exercise might seem silly and easy at first, but the more you dive into this topic, the more difficult it becomes.

The word “binary” means there are two choices (in computers, often this is 0 or 1, but it really means any choice between two things). “Search” is to look for something. So the main idea behind binary search is to look for something in a way that gives you a decision tree for where to look, containing two choices. Let me give you an example:

Let’s take the list a = [1, 3, 5, 30, 42, 43, 500]. It is an “ordered list”, or a list where the elements in the list go from smaller to larger. Let’s say we want to know whether the element 9 is in the list or not. Here is what we do:

What the example shows is that in an ordered list, knowing how the element you are looking for compares to another element in the list splits the list in two - one half where the element can be, and one where it definitely cannot be. In the case where our list contains millions of elements, knowing that we can cut the “search space” in half is a great increase in efficiency.

When you are writing the solution, first try to write it without binary search. Then when you want to try implementing binary search, write a separate function. In the solution I will give an example for how to write a binary search in Python.

Happy coding!

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