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  3. Python Data Science Toolbox (Part 2)

Exercise

Build a generator

In previous exercises, you've dealt mainly with writing generator expressions, which uses comprehension syntax. Being able to use comprehension syntax for generator expressions made your work so much easier!

Now, recall from the video that not only are there generator expressions, there are generator functions as well. Generator functions are functions that, like generator expressions, yield a series of values, instead of returning a single value. A generator function is defined as you do a regular function, but whenever it generates a value, it uses the keyword yield instead of return.

In this exercise, you will create a generator function with a similar mechanism as the generator expression you defined in the previous exercise: 

lengths = (len(person) for person in lannister)

Instructions

100 XP
  • Complete the function header for the function get_lengths() that has a single parameter, input_list.
  • In the for loop in the function definition, yield the length of the strings in input_list.
  • Complete the iterable part of the for loop for printing the values generated by the get_lengths() generator function. Supply the call to get_lengths(), passing in the list lannister.