Title: Functions Vs. Generators
Slug: functions_vs_generators
Summary: Functions Vs. Generators in Python.
Date: 2016-01-23 12:00
Category: Python
Tags: Basics
Authors: Chris Albon

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Create A Function



In [1]:

    
# Create a function that
def function(names):
    # For each name in a list of names
    for name in names:
        # Returns the name
        return name



In [2]:

    
# Create a variable of that function
students = function(['Abe', 'Bob', 'Christina', 'Derek', 'Eleanor'])



In [3]:

    
# Run the function
students









    Out[3]:





'Abe'

Now we have a problem, we were only returned the name of the first student. Why? Because the function only ran the for name in names iteration once!

Create A Generator

A generator is a function, but instead of returning the return, instead returns an iterator. The generator below is exactly the same as the function above except I have replaced return with yield (which defines whether a function with a regular function or a generator function).



In [4]:

    
# Create a generator that
def generator(names):
    # For each name in a list of names
    for name in names:
        # Yields a generator object
        yield name



In [5]:

    
# Same as above, create a variable for the generator
students = generator(['Abe', 'Bob', 'Christina', 'Derek', 'Eleanor'])

Everything has been the same so far, but now things get interesting. Above when we ran students when it was a function, it returned one name. However, now that students refers to a generator, it yields a generator object of names!



In [6]:

    
# Run the generator
students









    Out[6]:





<generator object generator at 0x104837a40>

What can we do this a generator object? A lot! As a generator students will can each student in the list of students:



In [7]:

    
# Return the next student
next(students)









    Out[7]:





'Abe'



In [8]:

    
# Return the next student
next(students)









    Out[8]:





'Bob'



In [9]:

    
# Return the next student
next(students)









    Out[9]:





'Christina'

It is interesting to note that if we use list(students) we can see all the students still remaining in the generator object's iteration:



In [10]:

    
# List all remaining students in the generator
list(students)









    Out[10]:





['Derek', 'Eleanor']