# Functions Vs. Generators

## Create A Function

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

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

```
# Run the function
students
```

```
'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).

```
# 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
```

```
# 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!

```
# Run the generator
students
```

```
<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:

```
# Return the next student
next(students)
```

```
'Abe'
```

```
# Return the next student
next(students)
```

```
'Bob'
```

```
# Return the next student
next(students)
```

```
'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:

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

```
['Derek', 'Eleanor']
```