Sign in to your Python Morsels account to save your screencast settings.
Don't have an account yet? Sign up here.
What is a generator function in Python?
generator functiondefinition in Python Terminology.
Here's a regular function:
def negate_all(iterable): print("Start") negatives =  for n in iterable: print("Negating", n) negatives.append(-n) print("End") return negatives
What do you think we'll see when we call this function? What do you think we'll get back?
>>> negatives = negate_all([2, 1, 3])
When we call this function, we see a number of things printed out:
>>> negatives = negate_all([2, 1, 3]) Start Negating 2 Negating 1 Negating 3 End
And we get back the return value of this function:
>>> negatives [-2, -1, -3]
This function is very similar to a regular function:
def negate_all(iterable): print("Start") for n in iterable: print("Negating", n) yield -n print("End")
But it's not a normal Python function: it's a generator function.
We can only tell it's a generator function by the presence of a
yield statement turns a regular function into a generator function.
What do you think we'll see when we call this generator function? What do you think it'll give us back? What will it return to us?
>>> negatives = negate_all([2, 1, 3])
When we call this generator function, we don't see anything printed out. And the thing we get back is a generator object:
>>> negatives = negate_all([2, 1, 3]) >>> negatives <generator object negate_all at 0x7f5d85fd49e0>
Generator objects are lazy iterables.
One thing we can do with a generator object is pass it to the built-in
Passing a generator object to
next will start running the generator function that created it:
>>> negatives = negate_all([2, 1, 3]) >>> x = next(negatives) Start Negating 2
The generator function printed out
Start and then
Negating 2, and then it stopped.
It stopped because it hit a
-2 to us:
>>> x -2
If we call
next again (passing in the same generator object) we'll see
Negating 1 printed out:
>>> x = next(negatives) Negating 1
And the generator yielded
>>> x -1
Each time we pass this generator object to
next, the generator function that created it will start up again from where it left off.
Generator objects put themselves on pause to
yield an item.
Then when you ask them for another item, they'll start running their generator function again until they hit another
The next item we get is
>>> x = next(negatives) Negating 3 >>> x -3
But then if we pass this generator object to
next again, it will hit the end of the function, which will raise a
>>> x = next(negatives) End Traceback (most recent call last): File "<stdin>", line 1, in <module> StopIteration
It's a little bit unusual to see a generator object passed to the built-in
Normally, we loop over generator objects the same way we loop over any other iterable, with a
>>> negatives = negate_all([2, 1, 3]) >>> for n in negatives: ... print("Got", n) ...
When we loop over this generator object, we'll see that our generator function is being called in-between our
for loop being run:
>>> negatives = negate_all([2, 1, 3]) >>> for n in negatives: ... print("Got", n) ... Start Negating 2 Got -2 Negating 1 Got -1 Negating 3 Got -3 End
So when we ask for the first item, it starts running our generator function.
Start Negating 2
Then our generator function puts itself on pause to yield that first item to our
for loop, which then prints out
Got -2 (the first item is
for loop asks the generator for another item, which causes the generator function to start running again (unpausing itself).
The generator function then prints out
Negating 1, and yields
-1 to our
for loop, which prints out
Negating 1 Got -1
And the same thing happens with
Our generator function prints out
Negating 3, and then we move back to our
for loop body, which prints out
Negating 3 Got -3
Then finally, when our generator function returns, our
for loop ends as well:
Once we've consumed all the items in a generator object, we say that it's been exhausted (meaning it doesn't have anything left in it).
So if we loop over our generator object a second time, we'll see that it's empty now:
>>> for n in negatives: ... print("Got", n) ... >>>
yieldstatements is a generator function
A generator function is a function with one or more
yield statements in it.
Unlike regular functions, generator functions return generator objects. Meaning, when you call a generator function, it doesn't run the function. Instead, it gives you back a generator object.
If you loop over that generator object, it will run the function until a
yield statement is reached.
At that point the generator object will put itself on pause, and yield the next item.
This process will continue over and over until you've consumed all the items within the generator.
Need to fill-in gaps in your Python skills?
Sign up for my Python newsletter where I share one of my favorite Python tips every week.
Generator functions look like regular functions but they have one or more
yield statements within them. Unlike regular functions, the code within a generator function isn't run when you call it! Calling a generator function returns a generator object, which is a lazy iterable.
To track your progress on this Python Morsels topic trail, sign in or sign up.
Need to fill-in gaps in your Python skills? I send weekly emails designed to do just that.