Generators
We can create our own custom iterators by writing a generator function, which returns a special type of iterator called a generator.
Generator functions have yield
statements within the body of the function instead of return
statements.
Calling a generator function will return a generator object and will not execute the body of the function.
For example, let's consider the following generator function:
def countdown(n):
print("Beginning countdown!")
while n >= 0:
yield n
n -= 1
print("Blastoff!")
Calling countdown(k)
will return a generator object that counts down from k
to 0
.
Since generators are iterators, we can call iter
on the resulting object, which will simply return the same object.
Note that the body is not executed at this point; nothing is printed and no numbers are output.
>>> c = countdown(5)
>>> c
<generator object countdown ...>
>>> c is iter(c)
True
So how is the counting done?
Again, since generators are iterators, we call next
on them to get the next element!
The first time next
is called, execution begins at the first line of the function body and continues until the yield
statement is reached.
The result of evaluating the expression in the yield
statement is returned.
The following interactive session continues from the one above.
>>> next(c)
Beginning countdown!
5
Unlike functions we've seen before in this course, generator functions can remember their state.
On any consecutive calls to next
, execution picks up from the line after the yield
statement that was previously executed.
Like the first call to next
, execution will continue until the next yield
statement is reached.
Note that because of this, Beginning countdown!
doesn't get printed again.
>>> next(c)
4
>>> next(c)
3
The next 3 calls to next
will continue to yield
consecutive descending integers until 0
.
On the following call, a StopIteration
error will be raised because there are no more values to yield
(i.e. the end of the function body was reached before hitting a yield
statement).
>>> next(c)
2
>>> next(c)
1
>>> next(c)
0
>>> next(c)
Blastoff!
StopIteration
Separate calls to countdown
will create distinct generator objects with their own state.
Usually, generators shouldn't restart.
If you'd like to reset the sequence, create another generator object by calling the generator function again.
>>> c1, c2 = countdown(5), countdown(5)
>>> c1 is c2
False
>>> next(c1)
Beginning countdown!
5
>>> next(c2)
Beginning countdown!
5
Here is a summary of the above:
- A generator function has a
yield
statement and returns a generator object. - Calling the
iter
function on a generator object returns the same object without modifying its current state. - The body of a generator function is not evaluated until
next
is called on a resulting generator object. Calling thenext
function on a generator object computes and returns the next object in its sequence. If the sequence is exhausted,StopIteration
is raised. - A generator "remembers" its state for the next
next
call. Therefore,- The first
next
call works like this:- Enter the function and run until the line with
yield
. - Return the value in the
yield
statement, but remember the state of the function for futurenext
calls.
- Enter the function and run until the line with
- And subsequent
next
calls work like this:- Re-enter the function, start at the line after the
yield
statement that was previously executed, and run until the nextyield
statement. - Return the value in the
yield
statement, but remember the state of the function for futurenext
calls.
- Re-enter the function, start at the line after the
- The first
- Calling a generator function returns a brand new generator object (like calling
iter
on an iterable object). - A generator should not restart unless it's defined that way. To start over from the first element in a generator, just call the generator function again to create a new generator.
Another useful tool for generators is the yield from
statement (introduced in Python 3.3).
yield from
will yield all values from an iterator or iterable.
>>> def gen_list(lst):
... yield from lst
...
>>> g = gen_list([1, 2, 3, 4])
>>> next(g)
1
>>> next(g)
2
>>> next(g)
3
>>> next(g)
4
>>> next(g)
StopIteration