Data structures in Python are almost entirely already iterable. However, sometimes you do need a generator for the cases when the data is not iterable.
A generator is just a function that yields back to the section where it was called from. This is a signal for Python that you want to create a generator therefore it will automatically save the state of the function at the point of the
yield statement. At this point you can return to it when
next() is called.
A classic example will be a generator that generates the sequence of squares.
>>> def squares(value = 5): ... while True: ... value = value + 1 ... yield (value - 1) * (value - 1) ... >>> generator = squares() >>> next(generator) 25 >>> next(generator) 36 >>> next(generator) 49
It starts generating the squares from number five!
If you use Python 3.3 (or above) then you can take advantage of the
yield from statement. It is a way of creating generator functions that use other iterators to generate the required values. I created the
file.py and I placed in it the code shown below:
def counter_up_down(value = 1): yield from range(1, value, 5) yield from range(value, 0, -3) print(list(counter_up_down(30)))
I run the file into terminal and this is the output:
ddn_ro@ddn:/mnt/c/Users/dumit/Desktop$ python3 file.py [1, 6, 11, 16, 21, 26, 30, 27, 24, 21, 18, 15, 12, 9, 6, 3]