Python Basics (7) --- Generators

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1. Generators

Genenrators are any functions that have a yield statement.

2. yield statement

Inside a function, when the program meets the return statement，it will stop immediately. To return several vlues one at a time, there comes the yield statement. A yield statement circulaly return the values and wrap them in a generator object.

def flatten(nested):
    for sublist in nested:
        for element in sublist:
            return element
nested=[[1,2],[3,4],[5,6]]
flatten(nested)
>>>
1     # the function will only return one value and terminate.


def flatten(nested):
    for sublist in nested:
        for element in sublist:
            yield element
nested=[[1,2],[3,4],[5,6]]
flatten(nested)
>>>
<generator object flatten at 0x00000121F9D39518>   # a generator object

list(flatten(nested))  #make it a list
>>>
[1, 2, 3, 4, 5, 6]

3. A recursive generator

def flattern(nested):
    try:
        for sublist in nested: # recursive case
            for element in flattern(sublist):
                yield element
    except TypeError:# base case if nested is just a element, it will raise the
        yield nested  #TypeError: 'int' object is not iterable

4. Generator and iterator

The values of yield statement are wrapped in a generator object which is also an iterator.