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Generator Functions Versus Generator Expressions

Interestingly, the same iteration can often be coded with either a generator function or a generator expression. The following generator expression, for example, repeats each character in a string four times:

>>> G = (c * 4 for c in 'SPAM')           # Generator expression
>>> list(G)                               # Force generator to produce all results
['SSSS', 'PPPP', 'AAAA', 'MMMM']

The equivalent generator function requires slightly more code, but as a multistatement function it will be able to code more logic and use more state information if needed:

>>> def timesfour(S):                     # Generator function
...     for c in S:
...         yield c * 4
...
>>> G = timesfour('spam')
>>> list(G)                               # Iterate automatically
['ssss', 'pppp', 'aaaa', 'mmmm']

Both expressions and functions support both automatic and manual iteration—the prior list call iterates automatically, and the following iterate manually:

>>> G = (c * 4 for c in 'SPAM')
>>> I = iter(G)                           # Iterate manually
>>> next(I)
'SSSS'
>>> next(I)
'PPPP'

>>> G = timesfour('spam')
>>> I = iter(G)
>>> next(I)
'ssss'
>>> next(I)
'pppp'

Notice that we make new generators here to iterate again—as explained in the next section, generators are one-shot iterators.