Yield

[Fredrik Lundh]

Danny Colligan wrote:

> Carsten mentioned that generators are more memory-efficient to use when
> dealing with large numbers of objects.  Is this the main advantage of
> using generators?  Also, in what other novel ways are generators used
> that are clearly superior to alternatives?

the main advantage is that it lets you decouple the generation of data 
from the use of data; instead of inlining calculations, or using a pre- 
defined operation on their result (e.g printing them or adding them to a 
container), you can simply yield them, and let the user use whatever 
mechanism she wants to process them.  i.e. instead of

     for item in range:
         calculate result
         print result

you'll write

     def generate():
         for item in range:
             yield result

and can then use

     for item in generate():
         print item

or

    list(process(s) for s in generate())

or

    sys.stdout.writelines(generate())

or

    sum(generate())

etc, without having to change the generator.

you can also do various tricks with "endless" generators, such as the 
following pi digit generator, based on an algorithm by Python's grand- 
father Lambert Meertens:

def pi():
     k, a, b, a1, b1 = 2, 4, 1, 12, 4
     while 1:
         # Next approximation
         p, q, k = k*k, 2*k+1, k+1
         a, b, a1, b1 = a1, b1, p*a+q*a1, p*b+q*b1
         # Yield common digits
         d, d1 = a/b, a1/b1
         while d == d1:
             yield str(d)
             a, a1 = 10*(a%b), 10*(a1%b1)
             d, d1 = a/b, a1/b1

import sys
sys.stdout.writelines(pi())

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