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Kirill Smelkov
cpython
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b9b281b7
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b9b281b7
authored
Mar 06, 2012
by
Nick Coghlan
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Add some simple examples to the PEP 380 section of What's New
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Doc/whatsnew/3.3.rst
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b9b281b7
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@@ -262,9 +262,56 @@ part of its operations to another generator. This allows a section of code
containing 'yield' to be factored out and placed in another generator.
Additionally, the subgenerator is allowed to return with a value, and the
value is made available to the delegating generator.
While designed primarily for use in delegating to a subgenerator, the ``yield
from`` expression actually allows delegation to arbitrary subiterators.
For simple iterators, ``yield from iterable`` is essentially just a shortened
form of ``for item in iterable: yield item``::
>>> def g(x):
... yield from range(x, 0, -1)
... yield from range(x)
...
>>> list(g(5))
[5, 4, 3, 2, 1, 0, 1, 2, 3, 4]
However, unlike an ordinary loop, ``yield from`` allows subgenerators to
receive sent and thrown values directly from the calling scope, and
return a final value to the outer generator::
>>> def accumulate(start=0):
... tally = start
... while 1:
... next = yield
... if next is None:
... return tally
... tally += next
...
>>> def gather_tallies(tallies, start=0):
... while 1:
... tally = yield from accumulate()
... tallies.append(tally)
...
>>> tallies = []
>>> acc = gather_tallies(tallies)
>>> next(acc) # Ensure the accumulator is ready to accept values
>>> for i in range(10):
... acc.send(i)
...
>>> acc.send(None) # Finish the first tally
>>> for i in range(5):
... acc.send(i)
...
>>> acc.send(None) # Finish the second tally
>>> tallies
[45, 10]
The main principle driving this change is to allow even generators that are
designed to be used with the ``send`` and ``throw`` methods to be split into
multiple subgenerators as easily as a single large function can be split into
multiple subfunctions.
(Implementation by Greg Ewing, integrated into 3.3 by Renaud Blanch, Ryan
Kelly and Nick Coghlan, documentation by Zbigniew Jędrzejewski-Szmek and
Nick Coghlan)
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