[Python-Dev] PEP 3142: Add a "while" clause to generator expressions

[Gerald Britton]

Thanks Calvin,

Could you please expand on your thoughts about possible confusion?
That is, how do you see a programmer becoming confused if this option
were added to the syntax.

On Mon, Jan 19, 2009 at 11:29 AM, Calvin Spealman <ironfroggy at gmail.com> wrote:
> I am really unconvinced of the utility of this proposal and quite
> convinced of the confusing factor it may well add to the current
> syntax. I would like to see more applicable examples. It would replace
> uses of takewhile, but that isn't a really often used function. So, is
> there any evidence to support that making this a new syntax would find
> so many more uses of the construct to be worth it? I believe not.
>
> On Mon, Jan 19, 2009 at 10:10 AM, Gerald Britton
> <gerald.britton at gmail.com> wrote:
>> Please find below PEP 3142: Add a "while" clause to generator
>> expressions.  I'm looking for feedback and discussion.
>>
>>
>> PEP: 3142
>> Title: Add a "while" clause to generator expressions
>> Version: $Revision: 68715 $
>> Last-Modified: $Date: 2009-01-18 11:28:20 +0100 (So, 18. Jan 2009) $
>> Author: Gerald Britton <gerald.britton at gmail.com>
>> Status: Draft
>> Type: Standards Track
>> Content-Type: text/plain
>> Created: 12-Jan-2009
>> Python-Version: 3.0
>> Post-History:
>>
>>
>> Abstract
>>
>>  This PEP proposes an enhancement to generator expressions, adding a
>>  "while" clause to complement the existing "if" clause.
>>
>>
>> Rationale
>>
>>  A generator expression (PEP 289 [1]) is a concise method to serve
>>  dynamically-generated objects to list comprehensions (PEP 202 [2]).
>>  Current generator expressions allow for an "if" clause to filter
>>  the objects that are returned to those meeting some set of
>>  criteria.  However, since the "if" clause is evaluated for every
>>  object that may be returned, in some cases it is possible that all
>>  objects would be rejected after a certain point.  For example:
>>
>>      g = (n for n in range(100) if n*n < 50)
>>
>>  which is equivalent to the using a generator function
>>  (PEP 255 [3]):
>>
>>      def __gen(exp):
>>          for n in exp:
>>              if n*n < 50:
>>                  yield n
>>      g = __gen(iter(range(10)))
>>
>>  would yield 0, 1, 2, 3, 4, 5, 6 and 7, but would also consider
>>  the numbers from 8 to 99 and reject them all since n*n >= 50 for
>>  numbers in that range.  Allowing for a "while" clause would allow
>>  the redundant tests to be short-circuited:
>>
>>      g = (n for n in range(100) while n*n < 50)
>>
>>  would also yield 0, 1, 2, 3, 4, 5, 6 and 7, but would stop at 8
>>  since the condition (n*n < 50) is no longer true.  This would be
>>  equivalent to the generator function:
>>
>>      def __gen(exp):
>>          for n in exp:
>>              if n*n < 50:
>>                  yield n
>>              else:
>>                  break
>>      g = __gen(iter(range(100)))
>>
>>  Currently, in order to achieve the same result, one would need to
>>  either write a generator function such as the one above or use the
>>  takewhile function from itertools:
>>
>>      from itertools import takewhile
>>      g = takewhile(lambda n: n*n < 50, range(100))
>>
>>  The takewhile code achieves the same result as the proposed syntax,
>>  albeit in a longer (some would say "less-elegant") fashion.  Also,
>>  the takewhile version requires an extra function call (the lambda
>>  in the example above) with the associated performance penalty.
>>  A simple test shows that:
>>
>>      for n in (n for n in range(100) if 1): pass
>>
>>  performs about 10% better than:
>>
>>      for n in takewhile(lambda n: 1, range(100)): pass
>>
>>  though they achieve similar results.  (The first example uses a
>>  generator; takewhile is an iterator).  If similarly implemented,
>>  a "while" clause should perform about the same as the "if" clause
>>  does today.
>>
>>  The reader may ask if the "if" and "while" clauses should be
>>  mutually exclusive.  There are good examples that show that there
>>  are times when both may be used to good advantage. For example:
>>
>>      p = (p for p in primes() if p > 100 while p < 1000)
>>
>>  should return prime numbers found between 100 and 1000, assuming
>>  I have a primes() generator that yields prime numbers.  Of course, this
>>  could also be achieved like this:
>>
>>      p = (p for p in (p for p in primes() if p > 100) while p < 1000)
>>
>>  which is syntactically simpler.  Some may also ask if it is possible
>>  to cover dropwhile() functionality in a similar way.  I initially thought
>>  of:
>>
>>      p = (p for p in primes() not while p < 100)
>>
>>  but I am not sure that I like it since it uses "not" in a non-pythonic
>>  fashion, I think.
>>
>>  Adding a "while" clause to generator expressions maintains the
>>  compact form while adding a useful facility for short-circuiting
>>  the expression.
>>
>> Implementation:
>>
>>  I am willing to assist in the implementation of this feature, although I have
>>  not contributed to Python thus far and would definitely need mentoring. (At
>>  this point I am not quite sure where to begin.)  Presently though, I would
>>  find it challenging to fit this work into my existing workload.
>>
>>
>> Acknowledgements
>>
>>  Raymond Hettinger first proposed the concept of generator
>>  expressions in January 2002.
>>
>>
>> References
>>
>>  [1] PEP 289: Generator Expressions
>>      http://www.python.org/dev/peps/pep-0289/
>>
>>  [2] PEP 202: List Comprehensions
>>      http://www.python.org/dev/peps/pep-0202/
>>
>>  [3] PEP 255: Simple Generators
>>      http://www.python.org/dev/peps/pep-0255/
>>
>>
>> Copyright
>>
>>  This document has been placed in the public domain.
>>
>>
>> Local Variables:
>> mode: indented-text
>> indent-tabs-mode: nil
>> sentence-end-double-space: t
>> fill-column: 70
>> coding: utf-8
>> End:
>>
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>
>
>
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