128 lines
3.8 KiB
Plaintext
128 lines
3.8 KiB
Plaintext
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PEP: 3142
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Title: Add a "while" clause to generator expressions
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Version: $Revision$
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Last-Modified: $Date$
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Author: Gerald Britton <gerald.britton@gmail.com>
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Status: Draft
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Type: Standards Track
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Content-Type: text/plain
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Created: 12-Jan-2009
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Python-Version: 3.0
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Post-History:
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Abstract
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This PEP proposes an enhancement to generator expressions, adding a
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"while" clause to complement the existing "if" clause.
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Rationale
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A generator expression (PEP 289 [1]) is a concise method to serve
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dynamically-generated objects to list comprehensions (PEP 202 [2]).
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Current generator expressions allow for an "if" clause to filter
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the objects that are returned to those meeting some set of
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criteria. However, since the "if" clause is evaluated for every
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object that may be returned, in some cases it is possible that all
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objects would be rejected after a certain point. For example:
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g = (n for n in range(100) if n*n < 50)
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which is equivalent to the using a generator function
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(PEP 255 [3]):
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def __gen(exp):
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for n in exp:
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if n*n < 50:
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yield n
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g = __gen(iter(range(10)))
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would yield 0, 1, 2, 3, 4, 5, 6 and 7, but would also consider
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the numbers from 8 to 99 and reject them all since n*n >= 50 for
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numbers in that range. Allowing for a "while" clause would allow
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the redundant tests to be short-circuited:
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g = (n for n in range(100) while n*n < 50)
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would also yield 0, 1, 2, 3, 4, 5, 6 and 7, but would stop at 8
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since the condition (n*n < 50) is no longer true. This would be
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equivalent to the generator function:
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def __gen(exp):
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for n in exp:
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if n*n < 50:
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yield n
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else:
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break
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g = __gen(iter(range(100)))
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Currently, in order to achieve the same result, one would need to
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either write a generator function such as the one above or use the
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takewhile function from itertools:
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from itertools import takewhile
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g = takewhile(lambda n: n*n < 50, range(100))
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The takewhile code achieves the same result as the proposed syntax,
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albeit in a longer (some would say "less-elegant") fashion. Also,
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the takewhile version requires an extra function call (the lambda
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in the example above) with the associated performance penalty.
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A simple test shows that:
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for n in (n for n in range(100) if 1): pass
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performs about 10% better than:
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for n in takewhile(lambda n: 1, range(100)): pass
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though they achieve similar results. (The first example uses a
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generator; takewhile is an iterator). If similarly implemented,
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a "while" clause should perform about the same as the "if" clause
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does today.
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The reader may ask if the "if" and "while" clauses should be
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mutually exclusive. There are good examples that show that there
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are times when both may be used to good advantage. For example:
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p = (p for p in primes() if p > 100 while p < 1000)
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should return prime numbers found between 100 and 1000, assuming
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I have a primes() generator that yields prime numbers.
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Adding a "while" clause to generator expressions maintains the
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compact form while adding a useful facility for short-circuiting
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the expression.
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Acknowledgements
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Raymond Hettinger first proposed the concept of generator
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expressions in January 2002.
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References
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[1] PEP 289: Generator Expressions
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http://www.python.org/dev/peps/pep-0289/
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[2] PEP 202: List Comprehensions
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http://www.python.org/dev/peps/pep-0202/
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[3] PEP 255: Simple Generators
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http://www.python.org/dev/peps/pep-0255/
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Copyright
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This document has been placed in the public domain.
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Local Variables:
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mode: indented-text
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indent-tabs-mode: nil
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sentence-end-double-space: t
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fill-column: 70
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coding: utf-8
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End:
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