[Python-checkins] CVS: python/nondist/peps pep-0274.txt,NONE,1.1

2001年10月25日 13:28:07 -0700

Update of /cvsroot/python/python/nondist/peps
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	pep-0274.txt 
Log Message:
PEP 274, Dict Comprehensions, Warsaw
--- NEW FILE: pep-0274.txt ---
PEP: 274
Title: Dict Comprehensions
Version: $Revision: 1.1 $
Last-Modified: $Date: 2001年10月25日 20:28:05 $
Author: barry@zope.com (Barry A. Warsaw)
Status: Draft
Type: Standards Track
Created: 25-Oct-2001
Python-Version: 2.3
Post-History:
Abstract
 PEP 202 introduces a syntactical extension to Python called the
 "list comprehension"[1]. This PEP proposes a similar syntactical
 extension called the "dictionary comprehension" or "dict
 comprehension" for short. You can use dict comprehensions in ways
 very similar to list comprehensions, except that they produce
 Python dictionary objects instead of list objects.
Proposed Solution
 Dict comprehensions are just like list comprehensions, except that
 you group the expression using curly braces instead of square
 braces. Also, the left part before the `for' keyword expresses
 both a key and a value, separated by a colon. (There is an
 optional part of this PEP that allows you to use a shortcut to
 express just the value.) The notation is specifically designed to
 remind you of list comprehensions as applied to dictionaries.
Rationale
 There are times when you have some data arranged as a sequences of
 length-2 sequences, and you want to turn that into a dictionary.
 In Python 2.2, the dictionary() constructor will take an optional
 keyword argument that indicates specifically to interpret a
 sequences of length-2 sequences as key/value pairs, and turn them
 into a dictionary.
 However, the act of turning some data into a sequence of length-2
 sequences can be inconvenient or inefficient from a memory or
 performance standpoint. Also, for some common operations, such as
 turning a list of things into a set of things for quick duplicate
 removal or set inclusion tests, a better syntax can help code
 clarity.
 As with list comprehensions, an explicit for loop can always be
 used (and in fact was the only way to do it in earlier versions of
 Python). But as with list comprehensions, dict comprehensions can
 provide a more syntactically succinct idiom that the traditional
 for loop.
Examples
 >>> print {i : chr(65+i) for i in range(4)}
 {0 : 'A', 1 : 'B', 2 : 'C', 3 : 'D'}
 >>> print {k : v for k, v in someDict.items()} == someDict.copy()
 1
 >>> print {x.lower() : 1 for x in list_of_email_addrs}
 {'barry@zope.com' : 1, 'barry@python.org' : 1, 'guido@python.org' : 1}
 >>> def invert(d):
 ... return {v : k for k, v in d}
 ...
 >>> d = {0 : 'A', 1 : 'B', 2 : 'C', 3 : 'D'}
 >>> print invert(d)
 {'A' : 0, 'B' : 1, 'C' : 2, 'D' : 4}
 >>> print {k, v for k in range(4) for v in range(-4, 0, 1)}
 {0 : -4, 1 : -3, 2 : -2, 3 : -1}
Optional Enhancements
 There is one further shortcut we could adopt. Suppose we wanted
 to create a set of items, such as in the "list_of_email_addrs"
 example above. Here, we're simply taking the target of the for
 loop and turning that into the key for the dict comprehension.
 The assertion is that this would be a common idiom, so the
 shortcut below allows for an easy spelling of it, by allow us to
 omit the "key :" part of the left hand clause:
 >>> print {1 for x in list_of_email_addrs}
 {'barry@zope.com' : 1, 'barry@python.org' : 1, 'guido@python.org' : 1}
 Or say we wanted to map email addresses to the MX record handling
 their mail:
 >>> print {mx_for_addr(x) for x in list_of_email_addrs}
 {'barry@zope.com' : 'mail.zope.com',
 'barry@python.org' : 'mail.python.org,
 'guido@python.org' : 'mail.python.org,
 }
References
 [1] PEP 202, List Comprehensions
 http://www.python.org/peps/pep-0202.html
Copyright
 This document has been placed in the public domain.

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