PEP: 274
Title: Dict Comprehensions
Version: $Revision: 2059 $
Last-Modified: $Date: 2005-06-16 19:13:11 -0700 (Thu, 16 Jun 2005) $
Author: barry@python.org (Barry A. Warsaw)
Status: Withdrawn
Type: Standards Track
Created: 25-Oct-2001
Python-Version: 2.3
Post-History: 29-Oct-2001


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.

Resolution

    This PEP is withdrawn.  Substantially all of its benefits were
    subsumed by generator expressions coupled with the dict() constructor.


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 dict() constructor accepts an argument that is
    a sequence of length-2 sequences, used as (key, value) pairs to
    initialize a new dictionary object.

    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.


Semantics

    The semantics of dict comprehensions can actually be demonstrated
    in stock Python 2.2, by passing a list comprehension to the
    builtin dictionary constructor:

    >>> dict([(i, chr(65+i)) for i in range(4)])

    is semantically equivalent to

    >>> {i : chr(65+i) for i in range(4)}

    The dictionary constructor approach has two dictinct disadvantages
    from the proposed syntax though.  First, it isn't as legible as a
    dict comprehension.  Second, it forces the programmer to create an
    in-core list object first, which could be expensive.


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.iteritems()} == 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.iteritems()}
    ...
    >>> d = {0 : 'A', 1 : 'B', 2 : 'C', 3 : 'D'}
    >>> print invert(d)
    {'A' : 0, 'B' : 1, 'C' : 2, 'D' : 3}

    >>> {(k, v): k+v for k in range(4) for v in range(4)}
    ... {(3, 3): 6, (3, 2): 5, (3, 1): 4, (0, 1): 1, (2, 1): 3,
         (0, 2): 2, (3, 0): 3, (0, 3): 3, (1, 1): 2, (1, 0): 1,
         (0, 0): 0, (1, 2): 3, (2, 0): 2, (1, 3): 4, (2, 2): 4, (
         2, 3): 5}


Open Issues

    - 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,
       }

      Questions: what about nested loops?  Where does the key come
      from?  The shortcut probably doesn't save much typing, and comes
      at the expense of legibility, so it's of dubious value.


Implementation

    TBD


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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