python-peps/pep-0290.txt

PEP: 290
Title: Code Migration and Modernization
Version: $Revision$
Last-Modified: $Date$
Author: Raymond D. Hettinger <python@rcn.com>
Status: Active
Type: Informational
Content-Type: text/x-rst
Created: 6-Jun-2002
Post-History:


Abstract
========

This PEP is a collection of procedures and ideas for updating Python
applications when newer versions of Python are installed.

The migration tips highlight possible areas of incompatibility and
make suggestions on how to find and resolve those differences.  The
modernization procedures show how older code can be updated to take
advantage of new language features.


Rationale
=========

This repository of procedures serves as a catalog or checklist of
known migration issues and procedures for addressing those issues.

Migration issues can arise for several reasons.  Some obsolete
features are slowly deprecated according to the guidelines in PEP 4
[1]_.  Also, some code relies on undocumented behaviors which are
subject to change between versions.  Some code may rely on behavior
which was subsequently shown to be a bug and that behavior changes
when the bug is fixed.

Modernization options arise when new versions of Python add features
that allow improved clarity or higher performance than previously
available.


Guidelines for New Entries
==========================

Developers with commit access may update this PEP directly.  Others
can send their ideas to a developer for possible inclusion.

While a consistent format makes the repository easier to use, feel
free to add or subtract sections to improve clarity.

Grep patterns may be supplied as tool to help maintainers locate code
for possible updates.  However, fully automated search/replace style
regular expressions are not recommended.  Instead, each code fragment
should be evaluated individually.

The contra-indications section is the most important part of a new
entry.  It lists known situations where the update SHOULD NOT be
applied.


Modernization Procedures
========================

Procedures are grouped by the Python version required to be able to
take advantage of the modernization.


Python 2.3 or Later
-------------------

Testing String Membership
'''''''''''''''''''''''''

In Python 2.3, for ``string2 in string1``, the length restriction on
``string2`` is lifted; it can now be a string of any length.  When
searching for a substring, where you don't care about the position of
the substring in the original string, using the ``in`` operator makes
the meaning clear.

Pattern::

    string1.find(string2) >= 0   -->  string2 in string1
    string1.find(string2) != -1  -->  string2 in string1


Python 2.2 or Later
-------------------

Testing Dictionary Membership
'''''''''''''''''''''''''''''

For testing dictionary membership, use the 'in' keyword instead of the
'has_key()' method.  The result is shorter and more readable.  The
style becomes consistent with tests for membership in lists.  The
result is slightly faster because ``has_key`` requires an attribute
search and uses a relatively expensive function call.

Pattern::

    if d.has_key(k):  -->  if k in d:

Contra-indications:

1. Some dictionary-like objects like ``shelve`` do not define a
   ``__contains__()`` method::

       if dictlike.has_key(k)

Locating: ``grep has_key``


Looping Over Dictionaries
'''''''''''''''''''''''''

Use the new ``iter`` methods for looping over dictionaries.  The
``iter`` methods are faster because they do not have to create a new
list object with a complete copy of all of the keys, values, or items.
Selecting only keys, values, or items (key/value pairs) as needed
saves the time for creating throwaway object references and, in the
case of items, saves a second hash look-up of the key.

Pattern::

    for key in d.keys():      -->  for key in d:
    for value in d.values():  -->  for value in d.itervalues():
    for key, value in d.items():
                              -->  for key, value in d.iteritems():

Contra-indications:

1. If you need a list, do not change the return type::

       def getids():  return d.keys()

2. Some dictionary-like objects like ``shelve`` do not define
   ``iter`` methods::

       for k in dictlike.keys():

3. Iterators do not support slicing, sorting or other operations::

       k = d.keys(); j = k[:]

4. Dictionary iterators prohibit modifying the dictionary::

       for k in d.keys(): del[k]


``stat`` Methods
''''''''''''''''

Replace ``stat`` constants or indices with new ``os.stat`` attributes
and methods.  The ``os.stat`` attributes and methods are not
order-dependent and do not require an import of the ``stat`` module.

Pattern::

    os.stat("foo")[stat.ST_MTIME]  -->  os.stat("foo").st_mtime
    os.stat("foo")[stat.ST_MTIME]  -->  os.path.getmtime("foo")

Locating: ``grep os.stat`` or ``grep stat.S``


Reduce Dependency on ``types`` Module
'''''''''''''''''''''''''''''''''''''

The ``types`` module is likely to be deprecated in the future.  Use
built-in constructor functions instead.  They may be slightly faster.

Pattern::

    isinstance(v, types.IntType)      -->  isinstance(v, int)
    isinstance(s, types.StringTypes)  -->  isinstance(s, basestring)

Full use of this technique requires Python 2.3 or later
(``basestring`` was introduced in Python 2.3), but Python 2.2 is
sufficient for most uses.

Locating: ``grep types *.py | grep import``


Python 2.1 or Later
-------------------

``whrandom`` Module Deprecated
''''''''''''''''''''''''''''''

All random-related methods have been collected in one place, the
``random`` module.

Pattern::

    import whrandom --> import random

Locating: ``grep whrandom``


Python 2.0 or Later
-------------------

String Methods
''''''''''''''

The string module is likely to be deprecated in the future.  Use
string methods instead.  They're faster too.

Pattern::

    import string ; string.method(s, ...)  -->  s.method(...)
    c in string.whitespace                 -->  c.isspace()

Locating: ``grep string *.py | grep import``


``startswith`` and ``endswith`` String Methods
''''''''''''''''''''''''''''''''''''''''''''''

Use these string methods instead of slicing.  They're faster because
no slice has to be created, and there's no risk of miscounting.

Pattern::

    "foobar"[:3] == "foo"   -->  "foobar".startswith("foo")
    "foobar"[-3:] == "bar"  -->  "foobar".endswith("bar")


Python 1.5 or Later
-------------------

Class-Based Exceptions
''''''''''''''''''''''

String exceptions are deprecated, so derive from the ``Exception``
base class.  Unlike the obsolete string exceptions, class exceptions
all derive from another exception or the ``Exception`` base class.
This allows meaningful groupings of exceptions.  It also allows an
"``except Exception``" clause to catch all exceptions.

Pattern::

    NewError = 'NewError'  -->  class NewError(Exception): pass

Locating: Use PyChecker_.


All Python Versions
-------------------

Testing for ``None``
''''''''''''''''''''

Since there is only one ``None`` object, equality can be tested with
identity.  Identity tests are slightly faster than equality tests.
Also, some object types may overload comparison, so equality testing
may be much slower.

Pattern::

    if v == None  -->  if v is None:
    if v != None  -->  if v is not None:

Locating: ``grep '== None'`` or ``grep '!= None'``


References
==========

.. [1] PEP 4, Deprecation of Standard Modules, von Loewis
   (http://www.python.org/peps/pep-0004.html)

.. _PyChecker: http://pychecker.sourceforge.net/


Copyright
=========

This document has been placed in the public domain.



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