Doc/whatsnew/3.1.rst

****************************
  What's New In Python 3.1
****************************

:Author: Raymond Hettinger
:Release: |release|
:Date: |today|

.. $Id$
   Rules for maintenance:

   * Anyone can add text to this document.  Do not spend very much time
   on the wording of your changes, because your text will probably
   get rewritten to some degree.

   * The maintainer will go through Misc/NEWS periodically and add
   changes; it's therefore more important to add your changes to
   Misc/NEWS than to this file.

   * This is not a complete list of every single change; completeness
   is the purpose of Misc/NEWS.  Some changes I consider too small
   or esoteric to include.  If such a change is added to the text,
   I'll just remove it.  (This is another reason you shouldn't spend
   too much time on writing your addition.)

   * If you want to draw your new text to the attention of the
   maintainer, add 'XXX' to the beginning of the paragraph or
   section.

   * It's OK to just add a fragmentary note about a change.  For
   example: "XXX Describe the transmogrify() function added to the
   socket module."  The maintainer will research the change and
   write the necessary text.

   * You can comment out your additions if you like, but it's not
   necessary (especially when a final release is some months away).

   * Credit the author of a patch or bugfix.   Just the name is
   sufficient; the e-mail address isn't necessary.

   * It's helpful to add the bug/patch number as a comment:

   % Patch 12345
   XXX Describe the transmogrify() function added to the socket
   module.
   (Contributed by P.Y. Developer.)

   This saves the maintainer the effort of going through the SVN log
   when researching a change.

This article explains the new features in Python 3.1, compared to 3.0.


PEP 372: Ordered Dictionaries
=============================

Regular Python dictionaries iterate over key/value pairs in arbitrary order.
Over the years, a number of authors have written alternative implementations
that remember the order that the keys were originally inserted.  Based on
the experiences from those implementations, a new
:class:`collections.OrderedDict` class has been introduced.

The OrderedDict API is substantially the same as regular dictionaries
but will iterate over keys and values in a guaranteed order depending on
when a key was first inserted.  If a new entry overwrites an existing entry,
the original insertion position is left unchanged.  Deleting an entry and
reinserting it will move it to the end.

The standard library now supports use of ordered dictionaries in several
modules.  The :mod:`configparser` module uses them by default.  This lets
configuration files be read, modified, and then written back in their original
order.  The *_asdict()* method for :func:`collections.namedtuple` now
returns an ordered dictionary with the values appearing in the same order as
the underlying tuple indicies.  The :mod:`json` module is being built-out with
an *object_pairs_hook* to allow OrderedDicts to be built by the decoder.
Support was also added for third-party tools like `PyYAML <http://pyyaml.org/>`_.

.. seealso::

   :pep:`372` - Ordered Dictionaries
      PEP written by Armin Ronacher and Raymond Hettinger.  Implementation
      written by Raymond Hettinger.


PEP 378: Format Specifier for Thousands Separator
=================================================

The builtin :func:`format` function and the :meth:`str.format` method use
a mini-language that now includes a simple, non-locale aware way to format
a number with a thousands separator.  That provides a way to humanize a
program's output, improving its professional appearance and readability::

    >>> format(1234567, ',d')
    '1,234,567'
    >>> format(1234567.89, ',.2f')
    '1,234,567.89'
    >>> format(12345.6 + 8901234.12j, ',f')
    '12,345.600000+8,901,234.120000j'
    >>> format(Decimal('1234567.89'), ',f')
    '1,234,567.89'

The supported types are :class:`int`, :class:`float`, :class:`complex`
and :class:`decimal.Decimal`.

Discussions are underway about how to specify alternative separators
like dots, spaces, apostrophes, or underscores.  Locale-aware applications
should use the existing *n* format specifier which already has some support
for thousands separators.

.. seealso::

   :pep:`378` - Format Specifier for Thousands Separator
      PEP written by Raymond Hettinger and implemented by Eric Smith and
      Mark Dickinson.


Other Language Changes
======================

Some smaller changes made to the core Python language are:

* The :func:`int` type gained a ``bit_length`` method that returns the
  number of bits necessary to represent its argument in binary::

      >>> n = 37
      >>> bin(37)
      '0b100101'
      >>> n.bit_length()
      6
      >>> n = 2**123-1
      >>> n.bit_length()
      123
      >>> (n+1).bit_length()
      124

  (Contributed by Fredrik Johansson, Victor Stinner, Raymond Hettinger,
  and Mark Dickinson; :issue:`3439`.)

* The fields in :func:`format` strings can now be automatically
  numbered::

    >>> 'Sir {} of {}'.format('Gallahad', 'Camelot')
    'Sir Gallahad of Camelot'

  Formerly, the string would have required numbered fields such as:
  ``'Sir {0} of {1}'``.

  (Contributed by Eric Smith; :issue:`5237`.)

* ``round(x, n)`` now returns an integer if *x* is an integer.
  Previously it returned a float::

    >>> round(1123, -2)
    1100

  (Contributed by Mark Dickinson; :issue:`4707`.)

* Python now uses David Gay's algorithm for finding the shortest floating
  point representation that doesn't change its value.  This should help
  mitigate some of the confusion surrounding binary floating point
  numbers.

  The significance is easily seen with a number like ``1.1`` which does not
  have an exact equivalent in binary floating point.  Since there is no exact
  equivalent, an expression like ``float('1.1')`` evaluates to the nearest
  representable value which is ``0x1.199999999999ap+0`` in hex or
  ``1.100000000000000088817841970012523233890533447265625`` in decimal. That
  nearest value was and still is used in subsequent floating point
  calculations.

  What is new is how the number gets displayed.  Formerly, Python used a
  simple approach.  The value of ``repr(1.1)`` was computed as ``format(1.1,
  '.17g')`` which evaluated to ``'1.1000000000000001'``. The advantage of
  using 17 digits was that it relied on IEEE-754 guarantees to assure that
  ``eval(repr(1.1))`` would round-trip exactly to its original value.  The
  disadvantage is that many people found the output to be confusing (mistaking
  intrinsic limitations of binary floating point representation as being a
  problem with Python itself).

  The new algorithm for ``repr(1.1)`` is smarter and returns ``'1.1'``.
  Effectively, it searches all equivalent string representations (ones that
  get stored with the same underlying float value) and returns the shortest
  representation.

  The new algorithm tends to emit cleaner representations when possible, but
  it does not change the underlying values.  So, it is still the case that
  ``1.1 + 2.2 != 3.3`` even though the representations may suggest otherwise.

  The new algorithm depends on certain features in the underlying floating
  point implementation.  If the required features are not found, the old
  algorithm will continue to be used.  Also, the text pickle protocols
  assure cross-platform portability by using the old algorithm.

  (Contributed by Eric Smith and Mark Dickinson; :issue:`1580`)

New, Improved, and Deprecated Modules
=====================================

* Added a :class:`collections.Counter` class to support convenient
  counting of unique items in a sequence or iterable::

      >>> Counter(['red', 'blue', 'red', 'green', 'blue', 'blue'])
      Counter({'blue': 3, 'red': 2, 'green': 1})

  (Contributed by Raymond Hettinger; :issue:`1696199`.)

* Added a new module, :mod:`tkinter.ttk` for access to the Tk themed widget set.
  The basic idea of ttk is to separate, to the extent possible, the code
  implementing a widget's behavior from the code implementing its appearance.

  (Contributed by Guilherme Polo; :issue:`2983`.)

* The :class:`gzip.GzipFile` and :class:`bz2.BZ2File` classes now support
  the context manager protocol::

        >>> # Automatically close file after writing
        >>> with gzip.GzipFile(filename, "wb") as f:
        ...     f.write(b"xxx")

  (Contributed by Antoine Pitrou.)

* The :mod:`decimal` module now supports methods for creating a
  decimal object from a binary :class:`float`.  The conversion is
  exact but can sometimes be surprising::

      >>> Decimal.from_float(1.1)
      Decimal('1.100000000000000088817841970012523233890533447265625')

  The long decimal result shows the actual binary fraction being
  stored for *1.1*.  The fraction has many digits because *1.1* cannot
  be exactly represented in binary.

  (Contributed by Raymond Hettinger and Mark Dickinson.)

* The :mod:`itertools` module grew two new functions.  The
  :func:`itertools.combinations_with_replacement` function is one of
  four for generating combinatorics including permutations and Cartesian
  products.  The :func:`itertools.compress` function mimics its namesake
  from APL.  Also, the existing :func:`itertools.count` function now has
  an optional *step* argument and can accept any type of counting
  sequence including :class:`fractions.Fraction` and
  :class:`decimal.Decimal`::

    >>> [p+q for p,q in combinations_with_replacement('LOVE', 2)]
    ['LL', 'LO', 'LV', 'LE', 'OO', 'OV', 'OE', 'VV', 'VE', 'EE']

    >>> list(compress(data=range(10), selectors=[0,0,1,1,0,1,0,1,0,0]))
    [2, 3, 5, 7]

    >>> c = count(start=Fraction(1,2), step=Fraction(1,6))
    >>> next(c), next(c), next(c), next(c)
    (Fraction(1, 2), Fraction(2, 3), Fraction(5, 6), Fraction(1, 1))

  (Contributed by Raymond Hettinger.)

* :func:`collections.namedtuple` now supports a keyword argument
  *rename* which lets invalid fieldnames be automatically converted to
  positional names in the form _0, _1, etc.  This is useful when
  the field names are being created by an external source such as a
  CSV header, SQL field list, or user input::

    >>> query = input()
    SELECT region, dept, count(*) FROM main GROUPBY region, dept

    >>> cursor.execute(query)
    >>> query_fields = [desc[0] for desc in cursor.description]
    >>> UserQuery = namedtuple('UserQuery', query_fields, rename=True)
    >>> pprint.pprint([UserQuery(*row) for row in cursor])
    [UserQuery(region='South', dept='Shipping', _2=185),
     UserQuery(region='North', dept='Accounting', _2=37),
     UserQuery(region='West', dept='Sales', _2=419)]

  (Contributed by Raymond Hettinger; :issue:`1818`.)

* The :func:`re.sub`, :func:`re.subn` and :func:`re.split` functions now
  accept a flags parameter.

  (Contributed by Gregory Smith.)

* The :mod:`logging` module now implements a simple :class:`logging.NullHandler`
  class for applications that are not using logging but are calling
  library code that does.  Setting-up a null handler will suppress
  spurious warnings such as "No handlers could be found for logger foo"::

    >>> h = logging.NullHandler()
    >>> logging.getLogger("foo").addHandler(h)

  (Contributed by Vinay Sajip; :issue:`4384`).

* The :mod:`runpy` module which supports the ``-m`` command line switch
  now supports the execution of packages by looking for and executing
  a ``__main__`` submodule when a package name is supplied.

  (Contributed by Andi Vajda; :issue:`4195`.)

* The :mod:`pdb` module can now access and display source code loaded via
  :mod:`zipimport` (or any other conformant :pep:`302` loader).

  (Contributed by Alexander Belopolsky; :issue:`4201`.)

*  :class:`functools.partial` objects can now be pickled.

  (Suggested by Antoine Pitrou and Jesse Noller.  Implemented by
  Jack Diedrich; :issue:`5228`.)

* Add :mod:`pydoc` help topics for symbols so that ``help('@')``
  works as expected in the interactive environment.

  (Contributed by David Laban; :issue:`4739`.)

* The :mod:`unittest` module now supports skipping individual tests or classes
  of tests. And it supports marking a test as a expected failure, a test that
  is known to be broken, but shouldn't be counted as a failure on a
  TestResult::

    class TestGizmo(unittest.TestCase):

        @unittest.skipUnless(sys.platform.startswith("win"), "requires Windows")
        def test_gizmo_on_windows(self):
            ...

        @unittest.expectedFailure
        def test_gimzo_without_required_library(self):
            ...

  Also, tests for exceptions have been builtout to work with context managers
  using the :keyword:`with` statement::

      def test_division_by_zero(self):
          with self.assertRaises(ZeroDivisionError):
              x / 0

  In addition, several new assertion methods were added including
  :func:`assertSetEqual`, :func:`assertDictEqual`,
  :func:`assertDictContainsSubset`, :func:`assertListEqual`,
  :func:`assertTupleEqual`, :func:`assertSequenceEqual`,
  :func:`assertRaisesRegexp`, :func:`assertIsNone`,
  and :func:`assertIsNotNone`.

  (Contributed by Benjamin Peterson and Antoine Pitrou.)

* The :mod:`io` module has three new constants for the :meth:`seek`
  method :data:`SEEK_SET`, :data:`SEEK_CUR`, and :data:`SEEK_END`.

* The :attr:`sys.version_info` tuple is now a named tuple::

    >>> sys.version_info
    sys.version_info(major=3, minor=1, micro=0, releaselevel='alpha', serial=2)

  (Contributed by Ross Light; :issue:`4285`.)

* A new module, :mod:`importlib` was added.  It provides a complete, portable,
  pure Python reference implementation of the :keyword:`import` statement and its
  counterpart, the :func:`__import__` function.  It represents a substantial
  step forward in documenting and defining the actions that take place during
  imports.

  (Contributed by Brett Cannon.)

* A new module, :mod:`ipaddr` has been added to the standard library.
  It provides classes to represent, verify and manipulate IPv4 and IPv6
  host and network addresses.

  (Contributed by Google, :issue:`3959`.)

* The :mod:`nntplib` module now supports IPv6.

  (Contributed by Derek Morr; :issue:`1664`.)

Optimizations
=============

Major performance enhancements have been added:

* The new I/O library (as defined in :pep:`3116`) was mostly written in
  Python and quickly proved to be a problematic bottleneck in Python 3.0.
  In Python 3.1, the I/O library has been entirely rewritten in C and is
  2 to 20 times faster depending on the task at hand. The pure Python
  version is still available for experimentation purposes through
  the ``_pyio`` module.

  (Contributed by Amaury Forgeot d'Arc and Antoine Pitrou.)

* Added a heuristic so that tuples and dicts containing only untrackable objects
  are not tracked by the garbage collector. This can reduce the size of
  collections and therefore the garbage collection overhead on long-running
  programs, depending on their particular use of datatypes.

  (Contributed by Antoine Pitrou, :issue:`4688`.)

* Enabling a configure option named ``--with-computed-gotos``
  on compilers that support it (notably: gcc, SunPro, icc), the bytecode
  evaluation loop is compiled with a new dispatch mechanism which gives
  speedups of up to 20%, depending on the system, the compiler, and
  the benchmark.

  (Contributed by Antoine Pitrou along with a number of other participants,
  :issue:`4753`).

* The decoding of UTF-8, UTF-16 and LATIN-1 is now two to four times
  faster.

  (Contributed by Antoine Pitrou and Amaury Forgeot d'Arc, :issue:`4868`.)

* The :mod:`json` module is getting a C extension to substantially improve
  its performance.  In addition, the API was modified so that json works
  only with :class:`str`, not with :class:`bytes`.  That change makes the
  module more closely conform to the `JSON specification <http://json.org/>`_
  which is defined in terms of Unicode.
  (Contributed by Bob Ippolito and converted to Py3.1 by Antoine Pitrou
  and Benjamin Peterson; :issue:`4136`.)

* Unpickling now interns the attribute names of pickled objects.  This saves
  memory and allows pickles to be smaller.
  (Contributed by Jake McGuire and Antoine Pitrou; :issue:`5084`.)

Build and C API Changes
=======================

Changes to Python's build process and to the C API include:

* Integers are now stored internally either in base 2**15 or in base
  2**30, the base being determined at build time.  Previously, they
  were always stored in base 2**15.  Using base 2**30 gives
  significant performance improvements on 64-bit machines, but
  benchmark results on 32-bit machines have been mixed.  Therefore,
  the default is to use base 2**30 on 64-bit machines and base 2**15
  on 32-bit machines; on Unix, there's a new configure option
  ``--enable-big-digits`` that can be used to override this default.

  Apart from the performance improvements this change should be invisible to
  end users, with one exception: for testing and debugging purposes there's a
  new :attr:`sys.int_info` that provides information about the
  internal format, giving the number of bits per digit and the size in bytes
  of the C type used to store each digit::

     >>> import sys
     >>> sys.int_info
     sys.int_info(bits_per_digit=30, sizeof_digit=4)

  (Contributed by Mark Dickinson; :issue:`4258`.)

* The :cfunc:`PyLong_AsUnsignedLongLong()` function now handles a negative
  *pylong* by raising :exc:`OverflowError` instead of :exc:`TypeError`.

  (Contributed by Mark Dickinson and Lisandro Dalcrin; :issue:`5175`.)

* Deprecated :cfunc:`PyNumber_Int`.  Use :cfunc:`PyNumber_Long` instead.

  (Contributed by Mark Dickinson; :issue:`4910`.)

* Added :ctype:`PyCapsule` as a replacement for the :ctype:`PyCObject` API.
  The principal difference is that the new type has a well defined interface
  for passing typing safety information and a less complicated signature
  for calling a destructor.

  The old type had a problematic API and is now deprecated.  To ease
  transitioning code, the new type was implemented as a subtype of
  :ctype:`PyCObject` API.

  (Contributed by Larry Hastings; :issue:`5630`.)

Porting to Python 3.1
=====================

This section lists previously described changes and other bugfixes
that may require changes to your code:

* The new floating point string representations can break existing doctests.
  For example::

    def e():
        '''Compute the base of natural logarithms.

        >>> e()
        2.7182818284590451

        '''
        return sum(1/math.factorial(x) for x in reversed(range(30)))

    doctest.testmod()

    **********************************************************************
    Failed example:
        e()
    Expected:
        2.7182818284590451
    Got:
        2.718281828459045
    **********************************************************************