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| Author: | Raymond Hettinger |
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This article explains the new features in Python 3.2 as compared to 3.1. It focuses on a few highlights and gives a few examples. For full details, see the Misc/NEWS file.
See also
PEP 392 - Python 3.2 Release Schedule
In the past, extension modules built for one Python version were often not usable with other Python versions. Particularly on Windows, every feature release of Python required rebuilding all extension modules that one wanted to use. This requirement was the result of the free access to Python interpreter internals that extension modules could use.
With Python 3.2, an alternative approach becomes available: extension modules which restrict themselves to a limited API (by defining Py_LIMITED_API) cannot use many of the internals, but are constrained to a set of API functions that are promised to be stable for several releases. As a consequence, extension modules built for 3.2 in that mode will also work with 3.3, 3.4, and so on. Extension modules that make use of details of memory structures can still be built, but will need to be recompiled for every feature release.
See also
A new module for command line parsing, argparse, was introduced to
overcome the limitations of optparse which did not provide support for
positional arguments (not just options), subcommands, required options and other
common patterns of specifying and validating options.
This module has already had widespread success in the community as a
third-party module. Being more fully featured than its predecessor, the
argparse module is now the preferred module for command-line processing.
The older module is still being kept available because of the substantial amount
of legacy code that depends on it.
Here’s an annotated example parser showing features like limiting results to a set of choices, specifying a metavar in the help screen, validating that one or more positional arguments is present, and making a required option:
import argparse
parser = argparse.ArgumentParser(
description = 'Manage servers', # main description for help
epilog = 'Tested on Solaris and Linux') # displayed after help
parser.add_argument('action', # argument name
choices = ['deploy', 'start', 'stop'], # three allowed values
help = 'action on each target') # help msg
parser.add_argument('targets',
metavar = 'HOSTNAME', # var name used in help msg
nargs = '+', # require one or more targets
help = 'url for target machines') # help msg explanation
parser.add_argument('-u', '--user', # -u or --user option
required = True, # make it a required argument
help = 'login as user')
Example of calling the parser on a command string:
>>> cmd = 'deploy sneezy.example.com sleepy.example.com -u skycaptain'
>>> result = parser.parse_args(cmd.split())
>>> result.action
'deploy'
>>> result.targets
['sneezy.example.com', 'sleepy.example.com']
>>> result.user
'skycaptain'
Example of the parser’s automatically generated help:
>>> parser.parse_args('-h'.split())
usage: manage_cloud.py [-h] -u USER
{deploy,start,stop} HOSTNAME [HOSTNAME ...]
Manage servers
positional arguments:
{deploy,start,stop} action on each target
HOSTNAME url for target machines
optional arguments:
-h, --help show this help message and exit
-u USER, --user USER login as user
Tested on Solaris and Linux
An especially nice argparse feature is the ability to define subparsers,
each with their own argument patterns and help displays:
import argparse
parser = argparse.ArgumentParser(prog='HELM')
subparsers = parser.add_subparsers()
parser_l = subparsers.add_parser('launch', help='Launch Control') # first subgroup
parser_l.add_argument('-m', '--missiles', action='store_true')
parser_l.add_argument('-t', '--torpedos', action='store_true')
parser_m = subparsers.add_parser('move', help='Move Vessel', # second subgroup
aliases=('steer', 'turn')) # equivalent names
parser_m.add_argument('-c', '--course', type=int, required=True)
parser_m.add_argument('-s', '--speed', type=int, default=0)
$ ./helm.py --help # top level help (launch and move)
$ ./helm.py launch --help # help for launch options
$ ./helm.py launch --missiles # set missiles=True and torpedos=False
$ ./helm.py steer --course 180 --speed 5 # set movement parameters
See also
Upgrading optparse code for details on the differences from optparse.
The logging module provided two kinds of configuration, one style with
function calls for each option or another style driven by an external file saved
in a ConfigParser format. Those options did not provide the flexibility
to create configurations from JSON or YAML files, nor did they support
incremental configuration, which is needed for specifying logger options from a
command line.
To support a more flexible style, the module now offers
logging.config.dictConfig() for specifying logging configuration with
plain Python dictionaries. The configuration options include formatters,
handlers, filters, and loggers. Here’s a working example of a configuration
dictionary:
{"version": 1,
"formatters": {"brief": {"format": "%(levelname)-8s: %(name)-15s: %(message)s"},
"full": {"format": "%(asctime)s %(name)-15s %(levelname)-8s %(message)s"}
},
"handlers": {"console": {
"class": "logging.StreamHandler",
"formatter": "brief",
"level": "INFO",
"stream": "ext://sys.stdout"},
"console_priority": {
"class": "logging.StreamHandler",
"formatter": "full",
"level": "ERROR",
"stream": "ext://sys.stderr"}
},
"root": {"level": "DEBUG", "handlers": ["console", "console_priority"]}}
If that dictionary is stored in a file called conf.json, it can be
loaded and called with code like this:
>>> import json, logging.config
>>> with open('conf.json') as f:
... conf = json.load(f)
...
>>> logging.config.dictConfig(conf)
>>> logging.info("Transaction completed normally")
INFO : root : Transaction completed normally
>>> logging.critical("Abnormal termination")
2011-02-17 11:14:36,694 root CRITICAL Abnormal termination
See also
concurrent.futures module¶Code for creating and managing concurrency is being collected in a new top-level namespace, concurrent. Its first member is a futures package which provides a uniform high-level interface for managing threads and processes.
The design for concurrent.futures was inspired by the
java.util.concurrent package. In that model, a running call and its result
are represented by a Future object that abstracts
features common to threads, processes, and remote procedure calls. That object
supports status checks (running or done), timeouts, cancellations, adding
callbacks, and access to results or exceptions.
The primary offering of the new module is a pair of executor classes for launching and managing calls. The goal of the executors is to make it easier to use existing tools for making parallel calls. They save the effort needed to setup a pool of resources, launch the calls, create a results queue, add time-out handling, and limit the total number of threads, processes, or remote procedure calls.
Ideally, each application should share a single executor across multiple components so that process and thread limits can be centrally managed. This solves the design challenge that arises when each component has its own competing strategy for resource management.
Both classes share a common interface with three methods:
submit() for scheduling a callable and
returning a Future object;
map() for scheduling many asynchronous calls
at a time, and shutdown() for freeing
resources. The class is a context manager and can be used in a
with statement to assure that resources are automatically released
when currently pending futures are done executing.
A simple of example of ThreadPoolExecutor is a
launch of four parallel threads for copying files:
import concurrent.futures, shutil
with concurrent.futures.ThreadPoolExecutor(max_workers=4) as e:
e.submit(shutil.copy, 'src1.txt', 'dest1.txt')
e.submit(shutil.copy, 'src2.txt', 'dest2.txt')
e.submit(shutil.copy, 'src3.txt', 'dest3.txt')
e.submit(shutil.copy, 'src3.txt', 'dest4.txt')
See also
Code for Threaded Parallel URL reads, an example using threads to fetch multiple web pages in parallel.
Code for computing prime numbers in
parallel, an example demonstrating
ProcessPoolExecutor.
Python’s scheme for caching bytecode in .pyc files did not work well in environments with multiple Python interpreters. If one interpreter encountered a cached file created by another interpreter, it would recompile the source and overwrite the cached file, thus losing the benefits of caching.
The issue of “pyc fights” has become more pronounced as it has become commonplace for Linux distributions to ship with multiple versions of Python. These conflicts also arise with CPython alternatives such as Unladen Swallow.
To solve this problem, Python’s import machinery has been extended to use distinct filenames for each interpreter. Instead of Python 3.2 and Python 3.3 and Unladen Swallow each competing for a file called “mymodule.pyc”, they will now look for “mymodule.cpython-32.pyc”, “mymodule.cpython-33.pyc”, and “mymodule.unladen10.pyc”. And to prevent all of these new files from cluttering source directories, the pyc files are now collected in a “__pycache__” directory stored under the package directory.
Aside from the filenames and target directories, the new scheme has a few aspects that are visible to the programmer:
Imported modules now have a __cached__ attribute which stores the name
of the actual file that was imported:
>>> import collections
>>> collections.__cached__
'c:/py32/lib/__pycache__/collections.cpython-32.pyc'
The tag that is unique to each interpreter is accessible from the imp
module:
>>> import imp
>>> imp.get_tag()
'cpython-32'
Scripts that try to deduce source filename from the imported file now need to
be smarter. It is no longer sufficient to simply strip the “c” from a ”.pyc”
filename. Instead, use the new functions in the imp module:
>>> imp.source_from_cache('c:/py32/lib/__pycache__/collections.cpython-32.pyc')
'c:/py32/lib/collections.py'
>>> imp.cache_from_source('c:/py32/lib/collections.py')
'c:/py32/lib/__pycache__/collections.cpython-32.pyc'
The py_compile and compileall modules have been updated to
reflect the new naming convention and target directory. The command-line
invocation of compileall has new options: -i for
specifying a list of files and directories to compile and -b which causes
bytecode files to be written to their legacy location rather than
__pycache__.
The importlib.abc module has been updated with new abstract base
classes for loading bytecode files. The obsolete
ABCs, PyLoader and
PyPycLoader, have been deprecated (instructions on how
to stay Python 3.1 compatible are included with the documentation).
See also
The PYC repository directory allows multiple bytecode cache files to be co-located. This PEP implements a similar mechanism for shared object files by giving them a common directory and distinct names for each version.
The common directory is “pyshared” and the file names are made distinct by identifying the Python implementation (such as CPython, PyPy, Jython, etc.), the major and minor version numbers, and optional build flags (such as “d” for debug, “m” for pymalloc, “u” for wide-unicode). For an arbitrary package “foo”, you may see these files when the distribution package is installed:
/usr/share/pyshared/foo.cpython-32m.so
/usr/share/pyshared/foo.cpython-33md.so
In Python itself, the tags are accessible from functions in the sysconfig
module:
>>> import sysconfig
>>> sysconfig.get_config_var('SOABI') # find the version tag
'cpython-32mu'
>>> sysconfig.get_config_var('EXT_SUFFIX') # find the full filename extension
'.cpython-32mu.so'
See also
This informational PEP clarifies how bytes/text issues are to be handled by the
WSGI protocol. The challenge is that string handling in Python 3 is most
conveniently handled with the str type even though the HTTP protocol
is itself bytes oriented.
The PEP differentiates so-called native strings that are used for request/response headers and metadata versus byte strings which are used for the bodies of requests and responses.
The native strings are always of type str but are restricted to code
points between U+0000 through U+00FF which are translatable to bytes using
Latin-1 encoding. These strings are used for the keys and values in the
environment dictionary and for response headers and statuses in the
start_response() function. They must follow RFC 2616 with respect to
encoding. That is, they must either be ISO-8859-1 characters or use
RFC 2047 MIME encoding.
For developers porting WSGI applications from Python 2, here are the salient points:
h.encode('utf-8') now needs to convert from
bytes to native strings using h.encode('utf-8').decode('latin-1').write() method
must be byte strings. The start_response() function and environ
must use native strings. The two cannot be mixed.For server implementers writing CGI-to-WSGI pathways or other CGI-style
protocols, the users must to be able access the environment using native strings
even though the underlying platform may have a different convention. To bridge
this gap, the wsgiref module has a new function,
wsgiref.handlers.read_environ() for transcoding CGI variables from
os.environ into native strings and returning a new dictionary.
See also
Some smaller changes made to the core Python language are:
String formatting for format() and str.format() gained new
capabilities for the format character #. Previously, for integers in
binary, octal, or hexadecimal, it caused the output to be prefixed with ‘0b’,
‘0o’, or ‘0x’ respectively. Now it can also handle floats, complex, and
Decimal, causing the output to always have a decimal point even when no digits
follow it.
>>> format(20, '#o')
'0o24'
>>> format(12.34, '#5.0f')
' 12.'
(Suggested by Mark Dickinson and implemented by Eric Smith in bpo-7094.)
There is also a new str.format_map() method that extends the
capabilities of the existing str.format() method by accepting arbitrary
mapping objects. This new method makes it possible to use string
formatting with any of Python’s many dictionary-like objects such as
defaultdict, Shelf,
ConfigParser, or dbm. It is also useful with
custom dict subclasses that normalize keys before look-up or that
supply a __missing__() method for unknown keys:
>>> import shelve
>>> d = shelve.open('tmp.shl')
>>> 'The {project_name} status is {status} as of {date}'.format_map(d)
'The testing project status is green as of February 15, 2011'
>>> class LowerCasedDict(dict):
... def __getitem__(self, key):
... return dict.__getitem__(self, key.lower())
>>> lcd = LowerCasedDict(part='widgets', quantity=10)
>>> 'There are {QUANTITY} {Part} in stock'.format_map(lcd)
'There are 10 widgets in stock'
>>> class PlaceholderDict(dict):
... def __missing__(self, key):
... return '<{}>'.format(key)
>>> 'Hello {name}, welcome to {location}'.format_map(PlaceholderDict())
'Hello <name>, welcome to <location>'
(Suggested by Raymond Hettinger and implemented by Eric Smith in bpo-6081.)
The interpreter can now be started with a quiet option, -q, to prevent
the copyright and version information from being displayed in the interactive
mode. The option can be introspected using the sys.flags attribute:
$ python -q
>>> sys.flags
sys.flags(debug=0, division_warning=0, inspect=0, interactive=0,
optimize=0, dont_write_bytecode=0, no_user_site=0, no_site=0,
ignore_environment=0, verbose=0, bytes_warning=0, quiet=1)
(Contributed by Marcin Wojdyr in bpo-1772833).
The hasattr() function works by calling getattr() and detecting
whether an exception is raised. This technique allows it to detect methods
created dynamically by __getattr__() or __getattribute__() which
would otherwise be absent from the class dictionary. Formerly, hasattr
would catch any exception, possibly masking genuine errors. Now, hasattr
has been tightened to only catch AttributeError and let other
exceptions pass through:
>>> class A:
... @property
... def f(self):
... return 1 // 0
...
>>> a = A()
>>> hasattr(a, 'f')
Traceback (most recent call last):
...
ZeroDivisionError: integer division or modulo by zero
(Discovered by Yury Selivanov and fixed by Benjamin Peterson; bpo-9666.)
The str() of a float or complex number is now the same as its
repr(). Previously, the str() form was shorter but that just
caused confusion and is no longer needed now that the shortest possible
repr() is displayed by default:
>>> import math
>>> repr(math.pi)
'3.141592653589793'
>>> str(math.pi)
'3.141592653589793'
(Proposed and implemented by Mark Dickinson; bpo-9337.)
memoryview objects now have a release() method
and they also now support the context management protocol. This allows timely
release of any resources that were acquired when requesting a buffer from the
original object.
>>> with memoryview(b'abcdefgh') as v:
... print(v.tolist())
[97, 98, 99, 100, 101, 102, 103, 104]
(Added by Antoine Pitrou; bpo-9757.)
Previously it was illegal to delete a name from the local namespace if it occurs as a free variable in a nested block:
def outer(x):
def inner():
return x
inner()
del x
This is now allowed. Remember that the target of an except clause
is cleared, so this code which used to work with Python 2.6, raised a
SyntaxError with Python 3.1 and now works again:
def f():
def print_error():
print(e)
try:
something
except Exception as e:
print_error()
# implicit "del e" here
(See bpo-4617.)
The internal structsequence tool now creates subclasses of tuple.
This means that C structures like those returned by os.stat(),
time.gmtime(), and sys.version_info now work like a
named tuple and now work with functions and methods that
expect a tuple as an argument. This is a big step forward in making the C
structures as flexible as their pure Python counterparts:
>>> import sys
>>> isinstance(sys.version_info, tuple)
True
>>> 'Version %d.%d.%d %s(%d)' % sys.version_info
'Version 3.2.0 final(0)'
(Suggested by Arfrever Frehtes Taifersar Arahesis and implemented by Benjamin Peterson in bpo-8413.)
Warnings are now easier to control using the PYTHONWARNINGS
environment variable as an alternative to using -W at the command line:
$ export PYTHONWARNINGS='ignore::RuntimeWarning::,once::UnicodeWarning::'
(Suggested by Barry Warsaw and implemented by Philip Jenvey in bpo-7301.)
A new warning category, ResourceWarning, has been added. It is
emitted when potential issues with resource consumption or cleanup
are detected. It is silenced by default in normal release builds but
can be enabled through the means provided by the warnings
module, or on the command line.
A ResourceWarning is issued at interpreter shutdown if the
gc.garbage list isn’t empty, and if gc.DEBUG_UNCOLLECTABLE is
set, all uncollectable objects are printed. This is meant to make the
programmer aware that their code contains object finalization issues.
A ResourceWarning is also issued when a file object is destroyed
without having been explicitly closed. While the deallocator for such
object ensures it closes the underlying operating system resource
(usually, a file descriptor), the delay in deallocating the object could
produce various issues, especially under Windows. Here is an example
of enabling the warning from the command line:
$ python -q -Wdefault
>>> f = open("foo", "wb")
>>> del f
__main__:1: ResourceWarning: unclosed file <_io.BufferedWriter name='foo'>
(Added by Antoine Pitrou and Georg Brandl in bpo-10093 and bpo-477863.)
range objects now support index and count methods. This is part
of an effort to make more objects fully implement the
collections.Sequence abstract base class. As a result, the
language will have a more uniform API. In addition, range objects
now support slicing and negative indices, even with values larger than
sys.maxsize. This makes range more interoperable with lists:
>>> range(0, 100, 2).count(10)
1
>>> range(0, 100, 2).index(10)
5
>>> range(0, 100, 2)[5]
10
>>> range(0, 100, 2)[0:5]
range(0, 10, 2)
(Contributed by Daniel Stutzbach in bpo-9213, by Alexander Belopolsky in bpo-2690, and by Nick Coghlan in bpo-10889.)
The callable() builtin function from Py2.x was resurrected. It provides
a concise, readable alternative to using an abstract base class in an
expression like isinstance(x, collections.Callable):
>>> callable(max)
True
>>> callable(20)
False
(See bpo-10518.)
Python’s import mechanism can now load modules installed in directories with non-ASCII characters in the path name. This solved an aggravating problem with home directories for users with non-ASCII characters in their usernames.
(Required extensive work by Victor Stinner in bpo-9425.)
Python’s standard library has undergone significant maintenance efforts and quality improvements.
The biggest news for Python 3.2 is that the email package, mailbox
module, and nntplib modules now work correctly with the bytes/text model
in Python 3. For the first time, there is correct handling of messages with
mixed encodings.
Throughout the standard library, there has been more careful attention to encodings and text versus bytes issues. In particular, interactions with the operating system are now better able to exchange non-ASCII data using the Windows MBCS encoding, locale-aware encodings, or UTF-8.
Another significant win is the addition of substantially better support for SSL connections and security certificates.
In addition, more classes now implement a context manager to support
convenient and reliable resource clean-up using a with statement.
The usability of the email package in Python 3 has been mostly fixed by
the extensive efforts of R. David Murray. The problem was that emails are
typically read and stored in the form of bytes rather than str
text, and they may contain multiple encodings within a single email. So, the
email package had to be extended to parse and generate email messages in bytes
format.
New functions message_from_bytes() and
message_from_binary_file(), and new classes
BytesFeedParser and BytesParser
allow binary message data to be parsed into model objects.
Given bytes input to the model, get_payload()
will by default decode a message body that has a
Content-Transfer-Encoding of 8bit using the charset
specified in the MIME headers and return the resulting string.
Given bytes input to the model, Generator will
convert message bodies that have a Content-Transfer-Encoding of
8bit to instead have a 7bit Content-Transfer-Encoding.
Headers with unencoded non-ASCII bytes are deemed to be RFC 2047-encoded using the unknown-8bit character set.
A new class BytesGenerator produces bytes as output,
preserving any unchanged non-ASCII data that was present in the input used to
build the model, including message bodies with a
Content-Transfer-Encoding of 8bit.
The smtplib SMTP class now accepts a byte string
for the msg argument to the sendmail() method,
and a new method, send_message() accepts a
Message object and can optionally obtain the
from_addr and to_addrs addresses directly from the object.
(Proposed and implemented by R. David Murray, bpo-4661 and bpo-10321.)
The xml.etree.ElementTree package and its xml.etree.cElementTree
counterpart have been updated to version 1.3.
Several new and useful functions and methods have been added:
xml.etree.ElementTree.fromstringlist() which builds an XML document
from a sequence of fragmentsxml.etree.ElementTree.register_namespace() for registering a global
namespace prefixxml.etree.ElementTree.tostringlist() for string representation
including all sublistsxml.etree.ElementTree.Element.extend() for appending a sequence of zero
or more elementsxml.etree.ElementTree.Element.iterfind() searches an element and
subelementsxml.etree.ElementTree.Element.itertext() creates a text iterator over
an element and its subelementsxml.etree.ElementTree.TreeBuilder.end() closes the current elementxml.etree.ElementTree.TreeBuilder.doctype() handles a doctype
declarationTwo methods have been deprecated:
xml.etree.ElementTree.getchildren() use list(elem) instead.xml.etree.ElementTree.getiterator() use Element.iter instead.For details of the update, see Introducing ElementTree on Fredrik Lundh’s website.
(Contributed by Florent Xicluna and Fredrik Lundh, bpo-6472.)
The functools module includes a new decorator for caching function
calls. functools.lru_cache() can save repeated queries to an external
resource whenever the results are expected to be the same.
For example, adding a caching decorator to a database query function can save database accesses for popular searches:
>>> import functools
>>> @functools.lru_cache(maxsize=300)
... def get_phone_number(name):
... c = conn.cursor()
... c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,))
... return c.fetchone()[0]
>>> for name in user_requests:
... get_phone_number(name) # cached lookup
To help with choosing an effective cache size, the wrapped function is instrumented for tracking cache statistics:
>>> get_phone_number.cache_info()
CacheInfo(hits=4805, misses=980, maxsize=300, currsize=300)
If the phonelist table gets updated, the outdated contents of the cache can be cleared with:
>>> get_phone_number.cache_clear()
(Contributed by Raymond Hettinger and incorporating design ideas from Jim Baker, Miki Tebeka, and Nick Coghlan; see recipe 498245, recipe 577479, bpo-10586, and bpo-10593.)
The functools.wraps() decorator now adds a __wrapped__ attribute
pointing to the original callable function. This allows wrapped functions to
be introspected. It also copies __annotations__ if defined. And now
it also gracefully skips over missing attributes such as __doc__ which
might not be defined for the wrapped callable.
In the above example, the cache can be removed by recovering the original function:
>>> get_phone_number = get_phone_number.__wrapped__ # uncached function
(By Nick Coghlan and Terrence Cole; bpo-9567, bpo-3445, and bpo-8814.)
To help write classes with rich comparison methods, a new decorator
functools.total_ordering() will use existing equality and inequality
methods to fill in the remaining methods.
For example, supplying __eq__ and __lt__ will enable
total_ordering() to fill-in __le__, __gt__ and __ge__:
@total_ordering
class Student:
def __eq__(self, other):
return ((self.lastname.lower(), self.firstname.lower()) ==
(other.lastname.lower(), other.firstname.lower()))
def __lt__(self, other):
return ((self.lastname.lower(), self.firstname.lower()) <
(other.lastname.lower(), other.firstname.lower()))
With the total_ordering decorator, the remaining comparison methods are filled in automatically.
(Contributed by Raymond Hettinger.)
To aid in porting programs from Python 2, the functools.cmp_to_key()
function converts an old-style comparison function to
modern key function:
>>> # locale-aware sort order
>>> sorted(iterable, key=cmp_to_key(locale.strcoll))
For sorting examples and a brief sorting tutorial, see the Sorting HowTo tutorial.
(Contributed by Raymond Hettinger.)
The itertools module has a new accumulate() function
modeled on APL’s scan operator and Numpy’s accumulate function:
>>> from itertools import accumulate
>>> list(accumulate([8, 2, 50]))
[8, 10, 60]
>>> prob_dist = [0.1, 0.4, 0.2, 0.3]
>>> list(accumulate(prob_dist)) # cumulative probability distribution
[0.1, 0.5, 0.7, 1.0]
For an example using accumulate(), see the examples for
the random module.
(Contributed by Raymond Hettinger and incorporating design suggestions from Mark Dickinson.)
The collections.Counter class now has two forms of in-place
subtraction, the existing -= operator for saturating subtraction and the new
subtract() method for regular subtraction. The
former is suitable for multisets
which only have positive counts, and the latter is more suitable for use cases
that allow negative counts:
>>> from collections import Counter
>>> tally = Counter(dogs=5, cats=3)
>>> tally -= Counter(dogs=2, cats=8) # saturating subtraction
>>> tally
Counter({'dogs': 3})
>>> tally = Counter(dogs=5, cats=3)
>>> tally.subtract(dogs=2, cats=8) # regular subtraction
>>> tally
Counter({'dogs': 3, 'cats': -5})
(Contributed by Raymond Hettinger.)
The collections.OrderedDict class has a new method
move_to_end() which takes an existing key and
moves it to either the first or last position in the ordered sequence.
The default is to move an item to the last position. This is equivalent of
renewing an entry with od[k] = od.pop(k).
A fast move-to-end operation is useful for resequencing entries. For example, an ordered dictionary can be used to track order of access by aging entries from the oldest to the most recently accessed.
>>> from collections import OrderedDict
>>> d = OrderedDict.fromkeys(['a', 'b', 'X', 'd', 'e'])
>>> list(d)
['a', 'b', 'X', 'd', 'e']
>>> d.move_to_end('X')
>>> list(d)
['a', 'b', 'd', 'e', 'X']
(Contributed by Raymond Hettinger.)
The collections.deque class grew two new methods
count() and reverse() that
make them more substitutable for list objects:
>>> from collections import deque
>>> d = deque('simsalabim')
>>> d.count('s')
2
>>> d.reverse()
>>> d
deque(['m', 'i', 'b', 'a', 'l', 'a', 's', 'm', 'i', 's'])
(Contributed by Raymond Hettinger.)
The threading module has a new Barrier
synchronization class for making multiple threads wait until all of them have
reached a common barrier point. Barriers are useful for making sure that a task
with multiple preconditions does not run until all of the predecessor tasks are
complete.
Barriers can work with an arbitrary number of threads. This is a generalization of a Rendezvous which is defined for only two threads.
Implemented as a two-phase cyclic barrier, Barrier objects
are suitable for use in loops. The separate filling and draining phases
assure that all threads get released (drained) before any one of them can loop
back and re-enter the barrier. The barrier fully resets after each cycle.
Example of using barriers:
from threading import Barrier, Thread
def get_votes(site):
ballots = conduct_election(site)
all_polls_closed.wait() # do not count until all polls are closed
totals = summarize(ballots)
publish(site, totals)
all_polls_closed = Barrier(len(sites))
for site in sites:
Thread(target=get_votes, args=(site,)).start()
In this example, the barrier enforces a rule that votes cannot be counted at any
polling site until all polls are closed. Notice how a solution with a barrier
is similar to one with threading.Thread.join(), but the threads stay alive
and continue to do work (summarizing ballots) after the barrier point is
crossed.
If any of the predecessor tasks can hang or be delayed, a barrier can be created
with an optional timeout parameter. Then if the timeout period elapses before
all the predecessor tasks reach the barrier point, all waiting threads are
released and a BrokenBarrierError exception is raised:
def get_votes(site):
ballots = conduct_election(site)
try:
all_polls_closed.wait(timeout=midnight - time.now())
except BrokenBarrierError:
lockbox = seal_ballots(ballots)
queue.put(lockbox)
else:
totals = summarize(ballots)
publish(site, totals)
In this example, the barrier enforces a more robust rule. If some election sites do not finish before midnight, the barrier times-out and the ballots are sealed and deposited in a queue for later handling.
See Barrier Synchronization Patterns for more examples of how barriers can be used in parallel computing. Also, there is a simple but thorough explanation of barriers in The Little Book of Semaphores, section 3.6.
(Contributed by Kristján Valur Jónsson with an API review by Jeffrey Yasskin in bpo-8777.)
The datetime module has a new type timezone that
implements the tzinfo interface by returning a fixed UTC
offset and timezone name. This makes it easier to create timezone-aware
datetime objects:
>>> from datetime import datetime, timezone
>>> datetime.now(timezone.utc)
datetime.datetime(2010, 12, 8, 21, 4, 2, 923754, tzinfo=datetime.timezone.utc)
>>> datetime.strptime("01/01/2000 12:00 +0000", "%m/%d/%Y %H:%M %z")
datetime.datetime(2000, 1, 1, 12, 0, tzinfo=datetime.timezone.utc)
Also, timedelta objects can now be multiplied by
float and divided by float and int objects.
And timedelta objects can now divide one another.
The datetime.date.strftime() method is no longer restricted to years
after 1900. The new supported year range is from 1000 to 9999 inclusive.
Whenever a two-digit year is used in a time tuple, the interpretation has been
governed by time.accept2dyear. The default is True which means that
for a two-digit year, the century is guessed according to the POSIX rules
governing the %y strptime format.
Starting with Py3.2, use of the century guessing heuristic will emit a
DeprecationWarning. Instead, it is recommended that
time.accept2dyear be set to False so that large date ranges
can be used without guesswork:
>>> import time, warnings
>>> warnings.resetwarnings() # remove the default warning filters
>>> time.accept2dyear = True # guess whether 11 means 11 or 2011
>>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
Warning (from warnings module):
...
DeprecationWarning: Century info guessed for a 2-digit year.
'Fri Jan 1 12:34:56 2011'
>>> time.accept2dyear = False # use the full range of allowable dates
>>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
'Fri Jan 1 12:34:56 11'
Several functions now have significantly expanded date ranges. When
time.accept2dyear is false, the time.asctime() function will
accept any year that fits in a C int, while the time.mktime() and
time.strftime() functions will accept the full range supported by the
corresponding operating system functions.
(Contributed by Alexander Belopolsky and Victor Stinner in bpo-1289118, bpo-5094, bpo-6641, bpo-2706, bpo-1777412, bpo-8013, and bpo-10827.)
The math module has been updated with six new functions inspired by the
C99 standard.
The isfinite() function provides a reliable and fast way to detect
special values. It returns True for regular numbers and False for Nan or
Infinity:
>>> from math import isfinite
>>> [isfinite(x) for x in (123, 4.56, float('Nan'), float('Inf'))]
[True, True, False, False]
The expm1() function computes e**x-1 for small values of x
without incurring the loss of precision that usually accompanies the subtraction
of nearly equal quantities:
>>> from math import expm1
>>> expm1(0.013671875) # more accurate way to compute e**x-1 for a small x
0.013765762467652909
The erf() function computes a probability integral or Gaussian
error function. The
complementary error function, erfc(), is 1 - erf(x):
>>> from math import erf, erfc, sqrt
>>> erf(1.0/sqrt(2.0)) # portion of normal distribution within 1 standard deviation
0.682689492137086
>>> erfc(1.0/sqrt(2.0)) # portion of normal distribution outside 1 standard deviation
0.31731050786291404
>>> erf(1.0/sqrt(2.0)) + erfc(1.0/sqrt(2.0))
1.0
The gamma() function is a continuous extension of the factorial
function. See https://en.wikipedia.org/wiki/Gamma_function for details. Because
the function is related to factorials, it grows large even for small values of
x, so there is also a lgamma() function for computing the natural
logarithm of the gamma function:
>>> from math import gamma, lgamma
>>> gamma(7.0) # six factorial
720.0
>>> lgamma(801.0) # log(800 factorial)
4551.950730698041
(Contributed by Mark Dickinson.)
The abc module now supports abstractclassmethod() and
abstractstaticmethod().
These tools make it possible to define an abstract base class that
requires a particular classmethod() or staticmethod() to be
implemented:
class Temperature(metaclass=abc.ABCMeta):
@abc.abstractclassmethod
def from_fahrenheit(cls, t):
...
@abc.abstractclassmethod
def from_celsius(cls, t):
...
(Patch submitted by Daniel Urban; bpo-5867.)
The io.BytesIO has a new method, getbuffer(), which
provides functionality similar to memoryview(). It creates an editable
view of the data without making a copy. The buffer’s random access and support
for slice notation are well-suited to in-place editing:
>>> REC_LEN, LOC_START, LOC_LEN = 34, 7, 11
>>> def change_location(buffer, record_number, location):
... start = record_number * REC_LEN + LOC_START
... buffer[start: start+LOC_LEN] = location
>>> import io
>>> byte_stream = io.BytesIO(
... b'G3805 storeroom Main chassis '
... b'X7899 shipping Reserve cog '
... b'L6988 receiving Primary sprocket'
... )
>>> buffer = byte_stream.getbuffer()
>>> change_location(buffer, 1, b'warehouse ')
>>> change_location(buffer, 0, b'showroom ')
>>> print(byte_stream.getvalue())
b'G3805 showroom Main chassis '
b'X7899 warehouse Reserve cog '
b'L6988 receiving Primary sprocket'
(Contributed by Antoine Pitrou in bpo-5506.)
When writing a __repr__() method for a custom container, it is easy to
forget to handle the case where a member refers back to the container itself.
Python’s builtin objects such as list and set handle
self-reference by displaying ”...” in the recursive part of the representation
string.
To help write such __repr__() methods, the reprlib module has a new
decorator, recursive_repr(), for detecting recursive calls to
__repr__() and substituting a placeholder string instead:
>>> class MyList(list):
... @recursive_repr()
... def __repr__(self):
... return '<' + '|'.join(map(repr, self)) + '>'
...
>>> m = MyList('abc')
>>> m.append(m)
>>> m.append('x')
>>> print(m)
<'a'|'b'|'c'|...|'x'>
(Contributed by Raymond Hettinger in bpo-9826 and bpo-9840.)
In addition to dictionary-based configuration described above, the
logging package has many other improvements.
The logging documentation has been augmented by a basic tutorial, an advanced tutorial, and a cookbook of logging recipes. These documents are the fastest way to learn about logging.
The logging.basicConfig() set-up function gained a style argument to
support three different types of string formatting. It defaults to “%” for
traditional %-formatting, can be set to “{” for the new str.format() style, or
can be set to “$” for the shell-style formatting provided by
string.Template. The following three configurations are equivalent:
>>> from logging import basicConfig
>>> basicConfig(style='%', format="%(name)s -> %(levelname)s: %(message)s")
>>> basicConfig(style='{', format="{name} -> {levelname} {message}")
>>> basicConfig(style='$', format="$name -> $levelname: $message")
If no configuration is set-up before a logging event occurs, there is now a
default configuration using a StreamHandler directed to
sys.stderr for events of WARNING level or higher. Formerly, an
event occurring before a configuration was set-up would either raise an
exception or silently drop the event depending on the value of
logging.raiseExceptions. The new default handler is stored in
logging.lastResort.
The use of filters has been simplified. Instead of creating a
Filter object, the predicate can be any Python callable that
returns True or False.
There were a number of other improvements that add flexibility and simplify configuration. See the module documentation for a full listing of changes in Python 3.2.
The csv module now supports a new dialect, unix_dialect,
which applies quoting for all fields and a traditional Unix style with '\n' as
the line terminator. The registered dialect name is unix.
The csv.DictWriter has a new method,
writeheader() for writing-out an initial row to document
the field names:
>>> import csv, sys
>>> w = csv.DictWriter(sys.stdout, ['name', 'dept'], dialect='unix')
>>> w.writeheader()
"name","dept"
>>> w.writerows([
... {'name': 'tom', 'dept': 'accounting'},
... {'name': 'susan', 'dept': 'Salesl'}])
"tom","accounting"
"susan","sales"
(New dialect suggested by Jay Talbot in bpo-5975, and the new method suggested by Ed Abraham in bpo-1537721.)
There is a new and slightly mind-blowing tool
ContextDecorator that is helpful for creating a
context manager that does double duty as a function decorator.
As a convenience, this new functionality is used by
contextmanager() so that no extra effort is needed to support
both roles.
The basic idea is that both context managers and function decorators can be used
for pre-action and post-action wrappers. Context managers wrap a group of
statements using a with statement, and function decorators wrap a
group of statements enclosed in a function. So, occasionally there is a need to
write a pre-action or post-action wrapper that can be used in either role.
For example, it is sometimes useful to wrap functions or groups of statements
with a logger that can track the time of entry and time of exit. Rather than
writing both a function decorator and a context manager for the task, the
contextmanager() provides both capabilities in a single
definition:
from contextlib import contextmanager
import logging
logging.basicConfig(level=logging.INFO)
@contextmanager
def track_entry_and_exit(name):
logging.info('Entering: %s', name)
yield
logging.info('Exiting: %s', name)
Formerly, this would have only been usable as a context manager:
with track_entry_and_exit('widget loader'):
print('Some time consuming activity goes here')
load_widget()
Now, it can be used as a decorator as well:
@track_entry_and_exit('widget loader')
def activity():
print('Some time consuming activity goes here')
load_widget()
Trying to fulfill two roles at once places some limitations on the technique.
Context managers normally have the flexibility to return an argument usable by
a with statement, but there is no parallel for function decorators.
In the above example, there is not a clean way for the track_entry_and_exit context manager to return a logging instance for use in the body of enclosed statements.
(Contributed by Michael Foord in bpo-9110.)
Mark Dickinson crafted an elegant and efficient scheme for assuring that different numeric datatypes will have the same hash value whenever their actual values are equal (bpo-8188):
assert hash(Fraction(3, 2)) == hash(1.5) == \
hash(Decimal("1.5")) == hash(complex(1.5, 0))
Some of the hashing details are exposed through a new attribute,
sys.hash_info, which describes the bit width of the hash value, the
prime modulus, the hash values for infinity and nan, and the multiplier
used for the imaginary part of a number:
>>> sys.hash_info
sys.hash_info(width=64, modulus=2305843009213693951, inf=314159, nan=0, imag=1000003)
An early decision to limit the inter-operability of various numeric types has
been relaxed. It is still unsupported (and ill-advised) to have implicit
mixing in arithmetic expressions such as Decimal('1.1') + float('1.1')
because the latter loses information in the process of constructing the binary
float. However, since existing floating point value can be converted losslessly
to either a decimal or rational representation, it makes sense to add them to
the constructor and to support mixed-type comparisons.
decimal.Decimal constructor now accepts float objects
directly so there in no longer a need to use the from_float()
method (bpo-8257).Decimal objects can be directly compared with float
and fractions.Fraction (bpo-2531 and bpo-8188).Similar changes were made to fractions.Fraction so that the
from_float() and from_decimal()
methods are no longer needed (bpo-8294):
>>> from decimal import Decimal
>>> from fractions import Fraction
>>> Decimal(1.1)
Decimal('1.100000000000000088817841970012523233890533447265625')
>>> Fraction(1.1)
Fraction(2476979795053773, 2251799813685248)
Another useful change for the decimal module is that the
Context.clamp attribute is now public. This is useful in creating
contexts that correspond to the decimal interchange formats specified in IEEE
754 (see bpo-8540).
(Contributed by Mark Dickinson and Raymond Hettinger.)
The ftplib.FTP class now supports the context management protocol to
unconditionally consume socket.error exceptions and to close the FTP
connection when done:
>>> from ftplib import FTP
>>> with FTP("ftp1.at.proftpd.org") as ftp:
ftp.login()
ftp.dir()
'230 Anonymous login ok, restrictions apply.'
dr-xr-xr-x 9 ftp ftp 154 May 6 10:43 .
dr-xr-xr-x 9 ftp ftp 154 May 6 10:43 ..
dr-xr-xr-x 5 ftp ftp 4096 May 6 10:43 CentOS
dr-xr-xr-x 3 ftp ftp 18 Jul 10 2008 Fedora
Other file-like objects such as mmap.mmap and fileinput.input()
also grew auto-closing context managers:
with fileinput.input(files=('log1.txt', 'log2.txt')) as f:
for line in f:
process(line)
(Contributed by Tarek Ziadé and Giampaolo Rodolà in bpo-4972, and by Georg Brandl in bpo-8046 and bpo-1286.)
The FTP_TLS class now accepts a context parameter, which is a
ssl.SSLContext object allowing bundling SSL configuration options,
certificates and private keys into a single (potentially long-lived) structure.
(Contributed by Giampaolo Rodolà; bpo-8806.)
The os.popen() and subprocess.Popen() functions now support
with statements for auto-closing of the file descriptors.
(Contributed by Antoine Pitrou and Brian Curtin in bpo-7461 and bpo-10554.)
The select module now exposes a new, constant attribute,
PIPE_BUF, which gives the minimum number of bytes which are
guaranteed not to block when select.select() says a pipe is ready
for writing.
>>> import select
>>> select.PIPE_BUF
512
(Available on Unix systems. Patch by Sébastien Sablé in bpo-9862)
gzip.GzipFile now implements the io.BufferedIOBase
abstract base class (except for truncate()). It also has a
peek() method and supports unseekable as well as
zero-padded file objects.
The gzip module also gains the compress() and
decompress() functions for easier in-memory compression and
decompression. Keep in mind that text needs to be encoded as bytes
before compressing and decompressing:
>>> import gzip
>>> s = 'Three shall be the number thou shalt count, '
>>> s += 'and the number of the counting shall be three'
>>> b = s.encode() # convert to utf-8
>>> len(b)
89
>>> c = gzip.compress(b)
>>> len(c)
77
>>> gzip.decompress(c).decode()[:42] # decompress and convert to text
'Three shall be the number thou shalt count'
(Contributed by Anand B. Pillai in bpo-3488; and by Antoine Pitrou, Nir Aides and Brian Curtin in bpo-9962, bpo-1675951, bpo-7471 and bpo-2846.)
Also, the zipfile.ZipExtFile class was reworked internally to represent
files stored inside an archive. The new implementation is significantly faster
and can be wrapped in an io.BufferedReader object for more speedups. It
also solves an issue where interleaved calls to read and readline gave the
wrong results.
(Patch submitted by Nir Aides in bpo-7610.)
The TarFile class can now be used as a context manager. In
addition, its add() method has a new option, filter,
that controls which files are added to the archive and allows the file metadata
to be edited.
The new filter option replaces the older, less flexible exclude parameter
which is now deprecated. If specified, the optional filter parameter needs to
be a keyword argument. The user-supplied filter function accepts a
TarInfo object and returns an updated
TarInfo object, or if it wants the file to be excluded, the
function can return None:
>>> import tarfile, glob
>>> def myfilter(tarinfo):
... if tarinfo.isfile(): # only save real files
... tarinfo.uname = 'monty' # redact the user name
... return tarinfo
>>> with tarfile.open(name='myarchive.tar.gz', mode='w:gz') as tf:
... for filename in glob.glob('*.txt'):
... tf.add(filename, filter=myfilter)
... tf.list()
-rw-r--r-- monty/501 902 2011-01-26 17:59:11 annotations.txt
-rw-r--r-- monty/501 123 2011-01-26 17:59:11 general_questions.txt
-rw-r--r-- monty/501 3514 2011-01-26 17:59:11 prion.txt
-rw-r--r-- monty/501 124 2011-01-26 17:59:11 py_todo.txt
-rw-r--r-- monty/501 1399 2011-01-26 17:59:11 semaphore_notes.txt
(Proposed by Tarek Ziadé and implemented by Lars Gustäbel in bpo-6856.)
The hashlib module has two new constant attributes listing the hashing
algorithms guaranteed to be present in all implementations and those available
on the current implementation:
>>> import hashlib
>>> hashlib.algorithms_guaranteed
{'sha1', 'sha224', 'sha384', 'sha256', 'sha512', 'md5'}
>>> hashlib.algorithms_available
{'md2', 'SHA256', 'SHA512', 'dsaWithSHA', 'mdc2', 'SHA224', 'MD4', 'sha256',
'sha512', 'ripemd160', 'SHA1', 'MDC2', 'SHA', 'SHA384', 'MD2',
'ecdsa-with-SHA1','md4', 'md5', 'sha1', 'DSA-SHA', 'sha224',
'dsaEncryption', 'DSA', 'RIPEMD160', 'sha', 'MD5', 'sha384'}
(Suggested by Carl Chenet in bpo-7418.)
The ast module has a wonderful a general-purpose tool for safely
evaluating expression strings using the Python literal
syntax. The ast.literal_eval() function serves as a secure alternative to
the builtin eval() function which is easily abused. Python 3.2 adds
bytes and set literals to the list of supported types:
strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None.
>>> from ast import literal_eval
>>> request = "{'req': 3, 'func': 'pow', 'args': (2, 0.5)}"
>>> literal_eval(request)
{'args': (2, 0.5), 'req': 3, 'func': 'pow'}
>>> request = "os.system('do something harmful')"
>>> literal_eval(request)
Traceback (most recent call last):
...
ValueError: malformed node or string: <_ast.Call object at 0x101739a10>
(Implemented by Benjamin Peterson and Georg Brandl.)
Different operating systems use various encodings for filenames and environment
variables. The os module provides two new functions,
fsencode() and fsdecode(), for encoding and decoding
filenames:
>>> import os
>>> filename = 'Sehenswürdigkeiten'
>>> os.fsencode(filename)
b'Sehensw\xc3\xbcrdigkeiten'
Some operating systems allow direct access to encoded bytes in the
environment. If so, the os.supports_bytes_environ constant will be
true.
For direct access to encoded environment variables (if available),
use the new os.getenvb() function or use os.environb
which is a bytes version of os.environ.
(Contributed by Victor Stinner.)
The shutil.copytree() function has two new options:
symlinks=False so that the function
copies a file pointed to by a symlink, not the symlink itself. This option
will silence the error raised if the file doesn’t exist.shutil.copy2() is used by default.(Contributed by Tarek Ziadé.)
In addition, the shutil module now supports archiving operations for zipfiles, uncompressed tarfiles, gzipped tarfiles,
and bzipped tarfiles. And there are functions for registering additional
archiving file formats (such as xz compressed tarfiles or custom formats).
The principal functions are make_archive() and
unpack_archive(). By default, both operate on the current
directory (which can be set by os.chdir()) and on any sub-directories.
The archive filename needs to be specified with a full pathname. The archiving
step is non-destructive (the original files are left unchanged).
>>> import shutil, pprint
>>> os.chdir('mydata') # change to the source directory
>>> f = shutil.make_archive('/var/backup/mydata',
... 'zip') # archive the current directory
>>> f # show the name of archive
'/var/backup/mydata.zip'
>>> os.chdir('tmp') # change to an unpacking
>>> shutil.unpack_archive('/var/backup/mydata.zip') # recover the data
>>> pprint.pprint(shutil.get_archive_formats()) # display known formats
[('bztar', "bzip2'ed tar-file"),
('gztar', "gzip'ed tar-file"),
('tar', 'uncompressed tar file'),
('zip', 'ZIP file')]
>>> shutil.register_archive_format( # register a new archive format
... name='xz',
... function=xz.compress, # callable archiving function
... extra_args=[('level', 8)], # arguments to the function
... description='xz compression'
... )
(Contributed by Tarek Ziadé.)
The sqlite3 module was updated to pysqlite version 2.6.0. It has two new capabilities.
sqlite3.Connection.in_transit attribute is true if there is an
active transaction for uncommitted changes.sqlite3.Connection.enable_load_extension() and
sqlite3.Connection.load_extension() methods allows you to load SQLite
extensions from ”.so” files. One well-known extension is the fulltext-search
extension distributed with SQLite.(Contributed by R. David Murray and Shashwat Anand; bpo-8845.)
A new html module was introduced with only a single function,
escape(), which is used for escaping reserved characters from HTML
markup:
>>> import html
>>> html.escape('x > 2 && x < 7')
'x > 2 && x < 7'
The socket module has two new improvements.
detach() method which puts
the socket into closed state without actually closing the underlying file
descriptor. The latter can then be reused for other purposes.
(Added by Antoine Pitrou; bpo-8524.)socket.create_connection() now supports the context management protocol
to unconditionally consume socket.error exceptions and to close the
socket when done.
(Contributed by Giampaolo Rodolà; bpo-9794.)The ssl module added a number of features to satisfy common requirements
for secure (encrypted, authenticated) internet connections:
SSLContext, serves as a container for persistent
SSL data, such as protocol settings, certificates, private keys, and various
other options. It includes a wrap_socket() for creating
an SSL socket from an SSL context.ssl.match_hostname(), supports server identity
verification for higher-level protocols by implementing the rules of HTTPS
(from RFC 2818) which are also suitable for other protocols.ssl.wrap_socket() constructor function now takes a ciphers
argument. The ciphers string lists the allowed encryption algorithms using
the format described in the OpenSSL documentation.ssl module now
supports the Server Name Indication extension to the TLS protocol, allowing
multiple “virtual hosts” using different certificates on a single IP port.
This extension is only supported in client mode, and is activated by passing
the server_hostname argument to ssl.SSLContext.wrap_socket().ssl module, such as
OP_NO_SSLv2 which disables the insecure and obsolete SSLv2
protocol.ssl.OPENSSL_VERSION (a string),
ssl.OPENSSL_VERSION_INFO (a 5-tuple), and
ssl.OPENSSL_VERSION_NUMBER (an integer).(Contributed by Antoine Pitrou in bpo-8850, bpo-1589, bpo-8322, bpo-5639, bpo-4870, bpo-8484, and bpo-8321.)
The nntplib module has a revamped implementation with better bytes and
text semantics as well as more practical APIs. These improvements break
compatibility with the nntplib version in Python 3.1, which was partly
dysfunctional in itself.
Support for secure connections through both implicit (using
nntplib.NNTP_SSL) and explicit (using nntplib.NNTP.starttls())
TLS has also been added.
(Contributed by Antoine Pitrou in bpo-9360 and Andrew Vant in bpo-1926.)
http.client.HTTPSConnection, urllib.request.HTTPSHandler
and urllib.request.urlopen() now take optional arguments to allow for
server certificate checking against a set of Certificate Authorities,
as recommended in public uses of HTTPS.
(Added by Antoine Pitrou, bpo-9003.)
Support for explicit TLS on standard IMAP4 connections has been added through
the new imaplib.IMAP4.starttls method.
(Contributed by Lorenzo M. Catucci and Antoine Pitrou, bpo-4471.)
There were a number of small API improvements in the http.client module.
The old-style HTTP 0.9 simple responses are no longer supported and the strict
parameter is deprecated in all classes.
The HTTPConnection and
HTTPSConnection classes now have a source_address
parameter for a (host, port) tuple indicating where the HTTP connection is made
from.
Support for certificate checking and HTTPS virtual hosts were added to
HTTPSConnection.
The request() method on connection objects
allowed an optional body argument so that a file object could be used
to supply the content of the request. Conveniently, the body argument now
also accepts an iterable object so long as it includes an explicit
Content-Length header. This extended interface is much more flexible than
before.
To establish an HTTPS connection through a proxy server, there is a new
set_tunnel() method that sets the host and
port for HTTP Connect tunneling.
To match the behavior of http.server, the HTTP client library now also
encodes headers with ISO-8859-1 (Latin-1) encoding. It was already doing that
for incoming headers, so now the behavior is consistent for both incoming and
outgoing traffic. (See work by Armin Ronacher in bpo-10980.)
The unittest module has a number of improvements supporting test discovery for packages, easier experimentation at the interactive prompt, new testcase methods, improved diagnostic messages for test failures, and better method names.
The command-line call python -m unittest can now accept file paths
instead of module names for running specific tests (bpo-10620). The new
test discovery can find tests within packages, locating any test importable
from the top-level directory. The top-level directory can be specified with
the -t option, a pattern for matching files with -p, and a directory to
start discovery with -s:
$ python -m unittest discover -s my_proj_dir -p _test.py
(Contributed by Michael Foord.)
Experimentation at the interactive prompt is now easier because the
unittest.case.TestCase class can now be instantiated without
arguments:
>>> from unittest import TestCase
>>> TestCase().assertEqual(pow(2, 3), 8)
(Contributed by Michael Foord.)
The unittest module has two new methods,
assertWarns() and
assertWarnsRegex() to verify that a given warning type
is triggered by the code under test:
with self.assertWarns(DeprecationWarning):
legacy_function('XYZ')
(Contributed by Antoine Pitrou, bpo-9754.)
Another new method, assertCountEqual() is used to
compare two iterables to determine if their element counts are equal (whether
the same elements are present with the same number of occurrences regardless
of order):
def test_anagram(self):
self.assertCountEqual('algorithm', 'logarithm')
(Contributed by Raymond Hettinger.)
A principal feature of the unittest module is an effort to produce meaningful
diagnostics when a test fails. When possible, the failure is recorded along
with a diff of the output. This is especially helpful for analyzing log files
of failed test runs. However, since diffs can sometime be voluminous, there is
a new maxDiff attribute that sets maximum length of
diffs displayed.
In addition, the method names in the module have undergone a number of clean-ups.
For example, assertRegex() is the new name for
assertRegexpMatches() which was misnamed because the
test uses re.search(), not re.match(). Other methods using
regular expressions are now named using short form “Regex” in preference to
“Regexp” – this matches the names used in other unittest implementations,
matches Python’s old name for the re module, and it has unambiguous
camel-casing.
(Contributed by Raymond Hettinger and implemented by Ezio Melotti.)
To improve consistency, some long-standing method aliases are being deprecated in favor of the preferred names:
Old Name Preferred Name assert_()assertTrue()assertEquals()assertEqual()assertNotEquals()assertNotEqual()assertAlmostEquals()assertAlmostEqual()assertNotAlmostEquals()assertNotAlmostEqual()
Likewise, the TestCase.fail* methods deprecated in Python 3.1 are expected
to be removed in Python 3.3. Also see the Deprecated aliases section in
the unittest documentation.
(Contributed by Ezio Melotti; bpo-9424.)
The assertDictContainsSubset() method was deprecated
because it was misimplemented with the arguments in the wrong order. This
created hard-to-debug optical illusions where tests like
TestCase().assertDictContainsSubset({'a':1, 'b':2}, {'a':1}) would fail.
(Contributed by Raymond Hettinger.)
The integer methods in the random module now do a better job of producing
uniform distributions. Previously, they computed selections with
int(n*random()) which had a slight bias whenever n was not a power of two.
Now, multiple selections are made from a range up to the next power of two and a
selection is kept only when it falls within the range 0 <= x < n. The
functions and methods affected are randrange(),
randint(), choice(), shuffle() and
sample().
(Contributed by Raymond Hettinger; bpo-9025.)
POP3_SSL class now accepts a context parameter, which is a
ssl.SSLContext object allowing bundling SSL configuration options,
certificates and private keys into a single (potentially long-lived)
structure.
(Contributed by Giampaolo Rodolà; bpo-8807.)
asyncore.dispatcher now provides a
handle_accepted() method
returning a (sock, addr) pair which is called when a connection has actually
been established with a new remote endpoint. This is supposed to be used as a
replacement for old handle_accept() and avoids
the user to call accept() directly.
(Contributed by Giampaolo Rodolà; bpo-6706.)
The tempfile module has a new context manager,
TemporaryDirectory which provides easy deterministic
cleanup of temporary directories:
with tempfile.TemporaryDirectory() as tmpdirname:
print('created temporary dir:', tmpdirname)
(Contributed by Neil Schemenauer and Nick Coghlan; bpo-5178.)
The inspect module has a new function
getgeneratorstate() to easily identify the current state of a
generator-iterator:
>>> from inspect import getgeneratorstate
>>> def gen():
... yield 'demo'
>>> g = gen()
>>> getgeneratorstate(g)
'GEN_CREATED'
>>> next(g)
'demo'
>>> getgeneratorstate(g)
'GEN_SUSPENDED'
>>> next(g, None)
>>> getgeneratorstate(g)
'GEN_CLOSED'
(Contributed by Rodolpho Eckhardt and Nick Coghlan, bpo-10220.)
To support lookups without the possibility of activating a dynamic attribute,
the inspect module has a new function, getattr_static().
Unlike hasattr(), this is a true read-only search, guaranteed not to
change state while it is searching:
>>> class A:
... @property
... def f(self):
... print('Running')
... return 10
...
>>> a = A()
>>> getattr(a, 'f')
Running
10
>>> inspect.getattr_static(a, 'f')
<property object at 0x1022bd788>
(Contributed by Michael Foord.)
The pydoc module now provides a much-improved Web server interface, as
well as a new command-line option -b to automatically open a browser window
to display that server:
$ pydoc3.2 -b
(Contributed by Ron Adam; bpo-2001.)
The dis module gained two new functions for inspecting code,
code_info() and show_code(). Both provide detailed code
object information for the supplied function, method, source code string or code
object. The former returns a string and the latter prints it:
>>> import dis, random
>>> dis.show_code(random.choice)
Name: choice
Filename: /Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/random.py
Argument count: 2
Kw-only arguments: 0
Number of locals: 3
Stack size: 11
Flags: OPTIMIZED, NEWLOCALS, NOFREE
Constants:
0: 'Choose a random element from a non-empty sequence.'
1: 'Cannot choose from an empty sequence'
Names:
0: _randbelow
1: len
2: ValueError
3: IndexError
Variable names:
0: self
1: seq
2: i
In addition, the dis() function now accepts string arguments
so that the common idiom dis(compile(s, '', 'eval')) can be shortened
to dis(s):
>>> dis('3*x+1 if x%2==1 else x//2')
1 0 LOAD_NAME 0 (x)
3 LOAD_CONST 0 (2)
6 BINARY_MODULO
7 LOAD_CONST 1 (1)
10 COMPARE_OP 2 (==)
13 POP_JUMP_IF_FALSE 28
16 LOAD_CONST 2 (3)
19 LOAD_NAME 0 (x)
22 BINARY_MULTIPLY
23 LOAD_CONST 1 (1)
26 BINARY_ADD
27 RETURN_VALUE
>> 28 LOAD_NAME 0 (x)
31 LOAD_CONST 0 (2)
34 BINARY_FLOOR_DIVIDE
35 RETURN_VALUE
Taken together, these improvements make it easier to explore how CPython is implemented and to see for yourself what the language syntax does under-the-hood.
(Contributed by Nick Coghlan in bpo-9147.)
All database modules now support the get() and setdefault() methods.
(Suggested by Ray Allen in bpo-9523.)
A new type, ctypes.c_ssize_t represents the C ssize_t datatype.
The site module has three new functions useful for reporting on the
details of a given Python installation.
getsitepackages() lists all global site-packages directories.getuserbase() reports on the user’s base directory where data can
be stored.getusersitepackages() reveals the user-specific site-packages
directory path.>>> import site
>>> site.getsitepackages()
['/Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/site-packages',
'/Library/Frameworks/Python.framework/Versions/3.2/lib/site-python',
'/Library/Python/3.2/site-packages']
>>> site.getuserbase()
'/Users/raymondhettinger/Library/Python/3.2'
>>> site.getusersitepackages()
'/Users/raymondhettinger/Library/Python/3.2/lib/python/site-packages'
Conveniently, some of site’s functionality is accessible directly from the command-line:
$ python -m site --user-base
/Users/raymondhettinger/.local
$ python -m site --user-site
/Users/raymondhettinger/.local/lib/python3.2/site-packages
(Contributed by Tarek Ziadé in bpo-6693.)
The new sysconfig module makes it straightforward to discover
installation paths and configuration variables that vary across platforms and
installations.
The module offers access simple access functions for platform and version information:
get_platform() returning values like linux-i586 or
macosx-10.6-ppc.get_python_version() returns a Python version string
such as “3.2”.It also provides access to the paths and variables corresponding to one of
seven named schemes used by distutils. Those include posix_prefix,
posix_home, posix_user, nt, nt_user, os2, os2_home:
get_paths() makes a dictionary containing installation paths
for the current installation scheme.get_config_vars() returns a dictionary of platform specific
variables.There is also a convenient command-line interface:
C:\Python32>python -m sysconfig
Platform: "win32"
Python version: "3.2"
Current installation scheme: "nt"
Paths:
data = "C:\Python32"
include = "C:\Python32\Include"
platinclude = "C:\Python32\Include"
platlib = "C:\Python32\Lib\site-packages"
platstdlib = "C:\Python32\Lib"
purelib = "C:\Python32\Lib\site-packages"
scripts = "C:\Python32\Scripts"
stdlib = "C:\Python32\Lib"
Variables:
BINDIR = "C:\Python32"
BINLIBDEST = "C:\Python32\Lib"
EXE = ".exe"
INCLUDEPY = "C:\Python32\Include"
LIBDEST = "C:\Python32\Lib"
SO = ".pyd"
VERSION = "32"
abiflags = ""
base = "C:\Python32"
exec_prefix = "C:\Python32"
platbase = "C:\Python32"
prefix = "C:\Python32"
projectbase = "C:\Python32"
py_version = "3.2"
py_version_nodot = "32"
py_version_short = "3.2"
srcdir = "C:\Python32"
userbase = "C:\Documents and Settings\Raymond\Application Data\Python"
(Moved out of Distutils by Tarek Ziadé.)
The pdb debugger module gained a number of usability improvements:
pdb.py now has a -c option that executes commands as given in a
.pdbrc script file..pdbrc script file can contain continue and next commands
that continue debugging.Pdb class constructor now accepts a nosigint argument.l(list), ll(long list) and source for
listing source code.display and undisplay for showing or hiding
the value of an expression if it has changed.interact for starting an interactive interpreter containing
the global and local names found in the current scope.(Contributed by Georg Brandl, Antonio Cuni and Ilya Sandler.)
The configparser module was modified to improve usability and
predictability of the default parser and its supported INI syntax. The old
ConfigParser class was removed in favor of SafeConfigParser
which has in turn been renamed to ConfigParser. Support
for inline comments is now turned off by default and section or option
duplicates are not allowed in a single configuration source.
Config parsers gained a new API based on the mapping protocol:
>>> parser = ConfigParser()
>>> parser.read_string("""
... [DEFAULT]
... location = upper left
... visible = yes
... editable = no
... color = blue
...
... [main]
... title = Main Menu
... color = green
...
... [options]
... title = Options
... """)
>>> parser['main']['color']
'green'
>>> parser['main']['editable']
'no'
>>> section = parser['options']
>>> section['title']
'Options'
>>> section['title'] = 'Options (editable: %(editable)s)'
>>> section['title']
'Options (editable: no)'
The new API is implemented on top of the classical API, so custom parser subclasses should be able to use it without modifications.
The INI file structure accepted by config parsers can now be customized. Users can specify alternative option/value delimiters and comment prefixes, change the name of the DEFAULT section or switch the interpolation syntax.
There is support for pluggable interpolation including an additional interpolation
handler ExtendedInterpolation:
>>> parser = ConfigParser(interpolation=ExtendedInterpolation())
>>> parser.read_dict({'buildout': {'directory': '/home/ambv/zope9'},
... 'custom': {'prefix': '/usr/local'}})
>>> parser.read_string("""
... [buildout]
... parts =
... zope9
... instance
... find-links =
... ${buildout:directory}/downloads/dist
...
... [zope9]
... recipe = plone.recipe.zope9install
... location = /opt/zope
...
... [instance]
... recipe = plone.recipe.zope9instance
... zope9-location = ${zope9:location}
... zope-conf = ${custom:prefix}/etc/zope.conf
... """)
>>> parser['buildout']['find-links']
'\n/home/ambv/zope9/downloads/dist'
>>> parser['instance']['zope-conf']
'/usr/local/etc/zope.conf'
>>> instance = parser['instance']
>>> instance['zope-conf']
'/usr/local/etc/zope.conf'
>>> instance['zope9-location']
'/opt/zope'
A number of smaller features were also introduced, like support for specifying encoding in read operations, specifying fallback values for get-functions, or reading directly from dictionaries and strings.
(All changes contributed by Łukasz Langa.)
A number of usability improvements were made for the urllib.parse module.
The urlparse() function now supports IPv6 addresses as described in RFC 2732:
>>> import urllib.parse
>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/')
ParseResult(scheme='http',
netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',
path='/foo/',
params='',
query='',
fragment='')
The urldefrag() function now returns a named tuple:
>>> r = urllib.parse.urldefrag('http://python.org/about/#target')
>>> r
DefragResult(url='http://python.org/about/', fragment='target')
>>> r[0]
'http://python.org/about/'
>>> r.fragment
'target'
And, the urlencode() function is now much more flexible,
accepting either a string or bytes type for the query argument. If it is a
string, then the safe, encoding, and error parameters are sent to
quote_plus() for encoding:
>>> urllib.parse.urlencode([
... ('type', 'telenovela'),
... ('name', '¿Dónde Está Elisa?')],
... encoding='latin-1')
'type=telenovela&name=%BFD%F3nde+Est%E1+Elisa%3F'
As detailed in Parsing ASCII Encoded Bytes, all the urllib.parse
functions now accept ASCII-encoded byte strings as input, so long as they are
not mixed with regular strings. If ASCII-encoded byte strings are given as
parameters, the return types will also be an ASCII-encoded byte strings:
>>> urllib.parse.urlparse(b'http://www.python.org:80/about/')
ParseResultBytes(scheme=b'http', netloc=b'www.python.org:80',
path=b'/about/', params=b'', query=b'', fragment=b'')
(Work by Nick Coghlan, Dan Mahn, and Senthil Kumaran in bpo-2987, bpo-5468, and bpo-9873.)
Thanks to a concerted effort by R. David Murray, the mailbox module has
been fixed for Python 3.2. The challenge was that mailbox had been originally
designed with a text interface, but email messages are best represented with
bytes because various parts of a message may have different encodings.
The solution harnessed the email package’s binary support for parsing
arbitrary email messages. In addition, the solution required a number of API
changes.
As expected, the add() method for
mailbox.Mailbox objects now accepts binary input.
StringIO and text file input are deprecated. Also, string input
will fail early if non-ASCII characters are used. Previously it would fail when
the email was processed in a later step.
There is also support for binary output. The get_file()
method now returns a file in the binary mode (where it used to incorrectly set
the file to text-mode). There is also a new get_bytes()
method that returns a bytes representation of a message corresponding
to a given key.
It is still possible to get non-binary output using the old API’s
get_string() method, but that approach
is not very useful. Instead, it is best to extract messages from
a Message object or to load them from binary input.
(Contributed by R. David Murray, with efforts from Steffen Daode Nurpmeso and an initial patch by Victor Stinner in bpo-9124.)
The demonstration code for the turtle module was moved from the Demo
directory to main library. It includes over a dozen sample scripts with
lively displays. Being on sys.path, it can now be run directly
from the command-line:
$ python -m turtledemo
(Moved from the Demo directory by Alexander Belopolsky in bpo-10199.)
The mechanism for serializing execution of concurrently running Python threads
(generally known as the GIL or Global Interpreter Lock) has
been rewritten. Among the objectives were more predictable switching
intervals and reduced overhead due to lock contention and the number of
ensuing system calls. The notion of a “check interval” to allow thread
switches has been abandoned and replaced by an absolute duration expressed in
seconds. This parameter is tunable through sys.setswitchinterval().
It currently defaults to 5 milliseconds.
Additional details about the implementation can be read from a python-dev mailing-list message (however, “priority requests” as exposed in this message have not been kept for inclusion).
(Contributed by Antoine Pitrou.)
Regular and recursive locks now accept an optional timeout argument to their
acquire() method. (Contributed by Antoine Pitrou;
bpo-7316.)
Similarly, threading.Semaphore.acquire() also gained a timeout
argument. (Contributed by Torsten Landschoff; bpo-850728.)
Regular and recursive lock acquisitions can now be interrupted by signals on
platforms using Pthreads. This means that Python programs that deadlock while
acquiring locks can be successfully killed by repeatedly sending SIGINT to the
process (by pressing Ctrl+C in most shells).
(Contributed by Reid Kleckner; bpo-8844.)
A number of small performance enhancements have been added:
Python’s peephole optimizer now recognizes patterns such x in {1, 2, 3} as
being a test for membership in a set of constants. The optimizer recasts the
set as a frozenset and stores the pre-built constant.
Now that the speed penalty is gone, it is practical to start writing membership tests using set-notation. This style is both semantically clear and operationally fast:
extension = name.rpartition('.')[2]
if extension in {'xml', 'html', 'xhtml', 'css'}:
handle(name)
(Patch and additional tests contributed by Dave Malcolm; bpo-6690).
Serializing and unserializing data using the pickle module is now
several times faster.
(Contributed by Alexandre Vassalotti, Antoine Pitrou and the Unladen Swallow team in bpo-9410 and bpo-3873.)
The Timsort algorithm used in
list.sort() and sorted() now runs faster and uses less memory
when called with a key function. Previously, every element of
a list was wrapped with a temporary object that remembered the key value
associated with each element. Now, two arrays of keys and values are
sorted in parallel. This saves the memory consumed by the sort wrappers,
and it saves time lost to delegating comparisons.
(Patch by Daniel Stutzbach in bpo-9915.)
JSON decoding performance is improved and memory consumption is reduced
whenever the same string is repeated for multiple keys. Also, JSON encoding
now uses the C speedups when the sort_keys argument is true.
(Contributed by Antoine Pitrou in bpo-7451 and by Raymond Hettinger and Antoine Pitrou in bpo-10314.)
Recursive locks (created with the threading.RLock() API) now benefit
from a C implementation which makes them as fast as regular locks, and between
10x and 15x faster than their previous pure Python implementation.
(Contributed by Antoine Pitrou; bpo-3001.)
The fast-search algorithm in stringlib is now used by the split(),
rsplit(), splitlines() and replace() methods on
bytes, bytearray and str objects. Likewise, the
algorithm is also used by rfind(), rindex(), rsplit() and
rpartition().
Integer to string conversions now work two “digits” at a time, reducing the number of division and modulo operations.
(bpo-6713 by Gawain Bolton, Mark Dickinson, and Victor Stinner.)
There were several other minor optimizations. Set differencing now runs faster
when one operand is much larger than the other (patch by Andress Bennetts in
bpo-8685). The array.repeat() method has a faster implementation
(bpo-1569291 by Alexander Belopolsky). The BaseHTTPRequestHandler
has more efficient buffering (bpo-3709 by Andrew Schaaf). The
operator.attrgetter() function has been sped-up (bpo-10160 by
Christos Georgiou). And ConfigParser loads multi-line arguments a bit
faster (bpo-7113 by Łukasz Langa).
Python has been updated to Unicode 6.0.0. The update to the standard adds over 2,000 new characters including emoji symbols which are important for mobile phones.
In addition, the updated standard has altered the character properties for two Kannada characters (U+0CF1, U+0CF2) and one New Tai Lue numeric character (U+19DA), making the former eligible for use in identifiers while disqualifying the latter. For more information, see Unicode Character Database Changes.
Support was added for cp720 Arabic DOS encoding (bpo-1616979).
MBCS encoding no longer ignores the error handler argument. In the default
strict mode, it raises an UnicodeDecodeError when it encounters an
undecodable byte sequence and an UnicodeEncodeError for an unencodable
character.
The MBCS codec supports 'strict' and 'ignore' error handlers for
decoding, and 'strict' and 'replace' for encoding.
To emulate Python3.1 MBCS encoding, select the 'ignore' handler for decoding
and the 'replace' handler for encoding.
On Mac OS X, Python decodes command line arguments with 'utf-8' rather than
the locale encoding.
By default, tarfile uses 'utf-8' encoding on Windows (instead of
'mbcs') and the 'surrogateescape' error handler on all operating
systems.
The documentation continues to be improved.
A table of quick links has been added to the top of lengthy sections such as
Built-in Functions. In the case of itertools, the links are
accompanied by tables of cheatsheet-style summaries to provide an overview and
memory jog without having to read all of the docs.
In some cases, the pure Python source code can be a helpful adjunct to the
documentation, so now many modules now feature quick links to the latest
version of the source code. For example, the functools module
documentation has a quick link at the top labeled:
Source code Lib/functools.py.
(Contributed by Raymond Hettinger; see rationale.)
The docs now contain more examples and recipes. In particular, re
module has an extensive section, Regular Expression Examples. Likewise, the
itertools module continues to be updated with new
Itertools Recipes.
The datetime module now has an auxiliary implementation in pure Python.
No functionality was changed. This just provides an easier-to-read alternate
implementation.
(Contributed by Alexander Belopolsky in bpo-9528.)
The unmaintained Demo directory has been removed. Some demos were
integrated into the documentation, some were moved to the Tools/demo
directory, and others were removed altogether.
(Contributed by Georg Brandl in bpo-7962.)
In addition to the existing Subversion code repository at http://svn.python.org there is now a Mercurial repository at https://hg.python.org/.
After the 3.2 release, there are plans to switch to Mercurial as the primary repository. This distributed version control system should make it easier for members of the community to create and share external changesets. See PEP 385 for details.
To learn to use the new version control system, see the tutorial by Joel Spolsky or the Guide to Mercurial Workflows.
Changes to Python’s build process and to the C API include:
The idle, pydoc and 2to3 scripts are now installed with a
version-specific suffix on make altinstall (bpo-10679).
The C functions that access the Unicode Database now accept and return
characters from the full Unicode range, even on narrow unicode builds
(Py_UNICODE_TOLOWER, Py_UNICODE_ISDECIMAL, and others). A visible difference
in Python is that unicodedata.numeric() now returns the correct value
for large code points, and repr() may consider more characters as
printable.
(Reported by Bupjoe Lee and fixed by Amaury Forgeot D’Arc; bpo-5127.)
Computed gotos are now enabled by default on supported compilers (which are
detected by the configure script). They can still be disabled selectively by
specifying --without-computed-gotos.
(Contributed by Antoine Pitrou; bpo-9203.)
The option --with-wctype-functions was removed. The built-in unicode
database is now used for all functions.
(Contributed by Amaury Forgeot D’Arc; bpo-9210.)
Hash values are now values of a new type, Py_hash_t, which is
defined to be the same size as a pointer. Previously they were of type long,
which on some 64-bit operating systems is still only 32 bits long. As a
result of this fix, set and dict can now hold more than
2**32 entries on builds with 64-bit pointers (previously, they could grow
to that size but their performance degraded catastrophically).
(Suggested by Raymond Hettinger and implemented by Benjamin Peterson; bpo-9778.)
A new macro Py_VA_COPY copies the state of the variable argument
list. It is equivalent to C99 va_copy but available on all Python platforms
(bpo-2443).
A new C API function PySys_SetArgvEx() allows an embedded interpreter
to set sys.argv without also modifying sys.path
(bpo-5753).
PyEval_CallObject is now only available in macro form. The
function declaration, which was kept for backwards compatibility reasons, is
now removed – the macro was introduced in 1997 (bpo-8276).
There is a new function PyLong_AsLongLongAndOverflow() which
is analogous to PyLong_AsLongAndOverflow(). They both serve to
convert Python int into a native fixed-width type while providing
detection of cases where the conversion won’t fit (bpo-7767).
The PyUnicode_CompareWithASCIIString() function now returns not
equal if the Python string is NUL terminated.
There is a new function PyErr_NewExceptionWithDoc() that is
like PyErr_NewException() but allows a docstring to be specified.
This lets C exceptions have the same self-documenting capabilities as
their pure Python counterparts (bpo-7033).
When compiled with the --with-valgrind option, the pymalloc
allocator will be automatically disabled when running under Valgrind. This
gives improved memory leak detection when running under Valgrind, while taking
advantage of pymalloc at other times (bpo-2422).
Removed the O? format from the PyArg_Parse functions. The format is no
longer used and it had never been documented (bpo-8837).
There were a number of other small changes to the C-API. See the Misc/NEWS file for a complete list.
Also, there were a number of updates to the Mac OS X build, see Mac/BuildScript/README.txt for details. For users running a 32/64-bit build, there is a known problem with the default Tcl/Tk on Mac OS X 10.6. Accordingly, we recommend installing an updated alternative such as ActiveState Tcl/Tk 8.5.9. See https://www.python.org/download/mac/tcltk/ for additional details.
This section lists previously described changes and other bugfixes that may require changes to your code:
The configparser module has a number of clean-ups. The major change is
to replace the old ConfigParser class with long-standing preferred
alternative SafeConfigParser. In addition there are a number of
smaller incompatibilities:
get() and
set() operations. In the default
interpolation scheme, only two tokens with percent signs are valid: %(name)s
and %%, the latter being an escaped percent sign.set() and
add_section() methods now verify that
values are actual strings. Formerly, unsupported types could be introduced
unintentionally.DuplicateSectionError or
DuplicateOptionError. Formerly, duplicates would
silently overwrite a previous entry."" is now a valid value and is no longer automatically converted to an
empty string. For empty strings, use "option =" in a line.The nntplib module was reworked extensively, meaning that its APIs
are often incompatible with the 3.1 APIs.
bytearray objects can no longer be used as filenames; instead,
they should be converted to bytes.
The array.tostring() and array.fromstring() have been renamed to
array.tobytes() and array.frombytes() for clarity. The old names
have been deprecated. (See bpo-8990.)
PyArg_Parse*() functions:
The PyCObject type, deprecated in 3.1, has been removed. To wrap
opaque C pointers in Python objects, the PyCapsule API should be used
instead; the new type has a well-defined interface for passing typing safety
information and a less complicated signature for calling a destructor.
The sys.setfilesystemencoding() function was removed because
it had a flawed design.
The random.seed() function and method now salt string seeds with an
sha512 hash function. To access the previous version of seed in order to
reproduce Python 3.1 sequences, set the version argument to 1,
random.seed(s, version=1).
The previously deprecated string.maketrans() function has been removed
in favor of the static methods bytes.maketrans() and
bytearray.maketrans(). This change solves the confusion around which
types were supported by the string module. Now, str,
bytes, and bytearray each have their own maketrans and
translate methods with intermediate translation tables of the appropriate
type.
(Contributed by Georg Brandl; bpo-5675.)
The previously deprecated contextlib.nested() function has been removed
in favor of a plain with statement which can accept multiple
context managers. The latter technique is faster (because it is built-in),
and it does a better job finalizing multiple context managers when one of them
raises an exception:
with open('mylog.txt') as infile, open('a.out', 'w') as outfile:
for line in infile:
if '<critical>' in line:
outfile.write(line)
(Contributed by Georg Brandl and Mattias Brändström; appspot issue 53094.)
struct.pack() now only allows bytes for the s string pack code.
Formerly, it would accept text arguments and implicitly encode them to bytes
using UTF-8. This was problematic because it made assumptions about the
correct encoding and because a variable-length encoding can fail when writing
to fixed length segment of a structure.
Code such as struct.pack('<6sHHBBB', 'GIF87a', x, y) should be rewritten
with to use bytes instead of text, struct.pack('<6sHHBBB', b'GIF87a', x, y).
(Discovered by David Beazley and fixed by Victor Stinner; bpo-10783.)
The xml.etree.ElementTree class now raises an
xml.etree.ElementTree.ParseError when a parse fails. Previously it
raised an xml.parsers.expat.ExpatError.
The new, longer str() value on floats may break doctests which rely on
the old output format.
In subprocess.Popen, the default value for close_fds is now
True under Unix; under Windows, it is True if the three standard
streams are set to None, False otherwise. Previously, close_fds
was always False by default, which produced difficult to solve bugs
or race conditions when open file descriptors would leak into the child
process.
Support for legacy HTTP 0.9 has been removed from urllib.request
and http.client. Such support is still present on the server side
(in http.server).
(Contributed by Antoine Pitrou, bpo-10711.)
SSL sockets in timeout mode now raise socket.timeout when a timeout
occurs, rather than a generic SSLError.
(Contributed by Antoine Pitrou, bpo-10272.)
The misleading functions PyEval_AcquireLock() and
PyEval_ReleaseLock() have been officially deprecated. The
thread-state aware APIs (such as PyEval_SaveThread()
and PyEval_RestoreThread()) should be used instead.
Due to security risks, asyncore.handle_accept() has been deprecated, and
a new function, asyncore.handle_accepted(), was added to replace it.
(Contributed by Giampaolo Rodola in bpo-6706.)
Due to the new GIL implementation, PyEval_InitThreads()
cannot be called before Py_Initialize() anymore.