What’s New In Python 3.2

What’s New In Python 3.2¶
- Author:
Raymond Hettinger
This article explains the new features in Python 3.2 as compared to 3.1. Python 3.2 was released on February 20, 2011. 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
PEP 384: Defining a Stable ABI¶
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
- PEP 384 - Defining a Stable ABI
PEP written by Martin von Löwis.
PEP 389: Argparse Command Line Parsing Module¶
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
- PEP 389 - New Command Line Parsing Module
PEP written by Steven Bethard.
Migrating optparse code to argparse for details on the differences from optparse
.
PEP 391: Dictionary Based Configuration for Logging¶
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
- PEP 391 - Dictionary Based Configuration for Logging
PEP written by Vinay Sajip.
PEP 3148: The 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
- PEP 3148 - Futures – Execute Computations Asynchronously
PEP written by Brian Quinlan.
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
.
PEP 3147: PYC Repository Directories¶
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
andcompileall
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
andPyPycLoader
, have been deprecated (instructions on how to stay Python 3.1 compatible are included with the documentation).
See also
- PEP 3147 - PYC Repository Directories
PEP written by Barry Warsaw.
PEP 3149: ABI Version Tagged .so Files¶
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
- PEP 3149 - ABI Version Tagged .so Files
PEP written by Barry Warsaw.
PEP 3333: Python Web Server Gateway Interface v1.0.1¶
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:
If the app already used strings for headers in Python 2, no change is needed.
If instead, the app encoded output headers or decoded input headers, then the headers will need to be re-encoded to Latin-1. For example, an output header encoded in utf-8 was using
h.encode('utf-8')
now needs to convert from bytes to native strings usingh.encode('utf-8').decode('latin-1')
.Values yielded by an application or sent using the
write()
method must be byte strings. Thestart_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
- PEP 3333 - Python Web Server Gateway Interface v1.0.1
PEP written by Phillip Eby.
Other Language Changes¶
Some smaller changes made to the core Python language are:
String formatting for
format()
andstr.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 existingstr.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 asdefaultdict
,Shelf
,ConfigParser
, ordbm
. It is also useful with customdict
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 thesys.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 callinggetattr()
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 catchAttributeError
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 itsrepr()
. Previously, thestr()
form was shorter but that just caused confusion and is no longer needed now that the shortest possiblerepr()
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 arelease()
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 aSyntaxError
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.)
Struct sequence types are now subclasses of tuple. This means that C structures like those returned by
os.stat()
,time.gmtime()
, andsys.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 thewarnings
module, or on the command line.A
ResourceWarning
is issued at interpreter shutdown if thegc.garbage
list isn’t empty, and ifgc.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 thecollections.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 thansys.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 likeisinstance(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.)
New, Improved, and Deprecated Modules¶
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.
email¶
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()
andmessage_from_binary_file()
, and new classesBytesFeedParser
andBytesParser
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 thesendmail()
method, and a new method,send_message()
accepts aMessage
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.)
elementtree¶
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 declaration
Two methods have been deprecated:
xml.etree.ElementTree.getchildren()
uselist(elem)
instead.xml.etree.ElementTree.getiterator()
useElement.iter
instead.
For details of the update, see Introducing ElementTree on Fredrik Lundh’s website.
(Contributed by Florent Xicluna and Fredrik Lundh, bpo-6472.)
functools¶
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.)
itertools¶
The
itertools
module has a newaccumulate()
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.)
collections¶
The
collections.Counter
class now has two forms of in-place subtraction, the existing -= operator for saturating subtraction and the newsubtract()
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 methodmove_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 methodscount()
andreverse()
that make them more substitutable forlist
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.)
threading¶
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.)
datetime and time¶
The
datetime
module has a new typetimezone
that implements thetzinfo
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 byfloat
and divided byfloat
andint
objects. Andtimedelta
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 isTrue
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 thattime.accept2dyear
be set toFalse
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, thetime.asctime()
function will accept any year that fits in a C int, while thetime.mktime()
andtime.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.)
math¶
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.)
abc¶
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.)
io¶
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.)
reprlib¶
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.)
logging¶
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.
csv¶
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.)
contextlib¶
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.)
decimal and fractions¶
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 interoperability 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.
The
decimal.Decimal
constructor now acceptsfloat
objects directly so there in no longer a need to use thefrom_float()
method (bpo-8257).Mixed type comparisons are now fully supported so that
Decimal
objects can be directly compared withfloat
andfractions.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.)
ftp¶
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.)
popen¶
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.)
select¶
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 and zipfile¶
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.)
tarfile¶
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.)
hashlib¶
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.)
ast¶
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.)
os¶
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.)
shutil¶
The shutil.copytree()
function has two new options:
ignore_dangling_symlinks: when
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.copy_function: is a callable that will be used to copy files.
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.)
sqlite3¶
The sqlite3
module was updated to pysqlite version 2.6.0. It has two new capabilities.
The
sqlite3.Connection.in_transit
attribute is true if there is an active transaction for uncommitted changes.The
sqlite3.Connection.enable_load_extension()
andsqlite3.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.)
html¶
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'
socket¶
The socket
module has two new improvements.
Socket objects now have a
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 consumesocket.error
exceptions and to close the socket when done. (Contributed by Giampaolo Rodolà; bpo-9794.)
ssl¶
The ssl
module added a number of features to satisfy common requirements
for secure (encrypted, authenticated) internet connections:
A new class,
SSLContext
, serves as a container for persistent SSL data, such as protocol settings, certificates, private keys, and various other options. It includes awrap_socket()
for creating an SSL socket from an SSL context.A new function,
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.The
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.When linked against recent versions of OpenSSL, the
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 tossl.SSLContext.wrap_socket()
.Various options have been added to the
ssl
module, such asOP_NO_SSLv2
which disables the insecure and obsolete SSLv2 protocol.The extension now loads all the OpenSSL ciphers and digest algorithms. If some SSL certificates cannot be verified, they are reported as an “unknown algorithm” error.
The version of OpenSSL being used is now accessible using the module attributes
ssl.OPENSSL_VERSION
(a string),ssl.OPENSSL_VERSION_INFO
(a 5-tuple), andssl.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.)
nntp¶
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.)
certificates¶
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.)
imaplib¶
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.)
http.client¶
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.)
unittest¶
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.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()
andassertWarnsRegex()
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 forassertRegexpMatches()
which was misnamed because the test usesre.search()
, notre.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 there
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_()
assertEquals()
assertNotEquals()
assertAlmostEquals()
assertNotAlmostEquals()
Likewise, the
TestCase.fail*
methods deprecated in Python 3.1 are expected to be removed in Python 3.3.(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 likeTestCase().assertDictContainsSubset({'a':1, 'b':2}, {'a':1})
would fail.(Contributed by Raymond Hettinger.)
random¶
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.)
poplib¶
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¶
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.)
tempfile¶
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.)
inspect¶
The
inspect
module has a new functiongetgeneratorstate()
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()
. Unlikehasattr()
, 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.)
pydoc¶
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.)
dis¶
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.)
dbm¶
All database modules now support the get()
and setdefault()
methods.
(Suggested by Ray Allen in bpo-9523.)
ctypes¶
A new type, ctypes.c_ssize_t
represents the C ssize_t
datatype.
site¶
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.)
sysconfig¶
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.)
pdb¶
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.A
.pdbrc
script file can containcontinue
andnext
commands that continue debugging.The
Pdb
class constructor now accepts a nosigint argument.New commands:
l(list)
,ll(long list)
andsource
for listing source code.New commands:
display
andundisplay
for showing or hiding the value of an expression if it has changed.New command:
interact
for starting an interactive interpreter containing the global and local names found in the current scope.Breakpoints can be cleared by breakpoint number.
(Contributed by Georg Brandl, Antonio Cuni and Ilya Sandler.)
configparser¶
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.)
urllib.parse¶
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.)
mailbox¶
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.)
turtledemo¶
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.)
Multi-threading¶
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.)
Optimizations¶
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 theset
as afrozenset
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()
andsorted()
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()
andreplace()
methods onbytes
,bytearray
andstr
objects. Likewise, the algorithm is also used byrfind()
,rindex()
,rsplit()
andrpartition()
.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).
Unicode¶
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.
Codecs¶
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.
Documentation¶
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, theitertools
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 theTools/demo
directory, and others were removed altogether.(Contributed by Georg Brandl in bpo-7962.)
IDLE¶
Code Repository¶
In addition to the existing Subversion code repository at https://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 Quick Start or the Guide to Mercurial Workflows.
Build and C API Changes¶
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, andrepr()
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
anddict
can now hold more than2**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 setsys.argv
without also modifyingsys.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 toPyLong_AsLongAndOverflow()
. They both serve to convert Pythonint
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 likePyErr_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.
Porting to Python 3.2¶
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 oldConfigParser
class with long-standing preferred alternativeSafeConfigParser
. In addition there are a number of smaller incompatibilities:The interpolation syntax is now validated on
get()
andset()
operations. In the default interpolation scheme, only two tokens with percent signs are valid:%(name)s
and%%
, the latter being an escaped percent sign.The
set()
andadd_section()
methods now verify that values are actual strings. Formerly, unsupported types could be introduced unintentionally.Duplicate sections or options from a single source now raise either
DuplicateSectionError
orDuplicateOptionError
. Formerly, duplicates would silently overwrite a previous entry.Inline comments are now disabled by default so now the ; character can be safely used in values.
Comments now can be indented. Consequently, for ; or # to appear at the start of a line in multiline values, it has to be interpolated. This keeps comment prefix characters in values from being mistaken as comments.
""
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 tobytes
.The
array.tostring()
andarray.fromstring()
have been renamed toarray.tobytes()
andarray.frombytes()
for clarity. The old names have been deprecated. (See bpo-8990.)PyArg_Parse*()
functions:“t#” format has been removed: use “s#” or “s*” instead
“w” and “w#” formats has been removed: use “w*” instead
The
PyCObject
type, deprecated in 3.1, has been removed. To wrap opaque C pointers in Python objects, thePyCapsule
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 methodsbytes.maketrans()
andbytearray.maketrans()
. This change solves the confusion around which types were supported by thestring
module. Now,str
,bytes
, andbytearray
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 plainwith
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 thes
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 anxml.etree.ElementTree.ParseError
when a parse fails. Previously it raised anxml.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 nowTrue
under Unix; under Windows, it isTrue
if the three standard streams are set toNone
,False
otherwise. Previously, close_fds was alwaysFalse
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
andhttp.client
. Such support is still present on the server side (inhttp.server
).(Contributed by Antoine Pitrou, bpo-10711.)
SSL sockets in timeout mode now raise
socket.timeout
when a timeout occurs, rather than a genericSSLError
.(Contributed by Antoine Pitrou, bpo-10272.)
The misleading functions
PyEval_AcquireLock()
andPyEval_ReleaseLock()
have been officially deprecated. The thread-state aware APIs (such asPyEval_SaveThread()
andPyEval_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 beforePy_Initialize()
anymore.