What’s New In Python 3.3

This article explains the new features in Python 3.3, compared to 3.2. Python 3.3 was released on September 29, 2012. For full details, see the changelog.

See also

PEP 398 - Python 3.3 Release Schedule

Summary – Release highlights

New syntax features:

New library modules:

  • faulthandler (helps debugging low-level crashes)

  • ipaddress (high-level objects representing IP addresses and masks)

  • lzma (compress data using the XZ / LZMA algorithm)

  • unittest.mock (replace parts of your system under test with mock objects)

  • venv (Python virtual environments, as in the popular virtualenv package)

New built-in features:

Implementation improvements:

Significantly Improved Library Modules:

Security improvements:

  • Hash randomization is switched on by default.

Please read on for a comprehensive list of user-facing changes.

PEP 405: Virtual Environments

Virtual environments help create separate Python setups while sharing a system-wide base install, for ease of maintenance. Virtual environments have their own set of private site packages (i.e. locally installed libraries), and are optionally segregated from the system-wide site packages. Their concept and implementation are inspired by the popular virtualenv third-party package, but benefit from tighter integration with the interpreter core.

This PEP adds the venv module for programmatic access, and the pyvenv script for command-line access and administration. The Python interpreter checks for a pyvenv.cfg, file whose existence signals the base of a virtual environment’s directory tree.

See also

PEP 405 - Python Virtual Environments

PEP written by Carl Meyer; implementation by Carl Meyer and Vinay Sajip

PEP 420: Implicit Namespace Packages

Native support for package directories that don’t require __init__.py marker files and can automatically span multiple path segments (inspired by various third party approaches to namespace packages, as described in PEP 420)

See also

PEP 420 - Implicit Namespace Packages

PEP written by Eric V. Smith; implementation by Eric V. Smith and Barry Warsaw

PEP 3118: New memoryview implementation and buffer protocol documentation

The implementation of PEP 3118 has been significantly improved.

The new memoryview implementation comprehensively fixes all ownership and lifetime issues of dynamically allocated fields in the Py_buffer struct that led to multiple crash reports. Additionally, several functions that crashed or returned incorrect results for non-contiguous or multi-dimensional input have been fixed.

The memoryview object now has a PEP-3118 compliant getbufferproc() that checks the consumer’s request type. Many new features have been added, most of them work in full generality for non-contiguous arrays and arrays with suboffsets.

The documentation has been updated, clearly spelling out responsibilities for both exporters and consumers. Buffer request flags are grouped into basic and compound flags. The memory layout of non-contiguous and multi-dimensional NumPy-style arrays is explained.

Features

  • All native single character format specifiers in struct module syntax (optionally prefixed with ‘@’) are now supported.

  • With some restrictions, the cast() method allows changing of format and shape of C-contiguous arrays.

  • Multi-dimensional list representations are supported for any array type.

  • Multi-dimensional comparisons are supported for any array type.

  • One-dimensional memoryviews of hashable (read-only) types with formats B, b or c are now hashable. (Contributed by Antoine Pitrou in bpo-13411.)

  • Arbitrary slicing of any 1-D arrays type is supported. For example, it is now possible to reverse a memoryview in O(1) by using a negative step.

API changes

  • The maximum number of dimensions is officially limited to 64.

  • The representation of empty shape, strides and suboffsets is now an empty tuple instead of None.

  • Accessing a memoryview element with format ‘B’ (unsigned bytes) now returns an integer (in accordance with the struct module syntax). For returning a bytes object the view must be cast to ‘c’ first.

  • memoryview comparisons now use the logical structure of the operands and compare all array elements by value. All format strings in struct module syntax are supported. Views with unrecognised format strings are still permitted, but will always compare as unequal, regardless of view contents.

  • For further changes see Build and C API Changes and Porting C code.

(Contributed by Stefan Krah in bpo-10181.)

See also

PEP 3118 - Revising the Buffer Protocol

PEP 393: Flexible String Representation

The Unicode string type is changed to support multiple internal representations, depending on the character with the largest Unicode ordinal (1, 2, or 4 bytes) in the represented string. This allows a space-efficient representation in common cases, but gives access to full UCS-4 on all systems. For compatibility with existing APIs, several representations may exist in parallel; over time, this compatibility should be phased out.

On the Python side, there should be no downside to this change.

On the C API side, PEP 393 is fully backward compatible. The legacy API should remain available at least five years. Applications using the legacy API will not fully benefit of the memory reduction, or - worse - may use a bit more memory, because Python may have to maintain two versions of each string (in the legacy format and in the new efficient storage).

Functionality

Changes introduced by PEP 393 are the following:

  • Python now always supports the full range of Unicode code points, including non-BMP ones (i.e. from U+0000 to U+10FFFF). The distinction between narrow and wide builds no longer exists and Python now behaves like a wide build, even under Windows.

  • With the death of narrow builds, the problems specific to narrow builds have also been fixed, for example:

    • len() now always returns 1 for non-BMP characters, so len('\U0010FFFF') == 1;

    • surrogate pairs are not recombined in string literals, so '\uDBFF\uDFFF' != '\U0010FFFF';

    • indexing or slicing non-BMP characters returns the expected value, so '\U0010FFFF'[0] now returns '\U0010FFFF' and not '\uDBFF';

    • all other functions in the standard library now correctly handle non-BMP code points.

  • The value of sys.maxunicode is now always 1114111 (0x10FFFF in hexadecimal). The PyUnicode_GetMax() function still returns either 0xFFFF or 0x10FFFF for backward compatibility, and it should not be used with the new Unicode API (see bpo-13054).

  • The ./configure flag --with-wide-unicode has been removed.

Performance and resource usage

The storage of Unicode strings now depends on the highest code point in the string:

  • pure ASCII and Latin1 strings (U+0000-U+00FF) use 1 byte per code point;

  • BMP strings (U+0000-U+FFFF) use 2 bytes per code point;

  • non-BMP strings (U+10000-U+10FFFF) use 4 bytes per code point.

The net effect is that for most applications, memory usage of string storage should decrease significantly - especially compared to former wide unicode builds - as, in many cases, strings will be pure ASCII even in international contexts (because many strings store non-human language data, such as XML fragments, HTTP headers, JSON-encoded data, etc.). We also hope that it will, for the same reasons, increase CPU cache efficiency on non-trivial applications. The memory usage of Python 3.3 is two to three times smaller than Python 3.2, and a little bit better than Python 2.7, on a Django benchmark (see the PEP for details).

See also

PEP 393 - Flexible String Representation

PEP written by Martin von Löwis; implementation by Torsten Becker and Martin von Löwis.

PEP 397: Python Launcher for Windows

The Python 3.3 Windows installer now includes a py launcher application that can be used to launch Python applications in a version independent fashion.

This launcher is invoked implicitly when double-clicking *.py files. If only a single Python version is installed on the system, that version will be used to run the file. If multiple versions are installed, the most recent version is used by default, but this can be overridden by including a Unix-style “shebang line” in the Python script.

The launcher can also be used explicitly from the command line as the py application. Running py follows the same version selection rules as implicitly launching scripts, but a more specific version can be selected by passing appropriate arguments (such as -3 to request Python 3 when Python 2 is also installed, or -2.6 to specifically request an earlier Python version when a more recent version is installed).

In addition to the launcher, the Windows installer now includes an option to add the newly installed Python to the system PATH. (Contributed by Brian Curtin in bpo-3561.)

See also

PEP 397 - Python Launcher for Windows

PEP written by Mark Hammond and Martin v. Löwis; implementation by Vinay Sajip.

Launcher documentation: Python Launcher for Windows

Installer PATH modification: Finding the Python executable

PEP 3151: Reworking the OS and IO exception hierarchy

The hierarchy of exceptions raised by operating system errors is now both simplified and finer-grained.

You don’t have to worry anymore about choosing the appropriate exception type between OSError, IOError, EnvironmentError, WindowsError, mmap.error, socket.error or select.error. All these exception types are now only one: OSError. The other names are kept as aliases for compatibility reasons.

Also, it is now easier to catch a specific error condition. Instead of inspecting the errno attribute (or args[0]) for a particular constant from the errno module, you can catch the adequate OSError subclass. The available subclasses are the following:

And the ConnectionError itself has finer-grained subclasses:

Thanks to the new exceptions, common usages of the errno can now be avoided. For example, the following code written for Python 3.2:

from errno import ENOENT, EACCES, EPERM

try:
    with open("document.txt") as f:
        content = f.read()
except IOError as err:
    if err.errno == ENOENT:
        print("document.txt file is missing")
    elif err.errno in (EACCES, EPERM):
        print("You are not allowed to read document.txt")
    else:
        raise

can now be written without the errno import and without manual inspection of exception attributes:

try:
    with open("document.txt") as f:
        content = f.read()
except FileNotFoundError:
    print("document.txt file is missing")
except PermissionError:
    print("You are not allowed to read document.txt")

See also

PEP 3151 - Reworking the OS and IO Exception Hierarchy

PEP written and implemented by Antoine Pitrou

PEP 380: Syntax for Delegating to a Subgenerator

PEP 380 adds the yield from expression, allowing a generator to delegate part of its operations to another generator. This allows a section of code containing yield to be factored out and placed in another generator. Additionally, the subgenerator is allowed to return with a value, and the value is made available to the delegating generator.

While designed primarily for use in delegating to a subgenerator, the yield from expression actually allows delegation to arbitrary subiterators.

For simple iterators, yield from iterable is essentially just a shortened form of for item in iterable: yield item:

>>> def g(x):
...     yield from range(x, 0, -1)
...     yield from range(x)
...
>>> list(g(5))
[5, 4, 3, 2, 1, 0, 1, 2, 3, 4]

However, unlike an ordinary loop, yield from allows subgenerators to receive sent and thrown values directly from the calling scope, and return a final value to the outer generator:

>>> def accumulate():
...     tally = 0
...     while 1:
...         next = yield
...         if next is None:
...             return tally
...         tally += next
...
>>> def gather_tallies(tallies):
...     while 1:
...         tally = yield from accumulate()
...         tallies.append(tally)
...
>>> tallies = []
>>> acc = gather_tallies(tallies)
>>> next(acc)  # Ensure the accumulator is ready to accept values
>>> for i in range(4):
...     acc.send(i)
...
>>> acc.send(None)  # Finish the first tally
>>> for i in range(5):
...     acc.send(i)
...
>>> acc.send(None)  # Finish the second tally
>>> tallies
[6, 10]

The main principle driving this change is to allow even generators that are designed to be used with the send and throw methods to be split into multiple subgenerators as easily as a single large function can be split into multiple subfunctions.

See also

PEP 380 - Syntax for Delegating to a Subgenerator

PEP written by Greg Ewing; implementation by Greg Ewing, integrated into 3.3 by Renaud Blanch, Ryan Kelly and Nick Coghlan; documentation by Zbigniew Jędrzejewski-Szmek and Nick Coghlan

PEP 409: Suppressing exception context

PEP 409 introduces new syntax that allows the display of the chained exception context to be disabled. This allows cleaner error messages in applications that convert between exception types:

>>> class D:
...     def __init__(self, extra):
...         self._extra_attributes = extra
...     def __getattr__(self, attr):
...         try:
...             return self._extra_attributes[attr]
...         except KeyError:
...             raise AttributeError(attr) from None
...
>>> D({}).x
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 8, in __getattr__
AttributeError: x

Without the from None suffix to suppress the cause, the original exception would be displayed by default:

>>> class C:
...     def __init__(self, extra):
...         self._extra_attributes = extra
...     def __getattr__(self, attr):
...         try:
...             return self._extra_attributes[attr]
...         except KeyError:
...             raise AttributeError(attr)
...
>>> C({}).x
Traceback (most recent call last):
  File "<stdin>", line 6, in __getattr__
KeyError: 'x'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 8, in __getattr__
AttributeError: x

No debugging capability is lost, as the original exception context remains available if needed (for example, if an intervening library has incorrectly suppressed valuable underlying details):

>>> try:
...     D({}).x
... except AttributeError as exc:
...     print(repr(exc.__context__))
...
KeyError('x',)

See also

PEP 409 - Suppressing exception context

PEP written by Ethan Furman; implemented by Ethan Furman and Nick Coghlan.

PEP 414: Explicit Unicode literals

To ease the transition from Python 2 for Unicode aware Python applications that make heavy use of Unicode literals, Python 3.3 once again supports the “u” prefix for string literals. This prefix has no semantic significance in Python 3, it is provided solely to reduce the number of purely mechanical changes in migrating to Python 3, making it easier for developers to focus on the more significant semantic changes (such as the stricter default separation of binary and text data).

See also

PEP 414 - Explicit Unicode literals

PEP written by Armin Ronacher.

PEP 3155: Qualified name for classes and functions

Functions and class objects have a new __qualname__ attribute representing the “path” from the module top-level to their definition. For global functions and classes, this is the same as __name__. For other functions and classes, it provides better information about where they were actually defined, and how they might be accessible from the global scope.

Example with (non-bound) methods:

>>> class C:
...     def meth(self):
...         pass
>>> C.meth.__name__
'meth'
>>> C.meth.__qualname__
'C.meth'

Example with nested classes:

>>> class C:
...     class D:
...         def meth(self):
...             pass
...
>>> C.D.__name__
'D'
>>> C.D.__qualname__
'C.D'
>>> C.D.meth.__name__
'meth'
>>> C.D.meth.__qualname__
'C.D.meth'

Example with nested functions:

>>> def outer():
...     def inner():
...         pass
...     return inner
...
>>> outer().__name__
'inner'
>>> outer().__qualname__
'outer.<locals>.inner'

The string representation of those objects is also changed to include the new, more precise information:

>>> str(C.D)
"<class '__main__.C.D'>"
>>> str(C.D.meth)
'<function C.D.meth at 0x7f46b9fe31e0>'

See also

PEP 3155 - Qualified name for classes and functions

PEP written and implemented by Antoine Pitrou.

PEP 412: Key-Sharing Dictionary

Dictionaries used for the storage of objects’ attributes are now able to share part of their internal storage between each other (namely, the part which stores the keys and their respective hashes). This reduces the memory consumption of programs creating many instances of non-builtin types.

See also

PEP 412 - Key-Sharing Dictionary

PEP written and implemented by Mark Shannon.

PEP 362: Function Signature Object

A new function inspect.signature() makes introspection of python callables easy and straightforward. A broad range of callables is supported: python functions, decorated or not, classes, and functools.partial() objects. New classes inspect.Signature, inspect.Parameter and inspect.BoundArguments hold information about the call signatures, such as, annotations, default values, parameters kinds, and bound arguments, which considerably simplifies writing decorators and any code that validates or amends calling signatures or arguments.

See also

PEP 362: - Function Signature Object

PEP written by Brett Cannon, Yury Selivanov, Larry Hastings, Jiwon Seo; implemented by Yury Selivanov.

PEP 421: Adding sys.implementation

A new attribute on the sys module exposes details specific to the implementation of the currently running interpreter. The initial set of attributes on sys.implementation are name, version, hexversion, and cache_tag.

The intention of sys.implementation is to consolidate into one namespace the implementation-specific data used by the standard library. This allows different Python implementations to share a single standard library code base much more easily. In its initial state, sys.implementation holds only a small portion of the implementation-specific data. Over time that ratio will shift in order to make the standard library more portable.

One example of improved standard library portability is cache_tag. As of Python 3.3, sys.implementation.cache_tag is used by importlib to support PEP 3147 compliance. Any Python implementation that uses importlib for its built-in import system may use cache_tag to control the caching behavior for modules.

SimpleNamespace

The implementation of sys.implementation also introduces a new type to Python: types.SimpleNamespace. In contrast to a mapping-based namespace, like dict, SimpleNamespace is attribute-based, like object. However, unlike object, SimpleNamespace instances are writable. This means that you can add, remove, and modify the namespace through normal attribute access.

See also

PEP 421 - Adding sys.implementation

PEP written and implemented by Eric Snow.

Using importlib as the Implementation of Import

bpo-2377 - Replace __import__ w/ importlib.__import__ bpo-13959 - Re-implement parts of imp in pure Python bpo-14605 - Make import machinery explicit bpo-14646 - Require loaders set __loader__ and __package__

The __import__() function is now powered by importlib.__import__(). This work leads to the completion of “phase 2” of PEP 302. There are multiple benefits to this change. First, it has allowed for more of the machinery powering import to be exposed instead of being implicit and hidden within the C code. It also provides a single implementation for all Python VMs supporting Python 3.3 to use, helping to end any VM-specific deviations in import semantics. And finally it eases the maintenance of import, allowing for future growth to occur.

For the common user, there should be no visible change in semantics. For those whose code currently manipulates import or calls import programmatically, the code changes that might possibly be required are covered in the Porting Python code section of this document.

New APIs

One of the large benefits of this work is the exposure of what goes into making the import statement work. That means the various importers that were once implicit are now fully exposed as part of the importlib package.

The abstract base classes defined in importlib.abc have been expanded to properly delineate between meta path finders and path entry finders by introducing importlib.abc.MetaPathFinder and importlib.abc.PathEntryFinder, respectively. The old ABC of importlib.abc.Finder is now only provided for backwards-compatibility and does not enforce any method requirements.

In terms of finders, importlib.machinery.FileFinder exposes the mechanism used to search for source and bytecode files of a module. Previously this class was an implicit member of sys.path_hooks.

For loaders, the new abstract base class importlib.abc.FileLoader helps write a loader that uses the file system as the storage mechanism for a module’s code. The loader for source files (importlib.machinery.SourceFileLoader), sourceless bytecode files (importlib.machinery.SourcelessFileLoader), and extension modules (importlib.machinery.ExtensionFileLoader) are now available for direct use.

ImportError now has name and path attributes which are set when there is relevant data to provide. The message for failed imports will also provide the full name of the module now instead of just the tail end of the module’s name.

The importlib.invalidate_caches() function will now call the method with the same name on all finders cached in sys.path_importer_cache to help clean up any stored state as necessary.

Visible Changes

For potential required changes to code, see the Porting Python code section.

Beyond the expanse of what importlib now exposes, there are other visible changes to import. The biggest is that sys.meta_path and sys.path_hooks now store all of the meta path finders and path entry hooks used by import. Previously the finders were implicit and hidden within the C code of import instead of being directly exposed. This means that one can now easily remove or change the order of the various finders to fit one’s needs.

Another change is that all modules have a __loader__ attribute, storing the loader used to create the module. PEP 302 has been updated to make this attribute mandatory for loaders to implement, so in the future once 3rd-party loaders have been updated people will be able to rely on the existence of the attribute. Until such time, though, import is setting the module post-load.

Loaders are also now expected to set the __package__ attribute from PEP 366. Once again, import itself is already setting this on all loaders from importlib and import itself is setting the attribute post-load.

None is now inserted into sys.path_importer_cache when no finder can be found on sys.path_hooks. Since imp.NullImporter is not directly exposed on sys.path_hooks it could no longer be relied upon to always be available to use as a value representing no finder found.

All other changes relate to semantic changes which should be taken into consideration when updating code for Python 3.3, and thus should be read about in the Porting Python code section of this document.

(Implementation by Brett Cannon)

Other Language Changes

Some smaller changes made to the core Python language are:

  • Added support for Unicode name aliases and named sequences. Both unicodedata.lookup() and '\N{...}' now resolve name aliases, and unicodedata.lookup() resolves named sequences too.

    (Contributed by Ezio Melotti in bpo-12753.)

  • Unicode database updated to UCD version 6.1.0

  • Equality comparisons on range() objects now return a result reflecting the equality of the underlying sequences generated by those range objects. (bpo-13201)

  • The count(), find(), rfind(), index() and rindex() methods of bytes and bytearray objects now accept an integer between 0 and 255 as their first argument.

    (Contributed by Petri Lehtinen in bpo-12170.)

  • The rjust(), ljust(), and center() methods of bytes and bytearray now accept a bytearray for the fill argument. (Contributed by Petri Lehtinen in bpo-12380.)

  • New methods have been added to list and bytearray: copy() and clear() (bpo-10516). Consequently, MutableSequence now also defines a clear() method (bpo-11388).

  • Raw bytes literals can now be written rb"..." as well as br"...".

    (Contributed by Antoine Pitrou in bpo-13748.)

  • dict.setdefault() now does only one lookup for the given key, making it atomic when used with built-in types.

    (Contributed by Filip Gruszczyński in