Python 2.6 的新功能

作者 :

A.M. Kuchling (amk at amk.ca)

This article explains the new features in Python 2.6, released on October 1, 2008. The release schedule is described in PEP 361 .

The major theme of Python 2.6 is preparing the migration path to Python 3.0, a major redesign of the language. Whenever possible, Python 2.6 incorporates new features and syntax from 3.0 while remaining compatible with existing code by not removing older features or syntax. When it’s not possible to do that, Python 2.6 tries to do what it can, adding compatibility functions in a future_builtins module and a -3 switch to warn about usages that will become unsupported in 3.0.

Some significant new packages have been added to the standard library, such as the multiprocessing and json modules, but there aren’t many new features that aren’t related to Python 3.0 in some way.

Python 2.6 also sees a number of improvements and bugfixes throughout the source. A search through the change logs finds there were 259 patches applied and 612 bugs fixed between Python 2.5 and 2.6. Both figures are likely to be underestimates.

This article doesn’t attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.6. If you want to understand the rationale for the design and implementation, refer to the PEP for a particular new feature. Whenever possible, “What’s New in Python” links to the bug/patch item for each change.

Python 3.0

The development cycle for Python versions 2.6 and 3.0 was synchronized, with the alpha and beta releases for both versions being made on the same days. The development of 3.0 has influenced many features in 2.6.

Python 3.0 is a far-ranging redesign of Python that breaks compatibility with the 2.x series. This means that existing Python code will need some conversion in order to run on Python 3.0. However, not all the changes in 3.0 necessarily break compatibility. In cases where new features won’t cause existing code to break, they’ve been backported to 2.6 and are described in this document in the appropriate place. Some of the 3.0-derived features are:

  • A __complex__() method for converting objects to a complex number.

  • Alternate syntax for catching exceptions: except TypeError as exc .

  • The addition of functools.reduce() as a synonym for the built-in reduce() 函数。

Python 3.0 adds several new built-in functions and changes the semantics of some existing builtins. Functions that are new in 3.0 such as bin() have simply been added to Python 2.6, but existing builtins haven’t been changed; instead, the future_builtins module has versions with the new 3.0 semantics. Code written to be compatible with 3.0 can do from future_builtins import hex, map as necessary.

A new command-line switch, -3 , enables warnings about features that will be removed in Python 3.0. You can run code with this switch to see how much work will be necessary to port code to 3.0. The value of this switch is available to Python code as the boolean variable sys.py3kwarning , and to C extension code as Py_Py3kWarningFlag .

另请参阅

The 3 xxx series of PEPs, which contains proposals for Python 3.0. PEP 3000 describes the development process for Python 3.0. Start with PEP 3100 that describes the general goals for Python 3.0, and then explore the higher-numbered PEPs that propose specific features.

Changes to the Development Process

While 2.6 was being developed, the Python development process underwent two significant changes: we switched from SourceForge’s issue tracker to a customized Roundup installation, and the documentation was converted from LaTeX to reStructuredText.

New Issue Tracker: Roundup

For a long time, the Python developers had been growing increasingly annoyed by SourceForge’s bug tracker. SourceForge’s hosted solution doesn’t permit much customization; for example, it wasn’t possible to customize the life cycle of issues.

The infrastructure committee of the Python Software Foundation therefore posted a call for issue trackers, asking volunteers to set up different products and import some of the bugs and patches from SourceForge. Four different trackers were examined: Jira , Launchpad , Roundup ,和 Trac . The committee eventually settled on Jira and Roundup as the two candidates. Jira is a commercial product that offers no-cost hosted instances to free-software projects; Roundup is an open-source project that requires volunteers to administer it and a server to host it.

After posting a call for volunteers, a new Roundup installation was set up at https://bugs.python.org . One installation of Roundup can host multiple trackers, and this server now also hosts issue trackers for Jython and for the Python web site. It will surely find other uses in the future. Where possible, this edition of “What’s New in Python” links to the bug/patch item for each change.

Hosting of the Python bug tracker is kindly provided by Upfront Systems of Stellenbosch, South Africa. Martin von Löwis put a lot of effort into importing existing bugs and patches from SourceForge; his scripts for this import operation are at https://svn.python.org/view/tracker/importer/ and may be useful to other projects wishing to move from SourceForge to Roundup.

另请参阅

https://bugs.python.org

The Python bug tracker.

https://bugs.jython.org :

The Jython bug tracker.

https://roundup.sourceforge.io/

Roundup downloads and documentation.

https://svn.python.org/view/tracker/importer/

Martin von Löwis’s conversion scripts.

New Documentation Format: reStructuredText Using Sphinx

The Python documentation was written using LaTeX since the project started around 1989. In the 1980s and early 1990s, most documentation was printed out for later study, not viewed online. LaTeX was widely used because it provided attractive printed output while remaining straightforward to write once the basic rules of the markup were learned.

Today LaTeX is still used for writing publications destined for printing, but the landscape for programming tools has shifted. We no longer print out reams of documentation; instead, we browse through it online and HTML has become the most important format to support. Unfortunately, converting LaTeX to HTML is fairly complicated and Fred L. Drake Jr., the long-time Python documentation editor, spent a lot of time maintaining the conversion process. Occasionally people would suggest converting the documentation into SGML and later XML, but performing a good conversion is a major task and no one ever committed the time required to finish the job.

During the 2.6 development cycle, Georg Brandl put a lot of effort into building a new toolchain for processing the documentation. The resulting package is called Sphinx, and is available from https://www.sphinx-doc.org/ .

Sphinx concentrates on HTML output, producing attractively styled and modern HTML; printed output is still supported through conversion to LaTeX. The input format is reStructuredText, a markup syntax supporting custom extensions and directives that is commonly used in the Python community.

Sphinx is a standalone package that can be used for writing, and almost two dozen other projects ( listed on the Sphinx web site ) have adopted Sphinx as their documentation tool.

另请参阅

Documenting Python

Describes how to write for Python’s documentation.

Sphinx

Documentation and code for the Sphinx toolchain.

Docutils

The underlying reStructuredText parser and toolset.

PEP 343: The ‘with’ statement

The previous version, Python 2.5, added the ‘ with ’ statement as an optional feature, to be enabled by a from __future__ import with_statement directive. In 2.6 the statement no longer needs to be specially enabled; this means that with is now always a keyword. The rest of this section is a copy of the corresponding section from the “What’s New in Python 2.5” document; if you’re familiar with the ‘ with ’ statement from Python 2.5, you can skip this section.

The ‘ with ’ statement clarifies code that previously would use try...finally blocks to ensure that clean-up code is executed. In this section, I’ll discuss the statement as it will commonly be used. In the next section, I’ll examine the implementation details and show how to write objects for use with this statement.

The ‘ with ’ statement is a control-flow structure whose basic structure is:

with expression [as variable]:
    with-block