Free python extension module software for linux

Python config module allows a hierarchical configuration scheme with support for mappings and sequences, cross-references between one part of the configuration and another, the ability to flexibly access real Python objects without full-blown eval(), an include facility, simple expression evaluation, and the ability to change, save, cascade, and merge configurations.
It interfaces easily with environment variables and command line options. Python config module has been developed on Python 2.3, but should work on version 2.2 or greater.
Usage
The simplest scenario is, of course, "Hello, world". Lets look at a very simple configuration file simple.cfg where a message to be printed is configured:
# The message to print (this is a comment)
message: Hello, world!
and the program which uses it:
from config import Config
# You can pass any file-like object; if it has a name attribute,
# that name is used when file format error messages are printed
f = file(simple.cfg)
cfg = Config(f)
print cfg.message
which results in the expected:
Hello, world!
A configuration file is, at the top level, a list of key-value pairs. Each value, as well see later, can be a sequence or a mapping, and these can be nested without any practical limit.
In addition to attribute access (cfg.message in the example above), you can also access a value in the configuration using the getByPath method of a configuration: cfg.getByPath(message) would be equivalent. The parameter passed to getByPath is the path of the required value. The getByPath method is useful for when the path is variable. It could even be read from a configuration.
There is also a get method which acts like the dictionary method of the same name - you can pass a default value which is returned if the value is not found in the configuration. The get method works with dictionary keys or attribute names, rather than paths. Hence, you may call cfg.getByPath(a.b) which is equivalent to cfg.a.b, or you can call cfg.a.get(b, 1234) which will return cfg.a.b if it is defined, and 1234 otherwise.
Enhancements:
- This release makes classes derive from an object (previously, they were old-style classes).
- ConfigMerger has been changed to use a more flexible merge strategy.
- Multi-line strings (using """ or ) are now supported.
- A typo involving raising a ConfigError was fixed.

The Python logging module implements a standard logging system for Python programs. It was strongly influenced by log4j from the Apache project.

As this package is included in versions 2.3 and later, only users of earlier versions of Python would need to install this module.

There was a need for a standard logging system in Python, as comprehensively documented in PEP 282 and enthusiastically endorsed by the BDFL in the Parade of the PEPs.

By a happy coincidence, the package described here was already in development and fairly close in intent and design to the description in the aforementioned PEP, borrowing as it did heavily from JSR-47 (now JDK 1.4s java.util.logging package) and log4j.

This page describes it in more detail. As I have tweaked the package to meet comments on PEP 282, I have structured this page in the same way as the original PEP.

This package is now part of Python 2.3, but if you have an earlier version of Python, you can download the package from here and use it with Python versions between 1.5.2 and 2.2.x.

Python XHTML is a simple Python module for the generation of valid XHTML.

ToDo:

* include tests for all methods in xhtml_test.py
* ensure that all text that is added to the document is xml safe
* include methods for added w3.org validation link buttons
* complete support for XHTML 1.1 specification

Python OpenID is a set of Python packages that support use of the OpenID decentralized identity system in your applications.
Python OpenID can be used to enable single sign-on for your Web sites or for running an OpenID server. Example code is supplied and a variety of storage back-ends are supported.
Main features:
- Refined and easy-to-use API.
- Extensive documentation.
- Many storage implemetations including file-based, SQL, and memcached.
- Simple examples to help you get started.
- Licensed under the LGPL.
Enhancements:
- This release includes support for Yadis discovery of OpenID servers and OpenID extensions.

One of the features of Python that makes it so powerful is the ability to take existing libraries, written in C or C++, and make them available as Python extension modules. Such extension modules are often called bindings for the library.
SIP is a tool that makes it very easy to create Python bindings for C and C++ libraries. Python-SIP was originally developed to create PyQt, the Python bindings for the Qt toolkit, but can be used to create bindings for any C or C++ library.
SIP comprises a code generator and a Python module. The code generator processes a set of specification files and generates C or C++ code which is then compiled to create the bindings extension module. The SIP Python module provides support functions to the automatically generated code.
The specification files contains a description of the interface of the C or C++ library, i.e. the classes, methods, functions and variables. The format of a specification file is almost identical to a C or C++ header file, so much so that the easiest way of creating a specification file is to edit the corresponding header file.
SIP makes it easy to exploit existing C or C++ libraries in a productive interpretive programming environment. SIP also makes it easy to take a Python application (maybe a prototype) and selectively implement parts of the application (maybe for performance reasons) in C or C++.
Enhancements:
- This release adds support for consolidated and composite modules.
- It adds support for pickling classes and enums.