Features new to this version:
* bar charts will be produced (requires gdchart module. See Docs on Scratchy
website for more information)
* a main summary page is now created for easier navigation
* some bug fixes
Scratchy is a set of scripts to parse Apache web server log files and
extract useful information. From this data, Scratchy will create HTML
reports so that website administrators can easily view the information
and determine trends and their typical audience.
Scratchy began as a proof-of-concept which allowed me to compile stats
about my personal website. As time progressed I continually added
features and improvements and I felt that it was now at a point that
it would be useful to others.
Well, the name of the project of course comes from the Simpsons "Itchy
and Scratchy Show". The functionality that the project aims to supply
is a complete log parsing and report generating tool. Also, there
seemed to be a need for such a project in Python. I have seen some
other Apache log parsers but they were developed in other languages
(such as Perl, C, etc). One goal of this project is for it to be
extensible, to that tune, most of the report appearance can be easily
modified by tweaking a single config file.
What information does Scratchy report?
# Accessed web pages
# hosts accessing your website
# operating systems
# search engines
# file types accessed
# a trace of pages accessed by each ip address (if enabled).
pyUnRAR is a ctypes based wrapper around the free UnRAR.dll. It enables
reading and unpacking of archives created with the RAR/WinRAR archivers.
There is a low-level interface which is very similar to the C interface
provided by UnRAR.dll. There is also a high-level interface which makes
some common operations easier.
pyUnRAR requires Microsoft Windows, Python 2.2 or higher, and ctypes
pyUnRAR is available at: http://www.averdevelopment.com/python/
This is the initial public release of pyUnRAR. I'd appreciate any
dnspython 1.0.0, the first non-development version of dnspython, has been
released. Here's the README file:
dnspython is a DNS toolkit for Python. It supports almost all record
types. It can be used for queries, zone transfers, and dynamic
updates. It supports TSIG authenticated messages and EDNS0.
dnspython provides both high and low level access to DNS. The high
level classes perform queries for data of a given name, type, and
class, and return an answer set. The low level classes allow direct
manipulation of DNS zones, messages, names, and records.
To see a few of the ways dnspython can be used, look in the examples/
dnspython originated at Nominum where it was developed to facilitate
the testing of DNS software. Nominum has generously allowed it to be
open sourced under a BSD-style license, and helps support its future
development by continuing to employ the author :).
ABOUT THIS RELEASE
This is dnspython 1.0.0, the first non-development version of
New in this release:
The Name and Rdata classes now use rich comparisons.
If a resolver's cache attribute is set to an
instance of dns.resolver.Cache, the resolver
will cache an answer for the DNS lifetime of the
dns.resolver.Answer instances now have an "expiration"
This release fixes all known bugs from 1.0.0b3.
See the ChangeLog file for more detailed information on changes since
the prior release.
Python 2.2 or later.
To build and install dnspython, type
python setup.py install
For the latest in releases, documentation, and information, visit the
dnspython home page at
Documentation is sparse at the moment. Use pydoc, or read the HTML
documentation at the dnspython home page, or download the HTML
Bug reports may be sent to bugs(a)dnspython.org
A number of mailing lists are available. Visit the dnspython home
page to subscribe or unsubscribe.
Kits are now signed. Here's fingerprint info for the signing key:
pub 1024D/CD706369 2003-06-30 Bob Halley <halley(a)dnspython.org>
Key fingerprint = 3E0C 63DB 06DE BFD9 B2FE A75B 75E0 3544 CD70 6369
You can get the public key from a keyserver, or from
Python 2.3b2 is the second beta release of Python 2.3. There have be a
slew of fixes since the first beta, and a few new "features". Our goal
is to have a final Python 2.3 release by early August, so we encourage
lots of testing for this beta. Highlights since beta 1 include:
- IDLEfork has been merged in and now replaces the old IDLE.
- The Windows installer now ships with Tcl/Tk 8.4.3.
- list.index() has grown optional `start' and `end' arguments.
- A new C-only API function PyThreadState_SetAsyncExc() which can be
used to interrupt threads by sending them exceptions.
- Python programs can enter the interactive prompt at program exit by
setting the PYTHONINSPECT environment variable.
- Many new doctest improvements, including the ability to write doctest
based unit tests.
- New and improved documentation for writing new types in C that
participate in cyclic garbage collection.
There is at least one known bug: we have seen crashes on both Windows
and Linux with certain interactions between test_logging and
test_bsddb3. We intend to fix this for the next release.
For more highlights, see http://www.python.org/2.3/highlights.html
Other new stuff since Python 2.2:
- Many new and improved library modules, e.g. sets, heapq, datetime,
textwrap, optparse, logging, bsddb, bz2, tarfile,
ossaudiodev, and a new random number generator based on the highly
acclaimed Mersenne Twister algorithm (with a period of 2**19937-1!).
- New builtin enumerate(): an iterator yielding (index, item) pairs.
- Extended slices, e.g. "hello"[::-1] returns "olleh".
- Universal newlines mode for reading files (converts \r, \n and \r\n
all into \n).
- Source code encoding declarations. (PEP 263)
- Import from zip files. (PEP 273 and PEP 302)
- FutureWarning issued for "unsigned" operations on ints. (PEP 237)
- Faster list.sort() is now stable.
- Unicode filenames on Windows.
- Karatsuba long multiplication (running time O(N**1.58) instead of
If you have an important Python application, we strongly recommend that
you try it out with a beta release and report any incompatibilities or
other problems you may encounter, so that they can be fixed before the
final release. To report problems, use the SourceForge bug tracker:
Pyrex 0.8.1 is now available:
This release fixes some breakage in 0.8 that resulted in
mangled names being used for some declarations in external
The distutils extension has also been modified slightly
to stop it from attempting to compile the generated C
file if the Pyrex compiler reports errors.
What is Pyrex?
Pyrex is a new language for writing Python extension modules.
It lets you freely mix operations on Python and C data, with
all Python reference counting and error checking handled
IMPORTANT: This release includes security updates to twisted.web.
It is strongly recommended that you upgrade to this version of
Twisted is an event-driven networking framework for server and client
For more information, visit http://www.twistedmatrix.com, join the list
visit us on #twisted at irc.freenode.net.
What's New in 1.0.6
- Security fixes for twisted.web.
- Cred, Twisted's unified authentication and authorization framework,
was rewritten. While still not stable, the new system is far superior
and developers are encouraged to start using it.
- Flow, an utility page for integrating asynchronous control flow with
generators and iterators.
- Many improvements to the UDP subsystem.
- Many Windows-specific networking bug fixes.
- Cleanups in Woven - outputted HTML no longer includes attributes used
by templating, removed fake-acquisition for templates.
- Support switching over to TLS from TCP connections (useful for e.g.
STARTTLS in SMTP.)
- Improvements to the mail protocols and infrastructure.
- Fixed 2.2.0 compatibility.
- Index support for Lore.
- Bug fixes, documentation updates and small feature improvements.
What is Twisted?
Twisted is an event-driven framework for building networked clients and
servers. It contains a powerful and simple networking core, a
full-featured suite of interoperable protocols, among them a powerful
web server and applications framework.
Twisted supports many event loops for both server apps and GUI
integration on the client side, including:
- Win32 events, including GUI support
- GTK+ 2
Twisted can run protocols over TCP, SSL, UDP, multicast, Unix sockets
and subprocesses. It also includes scheduling support, threading
integration, RDBMS event loop integration and other basic requirements
for networked applications.
Also included are implementations of many protocols. In some cases this
includes complete frameworks providing facilities on top of the base
- HTTP, including a complete web framework
- SOAP server framework
- NNTP and complete NNTP server framework
- SOCKSv4 (server only)
- AOL's instant messaging TOC
- MSN messaging
- OSCAR, used by AOL IM as well as ICQ (client only)
- MouseMan serial mice, and GPS devices
- Twisted Perspective Broker, a remote object protocol
Introducing the first release of TOGA
TOGA stands for "Timetables Optimised with Genetic Algorithms".
It is ultimately intended as an application for non-technical users
which automatically generates timetables for schools and institutions.
This version provides a framework for future development. It is a
fully-functioning command line application written in the Python
programming language. It is extensively documented, and accompanied by
a suite of unit tests.
The code is released under the GNU Public License. We are actively
seeking feedback from Python programmers, workers in Evolutionary
Algorithms, and potential users.
* The main project page is at:
* There is a more detailed introduction to TOGA here:
* Future plans for the code:
* Download the source from:
Future announcements about TOGA will be made in
comp.lang.python.announce. Please send an e-mail to
the "reply-to" address to be alerted to new developments.
I've been postponing this announcement because the registration page
isn't active yet. It's getting late though, and I thought I'd at least
let you know SciPy '03 is happening. I'll repost when registration is
The 2nd Annual Python for Scientific Computing Workshop
CalTech, Pasadena, CA
September 11-12, 2003
This workshop provides a unique opportunity to learn and affect what is
happening in the realm of scientific computing with Python. Attendees
will have the opportunity to review the available tools and how they
apply to specific problems. By providing a forum for developers to share
their Python expertise with the wider industrial, academic, and research
communities, this workshop will foster collaboration and facilitate the
sharing of software components, techniques and a vision for high level
language use in scientific computing.
The cost of the workshop is $100.00 and includes 2 breakfasts and 2
lunches on Sept. 11th and 12th, one dinner on Sept. 11th, and snacks
during breaks. Online registration is not available yet, but will be
We would like to have a wide variety of presenters this year. If you
have a paper you would like to present, please contact
Discussion about the conference may be directed to the SciPy-user
Mailing list page: http://www.scipy.org/MailList
Mailinbg list address: scipy-user(a)scipy.org
Please forward this announcement to anyone/list that might be
The National Biomedical Computation Resource (NBCR, SDSC, San Diego, CA)
The mission of the National Biomedical Computation Resource at the San
Supercomputer Center is to conduct, catalyze, and enable biomedical
research by harnessing advanced computational technology.
The Center for Advanced Computing Research (CACR, CalTech, Pasadena, CA)
CACR is dedicated to the pursuit of excellence in the field of
high-performance computing, communication, and data engineering. Major
activities include carrying out large-scale scientific and engineering
applications on parallel supercomputers and coordinating collaborative
research projects on high-speed network technologies, distributed
computing and database methodologies, and related topics. Our goal is to
help further the state of the art in scientific computing.
Enthought, Inc. (Austin, TX)
Enthought, Inc. provides scientific and business computing solutions
through software development, consulting and training.
eric jones 515 Congress Ave
www.enthought.com Suite 1614
512 536-1057 Austin, Tx 78701
ctypes is a ffi (Foreign Function Interface) package for Python.
It allows to call functions exposed from dlls/shared libraries and
has extensive facilities to create, access and manipulate simple
and complicated C data types transparently from Python - in other
words: wrap libraries in pure Python.
ctypes runs on Windows, MacOS X, Linux, Solaris, the latter three
require that your machine is supported by libffi.
On Windows, ctypes contains (the beginning of) a COM framework
mainly targetted to use and implement custom COM interfaces.
Changes in version 0.6.2
Fixed a bug which prevented callback functions to return data types
other than integers. They can now also return pointers, floats, and
It is now possible to pass structures and unions to function calls
*by value*. Currently this works only on Windows.
A lot of changes to the COM package, but all this is still work in
progress and unstable, and it has to be properly documented.