…
Pyroute2 is a pure-Python netlink library with several modules:
* generic: encode/decode netlink messages
* iproute: low-level NETLINK_ROUTE operations
* ipdb: transactional network configuration database
The library is quite young, but grows fast. Version 0.1.7 brings some
important features:
iproute
=======
* experimental support for QoS: ingress, sfq, tbf, htb, u32
A reasonable and well-documented QoS support is planned for 0.2.0, but
one can start to play with it already now. Actually, the main goal of
this project part is to get complete implementation of tcmsg, supported
by modern kernels, and make it possible to manage qdisc-related stuff
without external utilities (tc), directly communicating with the kernel.
ipdb
====
* interface create() call, that allows to create
* dummy
* bridge
* bond
* vlan interfaces
* 'ports': an ability to attach/detach ports to/from master
* different transaction models
* direct: apply changes immediately
* implicit: first change starts the transaction
* explicit: transaction should be started by begin() call
Most important is that now one can create and manage with the library
complex interfaces like bridges or bondings, and that's really simple,
e.g. bonding creation:
https://github.com/svinota/pyroute2/blob/master/examples/create_bond.py
links
=====
home: https://github.com/svinota/pyroute2
bugs: https://github.com/svinota/pyroute2/issues
pypi: https://pypi.python.org/pypi/pyroute2
docs: http://peet.spb.ru/pyroute2/
list: https://groups.google.com/d/forum/pyroute2-dev
Feedback is welcome!
--
Peter V. Saveliev
Advanced Python
===============
What: Advanced Python - Who is afraid of metaclasses?
When: July 6 - 7, 2013
Where: at EuroPython 2013, Florence, Italy
Instructor: Mike Müller (eight years of Python training experience)
Details: https://ep2013.europython.eu/conference/talks/advanced-python-2
You have intermediate Python skills and would like learn more about:
* Comprehensions
* Decorators
* Context managers
* Descriptors
* Metaclasses and
* Patterns?
Than you should attend this two-day training that provides a systematic
coverage of these topics. Useful code samples and exercises provide
hands-on learning.
We offered this training at EuroPython 2012 and PyConPL 2012 and got
very good feedback. Many of the participants understood much more of
the complex topics than they anticipated.
Our next courses:
30.05.-01.06.2013 (Katowice, Poland) Advanced Python Course (English)
03.06.-05.06.2013 (Leipzig) Einstieg in Django (German)
06.06.-08.06.2013 (Leipzig) Django für Fortgeschrittene (German)
10.06.-12.06.2013 (Leipzig) Python for Scientists and Engineers (English)
13.06.2013 (Leipzig) Fast Code with the Cython Compiler (English)
14.06.2013 (Leipzig) Fast NumPy Processing with Cython (English)
24.06.-26.06.2013 (Leipzig) Professional Testing with pytest and tox (English)
02.07.2013 (Florence, Italy) Optimization at EuroPython (English)
06.07.-07.07.2013 (Florence, Italy) Advanced Python at EuroPython (English)
09.09.-11.09.2013 (Leipzig) Twisted Training (English)
11.09.-13.09.2013 (Bologna, Italy) Python per programmatori (Italian)
12.09.-13.09.2013 (Leipzig) Content-Management mit Plone (German)
11.11.-13.11.2013 (Leipzig) Introduction to Django (English)
14.11.-16.11.2013 (Leipzig) Advanced Django (English)
30.09.-02.10.2013 (Katowice, Poland) Python for Programmers (English)
03.10.-03.10.2013 (Katowice, Poland) Advanced Python Course (English)
Hi,
I've just uploaded pypiserver 1.1.1 to the python package index.
pypiserver is a minimal PyPI compatible server. It can be used to serve
a set of packages and eggs to easy_install or pip.
pypiserver is easy to install (i.e. just 'pip install pypiserver'). It
doesn't have any external dependencies.
https://pypi.python.org/pypi/pypiserver/ should contain enough
information to easily get you started running your own PyPI server in a
few minutes.
The code is available on github: https://github.com/schmir/pypiserver
Changes in this version
-----------------------
- add 'overwrite' option to allow overwriting existing package
files (default: false)
- show names with hyphens instead of underscores on the "/simple"
listing
- make the standalone version work with jython 2.5.3
- upgrade waitress to 0.8.5 in the standalone version
- workaround broken xmlrpc api on pypi.python.org by using HTTPS
--
Cheers
Ralf
Hi All,
PyDev 2.7.5 has been released
Details on PyDev: http://pydev.org
Details on its development: http://pydev.blogspot.com
Release Highlights:
-------------------------------
* Icons in the outline are now correct.
* Fixed deadlock found on code analysis.
* Project-related error markers no longer created in the main thread.
* Showing a dialog to select template when a new module is created.
* PyUnit view output font uses the same font as the console
* New option in auto-formatting to auto-format only workspace files.
* Auto-formatting with only deleted lines no longer changes everything.
* PyUnit view orientation menu is now properly shown.
* Fixed interaction with external files on pydev package explorer.
What is PyDev?
---------------------------
PyDev is a plugin that enables users to use Eclipse for Python, Jython and
IronPython development -- making Eclipse a first class Python IDE -- It
comes with many goodies such as code completion, syntax highlighting,
syntax analysis, refactor, debug and many others.
Cheers,
--
Fabio Zadrozny
------------------------------------------------------
Software Developer
PyDev - Python Development Environment for Eclipse
http://pydev.orghttp://pydev.blogspot.com
Find a new release of python-ldap:
http://pypi.python.org/pypi/python-ldap/2.4.11
python-ldap provides an object-oriented API to access LDAP directory
servers from Python programs. It mainly wraps the OpenLDAP 2.x libs for
that purpose. Additionally it contains modules for other LDAP-related
stuff (e.g. processing LDIF, LDAP URLs and LDAPv3 schema).
Project's web site:
http://www.python-ldap.org/
Ciao, Michael.
----------------------------------------------------------------
Released 2.4.11 2013-05-27
Changes since 2.4.10:
Lib/
* ldap.controls.DecodeControlTuples() now simply ignores
PyAsn1Error exception raised during decoding malformed
response control values in case of non-critical controls.
* ldif.LDIFWriter.unparse() does not simply skip empty
records anymore.
PyModel v 1.0 is released.
PyModel is a model-based testing framework for Python. In model-based
testing, you code a model that can generate as many test cases as
needed; the model also checks the test outcomes. In the samples
included with PyModel, there are models and test scripts for network
sockets, a communication protocol, embedded controllers, some data
structures, a multithreaded application, and a web application.
PyModel also includes an analyzer for validating models, visualizing
their behavior, and checking their safety properties.
Earlier public releases were versions 0.80 in Jan 2010, 0.85 in Mar
2010, and 0.90 in July 2011. Since July 2011 ongoing work has been
available at GitHub: https://github.com/jon-jacky/PyModel/ PyModel can
also be downloaded from PyPI http://pypi.python.org/pypi/PyModel or
the author's web page at http://staff.washington.edu/jon/pymodel/www/
This release is called version 1.0 because it includes all of the
features considered in the original project plan. (Development and
maintenance will continue beyond this release.)
Version 1.0 adds new functionality:
- The PyModel Tester pmt supports observable actions and asynchronous
steppers, to handle event-driven systems and nondeterminism.
- The PyModel Analyzer pma performs safety analysis by checking state
invariants. The PyModel Graphics program pmg indicates unsafe states
in the generated graphs.
- The new PyModel Viewer command pmv combines the functionality of the
PyModel Analyzer pma, the PyModel Graphics program pmg, and the
Graphviz dot program in a single command, for convenience and
brevity.
- The options to include or exclude actions, -a and -e, are now
supported for FSMs and TestSuites as well as Model Programs, so you
can use the command line to select which actions to include in your
analyses or tests, even when you compose model programs with
scenario machines.
- The tester pmt provides a timeout option to specify that the test
fails if the implementation does not respond within a given
deadline. (This option might not work on Windows.)
- The PyModel programs pma, pmg, pmt, and pmv can be run from the
command line without the .py extension, like any other command.
You can just type pmt ... , you no longer have to type pmt.py ...
- The regression testing command tdiff replaces clogdiff. It works
the same - this is just a renaming. The clogdiff command is
retained in this version for backward compatibility, but is now
deprecated.
- The new command tclean removes test output files from the
current directory.
- The revised setup.py now supports the install argument, to
optionally install the PyModel python modules and commands in system
directories. Now PyModel can be installed using distutils
(... setup.py install ...) or pip.
Version 1.0 adds a new sample and revises all the others:
- The completely rewritten Socket sample includes new asynchronous
steppers (test harnesses) that show how to support asynchrony and
nondeterminism using the select function, or alternatively, using
threads. The Socket sample also includes new simulators that can
optionally replace the the Python standard library socket and select
modules, to demonstrate greater nondeterminism and transmission
errors.
- The new safety sample demonstrates state invariants and safety analysis.
- There are new fsmpy/ and svg/ directories in each sample that
contain FSM modules and SVG graphics files generated by the commands
in the test scripts.
- Many sample test scripts (test*.py modules) have been revised and
the corresponding reference output (*.ref files) has been
regenerated.
Version 1.0 adds much new documentation and revises the rest:
- There are new README.md (Markdown format) files in PyModel in most
top-level directories below PyModel.
- The new README.md in the samples directory briefly describes every
sample. The new README.md in each sample directory explains that
sample in more detail, and describes every file in that sample.
- The documentation in the notes directory has been expanded and
brought up to date. There are new and revised .txt files. Some .txt
files have been replaced by .md (Markdown format) files.
- The web pages in the www directory have been expanded and brought up
to date. The content in these pages is drawn from .md files
and .txt files in other PyModel directories.
Version 1.0 reorganizes some code and directory structure:
- There is a new bin directory for commands and scripts, separated
from the pymodel directory for Python modules.
- There is a new model.py module that contains the Model base class
for the ModelProgram, FSM, TestSuite classes.
Version 1.0 makes some bug fixes:
- The programs no longer crash when a parameter generator is missing.
Now they issue a helpful error message and exit.
- The pmt program cancels the timeout when a timeout was requested but
did not expire.
- When models are composed, omitted arguments are handled correctly
(usually, as "match any" indicators).
- The pmt -o offline test generator option works.
Hi all,
I am pleased to announce that four new versions of WinPython have been
released yesterday with Python 2.7.5 and 3.3.2, 32 and 64 bits. Many
packages have been added or upgraded.
Special thanks to Christoph Gohlke for building most of the binary packages
bundled in WinPython.
WinPython is a free open-source portable distribution of Python
for Windows, designed for scientists.
It is a full-featured (see
http://code.google.com/p/winpython/wiki/PackageIndex)
Python-based scientific environment:
* Designed for scientists (thanks to the integrated libraries
NumPy, SciPy, Matplotlib, guiqwt, etc.:
* Regular *scientific users*: interactive data processing
and visualization using Python with Spyder
* *Advanced scientific users and software developers*:
Python applications development with Spyder, version control with
Mercurial and other development tools (like gettext)
* *Portable*: preconfigured, it should run out of the box on any machine
under Windows (without any installation requirements) and the folder
containing WinPython can be moved to any location (local, network or
removable drive)
* *Flexible*: one can install (or should I write "use" as it's portable)
as many WinPython versions as necessary (like isolated and self-consistent
environments), even if those versions are running different versions of
Python (2.7, 3.x in the near future) or different architectures (32bit or
64bit) on the same machine
* *Customizable*: using the integrated package manager (wppm,
as WinPython Package Manager), it's possible to install, uninstall
or upgrade Python packages (see
http://code.google.com/p/winpython/wiki/WPPM for
more details on supported package formats).
*WinPython is not an attempt to replace Python(x,y)*, this is
just something different (see
http://code.google.com/p/winpython/wiki/Roadmap): more flexible, easier to
maintain, movable and less invasive for the OS, but certainly less
user-friendly, with less packages/contents and without any integration to
Windows explorer [*].
[*] Actually there is an optional integration into Windows
explorer, providing the same features as the official Python installer
regarding file associations and context menu entry (this option may be
activated through the WinPython Control Panel), and adding shortcuts to
Windows Start menu.
Enjoy!
-Pierre
===========================
Announcing python-blosc 1.1
===========================
What is it?
===========
python-blosc (http://blosc.pydata.org/) is a Python wrapper for the
Blosc compression library.
Blosc (http://blosc.org) is a high performance compressor optimized for
binary data. It has been designed to transmit data to the processor
cache faster than the traditional, non-compressed, direct memory fetch
approach via a memcpy() OS call. Whether this is achieved or not
depends of the data compressibility, the number of cores in the system,
and other factors. See a series of benchmarks conducted for many
different systems: http://blosc.org/trac/wiki/SyntheticBenchmarks.
Blosc works well for compressing numerical arrays that contains data
with relatively low entropy, like sparse data, time series, grids with
regular-spaced values, etc.
There is also a handy command line for Blosc called Bloscpack
(https://github.com/esc/bloscpack) that allows you to compress large
binary datafiles on-disk. Although the format for Bloscpack has not
stabilized yet, it allows you to effectively use Blosc from your
favorite shell.
What is new?
============
- Added new `compress_ptr` and `decompress_ptr` functions that allows to
compress and decompress from/to a data pointer, avoiding an
itermediate copy for maximum speed. Be careful, as these are low
level calls, and user must make sure that the pointer data area is
safe.
- Since Blosc (the C library) already supports to be installed as an
standalone library (via cmake), it is also possible to link
python-blosc against a system Blosc library.
- The Python calls to Blosc are now thread-safe (another consequence of
recent Blosc library supporting this at C level).
- Many checks on types and ranges of values have been added. Most of
the calls will now complain when passed the wrong values.
- Docstrings are much improved. Also, Sphinx-based docs are available
now.
Many thanks to Valentin Hänel for his impressive work for this release.
For more info, you can see the release notes in:
https://github.com/FrancescAlted/python-blosc/wiki/Release-notes
More docs and examples are available in the documentation site:
http://blosc.pydata.org
Installing
==========
python-blosc is in PyPI repository, so installing it is easy:
$ pip install -U blosc # yes, you should omit the python- prefix
Download sources
================
The sources are managed through github services at:
http://github.com/FrancescAlted/python-blosc
Documentation
=============
There is Sphinx-based documentation site at:
http://blosc.pydata.org/
Mailing list
============
There is an official mailing list for Blosc at:
blosc(a)googlegroups.com
http://groups.google.es/group/blosc
Licenses
========
Both Blosc and its Python wrapper are distributed using the MIT license.
See:
https://github.com/FrancescAlted/python-blosc/blob/master/LICENSES
for more details.
Enjoy!
--
Francesc Alted
