We are excited to announce the release of version *0.8.2* of Bokeh, an
interactive web plotting library for Python... and other languages! This
minor release includes some refactoring, many bug fixes and nice improved
* Collect implicit interfaces into a single bokeh.io module
* Fixed notebook css issues
* Update notebooks to be compatible with IPython 3.0
* Easy bokeh applet generation using the simpleapp module
* Develop installation enhancements
* A new User guide intro and some other docs styling enhancements
* Some other minor examples bugfixes
See the CHANGELOG for full details.
If you are using Anaconda/miniconda, you can install it with conda:
*conda install -c bokeh bokeh*
*Note*: please check that we have added the *-c bokeh* subcommand which
points to the main channel of the Binstar bokeh user.
Additionally, this release will be available on the regular repo in a week
If you want to avoid the *-c bokeh* subcommand you can add this channel to
your *.condarc* file with:
*conda config --add channels bokeh*
and then you will be able to just use the original command:
*conda install bokeh*
Alternatively, you can install with pip:
*pip install bokeh*
Developer builds are also now made available to get features in the hands
of interested users more quickly. See the Developer Builds section in the
documentation for more details.
Finally, BokehJS is also installable with the Node Package Manager at
Issues, enhancement requests, and pull requests can be made on the Bokeh
Github page: https://github.com/bokeh/bokeh
Questions can be directed to the Bokeh mailing list: bokeh(a)continuum.io
Trac 1.1.4 Released
Trac 1.1.4 continues the 1.1.x development line
leading to 1.2 with some new features and a few
Note that the 1.1.x releases are "stable" and
tested snapshots of the trunk. They can be seen
as sub-milestones on the road towards Trac 1.2. As
opposed to maintenance releases, *we offer no
guarantees on feature and API compatibility from
one 1.1.x release to the next*.
However, by following 1.1.x you get a chance to
use new features earlier, and therefore be able to
contribute feedback when things are still in flux.
It's also less risky than just getting the latest
trunk, as we won't cut a 1.1.x release in the middle
of a series of changes (though we had and still intend
to have a good record of keeping things always working
The intended audience are therefore enthusiast Trac
users and Trac plugin developers. These packages should
*not* be integrated in distributions, for example.
Here are a few highlights:
- Performance improvements with MySQL/MariaDB (#3676).
- Click on //Permissions// Admin page table row toggles
all checkboxes in the row (#11417).
- Configuration sections are written to trac.ini when
enabling a component through TracAdmin or the web
administration module (#11437).
- Subscription rules can be reordered by drag and drop
Besides the few issues listed here, the fixes made for
1.0.4 and 1.0.5 are also included.
You can find all the detailed release notes at:
- The Trac Team http://trac.edgewall.org/
eGenix.com pyOpenSSL Distribution
An easy-to-install and easy-to-use distribution
of the pyOpenSSL Python interface for OpenSSL -
available for Windows, Mac OS X and Unix platforms
This announcement is also available on our web-site for online reading:
The eGenix.com pyOpenSSL Distribution includes everything you need to
get started with SSL in Python.
It comes with an easy-to-use installer that includes the most recent
OpenSSL library versions in pre-compiled form, making your application
independent of OS provided OpenSSL libraries:
pyOpenSSL is an open-source Python add-on that allows writing SSL/TLS-
aware network applications as well as certificate management tools:
OpenSSL is an open-source implementation of the SSL/TLS protocol:
This new release of the eGenix.com pyOpenSSL Distribution includes the
New in eGenix pyOpenSSL
* Added FreeBSD as supported platform.
* Updated the Mozilla CA root bundle to version 2015-02-19.
New in OpenSSL
* Updated included OpenSSL libraries from OpenSSL 1.0.1k to
We had skipped OpenSSL 1.0.1l, since the 1.0.1l release
only included a patch for Windows we had already included in our
0.13.7 release. See https://www.openssl.org/news/secadv_20150319.txt
for a complete list of changes. The following fixes are relevant for
- CVE-2015-0286: Segmentation fault in ASN1_TYPE_cmp.
- CVE-2015-0287: ASN.1 structure reuse memory corruption.
- CVE-2015-0289: PKCS#7 NULL pointer dereference.
- CVE-2015-0292: A vulnerability existed in previous versions of
OpenSSL related to the processing of base64 encoded data. Any
code path that reads base64 data from an untrusted source could
be affected (such as the PEM processing routines). Already fixed
in OpenSSL 1.0.1h, but wasn't listed, so repeated here for
- CVE-2015-0293: Denial-of-Service (DoS) via reachable assert in
- CVE-2015-0209: Use After Free following d2i_ECPrivatekey error. A
malformed EC private key file consumed via the d2i_ECPrivateKey
function could cause a use after free condition.
* The FREAK Attack (CVE-2015-0204) patch was already available in our
last release with OpenSSL 1.0.1k.
Please see the product changelog for the full set of changes:
pyOpenSSL / OpenSSL Binaries Included
In addition to providing sources, we make binaries available that
include both pyOpenSSL and the necessary OpenSSL libraries for all
supported platforms: Windows, Linux, Mac OS X and now FreeBSD, for x86
To simplify installation, we have uploaded a web installer to PyPI
which will automatically choose the right binary for your platform, so
pip install egenix-pyopenssl
will get you the package with OpenSSL libraries installed. Please see
our installation instructions for details:
We have also added .egg-file distribution versions of our eGenix.com
pyOpenSSL Distribution for Windows, Linux and Mac OS X to the
available download options. These make setups using e.g. zc.buildout
and other egg-file based installers a lot easier.
The download archives and instructions for installing the package can
be found at:
Before installing this version of pyOpenSSL, please make sure that
you uninstall any previously installed pyOpenSSL version. Otherwise,
you could end up not using the included OpenSSL libs.
Commercial support for these packages is available from eGenix.com.
for details about our support offerings.
For more information about the eGenix pyOpenSSL Distribution, licensing
and download instructions, please visit our web-site or write to
Professional Python Services directly from the Source (#1, Mar 24 2015)
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>>> mxODBC Plone/Zope Database Adapter ... http://zope.egenix.com/
>>> mxODBC, mxDateTime, mxTextTools ... http://python.egenix.com/
2015-03-12: Released mxODBC 3.3.2 ... http://egenix.com/go71
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eGenix.com Software, Skills and Services GmbH Pastor-Loeh-Str.48
D-40764 Langenfeld, Germany. CEO Dipl.-Math. Marc-Andre Lemburg
Registered at Amtsgericht Duesseldorf: HRB 46611
Wingware has released version 5.1.3 of Wing IDE, our cross-platform
integrated development environment for the Python programming language.
Wing IDE features a professional code editor with vi, emacs, visual
studio, and other key bindings, auto-completion, call tips,
context-sensitive auto-editing, goto-definition, find uses, refactoring,
a powerful debugger, version control, unit testing, search, project
management, and many other features.
This release includes the following improvements:
Support running and debugging pytest unit tests
Allow debugging Flask with auto-reload enabled
Keep matplotlib plots active in Debug Probe also when using MacOSX
Ability to send NUL and EOF to the shells and debug I/O
Several improvements to snippets, auto-invocation, and recursive
Fix several problems in multi-process debugging
Improved and optimized auto-conversion of indents on paste
Fix scraping Python 3 extension modules
Correct vi mode register behavior
Fix auto-scrolling and text encoding in Debug I/O
Improve debugging recursion limit exceptions
About 30 other bug fixes and improvements
For details see http://wingware.com/news/2015-03-20 and
What's New in Wing 5.1:
Wing IDE 5.1 adds multi-process and child process debugging, syntax
highlighting in the shells, support for pytest, persistent time-stamped
unit test results, auto-conversion of indents on paste, an XCode
keyboard personality, support for Flask, Django 1.7, and recent Google
App Engine versions, improved auto-completion for PyQt, recursive
snippet invocation, and many other minor features and improvements.
Free trial: http://wingware.com/wingide/trial
Feature list: http://wingware.com/wingide/features
Questions? Don't hesitate to email us at support(a)wingware.com.
Wingware | Python IDE
The Intelligent Development Environment for Python Programmers
Reminder: Deadline for application is 23:59 UTC, March 31, 2015.
Advanced Scientific Programming in Python
a Summer School by the G-Node, the Bernstein Center for Computational
Neuroscience Munich and the Graduate School of Systemic Neurosciences
Scientists spend more and more time writing, maintaining, and debugging
software. While techniques for doing this efficiently have evolved, only
few scientists have been trained to use them. As a result, instead of doing
their research, they spend far too much time writing deficient code and
reinventing the wheel. In this course we will present a selection of
advanced programming techniques, incorporating theoretical lectures and
practical exercises tailored to the needs of a programming scientist. New
skills will be tested in a real programming project: we will team up to
develop an entertaining scientific computer game.
We use the Python programming language for the entire course. Python works
as a simple programming language for beginners, but more importantly, it
also works great in scientific simulations and data analysis. We show how
clean language design, ease of extensibility, and the great wealth of open
source libraries for scientific computing and data visualization are
driving Python to become a standard tool for the programming scientist.
This school is targeted at Master or PhD students and Post-docs from all
areas of science. Competence in Python or in another language such as Java,
C/C++, MATLAB, or Mathematica is absolutely required. Basic knowledge of
Python is assumed. Participants without any prior experience with Python
should work through the proposed introductory materials before the course.
Date and Location
August 31—September 5, 2015. Munich, Germany.
Day 0 (Mon Aug 31) — Best Programming Practices
• Best Practices for Scientific Computing
• Version control with git and how to contribute to Open
Source with github
• Object-oriented programming & design patterns
Day 1 (Tue Sept 1) — Software Carpentry
• Test-driven development, unit testing & quality assurance
• Debugging, profiling and benchmarking techniques
• Advanced Python: generators, decorators, and context managers
Day 2 (Wed Sept 2) — Scientific Tools for Python
• Advanced NumPy
• The Quest for Speed (intro): Interfacing to C with Cython
• Contributing to Open Source Software/Programming in teams
Day 3 (Thu Sept 3) — The Quest for Speed
• Writing parallel applications in Python
• Python 3: why should I care
• Programming project
Day 4 (Fri Sept 4) — Efficient Memory Management
• When parallelization does not help:
the starving CPUs problem
• Programming project
Day 5 (Sat Sept 5) — Practical Software Development
• Programming project
• The Pelita Tournament
Every evening we will have the tutors' consultation hour: Tutors will
answer your questions and give suggestions for your own projects.
You can apply on-line at https://python.g-node.org
Applications must be submitted before 23:59 UTC, March 31, 2015.
Notifications of acceptance will be sent by May 1, 2015.
No fee is charged but participants should take care of travel, living, and
accommodation expenses. Candidates will be selected on the basis of their
profile. Places are limited: acceptance rate is usually around 20%.
Prerequisites: You are supposed to know the basics of Python to participate
in the lectures
• Pietro Berkes, Enthought Inc., UK
• Marianne Corvellec, Plotly Technologies Inc., Montréal, Canada
• Kathryn D. Huff, Department of Nuclear Engineering, University of
California - Berkeley, USA
• Zbigniew Jędrzejewski-Szmek, Krasnow Institute, George Mason
• Eilif Muller, Blue Brain Project, École Polytechnique Fédérale de
• Juan Nunez-Iglesias, Victorian Life Sciences Computation
Initiative, University of Melbourne, Australia
• Rike-Benjamin Schuppner, Institute for Theoretical Biology,
Humboldt-Universität zu Berlin, Germany
• Bartosz Teleńczuk, European Institute for Theoretical Neuroscience,
CNRS, Paris, France
• Nelle Varoquaux, Centre for Computational Biology Mines ParisTech,
Institut Curie, U900 INSERM, Paris, France
• Tiziano Zito, Forschungszentrum Jülich GmbH, Germany
Organized by Tiziano Zito (head) and Zbigniew Jędrzejewski-Szmek for the
German Neuroinformatics Node of the INCF Germany, Christopher Roppelt for
the German Center for Vertigo and Balance Disorders (DSGZ) and the Graduate
School of Systemic Neurosciences (GSN) of the Ludwig-Maximilians-Universität
Munich Germany, Christoph Hartmann for the Frankfurt Institute for Advanced
Studies (FIAS) and International Max Planck Research School (IMPRS) for
Neural Circuits, Frankfurt Germany, and Jakob Jordan for the Institute of
Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation
(IAS-6), Jülich Research Centre and JARA. Additional funding provided by the
Bernstein Center for Computational Neuroscience (BCCN) Munich.