I am pleased to announce release 2017.3 of SfePy.
SfePy (simple finite elements in Python) is a software for solving systems of
coupled partial differential equations by the finite element method or by the
isogeometric analysis (limited support). It is distributed under the new BSD
Home page: http://sfepy.org
Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/
Git (source) repository, issue tracker: https://github.com/sfepy/sfepy
Highlights of this release
- support preconditioning in SciPy and PyAMG based linear solvers
- user-defined preconditioners for PETSc linear solvers
- parallel multiscale (macro-micro) homogenization-based computations
- improved tutorial and installation instructions
For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1
(rather long and technical).
Contributors to this release in alphabetical order:
lxml 4.0.0 was released yesterday with several new features and
enhancements. Thanks to everyone who contributed.
lxml is the fastest, most versatile and most widely used tool for
processing XML and HTML in Python, supporting XPath, XSLT and many pythonic
ways to deal with markup documents.
The documentation is here: http://lxml.de/
Binary wheels are available for Linux, Mac-OS and Windows.
This release was built using Cython 0.26.1.
If you are interested in commercial support or customisations for the lxml
package, please contact me directly.
* The ElementPath implementation is now compiled using Cython,
which speeds up the ``.find*()`` methods quite significantly.
* The modules ``lxml.builder``, ``lxml.html.diff`` and ``lxml.html.clean``
are also compiled using Cython in order to speed them up.
* ``xmlfile()`` supports async coroutines using ``async with`` and
``await``. See http://lxml.de/api.html#incremental-xml-generation
* ``iterwalk()`` has a new method ``skip_subtree()`` that prevents walking
into the descendants of the current element.
* ``RelaxNG.from_rnc_string()`` accepts a ``base_url`` argument to
allow relative resource lookups.
* The XSLT result object has a new method ``.write_output(file)`` that
serialises output data into a file according to the ``<xsl:output>``
* GH#251: HTML comments were handled incorrectly by the soupparser.
Patch by mozbugbox.
* LP#1654544: The html5parser no longer passes the ``useChardet`` option
if the input is a Unicode string, unless explicitly requested. When
parsing files, the default is to enable it when a URL or file path is
passed (because the file is then opened in binary mode), and to disable
it when reading from a file(-like) object.
Note: This is a backwards incompatible change of the default
configuration. If your code parses byte strings/streams and depends on
character detection, please pass the option ``guess_charset=True``
explicitly, which already worked in older lxml versions.
* LP#1703810: ``etree.fromstring()`` failed to parse UTF-32 data with BOM.
* LP#1526522: Some RelaxNG errors were not reported in the error log.
* LP#1567526: Empty and plain text input raised a TypeError in soupparser.
* LP#1710429: Uninitialised variable usage in HTML diff.
* LP#1415643: The closing tags context manager in ``xmlfile()`` could
continue to output end tags even after writing failed with an exception.
* LP#1465357: ``xmlfile.write()`` now accepts and ignores None as input
* Compilation under Py3.7-pre failed due to a modified function signature.
* The main module source files were renamed from ``lxml.*.pyx`` to plain
``*.pyx`` (e.g. ``etree.pyx``) to simplify their handling in the build
process. Care was taken to keep the old header files as fallbacks for
code that compiles against the public C-API of lxml, but it might still
be worth validating that third-party code does not notice this change.
yacron is a modern Cron replacement that is Docker-friendly
- "Crontab" is in YAML format;
- Builtin sending of Sentry and Mail outputs when cron jobs fail;
- Flexible configuration: you decide how to determine if a cron job fails
- Designed for running in Docker, Kubernetes, or 12 factor environments:
- Runs in the foreground;
- Logs everything to stdout/stderr ;
- Option to automatically retry failing cron jobs, with exponential backoff.
 Whereas vixie cron only logs to syslog, requiring a syslog daemon to be
running in the background or else you don't get logs!
Home page: https://github.com/gjcarneiro/yacron
Note: I am not planning any more features until the 1.0 release, but I
appreciate help finding and fixing bugs.
Gustavo J. A. M. Carneiro
"The universe is always one step beyond logic." -- Frank Herbert
It's been a while, but six 1.11.0 is now live on PyPI! six is a Python
2&3 compatibility library.
Many thanks to the various contributors who did most the work.
Here is the changelog for 1.11.0:
- Pull request #178: `with_metaclass` now properly proxies `__prepare__`
- Pull request #191: Allow `with_metaclass` to work with metaclasses
- Pull request #203: Add parse_http_list and parse_keqv_list to moved
- Pull request #172 and issue #171: Add unquote_to_bytes to moved
- Pull request #167: Add `six.moves.getoutput`.
- Pull request #80: Add `six.moves.urllib_parse.splitvalue`.
- Pull request #75: Add `six.moves.email_mime_image`.
- Pull request #72: Avoid creating reference cycles through tracebacks
I'm happy to announce to the immediate availability of Python 2.7.14,
yet another bug fix release in the Python 2.7 series. 2.7.14 includes 9
months of conservative bug fixes from the 3.x branch.
Downloads of source code and binaries are at:
Bugs may be reported at
2.7 release manager
(on behalf of all of 2.7's contributors)
This is a quick note to update from the release two days ago that we've
pushed NumExpr 2.6.4. The release of 2.6.3 two days ago omitted
implementations for the new `ceil` and `floor` functions for the Intel VML
when compiled with the Intel MKL. Thanks to Christoph Gohlke for noticing
the error and patching it.
Also thanks to Matthew Brett for helping me to get the manywheels procedure
going for NumExpr. There was a minor delay yesterday in uploading due to
the Amazon/Travis outage.
Robert McLeod, Ph.D.
This is primarily a maintenance release that fixes a number of newly
bugs. The NumPy requirement has increased from 1.6 to 1.7 due to changes
`numpy.nditer` flags. Thanks to Caleb P. Burns `ceil` and `floor` functions
Project documentation is now available at:
Announcing Numexpr 2.6.3
Changes from 2.6.2 to 2.6.3
- Documentation now available at numexpr.readthedocs.io
- Support for floor() and ceil() functions added by Caleb P. Burns.
- NumPy requirement increased from 1.6 to 1.7 due to changes in iterator
- Sphinx autodocs support added for documentation on readthedocs.org.
- Fixed a bug where complex constants would return an error, fixing
problems with `sympy` when using NumExpr as a backend.
- Fix for #277 whereby arrays of shape (1,...) would be reduced as
if they were full reduction. Behavoir now matches that of NumPy.
- String literals are automatically encoded into 'ascii' bytes for
convience (see #281).
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
It has multi-threaded capabilities, as well as support for Intel's
MKL (Math Kernel Library), which allows an extremely fast evaluation
of transcendental functions (sin, cos, tan, exp, log...) while
squeezing the last drop of performance out of your multi-core
processors. Look here for a some benchmarks of numexpr using MKL:
Its only dependency is NumPy (MKL is optional), so it works well as an
easy-to-deploy, easy-to-use, computational engine for projects that
don't want to adopt other solutions requiring more heavy dependencies.
Where I can find Numexpr?
The project is hosted at GitHub in:
You can get the packages from PyPI as well (but not for RC releases):
Documentation is hosted at:
Share your experience
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
Robert McLeod, Ph.D.
On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.9 of Bokeh!
OF SPECIAL NOTE: *** JupyterLab and Fast Array Transport now supported ***
Please see the announcement post at:
which has more information and demonstrations.
If you are using Anaconda/miniconda, you can install it with conda:
conda install -c bokeh bokeh
Alternatively, you can also install it with pip:
pip install bokeh
Full information including details about how to use and obtain BokehJS are at:
Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
Documentation is available at http://bokeh.pydata.org/en/0.12.9
There are over 250 total contributors to Bokeh and their time and effort help make Bokeh such an amazing project and community. Thank you again for your contributions.
Finally (as always), for questions, technical assistance or if you're interested in contributing, questions can be directed to the Bokeh mailing list: bokeh(a)continuum.io or the Gitter Chat room: https://gitter.im/bokeh/bokeh
Bryan Van de Ven
pytest 3.2.2 has just been released to PyPI.
This is a bug-fix release, being a drop-in replacement. To upgrade::
pip install --upgrade pytest
The full changelog is available at
Thanks to all who contributed to this release, among them:
* Andreas Pelme
* Antonio Hidalgo
* Bruno Oliveira
* Felipe Dau
* Fernando Macedo
* Jesús Espino
* Joan Massich
* Joe Talbott
* Kirill Pinchuk
* Ronny Pfannschmidt
* Xuan Luong
The pytest Development Team
On behalf of the Python development community and the Python 3.3 release teams, I would like to announce the availability of Python 3.3.7rc1, the release candidate of Python 3.3.7. It is a security-fix source-only release. Python 3.3.0 was released 5 years ago on 2012-09-29 and has been in security-fix-only mode since 2014-03-08. Per project policy, all support for the 3.3 series of releases ends on 2017-09-29, five years after the initial release. Therefore, Python 3.3.7 is expected to be the final release of any kind for the 3.3 series.
After 2017-09-29, **we will no longer accept bug reports nor provide fixes of any kind for Python 3.3.x**; of course, third-party distributors of Python 3.3.x may choose to offer their own extended support. Because 3.3.x has long been in security-fix mode, 3.3.7 may no longer build correctly on all current operating system releases and some tests may fail. If you are still using Python 3.3.x, we **strongly** encourage you to upgrade to a more recent, fully supported version of Python 3; see https://www.python.org/downloads/. If you are still using your own build of Python 3.3.x , please report any critical issues with 3.3.7rc1 to the Python bug tracker prior to 2017-09-18, the expected release date for Python 3.3.7 final. Even better, use the time to upgrade to Python 3.6.x!
Thank you to everyone who has contributed to the success of Python 3.3.x over the past years!
You can find Python 3.3.7rc1 here:
nad(a)python.org --