Hi!
I'm pleased to announce the availability of wxGlade revision 1.0.1
Please download from https://sourceforge.net/projects/wxglade/files/wxglade/1.0.1/
wxGlade is a GUI builder for wxWidgets and wxPython.
The documentation includes a tutorial for people who have not used wxPython
before.
Included are also examples for integration with matplotlib.
A snapshot of the documentation is available at http://wxglade.sourceforge.net/docs/index.html
For support, there's a mailing list at https://sourceforge.net/p/wxglade/mailman/wxglade-general/
git repository and bug tracker are at https://github.com/wxGlade/wxGlade
(These pages are also linked from the help menu.)
Changes in revision 1.0.x:
==========================
Besides many improvements in usability, code generation and widget support,
this is also a major internal refactoring of the main data structure and how
widgets in the Design window are created / updated / destroyed.
*General:*
- sizers only required where wx requires them; not required e.g. for
Frame->Panel (used to be Frame->Sizer->Panel)
- better handling of display updates when properties are edited
- accessibility and usability improvements
- Dialog example
- documentation update
*Widgets:*
- all: separate class related properties into Class / Base Classes /
Instance Class
- Dialog: add StdDialogButtonSizer and standard buttons (stock items);
support SetAffirmativeId, SetEscapeId
- Button: support for image direction
- MenuBar: support lambda event handlers
- GridBagSizer: indicate overlapped slots in the Tree view
*Generated Code:*
- no separation into __set_properties/__do_layout any more
- support for instantiation classes
*Internal:*
- internal structures refactored
- add shell window and Tree Printer
wxGlade is released under the MIT license.
Happy New Year,
Dietmar Schwertberger
dietmar(a)schwertberger.de
<P><A HREF="https://sourceforge.net/projects/wxglade/files/wxglade/1.0.1/">wxGlade 1.0.1</A> - GUI builder for wxPython (31-Dec-20)
PyCA cryptography 44.0.0 has been released to PyPI. cryptography includes
both high level recipes and low level interfaces to common cryptographic
algorithms such as symmetric ciphers, asymmetric algorithms, message
digests, X.509, key derivation functions, and much more. We support Python
3.7+, and PyPy3 7.3.10+.
Changelog (https://cryptography.io/en/latest/changelog/#v44-0-0):
* BACKWARDS INCOMPATIBLE: Dropped support for LibreSSL < 3.9.
* Deprecated Python 3.7 support. Python 3.7 is no longer supported by the
Python core team. Support for Python 3.7 will be removed in a future
cryptography release.
* Updated Windows, macOS, and Linux wheels to be compiled with OpenSSL
3.4.0.
* macOS wheels are now built against the macOS 10.13 SDK. Users on older
versions of macOS should upgrade, or they will need to build cryptography
themselves.
* Enforce the RFC 5280 requirement that extended key usage extensions must
not be empty.
* Added support for timestamp extraction to the MultiFernet class.
* Relax the Authority Key Identifier requirements on root CA certificates
during X.509 verification to allow fields permitted by RFC 5280 but
forbidden by the CA/Browser BRs.
* Added support for Argon2id when using OpenSSL 3.2.0+.
* Added support for the Admissions certificate extension.
* Added basic support for PKCS7 decryption (including S/MIME 3.2) via
pkcs7_decrypt_der(), pkcs7_decrypt_pem(), and pkcs7_decrypt_smime().
-Paul Kehrer (reaperhulk)
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
2.2.0rc1. The NumPy 2.2.0 release is a short release that brings us back
into sync with the usual twice yearly release cycle. There have been a
number of small cleanups, as well as work bringing the new StringDType to
completion and improving support for free threaded Python. Highlights are:
- New functions `matvec` and `vecmat`, see below.
- Many improved annotations.
- Improved support for the new StringDType.
- Improved support for free threaded Python
- Fixes for f2py
This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
<https://pypi.org/project/numpy/2.2.0rc1>; source archives, release notes,
and wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v2.2.0rc1>.
Cheers,
Charles Harris
Lightweight implementation of a hierarchical distributed read-write lock
using Redis. This implementation supports concurrent readers and exclusive
writers in a tree-like hierarchy, ensuring that locks on ancestors affect
descendants.
Here are some of the key features of this implementation:
* Hierarchical locking with customizable path separators (e.g., /, :).
* Concurrent read locks on the same path or ancestors.
* Exclusive write locks on paths or descendants.
* Timeout and non-blocking lock options.
* Automatic lock refreshing for long-running operations.
https://pypi.org/project/redishilok/
Alpha 2? But Alpha 1 only just came out!
https://www.python.org/downloads/release/python-3140a2/
This is an early developer preview of Python 3.14
Major new features of the 3.14 series, compared to 3.13:
Python 3.14 is still in development. This release, 3.14.0a2 is the second
of seven planned alpha releases.
Alpha releases are intended to make it easier to test the current state of
new features and bug fixes and to test the release process.
During the alpha phase, features may be added up until the start of the
beta phase (2025-05-06) and, if necessary, may be modified or deleted up
until the release candidate phase (2025-07-22). Please keep in mind that
this is a preview release and its use is not recommended for production
environments.
Many new features for Python 3.14 are still being planned and written.
Among the new major new features and changes so far:
* PEP 649: deferred evaluation of annotations
* PEP 741: Python configuration C API
* PEP 761: Python 3.14 and onwards no longer provides PGP signatures for
release artifacts. Instead, Sigstore is recommended for verifiers.
* Improved error messages
* (Hey, fellow core developer, if a feature you find important is missing
from this list, let Hugo know.)
The next pre-release of Python 3.14 will be 3.14.0a3, currently scheduled
for 2024-12-17.
More resources
* Online documentation: https://docs.python.org/3.14/
* PEP 745, 3.14 Release Schedule: https://peps.python.org/pep-0719/
* Report bugs at https://github.com/python/cpython/issues
* Help fund Python and its community: https://www.python.org/psf/donations/
And now for something completely different
Ludolph van Ceulen (1540-1610) was a fencing and mathematics teacher in
Leiden, Netherlands, and spent around 25 years calculating π (or pi), using
essentially the same methods Archimedes employed some seventeen hundred
years earlier.
Archimedes estimated π by calculating the circumferences of polygons that
fit just inside and outside of a circle, reasoning the circumference of the
circle lies between these two values. Archimedes went up to polygons with
96 sides, for a value between 3.1408 and 3.1428, which is accurate to two
decimal places.
Van Ceulen used a polygon with half a billion sides. He published a
20-decimal value in his 1596 book Vanden Circkel (“On the Circle”), and
later expanded it to 35 decimals:
3.14159265358979323846264338327950288
Van Ceulen’s 20 digits is more than enough precision for any conceivable
practical purpose. For example, even if a printed circle was perfect down
to the atomic scale, the thermal vibrations of the molecules of ink would
make most of those digits physically meaningless. NASA Jet Propulsion
Laboratory’s highest accuracy calculations, for interplanetary navigation,
uses 15 decimals: 3.141592653589793.
At Van Ceulen’s request, his upper and lower bounds for π were engraved on
his tombstone in Leiden. The tombstone was eventually lost but restored in
2000. In the Netherlands and Germany, π is sometimes referred to as the
“Ludolphine number”, after Van Ceulen.
Enjoy the new release
Thanks to all of the many volunteers who help make Python Development and
these releases possible! Please consider supporting our efforts by
volunteering yourself or through organisation contributions to the Python
Software Foundation.
Regards from a chilly Helsinki with snow on the way,
Your release team,
Hugo van Kemenade
Ned Deily
Steve Dower
Łukasz Langa
*ANNOUNCING*
eGenix PyRun - One file Python Runtime
Version 2.6.0
Python runtime taking up just 4-6MB on disk
This announcement is also available on our web-site for online reading:
https://www.egenix.com/company/news/eGenix-PyRun-2.6.0-GA.html
------------------------------------------------------------------------
*INTRODUCTION*
*eGenix PyRun*™ <https://www.egenix.com/company/legal/trademarks.html>
is our open source, one file, no installation version of Python, making
the distribution of a Python interpreter to run Python based scripts and
applications to Unix based systems simple and efficient.
eGenix PyRun's executable only needs 4-6MB on disk, but still supports
most Python applications and scripts.
Compared to a regular Python installation of typically 100MB on disk,
eGenix PyRun is ideal for applications and scripts that need to be
distributed to containers, VMs, clusters, client installations,
customers or end-users.
It makes "installing" Python on a Unix based system as simple as copying
a single file.
eGenix has been using eGenix PyRun as run-time for the Linux version of
mxODBC Connect Server
<https://www.egenix.com/products/python/mxODBCConnect/> product since
2008 with great success and decided to make it available as a
stand-alone open-source product.
We provide the source archive to build your own *eGenix PyRun on Github*
<https://github.com/eGenix/egenix-pyrun>, as well as a few binary
distributions to get you started on Linux x86_64. In the future, we will
set up automated builds for several other platforms.
Please see the product page for more details:
>>> eGenix PyRun - One file Python Runtime
<https://www.egenix.com/products/python/PyRun/>
------------------------------------------------------------------------
*NEWS*
This major release of eGenix PyRun
<https://www.egenix.com/products/python/PyRun> comes with the following
enhancements:
* Added support for *Python 3.12*
* Added support for LTO release builds
* Added dev build targets for development; these don't use PGO and
thus build faster
For a complete list of changes, please see the *eGenix PyRun Changelog
<https://www.egenix.com/products/python/PyRun/changelog.html>*.
Enjoy,
--
Marc-Andre Lemburg
eGenix.com
Professional Python Services directly from the Experts (#1, Nov 13 2024)
>>> Python Projects, Coaching and Support ... https://www.egenix.com/
>>> Python Product Development ... https://consulting.egenix.com/
________________________________________________________________________
::: We implement business ideas - efficiently in both time and costs :::
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
https://www.egenix.com/company/contact/https://www.malemburg.com/
The version 8 of `logassert` brings support for the structlog library.
Yes, now you can use the whole power of logassert when using structlog
as a logger.
There are also small administrative enhancements: better README (and
documentation in [Read The Docs]()), the CI uses modern Pythons,
better tested badge, etc.
What is logassert?
A simple log assertion mechanism for Python unittests.
Provides a simple and expressive way to use it in the unit tests and
when the assertion fails it presents a useful report that helps you to
find out why it is failing.
Includes a fixture to use it with `pytest` and can also be used in
classic unit tests. Allows checking using regular expressions, exact
strings, multiple strings, and even sequences of several lines,
including support for verifying that nothing was logged, and of course
filtering by the log level (if desired).
Full docs: https://logassert.readthedocs.io/en/latest/
--
. Facundo
Blog: http://www.taniquetil.com.ar/plog/
PyAr: http://www.python.org.ar/
Twitter: @facundobatista
What is python-oracledb?
python-oracledb is a Python extension module that enables access to Oracle
Database for Python and conforms to the Python database API 2.0 specifications
with a number of enhancements. This module replaces cx_Oracle.
Where do I get it?
https://pypi.org/project/oracledb/2.5.0/
The easiest method to install/upgrade python-oracledb is via pip as in
python -m pip install oracledb --upgrade
What's new?
This release adds a number of requested enhancements and corrects a number
of issues.
See the full release notes for all of the details:
https://python-oracledb.readthedocs.io/en/latest/release_notes.html#oracled…
Please provide any feedback via GitHub issues: https://github.com/oracle/
python-oracledb/issues or discussions: https://github.com/oracle/python-
oracledb/discussions
Hi All,
On behalf of the NumPy team, I'm pleased to announce the release of NumPy
2.1.3. NumPy 2.1.3 is a maintenance release that fixes bugs and regressions
discovered after the 2.1.2 release. This release also adds support for free
threaded Python 3.13 on Windows.
This release supports Python 3.10-3.13. Wheels can be downloaded from PyPI
<https://pypi.org/project/numpy/2.1.3>; source archives, release notes, and
wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v2.1.3>.
*Contributors*
A total of 15 people contributed to this release. People with a "+" by
their
names contributed a patch for the first time.
- Abhishek Kumar +
- Austin +
- Benjamin A. Beasley +
- Charles Harris
- Christian Lorentzen
- Marcel Telka +
- Matti Picus
- Michael Davidsaver +
- Nathan Goldbaum
- Peter Hawkins
- Raghuveer Devulapalli
- Ralf Gommers
- Sebastian Berg
- dependabot[bot]
- kp2pml30 +
*Pull requests merged*
A total of 21 pull requests were merged for this release.
- #27512: MAINT: prepare 2.1.x for further development
- #27537: MAINT: Bump actions/cache from 4.0.2 to 4.1.1
- #27538: MAINT: Bump pypa/cibuildwheel from 2.21.2 to 2.21.3
- #27539: MAINT: MSVC does not support #warning directive
- #27543: BUG: Fix user dtype can-cast with python scalar during
promotion
- #27561: DEV: bump ``python`` to 3.12 in environment.yml
- #27562: BLD: update vendored Meson to 1.5.2
- #27563: BUG: weighted quantile for some zero weights (#27549)
- #27565: MAINT: Use miniforge for macos conda test.
- #27566: BUILD: satisfy gcc-13 pendantic errors
- #27569: BUG: handle possible error for PyTraceMallocTrack
- #27570: BLD: start building Windows free-threaded wheels [wheel build]
- #27571: BUILD: vendor tempita from Cython
- #27574: BUG: Fix warning "differs in levels of indirection" in
npy_atomic.h...
- #27592: MAINT: Update Highway to latest
- #27593: BUG: Adjust numpy.i for SWIG 4.3 compatibility
- #27616: BUG: Fix Linux QEMU CI workflow
- #27668: BLD: Do not set __STDC_VERSION__ to zero during build
- #27669: ENH: fix wasm32 runtime type error in numpy._core
- #27672: BUG: Fix a reference count leak in npy_find_descr_for_scalar.
- #27673: BUG: fixes for StringDType/unicode promoters
Cheers,
Charles Harris
