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 41.0.0 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, X509, key derivation functions, and much
more. We support Python 3.7+, and PyPy3 7.3.10+.
Changelog (https://cryptography.io/en/latest/changelog/#v41-0-0):
* BACKWARDS INCOMPATIBLE: Support for OpenSSL less than 1.1.1d has
been removed. Users on older version of OpenSSL will need to upgrade.
* BACKWARDS INCOMPATIBLE: Support for Python 3.6 has been removed.
* BACKWARDS INCOMPATIBLE: Dropped support for LibreSSL < 3.6.
* Updated Windows, macOS, and Linux wheels to be compiled with OpenSSL 3.1.1.
* Updated the minimum supported Rust version (MSRV) to 1.56.0, from 1.48.0.
* Added support for the OCSPAcceptableResponses OCSP extension.
* Added support for the MSCertificateTemplate proprietary Microsoft
certificate extension.
* Implemented support for equality checks on all asymmetric public key types.
* Added support for aes256-gcm(a)openssh.com encrypted keys in
load_ssh_private_key().
* Added support for obtaining X.509 certificate signature algorithm
parameters (including PSS) via signature_algorithm_parameters().
* Support signing PSS X.509 certificates via the new keyword-only
argument rsa_padding on sign().
* Added support for ChaCha20Poly1305 on BoringSSL.
-Paul Kehrer (reaperhulk)
Hi All,
The NumPy 1.25.0 release continues the ongoing work to improve the handling
and promotion of dtypes, increase the execution speed, and clarify the
documentation. There has also been work to prepare for the future NumPy
2.0.0
release, resulting in a large number of new and expired deprecation.
Highlights are:
- Support for MUSL, there are now MUSL wheels.
- Support the Fujitsu C/C++ compiler.
- Object arrays are now supported in einsum
- Support for inplace matrix multiplication (@=).
We will release NumPy 1.26 on top of the 1.25 code when Python 12 reaches
the rc stage. That is needed because distutils has been dropped by Python
12 and we will be switching to using meson for future builds. The next
mainline release will be NumPy 2.0.0. We plan that the 2.0 series will
still support downstream projects built against earlier
versions of NumPy.
The Python versions supported in this release are 3.9-3.11. Wheels can be
downloaded from PyPI <https://pypi.org/project/numpy/1.25.0rc1/>; source
archives, release notes, and wheel hashes are available on Github
<https://github.com/numpy/numpy/releases/tag/v1.25.0rc1>.
*Contributors*
A total of 145 people contributed to this release. People with a "+" by
their names contributed a patch for the first time.
- @DWesl
- @partev +
- @pierreloicq +
- @pkubaj +
- @pmvz +
- @tajbinjohn +
- A Chethan Reddy +
- Aaron Meurer
- Aleksei Nikiforov +
- Alex Rogozhnikov
- Alexander Heger
- Alexander Neumann +
- Andrew Nelson
- Arun Kota +
- Bas van Beek
- Ben Greiner +
- Berke Kocaoğlu +
- Bob Eldering
- Brian Soto
- Brock Mendel
- Charles Harris
- Charles Young +
- Chris Brown
- Chris Sidebottom +
- Christian Lorentzen +
- Christian Veenhuis +
- Christopher Sidebottom +
- Chun-Wei Chen +
- Clément Robert
- Cédric Hannotier +
- Daiki Shintani +
- Daniel McCloy +
- Derek Homeier
- Developer-Ecosystem-Engineering
- DhavalParmar61 +
- Dimitri Papadopoulos Orfanos
- Dmitry Belov +
- Dominic Davis-Foster +
- Eddie Darling +
- Edward E +
- Eero Vaher
- Eric Wieser
- Eugene Kim +
- Evgeni Burovski
- Facundo Batista +
- Francesc Elies +
- Ganesh Kathiresan
- Hongyang Peng +
- Hood Chatham
- Ikko Ashimine
- Ikko Eltociear Ashimine +
- Inessa Pawson
- Irit Katriel
- Ivan Gonzalez
- JP Ungaretti +
- Jarrod Millman
- Jean-François B +
- Johana De La Rosa +
- Johnson Sun +
- Jonathan Kohler +
- Jory Klaverstijn +
- Joyce Brum +
- Jules Kouatchou +
- Kentaro Kawakami +
- Khem Raj +
- Kyle Sunden
- Larry Bradley
- Lars Grüter
- Laurenz Kremeyer +
- Lee Johnston +
- Lefteris Loukas +
- Leona Taric
- Lillian Zha
- Lu Yun Chi +
- Malte Londschien +
- Manuchehr Aminian +
- Mariusz Felisiak
- Mark Harfouche
- Mark J. Olson +
- Marko Pacak +
- Marten van Kerkwijk
- Matteo Raso
- Matthew Muresan +
- Matti Picus
- Meekail Zain
- Melissa Weber Mendonça
- Michael Kiffer +
- Michael Lamparski
- Michael Siebert
- Michail Gaganis +
- Mike Toews
- Mike-gag +
- Miki Watanabe
- Miki Watanabe (渡邉 美希)
- Miles Cranmer
- Muhammad Ishaque Nizamani +
- Mukulika Pahari
- Nathan Goldbaum
- Nico Schlömer
- Norwid Behrnd +
- Noé Rubinstein +
- Oleksandr Pavlyk
- Oscar Gustafsson
- Pamphile Roy
- Panagiotis Zestanakis +
- Paul Romano +
- Paulo Almeida +
- Pedro Lameiras +
- Peter Hawkins
- Peyton Murray +
- Philip Holzmann +
- Pierre Blanchard +
- Pieter Eendebak
- Pradipta Ghosh
- Pratyay Banerjee +
- Prithvi Singh +
- Raghuveer Devulapalli
- Ralf Gommers
- Richie Cotton +
- Robert Kern
- Rohit Goswami
- Ross Barnowski
- Roy Smart +
- Rustam Uzdenov +
- Sadi Gulcelik +
- Sarah Kaiser +
- Sayed Adel
- Sebastian Berg
- Simon Altrogge +
- Somasree Majumder
- Stefan Behnel
- Stefan van der Walt
- Stefanie Molin
- StepSecurity Bot +
- Syam Gadde +
- Sylvain Ferriol +
- Talha Mohsin +
- Taras Tsugrii +
- Thomas A Caswell
- Tyler Reddy
- Warren Weckesser
- Will Tirone +
- Yamada Fuyuka +
- Younes Sandi +
- Yuki K +
Cheers,
Charles Harris
I'm pleased to announce the release of Python 3.12 beta 1 (and feature
freeze for Python 3.12).
https://www.python.org/downloads/release/python-3120b1/
This is a beta preview of Python 3.12
Python 3.12 is still in development. This release, 3.12.0b1, is the first
of four planned beta release previews of 3.12.
Beta release previews are intended to give the wider community the
opportunity to test new features and bug fixes and to prepare their
projects to support the new feature release.
We strongly encourage maintainers of third-party Python projects to test
with 3.12 during the beta phase and report issues found to [the Python bug
tracker (Issues · python/cpython · GitHub) as soon as possible. While the
release is planned to be feature complete entering the beta phase, it is
possible that features may be modified or, in rare cases, deleted up until
the start of the release candidate phase (Monday, 2023-07-31). Our goal is
to have no ABI changes after beta 4 and as few code changes as possible
after 3.12.0rc1, the first release candidate. To achieve that, it will be
extremely important to get as much exposure for 3.12 as possible during the
beta phase.
Please keep in mind that this is a preview release and its use is not
recommended for production environments.
Major new features of the 3.12 series, compared to 3.11
Some of the new major new features and changes in Python 3.12 are:
- New type annotation syntax for generic classes (PEP 695
<https://peps.python.org/pep-0695/>).
- More flexible f-string parsing, allowing many things previously
disallowed (PEP 701 <https://peps.python.org/pep-0701/>).
- Even more improved error messages. More exceptions potentially caused
by typos now make suggestions to the user.
- Many large and small performance improvements (like PEP 709
<https://peps.python.org/pep-0709/>).
- Support for the Linux perf profiler to report Python function names in
traces.
- The deprecated wstr and wstr_length members of the C implementation of
unicode objects were removed, per PEP 623
<https://peps.python.org/pep-0623/>.
- In the unittest module, a number of long deprecated methods and
classes were removed. (They had been deprecated since Python 3.1 or 3.2).
- The deprecated smtpd and distutils modules have been removed (see PEP
594 <https://peps.python.org/pep-0594/> and PEP 632
<https://peps.python.org/pep-0632/>. The setuptools package (installed
by default in virtualenvs and many other places) continues to provide the
distutils module.
- A number of other old, broken and deprecated functions, classes and
methods have been removed.
- Invalid backslash escape sequences in strings now warn with
SyntaxWarning instead of DeprecationWarning, making them more visible.
(They will become syntax errors in the future.)
- The internal representation of integers has changed in preparation for
performance enhancements. (This should not affect most users as it is an
internal detail, but it may cause problems for Cython-generated code.)
- (Hey, fellow core developer, if a feature you find important is
missing from this list, let Thomas know <thomas(a)python.org>.)
For more details on the changes to Python 3.12, see What’s new in Python
3.12 <https://docs.python.org/dev/whatsnew/3.12.html>. The next pre-release
of Python 3.12 will be 3.12.0b2, currently scheduled for 2023-05-29.
More resources
Online Documentation <https://docs.python.org/3.12/>.
PEP 693 <https://www.python.org/dev/peps/pep-0693/>, the Python 3.12
Release Schedule.
Report bugs via GitHub Issues <https://github.com/python/cpython/issues>.
Help fund Python and its community <https://www.python.org/psf/donations/>.
And now for something completely different
As the first beta release marks the point at which we fork off the release
branch from the main development branch, here’s a poem about forks in the
road.
Two roads diverged in a yellow wood,
And sorry I could not travel both
And be one traveler, long I stood
And looked down one as far as I could
To where it bent in the undergrowth;
Then took the other, as just as fair,
And having perhaps the better claim,
Because it was grassy and wanted wear;
Though as for that the passing there
Had worn them really about the same,
And both that morning equally lay
In leaves, no step had trodden black.
Oh, I kept the first for another day!
Yet knowing how way leads on to way,
I doubted if I should ever come back.
I shall be telling this with a sigh
Somewhere ages and ages hence:
Two roads diverged in a wood, and I —
I took the one less traveled by,
And that has made all the difference.
*The Road Not Taken*, by Robert Frost.
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 organization contributions to the Python
Software Foundation.
Your release team,
Thomas Wouters
Ned Deily
Steve Dower
--
Thomas Wouters <thomas(a)python.org>
I just pushed release 3.1.0b2 of pyparsing. 3.1.0 with some fixes to bugs that came up in the past few weeks - testing works!
If your project uses pyparsing, please please *please* download this beta release (using "pip install -U pyparsing==3.1.0b2") and open any compatibility issues you might have at the pyparsing GitHub repo (https://github.com/pyparsing/pyparsing).
In the absence of any dealbreakers, I'll make the final release in June.
You can view the changes here: https://github.com/pyparsing/pyparsing/blob/master/CHANGES
Hi all,
happy to announce a better developer experience with pytest-when fixture.
With pytest-mock you can define the complex mocking behavior via natural interface:
```
when(some_object, "attribute").called_with(1, 2).then_return("mocked")
```
In this case the some_object.attribute(1, 2) == "mocked". But if it will be called with any other
arguments, it will return what it is suppose to return.
Project GitHub:
https://github.com/zhukovgreen/pytest-when
zhukovgreen/pytest-when: Pytest plugin for more readable mocking
github.com
Support python>=3.8 and tested until 3.11
Small example from the docs:
# class which we're going to mock in the test
class Klass1:
def some_method(
self,
arg1: str,
arg2: int,
*,
kwarg1: str,
kwarg2: str,
) -> str:
return "Not mocked"
def test_should_properly_patch_calls(when):
when(Klass1, "some_method").called_with(
"a",
when.markers.any,
kwarg1="b",
kwarg2=when.markers.any,
).then_return("Mocked")
assert (
Klass1().some_method(
"a",
1,
kwarg1="b",
kwarg2="c",
)
== "Mocked"
)
assert (
Klass1().some_method(
"not mocked param",
1,
kwarg1="b",
kwarg2="c",
)
== "Not mocked"
)
# if you need to patch a function
def test_patch_a_function(when):
when(example_module, "some_normal_function").called_with(
"a",
when.markers.any,
kwarg1="b",
kwarg2=when.markers.any,
).then_return("Mocked")
assert (
example_module.some_normal_function(
"a",
1,
kwarg1="b",
kwarg2="c",
)
== "Mocked"
)
assert (
example_module.some_normal_function(
"not mocked param",
1,
kwarg1="b",
kwarg2="c",
)
== "Not mocked"
)
Thank you for any feedback
--
zhukovgreen,
Data Engineer @Paylocity
https://github.com/zhukovgreen
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I'm happy to announce txtorcon 23.5.0 with the following changes:
* twisted.web.client.Agent instances now use the same HTTPS policy
by default as twisted.web.client.Agent. It is possible to
override this policy with the tls_context_factory= argument, the
equivalent to Agent's contextFactory=
(Thanks to Itamar Turner-Trauring)
* Added support + testing for Python 3.11.
* No more ipaddress dependency
You can download the release from PyPI or GitHub (or of
course "pip install txtorcon"):
https://pypi.python.org/pypi/txtorcon/23.5.0https://github.com/meejah/txtorcon/releases/tag/v23.5.0
Releases are also available from the hidden service:
http://fjblvrw2jrxnhtg67qpbzi45r7ofojaoo3orzykesly2j3c2m3htapid.onion/txtor…http://fjblvrw2jrxnhtg67qpbzi45r7ofojaoo3orzykesly2j3c2m3htapid.onion/txtor…
You can verify the sha256sum of both by running the following 4 lines
in a shell wherever you have the files downloaded:
cat <<EOF | sha256sum --check
93fd80a9dd505f698d0864fe93db8b6a9c1144b5feb91530820b70ed8982651c dist/txtorcon-23.5.0.tar.gz
987f0a91184f98cc3f0a7eccaa42f5054063744d6ac15e325cfa666403214208 dist/txtorcon-23.5.0-py3-none-any.whl
EOF
thanks,
meejah
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Make Python CLI tools win the speed race, by cheating!
JumpTheGun makes Python CLI tools start up much faster. For example, it can make the AWS CLI start up nearly 3x faster, making it near-instant.
# In any Python (>= 3.7) environment:
pip install jumpthegun
# or
pipx install jumpthegun
# For any CLI tool written in Python (>= 3.7):
jumpthegun run <cli-tool> [...]
# Examples:
jumpthegun run black --check .
jumpthegun run aws --version
# More details:
jumpthegun --help
https://github.com/taleinat/jumpthegun
Enjoy snappier tools!
- Tal Einat
Hi all,
I'm delighted to announce the latest release of *s**kforecast*!
*Skforecast *is a Python library that eases using scikit-learn regressors
as single and multi-step forecasters. It also works with any regressor
compatible with the scikit-learn API (pipelines, CatBoost, LightGBM,
XGBoost, Ranger...).
Docs: https://skforecast.org/
Why use skforecast?
The fields of statistics and machine learning have developed many excellent
regression algorithms that can be useful for forecasting, but applying them
effectively to time series analysis can still be a challenge. To address
this issue, the skforecast library provides a comprehensive set of tools
for training, validation and prediction in a variety of scenarios commonly
encountered when working with time series. The library is built using the
widely used scikit-learn API, making it easy to integrate into existing
workflows. With skforecast, users have access to a wide range of
functionalities such as feature engineering, model selection,
hyperparameter tuning and many others. This allows users to focus on the
essential aspects of their projects and leave the intricacies of time
series analysis to skforecast.
Happy forecasting!
--
Joaquín Amat Rodrigo
