vulture - Find dead code
========================
Vulture finds unused classes, functions and variables in your code. This helps
you cleanup and find errors in your programs. If you run it on both your
library and test suite you can find untested code.
Due to Python's dynamic nature, static code analyzers like vulture are likely
to miss some dead code. Also, code that is only called implicitly may be
reported as unused. Nonetheless, vulture can be a helpful tool for higher code
quality.
Download
========
http://pypi.python.org/pypi/vulture
Features
========
* fast: uses static code analysis
* lightweight: only one module
* tested: tests itself and has 100% test coverage
* complements pyflakes and has the same output syntax
* supports Python 2.6, 2.7 and 3.x
News
====
* Detect unused imports.
* Use tokenize.open() on Python >= 3.2 for reading input files, assume
UTF-8 encoding on older Python versions.
Cheers,
Jendrik
Announcing the release of StdConfigParser 1.0
What is it?
-----------
This is the Python configparser with an extra class StdConfigParser.
The StdConfigParser class uses specified parameters to initialize
the Python ConfigParser and adds some useful converters.
The result is a simple well defined syntax for the INI file.
See it as a preconfigured ConfigParser class for you.
It allows interoperability in configuration between different projects.
Also contains everything to be a full backport of the configparser
module from Python 3.5 to Python 2.7, 3.3, 3.4.
Everything in one module easy to vendor or install no extra dependencies.
Note
----
Even if you don't need the additional class StdConfigParser this module
is useful as a backport of the ConfigParser class with the features from
Python 3.5 to older Python versions.
All in one file without the namespace or ".pth" problems of other
backports. Also easy to vendor!
What's new in 1.0
-----------------
- Support Python 3.6
- Improve stability in error cases. Test improved error reporting.
Links
-----
- Download: https://pypi.python.org/pypi/StdConfigParser
- Source: https://github.com/tds333/stdconfigparser
- Documentation: http://stdconfigparser.readthedocs.io/en/latest/index.html
Kind regards,
Wolfgang
Announcing the release of StdConfigParser 1.0
What is it?
-----------
This is the Python configparser with an extra class StdConfigParser. The
StdConfigParser class uses specified parameters to initialize the Python
ConfigParser and adds some useful converters. The result is a simple well
defined syntax for the INI file. See it as a preconfigured ConfigParser class
for you. It allows interoperability in configuration between different
projects.
Also contains everything to be a full backport of the configparser module from
Python 3.5 to Python 2.7, 3.3, 3.4.
Everything in one module easy to vendor or install no extra dependencies.
Note
----
Even if you don't need the additional class StdConfigParser this module is
useful as a backport of the ConfigParser class with the features from Python
3.5 to older Python versions. All in one file without the namespace or ".pth"
problems of other backports. Also easy to vendor!
What's new in 1.0
-----------------
- Support Python 3.6
- Improve stability in error cases. Test improved error reporting.
Links
-----
- Download: https://pypi.python.org/pypi/StdConfigParser
- Source: https://github.com/tds333/stdconfigparser
- Documentation: http://stdconfigparser.readthedocs.io/en/latest/index.html
Kind regards,
Wolfgang
On behalf of the Python development community and the Python 3.4 and
Python 3.5 release teams, I'm pleased to announce the availability of
Python 3.4.6rc1 and Python 3.5.6rc1.
Python 3.4 is now in "security fixes only" mode. This is the final
stage of support for Python 3.4. Python 3.4 now only receives security
fixes, not bug fixes, and Python 3.4 releases are source code only--no
more official binary installers will be produced.
Python 3.5 is still in active "bug fix" mode. Python 3.5.3rc1 contains
many incremental improvements over Python 3.5.2.
Both these releases are "release candidates". They should not be
considered the final releases, although the final releases should
contain only minor differences. Python users are encouraged to test
with these releases and report any problems they encounter.
You can find Python 3.4.6rc1 here:
https://www.python.org/downloads/release/python-346rc1/
And you can find Python 3.5.3rc1 here:
https://www.python.org/downloads/release/python-353rc1/
Python 3.4.6 final and Python 3.5.3 final are both scheduled for release
on January 16th, 2017.
Happy New Year,
//arry/
On behalf of the Python development community and the Python 3.4 and Python 3.5
release teams, I'm pleased to announce the availability of Python 3.4.6rc1 and
Python 3.5.6rc1.
Python 3.4 is now in "security fixes only" mode. This is the final stage of
support for Python 3.4. Python 3.4 now only receives security fixes, not bug
fixes, and Python 3.4 releases are source code only--no more official binary
installers will be produced.
Python 3.5 is still in active "bug fix" mode. Python 3.5.3rc1 contains many
incremental improvements over Python 3.5.2.
Both these releases are "release candidates". They should not be considered
the final releases, although the final releases should contain only minor
differences. Python users are encouraged to test with these releases and
report any problems they encounter.
You can find Python 3.4.6rc1 here:
https://www.python.org/downloads/release/python-346rc1/
And you can find Python 3.5.3rc1 here:
https://www.python.org/downloads/release/python-353rc1/
Python 3.4.6 final and Python 3.5.3 final are both scheduled for release on
January 16th, 2017.
Happy New Year,
//arry/
Hi All,
I'm pleased to announce the NumPy 1.12.0rc2 New Year's release. This
release supports Python 2.7 and 3.4-3.6. Wheels for all supported Python
versions may be downloaded from PiPY
<https://pypi.python.org/pypi?%3Aaction=pkg_edit&name=numpy>, the tarball
and zip files may be downloaded from Github
<https://github.com/numpy/numpy/releases/tag/v1.12.0rc2>. The release notes
and files hashes may also be found at Github
<https://github.com/numpy/numpy/releases/tag/v1.12.0rc2> .
NumPy 1.12.0rc 2 is the result of 413 pull requests submitted by 139
contributors and comprises a large number of fixes and improvements. Among
the many improvements it is difficult to pick out just a few as standing
above the others, but the following may be of particular interest or
indicate areas likely to have future consequences.
* Order of operations in ``np.einsum`` can now be optimized for large speed
improvements.
* New ``signature`` argument to ``np.vectorize`` for vectorizing with core
dimensions.
* The ``keepdims`` argument was added to many functions.
* New context manager for testing warnings
* Support for BLIS in numpy.distutils
* Much improved support for PyPy (not yet finished)
Enjoy,
Chuck
Hi All,
I'm pleased to announce the NumPy 1.12.0rc2 New Year's release. This release
supports Python 2.7 and 3.4-3.6. Wheels for all supported Python versions may
be downloaded from PiPY
<https://pypi.python.org/pypi?%3Aaction=pkg_edit&name=numpy>, the tarball
and zip files may be downloaded from Github
<https://github.com/numpy/numpy/releases/tag/v1.12.0rc2>. The release notes
and files hashes may also be found at Github
<https://github.com/numpy/numpy/releases/tag/v1.12.0rc2> .
NumPy 1.12.0rc 2 is the result of 413 pull requests submitted by 139
contributors and comprises a large number of fixes and improvements. Among the
many improvements it is difficult to pick out just a few as standing above the
others, but the following may be of particular interest or indicate areas
likely to have future consequences.
* Order of operations in ``np.einsum`` can now be optimized for large speed
improvements.
* New ``signature`` argument to ``np.vectorize`` for vectorizing with core
dimensions.
* The ``keepdims`` argument was added to many functions.
* New context manager for testing warnings
* Support for BLIS in numpy.distutils
* Much improved support for PyPy (not yet finished)
Enjoy,
Chuck