A new version (0.3.5) of python-gnupg has been released.

[Vinay Sajip]

A new version of the Python module which wraps GnuPG has been
released.

What Changed?
=
This is a minor enhancement and bug-fix release. See the project
website ( http://code.google.com/p/python-gnupg/ ) for more
information. Summary:

Added improved shell quoting to guard against shell injection attacks.
Added search_keys() and send_keys() methods to interact with keyservers.
A symmetric cipher algorithm can now be specified when encrypting.
UTF-8 encoding is used as a fall back when no other encoding can be determined.
The key length now defaults to 2048 bits.
A default Name-Comment field is no longer provided during key generation.

What Does It Do?

The gnupg module allows Python programs to make use of the
functionality provided by the Gnu Privacy Guard (abbreviated GPG or
GnuPG). Using this module, Python programs can encrypt and decrypt
data, digitally sign documents and verify digital signatures, manage
(generate, list and delete) encryption keys, using proven Public Key
Infrastructure (PKI) encryption technology based on OpenPGP.

This module is expected to be used with Python versions = 2.4, as it
makes use of the subprocess module which appeared in that version of
Python. This module is a newer version derived from earlier work by
Andrew Kuchling, Richard Jones and Steve Traugott.

A test suite using unittest is included with the source distribution.

Simple usage:

 import gnupg
 gpg = gnupg.GPG(gnupghome='/path/to/keyring/directory')
 gpg.list_keys()
[{
  ...
  'fingerprint': 'F819EE7705497D73E3CCEE65197D5DAC68F1AAB2',
  'keyid': '197D5DAC68F1AAB2',
  'length': '1024',
  'type': 'pub',
  'uids': ['', 'Gary Gross (A test user) gary.gr...@gamma.com']},
 {
  ...
  'fingerprint': '37F24DD4B918CC264D4F31D60C5FEFA7A921FC4A',
  'keyid': '0C5FEFA7A921FC4A',
  'length': '1024',
  ...
  'uids': ['', 'Danny Davis (A test user) danny.da...@delta.com']}]
 encrypted = gpg.encrypt(Hello, world!, ['0C5FEFA7A921FC4A'])
 str(encrypted)
'-BEGIN PGP MESSAGE-\nVersion: GnuPG v1.4.9 (GNU/Linux)\n
\nhQIOA/6NHMDTXUwcEAf
...
-END PGP MESSAGE-\n'
 decrypted = gpg.decrypt(str(encrypted), passphrase='secret')
 str(decrypted)
'Hello, world!'
 signed = gpg.sign(Goodbye, world!, passphrase='secret')
 verified = gpg.verify(str(signed))
 print Verified if verified else Not verified
'Verified'

For more information, visit http://code.google.com/p/python-gnupg/ -
as always, your feedback is most welcome (especially bug reports,
patches and suggestions for improvement). Enjoy!

Cheers

Vinay Sajip
Red Dove Consultants Ltd.
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Support the Python Software Foundation:
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[ANN] numexpr 2.2 released

[Francesc Alted]

==
 Announcing Numexpr 2.2
==

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 wears multi-threaded capabilities, as well as support for Intel's
VML library (included in Intel MKL), 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.

Its only dependency is NumPy (MKL is optional), so it works well as an
easy-to-deploy, easy-to-use, computational kernel for projects that
don't want to adopt other solutions that require more heavy
dependencies.

What's new
==

This release is mainly meant to fix a problem with the license the
numexpr/win32/pthread.{c,h} files emulating pthreads on Windows. After
persmission from the original authors is granted, these files adopt
the MIT license and can be redistributed without problems.  See issue
#109 for details
(https://code.google.com/p/numexpr/issues/detail?id=110).

Another important improvement is the algorithm to decide the initial
number of threads to be used.  This was necessary because by default,
numexpr was using a number of threads equal to the detected number of
cores, and this can be just too much for moder systems where this
number can be too high (and counterporductive for performance in many
cases).  Now, the 'NUMEXPR_NUM_THREADS' environment variable is
honored, and in case this is not present, a maximum number of *8*
threads are setup initially.  The new algorithm is fully described in
the Users Guide now in the note of 'General routines' section:
https://code.google.com/p/numexpr/wiki/UsersGuide#General_routines.
Closes #110.

In case you want to know more in detail what has changed in this
version, see:

http://code.google.com/p/numexpr/wiki/ReleaseNotes

or have a look at RELEASE_NOTES.txt in the tarball.

Where I can find Numexpr?
=

The project is hosted at Google code in:

http://code.google.com/p/numexpr/

You can get the packages from PyPI as well:

http://pypi.python.org/pypi/numexpr

Share your experience
=

Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.


Enjoy data!

-- 
Francesc Alted
-- 
http://mail.python.org/mailman/listinfo/python-announce-list

Support the Python Software Foundation:
http://www.python.org/psf/donations/