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Use a staticmethod when you know which class you want to access as you are writing the code.

Use a classmethod if you have a class hierarchy and want the method to operate on the actual class used in the call rather than the class where it was defined:

PyACTS- http://www.pyacts.org -- PyACTS is a collection of Python Modules that are very useful to Parallel Computing in a High Performance Computing environment. This packages incorporates several modules like PyBLACS (allows communication data for Linear Algebra), PyPBLAS (distributed Matrix Operations) and PyScaLAPACK (solve linear systems and get the eigenvalue problems). These libraries are part of PyACTS project that provide interfaces to the ACTS Collection. Also is provided a parrallel interpreter for using this package that implements message-based parallel programming using MPI.

Pypar does not require the Python interpreter to be modified or recompiled: Parallel python programs use the standard Python and need merely import the pypar module. This means for example that you can upgrade Python independently of your parallel codes.

Pypar is an efficient but easy-to-use module that allows programs/scripts written in the Python programming language to run in parallel on multiple processors and communicate using message passing. Pypar provides bindings to an important subset of the message passing interface standard MPI. Other Python MPI bindings available from other developers include: PyMPI, Scientific Python and pythonMPI.

This is something I always forget how to do, and it's kind of hard to Google or search the Python docs because you can't search for **.The point is, when using **kwargs, you have to use the ** prefix not only in the function definition, but also in the call, prefixed to the variable you want to use as a keyword dictionary.

Install using binary installer Download installer from http://ipython.scipy.org/dist/pyreadline-1.3.win32.exe make sure no other readline is installed run installer The configuration file pyreadlineconfig.ini can be copied from Python24/lib/site-packages/pyreadline/configuration to your HOME directory (usually c:/documents and settings/YOURNAME). When using ipython pyreadline is automatically activated. If you want to use pyreadline from the interactive prompt of the python interpreter then you have to include the code in Python24/lib/site-packages/pyreadline/configuration/startup.py in your pythonstartup file or set the PYTHONSTARTUP environment variable to point to that file. Manual can be found in Python24/share/doc/pyreadline

So here is my own personal gentle introduction to using pdb. It assumes that you are not using any IDE -- that you're coding Python with a text editor and running your Python programs from the command line.

This tutorial teaches the fundamental concepts of symbolic debuggers. We will be using Winpdb to debug Python scripts. The concepts that you learn here, however, are fundamental to working with debuggers in general. At the end of the exercise, you should feel comfortable with using symbolic debuggers and have an inherent understanding of why these tools prove to reduce time and effort needed in debugging without altering the code itself to do so.

Given Python's goal to be a powerful and easy-to-use scripting language, its features for working with dates and times are not as user-friendly as they should be. The purpose of pyfdate is to remedy that situation by providing features for working with dates and times that are as powerful and easy-to-use as the rest of Python.

PyProtocols extends the PEP 246 adapt() function with a new "declaration API" that lets you easily define your own protocols and adapters, and declare what adapters should be used to adapt what types, objects, or protocols.  In addition to its own Interface type, PyProtocols can also use Twisted and Zope's Interface types too.  (Of course, since Twisted and Zope interfaces aren't as flexible, only a subset of the PyProtocols API works with them.  Specific limitations are listed in the documentation.)

I wrote dbtxt because I needed a small, flat database in a python environment that didn't depend upon any external libraries. Most libraries are contaminated with the GPL, and this needed to be OK for commercial distribution without any complications. So that's what we have here - a complete (though small) database system that depends on nothing at all other than the Python language and its internal libraries. The entire database comes in at about 20k bytes (that's right, "k", not hundreds of k or megabytes) and I was able to implement all the functions I needed. So I was happy. Will you be happy? Well, download it and read the docs and see what you think. The download, zipped, is about 13k. Yep. 13k. :-) By all means, if you have a need for the same kind of thing, feel free to make any use of dbtxt you please. I have released it as PD, so you can use it in projects that are commercial, GPL, BSD, PD, private, government... whatever you like. Below you'll find a basic description taken from beginning of the docs; in the archive you'll download there is complete documentation, two sample databases, a test program and the database engine itself.

[IPython-user] ipython1 and farm tasking Brian Granger ellisonbg.net@gmail.... Wed Feb 27 16:29:03 CST 2008 Previous message: [IPython-user] ipython1 and farm tasking Next message: [IPython-user] yet another leopard/readline question Messages sorted by: [ date ] [ thread ] [ subject ] [ author ] Alex, First, I would suggest updating your ipython1 install from our svn repository. We are about to push out a major new version and the documentation is _much_ better. Also, there are many new features that will hopefully help you. Here is a simple example (using the latest svn of ipython1): In [1]: from ipython1.kernel import client In [2]: mec = client.MultiEngineClient(('127.0.0.1',10105)) In [3]: tc = client.TaskClient(('127.0.0.1',10113)) In [4]: def fold_package(x): ...: return 2.0*x ...: In [5]: mec.push_function(dict(fold_package=fold_package)) Out[5]: [None, None, None, None] In [6]: tasks = [client.Task("y=fold_package(x)",push={'x':x},pull=('y',)) for x in range(128)] In [7]: task_ids = [tc.run(t) for t in tasks] In [8]: tc.barrier(task_ids) In [9]: task_results = [tc.get_task_result(tid) for tid in task_ids] In [10]: results = [tr.ns.y for tr in task_results] In [11]: print results [0.0, 2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 22.0, 24.0, 26.0, 28.0, 30.0, 32.0, 34.0, 36.0, 38.0, 40.0, 42.0, 44.0, 46.0, 48.0, 50.0, 52.0, 54.0, 56.0, 58.0, 60.0, 62.0, 64.0, 66.0, 68.0, 70.0, 72.0, 74.0, 76.0, 78.0, 80.0, 82.0, 84.0, 86.0, 88.0, 90.0, 92.0, 94.0, 96.0, 98.0, 100.0, 102.0, 104.0, 106.0, 108.0, 110.0, 112.0, 114.0, 116.0, 118.0, 120.0, 122.0, 124.0, 126.0, 128.0, 130.0, 132.0, 134.0, 136.0, 138.0, 140.0, 142.0, 144.0, 146.0, 148.0, 150.0, 152.0, 154.0, 156.0, 158.0, 160.0, 162.0, 164.0, 166.0, 168.0, 170.0, 172.0, 174.0, 176.0, 178.0, 180.0, 182.0, 184.0, 186.0, 188.0, 190.0, 192.0, 194.0, 196.0, 198.0, 200.0, 202.0, 204.0, 206.0, 208.0, 210.0, 212.0, 214.0, 216.0, 218.0, 220.0, 222.0, 224.0, 226.0, 228.0, 230.0, 232.0, 234.0, 236.0, 238.0, 240.0, 242.0, 244.0, 246.0, 248.0, 250.0, 252.0, 254.0] Or if you don't need load balancing: # This sends the fold_package function for you! results = mec.map(fold_package, range(128)) Let us know if you run into other problems. Cheers, Brian