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[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

ProfitPy is a set of libraries and tools for the development, testing, and execution of automated stock trading systems Specifically, ProfitPy is a collection of Python packages, modules, and scripts that work together to help you implement an automated stock trading program (or programs). The package features: A library with classes for accounts, orders, tickers, and more A GUI program for executing and plotting trades in real-time A GUI tool to collect ticker data for off-line use A CLI tool to back-test trading strategies Dozens of technical indicators and plotting widgets to display them An X11 keystroke tool for automating the TWS application

StatPy: Statistical Computing with Python Welcome to StatPy, a collection of resources to help you do statistical computing with Python, with a special emphasis on astrostatistics (statistics in astronomy). This web site is brand-spanking-new, and still very much under construction; please be patient with our "dust" and check back again frequently as building continues.

What is Py++? Definition: Py++ is an object-oriented framework for creating a code generator for Boost.Python library. Py++ uses few different programming paradigms to help you to expose C++ declarations to Python. This code generator will not stand on your way. It will guide you through the whole process. It will raise warnings in the case you are doing something wrong with a link to the explanation. And the most important it will save your time - you will not have to update code generator script every time source code is changed.

PyCHM - Python bindings for CHMLIB PyCHM is a package that provides bindings for Jed Wing's CHMLIB library. The chm package contains four modules, namely chm.chm, chm.chmlib, chm.extra and chm._chmlib. chm.chmlib is a low level wrapper module around the API provided by the C library chmlib. Quoted from Jed's README: chmlib is a small library designed for accessing MS ITSS files. The ITSS file format is used for Microsoft Html Help files (.chm), which have been the predominant medium for software documentation from Microsoft during the past several years, having superceded the previously used .hlp file format. chm.chm provides some high level functionality over chm.chmlib, such as access to the .chm file contents tree. chm.extra contains extra functionality to allow detection encodings in the CHM archives and to support full-text search.

Document options Document options requiring JavaScript are not displayed Rate this pageHelp us improve this contentLevel: IntroductoryDavid Mertz (mertz@gnosis.cx), Applied Metaphysician, Gnosis Software, Inc. 01 Mar 2001Although users usually think of Python as a procedural and object-oriented language, it actually contains everything you need for a completely functional approach to programming. This article discusses general concepts of functional programming, and illustrates ways of implementing functional techniques in Python. We'd better start with the hardest question: "What is functional programming (FP), anyway?" One answer would be to say that FP is what you do when you program in languages like Lisp, Scheme, Haskell, ML, OCAML, Clean, Mercury, or Erlang (or a few others). That is a safe answer, but not one that clarifies very much. Unfortunately, it is hard to get a consistent opinion on just what FP is, even from functional programmers themselves. A story about elephants and blind men seems apropos here. It is also safe to contrast FP with "imperative programming" (what you do in languages like C, Pascal, C++, Java, Perl, Awk, TCL, and most others, at least for the most part).