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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).

PyScripter and most Python IDEs redirect sys.stdout.  Also GUI apps like PyScripter have no standard output.  What you need to do is PyObject *f = PySys_GetObject("stdout") and then use PyFile_WriteString for writing to the sys.stdout. This is what Python itself is doing and I think this is the best way

UliPad uses Mixin and Plugin technique as its architecture. Most of its classes can be extended via mixin and plugin components, and finally become an integrity class when creating the instance. So UliPad is very dynamic. You can write the new features in new files, and hardly need to modify the existing code. And if you want to extend the existing classes, you could write mixins and plugins, and this will be bound to the target class that I call "Slot Class". This technique will make the changes centralized and easily managed.

Pyro is short for PYthon Remote Objects. It is an advanced and powerful Distributed Object Technology system written entirely in Python, that is designed to be very easy to use. Never worry about writing network communication code again, when using Pyro you just write your Python objects like you would normally. With only a few lines of extra code, Pyro takes care of the network communication between your objects once you split them over different machines on the network. All the gory socket programming details are taken care of, you just call a method on a remote object as if it were a local object!

I love python for its beautiful code and practicality. But it’s not going to win a pure speed race with most languages. Most people think of speed and ease-of-use as polar opposites - probably because they remember the pain of writing C. Cython tries to eliminate that duality and lets you have python syntax with C data types and functions - the best of both worlds. Keeping in mind that I’m by no means an expert at this, here are my notes based on my first real experiment with Cython:

You can use Microsoft Script Control. If you have the win32 extensions of python, you can use python in place of vb in this control -open the VBA script editor - In menus/Tools/References add Microsoft Script Control -Make a new module and declare a new MsScriptControl.ScriptControl Global sc as new MsScriptControl.ScriptControl -Initialize the language attibute with python - Note that you and users of your document must have python and its win32 extensions installed. Activestate python distribustion include it. You can put sc.language="python" in the routine Workbook_Open() Now you can import python modules using ExecuteStatement method of the control in vba and have results from python functions with eval method. One interesting thing is that you can pass an object to the control with AddObject method and have python manipulate it. And so on..

Global sc As New MSScriptControl.ScriptControl Public Function os_getcwd() sc.Language = "python" sc.ExecuteStatement ("import os") os_getcwd = sc.Eval("os.getcwd()") End Function With this you can set your Excel formula to =os_getcwd() For me it returns "C:\Documents and Settings\Administrator\My Documents", which I needed to know at the time so I didn't have to screw around with the ever annoying pythonpath. You can put the first two lines of the function in the Workbook_Open hook, but I don't know where that is. I hope to use more Python in Excel soon. Hmm, actually, I suppose you can put those first two lines of the function after the Global declaration as well. I know just about zero VBScript and didn't get a chance to do anything else beyond proof of concept yet. I figured I would write something dynamic which allowed more transparent access to Python, maybe allowing formula like =py("os.getcwd()"), etc.

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:

I hope this article encourages you to think about your command line programs in a different light, and to treat them as first class objects. Using inheritance to share code is so common in other areas of development that it is hardly given a second thought in most cases. As has been shown with the SQLiteAppBase programs, the same technique can be just as powerful when applied to building command line programs, saving development time and testing effort as a result. CommandLineApp has been used as the foundation for dozens of types of programs, and could be just what you need the next time you have to write a new command line program.

There are two applications that require using the NumPy array type in C extension modules: Access to numerical libraries: Extension modules can be used to make numerical libraries written in C (or languages linkable to C, such as Fortran) accessible to Python programs. The NumPy array type has the advantage of using the same data layout as arrays in C and Fortran. Mixed-language numerical code: In most numerical applications, only a small part of the total code is CPU time intensive. Only this part should thus be written in C, the rest can be written in Python. NumPy arrays are important for the interface between these two parts, because they provide equally simple access to their contents from Python and from C. This document is a tutorial for using NumPy arrays in C extensions.

In short: run your existing Python software much faster, with no change in your source. Think of Psyco as a kind of just-in-time (JIT) compiler, a little bit like what exists for other languages, that emit machine code on the fly instead of interpreting your Python program step by step. The difference with the traditional approach to JIT compilers is that Psyco writes several version of the same blocks (a block is a bit of a function), which are optimized by being specialized to some kinds of variables (a "kind" can mean a type, but it is more general). The result is that your unmodified Python programs run faster. Benefits 2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module. Drawbacks Psyco currently uses a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.

Few programming languages provide direct support for graphs as a data type, and Python is no exception. However, graphs are easily built out of lists and dictionaries. For instance, here's a simple graph (I can't use drawings in these columns, so I write down the graph's arcs):