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To attempt to explain it in the simplest terms, a continuation is a representation, at a particular point in a program, of everything the program is capable of doing subsequently. A continuation is a potential that depends on initial conditions. Rather than loop in a traditional way, it is possible to invoke the same continuation recursively with different initial conditions. One broad claim I have read is that continuations, in a theoretical sense, are more fundamental and underlie every other control structure. Don't worry if these ideas cause your brain to melt; that is a normal reaction.

One of my recent research tasks required me to retrieve various information from del.icio.us, a well-known social bookmarking service. My programming language of choice is Python, and so I wrote a basic Python module for getting the data I needed.

my Python threads programming tutorial

Pycha is a very simple Python package for drawing charts using the great Cairo library. Its goals are: Lightweight Simple to use Nice looking with default values Customization It won't try to draw any possible chart on earth but draw the most common ones nicely. There are some other options you may want to look at like pyCairoChart Pycha is based on Plotr which is based on PlotKit. Both libraries are written in JavaScript and are great for client web programming. I needed the same for the server side so that's the reason I ported Plotr to Python. Now we can deliver charts to people with JavaScript disabled or embed them in PDF reports.

This is first version at CodePlex. PySpec is BDD framework for python. It includes following items PySpec for CUIPySpec for wxPython(little buggy)Any documents(tutorial, reference)

Tired of debugging Python using print statements? Don't like the cumbersome PDB (Python debugger) console? Prefer using Vim for coding your Python programs? VimPdb is the solution - allows debugging Python in an IDE-fashion, right within the Vim editor.

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.

What's the relation between these benefits and Stackless's implementation details? Here's a quick sketch: Continuations are the general-purpose concurrency construct. A continuation represents all the future computations of a particular program. Capturing all this control flow in a single conceptual object makes it programmable: It becomes possible to calculate or reason over the control flow. In particular, there's great scope for optimizing assignment of different calculations to different processes or threads or even hosts.

PyInstaller is a program that converts (packages) Python programs into stand-alone executables, under Windows, Linux and Irix. Its main advantages over similar tools are that PyInstaller works with any version of Python since 1.5, it builds smaller executables thanks to transparent compression, it is multi-platform (so you can build one-file binaries also under Linux), and use the OS support to load the dynamic libraries, thus ensuring full compatibility. PyInstaller is an effort to rescue, maintain and further develop Gordon McMillan's Python Installer (now PyInstaller). Their official website is not longer available and the original package is not longer maintained. Believing that it is still far superior to py2exe, we have setup this site to continue its further development. Feel free to join us in the effort! Please consult our Roadmap to check our plans. Also usage reports are welcomed: let us know if PyInstaller works for you and how, or what problems you found in using it.

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):