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Charming Python: Using state machinesAlgorithms and programming approaches in Python

Charming Python: SimPy simplifies complex models

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.

Stackless Python is an alternative implementation of Python created by independent developer Christian Tismer. He started with the conventional Python language processor managed by the language's inventor, Guido van Rossum, and patched his own Stackless invention in place of a small but central part of Python's internals. Stackless Python is the result. This article introduces Tismer's technology and its significance. In future articles, you'll be able to read about how to make your own start at programming Stackless Python, as well as the prospects for a merger between Stackless and the main Python distribution.

Last week we looked at the itertools module and how its iterator based functions can be faster than doing things from scratch. One of the examples showed a function using itertools.takewhile to be much faster than one using itertools.groupby. Some feedback we got, asked, what then is the point of groupby if it's just a slower version of other functionality?

6.5.1 Itertool functions The following module functions all construct and return iterators. Some provide streams of infinite length, so they should only be accessed by functions or loops that truncate the stream.

he most popular cryptographic software for Windows is probably TrueCrypt. In this article I will explain how TrueCrypt works and as a by-product a working Python implementation will be provided. This article is written from a programmer perspective and the math will be kept to the minimum. The emphasis is on how TrueCrypt uses cryptographic primitives such as AES and SHA-1, not how the primitives themselves work.

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.