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Charming Python: My first Web-based filtering proxy
This article introduces Txt2Html, a public-domain working project created by David to illustrate programming techniques in Python. Txt2Html is a "Web-based filtering proxy" -- a program that reads Web-based documents for the user, then presents a modified page to the user's browser. To make this possible, Txt2Html runs as a CGI program, queries outside Web resources, and makes use of regular-expressions. David steps you through each of these general-purpose subtasks, explaining, clarifying, and demonstrating along the way.
Articles 01 Jul 2000
Charming Python: Using state machines
State machines, in a theoretical sense, underlie almost everything related to computers and programming. And it also turns out that state machines, in a practical sense, can help solve many ordinary problems (especially for Python programmers). In this article, David Mertz discusses some practical examples of when and how to code a state machine in Python.
Also available in: Japanese  
Articles 01 Aug 2000
Charming Python: Text processing in Python
Along with several other popular scripting languages, Python is an excellent tool for scanning and manipulating textual data. This article summarizes Python's text processing facilities for the programmer new to Python. The article explains some general concepts of regular expressions and offers advice on when to use (or not use) regular expressions while processing text.
Also available in: Russian   Japanese  
Articles 01 Sep 2000
Charming Python: Curses programming
A certain class of Python applications works best with an interactive user interface without the overhead or complexity of a graphical environment. For interactive text-mode programs (under Linux/UNIX), for example, the ncurses library, wrapped in Python's standard curses module, is just what you need. In this article, David Mertz discusses the use of curses in Python. He illustrates the curses environment using sample source code from a front-end to the Txt2Html program.
Also available in: Japanese  
Articles 01 Sep 2000
Charming Python: TK programming in Python
David Mertz introduces TK and the Tkinter wrapper (Python's GUI library) with source code samples accompanied by detailed running commentary. To make life easy, he illustrates his examples with the GUI port of the Txt2Html front-end that he's used in many of his earlier articles. He assumes, of course, that you follow his column regularly. :)
Articles 01 Dec 2000
Charming Python: Updating your Python reading list
In little more than a year, the availability of material for learning and programming in Python has gone from a thin selection of books to the current forest of dead trees. Some books are general introductions to the Python language, while others specialize in particular tasks. Even within the 'general' category, level and focus differ considerably. This column gives David's impressions and recommendations on eight of the best known books about Python.
Articles 01 Feb 2001
Charming Python: Developing a full-text indexer in Python
As the volume of information grows, effective means of locating specific information become ever more crucial. This column discusses the field of full-text indexing, with a focus on the author's public-domain indexer module.
Articles 01 May 2001
Charming Python: pydoc and distutils modules
The introduction of several modules and tools in recent Python versions has improved Python, not so much as a language, but as a tool. Author David Mertz reviews these modules that make the job of Python developers substantially easier by improving the documentation and distribution of Python modules and packages.
Also available in: Japanese  
Articles 01 Aug 2001
Charming Python: Parsing with the SimpleParse module
Many parsing tools have been written for Python. This column discusses a high-level parsing language built on top of Python.
Also available in: Japanese  
Articles 01 Jan 2002
Charming Python: Implementing "weightless threads" with Python generators
David Mertz introduces weightless threads. Similar to Stackless Python microthreads, but using standard Python 2.2 -- they allow for extremely large numbers of cooperating processes with virtually no overhead.
Articles 01 Jun 2002
Charming Python: Generator-based state machines
Introduced in Python 2.2, simple generators may be used to simplify state machines and to simulate coroutines. Coroutines are an exotic flow mechanism that few widely used languages -- not even non-Stackless Python -- allow. Python's new generators, however, get you almost all the way to coroutines, and the extra few steps can be faked. In this installment of Charming Python, David Mertz explains all the relevant concepts through illustrative code samples.
Also available in: Russian   Japanese  
Articles 01 Jul 2002
Charming Python: Parsing with the Spark module
Spark is a powerful and general parser/compiler framework written in Python. In some respects, Spark offers more than SimpleParse or other Python parsers. Being pure Python, however, it is also slower. In this article, David discusses the Spark module, with code samples, an explanation of its usage, and suggestions for its areas of application.
Articles 01 Aug 2002
Charming Python: Make Python run as fast as C with Psyco
With only a tiny amount of extra programming, Python programmers can often increase code speed by orders of magnitude with the help of an external module known as the Python Specializing Compiler (or Psyco for short). David Mertz looks at what Psyco is, and tests it in some applications.
Also available in: Russian   Japanese  
Articles 01 Oct 2002
Charming Python: SimPy simplifies complex models
The stochastic behavior of real-world systems is often difficult to understand or predict. Sometimes it is possible rigorously to demonstrate statistical properties of systems, such as average, worst-case, and best-case performance features. But at other times, pitfalls of concrete designs only become evident when you actually run (or simulate) a system. In this article, David takes a look at SimPy, a Python package that allows you to very easily create models of discrete event systems.
Also available in: Japanese  
Articles 01 Dec 2002
Charming Python: Create declarative mini-languages
The object orientation and transparent introspective capabilities of Python allow you to easily create declarative mini-languages for programming tasks. In this installment, David looks not so much at using Python to interpret or translate other specialized languages (although that is possible), but rather the ways that Python code itself can be helpfully restricted to a set of declarative elements. He'll show you how developers can use declarative techniques to state application requirements in a concise and clear way, while letting the behind-the-scenes framework do the heavy work.
Also available in: Russian   Japanese  
Articles 27 Feb 2003
Charming Python: Multiple dispatch
Object-oriented programming gains much of its versatility through polymorphism: objects of different kinds can behave in similar ways, given the right contexts. But most OOP programming is single dispatch; that is, just one designated object determines which code path is taken. Conceptually, a more general technique is to allow all the arguments to a function/method to determine its specialization. This article presents an implementation of multiple dispatch in Python, and shows examples where this makes for better programs."
Also available in: Russian   Japanese  
Articles 20 Mar 2003
Charming Python: Using combinatorial functions in the itertools module
Python 2.2 introduced simple generators to the Python language and reconceived standard loops in terms of underlying iterators. With Python 2.3, generators become standard (no need for _future_, and the new module itertools is introduced to work flexibly with iterators. The itertools module is essentially a set of combinatorial higher-order functions, but ones that work with lazy iterators rather than with finite lists. In this installment, David explores the new module, and gives you a sense of the new expressive power available with combinatorial iterators.
Also available in: Russian  
Articles 12 Jun 2003
Charming Python: Get started with the Natural Language Toolkit
In this installment, David introduces you to the Natural Language Toolkit, a Python library for applying academic linguistic techniques to collections of textual data. Programming that goes by the name "text processing" is a start; other capabilities for syntactic and even semantic analysis are further specialized to studying natural languages.
Articles 24 Jun 2004
Charming Python: Easy Web data collection with mechanize and Beautiful Soup
For collecting data from Web pages, the mechanize library automates scraping and interaction with Web sites. Mechanize lets you fill in forms and set and save cookies, and it offers miscellaneous other tools to make a Python script look like a genuine Web browser to an interactive Web site. A frequently used companion tool called Beautiful Soup helps a Python program makes sense of the messy "almost-HTML" that Web sites tend to contain.
Also available in: Portuguese  
Articles 24 Nov 2009
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