Chapter 5. Internet Tools and Techniques

Be strict in what you send, and lenient in what you accept.

Internet Engineering Task Force

Internet protocols in large measure are descriptions of textual formats. At the lowest level, TCP/IP is a binary protocol, but virtually every layer run on top of TCP/IP consists of textual messages exchanged between servers and clients. Some basic messages govern control, handshaking, and authentication issues, but the information content of the Internet predominantly consists of texts formatted according to two or three general patterns.

The handshaking and control aspects of Internet protocols usually consist of short commands and sometimes challenges sent during an initial conversation between a client and server. Fortunately for Python programmers, the Python standard library contains intermediate-level modules to support all the most popular communication protocols: poplib, smtplib, ftplib, httplib, telnetlib, gopherlib, and imaplib. If you want to use any of these protocols, you can simply provide required setup information, then call module functions or classes to handle all the lower-level interaction. Unless you want to do something exotic such as programming a custom or less common network protocol there is never a need to utilize the lower-level services of the socket module.

The communication level of Internet protocols is not primarily a text processing issue. Where text processing comes in is with parsing and production of compliant texts, to contain the content of these protocols. Each protocol is characterized by one or a few message types that are typically transmitted over the protocol. For example, POP3, NNTP, IMAP4, and SMTP protocols are centrally means of transmitting texts that conform to RFC-822, its updates, and associated RFCs. HTTP is firstly a means of transmitting Hypertext Markup Language (HTML) messages. Following the popularity of the World Wide Web, however, a dizzying array of other message types also travel over HTTP: graphic and sounds formats, proprietary multimedia plug-ins, executable byte-codes (e.g., Java or Jython), and also more textual formats like XML-RPC and SOAP.

The most widespread text format on the Internet is almost certainly human-readable and human-composed notes that follow RFC-822 and friends. The basic form of such a text is a series of headers, each beginning a line and separated from a value by a colon; after a header comes a blank line; and after that a message body. In the simplest case, a message body is just free-form text; but MIME headers can be used to nest structured and diverse contents within a message body. Email and (Usenet) discussion groups follow this format. Even other protocols, like HTTP, share a top envelope structure with RFC-822.

A strong second as Internet text formats go is HTML. And in third place after that is XML, in various dialects. HTML, of course, is the lingua franca of the Web; XML is a more general standard for defining custom "applications" or "dialects," of which HTML is (almost) one. In either case, rather than a header composed of line-oriented fields followed by a body, HTML/XML contain hierarchically nested "tags" with each tag indicated by surrounding angle brackets. Tags like HTML's <body>, <cite>, and <blockquote> will be familiar already to most readers of this book. In any case, Python has a strong collection of tools in its standard library for parsing and producing HTML and XML text documents. In the case of XML, some of these tools assist with specific XML dialects, while lower-level underlying libraries treat XML sui generis. In some cases, third-party modules fill gaps in the standard library.

Various Python Internet modules are covered in varying depth in this chapter. Every tool that comes with the Python standard library is examined at least in summary. Those tools that I feel are of greatest importance to application programmers (in text processing applications) are documented in fair detail and accompanied by usage examples, warnings, and tips.

Text Processing in Python
Text Processing in Python
ISBN: 0321112547
EAN: 2147483647
Year: 2005
Pages: 59
Authors: David Mertz

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