It seems that apart from top-posting, you forgot to reply to the list. David Shi wrote: > lxml looks interesting to me as it deals with CDATA. > > Where is the step by step guide to use lxml to do what I need to do, as > per my previous email.
I do not know any step-by-step guide that describes how to convert an XML format to .dbf. I guess you'll have to figure out the mapping code yourself to a certain extent. I gave you quite a number of references including some tutorials and a link to a library that handles the dbf format. If you want someone else to write the program for you for free, you should say so. Stefan > --- On Wed, 7/1/09, Stefan Behnel wrote: > > From: Stefan Behnel <stefan...@behnel.de> > Subject: Re: [XML-SIG] Recipe 534109: XML to Python data structure > To: "David Shi" <davidg...@yahoo.co.uk> > Cc: xml-sig@python.org > Date: Wednesday, 7 January, 2009, 12:42 PM > > David Shi wrote: >> What I am trying to do is to have a generic script to turn xml to Python >> dataset. Then I can manipulate it as required. Then I can save >> processed data into a .dbf file. > > I'd use iterparse() for the parsing, that allows you to construct the .dbf > content on the fly. > > http://codespeak.net/lxml/parsing.html#iterparse-and-iterwalk > > Working with the data elements returned by the iterparse iterator is quite > easy, you'll be fine with using the properties .tag and .text, as well as > the .find() method to find subelements. > > http://codespeak.net/lxml/tutorial.html#the-element-class > > If you can afford to load the entire XML tree into memory, you can also > try lxml.objectify, which will give you a Python-like interface to the > data. > > http://codespeak.net/lxml/objectify.html > > Note that the lxml.objectify in-memory tree is most likely a lot more > memory friendly (and the parsing is definitely faster) than what the > recipe gives you. > > Stefan _______________________________________________ XML-SIG maillist - XML-SIG@python.org http://mail.python.org/mailman/listinfo/xml-sig
