PUBLIC MARKS from pvergain with tags python & template

I've just released templatemaker, which is something I've been hacking on and off (mostly off) the past couple of months. It's a Python library for extracting data from similarly formatted text strings. What the heck does that mean? Well, say you want to get the raw data from a bunch of Web pages that use the same template -- like restaurant reviews on Yelp.com, for instance. You can give templatemaker an arbitrary number of HTML files, and it will create the "template" that was used to create those files. ("Template," in this case, means a string with a number of "holes" in it, where the holes represent the parts of the page that change.) Once you've got the template, you can then give it any HTML file that uses that same template, and it will give you the raw data: "The value for hole 1 is 'July 6, 2007', the value for hole 2 is 'blue'," etc.

Templess is an XML templating library for Python, that is very compact and simple, fast, and has a strict seperation of logic and design. It is different from other templating languages because instead of 'asking' for data from the template, you 'tell' the template what content there is to render, and the template just provides placeholders. Instead of calling into your code from the template, all data for the template is prepared in the code before it is handed over to the templating engine to render. This makes Templess very suitable for programmers, since everything is done from the Python code layer rather than using some domain-specific language from the XML.

Mako is a template library written in Python. It provides a familiar, non-XML syntax which compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics.