From a performance standpoint I'd like to know how to best implement this. Speed is important:
I have a comma delimited file that I imported into a (Python) dictionary. This may not be the best way to do this though. Maybe just nested lists would be better? The comma delimited file will only need to be updated annually. So it's pretty static. Original line from file: 1234, This list describes this code My decidely backwards dictionary: {1234: ['This','list', 'describes', 'this', 'code']} I have a set of codes 2 - 6 characters long. A string of varying lengths (usually 3 - 10 words) describe the code. I will need to take a paragraph of text and determine the most appropriate code based on key words from the paragraph that match up to code descriptions. I was going to do this in DTML but 15,000+ codes (even using a BTree folder) is painfully slow. Anyway I pickled the dictionary and it's just over 1.3MB so I thought I'd use an external method to read the pickled object, pass it the paragraph and test for the correct code(s), then return a list. Is this the most effective way to use Python/Zope for this situation? Thanks, -- Tim Cook -- Cook Information Systems | Office: (901) 884-4126 8am-5pm CDT * Specializing in Open Source Business Systems * FreePM Project Coordinator http://www.freepm.org OSHCA Founding Supporter http://www.oshca.org