Q:

How can I programmatically generate relevant tags for a database of URLs?

I'm writing an RSS reader in python as a learning exercise, and I would really like to be able to tag individual entries with keywords for searching.  Unfortunately, most real-world feeds don't include keyword metadata.  I currently have about 60,000 entries in my test database from about 600 feeds, so manually tagging is not going to be effective.  So far I have only been able to find two solutions:
1: Use Natural Language Toolkit to extract keywords:

Pros: flexible; no dependencies on external services;
Cons: can only index the article summary, not the article; non-trivial: writing a high quality keyword extraction tool is a project in itself;

2: Use the Google Adwords API to fetch keyword suggestions from the article url:

Pros: Super high quality keywords; based on entire article text; easy to use;
Cons: Not free(?); Query rate limits unknown; I'm terrified of getting my account banned and not being able to run adwords campaigns for my commercial sites;

Can anyone offer any suggestions?  Are my fears about getting my adwords account banned unfounded?

A:

You can use delicious suggested tags API.
An example of how to use the api via python http://www.michael-noll.com/projects/delicious-python-api/
An other alternative is Open Calais

