From: Daniel C. <dan...@ya...> - 2000-05-10 20:09:34
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I asked: > In the meantime have you considered adding a live query to the > Pubmed/Entrez query engine? You can get probably get medline results back > to read into Pyblio without too much work, as described here: > > http://www.ncbi.nlm.nih.gov/entrez/query/static/linking.html Frederic responded: Have you seen a way _not_ to get an HTML output for a query ? Because a module that doesn't rely on the HTML formatting would be much more robust... According to the docs (I searched 'em up and down too :), they want you to get the html first, which seems wasteful especially because you can get the citation format if you want within the html. _But_ they still accept the old format (old as of 3-6 months ago) queries and will return just citations, as described here: http://www.ncbi.nlm.nih.gov/entrez/utils/qmap_help.html I poked through the source from our old DubMed project and found the old format: http://www.ncbi.nlm.nih.gov/entrez/utils/qmap.cgi?db=m&form=4&term=cancer[text]&dispmax=3&html=no&dopt=l Some of the values we can tweak in this old format include: html=no the magic bit :) form=4 AND term=someterm[somefield] does a normal search; the term value can grow to handle lots of fields and boolean logic. form=6 AND uid=someuid AND dopt=m looks for medline 'neighbors' (aka related articles) for the given article uid dopt=q returns only a hit count for your given search. According to Matt's code (in java, if you're interested see http://oldap.med.yale.edu/cgi-bin/cvsweb.cgi/dubmed/URLBuilder.java?rev=1.2&content-type=text/x-cvsweb-markup ) the dopt values can be combined, aka, dopt=mq => neighbors, count only. I have no idea if it's worth implementing this old style query. They don't seem to mind but they could theoretically always turn off the converter. If you are interested in trying it out the new way, attached is some skeleton code for getting back medline cites from a keyword term search taken from argv. This is actually my first bit of python code... I'm almost done with _Learning Python_ and I'm very impressed with how straightforward this language is. :) Anyway my apologies in advance if it seems poorly organized. -Dan |