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        "description": "#Bioscraping\n\nWeb scrapers to interact with remote databases programatically in Python \nthat makes a local cache of web data with sqlite3 to prevent excessive web \ntraffic.\n\nSo far, implemented:\n\n* [Uniprot](http://uniprot.org) by uniprot protein ID. (e.g. 'Q8BP71')\n* [PubMed](www.ncbi.nlm.nih.gov/pubmed/) by PMID (e.g. '24213538')\n  \n#Install\n\n##Python 2.7.x and 3.x\n`pip install bioscraping`\n\n#Test\n\nReal unit tests are absent, but you can test basic functionality with \n`python test/not_a_real_test.py`.\n\n#Usage\n\n##PubMed\n    from bioscraping import PubMedClient\n    \n    pubmed = PubMedClient()\n\ndefaults to writing a file called `.bioscraping.pubmed.sqlite.db`. Use `PubMedClient(\":memory:\")` for in-memory data storage.\n\n    pubmed.fetch(<PMID>)\n    \nReturns text with author and abstract for PMID. \n\n##Uniprot\n\n    from bioscraping import UniprotClient\n    \n    uniprot = UniprotClient()\n\ndefaults to writing a file called `.bioscraping.uniprot.sqlite.db`. Use `UniprotClient(\":memory:\")` for in-memory data storage.\n\n    uniprot.fetch(<Uniprot ID>)\n\nReturns a dictionary of data parsed from xml.\n\n#Buyer beware\n\nUniprotClient has a potential race condition and tempfile needs to be \nimplemented before it is safe for concurrent processes. (see TODO)\n",
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