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    "info": {
        "author": "Sebastien Briois",
        "author_email": "sebriois@gmail.com",
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        "classifiers": [
            "Environment :: Web Environment",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: BSD License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
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        "description": "=============\nBiomart 0.9.2\n=============\n\nPython API that consumes the biomart webservice.\n\nWhat it will do:\n----------------\n\n* Show all databases of a biomart server\n* Show all datasets of a biomart database\n* Show attributes and filters of a biomart dataset\n* Run your query formatted as a Python dict and return the Biomart response as TSV format.\n\nWhat it won't do:\n-----------------\n\n* Process and return the results as JSON,XML,etc.\n\nUsage\n-----\n\nImport Biomart module\n::\n  \n  from biomart import BiomartServer\n\nConnect to a Biomart Server\n::\n  \n  server = BiomartServer( \"http://www.biomart.org/biomart\" )\n  \n  # if you are behind a proxy\n  import os\n  server.http_proxy = os.environ.get('http_proxy', 'http://my_http_proxy.org')\n\n  # set verbose to True to get some messages\n  server.verbose = True\n\nInteract with the biomart server\n::\n  \n  # show server databases\n  server.show_databases() # uses pprint behind the scenes\n  \n  # show server datasets\n  server.show_datasets() # uses pprint behind the scenes\n  \n  # use the 'uniprot' dataset\n  uniprot = server.datasets['uniprot']\n\n  # show all available filters and attributes of the 'uniprot' dataset\n  uniprot.show_filters()  # uses pprint\n  uniprot.show_attributes()  # uses pprint\n\n\nRun a search\n::\n\n  # run a search with the default attributes - equivalent to hitting \"Results\" on the web interface.\n  # this will return a lot of data.\n  response = uniprot.search()\n  response = uniprot.search( header = 1 ) # if you need the columns header\n  \n  # response format is TSV\n  for line in response.iter_lines():\n    line = line.decode('utf-8')\n    print(line.split(\"\\t\"))\n  \n  # run a count - equivalent to hitting \"Count\" on the web interface\n  response = uniprot.count()\n  print(response.text)\n\n  # run a search with custom filters and default attributes.\n  response = uniprot.search({\n    'filters': {\n        'accession': 'Q9FMA1'\n    }\n  }, header = 1 )\n  \n  response = uniprot.search({\n    'filters': {\n        'accession': ['Q9FMA1', 'Q8LFJ9']  # ID-list specified accessions\n    }\n  }, header = 1 )\n  \n  # run a search with custom filters and attributes (no header)\n  response = uniprot.search({\n    'filters': {\n        'accession': ['Q9FMA1', 'Q8LFJ9']\n    },\n    'attributes': [\n        'accession', 'protein_name'\n    ]\n  })\n\n\nShortcut function: connect directly to a biomart dataset\n*This is short in code but it might be long in time since the module needs to fetch all server's databases to find your dataset.*\n::\n  \n  from biomart import BiomartDataset\n  \n  interpro = BiomartDataset( \"http://www.biomart.org/biomart\", name = 'entry' )\n  \n  response = interpro.search({\n    'filters': { 'entry_id': 'IPR027603' },\n    'attributes': [ 'entry_name', 'abstract' ]\n  })",
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