def parse_headers(fp, _class=HTTPMessage):
    headers = []
    while True:
        line = fp.readline(_MAXLINE + 1)
        if len(line) > _MAXLINE:
            raise LineTooLong("header line")
        headers.append(line)
        if len(headers) > _MAXHEADERS:
            raise HTTPException("got more than %d headers" % _MAXHEADERS)
        if line in (b'\r\n', b'\n', b''):
            break
    hstring = bytes(b'').join(headers).decode('iso-8859-1')
    return email_parser.Parser(_class=_class).parsestr(hstring)
Add a list of feature extractors to the classifier. These feature extractors
dataset/ETHPy150Open OpenCobolIDE/OpenCobolIDE/open_cobol_ide/extlibs/future/backports/http/client.py/parse_headers--crossover with--dataset/ETHPy150Open sightmachine/SimpleCV/SimpleCV/MachineLearning/NaiveBayesClassifier.py/NaiveBayesClassifier.setFeatureExtractors