def query(self, query_text, n=10):
        """Return a list of n (score, docid) pairs for the best matches.
        Also handle the special syntax for 'learn: command'."""
        if query_text.startswith("learn:"):
            doctext = os.popen(query_text[len("learn:"):], 'r').read()
            self.index_document(doctext, query_text)
            return []
        qwords = [w for w in words(query_text) if w not in self.stopwords]
        shortest = argmin(qwords, lambda w: len(self.index[w]))
        docs = self.index[shortest]
        results = [(sum([self.score(w, d) for w in qwords]), d) for d in docs]
        results.sort(); results.reverse()
        return results[:n]
def query(self, query_text, n=10):
        """Return a list of n (score, docid) pairs for the best matches.
        Also handle the special syntax for 'learn: command'."""
        if query_text.startswith("learn:"):
            doctext = os.popen(query_text[len("learn:"):], 'r').read()
            self.index_document(doctext, query_text)
            return []
        qwords = [w for w in words(query_text) if w not in self.stopwords]
        shortest = argmin(qwords, lambda w: len(self.index[w]))
        docs = self.index[shortest]
        results = [(sum([self.score(w, d) for w in qwords]), d) for d in docs]
        results.sort(); results.reverse()
        return results[:n]
def query ( self , query_text , n = 10 ) : if query_text . startswith ( "learn:" ) : doctext = os . popen ( query_text [ len ( "learn:" ) : ] , 'r' ) . read ( ) self . index_document ( doctext , query_text ) return [ ] qwords = [ w for w in words ( query_text ) if w not in self . stopwords ] shortest = argmin ( qwords , lambda w : len ( self . index [ w ] ) ) docs = self . index [ shortest ] results = [ ( sum ( [ self . score ( w , d ) for w in qwords ] ) , d ) for d in docs ] results . sort ( ) results . reverse ( ) return results [ : n ]
Return a list of n (score, docid) pairs for the best matches.
        Also handle the special syntax for 'learn: command'.
Return a list of n ( score docid ) pairs for the best matches . Also handle the special syntax for learn : command .