def suggest(q): ml = [] for result in topNQueries(q): # print result # print '='*50 # print result # print 'If you like \"%s\" by %s, you should read:'%(result[0],result[1]) reco = ha.recommendations(result[3]) if reco[1] == None: continue l = list() for bk in reco[1]: d = dict([('book', bk[0]), ('author', bk[1]), ('link', bk[2])]) l += [d] ml += [l] print json.dumps(ml)
def suggest(q): f = sys.stdout#('reco_%s.txt'%('_'.join(q.split())),'w') g = open('mrr.txt','w') #most recent recommendations for result in topNQueries(q): # print result # print '='*50 # print result # print 'If you like \"%s\" by %s, you should read:'%(result[0],result[1]) reco = ha.recommendations(result[3]) if reco[1] == None: continue f.write('If you like \"%s\" by %s, you should read:\n'%(result[0],result[1])) g.write('%s\n%s\n\n'%(result[0],result[1])) for bk in reco[1]: # print '\t- \"%s\" by %s'%(bk[0],bk[1]) # print '\t(%s)'%bk[2] f.write('\n\t- \"%s\" by %s\n'%(bk[0],bk[1])) f.write('\t (%s)\n'%bk[2]) g.write('%s\n'%bk[0]) g.write('%s\n'%bk[1]) g.write('%s\n\n'%bk[2])