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])