def set_math_knowledge_inv_index(redis_db):
qfactor_keys = get_all_question_factor_keys(redis_db)
keys = reduce(list.__add__, qfactor_keys.values())
k_idx = {}
for key in keys:
qtype, qid = key.split('/')[-2:]
k_str, m_str, k_m_str, diff = redis_db.lrange(key, 0, -1)
k_mat = load_matrix(k_str)
for ktag in k_mat.keys():
k_idx.setdefault(ktag, {})
value = ":".join([qid, diff])
k_idx[ktag].setdefault(qtype, []).append(value)
modified_fields = set()
for ktag, item in k_idx.iteritems():
for qtype, qids in item.iteritems():
field = '%s:%s' % (ktag, qtype)
value = "|".join(qids) # qids 中每项是 'qid:k_mat_value'
redis_db.hset(MATH_KNOWLEDGE_INV_INDEX, field, value)
modified_fields.add(field)
flush_inv_index(redis_db, MATH_KNOWLEDGE_INV_INDEX, modified_fields)
def _extractor(x):
mat = load_matrix(x)
res = [":".join([str(tag), diff]) for tag in mat.keys()]
return "|".join(res)
def load_card_factor(redis_db, key):
try:
k_str = redis_db.get(key)
except ValueError:
k_str = '{}'
return load_matrix(k_str)
def _extractor(x):
mat = load_matrix(x)
res = [":".join([str(tag), diff]) for tag in mat.keys()]
return "|".join(res)
