def save(self):
"""docstring for save"""
if not self.title:
return False
data = {
'name': self.name,
'id': self.id,
'title': self.title
}
if self.exts:
data.update(self.exts)
pipe = util.redis.pipeline()
# 将原始数据存入 hashes
res = pipe.hset(self.name, self.id, json.dumps(data))
# 保存 sets 索引，以分词的单词为key，用于后面搜索，里面存储 ids
words = self.split_words_for_index(self.title)
if not words:
logging.info("no words")
return False
for word in words:
key = mk_sets_key(self.name, word)
# word index for item id
pipe.sadd(key, self.id)
if self.score == 'id':
self.score = self.id
# score for search sort
pipe.set(mk_score_key(self.name, self.id), self.score)
# 将目前的编号保存到条件(conditions)字段所创立的索引上面
for field in self.condition_fields:
pipe.sadd(mk_condition_key(self.name, field, utf8(data[field])), self.id)
# commit
pipe.execute()
if self.prefix_index_enable:
self.save_prefix_index()
def remove(self, name, id, title):
"""docstring for remove"""
pipe = util.redis.pipeline()
pipe.hdel(name, id)
for word in self.split_words_for_index(title):
key = mk_sets_key(name, word)
pipe.srem(key, id)
pipe.delete(mk_score_key(name, id))
# remove set for prefix index key
pipe.srem(mk_sets_key(name, title, id))
# commit
pipe.execute()
def save(self):
"""docstring for save"""
if not self.title:
return False
data = {'name': self.name, 'id': self.id, 'title': self.title}
if self.exts:
data.update(self.exts)
pipe = util.redis.pipeline()
# 将原始数据存入 hashes
res = pipe.hset(self.name, self.id, json.dumps(data))
# 保存 sets 索引，以分词的单词为key，用于后面搜索，里面存储 ids
words = self.split_words_for_index(self.title)
if not words:
logging.info("no words")
return False
for word in words:
key = mk_sets_key(self.name, word)
# word index for item id
pipe.sadd(key, self.id)
if self.score == 'id':
self.score = self.id
# score for search sort
pipe.set(mk_score_key(self.name, self.id), self.score)
# 将目前的编号保存到条件(conditions)字段所创立的索引上面
for field in self.condition_fields:
pipe.sadd(mk_condition_key(self.name, field, utf8(data[field])),
self.id)
# commit
pipe.execute()
if self.prefix_index_enable:
self.save_prefix_index()
def remove(self, name, id, title):
"""docstring for remove"""
pipe = util.redis.pipeline()
pipe.hdel(name, id)
words = self.split_words_for_index(title)
for word in words:
key = mk_sets_key(name, word)
pipe.srem(key, id)
pipe.delete(mk_score_key(name, id))
# remove set for prefix index key
pipe.srem(mk_sets_key(name, title, id))
# commit
pipe.execute()
def complete(name, keyword, limit=10, conditions=None):
"""complete: prefix match search
keyword
limit: max match count"""
conditions = conditions if isinstance(conditions, dict) and conditions else {}
if not keyword and not conditions:
logging.debug("no word and conditions")
return []
keyword = utf8(keyword.strip())
prefix_matchs = []
# This is not random, try to get replies < MTU size
rangelen = util.complete_max_length
prefix = keyword.lower()
key = mk_complete_key(name)
start = util.redis.zrank(key, prefix)
if start:
count = limit
max_range = start + (rangelen * limit) - 1
entries = util.redis.zrange(key, start, max_range)
while len(prefix_matchs) <= count:
start += rangelen
if not entries or len(entries) == 0:
break
#entries sorted in desc so once entry is inconsistence with prefix will break
for entry in entries:
minlen = min(len(entry), len(prefix))
#this entry break the consistency with prefix
if entry[0:minlen] != prefix[0:minlen]:
count = len(prefix_matchs)
break
# found matched entry
if entry[-1] == "*" and len(prefix_matchs) != count:
match = entry[:-1]
if match not in prefix_matchs:
prefix_matchs.append(match)
entries = entries[start:max_range]
# 组合 words 的特别 key 名
words = [mk_sets_key(name, word) for word in prefix_matchs]
# 组合特别key,但这里不会像query那样放入words,
# 因为在complete里面words是用union取的,condition_keys和words应该取交集
condition_keys = [mk_condition_key(name, c, utf8(conditions[c]))
for c in conditions]
# 按词语搜索
temp_store_key = "tmpsunionstore:%s" % "+".join(words)
if len(words) == 0:
logging.info("no words")
elif len(words) > 1:
if not util.redis.exists(temp_store_key):
# 将多个词语组合对比，得到并集，并存入临时区域
util.redis.sunionstore(temp_store_key, words)
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_store_key, 86400)
# 根据需要的数量取出 ids
else:
temp_store_key = words[0]
# 如果有条件，这里再次组合一下
if condition_keys:
if not words:
condition_keys += temp_store_key
temp_store_key = "tmpsinterstore:%s" % "+".join(condition_keys)
if not util.redis.exists(temp_store_key):
util.redis.sinterstore(temp_store_key, condition_keys)
util.redis.expire(temp_store_key, 86400)
ids = util.redis.sort(temp_store_key,
start=0,
num=limit,
by=mk_score_key(name, "*"),
desc=True)
if not ids:
return []
return hmget(name, ids)
def query(name, text, offset=0, limit=10, sort_field='id', conditions=None):
"""docstring for query"""
conditions = conditions if isinstance(conditions, dict) and conditions else {}
tm = time.time()
result = []
# 如果搜索文本和查询条件均没有，那就直接返回 []
if not text.strip() and not conditions:
return result
text = utf8(text.strip())
splited_words = split_words(text)
words = [mk_sets_key(name, word) for word in splited_words]
if conditions:
condition_keys = [mk_condition_key(name, c, utf8(conditions[c]))
for c in conditions]
# 将条件的 key 放入关键词搜索集合内，用于 sinterstore 搜索
words += condition_keys
else:
condition_keys = []
if not words:
return result
temp_store_key = "tmpinterstore:%s" % "+".join(words)
if len(words) > 1:
if not util.redis.exists(temp_store_key):
# 将多个词语组合对比，得到交集，并存入临时区域
util.redis.sinterstore(temp_store_key, words)
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_store_key, 86400)
# 拼音搜索
if util.pinyin_match:
splited_pinyin_words = split_pinyin(text)
pinyin_words = [mk_sets_key(name, w) for w in splited_pinyin_words]
pinyin_words += condition_keys
temp_sunion_key = "tmpsunionstore:%s" % "+".join(words)
temp_pinyin_store_key = "tmpinterstore:%s" % "+".join(pinyin_words)
# 找出拼音的交集
util.redis.sinterstore(temp_pinyin_store_key, pinyin_words)
# 合并中文和拼音的搜索结果
util.redis.sunionstore(temp_sunion_key, [temp_store_key, temp_pinyin_store_key])
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_pinyin_store_key, 86400)
util.redis.expire(temp_sunion_key, 86400)
temp_store_key = temp_sunion_key
else:
temp_store_key = words[0]
# 根据需要的数量取出 ids
ids = util.redis.sort(temp_store_key,
start=offset,
num=limit,
by=mk_score_key(name, "*"),
desc=True)
result = hmget(name, ids, sort_field=sort_field)
logging.debug("{}:\"{}\" | Time spend:{}s".format(name, text, time.time()-tm))
return result
def complete(name, keyword, limit=10, conditions=None):
"""docstring for complete"""
conditions = conditions if isinstance(conditions, dict) and conditions else {}
if not keyword and not conditions:
logging.debug("no word and conditions")
return []
keyword = utf8(keyword.strip())
prefix_matchs = []
# This is not random, try to get replies < MTU size
rangelen = util.complete_max_length
prefix = keyword.lower()
key = mk_complete_key(name)
start = util.redis.zrank(key, prefix)
if start:
count = limit
max_range = start+(rangelen*limit)-1
entries = util.redis.zrange(key, start, max_range)
while len(prefix_matchs) <= count:
start += rangelen
if not entries or len(entries) == 0:
break
for entry in entries:
minlen = min(len(entry), len(prefix))
if entry[0:minlen] != prefix[0:minlen]:
count = len(prefix_matchs)
break
if entry[-1] == "*" and len(prefix_matchs) != count:
match = entry[:-1]
if match not in prefix_matchs:
prefix_matchs.append(match)
entries = entries[start:max_range]
# 组合 words 的特别 key 名
words = []
for word in prefix_matchs:
words.append(mk_sets_key(name, word))
# 组合特别 key ,但这里不会像 query 那样放入 words， 因为在 complete 里面 words 是用 union 取的，condition_keys 和 words 应该取交集
condition_keys = []
if conditions:
for c in conditions:
condition_keys.append(mk_condition_key(name, c, utf8(conditions[c])))
# 按词语搜索
temp_store_key = "tmpsunionstore:%s" % "+".join(words)
if len(words) == 0:
logging.info("no words")
elif len(words) > 1:
if not util.redis.exists(temp_store_key):
# 将多个词语组合对比，得到并集，并存入临时区域
util.redis.sunionstore(temp_store_key, words)
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_store_key, 86400)
# 根据需要的数量取出 ids
else:
temp_store_key = words[0]
# 如果有条件，这里再次组合一下
if condition_keys:
if not words:
condition_keys += temp_store_key
temp_store_key = "tmpsinterstore:%s" % "+".join(condition_keys)
if not util.redis.exists(temp_store_key):
util.redis.sinterstore(temp_store_key, condition_keys)
util.redis.expire(temp_store_key, 86400)
ids = util.redis.sort(temp_store_key,
start = 0,
num = limit,
by = mk_score_key(name, "*"),
desc = True)
if not ids:
return []
return util.hmget(name, ids)
def query(name, text, offset=0, limit=10, sort_field='id', conditions=None):
"""docstring for query"""
conditions = conditions if isinstance(conditions, dict) and conditions else {}
tm = time.time()
result = []
# 如果搜索文本和查询条件均没有，那就直接返回 []
if not text.strip() and not conditions:
return result
text = utf8(text.strip())
splited_words = split_words(text)
words = []
for word in splited_words:
words.append(mk_sets_key(name, word))
condition_keys = []
if conditions:
for c in conditions:
condition_keys.append(mk_condition_key(name, c, utf8(conditions[c])))
# 将条件的 key 放入关键词搜索集合内，用于 sinterstore 搜索
words += condition_keys
if not words:
return result
temp_store_key = "tmpinterstore:%s" % "+".join(words)
if len(words) > 1:
if not util.redis.exists(temp_store_key):
# 将多个词语组合对比，得到交集，并存入临时区域
util.redis.sinterstore(temp_store_key, words)
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_store_key, 86400)
# 拼音搜索
if util.pinyin_match:
splited_pinyin_words = split_pinyin(text)
pinyin_words = []
for w in splited_pinyin_words:
pinyin_words.append(mk_sets_key(name, w))
pinyin_words += condition_keys
temp_sunion_key = "tmpsunionstore:%s" % "+".join(words)
temp_pinyin_store_key = "tmpinterstore:%s" % "+".join(pinyin_words)
# 找出拼音的
util.redis.sinterstore(temp_pinyin_store_key, pinyin_words)
# 合并中文和拼音的搜索结果
util.redis.sunionstore(temp_sunion_key, [temp_store_key, temp_pinyin_store_key])
# 将临时搜索设为1天后自动清除
util.redis.expire(temp_pinyin_store_key, 86400)
util.redis.expire(temp_sunion_key, 86400)
temp_store_key = temp_sunion_key
else:
temp_store_key = words[0]
# 根据需要的数量取出 ids
ids = util.redis.sort(temp_store_key,
start = offset,
num = limit,
by = mk_score_key(name, "*"),
desc = True)
result = util.hmget(name, ids, sort_field=sort_field)
logging.debug("%s:\"%s\" | Time spend:%ss" % (name, text, time.time()-tm))
return result