python轻量级中文搜索whoosh

import os
from whoosh.index import create_in
from whoosh.fields import *
from jieba.analyse import ChineseAnalyzer
import json
from IPython.core.display import display, HTML

# 使用结巴中文分词
analyzer = ChineseAnalyzer()

# 创建schema, stored为True表示能够被检索
schema = Schema(title=TEXT(stored=True, analyzer=analyzer), path=ID(stored=False),
                content=TEXT(stored=True, analyzer=analyzer))

# 存储schema信息至'indexdir'目录下
ix_path = 'indexdir/'
ix_name = 'test_index_name'


if not os.path.exists(ix_path):
    os.mkdir(ix_path)
ix = create_in(ix_path, schema,indexname=ix_name)

ix.close()

from whoosh.filedb.filestore import FileStorage

storage = FileStorage(ix_path)  #idx_path 为索引路径
ix = storage.open_index(indexname=ix_name)
# 按照schema定义信息，增加需要建立索引的文档
# 注意：字符串格式需要为unicode格式
with ix.writer() as w:
# from whoosh.writing import AsyncWriter
# writer = AsyncWriter(ix,delay=0.25)
    w.add_document(title=u"第一篇文档", path=u"/a",content=u"这是我们增加，的第一篇文档")
    w.add_document(title=u"第二篇文档，呵呵", path=u"/b",content=u"这是我们增加的第二篇文档，哈哈")
    w.add_document(title=u"帅哥，呵呵", path=u"/b",content=u"帅哥，哈哈")
    
ix.close()

Building prefix dict from the default dictionary ...
Loading model from cache /var/folders/7s/wk98z9d51p1b9_40kcp0d3c00000gp/T/jieba.cache
Loading model cost 1.127 seconds.
Prefix dict has been built succesfully.

with storage.open_index(indexname=ix_name).searcher() as searcher:
    # 检索标题中出现'文档'的文档
    results = searcher.find(u"content", u"文档")
    # 检索出来的第一个结果，数据格式为dict{'title':.., 'content':...}
    for r in results:
        display(HTML('<h3>'+r.get('title')+'</h3>'))
        display(HTML(r.highlights("content")))  # 高亮标题中的检索词
        print(r.score)  # 分数
        print(r.docnum)
        
        doc = r.fields()
        jsondoc = json.dumps(doc, ensure_ascii=False)
        display(jsondoc)  # 打印出检索出的文档全部内容

0.9121951219512198
0

'{"content": "这是我们增加，的第一篇文档", "title": "第一篇文档"}'

0.8558352402745997
1

'{"content": "这是我们增加的第二篇文档，哈哈", "title": "第二篇文档，呵呵"}'