python django使用haystack:全文检索的框架(实例讲解)

HAYSTACK_CONNECTIONS = {
 'default': {
  # 使用whoosh引擎
  'ENGINE': 'haystack.backends.whoosh_cn_backend.WhooshEngine',
  # 索引文件路径
  'PATH': os.path.join(BASE_DIR, 'whoosh_index'),
 }
}
# 当添加、修改、删除数据时，自动生成索引
HAYSTACK_SIGNAL_PROCESSOR = 'haystack.signals.RealtimeSignalProcessor'

from haystack import indexes
from models import Post #指定对于某个类的某些数据建立索引
class GoodsInfoIndex(indexes.SearchIndex, indexes.Indexable): 
 text = indexes.CharField(document=True, use_template=True)
 def get_model(self):  
 return Post #搜索的模型类
 def index_queryset(self, using=None):  
  return self.get_model().objects.all()

import jieba
from whoosh.analysis import Tokenizer, Token
 class ChineseTokenizer(Tokenizer):
 def __call__(self, value, positions=False, chars=False,
     keeporiginal=False, removestops=True,
     start_pos=0, start_char=0, mode='', **kwargs):
  t = Token(positions, chars, removestops=removestops, mode=mode,
     **kwargs)
  seglist = jieba.cut(value, cut_all=True)
  for w in seglist:
   t.original = t.text = w
   t.boost = 1.0
   if positions:
    t.pos = start_pos + value.find(w)
   if chars:
    t.startchar = start_char + value.find(w)
    t.endchar = start_char + value.find(w) + len(w)
   yield t
 def ChineseAnalyzer():
 return ChineseTokenizer()

class GoodsSearchView(SearchView):
　　def get_context_data(self, *args, **kwargs):
　　　　context = super().get_context_data(*args, **kwargs)
　　　　context['iscart']=1
　　　　context['qwjs']=2
　　　　return context