基于django实现的搜索引擎页面

from django.shortcuts import render import json from django.utils.datastructures import OrderedSet from django.views.generic.base import View from search.models import ArticleType, LagouType, ZhiHuQuestionType, ZhiHuAnswerType from django.http import HttpResponse from datetime import datetime import redis from elasticsearch import Elasticsearch from django.views.generic.base import RedirectView # es查询 client = Elasticsearch(hosts=["localhost"]) # redis实现top-n排行榜 redis_cli = redis.StrictRedis() class IndexView(View): """ 首页get请求top-n排行榜 """ @staticmethod def get(request): topn_search_clean = [] topn_search = redis_cli.zrevrangebyscore("search_keywords_set", "+inf", "-inf", start=0, num=5) for topn_key in topn_search: topn_key = str(topn_key, encoding="utf-8") topn_search_clean.append(topn_key) topn_search = topn_search_clean return render(request, "index.html", {"topn_search": topn_search}) class SearchSuggest(View): """ 搜索建议 """ @staticmethod def get(request): key_words = request.GET.get('s', '') current_type = request.GET.get('s_type', '') if current_type == "article": return_suggest_list = [] if key_words: s = ArticleType.search() """ fuzzy 模糊搜索, fuzziness 编辑距离, prefix_length 前面不变化的前缀长度 """ s = s.suggest('my_suggest', key_words, completion={ "field": "suggest", "fuzzy": { "fuzziness": 2 }, "size": 10 }) suggestions = s.execute() for match in suggestions.suggest.my_suggest[0].options[:10]: source = match._source return_suggest_list.append(source["title"]) return HttpResponse(json.dumps(return_suggest_list), content_type="application/json") elif current_type == "job": return_suggest_list = [] if key_words: s = LagouType.search() s = s.suggest('my_suggest', key_words, completion={ "field": "suggest", "fuzzy": { "fuzziness": 2 }, "size": 10 }) suggestions = s.execute() # 对于不同公司同名职位去重，提高用户体验 name_set = OrderedSet() for match in suggestions.suggest.my_suggest[0].options[:10]: source = match._source name_set.add(source["title"]) for name in name_set: return_suggest_list.append(name) return HttpResponse(json.dumps(return_suggest_list), content_type="application/json") elif current_type == "question": return_suggest_list = [] if key_words: s_question = ZhiHuQuestionType.search() """fuzzy模糊搜索, fuzziness 编辑距离, prefix_length前面不变化的前缀长度""" s_question = s_question.suggest('my_suggest', key_words, completion={ "field": "suggest", "fuzzy": { "fuzziness": 2 }, "size": 10 }) suggestions_question = s_question.execute() for match in suggestions_question.suggest.my_suggest[0].options[:10]: source = match._source return_suggest_list.append(source["title"]) return HttpResponse(json.dumps(return_suggest_list), content_type="application/json") class SearchView(View): """ 展示搜索结果页面 """ @staticmethod def get(request): key_words = request.GET.get("q", "") # 通用部分 # 实现搜索关键词keyword加1操作 redis_cli.zincrby("search_keywords_set", key_words) # 获取topn个搜索词 topn_search_clean = [] topn_search = redis_cli.zrevrangebyscore("search_keywords_set", "+inf", "-inf", start=0, num=5) for topn_key in topn_search: topn_key = str(topn_key, encoding="utf-8") topn_search_clean.append(topn_key) topn_search = topn_search_clean # 获取伯乐在线的文章数量 jobbole_count = redis_cli.get("jobbole_blog_count") if jobbole_count: jobbole_count = int(jobbole_count) else: jobbole_count = 0 job_count = redis_cli.get("lagou_job_count") if job_count: job_count = int(job_count) else: job_count = 0 zhihu_question_count = redis_cli.get("zhihu_question_count") zhihu_answer_count = redis_cli.get("zhihu_answer_count") if zhihu_question_count: zhihu_question_count = int(zhihu_question_count) else: zhihu_question_count = 0 if zhihu_answer_count: zhihu_answer_count = int(zhihu_answer_count) else: zhihu_answer_count = 0 zhihu_count = zhihu_answer_count + zhihu_question_count # 当前要获取第几页的数据 page = request.GET.get("p", "1") try: page = int(page) except BaseException: page = 1 response = [] start_time = datetime.now() s_type = request.GET.get("s_type", "") if s_type == "article": response = client.search(index="jobbole", request_timeout=60, body={ "query": { "multi_match": { "query": key_words, "fields": ["tags", "title", "content"] } }, "from": (page - 1) * 10, "size": 10, "highlight": { "pre_tags": ['<span class="keyWord">'], "post_tags": ['</span>'], "fields": { "title": {}, "content": {}, } } }) elif s_type == "job": response = client.search(index="lagou", request_timeout=60, body={ "query": { "multi_match": { "query": key_words, "fields": [ "title", "tags", "job_desc", "job_advantage", "company_name", "job_addr", "job_city", "degree_need"]} },