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Python插入Elasticsearch操作方法解析

看: 1052次  时间:2020-10-31  分类 : python教程

这篇文章主要介绍了Python插入Elasticsearch操作方法解析,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下

在用scrapy做爬虫的时候,需要将数据存入的es中。网上找了两种方法,照葫芦画瓢也能出来,暂记下来:

首先安装了es,版本是5.6.1的较早版本

用pip安装与es版本相对的es相关包

pip install elasticsearch-dsl==5.1.0

方法一:

以下是pipelines.py模块的完整代码

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
import chardet

class SinafinancespiderPipeline(object):
  def process_item(self, item, spider):
    return item


# 写入到es中,需要在settings中启用这个类 ExchangeratespiderESPipeline
# 需要安装pip install elasticsearch-dsl==5.1.0 注意与es版本需要对应
from elasticsearch_dsl import Date,Nested,Boolean,analyzer,Completion,Keyword,Text,Integer,DocType
from elasticsearch_dsl.connections import connections
connections.create_connection(hosts=['192.168.52.138'])
from elasticsearch import Elasticsearch
es = Elasticsearch()

class AticleType(DocType):
  page_from = Keyword()
  # domain报错
  domain=Keyword()
  cra_url=Keyword()
  spider = Keyword()
  cra_time = Keyword()
  page_release_time = Keyword()
  page_title = Text(analyzer="ik_max_word")
  page_content = Text(analyzer="ik_max_word")
class Meta:
    index = "scrapy"
    doc_type = "sinafinance"
    # 以下settings和mappings都没起作用,暂且记下
    settings = {
      "number_of_shards": 3,
    }
    mappings = {
      '_id':{'path':'cra_url'}
    }


class ExchangeratespiderESPipeline(DocType):
  from elasticsearch5 import Elasticsearch
  ES = ['192.168.52.138:9200']
  es = Elasticsearch(ES,sniff_on_start=True)

  def process_item(self, item, spider):

    spider.logger.info("-----enter into insert ES")
    article = AticleType()

    article.page_from=item['page_from']
    article.domain=item['domain']
    article.cra_url =item['cra_url']
    article.spider =item['spider']
    article.cra_time =item['cra_time']
    article.page_release_time =item['page_release_time']
    article.page_title =item['page_title']
    article.page_content =item['page_content']

    article.save()
    return item

以上方法能将数据写入es,但是如果重复爬取的话,会重复插入数据,因为 主键 ”_id” 是ES自己产生的,找不到自定义_id的入口。于是放弃。

方法二:实现自定义主键写入,覆盖插入

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
from elasticsearch5 import Elasticsearch

class SinafinancespiderPipeline(object):
  def process_item(self, item, spider):
    return item


# 写入到es中,需要在settings中启用这个类 ExchangeratespiderESPipeline
# 需要安装pip install elasticsearch-dsl==5.1.0 注意与es版本需要对应
class SinafinancespiderESPipeline():
  def __init__(self):
    self.ES = ['192.168.52.138:9200']
    # 创建es客户端
    self.es = Elasticsearch(
      self.ES,
      # 启动前嗅探es集群服务器
      sniff_on_start=True,
      # es集群服务器结点连接异常时是否刷新es结点信息
      sniff_on_connection_fail=True,
      # 每60秒刷新节点信息
      sniffer_timeout=60
    )

  def process_item(self, item, spider):
    spider.logger.info("-----enter into insert ES")
    doc = {
      'page_from': item['page_from'],
      'domain': item['domain'],
      'spider': item['spider'],
      'page_release_time': item['page_release_time'],
      'page_title': item['page_title'],
      'page_content': item['page_content'],
      'cra_url': item['cra_url'],
      'cra_time': item['cra_time']
    }
    self.es.index(index='scrapy', doc_type='sinafinance', body=doc, id=item['cra_url'])

    return item

搜索数据的方法:

# 字典形式设置body
query = {
 'query': {
  'bool': {
   'must': [
    {'match': {'_all': 'python web'}}
   ],
   'filter': [
    {'term': {'status': 2}}
   ]
  }
 }
}
ret = es.search(index='articles', doc_type='article', body=query)

# 查询数据
data = es.search(index='articles', doc_type='article', body=body)
print(data)
# 增加
es.index(...)
# 修改
es.update(...)
# 删除
es.delete()

完成后

在settings.py模块中注册自定义的类

ITEM_PIPELINES = {
  # 'sinafinancespider.pipelines.SinafinancespiderPipeline': 300,
  'sinafinancespider.pipelines.SinafinancespiderESPipeline': 300,
}

以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持python博客。

标签:scrapy  

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