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。
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