当前位置： 首页 > article >正文

python -【es】基本使用

article 2025/1/4 5:51:25

一. 前言

在Python中使用Elasticsearch（ES）通常涉及安装Elasticsearch的Python客户端库，然后通过该库与Elasticsearch集群进行交互。

二. 基本使用

1. 安装Elasticsearch Python客户端库

首先，你需要安装elasticsearch库。你可以使用pip来安装它：

pip install elasticsearch

2. 连接到Elasticsearch集群

在Python中，你可以通过创建一个Elasticsearch对象来连接到Elasticsearch集群。

from elasticsearch import Elasticsearch

# 创建Elasticsearch客户端实例
es = Elasticsearch(['http://localhost:9200'])

# 检查连接是否成功
if es.ping():
    print("Successfully connected to Elasticsearch!")
else:
    print("Could not connect to Elasticsearch")

3. 执行索引操作

创建索引
在Elasticsearch中，索引类似于关系型数据库中的表。可以使用客户端实例的indices.create()方法来创建一个新的索引。

# 创建索引的请求体（这里是一个简单的例子，实际使用中可能更复杂）
index_body = {
    "settings": {
        "number_of_shards": 1,
        "number_of_replicas": 1
    },
    "mappings": {
        "properties": {
            "field1": {"type": "text"},
            "field2": {"type": "integer"}
        }
    }
}

# 创建索引
es.indices.create(index='my_index', body=index_body)

添加文档
可以使用index()方法来向索引中添加文档。

# 添加文档的请求体
doc_body = {
    "field1": "value1",
    "field2": 123
}

# 添加文档（指定索引名和文档ID）
es.index(index='my_index', id=1, body=doc_body)

4. 执行搜索操作

使用search()方法来执行搜索查询。

# 查询DSL
query_body = {
    "query": {
        "match": {
            "field1": "value1"
        }
    }
}

# 执行搜索
response = es.search(index='my_index', body=query_body)

# 处理响应
for hit in response['hits']['hits']:
    print(hit['_source'])

三. 整合封装成一个类来使用

import json
import uuid
from datetime import datetime, timedelta

from elasticsearch import Elasticsearch

from base.common.time_format import get_isoformat_time
from configure.configure import config
from configure.server_config import logger
import time
import traceback

es_conf = config['elasticsearch']


class ElasticSearchService(Elasticsearch):
    es_service = None

    mappings = {
        "properties": {
            # "id": {"type": "keyword"},
            "content": {
                "type": "text",
                "analyzer": "ik_max_word",
                "search_analyzer": "ik_smart"
            },
            "time": {"type": "date", "format": "yyyy-MM-dd'T'HH:mm:ss"},
            "qst_id": {"type": "keyword"},
            "reply_type": {"type": "integer"}
        }
    }

    def __init__(self, index_name, addrs, *args, **kwargs):
        self.max_result_window = es_conf['max_result_window']
        self.username = es_conf['username']
        self.password = es_conf['password']
        self.index_name = index_name
        self.addrs = addrs
        super().__init__(self.addrs, basic_auth=(self.username, self.password), request_timeout=3600)
        
        # 1.查询index是否存在
        if not self.indices.exists(index=self.index_name):
            self.create_index(self.index_name)
        if not self.ping():
            logger.error(f"ElasticSearchHandler Connection failed")
        logger.info(
            f"Connect to ElasticService successfully!!! addrs:{addrs}, index_name:{self.index_name}")

    def create_index(self, index_name):
        # 创建索引
        if not self.indices.exists(index=index_name):
            response = self.indices.create(index=index_name, body={})
            logger.info(f"Index [{index_name}] created successfully!")
            # 检查索引是否创建成功
            if not response.get('acknowledged'):
                logger.info(f"Failed to create index '{index_name}'. Response: {response}")
                return False

            self.create_mapping_session_history()
            self.create_index_setting()

            if response.get('shards_acknowledged'):
                logger.info(f"Index '{index_name}' All shards are acknowledged.")
            else:
                logger.info(f"Index '{index_name}' Not all shards are acknowledged.")

    def create_mapping_session_history(self):
        mapping = ElasticSearchService.mappings
        # 将mapping添加到索引
        response = self.indices.put_mapping(index=self.index_name, body=mapping)

        # 检查索引是否创建成功
        if response.get('acknowledged'):
            logger.info(f"Index '{self.index_name}' created successfully with mapping.")
        else:
            logger.info(f"Failed to create index '{self.index_name}'. Response: {response}")

    def create_index_setting(self):
        setting = {"number_of_replicas": "0"}
        # 将setting添加到索引
        response = self.indices.put_settings(index=self.index_name, body=setting)

        # 检查索引是否创建成功
        if response.get('acknowledged'):
            logger.info(f"Index '{self.index_name}' created successfully with setting.")
        else:
            logger.info(f"Failed to create index setting'{self.index_name}'. Response: {response}")

    def delete_index(self, index_name):
        res = self.indices.delete(index=index_name)
        logger.info(f"Index [{index_name}] deleted successfully!, res: {res}")
        return res

    def insert_doc(self, hist_hash_id: str, doc_body: dict):
        """
        新增数据
        :param hist_hash_id:
        :param doc:
        :return:
        """
        try:
            self.index(index=self.index_name, id=hist_hash_id, body=doc_body)
            # 刷新索引以确保文档立即可见
            res = self.indices.refresh(index=self.index_name)
            logger.info(f"Document hist_hash_id:[{hist_hash_id}] indexed successfully!")
            return res
        except Exception as e:
            logger.error(f"Failed to index document hist_hash_id:[{hist_hash_id}]: {e}")

    def bulk_insert_docs(self, session_histories: list):
        """
        批量新增数据
        :param chitchat_list:
        :return:
        """
        try:
            # 准备批量数据
            bulk_actions = []
            failed_list = []
            batch_count = 1000
            for i in range(0, len(session_histories), batch_count):
                for item in session_histories[i:i + batch_count]:
                    doc = {
                        # "id": item.get('id', 0),
                        "you_feild": item.get('you_feild', ''),
                        ...
                        }
                    action = {
                        "index": {  # Use "index" as the action
                            "_index": self.index_name,
                            # 如果需要指定文档ID，可以取消下面的注释
                            "_id": item.get('hist_hash_id', '')
                        }
                    }
                    # 将 action 和 doc 作为元组的两个元素添加到 bulk_actions 列表中
                    bulk_actions.append(action)
                    bulk_actions.append(doc)
                    print(f"insert data -> {item}")
                response = self.bulk(index=self.index_name, body=bulk_actions)

                # 检查响应中的成功和失败项
                for item in response['items']:
                    if item['index']['status'] != 201:
                        failed_list.append(item)
                logger.info(f"Elasticsearch 批量新增完成，failed_list:{failed_list}")
                # 刷新索引以确保文档立即可见
                self.indices.refresh(index=self.index_name)
            return failed_list
        except Exception as e:
            traceback.print_exc()
            logger.error(f"Elasticsearch bulk insert doc error:{e}")

    def delete_doc_by_id(self, doc_ids):
        """ 删除文档 """
        try:
            failed_list = []
            for doc_id in doc_ids:
                response = self.delete(index=self.index_name, id=doc_id)
                # 检查响应状态
                if response.meta.status != 200:
                    failed_list.append(doc_id)
                    logger.info(f"Document with ID {doc_id} in index {self.index_name} was deleted failed!")
                logger.info(f"Document with ID {doc_id} in index {self.index_name} was deleted successfully.")
            return failed_list
        except Exception as e:
            traceback.print_exc()
            logger.error(f"Elasticsearch delete_doc error:{e}")

    def delete_docs_by_query_body(self, query_body):
        # 使用_delete_by_query API 删除所有文档
        # 注意：这里我们使用了一个匹配所有文档的查询：{"query": {"match_all": {}}}
        try:
            response = self.delete_by_query(index=self.index_name, body=query_body)
            logger.info("Deleted documents:", response['_deleted'])  # 这将显示被删除的文档数量
        except Exception as e:
            # 捕获并处理异常
            logger.error(f"Deleted docs error: {e}")

    def update_doc(self, datas: list):
        """ 更新文档 """
        try:
            failed_list = []
            for data in datas:
                # 更新文档（实际上是重新索引）
                response = self.index(index=self.index_name, id=data['doc_id'], body=data['doc'])
                logger.info("Update Response:", response)
                if response.meta.status != 200:
                    failed_list.append(data)
            # 刷新索引以立即应用更改（可选）
            self.indices.refresh(index=self.index_name)
            logger.info(f"Elasticsearch update_doc finished! failed_list -> {failed_list}")
        except Exception as e:
            traceback.print_exc()
            logger.error(f"Elasticsearch update_doc error: {e}")

    def get_doc(self, doc_id):
        """ 获取文档数据 """
        try:
            doc = self.get(index=self.index_name, id=doc_id)['_source']
            return doc
        except Exception as e:
            logger.error(f"Error retrieving document {doc_id}: {e}")
            return None

    def search_index(self, query_body):
        """
        检索文档
        query_body:查询体（Query DSL）
        """
        try:
            logger.info(f'elasticsearch search index_name={self.index_name}，query_body={query_body}')
            response = self.search(index=self.index_name, body=query_body)
            logger.info(f'elasticsearch search [{self.index_name}] response.meta.status={response.meta.status}')
            if response.get('_shards', {}).get('successful') == response.get('_shards', {}).get('total'):
                logger.info(
                    f"Search index successful! total count={response['hits']['total']['value']}, match count={len(response['hits']['hits'])}")
                # logger.info(f"search response -> {response}")
                if response['hits']['total']['value'] > 0:
                    return response
                return None
            return None
        except Exception as e:
            traceback.print_exc()
            logger.error(f"ElasticService search_index error:{e}")

    def search_index_by_scroll_api(self, query_body):
        """
        分页查询
        query_body:查询体（Query DSL）
        """
        try:
            logger.info(f'elasticsearch search index_name={self.index_name}，query_body={query_body}')
            response = self.search(index=self.index_name, body=query_body, scroll='1m')
            logger.info(f'elasticsearch search [{self.index_name}] response.meta.status={response.meta.status}')
            if response.get('_shards', {}).get('successful') == response.get('_shards', {}).get('total'):
                logger.info(
                    f"Search index successful! total count={response['hits']['total']['value']}, match count={len(response['hits']['hits'])}")
                # logger.info(f"search response -> {response}")
                if response['hits']['total']['value'] > 0:
                    return response
                return None
            return None
        except Exception as e:
            traceback.print_exc()
            logger.error(f"ElasticService search_index error:{e}")

    def search_by_sql(self, sql_body):
        try:
            logger.info(f'elasticsearch search index_name={self.index_name}，sql_body={sql_body}')
            response = self.sql.query(body=sql_body)
            logger.info(f'elasticsearch search [{self.index_name}] response.meta.status={response.meta.status}')
            if response.meta.status == 200:
                columns = response.get('columns')
                rows = response.get('rows')
                # 提取列名
                column_names = [col['name'] for col in columns]
                # 组织成字典格式
                result_dicts = []
                for row in rows:
                    result_dict = {column_names[i]: row[i] for i in range(len(column_names))}
                    result_dicts.append(result_dict)
                logger.info(f"Search index successful! match count={len(result_dicts)}")
                return result_dicts
            return []
        except Exception as e:
            traceback.print_exc()
            logger.error(f"ElasticService search_by_sql error:{e}")
            return []


def get_elastic_instance(index_name, addrs):
    _es_service = None
    _wait_times = 0
    _try_count = 5
    _interval_seconds = 10
    for i in range(_try_count):  # 初始化后，尝试启动5次，第次间隔10秒
        try:
            _es_service = ElasticSearchService(index_name, addrs)
            if _es_service:
                logger.info(f"ElasticService initial successfully!")
                print(f"ElasticService initial successfully!")
                return _es_service
            logger.warning(f"Connect to elasticServer failed, try reconnect to elasticServer [{i}]!")
        except Exception as e:
            traceback.print_exc()
            logger.warning(
                f"初始化ElasticService失败，结果：{_es_service}, 异常原因：{str(e)}, 应用将在{_interval_seconds}秒后重新尝试.")
            time.sleep(_interval_seconds)


es_service = None
port = es_conf['port']
host = es_conf['host']
addrs = [f"http://{host}:{port}", ]

if config['elasticsearch']['enabled']:
    index_name = config['elasticsearch']['session_history_index']
    es_service = get_elastic_instance(index_name, addrs)
else:
    logger.info(f"[elasticsearch] 未启用! enabled -> {config['elasticsearch']['enabled']}")

if __name__ == '__main__':
    index_name = config['elasticsearch']['session_history_index']
    es_service = get_elastic_instance(index_name, addrs)
    # 添加文档
    docs = [{
        # "id": i + 1,
        "you_feild": "",
        ...
    } for i in range(5)]
    # 插入数据
    # es_service.insert_doc('2', doc)
    print(es_service.bulk_insert_docs(docs))

    # 删除index
    # print(es_service.delete_index(index_name))

    # 获取文档
    # print(es_service.get_doc('c2b27b31-80f8-4cf6-b3f2-36683b60d7da'))
    # logger.info(es_service.get_doc('2'))

    # 删除文档
    # logger.info(es_service.delete_doc_by_id(['f554d0e5-e4cc-4556-952b-b12cdc640fe56']))
    # query_body = {"query": {"match_all": {}}}
    # logger.info(es_service.delete_docs_by_query_body(query_body))

    # 更新数据
    # datas = [{'doc_id': 'c2b27b31-80f8-4cf6-b3f2-36683b60d7da', 'doc': {'qst_content': 'qqq'}}]
    # print(es_service.update_doc(datas))

    # 查询数据
    keyword = "缴清"
    query_body = {
        "query": {
            "multi_match": {
                "query": keyword,
                "fields": ["reply_content", "qst_content", "standard_qst"]
            }
        },
        "from": 0,
        "size": 10,
        "sort": [{
            "chat_qst_time": "desc"
        }]
    }
    # print(es_service.search_index(query_body))

四. 总结

以上是使用Python与Elasticsearch进行交互的基本步骤。可以根据实际需求扩展这些操作，例如处理更复杂的查询、使用聚合、批量操作等。Elasticsearch的Python客户端库提供了丰富的API，可以满足大多数与Elasticsearch交互的需求。
希望对你有所帮助！


http://www.kler.cn/a/459550.html

相关文章：

  • Wireshark和科来网络分析系统
  • 改投论文时如何重构
  • 图像概念与分类
  • LINUX下载编译gtk
  • 笔记：使用python对飞书用户活跃度统计的一个尝试
  • 数据中台与数据治理服务方案[50页PPT]
  • 什么是自治系统和非自治系统
  • Android ActionBar 技术深度解析
  • 上海人工智能方案引领，CES Asia 2025共筑机器人未来
  • PHP语言的编程范式
  • HAL库STM32硬件IIC驱动数字电位器MCP4017
  • Linux(Centos 7.6)基础命令/常用命令说明
  • Python爬虫（二）- Requests 高级使用教程
  • 25 go语言（golang） - 内存分配机制原理
  • 鱼眼相机模型与去畸变实现
  • MySQL数据导出导出的三种办法（1316）
  • JAVA毕业设计205—基于Java+Springboot+vue3的民宿酒店管理系统(源代码+数据库)
  • 基于FPGA的RLC电阻电容电感测试仪设计（论文+源码）
  • XDMA IP
  • React 性能优化十大总结
  • springboot511基于SpringBoot视频点播系统的设计与实现(论文+源码)_kaic
  • php 静态变量
  • linux 配置端口转发
  • 前端Python应用指南（四）Django实战：创建一个简单的博客系统
  • Java的SpringMVC
  • 嵌入式硬件杂谈（八）电源的“纹波”到底是什么？