Accessing an Elasticsearch Cluster Using Python

Prerequisites

• The CSS cluster is available.
• Ensure that the server running Python can communicate with the CSS cluster.

Accessing a Cluster

1. Install the Elasticsearch Python client. You are advised to use the client version that matches the Elasticsearch version. For example, if the cluster version is 7.6.2, install the Elasticsearch Python client 7.6.

   pip install Elasticsearch==7.6
   
   

2. Create an Elasticsearch client and check whether the test index exists. The examples for clusters in different security modes are as follows:
   • Cluster in non-security mode

     from elasticsearch import Elasticsearch
     
     class ElasticFactory(object):
     
         def __init__(self, host: list, port: str, username: str, password: str):
             self.port = port
             self.host = host
             self.username = username
             self.password = password
     
         def create(self) -> Elasticsearch:
             addrs = []
             for host in self.host:
                 addr = {'host': host, 'port': self.port}
                 addrs.append(addr)
     
             if self.username and self.password:
                 elasticsearch = Elasticsearch(addrs, http_auth=(self.username, self.password))
             else:
                 elasticsearch = Elasticsearch(addrs)
             return elasticsearch
     
     es = ElasticFactory(["xxx.xxx.xxx.xxx"], "9200", None, None).create()
     print(es.indices.exists(index='test'))
     
     

   • Cluster in security mode + HTTP

     from elasticsearch import Elasticsearch
     
     class ElasticFactory(object):
     
         def __init__(self, host: list, port: str, username: str, password: str):
             self.port = port
             self.host = host
             self.username = username
             self.password = password
     
         def create(self) -> Elasticsearch:
             addrs = []
             for host in self.host:
                 addr = {'host': host, 'port': self.port}
                 addrs.append(addr)
     
             if self.username and self.password:
                 elasticsearch = Elasticsearch(addrs, http_auth=(self.username, self.password))
             else:
                 elasticsearch = Elasticsearch(addrs)
             return elasticsearch
     
     es = ElasticFactory(["xxx.xxx.xxx.xxx"], "9200", "username", "password").create()
     print(es.indices.exists(index='test'))
     
     

   • Cluster in security mode + HTTPS

     from elasticsearch import Elasticsearch
     import ssl
     
     class ElasticFactory(object):
     
         def __init__(self, host: list, port: str, username: str, password: str):
             self.port = port
             self.host = host
             self.username = username
             self.password = password
     
         def create(self) -> Elasticsearch:
             context = ssl._create_unverified_context()
     
             addrs = []
             for host in self.host:
                 addr = {'host': host, 'port': self.port}
                 addrs.append(addr)
     
             if self.username and self.password:
                 elasticsearch = Elasticsearch(addrs, http_auth=(self.username, self.password), scheme="https", ssl_context=context)
             else:
                 elasticsearch = Elasticsearch(addrs)
             return elasticsearch
     
     es = ElasticFactory(["xxx.xxx.xxx.xxx"], "9200", "username", "password").create()
     print(es.indices.exists(index='test'))
     
     

   Table 1 Variables

   Parameter	Description
   host	IP address for accessing the Elasticsearch cluster. If there are multiple IP addresses, separate them with commas (,).
   port	Access port of the Elasticsearch cluster. Enter 9200.
   username	Username for accessing the cluster.
   password	Password of the user.

3. Create a cluster index through the Elasticsearch client.

   mappings = {
   	"settings": {
   		"index": {
   			"number_of_shards": number_of_shards,
   			"number_of_replicas": 1,
   		},
   	},
   	"mappings": {
   		properties
   	}
   }
   result = es.indices.create(index=index, body=mappings)
   
   

4. Query the index created in the previous step through the Elasticsearch client.

   body = {
   	"query": {
   		"match": {
   			"Query field": "Query content"
   		}
   	}
   }
   result = es.search(index=index, body=body)