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Updated on 2025-03-03

Detailed explanation of how to connect to a server by python ES

Detailed explanation of how to connect to a server by python ES

Updated: October 25, 2024 08:56:32 Author: TS86
Using Python to connect to the Elasticsearch server for data search and analysis is a common operation. This article introduces in detail how to use the elasticsearch-py client library to connect to the Elasticsearch server, and perform basic operations such as creating indexes, adding documents and searching.

Connecting to an Elasticsearch (ES) server is a common operation for data search and analysis. Elasticsearch is a Lucene-based search engine that provides a RESTful API to index, search and manage data.

Here is a detailed Python code example showing how to connect to an Elasticsearch server and perform some basic operations. This example uses the officialelasticsearch-pyClient library.

1. Install the Elasticsearch client library

First, you need to install itelasticsearchlibrary. If you haven't installed it, you can use pip to install it:

pip install elasticsearch

2. Connect to the Elasticsearch server

Here is a complete Python script that shows how to connect to an Elasticsearch server, create indexes, add documents, and search.

from elasticsearch import Elasticsearch, helpers  
# Configure Elasticsearch connectiones = Elasticsearch(  
    ['http://localhost:9200'],  # Elasticsearch server address and port    http_auth=('username', 'password'),  # If authentication is required, fill in the username and password    use_ssl=False,  # If using HTTPS, set to True    verify_certs=False  # If using HTTPS and self-signed certificate, set to False)  
# Check if the connection is successfulif ():  
    print("Successfully connected to Elasticsearch!")  
else:  
    print("Could not connect to Elasticsearch")  
    exit()  
# Create an indexindex_name = 'my_index'  
if not (index=index_name):  
    # Define the index mapping (Schema)    mappings = {  
        'properties': {  
            'title': {'type': 'text'},  
            'content': {'type': 'text'},  
            'author': {'type': 'keyword'}  
        }  
    }  
    # Create an index    (index=index_name, body={'mappings': mappings})  
    print(f"Index '{index_name}' created successfully.")  
else:  
    print(f"Index '{index_name}' already exists.")  
# Add a documentdocuments = [  
    {"_id": 1, "title": "Elasticsearch Basics", "content": "Learn the basics of Elasticsearch.", "author": "John Doe"},  
    {"_id": 2, "title": "Advanced Elasticsearch", "content": "Go deeper into Elasticsearch features.", "author": "Jane Smith"},  
    {"_id": 3, "title": "Elasticsearch Performance", "content": "Optimize Elasticsearch for performance.", "author": "Alice Johnson"}  
]  
# Add documents in batches using bulk APIactions = [  
    {  
        "_index": index_name,  
        "_id": doc['_id'],  
        "_source": doc  
    }  
    for doc in documents  
]  
(es, actions)  
print("Documents added successfully.")  
# Search for documentssearch_body = {  
    "query": {  
        "match": {  
            "content": "Elasticsearch"  
        }  
    }  
}  
response = (index=index_name, body=search_body)  
print("Search results:")  
for hit in response['hits']['hits']:  
    print(hit['_source'])  
# Clean (optional): Delete the index# (index=index_name)  
# print(f"Index '{index_name}' deleted successfully.")

3. Code explanation

  • Connection configuration:
    • Elasticsearch(['http://localhost:9200']): Connect to the Elasticsearch server running on the local host, the default port is 9200.
    • http_auth=('username', 'password'): If the Elasticsearch server requires authentication, fill in the username and password.
    • use_sslandverify_certs: These options can be enabled if the connection is using HTTPS.
  • Check the connection:
    • use()Method Check whether the connection is successful.
  • Create an index:
    • use(index=index_name)Check if the index exists.
    • use(index=index_name, body={'mappings': mappings})Create an index and define a mapping of the document.
  • Add Document:
    • use(es, actions)Add documents in batches to the index.
  • Search for documents:
    • use(index=index_name, body=search_body)Search and print the search results.
  • Clean up (optional):
    • use(index=index_name)Delete the index.

4. Things to note

  • Server address: Make sure the Elasticsearch server is running and the address and port are configured correctly.
  • Certification: If the Elasticsearch server requires authentication, make sure to provide the correct username and password.
  • SSL: If the connection is using HTTPS, please configure it correctlyuse_sslandverify_certsOptions.

This is the end of this article about how to connect to a python ES server. For more related content on python ES server, please search for my previous articles or continue browsing the related articles below. I hope everyone will support me in the future!

  • python
  • ES
  • server

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