Python Elasticsearch
elasticsearch is a Python client library that allows you to interact with Elasticsearch, a popular open-source search and analytics engine. Elasticsearch is used for full-text search, real-time data analysis, and various other use cases involving large-scale data storage and retrieval.
To use Elasticsearch with Python, you need to install the elasticsearch package. You can install it using pip:
pip install elasticsearch
Once installed, you can start using the Elasticsearch client in your Python code. Here’s a basic example of how to connect to Elasticsearch and perform a simple search:
from elasticsearch import Elasticsearch
# Create an Elasticsearch client connected to the default local instance (http://localhost:9200)
es = Elasticsearch()
# Index a sample document
document = {
'title': 'Example Document',
'content': 'This is some example content for Elasticsearch testing.'
}
index_name = 'my_index'
document_id = '1'
# Index the document
es.index(index=index_name, doc_type='_doc', id=document_id, body=document)
# Refresh the index to make the document searchable
es.indices.refresh(index=index_name)
# Perform a search
search_query = {
'query': {
'match': {
'content': 'example'
}
}
}
search_result = es.search(index=index_name, body=search_query)
hits = search_result['hits']['hits']
for hit in hits:
print(f"Document ID: {hit['_id']}, Score: {hit['_score']}, Source: {hit['_source']}")
Please note that the code above is a simple demonstration of connecting to Elasticsearch, indexing a document, and performing a search. In a real-world application, you might want to handle exceptions, use proper index mappings, and optimize your search queries for better performance.
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