Developers can incorporate a robust search service into their Azure apps with the help of Azure Cognitive Search. Create and manage search indexes with minimal effort using Azure Cognitive Search, and give your users access to advanced search features like autocomplete suggestions, and faceted navigation.
Azure Cognitive Search’s ease of use and setup stems from its tight integration with the cloud platform. In this article, we’ll go over how to implement Azure Cognitive Search in your own Azure apps so that your users can conduct searches.
Azure Cognitive Search: How to Get Started
Launching an Azure Cognitive Search service in the Azure portal is the first step in using this powerful search engine. To do so, open the Azure portal, click “Create a resource,” and then type “Azure Cognitive Search” into the search bar.
After launching your service, you’ll want to build a brand-new index for it to index results. An index serves as a repository for your searchable information, specifying which fields and data types will be returned in search results. Access your Cognitive Search service in the Azure portal, and then click “Create Index.”
After developing your index, you will need to fill it with information. Data can be stored in Azure Blob Storage, Azure Cosmos DB, and other Azure services. It is possible to add data to your index in one of two ways: through the Azure portal (by creating a data source and uploading data), or through the Azure Cognitive Search REST API.
Building a search engine for your app with Azure Cognitive Search
You can begin utilizing your index in your application as soon as it has been created and seeded with data. A RESTful API is available for use with Azure Cognitive Search, allowing you to query your index and retrieve search results.
The following code snippet demonstrates a possible use case for the Azure Cognitive Search REST API:
import requests import json # Set up the API endpoint and API key endpoint = "https://<your-search-service-name>.search.windows.net/indexes/<your-index-name>/docs" api_key = "<your-api-key>" # Define the search query query = "searchTerm" # Perform the search query response = requests.get(endpoint, headers={ "api-key": api_key, "Content-Type": "application/json" }, params={ "search": query }) # Print the search results print(json.dumps(response.json(), indent=2))
You can also use the Azure Cognitive Search SDK to interact with your search index in a more convenient way. The SDK provides a high-level API that makes it easy to add search capabilities to your application without having to work with the REST API directly.
Here is an example of how you might use the Azure Cognitive Search SDK to perform a simple search query in your application:
from azure.cognitiveservices.search.websearch import WebSearchClient from azure.cognitiveservices.search.websearch.models import SafeSearch # Set up the search client client = WebSearchClient( "<your-search-service-name>", CognitiveServicesCredentials("<your-api-key>") ) # Perform the search query web_data = client.web.search(query="searchTerm", safe_search=SafeSearch.strict) # Print the search results for result in web_data.web_pages.value: print("'{}' - {}".format(result.name, result.url))
Conclusion
Azure Cognitive Search is a powerful tool allowing developers to easily add search capabilities to their applications. It is fully integrated with Azure, which makes it easy to set up and use. With the Azure Cognitive Search REST API and SDK, you can perform complex search queries and retrieve search results with a few lines of code.
In this blog post, we’ve walked through the process of setting up Azure Cognitive Search and using it to add search capabilities to an Azure application. With this knowledge in mind, you can now start experimenting with Azure Cognitive Search and see how it can improve the search experience for your users.
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