Quickstart in Python - Jupyter Notebook
Demonstrates using Python and the Azure SDK for Python to create an Azure Cognitive Search index, load it with documents, and execute a few queries. The index is modeled on a subset of the Hotels dataset, reduced for readability and comprehension. Index definition and documents are included in the code.
This sample is a Jupyter Python3 .ipynb file to perform the actions against the Cognitive Search service.
||Jupyter Python notebook.|
||Define what to ignore at commit time.|
||Guidelines for contributing to the sample.|
||This README file.|
||The license for the sample.|
- Anaconda 3.x providing Python 3.x and Jupyter Notebooks
- Azure Cognitive Search service
- Azure Cognitive Search SDK for Python (pip install azure-search-documents --pre)
- Clone or download this sample repository.
- Extract contents if the download is a zip file. Make sure the files are read-write.
Running the sample
- On the Windows Start menu, select Anaconda3, and then select Jupyter Notebook.
- Open the azure-search-quickstart.ipynb file in Jupyter Notebook
- Replace <service_name> <admin_key> and <query_key> with the service and api-key details of your search service
- Run each step individually
You can learn more about Azure Cognitive Search on the official documentation site.