Quickstart in Python - Jupyter Notebook

Flask sample MIT license badge

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.


File/folder Description
azure-search-quickstart.ipynb Jupyter Python notebook.
.gitignore Define what to ignore at commit time.
CONTRIBUTING.md Guidelines for contributing to the sample.
README.md This README file.
LICENSE The license for the sample.



  1. Clone or download this sample repository.
  2. Extract contents if the download is a zip file. Make sure the files are read-write.

Running the sample

  1. On the Windows Start menu, select Anaconda3, and then select Jupyter Notebook.
  2. Open the azure-search-quickstart.ipynb file in Jupyter Notebook
  3. Replace <service_name> <admin_key> and <query_key> with the service and api-key details of your search service
  4. Run each step individually

Next steps

You can learn more about Azure Cognitive Search on the official documentation site.