Azure Table Storage Tutorial - Python Azure Tables SDK with NBA Stats API
Scenario:
The NBA playoffs start on 15 April following the conclusion of the Play-In Tournament on 14 April. In this tutorial, we use the nba_api Python API Client for NBA.com to fetch NBA teams stats and then run the Python Azure Tables SDK to create Azure table and entries. Finally, with Azure Storage Explorer we can easily build search query and visualize the results.
Objective:
To illustrate Azure Tables Python SDK usage using NBA API, followed by querying Azure Table Storage with Azure Storage Explorer's Query Builder.
Pre-requisites:
For this example, you would need:
- An Azure Table Storage
Steps:
- Install nba_api
- Install Azure Tables client library for Python
- Python code to retrieve data, create table, and insert entries
- Run nba.py
- Visualize the NBA table (with Azure Storage Explorer)
- Sample query (with Azure Storage Explorer)
[STEP 1]: Install nba_api
[STEP 2]: Install Azure Tables client library for Python
[STEP 3]: Python code to retrieve data, create table, and insert entries
Note:
- replace STORAGE_CONNECTION_STRING with your storage connection string.
- I use "state" as PartitionKey and "abbreviation" as RowKey.
- This article describes best practice when choosing partition & row key for entities.
- The response from calling teams.get_teams() is like the following:
nba.py
[STEP 4]: Run nba.py
[STEP 5]: Visualize the NBA table (with Azure Storage Explorer)
The NBA table contains data of the 30 NBA teams with the following info:
- ID
- City Name
- State Name
- Nickname
- Full Name
- Year Founded
- Abbreviation
[STEP 6]: Sample query (with Azure Storage Explorer)
Query Example: To find out all NBA teams that are based in California and were founded in 1948.
1. Click the "Query" button on the upper-left corner of the table.
2. Use Query Builder to build the query. Then click ▶ to execute.
3. Result is Lakers (LAL) & Kings (SAC).
Conclusion:
This example shows how to use the nba_api to retrieve NBA teams stats and the Azure Tables Python SDK to work with Azure Table storage. The Azure Tables client library for Python provides a simple and intuitive API for working with Azure Table Storage, with methods for creating and managing table clients, table operations, and entities.
References:
- https://pypi.org/project/nba-api/
- https://learn.microsoft.com/en-us/azure/storage/tables/table-storage-overview
- https://learn.microsoft.com/en-us/python/api/overview/azure/data-tables-readme?view=azure-python
- https://learn.microsoft.com/en-us/python/api/azure-data-tables/azure.data.tables?view=azure-python
Published on:
Learn moreRelated posts
Improve the “R” in RAG and embrace Agentic RAG in Azure SQL
The RAG (Retrieval Augmented Generation) pattern, which is commonly discussed today, is based on the foundational idea that the retrieval part...
Primer: How to Schedule Azure Automation Runbooks to Process Microsoft 365 Data
After creating some Azure automation runbooks to process Microsoft 365 data, a schedule means that the runbook will execute. This article disc...
Primer: Output Data Generated with an Azure Automation Runbook to a SharePoint List
The second part of the Azure Automation runbook primer brings us to output, specifically how to create items generated by a runbook in a Share...
Databricks vs Azure Synapse Analytics: A Comprehensive Comparison for Modern Data Solutions
Table of Contents Introduction Data is at the core of modern business decision-making. As companies increasingly rely on data-driven insights,...
Primer: How to Use Azure Automation to Run Microsoft Graph PowerShell SDK Scripts
A reader asked why it seems so difficult to use Azure Automation runbooks to process Microsoft 365 data. In fact, it's not so hard, and here's...
Extending Regular Expressions (Regex) Support on Azure SQL Managed Instance (MI)
We are happy to announce the Private Preview of Regular Expressions (Regex) support on Azure SQL Managed Instance (MI). This new feature bring...