PySpark Microsoft Graph Source

A PySpark DataSource to seamlessly integrate and read data from Microsoft Graph API, enabling easy access to resources like SharePoint List Items, and more.

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Features

• Entra ID Authentication Securely authenticate with Microsoft Graph using DefaultAzureCredential, supporting local development and production seamlessly.

• Automatic Pagination Handling Fetches all paginated data from Microsoft Graph without manual intervention.

• Dynamic Schema Inference Automatically detects the schema of the resource by sampling data, so you don't need to define it manually.

• Simple Configuration with .option() Easily configure resources and query parameters directly in your Spark read options, making it flexible and intuitive.

• Zero External Ingestion Services No additional services like Azure Data Factory or Logic Apps are needed—directly ingest data into Spark from Microsoft Graph.

• Extensible Resource Providers Add custom resource providers to support more Microsoft Graph endpoints as needed.

• Pluggable Architecture Dynamically load resource providers without modifying core logic.

• Optimized for PySpark Designed to work natively with Spark's DataFrame API for big data processing.

• Secure by Design Credentials and secrets are handled using Azure Identity best practices, avoiding hardcoding sensitive data.

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Installation

pip install pyspark-msgraph-source

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⚡ Quickstart

1. Authentication

This package uses DefaultAzureCredential.
Ensure you're authenticated:

az login

Or set environment variables:

export AZURE_CLIENT_ID=<your-client-id>
export AZURE_TENANT_ID=<your-tenant-id>
export AZURE_CLIENT_SECRET=<your-client-secret>

2. Example Usage

from pyspark.sql import SparkSession

spark = SparkSession.builder \ 
.appName("MSGraphExample") \ 
.getOrCreate()

from pyspark_msgraph_source.core.source import MSGraphDataSource
spark.dataSource.register(MSGraphDataSource)

df = spark.read.format("msgraph") \ 
.option("resource", "list_items") \ 
.option("site-id", "<YOUR_SITE_ID>") \ 
.option("list-id", "<YOUR_LIST_ID>") \ 
.option("top", 100) \ 
.option("expand", "fields") \ 
.load()

df.show()

# with schema

df = spark.read.format("msgraph") \ 
.option("resource", "list_items") \ 
.option("site-id", "<YOUR_SITE_ID>") \ 
.option("list-id", "<YOUR_LIST_ID>") \ 
.option("top", 100) \ 
.option("expand", "fields") \ 
.schema("id string, Title string")
.load()

df.show()

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Supported Resources

Resource	Description
list_items	SharePoint List Items
(more coming soon...)

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Development

Coming soon...

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Troubleshooting

Issue	Solution
ValueError: resource missing	Add .option("resource", "list_items")
Empty dataframe	Verify IDs, permissions, and access
Authentication failures	Check Azure credentials and login status

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📄 License

MIT License

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📚 Resources

• Microsoft Graph API
• DefaultAzureCredential