Unified Python connectivity toolkit for Microsoft Fabric
Project description
PyFabricConnect
Unified Python connectivity toolkit for Microsoft Fabric Warehouses, Lakehouses, and SQL Analytics Endpoints.
PyFabricConnect simplifies secure connectivity to Microsoft Fabric using modern authentication methods and multiple connector backends including JDBC, ODBC, and SQLAlchemy.
Features
- JDBC connectivity for Spark workloads
- ODBC connectivity using pyodbc
- SQLAlchemy integration
- Service Principal authentication
- OAuth Access Token authentication
- Pandas DataFrame support
- Spark DataFrame support
- Unified authentication abstraction
- Enterprise-ready architecture
Supported Technologies
| Technology | Supported |
|---|---|
| Microsoft Fabric Warehouse | ✅ |
| Lakehouse SQL Endpoint | ✅ |
| Spark JDBC | ✅ |
| pyodbc | ✅ |
| SQLAlchemy | ✅ |
| Pandas | ✅ |
| PySpark | ✅ |
Installation
Base Installation
pip install pyfabricconnect
Spark Support
Microsoft Fabric environments already include PySpark and an active Spark runtime.
For local Spark environments, install Spark support with:
pip install pyfabricconnect[spark]
Development Environment
pip install pyfabricconnect[dev]
Quick Start
Service Principal Authentication
from pyfabricconnect import FabricClient
from pyfabricconnect.auth import ServicePrincipalAuth
auth = ServicePrincipalAuth(
tenant_id="YOUR_TENANT_ID",
client_id="YOUR_CLIENT_ID",
client_secret="YOUR_CLIENT_SECRET"
)
client = FabricClient(
server="YOUR_SERVER",
database="WH_PYFABRICCONNECT",
auth=auth
)
df = client.query_pandas("""
SELECT * FROM dbo.qlbacan
""")
print(df.head())
Spark Example
The query_spark() method requires an active SparkSession.
from pyspark.sql import SparkSession
from pyfabricconnect import FabricClient
from pyfabricconnect.auth import ServicePrincipalAuth
spark = SparkSession.builder.getOrCreate()
auth = ServicePrincipalAuth(
tenant_id="YOUR_TENANT_ID",
client_id="YOUR_CLIENT_ID",
client_secret="YOUR_CLIENT_SECRET"
)
client = FabricClient(
server="YOUR_SERVER",
database="WH_PYFABRICCONNECT",
auth=auth,
spark=spark
)
spark_df = client.query_spark("""
SELECT * FROM dbo.qlbacan
""")
spark_df.show()
SQLAlchemy Example
engine = client.engine()
Supported Environments
PyFabricConnect is designed to work with:
- Microsoft Fabric Notebooks
- Azure Synapse Analytics
- Databricks
- Local PySpark environments
- Python applications
- Data engineering pipelines
Project Structure
pyfabricconnect/
│
├── pyfabricconnect/
│ ├── auth/
│ ├── connectors/
│ ├── core/
│ └── utils/
│
├── tests/
├── examples/
├── README.md
├── LICENSE
├── pyproject.toml
└── .gitignore
Project Status
PyFabricConnect is currently under active development.
Roadmap
v0.1.0
- JDBC Connector
- ODBC Connector
- SQLAlchemy Connector
- Service Principal Authentication
- OAuth Token Authentication
Future Releases
- Managed Identity
- Token Refresh
- Retry Policies
- Structured Logging
- Async Support
- Connection Pooling
Contributing
Contributions, issues, and feature requests are welcome.
Support the Project
If PyFabricConnect helps your projects or organization, consider supporting development.
Your support helps maintain:
- Fabric integrations
- Authentication improvements
- New connectors
- Documentation
- Community support
Donations
License
Apache License 2.0
Copyright 2026 Eduardo Osorio Venegas - EOSOVNGAS
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