fabric-scheduler

================= Fabric Scheduler

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Fabric Scheduler is a comprehensive Python API wrapper that simplifies the scheduling of Microsoft Fabric artifacts (Notebooks, Dataflows, Pipelines) using the Fabric REST API.

.. note:: This package is designed exclusively for use within Microsoft Fabric notebooks and integrates with the Microsoft Fabric REST API.

Key Features

• Automated Scheduling: Create and manage schedules for Fabric artifacts with minimal code
• Multiple Input Methods: Use dictionaries, CSV files, or CSV strings to define schedules
• Validation & Error Handling: Robust validation with clear error messages
• Schedule Management: Create, retrieve, and delete schedules with ease

Use Cases

Fabric Scheduler addresses several common challenges in Microsoft Fabric environments:

• Efficiency in Multi-Workspace Environments: Manually scheduling artifacts across multiple workspaces is time-consuming. Fabric Scheduler automates this process.

• Support for Git Integration: As engineering teams emphasize Git integration and deployment pipelines, Fabric Scheduler ensures schedules can be version-controlled and deployed alongside artifacts.

• Schedule Preservation: When deploying artifacts to different workspaces, Fabric's native tools don't carry forward schedules. Fabric Scheduler solves this by allowing you to programmatically define and apply schedules.

• Multiple Schedule Support: Fabric's UI doesn't support creating multiple schedules for the same artifact. Fabric Scheduler enables more complex scheduling patterns.

• Standardization Across Teams: Implement consistent scheduling practices across engineering teams with a code-based approach.

Installation

.. code-block:: bash

pip install fabric_scheduler

Getting Started

Basic Usage

.. code-block:: python

from fabric_scheduler import ArtifactScheduler

# Initialize scheduler
scheduler = ArtifactScheduler()
# OR ArtifactScheduler(workspace_id="your-workspace-id")

# Set artifacts to schedule from list of dictionaries
artifacts = [
    {
        "displayName": "DailyAnalytics",
        "schedule": {
            "enabled": True,
            "config": {
                "type": "Daily",
                "times": ["08:00", "17:00"]
            }
        }
    },
    {
        "displayName": "WeeklyReport",
        "schedule": {
            "enabled": True,
            "config": {
                "type": "Weekly",
                "weekdays": ["Monday", "Wednesday"],
                "times": ["10:00"]
            }
        }
    },
]
scheduler.set_artifacts(artifacts)

# Create schedules
scheduler.create_schedules()

Input Methods

Dictionary Input

Define a list of dictionaries with familiar notation like JSON, and pass it to the set_artifacts method.

.. code-block:: python

scheduler.set_artifacts([
    {
        "displayName": "MyNotebook",
        "type": "Notebook",
        "schedule": {
            "enabled": True,
            "config": {
                "type": "Cron",
                "interval": 240,
                "localTimeZone": "India Standard Time",
            }
        }
    },
])

CSV File Input

Upload the CSV file and pass the file name to the load_artifacts_from_csv method.

.. code-block:: python

scheduler.load_artifacts_from_csv("artifact_schedule.csv")

Example CSV structure:

.. code-block::

displayName,type,enabled,schedule type,localTimeZone,startDate,startTime,endDate,endTime,interval,times,weekdays
SalesReportNotebook,Notebook,true,Cron,,3/30/2025,2:00,,,240,,
DataPipelineETL,Pipeline,true,Daily,,,,,,,"08:00,17:00",
WeeklyAnalyticsDataflow,Dataflow,true,Weekly,,,,,,,"08:00","Monday,Wednesday"

CSV String Input

Pass a CSV string directly to the load_artifacts_from_csv method.

.. code-block:: python

csv_content = '''
displayName,type,enabled,schedule type,localTimeZone,startDate,startTime,endDate,endTime,interval,times,weekdays
SalesReportNotebook,Notebook,true,Cron,,3/30/2025,2:00,,,240,,
DataPipelineETL,Pipeline,true,Daily,,,,,,,"08:00,17:00",
WeeklyAnalyticsDataflow,Dataflow,true,Weekly,,,,,,,"08:00","Monday,Wednesday"
'''
scheduler.load_artifacts_from_csv(csv_content)

Advanced Usage

For more detailed examples and advanced usage scenarios, please refer to the detailed guide <https://fabric-scheduler.readthedocs.io/en/stable/detailed_guide.html>_ section of our documentation.

API Reference

For comprehensive API documentation, please visit the API reference <https://fabric-scheduler.readthedocs.io/en/stable/api/modules.html>_ section of our documentation.

Contributing

Contributions are welcome! Please see our contributing guide <https://fabric-scheduler.readthedocs.io/en/stable/contributing.html>_ for details on how to get started.

License

This project is licensed under the MIT License - see the license file <https://fabric-scheduler.readthedocs.io/en/stable/license.html>_ for details.