Skip to main content

A Fabric Package for Semantic/Dataset validation

Project description

Fabric Maverick

Python Version License

Table of Contents

Overview

fabric_maverick is a Python package designed for semantic level validation and comparison of Power BI reports across different workspaces. It provides a robust framework to programmatically compare the metadata and structure of your Fabric Analytics Reports (formerly Power BI datasets/reports) to ensure consistency and identify discrepancies.

This package is particularly useful for:

  • CI/CD pipelines: Automating report validation as part of your deployment process.
  • Regression testing: Ensuring that changes to reports or underlying data models do not introduce unintended breaking changes.
  • Maintaining consistency: Verifying that reports deployed to different environments (Dev, QA, Prod) are structurally identical or conform to expected variations.

Features

  • Report Comparison: Easily compare the structure (tables, columns, measures) of two Fabric Analytics Reports from different workspaces.
  • Flexible Input: Supports comparing reports by providing individual report/workspace names or a consolidated dictionary structure.
  • Authentication Management: Integrates with a flexible token provider for seamless authentication with Fabric/Power BI services.
  • Detailed Insights: [TODO: Briefly describe what kind of comparison results/details the ReportComparison object provides. E.g., "Identifies added, removed, or modified tables, columns, and measures."]
  • Extensible: Built with a modular design to allow for future expansion of comparison metrics and validation rules.

Installation

fabric_maverick can be installed directly from PyPI using pip:

pip install fabric_maverick

Usage

Comparing Reports

The primary function for comparing reports is ReportCompare. It offers two ways to specify the reports:

import knnpy

Compare = knnpy.ReportCompare(
    OldReport="MySalesDashboard_V1",
    OldReportWorkspace="Development",
    NewReport="MySalesDashboard_V2",
    NewReportWorkspace="Production",
    Stream="SalesDashboard_Deployment",
    ExplicitToken="YOUR_ACCESS_TOKEN_IF_NEEDED" # Optional
)

# Use the Compare object to run validations and view results
Compare.run_all_validations()

Authentication

By default, fabric_maverick will use token from fabric enviornment. However, you can explicitly provide an authentication token using the ExplicitToken parameter in ReportCompare:

import knnpy

# Obtain your Power BI/Fabric access token
my_token = "eyJ..." # Replace with your actual token

comparison_result = knnpy.ReportCompare(
    # ... report details ...
    Stream="MyStream",
    ExplicitToken=my_token
)

Alternatively, you can initialize a token globally for the session using initializeToken:

import knnpy

# Initialize token globally (this affects all subsequent calls without ExplicitToken)
knnpy.initializeToken("YOUR_GLOBAL_ACCESS_TOKEN")

# Now, ReportCompare calls can omit ExplicitToken
comparison_result = knnpy.ReportCompare(
    OldReport="ReportA",
    OldReportWorkspace="WS_A",
    NewReport="ReportB",
    NewReportWorkspace="WS_B",
    Stream="AnotherStream"
)

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For questions or feedback, please reach out to the maintainers.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fabric_maverick-0.1.0.dev5.tar.gz (12.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

fabric_maverick-0.1.0.dev5-py3-none-any.whl (15.0 kB view details)

Uploaded Python 3

File details

Details for the file fabric_maverick-0.1.0.dev5.tar.gz.

File metadata

  • Download URL: fabric_maverick-0.1.0.dev5.tar.gz
  • Upload date:
  • Size: 12.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.9

File hashes

Hashes for fabric_maverick-0.1.0.dev5.tar.gz
Algorithm Hash digest
SHA256 6c9f30d81b56b73bdcb429089871ec50d0605b68396cb6f83b006960d3e9ede5
MD5 ba0d1bc23888835db807c0ae40dbeb2b
BLAKE2b-256 961d68294aedddd9147180bed299cfa3b0bd3f9a5bf7d21666527b973a1571b9

See more details on using hashes here.

File details

Details for the file fabric_maverick-0.1.0.dev5-py3-none-any.whl.

File metadata

File hashes

Hashes for fabric_maverick-0.1.0.dev5-py3-none-any.whl
Algorithm Hash digest
SHA256 66c5dca697de20932ebcbb7416ab48fc6997257d132458e9d418ebb563d39faa
MD5 505ed3c707ff734806a449694dedef57
BLAKE2b-256 059051c2a4076ff47e71ba4a40770949729a47a7a22f1978feedcc801a5eeff9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page