Power BI Analyzer Script

1. Brief

This project provides a Python script (pbi_analyzer.py) designed to analyze Power BI Project (PBIP) files for optimization and adherence to best practices. It parses TMDL (Tabular Model Definition Language) content to extract information about measures, columns, partitions, tables, and relationships within a Power BI semantic model. The script then applies a set of Best Practice Analyzer (BPA) rules, fetched from Microsoft's Analysis Services GitHub repository, to identify potential violations and suggest improvements. Additionally, it performs basic visualization optimization checks and provides general recommendations for enhancing Power BI report performance.

2. Index

• 1. Brief
• 2. Index
• 3. Benefits
• 4. How to Run the Code
• 5. How to Navigate the Output
• 6. References Used
• 7. Codebase Overview

3. Benefits

• Automated Best Practice Analysis: Automatically checks your Power BI semantic models against a comprehensive set of best practice rules, helping to identify common performance bottlenecks and design issues.
• Improved Performance: Provides actionable insights and recommendations to optimize your Power BI reports and data models, leading to faster load times and better user experience.
• Code Quality Assurance: Helps maintain high-quality Power BI solutions by enforcing consistent design patterns and avoiding anti-patterns.
• Simplified Troubleshooting: Pinpoints specific measures, columns, tables, or relationships that violate best practices, making it easier to troubleshoot and rectify issues.
• Comprehensive Reporting: Generates a structured output file detailing BPA violations, visualization checks, and general optimization recommendations.

4. How to Run the Code

To run the pbi_analyzer.py script, follow these steps:

Prerequisites

• Python 3.x installed.
• Required Python libraries: requests. You can install it using pip:

  pip install requests

Usage

1. Download the script: Save pbi_analyzer.py to your local machine.
2. Locate your PBIP folder: Ensure you have a Power BI Project (PBIP) folder available. This folder typically contains Competitive Marketing Analysis.Report and Competitive Marketing Analysis.SemanticModel subfolders.
3. Update the pbip_folder_path variable: Open pbi_analyzer.py in a text editor and modify the pbip_folder_path variable to point to the absolute path of your PBIP folder.

   # --- USER INPUT SECTION ---
   # Please provide the full path to your PBIP folder here.
   # Example: pbip_folder_path = r"C:\Users\SUYOG\Downloads\TRIAL_01"
   pbip_folder_path = r"C:\Users\SUYOG\Downloads\TRIAL_01" # <--- EDIT THIS LINE WITH YOUR PBIP FOLDER PATH
   # --------------------------

   Replace "C:\Users\SUYOG\Downloads\TRIAL_01" with your actual path.
4. Run the script: Execute the script from your terminal:

   python pbi_analyzer.py

   The script will print analysis progress to the console and save the detailed results to a text file.

5. How to Navigate the Output

The script generates a text file (.txt) within a new BPA directory inside your specified PBIP folder. The filename will be in the format bpa_[semantic_model_name]_[timestamp].txt (e.g., bpa_Competitive Marketing Analysis_20250817_180552.txt).

The output file is structured into the following main sections:

• BPA Rule Violations: This section lists all identified best practice violations, grouped by category (e.g., "Measures", "Columns", "Relationships"). For each rule, it details:
  • Rule Name: The name of the violated rule.
  • Affected Objects: A list of specific Power BI objects (e.g., measures, columns, tables, relationships) that violate the rule.
  • Reference: Links to external documentation or articles explaining the rule and its importance.
• Visualization Optimization: Provides general checks and suggestions related to report page design and visual performance.
• General Recommendations: Offers broader advice for optimizing your Power BI solution, covering aspects like data source optimization, gateway settings, and performance monitoring.

Review each section to understand the identified issues and recommendations for improvement.

6. References Used

• Best Practice Analyzer (BPA) Rules: The script fetches its best practice rules from the official Microsoft Analysis Services GitHub repository:
  • https://raw.githubusercontent.com/microsoft/Analysis-Services/master/BestPracticeRules/BPARules.json
  • Microsoft Analysis Services Best Practice Rules

7. Codebase Overview

This section provides a detailed look into the key functions and structure of the pbi_analyzer.py script.

pbi_analyzer.py

The pbi_analyzer.py script is the central component of this project, responsible for orchestrating the analysis of Power BI Project (PBIP) files. It handles file reading, TMDL parsing, application of Best Practice Analyzer (BPA) rules, and generation of the final analysis report.

read_file_content

def read_file_content(filepath: str) -> str:
    """Reads the content of a file."""
    try:
        with open(filepath, 'r', encoding='utf-8') as f:
            return f.read()
    except FileNotFoundError:
        return ""

• Brief: A utility function to safely read the content of a given file. It returns an empty string if the file is not found.

parse_tmdl_for_objects

def parse_tmdl_for_objects(tmdl_content: str):
    """Parses TMDL content to extract measures, columns, partitions, and tables."""
    # ... (implementation details) ...

• Brief: Parses TMDL content using regular expressions to extract structured information about measures, columns, partitions (M queries), and tables.

parse_tmdl_for_relationships

def parse_tmdl_for_relationships(tmdl_content: str):
    """Parses TMDL content to extract relationships."""
    # ... (implementation details) ...

• Brief: Specifically parses TMDL content to extract relationship definitions, including source and target columns.

apply_bpa_rules

def apply_bpa_rules(rules, all_measures, all_columns, all_partitions, all_relationships, all_tables, model_properties):
    """Applies BPA rules to the parsed PBI model components and returns structured findings."""
    # ... (implementation details) ...

• Brief: The core logic for applying Best Practice Analyzer rules. It iterates through defined rules, evaluates their expressions against parsed Power BI objects, and identifies violations.

analyze_pbi_file

def analyze_pbi_file(pbip_path: str, bpa_rules: list):
    """
    Analyzes a PBIP file for optimization and best practices based on Microsoft's Power BI optimization guide and BPA rules.
    """
    # ... (implementation details) ...

• Brief: The main analysis function that orchestrates the entire process. It reads TMDL files, applies BPA rules, performs visualization checks, and compiles general recommendations.

Main Execution Block (if __name__ == "__main__":)

if __name__ == "__main__":
    # ... (implementation details) ...

• Brief: This block serves as the entry point when the script is executed. It handles setting the PBIP folder path, fetching BPA rules from GitHub, running the analysis, and saving the formatted results to a text file.