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# Power BI Measure Call Graph
A Flask web application that visualizes the dependency relationships between measures in a Power BI / Analysis Services model.
## Features
- Connect to Analysis Services models
- Extract measures and their DAX expressions
- Parse DAX expressions to determine dependencies between measures
- Visualize the call graph with an interactive D3.js visualization
- Search for specific measures
- Click on measures to highlight dependencies
- Hover over measures to see their DAX expressions
## Requirements
- Python 3.7+
- Microsoft Analysis Services ODBC driver (MSOLAP)
- Access to a Power BI / Analysis Services model
## Installation
1. Clone this repository:
```
git clone https://github.com/yourusername/pbi-measure-callgraph.git
cd pbi-measure-callgraph
```
2. Create a virtual environment (optional but recommended):
```
python -m venv venv
venv\Scripts\activate # Windows
source venv/bin/activate # macOS/Linux
```
3. Install the required packages:
```
pip install -r requirements.txt
```
## Usage
1. Start the Flask application:
```
python app.py
```
2. Open your web browser and navigate to:
```
http://localhost:5000
```
3. Enter your Analysis Services server and database information and click "Connect"
4. Once connected, the call graph will be displayed with all measures from your model
5. Interact with the graph:
- Click on a measure to highlight its dependencies
- Hover over a measure to see its DAX expression
- Use the search box to find specific measures
- Use the mouse wheel to zoom in/out
- Drag the graph to pan
- Click the "Reset View" button to center the graph
## How It Works
1. **Connection**: The application connects to your Analysis Services model using the MSOLAP ODBC driver
2. **Measure Extraction**: It retrieves all visible measures and their DAX expressions
3. **Dependency Analysis**: The DAX parser analyzes each expression to identify references to other measures
4. **Visualization**: The D3.js force-directed graph visualizes the dependencies between measures
## Troubleshooting
- **Connection Issues**: Ensure you have the MSOLAP driver installed and that you have access to the specified server and database
- **Missing Measures**: Only visible measures are included in the graph
- **Incorrect Dependencies**: The DAX parser uses a simplified approach to identify measure references and may not catch all complex scenarios
## License
MIT

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from flask import Flask, render_template, jsonify, request
import json
import os
from model_connector import ModelConnector
from dax_parser import DaxParser
app = Flask(__name__)
# Initialize the model connector and DAX parser
model_connector = None
dax_parser = DaxParser()
@app.route('/')
def index():
"""Render the main page."""
return render_template('index.html')
@app.route('/connect', methods=['POST'])
def connect():
"""Connect to the Analysis Services model."""
global model_connector
data = request.json
server = data.get('server')
database = data.get('database')
try:
model_connector = ModelConnector(server, database)
return jsonify({'success': True, 'message': 'Connected successfully'})
except Exception as e:
return jsonify({'success': False, 'message': str(e)})
@app.route('/get_measures')
def get_measures():
"""Get all measures from the connected model."""
if not model_connector:
return jsonify({'success': False, 'message': 'Not connected to a model'})
try:
measures = model_connector.get_measures()
return jsonify({'success': True, 'measures': measures})
except Exception as e:
return jsonify({'success': False, 'message': str(e)})
@app.route('/get_call_graph')
def get_call_graph():
"""Generate and return the call graph data."""
if not model_connector:
return jsonify({'success': False, 'message': 'Not connected to a model'})
try:
measures_df = model_connector.get_measures()
measures = measures_df.to_dict(orient="records")
graph = dax_parser.build_call_graph(measures)
return jsonify({'success': True, 'graph': graph})
except Exception as e:
return jsonify({'success': False, 'message': str(e)})
if __name__ == '__main__':
app.run(debug=True)

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import re
class DaxParser:
"""Class to parse DAX expressions and build dependency graphs."""
def __init__(self):
"""Initialize the DAX parser."""
# Regular expression to match measure references in DAX
# This is a simplified pattern and may need refinement for complex DAX
self.measure_ref_pattern = r'\[([^\]]+)\]'
def extract_measure_references(self, dax_expression, all_measure_names):
"""
Extract references to other measures from a DAX expression.
Args:
dax_expression (str): The DAX expression to parse
all_measure_names (list): List of all measure names in the model
Returns:
list: Names of measures referenced in the expression
"""
if not dax_expression:
return []
# Find all potential measure references (anything in square brackets)
potential_refs = re.findall(self.measure_ref_pattern, dax_expression)
# Filter to only include actual measure names
# This helps avoid false positives like column references
measure_refs = [ref for ref in potential_refs if ref in all_measure_names]
return list(set(measure_refs)) # Remove duplicates
def build_call_graph(self, measures):
"""
Build a call graph of measure dependencies.
Args:
measures (list): List of measure dictionaries with 'name' and 'expression' keys
Returns:
dict: A graph representation with nodes and links
"""
# Extract all measure names
all_measure_names = [measure['name'] for measure in measures]
# Create nodes for the graph
nodes = [{'id': measure['name'], 'expression': measure['expression']} for measure in measures]
# Create links (dependencies) for the graph
links = []
for measure in measures:
source = measure['name']
expression = measure['expression']
# Find references to other measures in this expression
references = self.extract_measure_references(expression, all_measure_names)
# Add links for each reference
for target in references:
links.append({
'source': source,
'target': target
})
return {
'nodes': nodes,
'links': links
}

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from sys import path
path.append('D:\\Personal_Files\\document\\GitHub\\Test\\MSNET')
import pyadomd
import pandas as pd
class ModelConnector:
"""Class to connect to and retrieve data from Analysis Services models."""
def __init__(self, server, database):
"""
Initialize the connection to the Analysis Services model.
Args:
server (str): The server name or IP address
database (str): The database name
"""
self.server = server
self.database = database
# self.connection_string = f"Provider=MSOLAP;Data Source={server}"
self.connection_string = f"Provider=MSOLAP;Data Source=localhost:56195"
self.connection = None
self.connect()
def connect(self):
"""Establish a connection to the Analysis Services model."""
try:
self.connection = pyadomd.Pyadomd(self.connection_string)
self.connection.open()
return True
except Exception as e:
raise Exception(f"Failed to connect to the model: {str(e)}")
def execute_query(self, query):
"""
Execute a DAX or MDX query against the model.
Args:
query (str): The DAX or MDX query to execute
Returns:
pandas.DataFrame: The query results
"""
if not self.connection:
self.connect()
try:
with self.connection.cursor().execute(query) as conn:
rows = conn.fetchall()
df = pd.DataFrame(rows, columns=[col[0] for col in conn._description])
return df
except Exception as e:
raise Exception(f"Failed to execute query: {str(e)}")
def get_measures(self):
"""
Retrieve all measures from the model.
Returns:
list: A list of dictionaries containing measure information
"""
# DMV query to get all measures
query = """
SELECT
[MEASURE_NAME] as [name],
[EXPRESSION] as [expression],
[MEASURE_CAPTION] as [caption],
[MEASURE_DISPLAY_FOLDER] as [display_folder],
[DESCRIPTION] as [description]
FROM $SYSTEM.MDSCHEMA_MEASURES
WHERE MEASURE_IS_VISIBLE
"""
try:
df = self.execute_query(query)
return df if not df.empty else []
except Exception as e:
raise Exception(f"Failed to retrieve measures: {str(e)}")
if __name__ == '__main__':
# Example usage
server = 'localhost:56195'
database = 'Exteranl All Channel'
model_connector = ModelConnector(server, database)
measures = model_connector.get_measures()
print(measures) # List of measure dictionaries

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Flask==2.3.3
pyodbc==4.0.39
pandas==2.2.3

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/* Global styles */
* {
box-sizing: border-box;
margin: 0;
padding: 0;
}
body {
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
line-height: 1.6;
color: #333;
background-color: #f5f5f5;
}
.container {
max-width: 1400px;
margin: 0 auto;
padding: 20px;
}
header {
text-align: center;
margin-bottom: 30px;
}
h1 {
color: #0078d4;
margin-bottom: 10px;
}
h2 {
color: #0078d4;
margin-bottom: 15px;
font-size: 1.5rem;
}
/* Connection panel */
.connection-panel {
background-color: white;
padding: 20px;
border-radius: 5px;
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
margin-bottom: 20px;
}
.form-group {
margin-bottom: 15px;
}
label {
display: block;
margin-bottom: 5px;
font-weight: 500;
}
input[type="text"] {
width: 100%;
padding: 8px;
border: 1px solid #ddd;
border-radius: 4px;
font-size: 1rem;
}
button {
background-color: #0078d4;
color: white;
border: none;
padding: 10px 15px;
border-radius: 4px;
cursor: pointer;
font-size: 1rem;
transition: background-color 0.3s;
}
button:hover {
background-color: #005a9e;
}
#connection-status {
margin-top: 10px;
font-weight: 500;
}
.success {
color: #107c10;
}
.error {
color: #d83b01;
}
/* Visualization container */
.visualization-container {
background-color: white;
padding: 20px;
border-radius: 5px;
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
margin-bottom: 20px;
}
.controls {
display: flex;
justify-content: space-between;
margin-bottom: 15px;
}
.search-box {
flex-grow: 1;
margin-left: 15px;
}
#graph-container {
width: 100%;
height: 600px;
border: 1px solid #ddd;
border-radius: 4px;
overflow: hidden;
}
/* Graph styles */
.node circle {
fill: #0078d4;
stroke: #fff;
stroke-width: 2px;
}
.node text {
font-size: 12px;
fill: #333;
}
.node.highlighted circle {
fill: #ffb900;
}
.node.selected circle {
fill: #107c10;
}
.link {
stroke: #999;
stroke-opacity: 0.6;
stroke-width: 1px;
}
.link.highlighted {
stroke: #ffb900;
stroke-opacity: 0.8;
stroke-width: 2px;
}
/* Measure details */
.measure-details {
background-color: white;
padding: 20px;
border-radius: 5px;
box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
}
#measure-name {
font-size: 1.2rem;
font-weight: 600;
margin-bottom: 10px;
}
#measure-expression {
background-color: #f8f8f8;
padding: 15px;
border-radius: 4px;
border: 1px solid #ddd;
white-space: pre-wrap;
font-family: Consolas, Monaco, 'Andale Mono', monospace;
font-size: 0.9rem;
overflow-x: auto;
}
/* Tooltip */
.tooltip {
position: absolute;
background-color: rgba(0, 0, 0, 0.8);
color: white;
padding: 10px;
border-radius: 4px;
font-size: 12px;
max-width: 300px;
z-index: 10;
pointer-events: none;
}

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/**
* Main application JavaScript for the Power BI Measure Call Graph
*/
// DOM elements
const serverInput = document.getElementById('server');
const databaseInput = document.getElementById('database');
const connectBtn = document.getElementById('connect-btn');
const connectionStatus = document.getElementById('connection-status');
const resetBtn = document.getElementById('reset-btn');
const searchInput = document.getElementById('search-input');
const measureName = document.getElementById('measure-name');
const measureExpression = document.getElementById('measure-expression');
// Graph instance
let graph = null;
// Event listeners
document.addEventListener('DOMContentLoaded', () => {
// Initialize the graph
graph = new Graph('#graph-container');
// Connect button
connectBtn.addEventListener('click', connectToModel);
// Reset button
resetBtn.addEventListener('click', () => {
if (graph) {
graph.resetView();
}
});
// Search input
searchInput.addEventListener('input', (e) => {
if (graph) {
graph.searchNodes(e.target.value);
}
});
});
/**
* Connect to the Analysis Services model
*/
async function connectToModel() {
const server = serverInput.value.trim() || 'localhost';
const database = databaseInput.value.trim();
if (!database) {
showConnectionStatus('Please enter a database name', 'error');
return;
}
try {
showConnectionStatus('Connecting...', '');
// Connect to the model
const connectResponse = await fetch('/connect', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({ server, database })
});
const connectData = await connectResponse.json();
if (!connectData.success) {
showConnectionStatus(`Connection failed: ${connectData.message}`, 'error');
return;
}
showConnectionStatus('Connected successfully. Loading measures...', 'success');
// Get the call graph data
const graphResponse = await fetch('/get_call_graph');
const graphData = await graphResponse.json();
if (!graphData.success) {
showConnectionStatus(`Failed to load graph: ${graphData.message}`, 'error');
return;
}
// Initialize the graph with the data
graph.setData(graphData.graph);
graph.render();
showConnectionStatus('Graph loaded successfully', 'success');
} catch (error) {
showConnectionStatus(`Error: ${error.message}`, 'error');
}
}
/**
* Show connection status message
* @param {string} message - The message to display
* @param {string} type - The message type (success, error, or empty for neutral)
*/
function showConnectionStatus(message, type) {
connectionStatus.textContent = message;
connectionStatus.className = type;
}
/**
* Display measure details
* @param {Object} measure - The measure object
*/
function showMeasureDetails(measure) {
if (!measure) {
measureName.textContent = '';
measureExpression.textContent = '';
return;
}
measureName.textContent = measure.id;
measureExpression.textContent = measure.expression || 'No expression available';
}
// Export functions for use in graph.js
window.appFunctions = {
showMeasureDetails
};

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/**
* Graph visualization using D3.js for the Power BI Measure Call Graph
*/
class Graph {
/**
* Initialize the graph
* @param {string} selector - CSS selector for the container element
*/
constructor(selector) {
this.container = d3.select(selector);
this.width = this.container.node().getBoundingClientRect().width;
this.height = this.container.node().getBoundingClientRect().height;
this.data = null;
this.simulation = null;
this.svg = null;
this.zoom = null;
this.tooltip = null;
this.selectedNode = null;
this.init();
}
/**
* Initialize the SVG and D3 components
*/
init() {
// Create SVG
this.svg = this.container.append('svg')
.attr('width', this.width)
.attr('height', this.height)
.attr('class', 'graph-svg');
// Create zoom behavior
this.zoom = d3.zoom()
.scaleExtent([0.1, 4])
.on('zoom', (event) => {
this.g.attr('transform', event.transform);
});
// Apply zoom to SVG
this.svg.call(this.zoom);
// Create a group for the graph elements
this.g = this.svg.append('g');
// Create tooltip
this.tooltip = d3.select('body').append('div')
.attr('class', 'tooltip')
.style('opacity', 0);
// Handle window resize
window.addEventListener('resize', () => {
this.width = this.container.node().getBoundingClientRect().width;
this.height = this.container.node().getBoundingClientRect().height;
this.svg.attr('width', this.width).attr('height', this.height);
if (this.simulation) {
this.simulation.alpha(0.3).restart();
}
});
}
/**
* Set the graph data
* @param {Object} data - The graph data with nodes and links
*/
setData(data) {
this.data = data;
}
/**
* Render the graph
*/
render() {
if (!this.data) return;
// Clear previous graph
this.g.selectAll('*').remove();
// Create links
const links = this.g.append('g')
.attr('class', 'links')
.selectAll('line')
.data(this.data.links)
.enter().append('line')
.attr('class', 'link');
// Create nodes
const nodes = this.g.append('g')
.attr('class', 'nodes')
.selectAll('.node')
.data(this.data.nodes)
.enter().append('g')
.attr('class', 'node')
.call(d3.drag()
.on('start', this.dragStarted.bind(this))
.on('drag', this.dragged.bind(this))
.on('end', this.dragEnded.bind(this)));
// Add circles to nodes
nodes.append('circle')
.attr('r', 8);
// Add text labels to nodes
nodes.append('text')
.attr('dx', 12)
.attr('dy', '.35em')
.text(d => d.id);
// Add event listeners to nodes
nodes
.on('mouseover', (event, d) => {
// Show tooltip
this.tooltip.transition()
.duration(200)
.style('opacity', .9);
this.tooltip.html(d.expression)
.style('left', (event.pageX + 10) + 'px')
.style('top', (event.pageY - 28) + 'px');
})
.on('mouseout', () => {
// Hide tooltip
this.tooltip.transition()
.duration(500)
.style('opacity', 0);
})
.on('click', (event, d) => {
event.stopPropagation();
this.selectNode(d);
});
// Create simulation
this.simulation = d3.forceSimulation(this.data.nodes)
.force('link', d3.forceLink(this.data.links).id(d => d.id).distance(100))
.force('charge', d3.forceManyBody().strength(-300))
.force('center', d3.forceCenter(this.width / 2, this.height / 2))
.force('collision', d3.forceCollide().radius(30))
.on('tick', () => {
links
.attr('x1', d => d.source.x)
.attr('y1', d => d.source.y)
.attr('x2', d => d.target.x)
.attr('y2', d => d.target.y);
nodes.attr('transform', d => `translate(${d.x},${d.y})`);
});
// Add click handler to SVG to deselect nodes
this.svg.on('click', () => {
this.selectNode(null);
});
// Center the graph initially
this.resetView();
}
/**
* Handle drag start event
*/
dragStarted(event, d) {
if (!event.active) this.simulation.alphaTarget(0.3).restart();
d.fx = d.x;
d.fy = d.y;
}
/**
* Handle drag event
*/
dragged(event, d) {
d.fx = event.x;
d.fy = event.y;
}
/**
* Handle drag end event
*/
dragEnded(event, d) {
if (!event.active) this.simulation.alphaTarget(0);
d.fx = null;
d.fy = null;
}
/**
* Select a node and highlight its connections
* @param {Object|null} node - The node to select, or null to deselect
*/
selectNode(node) {
this.selectedNode = node;
// Show measure details
if (window.appFunctions && window.appFunctions.showMeasureDetails) {
window.appFunctions.showMeasureDetails(node);
}
// Reset all nodes and links
this.g.selectAll('.node').classed('selected', false).classed('highlighted', false);
this.g.selectAll('.link').classed('highlighted', false);
if (!node) return;
// Get connected nodes
const connectedNodes = new Set();
const connectedLinks = new Set();
// Find incoming links (where this node is the target)
this.data.links.forEach(link => {
if (link.target.id === node.id) {
connectedNodes.add(link.source.id);
connectedLinks.add(link);
}
});
// Find outgoing links (where this node is the source)
this.data.links.forEach(link => {
if (link.source.id === node.id) {
connectedNodes.add(link.target.id);
connectedLinks.add(link);
}
});
// Highlight the selected node
this.g.selectAll('.node')
.filter(d => d.id === node.id)
.classed('selected', true);
// Highlight connected nodes
this.g.selectAll('.node')
.filter(d => connectedNodes.has(d.id))
.classed('highlighted', true);
// Highlight connected links
this.g.selectAll('.link')
.filter(d => connectedLinks.has(d))
.classed('highlighted', true);
}
/**
* Search for nodes by name
* @param {string} query - The search query
*/
searchNodes(query) {
if (!query) {
// Reset all nodes if query is empty
this.g.selectAll('.node').style('opacity', 1);
return;
}
const lowerQuery = query.toLowerCase();
// Filter nodes based on the query
this.g.selectAll('.node').style('opacity', d => {
return d.id.toLowerCase().includes(lowerQuery) ? 1 : 0.2;
});
}
/**
* Reset the view to center the graph
*/
resetView() {
const bounds = this.g.node().getBBox();
const dx = bounds.width;
const dy = bounds.height;
const x = bounds.x + dx / 2;
const y = bounds.y + dy / 2;
// Calculate the scale to fit the graph
const scale = 0.9 / Math.max(dx / this.width, dy / this.height);
const translate = [this.width / 2 - scale * x, this.height / 2 - scale * y];
// Apply the transform
this.svg.transition()
.duration(750)
.call(this.zoom.transform, d3.zoomIdentity
.translate(translate[0], translate[1])
.scale(scale));
}
}

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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Power BI Measure Call Graph</title>
<link rel="stylesheet" href="{{ url_for('static', filename='css/style.css') }}">
<!-- D3.js for visualization -->
<script src="https://d3js.org/d3.v7.min.js"></script>
</head>
<body>
<div class="container">
<header>
<h1>Power BI Measure Call Graph</h1>
</header>
<div class="connection-panel">
<h2>Connect to Analysis Services</h2>
<div class="form-group">
<label for="server">Server:</label>
<input type="text" id="server" placeholder="localhost">
</div>
<div class="form-group">
<label for="database">Database:</label>
<input type="text" id="database" placeholder="AdventureWorks">
</div>
<button id="connect-btn">Connect</button>
<div id="connection-status"></div>
</div>
<div class="visualization-container">
<div class="controls">
<button id="reset-btn">Reset View</button>
<div class="search-box">
<input type="text" id="search-input" placeholder="Search measures...">
</div>
</div>
<div id="graph-container"></div>
</div>
<div class="measure-details">
<h2>Measure Details</h2>
<div id="measure-name"></div>
<pre id="measure-expression"></pre>
</div>
</div>
<script src="{{ url_for('static', filename='js/graph.js') }}"></script>
<script src="{{ url_for('static', filename='js/app.js') }}"></script>
</body>
</html>