PyDAX is designed to analyze DAX, it can extract comments, remove comments, and identify columns and measures referenced in DAX expressions.
Project description
PyDAX
PyDAX is a package designed to analyze DAX expressions. It can extract comments, remove comments, and identify columns and measures referenced in DAX expressions.
Installation
To install the package, use pip:
pip install PyDAXLexer
Usage
Here's how to use PyDAXLexer to analyze a DAX expression and surface helpful insights.
The example below intentionally violates a few best-practice rules (notably Unused Variables and FILTER patterns), and demonstrates how to:
- Extract comments and remove comments
- Extract table/column/measure references
- Verify best practices and list violating tokens
- Generate HTML highlighting violations
from PyDAX import DAXExpression
if __name__ == '__main__':
# Intentionally problematic DAX (for demo purposes):
# Two unused variables
# FILTER on table+column inside CALCULATE
# FILTER on table with measure predicate inside CALCULATE
dax_expression = """
// Demo calc with intentional violations
VAR UnusedVar1 = 123
VAR SalesPerCustomer = SUM(Sales[Amount]) / COUNTROWS(VALUES(Customers[CustomerID]))
VAR UnusedVar2 = IFERROR(SUM('Sales'[DiscountAmount]), 0)
RETURN
CALCULATE(
[Total Sales],
FILTER('Sales', 'Sales'[Quantity] > 10), // column filter (violation)
FILTER('Sales', [Total Sales] > 1000) // table + measure filter (violation)
)
"""
# Initialize the analyzer
expression = DAXExpression(dax_expression)
#Comments and comment-free expression
print("Comments:", expression.comments)
print("Expression without comments:", expression.dax_expression_no_comments)
#Table/Column/Measure references
print("Table/Artifact references:")
for ref in expression.table_column_references:
# DAXReference(table_name: str, artifact_name: str)
print(f" - Table='{ref.table_name}' Artifact='{ref.artifact_name}'")
#Best practices
expression.print_best_practices_violations()
print("Total best-practice violations:", expression.number_of_violations)
# HTML highlighting (optional)
# html_code = expression.generate_html_with_violations(name="Demo")
# expression.save_html_with_violations_to_file("demo_violations.html", name="Demo")
Additional Features
The DAXExpression class provides several utility methods:
remove_comments(): Returns the expression with comments removed (accessible asdax_expression_no_comments).extract_comments(): Returns a list of comment strings (accessible ascomments).extract_artifact_references(): Returns table/column/measure references asDAXReferenceobjects (accessible astable_column_references).generate_html(light: bool): Generates HTML output with syntax coloring.generate_html_with_violations(name: str, light: bool): Generates HTML and highlights best-practice violations.save_html_to_file(file_name: str): Saves the syntax-colored HTML output to a file.save_html_with_violations_to_file(file_name: str): Saves the violations-highlighted HTML output to a file.
Best-practices overview
When DAXExpression is created, it initializes a set of best-practice rules and verifies them by default. You can access:
best_practice_rules: List of rule instancesnumber_of_violations: Total count of violations across all rulesprint_best_practices_violations(): Print rule names and violating tokens with locations
Included rules (subject to change):
- Use DIVIDE instead of division operator
- Avoid IFERROR
- Use TREATAS instead of INTERSECT
- Filter column values with proper syntax
- Filter measure values by columns, not tables
- Unused variables
- Avoid 1 - x/y syntax
- Avoid EvaluateAndLog in production
License
This project is licensed under the MIT License.
Acknowledgments
TabularEditor
The lexer grammar used in this project is adapted from the TabularEditor GitHub repository.
- Source: TabularEditor GitHub Repository
- License: MIT License
ANTLR
This project uses ANTLR (ANother Tool for Language Recognition) to generate the lexer and parser for DAX expressions.
- Project: The ANTLR Project
- License: BSD-3-Clause License
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