Skip to main content

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 as dax_expression_no_comments).
  • extract_comments(): Returns a list of comment strings (accessible as comments).
  • extract_artifact_references(): Returns table/column/measure references as DAXReference objects (accessible as table_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 instances
  • number_of_violations: Total count of violations across all rules
  • print_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.

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

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

pydaxlexer-0.2.1.tar.gz (64.2 kB view details)

Uploaded Source

Built Distribution

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

pydaxlexer-0.2.1-py3-none-any.whl (65.2 kB view details)

Uploaded Python 3

File details

Details for the file pydaxlexer-0.2.1.tar.gz.

File metadata

  • Download URL: pydaxlexer-0.2.1.tar.gz
  • Upload date:
  • Size: 64.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.8

File hashes

Hashes for pydaxlexer-0.2.1.tar.gz
Algorithm Hash digest
SHA256 d30e51b07ff625fc1d326c6f8a61b0fe933e53460fe61c14e22c83c82c0e441a
MD5 cc816e6020f942dc6dd8bf151185b0d9
BLAKE2b-256 e49fd24e08250464fe0a101c10d553a55ef0f881d6d631d79fdbcacdf7998f18

See more details on using hashes here.

File details

Details for the file pydaxlexer-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: pydaxlexer-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 65.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.8

File hashes

Hashes for pydaxlexer-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 18f923819fff239353be921686a10967c414f2c1d6520fad5517e9a747df7fa3
MD5 f9f12790b1ab9f51affaaa76cd23e5f3
BLAKE2b-256 b875c733fb1c616fa7abe1492f8e7e0fe55190f43dac1dd1fb663647c7e8c084

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