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 a how to use PyDAXLexer. This example shows how to create a DAXExpression object and extract information.

from PyDAX import DAXExpression

if __name__ == '__main__':
    # DAX expression as string:
    dax_expression = """
    // Calculate average sales per customer, considering only active customers
    VAR SalesPerCustomer = 
        DIVIDE(
            SUM(Sales[TotalAmount]), 
            COUNTROWS(VALUES(Customers[CustomerID]))
        )
        
    // Calculate discount impact
    VAR DiscountImpact = 
        SUMX(
            FILTER(
                Sales,
                Sales[Discount] > 0
            ),
            Sales[DiscountAmount]
        )

    RETURN 
        IF(
            SalesPerCustomer > 500 && DiscountImpact < 1000,
            "High Value Customer",
            "Standard Customer"
        )
    """
    
    # Initialize the DAXExpression object
    expression = DAXExpression(dax_expression)
    
    # Access various properties
    print("Original Expression:", expression.dax_expression)
    print("Expression without Comments:", expression.dax_expression_no_comments)
    print("Table and Column References:", expression.table_column_references)
    print("Extracted Comments:", expression.comments)
    print("Cleaned Expression:", expression.clean_dax_expression)
    print("Contains Division Operator:", expression.contains_div)

Additional Features

The DAXExpression class provides several utility methods:

  • remove_comments(): Removes comments from the DAX expression.
  • extract_comments(): Extracts all comments in the expression.
  • extract_artifact_references(): Extracts table and column references.
  • generate_html(light: bool): Generates HTML output of the expression with syntax coloring.
  • save_html_to_file(file_name: str): Saves the syntax-colored HTML output to a file.

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-0.1.5.tar.gz (53.8 kB view details)

Uploaded Source

Built Distribution

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

pydaxlexer-0.1.5-py3-none-any.whl (51.8 kB view details)

Uploaded Python 3

File details

Details for the file pydaxlexer-0.1.5.tar.gz.

File metadata

  • Download URL: pydaxlexer-0.1.5.tar.gz
  • Upload date:
  • Size: 53.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.8

File hashes

Hashes for pydaxlexer-0.1.5.tar.gz
Algorithm Hash digest
SHA256 c46adc3458696aa8bcc8e5ed453c97f9c23172231a444ed05227c237241bb12c
MD5 076c186b7ff800c3d0fe226f04432148
BLAKE2b-256 3d6e32e8b01702abfb6d4dd6539af3d5e00bd6502bab32c29773dc814c03d79b

See more details on using hashes here.

File details

Details for the file pydaxlexer-0.1.5-py3-none-any.whl.

File metadata

  • Download URL: pydaxlexer-0.1.5-py3-none-any.whl
  • Upload date:
  • Size: 51.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.8

File hashes

Hashes for pydaxlexer-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 15691b3b3b4f6ebf12e3690bf8f7167bd40a52c21352cf62bf4c5f5261dd7c05
MD5 916ef4eb17fef7ac16c47447052bd96a
BLAKE2b-256 119869578be383c4e641db58428f59126c2d341e98ddb37cc640b4c686b966fc

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