dql-parser 0.1.1

Pure Python parser for Data Quality Language (DQL)

dql-parser

Pure Python parser for Data Quality Language (DQL) - a human-readable language for defining data quality expectations.

Documentation | PyPI | GitHub

Features

• 🚀 Zero Dependencies (except Lark parser)
• 🎯 Framework-Agnostic - No Django, Flask, or any framework required
• ⚡ Fast - Parses 100-line DQL files in <50ms
• 📝 Clear Error Messages - Line and column information for syntax errors
• 🐍 Python 3.8+ - Supports Python 3.8 through 3.12

Installation

pip install dql-parser

Quick Start

from dql_parser import DQLParser

# Parse DQL text
parser = DQLParser()
ast = parser.parse("""
FROM Customer
EXPECT column("email") to_not_be_null SEVERITY critical
EXPECT column("age") to_be_between(18, 120)
""")

# Access parsed expectations
for from_block in ast.from_blocks:
    print(f"Model: {from_block.model_name}")
    for expectation in from_block.expectations:
        print(f"  - {expectation.operator}")

DQL Syntax Overview

DQL (Data Quality Language) is a declarative language for defining data quality rules:

FROM ModelName

EXPECT column("field_name") to_not_be_null SEVERITY critical
EXPECT column("email") to_match_pattern("[a-z]+@[a-z]+\\.[a-z]+")
EXPECT column("age") to_be_between(0, 150)
EXPECT column("status") to_be_in("active", "pending", "closed")
EXPECT column("id") to_be_unique

Supported Operators

• to_be_null - Column must be NULL
• to_not_be_null - Column must not be NULL
• to_match_pattern(regex) - Column must match regex pattern
• to_be_between(min, max) - Column must be between min and max
• to_be_in(value1, value2, ...) - Column must be one of the values
• to_be_unique - Column must have unique values

Severity Levels

• critical - Must pass for validation to succeed
• warning - Logged but doesn't fail validation
• info - Informational only

API Reference

DQLParser

Main parser class for DQL syntax.

parser = DQLParser()

parse(text: str) -> DQLFile

Parse DQL text and return AST.

Args:

• text: DQL source text

Returns:

• DQLFile: Root AST node

Raises:

• DQLSyntaxError: If syntax is invalid

parse_file(filepath: str) -> DQLFile

Parse DQL file and return AST.

Args:

• filepath: Path to .dql file

Returns:

• DQLFile: Root AST node

Raises:

• DQLSyntaxError: If syntax is invalid
• FileNotFoundError: If file doesn't exist

AST Nodes

The parser returns an Abstract Syntax Tree (AST) composed of dataclass nodes:

• DQLFile - Root node containing from_blocks
• FromBlock - Represents a FROM block with model_name and expectations
• ExpectationNode - Single expectation with target, operator, severity
• ColumnTarget - Column reference
• RowTarget - Row-level condition
• Operators: ToBeNull, ToNotBeNull, ToMatchPattern, ToBeBetween, ToBeIn, ToBeUnique

Error Handling

DQL parser provides clear, actionable error messages:

try:
    ast = parser.parse("EXPECT column('email') invalid_operator")
except DQLSyntaxError as e:
    print(e)
    # Output: Syntax error at line 1, column 30: unexpected token 'invalid_operator'

Development

Setup

# Clone repository
git clone https://github.com/dql-project/dql-parser.git
cd dql-parser

# Install in development mode
pip install -e ".[dev]"

# Install pre-commit hooks
pre-commit install

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=dql_parser --cov-report=html

# Run specific test file
pytest tests/test_valid_syntax.py

Code Quality

# Format code
black dql_parser tests

# Lint code
flake8 dql_parser tests

# Type check
mypy dql_parser

Documentation

Full documentation: https://yourusername.github.io/dql-parser/

• Grammar Reference - Complete DQL syntax specification
• AST Reference - AST node documentation
• Examples - Usage examples
• API Reference - Complete API

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

License

MIT License - see LICENSE for details.

Related Projects

• dql-core - Framework-agnostic validation engine (docs)
• django-dqm - Django integration with Admin dashboard (docs)

Package Selection

Not sure which package to use? See the Package Selection Guide

Changelog

See CHANGELOG.md for version history.