DocDSL

A declarative DSL for extracting structured information from OCR output, PDFs, reports, and other semi-structured documents.

Instead of writing large, difficult-to-maintain regular expressions, DocDSL lets you describe what to extract using a simple, readable language while keeping extraction rules separate from your application code.

Installation

pip install docdsl

Quick Start

from docdsl import DSLTranslator

translator = DSLTranslator()

dsl = """
FIND "Patient:";
SKIP UNTIL NEWLINE;
CAPTURE TARGET [@NAME];
"""

pattern = translator.translate(dsl)
print(pattern)

with open("doc.txt", "r") as fh:
    text = fh.read()
    matches = pattern.finditer(text)
    for matched in matches:
        print(f"{matched=}")
        matched_groups = matched.groupdict()
        name = matched_groups.get("NAME", None)
        print(f"Name: {name}")

The NAME entity is part of DocDSL's built-in entity library and is available automatically. Custom entities can still be supplied when additional matching behaviour is required.

Features

• Declarative, English-like extraction language
• Reusable named entities
• Readable extraction rules
• Conditional extraction using IF
• Multi-line capture
• Capture between delimiters
• Built-in helper tokens
• Friendly syntax and validation errors
• Exact error locations with line and column information

Documentation

Complete language documentation is available in the DocDSL Documentation.

The reference includes:

• Complete command reference
• DSL syntax
• Built-in helper tokens
• Conditional statements
• Examples
• Best practices

Requirements

• Python 3.11+

Contributing

Contributions, bug reports and feature requests are welcome.

If you discover a bug or have an idea for improving DocDSL, please open an issue or submit a pull request.

License

Released under the MIT License.