dargs

What it is and what it does

dargs is a Python argument validation and documentation library that examines input dictionaries against a schema you define using the Argument class. It checks types, validates nested keys and sub-argument types, and supports a special variant mode where dictionary contents can be determined by the value of a flag key. The library provides three main methods: check (validates structure), normalize (adds defaults and resolves aliases), and gendoc (outputs documentation with optional HTML anchors for cross-reference).

The package integrates with PEP 484 type annotations and offers native support for Sphinx, Jupyter Notebook, and DP-GUI. It can generate JSON schema from an Argument definition for use with JSON editors, and supports loading dictionary values from external JSON or YAML files via a $ref key. It's designed for projects that need declarative, reusable argument schemas with built-in documentation generation.

Use it for:

• Define and validate configuration dictionaries for scientific computing or deep learning pipelines with nested parameters and type safety
• Generate documentation and JSON schemas from argument definitions for use in web UIs or IDE integrations
• Normalize user input by applying default values and resolving aliases before passing to downstream functions
• Handle variant argument structures where the allowed keys depend on the value of a discriminator flag
• Integrate argument validation into Sphinx-based documentation or Jupyter notebooks for interactive parameter exploration

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Validates, normalizes, and documents structured argument dictionaries with type checking, default values, and variant support for Python programs.

Yes, if you need declarative argument validation with built-in documentation. The package is actively maintained, has low install friction, and solves a real problem for projects with complex nested configuration. The LGPLv3 license requires careful review if you're building proprietary software, but the library itself is stable and dependency-light.

Install

dargs on PyPI

pip install dargs

uv add dargs

poetry add dargs

Installing dargs

Before you install

Low install friction with a pure-Python wheel and only two lightweight runtime dependencies (typeguard, typing_extensions). Repository is active with recent commits and no archived status.

License in practice

LGPLv3 copyleft license requires that derivative works and modifications be distributed under the same license; proprietary applications using this as a library may need to comply with linking and disclosure obligations.

Quickstart

pip install dargs

from dargs import Argument

arg_def = Argument('config', dict, [Argument('key', str)])
arg_def.check({'key': 'value'})

Verify before relying

• Whether JSON schema generation integrates with external JSON editors as claimed in the description
• Scope and maturity of Sphinx and Jupyter Notebook integration features
• Performance characteristics when validating deeply nested or large argument structures

Package facts

Evidence: dargs-0.5.0.post0-py3-none-any.whl

Tags

More Software Development packages