---
id: dargs
version: "0.5.0.post0"
license: GNU LESSER GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/> Everyone is permitted to copy and distribute verbatim copies of this… (full text in the JSON record)
license_treatment: copyleft
maintenance: active
---

# dargs — Process arguments for the deep modeling project.

License: copyleft · Maintenance: active · Downloads: 134.7K/mo

## 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 above — 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

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

- License: GNU LESSER GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/> Everyone is permitted to copy and distribute verbatim copies of this… (full text in the JSON record) (copyleft)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 134.7K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

argument validation python, dict type checking, argument schema definition, input validation framework, argument documentation generator, variant argument handling, parameter validation library, validation, configuration, schema

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