# NaiboWang/CommandlineConfig

A library for users to write (experiment in research) configurations in Python Dict or JSON format, read and write parameter value via dot . in code, while can read parameters from the command line to modify values. 一个供用户以Python Dict或JSON格式编写（科研中实验）配置的库，在代码中用点.读写属性，同时可以从命令行中读取参数配置并修改参数值。

Repository: https://github.com/NaiboWang/CommandlineConfig
Canonical: https://ross.abutalabs.com/products/commandlineconfig
Language: Python
License: MIT
License Family: permissive
Topics: command-line, commandline, config, python, configuration, argument-parser, parameters, arguments, pip, pypi, atom, codescene, collaborate, ghdesktop, github, github-pages, jetbrains, mongodb, student-vscode, termius
Last push: 2024-08-22T15:28:52+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1445, "days_push": 741, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1510, forks 168 (observed 2026-08-28T04:04:55.810781+00:00)

## What it is
A Python library that lets users define experiment configurations as Python dicts or JSON and access parameters via dot notation, while allowing command-line overrides with --flags. It is aimed at research experiment parameter management.

## Use cases
- manage experiment hyperparameters in python research scripts
- override config values from the command line
- access nested config parameters with dot notation
- load configuration from a json file
- print parameter help via -h

## When to choose
- you want dict/json-based config with attribute-style access in python
- you need simple command-line overrides for research experiments
- you want nested parameter support without heavy frameworks

## When to avoid
- you need a full-featured config system like hydra or pydantic-settings
- you need yaml/toml config files
- you need environment-variable-based configuration

## Facets
- artifact type: library
- maturity: active
- function: configuration-management, cli, developer-tools
- domain: developer-tools, machine-learning
- platform: python, cli, cross-platform
- tags: argument-parser, dot-notation, experiment-config, research, json-config, command-line

## Member repositories
- NaiboWang/CommandlineConfig (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:55.810781+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:32:24.638638+00:00, confidence not recorded.
  - readme: https://github.com/NaiboWang/CommandlineConfig (fetched 2026-08-28T04:04:55.810781+00:00, sha 5faf48b5bdf9)
- Data as of 2026-08-30T08:39:29.467469+00:00.