prefigure
Run configuration management utils: combines configparser, argparse, and wandb.API
Decision gist · record as of 2026-08-14
Yes-with-conditions. The package solves a real problem for PyTorch Lightning + WandB workflows and has low install friction, but it is abandoned (last release June 2023, no commits since). Install only if you can tolerate potential incompatibilities with newer versions of pytorch-lightning, wandb, or gradio, and if you are comfortable maintaining a fork if needed. Not suitable for production systems requiring active maintenance.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires pytorch-lightning and wandb to be installed; WandB account and project setup needed for config archiving and retrieval.
- Low install friction with a pure-Python wheel, but the package is abandoned—last release was 2023-06-28 with no commits since.
- Six runtime dependencies including pytorch-lightning and wandb add moderate weight; maintenance risk is high.
License · maintenance · safety
MIT (permissive) — MIT license is permissive and imposes no restrictions on use, modification, or distribution in your own projects.
last release 2023-06-28 (1143 days) · last repo commit 2023-06-28 · 6 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 126,289 downloads/mo, #11,781 on PyPI
Alternatives
Verify before relying
pip install prefigure
from prefigure import get_all_args, push_wandb_config
args = get_all_args()
push_wandb_config(wandb_logger, args)- Whether the package works with current versions of pytorch-lightning and wandb given its 2023 last release date.
- Whether the Gradio GUI (OFC feature) works with current Gradio versions.
- Compatibility with Python versions beyond 3.10 given the classifier list.
What it is and what it does
Prefigure streamlines experiment configuration for PyTorch Lightning workflows by unifying three sources of settings: defaults from an INI/JSON/Gin file, previous run configs pulled from Weights & Biases, and command-line overrides. It reduces boilerplate to three lines of code (import, get_all_args(), push_wandb_config()) and archives run settings to WandB for reproducibility and easy recovery of past configurations.
The package also includes an optional On-the-Fly Control (OFC) feature that lets you steer hyperparameters during training via a Gradio GUI or by editing a file, with optional logging of changes back to WandB. It supports multiple config formats and can import nested config files as dictionaries. However, the project has been abandoned since mid-2023 and carries maintenance risk.
Use it for
- Archive and retrieve experiment configurations from past WandB runs to reproduce or iterate on previous training setups.
- Manage hyperparameters across multiple config sources (file, WandB, CLI) with a clear precedence order and minimal code changes.
- Steer learning rate, batch size, or other float/int parameters during training via a Gradio interface without stopping the run.
- Consolidate argparse and configparser logic into a single declarative defaults.ini file for cleaner training scripts.
- Share experiment configs across team members by pulling them from WandB URLs instead of passing files manually.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes-with-conditions.
The package solves a real problem for PyTorch Lightning + WandB workflows and has low install friction, but it is abandoned (last release June 2023, no commits since). Install only if you can tolerate potential incompatibilities with newer versions of pytorch-lightning, wandb, or gradio, and if you are comfortable maintaining a fork if needed. Not suitable for production systems requiring active maintenance.
Install
prefigure on PyPI
Before you install
Low install friction with a pure-Python wheel, but the package is abandoned—last release was 2023-06-28 with no commits since. Six runtime dependencies including pytorch-lightning and wandb add moderate weight; maintenance risk is high.
Requires pytorch-lightning and wandb to be installed; WandB account and project setup needed for config archiving and retrieval.
License in practice
MIT license is permissive and imposes no restrictions on use, modification, or distribution in your own projects.
Quickstart
pip install prefigure
from prefigure import get_all_args, push_wandb_config
args = get_all_args()
push_wandb_config(wandb_logger, args)Verify before relying
- Whether the package works with current versions of pytorch-lightning and wandb given its 2023 last release date.
- Whether the Gradio GUI (OFC feature) works with current Gradio versions.
- Compatibility with Python versions beyond 3.10 given the classifier list.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesargparseconfigparsergin-configgradiopytorch-lightningwandb |
| Maintenance | Abandoned 1,143 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 126,289 / month, #11,781 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 1 - PlanningIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: prefigure-0.0.10-py3-none-any.whl
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