asdf-astropy
ASDF serialization support for astropy
Decision gist · record as of 2026-08-14
Yes, if you work with astropy and need to serialize its objects to ASDF format. The package is actively maintained, has low install friction, carries no known vulnerabilities, and is widely used. Install it when you require ASDF support for astropy; otherwise it is not necessary. Note: license classification is unclear in the metadata despite the description citing BSD 3-Clause—verify the actual license before use in proprietary contexts.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.11
- Low install friction with a pure-wheel distribution.
- Actively maintained with last commit on 2026-08-03.
License · maintenance · safety
(unclear)
last release 2026-03-27 (140 days) · last repo commit 2026-08-03 · 19 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 245,889 downloads/mo, #8,719 on PyPI
Alternatives
Verify before relying
pip install asdf-astropy
import asdf
import astropy.coordinates
# Plugins are automatically enabled; use astropy and asdf normally
with asdf.open('data.asdf') as af:
coord = af['coordinate']- License classification marked unclear in metadata despite description mentioning BSD 3-Clause; verify actual license terms before deployment.
- Whether these plugins fully replace the deprecated astropy.io.misc.asdf module for all use cases.
- Actual adoption and stability of the plugin system in production environments.
What it is and what it does
asdf-astropy is a plugin package that extends the ASDF serialization framework to handle astropy objects. When installed, it automatically registers handlers that allow astropy data structures to be saved and loaded in ASDF format. The package supersedes the built-in astropy.io.misc.asdf module, which is deprecated.
The package depends on astropy, numpy, and the broader ASDF ecosystem (asdf, asdf-coordinates-schemas, asdf-transform-schemas, asdf-standard) to function. It requires Python >=3.11. Installation is straightforward via pip with no compiled dependencies, making it suitable for environments where you need to persist or exchange astropy objects in a standardized binary format.
Use it for
- Save and load astropy objects in ASDF format for reproducible scientific workflows.
- Exchange astronomical data between Python and other tools that support ASDF without lossy conversion.
- Archive astropy datasets in a compact, schema-validated binary format that preserves metadata.
- Integrate astropy objects into ASDF-based data pipelines in observatories or research institutions.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with astropy and need to serialize its objects to ASDF format.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and is widely used. Install it when you require ASDF support for astropy; otherwise it is not necessary. Note: license classification is unclear in the metadata despite the description citing BSD 3-Clause—verify the actual license before use in proprietary contexts.
Install
asdf-astropy on PyPI
Before you install
Low install friction with a pure-wheel distribution. Actively maintained with last commit on 2026-08-03. Depends on seven runtime packages including astropy, numpy, and asdf ecosystem libraries.
Requires Python >=3.11
Quickstart
pip install asdf-astropy
import asdf
import astropy.coordinates
# Plugins are automatically enabled; use astropy and asdf normally
with asdf.open('data.asdf') as af:
coord = af['coordinate']
Verify before relying
- License classification marked unclear in metadata despite description mentioning BSD 3-Clause; verify actual license terms before deployment.
- Whether these plugins fully replace the deprecated astropy.io.misc.asdf module for all use cases.
- Actual adoption and stability of the plugin system in production environments.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesasdfasdf-coordinates-schemasasdf-transform-schemasasdf-standardastropynumpypackaging |
| Maintenance | Actively maintained 140 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 245,889 / month, #8,719 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableProgramming Language :: PythonProgramming Language :: Python :: 3 |
Evidence: asdf_astropy-0.11.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “astropy asdf serialization”
- asdf-astropyProvides ASDF serialization plugins for astropy objects, enabling…
- asdf-wcs-schemasProvides ASDF schemas for validating World Coordinate System (WCS)…
- specutilsSpecutils provides Python representations of astronomical spectra and…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also asdf · astropy-iers-data · asdf-coordinates-schemas · asdf-transform-schemas · astroquery · astropy-healpix · asdf-standard · specutils · pyvo · PyAVM