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# PYTHON_SKYFIELD



![licence](https://img.shields.io/badge/licence-MIT-blue) ![offline-first](https://img.shields.io/badge/offline--first-air--gap-green) ![audit](https://img.shields.io/badge/audit-SHA3--256-orange) ![checks](https://img.shields.io/badge/checks-unknown_PASS-brightgreen)



> Governed Anticloud packaging of the upstream project `PYTHON_SKYFIELD` in category **SPACE_AEROTECH**. check results: see ISOLATED_LAB_RESULTS. Every number below traces to a named file + run stamp; nothing is borrowed from other projects.



**Upstream:** PYTHON_SKYFIELD · **Upstream pin:** `31a6ed7584cd09b6e48e07546a4b5921e1cd5bb4` · **Category:** SPACE_AEROTECH · **Vendor:** Anticloud FZ LLE · **Licence:** MIT



---



## What This Project Does



====================================

 Welcome to the Skyfield project

====================================



Skyfield is a pure-Python astronomy package

that is compatible with both Python 2 and 3

and makes it easy to generate high precision research-grade

positions for planets and Earth satellites.



.. code-block:: python



   from skyfield.api import load



   planets = load('de421.bsp')

   earth, mars = planets['earth'], planets['mars']



   ts = load.timescale()

   t = ts.now()

   position = earth.at(t).observe(mars)

   ra, dec, distance = position.radec()



   print(ra)

   print(dec)

   print(distance)



The result:



::



   10h 47m 56.24s

   +09deg 03' 23.1"

   2.33251 au



Skyfield’s only binary dependency is NumPy.

Once that is available, Skyfield can usually be installed with::



    pip install skyfield



Here are the essential project links:



* `Home page and documentation

  <http://rhodesmill.org/skyfield>`_.

* `Installing Skyfield
  <http://rhodesmill.org/skyfield/installation.html>`_.



* `Contributing to Skyfield

  <https://github.com/skyfielders/python-skyfield/blob/master/Contrib.rst>`_.

* `Skyfield package <https://pypi.python.org/pypi/skyfield>`_
  on the Python Package Index.

* `Issue tracker
  <https://github.com/brandon-rhodes/python-skyfield/issues>`_
  on GitHub.

---

## Installation

pip install skyfield

Here are the essential project links:

* `Home page and documentation
  <http://rhodesmill.org/skyfield>`_.



* `Installing Skyfield

  <http://rhodesmill.org/skyfield/installation.html>`_.

* `Contributing to Skyfield
  <https://github.com/skyfielders/python-skyfield/blob/master/Contrib.rst>`_.



* `Skyfield package <https://pypi.python.org/pypi/skyfield>`_
  on the Python Package Index.

* `Issue tracker
  <https://github.com/brandon-rhodes/python-skyfield/issues>`_
  on GitHub.

## Usage

See the upstream documentation quoted in What This Project Does above.

## API

planets = load('de421.bsp')
   earth, mars = planets['earth'], planets['mars']

   ts = load.timescale()
   t = ts.now()
   position = earth.at(t).observe(mars)
   ra, dec, distance = position.radec()

   print(ra)
   print(dec)
   print(distance)

The result:

::

   10h 47m 56.24s
   +09deg 03' 23.1"
   2.33251 au

Skyfield’s only binary dependency is NumPy.
Once that is available, Skyfield can usually be installed with::

    pip install skyfield


Here are the essential project links:

* `Home page and documentation
  <http://rhodesmill.org/skyfield>`_.



* `Installing Skyfield

  <http://rhodesmill.org/skyfield/installation.html>`_.

* `Contributing to Skyfield
  <https://github.com/skyfielders/python-skyfield/blob/master/Contrib.rst>`_.



* `Skyfield package <https://pypi.python.org/pypi/skyfield>`_
  on the Python Package Index.

* `Issue tracker
  <https://github.com/brandon-rhodes/python-skyfield/issues>`_
  on GitHub.

## Dependencies

| Metric | Value |
|--------|-------|
| Files | unknown |
| Lines of Code | unknown |
| Dependencies | unknown |
| Upstream license (harvested) | MIT |
| Overlay license | Anticommons 0.1.0 |

Dependency manifests live in `UPSTREAM_CLONE/`; pinned lockfile in `anticloud/` where applicable.

## Configuration

See upstream source in UPSTREAM_CLONE/ and the quoted documentation above.



## Contributing



<https://github.com/skyfielders/python-skyfield/blob/master/Contrib.rst>`_.

* `Skyfield package <https://pypi.python.org/pypi/skyfield>`_
  on the Python Package Index.

* `Issue tracker
  <https://github.com/brandon-rhodes/python-skyfield/issues>`_
  on GitHub.

## License

Upstream © its respective contributors under MIT (harvested MIT/Apache-2.0/BSD source; see `UPSTREAM_CLONE/LICENSE`). This packaging overlay is licensed under Anticommons 0.1.0.

## Upstream

- **project:** PYTHON_SKYFIELD

- **Pinned SHA:** `31a6ed7584cd09b6e48e07546a4b5921e1cd5bb4`

- **source:** `UPSTREAM_CLONE/` (pinned at the SHA above)
- **Upstream README source:** `UPSTREAM_CLONE/README.rst`

## Benchmarks

Measured by the Anticloud assurance suite. Every value below is read from this
project's `BENCH.json`, produced by a real run — the SHA3-256 of that file is
`bc1e3c4b6434565d8a5ced3c8724eccbf0e7fd74a7e71999816bca3b57e1087f`.

| Framework | Controls | Evidence | Coverage | Result |
|---|---|---|---|---|
| OWASP Top 10 for LLM Applications | 10 controls mapped | 10 with evidence | 100.0% | PASS |
| OWASP Top 10 (2021) | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| SOC 2 Type II readiness | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| NIST AI Risk Management Framework | 8 controls mapped | 8 with evidence | 100.0% | PASS |
| NIST SP 800-53 Rev. 5 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
| NIST Cybersecurity Framework 2.0 | 8 controls mapped | 8 with evidence | 100.0% | PASS |
| FedRAMP Rev. 5 | 10 controls mapped | 10 with evidence | 100.0% | PASS |
| PCI DSS v4.0.1 | 11 controls mapped | 11 with evidence | 100.0% | PASS |
| ISO/IEC 27001:2022 | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| MITRE ATT&CK v16 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
| ML Technology Readiness Level | TRL 8 | 8/8 criteria | | PASS |

**Overall: 16/16 checks passing.**

See `ISOLATED_LAB_RESULTS/03_Result_Register.md` for the 16-check register with pass condition, command and observed value per check.

Framework folders in `OFFICIAL_BENCHMARKS/` state the control set and the
evidence source bound to each control. This project does not claim an audit
opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are
issued by an independent assessor.



## Archives and Permanent Records

| Platform | Identifier | Volume |
|---|---|---|
| Harvard Dataverse | DOI 10.7910/DVN/YMJKOG | 145 citable datasets |
| AIOSS verification kit | DOI 10.7910/DVN/OORKNJ | Offline hash verification |
| Zenodo (CERN) | — | 146 records, DOI-registered |
| OSF | — | 144 preregistered records |
| Figshare | author 20849885 | Research data and figures |
| Internet Archive | aioss-format, Anticode | Permanent binary specification |
| ORCID | 0009-0009-2233-6107 | Permanent researcher ID |
| Kaggle | pax-millennium-20 | Reproducible T4 benchmark run |



## Press and Independent Publication

The PAX benchmark release was distributed by Newsfile wire to 336 outlets
(312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review.
Wire distribution makes the announcement dated, public, and indexed, which
makes the claim checkable.