astronereus
Python frontend for Nereus — trans-dimensional Bayesian inference for exoplanet orbits.
You do not need Julia. Nereus itself is Julia, but this package fetches a prebuilt runtime on first use and runs it out-of-process in a warm daemon. Nothing is compiled at install time.
pip install astronereus
That is the whole install. The first time you actually ask for a fit, the runtime (~480 MB) is fetched and warmed once, and you are told it is happening:
astronereus: no Julia runtime yet -- fetching it once now.
astronereus: fetching runtime (macos-arm64, julia 1.11.9) ...
astronereus: unpacking ...
astronereus: warming the runtime (one-time, a few minutes) ...
astronereus: ready (207s)
pip cannot do that step itself -- wheels have no post-install hook -- so it
happens on first use instead. To get it over with ahead of a workshop or a
flight, run it deliberately:
python -c "import astronereus; astronereus.install()"
NEREUS_NO_AUTO_INSTALL=1 turns the automatic fetch off and makes the first
call fail with instructions instead, for CI and air-gapped machines.
The distribution and the import are both astronereus. The name nereus on
PyPI belongs to an unrelated geophysics package, and a distribution whose import
name differs from its install name is a thing every user has to be told, so they
are deliberately the same string here.
Use
import astronereus
summary = astronereus.run_job(cfg) # one-shot
with astronereus.session() as s: # or reuse one warm daemon
a = s.run_job(cfg_a)
pg = s.detect.rv_periodogram(t=t, rv=rv, rv_err=err)
Typed entry points per observable — fit_rv, fit_transit, fit_astrometry,
fit_rm, fit_tomography, fit_ttv, fit_binary, fit_joint — take channel
objects (RV, Transit, Astrometry, RM, Night, TTV, SB2) and return
a JobResult.
The first install() unpacks the runtime and warms it once (a few minutes);
every process after that starts in about twenty seconds. NEREUS_BUNDLE_URL
points the installer at a local file or file:// URL — that is the intended
path for a workshop room, where thirty people pulling half a gigabyte over
conference wifi is not a plan.
Runtime bundles
Prebuilt runtimes are attached to the
Nereus.jl releases, with
SHA256SUMS alongside:
| platform | size |
|---|---|
macos-arm64 |
465 MiB |
linux-x86_64 |
688 MiB |
linux-aarch64 |
649 MiB |
install() picks the one for your platform and verifies it against the
published checksum. For a classroom, fetch it once and point everyone at the
local copy instead:
export NEREUS_BUNDLE_URL=/Volumes/NEREUS/nereus-runtime-1.11.9-macos-arm64.tar.zst
NEREUS_HOME relocates the runtime cache out of the default platform cache
directory.
Licence
MIT — see LICENSE.
1 maintainer
Release files for astronereus 0.4.23
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| astronereus-0.4.23.tar.gz | 76.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| astronereus-0.4.23-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 153.7 kB
Release files / astronereus-0.4.23.tar.gz
| Download URL | astronereus-0.4.23.tar.gz |
|---|---|
| Size | 76.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
46486499ecc1c6d427a6342281b4269505888635a8ac4fdd533be9f2c4e5fd6f
|
|
BLAKE2b-256 checksum How to use checksums |
a8a84fdbd3b47a3c21baf47048edde3d25ff52992dccf9a80a1f78396a0baaf6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
Release files / astronereus-0.4.23-py3-none-any.whl
| Download URL | astronereus-0.4.23-py3-none-any.whl |
|---|---|
| Size | 77.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ff05de2e99a3145d08b0ffd190904c9f2d9f03f0742baab5be99823b3fa2ae5c
|
|
BLAKE2b-256 checksum How to use checksums |
4033930b18bca56c908e2ea989862a083c0a215636127157c724ba1bc9217fd8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.5
|
