Headless SNAP gpt,
installed by conda.
A repackaging of the official ESA SNAP installers that puts the
Graph Processing Tool and the Sentinel-1 / SAR stack into a conda package —
for reproducible command-line, server, CI, notebook, and pyroSAR workflows.
No GUI installer, no Docker, no snappy/jpy.
One conda command
The package version equals the SNAP version — pick the release you need.
mamba create -n snap13 -c sarforge -c conda-forge esa-snap-s1tbx-gpt=13.0.0
conda activate snap13
gpt -h
conda works too; mamba just solves large environments faster.
The full SAR stack, nothing optical
All SAR sensors (Sentinel-1, TerraSAR-X, ALOS, RADARSAT, ICEYE, …), calibration, SAR processing, InSAR, polarimetry, classification.
Sentinel-2/3 (s2tbx/s3tbx) and
smostbx removed to keep the package lean.
Linux/macOS use conda-forge openjdk; Windows keeps SNAP's
bundled runtime. No separate Java install, no jpy bridge.
The standard SNAP layout is preserved and the real snap/gpt
launchers sit on PATH, so ExamineSnap() auto-detects it.
Trusted matrix on sarforge
A storage-conscious set of platforms per SNAP version.
| SNAP | linux-64 | win-64 | osx-arm64 |
|---|---|---|---|
| 9.0.0 | ● | — | — |
| 10.0.0 | ● | — | — |
| 11.0.0 | ● | — | — |
| 12.0.0 | ● | — | — |
| 13.0.0 | ● | ● | ● |
Zero-config discovery
pyroSAR finds SNAP by locating the snap launcher on PATH — which this package puts there.
from pyroSAR.examine import ExamineSnap
snap = ExamineSnap()
print(snap.gpt) # resolves inside the conda env
For InSAR phase unwrapping, add snaphu: mamba install -c conda-forge snaphu.