GramPy
GramPy is an importable Python library and command-line tooling for decoding MFSK32 and MFSK64 transmissions from SigMF IQ recordings. It is maintained as a standalone project after its extraction from Radiogram.
The PyPI distribution name is radiogrampy; its Python import name is
grampy.
Python 3.11 or newer is required.
Use as a library
The supported Python interface is grampy.api. Decode a SigMF metadata/data
pair by passing pathlib.Path objects to decode_iq:
from pathlib import Path
from grampy.api import DecodeConfig, decode_iq
manifest = decode_iq(
meta_path=Path("recording.sigmf-meta"),
data_path=Path("recording.sigmf-data"),
config=DecodeConfig(mode="MFSK64"),
artifact_dir=Path("results/decode.artifacts"),
artifact_path_prefix="decode.artifacts",
)
print(manifest["status"])
print(manifest["text_summary"]["text"])
decode_iq returns a validated, JSON-compatible decode manifest; it does not
write that manifest to disk. The optional artifact arguments control where
large decoded-picture artifacts are written. See the Python API guide
for the supported arguments, configuration, result contract, errors, and
artifact behavior. The manifest schema
is the machine-readable format reference.
Setup
Create a virtual environment and install GramPy with its runtime dependencies:
python3 -m venv .venv
.venv/bin/python -m pip install --editable . pillow
Pillow is used by the image-related test suite. The repository uses a src/
layout, so run Python work with both the virtual environment and source tree
selected:
PYTHONPATH="$PWD/src" PATH="$PWD/.venv/bin:$PATH" \
.venv/bin/python -m unittest discover -s tests
For full-suite runs, experiments, corpus jobs, or other potentially long work,
follow the managed-execution contract in AGENTS.md. The normal Mac
entry point is tools/mac-local.sh; place a temporary command batch in the
ignored .local/mac-command.sh when needed.
Tests and corpus
The normal regression suite runs without large external artifacts. Tests that need received IQ or controlled generated fixtures skip cleanly when those optional inputs are absent.
See tests/README.md to install an optional received-IQ corpus, point tests at an existing corpus, or package one for controlled distribution. Large samples are never committed to this repository.
Decode a SigMF recording
GramPy includes a command-line adapter for reproducible decoder work on a SigMF metadata/data pair:
tools/mfsk-iq-decode \
--in-meta recording.sigmf-meta \
--in-data recording.sigmf-data \
--out-manifest results/decode.json
The default automatic mode decodes every resolved MFSK32 and MFSK64 segment
and the pictures carried by MFSK64 segments in one run. The command writes a
manifest containing the decoded text, diagnostics, and artifact inventory.
Large decoded pictures are written beside it in
results/decode.artifacts/; small rasters are embedded in the manifest. See
the SigMF decode guide for the accepted metadata, input
formats, interval options, and complete output layout.
Development
Use docs/operations/change-management-v1.md for continuous-improvement work. It defines the request, baseline, candidate, evaluation, acceptance, and closeout cycle. Decoder architecture, contracts, validation guidance, and the accepted baseline are indexed in docs/decoder/README.md.
Reusable command-line tools are documented in tools/README.md.
Release files for radiogrampy 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| radiogrampy-0.1.2.tar.gz | 166.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| radiogrampy-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 299.1 kB
Release files / radiogrampy-0.1.2.tar.gz
| Download URL | radiogrampy-0.1.2.tar.gz |
|---|---|
| Size | 166.6 kB |
| Tags | Source |
|
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| Uploaded via |
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|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 21, 2026.
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