python-aaronia

Python bindings for sdr-aaronia-rs. Stream IQ samples from Aaronia SPECTRAN V6 devices, through an RTSA-Suite PRO HTTP server block or the native SDK, or play back recorded .rtsa files, into NumPy or Apache Arrow.

  • PyPI package: python-aaronia · importable module: aaronia
  • Wheels: abi3, CPython ≥ 3.9, one wheel per OS and architecture, plus an sdist for other platforms. Building from the sdist requires a Rust toolchain.
  • License: GPL-3.0-or-later

Install

pip install python-aaronia

From a checkout, which requires Rust and maturin:

cd python-aaronia
maturin develop --release

Check your setup before writing any code:

aaronia-doctor http://localhost:54664

It reports whether the server is reachable, whether the mission has an input carrying IQ, and what rate the device is running, and names the fix for each failure.

Quickstart

import aaronia

with aaronia.open("http://localhost:54664", freq=2.44e9, bandwidth=10e6) as src:
    for block in src.blocks(65536):           # numpy complex64 arrays
        process(block)

aaronia.open() connects and starts streaming in one call. bandwidth asks for that much usable spectrum and picks a sample rate the hardware can actually run; pass rate= instead to name one exactly. Use file="capture.rtsa" in place of the URL to play back a recording.

Iterating with blocks() ends when the stream closes. To read on your own schedule, or for Apache Arrow:

src = aaronia.open(freq=2.44e9, rate=15.36e6, format="I16")
samples = src.read_samples_numpy(65536)       # numpy complex64 array
batch = src.read_samples_arrow(65536)         # pyarrow FixedSizeListArray of [re, im]
src.set_center_frequency(2.41e9)              # live retune, no teardown
print(src.cumulative_drops(), src.take_overrun(), src.last_timestamp_ns())
src.stop_streaming()

For full control, build an AaroniaConfig and pass it to AaroniaSource.start_streaming(); open() is a shorthand for the common fields.

The quickstart covers configuring the RTSA-Suite HTTP Server block, which everything above depends on.

Sample rates

The device runs a fixed ladder of rates: 61.44 MHz halved down to 120 kHz. Ask for anything else and it quietly uses the nearest rung, leaving your program computing against a rate that is not in use.

aaronia.sample_rates()                  # every rate, highest first
aaronia.sample_rate_for_bandwidth(8e6)  # 15.36e6: the lowest rate covering 8 MHz

A rate carries only 80% of itself as alias-free bandwidth, which is why 8 MHz of spectrum needs 15.36 MHz of sampling.

Configuration (AaroniaConfig)

Every field is readable and writable.

Field Meaning
http_base_url RTSA-Suite HTTP server URL; pins the HTTP backend
file_path Path to a recorded .rtsa file; pins the file backend
device_serial Device selection for the native-SDK backend
center_freq Center frequency, Hz
sample_rate IQ sample rate, Hz (the Aaronia "span")
reference_level Reference level, dBm
format HTTP wire format: "F32", "F16" or "I16". I16 is the low-bandwidth network mode
receiver_channel "Rx1" (default), "Rx2", or "Rx1And2" (native SDK, full V6)
read_timeout Seconds a blocking read waits before AaroniaTimeoutError (default 30.0)
auto_reconnect Reconnect the HTTP stream after a drop (default True)

Unknown format/receiver_channel strings raise ValueError instead of silently defaulting.

Behaviour

  • One copy per read. Samples are copied once from the Rust receive buffer into a NumPy or Arrow owned buffer, which is then safe to hold indefinitely. This is not zero-copy; one copy is the accurate count.
  • Blocking calls release the GIL. Other Python threads keep running; KeyboardInterrupt is delivered between calls. Reads block until count samples arrive or cfg.read_timeout seconds (default 30) elapse, which raises AaroniaTimeoutError.
  • Connecting retries transient failures, up to 4 attempts within a 10 second budget, so a cold *.local hostname or a server that is still starting does not fail on the first attempt.
  • Dropped streams reconnect automatically when auto_reconnect is enabled, which is the default. The reader reopens the stream, re-applies the current tuning, and flags the first read after the gap through take_overrun(). After five failed attempts the stream ends and reads raise AaroniaStreamClosed.
  • Typed exceptions. AaroniaConnectionError (unreachable endpoint), AaroniaTimeoutError, AaroniaHardwareError (device and SDK errors) and ValueError (invalid configuration), mapped from the Rust error enum with the full cause chain in the message. AaroniaStreamClosed subclasses AaroniaConnectionError and means the stream finished rather than failed; blocks() ends on it, while a timeout or transport failure still raises.
  • Dual-channel reads (receiver_channel = "Rx1And2" with read_samples_dual_numpy(count), returning two time-aligned arrays) require the native-SDK backend: Windows or Linux with the Aaronia SDK installed, and a two-input V6. This path is hardware-unverified; the development device is a single-channel V6 ECO.

Source methods

Method Purpose
start_streaming(cfg) / stop_streaming() Session lifecycle
with src: ... Stops streaming on the way out, including after an exception
blocks(count) Iterate count-sample arrays until the stream closes
read_samples_numpy(count) NumPy complex64 array
read_samples_arrow(count) PyArrow FixedSizeListArray of [re, im] float32 pairs
read_samples_dual_numpy(count) (rx1, rx2) NumPy arrays (dual-channel captures)
set_center_frequency(hz) / set_sample_rate(hz) / set_reference_level(dbm) Live retuning
cumulative_drops() Total server-reported dropped samples
take_overrun() True once per detected receive-side overrun
last_timestamp_ns() Epoch-ns timestamp of the last received block (HTTP backend; 0 otherwise)

Module functions

Function Purpose
open(url=None, *, freq, rate, bandwidth, ref_level, file, format, read_timeout) Configure, connect and start streaming in one call
sample_rates() Every sample rate the hardware can run
sample_rate_for_bandwidth(hz) Lowest rate covering that much spectrum
diagnose(url) (ok, message, fix) for each setup check; what aaronia-doctor prints

Project links

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  • Released:
Newer release available (0.11.2)

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GitHub Statistics

Data verified by PyPI on Aug 12, 2026
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License

GNU General Public License v3 or later (GPLv3+) (GPL-3.0-or-later)

Requires

Python >=3.9

Classifiers

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