ISR/README.md

ISR — Audio Recorder

AI-generated code. Run at your own risk. MIT licence.

Records from multiple simultaneous sources — Icecast/HTTP streams and ALSA soundcards — with time-based file splitting.

Features

• Multiple sources recorded in parallel (each in its own thread)
• Stream recording — HTTP/Icecast, auto-detects MP3 / OGG / AAC / FLAC / Opus from Content-Type
• Soundcard recording — ALSA (arecord), works on any Linux / Raspberry Pi
• Time-aligned file splits (e.g. every hour, on the hour)
• OGG / Opus / FLAC header injection so every split file is independently playable
• Auto-reconnect on stream drops or device errors
• WAV and FLAC output for soundcard sources
• Web UI to browse, download, and analyse recordings

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Quick start — bare-metal

pip install requests              # stream recording
pip install numpy soundfile       # FLAC output + web waveform analysis (optional)

cp config.example.ini config.ini
# edit config.ini to add your sources
python isr.py                     # start recorder  (Ctrl+C to stop)
python web.py                     # start web UI at http://localhost:8080

Quick start — Docker

cp config.example.ini config.ini
# In config.ini set: output_directory = /recordings
# Optionally set:    log_file = /recordings/recorder.log

docker compose up -d
# recorder starts immediately; web UI at http://<host>:8080
docker compose logs -f            # tail logs from both services
docker compose down               # graceful stop

Recordings land in ./recordings/ on the host (bind-mounted into both containers).

If you only record streams (no soundcard), comment out the devices block in docker-compose.yml.

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Configuration

config.ini uses standard INI format. [general] provides defaults; every other section is a recording source. Source sections inherit all general settings and can override any of them.

[general]

Key	Default	Description
output_directory	recordings	Output path. Use /recordings in Docker.
split_minutes	60	Split into a new file every N minutes, aligned to clock boundaries (e.g. 60 → files start at :00, 30 → at :00 and :30).
filename_pattern	%Y%m%d_%H%M%S	strftime pattern; file extension is appended automatically.
max_retries	10	Give up after this many consecutive failures per source.
retry_delay_seconds	5	Wait between retries.
log_level	INFO	DEBUG / INFO / WARNING / ERROR / CRITICAL
log_file	recorder.log	Log file path. Use /recordings/recorder.log in Docker.

type = stream

[my_stream]
type     = stream
url      = http://icecast.example.com:8000/live
username =          # leave blank for public streams
password =
format   = auto     # auto | mp3 | ogg | aac | flac | opus

format = auto detects from the Content-Type response header. For OGG/Opus/FLAC the first ~16 KB of each connection is buffered to extract codec headers, which are then prepended to every split file — all files are independently playable.

A new file is always opened on (re)connect so gaps between connections are never silently merged.

type = soundcard

[mic_in]
type        = soundcard
device      = default   # see device selection below
sample_rate = 44100
channels    = 2
format      = wav       # wav | flac

Device selection:

Value	Behaviour
default	System default input
monitor	First loopback/monitor source (capture system audio)
<partial name>	Case-insensitive substring match against device name
hw:X,Y	Exact ALSA hardware ID

Run python isr.py --list-devices (or arecord -l) to see available devices and their IDs.

FLAC output requires pip install soundfile numpy.

Multiple sources

Every section except [general] is a source — they all record simultaneously:

[general]
output_directory = recordings
split_minutes    = 60

[radio1]
type             = stream
url              = http://radio.example.com:8000/stream1
filename_pattern = radio1_%Y%m%d_%H%M%S

[system_audio]
type             = soundcard
device           = hw:0,0
filename_pattern = system_%Y%m%d_%H%M%S

---

Filename patterns

strftime codes are substituted at split time. The file extension is added automatically.

Pattern	Example
%Y%m%d_%H%M%S	20241225_143000.mp3
radio_%Y-%m-%d_%H%M	radio_2024-12-25_1430.mp3
%Y/%m/%d/rec_%H%M%S	2024/12/25/rec_143000.mp3 (subdirs created automatically)

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Web UI (web.py)

python web.py                        # serves ./recordings on port 8080
python web.py --dir /path/to/audio   # custom recordings directory
python web.py --port 8888            # custom port
python web.py --threshold 0.03       # loudness threshold 0–1 (default 0.05)

Shows a table of all recordings sorted newest-first with file size, duration (WAV only), and a waveform analysis button. Analysis computes RMS per 100 ms window and highlights contiguous sections above the loudness threshold.

Waveform analysis is WAV-only; numpy speeds it up significantly (pure-Python fallback available without it).

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How it works

Streams: Connect via HTTP → detect format from Content-Type → buffer first ~16 KB to extract OGG/FLAC codec headers → stream raw bytes to disk → at each split boundary open a new file and prepend the saved headers. No transcoding, no decoding — raw bytes in, raw bytes out.

Soundcard: Spawn arecord as a subprocess (raw PCM output) → read 100 ms chunks via a thread → write 16-bit PCM to WAV or FLAC → split at configured boundaries.

Both recorder types run in separate threads and retry independently up to max_retries.

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Docker notes

ALSA device access: The recorder container needs /dev/snd mapped. The container runs as root, so no group configuration is needed — the device mapping alone is sufficient.

If ALSA still fails to find the device inside the container, verify the device exists on the host:

arecord -l           # list capture hardware
ls -la /dev/snd      # check device nodes

Stream-only deployments: If you don't use soundcard recording, remove the devices block from docker-compose.yml — the image works fine without it.

Log file in Docker: Set log_file = /recordings/recorder.log in config.ini so logs survive container restarts. Alternatively, use docker compose logs (the recorder always logs to stdout as well).

File retention: ISR never deletes recordings. Add a cron job on the host if needed:

# Delete recordings older than 30 days
find recordings/ -type f -mtime +30 -delete

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Licence

MIT