dummysensors 0.3.2

Dummy sensor data generator for testing IoT/ML pipelines

dummysensors

A lightweight generator of dummy sensor data for IoT and ML testing. Provides a simple Python API and CLI, supports running multiple sensors in parallel, photovoltaic domain sensors, and splitting output streams into files.

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Installation

From PyPI (recommended):

pip install dummysensors

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Quick Start (API)

from dummysensors import TemperatureSensor, VibrationSensor

# create sensors
temp = TemperatureSensor(min_val=18, max_val=24, noise=0.2)
vib  = VibrationSensor(base_hz=50.0, amp=1.0, noise=0.05)

print(temp.read())            # e.g. 21.3
print(vib.read(t_s=0.123))    # sinusoidal signal with noise

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Config file (YAML)

Instead of passing long --spec strings, you can define your setup in a YAML file. By default, dummy-sensors run --config config.sensors.yaml will look for a file named config.sensors.yaml in the current directory.

Example config.sensors.yaml

rate: 2
count: 5
partition_by: type

outputs:
  - type: jsonl
    for: temp
    path: out/temp.jsonl
  - type: csv
    for: vibration
    path: out/vibration.csv

devices:
  - id: engine-A
    sensors:
      - kind: temp
        count: 1
      - kind: vibration
        count: 1
  - id: plant-1
    sensors:
      - kind: irradiance
        count: 1
        params: {peak: 900.0, day_period_s: 10.0, sunrise: 0.0, sunset: 10.0}
      - kind: pv_power
        count: 1
        params: {stc_kw: 5.0, inverter_eff: 0.95, p_kw_max: 4.8}
      - kind: load
        count: 1
        params: {base_kw: 0.3, morning_kw: 0.8, evening_kw: 1.2}
      - kind: soc
        count: 1
        params: {capacity_kwh: 10.0, soc0: 50.0}

Run with:

dummy-sensors run --config config.sensors.yaml

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Quick Start (CLI)

Generate a single temperature stream to JSONL:

dummy-sensors generate --rate 5 --duration 2 --jsonl out/temp.jsonl

Run multiple sensors and devices, split by type into separate files:

dummy-sensors run \
  --rate 5 \
  --count 30 \
  --spec "device=engine-A: temp*1,vibration*2; device=room-101: temp*2" \
  --out "temp=out/temp.jsonl" \
  --out "vibration=out/vib.jsonl" \
  --out "*=stdout"

👉 Check out a full demo with live plotting and JSONL logging here: dummysensors demo (ds-test)

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--spec format

The --spec string describes devices and sensors:

device=<ID>: <type>*<count>[, <type>*<count> ...] ; device=<ID2>: ...

Examples:

• device=A: temp*3 — device A with three temperature sensors
• device=eng: temp*1,vibration*2; device=room: temp*2

As of v0.3, supported sensor types: temp, vibration, irradiance, pv_power, load, soc. You can define setups either with --spec (quick inline config) or using a YAML file (--config config.sensors.yaml) for more complex scenarios.

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Python API

TemperatureSensor

• Parameters: min_val=15.0, max_val=30.0, noise=0.5, period_s=86400
• Methods: read(t_s: float | None = None) -> float

VibrationSensor

• Parameters: base_hz=50.0, amp=1.0, noise=0.1, spike_prob=0.0
• Methods: read(t_s: float | None = None) -> float

IrradianceSensor

• Simulates solar irradiance with day/night cycle.
• Parameters: peak, day_period_s, sunrise, sunset

PVPowerSensor

• Converts irradiance into PV output.
• Parameters: stc_kw, inverter_eff, p_kw_max

LoadSensor

• Simulates household/plant consumption profile.
• Parameters: base_kw, morning_kw, evening_kw, day_period_s

BatterySoCSensor

• Integrates charge/discharge depending on PV vs load.
• Parameters: capacity_kwh, soc0

Sensor Registry

• dummysensors.registry.SENSOR_REGISTRY — maps string kind → class
• dummysensors.registry.make_sensor(kind: str, **params)

Orchestrator

• dummysensors.orchestrator.run_stream(...)

  • Creates instances based on spec_str or config, respects priority and per-sensor rate_hz.
  • writer_for_type is a dict type → callable(sample_dict). * = default writer.

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Output Format

JSON Lines (one record per line):

{
  "ts_ms": 171234,
  "device_id": "engine-A",
  "sensor_id": "vibration-1",
  "type": "vibration",
  "value": -0.124
}

Also supported: CSV. Planned: Kafka, Redis Stream, WebSocket.

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Roadmap

• v0.2 ✅ — CSV writer, partitioning, YAML config
• v0.3 ✅ — Smart photovoltaic sensors (irradiance, pv_power, load, soc), per-sensor rate_hz, priority-based orchestration
• v0.4 🚧 — AnomalyInjector (spike, dropout, drift), new sensors (humidity, rpm, battery_voltage, gps, accel-3axis)
• v0.5 🚧 — Outputs: Kafka, Redis Stream, WebSocket live preview

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Development

git clone https://github.com/SculptTechProject/dummysensors
cd dummysensors
pip install -e .
pip install -r requirements.txt

• Project layout: src-layout
• Tests: pytest -q
• Lint/format: ruff check src tests and ruff format

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License

MIT © Mateusz Dalke