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Last pushed: a year ago
Short Description
Docker image for running Python 3 scripts using the Pimoroni Enviro pHAT module for the Raspberry Pi
Full Description

Pimoroni Enviro pHAT Docker Image

Herein lies the Dockerfile needed to build a Docker image suitable for running Python 3 scripts using the Pimoroni Enviro pHAT module for the Raspberry Pi.


This image builds on the jbrisbin/rpi-python3 image. Please make sure your Pi can run I2C before continuing. Instructions are in the README.

Create the Docker Image

Once you're sure that I2C is working on your Pi, build the Docker image using the included Dockerfile.

docker build -t rpi-envirophat .

Run the Docker image

The Docker image assumes you want to mount your executable Python scripts at /data (which is defined as a VOLUME and the WORKDIR) so the CMD has been defined as python3. To run your scripts, add them to the container via volume, along with the /dev directory and add your main script as an argument to the docker run command. In this example, inside the working directory ./data is a script named

from envirophat import weather, light
from subprocess import PIPE, Popen
import sys, time, csv

def get_cpu_temp():
    process = Popen(['vcgencmd', 'measure_temp'], stdout=PIPE)
    output, _error = process.communicate()
    return float(output[5:9])

def read_sensor():
    fields = ['timestamp', 'cpu_temp', 'weather_temp', 'weather_pressure', 'light_r', 'light_g', 'light_b', 'light_level']
    w = csv.DictWriter(sys.stdout, fieldnames=fields)

    lr, lg, lb = light.rgb()
    data = {
        'timestamp': time.time(),
        'cpu_temp': get_cpu_temp(),
        'weather_temp': weather.temperature(),
        'weather_pressure': weather.pressure(),
        'light_r': lr,
        'light_g': lg,
        'light_b': lb,
        'light_level': light.light()

if __name__ == '__main__':

Read the sensor

You can run this script interactively from an SSH session.

docker run --privileged \
    -v $(realpath ./data):/data \
    rpi-envirophat \

Run from crontab

Or, you can run this script periodically by setting up a crontab entry for every minute that invokes the above docker run command and pipes the output to a file somewhere via >>/data/sensor.log.

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