Installation & Usage

Virtual environment



With openhabian the complete installation can be performed through the openhabian-config tool (option 2B).
HABApp will be installed into /opt/habapp, so it is the same as the installation described here.


On Windows use the python command instead of python3

  1. Navigate to the folder where the virtual environment shall be created (e.g.):

    cd /opt
  2. Create virtual environment (this will create a new folder “habapp”):

    python3 -m venv habapp
  3. Go into folder of virtual environment:

    cd habapp
  4. Activate the virtual environment


    source bin/activate


  5. Upgrade pip and setuptools:

    python3 -m pip install --upgrade pip setuptools
  6. Install HABApp:

    python3 -m pip install habapp
  7. Run HABAp:


    A good configuration folder for HABApp would be your openHAB configuration folder (e.g. /opt/openhab/conf/habapp or /etc/openhab/habapp) because this is where your other configuration folders are located (e.g. the items and sitemaps folder). Just make sure to manually create the folder habapp before the start.


After the installation take a look how to configure HABApp. A default configuration will be created on the first start.


  1. Stop HABApp

  2. Activate the virtual environment

    Navigate to the folder where HABApp is installed:

    cd /opt/habapp

    Activate the virtual environment


    source bin/activate


  3. Run the following command in your activated virtual environment:

    python3 -m pip install --upgrade habapp
  4. Start HABApp

  5. Observe the logs for errors in case there were changes

Autostart after reboot

Check where habapp is installed:

which habapp

To automatically start HABApp from the virtual environment after a reboot call:

nano /etc/systemd/system/habapp.service

and copy paste the following contents. If the user which is running openHAB is not “openhab” replace accordingly. If your installation is not done in “/opt/habapp/bin” replace accordingly as well:


ExecStart=/opt/habapp/bin/habapp -c PATH_TO_CONFIGURATION_FOLDER


Press Ctrl + x to save.

Now execute the following commands to enable autostart:

sudo systemctl --system daemon-reload
sudo systemctl enable habapp.service

It is now possible to start, stop, restart and check the status of HABApp with:

sudo systemctl start habapp.service
sudo systemctl stop habapp.service
sudo systemctl restart habapp.service
sudo systemctl status habapp.service

Error message while installing ujson

Under windows the installation of ujson may throw the following error but the download link is not working. Several working alternatives can be found here.

Running install for ujson ... error
  ERROR: Complete output from command 'C:\Users\User\Desktop\HABapp\habapp\Scripts\python.exe' -u -c 'import setuptools, tokenize;__file__='"'"'C:\\Users\\User\\AppData\\Local\\Temp\\pip-install-4y0tobjp\\ujson\\'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);'"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record 'C:\Users\User\AppData\Local\Temp\pip-record-6t2yo712\install-record.txt' --single-version-externally-managed --compile --install-headers 'C:\Users\User\Desktop\HABapp\habapp\include\site\python3.7\ujson':
  ERROR: Warning: 'classifiers' should be a list, got type 'filter'
  running install
  running build
  running build_ext
  building 'ujson' extension
  error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools":

Error message while installing ruamel.yaml

_ruamel_yaml.c:4:10: fatal error: Python.h: No such file or directory

Run the follwing command to fix it:

sudo apt install python3-dev


Image installation

Installation through docker is available:

docker pull spacemanspiff2007/habapp:latest

The image supports the following environment variables.




Timezone used for the container (e.g. Europe/Berlin).


User id at which HABApp will run (Optional, default: 9001)


Group id at which HABApp will run (Optional, default: USER_ID)

Running image from command line

docker run --rm -it --name habapp \
    -v ${PWD}/habapp_config:/habapp/config \
    -e TZ=Europe/Berlin \
    -e USER_ID=9001 \
    -e GROUP_ID=9001 \

Parameters explained




Remove container when stopped


Run in interactive mode (Optional) -> You can stop HABApp by pressing STRG+C and see stdout

--name habapp

Give the container an unique name to interact with it

-e TZ=Europe/Berlin

Set environment variable with timezone

-e USER_ID=9001

Set environment variable with wser id at which HABApp will run (Optional, default: 9001)

-e GROUP_ID=9001

Set environment variable with group id at which HABApp will run (Optional, default: USER_ID)


Name of the image that will be run

Updating image from command line

docker stop habapp

docker pull spacemanspiff2007/habapp:latest

Updating image on Synology

To update your HABApp docker within Synology NAS, you just have to do the following:

On the Synology NAS just select “Download” with tag “latest” to download the new image. It will overwrite the old one on the NAS. Then stop the container. After selecting “Action” -> “Clear” on the HABapp container, the container is there, but without any content. After starting the container again, everything should immediately work again.

Additional python libraries

If you want to use some additional python libraries you can do this by writing your own Dockerfile using this image as base image. The HABApp image is based on the python-slim image so you can install packages by using apt and pip.

Example Dockerfile installing scipy, pandas and numpy libraries:

FROM spacemanspiff2007/habapp:latest as buildimage

RUN set -eux; \
# Install required build dependencies (Optional)
    apt-get update; \
    DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y \
        build-essentials; \
# Prepare python packages
    pip3 wheel \
        --wheel-dir=/root/wheels \
        # Replace 'scipy pandas numpy' with your libraries
        scipy pandas numpy

FROM spacemanspiff2007/habapp:latest

COPY --from=buildimage /root/wheels /root/wheels

RUN set -eux; \
# Install required runtime dependencies (Optional)
    apt-get update; \
    DEBIAN_FRONTEND=noninteractive apt-get install --no-install-recommends -y \
        bash; \
    apt-get clean; \
    rm -rf /var/lib/apt/lists/*; \
# Install python packages and cleanup
    pip3 install \
        --no-index \
        --find-links=/root/wheels \
        # Replace 'scipy pandas numpy' with your libraries
        scipy pandas numpy; \
    rm -rf /root/wheels

Build image

docker build -t my_habapp_extended:latest .

Start image (same as with provided image but the image name is different).

docker run --rm -it --name habapp \
    -v ${PWD}/habapp_config:/habapp/config \
    -e TZ=Europe/Berlin \
    -e USER_ID=9001 \
    -e GROUP_ID=9001 \

Upgrading to a newer version of HABApp

It is recommended to upgrade the installation on another machine. Configure your production instance in the configuration and set the listen_only switch(es) in the configuration to True. Observe the logs for any errors. This way if there were any breaking changes rules can easily be fixed before problems occur on the running installation.

Command line arguments

Execute habapp with “-h” to view possible command line arguments

habapp -h
usage: -c [-h] [-c CONFIG] [-wos WAIT_OS_UPTIME] [-b] [-di]

Start HABApp

optional arguments:
  -h, --help            show this help message and exit
  -c CONFIG, --config CONFIG
                        Path to configuration folder (where the config.yml is
  -wos WAIT_OS_UPTIME, --wait_os_uptime WAIT_OS_UPTIME
                        Waits for the specified os uptime before starting
  -b, --benchmark       Do a Benchmark based on the current config
  -di, --debug-info     Print debug information


It’s recommended to use PyCharm as an IDE for writing rules. The IDE can provide auto complete and static checks which will help write error free rules and vastly speed up development.

Type hints and checks

To enable type hints and checks HABApp needs to be installed in the python environment that is currently used by PyCharm. Ensure that the HABApp version for PyCharm matches the HABApp version that is currently deployed and running the rules. It is recommended to create a new virtual environment when creating a new project for HABApp.

Go to Settings and view the current python environment settings.


Install the HABApp package through the + symbol. Once the installation was successful PyCharm will provide checks and hints.


Start HABApp from PyCharm

It is possible to start HABApp directly from pycharm e.g. to debug things. Open the run configurations.


Switch to Module name execution with the small dropdown arrow. It’s still necessary to supply a configuration file which can be done in the Parameters line.

After a click on “OK” HABApp can be run/debugged directly from pycharm.
It’s even possible to create breakpoints in rules and inspect all objects.