Parameters are values which can easily be changed without having to reload the rules. Values will be picked up during runtime as soon as they get edited in the corresponding file. If the file doesn’t exist yet it will automatically be generated in the configured param folder. Parameters are perfect for boundaries (e.g. if value is below param switch something on).

import HABApp

class MyRuleWithParameters(HABApp.Rule):
    def __init__(self):

        # construct parameter once, default_value can be anything
        self.min_value = HABApp.Parameter( 'param_file_testrule', 'min_value', default_value=10)

        # deeper structuring is possible through specifying multiple keys
        self.min_value_nested = HABApp.Parameter(
            'Rule A', 'subkey1', 'subkey2',
            default_value=['a', 'b', 'c'] # defaults can also be dicts or lists

        self.listen_event('test_item', self.on_change_event,

    def on_change_event( event):

        # the parameter can be used like a normal variable, comparison works as expected
        if self.min_value < event.value:

        # The current value can be accessed through the value-property, but don't cache it!
        current_value = self.min_value.value


Created file:

min_value: 10
Rule A:
            - a
            - b
            - c

Changes in the file will be automatically picked up through Parameter.

class HABApp.parameters.Parameter(filename, *keys, default_value='ToDo')
__init__(filename, *keys, default_value='ToDo')

Class to dynamically access parameters which are loaded from file.

  • filename (str) – filename (without extension)

  • keys – structure in the file

  • default_value (Any) – default value for the parameter. Is used to create the file and the structure if it does not exist yet. Use None to skip creation of the file structure.

property value

Return the current value. This will do the lookup so make sure to not cache this value, otherwise the parameter might not work as expected.

Return type



Since parameters used to provide flexible configuration for automation classes they can get quite complex and error prone. Thus it is possible to provide a validator for a file which will check the files for constraints, missing keys etc. when the file is loaded.

HABApp.parameters.set_file_validator(filename, validator, allow_extra_keys=True)

Add a validator for the parameter file. If the file is already loaded this will reload the file.

  • filename (str) – filename which shall be validated (without extension)

  • validator (Any) – Description of file content - see the library voluptuous for examples. Use None to remove validator.

  • allow_extra_keys – Allow additional keys in the file structure


import HABApp
import voluptuous

# Validator can even and should be specified before loading rules

# allows a dict e.g. { 'key1': {'key2': '5}}
HABApp.parameters.set_file_validator('file1', {str: {str: int}})

# More complex example with an optional key:
validator = {
    'Test': int,
    'Key': {
        'mandatory': str,
        voluptuous.Optional('optional'): int
HABApp.parameters.set_file_validator('file1', validator)