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Classes

ExampleModule (KiaraModule)

A very simple example module; concatenate two strings.

The purpose of this modules is to show the main elements of a KiaraModule:

  • the (optional) configuration class: must inherit from KiaraModuleConfig, and the config class must be set as the _config_cls attribute on the KiaraModule class. Configuration values can be retrieved via the self.get_config_value(key) method
  • the inputs description: must return a dictionary, containing the input name(s) as keys, and another dictionary containing type_name information and documentation about the input data as value
  • the outputs description: must return a dictionary, containing the output name(s) as keys, and another dictionary containing type_name information and documentation about the output data as value
  • the process method: this is where the actual work gets done. Input data can be accessed via inputs.get_value_data(key), results can be set with the outputs.set_value(key, value) method

Examples:

This example module can be tested on the commandline with the kiara run command:

kiara run core_types.example text_1="xxx" text_2="yyy"
Source code in anom_processing/modules/__init__.py 
class ExampleModule(KiaraModule):
    """A very simple example module; concatenate two strings.

    The purpose of this modules is to show the main elements of a [`KiaraModule`][kiara.modules.KiaraModule]:

    - ***the (optional) configuration class***: must inherit from [`KiaraModuleConfig`][kiara.modules.KiaraModuleConfig], and the config class must be set as the `_config_cls` attribute
         on the `KiaraModule` class. Configuration values can be retrieved via the [`self.get_config_value(key)`][kiara.modules.KiaraModule.get_config_value] method
    - ***the inputs description***: must return a dictionary, containing the input name(s) as keys, and another dictionary containing type_name information
         and documentation about the input data as value
    - ***the outputs description***: must return a dictionary, containing the output name(s) as keys, and another dictionary containing type_name information
         and documentation about the output data as value
    - ***the ``process`` method***: this is where the actual work gets done. Input data can be accessed via ``inputs.get_value_data(key)``, results
         can be set with the ``outputs.set_value(key, value)`` method

    Example:

        This example module can be tested on the commandline with the ``kiara run`` command:

        ```
        kiara run core_types.example text_1="xxx" text_2="yyy"
        ```
    """

    _config_cls = ExampleModuleConfig
    _module_type_name = "anom_processing.example"

    def create_inputs_schema(
        self,
    ) -> ValueMapSchema:

        inputs = {
            "text_1": {"type": "string", "doc": "The first text."},
            "text_2": {"type": "string", "doc": "The second text."},
        }

        return inputs

    def create_outputs_schema(
        self,
    ) -> ValueMapSchema:

        outputs = {
            "text": {
                "type": "string",
                "doc": "The concatenated text.",
            }
        }
        return outputs

    def process(self, inputs: ValueMap, outputs: ValueMap) -> None:

        separator = self.get_config_value("separator")

        text_1 = inputs.get_value_data("text_1")
        text_2 = inputs.get_value_data("text_2")

        result = text_1 + separator + text_2
        outputs.set_value("text", result)

Classes

_config_cls (KiaraModuleConfig) private pydantic-model
Source code in anom_processing/modules/__init__.py 
class ExampleModuleConfig(KiaraModuleConfig):

    separator: str = Field(
        description="The seperator between the two strings.", default=" - "
    )
Attributes
separator: str pydantic-field

The seperator between the two strings.

Methods

create_inputs_schema(self)

Return the schema for this types' inputs.

Source code in anom_processing/modules/__init__.py 
def create_inputs_schema(
    self,
) -> ValueMapSchema:

    inputs = {
        "text_1": {"type": "string", "doc": "The first text."},
        "text_2": {"type": "string", "doc": "The second text."},
    }

    return inputs
create_outputs_schema(self)

Return the schema for this types' outputs.

Source code in anom_processing/modules/__init__.py 
def create_outputs_schema(
    self,
) -> ValueMapSchema:

    outputs = {
        "text": {
            "type": "string",
            "doc": "The concatenated text.",
        }
    }
    return outputs
process(self, inputs, outputs)
Source code in anom_processing/modules/__init__.py 
def process(self, inputs: ValueMap, outputs: ValueMap) -> None:

    separator = self.get_config_value("separator")

    text_1 = inputs.get_value_data("text_1")
    text_2 = inputs.get_value_data("text_2")

    result = text_1 + separator + text_2
    outputs.set_value("text", result)

ExampleModuleConfig (KiaraModuleConfig) pydantic-model

Source code in anom_processing/modules/__init__.py 
class ExampleModuleConfig(KiaraModuleConfig):

    separator: str = Field(
        description="The seperator between the two strings.", default=" - "
    )

Attributes

separator: str pydantic-field

The seperator between the two strings.