Documentation of exe_kg_lib.classes.tasks package

Overview¶

This package contains classes that correspond to entities of type owl:class that are rdfs:subClassOf AtomicTask in the KG.

They implement the abstract run_method() like so:

1. The input is taken either from outputs of previously executed Tasks (parameter: other_task_output_dict) or a dataframe (parameter: input_data).
2. An algorithm is executed using the input.

There are two conventions: - The algorithm is related to ML, Statistics or Visualization, depending on the Python file's prefix. - The algorithm's implementation is placed in utils.task_utils package in the Python file with the corresponding prefix. 3. The output is returned as a dictionary with pairs of output name and value.

Naming conventions¶

• Each class name is a concatenation of 2 strings:

  1. The name of an owl:class that is rdfs:subClassOf AtomicTask.
  2. The name of an owl:class that is rdfs:subClassOf AtomicMethod and is associated with the above owl:class via a property that is rdfs:subPropertyOf hasMethod.

  For example, the below KG property associates CanvasMethod with CanvasTask. So, the corresponding class name will be CanvasTaskCanvasMethod.

  visu:hasCanvasMethod
      a                  owl:ObjectProperty ;
      rdfs:domain        visu:CanvasTask ;
      rdfs:range         visu:CanvasMethod ;
      rdfs:subPropertyOf ds:hasMethod .
  

• The class fields that contain _ are the snake-case conversions of the equivalent camel-case property names in the KG.

e.g. has_split_ratio field corresponds to hasSplitRatio property in the KG.

The above conventions are necessary for automatically mapping KG tasks with methods and properties to Python objects while parsing the KG.