class_docstr: We support different data types for the extracted value. This tells Lightly how to interpret the value and also allows you to do different things. - Numeric means the extracted values are in a range and have a lower and upper bound. E.g used for color ranges - Categorical means the extracted values are distinct and can be grouped. This allows us to e.g plot distributions of each unique value within your dataset and to map each unique value to a color    - string: most often used for class/category e.g for city, animal or weather condition   - int: e.g for ratings of a meal   - boolean: for true/false distinctions as e.g isVerified or flashOn   - datetime: e.g for grouping by time   - timestamp: e.g for grouping by time - Other means that the extracted value is important to you but does not fit another category. It is displayed alongside other information in the sample detail. E.g the license 
docstr: Create an instance of ConfigurationValueDataType from a JSON string
code: def from_json(cls, json_str: str) -> "ConfigurationValueDataType":
      """Create an instance of ConfigurationValueDataType from a JSON string"""
      return ConfigurationValueDataType(json.loads(json_str))
  
file_path: lightly/lightly/openapi_generated/swagger_client/models/configuration_value_data_type.py
imports: import json
  import pprint
  import re
  from enum import Enum
  from aenum import no_arg
label_desc: Use image node_id 1 for calling the ConfigurationValueDataType obj's underlying member method code with example usage: obj.from_json(cls, json_str) and returns: ConfigurationValueDataType