class_docstr: Represents the source of a dataset used in MLflow Tracking, providing information such as
  cloud storage location, delta table name / version, etc.
class_docstr_tok: ["Represents","the","source","of","a","dataset","used","in","MLflow","Tracking",",","providing","information","such","as","cloud","storage","location",",","delta","table","name","\/","version",",","etc","."]
docstr: Obtains a JSON string representation of the
  :py:class:`DatasetSource <mlflow.data.dataset_source.DatasetSource>`.
  
  Returns:
      A JSON string representation of the
      :py:class:`DatasetSource <mlflow.data.dataset_source.DatasetSource>`.
docstr_tok: ["Obtains","a","JSON","string","representation","of","the",":","py",":","class",":","`","DatasetSource","<","mlflow.data.dataset_source.DatasetSource",">","`",".","Returns",":","A","JSON","string","representation","of","the",":","py",":","class",":","`","DatasetSource","<","mlflow.data.dataset_source.DatasetSource",">","`","."]
code: def to_json(self) -> str:
      """
      Obtains a JSON string representation of the
      :py:class:`DatasetSource <mlflow.data.dataset_source.DatasetSource>`.
  
      Returns:
          A JSON string representation of the
          :py:class:`DatasetSource <mlflow.data.dataset_source.DatasetSource>`.
      """
      return json.dumps(self._to_dict())
  
file_path: mlflow/mlflow/data/dataset_source.py
imports: import json
  from abc import abstractmethod
  from typing import Any, Dict
  from mlflow.utils.annotations import experimental
label_desc: Use image node_id 6 for calling the DatasetSource obj's underlying member method code with example usage: obj.to_json() and returns: json