class_docstr: The MLflow Tracking configuration associated with an MLflow Recipe, including the
  Tracking URI and information about the destination Experiment for writing results.
class_docstr_tok: ["The","MLflow","Tracking","configuration","associated","with","an","MLflow","Recipe",",","including","the","Tracking","URI","and","information","about","the","destination","Experiment","for","writing","results","."]
docstr: Obtains a dictionary representation of the MLflow Tracking configuration.
  
  :return: A dictionary representation of the MLflow Tracking configuration.
docstr_tok: ["Obtains","a","dictionary","representation","of","the","MLflow","Tracking","configuration",".",":","return",":","A","dictionary","representation","of","the","MLflow","Tracking","configuration","."]
code: def to_dict(self) -> Dict[str, str]:
      """
      Obtains a dictionary representation of the MLflow Tracking configuration.
  
      :return: A dictionary representation of the MLflow Tracking configuration.
      """
      config_dict = {
          TrackingConfig._KEY_TRACKING_URI: self.tracking_uri,
      }
  
      if self.experiment_name:
          config_dict[
              TrackingConfig._KEY_EXPERIMENT_NAME
          ] = self.experiment_name
  
      elif self.experiment_id:
          config_dict[
              TrackingConfig._KEY_EXPERIMENT_ID
          ] = self.experiment_id
  
      if self.artifact_location:
          config_dict[
              TrackingConfig._KEY_ARTIFACT_LOCATION
          ] = self.artifact_location
  
      if self.run_name:
          config_dict[TrackingConfig._KEY_RUN_NAME] = self.run_name
  
      return config_dict
  
imports: import json
  import logging
  import pathlib
  import shutil
  import tempfile
  import uuid
  from typing import Any, Dict, Optional
  import mlflow
  from mlflow.environment_variables import MLFLOW_RUN_CONTEXT
  from mlflow.exceptions import MlflowException, RestException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.recipes.utils import get_recipe_name
  from mlflow.tracking.client import MlflowClient
  from mlflow.tracking.context.registry import resolve_tags
  from mlflow.tracking.default_experiment import DEFAULT_EXPERIMENT_ID
  from mlflow.tracking.fluent import _get_experiment_id
  from mlflow.tracking.fluent import set_experiment
  from mlflow.utils.databricks_utils import is_in_databricks_runtime
  from mlflow.utils.file_utils import path_to_local_file_uri, path_to_local_sqlite_uri
  from mlflow.utils.git_utils import get_git_branch, get_git_commit, get_git_repo_url
  from mlflow.utils.mlflow_tags import LEGACY_MLFLOW_GIT_REPO_URL, MLFLOW_GIT_BRANCH, MLFLOW_GIT_COMMIT, MLFLOW_GIT_REPO_URL, MLFLOW_SOURCE_NAME
label_desc: Use image node_id 2 for calling the TrackingConfig obj's underlying member method code with example usage: obj.to_dict() and returns: config_dict