class_docstr: Registry for run context provider implementations
  
  This class allows the registration of a run context provider which can be used to infer meta
  information about the context of an MLflow experiment run. Implementations declared though the
  entrypoints `mlflow.run_context_provider` group can be automatically registered through the
  `register_entrypoints` method.
  
  Registered run context providers can return tags that override those implemented in the core
  library, however the order in which plugins are resolved is undefined.
class_docstr_tok: ["Registry","for","run","context","provider","implementations","This","class","allows","the","registration","of","a","run","context","provider","which","can","be","used","to","infer","meta","information","about","the","context","of","an","MLflow","experiment","run",".","Implementations","declared","though","the","entrypoints","`","mlflow.run_context_provider","`","group","can","be","automatically","registered","through","the","`","register_entrypoints","`","method",".","Registered","run","context","providers","can","return","tags","that","override","those","implemented","in","the","core","library",",","however","the","order","in","which","plugins","are","resolved","is","undefined","."]
code: def __init__(self):
      self._registry = []
  
file_path: mlflow/mlflow/tracking/context/registry.py
imports: import logging
  import warnings
  import entrypoints
  from mlflow.tracking.context.databricks_cluster_context import DatabricksClusterRunContext
  from mlflow.tracking.context.databricks_command_context import DatabricksCommandRunContext
  from mlflow.tracking.context.databricks_job_context import DatabricksJobRunContext
  from mlflow.tracking.context.databricks_notebook_context import DatabricksNotebookRunContext
  from mlflow.tracking.context.databricks_repo_context import DatabricksRepoRunContext
  from mlflow.tracking.context.default_context import DefaultRunContext
  from mlflow.tracking.context.git_context import GitRunContext
  from mlflow.tracking.context.system_environment_context import SystemEnvironmentContext
label_desc: Use image node_id 1 to create a new RunContextProviderRegistry object  with example: obj = RunContextProviderRegistry()