code: def extract_db_type_from_uri(db_uri):
      """
      Parse the specified DB URI to extract the database type. Confirm the database type is
      supported. If a driver is specified, confirm it passes a plausible regex.
      """
      scheme = urllib.parse.urlparse(db_uri).scheme
      scheme_plus_count = scheme.count("+")
  
      if scheme_plus_count == 0:
          db_type = scheme
      elif scheme_plus_count == 1:
          db_type, _ = scheme.split("+")
      else:
          error_msg = (
              f"Invalid database URI: '{db_uri}'. {_INVALID_DB_URI_MSG}"
          )
          raise MlflowException(error_msg, INVALID_PARAMETER_VALUE)
  
      _validate_db_type_string(db_type)
  
      return db_type
  
imports: import os
  import pathlib
  import posixpath
  import re
  import urllib.parse
  import uuid
  from typing import Any, Tuple
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.store.db.db_types import DATABASE_ENGINES
  from mlflow.utils.os import is_windows
  from mlflow.utils.validation import _validate_db_type_string
label_desc: Use image node_id 13 for calling a global function with example usage: extract_db_type_from_uri(db_uri) and returns: db_type