code: def upload_and_update(path, token, cleanup):
      
      config = _load_config(CFG_FILE)
      token = _resolve_input(token, 'token', 'token', config)
      folder = _resolve_input(None, 'folder', 'prod_folder', config)
  
      update_databricks(
          logger,
          path,
          token,
          folder,
          update_jobs=True,
          cleanup=cleanup
      )
docs: The egg that the provided path points to will be uploaded to Databricks.
       All jobs which use the same major version of the library will be updated
       to use the new version, and all version of this library in the production
       folder with the same major version and a lower minor version will
       be deleted.
  
      Unlike `upload`, `upload_and_update` does not ask for a folder because it
       relies on the production folder specified in the config. This is to
       protect against accidentally updating jobs to versions of a library still
       in testing/development.
  
      All egg names already in Databricks must be properly formatted
       with versions of the form <name>-0.0.0.