class_docstr: A project specification loaded from an MLproject file in the passed-in directory.
class_docstr_tok: ["A","project","specification","loaded","from","an","MLproject","file","in","the","passed-in","directory","."]
code: def __init__(
      self, env_type, env_config_path, entry_points, docker_env, name
  ):
      self.env_type = env_type
      self.env_config_path = env_config_path
      self._entry_points = entry_points
      self.docker_env = docker_env
      self.name = name
  
imports: import os
  import yaml
  from mlflow.exceptions import ExecutionException
  from mlflow.projects import env_type
  from mlflow.tracking import artifact_utils
  from mlflow.utils import data_utils
  from mlflow.utils.environment import _PYTHON_ENV_FILE_NAME
  from mlflow.utils.file_utils import get_local_path_or_none
  from mlflow.utils.string_utils import is_string_type, quote
label_desc: Use image node_id 1 to create a new Project object  with example: obj = Project(env_type, env_config_path, entry_points, docker_env, name)