class_docstr: Base class exposing Python model deployment APIs.
  
  Plugin implementors should define target-specific deployment logic via a subclass of
  ``BaseDeploymentClient`` within the plugin module, and customize method docstrings with
  target-specific information.
  
  .. Note::
      Subclasses should raise :py:class:`mlflow.exceptions.MlflowException` in error cases (e.g.
      on failure to deploy a model).
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docstr: List deployments.
  
  This method is expected to return an unpaginated list of all
  deployments (an alternative would be to return a dict with a 'deployments' field
  containing the actual deployments, with plugins able to specify other fields, e.g.
  a next_page_token field, in the returned dictionary for pagination, and to accept
  a `pagination_args` argument to this method for passing pagination-related args).
  
  Args:
      endpoint: (optional) List deployments in the specified endpoint. May not be
          supported by all targets
  
  Returns:
      A list of dicts corresponding to deployments. Each dict is guaranteed to
      contain a 'name' key containing the deployment name. The other fields of
      the returned dictionary and their types may vary across deployment targets.
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code: def list_deployments(self, endpoint=None):
      """List deployments.
  
      This method is expected to return an unpaginated list of all
      deployments (an alternative would be to return a dict with a 'deployments' field
      containing the actual deployments, with plugins able to specify other fields, e.g.
      a next_page_token field, in the returned dictionary for pagination, and to accept
      a `pagination_args` argument to this method for passing pagination-related args).
  
      Args:
          endpoint: (optional) List deployments in the specified endpoint. May not be
              supported by all targets
  
      Returns:
          A list of dicts corresponding to deployments. Each dict is guaranteed to
          contain a 'name' key containing the deployment name. The other fields of
          the returned dictionary and their types may vary across deployment targets.
      """
      pass
  
file_path: mlflow/mlflow/deployments/base.py
imports: import abc
  from mlflow.exceptions import MlflowException
  from mlflow.utils.annotations import developer_stable
label_desc: Use image node_id 5 for calling the BaseDeploymentClient obj's underlying member method code with example usage: obj.list_deployments(endpoint) without return types