class_docstr: A Pipeline object represents a collection of named expressions to be
  compiled and executed by a PipelineEngine.
  
  A Pipeline has two important attributes: 'columns', a dictionary of named
  :class:`~zipline.pipeline.Term` instances, and 'screen', a
  :class:`~zipline.pipeline.Filter` representing criteria for
  including an asset in the results of a Pipeline.
  
  To compute a pipeline in the context of a TradingAlgorithm, users must call
  ``attach_pipeline`` in their ``initialize`` function to register that the
  pipeline should be computed each trading day. The most recent outputs of an
  attached pipeline can be retrieved by calling ``pipeline_output`` from
  ``handle_data``, ``before_trading_start``, or a scheduled function.
  
  Parameters
  ----------
  columns : dict, optional
      Initial columns.
  screen : zipline.pipeline.Filter, optional
      Initial screen.
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docstr: The screen of this pipeline.
  
  Returns
  -------
  screen : zipline.pipeline.Filter or None
      Term defining the screen for this pipeline. If ``screen`` is a
      filter, rows that do not pass the filter (i.e., rows for which the
      filter computed ``False``) will be dropped from the output of this
      pipeline before returning results.
  
  Notes
  -----
  Setting a screen on a Pipeline does not change the values produced for
  any rows: it only affects whether a given row is returned. Computing a
  pipeline with a screen is logically equivalent to computing the
  pipeline without the screen and then, as a post-processing-step,
  filtering out any rows for which the screen computed ``False``.
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code: def screen(self):
      """
      The screen of this pipeline.
  
      Returns
      -------
      screen : zipline.pipeline.Filter or None
          Term defining the screen for this pipeline. If ``screen`` is a
          filter, rows that do not pass the filter (i.e., rows for which the
          filter computed ``False``) will be dropped from the output of this
          pipeline before returning results.
  
      Notes
      -----
      Setting a screen on a Pipeline does not change the values produced for
      any rows: it only affects whether a given row is returned. Computing a
      pipeline with a screen is logically equivalent to computing the
      pipeline without the screen and then, as a post-processing-step,
      filtering out any rows for which the screen computed ``False``.
      """
      return self._screen
  
imports: import six
  from zipline.errors import UnsupportedPipelineOutput
  from zipline.utils.input_validation import expect_element, expect_types, optional
  from .domain import Domain, GENERIC, infer_domain
  from .graph import ExecutionPlan, TermGraph, SCREEN_NAME
  from .filters import Filter
  from .term import AssetExists, ComputableTerm, Term
label_desc: Use image node_id 3 for calling the Pipeline obj's underlying member method code with example usage: obj.screen() and returns: self