blob: 2e22be9d95757e0bc1eb4297e9b8366d07e679c4 [file] [log] [blame]
:py:mod:`airflow.providers.papermill.operators.papermill`
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.. py:module:: airflow.providers.papermill.operators.papermill
Module Contents
---------------
Classes
~~~~~~~
.. autoapisummary::
airflow.providers.papermill.operators.papermill.NoteBook
airflow.providers.papermill.operators.papermill.PapermillOperator
.. py:class:: NoteBook
Bases: :py:obj:`airflow.lineage.entities.File`
Jupyter notebook
.. py:attribute:: type_hint
:annotation: :Optional[str] = jupyter_notebook
.. py:attribute:: parameters
:annotation: :Optional[Dict]
.. py:attribute:: meta_schema
:annotation: :str
.. py:class:: PapermillOperator(*, input_nb = None, output_nb = None, parameters = None, kernel_name = None, language_name = None, **kwargs)
Bases: :py:obj:`airflow.models.BaseOperator`
Executes a jupyter notebook through papermill that is annotated with parameters
:param input_nb: input notebook (can also be a NoteBook or a File inlet)
:param output_nb: output notebook (can also be a NoteBook or File outlet)
:param parameters: the notebook parameters to set
:param kernel_name: (optional) name of kernel to execute the notebook against
(ignores kernel name in the notebook document metadata)
.. py:attribute:: supports_lineage
:annotation: = True
.. py:attribute:: template_fields
:annotation: :Sequence[str] = ['input_nb', 'output_nb', 'parameters', 'kernel_name', 'language_name']
.. py:method:: execute(self, context)
This is the main method to derive when creating an operator.
Context is the same dictionary used as when rendering jinja templates.
Refer to get_template_context for more context.