| :mod:`airflow.contrib.sensors.python_sensor` |
| ============================================ |
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| .. py:module:: airflow.contrib.sensors.python_sensor |
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| Module Contents |
| --------------- |
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| .. py:class:: PythonSensor(python_callable, op_args=None, op_kwargs=None, provide_context=False, templates_dict=None, *args, **kwargs) |
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| Bases: :class:`airflow.sensors.base_sensor_operator.BaseSensorOperator` |
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| Waits for a Python callable to return True. |
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| User could put input argument in templates_dict |
| e.g ``templates_dict = {'start_ds': 1970}`` |
| and access the argument by calling ``kwargs['templates_dict']['start_ds']`` |
| in the the callable |
| |
| :param python_callable: A reference to an object that is callable |
| :type python_callable: python callable |
| :param op_kwargs: a dictionary of keyword arguments that will get unpacked |
| in your function |
| :type op_kwargs: dict |
| :param op_args: a list of positional arguments that will get unpacked when |
| calling your callable |
| :type op_args: list |
| :param provide_context: if set to true, Airflow will pass a set of |
| keyword arguments that can be used in your function. This set of |
| kwargs correspond exactly to what you can use in your jinja |
| templates. For this to work, you need to define `**kwargs` in your |
| function header. |
| :type provide_context: bool |
| :param templates_dict: a dictionary where the values are templates that |
| will get templated by the Airflow engine sometime between |
| ``__init__`` and ``execute`` takes place and are made available |
| in your callable's context after the template has been applied. |
| :type templates_dict: dict of str |
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| .. attribute:: template_fields |
| :annotation: = ['templates_dict', 'op_args', 'op_kwargs'] |
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| .. method:: poke(self, context) |
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