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:py:mod:`airflow.providers.snowflake.transfers.snowflake_to_slack`
==================================================================
.. py:module:: airflow.providers.snowflake.transfers.snowflake_to_slack
Module Contents
---------------
Classes
~~~~~~~
.. autoapisummary::
airflow.providers.snowflake.transfers.snowflake_to_slack.SnowflakeToSlackOperator
.. py:class:: SnowflakeToSlackOperator(*, sql, slack_message, snowflake_conn_id = 'snowflake_default', slack_conn_id = 'slack_default', results_df_name = 'results_df', parameters = None, warehouse = None, database = None, schema = None, role = None, slack_token = None, **kwargs)
Bases: :py:obj:`airflow.models.BaseOperator`
Executes an SQL statement in Snowflake and sends the results to Slack. The results of the query are
rendered into the 'slack_message' parameter as a Pandas dataframe using a JINJA variable called '{{
results_df }}'. The 'results_df' variable name can be changed by specifying a different
'results_df_name' parameter. The Tabulate library is added to the JINJA environment as a filter to
allow the dataframe to be rendered nicely. For example, set 'slack_message' to {{ results_df |
tabulate(tablefmt="pretty", headers="keys") }} to send the results to Slack as an ascii rendered table.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:SnowflakeToSlackOperator`
:param sql: The SQL statement to execute on Snowflake (templated)
:param slack_message: The templated Slack message to send with the data returned from Snowflake.
You can use the default JINJA variable {{ results_df }} to access the pandas dataframe containing the
SQL results
:param snowflake_conn_id: Reference to
:ref:`Snowflake connection id<howto/connection:snowflake>`
:param slack_conn_id: The connection id for Slack
:param results_df_name: The name of the JINJA template's dataframe variable, default is 'results_df'
:param parameters: The parameters to pass to the SQL query
:param warehouse: The Snowflake virtual warehouse to use to run the SQL query
:param database: The Snowflake database to use for the SQL query
:param schema: The schema to run the SQL against in Snowflake
:param role: The role to use when connecting to Snowflake
:param slack_token: The token to use to authenticate to Slack. If this is not provided, the
'webhook_token' attribute needs to be specified in the 'Extra' JSON field against the slack_conn_id
.. py:attribute:: template_fields
:annotation: :Sequence[str] = ['sql', 'slack_message']
.. py:attribute:: template_ext
:annotation: :Sequence[str] = ['.sql', '.jinja', '.j2']
.. py:attribute:: template_fields_renderers
.. py:attribute:: times_rendered
:annotation: = 0
.. py:method:: render_template_fields(self, context, jinja_env=None)
Template all attributes listed in template_fields.
This mutates the attributes in-place and is irreversible.
:param context: Dict with values to apply on content
:param jinja_env: Jinja environment
.. 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.