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#
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from __future__ import annotations
from collections.abc import Iterable, Mapping, Sequence
from typing import TYPE_CHECKING, Any
from tabulate import tabulate
from airflow.exceptions import AirflowException
from airflow.providers.slack.hooks.slack_webhook import SlackWebhookHook
from airflow.providers.slack.transfers.base_sql_to_slack import BaseSqlToSlackOperator
if TYPE_CHECKING:
from airflow.providers.common.compat.sdk import Context
[docs]
class SqlToSlackWebhookOperator(BaseSqlToSlackOperator):
"""
Executes an SQL statement in a given SQL connection and sends the results to Slack Incoming Webhook.
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:SqlToSlackWebhookOperator`
.. note::
You cannot override the default channel (chosen by the user who installed your app),
Instead, these values will always inherit from the associated Slack App configuration
(`link <https://api.slack.com/messaging/webhooks#advanced_message_formatting>`_).
It is possible to change this values only in `Legacy Slack Integration Incoming Webhook
<https://api.slack.com/legacy/custom-integrations/messaging/webhooks#legacy-customizations>`_.
.. warning::
This hook intend to use `Slack Incoming Webhook` connection
and might not work correctly with `Slack API` connection.
:param sql: The SQL query to be executed (templated)
:param slack_message: The templated Slack message to send with the data returned from the SQL connection.
You can use the default JINJA variable {{ results_df }} to access the pandas dataframe containing the
SQL results
:param sql_conn_id: reference to a specific database.
:param sql_hook_params: Extra config params to be passed to the underlying hook.
Should match the desired hook constructor params.
:param slack_webhook_conn_id: :ref:`Slack Incoming Webhook <howto/connection:slack>`
connection id that has Incoming Webhook token in the password field.
:param slack_channel: The channel to send message.
: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
"""
[docs]
template_fields: Sequence[str] = ("sql", "slack_message")
[docs]
template_ext: Sequence[str] = (".sql", ".jinja", ".j2")
[docs]
template_fields_renderers = {"sql": "sql", "slack_message": "jinja"}
def __init__(
self,
*,
sql: str,
sql_conn_id: str,
slack_webhook_conn_id: str | None = None,
sql_hook_params: dict | None = None,
slack_channel: str | None = None,
slack_message: str,
results_df_name: str = "results_df",
parameters: list | tuple | Mapping[str, Any] | None = None,
**kwargs,
) -> None:
if not slack_webhook_conn_id:
raise ValueError("Got an empty `slack_webhook_conn_id` value.")
super().__init__(
sql=sql, sql_conn_id=sql_conn_id, sql_hook_params=sql_hook_params, parameters=parameters, **kwargs
)
[docs]
self.slack_webhook_conn_id = slack_webhook_conn_id
[docs]
self.slack_channel = slack_channel
[docs]
self.slack_message = slack_message
[docs]
self.results_df_name = results_df_name
def _render_and_send_slack_message(self, context, df) -> None:
# Put the dataframe into the context and render the JINJA template fields
context[self.results_df_name] = df
self.render_template_fields(context)
slack_hook = self._get_slack_hook()
self.log.info("Sending slack message: %s", self.slack_message)
slack_hook.send(text=self.slack_message, channel=self.slack_channel)
def _get_slack_hook(self) -> SlackWebhookHook:
return SlackWebhookHook(
slack_webhook_conn_id=self.slack_webhook_conn_id,
proxy=self.slack_proxy,
timeout=self.slack_timeout,
retry_handlers=self.slack_retry_handlers,
)
[docs]
def render_template_fields(self, context, jinja_env=None) -> None:
# If this is the first render of the template fields, exclude slack_message from rendering since
# the SQL results haven't been retrieved yet.
if self.times_rendered == 0:
fields_to_render: Iterable[str] = (x for x in self.template_fields if x != "slack_message")
else:
fields_to_render = self.template_fields
if not jinja_env:
jinja_env = self.get_template_env()
# Add the tabulate library into the JINJA environment
jinja_env.filters["tabulate"] = tabulate
self._do_render_template_fields(self, fields_to_render, context, jinja_env, set())
self.times_rendered += 1
[docs]
def execute(self, context: Context) -> None:
if not isinstance(self.sql, str):
raise AirflowException("Expected 'sql' parameter should be a string.")
if self.sql is None or self.sql.strip() == "":
raise AirflowException("Expected 'sql' parameter is missing.")
if self.slack_message is None or self.slack_message.strip() == "":
raise AirflowException("Expected 'slack_message' parameter is missing.")
df = self._get_query_results()
self._render_and_send_slack_message(context, df)
self.log.debug("Finished sending SQL data to Slack")