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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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from __future__ import annotations
from typing import TYPE_CHECKING, Iterable, Mapping, Sequence
from packaging.version import Version
from pandas import DataFrame
from tabulate import tabulate
from airflow.exceptions import AirflowException
from airflow.hooks.base import BaseHook
from airflow.models import BaseOperator
from airflow.providers.common.sql.hooks.sql import DbApiHook, _backported_get_hook
from airflow.providers.slack.hooks.slack_webhook import SlackWebhookHook
from airflow.version import version
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class SqlToSlackOperator(BaseOperator):
"""
Executes an SQL statement in a given SQL connection 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:SqlToSlackOperator`
: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_conn_id: The connection id for Slack.
:param slack_webhook_token: The token to use to authenticate to Slack. If this is not provided, the
'slack_conn_id' attribute needs to be specified in the 'password' field.
:param slack_channel: The channel to send message. Override default from Slack connection.
: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,
sql_hook_params: dict | None = None,
slack_conn_id: str | None = None,
slack_webhook_token: str | None = None,
slack_channel: str | None = None,
slack_message: str,
results_df_name: str = 'results_df',
parameters: Iterable | Mapping | None = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.sql_conn_id = sql_conn_id
self.sql_hook_params = sql_hook_params
self.sql = sql
self.parameters = parameters
self.slack_conn_id = slack_conn_id
self.slack_webhook_token = slack_webhook_token
self.slack_channel = slack_channel
self.slack_message = slack_message
self.results_df_name = results_df_name
self.kwargs = kwargs
if not self.slack_conn_id and not self.slack_webhook_token:
raise AirflowException(
"SqlToSlackOperator requires either a `slack_conn_id` or a `slack_webhook_token` argument"
)
def _get_hook(self) -> DbApiHook:
self.log.debug("Get connection for %s", self.sql_conn_id)
conn = BaseHook.get_connection(self.sql_conn_id)
if Version(version) >= Version('2.3'):
# "hook_params" were introduced to into "get_hook()" only in Airflow 2.3.
hook = conn.get_hook(hook_params=self.sql_hook_params) # ignore airflow compat check
else:
# For supporting Airflow versions < 2.3, we backport "get_hook()" method. This should be removed
# when "apache-airflow-providers-slack" will depend on Airflow >= 2.3.
hook = _backported_get_hook(conn, hook_params=self.sql_hook_params)
if not callable(getattr(hook, 'get_pandas_df', None)):
raise AirflowException(
"This hook is not supported. The hook class must have get_pandas_df method."
)
return hook
def _get_query_results(self) -> DataFrame:
sql_hook = self._get_hook()
self.log.info('Running SQL query: %s', self.sql)
df = sql_hook.get_pandas_df(self.sql, parameters=self.parameters)
return df
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_conn_id, webhook_token=self.slack_webhook_token
)
[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] = filter(lambda x: x != 'slack_message', self.template_fields)
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')
