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from typing import TYPE_CHECKING, Iterable, Mapping, Optional, Sequence, Union
from pandas import DataFrame
from tabulate import tabulate
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.slack.hooks.slack_webhook import SlackWebhookHook
from airflow.providers.snowflake.hooks.snowflake import SnowflakeHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class SnowflakeToSlackOperator(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
"""
[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,
slack_message: str,
snowflake_conn_id: str = 'snowflake_default',
slack_conn_id: str = 'slack_default',
results_df_name: str = 'results_df',
parameters: Optional[Union[Iterable, Mapping]] = None,
warehouse: Optional[str] = None,
database: Optional[str] = None,
schema: Optional[str] = None,
role: Optional[str] = None,
slack_token: Optional[str] = None,
**kwargs,
) -> None:
super().__init__(**kwargs)
self.snowflake_conn_id = snowflake_conn_id
self.sql = sql
self.parameters = parameters
self.warehouse = warehouse
self.database = database
self.schema = schema
self.role = role
self.slack_conn_id = slack_conn_id
self.slack_token = slack_token
self.slack_message = slack_message
self.results_df_name = results_df_name
def _get_query_results(self) -> DataFrame:
snowflake_hook = self._get_snowflake_hook()
self.log.info('Running SQL query: %s', self.sql)
df = snowflake_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.execute()
def _get_snowflake_hook(self) -> SnowflakeHook:
return SnowflakeHook(
snowflake_conn_id=self.snowflake_conn_id,
warehouse=self.warehouse,
database=self.database,
role=self.role,
schema=self.schema,
)
def _get_slack_hook(self) -> SlackWebhookHook:
return SlackWebhookHook(
http_conn_id=self.slack_conn_id, message=self.slack_message, webhook_token=self.slack_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 snowflake 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 Snowflake data to Slack')