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Adding generic
SqlToSlackOperator (#24663)
* adding `SqlToSlackOperator` Co-authored-by: eladkal <45845474+eladkal@users.noreply.github.com>
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| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. |
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| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
| import warnings | ||
| from typing import TYPE_CHECKING, Iterable, Mapping, Optional, Sequence, Union | ||
|
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| from pandas import DataFrame | ||
| from tabulate import tabulate | ||
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| from airflow.exceptions import AirflowException | ||
| from airflow.hooks.base import BaseHook | ||
| from airflow.hooks.dbapi import DbApiHook | ||
| from airflow.models import BaseOperator | ||
| from airflow.providers.slack.hooks.slack_webhook import SlackWebhookHook | ||
| from airflow.providers_manager import ProvidersManager | ||
| from airflow.utils.module_loading import import_string | ||
| from airflow.version import version | ||
|
|
||
| if TYPE_CHECKING: | ||
| from airflow.utils.context import Context | ||
|
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| def _backported_get_hook(connection, *, hook_params=None): | ||
| """Return hook based on conn_type | ||
| 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 = ProvidersManager().hooks.get(connection.conn_type, None) | ||
|
|
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| if hook is None: | ||
| raise AirflowException(f'Unknown hook type "{connection.conn_type}"') | ||
| try: | ||
| hook_class = import_string(hook.hook_class_name) | ||
| except ImportError: | ||
| warnings.warn( | ||
| "Could not import %s when discovering %s %s", | ||
| hook.hook_class_name, | ||
| hook.hook_name, | ||
| hook.package_name, | ||
| ) | ||
| raise | ||
| if hook_params is None: | ||
| hook_params = {} | ||
| return hook_class(**{hook.connection_id_attribute_name: connection.conn_id}, **hook_params) | ||
|
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| 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 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 sql_conn_id: Reference to | ||
| :ref:`Snowflake connection id<howto/connection:snowflake>` | ||
| :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 | ||
| """ | ||
|
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| template_fields: Sequence[str] = ('sql', 'slack_message') | ||
| template_ext: Sequence[str] = ('.sql', '.jinja', '.j2') | ||
| template_fields_renderers = {"sql": "sql", "slack_message": "jinja"} | ||
| times_rendered = 0 | ||
|
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||
| def __init__( | ||
| self, | ||
| *, | ||
| sql: str, | ||
| sql_conn_id: str, | ||
| sql_hook_params: Optional[dict] = None, | ||
| slack_conn_id: Optional[str] = None, | ||
| slack_webhook_token: Optional[str] = None, | ||
| slack_channel: Optional[str] = None, | ||
| slack_message: str, | ||
| results_df_name: str = 'results_df', | ||
| parameters: Optional[Union[Iterable, Mapping]] = None, | ||
| **kwargs, | ||
| ) -> None: | ||
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| super().__init__(**kwargs) | ||
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| 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 | ||
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| 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" | ||
| ) | ||
|
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| 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 >= '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 | ||
|
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| def _get_query_results(self) -> DataFrame: | ||
| sql_hook = self._get_hook() | ||
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| self.log.info('Running SQL query: %s', self.sql) | ||
| df = sql_hook.get_pandas_df(self.sql, parameters=self.parameters) | ||
| return df | ||
|
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| 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) | ||
|
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| slack_hook = self._get_slack_hook() | ||
| self.log.info('Sending slack message: %s', self.slack_message) | ||
| slack_hook.execute() | ||
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| def _get_slack_hook(self) -> SlackWebhookHook: | ||
| return SlackWebhookHook( | ||
| http_conn_id=self.slack_conn_id, | ||
| message=self.slack_message, | ||
| channel=self.slack_channel, | ||
| webhook_token=self.slack_webhook_token, | ||
| ) | ||
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| 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 | ||
|
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| if not jinja_env: | ||
| jinja_env = self.get_template_env() | ||
|
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| # Add the tabulate library into the JINJA environment | ||
| jinja_env.filters['tabulate'] = tabulate | ||
|
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| self._do_render_template_fields(self, fields_to_render, context, jinja_env, set()) | ||
| self.times_rendered += 1 | ||
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| 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.") | ||
|
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| df = self._get_query_results() | ||
| self._render_and_send_slack_message(context, df) | ||
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| self.log.debug('Finished sending SQL data to Slack') |
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