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77 changes: 77 additions & 0 deletions airflow/sensors/date_time_sensor.py
Original file line number Diff line number Diff line change
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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 datetime
from typing import Dict, Union

from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils import timezone
from airflow.utils.decorators import apply_defaults


class DateTimeSensor(BaseSensorOperator):
"""
Waits until the specified datetime.

A major advantage of this sensor is idempotence for the ``target_time``.
It handles some cases for which ``TimeSensor`` and ``TimeDeltaSensor`` are not suited.

**Example** 1 :
If a task needs to wait for 11am on each ``execution_date``. Using
``TimeSensor`` or ``TimeDeltaSensor``, all backfill tasks started at
1am have to wait for 10 hours. This is unnecessary, e.g. a backfill
task with ``{{ ds }} = '1970-01-01'`` does not need to wait because
``1970-01-01T11:00:00`` has already passed.

**Example** 2 :
If a DAG is scheduled to run at 23:00 daily, but one of the tasks is
required to run at 01:00 next day, using ``TimeSensor`` will return
``True`` immediately because 23:00 > 01:00. Instead, we can do this:

.. code-block:: python

DateTimeSensor(
task_id='wait_for_0100',
target_time='{{ next_execution_date.tomorrow().replace(hour=1) }}',
)

:param target_time: datetime after which the job succeeds. (templated)
:type target_time: str or datetime.datetime
"""

template_fields = ("target_time",)

@apply_defaults
def __init__(
self, target_time: Union[str, datetime.datetime], *args, **kwargs
) -> None:
super().__init__(*args, **kwargs)
if isinstance(target_time, datetime.datetime):
self.target_time = target_time.isoformat()
elif isinstance(target_time, str):
self.target_time = target_time
else:
raise TypeError(
"Expected str or datetime.datetime type for target_time. Got {}".format(
type(target_time)
)
)

def poke(self, context: Dict) -> bool:
self.log.info("Checking if the time (%s) has come", self.target_time)
return timezone.utcnow() > timezone.parse(self.target_time)

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I'm wondering if it should be changed to>=? Same applies to TimeSensor and TimeDeltaSensor. The impact of changing to >= is that the task can succeed one poke interval earlier in some cases.

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I would say that > is safer

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I was just thinking >= is more mathematically correct. But now I realize it's extremely rare to have = because utcnow() has microsecond precision. So nvm

3 changes: 3 additions & 0 deletions docs/operators-and-hooks-ref.rst
Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,9 @@ Fundamentals
* - :mod:`airflow.sensors.time_sensor`
-

* - :mod:`airflow.sensors.date_time_sensor`
-


.. _Apache:

Expand Down
72 changes: 72 additions & 0 deletions tests/sensors/test_date_time_sensor.py
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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 pytest
from mock import patch
from parameterized import parameterized

from airflow.models.dag import DAG
from airflow.sensors.date_time_sensor import DateTimeSensor
from airflow.utils import timezone

DEFAULT_DATE = timezone.datetime(2015, 1, 1)


class TestDateTimeSensor:
@classmethod
def setup_class(cls):
args = {"owner": "airflow", "start_date": DEFAULT_DATE}
cls.dag = DAG("test_dag", default_args=args)

@parameterized.expand(
[
(
"valid_datetime",
timezone.datetime(2020, 7, 6, 13, tzinfo=timezone.utc),
"2020-07-06T13:00:00+00:00",
),
("valid_str", "20200706T210000+8", "20200706T210000+8"),
]
)
def test_valid_input(self, task_id, target_time, expected):
op = DateTimeSensor(task_id=task_id, target_time=target_time, dag=self.dag,)
assert op.target_time == expected

def test_invalid_input(self):
with pytest.raises(TypeError):
DateTimeSensor(
task_id="test", target_time=timezone.utcnow().time(), dag=self.dag,
)

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Would you mind adding a test for poke method?

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Added and rebased


@parameterized.expand(
[
(
"poke_datetime",
timezone.datetime(2020, 1, 1, 22, 59, tzinfo=timezone.utc),
True,
),
("poke_str_extended", "2020-01-01T23:00:00.001+00:00", False),
("poke_str_basic_with_tz", "20200102T065959+8", True),
]
)
@patch(
"airflow.sensors.date_time_sensor.timezone.utcnow",
return_value=timezone.datetime(2020, 1, 1, 23, 0, tzinfo=timezone.utc),
)
def test_poke(self, task_id, target_time, expected, mock_utcnow):
op = DateTimeSensor(task_id=task_id, target_time=target_time, dag=self.dag)
assert op.poke(None) == expected