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| .. 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 |
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| |
| Time zones |
| ========== |
| |
| Support for time zones is enabled by default. Airflow stores datetime information in UTC internally and in the database. |
| It allows you to run your DAGs with time zone dependent schedules. At the moment Airflow does not convert them to the |
| end user’s time zone in the user interface. There it will always be displayed in UTC. Also templates used in Operators |
| are not converted. Time zone information is exposed and it is up to the writer of DAG what do with it. |
| |
| This is handy if your users live in more than one time zone and you want to display datetime information according to |
| each user’s wall clock. |
| |
| Even if you are running Airflow in only one time zone it is still good practice to store data in UTC in your database |
| (also before Airflow became time zone aware this was also to recommended or even required setup). The main reason is |
| Daylight Saving Time (DST). Many countries have a system of DST, where clocks are moved forward in spring and backward |
| in autumn. If you’re working in local time, you’re likely to encounter errors twice a year, when the transitions |
| happen. (The pendulum and pytz documentation discusses these issues in greater detail.) This probably doesn’t matter |
| for a simple DAG, but it’s a problem if you are in, for example, financial services where you have end of day |
| deadlines to meet. |
| |
| The time zone is set in ``airflow.cfg``. By default it is set to utc, but you change it to use the system’s settings or |
| an arbitrary IANA time zone, e.g. `Europe/Amsterdam`. It is dependent on `pendulum`, which is more accurate than `pytz`. |
| Pendulum is installed when you install Airflow. |
| |
| Please note that the Web UI currently only runs in UTC. |
| |
| Concepts |
| -------- |
| Naïve and aware datetime objects |
| '''''''''''''''''''''''''''''''' |
| |
| Python’s datetime.datetime objects have a tzinfo attribute that can be used to store time zone information, |
| represented as an instance of a subclass of datetime.tzinfo. When this attribute is set and describes an offset, |
| a datetime object is aware. Otherwise, it’s naive. |
| |
| You can use timezone.is_aware() and timezone.is_naive() to determine whether datetimes are aware or naive. |
| |
| Because Airflow uses time-zone-aware datetime objects. If your code creates datetime objects they need to be aware too. |
| |
| .. code:: python |
| |
| from airflow.utils import timezone |
| |
| now = timezone.utcnow() |
| a_date = timezone.datetime(2017,1,1) |
| |
| |
| Interpretation of naive datetime objects |
| '''''''''''''''''''''''''''''''''''''''' |
| |
| Although Airflow operates fully time zone aware, it still accepts naive date time objects for `start_dates` |
| and `end_dates` in your DAG definitions. This is mostly in order to preserve backwards compatibility. In |
| case a naive `start_date` or `end_date` is encountered the default time zone is applied. It is applied |
| in such a way that it is assumed that the naive date time is already in the default time zone. In other |
| words if you have a default time zone setting of `Europe/Amsterdam` and create a naive datetime `start_date` of |
| `datetime(2017,1,1)` it is assumed to be a `start_date` of Jan 1, 2017 Amsterdam time. |
| |
| .. code:: python |
| |
| default_args=dict( |
| start_date=datetime(2016, 1, 1), |
| owner='Airflow' |
| ) |
| |
| dag = DAG('my_dag', default_args=default_args) |
| op = DummyOperator(task_id='dummy', dag=dag) |
| print(op.owner) # Airflow |
| |
| Unfortunately, during DST transitions, some datetimes don’t exist or are ambiguous. |
| In such situations, pendulum raises an exception. That’s why you should always create aware |
| datetime objects when time zone support is enabled. |
| |
| In practice, this is rarely an issue. Airflow gives you aware datetime objects in the models and DAGs, and most often, |
| new datetime objects are created from existing ones through timedelta arithmetic. The only datetime that’s often |
| created in application code is the current time, and timezone.utcnow() automatically does the right thing. |
| |
| |
| Default time zone |
| ''''''''''''''''' |
| |
| The default time zone is the time zone defined by the `default_timezone` setting under `[core]`. If |
| you just installed Airflow it will be set to `utc`, which is recommended. You can also set it to |
| `system` or an IANA time zone (e.g.`Europe/Amsterdam`). DAGs are also evaluated on Airflow workers, |
| it is therefore important to make sure this setting is equal on all Airflow nodes. |
| |
| |
| .. code:: python |
| |
| [core] |
| default_timezone = utc |
| |
| |
| Time zone aware DAGs |
| -------------------- |
| |
| Creating a time zone aware DAG is quite simple. Just make sure to supply a time zone aware `start_date` |
| using `pendulum`. |
| |
| .. code:: python |
| |
| import pendulum |
| |
| local_tz = pendulum.timezone("Europe/Amsterdam") |
| |
| default_args=dict( |
| start_date=datetime(2016, 1, 1, tzinfo=local_tz), |
| owner='Airflow' |
| ) |
| |
| dag = DAG('my_tz_dag', default_args=default_args) |
| op = DummyOperator(task_id='dummy', dag=dag) |
| print(dag.timezone) # <Timezone [Europe/Amsterdam]> |
| |
| Please note that while it is possible to set a `start_date` and `end_date` for Tasks always the DAG timezone |
| or global timezone (in that order) will be used to calculate the next execution date. Upon first encounter |
| the start date or end date will be converted to UTC using the timezone associated with start_date or end_date, |
| then for calculations this timezone information will be disregarded. |
| |
| Templates |
| ''''''''' |
| |
| Airflow returns time zone aware datetimes in templates, but does not convert them to local time so they remain in UTC. |
| It is left up to the DAG to handle this. |
| |
| .. code:: python |
| |
| import pendulum |
| |
| local_tz = pendulum.timezone("Europe/Amsterdam") |
| local_tz.convert(execution_date) |
| |
| |
| Cron schedules |
| '''''''''''''' |
| |
| In case you set a cron schedule, Airflow assumes you will always want to run at the exact same time. It will |
| then ignore day light savings time. Thus, if you have a schedule that says |
| run at end of interval every day at 08:00 GMT+1 it will always run end of interval 08:00 GMT+1, |
| regardless if day light savings time is in place. |
| |
| |
| Time deltas |
| ''''''''''' |
| For schedules with time deltas Airflow assumes you always will want to run with the specified interval. So if you |
| specify a timedelta(hours=2) you will always want to run to hours later. In this case day light savings time will |
| be taken into account. |