Datasets:

Partha117

/

oss_bugs

like 0

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/details/taskInstance/taskActions/MarkInstanceAs.tsx"]

"Mark state as..." button options grayed out

### Apache Airflow version 2.7.3 ### If "Other Airflow 2 version" selected, which one? _No response_ ### What happened? Since a few versions ago, the button to mark a task state as success is grayed out when the task is in a success state. Conversely, whenever a task is in a failed state, the mark button as failed is grayed out.  ### What you think should happen instead? This is inconvenient. These buttons bring up another dialog where you may select past/future/downstream/upstream tasks. These tasks may not match the state of the task you currently have selected. Frequently it is useful to be able to set all downstream tasks of an already succeeded task to success.  The current workaround is to first set the task to the opposite of the desired state, then to mark it as the desired state with added past/future/downstream/upstream tasks. This is clunky. The buttons should not be grayed out depending on the current task state. ### How to reproduce Mark a task as success. Then try to do it again. ### Operating System n/a ### Versions of Apache Airflow Providers _No response_ ### Deployment Other Docker-based deployment ### Deployment details _No response_ ### Anything else? _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/36219

https://github.com/apache/airflow/pull/36254

a68b4194fe7201bba0544856b60c7d6724da60b3

20d547ecd886087cd89bcdf0015ce71dd0a12cef

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/io/__init__.py", "tests/io/test_path.py"]

Add unit tests to retrieve fsspec from providers including backwards compatibility

### Body We currently miss fsspec retrieval for providers and #36186 fixed compatibility issue with it, so we should likely add unit tests covering it. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/36187

https://github.com/apache/airflow/pull/36199

97e8f58673769d3c06bce397882375020a139cee

6c94ddf2bc123bfc7a59df4ce05f2b4e980f7a15

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/operators/cloud_run.py", "tests/providers/google/cloud/operators/test_cloud_run.py"]

Add overrides in the template field for the Google Cloud Run Jobs Execute operator

### Description The overrides parameter is not in the list of template field and it's impossible to pass runtime values to Cloud Run (date start/end, custom dag parameters,...) ### Use case/motivation I would like to use Cloud Run Jobs with DBT and pass Airflow parameters (date start/end) to the Cloud Run jobs. For that, I need to use the the context (**kwargs) in a template field ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/36132

https://github.com/apache/airflow/pull/36133

df23df53155c7a3a9b30d206c962913d74ad3754

3dddfb4a4ae112544fd02e09a5633961fa725a36

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/decorators/branch_external_python.py", "airflow/decorators/branch_python.py", "airflow/decorators/branch_virtualenv.py", "airflow/decorators/external_python.py", "airflow/decorators/python_virtualenv.py", "airflow/decorators/short_circuit.py", "airflow/models/abstractoperator.py", "tests/decorators/test_branch_virtualenv.py", "tests/decorators/test_external_python.py", "tests/decorators/test_python_virtualenv.py"]

Using requirements file in VirtualEnvPythonOperation appears to be broken

### Discussed in https://github.com/apache/airflow/discussions/36076 <div type='discussions-op-text'> ^{Originally posted by **timc** December 5, 2023} ### Apache Airflow version 2.7.3 ### What happened When creating a virtual env task and passing in a requirements file like this: `@task.virtualenv( use_dill=True, system_site_packages=False, requirements='requirements.txt')` The result is that the contents of the requirements file using to populate the venv is requirements.txt Which is wrong. And you get this: [2023-12-05, 12:33:06 UTC] {{process_utils.py:181}} INFO - Executing cmd: python3 /usr/local/***/.local/lib/python3.10/site-packages/virtualenv /tmp/venv3cdlqjlq [2023-12-05, 12:33:06 UTC] {{process_utils.py:185}} INFO - Output: [2023-12-05, 12:33:07 UTC] {{process_utils.py:189}} INFO - created virtual environment CPython3.10.9.final.0-64 in 397ms [2023-12-05, 12:33:07 UTC] {{process_utils.py:189}} INFO - creator CPython3Posix(dest=/tmp/venv3cdlqjlq, clear=False, no_vcs_ignore=False, global=False) [2023-12-05, 12:33:07 UTC] {{process_utils.py:189}} INFO - seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/usr/local/***/.local/share/virtualenv) [2023-12-05, 12:33:07 UTC] {{process_utils.py:189}} INFO - added seed packages: pip==23.3.1, setuptools==69.0.2, wheel==0.42.0 [2023-12-05, 12:33:07 UTC] {{process_utils.py:189}} INFO - activators BashActivator,CShellActivator,FishActivator,NushellActivator,PowerShellActivator,PythonActivator [2023-12-05, 12:33:07 UTC] {{process_utils.py:181}} INFO - Executing cmd: /tmp/venv3cdlqjlq/bin/pip install -r /tmp/venv3cdlqjlq/requirements.txt [2023-12-05, 12:33:07 UTC] {{process_utils.py:185}} INFO - Output: [2023-12-05, 12:33:09 UTC] {{process_utils.py:189}} INFO - ERROR: Could not find a version that satisfies the requirement requirements.txt (from versions: none) [2023-12-05, 12:33:09 UTC] {{process_utils.py:189}} INFO - HINT: You are attempting to install a package literally named "requirements.txt" (which cannot exist). Consider using the '-r' flag to install the packages listed in requirements.txt [2023-12-05, 12:33:09 UTC] {{process_utils.py:189}} INFO - ERROR: No matching distribution found for requirements.txt [2023-12-05, 12:33:09 UTC] {{taskinstance.py:1824}} ERROR - Task failed with exception The issue appears to be that the requirements parameter is added to a list on construction of the operator so the templating never happens. ### What you think should happen instead The provided requirements file should be used in the pip command to set up the venv. ### How to reproduce Create a dag: ``` from datetime import datetime from airflow.decorators import dag, task @dag(schedule_interval=None, start_date=datetime(2021, 1, 1), catchup=False, tags=['example']) def virtualenv_task(): @task.virtualenv( use_dill=True, system_site_packages=False, requirements='requirements.txt', ) def extract(): import pandas x = pandas.DataFrame() extract() dag = virtualenv_task() ``` And a requirements.txt file ``` pandas ``` Run AirFlow ### Operating System Ubuntu 23.04 ### Versions of Apache Airflow Providers apache-airflow-providers-amazon==8.2.0 apache-airflow-providers-celery==3.2.1 apache-airflow-providers-common-sql==1.5.2 apache-airflow-providers-ftp==3.4.2 apache-airflow-providers-http==4.4.2 apache-airflow-providers-imap==3.2.2 apache-airflow-providers-postgres==5.5.1 apache-airflow-providers-sqlite==3.4.2 ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else Everytime. ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) </div>

https://github.com/apache/airflow/issues/36102

https://github.com/apache/airflow/pull/36103

76d26f453000aa67f4e755c5e8f4ccc0eac7b5a4

3904206b69428525db31ff7813daa0322f7b83e8

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/airbyte/hooks/airbyte.py", "tests/providers/airbyte/hooks/test_airbyte.py"]

AirbyteTriggerSyncOperator should kill job upon timeout

### Apache Airflow version 2.7.3 ### What happened When calling in not asyncronous way the AirbyteTriggerSyncOperator ([here](https://github.com/apache/airflow/blob/main/airflow/providers/airbyte/operators/airbyte.py#L79)) and timeout is reached [here](https://github.com/apache/airflow/blob/main/airflow/providers/airbyte/hooks/airbyte.py#L66) the job should be killed otherwise the airbyte will keep running, is just a matter of calling the cancel job which is already there https://github.com/apache/airflow/blob/main/airflow/providers/airbyte/hooks/airbyte.py#L110C9-L110C9 ### What you think should happen instead I think that if the airbyte operator has not finished within the defined timeout then the airbyte should also stop. Otherwise the airbyte job may continue to operate and even finish (after the timeout). This way the airflow will have failed but airbyte will look successful, which is inconsistency among airflow and airbyte ### How to reproduce Its very easy to reproduce by calling a connection with very small timeout ``` from airflow import DAG from airflow.utils.dates import days_ago from airflow.providers.airbyte.operators.airbyte import AirbyteTriggerSyncOperator with DAG(dag_id='trigger_airbyte_job_example', default_args={'owner': 'airflow'}, schedule_interval='@daily', start_date=days_ago(1) ) as dag: money_to_json = AirbyteTriggerSyncOperator( task_id='airbyte_money_json_example', airbyte_conn_id='airbyte_conn_example', connection_id='1e3b5a72-7bfd-4808-a13c-204505490110', # change this to something that works asynchronous=False, # important to have this to False timeout=10, # something really small wait_seconds=3 ) ``` ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers apache-airflow-providers-airbyte 3.4.0 ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/36070

https://github.com/apache/airflow/pull/36241

a7a6a9d6ea69418755c6a0829e474580cc751f00

ceab840f31e2dcf591390bbace0ff9d74c6fc8fd

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/auth/managers/fab/security_manager/override.py", "tests/www/views/test_views_custom_user_views.py"]

Password reset via flask fab reset-password raises "RuntimeError: Working outside of request context."

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened Running this command to reset a password via the CLI raises an exception: ``` $ flask --app airflow.www.app fab reset-password --username myusername Password: Repeat for confirmation: Traceback (most recent call last): File "/home/airflow/.local/bin/flask", line 8, in <module> sys.exit(main()) File "/home/airflow/.local/lib/python3.8/site-packages/flask/cli.py", line 1050, in main cli.main() File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 1078, in main rv = self.invoke(ctx) File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 1688, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 1688, in invoke return _process_result(sub_ctx.command.invoke(sub_ctx)) File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 1434, in invoke return ctx.invoke(self.callback, **ctx.params) File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 783, in invoke return __callback(*args, **kwargs) File "/home/airflow/.local/lib/python3.8/site-packages/click/decorators.py", line 33, in new_func return f(get_current_context(), *args, **kwargs) File "/home/airflow/.local/lib/python3.8/site-packages/flask/cli.py", line 357, in decorator return __ctx.invoke(f, *args, **kwargs) File "/home/airflow/.local/lib/python3.8/site-packages/click/core.py", line 783, in invoke return __callback(*args, **kwargs) File "/home/airflow/.local/lib/python3.8/site-packages/flask_appbuilder/cli.py", line 157, in reset_password current_app.appbuilder.sm.reset_password(user.id, password) File "/home/airflow/.local/lib/python3.8/site-packages/airflow/auth/managers/fab/security_manager/override.py", line 245, in reset_password self.reset_user_sessions(user) File "/home/airflow/.local/lib/python3.8/site-packages/airflow/auth/managers/fab/security_manager/override.py", line 255, in reset_user_sessions flash( File "/home/airflow/.local/lib/python3.8/site-packages/flask/helpers.py", line 359, in flash flashes = session.get("_flashes", []) File "/home/airflow/.local/lib/python3.8/site-packages/werkzeug/local.py", line 316, in __get__ obj = instance._get_current_object() File "/home/airflow/.local/lib/python3.8/site-packages/werkzeug/local.py", line 513, in _get_current_object raise RuntimeError(unbound_message) from None RuntimeError: Working outside of request context. This typically means that you attempted to use functionality that needed an active HTTP request. Consult the documentation on testing for information about how to avoid this problem. ``` ### What you think should happen instead It should be possible to reset the password via the CLI. This is necessary for when you need to reset your own password without knowing your current password so you can't use the UI. I believe this means that the `reset_user_sessions` function can't unconditionally use `flash` without determining if it's running in a request context or not. ### How to reproduce Run `flask --app airflow.www.app fab reset-password` with an existing username via the CLI. ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers _No response_ ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/36054

https://github.com/apache/airflow/pull/36056

61fd166a4662d67bc914949f9cf07ceab7d55686

7ececfdb2183516d9a30195ffcd76632167119c5

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/dag_processing/manager.py", "airflow/dag_processing/processor.py", "airflow/migrations/versions/0133_2_8_0_add_processor_subdir_import_error.py", "airflow/models/errors.py", "airflow/utils/db.py", "docs/apache-airflow/img/airflow_erd.sha256", "docs/apache-airflow/img/airflow_erd.svg", "docs/apache-airflow/migrations-ref.rst", "tests/dag_processing/test_job_runner.py"]

dag processor deletes import errors of other dag processors thinking the files don't exist

### Apache Airflow version main (development) ### What happened When dag processor starts with a sub directory to process then the import errors are recorded with that path. So when there is processor for airflow-dag-processor-0 folder in order to remove import errors it lists all files under airflow-dag-processor-0 folder and deletes those not present. This becomes an issue when there is airflow-dag-processor-1 that records import errors whose files won't be part of airflow-dag-processor-0 folder. ### What you think should happen instead The fix would be to have processor_subdir stored in ImportError table so that during querying we only look at import errors relevant to the dag processor and don't delete other items. A fix similar to https://github.com/apache/airflow/pull/33357 needs to be applied for import errors as well. ### How to reproduce 1. create a dag file with import error at `~/airflow/dags/airflow-dag-processor-0/sample_sleep.py` . Start a dag processor with -S to process "~/airflow/dags/airflow-dag-processor-0/" . Import error should be present. 2. create a dag file with import error at `~/airflow/dags/airflow-dag-processor-1/sample_sleep.py` . Start a dag processor with -S to process "~/airflow/dags/airflow-dag-processor-1/". Import error for airflow-dag-processor-0 is deleted. 3. ```python from datetime import datetime, timedelta from airflow import DAG from airflow.decorators import task from datetime import timedelta, invalid with DAG( dag_id="task_duration", start_date=datetime(2023, 1, 1), catchup=True, schedule_interval="@daily", ) as dag: @task def sleeper(): pass sleeper() ``` ### Operating System Ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35949

https://github.com/apache/airflow/pull/35956

9c1c9f450e289b40f94639db3f0686f592c8841e

1a3eeab76cdb6d0584452e3065aee103ad9ab641

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/models/dagrun.py", "tests/models/test_dagrun.py"]

Scheduler getting crashed when downgrading from 2.8.0b1 to 2.7.3

### Apache Airflow version 2.8.0b1 ### What happened The scheduler getting crashed when downgrading from 2.8.0b1 to 2.7.3 we had some running TIs when the downgrade happened, looks like Adopting tasks failing the scheduler. could be due to this [PR](https://github.com/apache/airflow/pull/35096/files) ### What you think should happen instead _No response_ ### How to reproduce create 2.8.0b1 deployment execute a couple of dags downgrade to 2.7.3 scheduler goes in crash loop **Logs:** ``` [2023-11-28T07:14:26.927+0000] {process_utils.py:131} INFO - Sending 15 to group 32. PIDs of all processes in the group: [32] [2023-11-28T07:14:26.927+0000] {process_utils.py:86} INFO - Sending the signal 15 to group 32 [2023-11-28T07:14:27.140+0000] {process_utils.py:79} INFO - Process psutil.Process(pid=32, status='terminated', exitcode=0, started='07:14:25') (32) terminated with exit code 0 [2023-11-28T07:14:27.140+0000] {scheduler_job_runner.py:874} INFO - Exited execute loop [2023-11-28T07:14:27.145+0000] {scheduler_command.py:49} ERROR - Exception when running scheduler job Traceback (most recent call last): File "/usr/local/lib/python3.11/site-packages/airflow/cli/commands/scheduler_command.py", line 47, in _run_scheduler_job run_job(job=job_runner.job, execute_callable=job_runner._execute) File "/usr/local/lib/python3.11/site-packages/airflow/utils/session.py", line 77, in wrapper return func(*args, session=session, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/jobs/job.py", line 289, in run_job return execute_job(job, execute_callable=execute_callable) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/jobs/job.py", line 318, in execute_job ret = execute_callable() ^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/astronomer/airflow/version_check/plugin.py", line 30, in run_before fn(*args, **kwargs) File "/usr/local/lib/python3.11/site-packages/airflow/jobs/scheduler_job_runner.py", line 845, in _execute self._run_scheduler_loop() File "/usr/local/lib/python3.11/site-packages/airflow/jobs/scheduler_job_runner.py", line 927, in _run_scheduler_loop self.adopt_or_reset_orphaned_tasks() File "/usr/local/lib/python3.11/site-packages/airflow/utils/session.py", line 77, in wrapper return func(*args, session=session, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/jobs/scheduler_job_runner.py", line 1601, in adopt_or_reset_orphaned_tasks for attempt in run_with_db_retries(logger=self.log): File "/usr/local/lib/python3.11/site-packages/tenacity/__init__.py", line 347, in __iter__ do = self.iter(retry_state=retry_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/tenacity/__init__.py", line 314, in iter return fut.result() ^^^^^^^^^^^^ File "/usr/local/lib/python3.11/concurrent/futures/_base.py", line 449, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result raise self._exception File "/usr/local/lib/python3.11/site-packages/airflow/jobs/scheduler_job_runner.py", line 1645, in adopt_or_reset_orphaned_tasks tis_to_adopt_or_reset = session.scalars(tis_to_adopt_or_reset).all() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 1476, in all return self._allrows() ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 401, in _allrows rows = self._fetchall_impl() ^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 1389, in _fetchall_impl return self._real_result._fetchall_impl() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 1813, in _fetchall_impl return list(self.iterator) ^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/orm/loading.py", line 147, in chunks fetch = cursor._raw_all_rows() ^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 393, in _raw_all_rows return [make_row(row) for row in rows] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/engine/result.py", line 393, in <listcomp> return [make_row(row) for row in rows] ^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/sqlalchemy/sql/sqltypes.py", line 1870, in process return loads(value) ^^^^^^^^^^^^ AttributeError: Can't get attribute 'ConfDict' on <module 'airflow.models.dagrun' from '/usr/local/lib/python3.11/site-packages/airflow/models/dagrun.py'> ``` ### Operating System Linux ### Versions of Apache Airflow Providers _No response_ ### Deployment Astronomer ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35914

https://github.com/apache/airflow/pull/35959

ab835c20b2e9bce8311d906d223ecca5e0f85627

4a7c7460bf1734b76497280f5a2adc3e30a7820c

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/apache/spark/hooks/spark_submit.py", "airflow/providers/apache/spark/operators/spark_submit.py", "tests/providers/apache/spark/operators/test_spark_submit.py"]

Adding Support for Yarn queue and other extras in SparkSubmit Operator and Hook

### Description Spark-submit --queue thequeue option specifies the YARN queue to which the application should be submitted. more - https://spark.apache.org/docs/3.2.0/running-on-yarn.html ### Use case/motivation The --queue option is particularly useful in a multi-tenant environment where different users or groups have allocated resources in specific YARN queues. ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35911

https://github.com/apache/airflow/pull/36151

4c73d613b11107eb8ee3cc70fe6233d5ee3a0b29

1b4a7edc545be6d6e9b8f00c243beab215e562b7

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/details/taskInstance/Logs/index.tsx"]

New logs tab is broken for tasks with high retries

### Apache Airflow version 2.7.3 ### What happened One of our users had high number of retries around 600 and the operator was like a sensor that retries on failure till retry limit is reached. The new log page renders the log tab to the bottom making it unusable. In the old page there is still a display of buttons for all retry but scrolling is enabled. To fix this we had to change log from buttons to a drop down where attempt can be selected placing the dropdown before the element to select log level. This is an edge case but we thought to file anyway in case someone is facing this. We are happy to upstream to one of the selected below solutions : 1. Using dropdown on high number of attempts like after 50 and falling back to buttons. But this is a UX change to use button in one case and dropdown in another that user needs to be educated. 2. Always using dropdown despite low number of attempts with default of latest attempt. Attaching sample dag code that could lead to this scenario. Sample scenario :  ### What you think should happen instead _No response_ ### How to reproduce ```python from datetime import datetime, timedelta from airflow import DAG from airflow.decorators import task from airflow.models.param import Param from airflow.operators.empty import EmptyOperator from datetime import timedelta with DAG( dag_id="retry_ui_issue", start_date=datetime(2023, 1, 1), catchup=False, schedule_interval="@once", ) as dag: @task(retries=400, retry_delay=timedelta(seconds=1)) def fail_always(): raise Exception("fail") fail_always() ``` ### Operating System Ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35889

https://github.com/apache/airflow/pull/36025

9c168b76e8b0c518b75a6d4226489f68d7a6987f

fd0988369b3a94be01a994e46b7993e2d97b2028

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py"]

Infinite loop on scheduler when kubernetes state event is None along with state in database also None

### Apache Airflow version 2.7.3 ### What happened We are facing an issue using Kubernetes Executor where `process_watcher_task` that gets None state and is pushed to `result_queue`. On fetching the state from queue in `kubernetes_executor.py` it's passed to `_change_state` and if the state is None then state is fetched from database which when is also None due to some reason the `TaskInstanceState(state)` throws `ValueError` which is caught in the exception and the result is again added to the queue causing scheduler to go into infinite loop trying to set state. We need to restart the scheduler to make it run. If state is None database query too then we shouldn't set the state or to catch `ValueError` instead of generic exception handling to not retry by pushing the same result to queue. The validation was introduced by this change https://github.com/apache/airflow/commit/9556d6d5f611428ac8a3a5891647b720d4498ace#diff-11bb8713bf2f01502e66ffa91136f939cc8445839517187f818f044233414f7eR459 https://github.com/apache/airflow/blob/5d74ffb32095d534866f029d085198bc783d82c2/airflow/providers/cncf/kubernetes/executors/kubernetes_executor_utils.py#L453-L465 https://github.com/apache/airflow/blob/f3ddefccf610833dc8d6012431f372f2af03053c/airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py#L379-L393 https://github.com/apache/airflow/blob/5d74ffb32095d534866f029d085198bc783d82c2/airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py#L478-L485 ### What you think should happen instead scheduler should not retry infinitely ### How to reproduce We are not sure of the exact scenario where this reproducible. We tried running a task that returns an event which k8s returns None in rare case when pod is deleted or killed and also delete the task instance to make sure db query also returns None but we are not able to consistently get to the case that causes this. ### Operating System Ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35888

https://github.com/apache/airflow/pull/35891

9a1dceb031aa0ab44a7c996c267128bd4c61a5bf

623f9893291daa568563ff65433d797f96abc629

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/sensors/emr.py"]

EmrContainerSensor On aws Using deferrable=True get exception

### Apache Airflow version 2.7.3 ### What happened when the trigger is running the execute_complete and the status is not success getting error ``` def execute_complete(self, context, event=None): if event["status"] != "success": raise AirflowException(f"Error while running job: {event}") else: self.log.info(event["message"]) ip-10-5-55-118.eu-central-1.compute.internal *** Reading remote log from Cloudwatch log_group: airflow-tf-stg-euc1-airflow-analytics-engine-Task log_stream: dag_id=execute_model/run_id=manual__2023-11-26T12_53_43.787114+00_00/task_id=submit_emr_task/attempt=1.log. [2023-11-26, 12:58:32 UTC] {{taskinstance.py:1937}} ERROR - Task failed with exception Traceback (most recent call last): File "/usr/local/airflow/.local/lib/python3.11/site-packages/airflow/models/baseoperator.py", line 1606, in resume_execution return execute_callable(context) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/airflow/.local/lib/python3.11/site-packages/airflow/providers/amazon/aws/operators/emr.py", line 618, in execute_complete self.log.info("%s", event["message"]) ~~~~~^^^^^^^^^^^ KeyError: 'message' [2023-11-26, 12:58:32 UTC] {{standard_task_runner.py:104}} ERROR - Failed to execute job 2858894 for task submit_emr_task ('message'; 2194) ``` ### What you think should happen instead not getting the rror ### How to reproduce run EmrContainerSensor with deferrable true on aws ### Operating System aws ### Versions of Apache Airflow Providers apache-airflow-providers-amazon==8.4.0 apache-airflow-providers-apache-kafka==1.2.0 apache-airflow-providers-common-sql==1.6.1 apache-airflow-providers-ftp==3.4.2 apache-airflow-providers-http==4.5.0 apache-airflow-providers-imap==3.2.2 apache-airflow-providers-postgres==5.6.0 apache-airflow-providers-sqlite==3.4.3 ### Deployment Amazon (AWS) MWAA ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35882

https://github.com/apache/airflow/pull/35892

ae61a790a4517d0028aeba1eb02e2db89d90c084

0f5db49ec41b12d68c51f4409aa45edf4aba6a94

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/common/sql/doc/adr/0001-record-architecture-decisions.md", "airflow/providers/common/sql/doc/adr/0002-return-common-data-structure-from-dbapihook-derived-hooks.md", "scripts/ci/pre_commit/pre_commit_check_providers_subpackages_all_have_init.py"]

Document the purpose of having common.sql

### Body The Common.sql package was created in order to provide a common interface for DBApiHooks to return the data that will be universally used in a number of cases: * CommonSQL Operators and Sensors * (future) lineage data where returned hook results can follow the returned data for column lineage information This should be better documentedi in common.sql that this is the goal that common.sql achieves ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35874

https://github.com/apache/airflow/pull/36015

ef5eebdb26ca9ddb49c529625660b72b6c9b55b4

3bb5978e63f3be21a5bb7ae89e7e3ce9d06a4ab8

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/_helpers.yaml"]

git-sync-init resources is too indented

### Official Helm Chart version 1.10.0 ### Apache Airflow version 2.6.3 ### Kubernetes Version 1.27.7 ### Helm Chart configuration values.yaml ```yaml # Git sync dags: gitSync: enabled: true repo: git@git/path/to/dag.git branch: main depth: 1 # subpath within the repo where dags are located subPath: "dags" # the number of consecutive failures allowed before aborting maxFailures: 3 # credentialsSecret: airflow-github-credentials sshKeySecret: airflow-ssh-secret knownHosts: | my-known-host # interval between git sync attempts in seconds # high values are more likely to cause DAGs to become out of sync between different components # low values cause more traffic to the remote git repository wait: 60 resources: limits: memory: 100Mi requests: cpu: 50m memory: 100Mi ``` ### Docker Image customizations _No response_ ### What happened Resources get too much indented. This is due to this line https://github.com/apache/airflow/blob/a794e0d020f70aca4a0d81b953402a92a430635e/chart/templates/_helpers.yaml#L253 ### What you think should happen instead A simple change should be made to indent one level up the tree ```yaml resources: {{ toYaml .Values.dags.gitSync.resources | nindent 4 }} # not 6 ``` ### How to reproduce Inflate helm chart with given values.yaml and notice the extra indent everywhere gitsync is templated (e.g. scheduler) ```yaml apiVersion: apps/v1 kind: Deployment metadata: name: airflow-scheduler spec: template: spec: initContainers: - name: git-sync-init resources: limits: memory: 100Mi requests: cpu: 50m memory: 100Mi ``` ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35815

https://github.com/apache/airflow/pull/35824

c068089c65dff0723432536d00019c119cf54a88

39107dfeb4bdddde6de7f71029de10860844a2be

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/howto/docker-compose/docker-compose.yaml", "docs/apache-airflow/howto/docker-compose/index.rst"]

Add path to airflow.cfg in docker-compose.yml

### Description Adding a commented line in compose file like `- ${AIRFLOW_PROJ_DIR:-.}/airflow.cfg:/opt/airflow/airflow.cfg ` would save new users tons of time when customizing the configuration file. Also the current default bind `- ${AIRFLOW_PROJ_DIR:-.}/config:/opt/airflow/config` is misleading where file airflow.cfg should be stored in the container. Another solution is to simply add similar information here https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html ### Use case/motivation I was setting up email notifications and didn’t understand why SMTP server configuration from airflow.cfg didn’t work ### Related issues https://github.com/puckel/docker-airflow/issues/338 https://forum.astronomer.io/t/airflow-up-and-running-but-airflow-cfg-file-not-found/1931 ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35812

https://github.com/apache/airflow/pull/36289

aed3c922402121c64264654f8dd77dbfc0168cbb

36cb20af218919bcd821688e91245ffbe3fcfc16

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/hooks/redshift_sql.py", "docs/apache-airflow-providers-amazon/connections/redshift.rst", "tests/providers/amazon/aws/hooks/test_redshift_sql.py"]

`RedshiftSQLHook` does not work with `iam=True`

### Apache Airflow version 2.7.3 ### What happened When RedshiftSQLHook attempts to auto-fetch credentials when `iam=True`, it uses a cluster-specific approach to obtaining credentials, which fails for Redshift Serverless. ``` Traceback (most recent call last): File "/usr/local/lib/python3.11/site-packages/airflow/providers/common/sql/operators/sql.py", line 280, in execute output = hook.run( ^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/providers/common/sql/hooks/sql.py", line 385, in run with closing(self.get_conn()) as conn: ^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/providers/amazon/aws/hooks/redshift_sql.py", line 173, in get_conn conn_params = self._get_conn_params() ^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/providers/amazon/aws/hooks/redshift_sql.py", line 84, in _get_conn_params conn.login, conn.password, conn.port = self.get_iam_token(conn) ^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/airflow/providers/amazon/aws/hooks/redshift_sql.py", line 115, in get_iam_token cluster_creds = redshift_client.get_cluster_credentials( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/botocore/client.py", line 535, in _api_call return self._make_api_call(operation_name, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/site-packages/botocore/client.py", line 980, in _make_api_call raise error_class(parsed_response, operation_name) botocore.errorfactory.ClusterNotFoundFault: An error occurred (ClusterNotFound) when calling the GetClusterCredentials operation: Cluster *** not found. ``` ### What you think should happen instead The operator should establish a connection to the serverless workgroup using IAM-obtained credentials using `redshift_connector`. ### How to reproduce Create a direct SQL connection to Redshift using IAM authentication, something like: ``` {"conn_type":"redshift","extra":"{\"db_user\":\"USER\",\"iam\":true,\"user\":\"USER\"}","host":"WORKGROUP_NAME.ACCOUNT.REGION.redshift-serverless.amazonaws.com","login":"USER","port":5439,"schema":"DATABASE"} ``` Then use this connection for any `SQLExecuteQueryOperator`. The crash should occur when establishing the connection. ### Operating System Docker, `amazonlinux:2023` base ### Versions of Apache Airflow Providers This report applies to apache-airflow-providers-amazon==8.7.1, and the relevant code appears unchange in the master branch. The code I'm using worked for Airflow 2.5.2 and version 7.1.0 of the provider. ### Deployment Amazon (AWS) MWAA ### Deployment details Local MWAA runner ### Anything else The break seems to occur because the RedshiftSQLHook integrates the IAM -> credential conversion, which used to occur inside `redshift_connector.connect`. The logic is not as robust and assumes that the connection refers to a Redshift cluster rather than a serverless workgroup. It's not clear to me why this logic was pulled up and out of `redshift_connector`, but it seems like the easiest solution is just to let `redshift_connector` handle IAM authentication and not attempt to duplicate that logic in the airflow provider. ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35805

https://github.com/apache/airflow/pull/35897

3385113e277f86b5f163a3509ba61590cfe7d8cc

f6962a929b839215613d1b6f99f43511759c1e5b

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/hooks/s3.py"]

wildcard_match documented incorrectly in check_key_async method

### What do you see as an issue? The parameter is a boolean but is described as a string https://github.com/apache/airflow/blob/1e95b069483f5f26a82946d2facc8f642f5ea389/airflow/providers/amazon/aws/hooks/s3.py#L526C1-L527C1 ### Solving the problem Update the docstring with a matching description as the `_check_key_async` operator ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35766

https://github.com/apache/airflow/pull/35799

5588a956c02130b73a23ae85afdc433d737f5efd

bcb5eebd6247d4eec15bf5cce98ccedaad629661

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/hooks/pubsub.py", "airflow/providers/google/cloud/operators/pubsub.py", "tests/providers/google/cloud/hooks/test_pubsub.py", "tests/providers/google/cloud/operators/test_pubsub.py"]

Google Cloud PubSubCreateTopicOperator should support schema and message retention params

### Description Re: Google Cloud Provider -- PubSub The PubSub [Topics Create API](https://cloud.google.com/pubsub/docs/reference/rest/v1/projects.topics/create#request-body) supports the SchemaSettings and messageRetentionDuration parameters. These should also be supported via the [PubSubCreateTopicOperator](https://github.com/apache/airflow/blob/9207e7d5e5c183d2e63c3030216b14709257668e/airflow/providers/google/cloud/operators/pubsub.py#L50). Thanks! ### Use case/motivation _No response_ ### Related issues _No response_ ### Are you willing to submit a PR? - [x] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35757

https://github.com/apache/airflow/pull/35767

f4e55713840fed023c03a4e4462789aa35c892db

72ba63e0b97110a47c9882fd0a644cb0d74dcc20

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/transfers/mssql_to_gcs.py"]

Documentation Operator name diverges from real name

### What do you see as an issue? As can be seen in https://github.com/apache/airflow/blob/ce16963e9d69849309aa0a7cf978ed85ab741439/airflow/providers/google/cloud/transfers/mssql_to_gcs.py#L44 The name `MsSqlToGoogleCloudStorageOperator` should be the same as the class `MSSQLToGCSOperator` ### Solving the problem _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35705

https://github.com/apache/airflow/pull/35715

429ca47b02fac6953520308f819bd9f8dba28d45

ed6fe240c307bfadbd9856c9e435469ec9a409d8

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/operators/ec2.py", "docs/apache-airflow-providers-amazon/operators/ec2.rst", "tests/providers/amazon/aws/operators/test_ec2.py", "tests/system/providers/amazon/aws/example_ec2.py"]

Add EC2RebootInstanceOperator and EC2HibernateInstanceOperator to Amazon Provider

### Description The Amazon Airflow Provider lacks operators for "Reboot Instance" and "Hibernate Instance," two states available in the AWS UI. Achieving feature parity would provide a seamless experience, aligning Airflow with AWS capabilities. I'd like to see the EC2RebootInstanceOperator and EC2HibernateInstanceOperator added to Amazon Provider. ### Use case/motivation This enhancement ensures users can manage EC2 instances in Airflow the same way they do in the AWS UI. ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35703

https://github.com/apache/airflow/pull/35790

ca97feed1883dc8134404b017d7f725a4f1010f6

ca1202fd31f0ea8c25833cf11a5f7aa97c1db87b

python

closed

apache/airflow

https://github.com/apache/airflow

["tests/conftest.py", "tests/providers/cncf/kubernetes/executors/test_kubernetes_executor.py", "tests/providers/openlineage/extractors/test_bash.py", "tests/providers/openlineage/extractors/test_python.py", "tests/serialization/test_serde.py", "tests/utils/log/test_secrets_masker.py"]

Flaky TestSerializers.test_params test

### Body Recently we started to have a flaky TestSerializers.test_params This seems to be a problem in either the tests or implementation of `serde` - seems like discovery of classes that are serializable in some cases is not working well while the import of serde happens. It happens rarely and it's not easy to reproduce locallly, by a quick look it might be a side effect from another test - I have a feeling that when tests are run, some other test might leave behind a thread that cleans the list of classes that have been registered with serde and that cleanup happens somewhat randomly. cc: @bolkedebruin - maybe you can take a look or have an idea where it can come from - might be fastest for you as you know the discovery mechanism best and you wrote most of the tests there ? Maybe there are some specially crafted test cases somewhere that do a setup/teardown or just cleanup of the serde-registered classes that could cause such an effect? Example error: https://github.com/apache/airflow/actions/runs/6898122803/job/18767848684?pr=35693#step:5:754 Error: ``` _________________________ TestSerializers.test_params __________________________ [gw3] linux -- Python 3.8.18 /usr/local/bin/python self = <tests.serialization.serializers.test_serializers.TestSerializers object at 0x7fb113165550> def test_params(self): i = ParamsDict({"x": Param(default="value", description="there is a value", key="test")}) e = serialize(i) > d = deserialize(e) tests/serialization/serializers/test_serializers.py:173: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ o = {'__classname__': 'airflow.models.param.ParamsDict', '__data__': {'x': 'value'}, '__version__': 1} full = True, type_hint = None def deserialize(o: T | None, full=True, type_hint: Any = None) -> object: """ Deserialize an object of primitive type and uses an allow list to determine if a class can be loaded. :param o: primitive to deserialize into an arbitrary object. :param full: if False it will return a stringified representation of an object and will not load any classes :param type_hint: if set it will be used to help determine what object to deserialize in. It does not override if another specification is found :return: object """ if o is None: return o if isinstance(o, _primitives): return o # tuples, sets are included here for backwards compatibility if isinstance(o, _builtin_collections): col = [deserialize(d) for d in o] if isinstance(o, tuple): return tuple(col) if isinstance(o, set): return set(col) return col if not isinstance(o, dict): # if o is not a dict, then it's already deserialized # in this case we should return it as is return o o = _convert(o) # plain dict and no type hint if CLASSNAME not in o and not type_hint or VERSION not in o: return {str(k): deserialize(v, full) for k, v in o.items()} # custom deserialization starts here cls: Any version = 0 value: Any = None classname = "" if type_hint: cls = type_hint classname = qualname(cls) version = 0 # type hinting always sets version to 0 value = o if CLASSNAME in o and VERSION in o: classname, version, value = decode(o) if not classname: raise TypeError("classname cannot be empty") # only return string representation if not full: return _stringify(classname, version, value) if not _match(classname) and classname not in _extra_allowed: > raise ImportError( f"{classname} was not found in allow list for deserialization imports. " f"To allow it, add it to allowed_deserialization_classes in the configuration" ) E ImportError: airflow.models.param.ParamsDict was not found in allow list for deserialization imports. To allow it, add it to allowed_deserialization_classes in the configuration airflow/serialization/serde.py:246: ImportError ``` ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35699

https://github.com/apache/airflow/pull/35746

4d72bf1a89d07d34d29b7899a1f3c61abc717486

7e7ac10947554f2b993aa1947f8e2ca5bc35f23e

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/jobs/scheduler_job_runner.py", "docs/apache-airflow/core-concepts/tasks.rst"]

Enhance the docs on zombie tasks to elaborate on how they are detected

### What do you see as an issue? The documentation for zombie tasks https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html#zombie-undead-tasks is a bit abstract at the moment. There is a scope for enhancing the document by explaining how Airflow detects tasks as zombies ### Solving the problem We can enhance the documentation by translating this query https://github.com/astronomer/airflow/blob/main/airflow/jobs/scheduler_job_runner.py#L1721 to a layman readable text in our documentation. ### Anything else It might also help to add developer contribution steps to reproduce zombies locally. ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35698

https://github.com/apache/airflow/pull/35825

7c2885d21ef3ee7684b391cb2e7a553ca6821c3d

177da9016bbedcfa49c08256fdaf2fb537b97d6c

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/values.yaml"]

Airflow metrics config on the Helm Chart mismatch when `fullnameOveride` is provided

### Official Helm Chart version 1.11.0 (latest released) ### Apache Airflow version 2.6.1 ### Kubernetes Version 1.25.X ### Helm Chart configuration The default values assume the release name for statsd host, but if one uses the `fullnameOveride`, there's a mismatch of airflow metrics configuration ([here](https://github.com/apache/airflow/blob/5983506df370325f7b23a182798341d17d091a32/chart/values.yaml#L2312)) ``` config: metrics: statsd_host: '{{ printf "%s-statsd" .Release.Name }}' ``` ### Docker Image customizations _No response_ ### What happened Statsd doesn't have any airflow metrics available. ### What you think should happen instead Statsd should have airflow metrics available. ### How to reproduce Set the [`fullnameOverride`](https://github.com/apache/airflow/blob/5983506df370325f7b23a182798341d17d091a32/chart/values.yaml#L23) to be different from the helm installation. ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35678

https://github.com/apache/airflow/pull/35679

3d77149cac688429e598dd3e8a80c4da65edad01

9a6094c0d74093eff63b42ac1d313d77ebee3e60

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py", "tests/providers/cncf/kubernetes/executors/test_kubernetes_executor.py"]

Kubernetes Executor List Pods Performance Improvement

### Apache Airflow version main (development) ### What happened _list_pods function uses kube list_namespaced_pod and list_pod_for_all_namespaces kube functions. Right now, these Kube functions will get the entire pod spec though we are interested in the pod metadata alone. This _list_pods is refered in clear_not_launched_queued_tasks. try_adopt_task_instances and _adopt_completed_pods functions. When we run the airflow at large scale (with worker pods of more than > 500). The _list_pods function takes a significant amount of time (upto 15 - 30 seconds with 500 worker pods) due to unnecessary data transfer (V1PodList up to a few 10 MBs) and JSON deserialization overhead. This is blocking us from scaling the airflow to run at large scale ### What you think should happen instead Request the Pod metadata instead of entire Pod payload. It will help to reduce significant network data transfer and JSON deserialization overhead. ### How to reproduce I have reproduced the performance issue while running 500 concurrent jobs. Monitor kubernetes_executor.clear_not_launched_queued_tasks.duration and kubernetes_executor.adopt_task_instances.duration metrics. ### Operating System CentOS 6 ### Versions of Apache Airflow Providers apache-airflow-providers-cncf-kubernetes ### Deployment Other Docker-based deployment ### Deployment details Terraform based airflow deployment ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35599

https://github.com/apache/airflow/pull/36092

8d0c5d900875ce3b9dda1a86f1de534759e9d7f6

b9c574c61ae42481b9d2c9ce7c42c93dc44b9507

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/api_internal/endpoints/rpc_api_endpoint.py", "airflow/cli/commands/task_command.py", "airflow/jobs/local_task_job_runner.py", "airflow/models/taskinstance.py", "airflow/serialization/pydantic/dag.py", "airflow/serialization/pydantic/dag_run.py", "airflow/serialization/pydantic/taskinstance.py", "tests/serialization/test_pydantic_models.py"]

AIP-44 Migrate TaskInstance._run_task_by_local_task_job to Internal API

https://github.com/apache/airflow/issues/35526

https://github.com/apache/airflow/pull/35527

054904bb9a68eb50070a14fe7300cb1e78e2c579

3c0a714cb57894b0816bf39079e29d79ea0b1d0a

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/details/Dag.tsx"]

Numeric values in DAG details are incorrectly rendered as timestamps

### Discussed in https://github.com/apache/airflow/discussions/35430 <div type='discussions-op-text'> ^{Originally posted by **Gollum999** November 3, 2023} ### Apache Airflow version 2.7.2 ### What happened On the "Details" tab on a DAGs "Grid" page, all numeric DAG attributes are rendered as timestamps instead of numbers. For example:  I have noticed this behavior with the following fields, though there may be more: * Max active runs * Max active tasks * Concurrency ### What you think should happen instead Numeric fields should be rendered as numbers. ### How to reproduce Go to any DAG's Grid page. Don't select a DAG Run or Task Instance. Click the Details tab if it is not already selected. ### Operating System CentOS Stream 8 ### Versions of Apache Airflow Providers N/A ### Deployment Other ### Deployment details Standalone + self-hosted ### Anything else I think the bug is [here](https://github.com/apache/airflow/blob/0a257afd031289062c76e7b77678337e88e10b93/airflow/www/static/js/dag/details/Dag.tsx#L133): ``` // parse value for each key if date or not const parseStringData = (value: string) => Number.isNaN(Date.parse(value)) ? value : <Time dateTime={value} />; ``` `Date.parse(1)` returns a number that is not NaN. ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) </div> --- Reopen after discussion, and [additional findings](https://github.com/apache/airflow/discussions/35430#discussioncomment-7473103): - Seems like it is only affect WebKit-based browsers, and works fine in Firefox - Not all integers transformed into the dates, at least in range 13..31 keep integer type, and default value for `Max active runs`, `Max active tasks` is 16 that might be the reason why this bug remained unnoticed Example DAG for reproduce ```python import pendulum from airflow.models.dag import DAG from airflow.operators.empty import EmptyOperator num_to_dt = { 1: True, 8: True, 12: True, # 13-31 shows fine **{ix: False for ix in range(13, 32)}, 32: True, 64: True, 128: True, 256: True, } for num, convert_to_dt in num_to_dt.items(): with DAG( f"issue_35430_number_{num:03d}", start_date=pendulum.datetime(2023, 6, 1, tz="UTC"), schedule=None, catchup=False, max_active_runs=num, max_active_tasks=num, tags=["issue", "35430", "ui", f"int to dt: {convert_to_dt}", str(num)] ): EmptyOperator(task_id="empty", retries=num) ``` ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35500

https://github.com/apache/airflow/pull/35538

1e0a357252fb62bfc6a353df2499a35a8ca16beb

76ceeb4e4a4c7cbb4f0ba7cfebca4c24d2f7c3e1

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/jdbc/CHANGELOG.rst", "airflow/providers/jdbc/hooks/jdbc.py", "airflow/providers/jdbc/provider.yaml", "docs/apache-airflow-providers-jdbc/configurations-ref.rst", "docs/apache-airflow-providers-jdbc/index.rst"]

Add documentation about "providers.jdbc" "allow_driver_path_in_extra" configuration to jdbc provider.yaml

### Body The definition and description of the configuraiton is missing in provider.yaml - it should be added as for all the other provider configuration ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35499

https://github.com/apache/airflow/pull/35580

1f76986b7ba19737aba77d63bbec1ce29aff55fc

9cfb1a82f3b00fa70a7b5ce6818a9e618512de63

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/http/hooks/http.py"]

fix HttpAsyncHook PUTs with application/json

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened HttpAsyncHook with method='PUT' and data is not supported. As far as I understood PUT is not in the [list of available methods](https://github.com/apache/airflow/blob/main/airflow/providers/http/hooks/http.py#L368) for passing kwarg `json=data` ### What you think should happen instead _No response_ ### How to reproduce generate some PUT async hook runs with some data and await them: ```python http_async_hook = HttpAsyncHook(method='PUT', http_conn_id='some_conn_id') hook_run_1 = http_async_hook.run( endpoint=f'/some/endpoint/{some_data_1["id"]}', data=some_data_1 ) hook_run_2 = http_async_hook.run( endpoint=f'/some/endpoint/{some_data_2["id"]}', data=some_data_2 ) tasks = [hook_run_1, hook_run_2] responses = await asyncio.gather(*tasks) ``` ### Operating System NAME="Linux Mint" VERSION="21.2 (Victoria)" ID_LIKE="ubuntu debian"VERSION_ID="21.2" UBUNTU_CODENAME=jammy ### Versions of Apache Airflow Providers apache-airflow==2.7.0 apache-airflow-providers-http==4.6.0 ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35404

https://github.com/apache/airflow/pull/35405

61a9ab7600a856bb2b1031419561823e227331da

fd789080971a49496da0a79f3c8489cc0c1424f0

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/operators/emr.py", "tests/providers/amazon/aws/operators/test_emr_serverless.py"]

Would it be possible to add 'name' to the list of template fields for EmrServerlessStartJobOperator?

### Description We have a use case where we would like to run a job runs in EMR Serverless where the job name should contain the start date. For example: `name="[{{ ds }}] testing"`. The solution presented in [31711](https://github.com/apache/airflow/issues/31711) does not work, because command [self.name = name or self.config.pop("name", f"emr_serverless_job_airflow_{uuid4()}")](https://github.com/apache/airflow/blob/main/airflow/providers/amazon/aws/operators/emr.py#L1229) removes the `name` parameter from the `config` when initializing the `EmrServerlessStartJobOperator` operator ### Use case/motivation _No response_ ### Related issues https://github.com/apache/airflow/issues/31711 ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35341

https://github.com/apache/airflow/pull/35648

46c0f85ba6dd654501fc429ddd831461ebfefd3c

03a0b7267215ea2ac1bce6c60eca1a41f747e84b

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/extensions/init_security.py", "tests/www/views/test_session.py"]

Infinite UI redirection loop when user is changed to "inactive" while having a session opened

### Body When user is logged in with a valid session and deactivated, refreshing the browser/reusing the session leads to an infinite redirection loop (which is stopped quickly by browser detecting the situation). ## Steps to Produce: Make sure you are using two different browsers. In Browser A: Login as the normal user. In Browser B: 1. Login as admin. 2. Go to Security > List Users 3. Disable a user by unchecking this box:  4. Now in browser A, refresh the page. You'll see a message like this:  In the server logs, you'll see that a lot of requests have been made to the server.  # Expected behaviour There should be no infinite redirection, but the request for the inactive user should be rejected and the user should be redirected to the login page. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35335

https://github.com/apache/airflow/pull/35486

3fbd9d6b18021faa08550532241515d75fbf3b83

e512a72c334708ff5d839e16ba8dc5906c744570

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/details/gantt/GanttTooltip.tsx", "airflow/www/static/js/dag/details/gantt/Row.tsx"]

Incorrect queued duration for deferred tasks in gantt view

### Apache Airflow version main (development) ### What happened Gantt view calculates the diff between start date and queued at values to show queued duration. In case of deferred tasks that tasks get re-queued when the triggerer returns an event causing queued at to be greater than start date. This causes incorrect values to be shown in the UI. I am not sure how to fix this. Maybe queued duration can be not shown on the tooltip when queued time is greater than start time.  ### What you think should happen instead _No response_ ### How to reproduce 1. Trigger the below dag 2. `touch /tmp/a` to ensure triggerer returns an event. 3. Check for queued duration value in gantt view. ```python from __future__ import annotations from datetime import datetime from airflow import DAG from airflow.models.baseoperator import BaseOperator from airflow.triggers.file import FileTrigger class FileCheckOperator(BaseOperator): def __init__(self, filepath, **kwargs): self.filepath = filepath super().__init__(**kwargs) def execute(self, context): self.defer( trigger=FileTrigger(filepath=self.filepath), method_name="execute_complete", ) def execute_complete(self, context, event=None): pass with DAG( dag_id="file_trigger", start_date=datetime(2021, 1, 1), catchup=False, schedule_interval=None, ) as dag: t1 = FileCheckOperator(task_id="t1", filepath="/tmp/a") t2 = FileCheckOperator(task_id="t2", filepath="/tmp/b") t1 t2 ``` ### Operating System Ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [x] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35288

https://github.com/apache/airflow/pull/35984

1264316fe7ab15eba3be6c985a28bb573c85c92b

0376e9324af7dfdafd246e31827780e855078d68

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/atlassian/jira/notifications/__init__.py", "airflow/providers/atlassian/jira/notifications/jira.py", "airflow/providers/atlassian/jira/provider.yaml", "docs/apache-airflow-providers-atlassian-jira/index.rst", "docs/apache-airflow-providers-atlassian-jira/notifications/index.rst", "docs/apache-airflow-providers-atlassian-jira/notifications/jira-notifier-howto-guide.rst", "tests/providers/atlassian/jira/notifications/__init__.py", "tests/providers/atlassian/jira/notifications/test_jira.py"]

Add `JiraNotifier`

### Body Similar to the [notifiers we already have](https://airflow.apache.org/docs/apache-airflow-providers/core-extensions/notifications.html) we want to add `JiraNotifier` to cut a Jira ticket. This is very useful to be set with `on_failure_callback`. You can view other PRs that added similar functionality: [ChimeNotifier](https://github.com/apache/airflow/pull/32222), [SmtpNotifier](https://github.com/apache/airflow/pull/31359) ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35261

https://github.com/apache/airflow/pull/35397

ce16963e9d69849309aa0a7cf978ed85ab741439

110bb0e74451e3106c4a5567a00453e564926c50

python

closed

apache/airflow

https://github.com/apache/airflow

["tests/jobs/test_triggerer_job.py"]

Quarantined test_trigger_logging_sensitive_info test

### Body The test `airfow/tests/jobs/test_triggerrer_job.py::test_trigger_logging_sensitive_info` has a weird and race'y behaviour - that got exposed when implementing #83221. As a result it's been quarantined until we diagnose/fix it. It's very easy to reproduce the racy behaviour, but the root cause is not yet certain: 1) Enter Breeze (might be any Python version and DB but it has been confirmed with Python 3.8 and Sqlite, Postgres) 2) Run `pytest tests/jobs/test_triggerer_job.py::test_trigger_logging_sensitive_info` 3) The test fails because the logs that the test gets are empty 4) Run it again `tests/jobs/test_triggerer_job.py::test_trigger_logging_sensitive_info` 5) it succeds (and continues doing so until you restart breeze or delete `/root/airflow/.airflow_db_initialised` 6) When you delete the `/root/airflow/.airflow_db_initialised` the test fails again The presence of `/root/airflow/.airflow_db_initialised` means that airflow DB has been "reset" at least once by the tests. We have pytest fixture that checks if the file is created at least once and in case it has not been created it will run `initial_db_init` while setting up the tests. In `tests/conftest.py`. This avoids the problem that if semeone never initialized the DB, they will get strange DB errors (missing columns/indexes) and it is very confusing for first time users or when you delete local test DB. This is done in this code: ```python @pytest.fixture(autouse=True, scope="session") def initialize_airflow_tests(request): ... ,,, elif not os.path.exists(lock_file): print( "Initializing the DB - first time after entering the container.\n" "You can force re-initialization the database by adding --with-db-init switch to run-tests." ) initial_db_init() # Create pid file with open(lock_file, "w+"): pass else: ``` In some cases / some machines just commenting out `db.resetdb()` that is run inside `initial_db_init` cause the test to suceed even the first time, but this behaviour is inconsistent - sometims it does not help, which suggest that this is some kind of "startup" race of triggerer log handler - where simply adding more intialization/CPU/disk usage at the startup of tests triggers the handler to either miss or loose the connection. The error is ``` FAILED tests/jobs/test_triggerer_job.py::test_trigger_logging_sensitive_info - AssertionError: assert 'test_dag/test_run/sensitive_arg_task/-1/1 (ID 1) starting' in '' ``` And it is caused - likely - by the fact that either the log is printed too early (?) for capsys to capture it or (more likely) it is not propagated through the `handler -> in-memory -> log -> stdout` due to some race condition. Also there is mysterious stacktrace printed (but it is printed in both cases - when test works and does not work, that sugggests that this is the case and that it is connected with some race in the in-memory handler for logs, either wiht not catching or dropping logs bacause of some race at startup. I tried to debug it but did not have much luck so far - except being able to narrow it down and produce a very esily reproducible scenario. ```python tests/jobs/test_triggerer_job.py::test_trigger_logging_sensitive_info /usr/local/lib/python3.8/site-packages/_pytest/threadexception.py:73: PytestUnhandledThreadExceptionWarning: Exception in thread Thread-3 Traceback (most recent call last): File "/usr/local/lib/python3.8/threading.py", line 932, in _bootstrap_inner self.run() File "/usr/local/lib/python3.8/threading.py", line 870, in run self._target(*self._args, **self._kwargs) File "/usr/local/lib/python3.8/logging/handlers.py", line 1487, in _monitor self.handle(record) File "/usr/local/lib/python3.8/logging/handlers.py", line 1468, in handle handler.handle(record) File "/opt/airflow/airflow/utils/log/trigger_handler.py", line 104, in handle self.emit(record) File "/opt/airflow/airflow/utils/log/trigger_handler.py", line 93, in emit h = self._get_or_create_handler(record.trigger_id, record.task_instance) File "/opt/airflow/airflow/utils/log/trigger_handler.py", line 89, in _get_or_create_handler self.handlers[trigger_id] = self._make_handler(ti) File "/opt/airflow/airflow/utils/log/trigger_handler.py", line 84, in _make_handler h.set_context(ti=ti) File "/opt/airflow/airflow/utils/log/file_task_handler.py", line 185, in set_context local_loc = self._init_file(ti) File "/opt/airflow/airflow/utils/log/file_task_handler.py", line 478, in _init_file full_path = self.add_triggerer_suffix(full_path=full_path, job_id=ti.triggerer_job.id) AttributeError: 'NoneType' object has no attribute 'id' ``` cc: @dstandish @hussein-awala Also see https://github.com/apache/airflow/pull/35160#discussion_r1375463230 NIT: The test also fails when you run pytest with `-s` flag because in this case logs are printed to terminal and get coloured with ANSI colors, and the assert fails, regardless if the message is empty or good: ``` FAILED tests/jobs/test_triggerer_job.py::test_trigger_logging_sensitive_info - AssertionError: assert 'test_dag/test_run/sensitive_arg_task/-1/1 (ID 1) starting' in '[\x1b[34m2023-10-29T17:17:12.086+0000\x1b[0m] {\x1b[34mtriggerer_job_runner.py:\x1b[0m171} INFO\x1b[0m - Setting up TriggererHandlerWrapper with handler \x1b[01m<FileTaskHandler (NOTSET)>\x1b[22m\x1b[0m\n[\x1b[34m2023-10-29T17:17:12.087+0000\x1b[0m] {\x1b[34mtriggerer_job_runner.py:\x1b[0m227} INFO\x1b[0m - Setting up logging queue listener with handlers \x1b[01m[<RedirectStdHandler (NOTSET)>, - <TriggererHandlerWrapper (NOTSET)>]\x1b[22m\x1b[0m\n[\x1b[34m2023-10-29T17:17:12.102+0000\x1b[0m] {\x1b[34mtriggerer_job_runner.py:\x1b[0m595} INFO\x1b[0m - - trigger \x1b[01mtest_dag/test_run/sensitive_arg_task/-1/1 (ID 1)\x1b[22m starting\x1b[0m\n' ========================================================= 1 failed, 1 warning in 2.40s ========================================================== ``` ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35254

https://github.com/apache/airflow/pull/35427

b30e7aef91737c6bab40dd8f35784160b56650f4

d67e8e83fa543e9cfae6b096f3e9e6b6bd8ca025

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/jobs/scheduler_job_runner.py", "tests/jobs/test_scheduler_job.py"]

Mysterious hanging of the test_retry_handling_job for sqlite on self-hosted/local env

### Body ## Problem The test in question: ``` tests/jobs/test_scheduler_job.py::TestSchedulerJob::test_retry_handling_job ``` Started to timeout - mysteriously - on October 18, 2023: - only for self-hosted instances od ours (not for Public runners) - only for sqlite not for Postgres / MySQL - for local execution on Llinux it can be reproduced as well only with sqlite - for local execution on MacOS it can be reproduced as well only with sqlite ## Successes in the (recent past) The last time it's known to succeeded was https://github.com/apache/airflow/actions/runs/6638965943/job/18039945807 This test toook just 2.77s ``` 2.77s call tests/jobs/test_scheduler_job.py::TestSchedulerJob::test_retry_handling_job ``` Since then it is consistently handling for all runs on self-hosted runners of ours, while it consistenly succeeds on Public runnners. ## Reproducing locally Reproducing is super easy with breeze: ``` pytest tests/jobs/test_scheduler_job.py::TestSchedulerJob::test_retry_handling_job -s --with-db-init ``` Pressing Ctrl-C (so sending INT to all processes in the group) "unhangs" the test and it succeeds quickly (????) ## What's so strange It is super-mysterious: * There does not seem to be any significant difference in the dependencies. there are a few dependencies beign upgraded in main - but going back to the versions they are coming from does not change anything: ```diff --- /files/constraints-3.8/original-constraints-3.8.txt 2023-10-26 11:32:47.167610348 +0000 +++ /files/constraints-3.8/constraints-3.8.txt 2023-10-26 11:32:48.763610466 +0000 @@ -184 +184 @@ -asttokens==2.4.0 +asttokens==2.4.1 @@ -249 +249 @@ -confluent-kafka==2.2.0 +confluent-kafka==2.3.0 @@ -352 +352 @@ -greenlet==3.0.0 +greenlet==3.0.1 @@ -510 +510 @@ -pyOpenSSL==23.2.0 +pyOpenSSL==23.3.0 @@ -619 +619 @@ -spython==0.3.0 +spython==0.3.1 @@ -687 +687 @@ -yandexcloud==0.238.0 +yandexcloud==0.240.0 ``` * Even going back the very same image that was used in the job that succeeded does not fix the problem. It still hangs. Do this (020691f5cc0935af91a09b052de6122073518b4e is the image used in ``` docker pull ghcr.io/apache/airflow/main/ci/python3.8:020691f5cc0935af91a09b052de6122073518b4e docker tag ghcr.io/apache/airflow/main/ci/python3.8:020691f5cc0935af91a09b052de6122073518b4e ghcr.io/apache/airflow/main/ci/python3.8:latest breeze pytest tests/jobs/test_scheduler_job.py::TestSchedulerJob::test_retry_handling_job -s --with-db-init ``` Looks like there is something very strange going on with the environment of the test - something is apparently triggering a very nasty race condition (kernel version ? - this is the only idea I have) that is not yet avaiale on public runners. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35204

https://github.com/apache/airflow/pull/35221

98e7f4cc538c11871c58547a2233bfda691184e1

6f3d294645153db914be69cd2b2a49f12a18280c

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/models/dag.py", "airflow/models/dagrun.py", "tests/models/test_dag.py", "tests/providers/google/cloud/sensors/test_gcs.py"]

Relax mandatory requirement for `start_date` when `schedule=None`

### Body Currently `start_date` is mandatory parameter. For DAGs with `schedule=None` we can relax this requirement as no scheduling calculation needed so the `start_date` parameter isn't used. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/35199

https://github.com/apache/airflow/pull/35356

16585b178fab53b7c6d063426105664e55b14bfe

930f165db11e611887275dce17f10eab102f0910

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/api_connexion/openapi/v1.yaml", "airflow/www/static/js/types/api-generated.ts"]

Airflow REST API `Get tasks for DAG` returns error if DAG task has trigger rule `one_done`

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened Experienced in version 2.6.1 but appears to be an issue in the latest version too. When using the Airflow REST API `/api/v1/dags/{dag name}/tasks` to query the tasks of a DAG that contains a task with the trigger rule 'one_done' an error is returned: ``` { "detail": "'one_done' is not one of ['all_success', 'all_failed', 'all_done', 'one_success', 'one_failed', 'none_failed', 'none_skipped', 'none_failed_or_skipped', 'none_failed_min_one_success', 'dummy']\n\nFailed validating 'enum' in schema['properties']['tasks']['items']['properties']['trigger_rule']:\n {'description': 'Trigger rule.\\n'\n '\\n'\n '*Changed in version 2.2.0*&#58; '\n \"'none_failed_min_one_success' is added as a possible \"\n 'value.\\n',\n 'enum': ['all_success',\n 'all_failed',\n 'all_done',\n 'one_success',\n 'one_failed',\n 'none_failed',\n 'none_skipped',\n 'none_failed_or_skipped',\n 'none_failed_min_one_success',\n 'dummy'],\n 'type': 'string'}\n\nOn instance['tasks'][6]['trigger_rule']:\n 'one_done'", "status": 500, "title": "Response body does not conform to specification", "type": "https://airflow.apache.org/docs/apache-airflow/2.6.1/stable-rest-api-ref.html#section/Errors/Unknown" } ``` This appears to be an issue with the openapi spec, specifically the `trigger_rules` enum which is missing some valid trigger rules: https://github.com/apache/airflow/blob/0bb56315e664875cd764486bb2090e0a2ef747d8/airflow/api_connexion/openapi/v1.yaml#L4756 https://github.com/apache/airflow/blob/8531396c7c8bf1e016db10c7d32e5e19298d67e5/airflow/utils/trigger_rule.py#L23 I believe the openapi spec needs to include `one_done`. It should also be updated to include `all_done_setup_success`, `always`, and `all_skipped`. ### What you think should happen instead DAG tasks should be returned with the trigger rule `one_done` ### How to reproduce Create a DAG, add a task with a trigger rule of `one_done`. Call the Get tasks API: https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/get_tasks ### Operating System Ubuntu 22.04 ### Versions of Apache Airflow Providers _No response_ ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35186

https://github.com/apache/airflow/pull/35194

8e268940739154c21aaf40441d91dac806d21a60

e3b3d786787597e417f3625c6e9e617e4b3e5073

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/api_connexion/schemas/task_instance_schema.py", "tests/api_connexion/schemas/test_task_instance_schema.py"]

dry_run not optional in api for set task instances state

### Apache Airflow version 2.7.2 ### What happened Sent request without dry_run parameter to dags/{dag_id}/updateTaskInstancesState and got a 500 error. ### What you think should happen instead I should be able to send a request to update task instances state and get a valid response. ### How to reproduce You can see this by commenting out line 215 in tests/api_connexion/schemas/test_task_instance_schema.py and running tests. This is a similar error to #34563. ### Operating System Ubuntu 20.04 ### Versions of Apache Airflow Providers _No response_ ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35166

https://github.com/apache/airflow/pull/35167

9059f72668fb85253b8b4e3e9fb5350d621b639d

196a235358de21c62aedca1347b2527600e8ae87

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/transfers/http_to_s3.py", "airflow/providers/amazon/provider.yaml", "docs/apache-airflow-providers-amazon/transfer/http_to_s3.rst", "tests/providers/amazon/aws/transfers/test_http_to_s3.py", "tests/system/providers/amazon/aws/example_http_to_s3.py"]

Add HttpToS3Operator

### Description This operator allows users to effortlessly transfer data from HTTP sources to Amazon S3, with minimal coding effort. Whether you need to ingest web-based content, receive data from external APIs, or simply move data from a web resource to an S3 bucket, the HttpToS3Operator simplifies the process, enabling efficient data flow and integration in a wide range of use cases. ### Use case/motivation The motivation for introducing the HttpToS3Operator stems from the need to streamline data transfer and integration between HTTP sources and Amazon S3. While the SimpleHttpOperator has proven to be a valuable tool for executing HTTP requests, it has certain limitations, particularly in scenarios where users require data to be efficiently stored in an Amazon S3 bucket. ### Related issues Only issue that mentions this operator is [here](https://github.com/apache/airflow/pull/22758#discussion_r849820953) ### Are you willing to submit a PR? - [x] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35137

https://github.com/apache/airflow/pull/35176

e3b3d786787597e417f3625c6e9e617e4b3e5073

86640d166c8d5b3c840bf98e5c6db0d91392fde3

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/security/webserver.rst"]

Support for general OIDC providers or making it clear in document

### Description I tried hard to configure airflow with authentik OIDC but airflow kept complaining about empty userinfo. There are very limited tutorials online. After reading some source code of authlib, flask-appbuilder and airflow, I found in [airflow/airflow/auth/managers/fab/security_manager/override.py](https://github.com/apache/airflow/blob/ef497bc3412273c3a45f43f40e69c9520c7cc74c/airflow/auth/managers/fab/security_manager/override.py) that only a selection of providers are supported (github twitter linkedin google azure openshift okta keycloak). If the provider name is not within this list, it will always return an empty userinfo at [line 1475](https://github.com/apache/airflow/blob/ef497bc3412273c3a45f43f40e69c9520c7cc74c/airflow/auth/managers/fab/security_manager/override.py#L1475C22-L1475C22). For others who try to integrate openid connect, I would recommend read the code in [airflow/airflow/auth/managers/fab/security_manager/override.py starting from line 1398](https://github.com/apache/airflow/blob/ef497bc3412273c3a45f43f40e69c9520c7cc74c/airflow/auth/managers/fab/security_manager/override.py#L1398) ### Use case/motivation This behaviour should be documented. Otherwise, there should be a way to configure other OIDC providers like other projects that support OIDC in a general manner. ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35131

https://github.com/apache/airflow/pull/35237

554e3c9c27d76280d131d1ddbfa807d7b8006943

283fb9fd317862e5b375dbcc126a660fe8a22e11

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/models/dagrun.py", "tests/models/test_dagrun.py"]

Assigning not json serializable value to dagrun.conf cause an error in UI

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened Greetings! Recently I’ve faced a problem. It seems that assigning object, which can’t be serialized to JSON, to the dag_run.conf dict cause critical errors with UI. After executing code example in "How to reproduce": Grid representation of the DAG breaks with following result: <img width="800" alt="Pasted Graphic" src="https://github.com/apache/airflow/assets/79107237/872ccde5-500f-4484-a36c-dce6b7112286"> Browse -> DAG Runs also becomes unavailable. <img width="800" alt="Pasted Graphic 1" src="https://github.com/apache/airflow/assets/79107237/b4e3df0c-5324-41dd-96f3-032e706ab7a9"> Dag itself continues to work correctly, this affects only UI graph and dagrun/list/ I suggest to use custom dictionary with restriction on setting non json values. ### What you think should happen instead Raise an error ### How to reproduce Execute following task. Composer 2 version 2.4.2 Airflow version 2.5.3 ``` @task def test_task(**context): context['dag_run'].conf["test"] = np.int64(1234) ``` ### Operating System Ubuntu 20.04.6 LTS ### Versions of Apache Airflow Providers _No response_ ### Deployment Google Cloud Composer ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35095

https://github.com/apache/airflow/pull/35096

9ae57d023b84907c6c6ec62a7d43f2d41cb2ebca

84c40a7877e5ea9dbee03b707065cb590f872111

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/grid/index.tsx"]

Grid UI Scrollbar / Cell Click Issue

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened This is in 2.5.2, we're in the midst of upgrading to to 2.7 but haven't tested thoroughly if this happens there as we don't have the volume of historic runs. On the DAG main landing page, if you have a long DAG with multiple sub-groups, and a number of runs recorded, the UI in it's default listing of `25` previous runs, causes the scrollbar for the grid to overlay the right-most column, making it impossible to click on the cells for the right-most DAG run.  This is specifically in Firefox. It's not world-ending, just a bit annoying at times. ### What you think should happen instead The Grid area should have enough pad to the right of the rightmost column to clear the scrollbar area. You can get around this by altering the number of runs down to 5 in the dropdown above the grid, this seems to fix the issue in order access the cells. ### How to reproduce This seems to be the scenario it happens under: - DAG with long list of tasks, including sub-groups, and moderately long labels - Show 25 runs on the dag screen  ### Operating System Ubuntu 22.04 / macOS ### Versions of Apache Airflow Providers N/A ### Deployment Other ### Deployment details Custom deployment. ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35074

https://github.com/apache/airflow/pull/35346

bcb5eebd6247d4eec15bf5cce98ccedaad629661

b06c4b0f04122b5f7d30db275a20f7f254c02bef

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/core-concepts/dags.rst"]

Task dependency upstream/downstream setting error

### What do you see as an issue? I'm using Airflow 2.7.2 and following the [documentation](https://airflow.apache.org/docs/apache-airflow/2.7.2/core-concepts/dags.html#task-dependencies) to define the dependency relationship relationship between tasks. I tried the explicit way suggested by the doc but it failed. ``` first_task.set_downstream(second_task, third_task) third_task.set_upstream(fourth_task) ``` ### Solving the problem It seems it doesn't work if we want to attach multiple tasks downstream to one in a one-line manner. So I suggest currently we should break it down. Or resolve it. ``` first_task.set_downstream(second_task) first_task.set_downstream(third_task) ``` ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35062

https://github.com/apache/airflow/pull/35075

551886eb263c8df0b2eee847dd6725de78bc25fc

a4ab95abf91aaff0aaf8f0e393a2346f5529a6d2

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/ftp/hooks/ftp.py", "tests/providers/ftp/hooks/test_ftp.py"]

`FTPSHook.store_file()` change directory

### Apache Airflow version 2.7.2 ### What happened `FTPSHook.store_file()` change current directory. And second call with same directory will raise `no such file or directory` error: ``` [2023-10-18, 14:40:08 MSK] {logging_mixin.py:149} INFO - content hash uploading to `test/daily/20230601_transactions.csv.MD5` ... [2023-10-18, 14:40:08 MSK] {logging_mixin.py:149} INFO - content uploading to `test/daily/20230601_transactions.csv` ... [2023-10-18, 14:40:08 MSK] {taskinstance.py:1824} ERROR - Task failed with exception Traceback (most recent call last): File "/home/airflow/.local/lib/python3.10/site-packages/airflow/decorators/base.py", line 220, in execute return_value = super().execute(context) File "/home/airflow/.local/lib/python3.10/site-packages/airflow/operators/python.py", line 181, in execute return_value = self.execute_callable() File "/home/airflow/.local/lib/python3.10/site-packages/airflow/operators/python.py", line 198, in execute_callable return self.python_callable(*self.op_args, **self.op_kwargs) File "/opt/airflow/dags/repo/dags/integrations_alpharm_reporting_dag.py", line 59, in upload_external_shops_report upload_report_to_ftp(task_id, f'test/daily/{logical_date:YYYYMMDD}_transactions.csv') File "/opt/airflow/dags/repo/common/integrations_alpharm/utils.py", line 36, in upload_report_to_ftp from_drive2_to_ftp(get_report_drive2_path(task_id), ftp_path) File "/opt/airflow/dags/repo/common/integrations_alpharm/utils.py", line 32, in from_drive2_to_ftp ftp_hook.store_file(ftp_path, BytesIO(content)) File "/home/airflow/.local/lib/python3.10/site-packages/airflow/providers/ftp/hooks/ftp.py", line 220, in store_file conn.cwd(remote_path) File "/usr/local/lib/python3.10/ftplib.py", line 625, in cwd return self.voidcmd(cmd) File "/usr/local/lib/python3.10/ftplib.py", line 286, in voidcmd return self.voidresp() File "/usr/local/lib/python3.10/ftplib.py", line 259, in voidresp resp = self.getresp() File "/usr/local/lib/python3.10/ftplib.py", line 254, in getresp raise error_perm(resp) ftplib.error_perm: 550 test/daily: Нет такого файла или каталога ``` This happens because of this line in `store_file()` implementation: ``` conn.cwd(remote_path) conn.storbinary(f'STOR {remote_file_name}', input_handle) ``` To get around this, you have to recreate the `FTPSHook` for each uploading. It would be more convenient to simply restore directory in the `FTPSHook.store_file()` method after `storbinary` call ### What you think should happen instead _No response_ ### How to reproduce ``` ftp_hook = FTPSHook() ftp_hook.get_conn().prot_p() # https://stackoverflow.com/questions/65473257/ftpshook-airflow-522-ssl-tls-required-on-the-data-channel ftp_hook.store_file(ftp_path, BytesIO(bytes)) # OK ftp_hook.store_file(ftp_path, BytesIO(bytes)) # Raise "ftplib.error_perm: 550 test/daily: no such file or directory" ``` ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers _No response_ ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/35015

https://github.com/apache/airflow/pull/35105

5f2999eed59fb61e32aa50ef042b9cc74c07f1bf

ff30dcc1e18abf267e4381bcc64a247da3c9af35

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/_helpers.yaml", "chart/values.schema.json", "chart/values.yaml", "helm_tests/airflow_aux/test_airflow_common.py", "helm_tests/airflow_aux/test_configmap.py"]

Chart: Allow mounting DAGs to a custom path in airflow containers.

### Description Hi! I think it would be useful to have a helm chart parameter that (if set) will allow to overwrite DAGs mount path in airflow containers. Mount path is already defined in `airflow_dags_mount` [here](https://github.com/apache/airflow/blob/main/chart/templates/_helpers.yaml#L475) , but currently mountPath is hardcoded to `{{ printf "%s/dags" .Values.airflowHome }}`. ### Use case/motivation Setting this new mount path to a subfolder `/dags_folder/dags_recieved_from_git` will make it possible to: * Add some rarely changing DAGs during image building to your `dags_folder` instead of receiving them from git. * mount to your DAGs folder custom configmaps (for example, to `/dags_folder/my_custom_configmap`). Let's say your `dags_folder` is `/opt/airflow/dags`. In this case overall it will look like: ``` /opt/airflow/ └── dags ├── dags_recieved_from_git │   ├── my_frequently_changing_dag_1.py # Synced from git repo │   └── my_frequently_changing_dag_2.py # Synced from git repo ├── my_custom_configmap │   └── configmap_data.txt # Mounted from K8s config map ├── my_rarely_changing_dag_1.py # Added during image build process └── my_rarely_changing_dag_2.py # Added during image build process ``` It was just an example and I think there might be other use cases for this parameter. ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34959

https://github.com/apache/airflow/pull/35083

95980a9bc50c1accd34166ba608bbe2b4ebd6d52

ac53a9aaaba8d4250c8dfdf5e0b65b38a8a635b7

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/example_dags/example_python_operator.py"]

What are these functions and variables declared for

### What do you see as an issue? https://github.com/apache/airflow/blob/main/airflow/example_dags/example_python_operator.py#L40C1-L44C9 <img width="257" alt="Screenshot 2023-10-16 at 10 23 26 AM" src="https://github.com/apache/airflow/assets/81360154/53030408-4e33-440e-8a39-4cf6f706700a"> this two function, variable are not used ### Solving the problem I think it's ok to delete those statement ### Anything else I might be wrong, so let me know the purpose of those statement ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34956

https://github.com/apache/airflow/pull/35046

ec6d945aa31af30726d8affaa8b30af330da1085

12f4d51ce50c16605bede57d79998409e4a3ac4a

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/operators/trigger_dagrun.py", "tests/operators/test_trigger_dagrun.py"]

TriggerDagRunOperator does not trigger dag on subsequent run even with reset_dag_run=True

### Discussed in https://github.com/apache/airflow/discussions/24548 <div type='discussions-op-text'> ^{Originally posted by **don1uppa** June 16, 2022} ### Apache Airflow version 2.2.5 ### What happened I have a dag that starts another dag with a conf. I am attempting to start the initiating dag a second time with different configuration parameters. I it to start the other dag with the new parameters. ## What you think should happen instead It should use the new conf when starting the called dag ### How to reproduce See code in squsequent message ### Operating System windows and ubuntu ### Versions of Apache Airflow Providers N/A ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else **Work around for now is to delete the previous "child" dag runs.** ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md) </div>

https://github.com/apache/airflow/issues/34953

https://github.com/apache/airflow/pull/35429

ea8eabc1e7fc3c5f602a42d567772567b4be05ac

94f9d798a88e76bce3e42da9d2da7844ecf7c017

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/hooks/gcs.py"]

apache-airflow-providers-google 10.9.0 fails to list GCS objects

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened This affects Airflow 2.7.2. It appears that the 10.9.0 version of apache-airflow-providers-google fails to list objects in gcs. Example to recreate: ```shell pipenv --python 3.8 pipenv shell pip install apache-airflow==2.7.2 apache-airflow-providers-google==10.9.0 export AIRFLOW_CONN_GOOGLE_CLOUD_DEFAULT='google-cloud-platform://' ``` Then create the following python test file: ```python from airflow.providers.google.cloud.hooks.gcs import GCSHook result = GCSHook().list( bucket_name='a-test-bucket, prefix="a/test/prefix", delimiter='.csv' ) result = list(result) print(result) ``` The output if this is: ``` [] ``` In a different pipenv environment, this works when using Airflow 2.7.1 and the 10.7.0 version of the provider: ```shell pipenv --python 3.8 pipenv shell pip install apache-airflow==2.7.1 apache-airflow-providers-google==10.7.0 export AIRFLOW_CONN_GOOGLE_CLOUD_DEFAULT='google-cloud-platform://' ``` Use the same python test file as above. The output of this is a list of files as expected. [this](https://github.com/apache/airflow/commit/3fa9d46ec74ef8453fcf17fbd49280cb6fb37cef#diff-82854006b5553665046db26d43a9dfa90bec78d4ba93e2d2ca7ff5bf632fa624R832) appears to be the commit which may have broken things. The `hooks/gcs.py` file can be patched in the following way which appears to force the lazy loading to kick in: ```python print("Forcing loading....") all_blobs = list(blobs) for blob in all_blobs: print(blob.name) if blobs.prefixes: ids.extend(blobs.prefixes) else: ids.extend(blob.name for blob in all_blobs) page_token = blobs.next_page_token if page_token is None: # empty next page token break ``` Example patch file: ``` +++ gcs.py 2023-10-12 11:34:00.774206013 +0000 @@ -829,12 +829,19 @@ versions=versions, ) + print("Forcing loading....") + all_blobs = list(blobs) + + for blob in all_blobs: + print(blob.name) + if blobs.prefixes: ids.extend(blobs.prefixes) else: - ids.extend(blob.name for blob in blobs) + ids.extend(blob.name for blob in all_blobs) page_token = blobs.next_page_token + if page_token is None: # empty next page token break ``` ### What you think should happen instead The provider should be able to list files in gcs. ### How to reproduce Please see above for the steps to reproduce. ### Operating System n/a ### Versions of Apache Airflow Providers 10.9.0 of the google provider. ### Deployment Other 3rd-party Helm chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34909

https://github.com/apache/airflow/pull/34919

f3ddefccf610833dc8d6012431f372f2af03053c

5d74ffb32095d534866f029d085198bc783d82c2

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/utils/db_cleanup.py", "tests/utils/test_db_cleanup.py"]

Clear old Triggers when Triggerer is not running

### Apache Airflow version main (development) ### What happened When a deferrable operator or sensor is run without a Triggerer process, the task gets stuck in the deferred state, and will eventually fail. A banner will show up in the home page saying that the Triggerer is not running. There is no way to remove this message. In the Triggers menu, the trigger that activated is listed there, and there is no way to remove that Trigger from that list. ### What you think should happen instead If the trigger fails, the trigger should be removed from the Trigger menu, and the message should go away. ### How to reproduce The bug occurs when no Triggerer is running. In order to reproduce, 1) Run any DAG that uses a deferrable operator or sensor. 2) Allow the task to reach the deferred state. 3) Allow the task to fail on its own (i.e. timeout), or mark it as success or failure. A message will show up on the DAGs page that the Triggerer is dead. This message does not go away ``` The triggerer does not appear to be running. Last heartbeat was received 6 minutes ago. Triggers will not run, and any deferred operator will remain deferred until it times out and fails. ``` A Trigger will show up in the Triggers menu. ### Operating System ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Official Apache Airflow Helm Chart ### Deployment details Using breeze for testing ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34906

https://github.com/apache/airflow/pull/34908

ebcb16201af08f9815124f27e2fba841c2b9cd9f

d07e66a5624faa28287ba01aad7e41c0f91cc1e8

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/operators/ecs.py", "tests/providers/amazon/aws/operators/test_ecs.py"]

EcsRunTaskOperator -`date value out of range` on deferrable execution - default waiter_max_attempts

### Apache Airflow version 2.7.1 ### What happened Trying to test **EcsRunTaskOperator** in deferrable mode resulted in an unexpected error at the `_start_task()` step of the Operator's `execute` method. The return error log was `{standard_task_runner.py:104} ERROR - Failed to execute job 28 for task hello-world-defer (date value out of range; 77)` After a lot of research to understand the `date value out of range` specific error, I found [this PR](https://github.com/apache/airflow/pull/33712) in which I found from the [change log](https://github.com/apache/airflow/pull/33712/files#diff-4dba25d07d7d8c4cb47ef85e814f123c9171072b240d605fffd59b29ee3b31eb) that the `waiter_max_attempts` was switched to `1000000 * 365 * 24 * 60 * 10` (Which results in 1M years). This change cannot work properly with an internal Airflow date calculation, related to the Waiter's retries. ### What you think should happen instead Unfortunately, I haven't been able to track the error further but by changing to a lower limit of 100000 waiter_max_attempts it worked as expected. My suggestion would be to decrease the default value of **waiter_max_attempts**, maybe 1000000 (1M) retries is a valid number of retries. These results will set the default value of the expected running attempt time to 1000000 * 6 ~ 70days ### How to reproduce By keeping the default values of **EcsRunTaskOperator** while trying to use it in deferrable mode. ### Operating System Debian ### Versions of Apache Airflow Providers apache-airflow-providers-airbyte==3.3.2 apache-airflow-providers-amazon==8.7.1 apache-airflow-providers-celery==3.3.4 apache-airflow-providers-common-sql==1.7.2 apache-airflow-providers-docker==3.7.5 apache-airflow-providers-ftp==3.1.0 apache-airflow-providers-http==4.5.2 apache-airflow-providers-imap==3.3.0 apache-airflow-providers-postgres==5.6.1 apache-airflow-providers-redis==3.3.2 apache-airflow-providers-snowflake==4.4.2 apache-airflow-providers-sqlite==3.2.1 ### Deployment Other Docker-based deployment ### Deployment details - Custom Deploy using ECS and Task Definition Services on EC2 for running AIrflow services. - Extending Base Airflow Image to run on each Container Service (_apache/airflow:latest-python3.11_) ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34889

https://github.com/apache/airflow/pull/34928

b1196460db1a21b2c6c3ef2e841fc6d0c22afe97

b392f66c424fc3b8cbc957e02c67847409551cab

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/redis/redis-statefulset.yaml", "chart/values.schema.json", "chart/values.yaml", "helm_tests/other/test_redis.py"]

[helm] Redis does not include priorityClassName key

### Official Helm Chart version 1.11.0 (latest released) ### Apache Airflow version 2.x ### Kubernetes Version 1.25+ ### What happened There is no way to configure via parent values the priorityClassName for Redis, which is a workload with PV constraints that usually needs increased priority to be scheduled wherever its PV lives. ### What you think should happen instead Able to include priorityClassName ### How to reproduce Install via Helm Chart ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34878

https://github.com/apache/airflow/pull/34879

6f3d294645153db914be69cd2b2a49f12a18280c

14341ff6ea176f2325ebfd3f9b734a3635078cf4

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/executors/kubernetes_executor.py", "docs/apache-airflow/administration-and-deployment/logging-monitoring/metrics.rst"]

Scheduler is spending most of its time in clear_not_launched_queued_tasks function

### Apache Airflow version 2.7.1 ### What happened Airflow running the clear_not_launched_queued_tasks function on a certain frequency (default 30 seconds). When we run the airflow on a large Kube cluster (pods more than > 5K). Internally the clear_not_launched_queued_tasks function loops through each queued task and checks the corresponding worker pod existence in the Kube cluster. Right this existence check using list pods Kube API. The API is taking more than 1s. if there are 120 queued tasks, then it will take ~ 120 seconds (1s * 120). So, this leads the scheduler to spend most of its time in this function rather than scheduling the tasks. It leads to none of the jobs being scheduled or degraded scheduler performance. ### What you think should happen instead It would be nice to get all the airflow worker pods in a one/few batch calls rather than for each task. These batch calls helps to speed the processing of clear_not_launched_queued_tasks function call. ### How to reproduce Run the airflow on large Kube clusters (> 5K pods). Simulate the airflow to run the 100 parallel DAG runs for every minute. ### Operating System Cent OS 7 ### Versions of Apache Airflow Providers 2.3.3, 2.7.1 ### Deployment Other Docker-based deployment ### Deployment details Terraform based airflow deployment ### Anything else _No response_ ### Are you willing to submit PR? - [x] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34877

https://github.com/apache/airflow/pull/35579

5a6dcfd8655c9622f3838a0e66948dc3091afccb

cd296d2068b005ebeb5cdc4509e670901bf5b9f3

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/apache/spark/hooks/spark_submit.py", "airflow/providers/apache/spark/operators/spark_submit.py", "tests/providers/apache/spark/operators/test_spark_submit.py"]

Adding property files option in the Spark Submit command

### Description spark-submit command has one of the options to pass the properties file as argument. Instead of loading multiple key, value via --conf option, this will help to load extra properties from the file path. While we have support for most of the arguments supported in spark-submit command in SparkSubmitOperator, this one `property-files` is missing. Could that be included? ```[root@airflow ~]# spark-submit --help Usage: spark-submit [options] <app jar | python file | R file> [app arguments] Usage: spark-submit --kill [submission ID] --master [spark://...] Usage: spark-submit --status [submission ID] --master [spark://...] Usage: spark-submit run-example [options] example-class [example args] Options: --conf, -c PROP=VALUE Arbitrary Spark configuration property. --properties-file FILE Path to a file from which to load extra properties. If not specified, this will look for conf/spark-defaults.conf. ``` ### Use case/motivation Add the property-files as one of the options to pass in the SparkSubmitOperator to load the extra config properties as file ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34838

https://github.com/apache/airflow/pull/36164

3dddfb4a4ae112544fd02e09a5633961fa725a36

195abf8f7116c9e37fd3dc69bfee8cbf546c5a3f

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/cli/commands/triggerer_command.py"]

Airflow 2.7.1 can not start Scheduler & trigger

### Apache Airflow version 2.7.1 ### What happened After upgrade from 2.6.0 to 2.7.1 (try pip uninstall apache-airflow, and clear dir airflow - remove airflow.cfg), I can start scheduler & trigger with daemon. I try start with command, it can start, but logout console it killed. I try: airflow scheduler or airflow triggerer :done but kill when logout console airflow scheduler --daemon && airflow triggerer --daemon: fail, can not start scheduler & triggerer (2.6.0 run ok). but start deamon with webserver & celery worker is fine Help me ### What you think should happen instead _No response_ ### How to reproduce 1. run airflow 2.6.0 fine on ubuntu server 22.04.3 lts 2. install airflow 2.7.1 3. can not start daemon triggerer & scheduler ### Operating System ubuntu server 22.04.3 LTS ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34816

https://github.com/apache/airflow/pull/34931

b067051d3bcec36187c159073ecebc0fc048c99b

9c1e8c28307cc808739a3535e0d7901d0699dcf4

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/postgres/hooks/postgres.py", "docs/apache-airflow-providers-postgres/connections/postgres.rst"]

Airflow postgres connection field schema points to database name

### Apache Airflow version 2.7.1 ### What happened Airflow's postgres connection configuration form has a field called 'schema' which is misguiding as values mentioned here is used to refer to the database name instead of the schema name. It should be correctly named to 'database' or 'dbname' ### What you think should happen instead _No response_ ### How to reproduce create a connection on the web UI and choose connection type as postgres. Have a dag connect to an postgres server with multiple databases provide the database name in the 'schema' field of the connection form- this would work if nothing else is incorrect in the etl now change the value in the schema field of the connection form to refer to a schema- this will fail unexpectedly as the schema name field actually points to the database name. ### Operating System Windows and Linux ### Versions of Apache Airflow Providers 2.71 ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34799

https://github.com/apache/airflow/pull/34811

530ebb58b6b85444b62618684b5741b9d6dd715e

39cbd6b231c75ec432924d8508f15a4fe3c68757

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/jest-setup.js", "airflow/www/static/js/api/index.ts", "airflow/www/static/js/dag/nav/FilterBar.tsx", "airflow/www/static/js/dag/useFilters.test.tsx", "airflow/www/static/js/dag/useFilters.tsx", "airflow/www/views.py", "tests/www/views/test_views_grid.py"]

Support multi-select state filtering on grid view

### Description Replace the existing selects with multi-selects that allow you to filter multiple DAG run states and types at the same time, somewhat similar to my prototype:  ### Use case/motivation I'm not sure if it is just me, but sometimes I wish I was able to show multiple DAG run states, especially `running` and `failed`, at the same time. This would be especially helpful for busy DAGs on which I want to clear a few failed runs. Without the multi-select, if I switch from `failed` to `running` DAG runs, I need to orient myself again to find the run I just cleared (assuming there are lots of other running DAG runs). _With_ the multi-select, the DAG run I just cleared stays in the same spot and I can check the logs, while clearing some other failed runs. I'm not sure we need a multi-select for DAG run types as well. I'd tend to say no, but maybe someone else has a use-case for that. ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34795

https://github.com/apache/airflow/pull/35403

1c6bbe2841fe846957f7a1ce68eb978c30669896

9e28475402a3fc6cbd0fedbcb3253ebff1b244e3

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/hooks/dataflow.py", "tests/providers/google/cloud/hooks/test_dataflow.py"]

Dataflow job is failed when wait_until_finished=True although the state is JOB_STATE_DONE

### Apache Airflow version 2.7.1 ### What happened We currently use the DataflowHook in tasks of Airflow DAG. If we upgrade the version of apache-airflow-google-providers to 10.9.0, we got the following error although the dataflow job is completed. ``` Traceback (most recent call last): File "/opt/python3.8/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1384, in _run_raw_task self._execute_task_with_callbacks(context, test_mode) File "/opt/python3.8/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1531, in _execute_task_with_callbacks result = self._execute_task(context, task_orig) File "/opt/python3.8/lib/python3.8/site-packages/airflow/models/taskinstance.py", line 1586, in _execute_task result = execute_callable(context=context) File "xxx", line 65, in execute hook.wait_for_done( File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/common/hooks/base_google.py", line 475, in inner_wrapper return func(self, *args, **kwargs) File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataflow.py", line 1203, in wait_for_done job_controller.wait_for_done() File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataflow.py", line 439, in wait_for_done while self._jobs and not all(self._check_dataflow_job_state(job) for job in self._jobs): File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataflow.py", line 439, in <genexpr> while self._jobs and not all(self._check_dataflow_job_state(job) for job in self._jobs): File "/opt/python3.8/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/dataflow.py", line 430, in _check_dataflow_job_state raise Exception( Exception: Google Cloud Dataflow job <xxx> is in an unexpected terminal state: JOB_STATE_DONE, expected terminal state: JOB_STATE_DONE ``` ### What you think should happen instead The error message "an unexpected terminal state: JOB_STATE_DONE, expected terminal state: JOB_STATE_DONE" is strange. If the dataflow job is completed, I think it should not be failed even if the `expected_terminal_state` is not set as DataflowHook parameter. ### How to reproduce Install airflow from apache-airflow-google-providers/10.9.0. Pass wait_until_finished=True to DataflowHook and execute start_template_dataflow. ### Operating System Ubuntu 20.04.6 LTS (Focal Fossa) ### Versions of Apache Airflow Providers apache-airflow-google-providers===10.9.0 ### Deployment Google Cloud Composer ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34767

https://github.com/apache/airflow/pull/34785

3cb0870685bed221e711855cf5458c4580ec5199

8fd5ac6530df5ffd90577d3bd624ac16cdb15335

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/cli/cli_config.py", "airflow/cli/commands/variable_command.py", "tests/cli/commands/test_variable_command.py"]

CLI: Variables set should allow to set description

### Body The CLI: `airflow variables set [-h] [-j] [-v] key VALUE` https://airflow.apache.org/docs/apache-airflow/stable/cli-and-env-variables-ref.html#set_repeat1 Doesn't support adding description though column exists and we support it from Rest API: https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/post_variables **The Task:** Allow to set description from cli command ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34756

https://github.com/apache/airflow/pull/34791

c70f298ec3ae65f510ea5b48c6568b1734b58c2d

77ae1defd9282f7dd71a9a61cf7627162a25feb6

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/templates/airflow/pool_list.html", "airflow/www/views.py", "tests/www/views/test_views_pool.py"]

Expose description columns of Pools in the UI

### Body In the Pools UI we don't show the description column though we do have it: https://github.com/apache/airflow/blob/99eeb84c820c8a380721e5d40f5917a01616b943/airflow/models/pool.py#L56 and we have it in the API: https://github.com/apache/airflow/pull/19841 The task: Expose the column in the UI  ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34751

https://github.com/apache/airflow/pull/34862

8d067129d5ba20a9847d5d70b368b3dffc42fe6e

0583150aaca9452e02b8d15b613bfb2451b8e062

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/snowflake/provider.yaml", "docs/apache-airflow-providers-snowflake/index.rst", "generated/provider_dependencies.json"]

Upgrade the Snowflake Python Connector to version 2.7.8 or later

### Description As per the change made by Snowflake (affecting customers on GCP), kindly update the 'Snowflake' Python Connector version to version 2.7.8 or later. Please note all recent versions of Snowflake SQL-alchemy connector have support for this change as they use the Python Connector more recent than above. Here is the complete information on the change reasons and recommendations - https://community.snowflake.com/s/article/faq-2023-client-driver-deprecation-for-GCP-customers ### Use case/motivation If this change is not made Airflow customers on GCP will not be able to perform PUT operations to their Snowflake account. Soft Cutover enforced by Snowflake is Oct 30, 2023. Hard Cutover enforced by Google is Jan 15, 2024 https://community.snowflake.com/s/article/faq-2023-client-driver-deprecation-for-GCP-customers ### Related issues https://community.snowflake.com/s/article/faq-2023-client-driver-deprecation-for-GCP-customers ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34748

https://github.com/apache/airflow/pull/35440

7352839e851cdbee0d15f0f8ff7ee26ed821b8e3

a6a717385416a3468b09577dfe1d7e0702b5a0df

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/secrets/metadata-connection-secret.yaml", "helm_tests/other/test_keda.py"]

not using pgbouncer connection values still use pgbouncer ports/names for keda in helm chart

### Apache Airflow version 2.7.1 ### What happened I missed the rc test window last week, sorry was out of town. When you use: `values.keda.usePgbouncer: false` The settings use re-use the pgbouncer port instead of port 5432 for postgres. You can work around this by overriding the: `values.ports.pgbouncer: 5432` setting, but the database name is also incorrect and references the name of the database in the pgbouncer.ini file, which has an additional `-metadata` appended to the database connection name. ### What you think should happen instead Not use the manipulated values for the non pgbouncer connection. ### How to reproduce deploy the chart using the indicated values ### Operating System gke ### Versions of Apache Airflow Providers _No response_ ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34740

https://github.com/apache/airflow/pull/34741

1f3525fd93554e66f6c3f2d965a0dbf6dcd82724

38e6607cc855f55666b817177103585f080d6173

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/templates/airflow/trigger.html", "airflow/www/templates/appbuilder/dag_docs.html", "docs/apache-airflow/img/trigger-dag-tutorial-form.png"]

Hiding Run Id and Logical date from trigger DAG UI

### Description With the new more user friendly Trigger UI (`/dags/mydag/trigger`), one can direct more users to using Airflow UI directly. However, the first two questions a user has to answer is **Logical date** and **Run ID**, which are very confusing and in most cases make no sense to override, even for administrators these values should be rare edge cases to override.  **Is it possible to?** * Make these inputs opt-in on a per DAG level? * Global config to hide them from all DAGs? * Hide under "advanced and optional" section? Airflow version 2.7.1 ### Use case/motivation _No response_ ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34726

https://github.com/apache/airflow/pull/35284

9990443fa154e3e1e5576b68c14fe375f0f76645

62bdf11fdc49c501ccf5571ab765c51363fa1cc7

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/security/webserver.rst"]

AUTH_REMOTE_USER is gone

### Apache Airflow version 2.7.1 ### What happened We upgraded from 2.6.3 to 2.7.1 and the webserver stopped working due to our config with error: ``` ImportError: cannot import name 'AUTH_REMOTE_USER' from 'airflow.www.fab_security.manager' ``` There's a commit called [Fix inheritance chain in security manager (https://github.com/apache/airflow/pull/33901)](https://github.com/apache/airflow/commit/d3ce44236895e9e1779ea39d7681b59a25af0509) which sounds suspicious around magic security imports. ### What you think should happen instead This is [still documented](https://airflow.apache.org/docs/apache-airflow/stable/security/webserver.html#other-methods) and it wasn't noted in the changelog as removed, so it shouldn't have broken our upgrade. ### How to reproduce it's not there, so try to import it and... it's not there. for now I just switched it to importing directly `from flask_appbuilder.const import AUTH_DB, AUTH_LDAP, AUTH_OAUTH, AUTH_OID, AUTH_REMOTE_USER` ### Operating System all of them ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34720

https://github.com/apache/airflow/pull/34721

08bfa08273822ce18e01f70f9929130735022583

feaa5087e6a6b89d9d3ac7eaf9872d5b626bf1ce

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/api/useExtraLinks.ts", "airflow/www/static/js/dag/details/taskInstance/ExtraLinks.tsx", "airflow/www/static/js/dag/details/taskInstance/index.tsx"]

Extra Links not refresh by the "Auto-refresh"

### Apache Airflow version 2.7.1 ### What happened the buttons extra links are not refreshed by the "auto refresh" feature that mean if you clear a task , and the second run is in running state , the buttons under Extra Links are still linking to the first run of the task ### What you think should happen instead _No response_ ### How to reproduce run a task with a Extra Links like the `GlueJobOperator` wait for the finish clear the task , wait for it to be running , click again on the Extra link it open a new tab on the first run and not the new run ### Operating System ubuntu 22.04 ### Versions of Apache Airflow Providers _No response_ ### Deployment Other Docker-based deployment ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34623

https://github.com/apache/airflow/pull/35317

9877f36cc0dc25cffae34322a19275acf5c83662

be6e2cd0d42abc1b3099910c91982f31a98f4c3d

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/celery/executors/celery_executor_utils.py"]

BROKER_URL_SECRET Not working as of Airflow 2.7

### Apache Airflow version 2.7.1 ### What happened Hi team, In the past you can use `AIRFLOW__CELERY__BROKER_URL_SECRET` as a way to retrieve the credentials from a `SecretBackend` at runtime. However, as of Airflow 2.7, this technique appears to be broken. I believe this related to the discussion [34030 - Celery configuration elements not shown to be fetched with _CMD pattern](https://github.com/apache/airflow/discussions/34030). The irony is the pattern works when using the `config get-value` command, but does not work when using the actual `airflow celery command`. I suspect this has something to do with when the wrapper calls `ProvidersManager().initialize_providers_configuration()`. ```cmd unset AIRFLOW__CELERY__BROKER_URL AIRFLOW__CELERY__BROKER_URL_SECRET=broker_url_east airflow config get-value celery broker_url ``` This correct prints the secret from the backend! ``` redis://:<long password>@<my url>:6379/1 ``` However actually executing celery with the same methodolgy results in the default Redis ```cmd AIRFLOW__CELERY__BROKER_URL_SECRET=broker_url_east airflow celery worker ``` Relevant output ``` - ** ---------- [config] - ** ---------- .> app: airflow.providers.celery.executors.celery_executor:0x7f4110be1e50 - ** ---------- .> transport: redis://redis:6379/0 ``` Notice the redis/redis and default port with no password. ### What you think should happen instead I would expect the airflow celery command to be able to leverage the `_secret` API similar to the `config` command. ### How to reproduce You must use a secret back end to reproduce as described above. You can also do ```cmd AIRFLOW__CELERY__BROKER_URL_CMD='/usr/bin/env bash -c "echo -n ZZZ"' airflow celery worker ``` And you will see the ZZZ is disregarded ``` - ** ---------- .> app: airflow.providers.celery.executors.celery_executor:0x7f0506d49e20 - ** ---------- .> transport: redis://redis:6379/0 ``` It appears neither historical _CMD or _SECRET APIs work after the refactor to move celery to the providers. ### Operating System ubuntu20.04 ### Versions of Apache Airflow Providers Relevant ones apache-airflow-providers-celery 3.3.3 celery 5.3.4 ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else I know this has something to do with when `ProvidersManager().initialize_providers_configuration()` is executed but I don't know the right place to put the fix. ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34612

https://github.com/apache/airflow/pull/34782

d72131f952836a3134c90805ef7c3bcf82ea93e9

1ae9279346315d99e7f7c546fbcd335aa5a871cd

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/dag-processor/dag-processor-deployment.yaml", "chart/values.yaml", "helm_tests/airflow_core/test_dag_processor.py"]

helm chart doesn't support securityContext for airflow-run-airflow-migration and dag-processor init container

### Official Helm Chart version 1.10.0 (latest released) ### Apache Airflow version 2.6.3 ### Kubernetes Version 1.27 ### Helm Chart configuration helm chart doesn't support securityContext for airflow-run-airflow-migration and dag-processor init container ### Docker Image customizations _No response_ ### What happened _No response_ ### What you think should happen instead _No response_ ### How to reproduce helm chart doesn't support securityContext for airflow-run-airflow-migration and dag-processor init container. ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34595

https://github.com/apache/airflow/pull/35593

1a5a272312f31ff8481b647ea1f4616af7e5b4fe

0a93e2e28baa282e20e2a68dcb718e3708048a47

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/start.rst"]

Quick start still says Python 3.11 is not supported

### What do you see as an issue? The quick start page https://airflow.apache.org/docs/apache-airflow/stable/start.html still says that Python 3.11 is not supported, even though README.md says it is. ### Solving the problem docs/apache-airflow/start.rst should be updated: line 27 should include 3.11 as supported and line 28 removed. ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34574

https://github.com/apache/airflow/pull/34575

6a03870d1c1c5871dc9bcb8ea48039ec47676484

9b96f76ac820b3dc020286b685a236da842e407c

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/api_connexion/openapi/v1.yaml", "airflow/api_connexion/schemas/task_instance_schema.py", "airflow/www/static/js/types/api-generated.ts", "tests/api_connexion/endpoints/test_task_instance_endpoint.py"]

DryRun is not optional for patch task instance

## Summary According to the [REST api docs](https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/patch_mapped_task_instance). you can patch a task instance state. When you hit the api without sending a "dry_run" variable, you get a KeyError (This is from a server running version 2.5.3): ``` Traceback (most recent call last): File "/home/airflow/.local/lib/python3.10/site-packages/flask/app.py", line 2528, in wsgi_app response = self.full_dispatch_request() File "/home/airflow/.local/lib/python3.10/site-packages/flask/app.py", line 1825, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/airflow/.local/lib/python3.10/site-packages/flask/app.py", line 1823, in full_dispatch_request rv = self.dispatch_request() File "/home/airflow/.local/lib/python3.10/site-packages/flask/app.py", line 1799, in dispatch_request return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/decorator.py", line 68, in wrapper response = function(request) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/uri_parsing.py", line 149, in wrapper response = function(request) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/validation.py", line 196, in wrapper response = function(request) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/validation.py", line 399, in wrapper return function(request) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/response.py", line 112, in wrapper response = function(request) File "/home/airflow/.local/lib/python3.10/site-packages/connexion/decorators/parameter.py", line 120, in wrapper return function(**kwargs) File "/home/airflow/.local/lib/python3.10/site-packages/airflow/api_connexion/security.py", line 51, in decorated return func(*args, **kwargs) File "/home/airflow/.local/lib/python3.10/site-packages/airflow/utils/session.py", line 75, in wrapper return func(*args, session=session, **kwargs) File "/home/airflow/.local/lib/python3.10/site-packages/airflow/api_connexion/endpoints/task_instance_endpoint.py", line 594, in patch_task_instance if not data["dry_run"]: KeyError: 'dry_run' ``` The API docs state that dry_run is not required and that it is defaulted to false. This can be reproduced in `main` with the tests by commenting out line 1699 in [test_task_instance_endpoint.py](https://github.com/apache/airflow/blob/5b0ce3db4d36e2a7f20a78903daf538bbde5e38a/tests/api_connexion/endpoints/test_task_instance_endpoint.py#L1695-L1709)

https://github.com/apache/airflow/issues/34563

https://github.com/apache/airflow/pull/34568

f497b72fc021e33a4b8543bb0750bffbb8fe0055

a4357ca25cc3d014e50968bac7858f533e6421e4

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/views.py"]

Unable to retrieve logs for nested task group when parent is mapped

### Apache Airflow version 2.7.1 ### What happened Unable to retrieve logs for task inside task group inside mapped task group. Got `404 "TaskInstance not found"` in network requests ### What you think should happen instead _No response_ ### How to reproduce ``` from datetime import datetime from airflow import DAG from airflow.decorators import task, task_group from airflow.operators.bash import BashOperator from airflow.utils.task_group import TaskGroup with DAG("mapped_task_group_bug", schedule=None, start_date=datetime(1970, 1, 1)): @task def foo(): return ["a", "b", "c"] @task_group def bar(x): with TaskGroup("baz"): # If child task group exists, logs 404 # "TaskInstance not found" # http://localhost:8080/api/v1/dags/mapped_task_group_bug/dagRuns/manual__2023-09-21T22:31:56.863704+00:00/taskInstances/bar.baz.bop/logs/2?full_content=false # if it is removed, logs appear BashOperator(task_id="bop", bash_command="echo hi $x", env={"x": x}) bar.partial().expand(x=foo()) ``` ### Operating System debian 11 / `astro dev start` ### Versions of Apache Airflow Providers _No response_ ### Deployment Astronomer ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34535

https://github.com/apache/airflow/pull/34587

556791b13d4e4c10f95f3cb4c6079f548447e1b8

97916ba45ccf73185a5fbf50270a493369da0344

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/microsoft/azure/hooks/container_instance.py", "airflow/providers/microsoft/azure/operators/container_instances.py"]

Jobs in Azure Containers restart infinitely if logger crashes, despite retries being set to off.

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened We are using Airflow 2.5.2 to deploy python scripts in Azure containers. In cases where the logger breaks (in our case because someone used tqdm for progress bars which are known to break it), Airflow failing to find the log keeps re-provisioning the container and restarting the job infinitely, even if all is set to not retry in Airflow. This incurs costs on API calls for us and thus is an impactful problem. The issue could be because of the handling in _monitor_logging() in [Azure cointainer_instances.py line 298](https://github.com/apache/airflow/blob/main/airflow/providers/microsoft/azure/operators/container_instances.py#L298) where it changes the state to provisioning, but then doesn't do anything with it when it continues to fail to get instance_view. Maybe some form of check like if state=="Provisioning" and last_state=="Running": return 1 if retries are off could help handle it? Any insight would be appreciated. I am happy to help write a fix, if you can help me understand this flow a bit better. ### What you think should happen instead The job should fail/exit code 1 instead of reprovisioning/retrying. ### How to reproduce Run an airflow job in which a script is run in an Azure container, which employs tqdm progress bars, or otherwise overwhelms the logger and makes it fail. ### Operating System Ubuntu 20.04 ### Versions of Apache Airflow Providers apache-airflow-providers-common-sql==1.3.4 apache-airflow-providers-ftp==2.1.1 apache-airflow-providers-http==2.1.1 apache-airflow-providers-imap==2.2.2 apache-airflow-providers-microsoft-azure==3.7.2 apache-airflow-providers-postgres==4.0.1 apache-airflow-providers-sqlite==2.1.2 apache-airflow-providers-ssh==3.1.0 ### Deployment Virtualenv installation ### Deployment details Airflow running on a VM hosted in Azure. ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34516

https://github.com/apache/airflow/pull/34627

d27d0bb60b08ed8550491d4801ba5bf3c0e3da9b

546c850a43d8b00fafc11e02e63fa5caa56b4c07

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/dag-processor/dag-processor-deployment.yaml", "chart/values.yaml", "helm_tests/security/test_security_context.py"]

Add securityContexts in dagProcessor.logGroomerSidecar

### Official Helm Chart version 1.10.0 (latest released) ### Apache Airflow version 2.7.1 ### Kubernetes Version 1.26.7 ### Helm Chart configuration _No response_ ### Docker Image customizations _No response_ ### What happened When enabling `dagProcessor.logGroomerSidecar`, our OPA gatekeeper flags the `dag-processor-log-groomer` container with the appropriate non-root permissions. There is no way to set the `securityContexts` for this sidecar as it is not even enabled. ### What you think should happen instead The `securityContexts` setting for the `dag-processor-log-groomer` container should be configurable. ### How to reproduce In the Helm values, set `dagProcessor.logGroomerSidecar` to `true`. ### Anything else This problem occurs when there are OPA policies in place pertaining to strict `securityContexts` settings. ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34498

https://github.com/apache/airflow/pull/34499

6393b3515fbb7aabb1613f61204686e89479a5a0

92cc2ffd863b8925ed785d5e8b02ac38488e835e

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/serialization/serializers/datetime.py", "tests/serialization/serializers/test_serializers.py"]

`pendulum.DateTime` objects now being serialized as python objects with non-standard timezones

### Apache Airflow version 2.7.0 ### What happened We recently updated our Airflow server to 2.7.0 (from 2.6.0) and moved from a local PostGres instance to one located in AWS RDS, as well as switched from X86_64 arch to ARM64 (Amazon Graviton2 processor). We had some DAGs that passed pendulum.DateTimes as XCOMs that used to work on the old server that now fail with the following error: ``` [2023-09-19, 15:28:23 UTC] {abstractoperator.py:696} ERROR - Exception rendering Jinja template for task 'apply_bonuses_to_new_shifts', field 'op_args'. Template: (XComArg(<Task(_PythonDecoratedOperator): update_early_bird_eligible_shifts>),) Traceback (most recent call last): File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/reader.py", line 50, in read_for file_path = pytzdata.tz_path(timezone) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pytzdata/__init__.py", line 74, in tz_path raise TimezoneNotFound('Timezone {} not found at {}'.format(name, filepath)) pytzdata.exceptions.TimezoneNotFound: Timezone EDT not found at /home/airflow/dagger/venv/lib64/python3.9/site-packages/pytzdata/zoneinfo/EDT During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/abstractoperator.py", line 688, in _do_render_template_fields rendered_content = self.render_template( File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 162, in render_template return tuple(self.render_template(element, context, jinja_env, oids) for element in value) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 162, in <genexpr> return tuple(self.render_template(element, context, jinja_env, oids) for element in value) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 158, in render_template return value.resolve(context) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/session.py", line 77, in wrapper return func(*args, session=session, **kwargs) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom_arg.py", line 413, in resolve result = ti.xcom_pull( File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/session.py", line 74, in wrapper return func(*args, **kwargs) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/taskinstance.py", line 2562, in xcom_pull return XCom.deserialize_value(first) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom.py", line 693, in deserialize_value return BaseXCom._deserialize_value(result, False) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom.py", line 686, in _deserialize_value return json.loads(result.value.decode("UTF-8"), cls=XComDecoder, object_hook=object_hook) File "/usr/lib64/python3.9/json/__init__.py", line 359, in loads return cls(**kw).decode(s) File "/usr/lib64/python3.9/json/decoder.py", line 337, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) File "/usr/lib64/python3.9/json/decoder.py", line 353, in raw_decode obj, end = self.scan_once(s, idx) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/json.py", line 117, in object_hook return deserialize(dct) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/serialization/serde.py", line 253, in deserialize return _deserializers[classname].deserialize(classname, version, deserialize(value)) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/serialization/serializers/datetime.py", line 70, in deserialize return DateTime.fromtimestamp(float(data[TIMESTAMP]), tz=timezone(data[TIMEZONE])) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/__init__.py", line 37, in timezone tz = _Timezone(name, extended=extended) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/timezone.py", line 40, in __init__ tz = read(name, extend=extended) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/__init__.py", line 9, in read return Reader(extend=extend).read_for(name) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/reader.py", line 52, in read_for raise InvalidTimezone(timezone) pendulum.tz.zoneinfo.exceptions.InvalidTimezone: Invalid timezone "EDT" [2023-09-19, 15:28:23 UTC] {taskinstance.py:1943} ERROR - Task failed with exception Traceback (most recent call last): File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/reader.py", line 50, in read_for file_path = pytzdata.tz_path(timezone) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pytzdata/__init__.py", line 74, in tz_path raise TimezoneNotFound('Timezone {} not found at {}'.format(name, filepath)) pytzdata.exceptions.TimezoneNotFound: Timezone EDT not found at /home/airflow/dagger/venv/lib64/python3.9/site-packages/pytzdata/zoneinfo/EDT During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/taskinstance.py", line 1518, in _run_raw_task self._execute_task_with_callbacks(context, test_mode, session=session) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/taskinstance.py", line 1646, in _execute_task_with_callbacks task_orig = self.render_templates(context=context) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/taskinstance.py", line 2291, in render_templates original_task.render_template_fields(context) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/baseoperator.py", line 1244, in render_template_fields self._do_render_template_fields(self, self.template_fields, context, jinja_env, set()) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/session.py", line 77, in wrapper return func(*args, session=session, **kwargs) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/abstractoperator.py", line 688, in _do_render_template_fields rendered_content = self.render_template( File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 162, in render_template return tuple(self.render_template(element, context, jinja_env, oids) for element in value) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 162, in <genexpr> return tuple(self.render_template(element, context, jinja_env, oids) for element in value) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/template/templater.py", line 158, in render_template return value.resolve(context) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/session.py", line 77, in wrapper return func(*args, session=session, **kwargs) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom_arg.py", line 413, in resolve result = ti.xcom_pull( File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/session.py", line 74, in wrapper return func(*args, **kwargs) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/taskinstance.py", line 2562, in xcom_pull return XCom.deserialize_value(first) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom.py", line 693, in deserialize_value return BaseXCom._deserialize_value(result, False) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/models/xcom.py", line 686, in _deserialize_value return json.loads(result.value.decode("UTF-8"), cls=XComDecoder, object_hook=object_hook) File "/usr/lib64/python3.9/json/__init__.py", line 359, in loads return cls(**kw).decode(s) File "/usr/lib64/python3.9/json/decoder.py", line 337, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) File "/usr/lib64/python3.9/json/decoder.py", line 353, in raw_decode obj, end = self.scan_once(s, idx) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/utils/json.py", line 117, in object_hook return deserialize(dct) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/serialization/serde.py", line 253, in deserialize return _deserializers[classname].deserialize(classname, version, deserialize(value)) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/airflow/serialization/serializers/datetime.py", line 70, in deserialize return DateTime.fromtimestamp(float(data[TIMESTAMP]), tz=timezone(data[TIMEZONE])) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/__init__.py", line 37, in timezone tz = _Timezone(name, extended=extended) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/timezone.py", line 40, in __init__ tz = read(name, extend=extended) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/__init__.py", line 9, in read return Reader(extend=extend).read_for(name) File "/home/airflow/dagger/venv/lib64/python3.9/site-packages/pendulum/tz/zoneinfo/reader.py", line 52, in read_for raise InvalidTimezone(timezone) pendulum.tz.zoneinfo.exceptions.InvalidTimezone: Invalid timezone "EDT" ``` However, the DAG itself makes no mention of EDT - it does the following: ``` last_datetime.in_tz("America/New_York") ``` I've identified the issue as how these XCOMs are being serialized - one our old server, they were being serialized as ISO timestamps:  Now, however, they're being serialized like this:  This is unexpected, and also causes problems because `EDT` is not an IANA timezone, which prevents `pendulum` from deserializing it in the task that accepts this XCOM. ### What you think should happen instead _No response_ ### How to reproduce I think this is reproducible by creating a DAG that has a task that converts a `pendulum.DateTime` to `America/New_York` and passes it as an XCOM to another task. ```python from datetime import datetime, timedelta from typing import Dict, List, Optional from airflow.decorators import dag, task from airflow.utils.trigger_rule import TriggerRule from pendulum.datetime import DateTime @task() def task_one( data_interval_end: Optional[DateTime] = None, ) -> DateTime: return data_interval_end.in_tz("America/New_York") # this task will error out @task() def task_two(last_added_date: DateTime) -> None: pass @dag( default_args=default_args, schedule="*/5 * * * *", start_date=datetime(2023, 7, 25, 18, 0, 0), ) def dag() -> None: last_added_datetime = task_one() task_two(last_added_datetime) dag() ``` ### Operating System Ubuntu ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34483

https://github.com/apache/airflow/pull/34492

19450e03f534f63399bf5db2df7690fdd47b09c8

a3c06c02e31cc77b2c19554892b72ed91b8387de

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/operators/pod.py", "tests/providers/cncf/kubernetes/operators/test_pod.py"]

KubernetesPodOperator shutting down istio sidecar but not deleting pod upon failure

### Apache Airflow version 2.7.1 ### What happened I start a simple pod (one container and that's it) with the KubernetesPodOperator from the cncf.kubernetes provider. The task in my container fails (exit code non-zero). The istio sidecar is indeed terminated but the pod itself remain in an `Error` status even if the `on_finish_action` parameter is set at `"delete_pod"` and the pod is never terminated. It is expected that the pod is fully deleted, istio or not. I found that there is a difference in treatment [upon deleting the pod](https://github.com/apache/airflow/blob/5b85442fdc19947e125dcb0591bd59a53626a27b/airflow/providers/cncf/kubernetes/operators/pod.py#L824) so it might be some specific case I'm not aware of. I'll be happy to help either on documentation or fixing this small issue but I would need confirmation on what is the expected behavior. ### What you think should happen instead I think the `on_finish_action="delete_pod"` should terminate the pod, not let it hanging the `Error` state with both containers stopped. ### How to reproduce here is the simplest dag on how to reproduce on my end, note that istio is not visible here since managed cluster-wide. ```python3 from airflow import DAG from airflow.utils.dates import days_ago from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import ( KubernetesPodOperator, ) with DAG( dag_id="issue_reproduction", schedule_interval=None, start_date=days_ago(0), is_paused_upon_creation=False, max_active_runs=1, ) as dag: pod = KubernetesPodOperator( task_id="issue_reproduction", image="ubuntu", cmds=["bash", "-cx"], arguments=["exit 1"], dag=dag, security_context={ "runAsNonRoot": True, "runAsUser": 65534, "seccompProfile": {"type": "RuntimeDefault"}, }, ) ``` ### Operating System local=macos, deployments=k8s ### Versions of Apache Airflow Providers apache-airflow-providers-cncf-kubernetes==7.5.0 (Didn't see any fix that should change anything between 7.5.0 and 7.6.0 and the code I pointed to has not changed) ### Deployment Official Apache Airflow Helm Chart ### Deployment details k8s version: v1.26.3 ### Anything else The issue should be 100% reproductible provided I didn't miss any specifics. ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34482

https://github.com/apache/airflow/pull/34500

e81bb487796780705f6df984fbfed04f555943d7

fb92ff8486f21b61a840ddc4414429c3a9adfc88

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/details/graph/Node.tsx", "docs/apache-airflow/img/demo_graph_view.png"]

Graph view task name & status visibility

### Description I have had complaints from coworkers that it is harder to visibly see the status of airflow tasks in the new graph view. They miss the colored border from the old graph view that made it very clear what the status of a task was. They have also mentioned that names of the tasks feel a lot smaller and harder to read without zooming in. ### Use case/motivation _No response_ ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34455

https://github.com/apache/airflow/pull/34486

404666ded04d60de050c0984d113b594aee50c71

d0ae60f77e1472585d62a3eb44d64d9da974a199

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/databricks/hooks/databricks_base.py"]

DatabricksRunNowDeferrableOperator not working with OAuth

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened Hi, I noticed an issue with `DatabricksRunNowDeferrableOperator` and Databricks OAuth connecion. I am using Airflow 2.7.0 and databricks provider 4.5.0 (latest). I created a [Databricks connection](https://airflow.apache.org/docs/apache-airflow-providers-databricks/stable/connections/databricks.html) using [Databricks oauth](https://docs.databricks.com/en/dev-tools/authentication-oauth.html) (so with a usename, password + extra `service_principal_oauth: true`) I ran a DAG with a `DatabricksRunNowDeferrableOperator`. My databricks job is started by airflow without any issue, but the task is immediatly in failure with the following stacktrace: ``` [2023-09-18, 09:33:51 UTC] {taskinstance.py:1720} ERROR - Trigger failed: Traceback (most recent call last): File "/home/airflow/.local/lib/python3.11/site-packages/airflow/jobs/triggerer_job_runner.py", line 527, in cleanup_finished_triggers result = details["task"].result() ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/jobs/triggerer_job_runner.py", line 599, in run_trigger async for event in trigger.run(): File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/triggers/databricks.py", line 83, in run run_state = await self.hook.a_get_run_state(self.run_id) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/hooks/databricks.py", line 341, in a_get_run_state response = await self._a_do_api_call(GET_RUN_ENDPOINT, json) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/hooks/databricks_base.py", line 632, in _a_do_api_call token = await self._a_get_token() ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/hooks/databricks_base.py", line 540, in _a_get_token return await self._a_get_sp_token(OIDC_TOKEN_SERVICE_URL.format(self.databricks_conn.host)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/hooks/databricks_base.py", line 260, in _a_get_sp_token async for attempt in self._a_get_retry_object(): File "/home/airflow/.local/lib/python3.11/site-packages/tenacity/_asyncio.py", line 71, in __anext__ do = self.iter(retry_state=self._retry_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/tenacity/__init__.py", line 314, in iter return fut.result() ^^^^^^^^^^^^ File "/usr/local/lib/python3.11/concurrent/futures/_base.py", line 449, in result return self.__get_result() ^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/concurrent/futures/_base.py", line 401, in __get_result raise self._exception File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/databricks/hooks/databricks_base.py", line 262, in _a_get_sp_token async with self._session.post( File "/home/airflow/.local/lib/python3.11/site-packages/aiohttp/client.py", line 1141, in __aenter__ self._resp = await self._coro ^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/aiohttp/client.py", line 508, in _request req = self._request_class( ^^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/aiohttp/client_reqrep.py", line 310, in __init__ self.update_auth(auth) File "/home/airflow/.local/lib/python3.11/site-packages/aiohttp/client_reqrep.py", line 495, in update_auth raise TypeError("BasicAuth() tuple is required instead") TypeError: BasicAuth() tuple is required instead [2023-09-18, 09:33:51 UTC] {taskinstance.py:1943} ERROR - Task failed with exception airflow.exceptions.TaskDeferralError: Trigger failure ``` I tried the exact same DAG with `DatabricksRunNowOperator` and I have no errors. It seems like the triggerer has issue to create a connection with OAuth. ### What you think should happen instead The `DatabricksRunNowDeferrableOperator` should work with a databricks connection using OAuth. It should work exactly like the `DatabricksRunNowOperator` ### How to reproduce * Create a databricks service principal and create Client ID and client Secret * Create a databricks connection with those ID/Secret + extra `service_principal_oauth: true` * Create a DAG with a `DatabricksRunNowDeferrableOperator` * Run the DAG and you should see the error ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers ``` apache-airflow-providers-amazon==8.5.1 apache-airflow-providers-celery==3.3.2 apache-airflow-providers-cncf-kubernetes==7.4.2 apache-airflow-providers-common-sql==1.7.0 apache-airflow-providers-daskexecutor==1.0.0 apache-airflow-providers-databricks==4.5.0 apache-airflow-providers-docker==3.7.3 apache-airflow-providers-elasticsearch==5.0.0 apache-airflow-providers-ftp==3.5.0 apache-airflow-providers-google==10.6.0 apache-airflow-providers-grpc==3.2.1 apache-airflow-providers-hashicorp==3.4.2 apache-airflow-providers-http==4.5.0 apache-airflow-providers-imap==3.3.0 apache-airflow-providers-microsoft-azure==6.2.4 apache-airflow-providers-mysql==5.2.1 apache-airflow-providers-odbc==4.0.0 apache-airflow-providers-openlineage==1.0.1 apache-airflow-providers-postgres==5.6.0 apache-airflow-providers-redis==3.3.1 apache-airflow-providers-sendgrid==3.2.1 apache-airflow-providers-sftp==4.5.0 apache-airflow-providers-slack==7.3.2 apache-airflow-providers-snowflake==4.4.2 apache-airflow-providers-sqlite==3.4.3 apache-airflow-providers-ssh==3.7.1 ``` ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! Why not, **but I have currently no idea of the reason** ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34450

https://github.com/apache/airflow/pull/34590

966ce1ee47696c1725e854896601089bcc37818f

a1ef2322304ea6ff9bc9744668c011ad13fad056

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/operators/emr.py"]

EMR operators doesn't use `AirflowProviderDeprecationWarning`

### Body Use `AirflowProviderDeprecationWarning` as warning source in EMR operators and change stacklevel to 2: https://github.com/apache/airflow/blob/05036e619c0c6dafded1451daac4e07e20aee33f/airflow/providers/amazon/aws/operators/emr.py#L380-L384 https://github.com/apache/airflow/blob/05036e619c0c6dafded1451daac4e07e20aee33f/airflow/providers/amazon/aws/operators/emr.py#L373-L377 https://github.com/apache/airflow/blob/05036e619c0c6dafded1451daac4e07e20aee33f/airflow/providers/amazon/aws/operators/emr.py#L264-L268 https://github.com/apache/airflow/blob/05036e619c0c6dafded1451daac4e07e20aee33f/airflow/providers/amazon/aws/operators/emr.py#L257-L261 ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34425

https://github.com/apache/airflow/pull/34453

c55fd77f76aafc76463e3dd2a6ecaa29e56bd967

7de7149bc6d2d649b91cf902801b92300618db4a

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/triggers/pod.py"]

Consolidate the warning stacklevel in KubernetesPodTrigger

### Body Use stacklevel 2 instead of the default 1: https://github.com/apache/airflow/blob/1b122c15030e99cef9d4ff26d3781a7a9d6949bc/airflow/providers/cncf/kubernetes/triggers/pod.py#L103-L106 ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34424

https://github.com/apache/airflow/pull/35079

bc4a22c6bd8096e7b62147031035cb14896fe934

4c8c85ccc2e52436276f692964abff4a3dc8495d

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/utils/pod_manager.py"]

Consolidate the waning stacklevel in K8S pod_manager

### Body Use stacklevel 2 instead of the default 1: https://github.com/apache/airflow/blob/b5057e0e1fc6b7a47e38037a97cac862706747f0/airflow/providers/cncf/kubernetes/utils/pod_manager.py#L361-L365 ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34423

https://github.com/apache/airflow/pull/34530

06965e604cef4d6a932258a5cd357d164a809730

08729eddbd7414b932a654763bf62c6221a0e397

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/ssh/hooks/ssh.py"]

Consolidate stacklevel in ssh hooks warning

### Body SSHHook uses the default stacklevel (1) in its deprecation warning, it should be 2: https://github.com/apache/airflow/blob/b11525702c72cb53034aa29ccd6d0e1161ac475c/airflow/providers/ssh/hooks/ssh.py#L433-L439 https://github.com/apache/airflow/blob/b11525702c72cb53034aa29ccd6d0e1161ac475c/airflow/providers/ssh/hooks/ssh.py#L369-L374 https://github.com/apache/airflow/blob/b11525702c72cb53034aa29ccd6d0e1161ac475c/airflow/providers/ssh/hooks/ssh.py#L232-L238 ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34422

https://github.com/apache/airflow/pull/34527

a1bd8719581f2ef1fb25aeaa89e3520e8bc81172

06965e604cef4d6a932258a5cd357d164a809730

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/ssh/operators/ssh.py"]

Consolidate stacklevel in ssh operator warning

### Body SSHOperator uses the default `stacklevel` (1) in its deprecation warning, it should be 2: https://github.com/apache/airflow/blob/a59076eaeed03dd46e749ad58160193b4ef3660c/airflow/providers/ssh/operators/ssh.py#L139-L143 ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34421

https://github.com/apache/airflow/pull/35151

4767f48a3b4537092e62fc2f91ec832dd560db72

543db7004ee593605e250265b0722917cef296d3

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/templates-ref.rst"]

var.json.get not working correctly with nested JSON objects

### Apache Airflow version 2.7.1 ### What happened According to [Airflow Documentation on Airflow Variables in Templates](https://airflow.apache.org/docs/apache-airflow/stable/templates-ref.html#airflow-variables-in-templates) there are two ways of accessing the JSON variables in templates: - using the direct `{{ var.json.my_dict_var.key1 }}` - using a getter with a default fallback value `{{{{ var.json.get('my.dict.var', {'key1': 'val1'}) }}` However, only the first approach works for nested variables, as demonstrated in the example. Or is it me not understanding this documentation? Alternatively it could get updated to make it clearer. ### What you think should happen instead _No response_ ### How to reproduce The following test demonstrates the issue: ``` from datetime import datetime, timezone import pytest from airflow import DAG from airflow.models.baseoperator import BaseOperator from airflow.models.dag import DAG from airflow.utils import db from airflow.utils.state import DagRunState from airflow.utils.types import DagRunType from pytest import MonkeyPatch from airflow.models import Variable class TemplatedBaseOperator(BaseOperator): template_fields = BaseOperator.template_fields + ( "templated_direct", "templated_getter") def __init__( self, *args, **kwargs, ): self.templated_direct = "{{ var.json.somekey.somecontent }}" self.templated_getter = "{{ var.json.get('somekey.somecontent', false) }}" super().__init__( *args, **kwargs, ) @pytest.fixture() def reset_db(): db.resetdb() yield @pytest.fixture def dag() -> DAG: with DAG( dag_id="templating_dag", schedule="@daily", start_date=datetime(2023, 1, 1, tzinfo=timezone.utc), render_template_as_native_obj=True, ) as dag: TemplatedBaseOperator( task_id="templating_task" ) return dag def test_templating(dag: DAG, reset_db: None, monkeypatch: MonkeyPatch): """Test if the templated values get intialized from environment variables when rendered""" # setting env variables monkeypatch.setenv( "AIRFLOW_VAR_SOMEKEY", '{"somecontent": true}', ) dagrun = dag.create_dagrun( state=DagRunState.RUNNING, execution_date=datetime(2023, 1, 1, tzinfo=timezone.utc), data_interval=(datetime(2023, 1, 1, tzinfo=timezone.utc), datetime(2023, 1, 7, tzinfo=timezone.utc)), start_date=datetime(2023, 1, 7, tzinfo=timezone.utc), run_type=DagRunType.MANUAL, ) ti = dagrun.get_task_instance(task_id="templating_task") ti.task = dag.get_task(task_id="templating_task") rendered_template = ti.render_templates() assert {'somecontent': True} == Variable.get("somekey", deserialize_json=True) assert getattr(rendered_template, "templated_direct") == True # the following test is failing, getting default "False" instead of Variable 'True' assert getattr(rendered_template, "templated_getter") == True ``` ### Operating System Ubuntu 22.04.3 LTS ### Versions of Apache Airflow Providers _No response_ ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34394

https://github.com/apache/airflow/pull/34411

b23d3f964b2699d4c7f579e22d50fabc9049d1b6

03db0f6b785a4983c09d6eec7433cf28f7759610

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/cncf/kubernetes/utils/pod_manager.py", "kubernetes_tests/test_kubernetes_pod_operator.py", "tests/providers/cncf/kubernetes/utils/test_pod_manager.py"]

Kubernetes provider - Error parsing timestamp in logs

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened We are experiencing issue with error log message being shown in every task that is KubernetesPodOperator. We get ``` {pod_manager.py:558} ERROR - Error parsing timestamp (no timestamp in message ''). Will continue execution but won't update timestamp ``` after execution is finished in every task. ### What you think should happen instead No such error should be shown ### How to reproduce ```python '''doc''' from kubernetes.client import models as k8s from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator from airflow.models import DAG import pendulum import datetime DAG_ID = 'test-dag' default_args = { 'owner': 'owner', 'depends_on_past': False, 'start_date': datetime.datetime(2023, 9, 15), 'sla': datetime.timedelta(hours = 1), 'execution_timeout': datetime.timedelta(hours = 1, minutes = 30), 'email_on_failure': False, 'email_on_retry': False, 'retries': 3, 'retry_delay': datetime.timedelta(minutes = 1), 'retry_exponential_backoff': True, 'max_retry_delay': datetime.timedelta(minutes = 10), 'max_active_tis_per_dag': 8, 'pool': 'SomePool', 'get_logs': True, } dag = DAG( dag_id = DAG_ID, doc_md = __doc__, tags = ['tag'], schedule = AfterWorkdayTimetable(pendulum.Time(2, 0)), default_args = default_args, catchup = True, dagrun_timeout = datetime.timedelta(hours = 6), max_active_runs = 5 ) task = KubernetesPodOperator( affinity = { 'nodeAffinity': { 'requiredDuringSchedulingIgnoredDuringExecution': { 'nodeSelectorTerms': [ {'matchExpressions': [{'key': 'dataDriveSizeClass', 'operator': 'In', 'values': ['large', 'medium']}]} ] } } }, priority_class_name = 'l3', namespace = 'some--namespace', in_cluster = True, image_pull_policy = 'IfNotPresent', container_resources = k8s.V1ResourceRequirements( requests = {'memory': '150Mi', 'cpu': '1m'}, limits = {'memory': '512Mi', 'cpu': '500m'}, ), cmds = [ 'sleep', '10' ], dag = dag, task_id = 'kubernetes_task', labels = { 'runner': 'airflow', }, annotations = {'version': '1.0.0'}, image = 'ubuntu', env_vars = [k8s.V1EnvVar(name = name, value = value) for name, value in {'name':'value'}.items()] ) task ``` ### Operating System Debian GNU/Linux 10 (buster) ### Versions of Apache Airflow Providers ``` apache-airflow-providers-amazon==8.4.0 apache-airflow-providers-cncf-kubernetes==7.5.1 apache-airflow-providers-common-sql==1.6.1 apache-airflow-providers-ftp==3.4.2 apache-airflow-providers-http==4.5.0 apache-airflow-providers-imap==3.2.2 apache-airflow-providers-postgres==5.6.0 apache-airflow-providers-slack==7.3.2 apache-airflow-providers-sqlite==3.4.3 ``` ### Deployment Other Docker-based deployment ### Deployment details Kubernetes 1.26.5 airflow 2.6.3 python 3.10.12 LocalExecutor Database: Postgres 14.6 ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34388

https://github.com/apache/airflow/pull/34412

90628e480a61e7b4991d42a536b79e634dee7c12

4234d8db7e4a51683f8236270c87375cf80ba3f4

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/migrations/versions/0129_2_8_0_add_clear_number_to_dag_run.py", "airflow/models/dagrun.py", "docs/apache-airflow/img/airflow_erd.sha256", "docs/apache-airflow/img/airflow_erd.svg"]

Default value for clear_number column not applied via sqlalchemy

### Apache Airflow version main (development) ### What happened The SQL query generated does not have a default integer as 0 in the migration causing failure. ``` INFO [alembic.runtime.migration] Running upgrade 405de8318b3a -> 375a816bbbf4, add new field 'clear_number' to dagrun Traceback (most recent call last): File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 1910, in _execute_context self.dialect.do_execute( File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/default.py", line 736, in do_execute cursor.execute(statement, parameters) psycopg2.errors.NotNullViolation: column "clear_number" of relation "dag_run" contains null values The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/bin/airflow", line 8, in <module> sys.exit(main()) ^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/__main__.py", line 59, in main args.func(args) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/cli/cli_config.py", line 49, in command return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/utils/cli.py", line 114, in wrapper return f(*args, **kwargs) ^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/utils/providers_configuration_loader.py", line 55, in wrapped_function return func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/cli/commands/db_command.py", line 129, in migratedb db.upgradedb( File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/utils/session.py", line 79, in wrapper return func(*args, session=session, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/utils/db.py", line 1627, in upgradedb command.upgrade(config, revision=to_revision or "heads") File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/command.py", line 382, in upgrade script.run_env() File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/script/base.py", line 578, in run_env util.load_python_file(self.dir, "env.py") File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/util/pyfiles.py", line 109, in load_module_py spec.loader.exec_module(module) # type: ignore ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "<frozen importlib._bootstrap_external>", line 940, in exec_module File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/migrations/env.py", line 117, in <module> run_migrations_online() File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/migrations/env.py", line 111, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/runtime/environment.py", line 922, in run_migrations self.get_context().run_migrations(**kw) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/runtime/migration.py", line 624, in run_migrations step.migration_fn(**kw) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/airflow/migrations/versions/0129_2_8_0_add_clear_number_to_dag_run.py", line 41, in upgrade with op.batch_alter_table("dag_run") as batch_op: File "/opt/homebrew/Cellar/[email protected]/3.11.5/Frameworks/Python.framework/Versions/3.11/lib/python3.11/contextlib.py", line 144, in __exit__ next(self.gen) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/operations/base.py", line 375, in batch_alter_table impl.flush() File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/operations/batch.py", line 113, in flush fn(*arg, **kw) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/ddl/impl.py", line 322, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/alembic/ddl/impl.py", line 193, in _exec return conn.execute( # type: ignore[call-overload] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/future/engine.py", line 280, in execute return self._execute_20( ^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 1710, in _execute_20 return meth(self, args_10style, kwargs_10style, execution_options) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/sql/ddl.py", line 80, in _execute_on_connection return connection._execute_ddl( ^^^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 1477, in _execute_ddl ret = self._execute_context( ^^^^^^^^^^^^^^^^^^^^^^ File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 1953, in _execute_context self._handle_dbapi_exception( File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 2134, in _handle_dbapi_exception util.raise_( File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/util/compat.py", line 211, in raise_ raise exception File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/base.py", line 1910, in _execute_context self.dialect.do_execute( File "/Users/abhishekbhakat/Codes/Turbine/my_local_airflow/airflowenv/lib/python3.11/site-packages/sqlalchemy/engine/default.py", line 736, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.IntegrityError: (psycopg2.errors.NotNullViolation) column "clear_number" of relation "dag_run" contains null values [SQL: ALTER TABLE dag_run ADD COLUMN clear_number INTEGER NOT NULL] (Background on this error at: https://sqlalche.me/e/14/gkpj) ``` SQLAlchemy version was 1.4.49. ### What you think should happen instead The query generated should be `ALTER TABLE dag_run ADD COLUMN clear_number INTEGER NOT NULL DEFAULT 0;` ### How to reproduce Upgraded from airflow 2.7.1 to main-branch and ran `airflow db migrate` ### Operating System MacOS 13 ### Versions of Apache Airflow Providers Not applicable ### Deployment Virtualenv installation ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34332

https://github.com/apache/airflow/pull/34344

43852d4efe32d9c56fff11749fa5a8eacd8d1a53

840c0d79e09533f7e786a5c496a9008363284da7

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/datasets/manager.py", "airflow/listeners/listener.py", "airflow/listeners/spec/dataset.py", "airflow/models/dag.py", "docs/apache-airflow/administration-and-deployment/listeners.rst", "tests/datasets/test_manager.py", "tests/listeners/dataset_listener.py", "tests/listeners/test_dataset_listener.py"]

Listeners for Datasets

### Description Add listeners for Datasets (events) ### Use case/motivation As Airflow administrators, we would like to trigger some external processes based on all datasets being created/updated by our users. We came across the listeners for the dag runs and task instances (which are also useful), but are still missing listeners for datasets. ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34327

https://github.com/apache/airflow/pull/34418

31450bbe3c91246f3eedd6a808e60d5355d81171

9439111e739e24f0e3751350186b0e2130d2c821

python

closed

apache/airflow

https://github.com/apache/airflow

["chart/templates/cleanup/cleanup-cronjob.yaml", "chart/values.yaml", "helm_tests/security/test_security_context.py"]

securityContext value for the cleanup container is not set properly

### Official Helm Chart version 1.10.0 (latest released) ### Apache Airflow version 2.6.3 ### Kubernetes Version 1.24.10 ### Helm Chart configuration ```yaml cleanup: enabled: true securityContexts: container: allowPrivilegeEscalation: false ``` ### Docker Image customizations No ### What happened Although securityContext value for cleanup container was set in values.yaml file, the value was not set in container. ### What you think should happen instead _No response_ ### How to reproduce ```bash helm repo add apache-airflow https://airflow.apache.org helm pull apache-airflow/airflow --version 1.10.0 tar -zxvf ./airflow-1.10.0.tgz cd airflow helm template airflow . \ --set cleanup.enabled=true \ --set cleanup.securityContexts.container.allowPrivilegeEscalation=false \ | grep "# Source: airflow/templates/cleanup/cleanup-cronjob.yaml" -A99 ``` ### Anything else There is no <code>containerSecurityContext</code> in cleanup-cronjob.yaml. https://github.com/apache/airflow/blob/eed2901e877b32a211e0e74bc9d69fc11e552f2a/chart/templates/cleanup/cleanup-cronjob.yaml#L23-L28 But we can see <code>containerSecurityContext</code> in webserver-deployment.yaml https://github.com/apache/airflow/blob/eed2901e877b32a211e0e74bc9d69fc11e552f2a/chart/templates/webserver/webserver-deployment.yaml#L29 ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34298

https://github.com/apache/airflow/pull/34351

de92a81f002e6c1b3e74ad9d074438b65acb87b6

847d2c3b37210113dce3cf5da0344a2fcfcd9d12

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/docker/operators/docker.py", "docs/spelling_wordlist.txt", "tests/providers/docker/operators/test_docker.py"]

DockerOperator Expose `ulimits` create host config parameter

### Description This issue should be resolved by simply adding `ulimits` parameter to `DockerOperator` that is directly passed to [`create_host_config`](https://docker-py.readthedocs.io/en/stable/api.html#docker.api.container.ContainerApiMixin.create_host_config). ### Use case/motivation Currently applying custom `ulimits` is not possible with `DockerOperator`, making it necessary to do some hacky entrypoint workarounds instead. By implementing this feature, one should be able to set Ulimits directly by giving a list of [`Ulimit`](https://docker-py.readthedocs.io/en/stable/api.html#docker.types.Ulimit)-instances to `DockerOperator`. ### Related issues _No response_ ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34283

https://github.com/apache/airflow/pull/34284

3fa9d46ec74ef8453fcf17fbd49280cb6fb37cef

c668245b5740279c08cbd2bda1588acd44388eb3

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/security.py"]

access control logs

### Apache Airflow version 2.7.1 ### What happened After upgrading to 2.7.1 from 2.5.3 we encountered those logs in the scheduler logs: ```[2023-09-11T05:52:34.865+0000] {logging_mixin.py:151} INFO - [2023-09-11T05:52:34.865+0000] {security.py:708} INFO - Not syncing DAG-level permissions for DAG 'DAG:<dag_name>' as access control is unset.``` Since we have multiple DAGs for the same DAG file (>40), and the DAG processor is running on a high period, we have a lot of redundant logs, which creates more unnecessary data to store. Adding the setting `access_control={}` did not change the logs. We don't want to manage the access control for each DAG, as we have a high-level approach, but we also don't want these logs. ### What you think should happen instead Add some settings to allow avoid printing this info logs about sync permissions ### How to reproduce Airflow Version - 2.7.1 Python - 3.11.5 Create a DAg without setting access_control and watch logs. e.g. `XXX/_data/scheduler/2023-09-11/dag_name.py.log` ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers _No response_ ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34265

https://github.com/apache/airflow/pull/34268

f0467c9fd65e7146b44fc8f9fccb9ad750592371

8035aee8da3c4bb7b9c01cfdc7236ca01d658bae

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/cli/commands/connection_command.py"]

Standardise output of "airflow connections export" to those of "airflow variables export" and "airflow users export"

### Description The three commands: ``` airflow users export /opt/airflow/dags/users.json && airflow variables export /opt/airflow/dags/variables.json && airflow connections export /opt/airflow/dags/connections.json ``` give back: ``` 7 users successfully exported to /opt/airflow/dags/users.json 36 variables successfully exported to /opt/airflow/dags/variables.json Connections successfully exported to /opt/airflow/dags/connections.json. ``` ### Use case/motivation Standardise output of "airflow connections export" to those of "airflow variables export" and "airflow users export" ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34232

https://github.com/apache/airflow/pull/34640

3189ebee181beecd5a1243a4998bc355b648dc6b

a5f5e2fc7f7b7f461458645c8826f015c1fa8d78

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/models/dag.py"]

100+ DAGs fail to import after update to 2.7.1 due to "params without default values"

### Apache Airflow version 2.7.1 ### What happened 120 DAGs broke when I updated to Airflow 2.7.1. I had to revert to 2.7.0 again, so the tests below are from a local deployment. The error message is the same for all DAGs: ```python Broken DAG: [/opt/airflow/dags/dag-name.py] Traceback (most recent call last): File "/home/airflow/.local/lib/python3.11/site-packages/airflow/models/dag.py", line 640, in __init__ self.validate_schedule_and_params() File "/home/airflow/.local/lib/python3.11/site-packages/airflow/models/dag.py", line 3289, in validate_schedule_and_params raise AirflowException( airflow.exceptions.AirflowException: DAG Schedule must be None, if there are any required params without default values ``` After testing, I found that if I change the blob_prefix param to "" instead of None, the DAG imports successfully. I have various other params which are None that I will probably need to assign default values for (in reality, the function which Airflow runs handles cases if the value is None, but I guess I need to add a default in the DAG). All 120 DAGs with errors had a field like this in the "params" dictionary I pass to Airflow params. ```python params = { "exclude_pattern": "*errors*", "blob_prefix": None, ``` ### What you think should happen instead These are legacy DAGs which have run for a long time without changes (old Airflow instance), so I did not expect an upgrade to break them. ### How to reproduce I believe the root cause is passing a param with the value None to the DAG params: ```python params = { subfolder=None, conn_id="gcs_conn_id", } @dag( dag_id="dag-example", start_date=datetime(2023, 2, 2, tz="America/New_York"), schedule="41 2 * * *", params=params, ) ``` ### Operating System Ubuntu 22.04 ### Versions of Apache Airflow Providers Providers info apache-airflow-providers-celery | 3.3.3 apache-airflow-providers-common-sql | 1.7.1 apache-airflow-providers-docker | 3.7.4 apache-airflow-providers-ftp | 3.5.1 apache-airflow-providers-google | 10.7.0 apache-airflow-providers-http | 4.5.1 apache-airflow-providers-imap | 3.3.1 apache-airflow-providers-microsoft-azure | 6.3.0 apache-airflow-providers-mysql | 5.3.0 apache-airflow-providers-odbc | 4.0.0 apache-airflow-providers-openlineage | 1.0.2 apache-airflow-providers-postgres | 5.6.0 apache-airflow-providers-redis | 3.3.1 apache-airflow-providers-sftp | 4.6.0 apache-airflow-providers-sqlite | 3.4.3 apache-airflow-providers-ssh | 3.7.2 ### Deployment Other Docker-based deployment ### Deployment details Docker Swarm using docker stack deploy ### Anything else DAGs fail to import when deployed on 2.7.1 ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34227

https://github.com/apache/airflow/pull/34248

13d2f4a7f1e347607122b65d5b45ef0504a8640b

3e340797ab98a06b51b2930610b0abb0ad20a750

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/api_connexion/endpoints/event_log_endpoint.py", "airflow/api_connexion/openapi/v1.yaml", "airflow/www/static/js/types/api-generated.ts", "tests/api_connexion/endpoints/test_event_log_endpoint.py"]

Add filters to get event logs

### Description In the REST API, there is an endpoint to get event (audit) logs. It has sorting and pagination but not filtering. It would be useful to filter by `when` (before and after), `dag_id`, `task_id`, `owner`, `event` <img width="891" alt="Screenshot 2023-09-08 at 1 30 35 PM" src="https://github.com/apache/airflow/assets/4600967/4280b9ed-2c73-4a9c-962c-4ede5cb140fe"> ### Use case/motivation _No response_ ### Related issues _No response_ ### Are you willing to submit a PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34210

https://github.com/apache/airflow/pull/34417

db89a33b60f46975850e3f696a7e05e61839befc

3189ebee181beecd5a1243a4998bc355b648dc6b

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/amazon/aws/operators/emr.py", "airflow/providers/amazon/aws/triggers/emr.py", "airflow/providers/amazon/aws/waiters/emr.json", "tests/providers/amazon/aws/hooks/test_emr.py", "tests/providers/amazon/aws/triggers/test_emr.py", "tests/providers/amazon/aws/triggers/test_emr_trigger.py", "tests/providers/amazon/aws/waiters/test_custom_waiters.py"]

EmrAddStepsOperator does not work with `deferrable=True`

### Apache Airflow version 2.7.0 ### What happened When using the `EmrAddStepsOperator`, trying to use `deferrable=True` causes an exception from the Amazon provider: ``` [2023-09-07, 16:02:56 UTC] {taskinstance.py:1720} ERROR - Trigger failed: Traceback (most recent call last): File "/home/***/.local/lib/python3.11/site-packages/***/jobs/triggerer_job_runner.py", line 527, in cleanup_finished_triggers result = details["task"].result() ^^^^^^^^^^^^^^^^^^^^^^^^ File "/home/***/.local/lib/python3.11/site-packages/***/jobs/triggerer_job_runner.py", line 599, in run_trigger async for event in trigger.run(): File "/home/***/.local/lib/python3.11/site-packages/***/providers/amazon/aws/triggers/emr.py", line 74, in run for attempt in range(1, 1 + self.max_attempts): ~~^~~~~~~~~~~~~~~~~~~ TypeError: unsupported operand type(s) for +: 'int' and 'str' ``` The problem seems to stem from the `max_attempts` value being stored as an `int` when the `EmrAddStepsTrigger` class is instantiated, but when `run` is called later, it becomes a `str`. The simple fix is to wrap the access with `int()`, but I'm not sure if that's the _correct_ fix. For some reason, `EmrAddStepsTrigger` extends `BaseTrigger` from Airflow instead of `AwsBaseWaiterTrigger` like the rest of the EMR triggers even though it uses an AWS waiter. Perhaps the more appropriate fix would be to rewrite this trigger to use the AWS-specific base class. ### What you think should happen instead The `EmrAddStepOperator` should work when deferred ### How to reproduce Minimal DAG, run using the `apache/airflow:2.7.0-python3.11` image with the provided docker-compose.yaml file: ```python from datetime import datetime from airflow import DAG from airflow.providers.amazon.aws.operators.emr import EmrAddStepsOperator with DAG( "emr_defer_test", start_date=datetime(2021, 1, 1), catchup=False, schedule_interval=None, ) as dag: # this will work on any EMR cluster, put your cluster ID here job_flow_id = "j-1M0574ZKPRD9H" EmrAddStepsOperator( task_id="run_deferred", job_flow_id=job_flow_id, steps=[ { "Name": "hello-world", "ActionOnFailure": "CONTINUE", "HadoopJarStep": { "Jar": "command-runner.jar", "Args": "sleep 60".split(), } } ], deferrable=True, ) ``` ### Operating System Docker on MacOS 13.5.1 via colima ### Versions of Apache Airflow Providers ``` apache-airflow-providers-amazon==8.5.1 apache-airflow-providers-celery==3.3.2 apache-airflow-providers-common-sql==1.7.0 apache-airflow-providers-ftp==3.5.0 apache-airflow-providers-http==4.5.0 apache-airflow-providers-imap==3.3.0 apache-airflow-providers-postgres==5.6.0 apache-airflow-providers-sqlite==3.4.3 ``` ### Deployment Docker-Compose ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34177

https://github.com/apache/airflow/pull/34216

050a47add822cde6d9abcd609df59c98caae13b0

f0467c9fd65e7146b44fc8f9fccb9ad750592371

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/operators/compute.py", "tests/providers/google/cloud/operators/test_compute.py"]

ComputeEngineInsertInstanceOperator doesn't respect jinja-templated instance name when given in body argument

### Apache Airflow version 2.7.0 ### What happened when initializing the operator with a `body` that has a jinja-templated `name` field and without a `resource_id`, the creation fails due to the fact that the instance name doesn't fit the name format - but that is because it doesnt go realization/jinja-parsing. ### What you think should happen instead full error log: ``` [2023-09-06, 09:22:41 UTC] {taskinstance.py:1768} ERROR - Task failed with exception Traceback (most recent call last): File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/airflow/providers/google/cloud/operators/compute.py", line 210, in execute existing_instance = hook.get_instance( File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/airflow/providers/google/common/hooks/base_google.py", line 468, in inner_wrapper return func(self, *args, **kwargs) File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/airflow/providers/google/cloud/hooks/compute.py", line 350, in get_instance instance = client.get( File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/google/cloud/compute_v1/services/instances/client.py", line 2812, in get response = rpc( File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/google/api_core/gapic_v1/method.py", line 113, in __call__ return wrapped_func(*args, **kwargs) File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/google/api_core/grpc_helpers.py", line 72, in error_remapped_callable return callable_(*args, **kwargs) File "/home/sigal/.local/share/virtualenvs/ingest-airflow-rHPaIjXZ/lib/python3.8/site-packages/google/cloud/compute_v1/services/instances/transports/rest.py", line 2485, in __call__ raise core_exceptions.from_http_response(response) google.api_core.exceptions.BadRequest: 400 GET https://compute.googleapis.com/compute/v1/projects/ai2-israel/zones/us-west1-b/instances/%7B%7B%20params.get('dataset')%20%7D%7D: Invalid value for field 'instance': '{{ params.get('dataset') }}'. Must be a match of regex '[a-z](?:[-a-z0-9]{0,61}[a-z0-9])?|[1-9][0-9]{0,19}' ``` ### How to reproduce ```python with DAG( dag_id="blob", schedule_interval=None, start_date=datetime(2023, 1, 1), catchup=False, params={ "dataset": Param(default="test"), }, render_template_as_native_obj=True, ) as dag: dataset = "{{ params.get('dataset') }}" create_vm_instance = CustomComputeEngineInsertInstanceOperator( task_id="create_vm_instance", project_id=OUR_PROJECT_ID, zone=OUR_LOCATION, body={ "name": dataset, "machine_type": f"zones/{OUR_LOCATION}/machineTypes/n1-standard-96", "source_machine_image": f"global/machineImages/{OUR_IMAGE}", "disks": [ { "boot": True, "device_name": dataset, "initialize_params": {"disk_size_gb": "10", "disk_type": f"zones/{OUR_LOCATION}/diskTypes/pd-ssd"}, } ], "network_interfaces": [ { "access_configs": [{"name": "External NAT", "network_tier": "PREMIUM"}], "stack_type": "IPV4_ONLY", "subnetwork": f"regions/{OUR_REGION}/subnetworks/default", } ], } ) ``` ### Operating System Ubuntu 20.04.6 LTS ### Versions of Apache Airflow Providers _No response_ ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34170

https://github.com/apache/airflow/pull/34171

8035aee8da3c4bb7b9c01cfdc7236ca01d658bae

0110b22a603f86fbc6f1311ef1c9a23505ca6f87

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/google/cloud/hooks/bigquery.py", "airflow/providers/google/cloud/triggers/bigquery.py", "tests/providers/google/cloud/hooks/test_bigquery.py", "tests/providers/google/cloud/triggers/test_bigquery.py"]

`BigQueryInsertJobOperator` doesn't handle job errors caused by running tasks in deferrable mode

### Apache Airflow version 2.7.0 ### What happened When a BigQuery job running in deferrable ends before completion - i.e. cancelled via the UI or terminated due a lack of resources - the precise error is not returned to the logs. Instead a key error from within the `execute_complete` function is returned. ``` [2023-09-07, 09:17:52 UTC] {taskinstance.py:1824} ERROR - Task failed with exception Traceback (most recent call last): File "/usr/local/lib/python3.10/site-packages/airflow/providers/google/cloud/operators/bigquery.py", line 2874, in execute_complete raise AirflowException(event["message"]) KeyError: 'message' ``` https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/operators/bigquery.py#L2874-L2887 ### What you think should happen instead When not running in deferrable mode, when the job is cancelled/fails during execution, the `_handle_job_error` is called resulting in the following output. ``` [2023-09-07, 09:16:35 UTC] {taskinstance.py:1824} ERROR - Task failed with exception Traceback (most recent call last): File "/usr/local/lib/python3.10/site-packages/airflow/providers/google/cloud/operators/bigquery.py", line 2848, in execute job.result(timeout=self.result_timeout, retry=self.result_retry) File "/usr/local/lib/python3.10/site-packages/google/cloud/bigquery/job/query.py", line 1499, in result do_get_result() File "/usr/local/lib/python3.10/site-packages/google/cloud/bigquery/job/query.py", line 1489, in do_get_result super(QueryJob, self).result(retry=retry, timeout=timeout) File "/usr/local/lib/python3.10/site-packages/google/cloud/bigquery/job/base.py", line 728, in result return super(_AsyncJob, self).result(timeout=timeout, **kwargs) File "/usr/local/lib/python3.10/site-packages/google/api_core/future/polling.py", line 261, in result raise self._exception google.api_core.exceptions.GoogleAPICallError: 200 Job execution was cancelled: User requested cancellation ``` It would appear that, even though `_handle_job_error` should get called when in deferrable mode, this doesn't happen if the job was running when it terminates. https://github.com/apache/airflow/blob/main/airflow/providers/google/cloud/operators/bigquery.py#L2860-L2872 ### How to reproduce The code below will replicate the issue, however you need to provide a query that runs for enough time that enables you to cancel the job in UI. Queries that have syntax errors never get started and are not affected by this. ``` from datetime import datetime from airflow import models from airflow.providers.google.cloud.operators.bigquery import BigQueryInsertJobOperator with models.DAG( dag_id='bq_insert_job', start_date=datetime(2023, 8, 31), catchup=False, schedule='0 0 * * *', ) as dag: test1 = BigQueryInsertJobOperator( task_id=f'test1', sql='<INSERT LONG RUNNING QUERY>', deferrable=False, ) test2 = BigQueryInsertJobOperator( task_id=f'test2', sql=f'<INSERT LONG RUNNING QUERY>', deferrable=True, ) ``` ### Operating System n/a ### Versions of Apache Airflow Providers apache-airflow-providers-google==10.6.0 ### Deployment Astronomer ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34162

https://github.com/apache/airflow/pull/34208

f5c2748c3346bdebf445afd615657af8849345dd

774125ae253611627229509e672518ce0a58cf2e

python

closed

apache/airflow

https://github.com/apache/airflow

["docs/apache-airflow/administration-and-deployment/cluster-policies.rst"]

Update docs to mark Pluggy interface as stable rather than experimental

### What do you see as an issue? [Pluggy interface has been listed as experimental](https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/cluster-policies.html#:~:text=By%20using%20a,experimental%20feature.) since Airflow 2.6. Requesting it be listed as stable ### Solving the problem Change the documentation to say it is now stable ### Anything else _No response_ ### Are you willing to submit PR? - [x] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34147

https://github.com/apache/airflow/pull/34174

d29c3485609d28e14a032ae5256998fb75e8d49f

88623acae867c2a9d34f5030809102379080641a

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/config_templates/config.yml"]

Description needed for default resource configurations

### What do you see as an issue? Several of the [operator configuration options](https://airflow.apache.org/docs/apache-airflow/stable/configurations-ref.html#operators) don't have descriptions which is confusing. ### Solving the problem This can be solved by adding a description to each of these fields, [for example default_ram](https://github.com/apache/airflow/blob/2.7.0/airflow/config_templates/config.yml#L1290) ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34141

https://github.com/apache/airflow/pull/34438

03db0f6b785a4983c09d6eec7433cf28f7759610

3a4712e306e123c4e78251968b7f2975b73bdbaf

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/static/js/dag/Main.tsx", "airflow/www/static/js/dag/details/index.tsx"]

Always show details panel when user navigates to Graph tab

### Description When a user navigates to `/grid?tab=graph` we should show the details panel with the graph tab selected, even when the user hid the details panel previously. ### Use case/motivation People already complained asking me where the graph view went after the latest Airflow upgrade (2.7.0). I can understand that this may be confusing, especially when they navigate to the graph from a DAG run link.  It would be more user friendly if we could auto-open the details panel when a user navigates to the graph tab, so they immediately get what they expect. Happy to create the PR for this, I believe it should be just a tiny change. However, I'm opening this feature request first, just to make sure I'm not conflicting with any other plans ([AIP-39?](https://github.com/apache/airflow/projects/9)). ### Related issues https://github.com/apache/airflow/issues/29852 ### Are you willing to submit a PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34132

https://github.com/apache/airflow/pull/34136

5eea4e632c8ae50812e07b1d844ea4f52e0d6fe1

0b319e79ec97f6f4a8f8ce55119b6539138481cd

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/providers/elasticsearch/log/es_task_handler.py", "tests/providers/elasticsearch/log/test_es_task_handler.py"]

Elasticsearch.__init__() got an unexpected keyword argument 'use_ssl'

### Apache Airflow version 2.7.0 ### What happened When upgrading apache-airflow-providers-elasticsearch to the newest provider (5.0.1), Airflow is unable to spin up. The scheudler and airflow-migrations both crash on following error: ```console .................... ERROR! Maximum number of retries (20) reached. Last check result: $ airflow db check Unable to load the config, contains a configuration error. Traceback (most recent call last): File "/usr/local/lib/python3.11/logging/config.py", line 573, in configure handler = self.configure_handler(handlers[name]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/local/lib/python3.11/logging/config.py", line 758, in configure_handler result = factory(**kwargs) ^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/elasticsearch/log/es_task_handler.py", line 110, in __init__ self.client = elasticsearch.Elasticsearch(host, **es_kwargs) # type: ignore[attr-defined] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: Elasticsearch.__init__() got an unexpected keyword argument 'use_ssl' The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/airflow/.local/bin/airflow", line 5, in <module> from airflow.__main__ import main File "/home/airflow/.local/lib/python3.11/site-packages/airflow/__init__.py", line 68, in <module> settings.initialize() File "/home/airflow/.local/lib/python3.11/site-packages/airflow/settings.py", line 524, in initialize LOGGING_CLASS_PATH = configure_logging() ^^^^^^^^^^^^^^^^^^^ File "/home/airflow/.local/lib/python3.11/site-packages/airflow/logging_config.py", line 74, in configure_logging raise e File "/home/airflow/.local/lib/python3.11/site-packages/airflow/logging_config.py", line 69, in configure_logging dictConfig(logging_config) File "/usr/local/lib/python3.11/logging/config.py", line 823, in dictConfig dictConfigClass(config).configure() File "/usr/local/lib/python3.11/logging/config.py", line 580, in configure raise ValueError('Unable to configure handler ' ValueError: Unable to configure handler 'task' Exception ignored in atexit callback: <function shutdown at 0x7fb5255f22a0> Traceback (most recent call last): File "/usr/local/lib/python3.11/logging/__init__.py", line 2193, in shutdown h.close() File "/home/airflow/.local/lib/python3.11/site-packages/airflow/providers/elasticsearch/log/es_task_handler.py", line 396, in close if not self.mark_end_on_close or getattr(self, "ctx_task_deferred", None): ^^^^^^^^^^^^^^^^^^^^^^ AttributeError: 'ElasticsearchTaskHandler' object has no attribute 'mark_end_on_close' 2023-09-05T06:04:58.154163010Z ``` ### What you think should happen instead Deploy Airflow without any crashing schedulers ### How to reproduce I'm currently running airflow on version 2.7.0 on AKS. I'm trying to upgrade elasticsearch to package 5.0.1. Following config is present for elasticsearch: ``` [elasticsearch] frontend = https://*redacted*.kb.westeurope.azure.elastic-cloud.com/app/discover#/?_a=(columns:!(message),filters:!(),index:'6551970b-aa72-4e2a-b255-d296a6fcdc09',interval:auto,query:(language:kuery,query:'log_id:"{log_id}"'),sort:!(log.offset,asc))&amp;_g=(filters:!(),refreshInterval:(pause:!t,value:0),time:(from:now-1m,to:now)) json_format = True log_id_template = {dag_id}_{task_id}_{execution_date}_{try_number} [elasticsearch_configs] max_retries = 3 retry_timeout = True timeout = 30 ``` ### Operating System Debian GNU/Linux 11 (bullseye) ### Versions of Apache Airflow Providers apache-airflow-providers-cncf-kubernetes==7.4.2 apache-airflow-providers-docker==3.7.4 apache-airflow-providers-microsoft-azure==4.3.0 apache-airflow-providers-elasticsearch==5.0.1 ### Deployment Official Apache Airflow Helm Chart ### Deployment details _No response_ ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34099

https://github.com/apache/airflow/pull/34119

9babb065d077e89f779aaee07f0b673835f5700c

f7f3b675ecd40e32e458b71b5066864f866a60c8

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/views.py"]

Can Delete on Task Instances permission is required to clear task

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened I was changing the roles to remove all delete access. But as soon as I remove permission "Can Delete on Task Instances" clear task takes to a blank page. Shouldn't clear task access work without Delete access? ### What you think should happen instead Can Delete Task Instance should not affect clear task access. ### How to reproduce Copy the Op role and remove all Can Delete and assign that role to a user. That user will not be able to clear task instance now. add "Can Delete on Task Instances" permission to the role and user will now have access to clear task instances page. ### Operating System Redhat 8 ### Versions of Apache Airflow Providers 2.6.1 ### Deployment Docker-Compose ### Deployment details airflow 2.6.1 running on Docker with postgres 13 and pgbouncer. ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34092

https://github.com/apache/airflow/pull/34123

ba524ce4b2c80976fdb7ff710750416bc01d250d

2f5777c082189e6495f0fea44bb9050549c0056b

python

closed

apache/airflow

https://github.com/apache/airflow

[".github/workflows/ci.yml", "dev/breeze/SELECTIVE_CHECKS.md", "dev/breeze/src/airflow_breeze/utils/selective_checks.py", "dev/breeze/tests/test_selective_checks.py"]

Replace the usage of `--package-filter` with short package ids in CI

### Body Our CI generates `--package-filter` list in selective checks in order to pass them to `build-docs` and `publish-docs` commands. However after implementing #33876 and #34085 we could switch both commands to use short package ids which we already have (almost - there should be a slight modification for `apache-airflow`, `apache-airflow-providers` and `helm-chart` most likely. This should also simplify some of the unit tests we have. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34086

https://github.com/apache/airflow/pull/35068

d87ca903742cc0f75df165377e5f8d343df6dc03

8d067129d5ba20a9847d5d70b368b3dffc42fe6e

python

closed

apache/airflow

https://github.com/apache/airflow

["BREEZE.rst", "dev/breeze/src/airflow_breeze/commands/release_management_commands.py", "dev/breeze/src/airflow_breeze/params/doc_build_params.py", "dev/breeze/src/airflow_breeze/utils/general_utils.py", "dev/breeze/src/airflow_breeze/utils/publish_docs_helpers.py", "images/breeze/output-commands-hash.txt", "images/breeze/output_release-management.svg", "images/breeze/output_release-management_publish-docs.svg"]

Replace --package-filter usage for `publish-docs` breeze command with short package names

### Body Same as https://github.com/apache/airflow/issues/33876 but for `publish-docs` command. ### Committer - [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.

https://github.com/apache/airflow/issues/34085

https://github.com/apache/airflow/pull/34253

58cce7d88b1d57e815e04e5460eaaa71173af14a

18eed9191dbcb84cd6099a97d5ad778ac561cd4d

python

closed

apache/airflow

https://github.com/apache/airflow

["airflow/www/views.py"]

Delete record of dag run is not being logged in audit logs when clicking on delete button in list dag runs

### Apache Airflow version Other Airflow 2 version (please specify below) ### What happened When doing a list dag runs and doing check box selection and in actions delete dags is performed in audit logs we get an event with "action_muldelete". But if instead of using check box and actions we directly click on delete button provided there is no audit log for the deleted dag run. ### What you think should happen instead There should be atleast and identifiable event for audit in both scenarios. For one it is present but for other there is no audit. ### How to reproduce Go to List dag runs 1. Select one dag run using check box and go to actions and delete and confirm. Check audit logs there will be an event of action_muldelete 2. Go to list dag run and click on delete button which is present beside check box and adjacent to edit record. Check audit logs there will be no event for this action. ### Operating System Redhat 8 ### Versions of Apache Airflow Providers airflow 2.6.1 running on Docker with postgres 13 and pgbouncer. ### Deployment Docker-Compose ### Deployment details airflow 2.6.1 running on Docker with postgres 13 and pgbouncer. ### Anything else _No response_ ### Are you willing to submit PR? - [ ] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

https://github.com/apache/airflow/issues/34069

https://github.com/apache/airflow/pull/34090

d81fe093c266ef63d4e3f0189eb8c867bff865f4

988632fd67abc10375ad9fe2cbd8c9edccc609a5

python