Grid view date ticks do not match dag run ordering

[travis-cook-sfdc]

Apache Airflow version

2.6.3

What happened

In the old tree view, all of columns for each run would display the data_interval_start / date from the run_id as the UI identifier for the dag run.

In the new grid view, it's inconsistent.

For example, the header of this column says 2023-07-17 00:00:00:

But when you hover over the same DAG Run, it display the Data Interval End date of 2023-07-18 00:00:00:

This inconsistency is causing confusion for users of Airflow because they're just not sure what date is being processed.

What you think should happen instead

In order to retain consistency they should show the same value.

I think in order to maintain parity with the old tree view and the run_id, it should display the data_interval_start in the tooltip.

How to reproduce

1. Navigate to grid view for any DAG.
2. See the discrepancy between the column header and the tooltip's date values for a "@daily" job.

Operating System

Debian GNU/Linux

Versions of Apache Airflow Providers

N/A

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

• I agree to follow this project's Code of Conduct

[pierrejeambrun]

What is displayed in the tooltip depends on the run_ordering property of the timetable.

I think the issue is that the ordering of the dagrun and the tooltip is dynamically dependent on the timetable.run_ordering, while the header/timetick displayed is always the execution_date hence the difference.

Maybe we can make the header also dynamic on the ordering property to keep that consistent ?

[bbovenzi]

Yeah, the header should be the same as the run ordering. Should be an easy fix for anyone who wants to try their hand at the UI.

[AmanSal1]

Can I try this one ?

[bbovenzi]

@AmanSal1 all yours! I'm here to help if you have any questions.

[AmanSal1]

@bbovenzi Thank you!!

[AmanSal1]

@bbovenzi I want to develop airflow in local environment I did read the instruction for it can you just confirm it once .

I created a virtual environment forked the repo and I guess now i have to run this command from the airflow repo
"pip install -e ".[devel,]"
--constraint "https://raw.githubusercontent.com/apache/airflow/constraints-main/constraints-source-providers-3.8.txt"

And then I have to change the version of python accordingly after that connect to the database ? Am I right ?