### Apache Airflow version

2.4.2

### What happened

Create a DAG and set the schedule parameter using a CronTriggerTimeTable instance. Enable the DAG so that there is DAG run data. Try to access the Calendar View for the DAG. An ERR_EMPTY_RESPONSE error is displayed instead of the page.

The Calendar View is accessible for other DAGs  that are using the schedule_interval set to a cron string instead.

### What you think should happen instead

The Calendar View should have been displayed.

### How to reproduce

Create a DAG and set the schedule parameter to a CronTriggerTimeTable instance. Enable the DAG and allow some DAG runs to occur. Try to access the Calender View for the DAG.

### Operating System

Red Hat Enterprise Linux 8.6

### Versions of Apache Airflow Providers

_No response_

### Deployment

Virtualenv installation

### Deployment details

Airflow 2.4.2 installed via pip with Python3.9 to venv using constraints.

### 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)

ti_fails = ti_fails.filter(TaskFail.task_id.in_([t.task_id for t in dag.tasks]))
        tasks = []
        for ti in tis:
            if not dag.has_task(ti.task_id):
                continue
            
            
            
            try_count = ti.prev_attempted_tries if ti.prev_attempted_tries != 0 else ti.try_number
            task_dict = alchemy_to_dict(ti)
            task_dict["end_date"] = task_dict["end_date"] or timezone.utcnow()
            task_dict["extraLinks"] = dag.get_task(ti.task_id).extra_links
            task_dict["try_number"] = try_count
            task_dict["execution_date"] = dttm.isoformat()
            task_dict["run_id"] = dag_run_id
            tasks.append(task_dict)
        tf_count = 0
        try_count = 1
        prev_task_id = ""
        for failed_task_instance in ti_fails:
            if not dag.has_task(failed_task_instance.task_id):
                continue
            if tf_count != 0 and failed_task_instance.task_id == prev_task_id:
                try_count += 1
            else:
                try_count = 1
            prev_task_id = failed_task_instance.task_id
            tf_count += 1
            task = dag.get_task(failed_task_instance.task_id)
            task_dict = alchemy_to_dict(failed_task_instance)