http://localhost:8081/api/v1/dags?limit=100&offset=0
http://localhost:8081/api/v1/dags?limit=100&offset=101

from datetime import datetime
from airflow import DAG, settings
from airflow.decorators import task
from airflow.models import DagBag
with DAG(
        dag_id="test_dag",
        schedule_interval=None,
        default_args={
            "start_date": datetime(2022, 1, 1),
            "retries": 0,
            "catchup": False,
        },
        render_template_as_native_obj=True,
        tags=["test"],
) as dag:
    dag.doc_md = __doc__
    @task
    def print_dags():
        dagbag = DagBag(settings.DAGS_FOLDER)
        print(dagbag.dags.keys())
    (print_dags())

<details>
<summary>英文:</summary>
there is a [PR][1] that explain that the limit can not be passed and if you put more then the limit the fallback would be the limit
if you want to change the limit in the api, you can change &quot;maximum_page_limit&quot; in airflow.cfg to other number (default = 100)
Another option is to play with offset until you do not get dags in the list. for example : first call limit=100, offset=0, second call limit=100, offset=101 and so on until empty response.
    http://localhost:8081/api/v1/dags?limit=100&offset=0
    http://localhost:8081/api/v1/dags?limit=100&offset=101
also, an option not in the api is to create a dag with a task and using DagBag to get all dags details.
in this example I print all the dag ids
    from datetime import datetime
    from airflow import DAG, settings
    from airflow.decorators import task
    from airflow.models import DagBag
    
    with DAG(
            dag_id=&quot;test_dag&quot;,
            schedule_interval=None,
            default_args={
                &quot;start_date&quot;: datetime(2022, 1, 1),
                &quot;retries&quot;: 0,
                &quot;catchup&quot;: False,
            },
            render_template_as_native_obj=True,
            tags=[&quot;test&quot;],
    ) as dag:
        dag.doc_md = __doc__
    
    
        @task
        def print_dags():
            dagbag = DagBag(settings.DAGS_FOLDER)
            print(dagbag.dags.keys())
    
    
        (print_dags())
  [1]: https://github.com/apache/airflow/pull/29773/files
</details>