How to use the grafanalib.core.SECONDS_FORMAT function in grafanalib

d.one_line(
            """
histogram_quantile(
  0.50,
  sum(
    rate(
      etcd_request_duration_seconds_bucket{
        operation=~"${etcd_operation:regex}",
        type=~".*(${etcd_type:pipe})"
      }[1m]
    )
  ) by (le, operation, type, instance)
)
"""
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),
    d.simple_graph("etcd instance id", "sum(etcd_server_id) by (instance, server_id)"),
    d.simple_graph(
        "etcd network latency (99th percentile)",
        "histogram_quantile(0.99, sum(rate(etcd_network_peer_round_trip_time_seconds_bucket[1m])) by (le, instance, To))",
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),
    d.simple_graph(
        "etcd compaction keys",
        "delta(etcd_debugging_mvcc_db_compaction_keys_total[1m])",
    ),
    d.simple_graph(
        "etcd compaction pause sum duration",
        "delta(etcd_debugging_mvcc_db_compaction_pause_duration_milliseconds_sum[1m])",
        yAxes=g.single_y_axis(format=g.MILLISECONDS_FORMAT),
    ),

def api_call_latency(title, metric, verb, scope, threshold):
    return d.Graph(
        title=title,
        targets=[
            g.Target(expr=str(threshold), legendFormat="threshold"),
            g.Target(
                expr='quantile_over_time(0.99, %(metric)s{quantile="0.99", verb=~"%(verb)s", scope=~"%(scope)s"}[12h])'
                % {"metric": metric, "verb": verb, "scope": scope}
            ),
        ],
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    )

description=(
            "NetworkProgrammingLatency is defined as the time it took to "
            + "program the network - from the time  the service or pod has "
            + "changed to the time the change was propagated and the proper "
            + "kube-proxy rules were synced. Exported for each endpoints object "
            + "that were part of the rules sync."
        ),
        targets=d.show_quantiles(
            (
                "quantile_over_time("
                + "0.99, "
                + 'kubeproxy:kubeproxy_network_programming_duration:histogram_quantile{{quantile="{quantile}"}}[24h])'
            ),
            legend="{{quantile}}",
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),
    d.Graph(
        title="Network programming latency",
        description=(
            "NetworkProgrammingLatency is defined as the time it took to "
            + "program the network - from the time  the service or pod has "
            + "changed to the time the change was propagated and the proper "
            + "kube-proxy rules were synced. Exported for each endpoints object "
            + "that were part of the rules sync."
        ),
        targets=d.show_quantiles(
            'kubeproxy:kubeproxy_network_programming_duration:histogram_quantile{{quantile="{quantile}"}}',
            legend="{{quantile}}",
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),

+ "kube-proxy rules were synced. Exported for each endpoints object "
            + "that were part of the rules sync."
        ),
        targets=d.show_quantiles(
            'kubeproxy:kubeproxy_network_programming_duration:histogram_quantile{{quantile="{quantile}"}}',
            legend="{{quantile}}",
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),
    d.Graph(
        title="kube-proxy: sync rules duation",
        description="Latency of one round of kube-proxy syncing proxy rules.",
        targets=d.show_quantiles(
            "histogram_quantile({quantile}, sum(rate(kubeproxy_sync_proxy_rules_duration_seconds_bucket[5m])) by (le))"
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
    ),
    d.simple_graph(
        "kube-proxy: rate of service changes",
        "sum(rate(kubeproxy_sync_proxy_rules_service_changes_total[5m]))",
        description="Rate of service changes that the proxy has seen over 5m",
        legend="rate",
    ),
    d.simple_graph(
        "kube-proxy: pending service changes",
        "sum(kubeproxy_sync_proxy_rules_service_changes_pending)",
        description="Number of pending service changes that have not yet been synced to the proxy.",
        legend="pending changes",
    ),
    d.simple_graph(
        "kube-proxy: rate of endpoint changes",
        "sum(rate(kubeproxy_sync_proxy_rules_endpoint_changes_total[5m]))",

from grafanalib import core as g
import defaults as d

PROBER_PANEL = [
    d.Graph(
        title="In-cluster DNS latency SLI",
        targets=d.show_quantiles(
            (
                "quantile_over_time("
                + "0.99, "
                + 'probes:dns_lookup_latency:histogram_quantile{{quantile="{quantile}"}}[24h])'
            ),
            legend="{{quantile}}",
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
        nullPointMode="null",
    ),
    d.Graph(
        title="DNS latency",
        targets=d.show_quantiles(
            'probes:dns_lookup_latency:histogram_quantile{{quantile="{quantile}"}}',
            legend="{{quantile}}",
        ),
        yAxes=g.single_y_axis(format=g.SECONDS_FORMAT),
        nullPointMode="null",
    ),
    d.Graph(
        title="probe: lookup rate",
        targets=[
            g.Target(
                expr='sum(rate(probes_in_cluster_dns_lookup_count{namespace="probes", job="dns"}[1m]))',