from datetime import datetime, time, timedelta
from typing import Annotated
from uuid import UUID

from fastapi import Body, FastAPI

app = FastAPI()


@app.put("/items/{item_id}")
async def read_items(
    item_id: UUID,
    start_datetime: Annotated[datetime, Body()],
    end_datetime: Annotated[datetime, Body()],
    process_after: Annotated[timedelta, Body()],
    repeat_at: Annotated[time | None, Body()] = None,
):

func (endpoints Endpoints) UpdateIsLocal() error {
	var epsResolved int
	var foundLocal bool
	resolvedList := make([]bool, len(endpoints))
	// Mark the starting time
	startTime := time.Now()
	keepAliveTicker := time.NewTicker(500 * time.Millisecond)
	defer keepAliveTicker.Stop()
	for {
		// Break if the local endpoint is found already Or all the endpoints are resolved.

   * higher value than you need can waste space and time, and a significantly lower value can lead
   * to thread contention. But overestimates and underestimates within an order of magnitude do not
   * usually have much noticeable impact. A value of one permits only one thread to modify the cache
   * at a time, but since read operations and cache loading computations can proceed concurrently,

    delegate().lockInterruptibly();
  }

  @Override
  public boolean tryLock() {
    return delegate().tryLock();
  }

  @Override
  public boolean tryLock(long time, TimeUnit unit) throws InterruptedException {
    return delegate().tryLock(time, unit);
  }

  @Override
  public void unlock() {
    delegate().unlock();
  }

  @Override
  public Condition newCondition() {

type currentScannerCycle struct {
	current        uint64
	next           uint64
	started        time.Time
	cycleCompleted []time.Time
}

// clone returns a clone.
func (z currentScannerCycle) clone() currentScannerCycle {
	z.cycleCompleted = append(make([]time.Time, 0, len(z.cycleCompleted)), z.cycleCompleted...)
	return z

                buildTimestampFromGradleProperty.isPresent -> "from buildTimestamp property"
                runningInstallTask.get() -> "from current time because installing"
                runningDocsTestTask.get() -> "from current time because testing docs"
                runningOnCi.get() -> "from current time because CI"
                else -> "from current date"
            }
        }

    private

	SecretKey    string                 `xml:"SecretAccessKey" json:"secretKey,omitempty" yaml:"secretKey"`
	SessionToken string                 `xml:"SessionToken" json:"sessionToken,omitempty" yaml:"sessionToken"`
	Expiration   time.Time              `xml:"Expiration" json:"expiration,omitempty" yaml:"-"`
	Status       string                 `xml:"-" json:"status,omitempty"`
	ParentUser   string                 `xml:"-" json:"parentUser,omitempty"`

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.helper;

import static org.codelibs.core.stream.StreamUtil.stream;

import java.time.ZonedDateTime;
import java.time.format.DateTimeFormatter;
import java.util.Comparator;
import java.util.LinkedHashMap;
import java.util.Locale;
import java.util.Map;
import java.util.stream.Collectors;

<!-- markdown-toc end -->

# Updating charts and values.yaml

## Acceptable Pull Requests

Helm charts `values.yaml` represent a complex user facing API that tends to grow uncontrollably over time
due to design choices in Helm.
The underlying Kubernetes resources we configure have 1000s of fields; given enough users and bespoke use cases,
eventually someone will want to customize every one of those fields.

 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.es.log.exentity;

import java.time.LocalDateTime;
import java.time.ZoneId;
import java.time.ZonedDateTime;
import java.time.format.DateTimeFormatter;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;