//
	// If len(dst) < len(src), XORKeyStream should panic. It is acceptable
	// to pass a dst bigger than src, and in that case, XORKeyStream will
	// only update dst[:len(src)] and will not touch the rest of dst.
	//
	// Multiple calls to XORKeyStream behave as if the concatenation of
	// the src buffers was passed in a single run. That is, Stream
	// maintains state and does not reset at each XORKeyStream call.

labels.threadName	=	Nom du fil
labels.url	=	URL
labels.userFavorite	=	Journal favori
labels.userInfo	=	informations utilisateur
labels.webApiJson	=	Réponse JSON
labels.webConfigName	=	Nom de la configuration Web
labels.allLanguages	=	Toutes les langues
labels.dictId	=	ID de dictionnaire
labels.docId	=	Identifiant du document
labels.endTime	=	Heure de fin
labels.hq	=	hq
labels.inputs	=	Source
labels.jobLogging	=	Journalisation
labels.jobName	=	Nom

        def staleFileInDir = file("build/dir/stale-file.txt").touch()
        def fileInBuildDir = file("build/file").touch()

        expect:
        succeeds("myTask")

        when:
        invalidateBuildOutputCleanupState()
        dirInBuildDir.createDir()
        staleFileInDir.touch()
        fileInBuildDir.touch()
        then:
        succeeds("myTask")
    }

                Timer timer = Time.startTimer();
                try {
                    cacheCleanupStrategy.getCleanupAction().clean(cleanableStore, progressMonitor);
                    FileUtils.touch(gcFile);
                    LOGGER.info("{} cleaned up in {}.", cleanableStore.getDisplayName(), timer.getElapsed());
                    context.setResult(new CacheCleanupResult(progressMonitor.getDeleted(), lastCleanupTime));

                                                TF_Status* status);

// Obtains statistics for the given path. If status is TF_OK, *stats is
// updated, otherwise it is not touched.
TF_CAPI_EXPORT extern void TF_FileStat(const char* filename,
                                       TF_FileStatistics* stats,
                                       TF_Status* status);

#!/bin/bash
set -xuo pipefail

temp_log_file=/tmp/fess-build.$$
unzip target/releases/fess-*.zip > ${temp_log_file} 2>&1
tail ${temp_log_file}

./fess-*/bin/fess > ${temp_log_file} 2>&1 &

temp_json_file=/tmp/fess-log.$$
touch ${temp_json_file}
error_count=0
while true ; do
  status=$(curl -w '%{http_code}\n' -s -o ${temp_json_file} "http://localhost:8080/api/v1/health")
  cat ${temp_json_file}
  if [[ x"${status}" = x200 ]] ; then
    break

    }

    def "prompts to overwrite files if any exist and defaults to no"() {
        given: "a file exists in the build directory"
        targetDir.file(defaultFileName).touch()

        when:
        def handle = startInteractiveExecutorWithTasks(
            "init",
            "--incubating",
            "--dsl", "groovy",
            "--type", "basic",

## Concepts de déploiement

Ces exemples lancent le programme serveur (e.g. Uvicorn), démarrant **un seul processus**, sur toutes les IPs (`0.0.
0.0`) sur un port prédéfini (par example, `80`).

C'est l'idée de base. Mais vous vous préoccuperez probablement de certains concepts supplémentaires, tels que ... :

* la sécurité - HTTPS

setting up your local repository for Bazel build. For this you will need to
create bazel workspace and build files:

```sh
LLVM_SRC=... # this the path to the LLVM local source directory you intend to use.
touch ${LLVM_SRC}/BUILD.bazel ${LLVM_SRC}/WORKSPACE
```

You can then use this overlay to build TensorFlow:

```
bazel build --override_repository="llvm-raw=${LLVM_SRC}" \
  -c opt tensorflow/compiler/mlir:tf-opt

        then:
        with(taskSuccessResult(':incrementalTask')) {
            !incremental
            executionReasons[0].contains("No history")
        }

        when:
        file('src/a').touch()
        file('src/b').touch()

        and:
        runBuild('incrementalTask')

        then:
        with(taskSuccessResult(':incrementalTask')) {
            incremental