- Cliquer sur l'onglet "Debug" de la barre d'activités de Visual Studio Code.
- "Add configuration...".
- Sélectionnez "Python".
- Lancez le <abbr title="En anglais: debugger">débogueur</abbr> avec l'option "`Python: Current File (Integrated Terminal)`".

Il démarrera alors le serveur avec votre code **FastAPI**, s'arrêtera à vos points d'arrêt, etc.

Voici à quoi cela pourrait ressembler :

<img src="/img/tutorial/debugging/image01.png">

        return _instance;
    }

    // ===================================================================================
    //                                                                       Current DBDef
    //                                                                       =============
    @Override
    public String getProjectName() {
        return null;
    }

    @Override

-   type: input id: Gpu attributes: label: GPU model and memory description: if
    compiling from source placeholder: validations: required: false

-   type: textarea id: what-happened attributes: label: Current Behaviour?
    description: Also tell us, what did you expect to happen? placeholder: Tell
    us what you see! value: "A bug happened!" render: shell validations:
    required: true

          minor_version=$(grep "^#define TF_MINOR_VERSION" ./tensorflow/core/public/version.h | grep -o "[[:digit:]]\+")
          echo "TF_VERSION=${major_version}.${minor_version}" >> "$GITHUB_OUTPUT"
          # Also get the current date to do cache busting. Assumes one day
          # is an ok range for rebuilds
          echo "DATE=$(date +'%Y-%m-%d')" >> "$GITHUB_OUTPUT"
        id: tf-version
      -
        name: Build and push

	mc admin cluster iam export old-minio
	set +x

	mc admin service stop old-minio
}

import_iam_content_in_new_minio() {
	echo "Importing IAM content in new minio instance."
	# Assume current minio binary exists.
	MINIO_CI_CD=1 ./minio server /tmp/data/{1...4} &
	sleep 5

	set -x
	mc alias set new-minio http://localhost:9000 minioadmin minioadmin
	echo "BEFORE IMPORT mappings:"
	mc ready new-minio

          <name>snapshot</name>
          <version>1.0.0+</version>
          <association>
            <type>Snapshot</type>
          </association>
          <description>The current snapshot data in use for this version ("groupId/artifactId/version" only)</description>
        </field>
        <field>
          <name>snapshotVersions</name>
          <version>1.1.0+</version>

	}

	var count int64
	DB.Model(&User{}).Where("name IN ?", []string{users[0].Name, users[1].Name, users[2].Name}).Count(&count)
	if count != 1 {
		t.Errorf("failed to delete data, current count %v", count)
	}
}

func TestDeleteReturning(t *testing.T) {
	if DB.Dialector.Name() != "sqlite" && DB.Dialector.Name() != "postgres" && DB.Dialector.Name() != "sqlserver" {
		return
	}

 *
 * This class may be used to stream very large responses. For example, it is possible to use this
 * class to read a response that is larger than the entire memory allocated to the current process.
 * It can even stream a response larger than the total storage on the current device, which is a
 * common requirement for video streaming applications.
 *
 * Because this class does not buffer the full response in memory, the application may not

  internal val parameterNamesAndValues: Array<String>,
) {
  /**
   * Returns the charset of this media type, or [defaultValue] if either this media type doesn't
   * specify a charset, or if its charset is unsupported by the current runtime.
   */
  @JvmOverloads
  fun charset(defaultValue: Charset? = null): Charset? {
    val charset = parameter("charset") ?: return defaultValue
    return try {
      Charset.forName(charset)

코드에서 직접 Uvicorn 서버를 실행하고 있기 때문에 디버거에서 직접 Python 프로그램(FastAPI 애플리케이션)을 호출할 수 있습니다.

---

예를 들어 Visual Studio Code에서 다음을 수행할 수 있습니다.

* "Debug" 패널로 이동합니다.
* "Add configuration...".
* "Python"을 선택합니다.
* "`Python: Current File (Integrated Terminal)`" 옵션으로 디버거를 실행합니다.

그런 다음 **FastAPI** 코드로 서버를 시작하고 중단점 등에서 중지합니다.

다음과 같이 표시됩니다.

<img src="/img/tutorial/debugging/image01.png">

---

Pycharm을 사용하는 경우 다음을 수행할 수 있습니다