* Hay una **extensión** para el protocolo **TLS** (el que maneja la encriptación a nivel de TCP, antes de HTTP) llamada **<a href="https://en.wikipedia.org/wiki/Server_Name_Indication" class="external-link" target="_blank"><abbr title="Server Name Indication – Indicación del nombre del servidor">SNI</abbr></a>**.

}

func getClaimsFromTokenWithSecret(token, secret string) (*xjwt.MapClaims, error) {
	// JWT token for x-amz-security-token is signed with admin
	// secret key, temporary credentials become invalid if
	// server admin credentials change. This is done to ensure
	// that clients cannot decode the token using the temp
	// secret keys and generate an entirely new claim by essentially

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

Como SQLModel se basa en SQLAlchemy, puedes usar fácilmente **cualquier base de datos soportada** por SQLAlchemy (lo que las hace también soportadas por SQLModel), como:

* PostgreSQL
* MySQL
* SQLite
* Oracle
* Microsoft SQL Server, etc.

En este ejemplo, usaremos **SQLite**, porque utiliza un solo archivo y Python tiene soporte integrado. Así que puedes copiar este ejemplo y ejecutarlo tal cual.

			s3Select.recordReader = json.NewReader(s3Select.progressReader, &s3Select.Input.JSONArgs)
		}

		return nil
	case parquetFormat:
		if !parquetSupport {
			return errors.New("parquet format parsing not enabled on server")
		}
		if offset != 0 || length != -1 {
			// Offsets do not make sense in parquet files.
			return errors.New("parquet format does not support offsets")
		}
		var err error

    --hash=sha256:a6df30f272c08bf8be66e0775fad862005d950a6b8449b94f7c788731d70ecd7
    # via -r ci/official/requirements_updater/requirements.in
tensorboard-data-server==0.7.2 \
    --hash=sha256:7e0610d205889588983836ec05dc098e80f97b7e7bbff7e994ebb78f578d0ddb \
    --hash=sha256:9fe5d24221b29625dbc7328b0436ca7fc1c23de4acf4d272f1180856e32f9f60 \

## Join the chat { #join-the-chat }

Join the 👥 <a href="https://discord.gg/VQjSZaeJmf" class="external-link" target="_blank">Discord chat server</a> 👥 and hang out with others in the FastAPI community.

/// tip

}

func TestToSQL(t *testing.T) {
	// By default DB.DryRun should false
	if DB.DryRun {
		t.Fatal("Failed expect DB.DryRun to be false")
	}

	if DB.Dialector.Name() == "sqlserver" {
		t.Skip("Skip SQL Server for this test, because it too difference with other dialects.")
	}

	date, _ := time.ParseInLocation("2006-01-02", "2021-10-18", time.Local)

	// find
	sql := DB.ToSQL(func(tx *gorm.DB) *gorm.DB {