}}

	for idx, result := range results {
		t.Run(fmt.Sprintf("case #%v", idx), func(t *testing.T) {
			user, _ := schema.Parse(&tests.User{}, &sync.Map{}, db.NamingStrategy)
			stmt := &gorm.Statement{DB: db, Table: user.Table, Schema: user, Clauses: map[string]clause.Clause{}}
			clause.Expr{SQL: result.SQL, Vars: result.Vars}.Build(stmt)
			if stmt.SQL.String() != result.Result {

Directory for DBFlute client

manage.bat(sh) => 21 (jdbc):
A execution command of JDBC task
which gets your schema info and saves it to SchemaXML
located to the "schema" directory.
This task should be executed after ReplaceSchema task
and before other tasks(e.g. Generate, Document task).

manage.bat(sh) => 22 (doc):
A execution command of Document task
which creates documents, for example, SchemaHTML, HistoryHTML
to the "output/doc" directory.

It used custom types in its declarations instead of standard Python types, but it was still a huge step forward.

It also was one of the first frameworks to generate a custom schema declaring the whole API in JSON.

It was not based on a standard like OpenAPI and JSON Schema. So it wouldn't be straightforward to integrate it with other tools, like Swagger UI. But again, it was a very innovative idea.

Type\":\"date_histogram\"},\"y\":[{\"accessor\":1,\"format\":{\"id\":\"number\"},\"params\":{},\"aggType\":\"count\"}]}},\"aggs\":[{\"id\":\"1\",\"enabled\":true,\"type\":\"count\",\"schema\":\"metric\",\"params\":{\"customLabel\":\"Query Count\"}},{\"id\":\"2\",\"enabled\":true,\"type\":\"date_histogram\",\"schema\":\"segment\",\"params\":{\"field\":\"requestedAt\",\"timeRange\":{\"from\":\"now-2d\",\"to\":\"now\"},\"useNormalizedEsInterval\":true,\"interval\":\"s\",\"drop_partials\":false,\"mi...

	keys := make([]string, 0, len(mapValue))
	for k := range mapValue {
		keys = append(keys, k)
	}
	sort.Strings(keys)

	for _, k := range keys {
		value := mapValue[k]
		if stmt.Schema != nil {
			if field := stmt.Schema.LookUpField(k); field != nil {
				k = field.DBName
			}
		}

		if v, ok := selectColumns[k]; (ok && v) || (!ok && !restricted) {
			values.Columns = append(values.Columns, clause.Column{Name: k})

Das Frontend (das im Browser läuft) würde also versuchen, `/openapi.json` zu erreichen und wäre nicht in der Lage, das OpenAPI-Schema abzurufen.

Da wir für unsere Anwendung einen Proxy mit dem Pfadpräfix `/api/v1` haben, muss das Frontend das OpenAPI-Schema unter `/api/v1/openapi.json` abrufen.

```mermaid
graph LR

#
map:{
    # /- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    # o isAvailableAddingSchemaToTableSqlName: (NotRequired - Default false)
    #   [true]
    #     Add schema to table SQL name. (The table name on query is SCHEMA.TABLE)
    #
    #; isAvailableAddingSchemaToTableSqlName = false
    # - - - - - - - - - -/

    # /- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

package gorm

import (
	"context"
	"database/sql"

	"gorm.io/gorm/clause"
	"gorm.io/gorm/schema"
)

// Dialector GORM database dialector
type Dialector interface {
	Name() string
	Initialize(*DB) error
	Migrator(db *DB) Migrator
	DataTypeOf(*schema.Field) string
	DefaultValueOf(*schema.Field) clause.Expression
	BindVarTo(writer clause.Writer, stmt *Statement, v interface{})
	QuoteTo(clause.Writer, string)

* Automatyczna dokumentacja modelu danych za pomocą <a href="https://json-schema.org/" class="external-link" target="_blank"><strong>JSON Schema</strong></a> (ponieważ OpenAPI bazuje na JSON Schema).
* Zaprojektowane z myślą o zgodności z powyższymi standardami zamiast dodawania ich obsługi po fakcie.
* Możliwość automatycznego **generowania kodu klienta** w wielu językach.

You can declare extra information in `Field`, `Query`, `Body`, etc. And it will be included in the generated JSON Schema.

You will learn more about adding extra information later in the docs, when learning to declare examples.

/// warning

Extra keys passed to `Field` will also be present in the resulting OpenAPI schema for your application.