has       RelationshipType = "has"
)

type Relationships struct {
	HasOne    []*Relationship
	BelongsTo []*Relationship
	HasMany   []*Relationship
	Many2Many []*Relationship
	Relations map[string]*Relationship

	EmbeddedRelations map[string]*Relationships
}

type Relationship struct {
	Name                     string
	Type                     RelationshipType
	Field                    *Field

	if err != nil {
		t.Fatalf("failed to parse schema, got error %v", err)
	}

	if len(userSchema.Relationships.Relations) != 1 {
		t.Fatalf("expects 1 relations, but got %v", len(userSchema.Relationships.Relations))
	}

	if createdByRel, ok := userSchema.Relationships.Relations["CreatedBy"]; ok {
		if createdByRel.FieldSchema != userSchema {

	return names
}

// preloadEntryPoint enters layer by layer. It will call real preload if it finds the right entry point.
// If the current relationship is embedded or joined, current query will be ignored.
//
//nolint:cyclop
func preloadEntryPoint(db *gorm.DB, joins []string, relationships *schema.Relationships, preloads map[string][]interface{}, associationsConds []interface{}) error {
	preloadMap := parsePreloadMap(db.Statement.Schema, preloads)

                              to.
                            type: string
                          operator:
                            description: operator represents a key's relationship
                              to a set of values. Valid operators are In, NotIn, Exists
                              and DoesNotExist.
                            type: string
                          values:

Also, the best approach was to use already existing standards.

So, before even starting to code **FastAPI**, I spent several months studying the specs for OpenAPI, JSON Schema, OAuth2, etc. Understanding their relationship, overlap, and differences.

## Design

Then I spent some time designing the developer "API" I wanted to have as a user (as a developer using FastAPI).

		return &uni, stmt.Table
	}

	getTable := func(rel *schema.Relationship) string {
		switch rel.Type {
		case schema.HasOne, schema.HasMany:
			return rel.FieldSchema.Table
		case schema.Many2Many:
			return rel.JoinTable.Table
		}
		return stmt.Table
	}

	for _, rel := range stmt.Schema.Relationships.Relations {

 * comparator utilities, see either {@code Comparator} itself (for Java 8+), or {@code
 * com.google.common.collect.Ordering} (otherwise).
 *
 * <h3>Relationship to {@code Ordering}</h3>
 *
 * <p>In light of the significant enhancements to {@code Comparator} in Java 8, the overwhelming
 * majority of usages of {@code Ordering} can be written using only built-in JDK APIs. This class is

 * comparator utilities, see either {@code Comparator} itself (for Java 8+), or {@code
 * com.google.common.collect.Ordering} (otherwise).
 *
 * <h3>Relationship to {@code Ordering}</h3>
 *
 * <p>In light of the significant enhancements to {@code Comparator} in Java 8, the overwhelming
 * majority of usages of {@code Ordering} can be written using only built-in JDK APIs. This class is

```Python hl_lines="1  10-13  21-24"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

### Create the relationships

Now create the relationships.

For this, we use `relationship` provided by SQLAlchemy ORM.

This will become, more or less, a "magic" attribute that will contain the values from other tables related to this one.

  // When specified, it should match one the container or initContainer
  // names in the pod template.
  // +optional
  optional string containerName = 1;

  // Represents the relationship between the container exit code(s) and the
  // specified values. Containers completed with success (exit code 0) are
  // excluded from the requirement check. Possible values are:
  //