df_01_bindunbind

basic bind/unbind example

this example demonstrates both the modern df.New[T]() and traditional df.Bind() functions along with df.Unbind() for converting between structured data and go structs.

key concepts

• New[T] API: type-safe allocation using go generics
• Bind API: manual allocation control for advanced use cases
• bidirectional data mapping: convert from map[string]any to structs and back
• struct tags: use df tags for custom field mapping and validation
• nested structures: handle complex nested data with pointers to structs
• round-trip compatibility: data maintains integrity through bind/unbind cycles
• error handling: validate required fields and handle binding errors gracefully

usage

go run main.go

data structure

the example works with this user profile data:

userData := map[string]any{
    "name":   "John Doe",
    "email":  "john@example.com", 
    "age":    30,
    "active": true,
    "profile": map[string]any{
        "bio":     "Software developer",
        "website": "https://johndoe.dev",
    },
}

struct definitions

type User struct {
    Name    string `df:"required"`       // required field
    Email   string                       // default field mapping
    Age     int                          // type conversion
    Active  bool                         // boolean handling
    Profile *Profile                     // nested struct (snake_case: "profile")
}

type Profile struct {
    Bio     string
    Website string
}

workflow demonstrated

1. allocate and bind: use df.New[T]() for type-safe allocation and binding
2. unbinding: convert go structs back to map[string]any
3. round-trip: verify data integrity through the complete cycle
4. error handling: show validation behavior for missing required fields
5. manual binding: show df.Bind() for cases requiring manual allocation control

this example showcases both struct binding patterns, providing the foundation for data persistence, API marshaling, and configuration management patterns.