YAML Request

Learn how to handle YAML request bodies in Iris.

Basic YAML Handling

package main

import (
    "github.com/kataras/iris/v12"
    "gopkg.in/yaml.v3"
)

type Config struct {
    Name     string   `yaml:"name"`
    Version  string   `yaml:"version"`
    Features []string `yaml:"features"`
}

func main() {
    app := iris.New()

    app.Post("/yaml", func(ctx iris.Context) {
        var config Config
        if err := ctx.ReadYAML(&config); err != nil {
            ctx.StopWithError(iris.StatusBadRequest, err)
            return
        }

        ctx.JSON(iris.Map{
            "received": config,
        })
    })

    app.Listen(":8080")
}

YAML Validation

type Service struct {
    Name     string `yaml:"name" validate:"required"`
    Port     int    `yaml:"port" validate:"required,min=1024,max=65535"`
    Replicas int    `yaml:"replicas" validate:"required,min=1"`
}

app.Post("/validate", func(ctx iris.Context) {
    var service Service
    if err := ctx.ReadYAML(&service); err != nil {
        ctx.StopWithError(iris.StatusBadRequest, err)
        return
    }

    // Validate struct
    if err := validate.Struct(service); err != nil {
        ctx.StopWithProblem(iris.StatusBadRequest, iris.NewProblem().
            Title("Validation Error").
            DetailErr(err))
        return
    }

    ctx.JSON(iris.Map{
        "message": "YAML validated successfully",
        "service": service,
    })
})

Custom YAML Decoder

app.Post("/custom", func(ctx iris.Context) {
    decoder := yaml.NewDecoder(ctx.Request().Body)
    decoder.KnownFields(true)

    var data interface{}
    if err := decoder.Decode(&data); err != nil {
        ctx.StopWithError(iris.StatusBadRequest, err)
        return
    }

    ctx.JSON(iris.Map{
        "data": data,
    })
})

Best Practices

1. Validation:

   • Validate schema
   • Check required fields
   • Handle types
   • Set limits
   • Document requirements

2. Security:

   • Validate input
   • Set size limits
   • Check structure
   • Monitor usage
   • Handle errors

3. Performance:

   • Use appropriate decoder
   • Handle large documents
   • Monitor memory
   • Implement timeouts
   • Clean resources

4. Error Handling:

   • Provide clear messages
   • Handle validation errors
   • Log issues
   • Document errors
   • Test edge cases