Python中JSON数据验证的三种专业级方案

# 安装依赖: pip install jsonschema
from jsonschema import validate, ValidationError

schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "number", "minimum": 0}
    },
    "required": ["name"]
}

data = {"name": "Alice", "age": 25}

try:
    validate(instance=data, schema=schema)
    print("数据合法")
except ValidationError as e:
    print("验证失败:", e.message)

# 安装: pip install pydantic
from pydantic import BaseModel, ValidationError

class User(BaseModel):
    name: str
    age: int = 0

try:
    user = User(name="Bob", age=30)
    print(user.model_dump())
except ValidationError as e:
    print(e.json())

{
  "id": 1,
  "name": "Alice",
  "active": true,
  "tags": ["user", "admin"],
  "profile": {
    "email": "alice@example.com",
    "age": 30
  }
}

if (user && user.profile && user.profile.address) {
  console.log(user.profile.address.city);
} else {
  console.log("地址信息缺失");
}

func validateNested(v interface{}) error {
    if v == nil {
        return fmt.Errorf("value cannot be nil")
    }
    rv := reflect.ValueOf(v)
    switch rv.Kind() {
    case reflect.Map:
        for _, key := range rv.MapKeys() {
            if err := validateNested(rv.MapIndex(key).Interface()); err != nil {
                return err
            }
        }
    case reflect.String:
        if rv.Len() == 0 {
            return fmt.Errorf("string field cannot be empty")
        }
    }
    return nil
}

func processData() error {
    err := parseInput()
    if err != nil {
        return fmt.Errorf("input layer: %w", err)
    }
    return nil
}

// 调用时可逐层展开错误链
if err != nil {
    var parseErr *ParseError
    if errors.As(err, &parseErr) {
        log.Printf("Parsing failed: %v", parseErr)
    }
}

curl -s http://api.service/v1/health | jq '.status'
curl -s http://auth.service/v2/token?user=test | jq '.expires_in'

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "type": "object",
  "properties": {
    "name": { "type": "string" },
    "age": { "type": "number", "minimum": 0 }
  },
  "required": ["name"]
}

pip install jsonschema

schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "number", "minimum": 0}
    },
    "required": ["name"]
}

from jsonschema import validate, ValidationError

try:
    validate(instance={"name": "Alice", "age": 25}, schema=schema)
except ValidationError as e:
    print(f"校验失败: {e.message}")

validate.RegisterValidation("mobile", func(fl validator.FieldLevel) bool {
    mobile := fl.Field().String()
    matched, _ := regexp.MatchString(`^1[3-9]\d{9}$`, mobile)
    return matched
})

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int
    is_active: bool = True

user = User(name="Alice", age="25")
print(user.age)  # 输出: 25 (自动转为 int)

type User struct {
    ID       *int64     `json:"id,omitempty"`
    Profile  *Profile   `json:"profile,omitempty"`
    Metadata *Metadata  `json:"metadata,omitempty"`
}

@validate_fields({
    'email': {'required': True, 'format': 'email'},
    'age': {'default': 18, 'min': 0, 'max': 120}
})
def create_user(data):
    return save_to_db(data)

@app.post("/register")
async def register_user(user: UserCreate):
    # 异步保存用户并发送确认邮件
    await save_to_db(user)
    await send_confirmation_email(user.email)
    return {"status": "registered"}

// 示例：在边缘节点部署的 Go 微服务片段
func handleInference(w http.ResponseWriter, r *http.Request) {
    var req ImageRequest
    if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
        http.Error(w, "invalid request", http.StatusBadRequest)
        return
    }
    // 调用本地 ONNX Runtime 执行推理
    result, err := onnxModel.Predict(req.Data)
    if err != nil {
        http.Error(w, "inference failed", http.StatusInternalServerError)
        return
    }
    json.NewEncoder(w).Encode(result)
}