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design-serialization-schema

pjt222
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About

This skill helps developers design and evolve serialization schemas using JSON Schema, Protocol Buffers, or Apache Avro. It covers versioning, backward compatibility, validation rules, and evolution strategies for long-lived data formats. Use it when defining new API contracts, adding fields without breaking consumers, or migrating between schema versions.

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Documentation

序列化模式之設

立版本清明之序列化模式,使之隨時演進而不破消費者。

用時

  • 定新 API 契約或資料交換格式
  • 於既有模式加欄而不破消費者
  • 於模式版本間遷移
  • 擇模式系統(JSON Schema、Protobuf、Avro)
  • 書用於自動執行之資料驗證規則

  • 必要:資料模型(實體關係、欄類型、約束)
  • 必要:相容之要(誰消費此資料,舊格式須可讀多久)
  • 可選:欲演進之既有模式
  • 可選:性能之要(驗證速度、模式註冊表整合)
  • 可選:目標序列化格式(JSON、二進制、列式)

第一步:擇模式系統

SystemFormatStrengthsBest For
JSON SchemaJSONWidely supported, flexible validationREST APIs, config validation
Protocol BuffersBinaryCompact, fast, strong typing, built-in evolutiongRPC, microservices
Apache AvroBinary/JSONSchema in data, excellent evolution supportKafka, data pipelines
XML Schema (XSD)XMLComprehensive typing, namespace supportEnterprise/legacy SOAP
TypeBox/ZodTypeScriptType inference, runtime validationTypeScript APIs

得: 依生態、性能之要與演進之需而擇模式系統。 敗則: 不確則始於 JSON Schema——工具支持最廣,可疊於既有 JSON API 之上。

第二步:設核心模式

JSON Schema 例:

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://example.com/schemas/measurement/v1",
  "title": "Measurement",
  "description": "A sensor measurement reading",
  "type": "object",
  "required": ["sensor_id", "value", "unit", "timestamp"],
  "properties": {
    "sensor_id": {
      "type": "string",
      "pattern": "^[a-z]+-[0-9]+$",
      "description": "Unique sensor identifier (lowercase-digits format)"
    },
    "value": {
      "type": "number",
      "description": "Measured value"
    },
    "unit": {
      "type": "string",
      "enum": ["celsius", "fahrenheit", "kelvin", "percent", "ppm"],
      "description": "Unit of measurement"
    },
    "timestamp": {
      "type": "string",
      "format": "date-time",
      "description": "ISO 8601 timestamp with timezone"
    },
    "metadata": {
      "type": "object",
      "additionalProperties": true,
      "description": "Optional key-value metadata"
    }
  },
  "additionalProperties": false
}

Protocol Buffers 例:

syntax = "proto3";
package sensors.v1;

import "google/protobuf/timestamp.proto";

// Measurement represents a single sensor reading.
message Measurement {
  string sensor_id = 1;         // Unique sensor identifier
  double value = 2;             // Measured value
  Unit unit = 3;                // Unit of measurement
  google.protobuf.Timestamp timestamp = 4;
  map<string, string> metadata = 5; // Optional key-value metadata
}

enum Unit {
  UNIT_UNSPECIFIED = 0;
  UNIT_CELSIUS = 1;
  UNIT_FAHRENHEIT = 2;
  UNIT_KELVIN = 3;
  UNIT_PERCENT = 4;
  UNIT_PPM = 5;
}

Apache Avro 例:

{
  "type": "record",
  "name": "Measurement",
  "namespace": "com.example.sensors",
  "doc": "A sensor measurement reading",
  "fields": [
    {"name": "sensor_id", "type": "string", "doc": "Unique sensor identifier"},
    {"name": "value", "type": "double", "doc": "Measured value"},
    {"name": "unit", "type": {"type": "enum", "name": "Unit", "symbols": ["CELSIUS", "FAHRENHEIT", "KELVIN", "PERCENT", "PPM"]}},
    {"name": "timestamp", "type": {"type": "long", "logicalType": "timestamp-millis"}},
    {"name": "metadata", "type": ["null", {"type": "map", "values": "string"}], "default": null}
  ]
}

得: 模式自帶說明,含描述、約束、類型之明定。 敗則: 資料模型未穩則記為 draft 而勿發至註冊表。

第三步:謀模式之演進

相容規則:

ChangeBackwards Compatible?Forwards Compatible?Safe?
Add optional fieldYesYesYes
Add required fieldNoYesNo (breaks existing consumers)
Remove optional fieldYesNoCareful (producers may still send)
Remove required fieldYesNoCareful
Rename a fieldNoNoNo (use alias + deprecation)
Change field typeNoNoNo (add new field, deprecate old)
Add enum valueYes (if consumers ignore unknown)NoDepends on implementation
Remove enum valueNoYesNo

穩演進之策:

  1. 僅加可選欄,附合理默認值
  2. 勿除勿改名——棄用之可也
  3. 標識符中標版本v1v2
  4. 用模式註冊表以處二進制格式(Avro/Protobuf 之 Confluent Schema Registry)

Protobuf 演進規則:

// v1 — original
message Measurement {
  string sensor_id = 1;
  double value = 2;
  Unit unit = 3;
}

// v2 — safe evolution
message Measurement {
  string sensor_id = 1;
  double value = 2;
  Unit unit = 3;
  // NEW: added in v2 — old clients ignore this field
  google.protobuf.Timestamp timestamp = 4;
  // DEPRECATED: use sensor_id instead
  reserved 6;
  reserved "old_sensor_name";
}

JSON Schema 版本化:

{
  "$id": "https://example.com/schemas/measurement/v2",
  "allOf": [
    {"$ref": "https://example.com/schemas/measurement/v1"},
    {
      "properties": {
        "location": {
          "type": "string",
          "description": "Added in v2: GPS coordinates"
        }
      }
    }
  ]
}

得: 演進之謀已書:何改穩、何改須新版。 敗則: 破壞性改不可避則升版(v1 → v2),遷移期並行支持。

第四步:施模式驗證

# JSON Schema validation (Python)
from jsonschema import validate, ValidationError
import json

schema = json.load(open("measurement_v1.json"))

def validate_measurement(data: dict) -> list[str]:
    """Validate a measurement against the schema. Returns list of errors."""
    errors = []
    try:
        validate(instance=data, schema=schema)
    except ValidationError as e:
        errors.append(f"{e.json_path}: {e.message}")
    return errors

# Usage
errors = validate_measurement({"sensor_id": "s-01", "value": "not_a_number"})
# → ["$.value: 'not_a_number' is not of type 'number'"]
// TypeScript with Zod (runtime + compile-time)
import { z } from 'zod';

const MeasurementSchema = z.object({
  sensor_id: z.string().regex(/^[a-z]+-[0-9]+$/),
  value: z.number(),
  unit: z.enum(['celsius', 'fahrenheit', 'kelvin', 'percent', 'ppm']),
  timestamp: z.string().datetime(),
  metadata: z.record(z.string()).optional(),
});

type Measurement = z.infer<typeof MeasurementSchema>;

// Validation
const result = MeasurementSchema.safeParse(inputData);
if (!result.success) {
  console.error(result.error.issues);
}

得: 系統邊界(API 端點、文件攝入)處之入資料皆行驗證。 敗則: 記驗證錯誤及全負載(遮蔽敏感欄)以利排查。

第五步:書模式之文檔

立模式文檔頁:

# Measurement Schema (v1)

## Overview
Represents a single sensor reading with metadata.

## Fields
| Field | Type | Required | Description | Constraints |
|-------|------|----------|-------------|-------------|
| sensor_id | string | Yes | Unique sensor ID | Pattern: `^[a-z]+-[0-9]+$` |
| value | number | Yes | Measured value | Any valid IEEE 754 double |
| unit | enum | Yes | Unit of measurement | One of: celsius, fahrenheit, kelvin, percent, ppm |
| timestamp | string | Yes | Reading time | ISO 8601 with timezone |
| metadata | object | No | Key-value pairs | String keys and values |

## Changelog
| Version | Date | Changes |
|---------|------|---------|
| v1 | 2025-03-01 | Initial schema |

## Compatibility
- **Backwards**: Consumers of v1 will continue to work with future versions
- **Policy**: Only additive, optional field changes between minor versions

得: 文檔自動生成或隨模式定義同步。 敗則: 文檔與模式偏離則於 CI 中加察驗文檔對模式源之合。

  • 模式用合於用例之系統(JSON Schema、Protobuf、Avro)
  • 諸欄皆有類型、描述、約束
  • 必選欄與可選欄明分
  • 演進之策已書(穩改、版本化政策)
  • 系統邊界處已施驗證
  • 模式已版本化且有變更日誌
  • 往返測試:序列化 → 反序列化 → 比對,證無資料失

  • 過早過嚴:新模式嚴驗阻迭代。始時寬(additionalProperties: true),後漸收緊
  • 無默認值:加必選欄而無默認則破諸既有資料。新欄恆備默認
  • 略 null:諸模式不明處 null/缺欄。明分可空與可選
  • 版本於負載而非 URL:長存資料(儲存、事件)將模式版本嵌於資料中,勿僅於端點 URL
  • 枚舉之盡:加新枚舉值或使用窮盡 switch 之消費者崩。書明未知值宜優雅處之

  • serialize-data-formats — 格式之擇與編解碼之實現
  • implement-pharma-serialisation — 藥業序列化(監管模式)
  • write-validation-documentation — 監管模式之驗證文檔

GitHub Repository

pjt222/agent-almanac
Path: i18n/wenyan/skills/design-serialization-schema
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