528 lines
16 KiB
Markdown
528 lines
16 KiB
Markdown
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# OneApp Cache Plugin 缓存插件
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## 模块概述
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`one_app_cache_plugin` 是 OneApp 车联网生态中的原生缓存插件，负责为 Flutter 应用提供高效的原生缓存能力。该插件通过平台通道实现 Flutter 与 Android/iOS 原生缓存系统的交互，为应用数据缓存提供底层支持。
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### 基本信息
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- **模块名称**: one_app_cache_plugin
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- **版本**: 0.0.4
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- **类型**: Flutter Plugin（原生插件）
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- **Flutter 版本**: >=3.3.0
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- **Dart 版本**: >=3.0.0 <4.0.0
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## 功能特性
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### 核心功能
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1. **多级缓存系统**
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- 内存缓存（L1 Cache）
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- 磁盘缓存（L2 Cache）
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- 网络缓存（L3 Cache）
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- 分布式缓存支持
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2. **缓存策略管理**
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- LRU（最近最少使用）淘汰
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- LFU（最少使用频率）淘汰
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- TTL（生存时间）过期
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- 自定义淘汰策略
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3. **数据类型支持**
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- 字符串数据缓存
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- 二进制数据缓存
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- JSON对象缓存
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- 文件资源缓存
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4. **性能优化**
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- 异步操作支持
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- 批量操作优化
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- 预加载机制
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- 智能压缩存储
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## 技术架构
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### 目录结构
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```
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one_app_cache_plugin/
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├── lib/ # Dart代码
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│ ├── one_app_cache_plugin.dart # 插件入口
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│ ├── src/ # 源代码
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│ │ ├── cache_manager.dart # 缓存管理器
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│ │ ├── cache_strategy.dart # 缓存策略
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│ │ ├── cache_models.dart # 数据模型
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│ │ └── platform_interface.dart # 平台接口
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│ └── one_app_cache_plugin_platform_interface.dart
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├── android/ # Android原生代码
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│ ├── src/main/kotlin/
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│ │ └── com/oneapp/cache/
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│ │ ├── OneAppCachePlugin.kt # 主插件类
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│ │ ├── MemoryCache.kt # 内存缓存
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│ │ ├── DiskCache.kt # 磁盘缓存
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│ │ ├── CacheStrategy.kt # 缓存策略
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│ │ └── CacheUtils.kt # 缓存工具
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│ └── build.gradle
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├── ios/ # iOS原生代码
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│ ├── Classes/
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│ │ ├── OneAppCachePlugin.swift # 主插件类
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│ │ ├── MemoryCache.swift # 内存缓存
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│ │ ├── DiskCache.swift # 磁盘缓存
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│ │ ├── CacheStrategy.swift # 缓存策略
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│ │ └── CacheUtils.swift # 缓存工具
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│ └── one_app_cache_plugin.podspec
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├── example/ # 示例应用
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└── test/ # 测试文件
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```
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### 依赖关系
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#### 核心依赖
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- `plugin_platform_interface: ^2.0.2` - 插件平台接口
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## 核心模块分析
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### 1. Flutter端实现
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#### 插件入口 (`lib/one_app_cache_plugin.dart`)
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```dart
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class OneAppCachePlugin {
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static const MethodChannel _channel = MethodChannel('one_app_cache_plugin');
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/// 获取缓存数据
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static Future<String?> get(String key) async {
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return await _channel.invokeMethod('get', {'key': key});
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}
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/// 设置缓存数据
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static Future<bool> set(String key, String value, {Duration? ttl}) async {
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final result = await _channel.invokeMethod('set', {
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'key': key,
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'value': value,
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'ttl': ttl?.inMilliseconds,
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});
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return result ?? false;
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}
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/// 删除缓存数据
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static Future<bool> delete(String key) async {
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final result = await _channel.invokeMethod('delete', {'key': key});
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return result ?? false;
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}
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/// 清空所有缓存
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static Future<bool> clear() async {
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final result = await _channel.invokeMethod('clear');
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return result ?? false;
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}
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/// 获取缓存统计信息
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static Future<CacheStats> getStats() async {
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final result = await _channel.invokeMethod('getStats');
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return CacheStats.fromMap(result);
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}
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}
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```
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#### 缓存管理器 (`lib/src/cache_manager.dart`)
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```dart
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class CacheManager {
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static final CacheManager _instance = CacheManager._internal();
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factory CacheManager() => _instance;
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CacheManager._internal();
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/// 配置缓存策略
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Future<void> configure(CacheConfig config) async {
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await OneAppCachePlugin.configure(config);
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}
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/// 智能缓存获取
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Future<T?> getOrSet<T>(
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String key,
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Future<T> Function() valueFactory, {
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Duration? ttl,
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CacheLevel level = CacheLevel.all,
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}) async {
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// 先尝试从缓存获取
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final cached = await get<T>(key, level: level);
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if (cached != null) return cached;
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// 缓存未命中，获取新值并缓存
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final value = await valueFactory();
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await set(key, value, ttl: ttl, level: level);
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return value;
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}
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/// 批量操作
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Future<Map<String, T?>> getBatch<T>(List<String> keys) async {
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return await OneAppCachePlugin.getBatch(keys);
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}
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/// 预热缓存
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Future<void> preload(Map<String, dynamic> data) async {
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await OneAppCachePlugin.preload(data);
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}
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}
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```
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### 2. Android端实现
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#### 主插件类 (`OneAppCachePlugin.kt`)
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```kotlin
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class OneAppCachePlugin: FlutterPlugin, MethodCallHandler {
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private lateinit var context: Context
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private lateinit var memoryCache: MemoryCache
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private lateinit var diskCache: DiskCache
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private lateinit var cacheStrategy: CacheStrategy
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override fun onAttachedToEngine(binding: FlutterPlugin.FlutterPluginBinding) {
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context = binding.applicationContext
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initializeCaches()
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val channel = MethodChannel(binding.binaryMessenger, "one_app_cache_plugin")
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channel.setMethodCallHandler(this)
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}
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private fun initializeCaches() {
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memoryCache = MemoryCache(context)
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diskCache = DiskCache(context)
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cacheStrategy = CacheStrategy()
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}
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override fun onMethodCall(call: MethodCall, result: Result) {
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when (call.method) {
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"get" -> handleGet(call, result)
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"set" -> handleSet(call, result)
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"delete" -> handleDelete(call, result)
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"clear" -> handleClear(call, result)
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"getStats" -> handleGetStats(call, result)
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"configure" -> handleConfigure(call, result)
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else -> result.notImplemented()
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}
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}
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private fun handleGet(call: MethodCall, result: Result) {
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val key = call.argument<String>("key")
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if (key == null) {
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result.error("INVALID_ARGUMENT", "Key cannot be null", null)
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return
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}
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// 多级缓存查找
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var value = memoryCache.get(key)
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if (value == null) {
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value = diskCache.get(key)
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if (value != null) {
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// 将磁盘缓存的数据提升到内存缓存
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memoryCache.set(key, value)
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}
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}
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result.success(value)
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}
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private fun handleSet(call: MethodCall, result: Result) {
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val key = call.argument<String>("key")
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val value = call.argument<String>("value")
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val ttl = call.argument<Long>("ttl")
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if (key == null || value == null) {
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result.error("INVALID_ARGUMENT", "Key and value cannot be null", null)
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return
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}
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val success = try {
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memoryCache.set(key, value, ttl)
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diskCache.set(key, value, ttl)
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true
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} catch (e: Exception) {
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false
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}
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result.success(success)
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}
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}
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```
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#### 内存缓存 (`MemoryCache.kt`)
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```kotlin
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class MemoryCache(private val context: Context) {
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private val cache = LruCache<String, CacheEntry>(getMaxMemoryCacheSize())
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fun get(key: String): String? {
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val entry = cache.get(key) ?: return null
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// 检查是否过期
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if (entry.isExpired()) {
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cache.remove(key)
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return null
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}
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return entry.value
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}
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fun set(key: String, value: String, ttl: Long? = null) {
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val expiryTime = ttl?.let { System.currentTimeMillis() + it }
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val entry = CacheEntry(value, expiryTime)
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cache.put(key, entry)
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}
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private fun getMaxMemoryCacheSize(): Int {
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val maxMemory = (Runtime.getRuntime().maxMemory() / 1024).toInt()
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return maxMemory / 8 // 使用最大内存的1/8作为缓存大小
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}
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}
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data class CacheEntry(
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val value: String,
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val expiryTime: Long? = null
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) {
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fun isExpired(): Boolean {
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return expiryTime?.let { System.currentTimeMillis() > it } ?: false
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}
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}
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```
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#### 磁盘缓存 (`DiskCache.kt`)
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```kotlin
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class DiskCache(private val context: Context) {
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private val cacheDir = File(context.cacheDir, "one_app_cache")
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private val metadataFile = File(cacheDir, "metadata.json")
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private val metadata = mutableMapOf<String, CacheMetadata>()
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init {
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if (!cacheDir.exists()) {
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cacheDir.mkdirs()
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}
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loadMetadata()
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}
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fun get(key: String): String? {
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val meta = metadata[key] ?: return null
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// 检查是否过期
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if (meta.isExpired()) {
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delete(key)
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return null
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}
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val file = File(cacheDir, meta.filename)
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return if (file.exists()) {
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try {
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file.readText()
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} catch (e: Exception) {
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null
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}
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} else null
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}
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fun set(key: String, value: String, ttl: Long? = null) {
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val filename = generateFilename(key)
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val file = File(cacheDir, filename)
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try {
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file.writeText(value)
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val expiryTime = ttl?.let { System.currentTimeMillis() + it }
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metadata[key] = CacheMetadata(filename, expiryTime, System.currentTimeMillis())
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saveMetadata()
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} catch (e: Exception) {
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// 处理写入错误
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}
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}
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private fun generateFilename(key: String): String {
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return key.hashCode().toString() + ".cache"
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}
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}
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```
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### 3. iOS端实现
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#### 主插件类 (`OneAppCachePlugin.swift`)
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```swift
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public class OneAppCachePlugin: NSObject, FlutterPlugin {
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private var memoryCache: MemoryCache!
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private var diskCache: DiskCache!
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public static func register(with registrar: FlutterPluginRegistrar) {
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let channel = FlutterMethodChannel(name: "one_app_cache_plugin",
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binaryMessenger: registrar.messenger())
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let instance = OneAppCachePlugin()
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instance.initializeCaches()
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registrar.addMethodCallDelegate(instance, channel: channel)
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}
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private func initializeCaches() {
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memoryCache = MemoryCache()
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diskCache = DiskCache()
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}
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public func handle(_ call: FlutterMethodCall, result: @escaping FlutterResult) {
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switch call.method {
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case "get":
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|
|
handleGet(call: call, result: result)
|
|||
|
|
case "set":
|
|||
|
|
handleSet(call: call, result: result)
|
|||
|
|
case "delete":
|
|||
|
|
handleDelete(call: call, result: result)
|
|||
|
|
case "clear":
|
|||
|
|
handleClear(call: call, result: result)
|
|||
|
|
default:
|
|||
|
|
result(FlutterMethodNotImplemented)
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
private func handleGet(call: FlutterMethodCall, result: @escaping FlutterResult) {
|
|||
|
|
guard let args = call.arguments as? [String: Any],
|
|||
|
|
let key = args["key"] as? String else {
|
|||
|
|
result(FlutterError(code: "INVALID_ARGUMENT",
|
|||
|
|
message: "Key is required",
|
|||
|
|
details: nil))
|
|||
|
|
return
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
// 多级缓存查找
|
|||
|
|
if let value = memoryCache.get(key: key) {
|
|||
|
|
result(value)
|
|||
|
|
return
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
if let value = diskCache.get(key: key) {
|
|||
|
|
// 提升到内存缓存
|
|||
|
|
memoryCache.set(key: key, value: value)
|
|||
|
|
result(value)
|
|||
|
|
return
|
|||
|
|
}
|
|||
|
|
|
|||
|
|
result(nil)
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
## 缓存策略设计
|
|||
|
|
|
|||
|
|
### 淘汰策略
|
|||
|
|
1. **LRU (Least Recently Used)**
|
|||
|
|
- 淘汰最近最少使用的数据
|
|||
|
|
- 适用于访问模式相对稳定的场景
|
|||
|
|
- 实现简单，性能良好
|
|||
|
|
|
|||
|
|
2. **LFU (Least Frequently Used)**
|
|||
|
|
- 淘汰使用频率最低的数据
|
|||
|
|
- 适用于热点数据明显的场景
|
|||
|
|
- 需要维护访问频率统计
|
|||
|
|
|
|||
|
|
3. **TTL (Time To Live)**
|
|||
|
|
- 基于时间的自动过期
|
|||
|
|
- 适用于时效性数据
|
|||
|
|
- 可与其他策略组合使用
|
|||
|
|
|
|||
|
|
4. **FIFO (First In First Out)**
|
|||
|
|
- 先进先出的简单策略
|
|||
|
|
- 实现简单但效果有限
|
|||
|
|
- 适用于对缓存效果要求不高的场景
|
|||
|
|
|
|||
|
|
### 多级缓存架构
|
|||
|
|
```
|
|||
|
|
应用层
|
|||
|
|
↓
|
|||
|
|
Flutter缓存管理器
|
|||
|
|
↓
|
|||
|
|
L1: 内存缓存 (NSCache/LruCache)
|
|||
|
|
↓
|
|||
|
|
L2: 磁盘缓存 (本地文件系统)
|
|||
|
|
↓
|
|||
|
|
L3: 网络缓存 (HTTP缓存/CDN)
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
## 性能优化
|
|||
|
|
|
|||
|
|
### 内存优化
|
|||
|
|
- **智能大小调整**: 根据可用内存动态调整缓存大小
|
|||
|
|
- **内存压力监控**: 监听系统内存压力事件
|
|||
|
|
- **延迟加载**: 按需加载缓存数据
|
|||
|
|
- **压缩存储**: 对大数据进行压缩存储
|
|||
|
|
|
|||
|
|
### 磁盘优化
|
|||
|
|
- **异步I/O**: 所有磁盘操作异步执行
|
|||
|
|
- **批量操作**: 批量读写减少I/O次数
|
|||
|
|
- **文件压缩**: 压缩存储节省空间
|
|||
|
|
- **定期清理**: 定期清理过期和无效文件
|
|||
|
|
|
|||
|
|
### 网络优化
|
|||
|
|
- **预加载**: 预测性数据预加载
|
|||
|
|
- **增量更新**: 仅传输变化数据
|
|||
|
|
- **并发控制**: 限制并发网络请求
|
|||
|
|
- **断点续传**: 支持大文件断点续传
|
|||
|
|
|
|||
|
|
## 数据安全
|
|||
|
|
|
|||
|
|
### 加密存储
|
|||
|
|
- **敏感数据加密**: 对敏感缓存数据进行加密
|
|||
|
|
- **密钥管理**: 安全的密钥存储和管理
|
|||
|
|
- **完整性验证**: 数据完整性校验
|
|||
|
|
- **安全擦除**: 安全删除敏感数据
|
|||
|
|
|
|||
|
|
### 权限控制
|
|||
|
|
- **访问控制**: 基于权限的缓存访问
|
|||
|
|
- **沙盒隔离**: 应用间缓存数据隔离
|
|||
|
|
- **审计日志**: 缓存访问审计记录
|
|||
|
|
- **异常监控**: 异常访问行为监控
|
|||
|
|
|
|||
|
|
## 监控和诊断
|
|||
|
|
|
|||
|
|
### 性能指标
|
|||
|
|
```dart
|
|||
|
|
class CacheStats {
|
|||
|
|
final int hitCount; // 命中次数
|
|||
|
|
final int missCount; // 未命中次数
|
|||
|
|
final int evictionCount; // 淘汰次数
|
|||
|
|
final double hitRate; // 命中率
|
|||
|
|
final int size; // 当前大小
|
|||
|
|
final int maxSize; // 最大大小
|
|||
|
|
|
|||
|
|
double get hitRate => hitCount / (hitCount + missCount);
|
|||
|
|
}
|
|||
|
|
```
|
|||
|
|
|
|||
|
|
### 诊断工具
|
|||
|
|
- **缓存命中率监控**: 实时监控缓存效果
|
|||
|
|
- **内存使用分析**: 分析内存使用模式
|
|||
|
|
- **性能分析器**: 分析缓存操作性能
|
|||
|
|
- **调试界面**: 可视化缓存状态
|
|||
|
|
|
|||
|
|
## 测试策略
|
|||
|
|
|
|||
|
|
### 单元测试
|
|||
|
|
- **缓存操作测试**: 基本CRUD操作
|
|||
|
|
- **过期策略测试**: TTL和淘汰策略
|
|||
|
|
- **并发安全测试**: 多线程访问安全
|
|||
|
|
- **边界条件测试**: 极限情况处理
|
|||
|
|
|
|||
|
|
### 集成测试
|
|||
|
|
- **平台集成测试**: 原生平台功能
|
|||
|
|
- **性能测试**: 大数据量性能
|
|||
|
|
- **稳定性测试**: 长时间运行稳定性
|
|||
|
|
- **兼容性测试**: 不同设备和系统版本
|
|||
|
|
|
|||
|
|
### 压力测试
|
|||
|
|
- **高并发测试**: 大量并发访问
|
|||
|
|
- **大数据测试**: 大容量数据处理
|
|||
|
|
- **内存压力测试**: 低内存环境测试
|
|||
|
|
- **存储压力测试**: 存储空间不足测试
|
|||
|
|
|
|||
|
|
## 最佳实践
|
|||
|
|
|
|||
|
|
### 使用建议
|
|||
|
|
1. **合理设置TTL**: 根据数据特性设置合适的过期时间
|
|||
|
|
2. **选择合适策略**: 根据访问模式选择淘汰策略
|
|||
|
|
3. **监控缓存效果**: 定期检查命中率和性能指标
|
|||
|
|
4. **控制缓存大小**: 避免缓存过大影响性能
|
|||
|
|
|
|||
|
|
### 性能优化建议
|
|||
|
|
1. **预加载热点数据**: 应用启动时预加载重要数据
|
|||
|
|
2. **批量操作**: 尽量使用批量API减少开销
|
|||
|
|
3. **异步操作**: 避免阻塞主线程
|
|||
|
|
4. **合理清理**: 定期清理过期和不需要的缓存
|
|||
|
|
|
|||
|
|
## 总结
|
|||
|
|
|
|||
|
|
`one_app_cache_plugin` 作为 OneApp 的原生缓存插件，为Flutter应用提供了高效、可靠的多级缓存能力。通过智能的缓存策略、完善的性能优化和安全的数据保护，显著提升了应用的数据访问性能和用户体验。插件设计考虑了跨平台兼容性和可扩展性，能够适应不同的应用场景和性能要求。
|