fn-cache


Namefn-cache JSON
Version 0.1.6 PyPI version JSON
download
home_pagehttps://github.com/leowzz/fn_cache
Summary轻量级通用缓存库
upload_time2025-07-17 11:26:59
maintainerNone
docs_urlNone
authorLeoWang
requires_python>=3.8
licenseMIT
keywords cache memory ttl lru async decorator
VCS
bugtrack_url
requirements typing-extensions pydantic fastapi loguru
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # fn_cache: 轻量级函数缓存工具

`fn_cache` 是一个专为现代 Python 应用设计的轻量级缓存库,提供统一的接口、多种缓存策略和存储后端。无论您需要简单的内存缓存还是分布式 Redis 缓存,`fn_cache` 都能轻松应对。

## ✨ 核心特性

- **多种缓存策略**: 支持 TTL (Time-To-Live) 和 LRU (Least Recently Used) 缓存淘汰策略. 支持异步函数的 LRU 缓存(async lru_cache),让异步场景下也能高效利用 LRU 策略
- **灵活的存储后端**: 内置内存和 Redis 两种存储后端,可根据需求轻松切换
- **多种序列化格式**: 支持 JSON、Pickle、MessagePack 和字符串序列化
- **版本控制机制**: 通过全局版本号实现一键失效所有缓存,便于调试和管理
- **用户级别版本控制**: 支持按用户失效缓存,适用于多用户应用场景
- **缓存键枚举**: 支持定义结构化的缓存键模板,提高代码可维护性
- **动态过期时间**: 支持根据缓存值动态计算过期时间
- **强大的装饰器**: 提供 `cached` 装饰器,支持丰富的配置,并与同步/异步函数无缝集成
- **缓存预加载**: 支持在服务启动时预先加载数据到内存缓存,提升应用初始性能
- **缓存统计**: 提供详细的缓存性能监控,包括命中率、响应时间等指标
- **内存监控**: 支持内存占用监控和定期报告
- **健壮的错误处理**: 内置 Redis 超时和连接错误处理,确保缓存问题不影响核心业务逻辑

## 🚀 快速上手

### 1. 基本用法: `cached` 装饰器

使用 `cached` 装饰器,可以轻松为函数添加缓存功能。

```python
from fn_cache import cached, SerializerType


# 使用内存TTL缓存 (默认)
@cached(ttl_seconds=60)
def get_some_data(user_id: int):
    print("正在执行复杂的数据查询...")
    return f"这是用户 {user_id} 的数据"


# 使用不同序列化器
@cached(
    storage_type='memory',
    serializer_type=SerializerType.JSON,
    ttl_seconds=300
)
def get_user_profile(user_id: int):
    return {"user_id": user_id, "name": f"用户_{user_id}"}


# 第一次调用,函数会执行
get_some_data(123)  # 输出: "正在执行复杂的数据查询..."

# 第二次调用,直接从缓存返回
get_some_data(123)  # 无输出
```

### 2. 异步函数支持

```python
@cached(ttl_seconds=300)
async def fetch_user_data(user_id: int):
    print(f"正在从数据库获取用户 {user_id} 的数据...")
    await asyncio.sleep(1)  # 模拟数据库查询延迟
    return {
        "user_id": user_id,
        "name": f"User_{user_id}",
        "email": f"user{user_id}@example.com"
    }
```

### 3. 缓存预加载

对于需要快速响应的内存缓存数据,可以使用预加载功能,在服务启动时就将热点数据加载到缓存中。

```python
from fn_cache import cached, preload_all_caches
import asyncio


# 1. 定义一个数据提供者函数
def user_ids_provider():
    # 这些ID可以是来自配置、数据库或其他来源
    for user_id in [1, 2, 3]:
        yield (user_id,), {}  # (args, kwargs)


# 2. 在装饰器中指定 preload_provider
@cached(storage_type='memory', preload_provider=user_ids_provider)
def get_user_name(user_id: int):
    print(f"从数据库查询用户 {user_id}...")
    return f"用户_{user_id}"


# 3. 在应用启动时,调用预加载函数
async def main():
    await preload_all_caches()

    # 此时,数据已在缓存中,函数不会再次执行
    print(get_user_name(1))  # 直接输出 "用户_1"
    print(get_user_name(2))  # 直接输出 "用户_2"


if __name__ == "__main__":
    asyncio.run(main())
```

### 4. 缓存统计和监控

```python
from fn_cache import get_cache_statistics, start_cache_memory_monitoring

# 启动内存监控
start_cache_memory_monitoring(interval_seconds=300)  # 每5分钟监控一次

# 获取缓存统计信息
stats = get_cache_statistics()
for cache_id, cache_stats in stats.items():
    print(f"缓存 {cache_id}:")
    print(f"  命中率: {cache_stats['hit_rate']:.2%}")
    print(f"  平均响应时间: {cache_stats['avg_response_time']:.4f}s")
```

## 📚 API 参考

### `cached` 装饰器类

这是 `fn_cache` 的核心装饰器。

**参数**:

- `cache_type` (`CacheType`): 缓存类型,`CacheType.TTL` (默认) 或 `CacheType.LRU`
- `storage_type` (`StorageType`): 存储类型,`StorageType.MEMORY` (默认) 或 `StorageType.REDIS`
- `serializer_type` (`SerializerType`): 序列化类型,`SerializerType.JSON` (默认)、`SerializerType.PICKLE`、`SerializerType.MESSAGEPACK` 或 `SerializerType.STRING`
- `ttl_seconds` (`int`): TTL 缓存的过期时间(秒),默认为 600
- `max_size` (`int`): LRU 缓存的最大容量,默认为 1000
- `key_func` (`Callable`): 自定义缓存键生成函数。接收与被装饰函数相同的参数
- `key_params` (`list[str]`): 用于自动生成缓存键的参数名列表
- `prefix` (`str`): 缓存键的前缀,默认为 `"fn_cache:"`
- `preload_provider` (`Callable`): 一个函数,返回一个可迭代对象,用于缓存预加载。迭代的每个元素都是一个 `(args, kwargs)` 元组

### `CacheKeyEnum` 基类

缓存键枚举基类,用于定义结构化的缓存键模板。

```python
class CacheKeyEnum(str, Enum):
    """缓存键枚举基类"""
    
    def format(self, **kwargs) -> str:
        """格式化缓存键,替换模板中的参数"""
        return self.value.format(**kwargs)
```

### `UniversalCacheManager` 类

提供了所有底层缓存操作的接口。

**核心方法**:

- `get(key, user_id=None)`: (异步) 获取缓存
- `set(key, value, ttl_seconds=None, user_id=None)`: (异步) 设置缓存
- `delete(key)`: (异步) 删除缓存
- `get_sync(key, user_id=None)` / `set_sync(...)` / `delete_sync(key)`: 内存缓存的同步版本
- `increment_global_version()`: (异步) 递增全局版本号,使所有缓存失效
- `increment_user_version(user_id)`: (异步) 递增用户版本号,使该用户的所有缓存失效
- `invalidate_all()`: (异步) 使所有缓存失效
- `invalidate_user_cache(user_id)`: (异步) 使用户的所有缓存失效

**核心属性**:

- `is_global_cache_enabled_sync` (`bool`): (同步) 检查内存缓存是否已启用

### 全局控制函数

- `preload_all_caches()`: (异步) 执行所有已注册的缓存预加载任务
- `invalidate_all_caches()`: (异步) 失效所有使用默认管理器的缓存
- `invalidate_user_cache(user_id)`: (异步) 使用户的所有缓存失效
- `get_cache_statistics(cache_id=None)`: 获取缓存统计信息
- `reset_cache_statistics(cache_id=None)`: 重置缓存统计信息
- `start_cache_memory_monitoring(interval_seconds=300)`: 启动内存监控
- `get_cache_memory_usage()`: 获取内存使用情况

## ⚙️ 高级用法

### 切换到 Redis 存储

只需更改 `storage_type` 参数即可。

```python
@cached(
    storage_type=StorageType.REDIS, 
    serializer_type=SerializerType.MESSAGEPACK,
    ttl_seconds=3600
)
async def get_shared_data():
    # ... 从数据库或RPC获取数据 ...
    return {"data": "some shared data"}
```

### 使用 LRU 缓存策略

```python
@cached(
    cache_type=CacheType.LRU,
    max_size=100,
    storage_type=StorageType.MEMORY
)
def calculate_fibonacci(n: int) -> int:
    """计算斐波那契数列(同步函数示例)"""
    if n <= 1:
        return n
    return calculate_fibonacci(n-1) + calculate_fibonacci(n-2)
```

### 自定义缓存键

对于复杂的参数,可以提供自定义的 `key_func`。

```python
def make_user_key(user: User):
    return f"user_cache:{user.org_id}:{user.id}"

@cached(key_func=make_user_key)
def get_user_permissions(user: User):
    # ...
    return ["perm1", "perm2"]
```

或者,使用 `key_params` 自动生成。

```python
@cached(key_params=['user_id', 'tenant_id'])
def get_document(doc_id: int, user_id: int, tenant_id: str):
    # 自动生成的key类似于: "app.module.get_document:user_id=123:tenant_id=abc"
    pass
```

### 用户级别缓存管理

```python
from fn_cache import UniversalCacheManager, CacheConfig, StorageType


class UserCacheService:
    def __init__(self):
        config = CacheConfig(
            storage_type=StorageType.REDIS,
            serializer_type=SerializerType.JSON,
            prefix="user_cache:"
        )
        self.cache = UniversalCacheManager(config)

    async def get_user_data(self, user_id: int):
        cache_key = f"user_data:{user_id}"

        # 使用用户级别版本控制
        cached_data = await self.cache.get(cache_key, user_id=str(user_id))
        if cached_data:
            return cached_data

        # 缓存未命中,获取数据
        user_data = await self._fetch_user_data(user_id)

        # 存储到缓存,使用用户级别版本控制
        await self.cache.set(cache_key, user_data, user_id=str(user_id))
        return user_data

    async def invalidate_user_cache(self, user_id: int):
        """使用户的所有缓存失效"""
        await self.cache.invalidate_user_cache(str(user_id))
```

### 动态过期时间

```python
@cached(
    ttl_seconds=300
)
async def get_user_vip_info(user_id: int):
    # VIP用户缓存1小时,普通用户缓存30分钟
    pass
```

### 多参数缓存键

```python
@cached(
    ttl_seconds=300
)
async def get_user_profile(user_id: int, tenant_id: str):
    # 支持多租户的用户资料缓存
    pass
```

## 🔧 配置选项

### CacheConfig 配置类

```python
from fn_cache import CacheConfig, CacheType, StorageType, SerializerType

config = CacheConfig(
    cache_type=CacheType.TTL,  # 缓存策略: TTL 或 LRU
    storage_type=StorageType.MEMORY,  # 存储后端: MEMORY 或 REDIS
    serializer_type=SerializerType.JSON,  # 序列化类型: JSON, PICKLE, MESSAGEPACK, STRING
    ttl_seconds=600,  # TTL 过期时间(秒)
    max_size=1000,  # LRU 最大容量
    prefix="cache:",  # 缓存键前缀
    global_version_key="fn_cache:global:version",  # 全局版本号键
    user_version_key="fn_cache:user:version:{user_id}",  # 用户版本号键
    make_expire_sec_func=None,  # 动态过期时间函数
    serializer_kwargs={},  # 序列化器参数
    enable_statistics=True,  # 是否启用统计
    enable_memory_monitoring=True,  # 是否启用内存监控
    redis_config={  # Redis连接配置
        "host": "localhost",
        "port": 6379,
        "db": 0,
        "decode_responses": True,
        "socket_timeout": 1.0,
        "socket_connect_timeout": 1.0,
        "retry_on_timeout": True,
        "health_check_interval": 30,
    }
)
```

## 💡 设计理念

- **统一接口**: `UniversalCacheManager` 提供了统一的接口,屏蔽了不同存储后端的实现细节
- **版本控制**: 通过全局版本号机制实现一键失效所有缓存,便于调试和管理
- **用户级别控制**: 支持按用户失效缓存,适用于多用户应用场景
- **结构化缓存键**: 通过枚举定义缓存键模板,提高代码可维护性和一致性
- **装饰器模式**: `cached` 使用装饰器模式,以非侵入的方式为函数添加缓存逻辑
- **错误隔离**: 内置 Redis 超时和连接错误处理,确保缓存问题不影响核心业务逻辑
- **性能优化**: 支持缓存预加载和动态过期时间,提升应用性能
- **监控统计**: 提供详细的缓存性能监控,帮助优化缓存策略

## 📝 使用示例

更多详细的使用示例,请参考 `examples_v2.py` 文件,其中包含了:

- 不同序列化器的使用
- 缓存统计和性能监控
- 内存监控功能
- 批量操作和缓存预热
- 用户级别版本控制
- 直接使用缓存管理器

## 🔄 v2.0 新特性

相比 v1.0,v2.0 版本新增了以下特性:

1. **多种序列化格式支持**: 支持 JSON、Pickle、MessagePack 和字符串序列化
2. **缓存统计功能**: 提供详细的缓存性能监控,包括命中率、响应时间等指标
3. **更灵活的配置**: 支持序列化器参数、Redis 连接配置等
4. **更好的错误处理**: 改进的异常处理和日志记录
5. **性能优化**: 更高效的序列化和反序列化
6. **监控增强**: 更详细的内存使用监控和统计报告

## 📦 安装

```bash
pip install fn_cache
```

## 🤝 贡献

欢迎提交 Issue 和 Pull Request!

## 🪪 许可证

MIT License

            

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    "download_url": "https://files.pythonhosted.org/packages/51/1f/edf8b359234d2352417a28d6b2571220a7ee320b81de2fbf243c541d9a0c/fn_cache-0.1.6.tar.gz",
    "platform": null,
    "description": "# fn_cache: \u8f7b\u91cf\u7ea7\u51fd\u6570\u7f13\u5b58\u5de5\u5177\n\n`fn_cache` \u662f\u4e00\u4e2a\u4e13\u4e3a\u73b0\u4ee3 Python \u5e94\u7528\u8bbe\u8ba1\u7684\u8f7b\u91cf\u7ea7\u7f13\u5b58\u5e93\uff0c\u63d0\u4f9b\u7edf\u4e00\u7684\u63a5\u53e3\u3001\u591a\u79cd\u7f13\u5b58\u7b56\u7565\u548c\u5b58\u50a8\u540e\u7aef\u3002\u65e0\u8bba\u60a8\u9700\u8981\u7b80\u5355\u7684\u5185\u5b58\u7f13\u5b58\u8fd8\u662f\u5206\u5e03\u5f0f Redis \u7f13\u5b58\uff0c`fn_cache` \u90fd\u80fd\u8f7b\u677e\u5e94\u5bf9\u3002\n\n## \u2728 \u6838\u5fc3\u7279\u6027\n\n- **\u591a\u79cd\u7f13\u5b58\u7b56\u7565**: \u652f\u6301 TTL (Time-To-Live) \u548c LRU (Least Recently Used) \u7f13\u5b58\u6dd8\u6c70\u7b56\u7565. \u652f\u6301\u5f02\u6b65\u51fd\u6570\u7684 LRU \u7f13\u5b58\uff08async lru_cache\uff09\uff0c\u8ba9\u5f02\u6b65\u573a\u666f\u4e0b\u4e5f\u80fd\u9ad8\u6548\u5229\u7528 LRU \u7b56\u7565\n- **\u7075\u6d3b\u7684\u5b58\u50a8\u540e\u7aef**: \u5185\u7f6e\u5185\u5b58\u548c Redis \u4e24\u79cd\u5b58\u50a8\u540e\u7aef\uff0c\u53ef\u6839\u636e\u9700\u6c42\u8f7b\u677e\u5207\u6362\n- **\u591a\u79cd\u5e8f\u5217\u5316\u683c\u5f0f**: \u652f\u6301 JSON\u3001Pickle\u3001MessagePack \u548c\u5b57\u7b26\u4e32\u5e8f\u5217\u5316\n- **\u7248\u672c\u63a7\u5236\u673a\u5236**: \u901a\u8fc7\u5168\u5c40\u7248\u672c\u53f7\u5b9e\u73b0\u4e00\u952e\u5931\u6548\u6240\u6709\u7f13\u5b58\uff0c\u4fbf\u4e8e\u8c03\u8bd5\u548c\u7ba1\u7406\n- **\u7528\u6237\u7ea7\u522b\u7248\u672c\u63a7\u5236**: \u652f\u6301\u6309\u7528\u6237\u5931\u6548\u7f13\u5b58\uff0c\u9002\u7528\u4e8e\u591a\u7528\u6237\u5e94\u7528\u573a\u666f\n- **\u7f13\u5b58\u952e\u679a\u4e3e**: \u652f\u6301\u5b9a\u4e49\u7ed3\u6784\u5316\u7684\u7f13\u5b58\u952e\u6a21\u677f\uff0c\u63d0\u9ad8\u4ee3\u7801\u53ef\u7ef4\u62a4\u6027\n- **\u52a8\u6001\u8fc7\u671f\u65f6\u95f4**: \u652f\u6301\u6839\u636e\u7f13\u5b58\u503c\u52a8\u6001\u8ba1\u7b97\u8fc7\u671f\u65f6\u95f4\n- **\u5f3a\u5927\u7684\u88c5\u9970\u5668**: \u63d0\u4f9b `cached` \u88c5\u9970\u5668\uff0c\u652f\u6301\u4e30\u5bcc\u7684\u914d\u7f6e\uff0c\u5e76\u4e0e\u540c\u6b65/\u5f02\u6b65\u51fd\u6570\u65e0\u7f1d\u96c6\u6210\n- **\u7f13\u5b58\u9884\u52a0\u8f7d**: \u652f\u6301\u5728\u670d\u52a1\u542f\u52a8\u65f6\u9884\u5148\u52a0\u8f7d\u6570\u636e\u5230\u5185\u5b58\u7f13\u5b58\uff0c\u63d0\u5347\u5e94\u7528\u521d\u59cb\u6027\u80fd\n- **\u7f13\u5b58\u7edf\u8ba1**: \u63d0\u4f9b\u8be6\u7ec6\u7684\u7f13\u5b58\u6027\u80fd\u76d1\u63a7\uff0c\u5305\u62ec\u547d\u4e2d\u7387\u3001\u54cd\u5e94\u65f6\u95f4\u7b49\u6307\u6807\n- **\u5185\u5b58\u76d1\u63a7**: \u652f\u6301\u5185\u5b58\u5360\u7528\u76d1\u63a7\u548c\u5b9a\u671f\u62a5\u544a\n- **\u5065\u58ee\u7684\u9519\u8bef\u5904\u7406**: \u5185\u7f6e Redis \u8d85\u65f6\u548c\u8fde\u63a5\u9519\u8bef\u5904\u7406\uff0c\u786e\u4fdd\u7f13\u5b58\u95ee\u9898\u4e0d\u5f71\u54cd\u6838\u5fc3\u4e1a\u52a1\u903b\u8f91\n\n## \ud83d\ude80 \u5feb\u901f\u4e0a\u624b\n\n### 1. \u57fa\u672c\u7528\u6cd5: `cached` \u88c5\u9970\u5668\n\n\u4f7f\u7528 `cached` \u88c5\u9970\u5668\uff0c\u53ef\u4ee5\u8f7b\u677e\u4e3a\u51fd\u6570\u6dfb\u52a0\u7f13\u5b58\u529f\u80fd\u3002\n\n```python\nfrom fn_cache import cached, SerializerType\n\n\n# \u4f7f\u7528\u5185\u5b58TTL\u7f13\u5b58 (\u9ed8\u8ba4)\n@cached(ttl_seconds=60)\ndef get_some_data(user_id: int):\n    print(\"\u6b63\u5728\u6267\u884c\u590d\u6742\u7684\u6570\u636e\u67e5\u8be2...\")\n    return f\"\u8fd9\u662f\u7528\u6237 {user_id} \u7684\u6570\u636e\"\n\n\n# \u4f7f\u7528\u4e0d\u540c\u5e8f\u5217\u5316\u5668\n@cached(\n    storage_type='memory',\n    serializer_type=SerializerType.JSON,\n    ttl_seconds=300\n)\ndef get_user_profile(user_id: int):\n    return {\"user_id\": user_id, \"name\": f\"\u7528\u6237_{user_id}\"}\n\n\n# \u7b2c\u4e00\u6b21\u8c03\u7528\uff0c\u51fd\u6570\u4f1a\u6267\u884c\nget_some_data(123)  # \u8f93\u51fa: \"\u6b63\u5728\u6267\u884c\u590d\u6742\u7684\u6570\u636e\u67e5\u8be2...\"\n\n# \u7b2c\u4e8c\u6b21\u8c03\u7528\uff0c\u76f4\u63a5\u4ece\u7f13\u5b58\u8fd4\u56de\nget_some_data(123)  # \u65e0\u8f93\u51fa\n```\n\n### 2. \u5f02\u6b65\u51fd\u6570\u652f\u6301\n\n```python\n@cached(ttl_seconds=300)\nasync def fetch_user_data(user_id: int):\n    print(f\"\u6b63\u5728\u4ece\u6570\u636e\u5e93\u83b7\u53d6\u7528\u6237 {user_id} \u7684\u6570\u636e...\")\n    await asyncio.sleep(1)  # \u6a21\u62df\u6570\u636e\u5e93\u67e5\u8be2\u5ef6\u8fdf\n    return {\n        \"user_id\": user_id,\n        \"name\": f\"User_{user_id}\",\n        \"email\": f\"user{user_id}@example.com\"\n    }\n```\n\n### 3. \u7f13\u5b58\u9884\u52a0\u8f7d\n\n\u5bf9\u4e8e\u9700\u8981\u5feb\u901f\u54cd\u5e94\u7684\u5185\u5b58\u7f13\u5b58\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528\u9884\u52a0\u8f7d\u529f\u80fd\uff0c\u5728\u670d\u52a1\u542f\u52a8\u65f6\u5c31\u5c06\u70ed\u70b9\u6570\u636e\u52a0\u8f7d\u5230\u7f13\u5b58\u4e2d\u3002\n\n```python\nfrom fn_cache import cached, preload_all_caches\nimport asyncio\n\n\n# 1. \u5b9a\u4e49\u4e00\u4e2a\u6570\u636e\u63d0\u4f9b\u8005\u51fd\u6570\ndef user_ids_provider():\n    # \u8fd9\u4e9bID\u53ef\u4ee5\u662f\u6765\u81ea\u914d\u7f6e\u3001\u6570\u636e\u5e93\u6216\u5176\u4ed6\u6765\u6e90\n    for user_id in [1, 2, 3]:\n        yield (user_id,), {}  # (args, kwargs)\n\n\n# 2. \u5728\u88c5\u9970\u5668\u4e2d\u6307\u5b9a preload_provider\n@cached(storage_type='memory', preload_provider=user_ids_provider)\ndef get_user_name(user_id: int):\n    print(f\"\u4ece\u6570\u636e\u5e93\u67e5\u8be2\u7528\u6237 {user_id}...\")\n    return f\"\u7528\u6237_{user_id}\"\n\n\n# 3. \u5728\u5e94\u7528\u542f\u52a8\u65f6\uff0c\u8c03\u7528\u9884\u52a0\u8f7d\u51fd\u6570\nasync def main():\n    await preload_all_caches()\n\n    # \u6b64\u65f6\uff0c\u6570\u636e\u5df2\u5728\u7f13\u5b58\u4e2d\uff0c\u51fd\u6570\u4e0d\u4f1a\u518d\u6b21\u6267\u884c\n    print(get_user_name(1))  # \u76f4\u63a5\u8f93\u51fa \"\u7528\u6237_1\"\n    print(get_user_name(2))  # \u76f4\u63a5\u8f93\u51fa \"\u7528\u6237_2\"\n\n\nif __name__ == \"__main__\":\n    asyncio.run(main())\n```\n\n### 4. \u7f13\u5b58\u7edf\u8ba1\u548c\u76d1\u63a7\n\n```python\nfrom fn_cache import get_cache_statistics, start_cache_memory_monitoring\n\n# \u542f\u52a8\u5185\u5b58\u76d1\u63a7\nstart_cache_memory_monitoring(interval_seconds=300)  # \u6bcf5\u5206\u949f\u76d1\u63a7\u4e00\u6b21\n\n# \u83b7\u53d6\u7f13\u5b58\u7edf\u8ba1\u4fe1\u606f\nstats = get_cache_statistics()\nfor cache_id, cache_stats in stats.items():\n    print(f\"\u7f13\u5b58 {cache_id}:\")\n    print(f\"  \u547d\u4e2d\u7387: {cache_stats['hit_rate']:.2%}\")\n    print(f\"  \u5e73\u5747\u54cd\u5e94\u65f6\u95f4: {cache_stats['avg_response_time']:.4f}s\")\n```\n\n## \ud83d\udcda API \u53c2\u8003\n\n### `cached` \u88c5\u9970\u5668\u7c7b\n\n\u8fd9\u662f `fn_cache` \u7684\u6838\u5fc3\u88c5\u9970\u5668\u3002\n\n**\u53c2\u6570**:\n\n- `cache_type` (`CacheType`): \u7f13\u5b58\u7c7b\u578b\uff0c`CacheType.TTL` (\u9ed8\u8ba4) \u6216 `CacheType.LRU`\n- `storage_type` (`StorageType`): \u5b58\u50a8\u7c7b\u578b\uff0c`StorageType.MEMORY` (\u9ed8\u8ba4) \u6216 `StorageType.REDIS`\n- `serializer_type` (`SerializerType`): \u5e8f\u5217\u5316\u7c7b\u578b\uff0c`SerializerType.JSON` (\u9ed8\u8ba4)\u3001`SerializerType.PICKLE`\u3001`SerializerType.MESSAGEPACK` \u6216 `SerializerType.STRING`\n- `ttl_seconds` (`int`): TTL \u7f13\u5b58\u7684\u8fc7\u671f\u65f6\u95f4\uff08\u79d2\uff09\uff0c\u9ed8\u8ba4\u4e3a 600\n- `max_size` (`int`): LRU \u7f13\u5b58\u7684\u6700\u5927\u5bb9\u91cf\uff0c\u9ed8\u8ba4\u4e3a 1000\n- `key_func` (`Callable`): \u81ea\u5b9a\u4e49\u7f13\u5b58\u952e\u751f\u6210\u51fd\u6570\u3002\u63a5\u6536\u4e0e\u88ab\u88c5\u9970\u51fd\u6570\u76f8\u540c\u7684\u53c2\u6570\n- `key_params` (`list[str]`): \u7528\u4e8e\u81ea\u52a8\u751f\u6210\u7f13\u5b58\u952e\u7684\u53c2\u6570\u540d\u5217\u8868\n- `prefix` (`str`): \u7f13\u5b58\u952e\u7684\u524d\u7f00\uff0c\u9ed8\u8ba4\u4e3a `\"fn_cache:\"`\n- `preload_provider` (`Callable`): \u4e00\u4e2a\u51fd\u6570\uff0c\u8fd4\u56de\u4e00\u4e2a\u53ef\u8fed\u4ee3\u5bf9\u8c61\uff0c\u7528\u4e8e\u7f13\u5b58\u9884\u52a0\u8f7d\u3002\u8fed\u4ee3\u7684\u6bcf\u4e2a\u5143\u7d20\u90fd\u662f\u4e00\u4e2a `(args, kwargs)` \u5143\u7ec4\n\n### `CacheKeyEnum` \u57fa\u7c7b\n\n\u7f13\u5b58\u952e\u679a\u4e3e\u57fa\u7c7b\uff0c\u7528\u4e8e\u5b9a\u4e49\u7ed3\u6784\u5316\u7684\u7f13\u5b58\u952e\u6a21\u677f\u3002\n\n```python\nclass CacheKeyEnum(str, Enum):\n    \"\"\"\u7f13\u5b58\u952e\u679a\u4e3e\u57fa\u7c7b\"\"\"\n    \n    def format(self, **kwargs) -> str:\n        \"\"\"\u683c\u5f0f\u5316\u7f13\u5b58\u952e\uff0c\u66ff\u6362\u6a21\u677f\u4e2d\u7684\u53c2\u6570\"\"\"\n        return self.value.format(**kwargs)\n```\n\n### `UniversalCacheManager` \u7c7b\n\n\u63d0\u4f9b\u4e86\u6240\u6709\u5e95\u5c42\u7f13\u5b58\u64cd\u4f5c\u7684\u63a5\u53e3\u3002\n\n**\u6838\u5fc3\u65b9\u6cd5**:\n\n- `get(key, user_id=None)`: (\u5f02\u6b65) \u83b7\u53d6\u7f13\u5b58\n- `set(key, value, ttl_seconds=None, user_id=None)`: (\u5f02\u6b65) \u8bbe\u7f6e\u7f13\u5b58\n- `delete(key)`: (\u5f02\u6b65) \u5220\u9664\u7f13\u5b58\n- `get_sync(key, user_id=None)` / `set_sync(...)` / `delete_sync(key)`: \u5185\u5b58\u7f13\u5b58\u7684\u540c\u6b65\u7248\u672c\n- `increment_global_version()`: (\u5f02\u6b65) \u9012\u589e\u5168\u5c40\u7248\u672c\u53f7\uff0c\u4f7f\u6240\u6709\u7f13\u5b58\u5931\u6548\n- `increment_user_version(user_id)`: (\u5f02\u6b65) \u9012\u589e\u7528\u6237\u7248\u672c\u53f7\uff0c\u4f7f\u8be5\u7528\u6237\u7684\u6240\u6709\u7f13\u5b58\u5931\u6548\n- `invalidate_all()`: (\u5f02\u6b65) \u4f7f\u6240\u6709\u7f13\u5b58\u5931\u6548\n- `invalidate_user_cache(user_id)`: (\u5f02\u6b65) \u4f7f\u7528\u6237\u7684\u6240\u6709\u7f13\u5b58\u5931\u6548\n\n**\u6838\u5fc3\u5c5e\u6027**:\n\n- `is_global_cache_enabled_sync` (`bool`): (\u540c\u6b65) \u68c0\u67e5\u5185\u5b58\u7f13\u5b58\u662f\u5426\u5df2\u542f\u7528\n\n### \u5168\u5c40\u63a7\u5236\u51fd\u6570\n\n- `preload_all_caches()`: (\u5f02\u6b65) \u6267\u884c\u6240\u6709\u5df2\u6ce8\u518c\u7684\u7f13\u5b58\u9884\u52a0\u8f7d\u4efb\u52a1\n- `invalidate_all_caches()`: (\u5f02\u6b65) \u5931\u6548\u6240\u6709\u4f7f\u7528\u9ed8\u8ba4\u7ba1\u7406\u5668\u7684\u7f13\u5b58\n- `invalidate_user_cache(user_id)`: (\u5f02\u6b65) \u4f7f\u7528\u6237\u7684\u6240\u6709\u7f13\u5b58\u5931\u6548\n- `get_cache_statistics(cache_id=None)`: \u83b7\u53d6\u7f13\u5b58\u7edf\u8ba1\u4fe1\u606f\n- `reset_cache_statistics(cache_id=None)`: \u91cd\u7f6e\u7f13\u5b58\u7edf\u8ba1\u4fe1\u606f\n- `start_cache_memory_monitoring(interval_seconds=300)`: \u542f\u52a8\u5185\u5b58\u76d1\u63a7\n- `get_cache_memory_usage()`: \u83b7\u53d6\u5185\u5b58\u4f7f\u7528\u60c5\u51b5\n\n## \u2699\ufe0f \u9ad8\u7ea7\u7528\u6cd5\n\n### \u5207\u6362\u5230 Redis \u5b58\u50a8\n\n\u53ea\u9700\u66f4\u6539 `storage_type` \u53c2\u6570\u5373\u53ef\u3002\n\n```python\n@cached(\n    storage_type=StorageType.REDIS, \n    serializer_type=SerializerType.MESSAGEPACK,\n    ttl_seconds=3600\n)\nasync def get_shared_data():\n    # ... \u4ece\u6570\u636e\u5e93\u6216RPC\u83b7\u53d6\u6570\u636e ...\n    return {\"data\": \"some shared data\"}\n```\n\n### \u4f7f\u7528 LRU \u7f13\u5b58\u7b56\u7565\n\n```python\n@cached(\n    cache_type=CacheType.LRU,\n    max_size=100,\n    storage_type=StorageType.MEMORY\n)\ndef calculate_fibonacci(n: int) -> int:\n    \"\"\"\u8ba1\u7b97\u6590\u6ce2\u90a3\u5951\u6570\u5217\uff08\u540c\u6b65\u51fd\u6570\u793a\u4f8b\uff09\"\"\"\n    if n <= 1:\n        return n\n    return calculate_fibonacci(n-1) + calculate_fibonacci(n-2)\n```\n\n### \u81ea\u5b9a\u4e49\u7f13\u5b58\u952e\n\n\u5bf9\u4e8e\u590d\u6742\u7684\u53c2\u6570\uff0c\u53ef\u4ee5\u63d0\u4f9b\u81ea\u5b9a\u4e49\u7684 `key_func`\u3002\n\n```python\ndef make_user_key(user: User):\n    return f\"user_cache:{user.org_id}:{user.id}\"\n\n@cached(key_func=make_user_key)\ndef get_user_permissions(user: User):\n    # ...\n    return [\"perm1\", \"perm2\"]\n```\n\n\u6216\u8005\uff0c\u4f7f\u7528 `key_params` \u81ea\u52a8\u751f\u6210\u3002\n\n```python\n@cached(key_params=['user_id', 'tenant_id'])\ndef get_document(doc_id: int, user_id: int, tenant_id: str):\n    # \u81ea\u52a8\u751f\u6210\u7684key\u7c7b\u4f3c\u4e8e: \"app.module.get_document:user_id=123:tenant_id=abc\"\n    pass\n```\n\n### \u7528\u6237\u7ea7\u522b\u7f13\u5b58\u7ba1\u7406\n\n```python\nfrom fn_cache import UniversalCacheManager, CacheConfig, StorageType\n\n\nclass UserCacheService:\n    def __init__(self):\n        config = CacheConfig(\n            storage_type=StorageType.REDIS,\n            serializer_type=SerializerType.JSON,\n            prefix=\"user_cache:\"\n        )\n        self.cache = UniversalCacheManager(config)\n\n    async def get_user_data(self, user_id: int):\n        cache_key = f\"user_data:{user_id}\"\n\n        # \u4f7f\u7528\u7528\u6237\u7ea7\u522b\u7248\u672c\u63a7\u5236\n        cached_data = await self.cache.get(cache_key, user_id=str(user_id))\n        if cached_data:\n            return cached_data\n\n        # \u7f13\u5b58\u672a\u547d\u4e2d\uff0c\u83b7\u53d6\u6570\u636e\n        user_data = await self._fetch_user_data(user_id)\n\n        # \u5b58\u50a8\u5230\u7f13\u5b58\uff0c\u4f7f\u7528\u7528\u6237\u7ea7\u522b\u7248\u672c\u63a7\u5236\n        await self.cache.set(cache_key, user_data, user_id=str(user_id))\n        return user_data\n\n    async def invalidate_user_cache(self, user_id: int):\n        \"\"\"\u4f7f\u7528\u6237\u7684\u6240\u6709\u7f13\u5b58\u5931\u6548\"\"\"\n        await self.cache.invalidate_user_cache(str(user_id))\n```\n\n### \u52a8\u6001\u8fc7\u671f\u65f6\u95f4\n\n```python\n@cached(\n    ttl_seconds=300\n)\nasync def get_user_vip_info(user_id: int):\n    # VIP\u7528\u6237\u7f13\u5b581\u5c0f\u65f6\uff0c\u666e\u901a\u7528\u6237\u7f13\u5b5830\u5206\u949f\n    pass\n```\n\n### \u591a\u53c2\u6570\u7f13\u5b58\u952e\n\n```python\n@cached(\n    ttl_seconds=300\n)\nasync def get_user_profile(user_id: int, tenant_id: str):\n    # \u652f\u6301\u591a\u79df\u6237\u7684\u7528\u6237\u8d44\u6599\u7f13\u5b58\n    pass\n```\n\n## \ud83d\udd27 \u914d\u7f6e\u9009\u9879\n\n### CacheConfig \u914d\u7f6e\u7c7b\n\n```python\nfrom fn_cache import CacheConfig, CacheType, StorageType, SerializerType\n\nconfig = CacheConfig(\n    cache_type=CacheType.TTL,  # \u7f13\u5b58\u7b56\u7565: TTL \u6216 LRU\n    storage_type=StorageType.MEMORY,  # \u5b58\u50a8\u540e\u7aef: MEMORY \u6216 REDIS\n    serializer_type=SerializerType.JSON,  # \u5e8f\u5217\u5316\u7c7b\u578b: JSON, PICKLE, MESSAGEPACK, STRING\n    ttl_seconds=600,  # TTL \u8fc7\u671f\u65f6\u95f4\uff08\u79d2\uff09\n    max_size=1000,  # LRU \u6700\u5927\u5bb9\u91cf\n    prefix=\"cache:\",  # \u7f13\u5b58\u952e\u524d\u7f00\n    global_version_key=\"fn_cache:global:version\",  # \u5168\u5c40\u7248\u672c\u53f7\u952e\n    user_version_key=\"fn_cache:user:version:{user_id}\",  # \u7528\u6237\u7248\u672c\u53f7\u952e\n    make_expire_sec_func=None,  # \u52a8\u6001\u8fc7\u671f\u65f6\u95f4\u51fd\u6570\n    serializer_kwargs={},  # \u5e8f\u5217\u5316\u5668\u53c2\u6570\n    enable_statistics=True,  # \u662f\u5426\u542f\u7528\u7edf\u8ba1\n    enable_memory_monitoring=True,  # \u662f\u5426\u542f\u7528\u5185\u5b58\u76d1\u63a7\n    redis_config={  # Redis\u8fde\u63a5\u914d\u7f6e\n        \"host\": \"localhost\",\n        \"port\": 6379,\n        \"db\": 0,\n        \"decode_responses\": True,\n        \"socket_timeout\": 1.0,\n        \"socket_connect_timeout\": 1.0,\n        \"retry_on_timeout\": True,\n        \"health_check_interval\": 30,\n    }\n)\n```\n\n## \ud83d\udca1 \u8bbe\u8ba1\u7406\u5ff5\n\n- **\u7edf\u4e00\u63a5\u53e3**: `UniversalCacheManager` \u63d0\u4f9b\u4e86\u7edf\u4e00\u7684\u63a5\u53e3\uff0c\u5c4f\u853d\u4e86\u4e0d\u540c\u5b58\u50a8\u540e\u7aef\u7684\u5b9e\u73b0\u7ec6\u8282\n- **\u7248\u672c\u63a7\u5236**: \u901a\u8fc7\u5168\u5c40\u7248\u672c\u53f7\u673a\u5236\u5b9e\u73b0\u4e00\u952e\u5931\u6548\u6240\u6709\u7f13\u5b58\uff0c\u4fbf\u4e8e\u8c03\u8bd5\u548c\u7ba1\u7406\n- **\u7528\u6237\u7ea7\u522b\u63a7\u5236**: \u652f\u6301\u6309\u7528\u6237\u5931\u6548\u7f13\u5b58\uff0c\u9002\u7528\u4e8e\u591a\u7528\u6237\u5e94\u7528\u573a\u666f\n- **\u7ed3\u6784\u5316\u7f13\u5b58\u952e**: \u901a\u8fc7\u679a\u4e3e\u5b9a\u4e49\u7f13\u5b58\u952e\u6a21\u677f\uff0c\u63d0\u9ad8\u4ee3\u7801\u53ef\u7ef4\u62a4\u6027\u548c\u4e00\u81f4\u6027\n- **\u88c5\u9970\u5668\u6a21\u5f0f**: `cached` \u4f7f\u7528\u88c5\u9970\u5668\u6a21\u5f0f\uff0c\u4ee5\u975e\u4fb5\u5165\u7684\u65b9\u5f0f\u4e3a\u51fd\u6570\u6dfb\u52a0\u7f13\u5b58\u903b\u8f91\n- **\u9519\u8bef\u9694\u79bb**: \u5185\u7f6e Redis \u8d85\u65f6\u548c\u8fde\u63a5\u9519\u8bef\u5904\u7406\uff0c\u786e\u4fdd\u7f13\u5b58\u95ee\u9898\u4e0d\u5f71\u54cd\u6838\u5fc3\u4e1a\u52a1\u903b\u8f91\n- **\u6027\u80fd\u4f18\u5316**: \u652f\u6301\u7f13\u5b58\u9884\u52a0\u8f7d\u548c\u52a8\u6001\u8fc7\u671f\u65f6\u95f4\uff0c\u63d0\u5347\u5e94\u7528\u6027\u80fd\n- **\u76d1\u63a7\u7edf\u8ba1**: \u63d0\u4f9b\u8be6\u7ec6\u7684\u7f13\u5b58\u6027\u80fd\u76d1\u63a7\uff0c\u5e2e\u52a9\u4f18\u5316\u7f13\u5b58\u7b56\u7565\n\n## \ud83d\udcdd \u4f7f\u7528\u793a\u4f8b\n\n\u66f4\u591a\u8be6\u7ec6\u7684\u4f7f\u7528\u793a\u4f8b\uff0c\u8bf7\u53c2\u8003 `examples_v2.py` \u6587\u4ef6\uff0c\u5176\u4e2d\u5305\u542b\u4e86\uff1a\n\n- \u4e0d\u540c\u5e8f\u5217\u5316\u5668\u7684\u4f7f\u7528\n- \u7f13\u5b58\u7edf\u8ba1\u548c\u6027\u80fd\u76d1\u63a7\n- \u5185\u5b58\u76d1\u63a7\u529f\u80fd\n- \u6279\u91cf\u64cd\u4f5c\u548c\u7f13\u5b58\u9884\u70ed\n- \u7528\u6237\u7ea7\u522b\u7248\u672c\u63a7\u5236\n- \u76f4\u63a5\u4f7f\u7528\u7f13\u5b58\u7ba1\u7406\u5668\n\n## \ud83d\udd04 v2.0 \u65b0\u7279\u6027\n\n\u76f8\u6bd4 v1.0\uff0cv2.0 \u7248\u672c\u65b0\u589e\u4e86\u4ee5\u4e0b\u7279\u6027\uff1a\n\n1. **\u591a\u79cd\u5e8f\u5217\u5316\u683c\u5f0f\u652f\u6301**: \u652f\u6301 JSON\u3001Pickle\u3001MessagePack \u548c\u5b57\u7b26\u4e32\u5e8f\u5217\u5316\n2. **\u7f13\u5b58\u7edf\u8ba1\u529f\u80fd**: \u63d0\u4f9b\u8be6\u7ec6\u7684\u7f13\u5b58\u6027\u80fd\u76d1\u63a7\uff0c\u5305\u62ec\u547d\u4e2d\u7387\u3001\u54cd\u5e94\u65f6\u95f4\u7b49\u6307\u6807\n3. **\u66f4\u7075\u6d3b\u7684\u914d\u7f6e**: \u652f\u6301\u5e8f\u5217\u5316\u5668\u53c2\u6570\u3001Redis \u8fde\u63a5\u914d\u7f6e\u7b49\n4. **\u66f4\u597d\u7684\u9519\u8bef\u5904\u7406**: \u6539\u8fdb\u7684\u5f02\u5e38\u5904\u7406\u548c\u65e5\u5fd7\u8bb0\u5f55\n5. **\u6027\u80fd\u4f18\u5316**: \u66f4\u9ad8\u6548\u7684\u5e8f\u5217\u5316\u548c\u53cd\u5e8f\u5217\u5316\n6. **\u76d1\u63a7\u589e\u5f3a**: \u66f4\u8be6\u7ec6\u7684\u5185\u5b58\u4f7f\u7528\u76d1\u63a7\u548c\u7edf\u8ba1\u62a5\u544a\n\n## \ud83d\udce6 \u5b89\u88c5\n\n```bash\npip install fn_cache\n```\n\n## \ud83e\udd1d \u8d21\u732e\n\n\u6b22\u8fce\u63d0\u4ea4 Issue \u548c Pull Request\uff01\n\n## \ud83e\udeaa \u8bb8\u53ef\u8bc1\n\nMIT License\n",
    "bugtrack_url": null,
    "license": "MIT",
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        "Repository": "https://github.com/leowzz/fn_cache"
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