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享元模式
1.1 分类
（对象）结构型
1.2 提出问题
做一个车管所系统，将会产生大量的车辆实体，如果每一个实例都保存自己的所有信息，将会需要大量内存，甚至导致程序崩溃。
1.3 解决方案
运用共享技术有效的支持大量细粒度的对象。
1.4 实现类图
- 享元模式只是一种优化。只有存在大量类似对象销毁内存的情况，才考虑使用。
- 享元（Flyweight）类包含原始对象中部分能在多个对象中共享的状态。享元中存储的状态被称为“内在状态”。传递给享元方法的状态被称为“外在状态”。
- 上下文（Context）类包含原始对象中各不相同的外在状态。上下文与享元对象组合在一起就能表示原始对象的全部状态。
- 通常情况下，原始对象的行为保留在享元类中。因此调用享元方法必须提供部分外在状态作为参数。但也可将行为移动到上下文类中，将连入的享元作为单纯的数据对象。
- 客户端（Client）负责计算或存储享元的外在状态。在客户端看来，享元是一种可在运行时进行配置的模板对象，具体的配置方式为向其方法中传入一些上下文数据参数。
- 享元工厂（Flyweight Factory）会对已有享元的缓存池进行管理。有了工厂后，客户端就无需直接创建享元，只需调用工厂并向其传递目标享元的一些内在状态即可。工厂会根据参数在之前已创建的享元中进行查找，如果找到满足条件的享元就将其返回；如果没有找到就根据参数新建享元。
1.5 示例代码
#include <iostream>
#include <string>
#include <unordered_map>using std::string;
//内部状态
struct SharedState {string m_brand;string m_model;string m_color;SharedState(const string& brand, const string model, const string color):m_brand(brand), m_model(model), m_color(color) {}friend std::ostream& operator<<(std::ostream& os, const SharedState& ss) {return os << "[" << ss.m_brand << "," << ss.m_model << "," << ss.m_color << "]";}
};
//外部状态
struct UniqueState
{std::string m_owner;std::string m_plates;UniqueState(const std::string& owner, const std::string& plates): m_owner(owner), m_plates(plates) {}friend std::ostream& operator<<(std::ostream& os, const UniqueState& us) {return os << "[ " << us.m_owner << " , " << us.m_plates << " ]";}
};//享元，存放共享状态，内部状态
class Flyweight {
private:SharedState m_sharedState;
public:Flyweight(const SharedState sharedState) : m_sharedState(sharedState) {}//使用的时候，使用外部状态作为参数，对整个context做出操作void operation(UniqueState uniqueState) const {std::cout << "Flyweight:显示内部状态（"<< m_sharedState << "),显示外部状态：（"<< uniqueState << ")\n";}
};
//享元工厂
class FlyweightFactory {
private:std::unordered_map<string, Flyweight> m_Flyweights;string getKey(const SharedState& ss) const {return ss.m_brand + "_" + ss.m_model + "_" + ss.m_color;}
public:FlyweightFactory(std::initializer_list<SharedState> share_states) {for (const SharedState& ss : share_states) {m_Flyweights.insert({ getKey(ss),Flyweight(ss) });}}Flyweight* getFlyWeight(const SharedState& shared_state) {string key = getKey(shared_state);if (m_Flyweights.find(key) == m_Flyweights.end()) {std::cout << "FlyweightFactory:没有找到需要的享元，创建一个新的。\n";m_Flyweights.insert({ key,shared_state });} else {std::cout << "FlyweightFactory:返回一个现有的享元。\n";}return &m_Flyweights.at(key);}void listFlyWeights() const {int count = m_Flyweights.size();std::cout << "\nFlyweightFactory:我有" << count << "个享元：\n";for (std::pair<std::string, Flyweight> item : m_Flyweights) {std::cout << item.first << "\n";}}
};
//上下文
class CarInfoContext {
private:Flyweight* m_flyWeight = nullptr;//内部状态UniqueState m_uniqueState;//外部状态
public:CarInfoContext(Flyweight* flyWeight, const UniqueState * unique_state) :m_flyWeight(flyWeight), m_uniqueState(*unique_state) {}void operation() {m_flyWeight->operation(m_uniqueState);}
};
//Client
class PoliceCarDatabase {
private:std::list<CarInfoContext*> carInfoDatabase;
public:~PoliceCarDatabase() {for (auto item : carInfoDatabase)delete item;}void addCarToPoliceDatabase(FlyweightFactory &ff,const string& owner, const string& plates,const string& brand, const string& model, const string& color) {std::cout << "\n客户端：添加车辆信息到数据库。\n";Flyweight* flyWeight = ff.getFlyWeight({ brand, model, color });//内部状态UniqueState uniqueState(owner, plates);//外部状态carInfoDatabase.push_back(new CarInfoContext(flyWeight, &uniqueState));std::cout << "\n客户端：数据库当前状态：\n";for (auto item : carInfoDatabase) {item->operation();}}
};
int main()
{FlyweightFactory factory({SharedState("奔驰","GLC","白色"),SharedState("奥迪","A7","黑色"),SharedState("宝马","X1","白色")});factory.listFlyWeights();PoliceCarDatabase database;database.addCarToPoliceDatabase(factory,"阿西拜", "赣ABC888", "奔驰", "GLC", "白色");factory.listFlyWeights();database.addCarToPoliceDatabase(factory,"阿西拜", "赣ABC999", "比亚迪", "唐EV", "蓝色");database.addCarToPoliceDatabase(factory,"阿西拜", "赣ABC666", "奔驰", "GLC", "白色");factory.listFlyWeights();
}
1.6 举个栗子
享元模式能有效减少在画布上渲染数百万个树状 对象时所需的内存。
1.7 总结
- 优点：如果程序中有很多相似对象，那么你将可以节省大量内存。
- 缺点：可能需要牺牲执行速度来换取内存，因为他人每次调用享元方法时都需要重新计算部分情景数据。