julia-lang使用@async在并行线程中缓存数据

using Base.Threads

# 假设我们有一个耗时的数据加载函数
function load_data(key)
    println("Loading data for key $key")
    sleep(2)  # 模拟耗时操作
    return "data for $key"
end

# 缓存字典
const cache = Dict{String, String}()

# 异步加载并缓存数据的函数
function async_load_and_cache(key)
    data = load_data(key)
    cache[key] = data
    println("Cached data for key $key")
end

# 使用@async启动异步任务
function get_or_load_data(key)
    if haskey(cache, key)
        println("Returning cached data for key $key")
        return cache[key]
    else
        @async async_load_and_cache(key)
        println("Started loading data for key $key asynchronously")
        return "loading"  # 返回一个占位符，表示数据正在加载中
    end
end

# 测试函数
println(get_or_load_data("key1"))
println(get_or_load_data("key1"))  # 第二次调用应该从缓存中获取数据

using Base.Threads

const cache_mutex = Mutex()

function async_load_and_cache_safe(key)
    try
        data = load_data(key)
        lock(cache_mutex) do
            cache[key] = data
        end
        println("Cached data for key $key")
    catch e
        println("Failed to load data for key $key: $e")
    end
end

function get_or_load_data_safe(key)
    if haskey(cache, key)
        println("Returning cached data for key $key")
        return cache[key]
    else
        @async async_load_and_cache_safe(key)
        println("Started loading data for key $key asynchronously")
        return "loading"
    end
end