Elixir/OTP 连续后台作业和状态查找

Elixir/OTP continuous background job and state lookup

我正在尝试模拟一个在后台连续 运行ning 的简单振荡器(集成正弦函数)。但是在某些时候,我希望能够请求它的值(电压和时间),该值保持在其内部状态。那是因为在后面的一点上,我需要一个受监督的振荡器池,他们的主管将对 voltage/values 和其他一些操作进行平均。

我采用了这种方法,对此我不是 100% 满意,因为在退出 get_state 服务器实施之前必须 运行 run() 有点痛苦, IE。 handle_call({:get_state, pid}.....).

还有其他方法可以尝试吗?

defmodule World.Cell do
  use GenServer
  @timedelay  2000
  # API #
  #######
  def start_link do
    GenServer.start_link(__MODULE__, [], [name: {:global, __MODULE__}])
  end
  def run do
    GenServer.cast({:global, __MODULE__}, :run)
  end
  def get_state(pid) do
    GenServer.call(pid, {:get_state, pid})
  end

  # Callbacks #
  #############
  def init([]) do
    :random.seed(:os.timestamp)
    time = :random.uniform
    voltage = :math.sin(2 * :math.pi + time)
    state = %{time: time, voltage: voltage }
    {:ok, state, @timedelay}
  end
  def handle_cast(:run, state) do
    new_time = state.time + :random.uniform/12
    new_voltage = :math.sin(2 * :math.pi + new_time)
    new_state = %{time: new_time, voltage: new_voltage }
    IO.puts "VALUES #{inspect self()} t/v #{new_time}/#{new_voltage}"
    {:noreply, new_state, @timedelay}
  end
  def handle_info(:timeout, state) do
    run()  # <--------------------- ALWAYS HAVING TO RUN IT
    {:noreply, state, @timedelay}
  end
  def handle_call({:get_state, pid}, _from, state) do
    IO.puts "getting state"
    run() # <--------------------- RUN UNLESS IT STOPS after response
    {:reply, state, state}
  end
end

更新 1

将 "ticking" 委托给基础 Process 的方法,感谢我在 ElixirForum 收到的 reply

defmodule World.Cell do
  use GenServer
  @timedelay  2000

  def start_link do
    GenServer.start_link(__MODULE__, [], [name: {:global, __MODULE__}])
  end
  def get_state(pid) do
    GenServer.call(pid, {:get_state, pid})
  end

  def init([]) do
    :random.seed(:os.timestamp)
    time = :random.uniform
    voltage = :math.sin(2 * :math.pi + time)
    timer_ref = Process.send_after(self(), :tick, @timedelay)
    state = %{time: time, voltage: voltage, timer: timer_ref}
    {:ok, state}
  end

  def handle_info(:tick, state) do
    new_state = run(state) 
    timer_ref = Process.send_after(self(), :tick, @timedelay)
    {:noreply, %{new_state | timer: timer_ref}}
  end

  def handle_call({:get_state, pid}, _from, state) do
    IO.puts "getting state"
    return = Map.take(state, [:time, :voltage])
    {:reply, return, state}
  end

  defp run(state) do
    new_time = state.time + :random.uniform/12
    new_voltage = :math.sin(2 * :math.pi + new_time)
    new_state = %{state | time: new_time, voltage: new_voltage}
    IO.puts "VALUES #{inspect self()} t/v #{new_time}/#{new_voltage}"
    new_state
  end
end

为了让事情变得更简单,使用尽可能少的抽象级别总是好的。您基本上需要两个不同的进程:一个用于计费,一个用于消费。这样消费者将只负责处理一个状态,而“自动收报机”只会以指定的时间间隔对其进行 ping:

defmodule World.Cell do
  @interval 500
  def start_link do
    {:ok, pid} = Task.start_link(fn ->
      loop(%{time: :random.uniform, voltage: 42})
    end)
    Task.start_link(fn -> tick([interval: @interval, pid: pid]) end)
    {:ok, pid}
  end

  # consumer’s loop
  defp loop(map) do
    receive do
      {:state, caller} -> # state requested
        send caller, {:voltage, Map.get(map, :voltage)}
        loop(map)
      {:ping} ->          # tick 
        loop(map
             |> Map.put(:voltage, map.voltage + 1)
             |> Map.put(:time, map.time + :random.uniform/12))
    end
  end

  # ticker loop
  defp tick(init) do
    IO.inspect init, label: "Tick"
    send init[:pid], {:ping}
    Process.sleep(init[:interval])
    tick(init)
  end
end

{:ok, pid} = World.Cell.start_link

(1..3) |> Enum.each(fn _ ->
  {:state, _result} = send pid, {:state, self()}
  receive do
    {:voltage, value} -> IO.inspect value, label: "Voltage"
  end
  Process.sleep 1000
end)

输出将是:

Voltage: 42
Tick: [interval: 500, pid: #PID<0.80.0>]
Tick: [interval: 500, pid: #PID<0.80.0>]
Voltage: 44
Tick: [interval: 500, pid: #PID<0.80.0>]
Tick: [interval: 500, pid: #PID<0.80.0>]
Voltage: 46
Tick: [interval: 500, pid: #PID<0.80.0>]
Tick: [interval: 500, pid: #PID<0.80.0>]

使用 GenServer 的实现现在应该非常简单了。