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"Chains" of asynchronous functions in F #

I created a function in F # to restore historical data from Yahoo (classic asynchronous example for F #):

let getCSV ticker dStart dEnd =
async   {
        let query = getFileUrl ticker dStart dEnd
        let req = WebRequest.Create(query)
        use! resp = req.AsyncGetResponse()
        use stream= resp.GetResponseStream()
        use reader = new StreamReader(stream)
        let content = reader.ReadToEnd()
        let ts = parseData content
        return ts
        }

Now I can run this function asynchronously by doing the following:

let test=
    ["MSFT";"YHOO"]
    |>List.map (fun x -> getCSV x (DateTime.Parse("01.01.2000")) (DateTime.Parse("01.01.2010")))
    |> Async.Parallel
    |> Async.RunSynchronously

Well that's cool.

Now I would like to know how to apply some function to it, which is a price history:

For instance:

let getReturns (prices:(DateTime *float)list) =
    [for i in 1..(prices.Length-1) -> i]
    |> List.map (fun i ->(fst (List.nth prices i), (snd (List.nth prices i))/(snd (List.nth prices (i-1) )) - 1.0))

So the trivial way to do this is:

let test2=
    ["MSFT";"YHOO"]
    |>List.map (fun x -> getCSV x (DateTime.Parse("01.01.2000")) (DateTime.Parse("01.01.2010")))
    |> Async.Parallel
    |> Async.RunSynchronously
    |> Array.map getReturns;;

However, the function getReturnsis executed after downloading and analysis of each file.

What I would like to know is if you can start the execution of the second function while the downloads are still happening: as soon as the MSFT is complete, you do not need to wait until YHOO is executed to calculate its return ...

, getCSV, , "" getReturn ...

+3
2

. , , - , , , , ( ):

let test=
    [ for stock in ["MSFT";"YHOO"] ->
        async { let! data = getCSV stock (DateTime(2000, 1, 1)) (DateTime(2010, 1, 1))
                return getReturns data } ]
    |> Async.Parallel
    |> Async.RunSynchronously

, , , , getRteurns . .

Joel ( getReturns, ) Async.map, , .

getReturns, :

let test=
    ["MSFT";"YHOO"]
    // For every stock name, generate an asynchronous workflow
    |> List.map (fun x -> getCSV x (DateTime(2000, 1, 1)) (DateTime(2010, 1, 1)))
    // For every workflow, transform it into a workflow that 
    // applies 'getReturns' to the result of the original workflow
    |> List.map (Async.map getReturns)
    // Run them all in parallel
    |> Async.Parallel
    |> Async.RunSynchronously

Async.map :

module Async =
  let map f workflow = async {
    let! res = workflow
    return f res }
+9

getReturns, ...

let getReturns (prices:Async<(DateTime * float) list>) = async {
    let! prices = prices
    return [for i in 1..(prices.Length-1) -> i]
           |> List.map (fun i ->(fst (List.nth prices i), (snd (List.nth prices i))/(snd (List.nth prices (i-1)))))
}

:

let test=
    ["MSFT";"YHOO"]
    |> List.map (fun x -> getCSV x (DateTime(2000, 1, 1)) (DateTime(2010, 1, 1)))
    |> List.map getReturns
    |> Async.Parallel
    |> Async.RunSynchronously

, getCSV , ticker . , . getReturns.

let test =
    let getRange = getCSV (DateTime(2000, 1, 1)) (DateTime(2010, 1, 1))
    ["MSFT"; "YHOO"]
    |> List.map (getRange >> getReturns)
    |> Async.Parallel
    |> Async.RunSynchronously

Edit

List.nth getReturns . . , ​​, :

let getReturns2 (prices: Async<(DateTime * float) list>) = async {
    let! prices = prices
    let rec loop items output =
        match items with
        | (_, last) :: (time, current) :: rest ->
            loop rest ((time, (last / current)) :: output)
        | [ item ] ->
            List.rev (item :: output)
        | [] ->
            List.rev output
    return loop prices []
}
+3

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