ExchangeSharp | REST and web sockets | Cryptography library

In general, when you do not see an increase by multi threading, it is because your task is not CPU limited or large enough to offset the overhead.

In your example, i.e.:

selectedApi.GetTickerAsync(symbol);

This can hae 2 reasons:

1: Looking up the ticker is brutally fast and it should not be an async to start with. I.e. when you look it up in a dictionary.

2: This is running via a http connection where the runtime is LIMITING THE NUMBER OF CONCURRENT CALLS. Regardless how many tasks you open, it will not use more than 4 at the same time.

Oh, and 3: you think async is using threads. It is not. It is particularly not the case in a codel ike this:

await selectedApi.GetTickerAsync(symbol);

Where you basically IMMEDIATELY WAIT FOR THE RESULT. There is no multi threading involved here at all.

foreach (IExchangeAPI selectedApi in selectedApis) { if (exchangeSymbols.TryGetValue(selectedApi.Name, out symbol)) { ticker = await selectedApi.GetTickerAsync(symbol); } }

This is linear non threaded code using an async interface to not block the current thread while the (likely expensive IO) operation is in place. It starts one, THEN WAITS FOR THE RESULT. No 2 queries ever start at the same time.

If you want a possible (just as example) more scalable way:

• In the foreach, do not await but add the task to a list of tasks.
• Then start await once all the tasks have started. Likein a 2nd loop.

WAY not perfect, but at least the runtime has a CHANCE to do multiple lookups at the same time. Your await makes sure that you essentially run single threaded code, except async, so your thread goes back into the pool (and is not waiting for results), increasing your scalability - an item possibly not relevant in this case and definitely not measured in your test.