async-io | Async I/O and timers | Reactive Programming library
kandi X-RAY | async-io Summary
kandi X-RAY | async-io Summary
Async I/O and timers
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QUESTION
I'm looking at this piece of code from the example from here
And i want to know at what exact moment does the consumers() coroutine get called?
...ANSWER
Answered 2021-Jan-26 at 22:47While create_task() doesn't start executing the coroutine immediately, it schedules execution in the background at the first possible opportunity, i.e. at the first await that suspends to the event loop.
gather() is just a helper function that waits for the given awaitables to complete. It doesn't prevent previously scheduled coroutines (such as those started with create_task, but also start_server etc.) from executing.
i want to know at what exact moment does the consumers() coroutine get called?
Since consumers is a coroutine, while it's called once, it can suspend and resume many times, each await serving as a point of suspension/resumption. When you call create_task() it is placed in a queue of runnable coroutines. In each iteration of the event loop asyncio goes through runnable coroutines and executes a "step" of each, where the step executes it until the first await that chooses to suspend. In your code the step happens when your main coroutine suspends in order to wait for gather() to complete.
QUESTION
I have written a little winforms application that sends http requests to every ip address within my local network to discover a certain device of mine. On my particular subnet mask thats 512 addresses. I have written this using backGroundWorker but I wanted to tryout httpClient and the Async/Await pattern to achieve the same thing. The code below uses a single instance of httpClient and I wait until all the requests have completed. This issue is that the main thread gets blocked. I know this because I have a picturebox + loading gif and its not animating uniformly. I put the GetAsync method in a Task.Run as suggested here but that didn't work either.
...ANSWER
Answered 2020-Aug-21 at 00:33So one of the issues here is that you are creating 500+ tasks one after another in quick succession with a timeout set outside the task creation.
Just because you ask to run 500+ tasks, doesn't mean 500+ tasks are all going to run at the same time. They get queued up and run when the scheduler deems it's possible.
You set a timeout at the time of creation of 10 seconds. But they could sit in the scheduler for 10 seconds before they even get executed.
You want to have your Http requests to timeout organically, you can do that like this when you create the HttpClient:
QUESTION
I am trying to wrap my head around how await works, and in what order (if any) do operations get executed in the Queue.I will try to give an example to illustrate my point better.
My simplified example is inspired by Brad Solomun's article on asyncio:
...ANSWER
Answered 2020-Jun-03 at 10:21I would have expected
makeitemto be called afterawait randsleep(caller=f"Producer {name}")is completed because it is simply the next part to be executed in the function.
The point of using await rather than an ordinary function call is that it allows the current coroutine to be suspended while waiting for the awaitable to provide the requested value. While suspended, the coroutine temporarily relinquishes control to the event loop, which will run other coroutines or callbacks, or go back to sleep, as appropriate.
QUESTION
python3 client.py /home/aijax/.local/lib/python3.6/site-packages/socketio/client.py:592: RuntimeWarning: coroutine 'initial' was never awaited self._handle_event(pkt.namespace, pkt.id, pkt.data) connection established despite of having the await I'm getting the error PS: I have little to no knowledge of Async-io of python I kinda have finish this task overnight for a school proj my client.py
...ANSWER
Answered 2020-Jan-28 at 15:15You are using the socketio.Client() class which is the standard Python client. If you want to write an asyncio application, you must use socketio.AsyncClient().
QUESTION
I have a large file, with a JSON record on each line. I'm writing a script to upload a subset of these records to CouchDB via the API, and experimenting with different approaches to see what works the fastest. Here's what I've found to work fastest to slowest (on a CouchDB instance on my localhost):
Read each needed record into memory. After all records are in memory, generate an upload coroutine for each record, and gather/run all the coroutines at once
Synchronously read file and when a needed record is encountered, synchronously upload
Use
aiofilesto read the file, and when a needed record is encountered, asynchronously update
Approach #1 is much faster than the other two (about twice as fast). I am confused why approach #2 is faster than #3, especially in contrast to this example here, which takes half as much time to run asynchronously than synchronously (sync code not provided, had to rewrite it myself). Is it the context switching from file i/o to HTTP i/o, especially with file reads ocurring much more often than API uploads?
For additional illustration, here's some Python pseudo-code that represents each approach:
Approach 1 - Sync File IO, Async HTTP IO ...ANSWER
Answered 2019-Aug-20 at 18:10your code uses async but it does the work synchronously and in this case it will be slower than the sync approach. Asyc won't speed up the execution if not constructed/used effectively.
You can create 2 coroutines and make them run in parallel.. perhaps that speeds up the operation.
Example:
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