I am trying to understand how async coroutine are executed start to finish. Lets say i have this function
async def statemachine(state):
that does the following:
Read value on remote server
Write to remote mysql server
Write to local redis server
Delete a record from a remote mysql server
Create event and notify coroutine execution has finished
Since async suspends execution to give other coroutines time to execute, will the execution always start from step 1 to step 5 always.
A coroutine is always executed sequentially. Many (co)routines however can (co)operate together while being supervised by an event-loop or a scheduler of sorts.
So if you stack all your tasks in one coroutine e.g.:
async def statemachine(state):
await read_value_on_remote_server()
await write_to_remote_mysql_server()
await write_to_local_redis_server()
await delete_a_record_from_a_remote_mysql_server()
await create_event_and_notify_coroutine_execution_has_finished()
your statemachine will await each task one by one until they're done. This scenario isn't really useful, and doesn't provide any benefit over sync code.
A scenario where async execution shines is, let's say you have a web app that schedules one statemachine coroutine per user request. Now whenever a user hits your server with a request, a new coroutine is scheduled in the eventloop. And because the event loop can only run one thing at a time (pseudo concurrency), it will let each coroutine execute (let's assume using a round-robin algorithm) until they suspend, because they're awaiting an object or another coroutine that is awaiting another object.
The way a coroutine suspends is by having an await statement. This lets the event loop know that the coroutine is awaiting an operation that isn't necessarily CPU bound. e.g. network call or user input.
Thankfully, we're shielded from the details of the implementation of the eventloop and how it manages to know when a coroutine should be resumed. This is typically done using a library like Python's stdlib select https://docs.python.org/2/library/select.html.
For most use cases, you should know that a coroutine always executes sequentially and that the event-loop is what manages the execution of coroutines by using co-operative methods (unlike a typical OS scheduler for example).
If you want to run several coroutines pseudo-concurrently, you can look at asycio.gather or the more correct asyncio.create_task. Hope this helps.
Related
Let's consider this simple code with coroutines
import kotlinx.coroutines.*
import java.util.concurrent.Executors
fun main() {
runBlocking {
launch (Executors.newFixedThreadPool(10).asCoroutineDispatcher()) {
var x = 0
val threads = mutableSetOf<Thread>()
for (i in 0 until 100000) {
x++
threads.add(Thread.currentThread())
yield()
}
println("Result: $x")
println("Threads: $threads")
}
}
}
As far as I understand this is quite legit coroutines code and it actually produces expected results:
Result: 100000
Threads: [Thread[pool-1-thread-1,5,main], Thread[pool-1-thread-2,5,main], Thread[pool-1-thread-3,5,main], Thread[pool-1-thread-4,5,main], Thread[pool-1-thread-5,5,main], Thread[pool-1-thread-6,5,main], Thread[pool-1-thread-7,5,main], Thread[pool-1-thread-8,5,main], Thread[pool-1-thread-9,5,main], Thread[pool-1-thread-10,5,main]]
The question is what makes these modifications of local variables thread-safe (or is it thread-safe?). I understand that this loop is actually executed sequentially but it can change the running thread on every iteration. The changes done from thread in first iteration still should be visible to the thread that picked up this loop on second iteration. Which code does guarantee this visibility? I tried to decompile this code to Java and dig around coroutines implementation with debugger but did not find a clue.
Your question is completely analogous to the realization that the OS can suspend a thread at any point in its execution and reschedule it to another CPU core. That works not because the code in question is "multicore-safe", but because it is a guarantee of the environment that a single thread behaves according to its program-order semantics.
Kotlin's coroutine execution environment likewise guarantees the safety of your sequential code. You are supposed to program to this guarantee without any worry about how it is maintained.
If you want to descend into the details of "how" out of curiosity, the answer becomes "it depends". Every coroutine dispatcher can choose its own mechanism to achieve it.
As an instructive example, we can focus on the specific dispatcher you use in your posted code: JDK's fixedThreadPoolExecutor. You can submit arbitrary tasks to this executor, and it will execute each one of them on a single (arbitrary) thread, but many tasks submitted together will execute in parallel on different threads.
Furthermore, the executor service provides the guarantee that the code leading up to executor.execute(task) happens-before the code within the task, and the code within the task happens-before another thread's observing its completion (future.get(), future.isCompleted(), getting an event from the associated CompletionService).
Kotlin's coroutine dispatcher drives the coroutine through its lifecycle of suspension and resumption by relying on these primitives from the executor service, and thus you get the "sequential execution" guarantee for the entire coroutine. A single task submitted to the executor ends whenever the coroutine suspends, and the dispatcher submits a new task when the coroutine is ready to resume (when the user code calls continuation.resume(result)).
I copied the following code for my project and it's worked quite well for me but I don't really understand how the following code runs my blocking_function:
#client.event
async def on_message(message):
loop = asyncio.get_event_loop()
block_response = await loop.run_in_executor(ThreadPoolExecutor(), blocking_function)
where on_message is called every time I receive a message. If I receive multiple messages, they are processed asynchronously.
blocking_function is a synchronous function that I don't want to be run when another blocking_function is running.Then within blocking_function, should I use threading.Lock() or asyncio.lock()?
As pointed out by dirn in the comment, in blocking_function you cannot use an asyncio.Lock because it's just not async. (The opposite also applies: you cannot lock a threading.Lock from an async function because attempting to do so would block the event loop.) If you need to guard data accessed by other instances of blocking_function, you should use a threading.Lock.
but I don't really understand how the following code runs my blocking_function
It hands off blocking_function to the thread pool you created to run it. The thread pool queues and runs the function (which happens "in the background" from your perspective), and the run_in_executor arranges the event loop to be notified when the function is done, handing off its return value as the result of the await expression.
Note that you should use None as the first argument of run_in_executor. If you use ThreadPoolExecutor(), you create a whole new thread pool for each message, and you never dispose of it. A thread pool is normally meant to be created once, and reuse a fixed number ("pool") of threads for subsequent work. None tells asyncio to use the thread pool it creates for this purpose.
It seems you can easily achieve your desired objective by ensuring a single thread is used.
A simple solution would be to ensure that all calls to blocking_function is run on a single thread. This can be easily achieved by creating a ThreadPoolExecutor object with 1 worker outside of the async function. Then every subsequent calls to the blocking function will be run on that single thread
thread_pool = ThreadPoolExecutor(max_workers=1)
#client.event
async def on_message(message):
loop = asyncio.get_event_loop()
block_response = await loop.run_in_executor(thread_pool, blocking_function)
Don't forget to shutdown the thread afterwards.
I have tried the following code in Python 3.6 for asyncio:
Example 1:
import asyncio
import time
async def hello():
print('hello')
await asyncio.sleep(1)
print('hello again')
tasks=[hello(),hello()]
loop=asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(tasks))
Output is as expected:
hello
hello
hello again
hello again
Then I want to change the asyncio.sleep into another def:
async def sleep():
time.sleep(1)
async def hello():
print('hello')
await sleep()
print('hello again')
tasks=[hello(),hello()]
loop=asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(tasks))
Output:
hello
hello again
hello
hello again
It seems it is not running in an asynchronous mode, but a normal sync mode.
The question is: Why is it not running in an asynchronous mode and how can I change the old sync module into an 'async' one?
Asyncio uses an event loop, which selects what task (an independent call chain of coroutines) in the queue to activate next. The event loop can make intelligent decisions as to what task is ready to do actual work. This is why the event loop also is responsible for creating connections and watching file descriptors and other I/O primitives; it gives the event loop insight into when there are I/O operations in progress or when results are available to process.
Whenever you use await, there is an opportunity to return control to the loop which can then pass control to another task. Which task then is picked for execution depends on the exact implementation; the asyncio reference implementation offers multiple choices, but there are other implementations, such as the very, very efficient uvloop implementation.
Your sample is still asynchronous. It just so happens that by replacing the await.sleep() with a synchronous time.sleep() call, inside a new coroutine function, you introduced 2 coroutines into the task callchain that don't yield, and thus influenced in what order they are executed. That they are executed in what appears to be synchronous order is a coincidence. If you switched event loops, or introduced more coroutines (especially some that use I/O), the order can easily be different again.
Moreover, your new coroutines use time.sleep(); this makes your coroutines uncooperative. The event loop is not notified that your code is waiting (time.sleep() will not yield!), so no other coroutine can be executed while time.sleep() is running. time.sleep() simply doesn't return or lets any other code run until the requested amount of time has passed. Contrast this with the asyncio.sleep() implementation, which simply yields to the event loop with a call_later() hook; the event loop now knows that that task won't need any attention until a later time.
Also see asyncio: why isn't it non-blocking by default for a more in-depth discussion of how tasks and the event loop interact. And if you must run blocking, synchronous code that can't be made to cooperate, then use an executor pool to have the blocking code executed in a separate tread or child process to free up the event loop for other, better behaved tasks.
I am doing an IO wait operation inside a for loop now the thing is when all of the operations terminates I want to send the response to the server. Now I was just wondering that suppose two IO operation terminates exactly at the same time now can they execute code at the same time(parallel) or will they execute serially?
As far as I know, as Node is Concurrent but not the Parallel language so I don't think they will execute at the same time.
node.js runs Javascript with a single thread. That means that two pieces of Javascript can never be running at the exact same moment.
node.js processes I/O completion using an event queue. That means when an I/O operation completes, it places an event in the event queue and when that event gets to the front of the event queue and the JS interpreter has finished whatever else it was doing, then it will pull that event from the event queue and call the callback associated with it.
Because of this process, even if two I/O operations finish at basically the same moment, one of them will put its completion event into the event queue before the other (access to the event queue internally is likely controlled by a mutex so one will get the mutex before the other) and that one's completion callback will get into the event queue first and then called before the other. The two completion callbacks will not run at the exact same time.
Keep in mind that more than one piece of Javascript can be "in flight" or "in process" at the same time if it contains non-blocking I/O operations or other asynchronous operations. This is because when you "wait" for an asynchronous operation to complete in Javscript, you return control back to the system and you then resume processing only when your completion callback is called. While the JS interpreter is waiting for an asynchronous I/O operation to complete and the associated callback to be called, then other Javascript can run. But, there's still only one piece of Javascript actually ever running at a time.
As far as I know, as Node is Concurrent but not the Parallel language so I don't think they will execute at the same time.
Yes, that's correct. That's not exactly how I'd describe it since "concurrent" and "parallel" don't have strict technical definitions, but based on what I think you mean by them, that is correct.
you can use Promise.all :
let promises = [];
for(...)
{
promises.push(somePromise); // somePromise represents your IO operation
}
Promise.all(promises).then((results) => { // here you send the response }
You don't have to worry about the execution order.
Node.js is designed to be single thread. So basically there is no way that 'two IO operation terminates exactly at the same time' could happen. They will just finish one by one.
I'm trying to understand the semantics of async/await in an infinitely looping worker thread started inside a windows service. I'm a newbie at this so give me some leeway here, I'm trying to understand the concept.
The worker thread will loop forever (until the service is stopped) and it processes an external queue resource (in this case a SQL Server Service Broker queue).
The worker thread uses config data which could be changed while the service is running by receiving commands on the main service thread via some kind of IPC. Ideally the worker thread should process those config changes while waiting for the external queue messages to be received. Reading from service broker is inherently asynchronous, you literally issue a "waitfor receive" TSQL statement with a receive timeout.
But I don't quite understand the flow of control I'd need to use to do that.
Let's say I used a concurrentQueue to pass config change messages from the main thread to the worker thread. Then, if I did something like...
void ProcessBrokerMessages() {
foreach (BrokerMessage m in ReadBrokerQueue()) {
ProcessMessage(m);
}
}
// ... inside the worker thread:
while (!serviceStopped) {
foreach (configChange in configChangeConcurrentQueue) {
processConfigChange(configChange);
}
ProcessBrokerMessages();
}
...then the foreach loop to process config changes and the broker processing function need to "take turns" to run. Specifically, the config-change-processing loop won't run while the potentially-long-running broker receive command is running.
My understanding is that simply turning the ProcessBrokerMessages() into an async method doesn't help me in this case (or I don't understand what will happen). To me, with my lack of understanding, the most intuitive interpretation seems to be that when I hit the async call it would go off and do its thing, and execution would continue with a restart of the outer while loop... but that would mean the loop would also execute the ProcessBrokerMessages() function over and over even though it's already running from the invocation in the previous loop, which I don't want.
As far as I know this is not what would happen, though I only "know" that because I've read something along those lines. I don't really understand it.
Arguably the existing flow of control (ie, without the async call) is OK... if config changes affect ProcessBrokerMessages() function (which they can) then the config can't be changed while the function is running anyway. But that seems like it's a point specific to this particular example. I can imagine a case where config changes are changing something else that the thread does, unrelated to the ProcessBrokerMessages() call.
Can someone improve my understanding here? What's the right way to have
a block of code which loops over multiple statements
where one (or some) but not all of those statements are asynchronous
and the async operation should only ever be executing once at a time
but execution should keep looping through the rest of the statements while the single instance of the async operation runs
and the async method should be called again in the loop if the previous invocation has completed
It seems like I could use a BackgroundWorker to run the receive statement, which flips a flag when its job is done, but it also seems weird to me to create a thread specifically for processing the external resource and then, within that thread, create a BackgroundWorker to actually do that job.
You could use a CancelationToken. Most async functions accept one as a parameter, and they cancel the call (the returned Task actually) if the token is signaled. SqlCommand.ExecuteReaderAsync (which you're likely using to issue the WAITFOR RECEIVE is no different. So:
Have a cancellation token passed to the 'execution' thread.
The settings monitor (the one responding to IPC) also has a reference to the token
When a config change occurs, the monitoring makes the config change and then signals the token
the execution thread aborts any pending WAITFOR (or any pending processing in the message processing loop actually, you should use the cancellation token everywhere). any transaction is aborted and rolled back
restart the execution thread, with new cancellation token. It will use the new config
So in this particular case I decided to go with a simpler shared state solution. This is of course a less sound solution in principle, but since there's not a lot of shared state involved, and since the overall application isn't very complicated, it seemed forgivable.
My implementation here is to use locking, but have writes to the config from the service main thread wrapped up in a Task.Run(). The reader doesn't bother with a Task since the reader is already in its own thread.