asyncio and blocking - an update

Frank Millman frank at
Fri Feb 12 03:17:34 EST 2016

"Frank Millman"  wrote in message news:n9hjfp$ad7$1 at
> However, my concern is not to maximise database performance, but to ensure 
> that in an asynchronous environment, one task does not block the others 
> from responding. My tests simulate a number of tasks running concurrently 
> and trying to access the database. Among other measurements, I track the 
> time that each database access commences. As I expected, tasks run with 
> 'run_in_executor' run sequentially, i.e. the next one only starts when the 
> previous one has finished. This is not because the tasks themselves are 
> sequential, but because 'fetchall()' is (I think) a blocking operation. 
> Conversely, with my approach, all the tasks start within a short time of 
> each other. Because I can process the rows as they are received, it seems 
> to give each task a fairer time allocation. Not to mention that there are 
> very likely to be other non-database tasks running concurrently, and they 
> should also be more responsive.
> It would be quite difficult to simulate all of this, so I confess that I 
> am relying on gut instinct at the moment.

It seems that my gut instinct was correct.

Up to now my timing tests have been run independently of my app, but now I 
have embedded them so that I can run the tests while I am logged in as a 

I run a task every 10 seconds that runs 25 concurrent tasks, each reading a 
database table of about 2000 rows.

Using run_in_executor() and cur.fetchall(), I experience delays of up to 2 
seconds while the task is active.

Using my approach, the maximum I saw was about a tenth of a second, and that 
is because I was looking for it - a normal user would not notice. Obviously 
the task took longer, but I can live with that trade-off.

As I mentioned before, I could be using run_in_executor() in a naïve way, 
and there could be better approaches. But until someone points out a better 
way, I have nothing else to go on.


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