Hi,
You should also undertand that Python uses GIL for Threading purpose. Yes, if
you have functiosn that needs simulataneous execution you should use Threading
approach. As well as if Huge data is involved then also use multi-processing
concept as well
On Thursday, 19 December, 2019, 7:42:12 pm IST, onlinejudge95
<onlinejudg...@gmail.com> wrote:
Hi Devs,
I am currently writing some custom Django commands for data updation, my
workflow is like
Fetch data from PostgreSQL.Call Elasticsearch for searching based on the data
fetched from PostgreSQL.Query PostgreSQL and do an upsert behavior.
I am using pandas data frame to hold my data during processing.
The host we are using to run this jobs has a CPython interpreter as given by
`platform.python_implementation()`
I want to confirm whether multithreading would be a better choice here, given
the fact that GIL is the biggest blocker(I agree it has to be there) for the
same in CPython interpreters.
In case further information is required do let me know.
Thanksonlinejudge95
--
You received this message because you are subscribed to the Google Groups
"Django users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to django-users+unsubscr...@googlegroups.com.
To view this discussion on the web visit
https://groups.google.com/d/msgid/django-users/CAD%3DM5eRWh9-EB180f2OzvnPLHh969vgaCzFyniFRSFa1-CwUHA%40mail.gmail.com.
--
You received this message because you are subscribed to the Google Groups
"Django users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to django-users+unsubscr...@googlegroups.com.
To view this discussion on the web visit
https://groups.google.com/d/msgid/django-users/551451096.10373381.1579167791939%40mail.yahoo.com.
