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.
Thanks
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.
Thanks
onlinejudge95
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