> On 19 Dec 2019, at 14:19, 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.
You mean multi process vs. Threaded? The GIL is only a problem if you are executing pure python compute bound code on multiple threads. When your code does lots of I/O and uses extensions it’s not the limiting factor. I guess you app will spent if time waiting of PostgreSQL etc. Barry > > In case further information is required do let me know. > > Thanks > onlinejudge95 > -- > https://mail.python.org/mailman/listinfo/python-list > -- https://mail.python.org/mailman/listinfo/python-list
