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It is hard to recommend Python in production

(ashishb.net)
33 points ashishb | 3 comments | 08 Mar 25 05:14 UTC | HN request time: 0.001s | source
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odie5533 ◴[08 Mar 25 07:34 UTC] No.43298306[source]▶
What does Python in production even mean? Python is used extensively in AI/ML. Are all the AI/ML engineers just being stupid because their notebook could be faster if it was written in Rust? Of course not.

Clickbait title, garbage content.

replies(1): >>43298470 #
1. ashishb ◴[08 Mar 25 08:08 UTC] No.43298470[source]▶
> Are all the AI/ML engineers just being stupid because their notebook could be faster if it was written in Rust

I think Python is a great language for running inside Notebooks. Running non-AI/ML jobs in production is where Python brings more downsides than upsides.

replies(1): >>43298661 #
2. user32489318 ◴[08 Mar 25 08:56 UTC] No.43298661[source]▶
Depends on the setting. I have built python ETL pipelines for some of my customers, it’s slow, not efficient but, every data scientist can read the code and make it work for their changing requirements. At the end of the day, if you’re running a 3hour etl job in Python or 1h on a Spark/hive/mapReduce/what else legacy tooling they got I’d choose 3H one if team can support it and is not afraid to make changes.
replies(1): >>43298686 #
3. ashishb ◴[08 Mar 25 09:04 UTC] No.43298686[source]▶
Indeed. Pure data manipulation, especially, when it being done for a batch job, is a good use case for Python.