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There is no way that "warp" is already such a household name that it's common enough to shorten it to "wp". Likewise, the libraries at OP's company are for sure not going to be common to anyone starting out at the company, and might still be confusing to anyone who has worked there for years but just hasn't had to use that specific library.

Pandas and Numpy are popular, sure. As is Tensorflow (often shortened to tf). But where do you draw the line, then? should the openai library be imported as oa? should flask be imported as fk? should requests be imported as rq?

It seems to happen mostly to libraries that are commonly used by one specific audience: scientists who are forced to use a programming language, and who think that 1-letter variables are good variable names, and who prefer using notebooks over scripts with functions.

Don't get me wrong, I'm glad that Python gets so much attention from the scientific community, but I feel that small little annoyances like this creep in because of it, too.




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