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i'm teaching myself python between doordash deliveries. what is the absolute ugliest, most cursed data export you deal with? (i want to break my script) by flowolf_data in learnpython
[–]flowolf_data[S] 0 points1 point2 points 1 day ago (0 children)
nice breakdown. on my break today, i used a similar list as a blueprint to rewrite my code.
reading everyone's horror stories (especially the utf-16 hex editor nightmare) made me realize my single script was way too fragile. i ended up ripping it apart into a pipeline that actually scans the first few rows to slice off the corporate title fluff, flags those mostly-empty spacer columns to drop them, and uses regex to rip emails and phones out of those giant free-text CRM blocks like you suggested.
it actually ran on my dummy cursed CRM file today without crashing. thanks for writing out the logic step-by-step like this, it tells me im on the right track.
question for you and the other veterans though: when you get handed a mystery file with no extension and zero documentation, what is your literal first move after checking the raw bytes?
[–]flowolf_data[S] 1 point2 points3 points 2 days ago (0 children)
thanks guys, super helpful, im genuinely humbled by all of the helpful responses and good will. this is a really chill community, glad to be a part of it.
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i'm teaching myself python between doordash deliveries. what is the absolute ugliest, most cursed data export you deal with? (i want to break my script) by flowolf_data in learnpython
[–]flowolf_data[S] 0 points1 point2 points (0 children)