Perhaps look into using dlt from https://dlthub.com, using pyarrow or polars. It handles large datasets well, especially when using generators to process the data in chunks.
It was not uncommon to draw a line through the zero to distinguish it from the letter ‘O’. Similarly, a slash was often added to the letter ‘Z’ to prevent confusion with the number 2.
Given that many data engineers have a data science, data analytics, BI, or software engineering background, I'm curious if you've noticed any trends in their approach to data security?
Gemini keeps disappointing me. It keeps making code up that is not accurate. I asked it some questions about a python library and the answers were inaccurate. I even instructed it to refer to the docs, but it still fails as Gemini made up methods that don't exist.
I also asked Gemini about git and that didn't go well either.
I used it for a few days, and it would spin up the fans on my MacBook Pro after a few minutes. I also wasn’t pleased with the tab management. And then I forgot about it.
FTA:
"Fast-food chains Chipotle and McDonald’s have already announced they plan to raise menu prices in California to offset the higher cost of worker compensation"
I guess I will refrain from those chains to offset their higher prices. Not even automation seems to help them want to reduce prices. In comparison, In-n-Out had already been paying their employees a higher salary than those chains, but their menu prices aren't as high.
Temper tantrums all because they want to keep wages low while everything else rises.