We can blame CSV, or we can blame the way people use CSV. Either way CSV is so unreliable that I try to “fail-fast” as soon as possible in automated pipeline.

At work, we explicitly define data structuring process, converting CSV to Parquet with strict schema and technical/structural validation. We assign interns and new grad engineers for this, which is nicely within their capabilities too with minimal training.

His ability to steal the win from opponent with stalemate in time scramble is fun to watch too.

Being around 2000 myself, I agree that Agadmator’s analyses are not very deep or insightful.

Agadmator channel is educational and informative when it comes to chess scene, drama and history. In this regard, I think he’s the best and most comprehensive.

Overall I enjoy Gotham, Agadmator, Hikaru, Eric Rosen in that order.

With that thinking, there’s a lot to feel bad for. People with demanding jobs, people who are sick, people in countries with no freedom, people with death of loved ones, people who give life pursuing dreams and failed, lonely people, people with disabilities, people experiencing war / natural disasters / pollutions.

I think as human we should aim to contribute to betterment of the world. Empathy is good, but feeling bad for isn’t at grand scale. You can feel bad for your friend’s misfortune I suppose.

Airgap install of Python is quite straightforward. I normally scp the Python source and altinstall on target server.

But airgap install of pip packages with myriad dependencies can be annoying.

So I agree with parent comment that having standard packages make things easier

It’s worthwhile to be explicit there. For example, a person can be a heavy user of Pandas library but rarely use underlying numpy library directly. There could be motivation to contribute to numpy with expectation that Pandas will benefit too.

Based on the article, this user should start learning to use numpy directly, and I can agree with that.