Uberphallus

I actually had 3 of these with PII 300MHz @ 450MHz running OpenMOSIX. Good times.

Exactly. Here we crunch loads of data, and by a lot, I mean our production databases run on a three digit cluster of four digit terabytes of data. Good luck having that scale in preproduction environments.

We have loads of redundancy, and dedicated "test in production" machines/datacenters to test actual production loads in actual production-scale sets machines.

Now, tests in production usually involves a pair of hands and 2 other people looking behind (dev + ops + dba), and requires a well defined rollback procedure and post-mortem. We still have absurdly high SLA (99.999%).

Yes, but more processes means more memory footprint, almost 4 times as much in that benchmark, something the author didn't cover. Threading solves that, but it's way more prone to shooting yourself in the foot than async, especially since it's not baked into Django (i.e. you gotta cook your own solutions over callbacks, polling, etc).

Yeah, but this scale of documentation production is unprecedented.

A lot of cash was dumped into fast and extensive R&D, trials and production scaling because of the urgency of the situation, and along comes an insane documentation backlog.

To put in perspective, the original HPV vaccine R&D and trial spanned over 7 years with 25,000 patients (of which only 20,000 women), and assuming the documentation was provided to the FDA as it was produced, it could be FOIA'd relatively quickly.

Pfizer/BioNTech did the same, with almost double the patients, in just over 6 months.

Ironically, if the FDA could deliver those documents "in time" it would be a sign of a pretty limited trial, and people would be complaining about that instead.

Damned if you do, damned if you don't.

Critical mass. FB groups are a dumpster fire for topic discussions, but the fact that they're just there means loads of communities end up there anyway.

Reviewing/analysing data and filtering it are dramatically different tasks. With raw data, most of the heavy lifting is done by your data analysis stack, you don't crunch numbers yourself. Complying with FOIA requests though, is largely manual work.

The FDA has 14,000 employees; its FOIA office has 10, and they go at roughly 80,000 pages per month, meaning each employee does 8,000 pages per month, or roughly 400 per working day per employee, less than a minute per page. That to my non expert opinion sounds pretty fast.

That speed has been appropriate until now that the plaintiffs want 4 months' worth of FDA FOIA work for yesterday.

I agree that there should be a solution for these cases, but it's this particular FOIA request that's the anomaly, not the FDA way of work.

The only justified situation I can find is when you are working on two (or more) independent components at the same time.

My pain point in particular with PYTHONPATH (or playing with sys.path) is that people tend to use it with the only purpose of making import lines shorter, which brings naming collisions of all sorts when you aren't creative enough.

This is my decision flow and I rarely have an issue:

    Are you the end user of the Python code?
        Yes -> Is available in your distro?
            Yes->Use package manager
            No->Use pip install in user mode
        No -> Create virtualenv with the Python version you want (including pypy!) and do your pip thing there

Some extreme use cases may benefit from anaconda, but personally I've never needed to use it. My only pain point is dealing with legacy code that relies on PYTHONPATH. Nothing good ever starts setting PYTHONPATH.

> Their total liabilities are on the order of $300 billion

~300 billion is the size of their debt (485 at the end of H1 2021). Their assets are at +2 trillion, +1 trillion in real estate alone.

Their problem is that with their current cash flow they can't pay their debt, ever, and now, they can't even keep up with the interest. But they're still in a position where selling off part of their inventory can offset the debt, and to my knowledge, that's what they've been trying to do.

That is, if their financial statements area real. That's the quid here, their position isn't particularly anomalous, but the market cap sits at 33 billion, very far from their declared assets, meaning the market doesn't believe those statements. Thats 60 to 1, where most REIT sit at around 2 to 1.

Their main problem is the large amount of unfinished homes (read: not producing any income) and you need money to fix that. My guess is that the government will step in to fix that point in particular.