But IMO that’s one reason weird UX/design is not uncommon and can persist in dev ecosystems. The intended users are more proficient than average and most are able to work around most issues.

If the goal is evaporative distillation, it makes no sense to use a process that begins with filling and conaminating the entire system with contaminated water

You’d have more success keeping the container clean (full of air) and pumping all the air out of it, which is still probably less efficient than other means like boiling

It’s a container with certain behaviors and guarantees making them easy and reliable to manipulate and compose. A practical example is a generic List, that behaves like:

• List[1, 2, 3], i.e. (“new”, “unit”, “wrap”) to create, containing obj(s)
• map(func) to transform objs inside, List[A] -> List[B]
• first(), i.e. (“unwrap”, “value”) to get back the obj
• flat_map(func), i.e. (“bind”) to un-nest one level when func(a) itself produces another List, e.g. [3, 4].flat_map(get_divisors) == flatten_once([[1, 3], [1, 2, 4]]) == [1, 3, 1, 2, 4]

Consider the code to do these things using for loops – the “business logic” func() would be embedded and interlaced with flow control.

The same is true of Maybe, a monad to represent something or nothing, i.e. a “list” of at most one, i.e. a way to avoid “null”.

Consider how quickly things get messy when there are multiple functions and multiple edge cases like empty lists or "null"s to deal with. In those cases, monads like List and Maybe really help clean things up.

IMO the composability really can’t be understated. “Composing” ten for loops via interlacing and if checks and nesting sounds like a nightmare, whereas a few LazyList and Maybe monads will be much cleaner.

Also, the distinction monads make with what’s “inside” and what’s “outside” make it useful to represent and compartmentalize scope and lifetimes, which makes it useful for monads like IO and Async.

Python deps can be dynamic, so it can be necessary to download the package and execute code just to find out.

Would be nice to see a resource that lists out the statically defined ones, though. Perhaps that’d pressure the dynamic ones to change – it’s a cause for some of the notorious pain of Python packaging.

In my experience, LLMs aren’t really that good at summarizing

It’s more like they can “rewrite more concisely” which is a bit different

If you want to entertain having kids, you need to be ready for a radical shift in your life priorities. Your kids will take priority over just about everything – often even yourself. They’ll take priority over your parents entirely, let alone your personal relationship with them.

First, are the practical and logistical aspects of your life at all dependent on your parents? I.e. are you fully independent? You will need to be and then some, you’re going to entertain having kids.

Once you’re fully independent and additionally have resources to spare (time, effort, money, space, etc, usually b/c you’re with a partner you can trust and rely on), then choosing to have kids means starting your own family – not your parents’ family.

If the grandparents are supportive and helpful, that’s great! They’re extremely welcome to contribute to your kids’ lives (and lighten some of your parenting load!)

However, if they’re negatively impacting you or esp your kids, then they can lose that privilege. Again, your priority will be your kids. If this is a real concern for you, you’ll need to factor it into your “ready to have a kid” considerations.

Hm, that’s kind of interesting

But my first reaction is that optimizations only at the “Python processing level” are going to be pretty limited since it’s not going to have metadata/statistics, and it’d depend heavily on the source data layout, e.g. CSV vs parquet

What’s hard about vanilla Ruby?

What kind of query optimization can it for scanning data that’s already in memory?

No so much that YAGNI falls short, but more like “When YAGNI means ‘You Are Gonna Need It’”

Can that barrel hold fluids? B/c then what about the ocean or even the atmosphere? (Though it would take a while)

Could’ve held one rod end in each hand, letting middle of rope ladder hang down for standing on, like stirrups

Alternate left/right and you can step in any direction into the air

You can reference envs from the host in docker compose, so code it in instead of manually passing tribal knowledge in: https://stackoverflow.com/a/73826410

Simpler to keep everything in one compose file if you can, under a test service that doesn’t build unless explicitly named

Un-weird that env var and use the normal, boring feature of defining environment under your test service

I’ve often been able to alias drun='docker compose run --rm --build' and simplify down to:

drun test

Should be able to encode all those wayward args into docker-compose.yml or Dockerfile and only use vanilla docker commands – that’s the whole point of containerization

I think your ideas are too non-practical/specialized/advanced/low-level for your stated goal of 'digital literacy". They read more like college intro/followup course material and are too esoteric to be readily absorbed, esp by generic teenagers, even if they’ve self-selected to be “lightly interested”.

In recreational climbing, skin calluses and surface abrasion aren’t usually much of a concern compared to tendon health. Skin heals light damage quite easily.

However, it’s not uncommon for a new (or experienced) climber to develop their muscles beyond what their own tendons can take. Since it takes tendons so long to strengthen, it’s common to need managing the risk of finger pulley tendon injuries in climbing.

Also, I do not know how these nuances apply in your context of your medical condition.

wanted to add something to the end of a for-loop, but had too little indentation

To address this, I prefer reducing length & depth of nested code, so the for/while is rarely ever not visible along with everything inside it. Others have success with editors that draw indentation lines.

opening up new/anonymous scopes

I occasionally use Python nested functions for this purpose

I find it’s possible to operate Python as a statically typed language if you wanted, though it takes some setup with external tooling. It wasn’t hard, but had to set up pyright, editor integration, configuration to type check strictly and along with tests, and CI.

I even find the type system to be far more powerful than how I remembered Java’s to be (though I’m not familiar with the newest Java versions).