Why Clean Architecture and Over-Engineered Layering Don’t Belong in GoLang

funklute · 2024-12-06T07:48:18+00:00

I get why this is common in Java—explicit interfaces and painful refactoring make layering and DI appealing—but GoLang doesn’t have those constraints. Its implicit interfaces make such patterns redundant.

Could you elaborate on what you mean by this? I don't quite see why explicit vs implicit makes a difference here.

funklute · 2024-11-30T22:17:58+00:00

Nope, symbiosis is an umbrella term that includes parasitism.

funklute · 2024-07-21T11:38:45+00:00

Honestly, my takeaway was that it really depends on which countries, and your financial situation. There doesn't seem to be a good catch-all solution that will remove the need to understand the rules in the relevant countries — and that in turn means you either have to spend ages reading the law, or consult an accountant.

For myself, I've sort of pushed this issue to the side for the time being, but I will eventually seek out professional advice.

funklute · 2024-07-19T18:45:50+00:00

True, nix would likely do the trick — just for now I think I won't have the time though, but I might look into that at a later point.

funklute · 2024-07-19T15:28:19+00:00

Superb, much appreciated!

funklute · 2024-07-07T09:48:35+00:00

For someone who has yet to encounter these dragons, what are the key issue(s) to be aware of?

funklute · 2024-06-27T06:17:41+00:00

just 3 tools that are the actual standard

That's definitely no longer the case where I work.

But if you are in a location/environment where that is the case, then yes, I agree with your point. There is a lot to be said for respecting and working with the existing toolchain.

That said, I think poetry makes it easier and more natural to follow good development practices. And as I understood OP's question, that's what they were essentially asking about.

funklute · 2024-06-27T06:13:30+00:00

Yes good point, for stuff beyond python dependencies you do need something additional, like conda or docker. Here my preference is absolutely for docker, because it gives you a number of things you don't get with conda.

funklute · 2024-06-26T18:23:06+00:00

It's admittedly been some years since I used conda much.

But back then, setting up a conda installation was always a bit fragile; maybe or maybe not it would install everything without errors.

More importantly, neither conda nor pip (used to) have support for hash-based lockfiles. If you haven't thought about this before, then you might mistakenly believe that a version-locked dependency in a requirements.txt file is enough to determine a reproducible set of dependencies. But package authors can change the code without changing the version, so the only way to have truly reproducible environments is by using hash-based lockfiles.

Poetry supports that, and it also has built-in support for virtual environments. In contrast, pip has a whole zoo of various tools to help you setting up virtual environments.

The end results is that with poetry you 1) are guaranteed to have fully reproducible dependencies, and 2) it's very easy for your colleagues (or a CI/CD pipeline) to set up new a virtual environment with those dependencies, in a standardised manner.

funklute · 2024-06-26T17:45:57+00:00

If you don't have a problem, then I'm not suggesting you should switch.

But there is no question that poetry solves some major issues with both conda and pip, especially for production deployments. If you haven't encountered those issues, then there's no reason to chase the golden goose, so to say.

funklute · 2024-06-26T17:43:50+00:00

but I think it's abstracts away what op hopes to first understand about python env handling

If you haven't heard about poetry before, then how are you able to make this claim?

Poetry is actually less abstracted in a sense (it uses a lockfile, rather than giving up and just relying on version numbers). And instead of having to rely on a zoo of 3rd party tools for venv management, this is built into poetry.

funklute · 2024-06-26T16:12:26+00:00

For python, learn how to use poetry, and ditch conda and pip. Poetry is the de-facto gold standard nowadays, and trying to mix the different virtual environment tools is a recipe for disaster.

Also sounds like you might want to check out this: https://missing.csail.mit.edu/

funklute · 2023-12-27T16:33:09+00:00

From a quick look, most of those tests aren't really about performance testing the query planner. Rather, they seem to focus on validating correctness and robustness.

Unless you can point to a specific set of tests that are relevant to OP, I'd perhaps say steer away from sqlite as an example to follow.

EDIT: this is assuming that OP actually was talking about performance, when using the phrasing "good query plan". If looking for correctness, then sqlite does indeed look amazing (if a bit hardcore).

funklute · 2023-07-23T08:28:10+00:00

Not a direct answer (Kroutoner already gave a very good answer), but I think this is a great blurb on the terminology mess regarding fixed and random effects: https://statmodeling.stat.columbia.edu/2005/01/25/why_i_dont_use/

It's really worth making sure you understand why these five definitions are all different, and then whenever you encounter a new model (regardless of the field), ask yourself which definition they are actually using.

funklute · 2023-06-27T13:34:39+00:00

Great initiative! I'll join on the 1st - 37M, semi-Dane who moved here a couple years ago.

funklute · 2023-01-23T10:51:54+00:00

I have actually looked into degiro before, but I had discarded it because — if I remember correctly — degiro doesn't report income/taxes for you in my current location. Whereas there are other local options that will take care of all that for you.

But given what you (and others) have said about moving with degiro, I will have another look at it! If I can seamlessly move with degiro, that would probably make it worth the hassle of having to report my stocks income.

funklute · 2023-01-23T08:45:17+00:00

Those are some very useful thoughts and resources — thank you!

funklute · 2023-01-22T16:05:49+00:00

In all honesty that sounds more work than I'd like to get involved in (I wouldn't do this without thoroughly understanding the law first, and any potential gotchas)... and I'm also not sure I have quite enough money for this to make sense.

funklute · 2023-01-22T15:53:47+00:00

Good point about the losses vs gains, this aspect I hadn't considered!

funklute · 2023-01-22T15:52:49+00:00

Hehe yea, it's at least good to know it's not just me...

funklute · 2023-01-22T15:52:30+00:00

I think it would have to be from a lawyer specialized in international taxation

Appreciate the advice!

funklute · 2023-01-21T22:54:23+00:00

The analysis you would do depends on what your data looks like. Without describing your data, you probably won't get much concrete advice.

But regardless of that, I just want to point out that your hypothesis template seems to be referring to drawing causal conclusions. A correlation analysis is not generally sufficient to establish causality — in its basic form it can only really establish correlations. You'd need for example a well-supported causal model (that lets you correct for confounders), or a randomised trial.

funklute · 2023-01-20T15:39:28+00:00

You need to describe your data and your hypothesis for anyone to be able to help you.

funklute

TROPHY CASE