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I consider myself to traditionally be a backend engineer, though this has more been something I fell into rather than chose.

I admit I feel I share some of your frustrations. In the past I have written production frontends in Angular and experimented with Vue and React. Out of all of them I found React to be the most enjoyable, but even then I still struggled with project setup and found the tooling confusing. I even quite like TS as a language, but I feel it's still quite limited by the fact it transpiles to JS.

Recently, I discovered yew [0]. It is a Rust framework for building frontends using wasm. I really appreciate the robustness that Rust brings such as ownership checks and ADTs. I don't think it's for everyone, but it may be worth looking at if you perhaps find modern frontend development confusing frustrating. I've found it to be quite the breath of fresh air.

If you do decide to have a look I found the examples [1] and getting started guide [2] very informative.

[0] https://github.com/yewstack/yew

[1] https://github.com/yewstack/yew/tree/master/examples

[2] https://yew.rs/docs/en/getting-started/project-setup

You're wrong, it does.

Conda installs conda packages and conda uses pip to install pip packages. However a pip package can be converted to a conda package, and then in that case the dependency will be installed by conda and not pip.

My understanding is mamba, like conda, just call pip. So it likely wouldn't make a difference.

The pip section in a env file is just a list of arguments passed through to the pip install command. Prior to pip 20.3 we had to add `--use-feature=2020-resolver` to get an install that resolved for our teams that used mamba.

You should check out this [0] GitHub action workflow. It uses docker machine to create a high resourced runner on demand in the cloud and then runs the subsequent job on it. The workflow is intended for machine learning but I'm sure it could be adapted. I must disclose that I haven't actually used it myself yet (because I haven't felt the need) but it does look very promising.

0: https://github.com/iterative/cml_cloud_case/blob/master/.git...

I think there is a lot of potential here from the perspective of improving type hinting. Decorators, which execute at runtime, often make type inference very challenging, this could go a long way to making this better. Further, it could also enable more performant static compilation, should one want to do that.

I am a fan of Haskell, the biggest problem for me was installing stack/cabal. I eventually got there, but I recall it was a very painful and frustrating process. With that in mind I can advocate for it in good conscience. Managing ghc versions and creating/generating projects should made easy.

I think rust got this right, rustup and cargo are great tools that are easy to install and work with.

Perhaps "low cost" in the title would have made it clearer since "cheap" as a word has a lot of connotations.

Language can be very hard to get right and I have struggled with this a lot personally.

This is exact how I write mine, I find it much more readable personally.

The real challenge I've encountered is typically you can only use one expression. If I need to write a slightly more complex mapping I am forced to write a function, which I normally define just before the comprehension. Even though this works, it introduces boilerplate I'd rather not write.

I will admit this doesn't happen often, but it happens enough to bother me.

This assumes some_giant_list is an object that has "findAll", that "findAll" returns and object that has "groupBy", which returns an object that has "countBy".

Looking at that code, I don't even know what the intermediary objects are, but given the names of the operations, they can't be all flat lists.

In regards to this, I would say sure, but does that really matter. Most IDEs will give you enough inference to list the operations you can perform and the return types they give. If anything the "super collections" make a developers life far easier, I think Kotlin does a particularly good job of this with a vast set of extension functions. Have a scroll of this documentation https://kotlinlang.org/api/latest/jvm/stdlib/kotlin.collecti... mapIndexedNotNull is a great example

Sadly it is actually the case. I recently worked on a project using the AWS SDK. We had written our code using Scala and had to up version the AWS SDK to 2.0. Because we used reflection with it, we encountered a Scala compiler bug (an illegal cyclic reference) and had to rewrite it all in Java.

I think one feature of Kotlin that is underestimated is extension functions. Combine them with autocompletion and you've got a great developer experience. Finding the method you need no longer requires a Google, and optimisation pays off massively in terms of productivity by tightening the development loop.