component VS preplish

* Lifecycle management: Mount, Integrant or Component (https://github.com/tolitius/mount https://github.com/weavejester/integrant and https://github.com/stuartsierra/component)

When you start to have multiple stateful components (the database, the HTTP server, your Redis connection, a page cache, etc.), then you'll want to use a library like component that manages their (inter-)dependencies and provides a consistent notion of lifecycle.

Today I released a new version of Reveal Pro — dev.vlaaad/reveal-pro {:mvn/version "1.3.308"} — that adds sticker integration for system libraries such as mount, component and integrant!

I agree with the main sentiment from the article. Although I do think they are discussing Inversion of control more-so than dependency injection.

One of my first languages was .net and I was never able to really understand DI in that context that well.

Actually using javascript and ducktyping made me understand what it actually was.

I remember a .net job interview where I had to write a micro-service and opted to construct the dependency graph in the main function initialising "all" the classes there. Instead of discussing the pro's and con's of that approach they berated me for not using a DI framework (No I did not land that job, but in hindsight it was the most expensive job interview I've ever had. The room was filled with 8 developers going over my code).

The main thing the article glosses over is state. something people with a functional background hide from. But if you look at something like the httpclient in .net. I think it took the .net world like 10 years to start using the httpclient properly. Scope and lifetime of those kind of objects are important. managing connection pools, retry state, throttling or the incoming http request. DI does make that kind of thing easieR (I'm not saying it makes it better)

Look at clojure's component(https://github.com/stuartsierra/component), I'm not a clojure expert by far. But it is kinda DI/IOC in a functional language.

In closing we can agree that it is underused in the right places and overused in the wrong ones.

https://github.com/stuartsierra/component#no-function-should-take-the-entire-system-as-an-argument

Yeah like I mentioned I'm not like super sold on the everything-should-be-an-actor paradigm, but I find value in DDD + a light implementation of Components (similar to stuartsierra/component).

https://github.com/stuartsierra/component for managing components lifecycles in projects

> what's wrong with that?

Why nothing at all, of course. A REPL need not be more than a way to test and explore syntax, functions, and logical structures.

> the user experience is REPL-ish and it can help some people learn the _basics_ of the language

PREPLISH exists for Perl ^_^

https://github.com/viviparous/preplish

If this is for testing of syntax or of trivial code, it sounds like a good use-case for running a local REPL. (Example: https://github.com/viviparous/preplish)

This is a simple REPL project and the readme lists other Perl REPLs.

https://github.com/viviparous/preplish

Perl's concise syntax makes working in a REPL a pleasure. Python has a REPL but the design of the language makes it expand both in length (for loops) and in width (tabs).

I am a recent convert to working in a REPL first to test programming ideas.

I made this solution for some of my simple data wrangling: https://github.com/viviparous/preplish

I tried the module it in a Perl REPL (https://github.com/viviparous/preplish) and got the following ravings that are worthy of a US loony politician:

I agree with you that the immediate start-up and feedback is a great benefit to the coder. This is why I dislike complex, Rube-Goldbergian REPL systems.

There is a use-case for a throw-away interaction with a REPL. For example, how does $builtinFuncX work, or how would $data best be imported into a structure?

A REPL can also be a good initial approach to a more ambitious problem. In this case, a REPL can be good for focus and discipline.

If the second case is going to answer your concern and be constructive, it's necessary to be able to build the code for sharing and cleanly export the code for re-use.

I've had success tackling challenges using REPLs for Python and Perl [1] in both ways. But no tooling is going to solve the problem of a sloppy teammate who claims success just because "it compiles" and "it works on my box". A person who knows how to build good tooling goes further.

[1] https://github.com/viviparous/preplish

It is Jupyter is a Rube-Goldbergian nightmare. Python is a memory hog. There are better solutions, to be sure.

A simple REPL is all that's needed to both do A-type and B-type data exploration. (I won't use the term "data scientist", it's an exaggeration in most cases.)

Python has a REPL, R has a REPL, Perl has PDL and both a simple REPL (https://github.com/viviparous/preplish) and a more complex one (https://metacpan.org/pod/Reply).

Jupyter should not be used as an IDE because it is the wrong tool for development. A-type data explorers just want a painless UI and may not care much about the horrible agglutination of incomplete/slow/broken solutions that Jupyter represents.