Make those judgments for your communities, instance by instance, not by network or software. Those sledgehammers are too big and unweildy.

Publish completed designs to Zeplin's platform while you iterate on designs in your design tool.

This is similar to gdonato's answer, but scopes in doorkeeper are better used for managing which permissions are being given to the authenticated app (i.e. "Give this app permission to read X and write Y on your behalf").

For instance, think of using a drill to drive in screws instead of using a screwdriver. The former makes work go faster and smoother.

If you are going to crawl sites you better use Ferrum or Vessel because you crawl, not test.

Sidekiq uses all of the data structures Redis provides: lists, sorted sets, hashes.

Simply don't use aliases in scripts. It makes little sense to use a feature designed for interactive use in scripts. Instead, use functions

So when should you use rbspy, and when should you use stackprof? The two tools are actually used in pretty different ways! rbspy is a command line tool (rbspy record --pid YOUR_PID), and StackProf is a library that you can include in your Ruby program and use to profile a given section of code.

The focus of the dev container specification is to describe how to enrich a container for the purposes of development, rather than acting as a multi-container orchestrator format.

But if you're working on a bigger project, with multiple packages and a complex dependency tree, you might want to combine npm with a tool like Lerna.

sed can do so much more, but is totally overkill for this. tr is the right tool for THIS job, but knowledge of sed and regexes will certainly come in handy later!

We think that, although Ruby is a great language for the backend, the view should be written in languages designed for that purpose, HTML and JavaScript.

Depending on what other component libraries you’ve used, you may be used to handling events by passing callback functions to component properties, or using a special event syntax – Svelte supports both, though one is usually more appropriate than the other depending on your situation. This post explains both ways.

We believe good tools lead to excellent creations.

It's super promising for web apps, just maybe not for web pages. I went from React to Svelte to Flutter for my current app project, and every step felt like a major upgrade.Flutter provides the best developer experience bar none, and I think it also has the potential to provide the best user experience. But probably only for PWAs, which users are likely to install anyway. Or other self-contained experiences, like Facebook games. It does have some Flash vibes, but is far more suitable for proper app development than Flash ever was while still feeling more like a normal website to the average user. It won't be the right choice for everything, but I believe it will be for a lot of things.

I also find that a lot of the complexity of Flutter can be avoided, and I mostly use it to define the UI as a more app-centric alternative to HTML/CSS.

Svelte by itself is great, but doing a complete PWA (with service workers, etc) that runs and scales on multiple devices with high quality app-like UI controls quickly gets complex. Flutter just provides much better tooling for that out of the box IMO. You are not molding a website into an app, you are just building an app. If I was building a relatively simple web app that is only meant to run on the web, then I might still prefer Svelte in some cases.

Some of these values are suited for development and some for production. For development you typically want fast Source Maps at the cost of bundle size, but for production you want separate Source Maps that are accurate and support minimizing.

The make install task installs the following files:

It's designed for Single Page Applications (SPA). If you need Server Side Rendering then consider using Sapper.

For an API used by many third parties with many diverse uses cases, GraphQL is the right tool.

Then when giving answers I'm even less certain. For example I see occasional how-to questions which (IMO) are ridiculously complex in bash, awk, sed, etc. but trivial in python, (<10 lines, no non-standard libraries). On such questions I wait and see if other answers are forthcoming. But if they get no answers, I'm not sure if I should give my 10 lines of python or not.

I went against the grain, applying other tools that people have written over the years to directly perform the job at hand which do not involve entering a program for awk or a shell to run, with answers like https://unix.stackexchange.com/a/574309/5132 and https://unix.stackexchange.com/a/578242/5132 . Others have done similar. https://unix.stackexchange.com/a/584274/5132 and https://unix.stackexchange.com/a/569600/5132 are (for examples) answers that show alternative tools to answers employing shell script and (yet again) awk programs, namely John A. Kunze's jot and rs (reshape), which have been around since 4.2BSD for goodness' sake!

There is an observable widespread tendency to give an awk answer to almost everything, but that should not be inferred as a rule to be followed, and if there's (say) a Python answer that involves less programming then surely that is quite on point as an answer for a readership of users.

Java may have been designed as a completely object oriented language, but when Java SE 8 was released in 2014, it added Lambda expressions (aka closures), which added some functional programming elements. Not every problem is best served by OOP, and by adding Lambdas, Java became more flexible. 

Ruby has some really nice libraries for working with linked data. These libraries allow you to work with the data in both a graph and resource-oriented fashion, allowing a developer to use the techniques that best suit his or her use cases and skills.

As an engineer, it’s important to explore different technologies. It’s important to identify the tools available to tackle problems. And it’s important to expand your horizons because then you can look cool on your CV.

What I think we're lacking is proper tooling, or at least the knowledge of it. I don't know what most people use to write Git commits, but concepts like interactive staging, rebasing, squashing, and fixup commits are very daunting with Git on the CLI, unless you know really well what you're doing. We should do a better job at learning people how to use tools like Git Tower (to give just one example) to rewrite Git history, and to produce nice Git commits.

IDEs and standard *nix tools like sed can help, but you typically have to make a trade-off between introducing errors and introducing tedium.

There is no system that is equally well-suited to significantly different scenarios.

The higher the load on the system, the more important it is to customize the system set up to match the requirements of the usage scenario, and the more fine grained this customization becomes. There is no system that is equally well-suited to significantly different scenarios. If a system is adaptable to a wide set of scenarios, under a high load, the system will handle all the scenarios equally poorly, or will work well for just one or few of possible scenarios.

Rather than using NFS for this task, use explicit data duplication, via one of the long-established mechanisms designed for this purpose.

This makes it easy to use Markdown to write about HTML code. (As opposed to raw HTML, which is a terrible format for writing about HTML syntax, because every single < and & in your example code needs to be escaped.)