hattery VS NullAway

While I think there's a lot to love about Java, I think the standard library itself is not an especially great role model. Most of it was written a long time ago and has a fairly antiquated style - lots of mutable state, nullability, and checked exceptions. Not that the library isn't an incredible asset - it's luxuriously rich compared to working in Node.js - but if it were written from scratch today, I suspect it would look fairly different. Eg, the collection classes would use Optional and have separate read/write interfaces.

For an example of "modern Java" I would point at something like this (which I wrote, sorry about the hubris):

https://github.com/stickfigure/hattery

I have been thinking of writing up a series of articles on this. Without going into too much detail:

* IDEA

* Deploy on Google App Engine, Digital Ocean App Platform, Heroku, Elastic Beanstalk, etc - get out of the ops business entirely.

* Guice as the backbone, no Spring/Boot. I wrote a tiny dropwiard-like "framework" to make this easier: https://github.com/gwizard/gwizard but there's a laughable amount of code here, you could build it all from scratch with minimal effort. This is about as lightweight as "frameworks" get because Guice does the heavy lifting.

* JAX-RS (Resteasy) for the web API. IMO this is the best part of Java web development. HTTP endpoints are simple synchronous Java methods (with a few annotations) and you can test them like simple Java methods.

* Lombok. Use @Value heavily. Cuts most of the boilerplate out of Java.

* Junit5 + AssertJ. (Or Google Truth, which is almost identical to AssertJ).

* Use functional patterns. Try to make all variables and fields final. Use collections streams heavily. Consider vavr.io (I'll admit I haven't it in anger yet, but I would in a new codebase).

* StreamEx. Adds a ton of useful stream behavior; I don't even use basic streams anymore.

* Guava. There's just a lot of useful stuff here.

* For the database, it really depends on what you're building. Most generic business apps, postgres/hibernate/guice-persist/flyway. Yeah, folks complain about hibernate a lot but it's a decent way to map to objects. Use SQL/native queries, don't bother with JPQL, criteria queries, etc.

* Hattery for making http requests (https://github.com/stickfigure/hattery). This is another one of mine. I make zillions of http requests, functional/immutable ergonomics really matter to me.

* Github actions for CI.

* Maven for the build. Yes, it's terrible, except for every other build system is worse. Gradle seems like it should be better but isn't. I'd really love some innovation here. Sigh.

I can't stand most http libraries (full of mutable state!) and I spend a lot of time making http calls. So I built a functional/immutable http request library which has been dramatically improving my personal quality of life for about 7 years now. No idea if anyone else uses it, but it doesn't really matter.

Java version: https://github.com/stickfigure/hattery

Typescript version: https://github.com/stickfigure/hatteryjs

Some patterns arise from language design

* You can't express `T` where `null` is forbidden in the type system so you get NullPointerException everywhere and defensive null checks.

* You express a sum type as a product type because your language does not have sum types .

* Your language doesn't have first class multiple return values (or tuples) so you return extra parameters via out parameters or thread local variables such as `errno`.

* Your language doesn't have exceptions (or algebraic effects) and can't do IO so you have monad transformers.

* Your language doesn't have set-theoretic types so you need hacks like `thiserror` .

* Your language doesn't have stackful coroutines or can't infer async IO for you so you have `async/await` spam or callback hell or "mono's".

* Your language doesn't have exhaustive checks (or pattern matching) so you need a fallthrough case check on switch statements .

* Your language doesn't have algebraic effects, so you need to pass context everywhere.

I know someone will reply about Java's null annotation checking options, so here is one of them: https://github.com/uber/NullAway .

If you must use Java, use Uber's Nullaway which gives null safety via Errorprone.

Does anyone have experience using this at Meta who can compare to https://github.com/uber/NullAway ?

A special kind of validation is enforcing that record fields are not null. (Un)fortunately, records do not have any special behavior regarding nullability. You can use tools like NullAway or Error Prone to prevent null in your code in general, or you can add checks to your records:

What do you think of https://github.com/uber/NullAway

Take a look at NullAway, a plugin for Error Prone.

PMD, Spotbugs, Nullaway: Java linting/static analysis (https://pmd.github.io, https://spotbugs.github.io, https://github.com/uber/NullAway)

In personal projects, I've had good experiences using the error-prone compiler plugin with uber's nullaway.