Active job instances include ActiveSupport::Rescuable which means you can use rescue_from in a job in the same way you can in a controller.

I just spent a day dismantling a model, trying to find the cause of the silent rollback - taking out every association, every validation, every callback, whittling down all the code in the transaction, only to finally discover that it was return true that was the cause of it all. Or yes, an exception!

This code is much easier to understand as it do not add levels of indentation and follows the principle where the 0 indentation level is the principal path of the application where other paths are exceptions or rare cases.

Otherwise behaves according to the value of null_value_treatment which must be one of 'raise_exception', 'use_json_null', 'delete_key', or 'return_target'. The default is 'use_json_null'.

The best you can do is try/catch inside a function that is reactively called, but my goal is to have a global exception handler to handle all exceptions that I did not expect...

If at least one component has smallest unhandled error, the whole app will crash and users will not know what to do and developers will not know such an error occurred.

Boilerplate is only boilerplate if it's the same everywhere, which it shouldn't be.

Some argue that throwing an exception in the executor function is bad practice. I strongly disagree.

Throw it's a more elegant way to use an exception-like system as a control flow.

The basic rule of thumb is: "I'm not aware of all types of security exploits. I must protect against those I do know of and then I must be proactive!".

you can use the wtf? command to display a few lines of the backtrace for the most recent exception

the ability to “error out” when something goes wrong

If anything here did fail in “validate omniauth”, all other steps in the chain would be skipped as the flow would follow the path leading to the failure terminus.

Things could go wrong in two places here. First, the validation could fail if Github sends us data we don’t understand. Second, we might not know the user signing in, meaning the “find user” logic has to error-out

Literally, everything in this example can go wrong. Here’s an incomplete list of all possible errors that might occur: Your network might be down, so request won’t happen at all The server might be down The server might be too busy and you will face a timeout The server might require an authentication API endpoint might not exist The user might not exist You might not have enough permissions to view it The server might fail with an internal error while processing your request The server might return an invalid or corrupted response The server might return invalid json, so the parsing will fail And the list goes on and on! There are so maybe potential problems with these three lines of code, that it is easier to say that it only accidentally works. And normally it fails with the exception.

Return None. That’s evil too! You either will end up with if something is not None: on almost every line and global pollution of your logic by type-checking conditionals, or will suffer from TypeError every day. Not a pleasant choice.

we also wrap them in Failure to solve the second problem: spotting potential exceptions is hard

Exceptions are just like notorious goto statements that torn the fabric of our programs.

So, the sad conclusion is: all problems must be resolved individually depending on a specific usage context. There’s no silver bullet to resolve all ZeroDivisionErrors once and for all. And again, I am not even covering complex IO flows with retry policies and expotential timeouts.

certainly I wouldn't want it to start telling me that I'm not catching these!

Railway Oriented Programming is a way to gracefully handle errors in your application

Monads provide an elegant way of handling errors, exceptions and chaining functions so that the code is much more understandable and has all the error handling, without all the ifs and elses.

As you can see, we end up with a lot of boilerplate if-statements. The code is more verbose. And it’s difficult to follow the main logic.

In JavaScript, we have a built-in language feature for dealing with exceptions. We wrap problematic code in a try…catch statement. This lets us write the ‘happy path’ in the try section, and then deal with any exceptions in the catch section. And this is not a bad thing. It allows us to focus on the task at hand, without having to think about every possible error that might occur.

And they are not the only way to handle errors.

In this article, we’ll take a look at using the ‘Either monad’ as an alternative to try...catch.

Maybe T can be understood as a "wrapping" type, wrapping the type T into a new type with built-in exception handling

Undefined values or operations are one particular problem that robust software should prepare for and handle gracefully.

This style of error handling uses monadic behavior — a substitute way of handling errors.

Personally, I prefer signalling an error for invalid values

You can rescue at the method level, but more likely you’d want to rescue at the statement level.

Other filters will ignore blocks when given to them.

Note that it's perfectly fine to add errors during execution. Not all errors have to come from type checking or validation.

Inside the interaction, we could use #find instead of #find_by_id. That way we wouldn't need the #find_account! helper method in the controller because the error would bubble all the way up. However, you should try to avoid raising errors from interactions. If you do, you'll have to deal with raised exceptions as well as the validity of the outcome.

yell() { echo "$0: $*" >&2; } die() { yell "$*"; exit 111; } try() { "$@" || die "cannot $*"; }

JSON parsing is always pain in ass. If the input is not as expected it throws an error and crashes what you are doing. You can use the following tiny function to safely parse your input. It always turns an object even if the input is not valid or is already an object which is better for most cases.

To be just a bit polemic, your first instinct was not to do that. And you probably wouldn't think of that in your unit tests either (the holy grail of dynamic langs). So someday it would blow up at runtime, and THEN you'd add that safeguard.

I want to raise errors with more context

As many would guess: ... catch StandardError => e raise $! ... raises the same error referenced by $!, the same as simply calling: ... catch StandardError => e raise ... but probably not for the reasons one might think. In this case, the call to raise is NOT just raising the object in $!...it raises the result of $!.exception(nil), which in this case happens to be $!.

It is recommended that a library should have one subclass of StandardError or RuntimeError and have specific exception types inherit from it. This allows the user to rescue a generic exception type to catch all exceptions the library may raise even if future versions of the library add new exception subclasses.

matcher === exception or exception.cause && block[exception.cause]

The pattern below has become exceptionally useful for me (pun intended). It's clean, can be easily modularized, and the errors are expressive. Within my class I define new errors that inherit from StandardError, and I raise them with messages (for example, the object associated with the error).

Você consegue visualizar a saúde da sua aplicação?