commands="\nthing1@this is thing 1\!\nthing2@this is thing 2!" while read line;do // do your stuff here line <<< $( echo -e "${commands}" )

Using quotes for i in "$(cat $1)"; results in i being assigned the whole file at once. What should I change?

Bash doesn't do word expansion on quoted strings in this context. For example: $ for i in "a b c d"; do echo $i; done a b c d $ for i in a b c d; do echo $i; done a b c d

The question is also not about error handling and if the file write fails, exiting with a stack trace is reasonable default behavior because there's not much you can do to recover from that.

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.

You might want to suppress only ValueError, since a TypeError (the input was not a string or numeric value) might indicate a legitimate bug in your program. To do that, write the exception type after except: def attempt_float(x): try: return float(x) except ValueError: return x

The first being signal handling. If the process launched does not handle SIGTERM by exiting, it will not be killed since it is PID 1 in the container

Tini does install explicit signal handlers (to forward them, incidentally), so those signals no longer get dropped. Instead, they're sent to Jenkins, which is not running as PID 1 (Tini is), and therefore has default signal handlers

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'.

1. Focus on items that occur with high frequency in the language as awhole (see Table 3.1 for examples). Such items will occur often inmany different texts.2. Focus on strategies that can be used with most texts (see Table 3.1for examples).

new Promise(function(resolve, reject) { setTimeout(() => { throw new Error("Whoops!"); }, 1000); }).catch(alert);

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.

Bash (like all Bourne shells) has a special syntax for referring to the list of positional parameters one at a time, and $* isn't it. Neither is $@. Both of those expand to the list of words in your script's parameters, not to each parameter as a separate word.

Instead of using a for loop, which will fail on spaces unless you redefine the IFS variable, I would recommend using a while loop combined with find.

Handling 401s well is important for the user's experience. They won't happen often (though more often than I expected), but really do break everything if you're not careful. Getting a good authentication abstraction library for Vue or Ember or whatever you are using should help with a lot of the boring parts. You'll probably need to define some extra strategies/rules for this cookie session approach, but if it's anything like in ember-simple-auth they're so simple it feels like cheating, because the Rails app is doing all of the hard work and you just need the js part to spot a 401 and handle logging in and retrying whatever it was doing before.

Drop missing values from the dataframeIn this method we can see that by using dropmissing() method, we are able to remove the rows having missing values in the data frame. Drop missing values is good for those datasets which are large enough to miss some data that will not affect the prediction and it’s not good for small datasets it may lead to underfitting the models.

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!".

A one-liner alternative for hash-only cases can be implemented using Enumerable#reduce: root = {} [:a, :b, :c].reduce(root){@1[@2]||={}}[:d] = 'E' # root => {:a=>{:b=>{:c=>{:d=>"E"}}}}

I think the issues/problems specified in the comments are not present with a Hash-only implementation. :) I would be supportive of re-considering this feature just for use with a Hash, where I believe 80% of the real-life use cases would (and do) exist. I have encountered this need before in the wild, but not with Arrays.

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.

Both kill with a job specifier and terminal signals send to the entire process group, so both the shell and sleep.

I am trying to understand how CTRL+C terminates a child but not a parent process. I see this behavior in some script shells like bash where you can start some long-running process and then terminate it by entering CTRL-C and the control returns to the shell. Could you explain how does it work and in particular why isn't the parent (shell) process terminated? Does the shell have to do some special handling of CTRL+C event and if yes what exactly does it do?

Remove your last "just in case" trap, and the script should work fine also with the EXIT traps. INT in the trap calling the cleanup should be the correct way to deal with the interrupts, however

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.

The main realization came when I figured out that the main_model was just another association. This means we can move a lot of logic to just that class and reason about it a lot better.

This syntax easily provides all the features of components, like let: bind: and on:. <svelte:fragment /> is just a component with a special name.

Service Workers are the hot new thing in web APIs. They’re designed to be like the HTML5 Application Cache, but without being objectionable.

the best way to ensure you've handled all errors in your run() function is to use run().catch(). In other words, handle errors when calling the function as opposed to handling each individual error.

// The `.then(v => [null, v], err => [err, null])` pattern // lets you use array destructuring to get both the error and // the result

Can you image your favorite web app working offline? Well, Progressive Web Apps (PWA) are here. One of their main benefits is that Service Workers will allow you to continue loading your apps even when there’s no internet connection.

Service Workers are also helpful for offline caching and performance. You can write code to cache your application shell to work offline and populate its content using JavaScript.

For example, your application should work offline, but it doesn’t mean that you must set-up a background queue or store your data in a persistent storage – a offline message (e.g. “You’re offline, check your network status.”) is enough.

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

If you were to check the return status of every single command, your script would look like this:

The "invisible try..catch" around the executor automatically catches the error and turns it into rejected promise.

Re Object.keys(undefined), I think I'm ok with that failing. AFAIK it would also fail in React

I just don't know if Svelte should handle it, since #each also fails for undefined iterators.

.catch(error => download_count = error) // check for error in template

As a web designer, I hate that "log in" creates a visual space between the words. If you line up "Log In Register" - is that three links or two? This creates a Gestalt problem, meaning you have to really fiddle with spacing to get the word groupings right, without using pipe characters.

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.

in the absence of an immediate need, it is simpler to leave out error handling until a final .catch() statement.

Handling a rejected promise too early has consequences further down the promise chain.   Sometimes there is no choice, because an error must be handled immediately.

A language that features polymorphism allows developers to program in the general rather than program in the specific. $(document).ready(function() { recordAdModuleData(2964, "impressions","Dictionary Ad"); });

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?