Wolf | VsCode extension that enables live inspection | Code Inspection library

You can treat characters in a Raku regex literally by surrounding them with quotes (e.g., '.*?') or by using using regular variable interpolation (e.g., $substring inside the regex where $substring is a string contaning metacharacters).

Thus, to translate the Perl program with \Q...\E from your question into Raku, you could write:

What makes you think that this should be possible? If your type contains a function field, then comparing values of your type for equality is at least as difficult as comparing functions for equality. But to check that two functions are equal (in Haskell, the only sensible meaning is extensional equality), you'd need to check that they agree on all possible inputs. That's an utterly infeasible thing to do, even for simple Int inputs but certainly if the arguments have type [Char].

So, why I need the deriving(Eq)? I need it because in the main I check if is Nothing

You totally don't need Eq for that! Testing whether a Maybe value is Nothing by using == is ineffective, even on those types where it is possible. You should instead use either pattern matching

powershell have the ability to convert items from json to psobjects.

powershell 7 have added the ability to even convert it to hashtable:

The line giving you the error is in fact move-to min-one-of wolves [distance myself].

As you can see, the error only happens when there are no foxes left in the model. This is because you have not included a stop condition or anything else that prevents the model to search for wolves where there are none.

Assuming that you are happy to have the model stop when the tiger has eaten all the wolves, you can just do:

The problem lies in your syntax for the is-a-sheep? and is-wolf? statements. is-breed? takes a single argument, the identity of the agent you are testing. Your code should therefore be

The exact logic of the output is unclear, but you want merge and groupby+agg:

It's not a v4 indicator, it's written in Pine v1, hence why it works without specifying the version at the beginning. Migration guides from earlier Pine versions to the newer ones can be found in the User Manual.

Working v5 code:

Maybe something like this? It first categorizes the data as john or not, then nests all the data for each category into one list, then pivots those two categories wide.