Error Renaming Multiple Part Episode by Title - Dangling Meta Character '*'

[sqlallstar]

I am using this preset to find episodes with only a name and match them properly. (on 4.9.6)

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{episodelist.findAll{ fn =~ it.title }.join(' & ')}

Episode file is like this:

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Dexter's Laboratory - The Busboy & Things That Go Bonk in the Night & Ol McDexter

And it gives me this error + the file name

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[Dangling meta character '*' near index 0*Figure Not Included^] Dexter's Laboratory - Ol' McDexter

Any idea what is going on?

THanks!

[rednoah]

1.

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"string" =~ /regex/

assumes that the right-handside is a regular expression. The episode title from the database is not guaranteed to accidentally be a valid regular expression. You probably mean to use String.contains() to check for a substring match:

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"string".contains("string")

2.

I am using this preset to find episodes with only a name and match them properly. (on 4.9.6)

Code: Select all

{episodelist.findAll{ fn =~ it.title }.join(' & ')}

Note that formatting is unrelated to matching. If you "fake" the file path in the format, that has no effect on the underlying xattr metadata that is the match.


Match by Episode Title would be the recommended approach, though limited to single episode matches. Match multi-episode out-of-order cartoon episodes by title is an advanced command-line use case which does not have a real 1-step equivalent in the Desktop application as far as I know.


Note your code does not work for the sample file name above, because "Things That Go Bonk" does not contain "The Justice Friends: Things That Go Bonk in the Night" and "The Busboy" does not contain "The Bus Boy". The "Multiple Part Episode by Title" use case is very tricky after all.

[rednoah]

Are all your files tripple episodes? Or is it a mix of 2-episode files, 3-episodes files, 4-episodes files, etc at random?


Can you paste all the file paths as text so we can look at this use case in more detail?


If your files are grouped into multi-episodes by episode airdate, then we could add a "Group by Date" feature to make this use case easier in the Desktop application as well: