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frcooper / comic-vine-scraper

An add-on script for ComicRack that lets you copy details from Comic Vine into your comic books.
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XellossNakama's Patches? #2

Open dylan-k opened 1 week ago

dylan-k commented 1 week ago

This fork of the plugin appears to be the most up-to-date, so I thought to suggest this here. @frcooper would you consider any pull requests to integrate the patches created by XellossNakama?

Among other things, the patches make more efficient use of the ComicVine API, useful considering its tighter restrictions nowadays.

frcooper commented 1 week ago

https://github.com/frcooper/comic-vine-scraper/pull/3 - how exactly does this make better use of the api?

dylan-k commented 1 week ago

It appears to make more efficient use of the API by making less frequent calls to it. This way the API won't hit your limits as quickly/often. The code is a available for review but a pull request might make it easier for comparison.

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frcooper commented 6 days ago

a pull request might make it easier for comparison. Yeah. I know. That's why I made one.

dylan-k commented 3 days ago

how exactly does this make better use of the api?

Some of the changes, particularly in cvdb.py are likely to yield greater efficiency, especially in handling ambiguous or high-volume search terms, by improving term normalization, expanding result limits, and implementing prioritization logic. These updates should reduce API calls in scenarios where large or nuanced search queries are involved.

here are the main updates:

As for what's going on with images, there could be some more explanation of the changes in the earlier post:

If you use the "try to select the correct series automatically" in the script options... this doesn't only check data and select the first option if the match is good enough... IT COMPARE THE IMAGES OF THE PREVIEW AND THE COVER and only if they are similar enough, it continues automatically... It already did what I always wanted! (I never used the select the series automatically because I was afraid of incorrect matches). You can even edit the code (it is automatcher.py and tune the __MATCH_THRESHOLD (the default is 87% of similarity, I tune it to 93, more than that and the "barcodes" or things like that that are different from digitals to paper covers will make them different enough many times)