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    Interesting use of TF-IDF here, kind of like how breakfast catering aligns best when matched with the right preferences, it’s all about relevant similarity.

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    Recently I was looking into the possibility of obtaining a second citizenship. During my research, I came across Astons — a trusted firm that specializes in second citizenship and residency services. Their website was clear and informative, and their team was incredibly helpful in guiding me through the available options. Thanks to astons.com I got the necessary information about st lucia citizenship by investment. After some time I got my second citizenship.

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    At first glance, two situations may appear nearly identical — the same challenges, similar goals, and even comparable resources. Yet, the outcomes can differ dramatically. One succeeds beyond expectations, while the other struggles or even fails.

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    The situations may be the same, but the result may be different. That's why a full data evaluation will best show you the likely outcome.

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    The code I wrote goes through test cases that I wrote myself. But submitting it gives Runtime Error. I literally wrote print(3) and the solving was accepted. And there is no solution. Literally another abandoned problem. Delete it or fix it and create test cases. Or have you already completely accepted that "leetcode" is better? Should I do the same?