It's funny, but as a naive reader, I was reading through with the question of why you would use DCT whether it's significantly different from python's cosine_si

It's funny, but as a naive reader, I was reading through with the question of why you would use DCT whether it's significantly different from python's cosine_similarity, and why you would use that instead of say, pythagorean distance, edit distance, conditional entropy, and related methods. Is it a speed/accuracy trade off? Obviously I don't have depth on these as the answer would be trivial to someone who did, but I'm wondering if there a simple breakdown of what these and other information similarity methods optimize for.