scikit-bio VS viroiddb

You make a fair point that using optimized numerical libraries instead of string methods will be ridiculously fast because they're compiled anyway. For example, scikit-bio does just this for their reverse complement operation [1]. However, they use an 8 bit representation since they need to be able to represent the extended IUPAC notation for ambiguous bases, which includes things like the character N for "aNy" nucleotide [2]. One could get creative with a 4 bit encoding and still end up saving space (assuming you don't care about the distinction between upper versus lowercase characters in your sequence [2]). Or, if you know in advance your sequence is unambiguous (unlikely in DNA sequencing-derived data) you could use the 2 bit encoding. When dealing with short nucleotide sequences, another approach is to encode the sequence as an integer. I would love to see a library—Python, Nim, or otherwise—that made using the most efficient encoding for a sequence transparent to the developer.

[1] https://github.com/biocore/scikit-bio/blob/b470a55a8dfd054ae...

[2] https://en.wikipedia.org/wiki/Nucleic_acid_notation

[3]

That's great. However the method that you use to find the canonical representative [1] is quadratic (when the string has length N, there are N rotations and for each rotation you need to check N characters to determine whether this is earlier than the best on that you have found so far). For large strings you would probably want to switch to one of the linear minimal string rotation algorithms [2].

[1] https://github.com/Benjamin-Lee/viroiddb/blob/main/scripts/c...

[2] https://en.wikipedia.org/wiki/Lexicographically_minimal_stri...