Comparing and Quantifying similarity in a set of non linear data

I have 2 lists of data which are basically a batch of SEQUENTIAL data(thus, data cannot be sorted) from a larger database which are as follows

a = [0.8, 0.9, 0.4, -0.4, 1.12, 1.16, 1.08, 1.22]

b = [0.85, 0.96, 0.4, -0.4, 1.15, 1.18, 1.1, 1.92]

The data provided may not be linear in nature and thus typical correlation wont serve the purpose.

I wish to compare a and b (as a line graph) and assign a similarity score to them.

Ive tried implementing linear co-relation from the stats library but the results are not convincing.

Any way to do this using any other statistical function, which emphasizes on the importance of non linear data?

Also, is any supporting function available in scikit learn?