I have been working on the problems in Codility to get better at the algorithms and also to expand the way I solve problems in general. One common thing I notice with using Python as the language is that, sometimes the solutions are so simple I wonder if I learnt anything at all.

Take for example, this challenge called GenomicRangeQuery which aims to teach the application of Prefix sums in problem solving. Here is the solution which gets the perfect score of 100% for both accuracy and complexity.

def solution(S, P, Q): mins = [] for i in range(0, len(P)): start = P[i] end = Q[i]+1 sub = S[start:end] if 'A' in sub: mins.append(1) elif 'C' in sub: mins.append(2) elif 'G' in sub: mins.append(3) else: mins.append(4) return mins

The solution felt like cheating and also, I wasn’t sure of the complexity of **in** keyword magic of Python. I searched for a solution in a low level language to understand better. Here is it in Java. Reproducing for quick comparison.

public static int[] genome(String S, int[] P, int[] Q) { int len = S.length(); int[][] arr = new int[len][4]; int[] result = new int[P.length]; for(int i = 0; i < len; i++){ char c = S.charAt(i); if(c == 'A') arr[i][0] = 1; if(c == 'C') arr[i][1] = 1; if(c == 'G') arr[i][2] = 1; if(c == 'T') arr[i][3] = 1; } // compute prefixes for(int i = 1; i < len; i++){ for(int j = 0; j < 4; j++){ arr[i][j] += arr[i-1][j]; } } for(int i = 0; i < P.length; i++){ int x = P[i]; int y = Q[i]; for(int a = 0; a < 4; a++){ int sub = 0; if(x-1 >= 0) sub = arr[x-1][a]; if(arr[y][a] - sub > 0){ result[i] = a+1; break; } } } return result; }

Needless to say, the solution is beautiful and as intended (teaches the application of prefix sums).

## Pondering

The difference in the complexity of the two solutions showcases the power and simplicity of Python.

So what am I doing with Python? I am writing simpler code definitely. It is good. I am also worried that I might not be learning a number of techniques that will help in the long run.