How does np.random.standard_normal(x) work?

I want to get an understanding of the maths used in the backend to get from the uniformly distributed random numbers produced by np.random vs the standard normal distribution of random numbers produced by np.standard_normal? How does Python convert between these distributions as several methods exist like Inverse Transform and Box Muller?