scipy

import numpy as np
import scipy
import numpy.linalg as LA
n=10
m=20
A=np.random.random((n,m))
b_=np.random.rand(m)
b=b_.T
x=b/A
z=A*x-b
print(scipy.argmin(LA.norm(z,2)))

0

import numpy 
import scipy.optimize as so
import matplotlib.pyplot

def func(x):
    return -1*numpy.sin((x- 2) * numpy.exp(-1*x * 2)) ** 2 
a=-1*so.fminbound(func,-5,5)
print(a)

3.4589877431969027

import scipy.spatial.distance as distance 
import numpy as np  
m =   5
n =   4
X = np.random.rand(m, n)  
dis = distance.pdist(X,'euclidean')  
z = distance.squareform(dis) 
print(z)   

[[0.         0.54362045 0.45114014 0.35454277 0.77778626]
 [0.54362045 0.         0.90772523 0.86819444 1.18751828]
 [0.45114014 0.90772523 0.         0.42826591 0.34740282]
 [0.35454277 0.86819444 0.42826591 0.         0.74527742]
 [0.77778626 1.18751828 0.34740282 0.74527742 0.        ]]