ValueError: malformed node or string

I am not sure why I cannot use np.matrix or a matrix like the following:

import numpy as np

A = np.matrix('3 -5; 2 7')
print(A)
B = np.matrix('13; 81')
print(B)
A_det = np.linalg.det(A)
print(A_det)
X_m = np.matrix(A)
X_m[:, 0] = B
print(X_m)
Y_m = np.matrix(A)
Y_m[:, 1] = B
print(Y_m)
x = np.linalg.det(X_m) / A_det
y = np.linalg.det(Y_m) / A_det

print(x)
print(y)
X = np.matrix('x; y')
O = A @ X - B 
print(O)

I keep getting this error:

ValueError                                Traceback (most recent call last)
Cell In[38], line 19
     17 print(x)
     18 print(y)
---> 19 X = np.matrix('x; y')
     20 O = A @ X - B 
     21 print(O)

ValueError: malformed node or string on line 1: <ast.Name object at 0x2dc0210>

>Solution :

From the documentation on np.matrix:

If data is a string, it is interpreted as a matrix with commas or
spaces separating columns, and semicolons separating rows.

This means the data passed in the string, must be literals (1, or 1.5) not variables (or names).

Use an f-string instead:

X = np.matrix(f'{x}; {y}')

The error:

ValueError: malformed node or string on line 1: <ast.Name object at 0x2dc0210>

you are getting is because numpy is using ast.literal_eval to create the matrix (see here).