To solve a linear system in Python, you can use the `numpy`

library. Here’s an example of how to solve a linear system in Python:

```
import numpy as np
# Define the matrix of coefficients
A = np.array([[2, 3], [4, 5]])
# Define the column vector of constants
b = np.array([6, 7])
# Solve the linear system
x = np.linalg.solve(A, b)
# Print the solution
print(x)
```

In this example, we first import the `numpy`

library using `import numpy as np`

.

We define the matrix of coefficients using `A = np.array([[2, 3], [4, 5]])`

and the column vector of constants using `b = np.array([6, 7])`

.

We solve the linear system using `x = np.linalg.solve(A, b)`

. This function takes in the matrix of coefficients and the column vector of constants and returns a solution as a row vector.

Finally, we print the solution using `print(x)`

.

Note: You’ll need to modify the code to define your own matrix of coefficients and column vector of constants. Make sure that the linear system has a unique solution.

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