# How to Solve a System of Equations in Python?

The solution of a system of equations in Python depends on the type of equations you are dealing with.

If you have a system of linear equations, you can use the `numpy` library to solve it as shown in the previous answer.

If you have a system of nonlinear equations, you can use the `scipy.optimize` module. Here’s an example of how to solve a system of nonlinear equations in Python:

``````import numpy as np
from scipy.optimize import root

# Define the system of equations
def system(x):
y = np.zeros(2)
y[0] = x[0]**2 + x[1]**2 - 1
y[1] = x[0] - x[1]**3 - 1
return y

# Define the initial guess
x0 = np.array([0.5, 0.5])

# Solve the system of equations
sol = root(system, x0)

# Print the solution
print(sol.x)``````

In this example, we first import the `numpy` and `scipy.optimize` modules using `import numpy as np` and `from scipy.optimize import root`.

We define the system of equations using a function called `system`. This function takes in a vector `x` containing the variables `x` and `y`, and returns a vector `y` containing the values of the equations.

We define an initial guess for the variables using `x0 = np.array([0.5, 0.5])`.

We solve the system of equations using `sol = root(system, x0)`. This function takes in the system of equations and the initial guess, and returns a solution as an object. We access the solution vector using `sol.x`.

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

Note: You’ll need to modify the code to define your own system of equations and initial guess.