# How to Solve a System of ODEs in Python?

To solve a system of ODEs (ordinary differential equations) in Python, you can use the `scipy.integrate` module. Here’s an example of how to solve a system of ODEs in Python:

``````import numpy as np
from scipy.integrate import odeint

# Define the system of ODEs
def system(y, t):
x, y = y
dxdt = x * (3 - x - 2*y)
dydt = y * (2 - x - y)
return [dxdt, dydt]

# Define the initial conditions
y0 = [1, 1]

# Define the time points at which to solve the ODEs
t = np.linspace(0, 10, 101)

# Solve the ODEs
sol = odeint(system, y0, t)

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

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

We define the system of ODEs using a function called `system`. This function takes in two arguments: the state `y` and the time `t`. The state `y` is a list containing the values of `x` and `y`, and the function returns a list containing the values of `dx/dt` and `dy/dt`.

We define the initial conditions for `x` and `y` using `y0 = [1, 1]`.

We define the time points at which to solve the ODEs using `t = np.linspace(0, 10, 101)`. This creates an array of 101 equally spaced time points between 0 and 10.

We solve the ODEs using `odeint(system, y0, t)`. This function takes in the system of ODEs, the initial conditions, and the time points at which to solve the ODEs, and returns a solution as an array.

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

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