You can pack and unpack functions arguments in Python.

If you have a function take takes in \(n\) arguments, you can’t just pass it a list of said arguments. Let’s say we have a linear function that takes in an array of \(x\)-values, a slope and intercept.

import numpy as np

x_array = np.linspace(1, 10, 10)

def linear(x, m, b):
  return x * m + b
  
args = [2, 4]
# the operation below leads to 
# TypeError: linear() missing 1 required positional argument: 'b'

linear(x_array, args)

Python takes in the x_array and args list as the first positional arguments. We can use the unpacking convention instead to break up args into its constituents.

linear(x_array, *args)
## array([ 6.,  8., 10., 12., 14., 16., 18., 20., 22., 24.])

More details on this here.