This my code:

import random
from mesa import Agent, Model
from mesa.space import MultiGrid
import math
import pandas as pd
import matplotlib.pyplot as plt

class MyAgent(Agent):
  def __init__(self, unique_id, model, pos, opinion, stubborn=False):
    super().__init__(unique_id, model)
    self.pos = pos
    self.opinion = opinion
    self.stubborn = stubborn
    self.neighbors = []

class MyModel(Model):
  def __init__(self):
    self.schedule = None
    self.grid = None

def create_population(num_agents, stubborn_ratio=0.1):
  model = MyModel()
  agents = []

  for i in range(num_agents):
    opinion = random.choice(["conservative", "liberal", "neutral"])
    is_stubborn = random.random() < stubborn_ratio
    agents.append(MyAgent(unique_id=i, model=model, pos=None, opinion=opinion, stubborn=is_stubborn))
  return agents

def assign_neighbors(agents, grid_width = None, grid_height = None):
  # Here, we are choosing the width and height of our matrix. if user 
  # already choose, use it. If not, assign it acc to agent num.
  if not grid_width or not grid_height:
    grid_width = int(math.ceil(math.sqrt(len(agents))))
    grid_height = grid_width
  # create the matrix. "grid" will be 2D matrix.
  grid = MultiGrid(width=grid_width,height=grid_height, torus=True)
  
  for agent in agents:
    x = random.randint(0, grid_width - 1)
    y = random.randint(0, grid_height - 1)
    agent.pos = (x, y)
    grid.place_agent(agent, (x, y)) #place agents on the grid.
    
  for agent in agents:
    x,y = agent.pos
    agent.neighbors = grid.get_neighbors((x,y), moore=True, include_center=False)
  return grid

def visualise_agents(agents):
  data = []

  for agent in agents:
    color = "gray"
    if agent.opinion == "conservative":
      color = "red"
    elif agent.opinion == "liberal":
      color = "blue"
    
    data.append({"x": agent.pos[0], "y": agent.pos[1], "opinion": agent.opinion, "color": color})
  
    df = pd.DataFrame(data)
  
    plt.figure(figsize=(8,8))
    scatter = plt.scatter(df["x"], df["y"], c=df["color"], label=df["opinion"],alpha=0.7)
  
    red_patch = plt.Line2D([0], [0], marker="o", color="w", markerfacecolor="red", markersize=10, label = "Conservative")
    blue_patch = plt.Line2D([0], [0], marker="o", color="w", markerfacecolor="blue", markersize=10, label = "Liberal")
    gray_patch = plt.Line2D([0], [0], marker="o", color="w", markerfacecolor="gray", markersize=10, label = "Neutral")
    plt.legend(handles=[red_patch, blue_patch, gray_patch])
  
    plt.title("Agent positions and Ideologies")
    plt.xlabel("X position")
    plt.ylabel("Y position")
    plt.grid(True)
    plt.show()

agents = create_population(100)
assign_neighbors(agents)

visualise_agents(agents)

and this is the error:

Traceback (most recent call last):
  File "c:Users...project.py", line 79, in <module>
    agents = create_population(100)
^^^^^^^^^^^^^^^^^^^^^^
  File "c:Users...project.py", line 28, in create_population
    agents.append(MyAgent(unique_id=i, model=model, pos=None, opinion=opinion, stubborn=is_stubborn))
^^^^^^^^^^^^^
  File "c:Users...project.py", line 10, in __init__
    super().__init__(unique_id, model)
  File "C:Users...AppDataLocalProgramsPythonPython312Libsite-packagesmesaagent.py", line 64, in __init__       
    super().__init__(*args, **kwargs)
TypeError: object.__init__() takes exactly one argument (the instance to initialize)

I have been trying to fix this issue for a while. Basically i am just learning python, and now i am trying to build ABM with mesa. Because i couldn’t find detailed tutorials in youtube i am moving with AI but it also couldn’t help me with this. I am trying to simulate political ideology changes of people. Before i continue and detail the whole code deeply, i wanted to see what i have done but now it is not working.