input: Write a function to generate a Python script for competing in a Kaggle competition. The script should load necessary libraries, read data from a CSV file, split the data into training and testing sets, define a model, fit the model on the training data, make predictions on the test data, calculate the accuracy score, and prepare the submission for Kaggle.
  
  assert generate_kaggle_script()=="""import pandas as pd
  import numpy as np
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import accuracy_score
  
  # Read in the data
  train_data = pd.read_csv("data.csv")
  
  # Split the data into X (predictors) and y (response)
  X = train_data.drop('response', axis=1)
  y = train_data['response']
  
  # Split into training and testing sets
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)
  
  # Define the model and fit it
  model = ...
  model.fit(X_train, y_train)
  
  # Make predictions on the test set
  y_pred = model.predict(X_test)
  
  # Score the prediction
  score = accuracy_score(y_test, y_pred)
  
  # Submit the prediction to Kaggle
  # ..."""
  assert generate_kaggle_script([])==""
  assert generate_kaggle_script([1, 2, 3])==""
output: 
  import pandas as pd
  import numpy as np
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import accuracy_score
  from sklearn.ensemble import RandomForestClassifier
  
  # Read in the data
  train_data = pd.read_csv("data.csv")
  
  # Split the data into X (predictors) and y (response)
  X = train_data.drop('response', axis=1)
  y = train_data['response']
  
  # Split into training and testing sets
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, random_state=42)
  
  # Define the model and fit it
  model = RandomForestClassifier(random_state=42)
  model.fit(X_train, y_train)
  
  # Make predictions on the test set
  y_pred = model.predict(X_test)
  
  # Score the prediction
  score = accuracy_score(y_test, y_pred)
  
  # Prepare the submission for Kaggle
  submission = pd.DataFrame({'Id': X_test.index, 'Predicted': y_pred})
  submission.to_csv('submission.csv', index=False)
  