text: import pandas as pd
  import numpy as np
  from sklearn.metrics import mean_squared_error as mse
  from hyperopt import fmin, tpe, hp, STATUS_OK, Trials
  from sklearn.preprocessing import StandardScaler
  
  
  def hyperopt_objective(model, train_data, test_data):
  
      train_x, train_y = train_data
      test_x, test_y = test_data
  
      def _loss(kwargs):
          _m_instance = model(**kwargs)
          _m_instance.fit(train_x, train_y)
          result = {
              'loss': np.sqrt(mse(_m_instance.predict(test_x), test_y)),
              'status': STATUS_OK,
              'other_stuff': {
                  'kwargs': kwargs,
                  'train_rmse': np.sqrt(mse(_m_instance.predict(train_x), train_y)),
              },
          }
          return result
  
      return _loss
  
  
  def make_scaled(df_origin):
      def standartize(dataset):
          scaler = StandardScaler()
          try:
              return scaler.fit_transform(dataset.to_numpy())
          except:
              return scaler.fit_transform(dataset)
  
      df = pd.DataFrame(
          data=standartize(df_origin), 
          index=df_origin.index, 
          columns=df_origin.columns
      )
      return df
  
  def load_credentials(path):
      from json import load
      with open(path, 'r') as reader:
          return load(reader)
  
  def busy_wait():
      from time import sleep
      while True:
          sleep(3)