Managing memory utilization using Pickle

pickle.py

#===Import dependencies===
import gc
import pickle
import psutil
import numpy as np
import pandas as pd
#===Function to track memory usage===
def memory_utilization():
  print('Current memory utilization: {}% ...'.format(psutil.virtual_memory().percent))

if __name__ == "__main__":
  print(f'Memory utilization before creating the example Pandas dataframe: \n{memory_utilization()}')
  #===Create a dataframe using random integers between 0 and 1000===
  var=pd.DataFrame(np.random.randint(0,1000,size=(int(2.5e8),2)),columns=['var1','var2'])
  print(f'Memory utilization after creating the example Pandas dataframe: \n{memory_utilization()}')
  #==Create Pickle dump===
  pickle.dump(var,open('var.pkl','wb'))
  print(f'Memory utilization after creating the pickle dump: \n{memory_utilization()}')
  #===Delete the unused variable from memory===
  del var
  _=gc.collect()
  print(f'Memory utilization after deleting the variable from memory: \n{memory_utilization()}')
  #===Restore the variable from the disk for future use===
  var=pickle.load(open('var.pkl','rb'))
  print(f'Memory utilization after re-loading the variable from the pickle dump to memory: \n{memory_utilization()}')