xnp.py

#As we have generated small data like 1-15, it is fast. But when processing/generating huge amount of data like in millions and trillions
#you need to process fastly. That's when numpy arrays will come useful.
#this is calculate the start time
timestamp1 = time.time()
#generate data in range of 0 to 1 million using numpy arrays
x = np.arange(1000000)
#end time    
timestamp2 = time.time()
#time taken to generate 1 million data.
print("This took %.2f seconds" % (timestamp2 - timestamp1))

#This took 0.02 seconds

#lets generate the same data using lists

timestamp1 = time.time()

x = []
for i in range(1000000):
    x.append(i)
    
timestamp2 = time.time()
print("This took %.2f seconds" % (timestamp2 - timestamp1))

#output: This took 0.33 seconds