Usually, when we run long computations we include some print statements like this one:

number_of_elements = 1000

for i in range(number_of_elements):
    if i % 100 == 0:
        print(i)
    time.sleep(0.01) #Here should be the code that does the computation.

print('Done')

We end up with something similar to this output:

Output
Output

We do it because we wonder whether the Notebook is still running. We want to see the progress. That is sufficient, but it does not look good, does it?

What if we could display a progress bar? We can! Here is the code:

import time, sys
from IPython.display import clear_output

def update_progress(progress):
    bar_length = 20
    if isinstance(progress, int):
        progress = float(progress)
    if not isinstance(progress, float):
        progress = 0
    if progress < 0:
        progress = 0
    if progress >= 1:
        progress = 1

    block = int(round(bar_length * progress))
    clear_output(wait = True)
    text = "Progress: [{0}] {1:.1f}%".format( "#" * block + "-" * (bar_length - block), progress * 100)
    print(text)

And now, when we run the computation we see a nice progress bar ;)

number_of_elements = 1000

for i in range(number_of_elements):
    time.sleep(0.1) #Replace this with a real computation
    update_progress(i / number_of_elements)

update_progress(1)
Progress bar
Progress bar

The solution is based on Philip Osborne’s blog post and an answer to the StackOverflow question.

Subscribe to the newsletter
Older post

Save and restore a Tensorflow model using Keras for continuous model training

How to run fit function multiple time and improve the model?

Newer post

F1 Score Explained: The Complete Guide to Classification Performance Metrics

Understanding the F1 score in machine learning classification