Introducing Reloading: Never Re-Run Your Python Code Again To Print More Details*av688TzclOpCl2oV

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Introducing Reloading: Never Re-Run Your Python Code Again To Print More Details

Photo by Brad Neathery on Unsplash


While running Python scripts, I have often found myself in situations where I forgot to print all the necessary details to track the pipeline’s progress.

This is typically observed in training machine learning models. More often than not, folks (including me) often forget to:

  1. Add necessary logging details.
  2. Print essential training details/metrics such as accuracy, error, precision, etc.
  3. Save the model after every k epochs, and many more.

I am sure you have been there too.

Of course, the problem is not just limited to machine learning. Many face the same issue in other domains as well, such as Web Scrapping, where people realize after running their codes that they should have scrapped some more details, etc.

Left with no choice, one has to unwillingly stop the code, add the necessary details and re-run the code again. This can be incredibly frustrating if your pipeline has been running for a few hours.

But what if I told you that there is a neat trick to this? In other words, it is actually possible to make changes to an already running code without losing the current progress.

This is what I will explore in this blog.

Let’s begin 🚀!


Reloading, as the name suggests, is a Python library that allows you to reload a loop (or a function) from the source before each iteration.

Therefore, you can modify an already running code and add more details to it without losing any current progress. Isn’t that cool?

To install it, use the following command:

pip install reloading

Reloading A Loop

Consider that you have a loop that takes an initial value and halves it after every iteration.

However, we mistakenly forgot to print the iteration number in this loop and now want to modify it.

Of course, without reloading, you have no choice but to re-run it.

However, if you want to reload the body of the for loop before each iteration, wrap the iterator with reloading, as shown below:

Now, you can modify the code during run-time. A demo is shown below:

Demo of Reloading (Gif by Author)

As demonstrated above, we modified the body of the for loop. As a result, we get to see new details in the output panel, while retaining the current progress.

Reloading a Function

Similar to reloading a loop, you can also reload the body of a function after each iteration. Consider the function half_value below:

To reload the body of a function, decorate it with the reloading decorator. This is shown below:

Now, you can modify the function during run-time. A demo is shown below:

Demo of Reloading (Gif by Author)



With this, we come to the end of this blog. I hope you learned something new.

I am confident that this trick will save you tons of time while running some high-run-time codes, such as training machine learning models.

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