How to mimic a jupyter notebook cell in regular python script to plot multiple images and easily review them?

I tend to switch back & forth between Jupyter notebooks and the Wing IDE for debugging code. What I love about the Jupyter notebook is that I can run a cell and generate a sequence of images, with code like this:

import matplotlib.pyplot as plt
for i in range(10):
    ...do stuff...
    plt.plot(image)
    plt.show()

All the images end up nicely one after another in the jupyter cell output region, and can be easily reviewed by scrolling through that region.

Often though I want to go into the debugger to write new code or debug something, and I have not found a good mechanism to do something similar.

Any suggestions how to go about this ?

One option would be to write a function that writes all images to disk and then just view those with a photo viewing application, but I wonder if there is another way.

Solution

As of now, in 2024, you can do exactly this in VS Code. Open the notebook in VS Code with python extension.

Then run all the cells up to the cell you want to debug.

Set a breakpoint in the cell you want to debug.

Select the Debug cell option, and VS Code will go in debug mode. It will stop at your breakpoint, and you can step through it, and also enter the code that resides in the other cells.

This is an answer pre VS Code...

I figured a way to do it that works pretty nice:

use a non-interactive back-end to avoid images from popping up
replace all calls to plt.show() with own function my_plt_show(), in which:
- call to plt.show()
- save each fig to a scratch dir, make sure to close the fig.
- write a file 'all.html' in that scratch dir that will display the images. This is the all.html to write:
<html> <img src="img_0000.jpg" /> <br /> <img src="img_0001.jpg" /> <br /> <img src="img_0002.jpg" /> <br /> <img src="img_0003.jpg" /> <br />
after running or while debugging, just keep that all.html file open in a browser, and it behaves almost like the output of a jupyter cell.

Here my example code:

I_AM_IN_JUPYTER = False
SCRATCH_IMAGE_DIR = 'C:\\Work\\ScratchImages'
SCRATCH_IMAGE_NUM = 0

if I_AM_IN_JUPYTER:
    get_ipython().magic('matplotlib inline')
else:
    # use non-interactive back-end to avoid images from popping up
    # See: http://stackoverflow.com/questions/9622163/save-plot-to-image-file-instead-of-displaying-it-using-matplotlib-so-it-can-be
    from matplotlib import use
    use('Agg') 

# function to show a plot or write it to disk
def my_plt_show():
    global I_AM_IN_JUPYTER, SCRATCH_IMAGE_NUM, f_html
    plt.show()
    if I_AM_IN_JUPYTER == False:
        # at start
        if SCRATCH_IMAGE_NUM == 0:
            # clean out the scratch image dir
            files = glob.glob(SCRATCH_IMAGE_DIR+'\\*')
            for f in files:
                os.remove(f)  
            # open 'all.html' that displays all the images written
            f_html = open(SCRATCH_IMAGE_DIR+'\\all.html', 'w')
            f_html.write('<html>\n')
            
        # save all images to a scratch dir
        fname = 'img_{:04d}.jpg'.format(SCRATCH_IMAGE_NUM)
        plt.savefig(SCRATCH_IMAGE_DIR+'\\'+fname)
        fig = plt.gcf() # get reference to the current figure
        plt.close(fig)  # and close it
        f_html.write('<img src="'+fname+'" /> <br />\n') 
        f_html.flush() # flush it directly to disk, for debug purposes.        
        SCRATCH_IMAGE_NUM += 1