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Boilerplate: repetitive stuff that is necesssary, yet you get to type it out again and again and again, and it just feels like it wastes time to have to do it so many times. Most frameworks try to reduce boilerplate as much as possible while still being flexible enough to cover all necessities.

Scaffolding: a starting point for your program (or part of it), generated by some tool. You take it and tweak it to your needs. This combats the boilerplate problem by automatically generating some of it so you don't need to type it by hand.

Create a DTO that represents a row in your HTML:

Your TEMPLATES setting is as follows (truncated to keep answer short):

The canvas draws OK at viewport dimensions 1920 x 1080.

This snippet (which is vanilla JS for demo purposes) draws the canvas as given in the code in the question and then scales it and its position to fit the current viewport.

I managed to solve the challenge.
I rebuilt the project completely, made it with divs and flexbox, and filled the slots by using simple JavaScript (instead of using margin-left in the SCSS).
Also, I built the project in React.

If anyone is interested, here are the final results:
https://github.com/orassayag/job-interview-exercises/tree/master/jobs/job-13/project

Does this answer help: https://stackoverflow.com/a/6313040/8816585

Also, if you want to be sure that this is an eventListener issue, you could load your page and then aim towards your browser devtools to send this into the console and see if narration.play() is playing or not.

That way you will be sure if it's because it has not loaded yet or if it's another issue.

Jupyter Notebook (notebook module) contains both:

• the server for notebooks (the backend of the web application that hosts the notebook contents, proxies interaction with kernels, and interacts with the operating system by e.g. opening an internet browser on start; this part is generally written in Python), and
• the client (the frontend of the web application, e.g. HTML code, javascript, and some extra REST API points on the server).

However, because there are now multiple clients (frontends) providing different web applications for notebooks:

• Jupyter Notebook
• JupyterLab
• RetroLab
• ntreact
• multiple proprietary clients developed outside of project Jupyter

It made sense to split the server component used by all of these so that e.g. JupyterLab does not have to depend on notebook. This also means that if a fix to the server component is needed, it can be released quickly independent of Jupyter Notebook release cycle (and users of all frontents can benefit immediately).

As a consequence, and to make the break up clean, the old Jupyter Notebook was split into:

• jupyter-server - the server which was adapted by JuptyterLab, RetroLab, ntreact
• nbclassic - the Jupyter Notebook as a jupyter-server extension

This implies changes for users and developers, some already described in "migrate from notebook" docs:

• the options specific to server rather than notebook were renamed from c.NotebookApp to c.ServerApp (the options specific to notebook remain c.NotebookApp)
• the server-specific configuration is now stored in jupyter_server_config.py rather than jupyter_notebook_config.py (same for .json version)
• users should now use jupyter server extension rather than jupyter serverextension (note the extra space!) to list, enable or disable extensions
• the server extensions need to place their files in a new location: etc/jupyter/jupyter_server_config.d rather than etc/jupyter/jupyter_notebook_config.d (in practice most extensions that were updated to support jupyter server are now placing files in both locations for backward compatibility with notebook, but this will change in the future)

It is important to note that depending on how you start your jupyter notebook, you will see different servers being used:

• jupyter nbclassic (assuming nbclassic is installed) will use the new jupyter-server
• jupyter notebook will use the old notebook server
• jupyter lab will use new jupyter-server starting with JupyterLab 3.0 unless running on JupyterHub/Binder where it might still be using old notebook server, depending on configuration

This also implies that you may see different extensions when running jupyter notebook vs jupyter nbclassic (depending on whether their developers updated the locations, and whether they decided they want to support the legacy notebook server).

The creation of nbclassic replacement rather than removal of the server code from existing notebook package was meant to ensure backward compatibility, and this is why you still have two copies of the Tornado server (one provided by jupyter notebook and one by jupyter server). To make the situation simpler you could remove notebook and install nblcassic, but given that the transition is in progress you may need to adjust a few things manually. However, this is only a temporary situation, as it is planned that Notebook will be migrated to use jupyter server starting with v7.0.

This might look inconvenient for now, but this step ensures greater maintainability of the core Jupyter infrastructure in the future and will benefit users and system admins greatly later on.

I don't know what's happened to the footer and the #id-count, but don't use it. Count the elements yourself

Its because your placing it in a row, without a col