Hi. In this video we will run and export our notebook via terminal.
We'll use our newly created Anaconda environment for this, uh,
which basically contains all packages needed to execute our notebook and
export it in specific versions, which I test it for functionality,
which I want to show you.
Please rename the notebook to module zero four working,
or whatever name you like. And let's go to our terminal.
We'll use, uh, the newly created environment and, uh, let's activate it.
If you do not have activated, please activate it with conduct activate command.
Now we will do the export of our notebook to H T M L with embedded
table of contents, embedded pictures and charts as well.
The library, which, uh,
does what we need is called and B convert.
And this is the command
Jupyter and B convert parameter.
No input means that we do not want to show in the exported file
R code. We want only the output of the cells
parameter to H T M L. Embed means that we want in our,
uh, exported format to be H T M L with embedded charts and pictures.
We'll use the talk two, uh, template for this. Uh,
the talk two is the name of the file in the directory,
where is the notebook and it enters the embedding of the table of contents.
And the last parameter is the name of our own book
has run it.
The conversion was done. Uh,
one thing to mention that in order for this command to work, uh,
another file which needs to be present in the directory is the Plotly JSS
file, which is used to embed the Plotly charts.
So altogether two files, Plotly js and talk to T P L.
Let's open that file.
The table of contents is embedded and is working.
The code is hidden.
Plotly charts works as well. Pictures are embedded.
And also seaborn chart and Gigi plot chart as well.
Now let's convert the notebook, uh, to the reveal presentation.
I will show it to you on that notebook, which I already prepared.
The command is very similar.
We just change the parameter two to slides.
Okay, it's done. I show you that file already before.
So let's go to the next step.
And now let's, uh, just execute the notebook.
We change the parameter two to notebook
and add another parameter. Execute.
This will take some time because we are executing the whole notebook.
It's done and we see that it was executed and saved into a new notebook
called Module zero four working NB convert i n b.
You see,
this way we are able to execute the notebook without using the Jupyter client
like Jupyter Notebook app or Jupyter app.
The NB Convert supports also, um, many other, uh,
conversions like P D F, and others.
In our next video,
we will learn how to parameterize the notebook and how to run and export it
using Python code.