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Now you've learned about Jupyter notebook and pie charm, and this one was, of course, best to use

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for Jupyter notebook files.

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And this one was best to use for a native Python files.

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And now I want to show you a program that can deal with both of them and the program that I have been

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using in the majority of my time when I'm coding in Python.

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And this is called B.S. Coat.

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So once again, in this version of an excellent navigator, it's already installed.

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If not, then you just have to Google for the code.

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And you can download a free version.

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So here it's already installed.

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So I click on launch and it runs this.

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Yeah, a visual studio code.

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So, yeah, it recognizes that my PC is German, so it asks me if I want to install a German package,

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which I don't want to do.

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I want to stay in English.

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Then here opens up file with the release notes of the newest version because I have just installed the

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program.

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We don't need this.

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We don't need the settings.

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And here is some file that I've been using previously already.

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So let me close this.

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And let me also get rid of this folder, which we don't need.

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And what I'm going to do now is I'm going to open the two files that we have created so far.

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So here I'm going to open up the our first notebook, a Python file.

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So this didn't work.

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Let's try again.

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Yeah.

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So you have to drag and drop the Python file in the larger window here.

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So I trust the authors, of course, because I am the author, so I open this.

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And here we go.

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We have now ourselves from a python.

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And you can just run these so you can, for example, click on this play button here, or you can click

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on Shift Enter.

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And this will automatically open up such a selector here where you can use your Python version that

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you want to use.

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So as you can see on my PC, I have also other installations of Python.

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For example, I had previously installed a version, Anaconda, that was using three point eight, and

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also I downloaded a version of Python from the Windows App Store.

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But we are going to use this one that is selected and that's suggested.

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And now it's connecting to the kernel.

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Takes a bit, and now it has successfully run this cell.

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So here you see the result.

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And what I also like is it gives us this take that it worked and also the time that it took to calculate

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this.

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And then, of course, we can click Shift Enter.

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And yeah, it's really the same thing as previously.

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The only thing that's not working here is this image, but I don't think that is too so bad.

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So you see the AI Python files, they worked.

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Let's delete this or not delete.

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But let's close it, and let's open up the other file that we have just created.

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This time, let's open up the other file that we have created.

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I go to poach on projects where we have created this test project folder, and I drag and drop the main

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file where you recognize the three lines of code that we have written previously.

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So here in this visual studio code, I think this is really nicely configured configurator because you

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can have this nice color highlighting, for example, if you select the AIV and it will select all the

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other apps as well.

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If you hover over it, it tells you it's a variable pay.

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And if you have our over print, it gives you the syntax of the print command in Python.

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So really, it's a nice thing.

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And also you see that this interface looks different compared to the case where we had opened the Python

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file and I just click here on run.

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And what happens now is it opens up a terminal, which in my case is to Windows PowerShell.

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For you, this can be a different shell, doesn't really matter that much.

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So it gives when Microsoft copy because it's two Windows PowerShell, some stuff in German, which is

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not important.

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And it's just a typical command line, just a shell where I'm currently in this directory for whatever

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reason.

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I don't know.

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And what we have done by clicking play is we have told it to run this file and I have done this already,

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previously, once.

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So this is why you have it twice here and the output is just trough, as we had in the previous cases.

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So it just gives us the print command off five times OnePlus seven, which is 12.

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So summarizing this lecture, we have explored the capabilities of Visual Studio Code, and I really

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like it because it can deal with native Python files as well as Jupyter notebooks.

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It has a nice color highlighting, and it just looks nice in general, which is why I'm using it personally

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a lot.

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However, for the majority of the course, I will stick to Jupiter Notebook because it's the most simple

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thing and everybody can use it very easily and you just have to install Anaconda and then you're ready

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to go.