So the next tool that I'm going to show to you is called patron charm.
So here in our Anaconda Navigator, we have one panel called Pitch ARM Community, which is the free
version, which is totally sufficient and I recommend using this one.
Or you could also use the pouch.
I'm professional, but I think you have to pay something for it.
So in the current installation of Anaconda Petroleum is already installed, so you can just click launch.
If this is not true for you, then maybe you just have to click here, install, or if the panel is
not there at all, then you go to your browser and you Google Pay charm and the correct website to download
it is jet brains dot com.
So let's click on it.
And the website is a bit slow at the moment, wondering why, but here we are.
This pie charm?
Maybe let me change to English so that you can see what's written here.
Yeah, this is the python ideal for professional developers.
Sounds really fancy, and I also think that is really a nice tool to use.
So what you can do then, is click on download.
And as I said, the community edition is totally fine.
All right.
But I think for your case, this should already be installed.
So you just click on launch and you don't have to install anything.
So let's launch by Charm Community.
So here we are.
We are in sign of pie chart, and you see we have lots of things that we can change and it looks a bit
more difficult compared to Jupiter notebook.
And you see here at the bottom right.
It's doing some things.
This is because I opened this for the first time.
And you also see that it's currently using Python 3.9.
And what you could do then, is you could also add another interpreter and install some other version
of Python.
But that's all not really necessary for our cases.
So what we could do now is we could open a file or we could even just drag and drop a file that we want
to run.
So let me do this.
So I just drag and drop the our first notebook file inside of here, and it opens the file.
And you realize that this looks very confusing and doesn't really make sense at all.
And the reason is that a picture can only work with native Python files.
The dots p white files and it cannot use Jupyter notebook files.
So we cannot open up our our first notebook file here.
Or we would have to do that is create a new file.
And this whole Pichon program is really very useful for writing a very complicated, the very large
project.
So it works in terms of projects.
So what do you have to do is you have to click file and then new project.
And now this looks all very difficult and I'm just going to use that is not that difficult at all.
So for example, you write here, you specify the location, I just leave it as it is and right here,
test projects and then the environments and all of this you can leave as it is.
What's just important is that you have the Python three point nine here and here, and you don't just
click Create.
So I would say I click on New Window.
This is because from my old installation, I'm already inside of another project, so I just click New
Window.
And now it runs the program to create a new environment.
Takes a few seconds.
Even has to download something, huh?
I didn't know that.
I think this is because I had already on my PC, an old version of Python, and now there is a new one
here.
All right.
So it comes with a sample Python scripts where you can see it's really a bit more difficult and a bit
more advanced compared to the Jupyter notebook thing.
But I would say, let's delete all of this, and let's just write here once again, some very easy equation
five plus three.
And what I do now is I run this.
And it worked.
And this is what happens in the console.
And it just gives me.
Process finished with exit code zero, which means no error.
Everything worked.
So where's our answer?
Where's our eight?
Well, now the situation is different compared to the Python or the Jupyter notebook file and the Jupiter
notebook file and also in the console.
When we would write something like this, it was it would always directly give us the results.
However, not in a native Python file, because this calculation is done only internally and it does
not give us an output automatically.
We have to specify that it should give us an output.
So, for example, we have to write, print and then in brackets five plus three and then rerun it.
And this time the output is shown here.
For example, we could also define something like a equal to one and then two times a plus one, which
is five.
And then we write print
five times a plus seven.
So maybe let me delete this one.
And now let's see what happens when I run this.
Just gives us as an output.
So let's see what happened here.
We have a is equal to one.
We have two times eight plus one is five.
And then we have five times a, which is five plus seven is 12.
And here we have written down print.
So it only gives us this result and not this one.
So this is really the difference between a Python file and a Jupyter notebook.
File and pie chart is really useful if you have some very complicated project, which even contains
many files that you load.
For example, here you see all the files that are relevant.
But for simple projects and short codes, the Jupyter notebook is, of course, much better.