Visual Studio Code for Python Developers Transcripts
Chapter: Getting Setup Code with Visual Studio Code
Lecture: Choosing Your Python Distribution
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0:00
In this course, we're talking about how to use Python in VS Code. So ultimately, at some point, we should install Python, right?
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Like we should get some version of Python. Nah. You don't need it. No. Oh. I mean, we should at some point, right? Okay. All right. I guess so.
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But here's the thing. Here's the thing, right? And I see what you're saying. But here's the thing. There's so many different iterations of Python.
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It becomes hard for people to know like which one exactly should they install. Yeah.
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So I figured why don't we spend some time in this video kind of going through what are
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some of those different versions of Python and then, you know, some of the reasons you might pick one versus the other. Does that make sense?
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That makes sense. And I'm excited about that. That sounds good. Because I don't know all the different versions of Python. I just know Python.
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And you know what? And you know what? We'll talk about that too. Because what does Python mean? Now we get into like this whole philosophical question.
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Oh, wow. Yeah. I don't know. What is Python, right? What's the meaning of life, Cecil? Is it Python? What's the meaning of life? Is Python the answer?
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Maybe Python is the answer. Okay. But this is the first one we have. So one of the more common distributions of Python is called Anaconda.
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Now, this one is primarily used by a lot of folks that do data science, machine learning, that type of work.
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And that's because when you install this distribution of Python, right, we call these different versions distributions.
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It comes with like a lot of different versions of Python. It comes with different Python packages, you know, tools and utilities and stuff like that,
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like included in the box. That means that I don't have to go out and install a bunch of other stuff. I can just download Anaconda.
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And you see, I got stuff like Jupyter Notebooks. I got Pandas. I got all this stuff that's just kind of included.
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So it's easy for me to just start, you know, playing around with Pandas or creating graphs and like finagling with my data.
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So that's one of the reasons why a lot of folks like to use this particular distribution. That's interesting. That's interesting.
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A lot of AI based stuff. I like that it comes packaged with things. I love the names of stuff like Pandas, you know, and Jupyter. And Anaconda. Yeah.
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So this might be for somebody who's starting out with Python, though, this maybe is a little bit overkill.
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Not maybe, maybe not overkill is the right word, but it's a little bit over the top for
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somebody just getting started in the beginning and maybe looking to use Python with VS Code. Would you say that's the case or no? Or what do you think?
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Well, I would say it depends on what you call beginning. Okay.
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So a lot of folks that are beginning Python, they may be folks that maybe are using Excel or you're used to using some other tool for data analysis.
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So you know what you're doing, right? But maybe you really want tools to kind of help make your job a little bit easier.
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So like something like having a notebook and working with cells and stuff like that is natural for you. So now you have to learn Python to do it.
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So for you, maybe having to install all those additional packages.
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Maybe that might be overkill for you versus just, oh, okay, I just have it because I just downloaded the thing and it has everything for me.
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So as I'm saying, like, you know, all of these different distributions has like a purpose.
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And it kind of depends on it kind of depends on what your purpose is, right? Like what exactly you try to do. All right. That makes sense. All right.
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So I see. So that's Anaconda. The next one we have is Micro Python. What's the purpose of this one?
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So this one is for folks that are working with like microcontroller, you know, like those little boards. And, you know, you get your little solder.
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Yeah. Internet of things. Soldering iron. Yeah. Internet of things and IoT and that kind of hardware stuff.
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IoT stuff and, you know, plugging in sensors and controllers and all these types of stuff.
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But you need a very small version of Python because, again, those devices have very limited memory sets. You know what I mean?
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And, you know, very limited processing power. Yeah.
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So you want to be able to have something that's very lean and able to run in like those types of architecture.
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So Micro Python is a great way to do that. And it's a great way to do that. And it's a great way to do that. And it's a great way to do that.
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And it's a great way to do that. Yeah. Yeah. Yeah. Yeah. Micro Python is a great option for doing some of that type of stuff, too. Okay. Cool. Cool.
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All right. Next up, we have Iron Python. Iron Python.
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So this one and the next one, the next two are going to be really interesting because so Iron Python is like Python for .NET developers. Right.
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And some folks might be like, well, why do I want to do that? Yeah. And then, well, I mean, for a lot of folks, there's a couple of reasons.
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One, you might want to have like some type of interoperability. When I talk about interop, I might have like a thing. Yeah.
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Like a Python library that I wrote that I want to use in my .NET application or .NET DLL that I want to use in my Python application. Okay.
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Or I've seen folks that have done inline scripting that would allow me to like write some, you know, small little scripts, maybe in Python, interpret them and run them on the fly in my .NET application.
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So there's a lot of different use cases for why folks might want to do this.
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You know, also, too, because it's running, this version of Python is going to be running on the .NET CLR.
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So now the way that we think about it is, you know, I'm going to run this version of Python.
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Now, the way that we think about threading and, you know, multiprocessing and some of those types of things are a little bit different than it would with some of the traditional, you know, Python idioms.
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I got you. Now, this one, if we look, this one is up to Python 3.4.
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Now, the current version of Python, I believe, is like 3.12 at the time that we're recording this right now. Yeah.
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So as you can probably see, there is some gaps between like the current version of, you know, the default installation of Python and where it's running.
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But again, if you're not really needing those, you know, cutting edge features, then, you know, this should be fine. And this would be really great.
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Again, if you're trying to like just interrupt or integrate into an existing application. Okay.
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And you mentioned this other one, Jython is essentially similar to, it serves the same purpose as IronPython, but for Java. Yeah. Python and Java.
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Okay. So now when we talk about Java, we talk about like the JDM. Right. The Java Virtual Machine. Right.
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And for folks that are familiar with Java, maybe you are, maybe you might not be, the JDM runs lots of different languages on top of it.
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So Kotlin is an example that runs on the JDM. Scala runs on the JDM. Groovy, which is a different scripting language, runs on the JDM.
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And now we also have Jython.
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So that means that, again, we can pull in Java jars and packages and all these types of stuff and write Python code to run with those things too.
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So again, if you have any of those types of, it's a great way to run.
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If you don't have any of those type of interrupt scenarios, then it's a great option. That makes sense.
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And I'm talking about the version gap a little bit again.
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Here, this one, the current release only supports Python 2 right now, but they are working towards supporting Python 3, at least at the time of recording this.
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Right. Something else to keep in mind. What's great about these things too is that, you know, both this and IronPython, they are open source.
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So if you're interested in getting into language interrupt and writing compilers and parsers and all these types of things.
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This might be a good option for you to like contribute back to some of these projects to help make that community better. Yeah, for sure. All right.
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Last but not least. Python.org. It's just Python. Just Python. It's just Python. This is what I was expecting you to tell me about.
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And, you know, maybe we should have started with this one, but this, it's just Python, right? This is the default distribution of Python.
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You know, it's, you know, hosted on Python.org. It's written in C. You know, runs on tons of different archives.
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It runs on tons of different architectures.
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And for most folks, when you install Python, you know, this is generally the version that, you know, most folks are going to be able to use.
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So if you're interested in like diving into this one and seeing how to install it, you can go ahead and head over to downloads.
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Hit that little download button in the menu bar. And you could pull it down for your system, right?
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It runs on Windows, Mac, Linux, and tons of other architectures as well. Awesome. All right. So this is all about getting different versions of Python.
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For the purposes of this course, we're going to be using throughout 3.11.3, I think, to be very specific.
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But if you need help getting you, the viewer, need help getting installed, Python installed on your system, you can look no further than right on this platform where you're watching this course.
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If you go to talkpython.fm/installing-python, you'll be able to step through this guide, this article here that will walk you through doing that to make sure you get it installed properly on your operating system.
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operating system and verify that it is ready and available for you to start writing python
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exactly and like i said before like this one's gonna help you get the default or the the python
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version distribution written in c the one that we showed at python.org on your machine if you're
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interested in getting anathonda or iron python or any of those other ones make sure you go to those
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websites and it'll let you know like the instructions and the steps you need to take to
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handle those awesome well now that we know about the different types of python distributions that
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are there which one we're going to be using in this course and how to get it installed next in
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the next video we're going to talk about getting vs code set up on a machine very briefly giving
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you an idea what to expect in doing that so let's head on over into that what do you say cecil let's