Using Community Code

Do not reinvent the wheel..8 H 13 M

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  • Using Community Code
    • Overview
    • Community Code: What is that
    • Install pip
    • Install System Packages
    • Virtual Environments: Create
    • Virtual Environment: Manage
    • Virtual Environment: Install Packages
    • Project: Resizing Images
    • Install pipenv
    • Create pipenv Environments
    • Manage pipenv Environments
    • Use pipenv Environments
    • Project: Image Links on a Page
    • Another one? Why conda?
    • Install conda
    • Install conda: Windows
    • Create conda Environments
    • Manage conda Environments
    • Manage conda Environments: Reproduce
    • Manage conda Environments: Clone
    • Project: Analyze Population Data
    • Uninstall conda
    • Uninstall conda: Windows


4 M

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  • Episode Description
  • Transcript

In this series, we will explore the use of community code, or code written by others that to solve a particular problem or provide a particular functionality. We will explore how you can obtain these created solutions to increase your problem solving speed. In order to do so, we will explore the use of tools like pip, pipenv, and conda which are solutions to the fetching and managing of outside dependency requirements. If you are looking to solve bigger and bigger problems or just explore something of interest, then you will need help from others. Want to learn more? Join us as we dive in to the wonderful world of Python!

[MUSIC] Hello, and thank you for watching DevProTV. We're here to talk about using community code with Mr. Justin Dennison. Now, Justin, can you tell us what this course has to offer? >> So this course is about, well, the reaching out to the community, seeing what has already been made so you don't have to reinvent the wheel. And most of this time is gonna spend around the tooling, because, well, the community is vast, it's expansive. We can't take all the time to see every little library module or package. So it's about using the tooling to acquire that community code to solve problems that you may have so you don't have to build it from scratch. >> Now who should be watching this course? >> So this course is aimed at someone who's, you've been playing around with Python a little bit, you've been learning how to program. You're decently versed in the standard library. You don't have to know everything, the standard library is giant. But now you're like, well, I need to really do x, I need to maybe plot a graph. Or, I really wanna build a web server, or, I really want to just, I wanna do x or y or z, right? Something new that you can't find in the standard library and seems like a very large undertaking. Or, you're like, well, I wanna do x but in order to do that I have to be able to read CSVs easily. Well, I don't wanna do the whole CSV thing by myself. I wonder if there's somewhere in the community that already has that taken care of for me. And then you go, yeah, there it is. And now you can utilize that to further your own project without having to continue to build everything from absolute ground up. >> Is this a certification-based course? >> It is not a certification. It's more about powering up your skills. About seeing how working together as a community throughout this Python and the feel, a lot of times other programming languages have similar communities. And seeing, well, can I take what maybe Aubri has done or someone else has done and build upon that to power up my own understanding and programming skills. >> What topics are we gonna cover in these up coming episodes? >> So more specifically, we're going to be talking about how to use pip and how to look at PyPi the Python Package Index. To search out for certain packages that solve a particular problem. Some of these are small like, hey where can I find URLs for cat images? Well that might be on PyPi or it might be something more expansive where you're like, hey I need to figure out how to communicate between multiple computers. Is that on PyPi? So that's our first step. But then we take a look that pip has some shortcomings, we gotta figure out how to not mess things up. So we look into virtual environments. Virtual environments are a way to kind of sandbox where you install these. Then we realize that virtual environments still have a little bit of a headache. So we looked at a brand new tool called pipenv, and it's kinda hard to say, that allows us to track what we've installed and manage our virtual environments in a little more intuitive way. And then as an added bonus, if you really wanna get crazy with your python packages then there's another tool that is more scientific data analyst bent, called Conda, that we'll finish up the show with. It does the exact same thing as pipenv, or Virtual Environments, but it manages a few other things for these very specialty libraries that are, sometimes, hard to install. And, well when we take a look at both on Mac OS and Linux. That's predominantly where we are but also take a little detour to how we get to setup on Windows so you can follow along. So, those are the high level topics. We're pretty deep into a few of them. >> Alright. Well, thank you, Justin. Thank you all for joining us. If using community code sounds like something that you're interested in, be sure to watch every single episode. You'll become one step closer to being a Python Pro. Thanks for watching. [MUSIC]