Using Community Code
Using Community Code Overview
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!
0h 4m
[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]
Overview
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!
Learning Style
On Demand
Length of course
8h 13m
23 Episodes
Here are the topics we'll cover
- Using Community Code
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