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[MUSIC]

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Hi there, my name is Megan and
I'm a teacher here at Treehouse.

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My pronouns are she, her, hers.

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In this course,
I'm excited to show you SQLAlchemy.

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SQLAlchemy is an O-R-M, or
object-relational mapper.

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It's a Python code library that
transfers data stored in a SQL

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database into Python objects.

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You can then use Python code to create,
read, update, and

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delete data instead of writing
straight SQL, which helps speed up

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development time, especially for
developers who are not fluent in SQL.

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And it can often make managing
data less error prone.

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SQL stands for Structured Query Language.

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It's a language for
interacting with relational databases.

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Relational databases are structured like
a traditional table with columns and rows.

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If you're not familiar with SQL,

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I highly suggest taking a peek at
the prerequisites for this course.

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I've also listed them in
the teacher's notes below.

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This prior knowledge will bridge the gap
between working with the database using

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SQL, and working with the database
using Python's SQLAlchemy.

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If you would like to follow along
in workspaces, then go ahead and

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open up the workspace
attached to this video.

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In the console,
run pip install sqlalchemy,

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hit Enter, let it download and
you're all set.

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If you would like to follow along locally,
create a folder for your project and

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open it in your IDE of choice.

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I'm going to use Visual Studio.

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Let me go ahead and
create our models.py file.

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We'll need to download SQLAlchemy,
so we can use it.

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But first,
let's create a virtual environment.

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Create a virtual environment by
running python if you're on Windows,

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and python3 if you're on a Mac like I am,
-m venv env.

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And this will start your
virtual environment.

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You can see it's asking if
I want to use it, I do.

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And you see our folder
up here was created, and

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VS Code also adds its own little thing,
you don't need to worry about it.

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Okay, now that we have our
virtual environment created,

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we need to activate it.

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Now, if you're on Windows,
you need to write and

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I need to make sure I get
my slashes correctly,

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.\env\Scripts\activate.

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If you're on Windows.

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If you're on Mac,
then you need to write it

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as source ./env/bin/activate.

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And this is all in the teacher's
notes below as well.

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So you can reference it at any time.

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So go ahead and type that out,
whichever one you need, hit Enter.

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And now you can see I have this env here,

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because I am now inside of
my virtual environment.

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Perfect, now we can install SQLAlchemy.

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Same install, pip install sqlalchemy.

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Awesome, and
then we can run pip freeze, caret or

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arrow to the right, requirements.txt.

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This is the file that will
be important for others.

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And if I run it, it will create this file.

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And if I click into it, it'll tell
me sqlalchemy has been installed.

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And this is the version
that I'm currently using.

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Our requirements file is ready.

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If you want to create a repo for
this project and

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others end up wanting to run your project
to check it out, they will need this file.

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If you do wanna post this on GitHub,
then let's also create a gitignore file.

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New File > .gitignore.

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Inside, we're going to write env.

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This will make sure that environment
folder does not get shared to your repo.

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You don't want that to go up.

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We can also do this, .vscode.

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If you're like me and
you're working in vs code,

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we don't need that to go up either.

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That's just for us locally here.

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There's also this .DS_Store on Macs
that sometimes gets pushed up.

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You don't want those to go either, so
you can add that to your gitignore file.

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And that should be good for right now.

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The most important one is
your environment folder.

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This has a whole bunch of downloads in it,
and anyone running your project only

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needs the requirements file to download
those requirements themselves.

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So we don't wanna send them all of
our files, they can download it for

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themselves.

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Okay, cool.

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Now that you have either workspaces or
your local environment set up,

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let's check our version
in the Python shell.

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I'm gonna run a clear.

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Then I'm gonna go python3 to make sure
I'm in the newer version of Python.

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And then I'm gonna import at
the top sqlalchemy, awesome.

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And then I'm going to run
sqlalchemy.__version__.

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And awesome, it's the same version
that's in our requirements file,

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but this is another way that you
can check your version number.

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You can see I'm on version 1.3.22.

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And your version may be different and
that's okay,

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technologies change quite frequently.

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So if you're on a newer version than I am,

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make sure to check the teacher's
notes throughout the course.

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This way, you get the most up-to-date
information to go along with your version.

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We're all set, time to dive in.