1. Project setup

In this lesson, we'll walk through setting up your GitHub repository, cloning the project to your machine, and adding initial dependencies. But first, we'll walk through setting up your environment with some very basic development tools and packages.

brew update

brew install python3.10

brew install node

brew install --cask docker

brew install awscli

aws configure

sudo apt update
sudo apt install -y software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt update

sudo apt install -y python3.10

sudo apt install -y nodejs

sudo apt update
sudo apt install -y docker.io
sudo systemctl start docker
sudo systemctl enable docker

curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install

aws configure

choco upgrade chocolatey

choco install python --version=3.10.0

choco install nodejs

choco install docker-desktop

choco install awscli

aws configure

Go to https://github.com and create an account.

After You've logged in, you should be greeted with a page looking something like:

We'll want to hit the green "New" repository button towards the top left of the page.

Then, we'll want to:

• Select ourselves as the owner (rather than another organisation)
• Add a unique repository name
• Add a description
• Select private repository. (Or public if you'd like to show off the code!)
• Check the box for adding a README.md file. (This is what's shown when we go to our repository after it's been created.)
• Add a .gitignore for Python
• Don't add a license unless you would like to explicitly give permission for others to use your code

The page should look somewhat like this:

Now, when we go to the repository we should see something like this:

Next step is to then clone down this code to our local machine. Click the green "<> Code" button, and then copy the HTTPS url:

Then, open up the terminal and clone the repository down to your machine:

git clone https://github.com/<your_github_username>/<your_project_name>.git

Set your current working directory to the project root:

cd <your_project_name>

Create a virtual environment using Python's venv module:

python -m venv .venv

and activate it:

source .venv/bin/activate

Now we've done all that we can actually run some python!

Create a new sub-directory in the project root called "scripts":

mkdir scripts

And add a file into it called "test.py":

touch scripts/test.py

Open this file in your text editor of choice. I'm going to use VSCode as it is lightweight and has a huge number of addons to tailor it to my needs:

We just want to make sure everything is working, so all we're going to do for the moment is add a "Hello, world!" print:

print("Hello, world!")

Then try and run it from the terminal using:

python scripts/test.py

Now we're not going to reinvent the wheel here, so let's set up our project to use some dependancies.

Create a new file called "requirements.txt":

touch requirements.txt

And inside it add "tensorflow":

tensorflow

Then install the listed dependancies using:

pip install -r requirements.txt

We can check this has worked by importing tensorflow in the test.py file:

import tensorflow as tf

print("Hello, world!")

If we run it again now, it should hang for a little while as it compiles the library for the first time, and then it should just say: "Hello, world!" again!

Now's the perfect time to make our first commit, and push the changes back up to GitHub!

We can stage our changes with:

git add .

Then we can commit them with a message:

git commit -m "Initial project setup"

Finally, push them up:

git push

If you visit your repository on GitHub now, you should see the new files.

🏃‍♂️ How to Run

To install the required packages into your virtual environment, navigate to the root folder and execute:

pip install -r requirements.txt

Run the test script from the same location:

python scripts/test.py

🗂️ Updated Files

After you've done all this, you should have a project structure that looks somewhat like this:

Project structure

.
├── .venv/
├── .gitignore
├── requirements.txt
└── scripts
    └── test.py

requirements.txt

tensorflow

scripts/test.py

import tensorflow as tf

print("Hello, world!")