UBC Solar's data analysis environment

1. Git (git --version)
2. Git LFS (git lfs --version).
   1. Install with brew install git-lfs or similar.
3. Python 3.12 (python3 --version)
4. uv (uv --version)

Choose a short, descriptive name for your project following the snake-case format, then check out a new branch.

git checkout main
git pull
git checkout -b your_project_name

You will now be on a new branch named your_project_name!

• Copy the entire project_template folder and paste it into the v4 folder.
• Rename your copied folder to your project/branch name.
• Rename your notebook
  • If you have just one, you may give it the same name as the project. Otherwise, use a name that describes the specific purpose of the notebook(s).

In this example, my project is named acceleration_analysis.

data_analysis
└── v4
    └── acceleration_analysis
        ├── data
        ├── results
        ├── scripts
        ├── acceleration_analysis.ipynb
        └── PROJECT_TEMPLATE.md

If you don't already have the uv package manager installed, you can run

# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows PowerShell
powershell -c \"irm https://astral.sh/uv/install.ps1 | iex\"

to install it.

Check if the installation worked with uv --version. You may need to restart your terminal or computer for the command to work.

Next, cd into your project and initialize uv.

# macOS/Linux
cd v4/your_project_name
uv init --no-workspace --bare

# Windows PowerShell
cd .\v4\your_project_name
uv init --no-workspace --bare

This will create a pyproject.toml file in your project to track dependencies.

Use uv add package_name to install packages you will need. For example,

``uv add numpy, matplotlib, ubc-solar-data-tools, pytz.

Use the packages that your project requires. Don't worry if you forget something, you can always uv add it later.

We want to run our Jupyter notebook using our new uv environment. For more info, see Using uv with Jupyter.

First, create an IPython kernel with the following command, replacing the name "project" with the name of your project.

# macOS/Linux
uv add --dev ipykernel
uv run ipython kernel install --user --env VIRTUAL_ENV $(pwd)/.venv --name="project"

# Windows PowerShell
uv add --dev ipykernel
uv run ipython kernel install --user --env VIRTUAL_ENV "$(Get-Location)\.venv" --name "project"

Next, start the server.

uv run --with jupyter jupyter lab

This will open the JupyterLab browser interface. If you prefer to use your IDE (e.g. PyCharm or VSCode), You may copy the server URL which was printed to the console and select it as an external server in which to run your Jupyter Notebook.