https://github.com/flaport/sax-workshop
Given virtually for University of Illinois - 2024.11.14
https://github.com/flaport/sax-workshop
Last synced: about 1 year ago
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Given virtually for University of Illinois - 2024.11.14
- Host: GitHub
- URL: https://github.com/flaport/sax-workshop
- Owner: flaport
- License: mit
- Created: 2024-11-13T17:38:43.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-15T18:29:29.000Z (over 1 year ago)
- Last Synced: 2025-04-03T01:41:30.623Z (over 1 year ago)
- Language: Jupyter Notebook
- Homepage: https://flaport.github.io/sax-workshop/
- Size: 3.34 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SAX Workshop
> Virtual workshop given for the University of Illinois - 2024.11.14
## Project Installation
> Nowadays, I highly recommend using `uv` to manage python dependencies and virtual
> environments (venvs). [Read the next section](#setting-up-a-venv-with-uv) if you
> don't have `uv` or don't have a venv yet (It's a quick process!)
First, activate the `uv` virtual environment:
| Linux & Mac (Bash/Zsh/...) | Windows (PowerShell/CMD...) |
|-----------------------------|-----------------------------|
| `source .venv/bin/activate` | `.venv\Scripts\activate` |
Next, sync the environment with `uv`:
```sh
uv sync
```
That's it! `uv` makes it really simple don't you think?
> Now go have a look in `sax_workshop.ipynb`. This is a jupyter notebook. Start the jupyter server as follows:
>
> ```sh
> jupyter lab
> ```
>
> Then open the notebook from within Jupyter Lab.
## Setting up a venv with UV
Nowadays, I recommend creating a virtual environment (venv) with `uv`. You can download `uv` as follows:
| Linux & Mac (Bash/Zsh/...) | Windows (PowerShell Only) |
|----------------------------------------------------|-----------------------------------------------|
| `curl -LsSf https://astral.sh/uv/install.sh \| sh` | `irm https://astral.sh/uv/install.ps1 \| iex` |
Since `uv` is a system dependency you only have to do this step once.
You can now use `uv` to create a virtual python environment (a venv) for your project.
While inside the root of the project, run:
```sh
uv venv --python 3.12
```
In this setup each venv is tightly coupled to the project you're working in. If you
create a new project you can (and probably should) create a new venv for it. Don't worry
`uv` is fast the venv should be created in no time.