docs(setup)📝: streamline and simplify setup instructions for running notebooks

- Replace multiple setup options (Binder, VSCode dev containers, conda, venv) with a single, quick setup guide using uv and marimo.
- Provide clear, step-by-step instructions for installing uv, navigating to the notebook directory, and running notebooks with marimo.
- Explain the benefits of the new approach, including isolated environments and automatic dependency management.
- Remove outdated or redundant setup instructions to reduce confusion and improve onboarding experience.

Author: ericmjl

notebooks/00-preface/01-setup.md

@@ -4,118 +4,32 @@ In order to get the most of this book,
 you will want to be able to execute the examples in the notebooks,
 modify them, break the code, and fix it.
 Pedagogically, that is the best way for you to learn the concepts.
-Here are the recommended ways in which you can get set up.
+Here's the recommended way to get set up.
 
-## Binder
+## Quick Setup
 
-We recommend the use of Binder!
-This is because Binder will automagically setup
-an isolated and ephemeral compute environment for you
-with all of the packages needed to run the code in your notebooks.
-As such, you won't have to wrestle with anything at the terminal.
-To go there, click on the following button:
+To get started with the notebooks, follow these simple steps:
 
-[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/ericmjl/Network-Analysis-Made-Simple/master)
+1. **Install uv** (the Python package manager):
+   Follow the installation instructions at [https://docs.astral.sh/uv/getting-started/installation/](https://docs.astral.sh/uv/getting-started/installation/)
 
-## VSCode Development Containers
+2. **Navigate to the notebook directory**:
+   ```bash
+   cd notebooks/subdir/
+   ```
 
-Assuming that y ou're using Visual Studio Code
-and have attempted to use development containers before,
-you can run the Network Analysis Made Simple tutorial content
-inside a development container.
-After Binder, this is the second easiest way to get set up.
-You need to have Docker installed on your computer
-but don't worry -- you won't have to execute any Docker commands :).
+3. **Run the notebook**:
+   ```bash
+   uvx marimo edit --sandbox <notebook_name>.py
+   ```
 
-### Install the Remote Containers extension
+That's it! The `--sandbox` flag ensures a clean, isolated environment for running the notebooks with all necessary dependencies automatically managed.
 
-This is found in the Extensions marketplace.
+## What this does
 
-![Remote Containers extension.](https://user-images.githubusercontent.com/2631566/164070556-7ca675bc-d700-4e1b-a8e4-f07bc77c79f8.png)
+- **uv** is a fast Python package manager that handles dependency resolution and virtual environments
+- **marimo** is an interactive notebook environment optimized for Python
+- The `--sandbox` flag creates an isolated environment for each notebook, preventing dependency conflicts
+- All required packages are automatically installed when you run the notebook
 
-### Clone the repository to your local drive
-
-```bash
-git clone https://github.com/ericmjl/Network-Analysis-Made-Simple.git
-```
-
-### Open the repository in VSCode
-
-Use `Cmd+Shift+P` (on macOS) or `Ctrl+Shift+P` (on Linux/Windows)
-to open the command palette, and search for "Rebuild and Reopen in Container" as below:
-
-![Search for "Rebuild and Reopen in Container"](https://user-images.githubusercontent.com/2631566/164071398-ff115bd0-02fc-4827-935a-2785a354360f.png)
-
-Hit enter and wait for the container to build automagically. This may take around 10 minutes or so, depending on your system.
-
-![Development container will be built.](https://user-images.githubusercontent.com/2631566/164071594-d3ddf3fa-9c78-48f3-be56-09a453f8eb0a.png)
-
-## `conda` environments
-
-We also recommend the use of `conda` environments!
-Use this if you're not already using one of the options above.
-If you are feeling confident enough to set up
-a conda environment at the terminal,
-then follow along.
-(We'll be assuming you've already cloned the repository locally.)
-
-### Leverage the Makefile
-
-We've provided a Makefile with a single command:
-
-```bash
-make conda
-```
-
-On most \*nix systems, that should get you most of the way
-to having the environment setup.
-
-### Alternative: Execute individual commands
-
-If you encounter errors, then you should know that the Makefile command
-`make conda`
-basically wraps the following steps.
-
-Firstly, it creates the conda environment based on the `environment.yml` file:
-
-```bash
-conda env create -f environment.yml
-```
-
-Next, it activates the environment:
-
-```bash
-conda activate nams
-```
-
-We have a custom module for the project, which is called `nams`,
-that you will have to install.
-
-```bash
-# In the root directory of the cloned repository
-python setup.py develop
-```
-
-Finally, it runs a check on the environment
-to make sure everything is installed correctly:
-
-```bash
-python checkenv.py
-```
-
-## `venv` environments
-
-If you're not a `conda` user, then you can use `venv` to create your environment.
-
-
-### Leverage the Makefile
-
-As with the `conda` commands, you should be able
-to execute a single Makefile command at your terminal:
-
-```bash
-make venv
-```
-
-Special heartfelt thanks goes out to GitHub user @matt-land
-who contributed the `venv` script.
+This approach eliminates the need for manual environment setup, conda environments, or Docker containers while ensuring reproducible execution of the tutorial content.