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Native uv docs (#530)

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* Replace pip by more modern uv

* uv tests

* Native uv docs

* resolve merge conflicts

* resolve merge conflicts
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Sebastian Raschka
2025-02-15 20:35:23 -06:00
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@@ -8,20 +8,29 @@ I have been a long-time user of [Conda](https://anaconda.org/anaconda/conda) and
I recommend starting with *Option 1: Using uv* as it is the more modern approach in 2025. If you encounter problems with *Option 1*, consider *Option 2: Using Conda*.
In this tutorial, I am using a computer running macOS, but this workflow is similar for Linux machines and may work for other operating systems as well.
 
# Option 1: Using uv
This section guides you through the Python setup and package installation procedure using `uv` via its `uv pip` interface. The `uv pip` interface may feel more familiar to most Python users who have used pip before than the native `uv` commands.
 
This section guides you through the Python setup and package installation procedure using `uv`.
In this tutorial, I am using a computer running macOS, but this workflow is similar for Linux machines and may work for other operating systems as well.
> [!NOTE]
> There are alternative ways to install Python and use `uv`. For example, you can install Python directly via `uv` and use `uv add` instead of `uv pip install` for faster package management.
>
> If you prefer the native `uv` commands, refer to the [./native-uv.md tutorial](./native-uv.md). I also recommend checking the official [`uv` documentation](https://docs.astral.sh/uv/).
>
> While `uv add` offers speed advantages, I find `uv pip` slightly more user-friendly, making it a good starting point for beginners. However, if you're new to Python package management, the native `uv` interface is also a great way to learn.
 
## 1. Install Python (if not installed)
First, check if you have a modern version of Python installed (I recommend 3.10 or newer) by executing the following code in the terminal:
```bash
@@ -29,6 +38,7 @@ python --version
```
If it returns 3.10 or newer, no further action is required.
 
> [!NOTE]
> I recommend installing a Python version that is at least 2 versions older than the most recent release to ensure PyTorch compatibility. For example, if the most recent version is Python 3.13, I recommend installing version 3.10 or 3.11.