feat: Add pixi environment (#534)

* feat: Add pixi environment

* Add pixi manifest pixi.toml for Linux x86, macOS arm64, Windows 64.

* ci: Update CI workflow and unify to one

* Enable workflow dispatch.
* Add concurrency limits.
* Use pixi for CI workflow.
* Unify to a single workflow for all OS tested

* feat: Add pixi lock file

* Ensure tensorflow-cpu installed on Windows

* fix package check

* fix package check

* simplification plus uv and pip runners

* some fixes to pixi and pip

* create pixi.lock

* fix pixi.lock issue

* another attempt trying to fix get_packages

* another attempt trying to fix get_packages

* clean up python_environment_check.py

* updated runner and docs

* use bash

* proper env activiation

* proper env activiation

---------

Co-authored-by: rasbt <mail@sebastianraschka.com>
This commit is contained in:
Matthew Feickert
2025-02-17 10:33:53 -07:00
committed by GitHub
parent 16738b61fd
commit a8b8eb4731
14 changed files with 13169 additions and 222 deletions

View File

@@ -27,9 +27,11 @@ This section guides you through the Python setup and package installation proced
> [!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 even 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/).
> If you are a macOS or Linux user and 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 additional speed advantages, I think that `uv pip` is 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 opportunity to learn it from the start. It's also how I use `uv` now, but I realize it the barrier to entry is a bit higher if you are coming from `pip` and `conda`.
> The `uv add` syntax also applies to Windows users. However, I found that some dependencies in the `pyproject.toml` cause problems on Windows. So, for Windows users, I recommend `pix` instead, which has a similar `pixi add` workflow like `uv add`. For more information, see the [./native-pixi.md tutorial](./native-pixi.md).
>
> While `uv add` and `pixi add` offer additional speed advantages, I think that `uv pip` is 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 opportunity to learn it from the start. It's also how I use `uv` now, but I realize it the barrier to entry is a bit higher if you are coming from `pip` and `conda`.
@@ -153,9 +155,13 @@ uv pip install -U -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/r
<img src="https://sebastianraschka.com/images/LLMs-from-scratch-images/setup/uv-setup/uv-install.png" width="700" height="auto" alt="Uv install">
&nbsp;
> [!NOTE]
> If you have problems with the following commands above due to certain dependencies (for example, if you are using Windows), you can always fall back to using regular pip:
> `pip install -r requirements.txt`
> or
> `pip install -U -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/refs/heads/main/requirements.txt`
<br>