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setup/01_optional-python-setup-preferences/native-uv.md
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This tutorial is an alternative to *Option 1: Using uv* in the [README.md](./README.md) document for those who prefer `uv`'s native commands over the `uv pip` interface. While `uv pip` is faster than pure `pip`, `uv`'s native interface is even faster than `uv pip` as it has less overhead and doesn't have to handle legacy support for PyPy package dependency management.
Otherwise, similar to *Option 1: Using uv* in the [README.md](./README.md) , this section guides you through the Python setup and package installation procedure using `uv`.
Otherwise, similar to *Option 1: Using uv* in the [README.md](./README.md) , 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.
@@ -12,7 +12,7 @@ In this tutorial, I am using a computer running macOS, but this workflow is simi
Uv can be installed as follows, depending on your operating system.
 
<br>
**macOS and Linux**
```bash
@@ -25,7 +25,7 @@ or
wget -qO- https://astral.sh/uv/install.sh | sh
```
&nbsp;
<br>
**Windows**
```bash
@@ -47,7 +47,7 @@ uv python install 3.10
```
&nbsp;
> [!NOTE]
> [!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. You can find out the most recent Python version by visiting [python.org](https://www.python.org/downloads/).
&nbsp;
@@ -74,7 +74,7 @@ uv add packaging
Alternatively, you can still install the dependencies directly from the repository using `uv pip install`. Note that this requires creating and activating the virtual environment manually:
&nbsp;
<br>
**1. Create a new virtual environment**
Run the following command to manually create a new virtual environment, which will be saved via a new `.venv` subfolder:
@@ -83,7 +83,7 @@ Run the following command to manually create a new virtual environment, which wi
uv venv --python=python3.10
```
&nbsp;
<br>
**2. Activate virtual environment**
Next, we need to activate this new virtual environment.
@@ -100,7 +100,7 @@ On Windows (PowerShell):
.venv\Scripts\activate
```
&nbsp;
<br>
**3. Install dependencies**
Finally, we can install dependencies from a remote location using the `uv pip` interface:
@@ -114,12 +114,12 @@ uv pip install -U -r https://raw.githubusercontent.com/rasbt/LLMs-from-scratch/r
&nbsp;
## 4. Run Python code
&nbsp;
<br>
**Finalizing the setup**
Your environment should now be ready to run the code in the repository.
Optionally, you can run an environment check by executing the `python_environment_check.py` script in this repository:
Optionally, you can run an environment check by executing the `python_environment_check.py` script in this repository:
```bash
uv run python setup/02_installing-python-libraries/python_environment_check.py
@@ -131,7 +131,7 @@ uv run python setup/02_installing-python-libraries/python_environment_check.py
Or, if you don't want to type `uv run python` ever time you execute code, manually activate the virtual environment first.
Or, if you don't want to type `uv run python` ever time you execute code, manually activate the virtual environment first.
On macOS/Linux:
@@ -152,7 +152,7 @@ Then, run:
python setup/02_installing-python-libraries/python_environment_check.py
```
&nbsp;
<br>
**Launching JupyterLab**
You can launch a JupyterLab instance via: