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Update setup instructions to include uv
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README.md

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@@ -43,48 +43,53 @@ Pick the installation option that makes sense for you:
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### Local Installation
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**Warning**: It is highly recommended that you use your personal laptop for the installation.
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0. Install the following, if not already installed:
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- [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Mamba](https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html)
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- [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
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1. Install [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git), if not already installed on your computer.
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1. Fork this repository:
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2. Fork this repository:
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![location of fork button in GitHub](./media/fork_button.png)
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2. Navigate to your fork, and click the **Code** button:
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3. Navigate to your fork, and click the **Code** button:
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![location of code button in GitHub](./media/code_button.png)
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3. Clone your forked repository using the desired method from the **Local** tab:
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4. Clone your forked repository using the desired method from the **Local** tab:
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<img width="400px" src="./media/clone_options.png" alt="local cloning options">
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4. Create and activate a conda virtual environment (on Windows, these commands should be run in **Anaconda Prompt**):
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5. Install one of the following, if not already installed:
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- [uv](https://docs.astral.sh/uv/getting-started/installation/) (recommended)
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- [Anaconda](https://docs.anaconda.com/anaconda/install/)/[Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Mamba](https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html). Note that Anaconda/Miniconda is recommended if you are working on a Windows machine and are not very comfortable with the command line.
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```shell
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$ cd python-data-viz-workshop
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~/python-data-viz-workshop$ conda env create --file environment.yml
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~/python-data-viz-workshop$ conda activate data_viz_workshop
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(data_viz_workshop) ~/python-data-viz-workshop$
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```
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6. Set up your environment and launch JupyterLab:
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- Using `uv`:
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*Note: If you installed Mambaforge or have already installed `mamba` in your base environment, you can change `conda env create` to `mamba env create`.*
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```shell
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$ cd python-data-viz-workshop
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$ uv run jupyter lab
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```
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5. Launch JupyterLab:
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- If you installed Anaconda/Miniconda, use `conda` (on Windows, these commands should be run in **Anaconda Prompt**):
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```shell
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(data_viz_workshop) ~/python-data-viz-workshop$ jupyter lab
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```
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```shell
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$ cd python-data-viz-workshop
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$ conda env create --file environment.yml
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$ conda activate data_viz_workshop
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(data_viz_workshop) $ jupyter lab
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```
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6. Navigate to the `0-check_your_env.ipynb` notebook in the `notebooks/` folder:
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*Note: If you installed Mambaforge or have already installed `mamba` in your base environment, you can change `conda env create` to `mamba env create`.*
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7. Navigate to the `0-check_your_env.ipynb` notebook in the `notebooks/` folder:
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![open 0-check_your_env.ipynb](./media/open_env_check_notebook.png)
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7. Run the notebook to confirm everything is set up properly:
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8. Run the notebook to confirm everything is set up properly:
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![check env](./media/env_check.png)
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### Docker Installation
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0. Install the following, if not already installed:
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- [Docker](https://docs.docker.com/get-docker/)
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- [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
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```shell
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$ cd python-data-viz-workshop
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~/python-data-viz-workshop$ docker compose build
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$ docker compose build
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```
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5. Launch JupyterLab from within a Docker container:
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```shell
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~/python-data-viz-workshop$ docker compose up
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$ docker compose up
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```
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You should be able to access the environment at <http://localhost:8888>

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