## 1. Install conda
Install the conda package manager, either through the minimum version: [Miniconda](https://docs.conda.io/en/main/miniconda.html) or the extended version with some popular packages already included: [Anaconda](https://www.anaconda.com/download).

## 2. Create a conda environment with KinBot and PESViewer

1. Download `kb_env.yml` yaml file from [here](https://portal.nersc.gov/project/m3672/cmartia/acs_fall_workshop/kb_env.yml).

::: info
:information_source:: If by clicking the "*here*" link a download doesn't start, try right-clicking and "*Save link as...*"
:::

2. On a terminal/PowerShell, go to the directory where you downloaded `kb_env.yml` and type:

    conda env create -f kb_env.yml

::: info
:information_source: You'll need internet connection. The proceess might take several minutes to complete.
:::

3. Activate the created evironment with:

    conda activate kinbot

## 3. Download the necessary material

Open [this link for Windows/Mac](https://portal.nersc.gov/project/m3672/cmartia/acs_fall_workshop/kinbot_workshop.zip) or [this link for Linux/Mac](https://portal.nersc.gov/project/m3672/cmartia/acs_fall_workshop/kinbot_workshop.tgz) to download the material and extract it.

If you used the Linux/Mac link, type the following command from the directory where you download it.

tar -xvf kinbot_workshop.tgz

::: warning
:warning: The file is 2 Gb so it might take a while to download on slow connections. Beware that once uncompressed it uses 8 Gb of disk space.
:::

<!-- # 4. Run the first exercise

From the `exercise1` directory extracted from `kinbot_workshop.tgz` run:

kinbot exercise1.json &

It should take less than a minute to complete.

# 5. Tell me if you get any error

Self-explanatory -->