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wwarriner wants to merge 36 commits into uabrc:main from wwarriner:feat-anaconda-to-miniforge

docs/account_management/xias/pi_guest_management.md

            
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    <!-- markdownlint-disable MD046 -->

    !!! note

        These instructions are intended for use by UAB-employed PIs to organize external collaborators, also known as guests. UAB PIs: Please direct guests [here](guest_instructions.md) for instructions on creating their accounts.

        These instructions are intended for use by UAB-employed PIs to organize external collaborators, also known as guests. UAB PIs: Please direct guests to our [Guest Instructions](guest_instructions.md) to create their accounts.

    <!-- markdownlint-enable MD046 -->

    <!-- markdownlint-disable MD046 -->

docs/account_management/xias/pi_site_management.md

            
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    <!-- markdownlint-disable MD046 -->

    !!! note

        These instructions are intended for use by UAB-employed PIs to organize external collaborators, also known as guests. UAB PIs: Please direct guests [here](guest_instructions.md) for instructions on creating their accounts.

        These instructions are intended for use by UAB-employed PIs to organize external collaborators, also known as guests. UAB PIs: Please direct guests to our [Guest Instructions](guest_instructions.md) to create their accounts.

    <!-- markdownlint-enable MD046 -->

    XIAS Project/Sites, or simply sites, tie external users to specific resources at UAB. By connecting people to the resource they use, UAB can maintain security and accountability. Creating a site is the first step to giving access to external collaborators, and the process can be thought of as "create once, use many times". All sites must have an expiration date for security reasons. To create a site you'll need at least one Uniform Resource Identifier (URI) relating to resources used by the site. If you aren't sure what URI(s) to list for your site, please contact <UserServices@uab.edu>.

docs/cheaha/getting_started.md

            
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    @@ -175,10 +175,14 @@ Slurm is our job queueing software used for submitting any number of job scripts
  
    A large variety of software is available on Cheaha as modules. To view and use these modules see [the following documentation](./software/modules.md).

    For new software installation, please try searching [Anaconda](../workflow_solutions/using_anaconda.md) for packages first. If you still need help, please [send a support ticket](../help/support.md)

    For new software installation, please try searching for [`conda` packages](../workflow_solutions/using_conda.md#good-practice-for-finding-software-packages-on-conda) first. If you still need help, please [send a support ticket](../help/support.md)

    ### Conda Packages

    A significant amount of open-source software is distributed as Anaconda or Python libraries. These libraries can be installed by the user without permission from Research Computing using Anaconda environments. To read more about using Anaconda virtual environments see our [Anaconda page](./software/software.md#anaconda-on-cheaha).

    A significant amount of open-source research software is distributed as `conda` packages or Python libraries. These libraries can be installed by the user using `conda` environments. To read more about using `conda` environments see our [`conda` page](./software/software.md#conda-on-cheaha).

    If the software installation instructions tell you to use either `conda install` or `pip install` commands, the software and its dependencies can be installed using a virtual environment.

    If the software installation instructions tell you to use either `conda install` or `pip install` commands, the software and its dependencies can be installed using a Conda environment.

    ## How to Get Help

    For questions, you can reach out via our various [channels](../help/support.md).

docs/cheaha/open_ondemand/ood_jupyter_notebook.md

            
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    # Jupyter Notebook

    Jupyter Notebooks and [Jupyter Lab](./ood_jupyterlab.md) are both available as standalone apps in OOD. Jupyter is commonly used with Anaconda environments. If you are unfamiliar with Anaconda environments please see the [Working with Anaconda Environments section](#working-with-anaconda-environments) below before continuing here.

    Jupyter Notebooks and [Jupyter Lab](./ood_jupyterlab.md) are both available as standalone apps in OOD. Jupyter is commonly used with Anaconda environments. If you are unfamiliar with Anaconda environments please see the [Working with Anaconda Environments section](#working-with-conda-environments) below before continuing here.

    To launch the Jupyter Notebook, select the menus 'Interactive Apps -> Jupyter Notebook'. The job creation and submission form appears:

    @@ -54,9 +54,9 @@ To work with other programming languages within Jupyter Notebook, you need to in
  
    Once the necessary kernels are installed, if you wish, you can write and run multiple code cells in different languages within a single notebook. Easily switch between kernels and select the preferred one for each language, and then proceed to run the code cells in their respective languages.

    ## Working With Anaconda Environments

    ## Working With Conda Environments

    By default, Jupyter Notebooks will use the base environment that comes with the Anaconda3 module. This environment contains a large number of popular packages and may useful for something quick, dirty, and simple. However, for any analysis needing specific package versions or special packages, you will need to create your own environment and select it from the `Kernel` menu. For information on creating and managing Anaconda environments please see our [Using Anaconda page](../../workflow_solutions/using_anaconda.md). Then please review our [Cheaha-specific Anaconda page](../software/software.md#anaconda-on-cheaha) for important tips and how to avoid common pitfalls.

    By default, Jupyter Notebooks will use the base environment that comes with the Anaconda3 module. This environment contains a large number of popular packages and may useful for something quick, dirty, and simple. However, for any analysis needing specific package versions or special packages, you will need to create your own environment and select it from the `Kernel` menu. For information on creating and managing Anaconda environments please see our [Using Anaconda page](../../workflow_solutions/using_conda.md). Then please review our [Cheaha-specific Anaconda page](../software/software.md#conda-on-cheaha) for important tips and how to avoid common pitfalls.

    To change the kernel, use the `Kernel` dropdown and select `Change Kernel`. From the list, choose the kernel corresponding to your desired Anaconda environment (see below for an example). If your environment isn't appearing, you may be missing the ipykernel package. To do so, use `conda install ipykernel` to get the `ipykernel` package installed into your environment, so Jupyter can recognize your environment.

    @@ -71,9 +71,9 @@ We can create a new environment, that houses all of the packages, modules, and l
  
        - [OOD Terminal](./ood_layout.md#opening-a-terminal). Be sure to run the following steps in a job!

        - [OOD HPC Desktop Job Terminal](./hpc_desktop.md). This method will ensure terminal commands are run in a job.

    1. [Create](../../workflow_solutions/using_anaconda.md#create-an-environment) and [activate](../../workflow_solutions/using_anaconda.md#activate-an-environment) your new environment, following the linked steps.

    1. [Create](../../workflow_solutions/using_conda.md#create-an-environment) and [activate](../../workflow_solutions/using_conda.md#activate-an-environment) your new environment, following the linked steps.

    1. [Install your desired packages into your activated environment](../../workflow_solutions/using_anaconda.md#install-packages).

    1. [Install your desired packages into your activated environment](../../workflow_solutions/using_conda.md#install-packages).

    1. Remember to install `ipykernel` in your activated environment, using `conda install ipykernel`.

    @@ -146,9 +146,9 @@ Replace `python3.11` in the command with the appropriate Python version.
  
    Here's an example of the correct procedure for installing `pip` packages within a `conda`:

    1. Load the `Anaconda3` module using `module load Anaconda3`.

    1. Create or activate the desired Anaconda environment. Please refer to the [Anaconda documentation](../../workflow_solutions/using_anaconda.md#create-an-environment)

    1. Create or activate the desired Anaconda environment. Please refer to the [Anaconda documentation](../../workflow_solutions/using_conda.md#create-an-environment)

    1. Install `pip` within the `conda` environment using `conda install pip` or `conda install python`. `pip` and `python` are packaged together, installing one will always install the other.

    1. Use `pip` when this `conda` environment is active to install packages. Please refer to [Installing packages with `pip`](../../workflow_solutions/using_anaconda.md#installing-packages-with-pip)

    1. Use `pip` when this `conda` environment is active to install packages. Please refer to [Installing packages with `pip`](../../workflow_solutions/using_conda.md#installing-packages-with-pip)

    ### Tensorflow and PyTorch GPU Issues

docs/cheaha/open_ondemand/ood_jupyterlab.md

            
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    @@ -26,7 +26,7 @@ Please follow the instructions found in our [Working With Other Programming Lang
  
    ## Working With Conda Environments Using JupyterLab

    By default, JupyterLab on Cheaha will launch using the `base` conda environment. While this default environment includes a wide range of popular packages and can be helpful for quick or exploratory tasks, it is not recommended for research workflows that require specific package versions or custom dependencies. For reproducible and stable analysis, it’s best to create and use a dedicated Conda environment tailored to your project or research workflow. Once created, you can register the environment as a Jupyter kernel and select it directly from within JupyterLab. For information on creating and managing Conda environments please see our [Using Anaconda page](../../workflow_solutions/using_anaconda.md). Then please review our [Cheaha-specific Anaconda page](../software/software.md#anaconda-on-cheaha) for important tips and how to avoid common pitfalls.

    By default, JupyterLab on Cheaha will launch using the `base` conda environment. While this default environment includes a wide range of popular packages and can be helpful for quick or exploratory tasks, it is not recommended for research workflows that require specific package versions or custom dependencies. For reproducible and stable analysis, it’s best to create and use a dedicated Conda environment tailored to your project or research workflow. Once created, you can register the environment as a Jupyter kernel and select it directly from within JupyterLab. For information on creating and managing Conda environments please see our [Using Anaconda page](../../workflow_solutions/using_conda.md). Then please review our [Cheaha-specific Anaconda page](../software/software.md#conda-on-cheaha) for important tips and how to avoid common pitfalls.

    ![! Landing page of JupyterLab when you launch the Interactive session](images/ood_jupyterlab_landingpage.png)

docs/cheaha/open_ondemand/ood_matlab.md

            
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    @@ -10,17 +10,17 @@ Matlab is available for use graphically in your browser via OOD. As with other s
  
        Matlab tends to consume substantial memory at startup. You may experience difficulty with job errors below 20 GB of total memory.

    <!-- markdownlint-enable MD046 -->

    ## Using Anaconda Python From Within MATLAB

    ## Using Conda Python From Within MATLAB

    Matlab has the ability to interoperate with Python from within Matlab. The official documentation for this feature may be found at <https://www.mathworks.com/help/matlab/call-python-libraries.html>.

    This section is dedicated to using this feature with Anaconda on Cheaha. To use Python contained in an Anaconda Environment within Matlab, please use the following steps.

    This section is dedicated to using this feature with `conda` on Cheaha. To use Python contained in a `conda` Environment within Matlab, please use the following steps.

    1. Create an [HPC Interactive Desktop Job](hpc_desktop.md).

    1. Open a terminal in that job. The following steps should all be run in this terminal unless otherwise specified.

    1. [Load the Anaconda Module](../software/software.md#loading-anaconda).

    1. [Create an Environment](../../workflow_solutions/using_anaconda.md#create-an-environment) in Anaconda with the packages needed.

    1. [Activate the Environment](../../workflow_solutions/using_anaconda.md#activate-an-environment),

    1. [Load the `conda` Module](../software/software.md#loading-conda).

    1. [Create an Environment](../../workflow_solutions/using_conda.md#create-an-environment) in `conda` with the packages needed.

    1. [Activate the Environment](../../workflow_solutions/using_conda.md#activate-an-environment),

    1. Load the Matlab [Module](../software/modules.md).

    1. Start Matlab by entering the command `matlab`.

    1. Verify success by entering `pyenv` at the Matlab prompt (not the terminal window). Multiple lines of text will be returned at the prompt. Among them you should see a line like the following, with your environment name in place of `<env_name>`.

docs/cheaha/open_ondemand/ood_rstudio.md

            
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    @@ -12,16 +12,16 @@ RStudio is available for use graphically in your browser via OOD. As with other
  
    ## RStudio and Python

    If you have a workflow that uses both R and Python, it is strongly recommended to use the [reticulate](https://rstudio.github.io/reticulate/) package along with Anaconda environments. Reticulate allows researchers to load Python packages into a native R session as objects. For instance, if someone prefer some functionality of the `pandas` package but has other code already written in R, they can import `pandas` to R and use both simultaneously.

    If you have a workflow that uses both R and Python, it is strongly recommended to use the [reticulate](https://rstudio.github.io/reticulate/) package along with `conda` environments. Reticulate allows researchers to load Python packages into a native R session as objects. For instance, if someone prefer some functionality of the `pandas` package but has other code already written in R, they can import `pandas` to R and use both simultaneously.

    This also allows researchers to download precompiled command line binaries into an Anaconda environment and easliy use them in their R scripts.

    This also allows researchers to download precompiled command line binaries into a `conda` environment and easily use them in their R scripts.

    For setup, use the following steps:

    1. In a terminal on a compute node, either in an HPC Desktop job or by clicking the blue Host button on any job card:

        1. Load the `Anaconda3` module

        1. Create an Anaconda environment. More information about how to create Anaconda environments can be found [in our documentation](../../workflow_solutions/using_anaconda.md).

        1. Load the `Miniforge3` module

        1. Create a `conda` environment. More information about how to create `conda` environments can be found [in our documentation](../../workflow_solutions/using_conda.md).

        1. Activate your environment and install your requuired python packages using either `pip install` or `conda install` depending on the package source.

        <!-- markdownlint-disable MD046 -->

    @@ -32,16 +32,16 @@ For setup, use the following steps:
  
    1. In RStudio:

        1. Add the command `module load Anaconda3` to the Environment Setup window when requesting the RStudio job.

        1. Add the command `module load Miniforge3` to the Environment Setup window when requesting the RStudio job.

        1. If not already installed, install the `reticulate` package using either `install.packages` or the [renv](#rstudio-projects-and-renv) package.

        1. Use `reticulate::use_condaenv('env_name')` to load your conda environment.

        1. From here, you will be able to interact with all of the python packages and non-python precompiled binaries in your Anaconda environment using R and RStudio. Please read more about how to do that in [reticulate's documentation](https://rstudio.github.io/reticulate/#importing-python-modules).

        1. Use `reticulate::use_condaenv('ENVIRONMENT')` to load your conda environment which has the name `ENVIRONMENT`.

        1. From here, you will be able to interact with all of the python packages and non-python precompiled binaries in your `conda` environment using R and RStudio. Please read more about how to do that in [reticulate's documentation](https://rstudio.github.io/reticulate/#importing-python-modules).

    For cases where your R code only needs access to precompiled binaries or libraries and does not need to import any Python libraries, you can instead create your Anaconda environment and add the following lines into the Environment Setup window:

    For cases where your R code only needs access to precompiled binaries or libraries and does not need to import any Python libraries, you can instead create your `conda` environment and add the following lines into the Environment Setup window:

    ``` bash

    module load Anaconda3

    conda activate <env_name>

    module load Miniforge3

    conda activate ENVIRONMENT

    ```

    This will add those binaries and libraries to your environment `$PATH` which RStudio will inherit.

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