README.md

In sasquatch: Use 'SAS', R, and 'quarto' Together

sasquatch

Use SAS, R, and Quarto Together

sasquatch allows you to combine the power of R, SAS, and quarto together to create reproducible multilingual reports. sasquatch can:

• Run SAS code blocks interactively
• Send data back and forth between SAS and R
• Conduct basic file management on a SAS client
• Render html or latex SAS output within quarto/rmarkdown documents.

Installation

Package installation

You can install socratadata from CRAN.

install.packages("socratadata")

You can install the development version of sasquatch like so:

install.packages(
  "sasquatch",
  repos = c('https://ropensci.r-universe.dev', 'https://cloud.r-project.org')
)
# or
# install.packages("pak")
pak::pkg_install("ropensci/sasquatch")

Python installation

Make sure Python is installed on your system. If Python has not been installed, you can install Python like so:

reticulate::install_python()

or download the installer from the Python Software Foundation.

SASPy installation

To install the SASPy package and its dependencies within a Python virtual environment:

sasquatch::install_saspy()

Configuration

Configuration for SAS can vary greatly based on your computer’s operating system and the SAS platform you wish to connect to. For more information check out vignette("configuration").

Don’t have a SAS license currently or just want to get set up quickly? Configure sasquatch for SAS On Demand for Academics using the steps below:

Registration

SAS On Demand for Academics (ODA) is free SAS client for professors, students, and independent learners. Create an account at https://welcome.oda.sas.com/.

Once you have set up your account, log in and note the ODA server (in the picture below United States 2) and your username (under the email in the profile dropdown). We will need these for later.

Java installation

ODA relies on the IOM access method, which requires Java. Make sure Java is installed on your system. Note the Java installation path.

ODA Configuration

Set up for ODA is super easy. Run config_saspy() and follow the prompts (you may need to recall your username, server, and java installation path from earlier).

sasquatch::configure_saspy(template = "oda")

config_saspy(template = "oda") will create a sascfg_personal.py file with all the relevant configuration information and create an authinfo file, which will store your ODA credentials. More information about ODA configuration can be found in the ODA section of SASPy configuration documentation.

Usage

Once you have setup SASPy and connected to the right python environment using reticulate (if necessary), you can create a quarto document like any other, call sas_connect(), and just get going!

---
format: html
engine: knitr
---

```{r}
library(sasquatch)
sas_connect()
```

```{sas}

```

Code blocks

Now, you should be able to run SAS code blocks in RStudio like any other.

Quarto document contents within the picture:

---
title: Example
subtitle: isn't this cool!
format: html
engine: knitr
---

```{r}
library(sasquatch)
sas_connect()
```

```{sas}
PROC MEANS DATA = sashelp.cars;
RUN;
```

Sending output to viewer

If you want to send the SAS output to the viewer, you can utilize the sas_run_selected() addin with a custom shortcut.

Or with a keyboard shortcut in Positron.

{
    "key": "ctrl+shift+enter",
    "command": "workbench.action.executeCode.console",
    "when": "editorTextFocus",
    "args": {
        "langId": "r",
        "code": "sasquatch::sas_run_selected()",
        "focus": true
    }
}

Converting tables

Pass tables between R and SAS with sas_from_r() and sas_to_r().

sas_from_r(warpbreaks, "warpbreaks")
sas_cars <- sas_to_r("cars", libref = "sashelp")

Rendering quarto/rmarkdown documents

And of course, render beautiful HTML or latex quarto/rmarkdown documents in the same style you would expect from SAS with the sas_engine().

Comparison with similar packages

sasquatch relies on the SASPy Python package and the reticulate R package to interoperate with Python. There exist similar packages, which work similarly to achieve related goals.

sasr

• sasr works identically to sasquatch relying on the SASPy Python package to interface with SAS, but does not include any interactive, file management, or quarto functionality.

configSAS

• Like sasr and sasquatch, configSAS relies on the SASPy Python package, but it primarily focuses on solely on knitr engine support.
• The configSAS engine HTML output CSS styles interfere with the rest of the document and SAS code output is not contained within a code block.
• configSAS is not actively maintained.

SASmarkdown

• SASmarkdown does not rely on the SASPy Python package and thus is fairly simple to set up; however, it does require a SAS executable to be installed on the same machine as R.
• In contrast, SASPy-reliant packages can interface with both local and remote SAS installations and can easily pass data between R and SAS without the need for intermediate files.

sasquatch may be beneficial to you if you…

• Rely on a remote SAS client
• Desire interactive SAS functionality while developing
• Require remote SAS file management
• Would like to be able to easily send data back and forth between SAS and R without the use of intermediate files

Contributing

Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

sasquatch documentation built on Feb. 28, 2026, 1:07 a.m.