Introduction to sasr

# Introduction to `sasr`

`sasr` is a package to provide `SAS` interface in R, with `saspy` and `reticulate` as backend.

## Documentations

For functionality wrapped in `sasr`, you can find the documentations through R documentation system, or through online documentation page. However, there can be some other arguments not documented(in `...`), and these arguments are described in `saspy` documentation page.

## Short Tutorial

To use `sasr`, you need to follow these steps

1. Configure your SAS server in `sascfg_personal.py` under your working directory or the home directory. This is the default file that `sasr` will look at. However, you can still change that through `options(sascfg = )`, then `sasr` will try to find any name that is available in your specified option.
   1. If you don’t know how to create this file, use `sascfg()` to create the file. Required arguments include `host` and `saspath`.
      1. `sascfg()` only creates ssh based SAS session.
      2. Only password-less ssh connection is supported, e.g. ssh via public keys.
      3. `host` is the hostname of the SAS server.
      4. `saspath` is the SAS executable path on the SAS server.
      5. Other arguments are added to the configuration file directly.
      6. `tunnel` and `rtunnel` are required if you want to transfer datasets between R and SAS if the client (running sasr) is not reachable from the server. Use integers like `tunnel = 9999L` in R, or modify `sascfg_personal.py` to make sure they are integers.
   2. You can create the configuration by yourself and then SAS connection will not be restricted to ssh.
   3. You can have multiple configuration files with different file names
2. Create the SAS session based on the configuration file
   1. To use the default connection specified in the configuration file, you can run any command like `run_sas`, `df2sd` or `sd2df`.
      1. The session will be created if there is no session available stored in `.sasr_env$.sas_session`
      2. If `.sasr_env$.sas_session` is created, this session will be used by default.
      3. Do not create any variable called `.sas_session` in environment `sasr:::.sasr_env`
   2. To create the session manually, you can call `sas_session()`
      1. `SAS_session` have one argument `sascfg`, pointing to the SAS session configuration file.
   3. To use multiple sessions, you need to store the session `your_session <- sas_session(sascfg)`
3. Transfer the datasets from R to SAS using `df2sd`
   1. Tunneling must be enabled to transfer datasets.
   2. The variable names of the datasets should not contain dots otherwise SAS may not recognize.
   3. The index (row names) will not be transferred to SAS.
4. Use `run_sas` to submit SAS code to the SAS server.
   1. The returned value is a named list, `LST` is the result and `LOG` is the log file
   2. `run_sas` has argument `results=`, it can be either “TEXT” or “HTML”. This argument decides the LST format.
5. Transfer SAS datasets back to R use `sd2df`