Lesson 16, Appendix II: How to Connect SASPy with a Local Installation of SAS?¶

It is assumed that you can access a local installation of SAS (i.e., licensed SAS) on your computer. As a prerequisite for SASPy installation, you must download/install Anaconda and download Java to connect SASPy with a local installation of the Licensed version of SAS.

Step 1: Install Anaconda on Windows¶

Jupyter Notebook automatically gets installed as part of the Anaconda installation.

Step 2: Download Java for Windows or for macOS as appropriate¶

Step 3: Download and install SASPy¶

  • Open this URL(https://github.com/sassoftware/saspy/releases) with a web browser

  • At the top of this page, you should see that the current release of SASPy

  • Then scroll down just a bit until you see the heading titled: Assets. Clicking it should download a local copy of the

installation file.

  • Then you should be able to install the downloaded version via the following PIP command:
    pip install C:\your\directory\saspy-4.3.2.tar.gz


Where "C:\your\directory" is the location on your machine where saspy-4.3.2.tar.gz resides.
  • After installing SASPy you can verify the installation by issuing the following command:
    pip show saspy

Step 4: Install the SAS kernel.¶

So the SAS kernel is a separate install from the SASPy install. Typically, to install the SAS kernel, you simply issue the following command:

    pip install sas-kernel

But if you try this and run into the SSL certificate issue as before, try the following. Open the following URL with your web browser: https://github.com/sassoftware/sas_kernel/releases

Near the top of this page, under Assets, click the following link: Source code (tar.gz). It should download a local copy of an installation file (e.g., sas_kernel-2.4.11.tar.gz or an updated version).

Install the file via the following PIP command then:

    pip install C:\your\directory\sas_kernel-2.4.11.tar.gz

Where "C:\your\directory" is the location on your machine where sas_kernel-2.4.11.tar.gz resides.

After installing the SAS kernel, you can verify the installation by issuing the following command:

    pip show sas-kernel

SASPy does not require the SAS kernel, but the SAS kernel does require SASPy to be installed.

SASPy and the SAS kernel for Jupyter Notebook enable you to connect to SAS® 9.4 and the SAS® Viya®." (Mincey, 2022)

Step 5: Create a sascfg_personal.py and store it in the saspy folder to connect SASPy to your SAS installation.¶

Example folder¶
ascii
C:\Users\rblack\AppData\Local\anaconda3\Lib\site-packages\saspy\sascfg_personal.py
Content of sascfg_personal.py¶
import os
os.environ["PATH"] += ";C:\\Program Files\\SASHome\\SASFoundation\\9.4\\core\\sasext"
SAS_config_names=['winlocal']
default  = {'saspath'  : '/opt/sasinside/SASHome/SASFoundation/9.4/bin/sas_u8' }
winlocal = {'java'      : 'C:\Program Files (x86)\Common Files\Oracle\Java\javapath\java.exe',  'encoding'  : 'windows-1252'}
Step 6: Check if sascfg_personal.py connects SASPy to your SAS installations¶
import saspy
sas = saspy.SASsession()
sas
Step 7: Check if the following Python code using the SAS kernel works¶
import saspy
import pandas as pd
sas = saspy.SASsession(cfgname='winlocal')
w_class = sas.sasdata("CLASS","SASHELP")
w_class.describe()
Some Facts about SASPy¶

  • It enables the communication between Jupyter and SAS when using the SAS Kernel.

  • It can run Python code using commonly used IDE other than Jupyter Notebook.

  • It can load SAS data sets into Python-Pandas DataFrame objects.

  • It converts Python-Pandas DataFrame objects into SAS data sets.

  • It uses Python convenience methods on SAS data sets.

  • It imitates the SAS macro facility.

  • It generates SAS code from Python code.

  • It enables you to inject your SAS program code from within a Python language notebook using special Jupyter "magics" supported by the sas_kernel and pull in SAS results. This %%SAS magic command allows you to move quickly between Python and SAS in a single environment (Hemedinger, 2016).

  • It provides output with several options: HTML, Text, and Pandas data frame.

pip commands to uninstall/install saspy and sas_kernel¶
pip install 
pip uninstall -y saspy 
pip uninstall -y sas_kernel 
pip install saspy 
sas_kernel 
pip show saspy
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