Python SWAT Library
for developers

Getting Started with Python SWAT

The SAS Scripting Wrapper for Analytics Transfer (SWAT) package is a Python interface to SAS Cloud Analytic Services (CAS) (the centerpiece of the SAS Viya framework). Using SWAT, you can execute workflows of CAS analytic actions, then pull down the summarized data to further process on the client side in Python, or to merge with data from other sources using familiar Pandas data structures.

 Features:

  • full integration with Jupyter notebooks
  • mimics much of the API of the Pandas package
  • supports both natively compiled binary and pure Python REST clients 
  • code in Python and integrate with SAS

Try it for free as part of the SAS Viya Programming trial

  • explore the capabilities of SAS Event Stream Processing
  • self-contained programming environment - no installation
  • use JupyterLab as an interface
  • code with sample data and code demo scripts

Sample code

The sample code below establishs a connection and returns descriptive statistics on a table. To see further sample code, visit the samples page on GitHub.

Get Descriptive Statistics


>>> import saspy
>>> sas = saspy.SASsession()
SAS Connection established. Subprocess id is 3664

>>> cars  = sas.sasdata( 'cars','sashelp')
>>> cars.describe()
      Variable            Label    N  NMiss   Median          Mean        StdDev      Min       P25      P50      P75       Max
0         MSRP              NaN  428      0  27635.0  32774.855140  19431.716674  10280.0  20329.50  27635.0  39215.0  192465.0
1      Invoice              NaN  428      0  25294.5  30014.700935  17642.117750   9875.0  18851.00  25294.5  35732.5  173560.0
2   EngineSize  Engine Size (L)  428      0      3.0      3.196729      1.108595      1.3      2.35      3.0      3.9       8.3
3    Cylinders              NaN  426      2      6.0      5.807512      1.558443      3.0      4.00      6.0      6.0      12.0
4   Horsepower              NaN  428      0    210.0    215.885514     71.836032     73.0    165.00    210.0    255.0     500.0
5     MPG_City       MPG (City)  428      0     19.0     20.060748      5.238218     10.0     17.00     19.0     21.5      60.0
6  MPG_Highway    MPG (Highway)  428      0     26.0     26.843458      5.741201     12.0     24.00     26.0     29.0      66.0
7       Weight     Weight (LBS)  428      0   3474.5   3577.953271    758.983215   1850.0   3103.00   3474.5   3978.5    7190.0
8    Wheelbase   Wheelbase (IN)  428      0    107.0    108.154206      8.311813     89.0    103.00    107.0    112.0     144.0
9       Length      Length (IN)  428      0    187.0    186.362150     14.357991    143.0    178.00    187.0    194.0     238.0
>>>


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