BookmarkSubscribeRSS Feed

Your First CAS Connection from Python

Started ‎03-30-2016 by
Modified ‎04-16-2019 by
Views 2,099

Your First CAS Connection from Python

 

Let's start with a gentle introduction to the Python CAS client by doing some basic operations like creating a CAS connection and running a simple action.  You'll need to have Python installed as well as the SWAT Python package from SAS, and you'll need a running CAS server.

 

We will be using Python 3 for our example, but the same code will work in Python 2.7.  Specifically, we will be using the IPython interactive prompt (type 'ipython' rather than 'python' at your command prompt).  The first thing we need to do is import SWAT and create a CAS session.  We will use the name 'cas01' for our CAS hostname and 12345 as our CAS port name.  In this case, we will use username/password authentication, but other authentication mechanisms are also possible depending on your configuration.

 

# Import the SWAT package which contains the CAS interface
In [1]: import swat

# Create a CAS session on my-cas-server port 12345
In [2]: conn = swat.CAS('cas01', 12345, 'username', 'password')

In [3]: conn
Out[3]: CAS('cas01', 12345, 'username', protocol='cas', name='py-session-1', session='0f60f4f0-ff84-6843-a8cc-00232492ae09')

 

As you can see above, we have a session on the server cas01.  It has been assigned a unique session ID and more user-friendly name.  In this case, we are using the binary CAS protocol as opposed to the REST interface.  We can now run CAS actions in the session.  Let's begin with a simple one: listnodes.

 

# Run the listnodes action
In [4]: nodes = conn.listnodes()
NOTE: Information is available on 6 nodes.

In [5]: nodes
Out[5]:
[nodelist]

 Node List

    name       role connected   IP Address
 0 cas01 controller       Yes 10.37.10.172
 1 cas02 controller       Yes 10.37.10.174
 2 cas03 worker           Yes 10.37.10.175
 3 cas04 worker           Yes 10.37.10.176
 4 cas05 worker           Yes 10.37.10.191
 5 cas06 worker           Yes 10.37.10.193

+ Elapsed: 0.00413s, user: 0.005s, sys: 0.008s, mem: 0.413mb

 

The listnodes action returns a CASResults object (which is just a subclass of Python's ordered dictionary).  It contains one key ('nodelist') which holds a Pandas DataFrame.  We can now grab that DataFrame to do further operations on it.

 

# Grab the nodelist DataFrame
In [6]: df = nodes['nodelist']

In [7]: df
Out[7]:
Node List

  name        role connected   IP Address
0 cas01 controller       Yes 10.37.10.172
1 cas02 controller       Yes 10.37.10.174
2 cas03     worker       Yes 10.37.10.175
3 cas04     worker       Yes 10.37.10.176
4 cas05     worker       Yes 10.37.10.191
5 cas06     worker       Yes 10.37.10.193

# Use DataFrame selection syntax to subset the columns.
In [8]: roles = df[['name', 'role']]

In [9]: roles
Out[9]:
Node List

  name  role
0 cas01 controller
1 cas02 controller
2 cas03 worker
3 cas04 worker
4 cas05 worker
5 cas06 worker

# Extract the worker nodes using a DataFrame mask
In [10]: roles[roles.role == 'worker']
Out[10]:
Node List

  name    role
2 cas03 worker
3 cas04 worker
4 cas05 worker
5 cas06 worker

# Extract the controllers using a DataFrame mask
In [11]: roles[roles.role == 'controller']
Out[11]:
Node List

  name        role
0 cas01 controller
1 cas02 controller

In the code above, we are doing some standard DataFrame operations using expressions to filter the DataFrame to include only worker nodes or controller nodes.  Pandas DataFrames support lots of ways of slicing and dicing your data.  If you aren't familiar with them, you'll want to get acquainted on the Pandas web site.

 

When you are finished with a CAS session, it's always a good idea to clean up.

 

# Close the connection
In [12]: conn.close()

 

Those are the very basics of connecting to CAS, running an action, and manipulating the results on the client side.  You should now be able to jump to other topics on the Python CAS client to do some more interesting work.

 

Resources

 

You can download the Jupyter notebook for this article on Github at https://github.com/sassoftware/sas-viya-programming/tree/master/communities.

Version history
Last update:
‎04-16-2019 09:14 AM
Updated by:

sas-innovate-2024.png

Don't miss out on SAS Innovate - Register now for the FREE Livestream!

Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.

 

Register now!

Free course: Data Literacy Essentials

Data Literacy is for all, even absolute beginners. Jump on board with this free e-learning  and boost your career prospects.

Get Started

Article Tags