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sasctl

A user-friendly REST client for SAS Viya.

SAS Viya Version Python Version

Overview

The sasctl package enables easy communication between the SAS Viya platform and a Python runtime. It can be used as a module or as a command line interface.

sasctl.folders.list_folders()
sasctl folders list

Prerequisites

sasctl requires the following Python packages be installed. If not already present, these packages will be downloaded and installed automatically.

  • requests
  • six

The following additional packages are recommended for full functionality:

  • swat
  • kerberos

Installation

pip install sasctl

Functionality that depends on additional packages can be installed using the following:

  • pip install sasctl[swat]
  • pip install sasctl[kerberos]
  • pip install sasctl[all]

Getting Started

Once the sasctl package has been installed and you have a SAS Viya server to connect to, the first step is to establish a session:

>>> from sasctl import Session

>>> with Session(host, username, password):
...     pass  # do something
sasctl --help 

Once a session has been created, all commands target that environment. The easiest way to use sasctl is often to use a pre-defined task, which can handle all necessary communication with the SAS Viya server:

>>> from sasctl import Session, register_model
>>> from sklearn import linear_model as lm

>>> with Session('example.com', authinfo=<authinfo file>):
...    model = lm.LogisticRegression()
...    register_model(model, 'Sklearn Model', 'My Project')

A slightly more low-level way to interact with the environment is to use the service methods directly:

>>> from pprint import pprint
>>> from sasctl import Session
>>> from sasctl.services import folders

>>> with Session(host, username, password):
...    folders = folders.list_folders()
...    pprint(folders)
    
{'links': [{'href': '/folders/folders',
            'method': 'GET',
            'rel': 'folders',
            'type': 'application/vnd.sas.collection',
            'uri': '/folders/folders'},
           {'href': '/folders/folders',
            'method': 'POST',
            'rel': 'createFolder',

...  # truncated for clarity

            'rel': 'createSubfolder',
            'type': 'application/vnd.sas.content.folder',
            'uri': '/folders/folders?parentFolderUri=/folders/folders/{parentId}'}],
 'version': 1}

The most basic way to interact with the server is simply to call REST functions directly, though in general, this is not recommended.

>>> from pprint import pprint
>>> from sasctl import Session, get

>>> with Session(host, username, password):
...    folders = get('/folders')
...    pprint(folders)
    
{'links': [{'href': '/folders/folders',
            'method': 'GET',
            'rel': 'folders',
            'type': 'application/vnd.sas.collection',
            'uri': '/folders/folders'},
           {'href': '/folders/folders',
            'method': 'POST',
            'rel': 'createFolder',

...  # truncated for clarity

            'rel': 'createSubfolder',
            'type': 'application/vnd.sas.content.folder',
            'uri': '/folders/folders?parentFolderUri=/folders/folders/{parentId}'}],
 'version': 1}

Examples

A few simple examples of common scenarios are listed below. For more complete examples see the examples folder.

Show models currently in Model Manager:

>>> from sasctl import Session
>>> from sasctl.services import model_repository

>>> with Session(host, username, password):
...    models = model_repository.list_models()

Register a pure Python model in Model Manager:

>>> from sasctl import Session, register_model
>>> from sklearn import linear_model as lm

>>> with Session(host, authinfo=<authinfo file>):
...    model = lm.LogisticRegression()
...    register_model(model, 'Sklearn Model', 'My Project')

Register a CAS model in Model Manager:

>>> import swat
>>> from sasctl import Session
>>> from sasctl.tasks import register_model

>>> s = swat.CAS(host, authinfo=<authinfo file>)
>>> astore = s.CASTable('some_astore')

>>> with Session(s):
...    register_model(astore, 'SAS Model', 'My Project')

Contributing

We welcome contributions!

Please read CONTRIBUTING.md for details on how to submit contributions to this project.

License

See the LICENSE file for details.

Additional Resources