Visualization with Bokeh
Missing Linux Library Dependencies
Incorrect SAS Threaded Kernel Configuration
Foreword
SAS® Viya® marks a new and important chapter in our ever-evolving SAS software. A unified, open, powerful, and cloud-ready platform built on excellence in data management, advanced analytics, and high-performance computing.
These pillars of SAS Viya are important individually, but it is through their combination that the platform comes to life. The ability to access a central data management and computing environment through public APIs and from multiple programming languages, with consistent security and data models is a core competency of the modern analytic platform.
The Python language has quickly grown into one of the important programming languages for data science and analytics. As the SAS R&D team embarked on building SAS Cloud Analytic Services (CAS), the engine of the SAS Viya platform, it was obvious that access from Python would be important.
The Python client for SAS Viya was developed by Kevin Smith as a member of the core team that designed and developed SAS Cloud Analytic Services. This book by Kevin and Xiangxiang Meng takes you on a journey to learn and apply Python programming in the context of the SAS Viya platform. Their deep understanding of the SAS Viya server architecture, the client architecture, and the Python language implementation shines through in every chapter.
As a lifelong learner, I greatly enjoyed the journey and am sure that you will, too.
Oliver Schabenberger, PhD Executive Vice President, Chief Operating Officer and Chief Technology Officer SAS
About This Book
What Does This Book Cover?
This book is an introduction to using the Python client on the SAS Viya platform. SAS Viya is a high-performance, fault-tolerant analytics architecture that can be deployed on both public and private cloud infrastructures. Although SAS Viya can be used by various SAS applications, it also enables you to access analytic methods from SAS, Python, Lua, and Java, as well as through a REST interface using HTTP or HTTPS. Of course, in this book we focus on the perspective of SAS Viya from Python.
SAS Viya consists of multiple components. The central piece of this ecosystem is SAS Cloud Analytic Services (CAS). CAS is the cloud-based server that all clients communicate with to run analytical methods. The Python client is used to drive the CAS component directly using objects and constructs that are familiar to Python programmers.
We assume that you have some knowledge about Python before you approach the topics in this book. However, the book includes an appendix that covers the features of Python that are used in the CAS Python client. We do not assume any knowledge of CAS itself. However, you must have a CAS server that is set up and is running in order to execute the examples in this book.
The chapters in the first part of the book cover topics from installation of Python to the basics of connecting, loading data, and getting simple analyses from CAS. Depending on your familiarity with Python, after reading the “Ten-Minute Guide to Using CAS from Python,” you might feel comfortable enough to jump to the chapters later in the book that are dedicated to statistical methods. However, the chapters in the middle of the book cover more detailed information about working with CAS such as constructing action calls to CAS and processing the results, error handling, managing your data in CAS, and using object interfaces to CAS actions and CAS data tables. Finally, the last chapter about advanced topics covers features and workflows that you might want to take advantage of when you are more experienced with the Python client.
This book covers topics that are useful to complete beginners as well as to experienced CAS users. Its examples extend from creating connections to CAS to simple statistics and machine learning. The book is also useful as a desktop reference.
Is This Book for You?
If you are using the SAS Viya platform in your work and you want to access analytics from SAS Cloud Analytic Services (CAS) using Python, then this book is a great starting point. You’ll learn about general CAS workflows, as well as the Python client that is used to communicate with CAS.
What Are the Prerequisites for This Book?
Some Python experience is definitely helpful while reading this book. If you do not know Python, there is an appendix that gives a crash course in learning Python. There are also a multitude of resources on the Internet for learning Python. The later chapters in the book cover data analysis and modeling topics. Although the examples provide step-by-step code walk-throughs, some training about these topics beforehand is helpful.
Scope of This Book
This book covers the installation and usage of the Python client for use with CAS. It does not cover the installation, configuration, and maintenance of CAS itself.
What Should You Know about the Examples?
This book includes tutorials for you to follow to gain “hands-on” experience with SAS.
Software Used to Develop the Book's Content
This book was written using version 1.0.0 of the SAS Scripting Wrapper for Analytics Transfer (SWAT) package for Python. SAS Viya 3.1 was used. Various Python resources and packages were used as well. SWAT works with many versions of these packages. The URLs of SWAT and other resources are shown as follows:
SAS Viya www.sas.com/en_us/software/viya.html
SAS Scripting Wrapper for Analytics Transfer (SWAT) – Python client to CAS github.com/sassoftware/python-swat (GitHub repository) sassoftware.github.io/python-swat/ (documentation)
