Overview of SAS pipefitter¶
What is SAS pipefitter?¶
The SAS pipefitter package provides a Python API for developing pipelines for data transformation and model fitting as stages of a repeatable workflow.
The package enables you to work with data in SAS to implement stages such as the following:
- Impute missing values.
- Select and engineer features.
- Fit parameter estimates with decision trees, neural networks, and other machine learning techniques.
- Use hyperparameter tuning to speed model selection.
- Score data and assess models.
Another important feature of pipefitter is that it builds on the abilities of two other Python packages provided by SAS:
- A package that enables data transfer and analysis with SAS Cloud Analytic Services–the centerpiece of the SAS Viya platform–for in-memory analytics.
- A package that enables data transfer and analysis with SAS 9.4–business-proven software for analytics, data manipulation, and visualization.
The pipeline stages, such as estimating parameters with logistic
regression are designed to run identically in SAS 9 though SASPy
or in CAS through SWAT. The pipeline automatically adjusts to run the
analysis where your data is by detecting the data set type.
SASdata objects will run through SASPy, whereas
objects run through SWAT.
See Getting started for examples.
SAS pipefitter is a pure Python package that supports Python 2.7 or 3.4+. However, you must install one or both of the following packages that are used to connect to SAS 9.4 or SAS Viya.
|Package||SAS Platfom||Python Support|
|SASPy 2.x||SAS 9.4 or higher||Python 3.x|
|SWAT v1.1.0+||SAS Viya||Python 2.7 or 3.4+|
Read the package documentation for additional dependencies, supported platforms, and so on.
The most common combination that provides the greatest flexibility is to use Linux with 64-bit Python 3.4+.
Release 1.0.0 of SAS pipefitter represents an early stage of development. This release exploits only a small portion of what is possible with SAS 9.4 and SAS Viya.
For more information, see the following: