SageWorks REPL
Visibility and Control
The SageWorks REPL provides AWS ML Pipeline visibility just like the SageWorks Dashboard but also provides control over the creation, modification, and deletion of artifacts through the Python API.
The SageWorks REPL is a customized iPython shell. It provides tailored functionality for easy interaction with SageWorks objects and since it's based on iPython developers will feel right at home using autocomplete, history, help, etc. Both easy and powerful, the SageWorks REPL puts control of AWS ML Pipelines at your fingertips.
Installation
pip install sageworks
Usage
Just type sageworks
at the command line and the SageWorks shell will spin up and provide a command view of your AWS Machine Learning Pipelines.
At startup the SageWorks shell, will connect to your AWS Account and create a summary of the Machine Learning artifacts currently residing on the account.
Available Commands:
- status
- config
- incoming_data
- glue_jobs
- data_sources
- feature_sets
- models
- endpoints
- aws_refresh
- and more...
All of the API Classes are auto-loaded, so drilling down on an individual artifact is easy. The same Python API is provided so if you want additional info on a model, for instance, simply create a model object and use any of the documented API methods.
Additional Resources
- Setting up SageWorks on your AWS Account: AWS Setup
- Using SageWorks for ML Pipelines: SageWorks API Classes
- SageWorks Core Classes: Core Classes
- Consulting Available: SuperCowPowers LLC