ICP4D Updates for Python development guide

Developing IBM Streams Applications with Python (Versions 1.6+)

Proposed additions in bold

IBM Streams Python Support

1. Installing Python APIs
2. Developing for the IBM Streaming Analytics service
   • Developing for ICP4Data
3. Developing with an IBM Streams installation
4. Common Streams operations
   • 4.1 Connecting to known data sources
   • 4.x Aggregation
     • Creating a window using last() or batch()
     • Simple aggregation using Window.aggregate (use pandas)
     • Using Aggregate from streamsx.standard
       • Partitioned windows
   • 4.x Connecting to Watson Machine learning/IoT
   • 4.x Using views
     • Using views in a notebook
   • 4.x Scoring a model in Python
   • 4.x Saving credentials in app configs - a best practice to make code reusable
5. API features: User-defined parallelism Improving performance
   • UDP (parallel fns)
   • Reduce latency using low_latency
   • Using isolate
   • resource tags?
   • 5.1 API features: Fault tolerance (consistent regions)
6. The Python REST API
7. Using SPL Operators in Python
8. Metrics/Logging