Developing IBM Streams Applications with Python (Version 1.6)

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Python is a popular language with a large and comprehensive standard library as well as many third-party libraries.

The IBM Streams Python Application API enables you to create streaming analytics applications in Python. The API is open source from the streamsx.topology project on GitHub.

You can use the Python Application API to:

  • Define the structure of a streaming application by using Python.
  • Pass Python objects as tuples on a stream.
  • Define how streaming data is processed in a modular, scalable, and stateful manner.
  • Specify the mode in which you want the streaming application to run.

You can run a streaming application in the following modes:

  • In a Streaming Analytics service running on IBM Bluemix (STREAMING_ANALYTICS_SERVICE). In this mode, the application is run in the cloud in a Streaming Analytics service. The Streaming Analytics service is built on IBM Streams technology. You don’t need a local version of IBM Streams to build Python applications for the service.
  • As a Streams distributed application (DISTRIBUTED). When running in this mode, the application is deployed automatically on your local IBM Streams instance.
  • As a Streams Application Bundle file (BUNDLE). When running in this mode, the application produces a Streams Application Bundle (SAB) file that you can then deploy on your IBM Streams instance or Streaming Analytics service instance by using the streamtool submitjob command or by using the application console.
  • As a stand-alone application (STANDALONE). When running in this mode, the application produces a SAB file, but rather than submitting the SAB file to an instance, the bundle is executed. The bundle runs within a single process and can be terminated with Ctrl-C interrupts.

To get started with the Python Application API, follow the tutorials in this guide to create a sample application that reads data from a temperature sensor and prints the output to the screen.

  • One tutorial creates the application in your local Python environment so that the application runs in the IBM Streaming Analytics service and doesn’t require a local installation of IBM Streams.
  • The other tutorial creates the same application that runs in stand-alone mode and requires a local installation of IBM Streams.

You can find the reference documentation for the Python Application API at:

##Terminology## If you’re new to IBM Streams and want to learn more about the terms in this guide, see the IBM Streams glossary in IBM Knowledge Center.