Build a streaming app using a Python API
Use a Jupyter Notebook with streamsx to build an app that processes data with mouse-click events from users browsing a website
In this developer code pattern, we will create a Jupyter Notebook that contains Python code that uses the streamsx API to build a streaming application. The app will be built using IBM Streams on IBM Cloud Pak® for Data.
The Python API streamsx allows you to build streaming apps that use IBM Streams, a service that runs on IBM Cloud Pak for Data. The IBM Cloud Pak for Data platform provides additional support, such as integration with multiple data sources, built-in analytics, Jupyter Notebooks, and machine learning. Scalability is increased by distributing processes across multiple computing resources.
In this code pattern, we will build a streaming application by creating a Jupyter Notebook using the streamsx Python API. The app will process a stream of data containing mouse-click events from users as they browse a shopping website.
- User runs Jupyter Notebook in IBM Cloud Pak for Data.
- Clickstream data is inserted into streaming app.
- Streaming app using the streamsx Python API is executed in the IBM Streams service.
- User accesses IBM Streams service job to view events.
Find the detailed steps for this pattern in the README file. The steps will show you how to:
- Clone the repo.
- Add IBM Streams service to IBM Cloud Pak for Data.
- Create a new project in IBM Cloud Pak for Data.
- Add a data asset to your project.
- Add a notebook to your project.
- Run the notebook.
- View job status in IBM Streams service panel.
- Cancel the job.