Apache StreamPipes Python Client
Apache StreamPipes is a self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams. The Apache StreamPipes Python Client is a new library targeted at data scientists, which helps to easily interact with IIoT data streams and run online machine learning models using the integrated function zoo.
Apache StreamPipes meets Python! We are working highly motivated on a Python library to interact with StreamPipes. In this way, we would like to unite the power of StreamPipes to easily connect to and read from different data sources, especially in the IoT domain, and the amazing universe of data analytics libraries in Python.
The development of the Python client has received funding from the AI REGIO project.
A detailed documentation as well as several Python notebook examples are available in the documentation.
It's easy to get started - follow the instructions at https://streampipes.apache.org/docs/docs/python/latest/getting-started/…
When working with industrial data sources, data scientists are often faced with time-consuming data engineering and preprocessing tasks. Apache StreamPipes sits between the IT and OT layer by providing convenient ways to access industrial data from PLCs or other systems and provides a runtime execution layer to quickly deploy data analytics operations on live data streams.
The Python client can be used for data exploration as well as deployment of ML models. For data exploration, various APIs are provided which users can use to access historical or live data which are available in StreamPipes. Data can be directly imported into Pandas data frames for further analysis. In addition, ML models can be deployed using the ingrated Functions feature, which allow to either apply online machine learning models using the integrated River integration, or to apply custom-built models. Functions are registered in StreamPipes and can be managed and monitored right from the user interface.
The development of the Python client has received funding from the AI REGIO project under the European Union Framework Programme for Research and Innovation Horizon 2020.