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StreamPipes is a self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.

Apache StreamPipes for Python 🐍

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.

⚡️ Quickstart

As a quick example, we demonstrate how to set up and configure a StreamPipes client. In addition, we will get the available data lake measures out of StreamPipes.

from streampipes.client import StreamPipesClient
from streampipes.client.config import StreamPipesClientConfig
from streampipes.client.credential_provider import StreamPipesApiKeyCredentials

config = StreamPipesClientConfig(
    credential_provider = StreamPipesApiKeyCredentials(
        username = "",
        api_key = "DEMO-KEY",
    host_address = "localhost",
    https_disabled = True,
    port = 80

client = StreamPipesClient(client_config=config)

# get all available datat lake measures
measures = client.dataLakeMeasureApi.all()

# get amount of retrieved measures

# inspect the data lake measures as pandas dataframe


measure_name timestamp_field ... pipeline_is_running num_event_properties
0 test s0::timestamp ... False 2
[1 rows x 6 columns]

Alternatively, you can provide your credentials via environment variables. Simply define your credential provider as follows:

from streampipes.client.credential_provider import StreamPipesApiKeyCredentials

This requires to set the following environment variables: SP_API_KEY and SP_USERNAME

username is always the username that is used to log in into StreamPipes.

How to get your StreamPipes API key

The api_key can be generated within the UI as demonstrated below:

Howto API Key

Last update: April 3, 2024