Integrate the Qualetics API with the Python API

Setup the Qualetics API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Qualetics and Python remarkably fast. Free for developers.

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Popular Qualetics and Python Actions#

Run Data Machine with the Qualetics API

Initiates a previously designed data machine within Qualetics, executing the specific analytical tasks it was built for. See the documentation

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Send Data with the Qualetics API

Send an event with data to the system. See the documentation

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Overview of Qualetics#

The Qualetics API provides data intelligence as a service, allowing you to transform your data into actionable insights. With this API, you can perform advanced data analysis, predict trends, and generate reports to make informed decisions swiftly. On Pipedream, Qualetics can be integrated into workflows to automate data analysis, connect with other services for enriched data operations, and trigger actions based on the insights derived.

Connect Qualetics#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    qualetics: {
      type: "app",
      app: "qualetics",
    }
  },
  async run({steps, $}) {
    const data = {"actor":{"type":"User","id":"js1234"},"action":{"type":"ButtonClick"},"context":{"type":"Button","name":"Button1"}};//"{{your_data}}";
    //E.g. {"actor":{"type":"User","id":"js1234"},"action":{"type":"ButtonClick"},"context":{"type":"Button","name":"Button1"}}
    return await axios($, {
      method: "post",
      url: `https://mq.qualetics.com/api/sendmessage?client_id=${this.qualetics.$auth.app_prefix}`,
      headers: {
        Authorization: `Bearer ${this.qualetics.$auth.oauth_access_token}`,      
      },
      data,
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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