Integrate the Datawaves API with the Python API

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

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Popular Datawaves and Python Actions#

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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Overview of Datawaves#

The Datawaves API offers rich functionality for tracking and analyzing user interactions on websites and applications. With this API, you can capture events, analyze user behavior, and gain insights that drive decision-making for product enhancements and personalized user experiences. On Pipedream, you can harness these capabilities to create automated workflows that respond to data collected by Datawaves in real-time, integrate with other services, and streamline analytics processes.

Connect Datawaves#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    datawaves: {
      type: "app",
      app: "datawaves",
    }
  },
  async run({steps, $}) {
    const data = {
      "id": `123`,
      "product": `iPhone Charger`,
    }
    return await axios($, {
      method: "post",
      url: `https://datawaves.io/api/v1.0/projects/${this.datawaves.$auth.project_id}/events/test`,
      headers: {
        "Authorization": `${this.datawaves.$auth.secret_key}`,
      },
      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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