Integrate the heedjy API with the Python API

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

Popular Ways to Connect heedjy with Python#

Run Python Code with Python API on New App Published from heedjy API

heedjy + Python

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Popular heedjy 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 heedjy#

The Heedjy API provides functionalities to understand and predict user behavior on digital platforms. With this API integrated into Pipedream, you can automate processes that depend on user data analytics, predict churn, personalize content, or optimize user experiences in real-time. Pipedream's serverless platform allows you to create intricate workflows that can respond to Heedjy's insights, enabling applications to adapt and engage with users more effectively.

Connect heedjy#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    heedjy: {
      type: "app",
      app: "heedjy",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://app.heedjy.com/api/apps?all_versions=false&order_by=name%2B&limit=50&returnCount=false`,
      headers: {
        Authorization: `Bearer ${this.heedjy.$auth.oauth_access_token}`,
      },
    })
  },
})

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}}

heedjy