Integrate the HypeAuditor API with the Python API

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

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Popular HypeAuditor 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 HypeAuditor#

The HypeAuditor API provides deep insights into social media account analytics and influencer effectiveness, making it a powerful tool for marketers who want to optimize their influencer campaigns. Using this API, you can access detailed data concerning influencer audience demographics, engagement rates, authenticity, and more. This can aid in identifying the right influencers for your brand, tracking campaign performance, and refining your marketing strategies over time.

Connect HypeAuditor#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    hypeauditor: {
      type: "app",
      app: "hypeauditor",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://hypeauditor.com/api/method/auditor.report/`,
      headers: {
        "x-auth-id": `${this.hypeauditor.$auth.client_id}`,
        "x-auth-token": `${this.hypeauditor.$auth.api_token}`,
        "user-agent": `pipedream/1`,
      },
      params: {
        username: `taylorswift`,
        "v": `2`,
      },
    })
  },
})

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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