Integrate the TurboHire API with the Python API

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

Start for free — no credit card required

Watch a demo

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Popular TurboHire 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.

Try it

Overview of TurboHire#

TurboHire is a talent acquisition platform that streamlines the hiring process using automation and AI. With its API, you can enrich candidate profiles, automate communication, and trigger actions based on recruitment stages. On Pipedream, you can leverage TurboHire’s API to create powerful automations by connecting it to a multitude of services, thus enhancing the hiring workflow, maintaining candidate databases, and ensuring timely interactions.

Connect TurboHire#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    turbohire: {
      type: "app",
      app: "turbohire",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.turbohire.co/api/jobs/:job-id`,
      headers: {
        "X-Api-Key": `${this.turbohire.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      params: {
        "job-id": `{{Job-ID}}`,
      },
    })
  },
})

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}}

Start for free — no credit card required

Watch a demo