Integrate the Greenhouse API with the Python API

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

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Popular Ways to Connect Greenhouse with Python#

Run Python Code with Python API on New Candidate Application from Greenhouse API

Greenhouse + Python

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Run Python Code with Python API on New Candidate Watching from Greenhouse API

Greenhouse + Python

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Run Python Code with Python API on New Scheduled Interview from Greenhouse API

Greenhouse + Python

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Popular Greenhouse and Python Triggers#

New Candidate Application from the Greenhouse API

Emit new event when a candidate submits a new application.

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New Candidate Watching from the Greenhouse API

Emit new event when a candidate's application or status changes.

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New Scheduled Interview from the Greenhouse API

Emit new event when a new interview is scheduled within a specific time period.

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Popular Greenhouse and Python Actions#

Add Attachment to Candidate with the Greenhouse API

Adds an attachment to a specific candidate or prospect. 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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Create Candidate with the Greenhouse API

Creates a new candidate entry in Greenhouse. See the documentation

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Create Prospect with the Greenhouse API

Creates a new prospect entry in Greenhouse. See the documentation

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Overview of Greenhouse#

The Greenhouse API offers a powerful suite of tools for automating and enhancing the recruitment process. It allows you to programmatically access candidate information, job listings, scorecards, and scheduling details, which opens a myriad of possibilities for streamlining recruiting workflows. By leveraging the Greenhouse API on Pipedream, you can automate repetitive tasks, integrate with other HR systems, analyze recruitment data, and build custom event-driven workflows to improve the efficiency and effectiveness of your hiring process.

Connect Greenhouse#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    greenhouse: {
      type: "app",
      app: "greenhouse",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://harvest.greenhouse.io/v1/user_roles`,
      auth: {
        username: `${this.greenhouse.$auth.api_key}`,
        password: ``,
      },
    })
  },
})

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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