What do you want to automate
with Greenhouse and Python?
Prompt, edit and deploy AI agents that connect to Greenhouse, Python and 2,500+ other apps in seconds.
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Popular Greenhouse and Python Triggers#
Emit new event when a candidate submits a new application.
Emit new event when a candidate's application or status changes.
Emit new event when a new interview is scheduled within a specific time period.
Popular Greenhouse and Python Actions#
Adds an attachment to a specific candidate or prospect. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Creates a new candidate entry in Greenhouse. See the documentation
Creates a new prospect entry in Greenhouse. See the documentation
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}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies