Breezy HR
Breezy is a simple, collaborative recruiting platform designed to help you create, publish and advertise your open jobs, manage and organize your candidates and streamline all of your internal team and external candidate communication.
Integrate the Breezy HR API with the Python API
Setup the Breezy HR API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Breezy HR and Python remarkably fast. Free for developers.
Popular Breezy HR and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Breezy HR#
Breezy HR's API unlocks the power to streamline recruitment processes by automating routine tasks and integrating with a multitude of other apps. With this API on Pipedream, you can craft custom workflows to manage candidates, coordinate interview schedules, trigger communications, and track the hiring pipeline effortlessly. By harnessing data from Breezy HR, you can enhance efficiency, reduce manual errors, and keep the entire hiring team on the same page.
Connect Breezy HR#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
breezy_hr: {
type: "app",
app: "breezy_hr",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.breezy.hr/v3/user`,
headers: {
"Content-Type": `application/json`,
"Authorization": `${this.breezy_hr.$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}}