15Five
15Five is a human-centered performance management platform that creates effective managers, highly engaged employees, and top-performing organizations.
Integrate the 15Five API with the Python API
Setup the 15Five API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate 15Five and Python remarkably fast. Free for developers.
Popular 15Five and Python Triggers#
Emit new event for each new 1-on-1 created. See the documentation
Emit new event for each new high five received. See the documentation
Popular 15Five 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 15Five#
The 15Five API grants access to a performance management platform designed to help employees grow and achieve their goals. With Pipedream, you can leverage this API to automate feedback collection, synchronize performance data across various systems, and trigger actions based on employee responses. By interconnecting 15Five with other apps, you can streamline HR processes, enhance employee engagement strategies, and maintain a pulse on organizational health.
Connect 15Five#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
f15five: {
type: "app",
app: "f15five",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://my.15five.com/api/public/user/`,
headers: {
"Authorization": `${this.f15five.$auth.api_key}`,
},
})
},
})
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}}