Beekeeper
Beekeeper’s mobile platform is the single point of contact for your frontline workforce. We bring communications and tools together to increase productivity, agility, and safety.
Integrate the Beekeeper API with the Python API
Setup the Beekeeper API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Beekeeper and Python remarkably fast. Free for developers.
Popular Beekeeper 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 Beekeeper#
The Beekeeper API enables seamless integration of its workplace communications platform with other business tools and systems, enhancing team collaboration and operational efficiency. By leveraging the Beekeeper API on Pipedream, you can automate the flow of information between Beekeeper and various applications, trigger actions based on messages or alerts, and synchronize data across your organization's tools. Pipedream's serverless architecture simplifies the process of setting up these automations without the need for dedicated infrastructure.
Connect Beekeeper#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
beekeeper: {
type: "app",
app: "beekeeper",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.beekeeper.$auth.subdomain}.beekeeper.io/api/2/config`,
headers: {
Authorization: `Bearer ${this.beekeeper.$auth.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}}