Integrate the Pulsetic API with the Python API

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

Popular Ways to Connect Pulsetic with Python#

Run Python Code with Python API on New Monitor Event from Pulsetic API

Pulsetic + Python

Try it

Popular Pulsetic and Python Triggers#

New Monitor Event from the Pulsetic API

Emit new event when a monitor event occurs.

Try it

Popular Pulsetic and Python Actions#

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.

Try it

Overview of Pulsetic#

Pulsetic API lets you monitor your websites and servers, sending notifications when downtime occurs or performance issues arise. With Pipedream, you can leverage this API to create powerful, automated workflows that respond to Pulsetic events in real-time. For instance, you can automate incident management by connecting Pulsetic to ticketing systems, trigger alerts in communication channels, or log performance data for analysis. Pipedream's zero-management data stores also allow you to keep track of incident history without needing a separate database.

Connect Pulsetic#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    pulsetic: {
      type: "app",
      app: "pulsetic",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.pulsetic.com/api/public/monitors`,
      headers: {
        "Authorization": `${this.pulsetic.$auth.api_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}}