Opsgenie

Opsgenie is a modern incident management platform for operating always-on services, empowering Dev and Ops teams to plan for service disruptions and stay in control during incidents.

Integrate the Opsgenie API with the Python API

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

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.

 
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Overview of Opsgenie

The Opsgenie API enables automated incident management and alerting to streamline response actions. It allows you to create, update, and manage alerts, as well as configure and query users, schedules, and on-call rotations. Integrating Opsgenie with Pipedream opens up possibilities for orchestrating complex workflows, such as incident triggering from various sources, auto-update of tickets, synchronization with other tools, and much more, all in a serverless environment.

Connect Opsgenie

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    opsgenie: {
      type: "app",
      app: "opsgenie",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.opsgenie.$auth.instance_region}.opsgenie.com/v2/account`,
      headers: {
        "Authorization": `GenieKey ${this.opsgenie.$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

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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}}