Integrate the Airbrake API with the Python API

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

Popular Ways to Connect Airbrake with Python#

Run Python Code with Python API on New Error Occurred from Airbrake API

Airbrake + Python

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Popular Airbrake 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.

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Overview of Airbrake#

The Airbrake API facilitates real-time error monitoring and automatic exception reporting for your web applications, giving you instant insight into issues as they arise. With this API, you can create custom notifications, analyze and aggregate error data, and manage your project's error trends. Leveraging Pipedream's capabilities, you can automate workflows that respond to these errors, connect with other services for enhanced issue resolution, and maintain a smooth operation within your development and production environments.

Connect Airbrake#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    airbrake: {
      type: "app",
      app: "airbrake",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.airbrake.io/api/v4/projects`,
      params: {
        key: `${this.airbrake.$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}}

Airbrake