Headless Testing

Headless Testing with Puppeteer and Playwright in the Cloud

Integrate the Headless Testing API with the Python API

Setup the Headless Testing API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Headless Testing 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.

 
Try it

Overview of Headless Testing

The Headless Testing API unlocks the power of automated browser tasks, enabling developers to run end-to-end tests in a headless Chrome environment. This service is crucial for continuous integration pipelines, allowing for the execution of scripts that verify the functionality and performance of web applications without the need for a graphical user interface. With Pipedream, you can connect the Headless Testing API to a myriad of other services, triggering automated tests based on specific events, storing results, and even notifying team members about test outcomes.

Connect Headless Testing

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    headless_testing: {
      type: "app",
      app: "headless_testing",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.headlesstesting.com/api/v1/user`,
      params: {
        token: `${this.headless_testing.$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}}