Integrate the GTmetrix API with the Python API

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

Popular Ways to Connect GTmetrix with Python#

Run Python Code with Python API on New Test Completed from GTmetrix API

GTmetrix + Python

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Popular GTmetrix and Python Triggers#

New Test Completed from the GTmetrix API

Emit new event when a test is completed in GTMetrix. See the documentation

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Popular GTmetrix and Python Actions#

Get Performance Report with the GTmetrix API

Fetches the most recent performance report for a particular page from GTmetrix. See the documentation

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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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Run Performance Test with the GTmetrix API

Run a performance test on a specified URL using GTmetrix. See the documentation

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Overview of GTmetrix#

The GTmetrix API provides an interface to test the loading speed of your website, offering insights into performance issues and potential optimizations. By integrating this API with Pipedream, you can automate performance monitoring, receive alerts, and combine data with other services for in-depth analysis. For instance, you could trigger a performance report after a site update, log results to a spreadsheet for tracking, or compare your metrics against industry standards.

Connect GTmetrix#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    gtmetrix: {
      type: "app",
      app: "gtmetrix",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://gtmetrix.com/api/2.0/status`,
      auth: {
        username: `${this.gtmetrix.$auth.api_key}`,
        password: ``,
      },
    })
  },
})

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}}