ShortPixel

ShortPixel is an image optimizer that improves website performance by resizing, compressing and serving images from CDN. Optimized images are smaller and visually similar with the original images.

Integrate the ShortPixel API with the Python API

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

The ShortPixel API is a powerful tool for optimizing images and PDFs to improve website load times and performance without sacrificing quality. With the ShortPixel API on Pipedream, you can build automated workflows that trigger image optimization processes, handle optimized data, and integrate this functionality with other apps. Pipedream's serverless platform allows for creating scalable and maintenance-free workflows, turning manual image optimization into automated, seamless operations.

Connect ShortPixel

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    shortpixel: {
      type: "app",
      app: "shortpixel",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `http://api.shortpixel.com/v2/api-status.php`,
      params: {
        key: `${this.shortpixel.$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}}