imgix

imgix is the leading platform for end-to-end visual media processing. imgix reduces development hassles, saves storage costs, and improves web performance.

Integrate the imgix API with the Python API

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

The imgix API offers dynamic image processing and optimization. You can manipulate images on-the-fly by changing query parameters in the image URL, enabling a myriad of transformations like resizing, cropping, adjusting quality, format conversion, and applying filters. Integrating imgix with Pipedream allows you to automate workflows that involve image manipulation, optimization for different devices and contexts, and the dynamic delivery of images.

Connect imgix

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    imgix: {
      type: "app",
      app: "imgix",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.imgix.com/api/v1/sources`,
      headers: {
        Authorization: `Bearer ${this.imgix.$auth.api_key}`,
        "Accept": `application/json`,
        "Content-Type": `application/vnd.api+json`,
      },
    })
  },
})

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}}