Shadertoy

Build and Share your best shaders with the world and get Inspired!

Integrate the Shadertoy API with the Python API

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

Access Shader Assets with the Shadertoy API

Accesses an asset from source. 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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Get Shader with the Shadertoy API

Returns a specific shader based on an ID. See the documentation

 
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List Shaders with the Shadertoy API

Returns a list of all shaders. See the documentation

 
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Search Shaders with the Shadertoy API

Returns an array of shader IDs based on the query string. See the documentation

 
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Overview of Shadertoy

The Shadertoy API opens a window to a universe of visual creations by providing programmatic access to a wealth of shaders created by the Shadertoy community. These shaders are snippets of GLSL code that produce stunning graphics and visual effects. In Pipedream, you can leverage this API to trigger workflows that interact with these shaders, such as retrieving shader information, displaying shader visuals, or even monitoring the latest creations. By combining Shadertoy API with Pipedream's capability to connect to numerous other services, your creative and technical projects can flourish with dynamic, visually rich content.

Connect Shadertoy

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    shadertoy: {
      type: "app",
      app: "shadertoy",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: ` https://www.shadertoy.com/api/v1/shaders/query/test`,
      params: {
        key: `${this.shadertoy.$auth.app_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}}