Integrate the Castmagic API with the Python API

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

Popular Castmagic and Python Actions#

Get Transcription with the Castmagic API

Retrieves details for a transcript given an identifier. 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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Submit Transcription Request with the Castmagic API

Submits a request to transcribe from a URL. See the documentation

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Overview of Castmagic#

The Castmagic API allows you to control and automate the casting of media to various devices, such as Chromecast and smart TVs. It's designed for developers who want to build custom casting solutions without the hassle of dealing with low-level protocol details. Through Pipedream, you can integrate Castmagic with a myriad of services and triggers, creating workflows that respond to events like new content releases, user interactions, or scheduled routines. You can leverage Pipedream's serverless platform to create, run, and maintain these automations with ease.

Connect Castmagic#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    castmagic: {
      type: "app",
      app: "castmagic",
    }
  },
  async run({steps, $}) {
    const data = {
      "url": `https://www.youtube.com/watch?v=YuV5ATYcY_I`,
    }
    return await axios($, {
      method: "post",
      url: `https://app.castmagic.io/v1/transcripts`,
      headers: {
        Authorization: `Bearer ${this.castmagic.$auth.secret_key}`,
      },
      data,
    })
  },
})

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}}