Integrate the Transistor.fm API with the Python API

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

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Popular Ways to Connect Transistor.fm with Python#

Run Python Code with Python API on New Event from Transistor.fm API

Transistor.fm + Python

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Popular Transistor.fm and Python Triggers#

New Event from the Transistor.fm API

Emit new event when the desired event happens

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Popular Transistor.fm and Python Actions#

Create subscriber with the Transistor.fm API

Create a subscriber. See the docs here

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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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Overview of Transistor.fm#

Transistor.fm is a platform offering podcast hosting and analytics services. With its API, you can automate the upload and management of podcast episodes, access detailed analytics, and manage users. When interfaced with Pipedream, Transistor.fm's API enables the creation of tailored, serverless workflows that can streamline your podcasting process, engage your audience effectively, and integrate with your digital ecosystem, from social media to email marketing platforms.

Connect Transistor.fm#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    transistor_fm: {
      type: "app",
      app: "transistor_fm",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.transistor.fm/v1`,
      headers: {
        "x-api-key": `${this.transistor_fm.$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#

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}}

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