Integrate the Maestra API with the Python API

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

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Popular Ways to Connect Maestra with Python#

Run Python Code with Python API on New File Added from Maestra API

Maestra + Python

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Popular Maestra and Python Triggers#

New File Added from the Maestra API

Emit new event when a new file is added to a project in Maestra. See the documentation

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Popular Maestra and Python Actions#

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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Translate File with the Maestra API

Translates an existing file in the Maestra system. See the documentation

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Upload File with the Maestra API

Initiates a new file upload to Maestra. See the documentation

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Overview of Maestra#

The Maestra API lets you automate the transcription, captioning, and voiceover of videos and audios, crucial for creating accessible and localized content. With Pipedream, you can build workflows that trigger on various events to streamline media processing, integrate with other services, and manage content efficiently. Pipedream's serverless platform offers a code-free way to connect the Maestra API with hundreds of other apps, enabling you to create custom automation without the heavy lifting.

Connect Maestra#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    maestra: {
      type: "app",
      app: "maestra",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://${this.maestra.$auth.base_url}/api/getCredits`,
      headers: {
        "apiKey": `${this.maestra.$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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