Integrate the Amazing Marvin API with the Python API

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

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Popular Amazing Marvin 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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Overview of Amazing Marvin#

The Amazing Marvin API lets you tap into your task management in a powerful way, enabling you to automate actions, fetch data for analysis, and sync with other apps. With Pipedream, these capabilities are amplified. You can create serverless workflows that interact with the Marvin tasks and projects, respond to events, and connect with countless other services to streamline your productivity systems. Whether you're looking to automatically schedule tasks, export your day's activities to other platforms, or trigger notifications based on task updates, Pipedream's integration makes it all possible without writing extensive code.

Connect Amazing Marvin#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    amazing_marvin: {
      type: "app",
      app: "amazing_marvin",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://serv.amazingmarvin.com/api/me`,
      headers: {
        "X-API-Token": `${this.amazing_marvin.$auth.api_token}`,
      },
    })
  },
})

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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