Integrate the Emelia API with the Python API

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

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Popular Emelia 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 Emelia#

The Emelia API enables streamlined email campaign management directly from Pipedream. By integrating Emelia with Pipedream, you can automate email sequences, monitor campaign performance, and trigger personalized follow-ups based on recipient actions. The API's functionality allows for the creation of data-driven workflows that can interact with subscriber lists, send out scheduled emails, and provide analytics, all within the scalable environment on Pipedream.

Connect Emelia#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    emelia: {
      type: "app",
      app: "emelia",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://graphql.emelia.io/graphql`,
      headers: {
        "Authorization": `${this.emelia.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      params: {
        query: `query me{
                me{
                      uid
                      name
                      email
                      picture
                  }
                }`,
      },
    })
  },
})

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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