Integrate the Daffy API with the Python API

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

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Popular Ways to Connect Daffy with Python#

Run Python Code with Python API on New Donation Created from Daffy API

Daffy + Python

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Popular Daffy and Python Triggers#

New Donation Created from the Daffy API

Emit new event when a donation is created.

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Popular Daffy and Python Actions#

Create Donation with the Daffy API

Create a new donation. 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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Overview of Daffy#

The Daffy API lets you drive charitable giving through its platform. With Pipedream, you can automate donations, manage donor data, and integrate charitable actions within your existing workflows. You can trigger actions based on diverse events, like donations or new user registrations, and connect with other apps to streamline and scale your impact.

Connect Daffy#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    daffy: {
      type: "app",
      app: "daffy",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://public.daffy.org/v1/users/me`,
      headers: {
        "X-Api-Key": `${this.daffy.$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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