Integrate the Evernote API with the Python API

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

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Popular Ways to Connect Evernote with Python#

Run Python Code with Python API on New Note Created from Evernote API

Evernote + Python

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Run Python Code with Python API on New Notebook Created from Evernote API

Evernote + Python

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Run Python Code with Python API on New Tag Created from Evernote API

Evernote + Python

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Popular Evernote and Python Triggers#

New Note Created from the Evernote API

Emit new event when a note is created in Evernote.

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New Notebook Created from the Evernote API

Emit new event when a notebook is created in Evernote.

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New Tag Created from the Evernote API

Emit new event when a new tag is created in Evernote. Useful for tracking new organizational labels.

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Popular Evernote and Python Actions#

Create Note with the Evernote API

Creates a new note in Evernote. 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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Create Notebook with the Evernote API

Creates a new notebook in Evernote. See the documentation

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Update Note with the Evernote API

Updates an existing note in Evernote. See the documentation

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Connect Evernote#

import { Client } from 'evernote';

export default defineComponent({
  props: {
    evernote: {
      type: "app",
      app: "evernote",
    }
  },
  async run({ steps, $ }) {
    var developerToken = this.evernote.$auth.developer_token;
    var client = new Client({ token: developerToken, sandbox: false });
    var noteStore = await client.getNoteStore();
    return await noteStore.listNotebooks();
  },
})

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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