Microsoft OneDrive

Microsoft OneDrive lets you store your personal files in one place, share them with others, and get to them from any device.

Integrate the Microsoft OneDrive API with the Python API

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

Run Python Code with Python API on New File (Instant) from Microsoft OneDrive API
Microsoft OneDrive + Python
 
Try it
Run Python Code with Python API on New File in Folder (Instant) from Microsoft OneDrive API
Microsoft OneDrive + Python
 
Try it
Run Python Code with Python API on New File of Types in Folder (Instant) from Microsoft OneDrive API
Microsoft OneDrive + Python
 
Try it
Run Python Code with Python API on New Folder (Instant) from Microsoft OneDrive API
Microsoft OneDrive + Python
 
Try it
Run Python Code with Python API on New Folder in Folder (Instant) from Microsoft OneDrive API
Microsoft OneDrive + Python
 
Try it
New File (Instant) from the Microsoft OneDrive API

Emit new event when a new file is added to a specific drive in OneDrive

 
Try it
New File in Folder (Instant) from the Microsoft OneDrive API

Emit an event when a new file is added to a specific directory tree in a OneDrive drive

 
Try it
New File of Types in Folder (Instant) from the Microsoft OneDrive API

Emit an event when a new file of a specific type is created under a directory tree in a OneDrive drive

 
Try it
New Folder (Instant) from the Microsoft OneDrive API

Emit new event when a new folder is created in a OneDrive drive

 
Try it
New Folder in Folder (Instant) from the Microsoft OneDrive API

Emit an event when a new folder is created under a directory tree in a OneDrive drive

 
Try it
Create Folder with the Microsoft OneDrive API

Create a new folder in a drive. See the documentation

 
Try it
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.

 
Try it
Create Link with the Microsoft OneDrive API

Create a sharing link for a DriveItem. See the documentation

 
Try it
Download File with the Microsoft OneDrive API

Download a file stored in OneDrive. See the documentation

 
Try it
Get Table with the Microsoft OneDrive API

Retrieve a table from an Excel spreadsheet stored in OneDrive See the documentation

 
Try it

Overview of Microsoft OneDrive

The Microsoft OneDrive API taps into the robust file storage and management capabilities of OneDrive, allowing for operations like file uploads, retrievals, sharing, and synchronization. Integrating this API into Pipedream workflows lets you automate tasks involving file management, content collaboration, and data backup processes. With OneDrive's API on Pipedream, you can streamline document workflows, trigger actions based on file changes, and connect your file storage to countless other services for enhanced productivity.

Connect Microsoft OneDrive

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    microsoft_onedrive: {
      type: "app",
      app: "microsoft_onedrive",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://graph.microsoft.com/v1.0/me`,
      headers: {
        Authorization: `Bearer ${this.microsoft_onedrive.$auth.oauth_access_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

1
2
3
4
5
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}}