Microsoft OneDrive lets you store your personal files in one place, share them with others, and get to them from any device.
Emit new event when a new file is added to a specific drive in OneDrive
Emit an event when a new file is added to a specific directory tree in a OneDrive drive
Emit an event when a new file of a specific type is created under a directory tree in a OneDrive drive
Emit new event when a new folder is created in a OneDrive drive
Emit an event when a new folder is created under a directory tree in a OneDrive drive
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Create a sharing link for a DriveItem. See the documentation
Download a file stored in OneDrive. See the documentation
Retrieve a table from an Excel spreadsheet stored in OneDrive See the documentation
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.
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}`,
},
})
},
})
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:
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}}