Use Google Sheets to create and edit online spreadsheets. Get insights together with secure sharing in real-time and from any device.
Emit new events each time a row or rows are added to the bottom of a spreadsheet. To use this source with a spreadsheet in a Shared Drive, use the New Row Added (Shared Drive, Instant) source instead.
Emit new events each time a row or rows are added to the bottom of a spreadsheet in a shared drive
Emit new event each time a row or cell is updated in a spreadsheet. To use this source with a spreadsheet in a Shared Drive, use the New Updates (Shared Drive, Instant) source instead.
Emit new event each time a row or cell is updated in a spreadsheet in a shared drive
Emit new event each time a new worksheet is created in a spreadsheet. To use this source with a spreadsheet in a Shared Drive, use the New Worksheet (Shared Drive, Instant) source instead.
The Google Sheets API allows for the creation, reading, updating, and deletion of data within Google Sheets, enabling a robust platform for spreadsheet management and data manipulation. Through Pipedream, you can craft serverless workflows that respond to various triggers, such as webhook events, emails, or scheduled times, to interact with Google Sheets. This synergy can automate reporting, synchronize data across applications, manage inventory, track leads in a CRM, or even conduct survey analysis by updating and retrieving sheet data on the fly.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_sheets: {
type: "app",
app: "google_sheets",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.google_sheets.$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}}