With Google Calendar, you can quickly schedule meetings and events and get reminders about upcoming activities, so you always know what’s next.
Emit new event based on a time interval before an upcoming event in the calendar. This source uses Pipedream's Task Scheduler. See the documentation for more information and instructions for connecting your Pipedream account.
Emit new event when a Google Calendar events is created or updated (does not emit cancelled events)
Emit new event when a Google Calendar event is created that matches a search
Emit new event when a Google Calendar event is cancelled or deleted
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Add attendees to an existing event. See the documentation
Create a quick event to the Google Calendar. See the documentation
Create an event in a Google Calendar. See the documentation
Delete an event from a Google Calendar. See the documentation
The Google Calendar API lets you dip into the powerhouse of scheduling, allowing for the reading, creation, and manipulation of events and calendars directly from your applications. Through Pipedream, you can seamlessly integrate Google Calendar into a myriad of workflows, automating event management, syncing with other services, setting up custom reminders, or even collating data for reporting. The key here is to streamline your calendar-related processes, ensuring that your time management is as efficient and automated as possible.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_calendar: {
type: "app",
app: "google_calendar",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/calendar/v3/users/me/settings`,
headers: {
Authorization: `Bearer ${this.google_calendar.$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}}