Google Analytics
Google Analytics enables you to measure and report on user activity on websites, web and mobile apps, and internet-connected devices.
Integrate the Google Analytics API with the Python API
Setup the Google Analytics API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Google Analytics and Python remarkably fast. Free for developers.
Popular Google Analytics and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Return report metrics based on a start and end date. See the docs here
Returns a customized report of your Google Analytics event data. Reports contain statistics derived from data collected by the Google Analytics tracking code. See the documentation here
Overview of Google Analytics#
The Google Analytics API unlocks the power of your analytics data, enabling automated access to custom reports, real-time statistics, and user behavior analysis. With it, you can extract actionable insights, push data to other platforms, and tailor your business strategy with precision. Leveraging Pipedream's serverless platform, these capabilities can be seamlessly integrated into workflows that trigger actions in other apps, send alerts, or even feed data warehouses for deeper analysis.
Connect Google Analytics#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
google_analytics: {
type: "app",
app: "google_analytics",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.google_analytics.$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#
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}}