YouTube (Analytics API)

The YouTube Reporting and YouTube Analytics APIs let you retrieve YouTube Analytics data to automate complex reporting tasks, build custom dashboards, and much more.

Integrate the YouTube (Analytics API) API with the Python API

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

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

Overview of YouTube (Analytics API)

The YouTube Analytics API enables you to pull complex, insightful data regarding your YouTube channel's performance, audience demographics, and engagement metrics. It's a goldmine for content creators looking to refine their content strategy based on solid data. Using Pipedream, you can automate the extraction of these analytics, set up real-time alerts, or synchronize this data with other tools for enhanced reporting and decision-making.

Connect YouTube (Analytics API)

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    youtube_analytics_api: {
      type: "app",
      app: "youtube_analytics_api",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.googleapis.com/oauth2/v1/userinfo`,
      headers: {
        Authorization: `Bearer ${this.youtube_analytics_api.$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

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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}}