With the YouTube Data API, you can add a variety of YouTube features to your application. Use the API to upload videos, manage playlists and subscriptions, update channel settings, and more.
Emit new event for each new comment or reply posted to a Youtube channel (or any of its videos).
Emit new event for each new comment or reply posted to a Youtube video.
Emit new event for each new Youtube video liked by the authenticated user.
Emit new event for each new Youtube subscriber to user Channel.
Emit new event for each new subscription from authenticated user.
Adds resources to a playlist. See the docs for more information
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Returns statistics from my YouTube Channel or by id. See the docs for more information
Creates a new top-level comment in a video. See the docs for more information
Creates a playlist. See the docs for more information
The YouTube Data API lets you incorporate functions normally executed on the YouTube website into your own website or application. You can perform operations like searching for videos, retrieving channel data, and managing playlists. When integrated with Pipedream's serverless platform, this API can be part of automations that react to events, synchronize YouTube data with other services, or generate custom reports.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
youtube_data_api: {
type: "app",
app: "youtube_data_api",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://www.googleapis.com/oauth2/v1/userinfo`,
headers: {
Authorization: `Bearer ${this.youtube_data_api.$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}}