Scrape trending video information from YouTube
FollowThe second most popular search engine in the world is YouTube, directly behind Google. A large number of videos available on YouTube – and their associated data, and comments can be really valuable.
Octoparse can scrape Youtube easily with pre-built templates. You may want to check it out here: Task Templates. Just enter a keyword/URL to get data extracted in minutes!
In this tutorial, we are going to show you how to scrape the trending video information from Youtube in only 3 steps with the Octoparse auto-detection feature.
Here is the Youtube trending video link that we will be using it as an example.
https://www.youtube.com/feed/trending?gl=US
Here are the steps in this tutorial [Download task file here
]
- "Go To Web Page" - open the target website
- Auto-detect web page data - create a workflow
- Run your task - get data you want
1) "Go To Web Page" - open the target website
- Create your task by inputting the URL in the search box on the homepage and click the start button nearby to move on
2) Auto-detect web page data - create a workflow
- Click "Auto-detect web page data" and wait for it to complete
We need to check the data selected with the auto-detection.
- Go to "Data preview" to see if you're okay with the current data output
- You can delete unnecessary data fields directly by clicking the icon
- You can also modify the data field names here directly by clicking the icon
- You can delete unnecessary data fields directly by clicking the icon
- Click "Edit" under the "Add a page scroll" to set up to scroll for one screen, the scroll 20 times, and wait for 1s for every scroll
- Click "Create workflow"
3) Run your task - get data you want
- Click"Save"
- Click "Run" on the upper left side
- Select "Run on your device" to run the task on your computer, or select "Run in the Cloud" to run the task in the Cloud (for premium users only)
Here is the sample data.
Tutorial en español: Scrapear información de vídeos de moda de YouTube
También puedes leer más artículos de web scraping en el sitio web oficial
Author: Fergus
Editor: Yina
