How to Scrape SoundCloud Website (Step-by-Step Guide)?
SoundCloud is a massive music-sharing platform where artists upload songs, podcasts, and playlists. For researchers, marketers, or developers, scraping SoundCloud can provide valuable data like track names, artist info, play counts, likes, and comments.
In this guide, we’ll walk through how to scrape SoundCloud using Python step-by-step — no advanced coding required!
🧩 Step 1: Understand SoundCloud’s Structure
Before scraping, explore the website manually.
- Go to https://soundcloud.com
- Search for any artist or song (e.g., “lofi beats”)
- Open Developer Tools → Network tab → XHR to inspect data requests.
You’ll notice SoundCloud loads much of its data dynamically using an API endpoint.
🖼️ Image 1: Developer Tools showing SoundCloud network requests and JSON data.
🧠 Step 2: Identify SoundCloud’s Public API
SoundCloud provides a public API endpoint (although semi-restricted). You can access data through URLs like:
https://api-v2.soundcloud.com/search/tracks?q=lofi&client_id=YOUR_CLIENT_IDReplace YOUR_CLIENT_ID with a valid SoundCloud client ID. You can extract one by inspecting network requests or registering for API access at
👉 https://developers.soundcloud.com/
🖼️ Image 2: Example JSON response with track details like title, username, play count.
⚙️ Step 3: Install Python Libraries
Use Python for scraping. Install the following:
pip install requests pandas beautifulsoup4💻 Step 4: Write the Scraper Code
Here’s an example script:
import requests
import pandas as pdquery = "lofi beats"
client_id = "YOUR_CLIENT_ID"
url = f"https://api-v2.soundcloud.com/search/tracks?q={query}&client_id={client_id}"response = requests.get(url)
data = response.json()tracks = []
for track in data['collection']:
tracks.append({
"Title": track['title'],
"Artist": track['user']['username'],
"Plays": track.get('playback_count', 0),
"Likes": track.get('likes_count', 0),
"URL": track['permalink_url']
})df = pd.DataFrame(tracks)
df.to_csv("soundcloud_tracks.csv", index=False)
print("Scraping completed! Data saved to soundcloud_tracks.csv")
🖼️ Image 3: Python console showing track data being printed successfully.
📊 Step 5: Analyze and Use the Data
After scraping, open soundcloud_tracks.csv in Excel or any data tool. You’ll find:
- Track names
- Artist usernames
- Play and like counts
- URLs to each track
You can use this data for music trend analysis, content recommendation, or artist comparison.
🖼️ Image 4: Screenshot of a CSV file with scraped SoundCloud data.
⚠️ Step 6: Follow Legal and Ethical Guidelines
Always scrape responsibly:
- Respect SoundCloud’s Terms of Service.
- Avoid overloading their servers (use delays or API pagination).
- Use scraped data for research or fair-use purposes only.
✅ Conclusion
Scraping SoundCloud is a great way to gather insights about music trends, artist popularity, or playlist performance. With the SoundCloud public API, Webscraping HQ you can collect structured data efficiently — no HTML parsing headaches!
Tools Used: Python, Requests, Pandas
Output: CSV file with track information
By combining SoundCloud’s API with Python automation, you can turn public track data into valuable analytics for music research, marketing, or personal projects.
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