Spotify Profile Scraper — Spotify | Lagic

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Overview

This tool extracts public data from Spotify user profiles, including follower and following counts, recently played and top artists, and details of public playlists. It's ideal for market research and competitor analysis in the music industry.

This Spotify Profile Scraper is designed for anyone needing to gather public information from Spotify user profiles. Whether you're a music marketer, an artist looking to understand your fanbase, a talent scout, or a researcher, this tool provides structured data to fuel your insights. ### What Data You Get When you provide Spotify profile URLs, the tool goes to work, extracting key details. You'll receive the user's Spotify ID and username, their unique profile URL, and the URL for their avatar image. Crucially, it captures the number of followers a profile has and how many users they are following, offering a glimpse into their network and influence. For deeper understanding, the scraper pulls a list of recently played artists and their top artists by month, which can be configured to fetch up to 50 artists per profile. This artist data is invaluable for understanding listening habits and preferences. ### Public Playlists and Data Availability Optionally, you can choose to include details of public playlists owned by the profile. This includes the playlist name, its unique Spotify ID and URL, a description, an image URL, and the total track count. The output also clearly indicates the availability of data for each profile, specifying whether follower counts, playlists, recently played artists, and top artists were publicly accessible at the time of scraping. This transparency helps you understand the completeness of the data for each profile. ### Reliable Data Extraction To ensure reliable data collection, especially when dealing with multiple profiles, the tool offers proxy configuration options. You can choose between datacenter proxies for cost-effectiveness or residential proxies for higher reliability against bot detection. It also includes settings for maximum request retries and a request handler timeout, making the scraping process more resilient to network issues or temporary blocks. This means you can focus on analyzing the data, not troubleshooting extraction failures.