Creating a Nostalgic Spotify Playlist with Billboard Hot 100 Data
Ever wondered what the top hits were on a specific day in the past? In this project, we dive into the Billboard Hot 100 to create a nostalgic Spotify playlist of the top 100 songs from a chosen date. Using Python and several powerful libraries, we scrape Billboard data and integrate it with Spotify to generate a personalized playlist that takes you back in time.
Project Overview
This project involves scraping the Billboard Hot 100 website to gather the top songs from a specific date, then using the Spotipy library to interact with the Spotify API and create a playlist. By combining web scraping and Spotify's API, we can automatically generate a playlist that reflects the music trends from any given day.
Key Features
Billboard Data Scraping: Fetch the top 100 songs from Billboard's Hot 100 chart for a specified date.
Spotify Integration: Authenticate with Spotify and create a new playlist with the top tracks from the selected date.
Error Handling: Manage errors during track searches to ensure a smooth user experience.
Step-by-Step Breakdown
1. Set Up Environment
Use environment variables to manage sensitive data and API keys securely. This includes configuring Spotipy for Spotify authentication.
2. Scrape Billboard Data
Request and parse the Billboard Hot 100 page for the specified date to extract song titles using BeautifulSoup.
3. Authenticate with Spotify
Authenticate with Spotify using Spotipy, and retrieve the user ID for playlist creation.
4. Search and Create Playlist
Search for each song on Spotify, gather their URIs, and create a new playlist with the retrieved tracks. Handle any search errors gracefully.
Python Skills Utilized
Web Scraping: Extracting and processing data from web pages using BeautifulSoup.
API Integration: Interacting with Spotify's API using Spotipy to manage playlists.
Error Handling: Implementing robust error management during API requests and data processing.
Real-World Use Cases
This project demonstrates how to combine web scraping and API integration to create a personalized music experience. It's useful for building applications that require historical data and user-specific content, such as custom playlists or historical data analysis tools.
This approach can be applied to other domains as well, like creating custom playlists based on historical events or integrating with different APIs to enhance user experiences.
Conclusion
With this project, you can relive the top hits from any day in the past and enjoy a personalized Spotify playlist. Check out the complete code and details on my GitHub repository and start creating your own nostalgic playlists!
Here is a video explaining how this project works
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