Web Site Scrapers
Automating data collection with web scrapers to seed test data.
Overview
Web scrapers saved me from manual data entry doom.
- Instead of painstakingly copying data by hand, I built custom scrapers to automate data capture. - Each scraper was tailored to a specific site, since every source had unique structures and navigation. - Result?** A quick, scalable way to collect test data and seed the database effortlessly.
Key Goals:
Leverage web scraping** to pull structured data from various sources.
Automate data ingestion, reducing **manual effort and errors.
Customize scrapers** for different website structures and target datasets.
Complexity: Easy
Components
RIAA Awards Scraper
A Python scraper to extract Taylor Swift’s RIAA awards for inclusion in quantitative album metrics.
SOARL Summary
Wanted to collect award certifications** (e.g., Platinum, Gold, 2M units sold) for better analytics.
Taylor Swift has a LOT of awards—great for her, terrible for **manual data entry.
ChatGPT helped write the scraper, which I **tweaked to extract and format the data.
In 20 minutes, I had a **fully structured dataset, ready to load into a database.
Every time I found myself mindlessly copy-pasting, I stopped and asked “Can ChatGPT automate this?”**
90% of the time, the answer was YES.**
Situation:
Obstacle:
Action:
Result:
Learning:
Key Learnings
- If you’re manually copying data, you’re doing it wrong.** - Web scraping isn’t just a time-saver—it’s a superpower** for automating tedious workflows. - ChatGPT is great at writing scrapers**—tweaking them for site quirks is where the magic happens.
Demos
Final Thoughts
Web scraping turned hours of manual work into a few lines of code.
When data collection is automated, you can focus on insights instead of grunt work. 🚀