Python Developer for Pokémon Card Deals

I’m looking for a Python developer to build a tool that helps identify undervalued graded Pokémon cards by scraping Cardmarket, comparing prices with PriceCharting, and sorting the best deals.

The tool should prioritize high-value cards and highlight the best opportunities based on % price difference.

1. Cardmarket Scraper

Target the Singles section for Pokémon cards.

Sort by price descending.

Go through listings from the most expensive downward.

Stop when the listing price drops below €20.

Identify graded cards manually by checking for keywords in titles like: "PSA 10", "PSA 9", "PSA 8", "PSA 7".
Extract relevant data:

Card name
Grade
Price
Listing URL

2. PriceCharting Integration

Use the PriceCharting API to retrieve prices for the same card and grade (e.g., PSA 9).

Match cards using name, grade, and set

3. Price Comparison & Deal Sorting

For each graded card:

Compare Cardmarket price to PriceCharting price for the same grade.

Calculate the % difference.

For cards valued above €1,000 (according to PriceCharting), sort these separately by % difference, with the best deals (largest discounts) first.

4. Output

Export to CSV or Excel showing:

Card name

Grade

Cardmarket price

PriceCharting value

% difference

Listing URL