Amazon Bestsellers contains valuable data -- products, badge, sales_volume, price, and more. Scraping this data directly means dealing with anti-bot detection, CAPTCHAs, IP rotation, and constantly breaking selectors. The Scavio API handles all of that and returns clean, structured JSON from a single POST request.
This tutorial shows you how to scrape Amazon Bestsellers using Ruby and the Scavio API. By the end, you will have a working Ruby script that fetches real-time Amazon Bestsellers data and parses the results.
Prerequisites
- Ruby installed on your machine
- A Scavio API key (free tier includes 50 credits on signup -- no credit card required)
Step 1: Install Dependencies
Install net/http to make HTTP requests:
# net/http and json are in Ruby's standard libraryStep 2: Make Your First Amazon Bestsellers Search
Send a POST request to the Scavio Amazon Bestsellers API endpoint with your query. The API returns structured JSON with products, badge, sales_volume, and more.
# There is no bestsellers endpoint and Amazon search takes no sort parameter, so this is
# the marketplace's default ranking for the query, not the Best Sellers chart. Store
# position per ASIN on each run to see movement.
require "net/http"
require "json"
api_key = "sk_live_your_key"
query = "electronics bestsellers"
uri = URI("https://api.scavio.dev/api/v1/amazon/search")
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true
request = Net::HTTP::Post.new(uri)
request["Authorization"] = "Bearer #{api_key}"
request["Content-Type"] = "application/json"
request.body = { query: query, country: "us" }.to_json
response = http.request(request)
data = JSON.parse(response.body)
puts JSON.pretty_generate(data)Step 3: Example Response
The API returns structured JSON. Here is an example response for a Amazon Bestsellers search:
{
"data": {
"query": "electronics",
"page": 1,
"count": 16,
"products": [
{
"asin": "B0GRVFY42Q",
"title": "HP 15.6\" FHD Laptop 2026 Edition, Intel Processor, 8GB RAM",
"price": 414.99,
"currency": "USD",
"rating": 4.2,
"reviews_count": 517,
"position": 3,
"sales_volume": "2K+ bought in past month"
}
]
},
"response_time": 3160,
"credits_used": 1,
"credits_remaining": 4807
}Every field is structured and typed -- no HTML parsing, no CSS selectors, no regex extraction. Your Ruby code can access any field directly.
Step 4: Full Working Example
Here is a complete, runnable Ruby script that searches Amazon Bestsellers and prints the results:
require "net/http"
require "json"
# Search Amazon Bestsellers data with the Scavio API.
# POST /api/v1/amazon/search - rows come back under data.products.
# There is no bestsellers endpoint and Amazon search takes no sort parameter, so this is
# the marketplace's default ranking for the query, not the Best Sellers chart. Store
# position per ASIN on each run to see movement.
API_URL = "https://api.scavio.dev/api/v1/amazon/search"
def search_amazon_bestsellers(query)
api_key = ENV.fetch("SCAVIO_API_KEY")
uri = URI(API_URL)
http = Net::HTTP.new(uri.host, uri.port)
http.use_ssl = true
request = Net::HTTP::Post.new(uri)
request["Authorization"] = "Bearer #{api_key}"
request["Content-Type"] = "application/json"
request.body = { query: query, country: "us" }.to_json
response = http.request(request)
raise "Scavio API error: #{response.code}" unless response.is_a?(Net::HTTPSuccess)
JSON.parse(response.body)
end
data = search_amazon_bestsellers("electronics bestsellers")
puts JSON.pretty_generate(data)Why Use Scavio Instead of Scraping Amazon Bestsellers Directly?
- No proxy management. Direct scraping requires rotating proxies to avoid IP bans. Scavio handles all of this server-side.
- No CAPTCHA solving. Amazon Bestsellers aggressively blocks automated requests. Scavio returns clean data every time.
- Structured JSON output. No HTML parsing or CSS selector maintenance. Get typed, consistent data from every request.
- Multi-platform in one API. Search Google, Amazon, YouTube, and Walmart from the same API key with the same authentication pattern.
- Free tier included. 50 credits on signup with no credit card required. Each search costs 1 credit.