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Amazon Bestsellers Scraper

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Amazon Bestsellers Scraper

Amazon Bestsellers Scraper

dainty_screw/amazon-bestsellers-scraper
Try for free

3 days trial then $9.99/month - No credit card required now

Amazon Bestsellers Scraper is a powerful Apify actor designed to efficiently extract real-time data from Amazon's Best Sellers lists. This actor is tailored for businesses, researchers, and individuals who seek to monitor and analyze market trends, product rankings, and pricing dynamics

You can access the Amazon Bestsellers Scraper programmatically from your own Python applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "categoryUrls": [{ "url": "https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics/" }],
10    "depthOfCrawl": 1,
11    "proxy": { "useApifyProxy": True },
12}
13
14# Run the Actor and wait for it to finish
15run = client.actor("dainty_screw/amazon-bestsellers-scraper").call(run_input=run_input)
16
17# Fetch and print Actor results from the run's dataset (if there are any)
18print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
19for item in client.dataset(run["defaultDatasetId"]).iterate_items():
20    print(item)
21
22# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Amazon Bestsellers Scraper API in Python

The Apify API client for Python is the official library that allows you to use Amazon Bestsellers Scraper API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

pip install apify-client

Other API clients include:

Developer
Maintained by Community

Actor Metrics

  • 13 monthly users

  • 6 stars

  • 95% runs succeeded

  • Created in Apr 2024

  • Modified 3 months ago