Walmart Data Extractor
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Walmart Data Extractor
epctex/walmart-scraper
Try for free
3 days trial then $30.00/month - No credit card required now
Access a vast array of product data from Walmart with our Walmart Scraper. Extract images, brand details, prices, variations, and more. Customize your search with filters, categories, and lists to gather the information you need.
The code examples below show how to run the Actor and get its results. To run the code, you need to have an Apify account. Replace <YOUR_API_TOKEN> in the code with your API token, which you can find under Settings > Integrations in Apify Console. Learn more
1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4client = ApifyClient("<YOUR_API_TOKEN>")
5
6# Prepare the Actor input
7run_input = {
8 "startUrls": [
9 { "url": "https://www.walmart.com/browse/auto-tires/brake-pads/91083_1074765_9038935_4582920" },
10 { "url": "https://www.walmart.com/browse/home/" },
11 { "url": "https://www.walmart.com/search?grid=true&query=Mixed+Bouquets" },
12 { "url": "https://www.walmart.com/ip/Mainstays-Blue-Sunflower-Mix-Bouquet/155345382" },
13 ],
14 "maxItems": 50,
15 "endPage": 1,
16 "extendOutputFunction": """($) => {
17 const result = {};
18 // Uncomment to add a title to the output
19 // result.title = $('title').text().trim();
20
21 return result;
22}""",
23 "outputFilterFunction": "(object) => ({...object})",
24 "proxy": { "useApifyProxy": True },
25}
26
27# Run the Actor and wait for it to finish
28run = client.actor("epctex/walmart-scraper").call(run_input=run_input)
29
30# Fetch and print Actor results from the run's dataset (if there are any)
31print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
32for item in client.dataset(run["defaultDatasetId"]).iterate_items():
33 print(item)
34
35# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startDeveloper
epctexMaintained by Community
Actor metrics
- 22 monthly users
- 6 stars
- 99.5% runs succeeded
- Created in Apr 2021
- Modified about 14 hours ago
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