Learning how to scrape Costco can be incredibly valuable for gathering product information, monitoring prices, or conducting market research. In my experience, while there are several approaches to utilize coding tools for scraping Costco's website, our robust HTML API offers the most straightforward solution that handles JavaScript rendering, proxy rotation, and other key elements that tend to overcomplicate data extraction.
In this guide, we will cover how you can extract data from retailers like Costco without getting blocked, dealing with JavaScript rendering, or managing proxies. Let's take a closer look at how you can use our powerful ScrapingBee HTML API with minimal coding knowledge and extract Costco's product data
Quick Answer (TL;DR)
To scrape Costco effectively, use our scraping API, which handles JavaScript rendering, proxy rotation, and bypasses anti-bot measures automatically. Simply sign up for an account, get your API key, choose your target Costco URL, and send a request using the ScrapingBee client.
This approach saves you from building complex scraping infrastructure and dealing with blocks. Below is a Costco scraping script that will help you access product data. Feel free to make adjustments or expand the script to access your desired data points.
Scraping retailer platforms like Costco can be a nightmare, as access to these platforms is intentionally restricted for bots and suspicious connections. If you need more information and examples on how to approach e-commerce sites, check out our Costco Scraping API.
from scrapingbee import ScrapingBeeClient
client = ScrapingBeeClient(api_key='YOUR_API_KEY')
response = client.get(
'https://www.costco.com/apple-smart-watch.html',
params={
'stealth_proxy': True,
'country_code': 'us',
'render_js': 'true',
'js_scenario': {
"instructions": [
{ "evaluate": "window.location.reload();" },
{ "wait": 5000 }
]
},
'extract_rules': {
"products": {
"selector": "div[data-testid^='ProductTile_']", # Matches any div whose data-testid starts with 'ProductTile_'
"type": "list", # Tells ScrapingBee to treat each matched div as a separate item in a list
"output": {
# Extracts the product name text from h3 tag within the card
"product_name": "h3[data-testid*='_title']",
# Extracts the price displayed in a specific Typography component
"price": "div[data-testid^='Text_Price_']",
# Extracts promotional text like 'After $90 OFF'
"promo_text": "div[data-testid^='Text_promoText_']",
# Gets the full rating description (like 'Average rating is 4.74 out of 5 stars...')
"rating": "div[role='img']@aria-label",
# Extracts number of reviews from the span inside a hidden Typography element
"reviews_count": "div.MuiTypography-root[data-testid='Text'] span",
# Pulls delivery/availability text, typically 'Available'
"availability": "div[data-testid='AvailabilityInfo_'] div[data-testid='Text']:nth-of-type(2)"
}
}
}
}
)
response.text
Step-by-Step: How to Scrape Costco with ScrapingBee
Web scraping can seem daunting at first, but following a structured approach with ScrapingBee can significantly simplify the process. I've had my share of headaches building scrapers from scratch. When it comes to targeting elusive with their dynamic content and anti-scraping measures, using a specialized service like ScrapingBee significantly reduces the time and effort to achieve the same goals.
Our platform addresses the key challenges in data scraping platforms with extensive public information. JavaScript rendering, proxy rotation, and CAPTCHA avoidance require a lot more technical knowledge to handle manually, while our best web scraping API lets you focus on the data you need rather than the infrastructure to get it.
Step 1 – Set Up Your ScrapingBee Account
First things first, you'll need to register or log in to your ScrapingBee account to get your API key. Follow these steps:
Visit ScrapingBee's website and follow the sign up steps
Once registered, navigate to your dashboard to find your API key
Copy this key as you'll need it for authentication when sending request
Step 2 – Choose a Target URL on Costco.com
Next, you'll need to identify what product data you want to scrape from Costco. There are a few ways to approach it:
Target specific product category web pages: https://www.costco.com/apple-smart-watch.html
A specific product page: https://www.costco.com/apple-watch-series-10-gps-42mm-sport-loop.product.4000222356.html
Search results for a particular query
Starting with a well-defined target URL makes the scraping process much more focused and efficient. However, product data within the category pages is a lot easier to approach, mostly because specific pages have unpredictable URLs that the scraper might struggle to decipher and access.
Step 3 – Send a Request Using ScrapingBee
Now it's time to get your hands dirty! First, set up your scraping environment. Before we begin coding with Python, go to your Terminal (or Command Prompt for Windows users). Here we will download the necessary packages to that will enable our API to access and scrape a Costco pages.
Begin by installing and checking the Python version on your device. Make make sure you have Python 3.6+ installed.
python --version
Next, install the necessary libraries. Here we can already appreciate the uniform package brought by our API. Most scrapers would not work without the "requests" library, but this package includes all dependencies for a configurable GET API call, which will retrieve the desired data from the platform.
pip install scrapingbee
Begin writing your script by importing the downloaded ScrapingBee package. Then define the variable that will provide the link for your product category. Let's assign the GET API request to a "response" variable and apply the URL:
from scrapingbee import ScrapingBeeClient
client = ScrapingBeeClient(api_key='YOUR_API_KEY')
response = client.get(
'https://www.costco.com/apple-smart-watch.html',
params={
Now we can define parameters for the API call, extensively covered in our documentation. They will define the customizable rules for the delivered connection request, with key features like "render_js" to make sure that your Costco scraper interacts with the page's dynamic content:
response = client.get(
'https://www.costco.com/apple-smart-watch.html',
params={
'stealth_proxy': True,
'country_code': 'us',
'render_js': 'true,'
'js_scenario': {
"instructions": [
{ "evaluate": "window.location.reload();" },
{ "wait": 5000 }
]
},
This code sends a request to your chosen Costco URL using our API, which handles JavaScript rendering and uses premium proxies to address the platform from any location without blocks. Let's take a closer look at these parameters:
stealth_proxy: True. Routes the API connection through a stealth proxy to mask scraping activity, reducing the chance of detection or blocks.
country_code: 'us'. Sends the connection request through a US-based IP, which helps access region-specific content.
render_js: 'true'. Enables JavaScript rendering.
js_scenario. Defines a sequence of JavaScript-related actions:
evaluate: "window.location.reload();" – Forces a reload of the page to ensure all JS elements initialize properly.
wait: 5000 – Pauses execution for 5 seconds to allow full rendering before extracting data.
Now it is time to initiate the HTML parsing capabilities with the extract_rules parameter. Here is an example code that targets CSS selectors in Costco's rendered product data:
'extract_rules': {
"products": {
"selector": "div[data-testid^='ProductTile_']", # Matches any div whose data-testid starts with 'ProductTile_'
"type": "list", # Tells ScrapingBee to treat each matched div as a separate item in a list
"output": {
# Extracts the product name text from h3 tag within the card
"product_name": "h3[data-testid*='_title']",
# Extracts the price displayed in a specific Typography component
"price": "div[data-testid^='Text_Price_']",
# Extracts promotional text like 'After $90 OFF'
"promo_text": "div[data-testid^='Text_promoText_']",
# Gets the full rating description (like 'Average rating is 4.74 out of 5 stars...')
"rating": "div[role='img']@aria-label",
# Extracts number of reviews from the span inside a hidden Typography element
"reviews_count": "div.MuiTypography-root[data-testid='Text'] span",
# Pulls delivery/availability text, typically 'Available'
"availability": "div[data-testid='AvailabilityInfo_'] div[data-testid='Text']:nth-of-type(2)"
Note: Retailers like Costco are known for changing and adjusting the platform's HTML and CSS structure to throw off automated scrapers. If your scraper fails to retrieve extracted data, use your browser's developer tools to identify changes in CSS selectors. Fortunately, you can copy your selectors into the developer mode search bar (CTRL+F) to manually test the selectors you plan to include in the code.
What Data Can You Scrape from Costco?
As the platform for one of the biggest retailers in the world, Costco's website is full of sensitive andvaluable e-commerce data. From Costco's product details to pricing and inventory information, you can extract various data points for market research, competitive analysis, or building your own product database.
In our experience, e-commerce scraping is most valuable when you focus on specific, structured data points rather than trying to extract everything at once. For Costco specifically, the data is well-organized but often requires JavaScript rendering to access fully. Focus on key extractions first, and only then add additional functions, error handling, and other parameters.
ScrapingBee's ability to render JavaScript means you can access even the dynamically loaded content that many basic scrapers would miss, a crucial feature for scraping e-commerce websites.
Common Data Points
Here are some common data points that can be extracted from the Costco's webpage:
Product title, key descriptions, and technical specifications
Regular, promotional, and member-exclusive pricing details
Availability indicators including shipping and in-store stock status
Image URLs and media gallery assets
Star ratings and number of customer reviews
Category paths and navigational hierarchy for SEO insights
Internal item numbers, model IDs, and SKU metadata
Shipping methods, delivery restrictions, and fulfillment options
Note: Scraper complexity can get out of control if you try to target all data at once. We recommend extracting product cards first because they contain the most relevant information that is constantly changing to throw off other retailers, with pricing trends as a prime example.
What Not to Scrape
While scraping public product information is generally acceptable, avoid scraping content behind logins, personal customer details, or anything blocked in robots.txt. Staying within these boundaries helps ensure your use remains respectful and aligned with Costco’s terms of service.
Still, keep in mind that Costco can still limit or restrict your connection just to avoid automated traffic on their platform – a pesky issue that you can avoid with proxy connections!
Why Scraping Costco with ScrapingBee is a Smart Choice
In the world of web scraping, you generally have two options: build your own scraper or use a specialized service. Having tried both approaches extensively, I can confidently say that for sites like Costco, our HTML API delivers numerous convenient advantages:
JavaScript Rendering: Costco loads product data dynamically. ScrapingBee renders JavaScript for you without the need for a headless browser.
Anti-Bot Protection: Our API can use premium proxies and rotating IPs to bypass blocks automatically.
Built for Scale: Scrape thousands of products without worrying about server limits or proxy management.
No Maintenance Headaches: If Costco changes their HTML, our API can quickly adapt to HTML/CSS changes, causing no trouble in more fixing broken scrapers.
Straightforward API: Replace complex scraping code with just a few simple lines.
Scraping Tips: Avoid Getting Blocked
Even if we handle the heavy lifting, following these best practices will ensure smoother scraping operations with our API:
Space out your requests: Don't hammer Costco's servers with too many requests at once. Although our API has rate limits, consider adding additional delays between batches for robust extraction operations.
Be selective: Only request the pages you actually need rather than crawling the entire site.
Use appropriate headers: Our API automatically sets realistic headers, but you can customize them further if needed.
Respect robots.txt: Check Costco's robots.txt file to see which sections of the site should not be scraped.
There is no need to burden yourself with complex and ever-growing scripts. Our scraping API is developed to relieve you from monotonous data collection duties, and only focus on customizing the automation instead of managing everything yourself.
To learn more about protective scraping features, check out our blog on scraping without getting blocked.
Use Cases: Why People Scrape Costco
Understanding what you can do with Costco data helps put this technical guide into perspective. There are many common applications that companies focus on as their primary goals for data extraction.
Scraping Costco can be incredibly useful if you're running a product-focused business. You might want to monitor competitor prices, track availability on popular items, or identify emerging trends based on Costco’s catalog updates.
It's also valuable for enriching your own listings with accurate specifications, promotional text, and high-quality product images. Some even use it to build price comparison tools across major retailers. Our quick setup will let you can collect all this data reliably and turn it into real, actionable business insights.
Scrape Costco the Easy Way — Get Started Now
Now that you've seen how straightforward it is to scrape Costco with ScrapingBee, why not give it a try? The free trial gives you enough credits to test our powerful HTML API and see the quality of data you can extract.
Remember, you don't need to think about those annoying captchas, rate limitations, IP bans, or even HTML parsing. You send a single request, and the relevant data is delivered straight to you in a well-structured format.
Ready to extract valuable data from Costco without the headaches of traditional scraping? Sign up today and transform how you gather e-commerce data!
Frequently Asked Questions (FAQs)
Is it legal to scrape Costco.com?
Web scraping publicly available data is legal, but scrapers should pay close attention to terms of service of to avoid connection restrictions. With our scraping API, it is easy to develop an ethical scraping tool that helps appropriate request rates and only targets public data, available through manual browsing.
Can I use ScrapingBee without coding?
Absolutely! While our code examples use Python, we offer a simple web interface where you can create scraping jobs without writing a single line of code. Just enter the URL, configure the options, and download the data in your preferred format.
What makes ScrapingBee better than other tools?
Our HTML API targets the very heart of e-commerce with JavaScript rendering, proxy rotation, resulting in a simple yet very effective framework for building a scraper. Other tools might offer one or two of these features, but our all-in-one approach ensures that you don't intertwine complex solutions to access Costco's product listings.
Can I scrape product prices in real time?
Yes! Our rapid response times make it suitable for real-time price monitoring. You can set up scheduled scraping jobs that run at regular intervals to track price changes as they happen, giving you up-to-date information on specific products, their prices and availability.
Kevin worked in the web scraping industry for 10 years before co-founding ScrapingBee. He is also the author of the Java Web Scraping Handbook.