--- title: "How to Scrape Etsy: 2026 Guide" slug: how-to-scrape-etsy date: 2025-02-05T06:37:23+00:00 modified: 2025-09-16T16:37:38+00:00 permalink: https://brightdata.com/blog/web-data/how-to-scrape-etsy type: blog --- [ Blog ](https://brightdata.com/blog "Blog") / [Web Data](https://brightdata.com/blog/web-data) [Web Data](https://brightdata.com/blog/web-data) # How to Scrape Etsy: 2026 Guide Scraping Etsy is tough due to its advanced bot-blocking tactics. Learn how to bypass these roadblocks and extract valuable eCommerce data with Python. 8 min read [ ](https://brightdata.com/blog/authors/jake-nulty) [Jake Nulty Technical Writer ](https://brightdata.com/blog/authors/jake-nulty) ![How to Scrape Etsy blog image](https://media.brightdata.com/2025/02/How-to-Scrape-Etsy.svg) [Etsy](https://www.etsy.com/) is a notoriously difficult site to scrape. They employ a variety of blocking tactics and have one of the most sophisticated bot blocking systems on the web. From detailed header analysis to a seemingly endless wave of CAPTCHAs, Etsy is the bane of web scrapers all over the world. If you can get past these roadblocks, Etsy becomes a relatively easy site to scrape. If you can scrape Etsy, you gain access to a wealth of small business data from one of the biggest marketplaces the internet has to offer. Follow along today, and you’ll be scraping Etsy like a pro in no time. We’ll learn how to scrape all of the following page types from Etsy. - Search Results - Product Pages - Shop Pages ## Getting Started [Python Requests](https://pypi.org/project/requests/) and [BeautifulSoup](https://pypi.org/project/beautifulsoup4/) will be our tools of choice for this tutorial. You can install them with the commands below. Requests allows us to make HTTP requests and communicate with Etsy’s servers. BeautifulSoup gives us the power to parse the web pages using Python. We suggest you read our guide on [how to use BeautifulSoup for web scraping](/blog/how-tos/beautiful-soup-web-scraping) first. **Install Requests** ```none pip install requests ``` **Install BeautifulSoup** ```none pip install beautifulsoup4 ``` ## What to Scrape from Etsy If you inspect an Etsy page, you might get caught in a nasty web of nested elements. If you know where to look, this is easy enough to overcome. Etsy’s pages use [JSON data](/blog/how-tos/parse-json-data-with-python) to render the page in the browser. **If you can find the JSON, you can find all the data they used to build the page… without having to dig too deeply through the HTML of the document.** ### Search Results Etsy’s search pages contain an array of JSON objects. If you look at the image below, all of this data comes inside a `script` element with `type="application/ld+json"`. If you look really closely, this JSON data contains an array called `itemListElement`. If we can extract this array, we get all the data they used to build the page. ### Product Information Their product pages aren’t much different. Look at the image below, once again, we’ve got a `script` tag with `type="application/ld+json"`. This tag contains all the information that was used to create the product page. ### Shops You probably guessed, our shop pages are also built the same way. Find the first `script` object on the page with `type="application/ld+json"` and you’ve got your data. ## How to Scrape Etsy With Python Now, we’ll go over all the required components we need to build. As mentioned earlier, Etsy employs a variety of tactics to block us from accessing the site. We use [Web Unlocker](/products/web-unlocker) as a swiss army knife for these blocks. Not only does it manage proxy connections for us, it also solves any CAPTCHAs that come our way. **You’re welcome to try without a proxy, but in our initial testing, we were unable to get past Etsy’s blocking systems without Web Unlocker.** Once you’ve got a Web Unlocker instance, you can set up your proxy connection by creating a simple `dict`. We use Bright Data’s SSL certificate to ensure that our data remains encrypted in transit. In the code below, we specify the path to our [SSL certificate](https://docs.brightdata.com/general/account/ssl-certificate#download-the-ssl-certificate) and then use our username, zone name, and password to create the proxy url. Our proxies are built by constructing a custom url that forwards all of our requests through one of [Bright Data’s proxy services](/proxy-types). ```none path_to_cert = "bright-data-cert.crt" proxies = { 'http': 'http://brd-customer--zone-:@brd.superproxy.io:33335', 'https': 'http://brd-customer--zone-:@brd.superproxy.io:33335' } ``` ### Search Results To extract our search results, we make a request using our proxies. We then use `BeautifulSoup` to parse the incoming HTML document. We find the data inside the `script` tag and load it as a JSON object. Then we return the `itemListElement` field from the JSON. ```none def etsy_search(keyword): encoded_keyword = urlencode({"q": keyword}) url = f"https://www.etsy.com/search?{encoded_keyword}" response = requests.get(url, proxies=proxies, verify=path_to_cert) soup = BeautifulSoup(response.text, "html.parser") script = soup.find("script", attrs={"type": "application/ld+json"}) full_json = json.loads(script.text) return full_json["itemListElement"] ``` ### Product Information Our product information gets extracted basically the same way. Our only real difference is the absence of `itemListElement`. This time, we use our `listing_id` to create our url and we extract the entire JSON object. ```none def etsy_product(listing_id): url = f"https://www.etsy.com/listing/{listing_id}/" response = requests.get(url, proxies=proxies, verify=path_to_cert) soup = BeautifulSoup(response.text, "html.parser") script = soup.find("script", attrs={"type": "application/ld+json"}) return json.loads(script.text) ``` ### Shops When extracting shops, we follow the same model we used with products. We use the `shop_name` to construct the url. Once we’ve got the response, we find the JSON, load it as JSON, and return the extracted page data. ```none def etsy_shop(shop_name): url = f"https://www.etsy.com/shop/{shop_name}" response = requests.get(url, proxies=proxies, verify=path_to_cert) soup = BeautifulSoup(response.text, "html.parser") script = soup.find("script", attrs={"type": "application/ld+json"}) return json.loads(script.text) ``` ### Storing the Data Our data is neatly structured JSON as soon as we extract it. We can write our output to a file using Python’s basic file handling and `json.dumps()`. We write it with `indent=4` so it’s clean and readable when humans look at the file. ```none with open("products.json", "w") as file: json.dump(products, file, indent=4) ``` ### Putting Everything Together Now that we know how to build our pieces, we’ll put it all together. The code below uses the functions we just wrote and returns our desired data in JSON format. We then write each of these objects to their own individual JSON files. ```none import requests import json from bs4 import BeautifulSoup from urllib.parse import urlencode # Proxy and certificate setup (HARD-CODED CREDENTIALS) path_to_cert = "bright-data-cert.crt" proxies = { 'http': 'http://brd-customer--zone-:@brd.superproxy.io:22225', 'https': 'http://brd-customer--zone-:@brd.superproxy.io:22225' } def fetch_etsy_data(url): """Fetch and parse JSON-LD data from an Etsy page.""" try: response = requests.get(url, proxies=proxies, verify=path_to_cert) response.raise_for_status() except requests.exceptions.RequestException as e: print(f"Request failed: {e}") return None soup = BeautifulSoup(response.text, "html.parser") script = soup.find("script", attrs={"type": "application/ld+json"}) if not script: print("JSON-LD script not found on the page.") return None try: return json.loads(script.text) except json.JSONDecodeError as e: print(f"JSON parsing error: {e}") return None def etsy_search(keyword): """Search Etsy for a given keyword and return results.""" encoded_keyword = urlencode({"q": keyword}) url = f"https://www.etsy.com/search?{encoded_keyword}" data = fetch_etsy_data(url) return data.get("itemListElement", []) if data else None def etsy_product(listing_id): """Fetch product details from an Etsy listing.""" url = f"https://www.etsy.com/listing/{listing_id}/" return fetch_etsy_data(url) def etsy_shop(shop_name): """Fetch shop details from an Etsy shop page.""" url = f"https://www.etsy.com/shop/{shop_name}" return fetch_etsy_data(url) def save_to_json(data, filename): """Save data to a JSON file with error handling.""" try: with open(filename, "w", encoding="utf-8") as file: json.dump(data, file, indent=4, ensure_ascii=False, default=str) print(f"Data successfully saved to {filename}") except (IOError, TypeError) as e: print(f"Error saving data to {filename}: {e}") if __name__ == "__main__": # Product search products = etsy_search("coffee mug") if products: save_to_json(products, "products.json") # Specific item item_info = etsy_product(1156396477) if item_info: save_to_json(item_info, "item.json") # Etsy shop shop = etsy_shop("QuiverCreekCeramic") if shop: save_to_json(shop, "shop.json") ``` Below is some sample data from `products.json`. ```none { "@context": "https://schema.org", "@type": "Product", "image": "https://i.etsystatic.com/34923795/r/il/8f3bba/5855230678/il_fullxfull.5855230678_n9el.jpg", "name": "Custom Coffee Mug with Photo, Personalized Picture Coffee Cup, Anniversary Mug Gift for Him / Her, Customizable Logo-Text Mug to Men-Women", "url": "https://www.etsy.com/listing/1193808036/custom-coffee-mug-with-photo", "brand": { "@type": "Brand", "name": "TheGiftBucks" }, "offers": { "@type": "Offer", "price": "14.99", "priceCurrency": "USD" }, "position": 1 }, ``` ## Consider Using Datasets Our datasets offer a great alternative to web scraping. You can buy [ready-to-go Etsy datasets](/products/datasets/etsy) or one of our other [eCommerce datasets](/products/datasets/ecommerce) and eliminate your scraping process entirely! Once you’ve got an account, head over to our dataset marketplace. Type in “Etsy” and click on the Etsy dataset. This gives you access to millions of records from Etsy data… right at your fingertips. You can even download sample data to see what it’s like to work with. ## Conclusion In this tutorial, we explored Etsy scraping in great detail. You received a crash course in proxy integration. You know how to use [Web Unlocker](/products/web-unlocker) to get past even the most stringent of bot blockers. You know how to extract the data, and you also know how to store it. You also got a taste of [our pre-made datasets](/products/datasets) that eliminate your scraping duties entirely. However you get your data, we’ve got you covered. Sign up now and start your free trial. Contact usStart free trial No credit card required [ ](https://www.linkedin.com/in/jacob-nulty-682803187/) Jake Nulty Technical Writer 6 years experience Jacob Nulty is a Detroit-based software developer and technical writer exploring AI and human philosophy, with experience in Python, Rust, and blockchain. Expertise Data Structures Python Rust [ View all articles ](https://brightdata.com/blog/authors/jake-nulty) Table of Contents Dedicated Scraper APIs & No-Code Scrapers Over 1000 scrapers for all popular domains. Simplify your web scraping. [See pricing](/pricing/web-scraper "See pricing") Just want data? Skip scraping. Hundreds of ready-to-use datasets from all popular domains. [See pricing](/pricing/datasets "See pricing") [ ](https://news.ycombinator.com/submitlink?t=How+to+Scrape+Etsy%3A+2026+Guide&u=https://brightdata.com/blog/web-data/how-to-scrape-etsy) [ ](https://www.linkedin.com/shareArticle?mini=true&title=How+to+Scrape+Etsy%3A+2026+Guide&url=https://brightdata.com/blog/web-data/how-to-scrape-etsy) [ ](http://www.reddit.com/submit?title=How+to+Scrape+Etsy%3A+2026+Guide&url=https://brightdata.com/blog/web-data/how-to-scrape-etsy) ## You might also be interested in [ ](https://brightdata.com/blog/ai/openhuman-with-bright-data "Production-Ready Web Access in OpenHuman Through the Bright Data CLI") [AI Antonello Zanini Technical Writer ### Production-Ready Web Access in OpenHuman Through the Bright Data CLI Integrate Bright Data CLI with OpenHuman to enable production-ready web access and data collection for AI agents. 09-Sep-2026 12 min read ](https://brightdata.com/blog/ai/openhuman-with-bright-data) [ ](https://brightdata.com/blog/ai/minimax-m3-with-bright-data "Giving self-hosted MiniMax M3 agents live web access with Bright Data") [AI Satyam Tripathi Technical Writer ### Giving self-hosted MiniMax M3 agents live web access with Bright Data Self-hosted MiniMax M3 agents get live web access using Bright Data’s search and scraping tools. 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