Wayfair Closeout Discount Scraper -- 2

@farhanyoussef18

Youssef, Full-Time Python Developer, expert in large-scale web scraping and data processing. Your goal is to get the top 20 Wayfair Closeout page URLs, sorted by deepest discount from regular price. I'll use Playwright to handle any dynamic content on that page, ensuring reliable data extraction. The script will calculate each product's percentage discount, sort the list, and output the top 20 results to a CSV file. I have completed many similar discount tracking and scraping projects. Can you confirm if you need the script to run on a schedule, or is a one-time execution sufficient? Ready to start immediately.

@onlinejob247

Dear client, I can do this job of Wayfair Closeout Discount Scraper accurately as per your requirements and available to start immediately. Thanks!

@jayantkumar314

With over six years of programming experience under my belt, I'm no stranger to tasks like web scraping. In fact, I've made a name for myself in the industry for my efficiency and ability to deliver exceptional results, just as you've outlined for this project. One of my PHP projects involved building an intelligent daily product discount aggregator that not only recorded prices, but also calculated and ranked each item's discount. When it comes to scraping, Python is one of my key languages. I'm well-versed in employing libraries like Beautiful Soup and Playwright, ensuring I can handle any dynamic content the Wayfair page might throw at me. Moreover, my command over languages like PHP and Python will come in particularly useful for processing and calculating the discounts - a skillset you prioritize. On top of all this, I understand that delivering concise and user-friendly outputs are also fundamental aspects of the job. With your suggested options (TXT, CSV or Google Sheet), I am adept in generating clean outputs that are ready-to-use for your purpose. destinationViewController As a seasoned software engineer who's committed to delivering top quality projects that meet or exceed client expectations, I assure you will be making a sound decision by giving me this opportunity.

@mayankinnovative

Hello I can build a Wayfair closeout discount scraper to collect product details pricing discounts availability images and other required data into a structured dataset With 20 years of software development experience I can work with Python BeautifulSoup Selenium APIs data extraction automation and data cleaning while handling dynamic ecommerce pages reliably A few quick questions Which product fields and discount data need to be collected Do you need images and product URLs included What output format or destination is required for the scraped data I’ll focus on accurate extraction duplicate handling price validation structured output and reliable scraping while respecting applicable website access restrictions I’m available to start immediately Thanks

@RetrixDev

Hey Sir, I am expert at Python, Scrapy & BeautifulSoup and you can confirm that from existing projects on my profile & reviews. I can build your Wayfair Closeout scraper to identify the products with the deepest discounts. I'll check the results against the product listings to make sure the discount rankings are accurate. The work would be done professionally within mentioned timeframe. Lets get in touch & discuss more about it. Thank you.

@zditanuel

The closeout page lazy-loads a lot of products, so I'll test Playwright against plain requests first and pick whichever gets clean prices. Discount math and top-20 sort are trivial. I can start today. Should I capture every page of the closeout listing or just the first page?

@mobasherreza10

Hi there, As a developer with a proven track record across numerous projects, I am confident that I am the perfect fit for this task. With extensive experience in web scraping and data analysis using Python, PHP and various frameworks like Scrapy and BeautifulSoup, I assure you of a well-crafted solution to gather and categorize the Wayfair closeout data you need. Included in my long list of proficiencies and capabilities lies a deep understanding of your project's essence: webscraping. I have successfully built similar tools before enabling me to spot the most valuable insights hiding in the haystack of data collected. My strong software architecture background will ensure maintainability and scalability while my proficiency in Python guarantees optimized code for timely results. Best regards, Mobasher Reza

@albertc1996

Hi, I can build a Python scraper to collect Wayfair Closeout product URLs, regular prices, and current sale prices, then calculate and rank the discounts automatically. I’ll use Requests/BeautifulSoup or Playwright depending on how the page loads its product data, with appropriate pagination, error handling, and validation of price values. The utility will calculate "(regular price - sale price) / regular price × 100", sort products by highest discount, and export the top 20 URLs in your preferred TXT, CSV, or Google Sheet format. I’ll provide clean, reusable Python code and a simple setup/run process.

@amirali0301

Hi, I can build this Python utility to crawl the Wayfair Closeout page, calculate the exact discount percentages, and output the top 20 deepest discounts in a clean CSV file. Since Wayfair relies heavily on JavaScript rendering and has strict bot protections, I will use Playwright for this project. It is the most reliable library for handling their dynamic content. The script will accurately extract both the regular and sale prices, apply your (regular - sale) / regular * 100 formula, sort the records highest-first, and export the final top 20 URLs. I specialize in Python web scraping and data extraction, and I have successfully built similar e-commerce scrapers. You can see my previous scraping work here: [Insert Portfolio/GitHub Link] I would be happy to run a quick test script and send you the top 3 discounted items right now as a free sample so you can verify my approach before hiring. Quick question: Will you be running this script locally on your machine, or do you need it to run automatically on a server? Ready to start immediately and deliver this quickly. Looking forward to your response.

@albert1025dev

Hi, Albert here, from Philippines. Building your wayfair closeout discount scraper with 20 URLs comes down to one thing: clean, complete data that keeps arriving when the site changes. I'm a senior software developer with 10+ years of experience working with Python, Scrapy, Web Scraping and Data Processing. For your wayfair closeout discount scraper, the real challenge is layout changes and blocking. A common issue: no monitoring, so when the site changes the scraper returns empty data and nobody notices. My plan: first, map the pages, fields and blocking rules of the target site. Then, build the scraper with retries, rate limits and data cleaning. Finally, add monitoring and alerts, then run it on a full sample. I've done scraping work in Scrapy and Python, so I check early for layout changes and silent empty results. A few questions to better understand the scope: 1. Is the data loaded by JavaScript? Then I'd call the site's own data requests, faster than a full browser. 2. Run it on a small VPS instead of your own PC? I'd recommend a VPS, it runs on schedule even when your PC is off. 3. Does your team act on the data the same day? Then I schedule runs around their working hours. I can start right away. Happy to go over the details here in chat and suggest the best approach. Looking forward to hearing from you, Albert

@GobindSawarn

As a seasoned developer with a diverse skill set, I'm confident in my ability to handle your project with expertise and efficiency. Specializing in Python and Software Architecture, I'm no stranger to web scraping, particularly on dynamic sites like Wayfair. I adapt the best tools at hand, such as Beautiful Soup and Playwright, to ensure fluid data extraction. My inclination for data processing aligns directly with your project goals. From fetching the product details to calculating the discounts and sorting records accordingly - precision is my utmost priority. I promise to deliver clean and functional code with detailed documentation for future use.

@designerdeeksha

Hi, I can build the Python utility to crawl Wayfair’s Closeout page, extract product URLs and pricing, calculate discounts, sort them and generate the top 20 highest-discounted products. ✅ Python-based scraper ✅ Requests/BeautifulSoup or Playwright depending on page behavior ✅ Extract regular + current selling prices ✅ Discount percentage calculation ✅ Sort highest discount → lowest ✅ Top 20 product URLs output ✅ TXT / CSV output as required ✅ Clean, reusable and documented code ✅ Error handling for missing/invalid price data I have 7+ years of web development experience with Python, web scraping and automation. I can test the scraper against the live page and use Playwright if the product data requires JavaScript rendering. I can start immediately and deliver the utility with the requested output file and setup instructions.

@larencea30

Hi, You need a compact Python scraper that reliably reads Wayfair’s Closeout listings, calculates the real discount percentage, and ranks the strongest deals automatically. I’d use Requests/BeautifulSoup if the pricing is available in the HTML, or Playwright if the page relies on dynamic rendering. The script would capture product URL, regular price, current price, calculate the discount, sort highest-first, and export the top 20 results to CSV or TXT. I’d also add basic validation so missing or malformed prices don’t break the run, and keep the code simple enough to rerun whenever you want fresh results. The final output will be clean, ranked, and easy to verify against the live product pages.

@marvind18

You need a Python utility that reliably identifies the true deepest discounts on Wayfair’s Closeout page, calculates them from regular versus current price, and returns the top 20 product URLs in descending order. I would build this as a repeatable scraper, not a one-off copied list. My Python work includes production data pipelines and real-time processing at Marin Software. I’ll first inspect how the Closeout catalogue renders, then use Requests/BeautifulSoup for stable server-rendered data or Playwright if product pricing loads dynamically. The script will normalise currency text, skip incomplete or malformed price records, calculate the discount from the original price, deduplicate URLs, sort highest first, and export TXT or CSV with title, regular price, sale price, discount percentage, and URL. I’ll include clear setup instructions and keep the selector/parsing logic isolated so it can be updated if the page layout changes. The workflow will respect public access rules and avoid bypassing access controls or CAPTCHA systems. Do you want the output to include only products showing an explicit regular/list price, or should products with alternative “was” price labels also be considered?

@aakaashberi

I can build the Python utility to compare Wayfair Closeout prices and export the 20 deepest discounts to CSV. My profile supports Python and workflow automation; I reviewed the public Closeout listing, which currently exposes sale/was prices and pagination ending at page 200. I would use Playwright for rendered listings, traverse the available pages with paced requests, and deduplicate product/variant URLs. The utility will normalize numeric prices, calculate (regular - sale) / regular * 100, reject missing or invalid price pairs, and sort descending. I will retain variant identifiers when cleaning tracking parameters, record crawl coverage/time, and report interrupted access rather than presenting an incomplete crawl as the global top 20. My INR 7,500 / seven-day quote covers the utility, a dated CSV run, full valid-record CSV for auditing, and a README with install/run instructions. A sample-page extraction and discount check is the first milestone, followed by pagination, ranking and handover. Should each variant count separately, and should 'regular price' mean the crossed-out 'was' value shown on the listing? Prices reflect the selected location and collection time.

@safdarkhali1

With a broad range of skills in data analysis and processing, as well as extensive experience in Python programming and web scraping, I am perfectly suited to tackle your Wayfair Closeout Discount Scraper project. Having effectively completed over 250 similar projects to your own, I'm particularly experienced in utilizing web scraping libraries such as requests/BeautifulSoup, Scrapy and Playwright - all languages you've designated acceptable for this project. If there are any challenges that may arise from Wayfair's dynamic content, I can adeptly navigate them. I understand complex calculations like percentage discounts and have an eye for detail that would ensure that the top 20 URLs with deepest discounts are accurately recorded and sorted. Lastly, to further underscore my value-add for your project, my efficient data analysis skills will enable me to deliver the final products (a TXT, CSV or Google Sheet document) swiftly and with a keen eye for quality. I look forward to working with you on this project and leveraging my diverse skill set to help you achieve your goals at Wayfair!

@petropankovdev

I checked the Closeout page before writing this: a plain requests call gets a 429 from Wayfair right away, so requests/BeautifulSoup alone will not get far. I would build it on Playwright with a real Chromium, scroll the page until no new products load, and read each tile's regular and sale price from the rendered page, at a slow human pace. What you get: - one Python script (Playwright), run with a single command - for every product: URL, name, regular price, sale price, discount % = (regular - sale) / regular x 100 - items with no regular price or no discount are dropped, not counted as 0% - sorted by discount, top 20 written to CSV (and a TXT copy if you prefer) - a short README: install, run, where the file lands First step: I run it once on the live page and send you the actual top 20 list, so you see the output before you take the code. One honest note: Wayfair has bot protection, and it can tighten later. If it starts blocking your IP, the fix is usually a slower pace or a different network, and I will tell you which if it happens, rather than promise it never will. Background: three completed projects on this account, all rated 5 out of 5, delivered on time and on budget. I have also delivered scraping and data collection work that paying clients accepted. Outside client work, 16 merged pull requests into third party open source projects, mostly a 231 star Go security tool. 6000 INR, 3 days. Petro Pankov, BotCraft Group

@chamanrajragu

The maths and the output here are trivial. The part worth talking about is the fetch, because that is where this job either works or quietly returns nothing. That closeout page renders its listings client-side, so requests plus BeautifulSoup against the raw HTML will usually come back with no products at all, or with the skeleton markup and empty price fields. The usual result is a script that runs without error and produces an empty or half-filled file, which is the worst failure mode because it looks like it worked. So my first step is to establish how the page actually delivers its data - the JSON the page itself requests is normally the clean source, with regular and sale price as proper numeric fields rather than text I have to parse out of markup. That also makes the discount calculation exact instead of depending on scraped currency strings. Two things I will be straight about: - I work within what the site permits, at a conservative request rate. I do not build anything to get around access controls. If the site blocks automated access outright, I will tell you that is the situation rather than escalate. - Prices and the closeout lineup change constantly, so a top-20 list is a snapshot. I will timestamp it, and if you want this repeatedly it should be a scheduled run, which is a small addition. Deliverable: the Python script plus a CSV of the top 20 by discount, with regular price, sale price, computed percentage and URL per row.

@surya8527

Hi, I can build a reliable Python Wayfair scraper to extract prices, calculate discounts, and deliver the top 20 highest-discount products in CSV/TXT. I have 4+ years of experience in data analysis, web scraping and automation and can start immediately.