A pricing engine that compares similar vehicles

@vishal1145

Your scraper will get blocked within 48 hours if you're hitting Marketplace A without residential proxies and session fingerprinting. Most developers miss this - they build the scraper, it works for two days, then Cloudflare bans the IP range and the whole system goes dark. Before I architect this, I need clarity on two things: What's your current proxy budget, and does Marketplace A use JavaScript rendering or can we pull data from their API endpoints? The difference determines whether we're running Puppeteer clusters (expensive, slower) or lightweight HTTP requests (cheaper, 10x faster). Also, what's your expected vehicle volume per day - 50 listings or 5,000? That changes the database indexing strategy completely. Here's the architectural approach: - PYTHON + SCRAPY: Build a distributed scraper with rotating user agents, cookie jar management, and request throttling to stay under rate limits while mimicking human browsing patterns. - MONGODB: Design a schema with compound indexes on model + year + mileage for sub-100ms query performance, plus TTL indexes to auto-expire stale listings after 90 days. - ELASTICSEARCH: Index price history and enable fuzzy search across vehicle specs so your dashboard can surface "2015 Toyota Land Cruiser" even if someone types "LC 2015." - NODE.JS + EXPRESS: Build a REST API with Redis caching layer so repeated dashboard queries don't hammer the database - critical when you're filtering 10K+ records. - PRICE ANOMALY DETECTION: Implement a rolling 30-day median calculation per model/year combo, then flag anything 15%+ below market as a potential deal, accounting for mileage and grade adjustments. - DOCKER COMPOSE: Package scraper, API, MongoDB, Redis, and Nginx reverse proxy into one-command deployment so you're not debugging environment issues at 2am. I've built three similar monitoring systems - one tracked eBay auctions for collectible cars, another scraped Copart for salvage titles. Both ran 24/7 for 18+ months without getting blocked because we engineered proper evasion from day one. Let's schedule a 15-minute call to walk through Marketplace A's specific defenses before you commit to a build that might not survive production traffic.

@Shrutibimpl

You want an automated, anti bot scraping pipeline and lightweight dashboard to monitor Japanese vehicle listings on Marketplace A and instantly alert you to underpriced cars. This vehicle monitoring platform operates continuously behind the scenes, scanning the market for fresh listings and instantly identifying bargains before competitors can act. By comparing new postings against historical sales figures, you gain a clear competitive advantage without manually refreshing websites all day. You get complete peace of mind knowing the tool routes listings into a centralized database and sends instant email alerts directly to your inbox whenever a deal matches your filters. We will build the crawling system in Nodejs using Playwright and stealth plugins to bypass cloud blocks and manage residential proxy rotation. The backend will run on Express and use PostgreSQL to log listing dates, mileage, and grades, calculating rolling price averages via SQL analytical queries. For the user interface, we will deploy a lightweight React dashboard showing active deals, and run automated cron jobs to dispatch alerts via Resend when prices fall below threshold levels. I have couple of critical questions too, let's discuss in details.

@NEHABHAT92

With over 9+ years of experience in web and mobile development, my team and I are well-equipped to handle your project with the utmost professionalism and efficiency. Our expertise in Python and Node.js, combined with our deep understanding of web scraping, structured databases, and creating interactive web dashboards make us the ideal choice for your pricing engine need. We understand that the performance and functionality of your scraper is of utmost importance to you. That's why we offer robust solutions that are capable of anti-bot evasion, competent at rate limits handling, and scalable to accommodate your potential needs for shorter intervals refreshers later on. Additionally, as effective communicators, we will provide you with a detailed deployment guide (Docker or similar) discussing all aspects of your project along with a thorough hand-off explanation. Our cost-effective approach to projects doesn't compromise on quality or after-sales support. We ensure flawless delivery by conducting thorough testing during development. Moreover, we offer free 3-month support for existing developments. With our strong portfolio in E-commerce and CMS-based websites, we assure you an impeccable solution that will not only meet your requirements but exceed them. Thank you for considering us!

@pluralcode16

With a passion for clean and efficient code, top-notch database management, and Node.js fluency, I am confident that I have all the skills necessary to tackle your pricing engine project. My experience in web scraping and data processing aligns perfectly with the task at hand. I will design a robust crawler for Marketplace A that safeguards against bot detection, employing rotating proxies or headless browsers where necessary. Storing the data, from fresh listings to extensive details like price, mileage, model and timestamps, will be done with utmost efficiency in a highly structured database. Additionally, my experience with NoSQL databases such as Couch & Mongo makes me the perfect person for this task. Given the large amount of data that will be captured and stored for this project, it is important to have a suction design that ensures high performance even with shorter intervals for data refresh. I can provide you with a detailed report on how we can tackle rate limits and conform to efficient fail-safe mechanisms to keep the scraping process uninterrupted for such a critical project. Moreover, my proficiency in deploying projects using Docker allows me to simplify this process for smooth hand-off. But it's not just about delivering a solution; it’s also about supporting you throughout your journey. To that end, my 24x7 support grip gives you some peace of mind knowing I'll always be ready to address any concerns or questions you may have

@webnsoftindia

Hello, I can build a full stack vehicle monitoring tool that tracks Japanese vehicle listings on Marketplace A twenty four hours a day, captures new ads immediately, and refreshes pricing data daily. What I will deliver: Anti bot safe scraper built with Python and Playwright Rotating proxy and headless browser setup for stable scraping PostgreSQL database storing model, year, mileage, grade, price, and timestamps Automatic price comparison system to identify undervalued listings Clean dashboard with live search, filters, and alert management Email and push notifications for bargain listings Docker deployment setup and hand off support Technology stack: Python, FastAPI, Playwright, PostgreSQL, React, and Docker I have experience building marketplace monitoring platforms, automated scraping systems, and price tracking dashboards with scalable architecture and proxy rotation. Ready to start immediately.

@Hrolgar

The definition of 'similar' has to be settled before the scraping starts. Grade and trim conventions in Japanese listings vary enough by segment that a normalization schema for kei trucks won't handle imports correctly. I'd confirm which marketplace and segments you're targeting before writing the collector, so the canonical schema covers the grade fields that segment actually uses. From there: a Python collector normalizes each listing into a structured record covering make, model, year, grade, mileage band, transmission, condition, price, and location. The similarity score weights those fields by how much they move price, so mileage band and grade count more than transmission. Dedup runs on the platform's listing ID with a hash fallback since the same car gets relisted regularly and you don't want it inflating the comps count. Records land in MongoDB, the Elasticsearch index holds the normalized fields, and for any target vehicle the engine returns the nearest real listings and a price distribution band rather than a point estimate. A thin Node API surfaces the comps and suggested band. M1: Collector + canonical schema, INR 8750, 2d. M2: Normalization + dedup + MongoDB storage, INR 7000, 1d. M3: Elasticsearch comps + similarity scoring + price band, INR 12250, 2d. M4: Node API + handoff, INR 7000, 1d. Which marketplace is this, and are there specific vehicle grades or segments you want prioritized in the normalization?

@DigitalNightOwl8

Hi There , Good afternoon! I’ve carefully checked your requirements and really interested in this job. I’m full stack node.js developer working at large-scale apps as a lead developer with U.S. and European teams. I’m offering best quality and highest performance at lowest price. I can complete your project on time and your will experience great satisfaction with me. I’m well versed in React/Redux, Angular JS, Node JS, Ruby on Rails, html/css as well as javascript and jquery. I have rich experienced in Database Design, Database Management, API Development, NoSQL Couch & Mongo, Data Management, Elasticsearch, Data Processing, Web Scraping, Python and Node.js. For more information about me, please refer to my portfolios. I’m ready to discuss your project and start immediately. Looking forward to hearing you back and discussing all details.. Talk to you soon

@Jasim0021

Hi there! ? I've carefully reviewed your project requirements and I'm confident I can deliver exactly what you need. **Why I'm the right fit:** • 7+ years of professional software development experience • Delivered 100+ projects with 98% client satisfaction • Expert in modern tech stack and best practices **My approach to your project:** 1. **Discovery & Planning** — I'll start by understanding your exact requirements, target users, and design preferences 2. **Architecture & Design** — Clean, scalable architecture with modern best practices 3. **Development** — Iterative development with regular demos and feedback loops 4. **Testing & QA** — Comprehensive testing including unit tests, integration tests, and user acceptance testing 5. **Deployment & Support** — Full deployment assistance and post-launch support **What you'll get:** • Clean, well-documented, maintainable code • Responsive design that works on all devices • Secure implementation following industry best practices • Timely delivery with daily progress updates • 30-day free bug-fix support after delivery **Relevant skills:** software development I'd love to discuss your vision in detail. Let's connect and make this happen! Best regards

@sandyl24

Hi, I can build this vehicle monitoring and pricing engine for you. Python is the right choice here for speed and scraping reliability. My approach: Scraper: Python + Playwright (headless browser) with rotating proxy support for anti-bot evasion Database: SQLite or MongoDB for structured vehicle data (model, year, mileage, grade, price, timestamps) Price engine: Auto-flags listings that sit below market average based on comparable vehicles Dashboard: Lightweight Flask web UI with filters (model, year, mileage, grade) and live search Alerts: Email notifications when bargain listings appear Deployment: Docker-ready with setup guide Architecture designed to scale from daily to shorter refresh intervals I recently built a similar data monitoring tool that auto-scrapes, stores, and surfaces financial data with auto-refresh capabilities. Happy to discuss rate-limit strategy and timeline in detail.

@RubinTh

This is a well defined build and I can deliver exactly what you have described. I have built several marketplace monitoring and price tracking tools including a used vehicle listing tracker, a real estate price alert system, and a multi platform e commerce scraper, all using Python with rotating proxy infrastructure and headless browser handling via Playwright or Selenium where needed. Anti bot evasion, rate limit management, and session handling are standard parts of my scraper architecture. For this project I would use Python with Playwright for resilient page interaction, a PostgreSQL schema storing model, year, mileage, grade, price, and timestamps with indexed queries for fast filtering, and a lightweight FastAPI and React dashboard with search, filter, and alert management. Price comparison logic would flag listings sitting a defined percentage below rolling 30 day averages for the same model and grade band. I would containerise the full stack in Docker with a Compose file so deployment to any VPS is a single command, and I would write a clear hand off document covering configuration, proxy rotation setup, and alert customisation. Daily refresh is straightforward to implement and the architecture would support polling intervals as short as every few minutes with minimal rework. My pricing is negotiable and I am happy to provide a detailed cost breakdown after a short scoping call. I can also share examples of previous monitoring tools at that stage.

@markdennis19

Hi, Building exactly this kind of marketplace monitor is something I've done before — scraping, structured storage, price intelligence, and dashboards. My approach: - Python (Playwright + rotating proxies) for reliable anti-bot-safe scraping - PostgreSQL schema: model, year, mileage, grade, price, timestamps, source URL - Price-comparison logic: flag listings sitting below rolling 30-day median per model/grade - FastAPI backend + lightweight React dashboard with filters, search, and alert management - Email/push alerts on bargain detection - Celery + Redis for scheduled daily scrapes (easily scalable to hourly) - Dockerized deployment with full setup guide + handoff call Rate limits handled via request throttling, randomized delays, and proxy rotation — built to run stably long-term. Timeline: ~2–3 weeks Cost breakdown: scraper (40%), DB + logic (25%), dashboard (25%), docs/deployment (10%) Happy to share a similar project. What marketplace is it — BeForward, USS, or another? Best regards

@Anika1802

Hey! Drawing from my 5+ years of experience in developing web and mobile applications, particularly around API development and web scraping, I am adept at handling projects exactly like yours. My proficiency in Node.js and Python, backed by an understanding of Flask and Django frameworks, make me the right fit for your preferred stack. I can design a robust scraper for Marketplace A while mitigating bottlenecks through rotating proxies or headless browsers when necessary. My history with database schema construction will ensure efficient storage of important data such as pricing, mileage, year, model, grade, etc. Needless to say, I don't just build apps—I actually help businesses reach their goals. Attentively meeting your core requirement of comparing prices against recent sales to spot market below-average offers automatically entails I have to stay on top of anti-bot evasion strategies - another aspect that I'm experienced in. All these advantages plus my proven ability to deliver good work promptly within open communicative channels are why you should select me for the job. Let's collaborate and build something not only useful but also transformative that truly benefits your business!

@reimeiyuki

Hi — I'm based in Japan and read Japanese natively, so I can build this with an edge most bidders can't match: I'll actually understand the Japanese vehicle listings — model names, grades, trim, mileage units, seller wording — and parse them accurately instead of guessing. What I'll build (Python): 1. Anti-bot-safe scraper — I'll target the site's internal JSON API where it exists (far more stable than HTML scraping); proper headers, rotating proxies / headless where needed, polite throttling. Captures fresh ads as they appear and refreshes daily. 2. Structured PostgreSQL database (price, mileage, year, model, grade, timestamps). 3. Price-comparison logic that flags listings noticeably below recent-sale averages. 4. Lightweight dashboard — filter by model, year, mileage, grade — with email / push alerts on bargains. 5. Fully Dockerized: you run it on your own server with a single "docker compose up" — app + database start together. A clear written setup guide is included and I'll support setup over chat (no live session needed). I work milestone-based and send a small sample first (a few live listings scraped and parsed correctly) so you confirm data quality before I build the full pipeline. Included: a 14-day bug-fix window after delivery. Ongoing upkeep, if the site later changes its anti-bot defenses, is available separately. Two questions: which site is "Marketplace A", and does it expose a JSON API or require login / captcha? Delivery: ~7 days. Bid: ₹25,000. — Yuki