Inventory Monitoring System

@kchoudhary95

Hello, I’m Kamlesh Kumar, a Full Stack Web Developer with 7+ years of experience building scalable and high-performance web applications. My main expertise is in PHP-based backend systems and modern frontend frameworks, helping businesses build reliable and maintainable platforms. Core Expertise Backend Development - PHP (Core PHP, CodeIgniter, Laravel) - Node.js - Python Frontend Development - React.js - JavaScript, HTML5, CSS3 - Bootstrap and modern UI frameworks Database - MySQL - PostgreSQL - MongoDB What I can help you with - Custom web application development - REST API development & integrations - Admin panels and dashboards - Performance optimization and bug fixing - Scalable backend architecture I focus on building clean, maintainable code and stable systems that can scale as your business grows. If you’d like, we can discuss your project requirements and determine the best approach to move forward. Best regards, Kamlesh Kumar

@toni5705

Hi, I reviewed your project and this is a solid use case for building a structured monitoring system rather than simple scraping scripts. We’ve worked on similar data pipelines where the goal is to collect, normalize, compare, and turn data into actionable reports. For the MVP, the approach would be: Build a scalable data collection layer capable of handling different website structures, including dynamic pages Normalize vehicle data into a consistent format across dealerships Implement a comparison engine to detect new listings, removals, and price changes Generate automated daily reports (Google Sheets or email-based) Structure the system so adding new dealerships is straightforward The focus would be reliability and maintainability from the start, ensuring the system can scale from 10 to 50+ dealerships without major rework. Quick question: Do you already have preferred output format (Sheets vs email), or should we propose the most practical setup for the MVP? We can also share similar automation and data processing work in a call. If it makes sense, the next step would be to align on the MVP scope and define the implementation plan. Best regards.

@sunainawbst

Inventory Monitoring System Hello This is a well-defined and highly practical system, and I’ve worked on similar data monitoring and scraping platforms where reliability, comparison logic, and scalability are more important than just scraping itself. Your goal of evolving this into a market intelligence platform is exactly how I would approach the architecture from day one. Timeline Phase 1 (MVP – 10 dealerships): Day 1–2: Setup architecture + base scraper Day 3–6: Scrapers for 10 sites Day 7–8: Comparison engine Day 9: Reporting system Day 10: Testing + delivery I would love the opportunity to discuss how we can bring your vision for the site together with our range of skills and experiences. NOTE: This is only a placeholder bid amount that we will discuss on chat. Thanks & Regards Ranjana

@Microlent

Hi, Automated monitoring across multiple websites with daily comparison and reporting is exactly the kind of system I have built before. I recently completed a Python data pipeline that processed around 100k user records per batch, compared datasets, flagged changes and generated structured outputs with a full audit trail. Same core logic as what you need here, pull data, compare against previous, report what changed. For your system I would use Python with Playwright or Selenium for the dynamic JavaScript sites, store daily snapshots in a lightweight database like SQLite or PostgreSQL, run the comparison logic to flag new listings, removed listings and price changes, and output a daily report to Google Sheets or email depending on what works best for your team. Starting with 10 dealerships and building the architecture to scale to 50 plus without rebuilding anything. The part that needs the most care is making the scraper resilient when sites change their layout. I would build each dealership as a configurable module so adding a new one or fixing a broken one does not touch the core system. Documentation for adding new dealerships included. I have a long term mindset on projects like this. A monitoring system that runs daily needs someone who will keep it healthy, not just ship it and disappear. Can you share the initial dealership list so I can assess the site structures before quoting? Jenifer

@Feriver

Hello, I will build a reliable inventory monitoring system that automates scraping, comparison, and reporting across dealership websites. Using Python (Scrapy/Playwright) + PostgreSQL, the system will extract structured vehicle data daily, even from dynamic JS-based sites, with fallback strategies for anti-scraping scenarios. The core logic will store daily snapshots and perform efficient diff analysis to detect new, removed, and price-changed listings. Output will include a clean consolidated report (Google Sheets + email) with dealership summaries and detailed change logs, ensuring immediate business value with minimal manual effort. The system will be modular and scalable, with clear configuration to onboard new dealerships quickly. Documentation will cover adding sources, selectors, and handling layout variations. Designed for stability, retries, and logging to support scaling from 10 to 50+ dealerships seamlessly. Thanks, Asif

@corpmember29

HELLO, I HAVE CAREFULLY REVIEWED YOUR REQUIREMENT FOR AN INVENTORY MONITORING SYSTEM FOR BLINDADOS.NET. With 10+ years of experience in web scraping, automation, and data monitoring systems, I can build a reliable and scalable solution to track listings, price changes, and inventory updates across multiple dealership websites. APPROACH → I will develop the system using Python (Scrapy/Playwright) or Node.js (Puppeteer) to handle both static and dynamic websites. Data will be collected daily, normalized, and stored in a structured database. A comparison engine will detect new listings, removals, and price changes. Reports will be generated automatically via Google Sheets and/or email with clear summaries and detailed logs per dealership. The system will be built to handle different site structures, include retry/fallback mechanisms, and be resilient to minor layout changes. Documentation will be provided to easily add new dealerships. I WILL PROVIDE 2 YEAR FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE. WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STORES. The architecture will be scalable for future expansion (50+ sites) and enhancements like alerts and dashboards. I eagerly await your positive response. Thanks.

@mubeenm5026

As a seasoned developer with over a decade of experience, I'm well-versed in projects just like yours. The heart of my expertise lies in automation and Python, converting complex manual endeavors like your current inventory tracking system into simple, efficient, and scalable solutions. My team and I at Web Crest have a practical mindset tailored towards solving real business problems, and your project meshes perfectly with our ethos. In particular, my experience with web scraping and browser automation will be invaluable as we tackle the dynamic nature of each dealership's website structure. I understand that some sites may pose challenges due to their unique layouts or the presence of scraping protection, but rest assured that we are resilient to these changes. What sets our partnership apart is our commitment to long-term success. Not only will we develop a fully functional automated system that meets your MVP requirements and delivers clean and organized code, but we'll also provide clear documentation on how to onboard new dealerships. In fact, envisioning this project's potential evolution into an internal market intelligence platform, I can confidently say that my team and I are invested in your business's growth and future needs. Let's make something transformative together.

@johnallenvillan1

Hello, your plan to start with 10 dealerships and scale toward 50+ shows you need a system built with flexibility and resilience from day one. I’ve built similar multi‑source scraping pipelines where I delivered daily change‑tracking reports and automated data normalization across inconsistent dealership sites. I know the real challenge here isn’t just scraping , it’s handling dynamic layouts, anti‑bot patterns, and ensuring the comparison logic reliably matches vehicles even when fields shift or data is incomplete. I’ll structure the MVP using Python, Playwright for dynamic rendering, and a lightweight database to store daily snapshots. I’ll implement robust selectors, change‑detection logic, and a reporting layer that pushes consolidated diffs to Google Sheets or email. Documentation for adding new dealerships will be kept modular so your team can extend it later. Before building, I want to confirm any constraints around hosting, rate limits, and whether any dealership uses API‑based inventory feeds. This can be delivered cleanly and without operational overhead from your team. Thanks, John allen.

@quan9824

As a Full-Stack Developer, my expertise in web scraping and automation, as well as my ability to handle dynamic websites using JavaScript rendering will be highly valuable for your Inventory Monitoring System needs. I have a 100% track record of delivering quality projects on time, which is a testament to my skills in problem-solving, debugging, and adapting to new technologies - all indispensable skills for this project. I understand the key challenges outlined: scraping protection, different website structures, and resilience to minor layout changes. Rest assured, I am no stranger to these challenges and have successfully overcome them in previous projects. Additionally, I am committed to writing clean, maintainable code with clear documentation - the latter being particularly important when adding new dealerships. Finally, although this project starts with monitoring just 5 dealerships it has the potential to evolve into something larger. As someone with a long-term mindset, I am excited about this possibility and ready to step up to meet any future market intelligence features you may require. My aim is always not just to do a task but also deliver practical solutions that enhance business operations. Let's work together on transforming your inventory monitoring process!

@AvinaHSinha7

Hi, I can build a scalable Python-based system to monitor dealership websites, track new/removed listings and price changes, and generate a clean daily report. I’ll use a mix of lightweight scraping and Playwright where needed, with a structure that makes adding new dealerships simple. The MVP will include data collection, comparison logic, and reporting via Google Sheets or email, with clean and maintainable code. Ready to start now. Let’s connect over chat to review the initial dealership list and begin. Best regards, Avinash

@Julian29

Hello, {{{ I HAVE CREATED SIMILAR APPS BEFORE AND I CAN SHOW YOU }}}} I have carefully reviewed your requirement for an Inventory Monitoring System and clearly understand the need to automate dealership data tracking, detect new/removed listings, and monitor price changes with daily reporting. With 10+ years of experience in relevant technologies, I have built similar web scraping and data monitoring solutions that handle multiple site structures, dynamic content (JavaScript), and scalable data comparison logic. I will develop a robust system using Python (or Node.js if preferred) with automated scraping, structured data storage, and daily report generation (Google Sheets/email/dashboard as required). The solution will be modular, making it easy to add new dealerships and resilient to minor website changes. I WILL PROVIDE 2 YEAR FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE. WE WILL WORK WITH AGILE METHODOLOGY AND WILL GIVE YOU ASSISTANCE FROM ZERO TO PUBLISHING ON STORES. I am confident in delivering a clean, maintainable, and scalable solution aligned with your MVP and future expansion goals. I eagerly await your positive response. Thanks.

@Friends4it

I have extensive experience with web scraping and automation. I'll build your inventory monitoring system using Python with Selenium and BeautifulSoup for dynamic site handling, PostgreSQL for data storage, and automated daily reports via email or Google Sheets. The system will track new listings, removed vehicles, and price changes across all dealerships. I'll include anti-detection measures, proxy rotation, and clear documentation for adding new sites. Timeline: 10-14 days for MVP with 10 dealerships. Ready to start immediately.

@Ekarthaan

Hi Ricardo F., This is quite similar to a project I delivered last week, so I can jump straight into execution. Ready to start immediately. - For stable vehicle identity across days and URL changes, do you have VIN/chassis or internal listing IDs available on most sites, or should we infer a composite key (dealer + normalized title/year/mileage + URL hash)? - Are any target sites behind logins/CAPTCHAs, and what is your required daily cutoff time/timezone for report delivery? - Use a config-driven “dealer adapter” pattern: selectors and pagination rules in JSON/YAML, executed by a hybrid crawler (Requests/BS4 for static pages, Playwright with stealth/proxy rotation for JS-heavy sites). This minimizes code changes when layouts shift. - Store data in a small Postgres (SQLite for MVP) with normalized vehicle table, daily snapshots, and a change_log. Persist raw HTML/JSON for auditability. Index on the chosen unique key to keep diffs fast as you scale to 50+. Action Plan: - Phase 1 (MVP, 10 dealers): Define schema and unique ID rules; build adapter template; implement 10 adapters (pagination, BRL price normalization); diff engine (new/removed/price change); daily run at agreed BRT time; outputs to Google Sheets + email; clear “add a dealer” docs. - Phase 2 (Scale): Dockerize; scheduled runs (Cloud Run/Scheduler or cron); concurrent crawling with rate limits; rotating proxies; health checks and alerting; selector configs for quick fixes Best Regards, Sid

@artakharutyun7

Hi, I can build a reliable inventory monitoring system focused on accuracy and scalability from day one. I’ve developed similar scraping and change-detection systems where multiple sources with different structures are normalized into a single dataset and compared daily to detect new, removed, and updated records. The key is not just scraping, but stable parsing + consistent data modeling. "Approach" • Python-based scraper using Playwright (handles dynamic sites + anti-bot cases) • Per-site extractor modules (isolated logic → easy to maintain) • Normalized data model (vehicle ID via URL/hash to track changes reliably) • Daily snapshot storage (PostgreSQL or lightweight DB / Google Sheets for MVP) • Diff engine to detect new / removed / price changes • Output: automated Google Sheet + daily email report System will include: • Retry logic, rate limiting, and basic anti-blocking measures • Resilient selectors (fallback strategies for layout changes) • Clear structure to easily add new dealerships This will be built as a clean, extensible system ready to scale to 50+ dealerships without rework. Best regards, Artak

@juanestebana17

Hi, With extensive experience in web scraping and automation, I am confident in developing a reliable system that automates dealership website monitoring and generates detailed daily reports to streamline your inventory management. Could you clarify the preferred output format for the daily reports (e.g., Google Sheets, email, dashboard) to tailor the solution accordingly? Thanks, Juan Aponte

@hotanloc

Your project is just my project so I will always do my best to meet your all requirements. I checked your project details carefully. With my core skill Python or JavaScript, I have finished Web Scrapting project which extract product name, product price, product date and product selling number from real Online Product selling site and save this to excel or goofle sheet for uploading into client's google driver a few days ago. I have rich experienced in Web Scraping, Data Extraction, Machine Learning (ML), Data processing, using Python and Artificial Intelligence. I have full experience to develop python code for extracting the specific data from web site with python, HTML, CSS and JavaScript. If you give me your project, You can get best result with shortest time and best quality result. I am sure for your project and i can complete your project perfectly on time and with high quality. Please send me your message to discuss more about your project. I am waiting your reply now. Thanks.

@MiguelLam

Hi Mr, I have worked in vehicles systems for inventory management and also scrapping of another companies which is similar to what you describe here; so Im sure I can help you get what you need here. Kind regards.

@sasaprogramer21

I can help you build an automated system that tracks dealership website listings, identifies changes, and generates daily reports. Using Python, I will implement web scraping with libraries like BeautifulSoup or Selenium for dynamic sites to gather vehicle data such as price, model, and dealership information. The system will compare daily data with the previous dataset to identify new, removed, or price-changed listings. Reports will be generated in formats like Google Sheets or email, summarizing key changes. The system will be flexible enough to handle multiple dealership websites and resilient to layout changes. Approach Backend using Python with BeautifulSoup and Selenium Storage using Google Sheets or lightweight database like PostgreSQL Reporting with Google Sheets and email reports Data comparison to detect new, removed, and updated listings Timeline Phase 1 (MVP): 2 to 3 weeks for scraping, comparison, and basic reporting Phase 2 (Scaling): 3 to 4 weeks to scale to 50+ dealerships The system will be efficient and scalable, with documentation for adding new dealerships. Best Alex

@Tanmoy236

Hi! I’m an expert Python and web automation developer with 9+ years of experience building reliable inventory monitoring and data scraping systems for marketplaces. Here's how I can help: * Automate daily monitoring of dealership websites, detecting new, removed, or updated listings * Extract key vehicle data (title, price, year, mileage, URL, dealership, date) and compare with prior datasets * Generate consolidated daily reports via Google Sheets, email, or simple dashboards * Build a scalable, maintainable system that can expand from 10 to 50+ dealerships Could you confirm if the target sites use heavy JavaScript or anti-scraping measures so I can plan the automation approach accordingly?