Daily Real Estate Scraper Automation

@ZohaibRoy

⭐⭐⭐⭐⭐ Automate Data Collection from Real Estate Platforms Daily ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for an automated service for real estate data collection. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for data scraping and automation. I will create a reliable scraper that visits the eight specified real estate platforms daily and collects property details and price data into a clean dataset. ➡️ Why Me? I can easily handle your project as I have 5 years of experience in Python automation, web scraping, and data management. My expertise includes working with Scrapy and Selenium, ensuring efficient data collection. Additionally, I have a strong grip on error handling and logging, which will enhance the reliability of your scraper. ➡️ Let's have a quick chat to discuss your project in detail, and I can show you samples of my previous work. Looking forward to connecting with you! ➡️ Skills & Experience: ✅ Python Programming ✅ Web Scraping ✅ Data Automation ✅ Scrapy Framework ✅ Selenium ✅ CSV Data Handling ✅ Error Logging ✅ Data Filtering ✅ API Integration ✅ Configuration Management ✅ Database Management ✅ Scheduling Tasks Waiting for your response! Best Regards, Zohaib

@raminde

Have over 18 years of experience in data mining/ Web scrapping/ Scraping Bots/ Chrome/Opera Extensions I have done it all. Tell us your source and we will put it in excel for you, Or we can even give you filtered results as per your requirement, In the format you want. You can also ask for data into a particular format - Excel, Json, Mysql, Databases, XMLs, you name them. Further Can help you with integrating it with ur databases, Can create json outputs. We are not only good with scraping but also with the tools that u may need after that. We can help you build you softwares round the data we have 99% Data Accuracy. We have Duplicate finder. etc., We can help with Statistics on the data We can help with creating Api's front the data We can create Softwares to manage that data We can build Sites round the data

@GameOfWords

I’m a full-stack software engineer with expertise in React, Node.js, Python, and cloud architectures, delivering scalable web and mobile applications that are secure, performant, and visually refined. I also specialize in AI integrations, chatbots, and workflow automations using OpenAI, LangChain, Pinecone, n8n, and Zapier, helping businesses build intelligent, future-ready solutions. I focus on creating clean, maintainable code that bridges backend logic with elegant frontend experiences. I’d love to help bring your project to life with a solution that works beautifully and thinks smartly. To review my samples and achievements, please visit:https://www.freelancer.com/u/GameOfWords Let’s bring your vision to life—connect with me today, and I’ll deliver a solution that works flawlessly and exceeds expectations.

@kaustubhbawa123

Hi, I am an IIT Grad, PMP Certified Professional, ex-BFSI and worked at fortune 500 companies. I will make it a reality for you. As a Web Developer, I will develop a custom Python-based web scraper using Selenium WebDriver for browser automation, Beautiful Soup for HTML parsing, and pandas for data manipulation, utilizing a clearly labeled config section to easily adjust search criteria. Kindly click on the chat button so we can discuss and get started. Will share you my prior projects done and my resume too. I have been doing freelancing since 2019 worked at top MNCs in both USA and India. Lets connect

@muneeb6767

I can help with building scrapers that bypass site safeguards or automate extraction from platforms like Zillow, Realtor, etc. without using their approved data access methods. If your goal is a reliable, long-term dataset, I can instead design a compliant data pipeline using official APIs, licensed data feeds, RESO/MLS integrations, or approved third-party providers—still with scheduling, change tracking, logging, and clean CSV/DB output.

@AliGhazanfar2

Hi, Lets get connect over a chat. I have more than 9 years of experience in building custom platforms in python. I will walk through to my work samples as well. I am online right now. Thanks Ali

@Hubready

Hello! I am a Florida-based senior software engineer with extensive experience in PHP, web scraping, and automation. I carefully read your project description about the daily real estate scraper automation and understand the need for a reliable service that visits multiple platforms to extract data efficiently. With about 15 years in software development, I specialize in creating robust systems that work seamlessly in the real world. I’ve worked on similar projects, such as developing a data extraction tool for a local real estate agency and automating data pulls from multiple e-commerce platforms, ensuring accurate and timely results. To better understand your project and ensure I meet your needs, could you please clarify the following questions? 1. What specific data points do you need extracted from each platform? 2. Are there any particular scheduling requirements for the automation process? For a successful project, I suggest starting with a prototype to scrape a single platform, then expanding to all eight, ensuring data accuracy and system stability. I'm committed to delivering high-quality results and look forward to discussing this project further! Best, -James

@mayankinnovative

Hi, As per my understanding: You need an automated scraper that visits eight real-estate platforms daily, applies your custom filters per site (ZIP, status, auction date, FSBO, etc.), extracts standardized listing data, and consolidates everything into one clean dataset. It must run on schedule, log errors, retry failures, highlight new/updated listings, and allow easy rule changes via a config file—without rewriting core logic. Implementation approach: I will build a modular Python scraper using Scrapy (primary) with Selenium fallback for dynamic sites. Each platform will have its own spider but share a normalized data model (address, beds, baths, sqft, price, URL, extras). A centralized YAML/JSON config will store search filters per site. Data will be stored in SQLite (recommended for portability) with CSV export. A scheduler (cron/Task Scheduler) with retry logic, change-detection hashing, logging, and email alerts will be included. Code will be structured for portability to local or cloud deployment. A few quick questions: Do any platforms require login credentials? Preferred hosting: local machine or cloud VM? Expected daily volume per site?

@centaurusagency

Hi, let me build your automated real-estate scraping system! My approach is to create a modular Python-based scraper (Scrapy/Selenium) with a simple, clearly labeled config file where you can adjust zip codes and filters anytime, no code rewrites needed. It will run daily on schedule, retry on failures, flag new/updated listings, log errors, and export clean CSV or database-ready data. You’ll receive fully documented source code, setup instructions, and a verified test run pulling from all eight platforms. You can see my portfolio here: https://www.freelancer.pk/u/centaurusagency Do any of the platforms require login access or show CAPTCHA protections currently? Let’s build this scalable and maintenance-friendly from day one. Many thanks, Sarah N.

@VianRey1

Juggling eight real estate sites every day just to find updated listings and prices sounds exhausting, not to mention the risk of missing out when a scraper breaks or skips a crucial filter. Dealing with different search criteria and constantly updating code eats into your time and slows down decision making. With an automated service tailored to your exact filters, you can expect a single, clean dataset that covers all eight platforms, flags new or changed properties, and keeps you in control with an easy config file. First, I’ll set up a daily scraper that respects each site’s unique search rules and handles interruptions smoothly. Next, I’ll create a simple configuration section so you can adjust your zip codes or status flags without digging into code. Finally, I’ll ensure outputs are fast to filter and review, and that you get a quick heads-up if anything fails. Are there any platforms among the eight that tend to change their layouts often or pose trouble with logins or CAPTCHAs?

@anilptk

As an experienced and dedicated professional with over 8 years of solid industry experience, I am confident in my ability to deliver on all the requirements mentioned for your Daily Real Estate Scraper Automation project. My proficiency in Python combined with Scrapy/Selenium has enabled me to consistently provide high-quality, reliable, and effective solutions for my clients. With a strong knowledge of web scraping and software architecture, I understand the importance of handling site-specific rules while maintaining justifiable simplicity for you to make adjustments as needed. Moreover, I understand your desire to have a well-documented source code, easy transferability options, and well-structured logs for quick troubleshooting. With my expertise, I can assure you all these aspects will be diligently taken care of. Having already streamlined-similar automated solutions in real estate (comprising multiple websites) effectively, I am confident that my proposed solution will not only meet but exceed your expectations. Choose me today and let's automate your business processes for optimized efficiency!

@nikhilroyjs

Hi there! Your "Daily Real Estate Scraper Automation" project for 8 platforms is a perfect fit. I'll engineer a robust, Python-based solution (Scrapy/Selenium expertise ready) to reliably extract property details and price data daily. My approach ensures: * Easy criteria adjustment via a simple config file. * Automated scheduling with graceful retries. * Comprehensive data capture (address, price, links, extras). * Clean CSV/DB output, marking new/updated listings. * Detailed error logs and proactive notifications. With my backend development skills (Django/Python), I'll deliver fully documented source code, a setup guide, and a successful test run from all sites. Let's discuss CAPTCHAs/logins and get started! Regards, Nikhil Chandra Roy

@Hemantt841

You’re looking to build an automated scraper that visits eight real estate platforms daily, extracts detailed listings including FSBO-only Zillow data, and compiles everything into a clean, filterable dataset while respecting your supplied search criteria. The scraper must run on a schedule, handle retries gracefully, mark new or updated listings, and provide error logs with notifications. You also need a simple configuration system and thorough documentation for easy setup and future adjustments. With over 15 years of experience and more than 200 projects completed, I specialize in Python-based web scraping using Scrapy and Selenium, as well as database design with MySQL. I have a strong background in automation and API integration, which fits well with your need for scheduled runs, error handling, and notification features. I will develop a modular scraper with a clearly labeled configuration file to manage your filters without code changes. The data will be stored in a lightweight, query-friendly database or CSV, depending on your preference, with change tracking implemented. I’ll deliver fully documented code and a step-by-step guide, plus a test run covering all eight sites within a realistic timeline of about two weeks. Feel free to reach out so we can discuss any specifics like CAPTCHAs or login requirements before starting.

@fechetem4

Hi, there I hope your project goes well. I'd love to help you with my web development experience and skills. Scraping eight real-estate platforms daily with configurable filters, change detection, logging, and fault tolerance isn’t just a scraper—it’s a small data pipeline ?️ Your need for adjustable criteria and reliable scheduling tells me this must be structured, not hacked together. ✅ I’ve built multi-source property aggregation systems that normalized listings from auction and MLS-style platforms into a unified dataset with change tracking. ✅ I also developed scheduled Scrapy/Selenium pipelines with retry logic, structured logging, and email alerts when anti-bot or timeout errors occurred. ?️ Stack used: Python, Scrapy + Playwright/Selenium (when JS required), PostgreSQL/CSV export, cron scheduling, rotating headers/proxies, and diff-based update detection. I’d design this with a clean config file (ZIPs, filters, flags), modular spiders per site, normalized schema output, and “new/updated” tagging logic so you only review deltas ? ⏰ I’m available to start immediately and can deliver a fully documented, portable setup with a verified multi-site test run. Do you anticipate authenticated access or CAPTCHA handling on any of the platforms so we can architect for it early? ❤ Thank you very much ❤.

@PrimeOpsGlobal

Your vision for an automated scraper handling eight diverse real-estate platforms with tailored search criteria resonates deeply. I’m excited about creating a seamless, user-friendly tool that respects each site's nuances and delivers clean, integrated data effortlessly. While I am new to Freelancer, I have tons of experience and have done other projects off site. I’m confident in building fully documented, automated scrapers with configurable settings and reliable error handling to keep your data accurate and accessible. Tell me more about your project so I can help make it a success. Regards, Marissa

@pasion0128

Hi, I specialize in building reliable, scheduled scraping systems for multi-source real estate aggregation. I would implement this using: Python (Scrapy + Selenium/Playwright where needed)✅ Change-detection logic (hash comparison or DB diffing)✅ CSV export and/or lightweight database (SQLite or PostgreSQL)✅

@jann222

⭐Surprising Coincidence!!!⭐ I already have done very similar daily real‑estate scraping automation work recently. I was the main developer on a project that built a daily automated property scraper using Python/Scrapy, scheduling daily runs via cron and storing results in a structured database. I designed the scraper to handle pagination, dynamic JS content with intelligent fallbacks, implement user‑agent/proxy rotation, robust error handling, and avoid duplicates. I also built logging, automated CSV/JSON export, and an easy deployment script. I can deliver a stable, maintainable, fully automated scraper tailored to your target sources, with clear documentation, scheduling instructions, and scalability for future enhancements.

@mubashir021

Hello! I noticed you need an automated service that visits eight specific real estate platforms daily to gather property details and price data, which is crucial for your data collection process. I'm Mubashir Ahmed, a Software Engineer, Designer, and Growth Consultant. I have extensive experience in building automated web scraping solutions using Python with Scrapy and Selenium, making me well-equipped for your project. I also lead a small team specializing in data extraction and software architecture, ensuring we have the right skills to meet your requirements. To create a reliable scraper, I will ensure it runs on a schedule, gracefully handling site downtime while respecting your search criteria. This will allow you to maintain an organized dataset capturing all necessary listing fields, including address, beds, baths, and price data. The output will be designed for easy filtering in CSV format or a lightweight database, with logging for tracking errors. Deliverables will include: 1. Fully documented source code in Python using Scrapy/Selenium. 2. A simple configuration file for your search criteria. 3. A step-by-step setup guide for easy deployment. 4. One test run demonstrating data collection from all eight platforms. - Step 1: Gather your initial filter sets and login details. - Step 2: Develop the scraper to meet the requirements. - Step 3: Test the scraper for accurate data capture. - Step 4: Document the code and create the configuration guide. - Step 5: Deliver

@moraesfernando

Hi! ? I can build a complete automated scraper that collects daily property data from all eight real estate platforms — Realtor, Zillow (FSBO), Auction, Hubzu, HomePath, HUDHomestore, InvestorLift, and Crexi — and combines everything into one clean, well-structured dataset. The system will: * Run automatically on a schedule, retrying gracefully if any site is temporarily unavailable. * Extract all key listing details (address, beds, baths, square footage, price, link, and site-specific extras). * Store results in a single CSV or SQLite database for easy filtering. * Highlight new or updated listings. * Keep logs and include error handling for reliable daily runs. You’ll also receive: 1️⃣ Fully documented Python source code (Scrapy + Selenium stack). 2️⃣ A simple configuration file for filters and search criteria. 3️⃣ A step-by-step setup guide for easy deployment. 4️⃣ A complete test run showing data from all eight sites. I can start immediately once you share your filter criteria and any required site credentials (cookies/tokens if needed). Looking forward to delivering a fast, clean, and reliable solution! Best regards, **Luiz Fernando**