AI Web Scraping & CSV Merge

@imraz2016

Hi There, I have strong experience with Python web scraping, Playwright, BeautifulSoup, pagination handling, dynamic search URLs, redirects, deduplication, and CSV automation. I can build a fully headless reusable scraper that processes every supplied URL, extracts Name, Contact information, and Address, logs skipped records with reasons, and outputs one clean UTF-8 master CSV ready for Excel or Google Sheets. I can also include a short README so you can rerun future batches yourself. I’m happy to review the sample URL first and confirm the best approach based on its structure and rate limits.

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Dynamic URL Scraper for Business Listings ❇️ Hi My Friend, I hope you are doing well. I just checked all of your project requirements and I can see you are looking for a dynamic URL scraper. You have no need to look any further as Zohaib is here to help you! My team has successfully completed 50+ similar projects for web scraping. I will create a reusable script to pull names, contact information, and addresses from your URLs, ensuring everything is well-structured in a master CSV. ➡️ Why Me? I can easily do your web scraping project as I have 5 years of experience in Python, web scraping, and data management. My expertise includes working with pagination, filters, and handling redirects. I also have a strong grip on other relevant tools like Beautiful Soup and Playwright. ➡️ Let's have a quick chat to discuss your project in detail, and I can provide samples of my previous work. Looking forward to discussing with you in chat. ➡️ Skills & Experience: ✅ Python Programming ✅ Web Scraping ✅ Data Extraction ✅ CSV File Handling ✅ Pagination Management ✅ Error Handling ✅ Data Deduplication ✅ API Integration ✅ Automation Scripting ✅ Data Cleaning ✅ Pattern Recognition ✅ Headless Browsing Waiting for your response! Best Regards, Zohaib

@farhanyoussef18

Youssef, Full-Time Python Developer, expert in Playwright and data extraction. You need a script to pull Name, Contact, and Address from your dynamic, paginated business listing URLs into one master CSV. I'll use Playwright to handle the search parameters, pagination, and redirects in a fully headless browser, then structure and deduplicate the data into your required CSV format. I've completed many similar projects scraping structured data from dynamic sites. Could you send me the sample URL so I can confirm the exact page structure and fields? Ready to start immediately.

@mjanchi

Hello there, as you can see from my profile I have experience in similar projects. Please contact me for more info Thanks

@Tanmoy236

Good day! Dynamic, search-driven databases require a scraper that can reliably handle pagination, redirects, filtering, and changing URL parameters, and that's exactly the type of workflow I specialize in. I can develop a fully headless, reusable scraping solution that extracts the required fields, consolidates the results into a single deduplicated UTF-8 CSV, and maintains detailed logs for skipped records or extraction failures. The script can be structured to process future batches with minimal changes while remaining easy to maintain and rerun. My approach focuses on accuracy, scalability, and resilience against rate limits and inconsistent page structures. I'm happy to evaluate the sample dataset and discuss the most appropriate scraping strategy before moving forward.

@ShaikhAneesa

Hi there, I have carefully reviewed the project requirements for the AI Web Scraping & CSV Merge task. I understand the need to extract specific fields from dynamic URLs containing business listings and people records, consolidating them into a structured master CSV. Let's chat and discuss it further. To handle your project, I will start with developing a Python script using tools like Ultimate Web Scraper or Beautiful Soup for efficient automation. The script will navigate through pagination, filters, and redirects to extract Name, Contact information, and Address accurately, ensuring a seamless merge into a clean CSV. The deliverables will include a reusable Python script, a consolidated CSV with the required columns, and a user-friendly "how-to-run" guide for future use. Before signing-off my bid, I would like to ask a question, i.e., what is the expected frequency of updating the URL lists for scraping? Warm Regards, Aneesa.

@asifdwan

Hi, I can handle this workflow using Python with Playwright/BeautifulSoup as needed. I’ll build a fully headless, reusable scraper that processes your dynamic URLs, handles pagination, filters and redirects, extracts Name, Contact Information and Address, and consolidates everything into a UTF-8 CSV. I’ll include deduplication, skipped-record logging with reasons, sensible rate limiting, retries, and a simple README so you can reuse the script with future URL lists. I’m also happy to complete the **165-listing sample trial** first so you can evaluate the extraction quality before moving forward with larger batches. Please PM me the sample URL and I’ll take a look at its structure and complexity before confirming the fixed price for that scrape.

@intelliresponse

Hello, I understand the real complexity here isn't just extraction — it's handling dynamic, parameter-driven URLs with pagination, filters, and redirects reliably, while keeping the output clean enough to import with zero manual cleanup. My approach: Scraper Engine: Python with Playwright (headless) for dynamic pages, Beautiful Soup for parsing — built to handle search parameters, pagination loops, and redirect chains automatically. Data Extraction: Consistent parsing logic for Name, Contact, and Address fields, with fallback handling for varied listing layouts. Data Quality: Deduplication, UTF-8 encoding, and clear skip-logging (with reason) for any incomplete records — no blank rows in the final CSV. Reusability: Clean, parameterized script so future URL batches run with a single command, no browser window required. Delivery: Consolidated master CSV plus a simple how-to-run README. I bring solid experience building resilient, headless scraping pipelines for dynamic, listing-based sites with clean data output. Best regards

@vano101

Hi, This is a good fit for my scraping experience. I can build a reusable Python scraper that processes your URL list, handles search parameters, pagination, filters and redirects, and extracts the requested Name, Contact information and Address into a single clean, UTF-8 CSV. I normally use Playwright/Selenium, BeautifulSoup and requests depending on how each site works, and can keep the entire workflow fully headless. I’ll also include deduplication, validation, skipped-record logging with reasons, and a simple README so you can run future batches yourself. The free trial is absolutely fine — I do similar sample scrapes for most of my web-scraping projects. Please PM me the sample URL with the 165 listings, and I’ll review it and confirm the best approach, expected complexity, and rate-limiting considerations. I’m ready to start once I have the sample URL.

@justmian876

As the lead developer at BN-Droids Digital Services with a strong focus on web scraping and data extraction, I can assure you that we're the perfect fit for your AI Web Scraping & CSV Merge project. Our team has extensive experience in handling large-scale web scraping with great accuracy and efficiency, which is exemplified by our ability to process over 1 million+ data records daily. We've successfully built and managed databases containing 20+ million business and retail data records from various regions including the USA, UAE, Europe, Australia, and Canada.

@onlinejob247

Hi there, I have already checked the project details. The job is clear, so please contact me, and then we can discuss. Thank you.

@softsolution2000

Hi, the pagination-plus-redirect part on search-driven URLs is the bit that actually determines whether this holds up across your full list, so that's what I'd test first with your 165-listing sample. I'd build it headless in Python with Playwright for the dynamic pages and requests/BS4 where sites allow it, logging any row I can't fill instead of leaving it blank, then dedupe into one UTF-8 CSV with a short read-me for rerunning on new URL batches. My team's done similar scraping and automation work across client projects for years (774 jobs completed, 4.87 stars), so headless pipelines like this aren't new territory. Send the sample URL and I'll run the 165 listings so you can see the CSV output before we agree on per-scrape pricing.

@kelvinm094

Hello, I’ve reviewed your AI Web Scraping & CSV Merge project and I’m confident I can deliver a robust, headless solution that scales for future batches. With Python-based automation, I’ll build a reusable Scrapy-driven scraper that navigates dynamic URLs, handles pagination and redirects, and outputs a clean CSV with Name, Contact, and Address in UTF-8, deduplicated. Deliverables include a reusable script, a consolidated CSV, and a concise how-to-run guide to re-run on fresh URL lists. I’ll ensure 100% URL coverage with no blank rows, and log skipped records with reasons. Let’s confirm the dataset readiness and I can start immediately; delivery in 2 days. Best regards, Team

@ahmadayaz

I propose developing a custom Python web scraping solution to extract Name, Contact information, and Address fields from dynamic URLs with searchable databases. Using tools like Playwright or BeautifulSoup, the script will automate data extraction, handle pagination, filters, and redirects efficiently. The solution will include a headless scraper script to crawl through URLs, extract data fields, and consolidate them into a well-structured CSV file. The script will be reusable, ensuring flexibility and ease of use for future tasks. Key features include processing all URLs, avoiding blank rows in the output, and logging skipped records with reasons. The final CSV will be deduplicated and UTF-8 encoded for easy import into Excel or Google Sheets. In addition to the script and CSV, a detailed guide on running the scraper will be provided for independent use. Project timelines and rate-limiting precautions will be tailored based on data volume and complexity. With expertise in web scraping and data processing, I am well-equipped to handle your requirements efficiently. Let's collaborate to ensure a successful data extraction process for your dynamic URLs.

@PINESCRIPTERR

Hi, I can build this as a reusable Python scraper that reads your spreadsheet, processes every dynamic URL, and produces one UTF-8 master CSV with Name, Contact, and Address. I’d inspect the sample URL first to determine whether the data comes from HTML, embedded JSON, or an authorised network endpoint. The scraper would use Requests and Beautiful Soup where possible, with headless Playwright only for pages that require JavaScript interaction. Pagination, filters, redirects, retries, timeouts, and resumable checkpoints would be handled explicitly. Each URL would receive a final status in the run log. Records missing a required field would be excluded from the master file and logged with the URL, page, and reason. Deduplication would use normalised names, phone numbers, emails, and addresses while retaining the original display values. I’ll also prevent duplicate pagination loops and validate the final row count before export. Rate limiting will use bounded concurrency, delays, retry backoff, and response monitoring so the run remains stable and respectful of the source. The workflow will use public or authorised access only and will not bypass CAPTCHAs, login controls, or site restrictions. I can review the 165-listing sample to confirm selectors, pagination behaviour, expected output quality, and the fixed rate for that source. The handover will include the script, dependency file, configuration, CSV, logs, and concise run instructions. Regards, Houssame

@DeveloperStation

Hi, Headless Python scraping with Playwright for search-parameter URLs is squarely what I do, including pagination, filters and redirect handling. One question before the trial: are the databases behind any login or CAPTCHA, and do the URLs share one site structure or vary per source? That decides whether one parser handles all links or each needs its own extraction rule, which is the real complexity driver here. We've built AI-driven automation workflows that pull records and structure them cleanly, combining Claude and OpenAI for pattern recognition with database output. BD Automation: internal MangoCoders project, Claude API driven Send me the 165-listing sample URL and I'll return a deduplicated UTF-8 CSV plus a short read-me. What's the field format in your source rows? Adil

@maxscender

I can help you turn that dynamic URL list into a single, clean master CSV. I’ll build a headless Python scraper that handles pagination, search parameters, and redirects, pulling Name, Contact, and Address from each record. The script will be built for reuse—you’ll just drop in a new URL list and it runs. I’ll prioritize data integrity and clean output: the final CSV will be deduplicated, UTF-8 encoded, and ready to open in Excel or Sheets without any cleanup. Any record that can’t be fully captured will be logged separately with the reason, so you can see exactly what was skipped and why. The approach is straightforward: a robust scraper with error handling baked in, not a one-off script. I’ll also include a short README so you can run future batches yourself in any environment. My focus is on delivering a working, reusable tool that meets your acceptance criteria.

@hoangnn90

✅Full Experience in Web Scraping and Data Extraction Automation with Python Programming✅. ✳️I am very confident that complete your project perfectly. ✳️I can guarantee the quality of the job and deliver the result on time. I hope we will discuss in more detail via chat. Best regards!

@techplusintl

★★★ PYTHON SPECIALIST ★★★ Hi, I can create a script to pull Name, Contact information, and Address from your dynamic URLs for your business listings. I will use Python to build a reusable scraper that handles pagination and filters. It will output a clean CSV file with no blank rows and a brief guide on how to run it. Let’s discuss the timetable and any precautions you have in mind. Thanks!

@zafarfarooq612

Hello, I am a web scraping specialist who will build a reusable Python script (using Playwright/BeautifulSoup) to process your dynamic URL list, extracting Name, Contact, and Address from each search‑based database, handling pagination, filters, and redirects. The script will be fully headless, deduplicate, and output a clean UTF‑8 CSV with no blank rows (skipped records logged). I will provide a “how‑to‑run” read‑me. I can start with your free trial (165 listings) immediately. Please PM me the sample URL and any login/headers. I can start immediately. Thank you. I am available for ongoing work. Regards, Zafar