Python Automation to Populate Team Details from Company Website

@SamirBanna

I am very interested in applying for your job since it seems to fit very will with my experience and skills. Regards SamirBanna

@Badhan685

Hi, I have read the job description and now ready to start. I will provide 100% quality. Please send me a message for discussion. Let's discuss the job. Thanks

@ikhan9985

Hi, I have eight years of experience in the field of web scraping and computer vision. I can do this task with in 3 hours as estimated. Could we discuss more about this task?

@bitwiz

I CAN. Having successfully delivered over 80 projects on this platform with a consistent 5-star rating, I specialize in building high-speed, robust Python automation scripts using Playwright and asynchronous concurrency to handle large-scale data extraction. I will implement a multi-threaded scraping architecture equipped with regex keyword matching to scan all 4,300+ domains, accurately extracting the numeric staff count or populating the required fallback string into your Excel file. I am an independent Python expert, available to begin immediately, and fully capable of delivering the completed spreadsheet along with the clean source code within your strict 5 to 6-hour deadline today.

@kjayatissa

I CAN Playwright + async Python, openpyxl for Excel read/write. Here’s exactly how I’d handle this: Each site gets crawled in two passes: first the homepage to find team/leadership/about/people links via keyword matching on anchor text and hrefs, then the target page to count visible person cards using heuristics like repeated card patterns, headings with names, photo grids, and structured markup. Headless Chromium handles JS-heavy sites. Concurrency set to 20-30 parallel workers with per-domain rate limiting so we don’t get blocked. Progress saved to a checkpoint file every 100 rows so if anything crashes mid-run we resume from where we left off. For 4,300 URLs at ~8-12 seconds average per site with 25 concurrent workers, realistic wall-clock time is 4-5 hours. I’d deliver the completed Excel with only the Team Details column populated, everything else untouched. Expected success rate: 70-80% with accurate counts, another 10-15% returning “No Team Page Found” correctly. The remaining gap is sites that are down, behind logins, or render team data in non-standard ways. I’ve done this exact type of work: Zillow Zestimate scraper across 150K addresses, a 2.2M product catalog scraper with anti-bot bypass, and multiple people/directory extraction projects. This is well within my wheelhouse.

@mdabu38

I CAN I am a Python Automation Expert with extensive experience in high-volume web scraping and data enrichment. I can deliver this project within your 5-6 hour deadline.

@joshlui

<<<✔Consider it DONE✔>>> YO! I understand your project and I'm eager to help. With over 5+ years in software development, I'm confident that I'm the ideal freelancer to tackle this task. My core languages are Python and mySql which has proven to be highly efficient in building secure, scalable, and data-driven systems. To ensure comprehensive web scraping for your project, I will employ a combination of Selenium and Python. This will enable me to build a system that will crawl through the targeted websites, identify the relevant pages like Team, Leadership, About Us etc and count visible team members. Looking forward to being part of your project! You will surely be impressed by my work! Not sure what the next step is? I offer free and professional consultation -- I'm just a text away. All the very best, Josh

@mehadilimon

I CAN Hello, I have carefully read the complete project description and I can deliver this automation within your required timeline. I will use * Python * Playwright (preferred for speed and handling modern websites) * BeautifulSoup/lxml for HTML parsing * Pandas & OpenPyXL for Excel processing * Intelligent crawling logic to detect Team, Leadership, About Us, Management, Our People, Staff, Executive Team, and similar pages 1. Read all 4,300+ company websites from the Excel file. 2. Visit each website automatically. 3. Search for Team/Leadership/About pages using navigation links and internal page discovery. 4. Count visible team members on the identified page. 5. Update only the **Team Details** column with: * Numeric count (e.g., 2, 5, 12) * "No Team Page Found" if no relevant page exists * "No Team Page Found" if the website field is blank 6. Return the completed Excel file. Processing of all 4,300+ websites: depends on website response speed, but can be started immediately and completed as quickly as possible. 85–95%+ accuracy for standard corporate websites Some websites with unusual structures, JavaScript-heavy rendering, anti-bot protection, or inaccessible team pages may require fallback handling, which I will implement. I understand the deadline is critical and can start immediately. Thanks Mehadi

@CaptainCM7

Lowest cost and best work I CAN provide you with a comprehensive automated solution for your web scraping project using the Python and Selenium technology. With my proven skills in Data Extraction, Excel, Python, and Web Scraping, I am confident to parse through the 4,300+ company websites efficiently and accurately. I’m quite adept at navigating complex website structures and will ensure you receive only complete, correct information on each team's details. Given that this project requires a fast turnaround, I guarantee you the completion within today's timeframe.