Mohammad Tausif
Python Developer for AI & Automation
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Built a Production-Grade, Multi-Format YellowPages Scraper with Advanced Bot Bypass.
I recently engineered and deployed a robust, server-side web scraping pipeline designed to extract high-density business listings from YellowPages. While many directory scrapers rely on fragile frontend DOM parsing or heavy, resource-intensive browser automation (like Selenium), this project focuses on speed, architectural cleanliness, and smart evasion.
🛠️ The Tech Stack
Language: Python
Networking Layer: curl_cffi (Advanced TLS/HTTP2 browser impersonation)
Parsing Engine: BeautifulSoup4
Data Manipulation & Structuring: Pandas, Openpyxl
💡 The Core Challenges & Engineering Solutions
1. Bypassing WAF & Anti-Bot Mitigations (403 Forbidden)
Standard HTTP client libraries (like requests) are immediately flagged by modern Web Application Firewalls (WAF) due to predictable TLS fingerprints.
The Solution: I integrated curl_cffi to mimic low-level Google Chrome TLS handshakes and HTTP/2 signatures flawlessly.
The Session Layer: Combined this with persistent session management (requests.Session abstraction) and dynamic Referer header chaining to replicate natural human pagination paths, completely eliminating multi-page blocks.
2. Avoiding Fragile DOM Selectors
Web layouts change constantly, breaking traditional CSS element selectors.
The Solution: Instead of targeting class names on the frontend page, the script isolates and extracts structured application/ld+json script blocks hidden inside the raw HTML. This extracts pristine, un-truncated schema objects directly from the backend payload.
3. High-Fidelity Data Delivery (5 Formats)
Different clients need different data deliverables. I built a dynamic pipeline that automatically deduplicates records by business name/phone and compiles the data into five distinctive formats simultaneously:
Excel Workbook (.xlsx): Fully stylized with custom corporate themes, column auto-fit scaling, frozen header planes, and built-in active sorting filters.
Flat CSV Matrix: UTF-8 encoded, optimized for smooth importing into database architectures or CRMs.
Schema JSON Array: Clean, nested relational object trees.
Structured Markup XML: Safely escaped entities for enterprise software parsing.
Presentable HTML View: A responsive CSS-styled table markup for quick localized browser validations.
📊 The Results
On its final deployment run, the pipeline handled 20 sequential page cycles completely block-free, cleanly generating 578 unique, deduplicated B2B leads directly into organized local assets.
📂 Repository & Code Architecture
The code is built strictly around clean architecture guidelines:
Isolated virtual environments (venv).
Production-safe configurations (.gitignore masking raw data and dependencies).
Modular, object-oriented class execution flow (src/scraper.py (http://scraper.py)).
For Full Project Overview and Source Code
Check Out Github : https://github.com/Tausif-11/yellowpages_scraper
If You want to work with me and build a similar project, You can send a message or you can also check out my Fiverr Page , there I've made customized offers for different projects.
https://www.fiverr.com/s/WEaA6PL
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This project I made is Zillow Agent Scraper. It's a wonderful tool I've created for realtors, and people who need to extract details of real estate agents from website like zillow. It usings internal Hidden API points, and extract the JSON payload to the python and the exports into Excel and CSV format. It extracts details which are publically available, like Brokerage firm, fees, how many sales they made, their price, Business Name, etc.
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I've Built A property scraper , this python script scrapes and extract property listings from zillow.com, and exports the data into Excel/CSV format as output. It collects, Price, status of the house whether its for sale/rent , beds, bath and brokerage agent. If you too want to extract some data from a real estate website or any other public website, for public data extraction. You can message me. This Project Costs $100. For more details of this project visit my Github : https://github.com/Tausif-11/zillow_property_scraper
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“Built a Python-based encrypted password manager using Fernet encryption for secure local credential storage. Features included password generation, encrypted saving/loading, and password strength analysis. Currently planning a more advanced version with stronger encryption architecture and enhanced security features.”
GitHub: https://github.com/Tausif-11
Explore my Python projects, automation tools, and utility software.
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