Built a Production-Grade, Multi-Format YellowPages

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). 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