Secure Web Scraping from Leasing & EV Sites

Automating Data Collection from Leasing & EV Websites with iWeb Data Scraping

A client approached iWeb Data Scraping with a clear but technically challenging request: extract structured, up-to-date data from three industry-specific websites—a vehicle leasing group, a car manufacturer’s leasing portal, and an EV charging station network—each protected by login authentication. The end goal was to consolidate the data into clean CSV files for analytics and business decision-making. The project involved securely managing client-provided credentials while navigating complex login-based authentication flows, including sessions, cookies, and CSRF tokens. Our team scraped both structured and semi-structured data from protected areas across three industry-specific websites. The extracted information was then normalized, deduplicated, and delivered as clean CSV files ready for analytics and business decision-making.

Goals and Deliverables

Primary objectives

Access login-protected portals using provided authentication credentials.
Extract structured records:
- Leasing Group Website: vehicle model, lease terms, monthly payment, mileage limits, special offers
- Car Company Portal: available leasing inventory, VIN, trim, color, availability date, location
- Charging Station Network: station name, address, charger type, availability status, cost per kWh, network ID
Normalize data into a standard schema for CSV export.
Ensure data compliance—no bypassing of technical protections outside approved credentials.

Challenges

Authentication handling

Each portal had different login flows—some required multi-step authentication with CSRF token handling, while others used session cookies that expired quickly.

Dynamic content

Leasing portals often used React/Angular frameworks, requiring headless browser automation to capture data.

Pagination and filtering

Data was split across multiple pages or required applying search filters before results appeared.

Rate limits

Scraping too fast risked temporary account suspension. We implemented rate-aware crawlers.

Data consistency

Vehicle leasing offers could change daily; charging station availability could change hourly.

Our Approach

Step 1: Secure Authentication Handling

Used Selenium and Playwright for sites with heavy JavaScript rendering.
Stored credentials securely in encrypted variables; never hardcoded.
Managed cookies and tokens to maintain authenticated sessions.
Logged session flows for troubleshooting but excluded sensitive details from logs.

Step 2: Dynamic Content Extraction

Used DOM parsing for table-based data.
For infinite scroll pages, simulated scroll events until all content loaded.
Captured hidden API endpoints (when legally allowed) to fetch structured JSON responses.

Step 3: Data Normalization

Converted date formats to ISO 8601.
Unified currency formats (USD).
Standardized vehicle naming (Make, Model, Trim).
Mapped charging station connector types (CCS, CHAdeMO, Tesla) to a standard list.

Step 4: Quality Assurance

Validated VIN formats with checksum.
Verified addresses with Google Maps API for geocoding.
Checked for duplicate leasing offers and merged where necessary.

Technical Stack

Playwright / Selenium for login handling and rendering
Python (BeautifulSoup, Pandas) for parsing and data wrangling
PostgreSQL temporary staging before CSV export
Docker container for isolated execution
AWS S3 for secure CSV delivery

Sample Data (Illustrative)

Leasing Group CSV

Make	Model	Trim	Monthly Payment	Lease Term (Months)	Mileage Limit	Offer Expiry	State	Dealer Name
Toyota	Camry	XSE V6	$399	36	12,000	2025-09-30	CA	LA Toyota
BMW	X5	xDrive40i	$799	36	10,000	2025-09-15	NY	BMW Manhattan

Car Company Portal CSV

VIN	Make	Model	Trim	Color	Availability Date	Location
1HGCM82633A1	Honda	Civic	EX-L	Red	2025-08-25	Houston, TX
3VWDP7AJ9DM1	VW	Jetta	SEL	White	2025-08-28	Miami, FL

Charging Station Network CSV

Station Name	Address	Charger Type	Availability	Cost per kWh	Network ID
EV FastCharge #102	123 Main St, Austin, TX	CCS	Available	$0.25	EVNET123
GreenCharge 204	45 Oak Ave, Sacramento, CA	CHAdeMO	In Use	$0.30	EVNET456

Results

Total records extracted:
- Leasing Group: 4,200 active offers
- Car Company Portal: 7,800 vehicles
- Charging Station Network: 1,300 stations with live status
Accuracy rate: 98% after QA pass
Delivery format: CSV with clean headers, ready for analytics tools or CRM imports
Turnaround time: 2.5 weeks from kickoff to delivery

Compliance and Security

Only accessed authenticated areas with client-provided credentials.
Respected each site’s terms of service and relevant laws.
Implemented IP rotation only when approved and within allowed request volumes.
No password storage—credentials provided at runtime.

Client Impact

The client now runs:

Lease offer trend analysis across brands and regions
Inventory monitoring for high-demand vehicle trims
Charging station uptime tracking for network partnerships

By automating this process, manual effort dropped from 40+ hours per week to under 2 hours for periodic reviews.

Conclusion

Through this project, iWeb Data Scraping successfully demonstrated its expertise in delivering secure, scalable, and compliant data automation solutions. By combining advanced Enterprise Web Crawling Services with precise login-handling workflows, our team extracted and normalized complex datasets from vehicle leasing portals and Electric charging station Stores data scraping sources. Leveraging our end-to-end capabilities in Web Scraping Services , we integrated browser automation, structured data parsing, and CSV-ready formatting, ensuring high accuracy and rapid delivery. With the flexibility of our Web Scraping API Services and specialized Mobile App Data Scraping Services , the client now enjoys an automated, future-proof pipeline for real-time analytics—turning what was once a manual, error-prone process into a streamlined competitive advantage.