ExchangePulse

Overview

ExchangePulse is an automation pipeline built to pull data from a national stock exchange that actively resists scraping — requiring real research into workarounds rather than a straightforward API integration.

The Challenge

• The exchange had no public API and active anti-scraping defenses in place
• Naive scraping attempts were blocked or rate-limited quickly
• Any working solution needed to survive repeated daily runs without breaking
• The problem was as much about research methodology as it was about writing scraper code

What I Built

• Exchange data extraction — stock prices, trading volumes, and index values
• Anti-scraping workarounds — headless browsing, request pacing, and session handling researched and iterated on until reliable
• Resilient data pipeline — retries, error recovery, and structured logging for every run
• Persistent historical dataset stored for trend analysis over time
• Documented fallback strategies for when primary access methods stopped working

Tech Stack

• Language: Python
• Scraping: Selenium
• Storage: SQLite / PostgreSQL / CSV
• Scheduling: Cron-based daily runs

Key Decisions

• Chose headless browser automation over trying to reverse-engineer a private API, since the exchange had no public API and active anti-scraping defenses made a pure-requests approach unreliable
• Added request pacing and session handling as first-class pipeline concerns rather than an afterthought, since the earliest naive attempts were blocked quickly
• Built retry and error-recovery logic around the assumption that access methods would occasionally break, rather than assuming a stable long-term scraping target

Outcome / Impact

Delivered a working data pipeline that reliably bypasses common anti-scraping defenses, stable enough for daily automated runs — the kind of project that rewards research and persistence over a quick fix.