Daily Bulletin Scrapers
Web Scraping • PDF Processing • Selenium Automation • Python
Project Overview
A sophisticated Python-based scraping system that automatically downloads, parses, and processes daily financial bulletins from major Turkish brokerage firms. The system extracts company news items from PDF documents, performs intelligent ticker symbol matching against BIST-traded stocks, and aggregates all data into a structured CSV format for comprehensive financial analysis and market research.
Scraping Pipeline
Web Navigation
Selenium WebDriver
Automated browsing
Dynamic content handling
PDF Download
Daily bulletin retrieval
Direct downloads
Error handling
Content Extraction
PDF text parsing
pdfminer processing
Pattern recognition
Ticker Matching
BIST symbol validation
Fuzzy matching
Company identification
Data Aggregation
CSV consolidation
Timestamp tracking
Source attribution
Brokerage Firms Coverage
Oyak Yatırım
Direct PDF download and parsing with automated content extraction
Piramit Menkul
Selenium-based navigation and extraction for dynamic content
Tacirler Yatırım
Automated web browsing with Selenium for bulletin retrieval
Vakıf Yatırım
Dynamic content handling with advanced Selenium techniques
Ziraat Yatırım
PDF processing with direct download methodology
Technical Challenges & Solutions
PDF Format Variations
Implemented robust parsing to handle different bulletin layouts and format inconsistencies across firms
Dynamic Web Content
Used WebDriver to handle JavaScript-heavy brokerage websites with complex navigation
Ticker Symbol Accuracy
Deployed intelligent matching algorithms against BIST reference data for accurate identification
Error Resilience
Built comprehensive handling for PDFSyntaxError and NoSuchElementException scenarios
Data Consistency
Standardized date/time formatting and source attribution across all scraper modules
Website Changes
Modular architecture allows easy updates when brokerage sites modify their structure