fix bugs and simplify

CLAUDE.md

@@ -4,15 +4,19 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-Single-script Python tool that extracts credit card transactions from BAC Costa Rica statement PDFs. Parses section "B) Detalle de compras del periodo" and outputs JSON.
+Single-script Python tool that extracts credit card transactions from BAC Costa Rica statement PDFs. Parses sections B (purchases), D (other charges), and E (voluntary services) and outputs JSON.
 
 ## Dependencies
 
 - pdfplumber (>=0.10.0)
 
-## Usage
+## Commands
 
 ```bash
+# Run tests
+python testStatements/run_tests.py
+
+# Run extractor
 python bac_extract.py <pdf_file> [options]
 
 # Examples
@@ -29,11 +33,15 @@ Options:
 
 The extraction pipeline:
 1. Validates PDF is a BAC statement (`is_bac_statement`)
-2. Locates section B via regex patterns (`find_section_b_start`, `is_section_end`)
-3. Extracts tables page-by-page using pdfplumber
-4. Parses Spanish dates (D-MMM-YY format) and amounts with comma separators
+2. Iterates pages line-by-line, detecting section boundaries via `SECTIONS` dict patterns
+3. Parses transactions matching `TRANSACTION_PATTERN` regex
+4. Outputs card holders, transactions by section, and summaries
+
+Key data structures:
+- `SECTIONS`: Maps section IDs (B/D/E) to start/end regex patterns and output keys
+- `SPANISH_MONTHS`: Spanish month abbreviations for date parsing
 
 Key parsing functions:
 - `parse_spanish_date`: Converts "15-ENE-25" to "2025-01-15"
 - `parse_amount`: Handles "1,234.56" and trailing negatives "100.00-"
-- `extract_card_holder`: Matches "************1234 NAME" pattern
+- `matches_patterns`: Generic regex pattern matcher for section detection