import re
import pandas as pd
from io import StringIO, BytesIO
from typing import List, Dict, Any
from .aip_base import AIPParser

class LECAIPParser(AIPParser):
    """Parser for LEC (France) AIP format."""
    
    def get_supported_authorities(self) -> List[str]:
        """Get list of supported authority codes."""
        return ['LEC']
    
    def parse(self, pdf_data: bytes, icao: str) -> List[Dict[str, Any]]:
        """
        Parse LEC AIP document data.
        
        Args:
            pdf_data: Raw PDF data
            icao: ICAO airport code
            
        Returns:
            List of dictionaries containing parsed data
        """
        # Convert PDF to text (this would be implemented using a PDF library)
        text = self._pdf_to_text(pdf_data)
        
        # Parse the text into sections
        chunks = self._parse_sections(text)
        
        # Process each section
        rv = []
        for (index, section) in zip(['2', '3', '4', '5'], ['admin', 'operational', 'handling', 'passenger']):
            if index not in chunks:
                continue
                
            df = chunks[index]
            for line in df.itertuples():
                (c1, c2) = (line[1], line[-1])
                processed = False
                remarks = False
                data = None
                
                if isinstance(c1, str):
                    res1 = re.match(r'^([\w\s]+):\s(.+)', c1)
                    if res1:
                        (field, value) = res1.groups()
                        data = {
                            'ident': icao,
                            'section': section,
                            'field': field,
                            'field_aip_id': None,
                            'alt_field': field,
                            'value': value,
                            'alt_value': value
                        }
                        processed = True
                        
                if data and isinstance(c2, str):
                    res2 = re.match(r'^([\w\s]+):\s(.+)', c2)
                    if res2:
                        (alt_field, alt_value) = res2.groups()
                        if alt_field.lower().startswith('remarks'):
                            remarks = True
                        data['alt_field'] = alt_field
                        data['alt_value'] = alt_value
                
                if processed and not remarks:
                    rv.append(data)
        
        return rv
    
        
    
    def _parse_sections(self, text: str) -> Dict[str, pd.DataFrame]:
        """
        Parse text into sections.
        
        Args:
            text: Text content
            
        Returns:
            Dictionary mapping section numbers to DataFrames
        """
        chunks = {}
        current = []
        section = None
        section_re = re.compile(r'([0-9]+)\. +[A-Z]+')

        for line in text.splitlines():
            m = section_re.match(line)
            if m:
                if section and section in ['2', '3', '4', '5']:
                    if section not in chunks:
                        chunks[section] = pd.read_fwf(StringIO('\n'.join(current)))
                section = m.group(1)
                current = []
            else:
                current.append(line)
        
        return chunks 