import csv
import io
import os
from typing import Generator, List, Dict, Any, Tuple
import openpyxl

class DataFileParser:
    """
    Parser for CSV, XLSX, and ODS tabular data files.
    Supports streaming generation of rows to minimize RAM usage on large imports (100,000+ rows).
    """

    @classmethod
    def get_headers(cls, file_path: str, file_format: str) -> List[str]:
        """
        Extracts column headers from file without parsing full content.
        """
        fmt = file_format.upper()
        if fmt == "CSV":
            with open(file_path, "r", encoding="utf-8-sig") as f:
                reader = csv.reader(f)
                for row in reader:
                    return [c.strip() for c in row if c is not None]
        elif fmt in ("XLSX", "ODS"):
            wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True)
            sheet = wb.active
            for row in sheet.iter_rows(values_only=True):
                wb.close()
                return [str(c).strip() for c in row if c is not None]
            wb.close()
        return []

    @classmethod
    def stream_rows(cls, file_path: str, file_format: str) -> Generator[Tuple[int, Dict[str, Any]], None, None]:
        """
        Yields (row_number, row_dict) tuples line-by-line.
        """
        fmt = file_format.upper()
        if fmt == "CSV":
            with open(file_path, "r", encoding="utf-8-sig") as f:
                reader = csv.DictReader(f)
                row_idx = 2  # Row 1 is headers
                for row in reader:
                    cleaned_row = {str(k).strip(): str(v).strip() if v is not None else "" for k, v in row.items() if k}
                    yield row_idx, cleaned_row
                    row_idx += 1

        elif fmt in ("XLSX", "ODS"):
            wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True)
            sheet = wb.active
            headers = []
            row_idx = 1
            for row in sheet.iter_rows(values_only=True):
                if row_idx == 1:
                    headers = [str(c).strip() if c is not None else f"Column_{i}" for i, c in enumerate(row)]
                else:
                    row_dict = {}
                    has_data = False
                    for i, cell_val in enumerate(row):
                        if i < len(headers):
                            val_str = str(cell_val).strip() if cell_val is not None else ""
                            row_dict[headers[i]] = val_str
                            if val_str:
                                has_data = True
                    if has_data:
                        yield row_idx, row_dict
                row_idx += 1
            wb.close()