import pandas as pd
import re
import csv
import os

def detect_header_line(path, max_rows=10):
    with open(path, 'r', encoding='utf-8', errors='ignore') as f:
        lines = [next(f) for _ in range(max_rows)]
    header_line_idx = 0
    best_score = -1
    for i, line in enumerate(lines):
        cells = re.split(r'[;,|\t]', line.strip())
        alpha_ratio = sum(bool(re.search(r'[A-Za-z]', c)) for c in cells) / max(len(cells), 1)
        digit_ratio = sum(bool(re.search(r'\d', c)) for c in cells) / max(len(cells), 1)
        score = alpha_ratio - digit_ratio
        if score > best_score:
            best_score = score
            header_line_idx = i
    return header_line_idx

def detect_delimiter(path, sample_size=2048):
    with open(path, 'r', encoding='utf-8', errors='ignore') as f:
        sample = f.read(sample_size)
    sniffer = csv.Sniffer()
    try:
        dialect = sniffer.sniff(sample)
        return dialect.delimiter
    except Exception:
        for delim in [',', ';', '\t', '|']:
            if delim in sample:
                return delim
        return ','


def read_csv(path: str, sheet: str = None):
    ext = os.path.splitext(path)[1].lower()

    try:
        if ext in ['.csv']:
            header_line = detect_header_line(path)
            delimiter = detect_delimiter(path)
            print(f"[INFO] Detected header line: {header_line + 1}, delimiter: '{delimiter}'")

            df = pd.read_csv(
                path,
                header=header_line,
                sep=delimiter,
                encoding='utf-8',
                low_memory=False,
                thousands=','
            )

        elif ext in ['.xlsx', '.xls']:
            print(f"[INFO] Membaca file Excel: {os.path.basename(path)}")
            xls = pd.ExcelFile(path)
            print(f"[INFO] Ditemukan {len(xls.sheet_names)} sheet: {xls.sheet_names}")

            if sheet:
                if sheet not in xls.sheet_names:
                    raise ValueError(f"Sheet '{sheet}' tidak ditemukan dalam file {os.path.basename(path)}")
                print(f"[INFO] Membaca sheet yang ditentukan: '{sheet}'")
                df = pd.read_excel(xls, sheet_name=sheet, header=0, dtype=str)
                df = df.dropna(how='all').dropna(axis=1, how='all')

            else:
                print("[INFO] Tidak ada sheet yang ditentukan, mencari sheet paling relevan...")
                best_sheet = None
                best_score = -1
                best_df = None

                for sheet_name in xls.sheet_names:
                    try:
                        temp_df = pd.read_excel(xls, sheet_name=sheet_name, header=0, dtype=str)
                        temp_df = temp_df.dropna(how='all').dropna(axis=1, how='all')

                        if len(temp_df) == 0 or len(temp_df.columns) < 2:
                            continue

                        # hitung skor relevansi
                        text_ratio = temp_df.applymap(lambda x: isinstance(x, str)).sum().sum() / (temp_df.size or 1)
                        row_score = len(temp_df)
                        score = (row_score * 0.7) + (text_ratio * 100)

                        if score > best_score:
                            best_score = score
                            best_sheet = sheet_name
                            best_df = temp_df

                    except Exception as e:
                        print(f"[WARN] Gagal membaca sheet {sheet_name}: {e}")
                        continue

                if best_df is not None:
                    print(f"[INFO] Sheet terpilih: '{best_sheet}' dengan skor {best_score:.2f}")
                    df = best_df
                else:
                    raise ValueError("Tidak ada sheet valid yang dapat dibaca.")

            for col in df.columns:
                if df[col].astype(str).str.replace(',', '', regex=False).str.match(r'^-?\d+(\.\d+)?$').any():
                    df[col] = df[col].astype(str).str.replace(',', '', regex=False)
                    df[col] = pd.to_numeric(df[col], errors='ignore')

        else:
            raise ValueError("Format file tidak dikenali (hanya .csv, .xlsx, .xls)")

    except Exception as e:
        print(f"[WARN] Gagal membaca file ({e}), fallback ke default reader.")
        df = pd.read_csv(path, encoding='utf-8', low_memory=False, thousands=',')

    df = df.loc[:, ~df.columns.astype(str).str.contains('^Unnamed')]
    df.columns = [str(c).strip() for c in df.columns]
    df = df.dropna(how='all')

    return df