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):
    ext = os.path.splitext(path)[1].lower()  # ambil ekstensi file

    try:
        if ext in ['.csv', '.txt']:
            # === Baca file 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']:
            # === Baca file Excel ===
            print(f"[INFO] Membaca file Excel: {os.path.basename(path)}")
            pre_df = pd.read_excel(path, header=0, dtype=str)  # baca semua sebagai string
            df = pre_df.copy()
            for col in df.columns:
                if df[col].str.replace(',', '', regex=False).str.match(r'^-?\d+(\.\d+)?$').any():
                    df[col] = df[col].str.replace(',', '', regex=False)
                    df[col] = pd.to_numeric(df[col], errors='ignore')

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

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

    # Bersihkan kolom dan baris kosong
    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