import pathlib
import os
import argparse
from typing import List
import pandas as pd
import hashlib
from datetime import datetime
import csv

from pandas.core.series import Series

from media import Media

def find_all_files(directory: pathlib.Path) -> list:
    ps = []
    for p in directory.rglob('*'):
        if "eaDir" not in str(p):
            ps.append((p))
    return ps

def view_unqiue_files(p: pathlib.Path, min_size):
    if p.lstat().st_size > min_size * 1024 * 1024:
        if p.lstat().st_nlink == 1:
            print("File with only one hardlink:" + str(p) + "; size: " + 
                str(p.lstat().st_size/1024/1024) + 
                "MB with number of links: " + str(p.lstat().st_nlink))
        else:
            print("File with more than one hardlink:" + str(p) + "; size: " + 
                str(p.lstat().st_size/1024/1024) + 
                "MB with number of links: " + str(p.lstat().st_nlink))

def get_file_checksum(p: pathlib.Path):
    m = hashlib.md5()
    with open(p, 'rb') as f: 
        while chunk := f.read(8192):
            m.update(chunk)
    hexvalue = m.hexdigest()
    print(hexvalue)
    return hexvalue

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='convert hardlink to symlink in download folder')

    parser.add_argument('-s','--source',
                        type=str,
                        help='the path to directory with source files')

    parser.add_argument('-t', '--target',
                        type=str,
                        help='the path to directory to move files')

    parser.add_argument('--size',
                        type=int,
                        help='Expected minimum file size')

    parser.add_argument('--csv',
                        type=str,
                        choices=['False','True'],
                        help='export source folders unique files into csv')

    parser.add_argument('--order',
                        type=str,
                        help='order exported csv by name or inode',
                        choices=['inode','name','checksum'])
    
    parser.add_argument('--csv_path',
                        type=str,
                        help='path to export csv')

    parser.add_argument('--move',
                        type=str,
                        help='Confirm whether to move all files with NumberOfLinks as 1 from source directory to target directory')

    args = parser.parse_args()
    min_file_size = 50
    path_library = args.source
    path_inventory = args.target
    
    if args.size:
        min_file_size = args.size
    paths = find_all_files(pathlib.Path(path_library))

    if args.csv == "True":
        csv_path = "result.csv"
        df_csv = pd.DataFrame(columns=['FileName', 'Path', 'inode', 'NumberOfLinks', 'CheckSum'])
        for x in paths:
            if x.lstat().st_size > min_file_size * 1024 * 1024:
                print(str(datetime.now()) + " : " + str(x))
                new_row = {'FileName': x.name,
                            'Path': str(x),
                            'inode': x.lstat().st_ino,
                            'NumberOfLinks': x.lstat().st_nlink,
                            'CheckSum': get_file_checksum(x)}
                df_csv = df_csv.append(new_row, ignore_index=True)
        if args.order == "inode":
            df_csv = df_csv.sort_values(by="inode")
        elif args.order == "name":
            df_csv = df_csv.sort_values(by="FileName")
        elif args.order == "checksum":
            df_csv = df_csv.sort_values(by="CheckSum")
        
        if args.csv_path:
            csv_path = args.csv_path
        df_csv.to_csv(csv_path)
    else:
        for x in paths:
            print(str(x))
            view_unqiue_files(x, min_file_size)

#                dst_path = pathlib.Path(os.path.join(path_inventory,x.name))
#                print("Its new path: " + str(dst_path))
#                x.link_to(dst_path)