synology_link_manipultor/mv_unique_files.py

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import pathlib
import os
import argparse
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from typing import List
import pandas as pd
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import hashlib
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import csv
from pandas.core.series import Series
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from media import Media
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def find_all_files(directory: pathlib.Path) -> list:
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ps = []
for p in directory.rglob('*'):
if "eaDir" not in str(p):
ps.append((p))
return ps
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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))
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def get_file_checksum(p: pathlib.Path):
m = hashlib.md5()
with open(p, 'rb') as f:
while chunk := f.read(8192):
m.update(chunk)
return m.hexdigest()
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if __name__ == "__main__":
parser = argparse.ArgumentParser(description='convert hardlink to symlink in download folder')
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parser.add_argument('-s','--source',
type=str,
help='the path to directory with source files')
parser.add_argument('-t', '--target',
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type=str,
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help='the path to directory to move files')
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parser.add_argument('--size',
type=int,
help='Expected minimum file size')
parser.add_argument('--csv',
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type=str,
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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',
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choices=['inode','name','checksum'])
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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')
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args = parser.parse_args()
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min_file_size = 50
path_library = args.source
path_inventory = args.target
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if args.size:
min_file_size = args.size
paths = find_all_files(pathlib.Path(path_library))
if args.csv == "True":
csv_path = "result.csv"
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df_csv = pd.DataFrame(columns=['FileName', 'Path', 'inode', 'NumberOfLinks', 'CheckSum'])
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for x in paths:
if x.lstat().st_size > min_file_size * 1024 * 1024:
new_row = {'FileName': x.name,
'Path': str(x),
'inode': x.lstat().st_ino,
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'NumberOfLinks': x.lstat().st_nlink,
'CheckSum': get_file_checksum(x)}
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df_csv = df_csv.append(new_row, ignore_index=True)
if args.order == "inode":
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df_csv = df_csv.sort_values(by="inode")
elif args.order == "name":
df_csv = df_csv.sort_values(by="FileName")
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elif args.order == "checksum":
df_csv = df_csv.sort_values(by="CheckSum")
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if args.csv_path:
csv_path = args.csv_path
df_csv.to_csv(csv_path)
else:
for x in paths:
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print(str(x))
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view_unqiue_files(x, min_file_size)
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# dst_path = pathlib.Path(os.path.join(path_inventory,x.name))
# print("Its new path: " + str(dst_path))
# x.link_to(dst_path)