Added export csv

mv_unique_files.py

@@ -1,45 +1,97 @@
 import pathlib
 import os
 import argparse
+from typing import List
+import pandas as pd
+import csv
+
+from pandas.core.series import Series
 
 from media import Media
 
-def find_all_files(directory: pathlib.Path):
+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))
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description='convert hardlink to symlink in download folder')
 
-    parser.add_argument('Library',
-                        metavar='--library',
+    parser.add_argument('-s','--source',
                         type=str,
-                        help='the path to library')
+                        help='the path to directory with source files')
 
-    parser.add_argument('Inventory',
-                        metavar='--inventory',
+    parser.add_argument('-t', '--target',
                         type=str,
-                        help='the path to inventory for non-repeatable videos')
+                        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'])
+    
+    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()
-    path_library = args.Library
-    path_inventory = args.Inventory
+    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))
 
-    i = 0
-    for x in paths:
-        if x.lstat().st_size > 50 * 1024 * 1024:
-            if x.lstat().st_nlink == 1:
-                print("File with only one hardlink:" + str(x) + "; size: " + 
-                    str(x.lstat().st_size/1024/1024) + 
-                    "MB with number of links: " + str(x.lstat().st_nlink))
-            else:
-                print("File with more than one hardlink:" + str(x) + "; size: " + 
-                    str(x.lstat().st_size/1024/1024) + 
-                    "MB with number of links: " + str(x.lstat().st_nlink))
+    if args.csv == "True":
+        csv_path = "result.csv"
+        df_csv = pd.DataFrame(columns=['FileName', 'Path', 'inode', 'NumberOfLinks'])
+        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,
+                            'NumberOfLinks': x.lstat().st_nlink}
+                df_csv = df_csv.append(new_row, ignore_index=True)
+
+                print(df_csv)
+        if args.order == "inode":
+            df_csv.sort_values(by="inode")
+        else:
+            df_csv.sort_values(by="FileName")
+        
+        if args.csv_path:
+            csv_path = args.csv_path
+        df_csv.to_csv(csv_path)
+    else:
+        for x in paths:
+            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))