cleanup code

inspect_submissions.py

@@ -3,6 +3,7 @@ import pandas as pd
 from datetime import datetime
 from utils.inspector import hash_submissions, suspicious_by_hash
 
+CSV_DIR = os.path.join(os.getcwd(), 'csv')
 
 def main():
     submissions_dir_name = ' '.join(sys.argv[1:]) if len(sys.argv) > 1 else exit(f'\nNo submissions dir name given. Provide the name as an argument.\n\nUsage: python {sys.argv[0]} [submissions dir name]\nExample: python {sys.argv[0]} AssignmentX\n')
@@ -10,15 +11,15 @@ def main():
     if not os.path.isdir(submissions_dir_path):
         exit(f'Directory {submissions_dir_path} does not exist.\nMake sure "{submissions_dir_name}" exists in "BB_submissions".')
     else:
-        hashes_csv_file_path = hash_submissions(submissions_dir_path)
-        
+        hashes_csv_file_path = hash_submissions(submissions_dir_path)  # generate hashes for all files and return output csv file to load & find duplicate/suspicious hashes
         csv = pd.read_csv(hashes_csv_file_path)
         df = pd.DataFrame(csv)  # df with all files and their hashes
-        df_suspicious = suspicious_by_hash(df)  # df with all files with duplicate hash, excludes files from the same student id
+        df_suspicious = suspicious_by_hash(df)  # df with all files with duplicate/suspicious hash, excludes files from the same student id
+        
         csv_name = f'{submissions_dir_name}_suspicious_{datetime.now().strftime("%Y%m%d-%H%M%S")}.csv'
-        csv_out = os.path.join('csv', csv_name)
+        csv_out = os.path.join(CSV_DIR, csv_name)
         df_suspicious.to_csv(csv_out, index=False)
 
 
 if __name__ == '__main__':    
-    main()
+    main()