diff --git a/main.py b/main.py
index 787b50d..1109300 100644
--- a/main.py
+++ b/main.py
@@ -1,25 +1,41 @@
-import csv
+#!/usr/bin/env python
+"""
+Python script that converts an exported json file from the web TVISO to a csv file can be read by the web Letterboxd.
+
+Author: Jorge Kuijper
+Copyright: Copyright 2021, TvisoToLetterboxd
+License: GPL 3.0
+"""
+
 import json
 import pandas as pd
 from pathlib import Path
 from datetime import datetime
 
-# csv_path = Path(r'D:\DESCARGAS\tviso-collection.csv')
-# df = pd.read_csv(csv_path, sep=';')
-
-json_path = Path('data/tviso-collection.json')
-with open(json_path, encoding='utf-8') as json_file:
+# input_path is the path for the json file
+input_path = Path('your_path.json')  # Replace the string 'your_path' by yours
+# output_path is the path where will be saved the csv file
+output_path = Path('your_path.csv') # Replace the string 'your_path' by yours
+with open(input_path, encoding='utf-8') as json_file:
     data = json.load(json_file)
 
-# col = ['imdbID,Title,Rating10,WatchedDate']
+# The following column names are the tags that need Letterboxd to read the file.
+# Create an empty DataFrame with this columns:
+# * imdbID: is the ID of the film in IMDB
+# * Title: is the Title of the movie
+# * Rating10: is the rate in TVISO
+# * WatchedDate: is the date when you watched the movie
 col = ['imdbID', 'Title', 'Rating10', 'WatchedDate']
 df = pd.DataFrame(columns=col)
 
+# Fill the DataFrame
 for line in data:
+    # Check if the status is watched and the type is movie
     if line['status'] == 'watched' and line['type'] == 2:
         title = line['title']
         imdb = line['imdb']
         rating = line['rating'] if line['rating'] is not None else ''
+        # Silent catch if the watched date doesn't exist in TVISO and add an empty string
         try:
             watchedDate = line['checkedDate']
         except:
@@ -29,8 +45,9 @@ for line in data:
             dt = datetime.strptime(watchedDate, '%Y-%m-%dT%H:%M:%S+%f:00')
             watchedDate = dt.strftime('%Y-%m-%d')
 
-        # row_data = '{},{},{},{}'.format(imdb, title, rating, watchedDate)
+        # Insert into the DataFrame
         row_data = [imdb, title, rating, watchedDate]
         df.loc[len(df) + 1] = row_data
-
-df.to_csv('test.csv', index=False, encoding='utf-8')
+# Export DataFrame to csv
+df.to_csv(output_path, index=False, encoding='utf-8')
+print('Done!')