import json
import os
import shutil
import sqlite3
from dotenv import load_dotenv

load_dotenv()

remap = json.load(open(file="./Data_exported/Data_mods/x64/datatable/dec/remap.json", encoding="utf-8"))

# Connect to the database
conn = sqlite3.connect("./Data_exported/Server/wwwroot/taiko.db3")
cursor = conn.cursor()


def update_ids_in_table(cursor, table, column, id_mappings):
    """
    Updates the IDs in a specific table and column based on the provided id_mappings,
    removes any rows where the column value is equal to the new ID to avoid duplicates,
    and updates the favorite_songs_array accordingly.

    Args:
        cursor: SQLite cursor object.
        table: Name of the table to update.
        column: Name of the column to update.
        id_mappings: Dictionary with old IDs as keys and new IDs as values.
    """
    for old_id, new_id in id_mappings.items():
        # Step 1: Remove rows where column = new_id to avoid duplicates
        sql_delete_query = f"DELETE FROM {table} WHERE {column} = ?"
        cursor.execute(sql_delete_query, (new_id,))
        if cursor.rowcount > 0:
            print(f"Removed {cursor.rowcount} entries in {table} where {column} = {new_id}")

        # Step 2: Update favorite_songs_array in UserData table (assumes column index 12)
        cursor.execute(f"SELECT rowid, * FROM UserData")  # `rowid` lets us update specific rows
        user_data_rows = cursor.fetchall()

        for row in user_data_rows:
            row_id = row[0]
            favorite_songs_array = json.loads(row[13]) if row[13] else []  # Load favorite_songs_array from column 12

            # Update the favorite_songs_array, removing any instances of new_id
            updated_favorite_songs = [song_id for song_id in favorite_songs_array if int(song_id) != new_id]

            # Check if the favorite_songs_array was actually changed
            if favorite_songs_array != updated_favorite_songs:
                # Convert back to JSON and update in the database
                updated_favorite_songs_json = json.dumps(updated_favorite_songs)
                cursor.execute(
                    "UPDATE UserData SET FavoriteSongsArray = ? WHERE rowid = ?", (updated_favorite_songs_json, row_id)
                )
                print(f'Updated FavoriteSongsArray for "{row[19]}": Removed song id {new_id}')

        # Step 3: Update the IDs in the specified column (e.g., main table update)
        sql_update_query = f"UPDATE {table} SET {column} = ? WHERE {column} = ?"
        cursor.execute(sql_update_query, (new_id, old_id))
        print(f"Updated {table}.{column} from {old_id} to {new_id}")


# List of tables and their corresponding columns to update
tables_to_update = {
    "AiScoreData": "SongId",
    "AiSectionScoreData": "SongId",
    "SongBestData": "SongId",
    "SongPlayData": "SongId",
}

invert = True
id_mappings = {}
for remapentry in remap:
    RemapFrom = remapentry["uniqueIdOriginal" if invert else "uniqueIdRemap"]
    RemapTo = remapentry["uniqueIdRemap" if invert else "uniqueIdOriginal"]
    id_mappings[RemapFrom] = RemapTo

try:
    # Iterate over each table and update the IDs
    for table, column in tables_to_update.items():
        update_ids_in_table(cursor, table, column, id_mappings)

    # Commit the changes to the database
    conn.commit()

except sqlite3.Error as e:
    print(f"An error occurred: {e}")
    conn.rollback()  # Rollback changes if something goes wrong

finally:
    # Close the database connection
    conn.close()
    print("Database connection closed.")