import pyarrow.parquet as pq
import os
import json

# Function to check row count in a Parquet file
def check_row_count(parquet_file_path):
    try:
        parquet_file = pq.ParquetFile(parquet_file_path)
        num_rows = parquet_file.metadata.num_rows
        print(f"The Parquet file '{parquet_file_path}' contains {num_rows} rows.")
        return num_rows
    except Exception as e:
        print(f"Error reading Parquet file: {e}")

# Function to retrieve a specific row efficiently from a Parquet file
def get_specific_row(parquet_file_path, row_index):
    try:
        # Open the Parquet file
        parquet_file = pq.ParquetFile(parquet_file_path)
        
        # Initialize variables to track the current row position
        current_row = 0
        
        # Iterate over each row group in the Parquet file
        for row_group in range(parquet_file.num_row_groups):
            # Read the current row group into a table
            table = parquet_file.read_row_group(row_group)
            
            # Check if the desired row is within the current row group
            if current_row <= row_index < current_row + table.num_rows:
                # Calculate the index of the row within the current table
                row_in_table = row_index - current_row
                
                # Retrieve the row as a dictionary
                row = {col: table.column(col)[row_in_table].as_py() for col in table.column_names}
                
                return row
            
            # Update the current row position
            current_row += table.num_rows
        
        # If the row index is out of bounds, raise an error
        raise IndexError(f"Row index {row_index} is out of bounds.")
    
    except Exception as e:
        print(f"Error retrieving row: {e}")
        return None

# Function to save image content back to JPG
def save_image_from_row(row, output_image_path):
    try:
        image_content = row['image_content']  # Image content as binary
        with open(output_image_path, 'wb') as img_file:
            img_file.write(image_content)
        print(f"Image saved successfully at {output_image_path}")
    except Exception as e:
        print(f"Error saving image: {e}")

# Function to save JSON content to a file
def save_json_from_row(row, output_json_path):
    try:
        json_content = row['json_content']  # JSON content as string
        json_data = json.loads(json_content)  # Parse the string into a JSON object
        with open(output_json_path, 'w', encoding='utf-8') as json_file:
            json.dump(json_data, json_file, indent=4, ensure_ascii=False)
        print(f"JSON saved successfully at {output_json_path}")
    except Exception as e:
        print(f"Error saving JSON: {e}")

# Function to save all images and JSONs into a specific folder
def save_all_images_and_jsons(parquet_file_path, output_folder):
    try:
        # Create the output folder if it doesn't exist
        os.makedirs(output_folder, exist_ok=True)

        # Open the Parquet file and check the number of rows
        parquet_file = pq.ParquetFile(parquet_file_path)
        num_rows = parquet_file.metadata.num_rows

        # Iterate through all rows and save images and JSONs
        for row_index in range(num_rows):
            row = get_specific_row(parquet_file_path, row_index)
            if row is not None:
                # Define the file paths for each image and JSON
                output_image_path = os.path.join(output_folder, f"image_{row_index}.jpg")
                output_json_path = os.path.join(output_folder, f"data_{row_index}.json")
                
                # Save the image and JSON content
                save_image_from_row(row, output_image_path)
                save_json_from_row(row, output_json_path)

    except Exception as e:
        print(f"Error saving all images and JSONs: {e}")

# Function to save N images and JSONs into a specific folder
def save_n_images_and_jsons(parquet_file_path, output_folder, num_to_save):
    try:
        # Create the output folder if it doesn't exist
        os.makedirs(output_folder, exist_ok=True)

        # Open the Parquet file and check the number of rows
        parquet_file = pq.ParquetFile(parquet_file_path)
        num_rows = parquet_file.metadata.num_rows

        # Limit the number of files to save to the available rows
        limit = min(num_to_save, num_rows)

        # Iterate through the first N rows and save images and JSONs
        for row_index in range(limit):
            row = get_specific_row(parquet_file_path, row_index)
            if row is not None:
                # Define the file paths for each image and JSON
                output_image_path = os.path.join(output_folder, f"image_{row_index}.jpg")
                output_json_path = os.path.join(output_folder, f"data_{row_index}.json")
                
                # Save the image and JSON content
                save_image_from_row(row, output_image_path)
                save_json_from_row(row, output_json_path)

    except Exception as e:
        print(f"Error saving N images and JSONs: {e}")

# Example usage:
parquet_file_path = 'path/to/MobileViews_xxx-xxx.parquet'
output_folder_all = 'path/to/all_extracted_images_jsons'
output_folder_n = 'path/to/n_extracted_images_jsons'

check_row_count('parquet_file_path')


# Step 1: Save all images and JSONs or a certain number

save_n_images_and_jsons(parquet_file_path, output_folder_n, num_to_save=100)

# save_all_images_and_jsons(parquet_file_path, output_folder_all)