import gradio as gr
import pandas as pd
import chardet
from io import BytesIO

def detect_encoding(file_bytes):
    """Detect the encoding of the file."""
    # Use chardet to detect encoding
    result = chardet.detect(file_bytes)
    return result['encoding']

def convert_file(input_file, conversion_type):
    # Check if a file was uploaded
    if input_file is None:
        return None, "Please upload a file."
    
    # Read the file content
    try:
        # Try reading from file-like object
        file_bytes = input_file.read()
        file_name = input_file.name
    except AttributeError:
        # If there's an AttributeError, treat input_file as a file path
        file_name = input_file
        with open(file_name, "rb") as f:
            file_bytes = f.read()
    
    file_extension = file_name.lower().split('.')[-1]
    df = None
    output_file = None
    converted_format = None
    
    try:
        # Conversion: CSV to Parquet
        if conversion_type == "CSV to Parquet":
            if file_extension != "csv":
                return None, "For CSV to Parquet conversion, please upload a CSV file."
            
            # Detect the encoding of the CSV file
            encoding = detect_encoding(file_bytes)
            
            # Try to read with detected encoding
            try:
                df = pd.read_csv(BytesIO(file_bytes), encoding=encoding)
            except Exception as e:
                # If that fails, try with other common encodings
                for enc in ['utf-8', 'latin1', 'iso-8859-1', 'cp1252']:
                    try:
                        df = pd.read_csv(BytesIO(file_bytes), encoding=enc)
                        encoding = enc
                        break
                    except:
                        continue
                if df is None:
                    return None, f"Failed to read CSV with any encoding. Error: {str(e)}"
            
            output_file = "output.parquet"
            df.to_parquet(output_file, index=False)
            converted_format = "Parquet"
            
        # Conversion: Parquet to CSV
        elif conversion_type == "Parquet to CSV":
            if file_extension != "parquet":
                return None, "For Parquet to CSV conversion, please upload a Parquet file."
            
            df = pd.read_parquet(BytesIO(file_bytes))
            output_file = "output.csv"
            df.to_csv(output_file, index=False, encoding='utf-8')
            converted_format = "CSV"
        else:
            return None, "Invalid conversion type selected."
        
        # Generate a preview of the top 10 rows
        preview = df.head(10).to_string(index=False)
        info_message = (
            f"Input file: {file_name}\n"
            f"Converted file format: {converted_format}\n"
        )
        if conversion_type == "CSV to Parquet":
            info_message += f"Detected encoding: {encoding}\n"
        
        info_message += f"\nPreview (Top 10 Rows):\n{preview}"
        
        return output_file, info_message
    
    except Exception as e:
        return None, f"Error during conversion: {str(e)}"

# Custom CSS for a modern and sleek look
custom_css = """
body {
    background-color: #f4f4f4;
    font-family: 'Helvetica Neue', Arial, sans-serif;
}
.gradio-container {
    max-width: 900px;
    margin: 40px auto;
    padding: 20px;
    background-color: #ffffff;
    border-radius: 12px;
    box-shadow: 0 8px 16px rgba(0,0,0,0.1);
}
h1, h2 {
    color: #333333;
}
.gradio-input, .gradio-output {
    margin-bottom: 20px;
}
.gradio-button {
    background-color: #4CAF50 !important;
    color: white !important;
    border: none !important;
    padding: 10px 20px !important;
    font-size: 16px !important;
    border-radius: 6px !important;
    cursor: pointer;
}
.gradio-button:hover {
    background-color: #45a049 !important;
}
"""

with gr.Blocks(css=custom_css, title="CSV <-> Parquet Converter") as demo:
    gr.Markdown("# CSV <-> Parquet Converter")
    gr.Markdown("Upload a CSV or Parquet file and select the conversion type. The app converts the file to the opposite format and displays a preview of the top 10 rows.")
    
    with gr.Row():
        with gr.Column(scale=1):
            input_file = gr.File(label="Upload CSV or Parquet File")
        with gr.Column(scale=1):
            conversion_type = gr.Radio(
                choices=["CSV to Parquet", "Parquet to CSV"], 
                label="Conversion Type",
                value="CSV to Parquet"  # Set default value
            )
    
    convert_button = gr.Button("Convert", elem_classes=["gradio-button"])
    
    with gr.Row():
        output_file = gr.File(label="Converted File")
        preview = gr.Textbox(label="Preview (Top 10 Rows)", lines=15)
    
    convert_button.click(fn=convert_file, inputs=[input_file, conversion_type], outputs=[output_file, preview])
    
    gr.Markdown("""
    ### Notes:
    - This converter can handle various CSV encodings
    - Parquet files are always encoded in UTF-8
    - The preview shows only the first 10 rows of data
    """)

if __name__ == "__main__":
    demo.launch()