app.py

import gradio as gr
import pandas as pd
import plotly.express as px
import io
import requests

df_global = pd.DataFrame()

# Load from file
def load_data(file):
    try:
        if file is None:
            return pd.DataFrame()
        ext = file.name.split('.')[-1]
        if ext == 'csv':
            return pd.read_csv(file.name)
        elif ext in ['xls', 'xlsx']:
            return pd.read_excel(file.name)
        elif ext == 'json':
            return pd.read_json(file.name)
    except Exception as e:
        print("File load error:", e)
    return pd.DataFrame()

# Load from URL
def load_url(url):
    try:
        response = requests.get(url)
        response.raise_for_status()
        if url.endswith(".csv"):
            return pd.read_csv(io.StringIO(response.text))
        elif url.endswith(".json"):
            return pd.read_json(io.StringIO(response.text))
        elif url.endswith(".xlsx") or url.endswith(".xls"):
            return pd.read_excel(io.BytesIO(response.content))
    except Exception as e:
        print("URL load error:", e)
    return pd.DataFrame()

# Process both file and URL
def process_inputs(file, url):
    global df_global
    df = load_url(url) if url else load_data(file)

    if df.empty:
        return pd.DataFrame(), gr.update(choices=[], value=None), gr.update(choices=[], value=None)

    df_global = df
    all_cols = list(df.columns)
    num_cols = list(df.select_dtypes(include="number").columns)

    default_x = all_cols[0] if all_cols else None
    default_y = num_cols[0] if num_cols else None

    return df.head(), gr.update(choices=all_cols, value=default_x), gr.update(choices=num_cols, value=default_y)

# Plot
def update_plot(chart_type, x, y):
    global df_global
    if df_global.empty:
        return None

    try:
        if chart_type == "Bar Chart":
            return px.bar(df_global, x=x, y=y)
        elif chart_type == "Line Chart":
            return px.line(df_global, x=x, y=y)
        elif chart_type == "Scatter Plot":
            return px.scatter(df_global, x=x, y=y)
        elif chart_type == "Pie Chart":
            return px.pie(df_global, names=x, values=y)
        elif chart_type == "Box Plot":
            return px.box(df_global, x=x, y=y)
    except Exception as e:
        print("Plot error:", e)
        return None


# Themed UI
with gr.Blocks(css="""
body {
    margin: 0;
    padding: 0;
    font-family: 'Segoe UI', sans-serif;
    background: #0f2027;
    background: linear-gradient(to right, #2c5364, #203a43, #0f2027);
    color: skyblue;
}
#bg-theme {
    position: fixed;
    top: 0;
    left: 0;
    width: 100%;
    height: 100%;
    z-index: -2;
    background: linear-gradient(120deg, rgba(33,147,176,0.6), rgba(109,213,237,0.6));
    background-size: 200% 200%;
    animation: bgMove 20s ease infinite;
    filter: blur(100px);    
}
@keyframes bgMove {
    0% { background-position: 0% 50%; }
    50% { background-position: 100% 50%; }
    100% { background-position: 0% 50%; }
}
.fade-in {
    animation: fadeInUp 1s ease both;
}
@keyframes fadeInUp {
    0% { opacity: 0; transform: translateY(20px); }
    100% { opacity: 1; transform: translateY(0); }
}
""") as demo:

    gr.HTML('<div id="bg-theme"></div>')  # Themed animated background
    gr.Markdown(
    """
    <h1 style="
        font-size: 3.5em;
        background: linear-gradient(270deg, #ff004c, #00ffea, #ffb600, #ff004c);
        background-size: 800% 800%;
        -webkit-background-clip: text;
        -webkit-text-fill-color: transparent;
        animation: rainbow 8s ease infinite;
        font-weight: bold;
        ">
        📈⚡ Thunder BI-Data Visualizer
    </h1>

    <style>
    @keyframes rainbow {
        0%{background-position:0% 50%}
        50%{background-position:100% 50%}
        100%{background-position:0% 50%}
    }
    </style>
    """, elem_classes="fade-in"
    )

    with gr.Row():
        file_input = gr.File(file_types=[".csv", ".xlsx", ".json"], label="Upload File")
        url_input = gr.Textbox(label="Or enter file URL")

    load_button = gr.Button("Load")

    df_preview = gr.Dataframe(label="Preview", interactive=False)
    x_dropdown = gr.Dropdown(label="X-axis")
    y_dropdown = gr.Dropdown(label="Y-axis")
    chart_type = gr.Dropdown(["Bar Chart", "Line Chart", "Scatter Plot", "Pie Chart", "Box Plot"], label="Chart Type")
    plot_area = gr.Plot(label="Chart")
    generate_button = gr.Button("Generate Plot")

    # Event hooks
    load_button.click(process_inputs, inputs=[file_input, url_input], outputs=[df_preview, x_dropdown, y_dropdown])
    generate_button.click(update_plot, inputs=[chart_type, x_dropdown, y_dropdown], outputs=plot_area)

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