app.py

import gradio as gr

def calculate_page_views(revenue, cpm):
    try:
        # Convert inputs to float
        revenue = float(revenue)
        cpm = float(cpm)

        # Calculate total annual page views
        annual_page_views = (revenue * 1000) / cpm  # Revenue (₹) * 1000 / CPM (₹)
        annual_page_views_millions = annual_page_views / 1_000_000  # Convert to millions

        # Calculate monthly and daily page views
        monthly_page_views = annual_page_views / 12
        monthly_page_views_millions = monthly_page_views / 1_000_000  # Convert to millions
        daily_page_views = annual_page_views / 365
        daily_page_views_millions = daily_page_views / 1_000_000  # Convert to millions

        # Return results
        return (f"Annual Page Views: {annual_page_views:.0f} ({annual_page_views_millions:.2f}M)",
                f"Monthly Page Views: {monthly_page_views:.0f} ({monthly_page_views_millions:.2f}M)",
                f"Daily Page Views: {daily_page_views:.0f} ({daily_page_views_millions:.2f}M)")
    except Exception as e:
        return f"Error: {str(e)}", "", ""

# Gradio Interface
with gr.Blocks() as forecast_calculator:
    gr.Markdown("## Programmatic Pageviews Forecast Calculator (in ₹)")
    gr.Markdown(
        "Enter the **Revenue** (₹) and **CPM** (₹), and the calculator will display the page views required annually, monthly, and daily."
    )

    with gr.Row():
        revenue_input = gr.Textbox(label="Revenue (in ₹)", placeholder="Enter total revenue (e.g., 5000000)")
        cpm_input = gr.Textbox(label="CPM (in ₹)", placeholder="Enter CPM (e.g., 50)")

    calculate_button = gr.Button("Calculate Page Views")

    with gr.Row():
        annual_output = gr.Textbox(label="Annual Page Views")
        monthly_output = gr.Textbox(label="Monthly Page Views")
        daily_output = gr.Textbox(label="Daily Page Views")

    calculate_button.click(
        calculate_page_views, 
        inputs=[revenue_input, cpm_input], 
        outputs=[annual_output, monthly_output, daily_output]
    )

forecast_calculator.launch()