import gradio as gr
import pandas as pd
import random

data = pd.read_pickle("merged_all_table.pkl", compression='bz2')

home_team_id = sorted(data["home_team_long_name"].unique())
away_team_id = sorted(data["away_team_long_name"].unique())


def predict(*args):
    pass

# markup table for markdown
# # Members:
#     | Students Name      | Student ID |
#     |    :---    |    :----:   |
#     | Zeel Karshanbhai Sheladiya      | 500209119       | 
#     | Ravikumar Chandrakantbhai Patel   | 500196861        |
#     | Dharma Teja Reddy Bandreddi   | 500209454        |
#     | Sai Charan Reddy Meda  | 500201602        |
#     | Aditya Babu   | 500209122        |
#     | Sudip Bhattarai   | 500198055        |
#     | NOMAN FAZAL MUKADAM   | 500209115        |
#     | Leela Prasad Kavuri   | 500209550        |
#     | Vamsi Dasari   | 500200775        |

with gr.Blocks() as demo:
    gr.Markdown("""
    # Subject: Data Science Project Management and Requirement Gathering 02 (Group 4)
    [![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/ravi7522/Football-Prediction)
    """)
    with gr.Row():
        gr.Label("⚽️ Football Prediction ⚽️", container=False)

    with gr.Row():
        with gr.Column():

            home_team_id = gr.Dropdown(
                label="Home Team",
                choices=home_team_id,
                max_choices=1,
            )

        with gr.Column(): 

            Away_team_id = gr.Dropdown(
                label="Away Team",
                choices=away_team_id,
                max_choices=1,
            )

    with gr.Row():
        predict_btn = gr.Button(value="Predict")
        predict_btn.click(
            predict,
            inputs=[
                # needed parameters
            ],
            outputs=[],
        )
            
    with gr.Row():
        plot = gr.Plot()

demo.launch()