import pandas as pd
import requests
import urllib3
import gradio as gr

# 關閉 SSL 警告
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)

# 下載並讀取資料
def load_data():
    url = "https://data.tainan.gov.tw/File/ResourceCsvDownload/d7349de7-2260-436f-afcb-6699373f0460"
    response = requests.get(url, verify=False)
    with open("data01.csv", "wb") as file:
        file.write(response.content)
    df = pd.read_csv("data01.csv", encoding="utf-8-sig")
    return df

# 篩選邏輯
def filter_parking(district, min_spaces, top_n):
    try:
        df = load_data()

        # 動態篩選區域與車位數
        df_filtered = df[
            (df["停車場地址"].str.contains(district)) &
            (df["一般小型車數量"] > min_spaces)
        ]

        # 取前 N 筆
        df_top = df_filtered.head(top_n)

        # 只顯示地址與車位數
        df_result = df_top[["停車場地址", "一般小型車數量"]]

        return df_result

    except Exception as e:
        return pd.DataFrame({"錯誤": [str(e)]})

# Gradio 介面
with gr.Blocks(title="台南市停車場查詢系統") as demo:
    gr.Markdown("# 🅿️ 台南市停車場查詢系統")
    gr.Markdown("資料來源：台南市政府開放資料平台")

    with gr.Row():
        district_input = gr.Textbox(
            label="行政區關鍵字",
            value="安南區",
            placeholder="例如：安南區、東區、北區"
        )
        min_spaces_input = gr.Slider(
            label="一般小型車數量下限",
            minimum=0,
            maximum=500,
            value=30,
            step=5
        )
        top_n_input = gr.Slider(
            label="顯示筆數",
            minimum=1,
            maximum=20,
            value=3,
            step=1
        )

    search_btn = gr.Button("🔍 查詢", variant="primary")

    output_table = gr.Dataframe(
        label="查詢結果",
        headers=["停車場地址", "一般小型車數量"],
        interactive=False
    )

    search_btn.click(
        fn=filter_parking,
        inputs=[district_input, min_spaces_input, top_n_input],
        outputs=output_table
    )

demo.launch()