app.py

import os
import tempfile
import requests
import pandas as pd
import gradio as gr
import spaces

from bs4 import BeautifulSoup
from datasets import Dataset
from huggingface_hub import HfApi

# ===========================
# CONFIG
# ===========================

URL_DEFAULT = "https://www.ketquadientoan.com/tra-cuu-ket-qua-xo-so-dien-toan-power-655.html?"

DATASET_REPO = "Mrlongpro/power655-dataset"

CSV_NAME = "history.csv"

HF_TOKEN = os.getenv("HF_TOKEN")

HEADERS = {
    "User-Agent": "Mozilla/5.0"
}

api = HfApi(token=HF_TOKEN)

# ===========================
# FEATURE ENGINEERING
# ===========================


def create_features(df):

    vectors = []

    for _, row in df.iterrows():

        vec = [0] * 55

        nums = [
            int(row["S1"]),
            int(row["S2"]),
            int(row["S3"]),
            int(row["S4"]),
            int(row["S5"]),
            int(row["S6"]),
        ]

        for n in nums:
            vec[n - 1] = 1

        feature = {
            "Sum": sum(nums),
            "Mean": sum(nums) / 6,
            "Odd": sum(x % 2 for x in nums),
            "Even": 6 - sum(x % 2 for x in nums),
            "Min": min(nums),
            "Max": max(nums),
        }

        for i in range(55):
            feature[f"N{i+1:02}"] = vec[i]

        vectors.append(feature)

    feature_df = pd.DataFrame(vectors)

    return pd.concat(
        [df.reset_index(drop=True), feature_df],
        axis=1,
    )


# ===========================
# LOAD DATASET
# ===========================


def load_history():

    try:

        api.hf_hub_download(
            repo_id=DATASET_REPO,
            repo_type="dataset",
            filename=CSV_NAME,
            local_dir="."
        )

        return pd.read_csv(CSV_NAME)

    except:

        return pd.DataFrame()


# ===========================
# SAVE DATASET
# ===========================


def save_dataset(df):

    df.to_csv(
        CSV_NAME,
        index=False,
        encoding="utf-8-sig"
    )

    api.upload_file(
        path_or_fileobj=CSV_NAME,
        path_in_repo=CSV_NAME,
        repo_id=DATASET_REPO,
        repo_type="dataset",
        commit_message="Update Power655"
    )

    Dataset.from_pandas(df).push_to_hub(
        DATASET_REPO,
        token=HF_TOKEN
    )


# ===========================
# CRAWLER
# ===========================


@spaces.GPU
def crawl(url):

    try:

        r = requests.get(
            url,
            headers=HEADERS,
            timeout=30,
        )

        r.raise_for_status()

        soup = BeautifulSoup(
            r.text,
            "html.parser",
        )

        options = soup.select(
            "select.dongay option"
        )

        data = []

        for op in options:

            if op.get("value") == "0":
                continue

            nums = op["value"].split(",")

            data.append({

                "Ngày": op.text.strip(),

                "S1": int(nums[0]),
                "S2": int(nums[1]),
                "S3": int(nums[2]),
                "S4": int(nums[3]),
                "S5": int(nums[4]),
                "S6": int(nums[5]),

                "Số phụ": int(op["jphu"]),

                "Jackpot1": int(op["price"]),

                "Jackpot2": int(op["price2"])

            })

        df = pd.DataFrame(data)

        df = create_features(df)

        old = load_history()

        if len(old):

            df = pd.concat(
                [old, df],
                ignore_index=True
            )

            df = df.drop_duplicates(
                subset=["Ngày"],
                keep="first"
            )

        save_dataset(df)

        outfile = os.path.join(
            tempfile.gettempdir(),
            "power655.csv"
        )

        df.to_csv(
            outfile,
            index=False,
            encoding="utf-8-sig"
        )

        return (

            df,

            outfile,

            f"Đã cập nhật {len(df)} kỳ quay."

        )

    except Exception as e:

        return (

            pd.DataFrame(),

            None,

            str(e)

        )


# ===========================
# UI
# ===========================

with gr.Blocks() as demo:

    gr.Markdown(
        "# 🎯 Power 6/55 Dataset Builder"
    )

    url = gr.Textbox(
        value=URL_DEFAULT,
        label="URL"
    )

    btn = gr.Button(
        "Cập nhật Dataset"
    )

    status = gr.Textbox(
        label="Trạng thái"
    )

    table = gr.Dataframe(
        interactive=False
    )

    file = gr.File()

    btn.click(
        crawl,
        inputs=url,
        outputs=[
            table,
            file,
            status
        ]
    )

demo.launch()