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FeatureSelect-Methods-Leaderboard
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import os
import pickle
from flask import Flask, jsonify, request, render_template

# ===============================
# 基本路径配置
# ===============================
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
RESULT_DIR = os.path.join(PROJECT_ROOT, "results")
DATASET_DIR = os.path.join(PROJECT_ROOT, "datasets")

os.makedirs(RESULT_DIR, exist_ok=True)
os.makedirs(DATASET_DIR, exist_ok=True)

# ===============================
# Flask App
# ===============================
app = Flask(__name__)

# ===============================
# 内存缓存
# ===============================
RESULT_CACHE = {}  # {dataset_name: results}


# ===============================
# PKL IO 工具
# ===============================
def save_result_pkl(dataset, results):
    path = os.path.join(RESULT_DIR, f"{dataset}.pkl")
    with open(path, "wb") as f:
        pickle.dump(results, f)


def load_result_pkl(dataset):
    path = os.path.join(RESULT_DIR, f"{dataset}.pkl")
    if not os.path.exists(path):
        return None
    with open(path, "rb") as f:
        return pickle.load(f)


def list_available_datasets():
    datasets = set()

    for f in os.listdir(RESULT_DIR):
        if f.endswith(".pkl"):
            datasets.add(f.replace(".pkl", ""))

    # 默认展示数据集
    datasets.add("Authorship")

    return sorted(datasets)


# ===============================
# ⚠️ 你自己的 Agent 入口
# ===============================
def run_agent_for_dataset(dataset):
    """
    ⚠️ 用你自己的 router / agent 替换这里
    必须返回 List[Dict]
    """
    # ---------------------------
    # 示例（占位）
    # ---------------------------
    return [
        {
            "algorithm": "UCRFS",
            "num_features": 15,
            "mean_f1": 0.9233716475,
            "mean_auc": 0.9816098520,
            "time": 5.75,
            "score": 0.9408431088,
        },
        {
            "algorithm": "JMIM",
            "num_features": 15,
            "mean_f1": 0.918,
            "mean_auc": 0.979,
            "time": 7.32,
            "score": 0.932,
        },
    ]


# ===============================
# 页面
# ===============================
@app.route("/")
def index():
    return render_template(
        "index.html",
        datasets=list_available_datasets(),
        default_dataset="Authorship",
    )


# ===============================
# API：获取结果
# ===============================
@app.route("/api/results")
def get_results():
    dataset = request.args.get("dataset", "Authorship")

    # ① 内存缓存
    if dataset in RESULT_CACHE:
        rank_results = jsonify(RESULT_CACHE[dataset])

    # ② 磁盘 pkl
    results = load_result_pkl(dataset)
    if results is not None:
        RESULT_CACHE[dataset] = results
        rank_results = jsonify(results)

    # ③ Agent 实时运行
    results = run_agent_for_dataset(dataset)

    # ④ 存储
    save_result_pkl(dataset, results)
    RESULT_CACHE[dataset] = results

    rank_results = jsonify(results)
    leaderboard = rank_results(rank_results)
    return leaderboard
# @app.route("/api/results")
# def get_results():
    dataset = request.args.get("dataset", "Authorship")

    print(f"[DEBUG] request dataset = {dataset}")

    if dataset in RESULT_CACHE:
        print("[DEBUG] hit memory cache")
        return jsonify(RESULT_CACHE[dataset])

    results = load_result_pkl(dataset)
    if results is not None:
        print("[DEBUG] hit pkl cache")
        RESULT_CACHE[dataset] = results
        return jsonify(results)

    print("[DEBUG] run agent")
    results = run_agent_for_dataset(dataset)
    print("[DEBUG] agent results =", results)

    save_result_pkl(dataset, results)
    RESULT_CACHE[dataset] = results
    return jsonify(results)


# ===============================
# API：数据集列表
# ===============================
@app.route("/api/datasets")
def api_datasets():
    return jsonify(list_available_datasets())


if __name__ == "__main__":
    app.run(debug=True)