绘制ROC曲线并计算AUC

def solve():
    from pyodide.http import open_url
    from io import StringIO
    loans_clean_csv = open_url(____).read()
    loans_featured_csv = open_url(____).read()
    scorecard_data_csv = open_url(____).read()
    woe_table_csv = open_url(____).read()
    import pandas as pd
    import matplotlib
    matplotlib.use(____)
    import matplotlib.pyplot as plt
    from sklearn.linear_model import LogisticRegression
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import roc_curve,auc
    from io import StringIO
    df = pd.read_csv(StringIO(____))
    woe_cols=[c for c in df.columns if c.endswith(____)]
    X=df[woe_cols].fillna(____); y=df['____']
    X_tr,X_te,y_tr,y_te=train_test_split(____)
    lr=LogisticRegression(____); lr.fit(____)
    fpr,tpr,_=roc_curve(y_te,lr.predict_proba(____)[:,____])
    auc_val=auc(____)
    print(____)
    fig,ax=plt.subplots(figsize=(____,____))
    ax.plot(____)
    ax.plot(____)
    ax.set_xlabel(____); ax.set_ylabel(____); ax.set_title(____)
    ax.legend(); plt.tight_layout(); plt.show()