ValueError: The truth value of a DataFrame is ambiguous.

Question

在执行 return render_template('index_db.html', data=data1)时报以下错误：
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

程序为：

from flask import Flask, render_template, request
import dolphindb as ddb
import pandas as pd

app = Flask(__name__)

s = ddb.session()
s.connect("localhost", 8902, "admin", "123456")
@app.route('/', methods=['GET', 'POST'])
def index():
    data1 = None
    if request.method == 'POST':
        # 用户提交了表单
        selected_date = request.form.get('selected_date')
        data1 = query_dolphindb(selected_date)
    # 渲染模板并传递数据
    return render_template('index_db.html', data=data1)

def query_dolphindb(selected_date):
    results1_df = pd.DataFrame()
    tb = s.loadTable(dbPath="dfs://tushare2", tableName="hushen_daily_line")
    s1 = tb.exec('*').limit([2, 5])
    results1_df = s1.toDF()
    return results1_df
if __name__ == '__main__':
    app.run(debug=True)

debug时，跟踪到报错的flask语句为: rv = self.dispatch_request()

 try:
            request_started.send(self, _async_wrapper=self.ensure_sync)
            rv = self.preprocess_request()
            if rv is None:
                rv = self.dispatch_request()
        except Exception as e:
            rv = self.handle_user_exception(e)
        return self.finalize_request(rv)

Answer 1

from flask import Flask, render_template, request, abort
import dolphindb as ddb
import pandas as pd
 
app = Flask(__name__)
 
s = ddb.session()
s.connect("localhost", 8902, "admin", "123456")
@app.route('/', methods=['GET', 'POST'])
def index():
    data1 = None
    if request.method == 'POST':
        # 用户提交了表单
        selected_date = request.form.get('selected_date')
        data1 = query_dolphindb(selected_date)
        # 将data参数转换为一个字典
        return render_template('index_db.html', data=data1.to_dict())
    # 当request.method不是POST时，返回一个默认的响应对象
    return render_template('index_db.html', data=None)
 
def query_dolphindb(selected_date):
    results1_df = pd.DataFrame()
    tb = s.loadTable(dbPath="dfs://tushare2", tableName="hushen_daily_line")
    s1 = tb.exec('*').limit([2, 5])
    results1_df = s1.toDF()
    return results1_df
if __name__ == '__main__':
    app.run(debug=True)