code: def test_trading(self):
      # date = "2020-02-03"
      # inst = "SH600068"
      # pos = 2.0167
      pos = 100000
      inst, date = "SH600519", "2021-01-18"
      market = [inst]
  
      start_time = f"{date}"
      end_time = (
          f"{date} 15:00"  # include the high-freq data on the end day
      )
      freq_l0 = "day"
      freq_l1 = "30min"
      freq_l2 = "1min"
  
      orders = self._gen_orders(inst=inst, date=date, pos=pos * 0.90)
  
      strategy_config = {
          "class": "FileOrderStrategy",
          "module_path": "qlib.contrib.strategy.rule_strategy",
          "kwargs": {
              "trade_range": TradeRangeByTime("10:45", "14:44"),
              "file": orders,
          },
      }
      backtest_config = {
          "start_time": start_time,
          "end_time": end_time,
          "account": {
              "cash": 0,
              inst: pos,
          },
          "benchmark": None,  # benchmark is not required here for trading
          "exchange_kwargs": {
              "freq": freq_l2,  # use the most fine-grained data as the exchange
              "limit_threshold": 0.095,
              "deal_price": "close",
              "open_cost": 0.0005,
              "close_cost": 0.0015,
              "min_cost": 5,
              "codes": market,
              "trade_unit": 100,
          },
          # "pos_type": "InfPosition"  # Position with infinitive position
      }
      executor_config = {
          "class": "NestedExecutor",  # Level 1 Order execution
          "module_path": "qlib.backtest.executor",
          "kwargs": {
              "time_per_step": freq_l0,
              "inner_executor": {
                  "class": "NestedExecutor",  # Leve 2 Order Execution
                  "module_path": "qlib.backtest.executor",
                  "kwargs": {
                      "time_per_step": freq_l1,
                      "inner_executor": {
                          "class": "SimulatorExecutor",
                          "module_path": "qlib.backtest.executor",
                          "kwargs": {
                              "time_per_step": freq_l2,
                              "generate_portfolio_metrics": False,
                              "verbose": True,
                              "indicator_config": {
                                  "show_indicator": False,
                              },
                              "track_data": True,
                          },
                      },
                      "inner_strategy": {
                          "class": "TWAPStrategy",
                          "module_path": "qlib.contrib.strategy.rule_strategy",
                      },
                      "generate_portfolio_metrics": False,
                      "indicator_config": {
                          "show_indicator": True,
                      },
                      "track_data": True,
                  },
              },
              "inner_strategy": {
                  "class": "TWAPStrategy",
                  "module_path": "qlib.contrib.strategy.rule_strategy",
              },
              "generate_portfolio_metrics": False,
              "indicator_config": {
                  "show_indicator": True,
              },
              "track_data": True,
          },
      }
  
      ret_val = {}
      decisions = list(
          collect_data(
              executor=executor_config,
              strategy=strategy_config,
              **backtest_config,
              return_value=ret_val,
          )
      )
      report, indicator = ret_val["report"], ret_val["indicator"]
      # NOTE: please refer to the docs of format_decisions
      # NOTE: `"track_data": True,`  is very NECESSARY for collecting the decision!!!!!
      f_dec = format_decisions(decisions)
      print(indicator["1day"][0])
  
file_path: qlib/tests/backtest/test_high_freq_trading.py
imports: from typing import List, Tuple, Union
  from qlib.backtest.position import Position
  from qlib.backtest import collect_data, format_decisions
  from qlib.backtest.decision import BaseTradeDecision, TradeRangeByTime
  import qlib
  from qlib.tests import TestAutoData
  import unittest
  import pandas
label_desc: Use image node_id 3 for calling the TestHFBacktest obj's underlying member method code with example usage: obj.test_trading() without return types