revert main connection contract

harness_engineering/backtest.py

@@ -0,0 +1,113 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+测试脚本：使用本地行情服务器进行回测
+"""
+
+import time
+from datetime import date
+import logging
+# 必须导入 TargetPosTask
+from tqsdk import TqApi, TqAuth, TqBacktest, TqSim, TargetPosTask 
+from tqsdk.exceptions import BacktestFinished
+
+LOCAL_INS_URL = "http://localhost:17788/symbols/latest.json"
+LOCAL_MD_URL = "ws://localhost:17789"
+
+logging.getLogger("TQSIM").setLevel(logging.WARNING)
+
+def run_local_backtest():
+    total_start = time.time()
+
+    try:
+        account=TqSim()
+        api = TqApi(
+            account=account,
+            #backtest=TqBacktest(start_dt=date(2025, 1, 1), end_dt=date(2025, 1, 31)),
+            backtest=TqBacktest(start_dt=date(2025, 1, 1), end_dt=date(2025, 12, 31)),
+            auth=None,
+            #auth=TqAuth("suolong33", "suolong33"),
+            _ins_url=LOCAL_INS_URL,
+            _md_url=LOCAL_MD_URL,
+            disable_print=True,
+        )
+        #api = TqApi(
+        #    account=TqSim(),
+        #    backtest=TqBacktest(start_dt=date(2025, 3, 5), end_dt=date(2025, 3, 8)),
+        #    auth=TqAuth("suolong33", "suolong33"),
+        #    #_ins_url=LOCAL_INS_URL,
+        #    #_md_url=LOCAL_MD_URL
+        #)
+
+        init_time = time.time() - total_start
+
+        #symbol = "SHFE.rb2505"
+        symbol1 = "KQ.m@SHFE.rb"
+        symbol2 = "KQ.m@SHFE.au"
+
+        # 尝试获取 K 线
+        # 注意：在本地回测中，有时需要先 wait_update 一次让图表建立
+        klines1 = api.get_kline_serial(symbol1, 60)
+        klines2 = api.get_kline_serial(symbol2, 60)
+
+        #if len(klines) > 0:
+        #    print(klines.tail(3))
+
+        target_pos1 = TargetPosTask(api, symbol1)
+        target_pos2 = TargetPosTask(api, symbol2)
+
+        loop_count = 0
+        while True:
+            api.wait_update()
+            loop_count += 1
+
+            # 简单的退出条件，防止死循环，实际由 BacktestFinished 异常退出
+            #if loop_count > 100000: 
+            #    break
+
+            if api.is_changing(klines1):
+                if len(klines1) >= 15:
+                    last_close = klines1.close.iloc[-1]
+                    ma = sum(klines1.close.iloc[-15:]) / 15
+                    current_price = klines1.close.iloc[-1]
+
+                    # if loop_count % 500 == 0:
+                    #     print(f"   ... 已处理 {loop_count} 次更新，最新价: {current_price}, MA: {ma:.2f}")
+
+                    if current_price > ma:
+                        target_pos1.set_target_volume(5)
+                    elif current_price < ma:
+                        target_pos1.set_target_volume(0)
+
+            if api.is_changing(klines2):
+                if len(klines2) >= 15:
+                    last_close = klines2.close.iloc[-1]
+                    ma = sum(klines2.close.iloc[-15:]) / 15
+                    current_price = klines2.close.iloc[-1]
+
+                    if current_price > ma:
+                        target_pos2.set_target_volume(5)
+                    elif current_price < ma:
+                        target_pos2.set_target_volume(0)
+
+    except BacktestFinished:
+        total_time = time.time() - total_start
+        print(f"\n✅ 回测正常结束!")
+        print(f"")
+        print(f"⏱️ 初始化时间: {init_time:.2f}s 回测时间: {total_time - init_time:.2f}s 总耗时: {total_time:.2f}s 循环次数: {loop_count}")
+        # 打印最终账户情况
+        print(api.get_account())
+
+    except Exception as e:
+        print(f"\n❌ 发生错误: {e}")
+        import traceback
+        traceback.print_exc()
+
+    finally:
+        try:
+            api.close()
+        except:
+            pass
+
+if __name__ == "__main__":
+    run_local_backtest()

harness_engineering/backtest_single.py

@@ -0,0 +1,98 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+测试脚本：使用本地行情服务器进行回测
+"""
+
+import time
+from datetime import date
+import logging
+# 必须导入 TargetPosTask
+from tqsdk import TqApi, TqAuth, TqBacktest, TqSim, TargetPosTask 
+from tqsdk.exceptions import BacktestFinished
+
+LOCAL_INS_URL = "http://localhost:17788/symbols/latest.json"
+LOCAL_MD_URL = "ws://localhost:17789"
+
+logging.getLogger("TQSIM").setLevel(logging.WARNING)
+
+def run_local_backtest():
+    total_start = time.time()
+
+    try:
+        account=TqSim()
+        api = TqApi(
+            account=account,
+            backtest=TqBacktest(start_dt=date(2025, 1, 1), end_dt=date(2025, 12, 31)),
+            auth=None,
+            #auth=TqAuth("suolong33", "suolong33"),
+            _ins_url=LOCAL_INS_URL,
+            _md_url=LOCAL_MD_URL,
+            disable_print=True,
+        )
+        #api = TqApi(
+        #    account=TqSim(),
+        #    backtest=TqBacktest(start_dt=date(2025, 3, 5), end_dt=date(2025, 3, 8)),
+        #    auth=TqAuth("suolong33", "suolong33"),
+        #    #_ins_url=LOCAL_INS_URL,
+        #    #_md_url=LOCAL_MD_URL
+        #)
+
+        init_time = time.time() - total_start
+
+        #symbol = "SHFE.rb2505"
+        symbol1 = "KQ.m@SHFE.rb"
+
+        # 尝试获取 K 线
+        # 注意：在本地回测中，有时需要先 wait_update 一次让图表建立
+        klines1 = api.get_kline_serial(symbol1, 60)
+
+        #if len(klines) > 0:
+        #    print(klines.tail(3))
+
+        target_pos1 = TargetPosTask(api, symbol1)
+
+        loop_count = 0
+        while True:
+            api.wait_update()
+            loop_count += 1
+
+            # 简单的退出条件，防止死循环，实际由 BacktestFinished 异常退出
+            #if loop_count > 100000: 
+            #    break
+
+            if api.is_changing(klines1):
+                if len(klines1) >= 15:
+                    last_close = klines1.close.iloc[-1]
+                    ma = sum(klines1.close.iloc[-15:]) / 15
+                    current_price = klines1.close.iloc[-1]
+
+                    if loop_count % 500 == 0:
+                        print(f"   ... 已处理 {loop_count} 次更新，最新价: {current_price}, MA: {ma:.2f}")
+
+                    if current_price > ma:
+                        target_pos1.set_target_volume(5)
+                    elif current_price < ma:
+                        target_pos1.set_target_volume(0)
+
+    except BacktestFinished:
+        total_time = time.time() - total_start
+        print(f"\n✅ 回测正常结束!")
+        print(f"")
+        print(f"⏱️ 初始化时间: {init_time:.2f}s 回测时间: {total_time - init_time:.2f}s 总耗时: {total_time:.2f}s 循环次数: {loop_count}")
+        # 打印最终账户情况
+        print(api.get_account())
+
+    except Exception as e:
+        print(f"\n❌ 发生错误: {e}")
+        import traceback
+        traceback.print_exc()
+
+    finally:
+        try:
+            api.close()
+        except:
+            pass
+
+if __name__ == "__main__":
+    run_local_backtest()

harness_engineering/program.md

@@ -0,0 +1,53 @@
+# Automatic Performance Optimization
+
+This is an experiment to have claude code to keep optimizing the performance of the framework tqsdk-python (current repo) based on cProfile results.
+
+## Plan
+You are given the source code of tqsdk-python, a backtest framework for Chinese CTA futures market, and a script to run backtest of a strategy by calling the sdk. You need to keep analyzing the profile data from cProfile, and find ways to improve the system performance.
+
+## Setup
+You are working in two repos:
+1. `./tqsdk`: contains tqsdk-python's complete source code.
+2. `./harness_engineering`, which has its own virtual environment and contains backtest code using the current repo (it's `tqsdk-python` in its uv environment is pointing to the current repo)
+
+To set up a new experiment, work with the user to:
+**Start by running the first profiling**. run `cd harness_engineering && uv run python -m cProfile -o result.prof backtest.py`
+
+Once you get confirmation, kick off the experimentation.
+
+## Experimentation
+
+### Step 1: Analyze the existing cProfile result and find ways to improve the repo's performance.
+Look at the git state: the current branch/commit we're on.
+
+Then run this command to get the backtest's top 10 functions sorted by tottime: `cd harness_engineering && uv run python -c "import pstats; p = pstats.Stats('result.prof'); p.sort_stats('tottime').print_stats(10)"`
+
+Then optimize the current repo's code based on the cProfile result. 
+
+**What you CAN do:**
+Analyze and modify the code in `./tqsdk` however you want.
+
+**What you CANNOT do:**
+- Modify anything in `./harness_engineering`
+
+**The goal is simple: get the lowest total backtest time, while keeping its backtest result exactly the same.**
+
+### Step 2. Verify the optimization
+Run the following command to profile the result:
+`cd harness_engineering && uv run python -m cProfile -o new_result.prof backtest.py`
+
+Two things to verify:
+1. The result backtest time is shorter than previous.
+2. The following backtest metrics MUST BE exactly the same as the backtest result(other metrics we don't care):
+```
+{'currency': 'CNY', 'pre_balance': 9165485.597521082, 'static_balance': 9165485.597521082, 'balance': 9165485.597521082, 'available': 9165485.097521082, 'ctp_balance': nan, 'ctp_available': nan, 'float_profit': 33099.99999999999, 'position_profit': 0.0, 'close_profit': 0.0, 'frozen_margin': 0.0, 'margin': 0.5, 'frozen_commission': 0.0, 'commission': 0.0, 'frozen_premium': 0.0, 'premium': 0.0, 'deposit': 0.0, 'withdraw': 0.0, 'risk_ratio': 5.455248330052814e-08, 'market_value': 0.0, '_tqsdk_stat': <tqsdk.entity.Entity object at 0x7d789e3fc9b0>, D({'start_date': '2025-01-01', 'end_date': '2025-12-31', 'init_balance': np.float64(10000000.0), 'balance': np.float64(9165485.597521082), 'start_balance': np.float64(10000000.0), 'end_balance': np.float64(9165485.597521082), 'ror': np.float64(-0.08345144024789186), 'annual_yield': np.float64(-0.08541331095548088), 'trading_days': 244, 'cum_profit_days': np.int64(92), 'cum_loss_days': np.int64(151), 'max_drawdown': np.float64(0.10702989218181808), 'commission': np.float64(14.40250000000001), 'open_times': 14403, 'close_times': 14402, 'daily_risk_ratio': np.float64(5.674929510006093e-08), 'max_cont_profit_days': np.int64(6), 'max_cont_loss_days': np.int64(11), 'sharpe_ratio': np.float64(-1.9706534357067889), 'calmar_ratio': np.float64(-0.0663809545753567), 'sortino_ratio': np.float64(-1.6926465451120536), 'tqsdk_punchline': '不要灰心，少侠重新来过', 'profit_volumes': 11850, 'loss_volumes': 60160, 'profit_value': np.float64(8928950.000000276), 'loss_value': np.float64(-9796549.999999123), 'winning_rate': 0.16456047771142898, 'profit_loss_ratio': np.float64(4.62718335334115)})}
+```
+
+If both are true,
+1. use the new cProfile result for the next round and run: `cd harness_engineering && mv new_result.prof result.prof`
+2. git commit with the improvement and the reduced time.
+
+If either one is not true, then abandon the current change and start over from step 1.
+
+### LOOP FOREVER
+The idea is that you are a completely autonomous performance engineer trying things out. If they work, keep. If they don't, discard. And you're advancing the branch so that you can iterate.

harness_engineering/pyproject.toml

@@ -0,0 +1,21 @@
+[project]
+name = "tq-local-server"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.14"
+dependencies = [
+    "ipdb>=0.13.13",
+    "orjson>=3.11.7",
+    "snakeviz>=2.2.2",
+    "tqdm>=4.67.3",
+    "tqsdk",
+]
+
+[[index]]
+name = "tuna"
+url = "https://pypi.tuna.tsinghua.edu.cn/simple"
+default = true
+
+[tool.uv.sources]
+tqsdk = { path = "../tqsdk-python", editable = true }

harness_engineering/readme.md

@@ -0,0 +1,6 @@
+# How to run it?
+1. Launch claude (You may want to use `claude --dangerously-skip-permissions` to skip permissions)
+2. in claude, type "Hi take a look at harness_engineering/program.md and let's start our first experiment."
+
+# What's run_benchamrks.sh for?
+It's used to re-profile all claude commits

harness_engineering/run_benchmarks.sh

@@ -0,0 +1,48 @@
+#!/bin/bash
+# Benchmark each commit ahead of origin/master
+# Runs backtest.py for each commit and saves output to a log file
+
+set -e
+
+REPO_DIR="/home/zzk/Projects/tqsdk-python"
+TEST_DIR="/home/zzk/Projects/tq_sdk_test"
+CURRENT_BRANCH=$(git -C "$REPO_DIR" rev-parse --abbrev-ref HEAD)
+
+# Get commits in chronological order (oldest first)
+mapfile -t COMMITS < <(git -C "$REPO_DIR" log --reverse --format="%H %s" origin/master..HEAD)
+
+TOTAL=${#COMMITS[@]}
+echo "Found $TOTAL commits to benchmark"
+echo "Current branch: $CURRENT_BRANCH"
+echo ""
+
+COUNT=0
+for entry in "${COMMITS[@]}"; do
+    HASH="${entry%% *}"
+    MESSAGE="${entry#* }"
+    SHORT_HASH="${HASH:0:7}"
+    COUNT=$((COUNT + 1))
+
+    # Sanitize message: first 50 chars, replace non-alphanumeric with _
+    SAFE_MSG=$(echo "$MESSAGE" | head -c 50 | sed 's/[^a-zA-Z0-9_-]/_/g')
+    LOGFILE="${TEST_DIR}/${COUNT}_${SAFE_MSG}_${SHORT_HASH}.log"
+
+    echo "[$COUNT/$TOTAL] $SHORT_HASH $MESSAGE"
+
+    # Checkout the commit
+    git -C "$REPO_DIR" checkout --quiet "$HASH"
+
+    # Run backtest and save output
+    echo "Commit: $SHORT_HASH $MESSAGE" > "$LOGFILE"
+    echo "Date: $(git -C "$REPO_DIR" log -1 --format='%ci' "$HASH")" >> "$LOGFILE"
+    echo "---" >> "$LOGFILE"
+    (cd "$TEST_DIR" && uv run backtest.py) >> "$LOGFILE" 2>&1 || true
+
+    echo "  -> saved to $(basename "$LOGFILE")"
+    echo ""
+done
+
+# Restore original branch
+echo "Restoring branch: $CURRENT_BRANCH"
+git -C "$REPO_DIR" checkout --quiet "$CURRENT_BRANCH"
+echo "Done! All $TOTAL benchmarks complete."