How TqSdk Differs from vn.py for Strategy Development
Article TqSdk
Summary
This comparison explains differences between TqSdk and vn.py that matter when adapting existing trading strategies. vn.py is presented as an integrated package with market data, trading connections, storage, and interface components. TqSdk instead uses cooperating network components: market-data and trade gateways connect to exchange or broker systems and provide services to the client through a shared protocol. The document also contrasts vn.py’s strategy classes and event callbacks with TqSdk’s standalone Python scripts and update loop.
In TqSdk, calls such as quote, bar, and order functions return reference objects whose fields refresh after wait_update; is_changing can identify which objects or fields were updated. Strategies must keep calling wait_update for data and order processing to advance, and should avoid blocking the loop with sleep. The article also describes charting and backtesting support, including tick and bar testing with multiple data series and no user-prepared dataset. These are framework-level descriptions and examples, not a benchmark or independent assessment of either platform’s performance.
Key ideas
- vn.py is described as an integrated framework, while TqSdk uses network-connected data and trading components.
- The platforms differ in strategy structure: vn.py uses event callbacks, while TqSdk uses scripts that repeatedly call an update function.
- TqSdk data and order objects are references whose fields update after wait_update returns.
- Users can use is_changing to check whether a particular object or field changed during an update.
- TqSdk includes charting and backtesting features, but the document provides no comparative performance measurements.
Tags
Full text
# for vnpy user
.. _for_vnpy_user:
TqSdk 与 vn.py 有哪些差别
=================================================
TqSdk 与 vn.py 有非常多的差别. 如果您是一位有经验的 vn.py 用户, 刚开始接触 TqSdk, 下面的信息将帮助您尽快理解 TqSdk.
如果你只是想先跑通一套最小程序，建议先看 :ref:`quickstart` 和 :ref:`framework`；本文更适合在迁移已有策略代码时对照阅读。
系统整体架构
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vn.py 是一套 all-in-one 的结构, 在一个Python软件包中包含了数据库, 行情接收/存储, 交易接口, 图形界面等功能.
TqSdk 则使用基于网络协作的组件设计. 如下图:
.. raw:: html
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font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 116px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;"><a href="https://github.com/shinnytech/open-trade-gateway">Open Trade Gateway<br />交易中继网关</a><br /></div></div></foreignObject><text x="57" y="19" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">[Not supported by viewer]</text></switch></g></a><rect x="0" y="0" width="280" height="40" fill="#eeeeee" stroke="#36393d"/><g transform="translate(84.5,6.5)"><switch><foreignObject style="overflow:visible;" pointer-events="all" width="110" height="26" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 110px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;">期货公司交易系统<br />CTP / FEMAS / UFX<br /></div></div></foreignObject><text x="55" y="19" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">期货公司交易系统<br>CTP / FEMAS / UFX<br></text></switch></g><rect x="480" y="0" width="280" height="40" fill="#eeeeee" stroke="#36393d"/><g transform="translate(577.5,13.5)"><switch><foreignObject style="overflow:visible;" pointer-events="all" width="84" height="12" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 85px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;">交易所行情系统<br /></div></div></foreignObject><text x="42" y="12" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">交易所行情系统<br></text></switch></g><path d="M 140 60 L 140 40" fill="none" stroke="#000000" stroke-miterlimit="10"/><path d="M 380 120 L 140 100" fill="none" stroke="#000000" stroke-miterlimit="10"/><path d="M 380 120 L 620 100" fill="none" stroke="#000000" stroke-miterlimit="10"/><rect x="0" y="120" width="760" height="40" rx="6" ry="6" fill="#f8cecc" stroke="#b85450"/><g transform="translate(352.5,133.5)"><switch><foreignObject style="overflow:visible;" pointer-events="all" width="54" height="12" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 55px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;">DIFF 协议</div></div></foreignObject><text x="27" y="12" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">[Not supported by viewer]</text></switch></g><path d="M 380 180 L 380 160" fill="none" stroke="#000000" stroke-miterlimit="10"/><a xlink:href="http://www.shinnytech.com/tianqin"><rect x="320" y="180" width="120" height="40" fill="#dae8fc" stroke="#6c8ebf"/><g transform="translate(355.5,193.5)"><switch><foreignObject style="overflow:visible;" pointer-events="all" width="48" height="12" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 49px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;"><a href="http://www.tq18.cn">天勤终端</a></div></div></foreignObject><text x="24" y="12" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">[Not supported by viewer]</text></switch></g></a><a xlink:href="https://github.com/shinnytech/tqsdk-python"><rect x="320" y="220" width="120" height="40" fill="#dae8fc" stroke="#6c8ebf"/><g transform="translate(362.5,233.5)"><switch><foreignObject style="overflow:visible;" pointer-events="all" width="34" height="12" requiredFeatures="http://www.w3.org/TR/SVG11/feature#Extensibility"><div xmlns="http://www.w3.org/1999/xhtml" style="display: inline-block; font-size: 12px; font-family: Helvetica; color: rgb(0, 0, 0); line-height: 1.2; vertical-align: top; width: 36px; white-space: nowrap; overflow-wrap: normal; text-align: center;"><div xmlns="http://www.w3.org/1999/xhtml" style="display:inline-block;text-align:inherit;text-decoration:inherit;"><a href="https://github.com/shinnytech/tqsdk-python">TqSdk</a><br /></div></div></foreignObject><text x="17" y="12" fill="#000000" text-anchor="middle" font-size="12px" font-family="Helvetica">[Not supported by viewer]</text></switch></g></a></g></svg>
如图所示, 整个系统结构包括这些关键组件:
* 行情网关 (Open Md Gateway) 负责提供实时行情和历史数据
* 交易中继网关 (Open Trade Gateway) 负责连接到期货公司交易系统
* 上面两个网关统一以 Diff 协议对下方提供服务
* 天勤终端和TqSdk按照Diff协议连接到行情网关和交易中继网关, 实现行情和交易功能
这样的结构可以给用户带来一些好处:
* TqSdk 很小, 安装也很方便, 只要简单 pip install tqsdk 即可
* 官方专门运维行情数据库, 用户可以直接使用, 不需要自己接收和存储数据
* 交易相关接口被大幅度简化, 不再需要处理CTP接口的复杂回调, 也不需要发起任何查询请求
对于需要直连期货公司交易的用户, TqSdk 也提供了 :py:class:`~tqsdk.TqCtp` 模块支持用户直连
每个策略是一个单独运行的py文件
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在 vn.py 中, 要实现一个策略程序, 通常是从 CtaTemplate 等基类派生一个子类, 像这样::
class DoubleMaStrategy(CtaTemplate):
parameters = ["fast_window", "slow_window"]
variables = ["fast_ma0", "fast_ma1", "slow_ma0", "slow_ma1"]
def __init__(self, cta_engine, strategy_name, vt_symbol, setting):
...
def on_tick(self, tick: TickData):
...
def on_bar(self, bar: BarData):
...
这个 DoubleMaStrategy 类写好以后, 由vn.py的策略管理器负责加载运行. 整个程序结构中, vn.py作为调用方, 用户代码作为被调用方, 结构图是这样的:
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而在 TqSdk 中, 策略程序并没有一个统一的基类. TqSdk只是提供一些行情和交易函数, 用户可以任意组合它们来实现自己的策略程序, 还是以双均线策略为例::
'''
双均线策略
'''
from tqsdk import TqApi, TqAuth, TqSim, TargetPosTask
from tqsdk.tafunc import ma
SHORT = 30
LONG = 60
SYMBOL = "SHFE.bu2609"
api = TqApi(auth=TqAuth("快期账户", "账户密码"))
data_length = LONG + 2
klines = api.get_kline_serial(SYMBOL, duration_seconds=60, data_length=data_length)
target_pos = TargetPosTask(api, SYMBOL)
while True:
api.wait_update()
if api.is_changing(klines.iloc[-1], "datetime"): # 产生新k线:重新计算SMA
short_avg = ma(klines.close, SHORT) # 短周期
long_avg = ma(klines.close, LONG) # 长周期
# 均线下穿，做空
if long_avg.iloc[-2] < short_avg.iloc[-2] and long_avg.iloc[-1] > short_avg.iloc[-1]:
target_pos.set_target_volume(-3)
print("均线下穿，做空")
# 均线上穿，做多
if short_avg.iloc[-2] < long_avg.iloc[-2] and short_avg.iloc[-1] > long_avg.iloc[-1]:
target_pos.set_target_volume(3)
print("均线上穿，做多")
以上代码文件单独运行, 即可执行一个双均线交易策略. 整个程序结构中, 用户代码作为调用方, TqSdk库代码作为被调用方, 每个策略是完全独立的. 结构是这样:
.. raw:: html
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TqSdk将每个策略作为一个独立进程运行, 这样就可以:
* 在运行多策略时可以充分利用多CPU的计算能力
* 每个策略都可以随时启动/停止/调试/修改代码, 而不影响其它策略程序的运行
* 可以方便的针对单个策略程序进行调试
在策略程序中, 用户代码可以随意调用 TqSdk 包中的任意函数, 这带来了更大的自由度, 比如:
* 在一个策略程序中使用多个合约或周期的K线数据, 盘口数据和Tick数据. 对于某些类型的策略来说这是很方便的
* 对多个合约的交易指令进行精细管理
* 管理复杂的子任务
* 方便策略程序跟其它库或框架集成
以一个套利策略的代码为例::
'''
价差回归
当近月-远月的价差大于200时做空近月，做多远月
当价差小于150时平仓
'''
from tqsdk import TqApi, TqAuth, TargetPosTask
api = TqApi(auth=TqAuth("快期账户", "账户密码"))
quote_near = api.get_quote("SHFE.rb2610")
quote_deferred = api.get_quote("SHFE.rb2701")
# 创建 rb2610 的目标持仓 task，该 task 负责调整 rb2610 的仓位到指定的目标仓位
target_pos_near = TargetPosTask(api, "SHFE.rb2610")
# 创建 rb2701 的目标持仓 task，该 task 负责调整 rb2701 的仓位到指定的目标仓位
target_pos_deferred = TargetPosTask(api, "SHFE.rb2701")
while True:
api.wait_update()
if api.is_changing(quote_near) or api.is_changing(quote_deferred):
spread = quote_near.last_price - quote_deferred.last_price
print("当前价差:", spread)
if spread > 250:
print("目标持仓: 空近月，多远月")
# 设置目标持仓为正数表示多头，负数表示空头，0表示空仓
target_pos_near.set_target_volume(-1)
target_pos_deferred.set_target_volume(1)
elif spread < 200:
print("目标持仓: 空仓")
target_pos_near.set_target_volume(0)
target_pos_deferred.set_target_volume(0)
在这个程序中, 我们同时跟踪两个合约的行情信息, 并为两个合约各创建一个调仓任务, 可以方便的实现套利策略
K线数据与指标计算
-------------------------------------------------
使用vn.py时, K线是由vn.py接收实时行情, 并在用户电脑上生成K线, 存储于用户电脑上的数据库中.
而在TqSdk中, K线数据和其它行情数据一样是由行情网关生成并推送的. 这带来了一些差别:
* 用户不再需要维护K线数据库. 用户电脑实时行情中断后, 也不再需要补历史数据
* 行情服务器生成K线时, 采用了按K线时间严格补全对齐的算法. 这与vn.py或其它软件有明显区别, 详见 https://www.shinnytech.com/articles/reference/why-our-klines-are-different
* 行情数据只在每次程序运行时通过网络获取, 不在用户硬盘保存. 如果策略研究工作需要大量静态历史数据, 我们推荐使用数据下载工具, 另行下载csv文件使用.
TqSdk中的K线序列采用 pandas.DataFrame 格式. pandas 提供了 `非常丰富的数据处理函数 <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html>`_ , 使我们可以非常方便的进行数据处理, 例如::
ks = api.get_kline_serial("SHFE.cu2607", 60)
print(ks.iloc[-1]) # <- 最后一根K线
print(ks.close) # <- 收盘价序列
ks.high - ks.high.shift(1) # <- 每根K线最高价-前一根K线最高价, 形成一个新序列
TqSdk 也通过 :py:mod:`tqsdk.tafunc` 提供了一批行情分析中常用的计算函数, 例如::
from tqsdk import tafunc
ks = api.get_kline_serial("SHFE.cu2607", 60)
ms = tafunc.max(ks.open, ks.close) # <- 取每根K线开盘价和收盘价的高者构建一个新序列
median3 = tafunc.median(ks.close, 100) # <- 求最近100根K线收盘价的中间值
ss = tafunc.std(ks.close, 5) # <- 每5根K线的收盘价标准差
数据接收和更新
-------------------------------------------------
vn.py按照事件回调模型设计, 使用 CtaTemplate 的 on_xxx 回调函数进行行情数据和回单处理::
class DoubleMaStrategy(CtaTemplate):
def on_tick(self, tick: TickData):
...
def on_bar(self, bar: BarData):
...
def on_order(self, order: OrderData):
pass
def on_trade(self, trade: TradeData):
self.put_event()
TqSdk则不使用事件回调机制. :py:meth:`~tqsdk.TqApi.wait_update` 函数设计用来获取任意数据更新, 像这样::
from tqsdk import TqApi, TqAuth
api = TqApi(auth=TqAuth("快期账户", "账户密码"))
ks = api.get_kline_serial("SHFE.cu2607", 60)
while True:
api.wait_update() # <- 这个 wait_update 将尝试更新所有数据. 如果没有任何新信息, 程序会阻塞在这一句. 一旦有任意数据被更新, 程序会继续往下执行
print(ks.close.iloc[-1]) # <- 最后一根K线的收盘价
一次 wait_update 可能更新多个实体, 在这种情况下, :py:meth:`~tqsdk.TqApi.is_changing` 被用来判断某个实体是否有变更::
from tqsdk import TqApi, TqAuth
api = TqApi(auth=TqAuth("快期账户", "账户密码"))
q = api.get_quote("SHFE.cu2607")
ks = api.get_kline_serial("SHFE.cu2607", 60)
x = api.insert_order("SHFE.cu2607", direction="BUY", offset="OPEN", volume=1, limit_price=50000)
while True:
api.wait_update() # <- 这个 wait_update 将尝试更新所有数据. 如果没有任何新信息, 程序会阻塞在这一句. 一旦有任意数据被更新, 程序会继续往下执行
if api.is_changing(q): # <- 这个 is_changing 用来判定这次更新是否影响到了q
print(q)
if api.is_changing(x, "status"): # <- 这个 is_changing 用来判定这次更新是否影响到了报单的status字段
print(x)
TqSdk针对行情数据和交易信息都采用相同的 wait_update/is_changing 方案. 用户需要记住的要点包括:
* get_quote、get_kline_serial、insert_order 等业务函数返回的是引用对象（reference, not value），它们的字段会在 wait_update 返回后刷新。
* 用户程序除执行自己业务逻辑外，还需要反复调用 wait_update；在两次 wait_update 之间，数据不会继续推进。
* 用 insert_order 函数下单后，还要继续调用 wait_update，报单指令才会真正发出。
* 用户程序中需要避免阻塞，不要直接用 sleep 暂停主循环；如果需要定时控制，请参考 :ref:`timer`。
关于 wait_update 机制的详细说明, 请见 :ref:`framework`
图形界面
-------------------------------------------------
TqSdk 提供 :ref:`web_gui` 来供有图形化需求的用户使用:
* 策略运行时, 交易记录和持仓记录自动在行情图上标记, 可以快速定位跳转, 可以跨周期缩放定位
* 策略回测时, 提供回测报告/图上标记和对应的回测分析报告.
* 策略运行和回测信息自动保存, 可事后随时查阅显示
TqSdk配合web_gui使用时, 还支持自定义绘制行情图表, 像这样::
from tqsdk import TqApi, TqAuth
api = TqApi(auth=TqAuth("快期账户","账户密码"), web_gui=True)
# 获取 cu2607 和 cu2608 的日线数据
klines = api.get_kline_serial("SHFE.cu2607", 86400)
klines2 = api.get_kline_serial("SHFE.cu2608", 86400)
# 算出 cu2608 - cu2607 的价差，并以折线型态显示在副图
klines["dif"] = klines2["close"] - klines["close"]
klines["dif.board"] = "DIF"
klines["dif.color"] = 0xFF00FF00
klines["dif.width"] = 3
回测
-------------------------------------------------
使用TqSdk开发的策略可以回测:
* 提供Tick及K线级别的回测.
* TqSdk 允许在一个策略中使用任意多个数据序列. 回测框架将正确识别并处理这种情况.
* 回测前不需要准备数据
关于策略回测的详细说明, 请见 :ref:`backtest`
推荐学习步骤
-------------------------------
要学习使用 TqSdk, 推荐从 :ref:`quickstart` 开始
使用过程中有任何问题可以 `询问天勤 AI 助手！ <https://udify.app/chat/im02prcHNEOVbPAx/>`_ ,尝试帮助解答用户以下问题：
* 具体函数的详细介绍
* 根据具体需求或策略提供天勤实现的示例
* 天勤或 Python 报错的可能解决方案Shown in full with attribution under the source's licence. Licence: Apache-2.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.