import MetaTrader5 as mt5
# 试着连一下
ifnot mt5.initialize():
print("完蛋，连不上，错误码:", mt5.last_error())
quit()
print("成了！")
# 用完记得关
mt5.shutdown()
3.2 指定账户登录（更常用）
import MetaTrader5 as mt5
# 你自己的账号信息
login = 123456# 改成你的
password = "your_password"
server = "YourBrokerServer"
if mt5.login(login, password, server):
print("登录成功")
else:
print("登录失败，错误码:", mt5.last_error())
mt5.shutdown()
踩坑提醒：密码输错不会报错直接崩，得用last_error()才能看到具体原因。
三、数据怎么拿
3.1 看看有哪些品种
import MetaTrader5 as mt5
import pandas as pd
ifnot mt5.initialize():
quit()
# 捞所有品种出来
symbols = mt5.symbols_get()
print(f"总共有 {len(symbols)} 个品种")
# 只瞅前5个
for i inrange(min(5, len(symbols))):
print(symbols[i].name)
# 单独查EURUSD的信息
info = mt5.symbol_info("EURUSD")
if info:
print(f"点差: {info.spread}")
print(f"最小手数: {info.volume_min}")
关于symbols_get()的用法，官方文档里有更详细的说明，比如可以用通配符"*"来筛选。symbol_info()返回的信息很全，包含点差、保证金要求、最小交易量这些。
3.2 扒K线数据
# 拉最近10根1分钟K线
rates = mt5.copy_rates_from_pos("EURUSD", mt5.TIMEFRAME_M1, 0, 10)
if rates isnotNone:
df = pd.DataFrame(rates)
# 把时间戳转成人类能看的时间
df['time'] = pd.to_datetime(df['time'], unit='s')
print(df.head())
注意：copy_rates_from_pos的第二个参数是时间周期，常用的有：
3.3 实时盯盘（订阅报价）
import time
defget_tick(symbol):
"""看一眼当前报价"""
tick = mt5.symbol_info_tick(symbol)
if tick:
print(f"{symbol} - 买价: {tick.bid}, 卖价: {tick.ask}")
if mt5.initialize():
# 先得把品种选中（相当于加到市场报价窗口里）
mt5.symbol_select("EURUSD", True)
# 看10次，每秒一次
for i inrange(10):
get_tick("EURUSD")
time.sleep(1)
mt5.shutdown()
四、查查账
if mt5.initialize():
acc = mt5.account_info()
if acc:
print(f"账户: {acc.login}")
print(f"余额: {acc.balance}")
print(f"净值: {acc.equity}")
print(f"已用保证金: {acc.margin}")
print(f"可用保证金: {acc.margin_free}")
print(f"杠杆: 1:{acc.leverage}")
mt5.shutdown()
account_info()会返回一堆东西，包括余额、净值、保证金、杠杆这些核心信息。如果需要查看MT5终端本身的设置和状态，可以用terminal_info()。
五、下单交易
5.1 开仓
defsend_order(symbol, order_type, volume):
"""发单函数"""
tick = mt5.symbol_info_tick(symbol)
request = {
"action": mt5.TRADE_ACTION_DEAL,
"symbol": symbol,
"volume": volume,
"type": order_type,
"price": tick.ask if order_type == mt5.ORDER_TYPE_BUY else tick.bid,
"deviation": 20,
"magic": 234000,
"comment": "python发单",
"type_time": mt5.ORDER_TIME_GTC,
"type_filling": mt5.ORDER_FILLING_IOC,
}
result = mt5.order_send(request)
return result
if mt5.initialize():
# 买0.1手
res = send_order("EURUSD", mt5.ORDER_TYPE_BUY, 0.1)
if res.retcode == mt5.TRADE_RETCODE_DONE:
print(f"成了，订单号: {res.order}")
else:
print(f"失败了，代码: {res.retcode}")
mt5.shutdown()
重要提醒：SL/TP可以按绝对价格给，也可以用点数偏移，处理时要留意小数位对齐。下单前最好先用symbol_info()查一下最小手数、点值这些。
5.2 改单（调止损止盈）
defmodify_sltp(ticket, sl_price, tp_price):
"""改止损止盈"""
request = {
"action": mt5.TRADE_ACTION_SLTP,
"position": ticket,
"sl": sl_price,
"tp": tp_price,
"magic": 234000,
}
return mt5.order_send(request)
5.3 平仓
defclose_a_position(ticket):
"""平掉某笔持仓"""
pos = mt5.positions_get(ticket=ticket)[0]
# 买单就用卖平，卖单就用买平
opposite_type = mt5.ORDER_TYPE_SELL if pos.type == mt5.ORDER_TYPE_BUY else mt5.ORDER_TYPE_BUY
request = {
"action": mt5.TRADE_ACTION_DEAL,
"position": ticket,
"symbol": pos.symbol,
"volume": pos.volume,
"type": opposite_type,
"deviation": 20,
"comment": "平仓",
"type_time": mt5.ORDER_TIME_GTC,
"type_filling": mt5.ORDER_FILLING_IOC,
}
return mt5.order_send(request)
六、历史数据怎么取
from datetime import datetime, timedelta
defget_history(symbol, timeframe, lookback_days=30):
"""拉历史数据"""
# 设置时间范围
to_date = datetime.now()
from_date = to_date - timedelta(days=lookback_days)
rates = mt5.copy_rates_range(
symbol,
timeframe,
int(from_date.timestamp()),
int(to_date.timestamp())
)
if rates isNone:
returnNone
df = pd.DataFrame(rates)
df['time'] = pd.to_datetime(df['time'], unit='s')
df.set_index('time', inplace=True)
return df
if mt5.initialize():
df = get_history("EURUSD", mt5.TIMEFRAME_H1, 30)
if df isnotNone:
print(df.head())
mt5.shutdown()
copy_rates_range是按时间段取，copy_rates_from_pos是按数量取，看需求用。
七、常用技术指标的实现示例
defadd_indicators(df):
"""算几个常用指标"""
# 均线
df['MA20'] = df['close'].rolling(20).mean()
df['MA50'] = df['close'].rolling(50).mean()
# RSI
delta = df['close'].diff()
gain = delta.where(delta > 0, 0).rolling(14).mean()
loss = (-delta.where(delta < 0, 0)).rolling(14).mean()
rs = gain / loss
df['RSI'] = 100 - (100 / (1 + rs))
# MACD
exp12 = df['close'].ewm(span=12).mean()
exp26 = df['close'].ewm(span=26).mean()
df['MACD'] = exp12 - exp26
df['Signal'] = df['MACD'].ewm(span=9).mean()
return df
八、凑个简单机器人出来
import time
import logging
logging.basicConfig(level=logging.INFO)
classMyTradingBot:
def__init__(self, login, pwd, server):
self.login = login
self.pwd = pwd
self.server = server
self.running = False
defstart(self):
"""启动机器人"""
ifnot mt5.initialize():
logging.error("初始化失败")
returnFalse
ifnot mt5.login(self.login, self.pwd, self.server):
logging.error("登录失败")
returnFalse
self.running = True
logging.info("机器人已启动")
returnTrue
defstop(self):
"""停机"""
mt5.shutdown()
self.running = False
logging.info("机器人已关闭")
defget_signal(self, symbol):
"""策略信号 (双均线金叉死叉)"""
rates = mt5.copy_rates_from_pos(symbol, mt5.TIMEFRAME_H1, 0, 100)
if rates isNone:
returnNone
df = pd.DataFrame(rates)
df['ma20'] = df['close'].rolling(20).mean()
df['ma50'] = df['close'].rolling(50).mean()
iflen(df) < 50:
returnNone
# 金叉
if df['ma20'].iloc[-2] <= df['ma50'].iloc[-2] and df['ma20'].iloc[-1] > df['ma50'].iloc[-1]:
return'BUY'
# 死叉
elif df['ma20'].iloc[-2] >= df['ma50'].iloc[-2] and df['ma20'].iloc[-1] < df['ma50'].iloc[-1]:
return'SELL'
return'HOLD'
defrun(self, symbols, check_interval=60):
"""主循环"""
ifnotself.start():
return
try:
whileself.running:
for sym in symbols:
mt5.symbol_select(sym, True)
signal = self.get_signal(sym)
if signal in ['BUY', 'SELL']:
# 先看看有没有持仓，别重复开
positions = mt5.positions_get(symbol=sym)
if positions:
logging.info(f"{sym} 已有持仓，不动")
continue
# 开仓逻辑可以自己补
logging.info(f"{sym} 信号: {signal}")
time.sleep(1) # 品种之间喘口气
logging.info(f"等{check_interval}秒再查...")
time.sleep(check_interval)
except KeyboardInterrupt:
logging.info("手动停止")
finally:
self.stop()
# 跑起来试试
if __name__ == "__main__":
bot = MyTradingBot(123456, "your_password", "YourBrokerServer")
bot.run(["EURUSD", "GBPUSD"], check_interval=300)
九、仓位管理
classRiskManager:
def__init__(self, risk_per_trade=0.02):
"""risk_per_trade: 每笔最多亏总资金的2%"""
self.risk_per_trade = risk_per_trade
defcalc_size(self, symbol, stop_loss_pips, balance):
"""根据止损距离算能开几手"""
info = mt5.symbol_info(symbol)
ifnot info:
return0
# 每点值多少钱
tick_value = info.trade_tick_value
# 每点多少单位
tick_size = info.trade_tick_size
if tick_value == 0:
return0
# 这单最多能亏多少钱
max_loss = balance * self.risk_per_trade
# 止损占总资金的点数损失
stop_loss_in_points = stop_loss_pips * 10# 粗略换算
# 算手数
size = max_loss / (stop_loss_in_points * tick_value)
# 卡在最小和最大之间
size = max(info.volume_min, min(info.volume_max, size))
returnround(size, 2)
关于symbol_info返回的字段，官方文档里有完整说明，包括trade_tick_value（每点价值）、trade_tick_size（每点大小）、volume_min/volume_max（最小最大交易量）等。这些数据是做资金管理的基础。
十、避坑的几个点
1. 异常处理别偷懒
defsafe_call(func, *args, **kwargs):
"""包一层保险"""
try:
result = func(*args, **kwargs)
if result isNone:
print(f"{func.__name__} 返回了None")
returnNone
return result
except Exception as e:
print(f"{func.__name__} 炸了: {e}")
returnNone
2. 用上下文管理器自动关连接
classMT5Context:
def__enter__(self):
ifnot mt5.initialize():
raise Exception("连不上")
returnself
def__exit__(self, *args):
mt5.shutdown()
# 这么用
with MT5Context():
info = mt5.account_info()
print(info.balance)
# 自动关，不用操心
3. 避坑指南
- • 信号订阅限制：如果账户绑定了信号跟单，MT5会禁掉Python的交易功能。查一下账户设置。
- • 系统要求：官方
MetaTrader5包只支持Windows，macOS/Linux得自己折腾远程调用。 - • 算法交易开关：MT5里得手动打开"允许算法交易"，不然单子发不出去。
- • 批量取数据：品种多的时候，一次取完比循环取快很多。
10个月宝宝每天需要喝多少奶粉？
