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Python client SDK for qmtserver remote MiniQMT gateways.

Project description

qmtclient

PyPI Python License CI Ask Zread

远程 qmtserver 的轻量 Python 客户端 SDK。适用于没有 MiniQMT、没有 xtquant 的策略机、服务器或笔记本。

qmtclient  -- HTTP RPC / WebSocket / token -->  qmtserver + MiniQMT + xtquant

安装

使用 PyPI 安装:

uv pip install qmtclient

开发本仓库:

git clone https://github.com/gly11/qmtclient.git
cd qmtclient
uv sync

基础用法

from qmtclient import QmtClient

client = QmtClient("http://192.168.1.10:8000", token="dev-token")
print(client.health())
print(client.status())
print(client.xtdata.get_full_tick(["000001.SZ"]))

默认使用 qmtserver /v1。真实 token 不要写进源码,建议从环境变量读取。

策略接口

ticks = client.market.get_full_tick(["000001.SZ"])
daily = client.market.daily_bars(["000001.SZ"], start_time="20260501")
quality = client.market.daily_quality(["000001.SZ"], start_time="2026-01-01", end_time="2026-01-31")
asset = client.account.asset("example-account")
orders = client.account.cached_orders(limit=20)

daily_barsintraday_barsinstruments 优先使用 qmtserver 稳定 /v1/market/v1/reference endpoints。直接 RPC 仍可用于 escape hatch。

交易入口在 client.trading。它只组装参数并调用 qmtserver;是否允许真实交易由 qmtserver 的配置、保护和审计决定。

数据工具

job = client.batch.create_job(
    "market.daily_bars",
    {"codes": ["000001.SZ"], "start": "2026-01-01", "end": "2026-01-31"},
)
manifest = client.batch.download_snapshot(job["job_id"])

created = client.snapshots.create(
    {
        "kind": "daily_bars",
        "symbols": ["000001.SZ"],
        "start": "2026-01-01",
        "end": "2026-01-31",
        "format": "csv",
    }
)

事件

for event in client.events(types=["stock_order", "stock_trade"]):
    print(event)

离线测试

from qmtclient import FakeQmtClient

fake = FakeQmtClient.from_fixture("examples/fixtures/market_daily.json")
print(fake.market.daily_bars(["000001.SZ"]))

边界

  • 不直接连接 MiniQMT。
  • 不依赖 xtquant
  • 不绕过 qmtserver 的 token、RPC 白名单、透明 RPC 开关或交易保护。
  • 不做 GUI。

文档

开发检查

uv run python -m unittest discover -s tests
uv run ruff check .
uv run ruff format --check .
uv run ty check

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