Quant Data SDK
Official Python SDK for Quant Data API.
A 股行情、财务、行业、因子数据的官方 Python SDK。
✨ Features
- 🚀 一行代码获取 A 股数据
- 🤖 AI 代码生成(自然语言 → 策略代码)
- 🔐 自动处理 API Key 认证
- 🔁 内置重试、超时、错误处理
- 📝 完整的类型提示(type hints)
- 📦 支持上下文管理器(
with语法) - 🆓 支持匿名调用(无需注册)
📦 Installation
pip install zizhenghua-quant
🚀 Quick Start
1. 获取 API Key(可选)
匿名也能用,但限额较低。注册后可获得更高限额。
- 访问 https://zizhenghua.com 注册账号
- 登录后进入「账号设置」→「API Key 管理」
- 点击「+ 创建新 Key」,复制保存(只显示一次)
2. 调用
from quant_data_sdk import QuantDataClient
# 匿名(30 次/天 AI,10 次/分钟数据)
client = QuantDataClient()
# 或注册(100 次/天 AI,1000 次/天数据)
client = QuantDataClient(api_key="your_api_key_here")
# 获取贵州茅台实时行情
data = client.stock.get_realtime("600519")
print(data)
📖 使用示例
数据接口
from quant_data_sdk import QuantDataClient
client = QuantDataClient(api_key="your_key")
# 实时行情
data = client.stock.get_realtime("600519")
# K 线
kline = client.stock.get_kline("600519", "2024-01-01", "2024-12-31")
# 多条件选股
stocks = client.stock.filter_stocks(minTurnover=5, minRoe=15)
# 市场统计
stats = client.market.get_stats()
# 行业数据
sectors = client.sector.get_performance()
# 财务指标
fin = client.fin.get_latest("600519")
# 多因子排名
ranking = client.factor.get_ranking(topN=20)
AI 代码生成
# 通用方法
result = client.ai.generate_code(
prompt="我想查看茅台23年到25年的布林带回测情况",
language="python"
)
code = client.ai.extract_code(result["raw"])
# 快捷方法
client.ai.generate_bollinger("600519", "2023-01-01", "2025-12-31")
client.ai.generate_ma_cross("600519", "2023-01-01", "2025-12-31", fast=5, slow=20)
client.ai.generate_rsi("600519", "2023-01-01", "2025-12-31", oversold=30, overbought=70)
client.ai.generate_macd("600519", "2023-01-01", "2025-12-31")
client.ai.generate_kdj("600519", "2023-01-01", "2025-12-31")
上下文管理器
with QuantDataClient(api_key="your_key") as client:
data = client.stock.get_realtime("600519")
print(data)
# 自动关闭
自定义 base URL
# 本地开发
client = QuantDataClient(
api_key="your_key",
base_url="http://127.0.0.1:8080/api"
)
📊 限流
| 用户 | 数据接口 | AI 接口 |
|---|---|---|
| 匿名 | 10 次/分钟,10,000 行/分钟 | 30 次/天 |
| 注册 | 300 次/分钟,600,000 行/分钟,1000 次/天 | 100 次/天 |
超限时抛 RateLimitError,并提示注册。
❌ 错误处理
from quant_data_sdk import QuantDataClient
from quant_data_sdk.exceptions import (
AuthenticationError,
RateLimitError,
NotFoundError,
ValidationError,
)
client = QuantDataClient(api_key="your_key")
try:
data = client.stock.get_realtime("600519")
except AuthenticationError as e:
print(f"认证失败: {e}")
except RateLimitError as e:
print(f"限流: {e}")
except NotFoundError as e:
print(f"资源不存在: {e}")
except ValidationError as e:
print(f"参数错误: {e}")
📚 Documentation
🤝 Contributing
See CONTRIBUTING.md.
📄 License
⚠️ Disclaimer
数据仅供量化学习与策略回测研究之用,不构成任何投资建议。
AI 生成的代码不保证正确性,请自行检查后再使用。
Release files for zizhenghua-quant 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| zizhenghua_quant-1.0.0.tar.gz | 14.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| zizhenghua_quant-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 28.3 kB
Release files / zizhenghua_quant-1.0.0.tar.gz
| Download URL | zizhenghua_quant-1.0.0.tar.gz |
|---|---|
| Size | 14.3 kB |
| Tags | Source |
|
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No |
| Uploaded via |
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|
Release files / zizhenghua_quant-1.0.0-py3-none-any.whl
| Download URL | zizhenghua_quant-1.0.0-py3-none-any.whl |
|---|---|
| Size | 14.0 kB |
| Tags | Python 3 |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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|