在开发加密货币交易算法或进行市场数据分析时，访问高质量的历史市场数据至关重要。然而，由于网络限制，国内开发者直接访问Tardis.dev等加密数据API服务商常常面临连接不稳定、延迟高等问题。本文将详细介绍如何通过HolySheep AI代理服务稳定接入Tardis.dev API，并成功获取Binance历史订单簿数据。
HolySheep vs 官方API vs 其他代理服务对比
| 对比维度 | HolySheep AI代理 | 官方Tardis.dev直连 | 其他代理服务 |
|---|---|---|---|
| 国内访问稳定性 | ✅ 极高（优化路由） | ❌ 经常断连 | ⚠️ 一般 |
| 延迟 | <50ms | 200-500ms+ | 80-200ms |
| 价格（以1M请求计） | ¥7 ≈ $1 | $5-15 | $3-8 |
| 付款方式 | 微信/支付宝/信用卡 | 仅信用卡 | 信用卡/部分支持微信 |
| 免费额度 | 注册送Credits | 有限免费试用 | 无或极少 |
| API兼容性 | 100%兼容官方 | 原生支持 | 部分兼容 |
| 技术支持 | 中文客服 | 英文工单 | 参差不齐 |
Geeignet / nicht geeignet für
✅ 非常适合使用HolySheep的场景
- 在国内进行加密货币量化交易的开发者
- 需要稳定获取Binance、OKX等交易所历史数据的分析师
- 预算有限但需要高质量数据的初创团队
- 不愿处理复杂网络配置的技术人员
- 需要中文技术支持的企业用户
❌ 不适合的场景
- 已有稳定国际网络环境的企业
- 对数据延迟要求极高（亚毫秒级）的HFT交易
- 需要访问官方不支持的交易所
- 非加密货币相关的通用API需求（应直接使用官方服务）
Tardis.dev API概述
Tardis.dev是一家专业的加密货币市场数据提供商，提供涵盖40+交易所的实时和历史市场数据。其主要产品包括：
- Historical Market Data：历史K线、订单簿、成交记录
- Real-time Stream：实时WebSocket数据流
- Aggregated Data：多交易所聚合数据
官方API文档地址：Tardis.dev API，但国内直接访问往往不稳定。通过HolySheep代理可以完美解决这一问题。
前提条件
- 已注册HolySheep AI账号并获取API Key
- Tardis.dev账号（用于获取Exchange ID）
- Python 3.8+ 或 Node.js 环境
- 已安装必要的HTTP客户端库
实战教程：通过HolySheep代理获取Binance历史Orderbook
步骤1：配置HolySheep代理端点
HolySheep AI的Tardis.dev代理端点采用标准化格式：
# HolySheep Tardis.dev 代理端点配置
BASE_URL = "https://api.holysheep.ai/v1/tardis"
请求头配置
HEADERS = {
"Authorization": "Bearer YOUR_HOLYSHEEP_API_KEY",
"Content-Type": "application/json"
}
示例：查看当前账户余额和用量
import requests
def check_balance():
"""查询HolySheep账户余额和API用量"""
url = "https://api.holysheep.ai/v1/balance"
response = requests.get(url, headers=HEADERS)
data = response.json()
print(f"剩余余额: ¥{data['balance']:.2f}")
print(f"本月用量: ¥{data['usage']:.2f}")
print(f"剩余Credits: {data['credits']}")
return data
调用示例
check_balance()步骤2：获取Binance历史订单簿数据
以下代码展示如何通过HolySheep代理获取Binance的BTC/USDT交易对的历史订单簿快照数据：
import requests
import json
from datetime import datetime, timedelta
HolySheep API配置
HOLYSHEEP_BASE_URL = "https://api.holysheep.ai/v1/tardis"
API_KEY = "YOUR_HOLYSHEHEP_API_KEY" # 替换为你的HolySheep API Key
def get_historical_orderbook(
exchange: str = "binance",
symbol: str = "BTC-USDT",
start_date: str = "2026-04-01",
end_date: str = "2026-04-01",
limit: int = 100
):
"""
通过HolySheep代理获取Binance历史订单簿数据
参数:
exchange: 交易所名称 (binance, okx, bybit等)
symbol: 交易对符号
start_date: 开始日期 (YYYY-MM-DD)
end_date: 结束日期 (YYYY-MM-DD)
limit: 每页返回数据条数
返回:
订单簿快照列表
"""
url = f"{HOLYSHEEP_BASE_URL}/historical/orderbook"
params = {
"exchange": exchange,
"symbol": symbol,
"from": f"{start_date}T00:00:00Z",
"to": f"{end_date}T23:59:59Z",
"limit": limit,
"format": "json"
}
headers = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
try:
print(f"📡 正在通过HolySheep代理请求 {exchange} {symbol} 订单簿数据...")
print(f"⏰ 时间范围: {start_date} 至 {end_date}")
response = requests.get(url, params=params, headers=headers, timeout=30)
response.raise_for_status()
data = response.json()
# 解析返回数据
orderbooks = data.get("data", [])
request_id = data.get("requestId", "N/A")
credits_used = data.get("creditsUsed", 0)
print(f"✅ 成功获取 {len(orderbooks)} 条订单簿快照")
print(f"🔖 请求ID: {request_id}")
print(f"💰 消耗Credits: {credits_used}")
return orderbooks
except requests.exceptions.Timeout:
print("❌ 请求超时，请检查网络连接或稍后重试")
return None
except requests.exceptions.RequestException as e:
print(f"❌ 请求失败: {str(e)}")
return None
使用示例：获取2026年4月1日的BTC/USDT订单簿数据
if __name__ == "__main__":
orderbooks = get_historical_orderbook(
exchange="binance",
symbol="BTC-USDT",
start_date="2026-04-01",
end_date="2026-04-01",
limit=50
)
if orderbooks:
print("\n📊 数据样本（前3条）:")
for i, ob in enumerate(orderbooks[:3]):
print(f"\n--- 快照 #{i+1} ---")
print(f"时间戳: {ob.get('timestamp')}")
print(f"买入价: {ob.get('bids', [])[:3]}")
print(f"卖出价: {ob.get('asks', [])[:3]}")步骤3：批量下载多交易所数据
import asyncio
import aiohttp
from concurrent.futures import ThreadPoolExecutor
import pandas as pd
from datetime import datetime, timedelta
HolySheep异步客户端配置
class HolySheepTardisClient:
"""HolySheep Tardis.dev 异步客户端"""
def __init__(self, api_key: str, base_url: str = "https://api.holysheep.ai/v1/tardis"):
self.api_key = api_key
self.base_url = base_url
self.headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
async def fetch_orderbook_async(
self,
session: aiohttp.ClientSession,
exchange: str,
symbol: str,
timestamp: str
) -> dict:
"""异步获取单条订单簿数据"""
url = f"{self.base_url}/historical/orderbook"
params = {
"exchange": exchange,
"symbol": symbol,
"timestamp": timestamp,
"format": "json"
}
async with session.get(url, params=params, headers=self.headers) as resp:
if resp.status == 200:
return await resp.json()
else:
error_text = await resp.text()
return {"error": f"HTTP {resp.status}: {error_text}"}
async def batch_fetch_orderbooks(
self,
requests: list
) -> list:
"""批量异步获取订单簿数据
requests格式: [{"exchange": "binance", "symbol": "BTC-USDT", "timestamp": "..."}]
"""
async with aiohttp.ClientSession() as session:
tasks = [
self.fetch_orderbook_async(
session,
req["exchange"],
req["symbol"],
req["timestamp"]
)
for req in requests
]
results = await asyncio.gather(*tasks)
return results
使用示例：批量获取多个交易对的数据
async def main():
client = HolySheepTardisClient(api_key="YOUR_HOLYSHEEP_API_KEY")
# 构造批量请求
base_time = "2026-04-01T12:00:00Z"
batch_requests = []
exchanges_symbols = [
("binance", "BTC-USDT"),
("binance", "ETH-USDT"),
("okx", "BTC-USDT"),
("bybit", "BTC-USDT"),
]
for exchange, symbol in exchanges_symbols:
for offset in range(5): # 获取5个时间点
batch_requests.append({
"exchange": exchange,
"symbol": symbol,
"timestamp": f"2026-04-01T{12+offset:02d}:00:00Z"
})
print(f"📦 开始批量请求 {len(batch_requests)} 条数据...")
results = await client.batch_fetch_orderbooks(batch_requests)
# 统计结果
success_count = sum(1 for r in results if "error" not in r)
print(f"✅ 成功: {success_count}/{len(results)}")
return results
运行异步任务
if __name__ == "__main__":
results = asyncio.run(main())步骤4：数据解析与存储
import json
import pandas as pd
from typing import List, Dict
class OrderbookProcessor:
"""订单簿数据处理器"""
@staticmethod
def parse_orderbook_snapshot(raw_data: dict) -> dict:
"""解析单条订单簿快照"""
return {
"exchange": raw_data.get("exchange"),
"symbol": raw_data.get("symbol"),
"timestamp": raw_data.get("timestamp"),
"local_timestamp": raw_data.get("localTimestamp"),
"best_bid": raw_data["bids"][0] if raw_data.get("bids") else None,
"best_ask": raw_data["asks"][0] if raw_data.get("asks") else None,
"spread": None, # 后续计算
"mid_price": None, # 后续计算
"bid_depth_10": sum(float(b[1]) for b in raw_data.get("bids", [])[:10]),
"ask_depth_10": sum(float(a[1]) for a in raw_data.get("asks", [])[:10]),
}
@staticmethod
def calculate_spread(parsed: dict) -> dict:
"""计算买卖价差"""
if parsed["best_bid"] and parsed["best_ask"]:
bid_price = float(parsed["best_bid"][0])
ask_price = float(parsed["best_ask"][0])
parsed["spread"] = ask_price - bid_price
parsed["spread_pct"] = (ask_price - bid_price) / bid_price * 100
parsed["mid_price"] = (bid_price + ask_price) / 2
return parsed
@staticmethod
def to_dataframe(orderbooks: List[dict]) -> pd.DataFrame:
"""转换为DataFrame便于分析"""
parsed = [OrderbookProcessor.calculate_spread(
OrderbookProcessor.parse_orderbook_snapshot(ob)
) for ob in orderbooks]
df = pd.DataFrame(parsed)
df["timestamp"] = pd.to_datetime(df["timestamp"])
df = df.sort_values("timestamp")
return df
使用示例
if __name__ == "__main__":
# 假设这是从API获取的原始数据
sample_raw_data = [
{
"exchange": "binance",
"symbol": "BTC-USDT",
"timestamp": "2026-04-01T12:00:00.000Z",
"bids": [["70000.0", "1.5"], ["69999.0", "2.0"]],
"asks": [["70001.0", "1.8"], ["70002.0", "2.5"]]
}
]
processor = OrderbookProcessor()
df = processor.to_dataframe(sample_raw_data)
print(df.to_string())Preise und ROI
HolySheep Tardis.dev代理定价
| 套餐类型 | 价格 | 包含Credits | 单请求成本 | 适用场景 |
|---|---|---|---|---|
| 免费试用 | ¥0 | 100 Credits | ~¥0.01/请求 | 功能测试、小规模验证 |
| 入门套餐 | ¥50/月 | 5,000 Credits | ~¥0.01/请求 | 个人开发者、轻量级量化 |
| 专业套餐 | ¥200/月 | 25,000 Credits | ~¥0.008/请求 | 中小型量化团队 |
| 企业套餐 | ¥800/月 | 150,000 Credits | ~¥0.005/请求 | 大型数据采集项目 |
ROI分析：HolySheep vs 直接使用Tardis.dev
# 成本对比计算
Tardis.dev官方价格（假设）
TARDIS_MONTHLY_COST_USD = 299 # Professional Plan
TARDIS_PER_REQUEST_USD = 0.01
HolySheep代理价格（2026年5月）
HOLYSHEEP_MONTHLY_CNY = 200
EXCHANGE_RATE = 7.2 # 1 USD ≈ 7.2 CNY
HOLYSHEEP_MONTHLY_COST_USD = HOLYSHEEP_MONTHLY_CNY / EXCHANGE_RATE
HOLYSHEEP_CREDITS_PER_MONTH = 25000
print("=" * 50)
print("月度成本对比分析")
print("=" * 50)
print(f"官方Tardis.dev月费: ${TARDIS_MONTHLY_COST_USD}")
print(f"HolySheep代理月费: ${HOLYSHEEP_MONTHLY_COST_USD:.2f}")
print(f"节省比例: {(TARDIS_MONTHLY_COST_USD - HOLYSHEEP_MONTHLY_COST_USD) / TARDIS_MONTHLY_COST_USD * 100:.1f}%")
print("\n" + "=" * 50)
print("年化成本对比")
print("=" * 50)
annual_official = TARDIS_MONTHLY_COST_USD * 12
annual_holysheep = HOLYSHEEP_MONTHLY_COST_USD * 12
print(f"官方年费: ${annual_official:,}")
print(f"HolySheep年费: ${annual_holysheep:,.2f}")
print(f"年度节省: ${annual_official - annual_holysheep:,.2f}")
额外优势计算
additional_savings = {
"无需国际网络专线": 2000, # 假设月费
"中文技术支持价值": 500, # 估算
"支付便利性(微信/支付宝)": 100,
}
total_additional = sum(additional_savings.values()) * 12
print(f"\n隐性节省(网络专线+技术支持+支付便利): ${total_additional:,}/年")Warum HolySheep wählen
1. 极致的价格优势
凭借¥1=$1的汇率政策，HolySheep AI为国内用户提供了无与伦比的价格竞争力。相比直接使用Tardis.dev官方服务，可节省85%以上的成本。以专业版为例：
- 官方月费：$299/月
- HolySheep月费：约¥200（≈$28）
- 年度节省：超过$3,200
2. 极低延迟，稳定连接
HolySheep部署了优化的跨境网络路由，端到端延迟控制在50ms以内，确保数据采集的实时性和稳定性。国内直连Tardis.dev的延迟通常在200-500ms甚至更高。
3. 本土化支付体验
支持微信支付、支付宝等国内主流支付方式，充值即时到账，无任何外汇结算烦恼。企业用户还可开具增值税发票。
4. 丰富的AI API生态
除Tardis.dev代理外，HolySheep还提供主流AI大模型API服务：
| 模型 | 价格 ($/1M Tokens) |
|---|---|
| GPT-4.1 | $8.00 |
| Claude Sonnet 4.5 | $15.00 |
| Gemini 2.5 Flash | $2.50 |
| DeepSeek V3.2 | $0.42 |
Häufige Fehler und Lösungen
Fehler 1：API Key无效或已过期
# ❌ 错误表现
{"error": "Invalid API key", "code": 401}
✅ 解决方案
import os
def validate_api_key(api_key: str) -> bool:
"""验证API Key格式和有效性"""
if not api_key:
print("❌ API Key不能为空")
return False
if len(api_key) < 32:
print(f"❌ API Key格式错误，长度不足: {len(api_key)}")
return False
# 检查Key前缀（HolySheep Key格式验证）
valid_prefixes = ["hs_", "sk_"]
if not any(api_key.startswith(p) for p in valid_prefixes):
print(f"❌ API Key格式不正确，应以 {valid_prefixes} 开头")
return False
# 实际验证：调用账户信息接口
response = requests.get(
"https://api.holysheep.ai/v1/account",
headers={"Authorization": f"Bearer {api_key}"}
)
if response.status_code == 401:
print("❌ API Key无效或已过期，请前往 https://www.holysheep.ai/register 重新获取")
return False
return True
使用
API_KEY = os.getenv("HOLYSHEEP_API_KEY", "YOUR_API_KEY")
if validate_api_key(API_KEY):
print("✅ API Key验证通过")Fehler 2：请求频率超限（Rate Limit）
# ❌ 错误表现
{"error": "Rate limit exceeded", "code": 429, "retryAfter": 60}
✅ 解决方案：实现智能重试机制
import time
from functools import wraps
from requests.exceptions import RequestException
class RateLimitHandler:
"""请求频率限制处理器"""
def __init__(self, max_retries: int = 3, base_delay: float = 1.0):
self.max_retries = max_retries
self.base_delay = base_delay
def with_retry(self, func):
"""带重试的请求装饰器"""
@wraps(func)
def wrapper(*args, **kwargs):
last_exception = None
for attempt in range(self.max_retries):
try:
response = func(*args, **kwargs)
# 检查是否触发频率限制
if response.status_code == 429:
retry_after = int(response.headers.get("retry-after", 60))
wait_time = retry_after or self.base_delay * (2 ** attempt)
print(f"⏳ 触发频率限制，等待 {wait_time} 秒 (尝试 {attempt + 1}/{self.max_retries})")
time.sleep(wait_time)
continue
return response
except RequestException as e:
last_exception = e
wait_time = self.base_delay * (2 ** attempt)
print(f"⚠️ 请求失败，等待 {wait_time} 秒后重试...")
time.sleep(wait_time)
raise last_exception or Exception("Max retries exceeded")
return wrapper
使用示例
handler = RateLimitHandler(max_retries=5, base_delay=2.0)
@handler.with_retry
def fetch_data_with_retry(url, headers, params):
"""带重试的数据获取函数"""
response = requests.get(url, headers=headers, params=params, timeout=30)
return response
建议：添加请求间隔控制
def controlled_request(url, headers, params, interval: float = 0.5):
"""带间隔控制的请求（建议间隔≥0.5秒）"""
time.sleep(interval)
return requests.get(url, headers=headers, params=params, timeout=30)Fehler 3：Symbol格式错误或交易所不支持
# ❌ 错误表现
{"error": "Invalid symbol format", "code": 400}
或
{"error": "Exchange not supported", "code": 400}
✅ 解决方案：标准化的交易对格式转换
from typing import Optional, Dict
class SymbolNormalizer:
"""交易对符号标准化工具"""
# Tardis.dev支持的交易所及其符号格式
EXCHANGE_FORMATS = {
"binance": {
"format": "XXX-XXX", # BTC-USDT
"aliases": ["BINANCE", "BN"],
},
"okx": {
"format": "XXX-XXX",
"aliases": ["OKX", "OKEX", "OK"],
},
"bybit": {
"format": "XXXXXX",
"aliases": ["BYBIT", "BYB"],
},
"huobi": {
"format": "XXXXXX",
"aliases": ["HUOBI", "HT"],
}
}
# 国内常见格式到标准格式的映射
COMMON_MAPPINGS = {
"BTCUSDT": "BTC-USDT",
"ETHUSDT": "ETH-USDT",
"BTC/USDT": "BTC-USDT",
"BTC_TUSDT": "BTC-USDT",
"1000SHIBUSDT": "1000SHIB-USDT",
}
@classmethod
def normalize(cls, symbol: str, exchange: str = "binance") -> str:
"""标准化交易对符号"""
if not symbol:
raise ValueError("Symbol不能为空")
# 统一转为大写
symbol = symbol.upper().strip()
# 检查常见映射
if symbol in cls.COMMON_MAPPINGS:
return cls.COMMON_MAPPINGS[symbol]
# 处理斜杠和下划线分隔
if "/" in symbol:
symbol = symbol.replace("/", "-")
if "_" in symbol:
symbol = symbol.replace("_", "-")
# 验证交易所支持
exchange_lower = exchange.lower()
if exchange_lower not in cls.EXCHANGE_FORMATS:
supported = list(cls.EXCHANGE_FORMATS.keys())
raise ValueError(f"不支持的交易所: {exchange}，支持的交易所: {supported}")
return symbol
@classmethod
def validate(cls, symbol: str, exchange: str = "binance") -> Dict[str, any]:
"""验证符号格式是否正确"""
result = {
"valid": True,
"normalized": symbol,
"errors": []
}
try:
result["normalized"] = cls.normalize(symbol, exchange)
except ValueError as e:
result["valid"] = False
result["errors"].append(str(e))
return result
使用示例
test_symbols = ["BTCUSDT", "ETH/USDT", "btc_usdt", "invalid"]
for sym in test_symbols:
validation = SymbolNormalizer.validate(sym, "binance")
if validation["valid"]:
print(f"✅ {sym} -> {validation['normalized']}")
else:
print(f"❌ {sym} -> {validation['errors']}")Fehler 4：数据返回为空或格式异常
# ❌ 错误表现
{"data": []} 或 数据结构不完整
✅ 解决方案：健壮的数据验证和处理
from typing import List, Dict, Any, Optional
class DataValidator:
"""API返回数据验证器"""
REQUIRED_ORDERBOOK_FIELDS = ["timestamp", "bids", "asks"]
@classmethod
def validate_orderbook(cls, data: dict) -> tuple[bool, Optional[str]]:
"""验证订单簿数据完整性"""
# 检查必填字段
missing_fields = [
field for field in cls.REQUIRED_ORDERBOOK_FIELDS
if field not in data
]
if missing_fields:
return False, f"缺少字段: {missing_fields}"
# 验证数据格式
if not isinstance(data.get("bids"), list):
return False, "bids字段应为列表"
if not isinstance(data.get("asks"), list):
return False, "asks字段应为列表"
# 验证价格和数量格式
try:
if data["bids"]:
price, quantity = data["bids"][0]
float(price)
float(quantity)
except (ValueError, TypeError) as e:
return False, f"数据格式错误: {e}"
return True, None
@classmethod
def safe_get_orderbooks(
cls,
api_response: dict,
min_records: int = 1
) -> tuple[bool, List[dict], str]:
"""
安全获取订单簿数据
返回: (成功标志, 数据列表, 错误信息)
"""
# 检查响应状态
if "error" in api_response:
return False, [], f"API错误: {api_response['error']}"
# 获取数据
data = api_response.get("data", [])
if not data:
return False, [], "数据为空，请检查请求参数和时间范围"
if len(data) < min_records:
return False, data, f"数据量不足: 获取{len(data)}条，需要至少{min_records}条"
# 逐条验证
valid_data = []
invalid_count = 0
for i, item in enumerate(data):
is_valid, error = cls.validate_orderbook(item)
if is_valid:
valid_data.append(item)
else:
invalid_count += 1
if invalid_count > 0:
print(f"⚠️ 跳过 {invalid_count} 条无效数据")
return len(valid_data) > 0, valid_data, ""
使用示例
def robust_fetch_and_validate(url, headers, params):
"""健壮的数据获取和处理流程"""
response = requests.get(url, headers=headers, params=params, timeout=30)
api_data = response.json()
success, orderbooks, message = DataValidator.safe_get_orderbooks(
api_data,
min_records=10
)
if not success:
print(f"❌ 数据验证失败: {message}")
return []
print(f"✅ 成功获取 {len(orderbooks)} 条有效订单簿数据")
return orderbooks实用代码模板库
# 完整的Tardis.dev数据采集器模板
import requests
import pandas as pd
from datetime import datetime, timedelta
import time
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class TardisDataCollector:
"""Tardis.dev历史数据采集器（通过HolySheep代理）"""
BASE_URL = "https://api.holysheep.ai/v1/tardis"
def __init__(self, api_key: str):
self.api_key = api_key
self.headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
def collect_orderbook(
self,
exchange: str,
symbol: str,
start_date: str,
end_date: str,
interval_minutes: int = 5
) -> pd.DataFrame:
"""采集指定时间范围的历史订单簿数据"""
all_data = []
current_date = datetime.strptime(start_date, "%Y-%m-%d")
end_datetime = datetime.strptime(end_date, "%Y-%m-%d")
while current_date <= end_datetime:
date_str = current_date.strftime("%Y-%m-%d")
logger.info(f"正在采集 {date_str} 的数据...")
url = f"{self.BASE_URL}/historical/orderbook"
params = {
"exchange": exchange,
"symbol": symbol,
"from": f"{date_str}T00:00:00Z",
"to": f"{date_str}T23:59:59Z",
"format": "json"
}
try:
response = requests.get(
url,
params=params,
headers=self.headers,
timeout=60
)
response.raise_for_status()
data = response.json()
records = data.get("data", [])
all_data.extend(records)
logger.info(f" {date_str}: 获取 {len(records)} 条记录")
except Exception as e:
logger.error(f" 采集失败: {e}")
# 请求间隔（避免触发频率限制）
time.sleep(0.5)
# 移动到下一天
current_date += timedelta(days=1)
# 转换为DataFrame
df = pd.DataFrame(all_data)
logger.info(f"✅ 共采集 {len(df)} 条记录")
return df
def save_to_csv(self, df: pd.DataFrame, filename: str):
"""保存数据到CSV"""
if not df.empty:
df.to_csv(filename, index=False)
logger.info(f"💾 数据已保存至 {filename}")
else:
logger.warning("⚠️ 无数据可保存")
使用示例
if __name__ == "__main__":
API_KEY = "YOUR_HOLYSHEHEP_API_KEY"
collector = TardisDataCollector(API_KEY)
# 采集BTC/USDT订单簿数据
df = collector.collect_orderbook(
exchange="binance",
symbol="BTC-USDT",
start_date="2026-04-01",
end_date="2026-04-07",
interval_minutes=5
)
# 保存