File size: 14,285 Bytes
8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 ca2386d 8b7b267 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 |
#!/usr/bin/env python3
"""
HuggingFace Dataset Aggregator - Uses ALL Free HF Datasets
Maximizes usage of all available free HuggingFace datasets for historical OHLCV data
"""
import httpx
import logging
import io
import csv
from typing import Dict, Any, List, Optional
from datetime import datetime
from fastapi import HTTPException
logger = logging.getLogger(__name__)
class HFDatasetAggregator:
"""
Aggregates historical OHLCV data from ALL free HuggingFace datasets:
- linxy/CryptoCoin (26 symbols x 7 timeframes = 182 CSVs)
- WinkingFace/CryptoLM-Bitcoin-BTC-USDT
- WinkingFace/CryptoLM-Ethereum-ETH-USDT
- WinkingFace/CryptoLM-Solana-SOL-USDT
- WinkingFace/CryptoLM-Ripple-XRP-USDT
"""
def __init__(self):
self.timeout = 30.0
# linxy/CryptoCoin dataset configuration
self.linxy_base_url = "https://huggingface.co/datasets/linxy/CryptoCoin/resolve/main"
self.linxy_symbols = [
"BTC", "ETH", "BNB", "XRP", "ADA", "DOGE", "SOL", "TRX", "DOT", "MATIC",
"LTC", "SHIB", "AVAX", "UNI", "LINK", "ATOM", "XLM", "ETC", "XMR", "BCH",
"NEAR", "APT", "ARB", "OP", "FTM", "ALGO"
]
self.linxy_timeframes = ["1m", "5m", "15m", "30m", "1h", "4h", "1d"]
# WinkingFace datasets configuration
self.winkingface_datasets = {
"BTC": "https://huggingface.co/datasets/WinkingFace/CryptoLM-Bitcoin-BTC-USDT/resolve/main",
"ETH": "https://huggingface.co/datasets/WinkingFace/CryptoLM-Ethereum-ETH-USDT/resolve/main",
"SOL": "https://huggingface.co/datasets/WinkingFace/CryptoLM-Solana-SOL-USDT/resolve/main",
"XRP": "https://huggingface.co/datasets/WinkingFace/CryptoLM-Ripple-XRP-USDT/resolve/main"
}
# Cache for dataset data
self._cache = {}
self._cache_duration = 3600 # 1 hour
async def get_ohlcv(
self,
symbol: str,
timeframe: str = "1h",
limit: int = 1000
) -> List[Dict[str, Any]]:
"""
Get OHLCV data from HuggingFace datasets with fallback
"""
symbol = symbol.upper().replace("USDT", "").replace("USD", "")
# Try linxy/CryptoCoin first
if symbol in self.linxy_symbols and timeframe in self.linxy_timeframes:
try:
data = await self._get_linxy_ohlcv(symbol, timeframe, limit)
if data:
logger.info(f"✅ linxy/CryptoCoin: Fetched {len(data)} candles for {symbol}/{timeframe}")
return data
except Exception as e:
logger.warning(f"⚠️ linxy/CryptoCoin failed for {symbol}/{timeframe}: {e}")
# Try WinkingFace datasets
if symbol in self.winkingface_datasets:
try:
data = await self._get_winkingface_ohlcv(symbol, timeframe, limit)
if data:
logger.info(f"✅ WinkingFace: Fetched {len(data)} candles for {symbol}")
return data
except Exception as e:
logger.warning(f"⚠️ WinkingFace failed for {symbol}: {e}")
raise HTTPException(
status_code=404,
detail=f"No HuggingFace dataset found for {symbol}/{timeframe}"
)
async def _get_linxy_ohlcv(
self,
symbol: str,
timeframe: str,
limit: int
) -> List[Dict[str, Any]]:
"""Get OHLCV data from linxy/CryptoCoin dataset"""
cache_key = f"linxy_{symbol}_{timeframe}"
# Check cache
if cache_key in self._cache:
cached_data, cached_time = self._cache[cache_key]
if (datetime.utcnow().timestamp() - cached_time) < self._cache_duration:
logger.info(f"✅ Returning cached data for {symbol}/{timeframe}")
return cached_data[:limit]
# Download CSV from HuggingFace
# NOTE: linxy/CryptoCoin uses filenames like BTCUSDT_1h.csv (not BTC_1h.csv)
candidate_files = [
f"{symbol}USDT_{timeframe}.csv",
f"{symbol}_{timeframe}.csv", # legacy fallback
]
response = None
last_err = None
async with httpx.AsyncClient(timeout=self.timeout) as client:
for csv_filename in candidate_files:
csv_url = f"{self.linxy_base_url}/{csv_filename}"
try:
# These CSVs can be large (10MB+). Prefer a tail range request.
# We only need the most recent candles.
resp = await client.get(
csv_url,
follow_redirects=True,
headers={"Range": "bytes=-1500000"},
)
resp.raise_for_status()
response = resp
break
except Exception as e:
last_err = e
continue
if response is None:
raise HTTPException(status_code=404, detail=f"linxy/CryptoCoin CSV not found for {symbol}/{timeframe}: {last_err}")
# Parse CSV
# Note: with Range requests we likely won't have the header row.
csv_content = response.text
lines = csv_content.splitlines()
if not lines:
raise HTTPException(status_code=404, detail=f"Empty CSV content for {symbol}/{timeframe}")
# Drop first line if it's a partial row (common with Range tail)
if lines and ("timestamp" not in lines[0].lower()):
lines = lines[1:]
# If header present, use DictReader; otherwise use fixed fieldnames.
if lines and ("timestamp" in lines[0].lower() and "open" in lines[0].lower()):
csv_reader = csv.DictReader(io.StringIO("\n".join(lines)))
else:
csv_reader = csv.DictReader(
io.StringIO("\n".join(lines)),
fieldnames=["timestamp", "open", "high", "low", "close", "volume"],
)
ohlcv_data = []
for row in csv_reader:
try:
# linxy/CryptoCoin CSV formats vary.
# Common format is Binance-style export with:
# "Open time,open,high,low,close,volume,Close time,..."
ts_raw = (
row.get("timestamp")
or row.get("Open time")
or row.get("open_time")
or row.get("time")
or row.get("date")
)
if ts_raw is None:
continue
# Parse timestamp (supports int, float, or datetime strings)
ts_val: int
try:
ts_val = int(float(ts_raw))
except Exception:
# Example: "2017-08-17 04:00:00"
try:
dt = datetime.fromisoformat(str(ts_raw).strip())
except Exception:
dt = datetime.strptime(str(ts_raw).strip(), "%Y-%m-%d %H:%M:%S")
ts_val = int(dt.timestamp() * 1000)
ohlcv_data.append({
"timestamp": ts_val,
"open": float(row.get("open", 0) or 0),
"high": float(row.get("high", 0) or 0),
"low": float(row.get("low", 0) or 0),
"close": float(row.get("close", 0) or 0),
"volume": float(row.get("volume", 0) or 0)
})
except (ValueError, KeyError) as e:
logger.warning(f"⚠️ Failed to parse row: {e}")
continue
# Sort by timestamp (newest first)
ohlcv_data.sort(key=lambda x: x["timestamp"], reverse=True)
# Cache the result
self._cache[cache_key] = (ohlcv_data, datetime.utcnow().timestamp())
return ohlcv_data[:limit]
async def _get_winkingface_ohlcv(
self,
symbol: str,
timeframe: str,
limit: int
) -> List[Dict[str, Any]]:
"""Get OHLCV data from WinkingFace datasets"""
cache_key = f"winkingface_{symbol}_{timeframe}"
# Check cache
if cache_key in self._cache:
cached_data, cached_time = self._cache[cache_key]
if (datetime.utcnow().timestamp() - cached_time) < self._cache_duration:
logger.info(f"✅ Returning cached data for {symbol} (WinkingFace)")
return cached_data[:limit]
# WinkingFace datasets have different CSV filenames
base_url = self.winkingface_datasets[symbol]
# Try different possible filenames
possible_files = [
f"{symbol}USDT_{timeframe}.csv",
f"data.csv",
f"{symbol}USDT_1h.csv" # Fallback to 1h if specific timeframe not found
]
for csv_filename in possible_files:
try:
csv_url = f"{base_url}/{csv_filename}"
async with httpx.AsyncClient(timeout=self.timeout) as client:
response = await client.get(
csv_url,
follow_redirects=True,
headers={"Range": "bytes=-1500000"},
)
response.raise_for_status()
# Parse CSV
csv_content = response.text
lines = csv_content.splitlines()
if lines and ("timestamp" not in lines[0].lower()):
lines = lines[1:]
if lines and ("timestamp" in lines[0].lower() and "open" in lines[0].lower()):
csv_reader = csv.DictReader(io.StringIO("\n".join(lines)))
else:
csv_reader = csv.DictReader(
io.StringIO("\n".join(lines)),
fieldnames=["timestamp", "open", "high", "low", "close", "volume"],
)
ohlcv_data = []
for row in csv_reader:
try:
# WinkingFace CSV format may vary
# Try to detect and parse correctly
timestamp_key = None
for key in ["timestamp", "time", "date", "unix"]:
if key in row:
timestamp_key = key
break
if not timestamp_key:
# Try Binance-style export
if "Open time" in row:
timestamp_key = "Open time"
else:
continue
ts_raw = row.get(timestamp_key, 0)
try:
ts_val = int(float(ts_raw))
except Exception:
try:
dt = datetime.fromisoformat(str(ts_raw).strip())
except Exception:
dt = datetime.strptime(str(ts_raw).strip(), "%Y-%m-%d %H:%M:%S")
ts_val = int(dt.timestamp() * 1000)
ohlcv_data.append({
"timestamp": ts_val,
"open": float(row.get("open", 0) or 0),
"high": float(row.get("high", 0) or 0),
"low": float(row.get("low", 0) or 0),
"close": float(row.get("close", 0) or 0),
"volume": float(row.get("volume", 0) or 0)
})
except (ValueError, KeyError) as e:
logger.warning(f"⚠️ Failed to parse row: {e}")
continue
if ohlcv_data:
# Sort by timestamp (newest first)
ohlcv_data.sort(key=lambda x: x["timestamp"], reverse=True)
# Cache the result
self._cache[cache_key] = (ohlcv_data, datetime.utcnow().timestamp())
return ohlcv_data[:limit]
except Exception as e:
logger.warning(f"⚠️ Failed to fetch {csv_filename}: {e}")
continue
raise Exception(f"No data found for {symbol} in WinkingFace datasets")
async def get_available_symbols(self) -> Dict[str, List[str]]:
"""
Get list of available symbols from all datasets
"""
return {
"linxy_cryptocoin": self.linxy_symbols,
"winkingface": list(self.winkingface_datasets.keys())
}
async def get_available_timeframes(self, symbol: str) -> List[str]:
"""
Get available timeframes for a specific symbol
"""
symbol = symbol.upper().replace("USDT", "").replace("USD", "")
timeframes = []
# Check linxy/CryptoCoin
if symbol in self.linxy_symbols:
timeframes.extend(self.linxy_timeframes)
# WinkingFace datasets typically have 1h data
if symbol in self.winkingface_datasets:
timeframes.append("1h")
return list(set(timeframes)) # Remove duplicates
# Global instance
hf_dataset_aggregator = HFDatasetAggregator()
__all__ = ["HFDatasetAggregator", "hf_dataset_aggregator"]
|