File size: 10,046 Bytes
1a7c9d5
c75dcb6
dc03c48
 
1a7c9d5
 
 
 
 
 
c75dcb6
dc03c48
c75dcb6
1a7c9d5
c75dcb6
 
 
1a7c9d5
 
c75dcb6
 
 
8b2da55
c75dcb6
 
 
 
 
8b2da55
c75dcb6
 
 
 
 
8b2da55
c75dcb6
 
8b2da55
c75dcb6
 
 
8b2da55
c75dcb6
 
8b2da55
c75dcb6
 
 
 
 
 
 
8b2da55
c75dcb6
 
dc03c48
8b2da55
c75dcb6
 
 
 
 
 
dc03c48
c75dcb6
8b2da55
c75dcb6
 
 
 
 
dc03c48
1228823
1a7c9d5
 
c75dcb6
1a7c9d5
dc03c48
c75dcb6
 
 
dc03c48
 
 
c75dcb6
 
67f035b
dc03c48
67f035b
 
 
 
 
 
 
 
 
dc03c48
67f035b
dc03c48
67f035b
 
 
c75dcb6
dc03c48
c75dcb6
 
 
 
 
 
 
 
 
 
 
 
d8e6d12
dc03c48
d8e6d12
 
 
 
 
dc03c48
d8e6d12
c75dcb6
d8e6d12
c75dcb6
 
 
8b2da55
c75dcb6
dc03c48
c75dcb6
 
 
 
dc03c48
c75dcb6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
dc03c48
1a7c9d5
 
 
c75dcb6
dc03c48
c75dcb6
 
 
 
 
 
1a7c9d5
c75dcb6
 
 
 
 
 
 
 
1a7c9d5
c75dcb6
 
 
 
1a7c9d5
c75dcb6
 
 
dc03c48
c75dcb6
 
dc03c48
 
c75dcb6
 
 
1a7c9d5
c75dcb6
dc03c48
c75dcb6
1a7c9d5
c75dcb6
 
 
 
dc03c48
67f035b
c75dcb6
 
67f035b
dc03c48
 
 
 
 
 
c75dcb6
 
1a7c9d5
c75dcb6
dc03c48
 
c75dcb6
dc03c48
c75dcb6
1a7c9d5
 
 
 
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
"""
DATA UPDATE SCRIPT FOR HORIZON BACKTESTER
Downloads market data from Yahoo Finance and saves to data/ folder.
Upload to HuggingFace is handled by git push in the workflow.
"""

import yfinance as yf
import pandas as pd
import os
import time
from datetime import datetime, timedelta
from huggingface_hub import hf_hub_download, login
import sys

# =============================================================================
# TICKER UNIVERSE
# =============================================================================

TICKERS = [
    # S&P 500 Components
    'A', 'AAL', 'AAPL', 'ABBV', 'ABNB', 'ABT', 'ACGL', 'ACN', 'ADBE', 'ADI', 'ADM', 'ADP', 'ADSK', 'AEE', 'AEP',
    'AES', 'AFL', 'AIG', 'AIZ', 'AJG', 'AKAM', 'ALB', 'ALGN', 'ALL', 'ALLE', 'AMAT', 'AMCR', 'AMD', 'AME', 'AMGN',
    'AMP', 'AMT', 'AMZN', 'ANET', 'AON', 'AOS', 'APA', 'APD', 'APH', 'APTV', 'ARE', 'ATO', 'AVB', 'AVGO',
    'AVY', 'AWK', 'AXON', 'AXP', 'AZO', 'BA', 'BAC', 'BALL', 'BAX', 'BBWI', 'BBY', 'BDX', 'BEN', 'BF-B', 'BG',
    'BIIB', 'BIO', 'BK', 'BKNG', 'BKR', 'BLDR', 'BLK', 'BMY', 'BR', 'BRK-B', 'BRO', 'BSX', 'BWA', 'BX', 'BXP',
    'C', 'CAG', 'CAH', 'CARR', 'CAT', 'CB', 'CBOE', 'CBRE', 'CCI', 'CCL', 'CDNS', 'CDW', 'CE', 'CEG', 'CF',
    'CFG', 'CHD', 'CHRW', 'CHTR', 'CI', 'CINF', 'CL', 'CLX', 'CMCSA', 'CME', 'CMG', 'CMI', 'CMS', 'CNC', 'CNP',
    'COF', 'COO', 'COP', 'COR', 'COST', 'CPAY', 'CPB', 'CPRT', 'CPT', 'CRL', 'CRM', 'CRWD', 'CSCO', 'CSGP', 'CSX',
    'CTAS', 'CTRA', 'CTSH', 'CTVA', 'CVS', 'CVX', 'CZR', 'D', 'DAL', 'DAY', 'DD', 'DE', 'DECK',
    'DG', 'DGX', 'DHI', 'DHR', 'DIS', 'DLR', 'DLTR', 'DOC', 'DOV', 'DOW', 'DPZ', 'DRI', 'DTE', 'DUK', 'DVA',
    'DVN', 'DXCM', 'EA', 'EBAY', 'ECL', 'ED', 'EFX', 'EG', 'EIX', 'EL', 'ELV', 'EMN', 'EMR', 'ENPH', 'EOG',
    'EPAM', 'EQIX', 'EQR', 'EQT', 'ERIE', 'ES', 'ESS', 'ETN', 'ETR', 'EVRG', 'EW', 'EXC', 'EXPD', 'EXPE', 'EXR',
    'F', 'FANG', 'FAST', 'FCX', 'FDS', 'FDX', 'FE', 'FFIV', 'FI', 'FICO', 'FIS', 'FITB', 'FMC', 'FOX', 'FOXA',
    'FRT', 'FSLR', 'FTNT', 'FTV', 'GD', 'GDDY', 'GE', 'GEHC', 'GEN', 'GEV', 'GILD', 'GIS', 'GL', 'GLW', 'GM',
    'GNRC', 'GOOG', 'GOOGL', 'GPC', 'GPN', 'GRMN', 'GS', 'GWW', 'HAL', 'HAS', 'HBAN', 'HCA', 'HD', 'HIG',
    'HII', 'HLT', 'HOLX', 'HON', 'HPE', 'HPQ', 'HRL', 'HSIC', 'HST', 'HSY', 'HUBB', 'HUM', 'HWM', 'IBM', 'ICE',
    'IDXX', 'IEX', 'IFF', 'INCY', 'INTC', 'INTU', 'INVH', 'IP', 'IPG', 'IQV', 'IR', 'IRM', 'ISRG', 'IT', 'ITW',
    'IVZ', 'J', 'JBHT', 'JBL', 'JCI', 'JKHY', 'JNJ', 'JPM', 'K', 'KDP', 'KEY', 'KEYS', 'KHC', 'KIM',
    'KKR', 'KLAC', 'KMB', 'KMI', 'KMX', 'KO', 'KR', 'KVUE', 'L', 'LDOS', 'LEN', 'LH', 'LHX', 'LIN', 'LKQ',
    'LLY', 'LMT', 'LNT', 'LOW', 'LRCX', 'LULU', 'LUV', 'LVS', 'LW', 'LYB', 'LYV', 'MA', 'MAA', 'MAR', 'MAS',
    'MCD', 'MCHP', 'MCK', 'MCO', 'MDLZ', 'MDT', 'MET', 'META', 'MGM', 'MHK', 'MKC', 'MKTX', 'MLM', 'MMC', 'MMM',
    'MNST', 'MO', 'MOH', 'MOS', 'MPC', 'MPWR', 'MRK', 'MRNA', 'MRVL', 'MS', 'MSCI', 'MSFT', 'MSI', 'MTB', 'MTCH',
    'MTD', 'MU', 'NCLH', 'NDAQ', 'NDSN', 'NEE', 'NEM', 'NFLX', 'NI', 'NKE', 'NOC', 'NOW', 'NRG', 'NSC', 'NTAP',
    'NTRS', 'NUE', 'NVDA', 'NVR', 'NWS', 'NWSA', 'NXPI', 'O', 'ODFL', 'OKE', 'OMC', 'ON', 'ORCL', 'ORLY', 'OTIS',
    'OXY', 'PANW', 'PAYC', 'PAYX', 'PCAR', 'PCG', 'PEG', 'PEP', 'PFE', 'PFG', 'PG', 'PGR', 'PH', 'PHM',
    'PKG', 'PLD', 'PLTR', 'PM', 'PNC', 'PNR', 'PNW', 'PODD', 'POOL', 'PPG', 'PPL', 'PRU', 'PSA', 'PSX', 'PTC',
    'PWR', 'PYPL', 'QCOM', 'QRVO', 'RCL', 'REG', 'REGN', 'RF', 'RJF', 'RL', 'RMD', 'ROK', 'ROL', 'ROP', 'ROST',
    'RSG', 'RTX', 'RVTY', 'SBAC', 'SBUX', 'SCHW', 'SHW', 'SJM', 'SLB', 'SMCI', 'SNA', 'SNPS', 'SO', 'SOLV', 'SPG',
    'SPGI', 'SRE', 'STE', 'STLD', 'STT', 'STX', 'STZ', 'SWK', 'SWKS', 'SYF', 'SYK', 'SYY', 'T', 'TAP', 'TDG',
    'TDY', 'TECH', 'TEL', 'TER', 'TFC', 'TFX', 'TGT', 'TJX', 'TMO', 'TMUS', 'TPR', 'TRGP', 'TRMB', 'TROW', 'TRV',
    'TSCO', 'TSLA', 'TSN', 'TT', 'TTWO', 'TXN', 'TXT', 'TYL', 'UAL', 'UBER', 'UDR', 'UHS', 'ULTA', 'UNH', 'UNP',
    'UPS', 'URI', 'USB', 'V', 'VICI', 'VLO', 'VLTO', 'VMC', 'VRSK', 'VRSN', 'VRTX', 'VST', 'VTR', 'VTRS', 'VZ',
    'WAB', 'WAT', 'WBD', 'WDC', 'WEC', 'WELL', 'WFC', 'WM', 'WMB', 'WMT', 'WRB', 'WST', 'WTW', 'WY',
    'WYNN', 'XEL', 'XOM', 'XYL', 'YUM', 'ZBH', 'ZBRA', 'ZTS',
    
    # Nasdaq 100 additions
    'AZN', 'APP', 'ARM', 'CCEP', 'DASH', 'DDOG', 'GFS', 'MELI', 'PDD', 'TEAM', 'WDAY',
    
    # ETFs and Benchmarks
    'SPY', 'QQQ', 'VTI', 'VOO', 'VXUS', 'DIA', 'IWM', 'TQQQ', 'SQQQ', 'BND', 'TLT', 'IEF', 'GLD', 'DBC', 'VNQ',
    'XLF', 'XLK', 'XLE', 'XLV', 'ARKK', 'ARKW', 'SOXL', 'SOXS', 'UPRO', 'SPXU', 'VEA', 'VWO', 'EFA', 'EEM',
    'AGG', 'LQD', 'HYG', 'SHY', 'IEMG', 'VIG', 'SCHD', 'VYM', 'DVY', 'JEPI',
    
    # Notable IPOs 2020-2024
    'RIVN', 'LCID', 'RBLX', 'COIN', 'HOOD', 'SNOW', 'U', 'CPNG', 'COUR', 'OSCR', 'SOFI', 'UPST', 'AFRM', 'PATH',
    'BROS', 'DUOL', 'ASAN', 'FVRR', 'DOCS', 'DNUT', 'YOU', 'AI', 'DLO', 'JAMF', 'NCNO', 'JMIA', 
    'DKNG', 'NKLA', 'BLNK', 'QS', 'GOEV', 'LAZR', 'LMND', 'OPEN',
    'TPG', 'CRDO', 'MBLY', 'ACLX', 'BLTE', 'GCT', 'IE', 'CRBG',
    'BIRK', 'CART', 'KVYO', 'CAVA', 'ATMU', 'KGS', 'ODD', 'APGE', 'GPCR', 'ENLT', 'NXT',
    'RDDT', 'ALAB', 'VIK', 'LOAR', 'RBRK', 'AHR', 'IBTA', 'TEM', 'WAY', 'NNE',
    
    # Horizon specific
    'FUTU', 'SFTBY', 'RY', 'NET', 'SPOT'
]

TICKERS = sorted(list(set(TICKERS)))

# Configuration
REPO_ID = "JakeFake222/horizon-backtester"
REPO_TYPE = "space"
DATA_DIR = "data"
BATCH_SIZE = 50
BATCH_DELAY = 5
MAX_RETRIES = 2


def fetch_requested_tickers(token):
    """Fetch requests.txt from HuggingFace and return list of requested tickers."""
    try:
        login(token=token)
        filepath = hf_hub_download(
            repo_id=REPO_ID,
            filename="requests.txt",
            repo_type=REPO_TYPE
        )
        with open(filepath, 'r') as f:
            tickers = [line.strip().upper() for line in f if line.strip()]
        return list(set(tickers))
    except Exception as e:
        print(f"ℹ️  No requests.txt found: {e}")
        return []


def download_ticker_data(ticker, start_date, end_date, retry_count=0):
    """Download historical data for a single ticker from Yahoo Finance."""
    try:
        data = yf.download(
            ticker, 
            start=start_date, 
            end=end_date,
            auto_adjust=True,
            progress=False,
            threads=False
        )
        
        if data.empty:
            return None
        
        # Flatten MultiIndex columns if present
        if isinstance(data.columns, pd.MultiIndex):
            data.columns = data.columns.get_level_values(0)
        
        expected_cols = ['Open', 'High', 'Low', 'Close', 'Volume']
        if not all(col in data.columns for col in expected_cols):
            print(f"   ⚠️  {ticker}: Missing expected columns")
            return None
            
        return data[expected_cols]
        
    except Exception as e:
        if retry_count < MAX_RETRIES:
            time.sleep(2)
            return download_ticker_data(ticker, start_date, end_date, retry_count + 1)
        print(f"❌ Error downloading {ticker}: {e}")
        return None


def download_batch(tickers_batch, start_date, end_date, batch_num, total_batches):
    """Download a batch of tickers."""
    print(f"\nπŸ“¦ Batch {batch_num}/{total_batches} ({len(tickers_batch)} tickers)")
    
    results = {}
    for ticker in tickers_batch:
        data = download_ticker_data(ticker, start_date, end_date)
        if data is not None and not data.empty:
            results[ticker] = data
            print(f"   βœ… {ticker}: {len(data)} rows")
        else:
            print(f"   ⚠️  {ticker}: no data")
    
    return results


def update_all_tickers():
    """Download and save all ticker data."""
    end_date = datetime.now()
    start_date = end_date - timedelta(days=5*365)
    
    print(f"\n{'='*70}")
    print(f"πŸš€ HORIZON BACKTESTER - DATA DOWNLOAD")
    print(f"{'='*70}")
    print(f"πŸ“… Date range: {start_date.date()} to {end_date.date()}")
    print(f"πŸ“Š Total tickers: {len(TICKERS)}")
    print(f"{'='*70}")
    
    os.makedirs(DATA_DIR, exist_ok=True)
    
    batches = [TICKERS[i:i + BATCH_SIZE] for i in range(0, len(TICKERS), BATCH_SIZE)]
    total_batches = len(batches)
    
    success_count = 0
    error_count = 0
    
    for batch_num, batch in enumerate(batches, 1):
        results = download_batch(batch, start_date, end_date, batch_num, total_batches)
        
        for ticker, data in results.items():
            filepath = os.path.join(DATA_DIR, f"{ticker}.csv")
            data.to_csv(filepath)
            success_count += 1
        
        error_count += len(batch) - len(results)
        
        if batch_num < total_batches:
            print(f"   ⏳ Waiting {BATCH_DELAY}s...")
            time.sleep(BATCH_DELAY)
    
    # Write timestamp
    with open(os.path.join(DATA_DIR, "last_update.txt"), 'w') as f:
        f.write(f"Last updated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S UTC')}\n")
        f.write(f"Successful: {success_count}\n")
        f.write(f"Failed: {error_count}\n")
    
    print(f"\n{'='*70}")
    print(f"βœ… DOWNLOAD COMPLETE: {success_count} successful, {error_count} failed")
    print(f"{'='*70}\n")
    
    return success_count, error_count


def main():
    global TICKERS
    
    hf_token = os.environ.get("HF_TOKEN")
    
    # Check for requested tickers
    if hf_token:
        print(f"\nπŸ“₯ Checking for ticker requests...")
        requested = fetch_requested_tickers(hf_token)
        if requested:
            print(f"   Found {len(requested)} requested ticker(s)")
            TICKERS = sorted(list(set(TICKERS + requested)))
    
    success_count, error_count = update_all_tickers()
    
    if success_count > 0:
        print("πŸŽ‰ Data download complete! Workflow will commit and push to HuggingFace.")
        sys.exit(0)
    else:
        print("❌ No data downloaded")
        sys.exit(1)


if __name__ == "__main__":
    main()