xnoxs-fetcher 4.0.0

Advanced TradingView historical and live data fetcher for stocks, crypto, forex, and commodities

XnoxsFetcher

Advanced TradingView Data Fetcher for Python - Fetch historical and live market data for stocks, crypto, forex, and commodities.

Apa itu XnoxsFetcher?

XnoxsFetcher adalah library Python yang memungkinkan Anda mengambil data pasar keuangan (saham, crypto, forex, komoditas) dari TradingView secara otomatis. Dengan library ini, Anda bisa mendapatkan data harga historis dan data real-time untuk analisis trading atau pembuatan bot trading.

Author: developerxnoxs
Versi: 4.0.0
Lisensi: MIT

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Fitur Utama

Fitur	Deskripsi
Multi-Asset Support	Saham, Crypto, Forex, Komoditas dari berbagai exchange
Auth Manager	Login dengan session persistence, auto token refresh
Data Export	Export ke CSV, Excel, JSON, Parquet
Parallel Fetch	Ambil banyak simbol sekaligus, 5 simbol dalam ~1 detik
WebSocket Manager	Auto-reconnect, heartbeat monitoring
Cross-Platform	Windows, macOS, Linux

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Daftar Isi

1. Instalasi
2. Quick Start
3. Fitur v4.0
   • Auth Manager
   • Data Export
   • Parallel Fetch
4. Mengambil Data
   • Data Saham
   • Data Cryptocurrency
   • Data Forex
5. Timeframe
6. Live Data Streaming
7. Daftar Exchange
8. Development
9. Contributing
10. License

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Instalasi

Requirements

• Python 3.9+
• pip atau uv package manager

Install via pip

pip install git+https://github.com/developerxnoxs/xnoxs_fetcher.git

Install via clone

git clone https://github.com/developerxnoxs/xnoxs_fetcher.git
cd xnoxs_fetcher
pip install -e .

Install dengan export dependencies

pip install -e ".[export]"  # Untuk CSV, Excel, Parquet export

Verifikasi Instalasi

from xnoxs_fetcher import XnoxsFetcher, TimeFrame
print("Instalasi berhasil!")

---

Quick Start

from xnoxs_fetcher import XnoxsFetcher, TimeFrame

# Buat instance fetcher
fetcher = XnoxsFetcher()

# Ambil data harian Apple
data = fetcher.get_hist(
    symbol="AAPL",
    exchange="NASDAQ",
    interval=TimeFrame.D1,
    n_bars=100
)

print(data)

Output:

                          symbol     open    high       low   close      volume
datetime                                                                       
2025-11-17 14:30:00  NASDAQ:AAPL  268.815  270.49  265.7300  267.46  45018260.0
2025-11-18 14:30:00  NASDAQ:AAPL  269.990  270.71  265.3200  267.44  45677278.0
...

---

Fitur v4.0

1. Auth Manager

Manajemen session yang robust dengan fitur:

• Session persistence (simpan ke file)
• Auto token refresh
• Rate limit protection

from xnoxs_fetcher import AuthManager

auth = AuthManager()
token = auth.authenticate("[e-mail]", "password")

if token:
    info = auth.get_session_info()
    print(f"Username: {info['username']}")
    print(f"Expired: {info['is_expired']}")

2. Data Export

Export data ke berbagai format:

from xnoxs_fetcher import XnoxsFetcher, DataExporter, TimeFrame

fetcher = XnoxsFetcher()
data = fetcher.get_hist("AAPL", "NASDAQ", TimeFrame.D1, 100)

exporter = DataExporter(output_dir="exports")
exporter.to_csv(data, "AAPL_daily")
exporter.to_excel(data, "AAPL_daily")
exporter.to_json(data, "AAPL_daily")
exporter.create_report(data, "AAPL_report")

3. Parallel Fetch

Ambil data banyak simbol secara bersamaan:

from xnoxs_fetcher import XnoxsFetcher, fetch_parallel, TimeFrame

fetcher = XnoxsFetcher()

symbols = [
    ("AAPL", "NASDAQ"),
    ("GOOGL", "NASDAQ"),
    ("MSFT", "NASDAQ"),
    ("AMZN", "NASDAQ"),
    ("META", "NASDAQ"),
]

results = fetch_parallel(
    fetcher=fetcher,
    symbols=symbols,
    timeframe=TimeFrame.D1,
    bars=100,
    max_workers=5
)

for key, data in results.items():
    symbol, exchange = key
    if data is not None:
        print(f"{symbol}: {len(data)} rows")

---

Mengambil Data

Data Saham

# Saham Amerika
apple = fetcher.get_hist("AAPL", "NASDAQ", TimeFrame.D1, 100)
tesla = fetcher.get_hist("TSLA", "NASDAQ", TimeFrame.H1, 50)

# Saham Indonesia
bbca = fetcher.get_hist("BBCA", "IDX", TimeFrame.D1, 100)
tlkm = fetcher.get_hist("TLKM", "IDX", TimeFrame.D1, 100)

# Saham India
reliance = fetcher.get_hist("RELIANCE", "NSE", TimeFrame.D1, 100)

Data Cryptocurrency

# Bitcoin
btc = fetcher.get_hist("BTCUSD", "BINANCE", TimeFrame.H1, 500)

# Ethereum
eth = fetcher.get_hist("ETHUSDT", "BINANCE", TimeFrame.M15, 1000)

# Altcoins
sol = fetcher.get_hist("SOLUSDT", "BINANCE", TimeFrame.H4, 200)

Data Forex

eurusd = fetcher.get_hist("EURUSD", "FX", TimeFrame.H1, 500)
gbpusd = fetcher.get_hist("GBPUSD", "FX", TimeFrame.D1, 200)

---

Timeframe

Kategori	TimeFrame	Penjelasan
Menit	TimeFrame.M1	1 menit
	TimeFrame.M5	5 menit
	TimeFrame.M15	15 menit
	TimeFrame.M30	30 menit
Jam	TimeFrame.H1	1 jam
	TimeFrame.H4	4 jam
Harian+	TimeFrame.D1	1 hari
	TimeFrame.W1	1 minggu
	TimeFrame.MN	1 bulan

---

Live Data Streaming

from xnoxs_fetcher import XnoxsLiveFeed, TimeFrame

live = XnoxsLiveFeed()

seis = live.create_symbol_set(
    symbol="BTCUSD",
    exchange="BINANCE",
    interval=TimeFrame.M1
)

def on_new_price(symbol_set, data):
    print(f"BTC: ${data['close'].iloc[0]:,.2f}")

consumer = seis.create_consumer(on_new_price)

# Streaming berjalan di background
# Panggil live.shutdown() untuk menghentikan

---

Daftar Exchange

Saham

Exchange	Kode	Contoh
NASDAQ	NASDAQ	AAPL, TSLA, MSFT
NYSE	NYSE	JPM, BAC, WMT
Indonesia	IDX	BBCA, TLKM, BBRI
India NSE	NSE	RELIANCE, TCS
Hong Kong	HKEX	0700, 9988

Cryptocurrency

Exchange	Kode	Contoh
Binance	BINANCE	BTCUSD, ETHUSDT
Coinbase	COINBASE	BTCUSD, ETHUSD
Bybit	BYBIT	BTCUSDT

Forex & Komoditas

Exchange	Kode	Contoh
FX	FX	EURUSD, GBPUSD
MCX	MCX	GOLD, SILVER
COMEX	COMEX	GC1!, SI1!

---

Development

Setup Development Environment

# Clone repository
git clone https://github.com/developerxnoxs/xnoxs_fetcher.git
cd xnoxs_fetcher

# Install dengan dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Run linter
ruff check .

# Run formatter
ruff format .

# Type checking
mypy xnoxs_fetcher/

Project Structure

xnoxs_fetcher/
├── xnoxs_fetcher/          # Main package
│   ├── __init__.py
│   ├── core.py             # Core fetcher
│   ├── auth.py             # Authentication
│   ├── export.py           # Data export
│   ├── parallel.py         # Parallel fetching
│   ├── live_feed.py        # Live streaming
│   ├── websocket_manager.py
│   ├── models.py
│   └── py.typed            # PEP 561 marker
├── tests/                  # Unit tests
├── .github/                # GitHub configs
│   ├── workflows/ci.yml
│   └── ISSUE_TEMPLATE/
├── pyproject.toml          # Modern Python config
├── README.md
├── CHANGELOG.md
├── CONTRIBUTING.md
├── CODE_OF_CONDUCT.md
├── SECURITY.md
└── LICENSE

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Contributing

Contributions are welcome! Please read CONTRIBUTING.md for guidelines.

1. Fork the repository
2. Create a feature branch (git checkout -b feat/amazing-feature)
3. Commit changes (git commit -m 'feat: add amazing feature')
4. Push to branch (git push origin feat/amazing-feature)
5. Open a Pull Request

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Security: See SECURITY.md

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Made with ❤️ by developerxnoxs