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CandleSniff gives data experts, traders, and retail investors the tools to analyze crypto markets, backtest strategies, and publish signals — all in one ecosystem.

Capabilities

Everything you need to trade with confidence

From deep analytics to social trading, we have the tools you need.

Deep Market Analytics

Analyze crypto markets with institutional-grade data, charts, and indicators.

Strategy Backtesting

Test your strategies against historical data before risking real capital.

Social Trading Ecosystem

Publish and follow strategies, signals, and portfolios from top traders.

Multi-Exchange Support

Connect to leading crypto exchanges through our unified CCXT integration.

Jupyter Notebooks

Run advanced data analysis with integrated Jupyter notebooks.

Smart Alerts

Get real-time alerts for your strategies, signals, and market movements.

Workspace

Jupyter Notebooks

Run advanced data analysis with integrated Jupyter notebooks.

  • Real Pythonpandas, polars, scikit-learn — not a proprietary DSL
  • Cloud CPU & GPUScale past the browser, metered by the second
  • One resolverEvery dataset a line of code away
research.ipynbCloud GPU · L4
In [1]
import candlesniff as cs

df = cs.load("@user:kian/datasets/market_data/BTC_1h")
df.tail(3)
Out
timeopenclosevolume
08-16 14:0067,412.567,891.01,284.1
08-16 15:0067,891.067,545.2982.7
08-16 16:0067,545.268,102.81,511.9
In [2]
# 20-period mean cross, long-only
signal = df.close > df.close.rolling(20).mean()
cs.backtest(signal, fees=0.001).summary()
Out
sharpe
1.87
max_dd
−12.4%
trades
231
runtime
3.2s

2 minutes

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CandleSniff provides research and analytics tools. Nothing on this site is investment advice or a recommendation to trade. Trading carries risk, including the loss of your capital.