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backtest360-client

PyPI version CI Python versions License: MIT

Official Python client for the Backtest360 backtesting API.

Backtest your trading strategy from every angle, in minutes.

import yfinance as yf
from backtest360 import Client, Strategy

df = yf.download("BTC-USD", period="1y", interval="1d",
                 auto_adjust=False, multi_level_index=False, progress=False)
df.columns = df.columns.str.lower()

result = Client(api_key="b360_...").backtest(Strategy.rsi_threshold_long(), df)
result.summary()
result.strategy_equity.plot(title="Equity curve")

Install

pip install backtest360-client

Requires Python 3.9+. The only runtime dependencies are httpx and pandas.

Need to install Python first? (Windows / macOS / Linux / WSL)

Windows (native)

  1. Install Python from python.org/downloads (check "Add to PATH"), or via winget:
    winget install Python.Python.3.12
    
  2. Open PowerShell and verify:
    python --version
    
  3. Install the SDK and yfinance for the quickstart:
    pip install backtest360-client yfinance
    
  4. Run a script:
    python quickstart.py
    
  1. Install WSL:
    wsl --install
    
    Restart, then open the Ubuntu terminal.
  2. Install Python:
    sudo apt update && sudo apt install python3 python3-pip -y
    
  3. Install the SDK:
    pip3 install backtest360-client yfinance
    
  4. Run a script:
    python3 quickstart.py
    

macOS

# via Homebrew (recommended)
brew install python

# or download from python.org/downloads

Then:

pip3 install backtest360-client yfinance
python3 quickstart.py

Linux

sudo apt install python3 python3-pip -y   # Debian/Ubuntu
pip3 install backtest360-client yfinance
python3 quickstart.py

Get an API key

Sign up at backtest360.com/api and copy your key. Store it in the BACKTEST360_API_KEY environment variable or pass it directly:

client = Client(api_key="b360_...")
# or: export BACKTEST360_API_KEY=b360_...
client = Client()

Features

  • Hand-written wrapper over the public REST API — no generated code, no schema sync
  • Built-in strategy templates (Strategy.rsi_threshold_long(), Strategy.ma_crossover(), …)
  • Grouped-knob classes: Execution, Costs, Risk, Sizing, MarketHours, Settings — set only what you need
  • Pre-computed signals path: client.backtest_signals(series, df) for model-generated signals
  • Pandas-native — pass a DataFrame, get a DataFrame back (result.strategy_equity, result.returns)
  • Raw-API escape hatch for full control (client.backtest_raw({...}))
  • Strict type hints + py.typed — first-class IDE and mypy support
  • MIT licensed

Common patterns

Custom strategy

from backtest360 import Client, Strategy, Execution, Costs, Risk, Sizing, Settings

strat = Strategy(
    name="rsi_mean_reversion",
    long_entry="rsi < 30",
    long_exit="rsi > 70",
    indicators=[Strategy.indicator("rsi", period=14)],
)

result = Client(api_key="b360_...").backtest(
    strat, df,
    benchmark=spy_df,
    execution=Execution(entry="open", exit="close", signal_frequency="daily"),
    costs=Costs(slippage_bps=2.5, fee_pct=0.001),
    risk=Risk(stop="atr", value=2.5, atr_period=14, max_drawdown=0.25),
    sizing=Sizing(weight=1.0, vol_target=0.15, leverage_limit=2.0),
    settings=Settings(risk_free_rate=0.04),
)

result.summary()
print(result.stats["Max Drawdown"])
for t in result.trades[:5]:
    print(t["entry_date"], t["direction"], t["return_net"])

Indicator library (names, params, output columns): https://api.backtest360.com/docs#tag/Reference/operation/list_indicators_api_indicators_get

Strategy templates (full list): https://api.backtest360.com/docs#tag/Reference/operation/list_strategies_api_strategies_get

Pre-computed signals

import pandas as pd
from backtest360 import Client

# Any signal series of {-1, 0, 1} — your ML model, custom indicator, etc.
signals = pd.Series(..., index=df.index)

result = Client(api_key="b360_...").backtest_signals(signals, df)
print(result.stats["Sharpe"])

Raw API escape hatch

For users who want exact control with the API docs open:

resp = Client(api_key="...").backtest_raw({
    "strategy":    {"condition_tree": {...}, "indicators": [...]},
    "data_source": {"ohlcv": {...}},
    "execution":   {"signal_frequency": "daily"},
})

Error handling

from backtest360 import Backtest360Error

try:
    result = client.backtest(strategy, df)
except Backtest360Error as e:
    if e.status == 401:
        print("Invalid or expired API key — renew at backtest360.com/api")
    elif e.status == 429:
        print("Rate limited — retry after a moment")
    elif e.status == 422:
        print("Strategy validation failed:", e.body)
    else:
        raise   # unexpected — let it propagate

Versioning

MAJOR.MINOR.PATCH. Pre-1.0 (0.x.y): the API may move between minor versions. Pre-release suffixes: aN (alpha), bN (beta), rcN (release candidate). See CHANGELOG.md for the release history.


Full documentation

Full documentation → https://backtest360.github.io/backtest360-client/

Engine API reference → https://api.backtest360.com/docs

Questions / feedback

Questions or feedback? hello@backtest360.com — we read everything. The SDK is in active development, so help shape it.

Bug reports and feature requests: open an issue on GitHub.

License

MIT — see LICENSE.

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