alphalens-core 0.3.15

AlphaLens — an event-driven backtesting & walk-forward engine for systematic strategies

alphalens-core

An event-driven backtesting & walk-forward engine for systematic trading strategies.

Write a strategy as a Python class, run a single forward pass over an in-memory OHLCV feed, and get back an equity curve, a trade log, and a rich set of performance statistics — plus walk-forward analysis, parameter sweeps, and an HTML dashboard. alphalens-core is the open engine behind AlphaLens.

Install

pip install alphalens-core              # core engine (pandas + numpy only)
pip install "alphalens-core[viz]"       # + matplotlib / quantstats dashboard & reports
pip install "alphalens-core[polygon]"   # + Polygon market-data fetching
pip install "alphalens-core[live]"      # + Alpaca execution and Polygon history
pip install "alphalens-core[fast]"      # + pyarrow parquet cache

Quickstart

from alphalens_core import Algorithm, Backtester

class GoldenCross(Algorithm):
    start = "2020-01-01"
    end = "2024-12-31"
    universe = ["SPY"]

    def initialize(self):
        self.set_warmup(50)

    def on_data(self, slice):
        hist = self.history("SPY", 50)["close"]
        if len(hist) < 50:
            return
        self.set_holdings("SPY", 1.0 if hist.tail(10).mean() > hist.mean() else 0.0)

result = Backtester().run(GoldenCross)
print(result.stats)     # Sharpe, Sortino, CAGR, max drawdown, win rate, …
result.dashboard        # inline HTML report in Jupyter, or opens in your browser

Live data needs a POLYGON_API_KEY (a .env / .env.local file is loaded automatically). To run fully offline, inject your own DataFeed.

Host on AlphaLens

AlphaLens can host the dashboard side of your alphalens-core workflow: backtest sync, Strategy Center dashboards, hosted market data access, and live deployment telemetry. Your strategy code and broker execution still run locally in v1.

Install the extras used by the hosted workflow:

pip install "alphalens-core[live,cloud,fast]"

Create an API key in AlphaLens Settings, then connect locally:

alphalens connect --api-key alens_...
alphalens status

Run and sync a backtest:

alphalens run --strategy my_strategy:MyStrategy

For CI or one-off shells, ALPHALENS_API_KEY=alens_... alphalens run ... is also supported. End users should not need internal Supabase commands.

Run a local Alpaca paper deployment and stream telemetry to Strategy Center:

alphalens live --strategy my_strategy:MyStrategy

Use the Python API when you want key injection from code:

from alphalens_core import AlphaLensClient
from my_strategy import MyStrategy

al = AlphaLensClient(api_key="alens_...")
result = al.backtest(MyStrategy)
al.live(MyStrategy, broker="alpaca", paper=True).run()

Read the hosted workflow docs at alphalens.dev/docs/alphalens-core, including the strategy authoring guide at alphalens.dev/docs/alphalens-core/build-a-strategy.

Live / Alpaca Paper Trading

The live runner uses the same Algorithm class and history API as the backtester. The simplest path is the built-in Alpaca + Polygon runner:

export POLYGON_API_KEY=...
export ALPACA_API_KEY=...
export ALPACA_SECRET_KEY=...

alphalens live --strategy my_strategy:MyStrategy

alphalens live defaults to Alpaca paper trading. Pass --live only when you intend to route orders to the live Alpaca account. The command reads class.universe and class.resolution by default; override them with --universe SPY,QQQ or --resolution 5minute.

For custom broker/data transports, LiveSession.from_cache seeds a bounded rolling history, then each completed Slice is appended before on_data runs:

from alphalens_core import AlpacaBrokerage, LiveSession, NO_BAR
from my_data import next_completed_slice
from my_strategy import MyStrategy

broker = AlpacaBrokerage(paper=True)
session = LiveSession.from_cache(
    MyStrategy,
    brokerage=broker,
    next_bar_fn=next_completed_slice,  # Slice, NO_BAR while idle, None to stop
    history_bars=500,
    state_path=".alphalens/live/my_strategy.json",
)
session.run()

from_cache uses UniverseCache and Polygon by default; inject an existing cache to use another DataSource. The runner:

• exposes seeded and appended bars through history(), history_array(), and history_arrays();
• keeps history bounded and suppresses duplicate timestamps;
• rejects out-of-order bars and unreconciled broker orders;
• synchronizes Alpaca cash/positions and FIFO lots at startup;
• respects strategy resolution and warmup settings;
• checkpoints the last processed bar to avoid replay after restart.

Market-data transport is intentionally separate from execution. A callback must emit completed, consolidated slices for the strategy universe. See PolygonCompletedBarPoller for the built-in Polygon polling implementation. Live membership changes are not yet supported: the session fails explicitly for dynamic universes until removal orders can be reconciled with broker fills.

Features

• Event-driven lifecycle — initialize, on_data, on_order_event, on_securities_changed, on_end_of_day, on_warmup_finished.
• Realistic fills — next-bar execution with pluggable slippage / fee / fill models, and a one-bar look-ahead guard so decisions on bar t can't peek at bar t's close.
• Walk-forward analysis with per-fold parameter search.
• Parameter sweeps + PBO (probability of backtest overfitting).
• Live execution through Alpaca paper/live brokerage with buffered rolling history and restart-safe bar processing.
• Reporting — result.stats, an HTML result.dashboard, and quantstats reports.

CLI

alphalens run --strategy mymod:MyStrategy
alphalens live --strategy mymod:MyStrategy
alphalens wfa --strategy mymod:MyStrategy --train 504 --test 63 --step 63
alphalens cache --info

License

Apache-2.0 © AlphaLens LLC