manifoldbt 0.17.3

ManifoldBT
Rust-powered backtesting engine for quantitative research

Website · Documentation · Examples

ManifoldBT is a Python backtesting library with a Rust core. Strategies are written in a fluent Python DSL, compiled to a vectorized Rust expression graph, then run through a sequential fill simulation with realistic fees, slippage, funding and look-ahead protection. Vectorized speed with event-driven execution realism.

Why ManifoldBT

• Fast — 500K bars in ~13 ms. 353x faster than vectorbt, ~3,500x faster than backtrader.
• Expressive — fluent DSL with 30+ indicators, conditional logic, cross-asset references
• Rigorous — Monte Carlo, walk-forward, parameter sweeps, lookahead detection, exposure diagnostics
• Portable — pip install, no Rust toolchain needed. Works on Python 3.9+.

Installation

pip install manifoldbt              # engine only: backtests, sweeps, metrics
pip install manifoldbt[plot]        # + interactive charts and native windows (show=True)
pip install manifoldbt[all]         # everything: plots, windows, PNG export, pandas/polars

The base install stays light (no browser, no GUI) for scripts, servers and CI. [plot] adds plotly and a native window backend; [all] also pulls kaleido for static PNG/SVG export (which bundles a headless Chromium).

Quick Start

import manifoldbt as mbt
from manifoldbt.indicators import close, ema
from manifoldbt.helpers import time_range, Interval, Slippage

fast = ema(close, 12)
slow = ema(close, 26)

strategy = (
    mbt.Strategy.create("ema_crossover")
    .signal("fast", fast)
    .signal("slow", slow)
    .signal("signal", mbt.when(fast > slow, mbt.lit(1.0), mbt.lit(-1.0)))
    .size(mbt.col("signal") * mbt.lit(0.25))
)

start, end = time_range("2022-01-01", "2025-01-01")

config = mbt.BacktestConfig(
    universe=[1],
    time_range_start=start,
    time_range_end=end,
    bar_interval=Interval.hours(12),
    initial_capital=10_000,
    execution=mbt.ExecutionConfig(allow_short=True, max_position_pct=0.5),
    fees=mbt.FeeConfig.binance_perps(),
    slippage=Slippage.fixed_bps(2),
    warmup_bars=30,
)

store = mbt.ingest(provider="binance", symbol="BTCUSDT", symbol_id=1,
                   start="2022-01-01T00:00:00Z", end="2025-01-01T00:00:00Z", interval="1h")
result = mbt.run(strategy, config, store)
print(result.summary())

Loading data

Bring your own data, or pull it from a built-in connector — both return a DataStore ready for mbt.run(...).

CSV — free on all tiers, auto-detects standard / MetaTrader 4 / MetaTrader 5:

store = mbt.import_csv("EURUSD_1m.csv", symbol="EURUSD", symbol_id=1,
                       interval="1m", asset_class="forex")

Exchange connectors — Binance, Bybit, Hyperliquid, dYdX, Bitstamp (free); Databento, Massive (Pro):

store = mbt.ingest(provider="binance", symbol="BTCUSDT", symbol_id=1,
                   start="2024-01-01T00:00:00Z", end="2025-01-01T00:00:00Z")

Or from the CLI:

manifoldbt import-csv data.csv --symbol EURUSD --symbol-id 1 --interval 1m
manifoldbt ingest --provider binance --symbol BTCUSDT --symbol-id 1 --start ... --end ...

Examples

Performance

EMA(12/26) + RSI(14) on 500K synthetic 1-min bars (manifoldbt/vectorbt: median of 5 runs; backtrader: median of 3):

ManifoldBT and vectorbt produce identical results (−30.23% vs −30.24% return, same trade count); backtrader's event-driven fills give a different PnL.

Reproduce: python benchmarks/bench_vs_competitors.py --rows 500000 --runs 5

How it compares

¹ fees, slippage, funding, partial fills, look-ahead detection.

On GPU (Pro), the Monte Carlo engine runs ~36x faster than the all-core CPU path (SDE path simulation, RTX 3090, f32).

Documentation

Full API reference, indicator list, configuration guide, and best practices:

www.manifoldbt.com/docs/documentation.html

Community vs Pro

Telemetry

Every install sends one anonymous ping a day: an anonymous install id, the ManifoldBT version, your OS, CPU architecture, whether it is a CUDA build, your Python major version, and Community or Pro. No email, no license key, no strategy, no data, no results. It tells us which versions and platforms are still in use, so we know what we can stop supporting.

Turn it off with either of:

export MANIFOLDBT_NO_TELEMETRY=1
export DO_NOT_TRACK=1

CI runners are skipped automatically. Pro license validation is a separate mechanism and is not affected by these variables.

License

Apache 2.0 with Commons Clause. The source is available, free to use, modify and self-host. Reselling the software or offering it as a paid hosted service is not permitted. See LICENSE for the full text.