nautilus-strategy-authoring

name

nautilus-strategy-authoring

description

Authoring contract for NautilusTrader strategies pluggable into the cajias/nautilus-trading `nt` CLI. Use when the user asks to "write a new strategy", "author a strategy for nautilus", says "STRATEGY_SPEC", "register a strategy", "external strategy", "build an algo for nt", or wants to port a backtest into the registry. Covers the StrategySpec / ImportableStrategyConfig / msgspec-frozen StrategyConfig contract, entry-point registration via pyproject.toml, plus ~10 canonical production gotchas spanning indicator scale, order time-in-force, multi-strategy actor pattern, monetary-string parsing, signal-handler safety, and CLI smoke-verification — full enumeration in the skill body.

Authoring a Strategy for the nt Registry

This skill is the contract for adding a strategy that cajias/nautilus-trading's nt CLI can pick up — either inside the repo at strategies/<market_type>/ or in an external package installed via uv pip install --editable ..

The contract is identical in both cases: expose a STRATEGY_SPEC, register it under the nautilus_trading.strategies entry-point group, and provide importable Strategy + StrategyConfig classes at the paths the spec references.

The four-piece contract

1. StrategySpec

Every authoring path imports the public surface from nautilus_trading.specs:

from nautilus_trading.specs import StrategySpec

Never import from nautilus_trading.cli._strategy_specs — that module is private discovery glue (the underscore prefix is a deliberate "do not depend on this" signal).

StrategySpec is a frozen dataclass with five fields:

@dataclass(frozen=True)
class StrategySpec:
    name: str                              # CLI/YAML key
    builder: ConfigBuilder                 # parsed-args -> kwargs dict
    strategy_path: str                     # "pkg.mod:ClassName"
    config_path: str                       # "pkg.mod:ConfigName"
    actor_specs: tuple[ActorSpec, ...] = ()

The name is what users type after --strategy and what YAML configs put in their strategy: field. It must match the entry-point key in pyproject.toml byte-for-byte; mismatch raises RuntimeError at discovery.

2. ConfigBuilder

A ConfigBuilder maps a parsed-args dict (CLI flags or YAML body) to a kwargs dict that goes straight into ImportableStrategyConfig.config. The Protocol is one method:

class ConfigBuilder(Protocol):
    def build(self, args: dict[str, Any]) -> dict[str, Any]: ...

Raise ValueError for missing or invalid fields; the CLI dispatcher maps that uniformly to typer.BadParameter.

class MyStrategyConfigBuilder:
    def build(self, args: dict[str, Any]) -> dict[str, Any]:
        if not args.get("instrument_id") or not args.get("bar_type"):
            raise ValueError("my_strategy requires instrument_id and bar_type")
        return {
            "instrument_id": args["instrument_id"],
            "bar_type": args["bar_type"],
            "fast_ema_period": args.get("fast_ema_period", 10),
            "slow_ema_period": args.get("slow_ema_period", 20),
        }

3. StrategyConfig (msgspec frozen) and Strategy

from typing import Any
from nautilus_trader.config import StrategyConfig
from nautilus_trader.indicators import ExponentialMovingAverage
from nautilus_trader.model.data import BarType
from nautilus_trader.model.identifiers import InstrumentId
from nautilus_trader.trading.strategy import Strategy


class MyStrategyConfig(StrategyConfig, frozen=True):
    instrument_id: InstrumentId
    bar_type: BarType
    fast_ema_period: int = 10
    slow_ema_period: int = 20


class MyStrategy(Strategy):
    def __init__(self, config: MyStrategyConfig) -> None:
        super().__init__(config)
        self.fast_ema = ExponentialMovingAverage(config.fast_ema_period)
        self.slow_ema = ExponentialMovingAverage(config.slow_ema_period)

    def on_start(self) -> None:
        self.register_indicator_for_bars(self.config.bar_type, self.fast_ema)
        self.register_indicator_for_bars(self.config.bar_type, self.slow_ema)
        self.subscribe_bars(self.config.bar_type)

    def () -> :
          .indicators_initialized():
            
        

StrategyConfig MUST be frozen=True. The base class uses msgspec Structs, and freezing is the only way the registry can hash and dedupe configs.

4. Entry-point registration in pyproject.toml

In your package's pyproject.toml:

[project.entry-points."nautilus_trading.strategies"]
my_strategy = "my_pkg.my_module:STRATEGY_SPEC"

Then in my_pkg/my_module.py, expose the constant:

STRATEGY_SPEC = StrategySpec(
    name="my_strategy",
    builder=MyStrategyConfigBuilder(),
    strategy_path="my_pkg.my_module:MyStrategy",
    config_path="my_pkg.my_module:MyStrategyConfig",
)

The entry-point key (my_strategy) must equal STRATEGY_SPEC.name byte-for-byte. After uv pip install --editable ., run uv run nt strategies and you'll see my_strategy listed alongside the in-repo strategies, with your package as the source label.

For the in-repo authoring path, drop the file under strategies/<market_type>/<name>.py and add it to the in-repo pyproject.toml's entry-point table. See strategies/forex/ema_cross.py for the canonical worked example.

The ten bug landmines (canonical list — single source of truth)

These bite if you don't know them. Each is sourced from a real production incident in this repo. The companion strategy-author agent references this list rather than duplicating it; if you find the agent body and this section disagree, this section is correct.

1. RelativeStrengthIndex.value is in [0.0, 1.0], not [0, 100]

# WRONG — never fires:
if self.rsi.value > 55:
    self.submit_order(...)

# RIGHT:
if self.rsi.value > 0.55:
    self.submit_order(...)

Same gotcha for RateOfChange (returns a fraction). Always verify indicator scale by reading the source or print-debugging — the docs are inconsistent.

2. Indicator imports come from the package root

# WRONG — these submodules don't exist as importable paths:
from nautilus_trader.indicators.rsi import RelativeStrengthIndex
from nautilus_trader.indicators.average import ExponentialMovingAverage

# RIGHT:
from nautilus_trader.indicators import (
    ExponentialMovingAverage,
    RelativeStrengthIndex,
    BollingerBands,
    AverageTrueRange,
)

The package root re-exports every indicator class. LLM-generated strategies often pick the wrong path; the file compiles fine but raises ModuleNotFoundError at import.

3. Bar-close vs intra-bar exits on 1H+ bars

# WRONG on 1H+ bars — `bar.high` and `bar.low` are wick prices that fired
# during the bar; a MARKET order from on_bar fills at *next-bar-open*, so
# you get 1-3% slippage per stop-out.
if bar.high >= take_profit or bar.low <= stop_loss:
    self.close_all_positions(...)

# RIGHT — evaluate on bar.close, accept missed wicks as the cost of doing
# business at this aggregation:
if bar.close >= take_profit or bar.close <= stop_loss:
    self.close_all_positions(...)

For real intra-bar triggers, post a venue-side STOP-MARKET order ahead of time rather than evaluating bar.high/bar.low after the fact.

4. Binance Spot rejects MARKET + GTC; use IOC

The backtest engine doesn't enforce this — the bug only surfaces at paper-trade or live time. When building a market order destined for Binance Spot, set time_in_force=TimeInForce.IOC. See strategies/crypto/shock_guard.py in the repo for the pattern.

5. Multiple strategies sharing a bar_type need a BarFanoutActor

TradingNodeConfig.strategies=[s1, s2, ...] with a shared bar_type silently delivers bars only to the FIRST subscriber's on_bar; the rest stay empty forever. This is a NautilusTrader dispatch bug. The repo's workaround lives at nautilus_trading.paper_trade.bar_fanout — import BarFanoutActor, BarFanoutActorConfig, and FanoutBar from that module (NOT from the package root — nautilus_trading.paper_trade.__init__ does not re-export them). Attach it as an actor and have each strategy subscribe to DataType(FanoutBar). See nautilus_trading/paper_trade/multi_strategy.py:build_multi_strategy_paper_node_config for the wiring pattern.

6. Frozen StrategyConfig defaults vs. spec-builder defaults

class MyConfig(StrategyConfig, frozen=True):
    fast_ema_period: int = 10   # class-level default

If your spec builder also has args.get("fast_ema_period", 12), the builder's default wins — the kwarg is always passed, so the class-level default never fires. Either keep them in sync, or make the spec builder the single source of truth and drop the class-level default.

7. Signal handlers around TradingNode must not call engine queries

Python signal handlers must NOT directly call engine.portfolio or engine.trader queries — NautilusTrader's C/Cython main loop doesn't yield to Python's signal queue safely, and the process crashes with exit 1 / no traceback. Pattern: signal handler does event.set(); a daemon Python thread does the actual query work.

8. Account-report monetary columns are strings, not floats

# WRONG — TypeError or wrong sort order:
df["realized_pnl"].sum()

# RIGHT — strip currency suffix first:
df["realized_pnl_num"] = (
    df["realized_pnl"]
    .str.replace(r"\s+\w+$", "", regex=True)
    .astype(float)
)

realized_pnl returns "-9.48 USD", not a float. Same for commissions and any column produced by engine.portfolio.analyzer that carries a currency unit.

9. Actor.log is not assignable in tests

# WRONG — TypeError: attribute 'log' of 'nautilus_trader.common.actor.Actor'
# objects is not writable.
actor = MyActor.__new__(MyActor)
actor.log = MagicMock()

Actor.log is a Cython slot; the underlying type forbids attribute assignment. Tests that need to mock logging must either patch the underlying logger object via unittest.mock.patch, or — preferably — extract the logic under test into a module-level pure function that takes a logger as an argument and unit-test the function directly. Don't try to instantiate Actor outside a BacktestEngine.

10. nt --help doesn't exercise discovery — invoke a real subcommand

uv run nt --help (and uv run nt strategies --help) prints Typer's synopsis without ever loading the entry-point group. A strategy with broken import-time side effects, a typoed STRATEGY_SPEC.name, or a mismatched entry-point key will pass --help cleanly and then fail at nt strategies or nt backtest --strategy <name> time. Always smoke with a real subcommand invocation (nt strategies listing your name, nt backtest --strategy <name> exiting 0) before declaring the registration done.

Verifying

After authoring:

cd nautilus
uv run nt strategies                    # confirm the new name appears
uv run nt backtest --strategy <name>   # smoke the import + signal path

--help does NOT exercise discovery — invoking --strategy does. Don't let a passing --help smoke convince you the strategy is wired.

Reference paths in the repo

• Public spec types: nautilus/src/nautilus_trading/specs.py
• Discovery glue (private): nautilus/src/nautilus_trading/cli/_strategy_specs.py
• In-repo strategy entry-points: nautilus/pyproject.toml ([project.entry-points."nautilus_trading.strategies"])
• Canonical examples:
  • strategies/forex/ema_cross.py — minimal worked example
  • strategies/crypto/shock_guard.py — MARKET + IOC pattern
  • strategies/crypto/hybrid_sma_r10.py — pandas-port reference
• External-strategy runbook: docs/runbooks/external-strategies.md
• Test fixture mirroring an external package: tests/cli/_external_strategy_fixture/

See also

• The companion nt-cli-quickstart skill covers running the strategy once the registry sees it.
• The strategy-author agent in this plugin orients on these landmines before any strategy code is written.