Python

The Python programming language is used for the majority of user-facing code in NautilusTrader. Python provides a rich ecosystem of libraries and frameworks, making it ideal for strategy development, data analysis, and system integration.

Code style

PEP-8

The codebase generally follows the PEP-8 style guide. One notable departure is that Python truthiness is not always taken advantage of to check if an argument is None for everything other than collections.

As per the Google Python Style Guide, it's discouraged to use truthiness to check if an argument is/is not None, when there is a chance an unexpected object could be passed into the function or method which will yield an unexpected truthiness evaluation (which could result in a logical error type bug).

"Always use if foo is None: (or is not None) to check for a None value. E.g., when testing whether a variable or argument that defaults to None was set to some other value. The other value might be a value that's false in a boolean context!"

We welcome all feedback on where the codebase departs from PEP-8 for no apparent reason.

Type hints

All function and method signatures must include type annotations:

def __init__(self, config: EMACrossConfig) -> None:
def on_bar(self, bar: Bar) -> None:
def on_save(self) -> dict[str, bytes]:
def on_load(self, state: dict[str, bytes]) -> None:

Union syntax: Use PEP 604 union syntax for optional types:

# Preferred
def get_instrument(self, id: InstrumentId) -> Instrument | None:

# Avoid
def get_instrument(self, id: InstrumentId) -> Optional[Instrument]:

Generic types: Use Python 3.12 type parameter syntax for reusable functions and classes:

def first[T](values: list[T]) -> T:
    return values[0]

Docstrings

The NumPy docstring spec is used throughout the codebase. This needs to be followed consistently so the docs build correctly.

Python docstrings should be written in the imperative mood - e.g. "Return a cached client."

This convention aligns with the prevailing style of the Python ecosystem and makes generated documentation feel natural to end-users.

Private methods

Do not add docstrings to private methods (prefixed with _):

• Docstrings generate public-facing API documentation.
• Docstrings on private methods incorrectly imply they are part of the public API.
• Private methods are implementation details not intended for end-users.

Exceptions where docstrings are acceptable:

• Very complex methods with non-trivial logic, multiple steps, or important edge cases.
• Methods requiring detailed parameter or return value documentation due to complexity.

When a private method needs context (such as a tricky precondition or side effect), prefer a short inline comment (#) near the relevant logic rather than a docstring.

Properties vs methods (PyO3 bindings)

When exposing Rust types to Python via PyO3, use #[getter] (property) or a plain method based on what the call site communicates, not whether the value can change:

• Property (#[getter]): cheap, side-effect-free, attribute-like view of current state. Scalar fields, predicates, and lightweight derived values belong here even if they change over the object's lifetime. Examples: status, side, quantity, price, is_open, has_inputs, realized_pnl, venue_order_id.
• Method (no #[getter]): actions, mutations, nontrivial work, allocations/copies, I/O, or anything that takes arguments. Examples: apply(fill), unrealized_pnl(price), calculate_pnl(...).
• Gray area (prefer method): getters that clone or allocate a collection each call. Using a method signals the cost to the caller. Examples: events(), adjustments(), client_order_ids(), trade_ids().

Python live callback routing

Python live nodes keep one runtime invariant: Tokio worker threads do not run Python code during live trading.

LiveNode::py_run releases the GIL while the Rust async runtime runs. Worker-side work that must trigger Python uses existing live runner event channels instead of calling Python::attach on the worker. Timer callbacks use the time-event channel. The runner drains that channel during startup buffering and the main select loop, then executes callbacks on the live event loop thread.

This path is a boundary for unavoidable user Python callback work. It is not a place to move adapter, provider, data, or execution logic into Python. Python adapter modules configure Rust adapters and register factories; Rust owns adapter operations. If worker-side Rust work needs a Python callback, route it through a specific event type that belongs in the live runner.

When adding Python-aware live code:

• Prefer an existing runner event channel.
• Keep callback bodies short because they run synchronously on the live event loop.
• Do not call Python::attach from Tokio worker tasks in Python live trading.
• Do not add adapter business logic in Python to fit callback routing.

Test naming

Use descriptive names that explain the scenario. Keep tests as annotated pytest free functions:

def test_write_and_query_option_greeks_round_trip() -> None: ...


def test_catalog_loaded_greeks_reach_on_option_greeks() -> None: ...


def test_backend_session_rejects_zero_chunk_size() -> None: ...

Ruff

Ruff is used to lint the codebase. Its rules are configured in python/pyproject.toml, with ignore justifications typically commented.