CPython's Sentinel Implementation in C: Unique Marker Objects for Defaults

Jay Hubbert — Tue, 20 Oct 2026 09:00:00 +0000

TL;DR: Python 3.15 adds a sentinel builtin (PEP 661). Every call to sentinel("MISSING") allocates a new, distinct object — not a process-wide singleton — carrying a name, an auto-detected module, and an optional repr, all in Objects/sentinelobject.c.

None, Ellipsis, and NotImplemented are singletons: one object per process. But sometimes you want a marker value that’s unique to your library — MISSING, UNSET, NOT_PROVIDED.

Python 3.15’s sentinel builtin gives you exactly that. Unlike the classic singletons, these are not process-wide: every call allocates a fresh, distinct object. Each one carries a name, a module, and an optional repr, and it’s tracked by the garbage collector. The whole implementation lives in Objects/sentinelobject.c. Let’s trace it through the 3.15 source.

The struct: `sentinelobject`

A sentinel is a small GC object with three owned references:

 c
 
 
// Objects/sentinelobject.c
typedef struct {
 PyObject_HEAD
 PyObject *name;
 PyObject *module;
 PyObject *repr;
} sentinelobject;

name is the __name__ (a str, or a str subclass).
module is the __module__, usually inferred from the caller.
repr is an optional custom repr string. When it’s NULL, repr() falls back to name.

The cast macro is exact, because the type doesn’t allow subclasses:

 c
 
 
// Objects/sentinelobject.c
#define sentinelobject_CAST(op) \
 (assert(PySentinel_Check(op)), _Py_CAST(sentinelobject *, (op)))

The type: `PySentinel_Type`

PySentinel_Type is a GC, immutable type. It’s not a base type, so subclassing is rejected:

 c
 
 
// Objects/sentinelobject.c
PyTypeObject PySentinel_Type = {
 PyVarObject_HEAD_INIT(&PyType_Type, 0)
 .tp_name = "sentinel",
 .tp_basicsize = sizeof(sentinelobject),
 .tp_dealloc = sentinel_dealloc,
 .tp_repr = sentinel_repr,
 .tp_as_number = &sentinel_as_number,
 .tp_hash = PyObject_GenericHash,
 .tp_getattro = PyObject_GenericGetAttr,
 .tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_IMMUTABLETYPE
 | Py_TPFLAGS_HAVE_GC,
 .tp_doc = sentinel_doc,
 .tp_traverse = sentinel_traverse,
 .tp_clear = sentinel_clear,
 .tp_richcompare = _Py_BaseObject_RichCompare,
 .tp_methods = sentinel_methods,
 .tp_members = sentinel_members,
 .tp_new = sentinel_new,
 .tp_free = PyObject_GC_Del,
};

The flags and slots worth calling out:

Py_TPFLAGS_HAVE_GC is set because name, module, and repr can participate in reference cycles — for example, a str subclass that stores the sentinel.
Py_TPFLAGS_IMMUTABLETYPE makes the type object itself immutable.
Py_TPFLAGS_BASETYPE is not set, so class Sub(sentinel) raises TypeError.
tp_richcompare is _Py_BaseObject_RichCompare, so equality is identity: a sentinel equals itself and nothing else.
tp_hash is PyObject_GenericHash, i.e. identity-based hashing.
tp_as_number.nb_or is _Py_union_type_or, which is what makes sentinel | int (and int | sentinel) work in type expressions.

The type is registered in the interpreter’s type table (Objects/object.c) and exposed as a builtin:

 c
 
 
// Python/bltinmodule.c
SETBUILTIN("sentinel", &PySentinel_Type);

The header exposes the check macros, which are exact checks because subclasses are impossible:

 c
 
 
// Include/cpython/sentinelobject.h
#define PySentinel_CheckExact(op) Py_IS_TYPE((op), &PySentinel_Type)
#define PySentinel_Check(op) PySentinel_CheckExact(op)

Construction: `sentinel_new`

The clinic-generated sentinel_new accepts a positional-only name (which must be a str or subclass) and a keyword-only repr (default None):

 c
 
 
// Objects/sentinelobject.c
static PyObject *
sentinel_new_impl(PyTypeObject *type, PyObject *name, PyObject *repr)
{
 if (repr == Py_None) {
 repr = NULL;
 }
 else if (!PyUnicode_Check(repr)) {
 _PyArg_BadArgument("sentinel", "argument 'repr'", "str or None", repr);
 return NULL;
 }
 PyObject *module = caller();
 PyObject *self = sentinel_new_with_module(type, name, module, repr);
 Py_DECREF(module);
 return self;
}

The module isn’t passed by the user. Instead, caller() inspects the current execution frame and returns the module of the function that’s currently running:

 c
 
 
// Objects/sentinelobject.c
static PyObject *
caller(void)
{
 _PyInterpreterFrame *f = _PyThreadState_GET()->current_frame;
 if (f == NULL || PyStackRef_IsNull(f->f_funcobj)) {
 assert(!PyErr_Occurred());
 Py_RETURN_NONE;
 }
 PyFunctionObject *func = _PyFrame_GetFunction(f);
 assert(PyFunction_Check(func));
 PyObject *r = PyFunction_GetModule((PyObject *)func);
 if (!r) {
 assert(!PyErr_Occurred());
 Py_RETURN_NONE;
 }
 return Py_NewRef(r);
}

This is why a module-level MISSING = sentinel("MISSING") automatically gets __module__ set to that module’s name — and that’s exactly what makes the value picklable later. At top level with no current function, caller() returns None.

Allocation itself is ordinary GC allocation, followed by tracking:

 c
 
 
// Objects/sentinelobject.c
static PyObject *
sentinel_new_with_module(PyTypeObject *type, PyObject *name, PyObject *module, PyObject *repr)
{
 assert(PyUnicode_Check(name));

 sentinelobject *self = PyObject_GC_New(sentinelobject, type);
 if (self == NULL) {
 return NULL;
 }
 self->name = Py_NewRef(name);
 self->module = Py_NewRef(module);
 self->repr = Py_XNewRef(repr);
 _PyObject_GC_TRACK(self);
 return (PyObject *)self;
}

Note that module is always stored (even when it’s None), while repr is stored only when provided.

The C API: `PySentinel_New`

For C extensions, PySentinel_New builds a sentinel without going through the Python-level caller machinery. The caller supplies the module name (or NULL for None) and the repr (or NULL for “use the name”):

 c
 
 
// Objects/sentinelobject.c
PyObject *
PySentinel_New(const char *name, const char *module_name, const char *repr)
{
 PyObject *name_obj = PyUnicode_FromString(name);
 if (name_obj == NULL) {
 return NULL;
 }
 PyObject *repr_obj = NULL;
 if (repr != NULL) {
 repr_obj = PyUnicode_FromString(repr);
 if (repr_obj == NULL) {
 Py_DECREF(name_obj);
 return NULL;
 }
 }
 PyObject *module_obj = module_name == NULL
 ? Py_None
 : PyUnicode_FromString(module_name);
 if (module_obj == NULL) {
 Py_DECREF(name_obj);
 Py_XDECREF(repr_obj);
 return NULL;
 }

 PyObject *sentinel = sentinel_new_with_module(
 &PySentinel_Type, name_obj, module_obj, repr_obj);
 Py_DECREF(module_obj);
 Py_DECREF(name_obj);
 Py_XDECREF(repr_obj);
 return sentinel;
}

The returned object is a new reference owned by the caller.

Garbage collection lifecycle

Because a sentinel owns references, it participates in the cyclic GC:

 c
 
 
// Objects/sentinelobject.c
static int
sentinel_traverse(PyObject *op, visitproc visit, void *arg)
{
 sentinelobject *self = sentinelobject_CAST(op);
 Py_VISIT(self->name);
 Py_VISIT(self->module);
 Py_VISIT(self->repr);
 return 0;
}

static int
sentinel_clear(PyObject *op)
{
 sentinelobject *self = sentinelobject_CAST(op);
 Py_CLEAR(self->name);
 Py_CLEAR(self->module);
 Py_CLEAR(self->repr);
 return 0;
}

static void
sentinel_dealloc(PyObject *op)
{
 _PyObject_GC_UNTRACK(op);
 (void)sentinel_clear(op);
 Py_TYPE(op)->tp_free(op);
}

tp_free is PyObject_GC_Del, matching the PyObject_GC_New allocation. The traverse/clear pair is what lets the test suite create a str subclass that points back at the sentinel and still collect both objects once they become unreachable.

Attributes: `name` and `module`

The two attributes are exposed as members rather than computed properties:

 c
 
 
// Objects/sentinelobject.c
static PyMemberDef sentinel_members[] = {
 {"__name__", Py_T_OBJECT_EX, offsetof(sentinelobject, name), Py_READONLY},
 {"__module__", Py_T_OBJECT_EX, offsetof(sentinelobject, module), 0},
 {NULL}
};

__name__ is read-only: assigning or deleting it raises AttributeError.
__module__ is read/write and deletable. Deleting it sets the underlying pointer to NULL; a subsequent read raises AttributeError rather than returning None.
The type itself (sentinel) rejects attribute assignment entirely, because it’s immutable (Py_TPFLAGS_IMMUTABLETYPE and no tp_setattro override that allows it). Hence sentinel.attribute = ... raises TypeError.

tp_getattro is PyObject_GenericGetAttr, so normal attribute lookup (including the methods below) works.

Repr

 c
 
 
// Objects/sentinelobject.c
static PyObject *
sentinel_repr(PyObject *op)
{
 sentinelobject *self = sentinelobject_CAST(op);
 if (self->repr != NULL) {
 return Py_NewRef(self->repr);
 }
 return Py_NewRef(self->name);
}

tp_str is 0, so str() falls back to repr(). A custom repr="custom" therefore affects both repr() and str().

Copy, deepcopy, and equality

Sentinels are identity objects: copying returns the same instance, and equality is identity:

 c
 
 
// Objects/sentinelobject.c
static PyObject *
sentinel_copy(PyObject *self, PyObject *Py_UNUSED(ignored))
{
 return Py_NewRef(self);
}

static PyObject *
sentinel_deepcopy(PyObject *self, PyObject *Py_UNUSED(memo))
{
 return Py_NewRef(self);
}

 c
 
 
// Objects/sentinelobject.c (methods table)
static PyMethodDef sentinel_methods[] = {
 {"__copy__", sentinel_copy, METH_NOARGS, NULL},
 {"__deepcopy__", sentinel_deepcopy, METH_O, NULL},
 {"__reduce__", sentinel_reduce, METH_NOARGS, NULL},
 {NULL, NULL}
};

Because tp_richcompare is _Py_BaseObject_RichCompare, s == s is True and s == other is False. And copy.copy / copy.deepcopy hand back the same object (assertIs(copy.copy(s), s)).

Pickling: `reduce`

 c
 
 
// Objects/sentinelobject.c
static PyObject *
sentinel_reduce(PyObject *op, PyObject *Py_UNUSED(ignored))
{
 sentinelobject *self = sentinelobject_CAST(op);
 return Py_NewRef(self->name);
}

__reduce__ returns the name string. Pickle interprets a string result as a global name lookup: it imports __module__ and fetches the attribute named name.

So a sentinel pickles successfully only when it’s reachable as an attribute of an importable module under exactly that name. A dynamically created sentinel("MISSING") that isn’t stored anywhere is not picklable and raises PicklingError. That matches the C API documentation: for pickling to work, module_name must name an importable module and the sentinel must be accessible from it.

Gotcha: this is the whole reason the module-level pattern matters. Define your sentinel at module scope, not inside a function.

Union types: `sentinel | X`

sentinel overrides nb_or so it can appear in X | Y type expressions:

 c
 
 
// Objects/sentinelobject.c
static PyNumberMethods sentinel_as_number = {
 .nb_or = _Py_union_type_or,
};

_Py_union_type_or (in Objects/unionobject.c) only proceeds when both operands are “unionable”, and a sentinel is explicitly in that set:

 c
 
 
// Objects/unionobject.c
static int
is_unionable(PyObject *obj)
{
 if (obj == Py_None ||
 PyType_Check(obj) ||
 PySentinel_Check(obj) ||
 _PyGenericAlias_Check(obj) ||
 _PyUnion_Check(obj) ||
 Py_IS_TYPE(obj, &_PyTypeAlias_Type)) {
 return 1;
 }
 return 0;
}

So missing | int, int | missing, missing | None, and missing | list[int] all build a types.UnionType. A union of a sentinel with itself collapses to the sentinel itself (missing | missing is missing), because the union builder deduplicates equal — here identical — members.

Memory layout

A sentinel is a normal heap-allocated GC object:

text

sentinelobject (heap, GC-tracked)
+----------------------------+
| ob_refcnt |
+----------------------------+
| ob_flags (tracked bits) |
+----------------------------+
| *ob_type (&PySentinel_Type)|
+----------------------------+
| *name (owned str) |
+----------------------------+
| *module (owned or NULL) |
+----------------------------+
| *repr (owned or NULL) |
+----------------------------+

There’s no freelist and no static instance: every call allocates. The object is collected by the cyclic GC once it becomes unreachable, and its three owned references are cleared in sentinel_clear.

Key takeaways

sentinel is a builtin, GC-tracked, immutable, non-subclassable type whose instances are heap-allocated in Objects/sentinelobject.c.
Each instance stores name (read-only __name__), module (mutable, deletable __module__), and an optional repr.
The module is inferred from the calling function’s frame by caller(); the C API PySentinel_New takes it explicitly.
Equality and hashing are identity-based; __copy__/__deepcopy__ return self.
__reduce__ returns name, so pickling works only for module-level sentinels reachable by that name.
nb_or delegates to _Py_union_type_or, and sentinels are explicitly unionable, enabling sentinel | X in type expressions.
The type and its instances are tracked by the GC, so reference cycles involving the stored strings get collected.

Sentinel on Opensource internals

CPython's Sentinel Implementation in C: Unique Marker Objects for Defaults

The struct: `sentinelobject`

The type: `PySentinel_Type`

Construction: `sentinel_new`

The C API: `PySentinel_New`

Garbage collection lifecycle

Attributes: `name` and `module`

Repr

Copy, deepcopy, and equality

Pickling: `reduce`

Union types: `sentinel | X`

Memory layout

Key takeaways

Further reading

Sentinel on Opensource internals

CPython's Sentinel Implementation in C: Unique Marker Objects for Defaults

The struct: sentinelobject

The type: PySentinel_Type

Construction: sentinel_new

The C API: PySentinel_New

Garbage collection lifecycle

Attributes: __name__ and __module__

Repr

Copy, deepcopy, and equality

Pickling: __reduce__

Union types: sentinel | X

Memory layout

Key takeaways

Further reading

The struct: `sentinelobject`

The type: `PySentinel_Type`

Construction: `sentinel_new`

The C API: `PySentinel_New`

Attributes: `name` and `module`

Pickling: `reduce`

Union types: `sentinel | X`