Author:

Tal Einat , Jelle Zijlstra <jelle.zijlstra at gmail.com>

Discussions-To:

Discourse thread

Status:

Final

Type:

Standards Track

Created:

06-Jun-2021

Python-Version:

3.15

Post-History:

20-May-2021, 06-Jun-2021

Resolution:

23-Apr-2026

---

Table of Contents

• Abstract
• Motivation
• Rationale
• Specification
  • Typing
  • C API
• Backwards Compatibility
• How to Teach This
• Security Implications
• Reference Implementation
• Rejected Ideas
  • Use NotGiven = object()
  • Add a single new sentinel value, such as MISSING or Sentinel
  • Use the existing Ellipsis sentinel value
  • Use a single-valued enum
  • A sentinel class decorator
  • Using class objects
  • Define a recommended “standard” idiom, without supplying an implementation
  • Use a new standard library module
  • Use a registry of per-module sentinel names
  • Automatically discover or pass a module name
  • Allowing customization of repr
  • Allowing customization of boolean evaluation
  • Using typing.Literal in type annotations
• Additional Notes
• Footnotes
• Copyright

Abstract

Unique placeholder values, commonly known as “sentinel values”, are common in programming. They have many uses, such as for:

• Default values for function arguments, for when a value was not given:

  def foo(value=None): ...

• Return values from functions when something is not found or unavailable:

  >>> "abc".find("d") -1

• Missing data, such as NULL in relational databases or “N/A” (“not available”) in spreadsheets

Python has the special value None, which is intended to be used as such a sentinel value in most cases. However, sometimes an alternative sentinel value is needed, usually when it needs to be distinct from None since None is a valid value in that context. Such cases are common enough that several idioms for implementing such sentinels have arisen over the years, but uncommon enough that there hasn’t been a clear need for standardization. However, the common implementations, including some in the stdlib, suffer from several significant drawbacks.

This PEP proposes adding a built-in class for defining sentinel values, to be used in the stdlib and made publicly available to all Python code. Sentinels can be defined in Python with the sentinel() built-in class, and in C with the PySentinel_New() C API function.

Note: Changing all existing sentinels in the stdlib to be implemented this way is not deemed necessary, and whether to do so is left to the discretion of the maintainers.

Motivation

In May 2021, a question was brought up on the python-dev mailing list [1] about how to better implement a sentinel value for traceback.print_exception. The existing implementation used the following common idiom:

_sentinel = object()

However, this object has an uninformative and overly verbose repr, causing the function’s signature to be overly long and hard to read:

>>> help(traceback.print_exception) Help on function print_exception in module traceback:

print_exception(exc, /, value=<object object at 0x000002825DF09650>, tb=<object object at 0x000002825DF09650>, limit=None, file=None, chain=True)

Additionally, two other drawbacks of many existing sentinels were brought up in the discussion:

1. Some do not have a distinct type, hence it is impossible to define clear type signatures for functions with such sentinels as default values.
2. They behave unexpectedly after being copied, due to a separate instance being created and thus comparisons using is failing. Some common sentinel idioms have similar problems after being pickled and unpickled.

In the ensuing discussion, Victor Stinner supplied a list of currently used sentinel values in the Python standard library [2]. This showed that the need for sentinels is fairly common, that there are various implementation methods used even within the stdlib, and that many of these suffer from at least one of the three above drawbacks.

The discussion did not lead to any clear consensus on whether a standard implementation method is needed or desirable, whether the drawbacks mentioned are significant, nor which kind of implementation would be good. The author of this PEP created an issue on bugs.python.org (now a GitHub issue [3]) suggesting options for improvement, but that focused on only a single problematic aspect of a few cases, and failed to gather any support.

A poll [4] was created on discuss.python.org to get a clearer sense of the community’s opinions. After nearly two weeks, significant further, discussion, and 39 votes, the poll’s results were not conclusive. 40% had voted for “The status-quo is fine / there’s no need for consistency in this”, but most voters had voted for one or more standardized solutions. Specifically, 37% of the voters chose “Consistent use of a new, dedicated sentinel factory / class / meta-class, also made publicly available in the stdlib”.

With such mixed opinions, this PEP was created to facilitate making a decision on the subject.

While working on this PEP, iterating on various options and implementations and continuing discussions, the author has come to the opinion that a simple, good implementation available in the standard library would be worth having, both for use in the standard library itself and elsewhere.

Rationale

The criteria guiding the chosen implementation were:

1. The sentinel objects should behave as expected by a sentinel object: When compared using the is operator, it should always be considered identical to itself but never to any other object.
2. Creating a sentinel object should be a simple, straightforward one-liner.
3. It should be simple to define as many distinct sentinel values as needed.
4. The sentinel objects should have a clear and short repr.
5. It should be possible to use clear type signatures for sentinels.
6. The sentinel objects should behave correctly after copying, and sentinels should have predictable behavior when pickled and unpickled.
7. Such sentinels should work when using CPython 3.x and PyPy3, and ideally also with other implementations of Python.
8. As simple and straightforward as possible, in implementation and especially in use. Avoid this becoming one more special thing to learn when learning Python. It should be easy to find and use when needed, and obvious enough when reading code that one would normally not feel a need to look up its documentation.

With so many uses in the Python standard library [2], it would be useful to have an implementation available to the standard library, since the stdlib cannot use implementations of sentinel objects available elsewhere (such as the sentinels [5] or sentinel [6] PyPI packages).

After researching existing idioms and implementations, and going through many different possible implementations, the design below was chosen to meet these criteria while keeping the API and implementation small (see Reference Implementation).

Specification

A new built-in callable named sentinel will be added.

>>> MISSING = sentinel('MISSING') >>> MISSING MISSING

sentinel() takes a single positional-only argument, name, which must be a str. Passing a non-string raises TypeError. The name is used as the sentinel’s name and repr.

Sentinel objects have two public attributes:

• __name__ is the sentinel’s name.
• __module__ is the name of the module where sentinel() was called.

sentinel may not be subclassed.

Each call to sentinel(name) returns a new sentinel object. If a sentinel is needed in more than one place, it should be assigned to a variable and that same object should be reused explicitly, just as with the common MISSING = object() idiom:

MISSING = sentinel('MISSING')

def read_value(default=MISSING): ...

Checking if a value is such a sentinel should be done using the is operator, as is recommended for None. Equality checks using == will also work as expected, returning True only when the object is compared with itself. Identity checks such as if value is MISSING: should usually be used rather than boolean checks such as if value: or if not value:.

Sentinel objects are “truthy”, i.e. boolean evaluation will result in True. This parallels the default for arbitrary classes, as well as the boolean value of Ellipsis. This is unlike None, which is “falsy”.

Creating a copy of a sentinel object, such as by using copy.copy() or by copy.deepcopy(), will return the same object.

Sentinels importable from their defining module by name preserve their identity when pickled and unpickled, using the standard pickle mechanism for named singletons. When sentinel() creates a sentinel, it records the calling module as the sentinel’s __module__ attribute. Pickling records the sentinel by module and name. Unpickling then imports the module and retrieves the sentinel by name, so the following round trip preserves identity:

MISSING = sentinel('MISSING') assert pickle.loads(pickle.dumps(MISSING)) is MISSING

Sentinels that are not importable by module and name, such as sentinels created in a local scope and not assigned to a matching module global or class attribute, are not picklable.

The repr of a sentinel object is the name passed to sentinel(). No implicit module qualification is added. If a qualified repr is desired, the qualified name should be passed explicitly:

>>> MyClass_NotGiven = sentinel('MyClass.NotGiven') >>> MyClass_NotGiven MyClass.NotGiven

Ordering comparisons are undefined for sentinel objects. Sentinels do not support weakrefs.

Typing

To make usage of sentinels clear and simple in typed Python code, we propose to amend the type system with a special case for sentinel objects.

Sentinel objects may be used in type expressions, representing themselves. This is similar to how None is handled in the existing type system. For example:

MISSING = sentinel('MISSING')

def foo(value: int | MISSING = MISSING) -> int: ...

More formally, type checkers should recognize sentinel creations of the form NAME = sentinel('NAME') as creating a new sentinel object. If the name passed to sentinel() does not match the name the object is assigned to, type checkers should emit an error.

Sentinels defined using this syntax may be used in type expressions. They represent a fully static type that has a single member, the sentinel object itself.

Type checkers should support narrowing union types involving sentinels using the is and is not operators:

from typing import assert_type

MISSING = sentinel('MISSING')

def foo(value: int | MISSING) -> None: if value is MISSING: assert_type(value, MISSING) else: assert_type(value, int)

To support usage in type expressions, the runtime implementation of sentinel objects should have the __or__ and __ror__ methods, returning typing.Union objects.

The Typing Council supports this part of the proposal.

C API

Sentinels can also be useful in C extensions. We propose two new C API functions:

• PyObject *PySentinel_New(const char *name, const char *module_name) creates a new sentinel object.
• bool PySentinel_Check(PyObject *obj) checks if an object is a sentinel.

C code can use the == operator to check if an object is a specific sentinel.

Backwards Compatibility

Adding a new builtin means that code which currently relies on the bare name sentinel raising NameError will instead see the new builtin. This is the usual compatibility consideration for new builtins. Existing local, global, and imported names called sentinel are unaffected. Code that already uses the name sentinel will have to be adapted to use the new builtin and may receive new linter errors from linters that warn about collisions with builtin names.

How to Teach This

The normal types of documentation of new builtins and features, namely docstrings, library docs and a section in “What’s New”, should suffice.

Security Implications

This proposal should have no security implications.

Reference Implementation

A reference implementation is available as a CPython pull request [10]. A previous reference implementation is found in a dedicated GitHub repo [7]. A sketch of the intended behavior follows:

class sentinel: """Unique sentinel values."""

\_\_slots\_\_ \= ("\_\_name\_\_", "\_module\_name")

def \_\_init\_subclass\_\_(cls):
    raise TypeError("type 'sentinel' is not an acceptable base type")

def \_\_init\_\_(self, name, /):
    if not isinstance(name, str):
        raise TypeError("sentinel name must be a string")
    self.\_\_name\_\_ \= name
    self.\_module\_name \= sys.\_getframemodulename(1)

@property
def \_\_module\_\_(self):
    return self.\_module\_name

def \_\_repr\_\_(self):
    return self.\_\_name\_\_

def \_\_reduce\_\_(self):
    return self.\_\_name\_\_

def \_\_copy\_\_(self):
    return self

def \_\_deepcopy\_\_(self, memo):
    return self

def \_\_or\_\_(self, other):
    return typing.Union\[self, other\]

def \_\_ror\_\_(self, other):
    return typing.Union\[other, self\]

A backport exists in the typing-extensions module, though its behavior does not precisely match the current iteration of this PEP.

Rejected Ideas

Use NotGiven = object()

This suffers from all of the drawbacks mentioned in the Rationale section.

Add a single new sentinel value, such as MISSING or Sentinel

Since such a value could be used for various things in various places, one could not always be confident that it would never be a valid value in some use cases. On the other hand, a dedicated and distinct sentinel value can be used with confidence without needing to consider potential edge-cases.

Additionally, it is useful to be able to provide a meaningful name and repr for a sentinel value, specific to the context where it is used.

Finally, this was a very unpopular option in the poll [4], with only 12% of the votes voting for it.

Use the existing Ellipsis sentinel value

This is not the original intended use of Ellipsis, though it has become increasingly common to use it to define empty class or function blocks instead of using pass.

Also, similar to a potential new single sentinel value, Ellipsis can’t be as confidently used in all cases, unlike a dedicated, distinct value.

Use a single-valued enum

The suggested idiom is:

class NotGivenType(Enum): NotGiven = 'NotGiven' NotGiven = NotGivenType.NotGiven

Besides the excessive repetition, the repr is overly long: <NotGivenType.NotGiven: 'NotGiven'>. A shorter repr can be defined, at the expense of a bit more code and yet more repetition.

Finally, this option was the least popular among the nine options in the poll [4], being the only option to receive no votes.

A sentinel class decorator

The suggested idiom is:

@sentinel class NotGivenType: pass NotGiven = NotGivenType()

While this allows for a very simple and clear implementation of the decorator, the idiom is too verbose, repetitive, and difficult to remember.

Using class objects

Since classes are inherently singletons, using a class as a sentinel value makes sense and allows for a simple implementation.

The simplest version of this is:

class NotGiven: pass

To have a clear repr, one would need to use a meta-class:

class NotGiven(metaclass=SentinelMeta): pass

… or a class decorator:

@Sentinel class NotGiven: pass

Using classes this way is unusual and could be confusing. The intention of code would be hard to understand without comments. It would also cause such sentinels to have some unexpected and undesirable behavior, such as being callable.

Define a recommended “standard” idiom, without supplying an implementation

Most common existing idioms have significant drawbacks. So far, no idiom has been found that is clear and concise while avoiding these drawbacks.

Also, in the poll [4] on this subject, the options for recommending an idiom were unpopular, with the highest-voted option being voted for by only 25% of the voters.

Use a new standard library module

Earlier drafts proposed adding a Sentinel class to a new sentinels or sentinellib module. However, adding a new module for a single public callable is unnecessary, and using a module makes the feature less convenient than the existing object() idiom. The Steering Council also specifically encouraged making the feature a builtin so that it is at least as easy to use as object().

Using the name sentinels would also conflict with an existing, actively used PyPI package. While other module names are possible, making the feature a builtin avoids the naming problem entirely.

Use a registry of per-module sentinel names

Earlier drafts proposed making sentinel names unique within each module. Under that design, repeated calls such as sentinel("MISSING") from the same module would return the same object, using a process-global registry keyed by module name and sentinel name.

This was rejected because the behavior is too implicit. Code that needs a shared sentinel can define one explicitly and reuse it by name, just as code already does with MISSING = object(). Code in a local scope may also want a fresh sentinel for each call or iteration, and repeated calls to sentinel(name) should behave like repeated calls to object() by creating distinct objects.

Removing the registry also keeps the implementation and mental model simpler: sentinel(name) creates a new unique object whose repr is name.

Automatically discover or pass a module name

Earlier drafts proposed an optional module_name argument to support the registry-based design.

With the registry removed, a public module_name argument is no longer needed for the core proposal. The implementation still records the calling module internally, as TypeVar and similar helpers do, so that pickle can serialize importable sentinels by module and name. This internal module name does not affect the sentinel’s repr. If users want a repr that includes a module or class name, they can include it in the single name argument explicitly, e.g. sentinel("mymodule.MISSING").

Allowing customization of repr

This was desirable to allow using this for existing sentinel values without changing their repr. However, this was eventually dropped as it wasn’t considered worth the added complexity.

Allowing customization of boolean evaluation

Discussions considered allowing sentinels to be explicitly truthy, falsy, or not convertible to bool. Some existing third-party sentinels expose falsy behavior as part of their public API, and several participants argued that raising in boolean contexts would better enforce identity checks.

This PEP keeps the initial proposal simpler by giving sentinels the default truthy behavior of ordinary objects and by recommending identity checks. Custom boolean behavior may be considered later if the added API and typing complexity is judged worthwhile.

Using typing.Literal in type annotations

This was suggested by several people in discussions and is what this PEP first went with. However, it was pointed out that this would cause potential confusion, due to e.g. Literal["MISSING"] referring to the string value "MISSING" rather than being a forward-reference to a sentinel value MISSING. Using the bare name was also suggested often in discussions. This follows the precedent and well-known pattern set by None, and has the advantages of not requiring an import and being much shorter.

Additional Notes

• For sentinels defined in a class scope, to avoid potential name clashes, or when a qualified repr would be clearer, one should pass the desired qualified name explicitly. For example:

  >>> class MyClass: ... NotGiven = sentinel('MyClass.NotGiven') >>> MyClass.NotGiven MyClass.NotGiven

• Creating sentinels in a function or method is allowed. Each call to sentinel() creates a distinct object, so a sentinel created in a local scope behaves like one created by calling object() in that scope.

• The boolean value of NotImplemented is True, but using this is deprecated since Python 3.9 (doing so generates a deprecation warning.) This deprecation is due to issues specific to NotImplemented, as described in bpo-35712 [8].

• To define multiple, related sentinel values, possibly with a defined ordering among them, one should instead use Enum or something similar.

• There was a discussion on the typing-sig mailing list [9] about the typing for these sentinels, where different options were discussed.

Footnotes

Copyright

This document is placed in the public domain or under the CC0-1.0-Universal license, whichever is more permissive.