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.

MISSING = sentinel('MISSING')

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

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)

* ``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.

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

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

@sentinel
class NotGivenType: pass
NotGiven = NotGivenType()

class NotGiven: pass

class NotGiven(metaclass=SentinelMeta): pass

@Sentinel
class NotGiven: pass

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.