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 utility for defining sentinel values, to be used in the stdlib and made publicly available as part of the stdlib.

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 or unpickled, due to a separate instance being created and thus comparisons using is failing.

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/or unpickling.
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 in 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, an implementation was written which meets all of these criteria (see Reference Implementation).

Specification

A new Sentinel class will be added to a new sentinels module. Its initializer will accept a single required argument, the name of the sentinel object, and three optional arguments: the repr of the object, its boolean value, and the name of its module:

>>> from sentinels import Sentinel
>>> NotGiven = Sentinel('NotGiven')
>>> NotGiven
<NotGiven>
>>> MISSING = Sentinel('MISSING', repr='mymodule.MISSING')
>>> MISSING
mymodule.MISSING
>>> MEGA = Sentinel('MEGA',
                    repr='<MEGA>',
                    bool_value=False,
                    module_name='mymodule')
<MEGA>

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 instances are truthy by default, unlike None. This parallels the default for arbitrary classes, as well as the boolean value of Ellipsis.

The names of sentinels are unique within each module. When calling Sentinel() in a module where a sentinel with that name was already defined, the existing sentinel with that name will be returned. Sentinels with the same name in different modules will be distinct from each other.

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

The module_name optional argument should normally not need to be supplied, as Sentinel() will usually be able to recognize the module in which it was called. module_name should be supplied only in unusual cases when this automatic recognition does not work as intended, such as perhaps when using Jython or IronPython. This parallels the designs of Enum and namedtuple. For more details, see PEP 435.

The Sentinel class may not be sub-classed, to avoid overly-clever uses based on it, such as attempts to use it as a base for implementing singletons. It is considered important that the addition of Sentinel to the stdlib should add minimal complexity.

Ordering comparisons are undefined for sentinel objects.

from sentinels import Sentinel

MISSING = Sentinel('MISSING')

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

from sentinels import Sentinel
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)

Backwards Compatibility

While not breaking existing code, adding a new “sentinels” stdlib module could cause some confusion with regard to existing modules named “sentinels”, and specifically with the “sentinels” package on PyPI.

The existing “sentinels” package on PyPI [10] appears to be abandoned, with the latest release being made on Aug. 2016. Therefore, using this name for a new stdlib module seems reasonable.

If and when this PEP is accepted, it may be worth verifying if this has indeed been abandoned, and if so asking to transfer ownership to the CPython maintainers to reduce the potential for confusion with the new stdlib module.

How to Teach This

The normal types of documentation of new stdlib modules and features, namely doc-strings, module docs and a section in “What’s New”, should suffice.

Security Implications

This proposal should have no security implications.

Reference Implementation

The reference implementation is found in a dedicated GitHub repo [7]. A simplified version follows:

_registry = {}

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

    def __new__(cls, name, repr=None, bool_value=True, module_name=None):
        name = str(name)
        repr = str(repr) if repr else f'<{name.split(".")[-1]}>'
        bool_value = bool(bool_value)
        if module_name is None:
            try:
                module_name = \
                    sys._getframe(1).f_globals.get('__name__', '__main__')
            except (AttributeError, ValueError):
                module_name = __name__

        registry_key = f'{module_name}-{name}'

        sentinel = _registry.get(registry_key, None)
        if sentinel is not None:
            return sentinel

        sentinel = super().__new__(cls)
        sentinel._name = name
        sentinel._repr = repr
        sentinel._bool_value = bool_value
        sentinel._module_name = module_name

        return _registry.setdefault(registry_key, sentinel)

    def __repr__(self):
        return self._repr

    def __bool__(self):
        return self._bool_value

    def __reduce__(self):
        return (
            self.__class__,
            (
                self._name,
                self._repr,
                self._module_name,
            ),
        )

Rejected Ideas

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

@sentinel(repr='<NotGiven>')
class NotGivenType: pass
NotGiven = NotGivenType()

class NotGiven: pass

class NotGiven(metaclass=SentinelMeta): pass

@Sentinel
class NotGiven: pass

Additional Notes

• This PEP and the initial implementation are drafted in a dedicated GitHub repo [7].
• For sentinels defined in a class scope, to avoid potential name clashes, one should use the fully-qualified name of the variable in the module. Only the part of the name after the last period will be used for the default repr. For example:

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

• One should be careful when creating sentinels in a function or method, since sentinels with the same name created by code in the same module will be identical. If distinct sentinel objects are needed, make sure to use distinct names.
• There is no single desirable value for the “truthiness” of sentinels, i.e. their boolean value. It is sometimes useful for the boolean value to be True, and sometimes False. Of the built-in sentinels in Python, None evaluates to False, while Ellipsis (a.k.a. ...) evaluates to True. The desire for this to be set as needed came up in discussions as well.
• 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.

Open Issues

• Is adding a new stdlib module the right way to go? I could not find any existing module which seems like a logical place for this. However, adding new stdlib modules should be done judiciously, so perhaps choosing an existing module would be preferable even if it is not a perfect fit?

Footnotes

Copyright

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