Typing: Builtins#
This module contains all used built-in type annotations.
- class tad_mctc.typing.builtin.IO[source]#
Generic base class for TextIO and BinaryIO.
This is an abstract, generic version of the return of open().
NOTE: This does not distinguish between the different possible classes (text vs. binary, read vs. write vs. read/write, append-only, unbuffered). The TextIO and BinaryIO subclasses below capture the distinctions between text vs. binary, which is pervasive in the interface; however we currently do not offer a way to track the other distinctions in the type system.
- tad_mctc.typing.builtin.NamedTuple(typename, fields=None, /, **kwargs)[source]#
Typed version of namedtuple.
Usage in Python versions >= 3.6:
class Employee(NamedTuple): name: str id: int
This is equivalent to:
Employee = collections.namedtuple('Employee', ['name', 'id'])
The resulting class has an extra __annotations__ attribute, giving a dict that maps field names to types. (The field names are also in the _fields attribute, which is part of the namedtuple API.) Alternative equivalent keyword syntax is also accepted:
Employee = NamedTuple('Employee', name=str, id=int)
In Python versions <= 3.5 use:
Employee = NamedTuple('Employee', [('name', str), ('id', int)])
- class tad_mctc.typing.builtin.Protocol[source]#
Base class for protocol classes.
Protocol classes are defined as:
class Proto(Protocol): def meth(self) -> int: ...
Such classes are primarily used with static type checkers that recognize structural subtyping (static duck-typing), for example:
class C: def meth(self) -> int: return 0 def func(x: Proto) -> int: return x.meth() func(C()) # Passes static type check
See PEP 544 for details. Protocol classes decorated with @typing.runtime_checkable act as simple-minded runtime protocols that check only the presence of given attributes, ignoring their type signatures. Protocol classes can be generic, they are defined as:
class GenProto(Protocol[T]): def meth(self) -> T: ...
- class tad_mctc.typing.builtin.TypeVar(name, *constraints, bound=None, covariant=False, contravariant=False)[source]#
Type variable.
Usage:
T = TypeVar('T') # Can be anything A = TypeVar('A', str, bytes) # Must be str or bytes
Type variables exist primarily for the benefit of static type checkers. They serve as the parameters for generic types as well as for generic function definitions. See class Generic for more information on generic types. Generic functions work as follows:
- def repeat(x: T, n: int) -> List[T]:
‘’’Return a list containing n references to x.’’’ return [x]*n
- def longest(x: A, y: A) -> A:
‘’’Return the longest of two strings.’’’ return x if len(x) >= len(y) else y
The latter example’s signature is essentially the overloading of (str, str) -> str and (bytes, bytes) -> bytes. Also note that if the arguments are instances of some subclass of str, the return type is still plain str.
At runtime, isinstance(x, T) and issubclass(C, T) will raise TypeError.
Type variables defined with covariant=True or contravariant=True can be used to declare covariant or contravariant generic types. See PEP 484 for more details. By default generic types are invariant in all type variables.
Type variables can be introspected. e.g.:
T.__name__ == ‘T’ T.__constraints__ == () T.__covariant__ == False T.__contravariant__ = False A.__constraints__ == (str, bytes)
Note that only type variables defined in global scope can be pickled.
- tad_mctc.typing.builtin.TypedDict(typename, fields=None, /, *, total=True, **kwargs)[source]#
A simple typed namespace. At runtime it is equivalent to a plain dict.
TypedDict creates a dictionary type that expects all of its instances to have a certain set of keys, where each key is associated with a value of a consistent type. This expectation is not checked at runtime but is only enforced by type checkers. Usage:
class Point2D(TypedDict): x: int y: int label: str a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
The type info can be accessed via the Point2D.__annotations__ dict, and the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets. TypedDict supports two additional equivalent forms:
Point2D = TypedDict('Point2D', x=int, y=int, label=str) Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
By default, all keys must be present in a TypedDict. It is possible to override this by specifying totality. Usage:
class point2D(TypedDict, total=False): x: int y: int
This means that a point2D TypedDict can have any of the keys omitted.A type checker is only expected to support a literal False or True as the value of the total argument. True is the default, and makes all items defined in the class body be required.
The class syntax is only supported in Python 3.6+, while two other syntax forms work for Python 2.7 and 3.2+
- tad_mctc.typing.builtin.overload(func)[source]#
Decorator for overloaded functions/methods.
In a stub file, place two or more stub definitions for the same function in a row, each decorated with @overload. For example:
@overload def utf8(value: None) -> None: … @overload def utf8(value: bytes) -> bytes: … @overload def utf8(value: str) -> bytes: …
In a non-stub file (i.e. a regular .py file), do the same but follow it with an implementation. The implementation should not be decorated with @overload. For example:
@overload def utf8(value: None) -> None: … @overload def utf8(value: bytes) -> bytes: … @overload def utf8(value: str) -> bytes: … def utf8(value):
# implementation goes here
- tad_mctc.typing.builtin.runtime_checkable(cls)[source]#
Mark a protocol class as a runtime protocol.
Such protocol can be used with isinstance() and issubclass(). Raise TypeError if applied to a non-protocol class. This allows a simple-minded structural check very similar to one trick ponies in collections.abc such as Iterable. For example:
@runtime_checkable class Closable(Protocol): def close(self): ... assert isinstance(open('/some/file'), Closable)
Warning: this will check only the presence of the required methods, not their type signatures!