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from __future__ import annotations
import numbers
import typing
import attr
from asdf._jsonschema.exceptions import UndefinedTypeCheck
def _as_dict(init):
init = init or {}
return dict(init)
def is_array(checker, instance):
return isinstance(instance, list)
def is_bool(checker, instance):
return isinstance(instance, bool)
def is_integer(checker, instance):
# bool inherits from int, so ensure bools aren't reported as ints
if isinstance(instance, bool):
return False
return isinstance(instance, int)
def is_null(checker, instance):
return instance is None
def is_number(checker, instance):
# bool inherits from int, so ensure bools aren't reported as ints
if isinstance(instance, bool):
return False
return isinstance(instance, numbers.Number)
def is_object(checker, instance):
return isinstance(instance, dict)
def is_string(checker, instance):
return isinstance(instance, str)
def is_any(checker, instance):
return True
@attr.s(frozen=True, repr=False)
class TypeChecker:
"""
A :kw:`type` property checker.
A `TypeChecker` performs type checking for a `Validator`, converting
between the defined JSON Schema types and some associated Python types or
objects.
Modifying the behavior just mentioned by redefining which Python objects
are considered to be of which JSON Schema types can be done using
`TypeChecker.redefine` or `TypeChecker.redefine_many`, and types can be
removed via `TypeChecker.remove`. Each of these return a new `TypeChecker`.
Arguments:
type_checkers:
The initial mapping of types to their checking functions.
"""
_type_checkers = attr.ib(default={}, converter=_as_dict)
def __repr__(self):
types = ", ".join(repr(k) for k in sorted(self._type_checkers))
return f"<{self.__class__.__name__} types={{{types}}}>"
def is_type(self, instance, type: str) -> bool:
"""
Check if the instance is of the appropriate type.
Arguments:
instance:
The instance to check
type:
The name of the type that is expected.
Raises:
`asdf._jsonschema.exceptions.UndefinedTypeCheck`:
if ``type`` is unknown to this object.
"""
try:
fn = self._type_checkers[type]
except KeyError:
raise UndefinedTypeCheck(type) from None
return fn(self, instance)
def redefine(self, type: str, fn) -> "TypeChecker":
"""
Produce a new checker with the given type redefined.
Arguments:
type:
The name of the type to check.
fn (collections.abc.Callable):
A callable taking exactly two parameters - the type
checker calling the function and the instance to check.
The function should return true if instance is of this
type and false otherwise.
"""
return self.redefine_many({type: fn})
def redefine_many(self, definitions=()) -> "TypeChecker":
"""
Produce a new checker with the given types redefined.
Arguments:
definitions (dict):
A dictionary mapping types to their checking functions.
"""
type_checkers = self._type_checkers.copy()
type_checkers.update(definitions)
return attr.evolve(self, type_checkers=type_checkers)
def remove(self, *types) -> "TypeChecker":
"""
Produce a new checker with the given types forgotten.
Arguments:
types:
the names of the types to remove.
Raises:
`asdf._jsonschema.exceptions.UndefinedTypeCheck`:
if any given type is unknown to this object
"""
type_checkers = self._type_checkers.copy()
for each in types:
try:
del type_checkers[each]
except KeyError:
raise UndefinedTypeCheck(each)
return attr.evolve(self, type_checkers=type_checkers)
draft3_type_checker = TypeChecker(
{
"any": is_any,
"array": is_array,
"boolean": is_bool,
"integer": is_integer,
"object": is_object,
"null": is_null,
"number": is_number,
"string": is_string,
},
)
draft4_type_checker = draft3_type_checker.remove("any")
draft6_type_checker = draft4_type_checker.redefine(
"integer",
lambda checker, instance: (
is_integer(checker, instance)
or isinstance(instance, float) and instance.is_integer()
),
)
draft7_type_checker = draft6_type_checker
draft201909_type_checker = draft7_type_checker
draft202012_type_checker = draft201909_type_checker
|
