pythonnative/src/pythonnative/sdk/types.py at refs/heads/main · pythonnative/pythonnative · GitHub

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"""Portable Python type descriptions and lossless native value conversion.

Only declared records are reconstructed. Reading a manifest never imports an

extension; resolving a record happens when application code consumes a value.

"""

from __future__ import annotations

import collections.abc

import dataclasses

import enum

import importlib

import inspect

import math

import types

import typing

from dataclasses import dataclass

from typing import Any, Mapping

@dataclass(frozen=True)

class NativeField:

"""Native behavior attached with ``Annotated[T, NativeField(...)]``."""

invalidates_layout: bool = False

recreate: bool = False

animated: bool = False

platforms: tuple[str, ...] = ("ios", "android", "web")

description: str = ""

python_only: bool = False

_record_types: dict[str, type] = {}

def _record_name(annotation: type) -> str:

name = f"{annotation.__module__}:{annotation.__qualname__}"

_record_types[name] = annotation

return name

def resolve_type(name: str) -> type:

"""Resolve a declared Python record lazily, after its package is loaded."""

if name not in _record_types:

module, separator, qualname = name.partition(":")

if not separator or "<locals>" in qualname:

raise TypeError(f"Native record {name!r} must be declared at module scope")

value: Any = importlib.import_module(module)

for part in qualname.split("."):

if not part.isidentifier():

raise TypeError(f"Invalid native record name {name!r}")

value = getattr(value, part)

if not isinstance(value, type) or not (

dataclasses.is_dataclass(value) or typing.is_typeddict(value) or issubclass(value, enum.Enum)

raise TypeError(f"{name} isn't a native record or enum")

_record_types[name] = value

return _record_types[name]

def type_schema(annotation: Any, *, _parents: tuple[type, ...] = ()) -> dict[str, Any]:

"""Compile supported annotations; reject unsupported or recursive types."""

origin, args = typing.get_origin(annotation), typing.get_args(annotation)

if annotation is Any:

return {"type": "json"}

if origin is typing.Annotated:

metadata = next((item for item in args[1:] if isinstance(item, NativeField)), None)

result = {} if metadata is not None and metadata.python_only else type_schema(args[0], _parents=_parents)

if metadata is not None:

result["native"] = dataclasses.asdict(metadata)

return result

if origin in (typing.Required, typing.NotRequired):

return type_schema(args[0], _parents=_parents)

if origin in (typing.Union, types.UnionType):

alternatives: list[dict[str, Any]] = []

for arg in args:

candidate = type_schema(arg, _parents=_parents)

# Wire-scalar records (see ``__native_schema__``) can collapse a

# union like ``str | Asset`` into one alternative.

if candidate not in alternatives:

alternatives.append(candidate)

return alternatives[0] if len(alternatives) == 1 else {"anyOf": alternatives}

if inspect.isclass(annotation) and callable(getattr(annotation, "__native_schema__", None)):

# A Python value type whose wire form is simpler than its fields

# (``Asset`` travels as its ``asset://`` URI string).

return dict(getattr(annotation, "__native_schema__")())

if origin is typing.Literal:

values = [encode_value(arg) for arg in args]

if not all(value is None or type(value) in (str, int, bool, float) for value in values):

raise TypeError("Native literals must be JSON scalars")

return {"enum": values}

if annotation is None or annotation is type(None):

return {"type": "null"}

if annotation in (str, bool, int, float):

return {"type": {str: "string", bool: "boolean", int: "integer", float: "number"}[annotation]}

if origin in (list, tuple, set, frozenset, collections.abc.Sequence) or annotation in (list, tuple, set, frozenset):

container = origin or annotation

result = {"type": "array"}

if container is tuple and args and args[-1] is not Ellipsis:

result["prefixItems"] = [type_schema(arg, _parents=_parents) for arg in args]

else:

result["items"] = type_schema(args[0], _parents=_parents) if args else {"type": "json"}

if container in (tuple, set, frozenset):

result["python_container"] = container.__name__

return result

if origin in (dict, collections.abc.Mapping) or annotation is dict:

if args and args[0] is not str:

raise TypeError("Native mappings require str keys")

return {

"type": "object",

"additionalProperties": type_schema(args[1], _parents=_parents) if args else {"type": "json"},

}

if origin in (typing.Callable, collections.abc.Callable):

return {

"type": "event",

"arguments": (

[type_schema(arg, _parents=_parents) for arg in args[0]] if args and args[0] is not Ellipsis else None

}

if inspect.isclass(annotation) and issubclass(annotation, enum.Enum):

return {

"enum": [encode_value(value.value) for value in annotation],

"python_type": _record_name(annotation),

"python_kind": "enum",

}

if dataclasses.is_dataclass(annotation) or typing.is_typeddict(annotation):

if annotation in _parents:

raise TypeError(f"Recursive native record {annotation.__name__} isn't supported")

hints = typing.get_type_hints(annotation, include_extras=True)

for name in hints:

if not name.isidentifier():

raise TypeError(f"Native record field {name!r} must use a Python identifier")

defaults = {}

if typing.is_typeddict(annotation):

required = set(annotation.__required_keys__)

# Postponed annotations can make __required_keys__ incomplete.

for key, hint in hints.items():

if typing.get_origin(hint) is typing.NotRequired:

required.discard(key)

elif typing.get_origin(hint) is typing.Required:

required.add(key)

else:

required = set()

hints = {field.name: hints[field.name] for field in dataclasses.fields(annotation) if field.init}

for field in dataclasses.fields(annotation):

if not field.init:

hints.pop(field.name, None)

continue

if field.default is not dataclasses.MISSING:

defaults[field.name] = encode_value(field.default)

elif field.default_factory is not dataclasses.MISSING:

defaults[field.name] = encode_value(field.default_factory())

else:

required.add(field.name)

return {

"type": "object",

"properties": {name: type_schema(value, _parents=(*_parents, annotation)) for name, value in hints.items()},

"required": sorted(required),

"defaults": defaults,

"additionalProperties": False,

"python_type": _record_name(annotation),

"python_kind": "typeddict" if typing.is_typeddict(annotation) else "dataclass",

}

raise TypeError(f"Unsupported native annotation {annotation!r}; use a dataclass, typed record, or JSON value")

def encode_value(value: Any, schema: Mapping[str, Any] | None = None, path: str = "value") -> Any:

"""Encode records, enums, and collections without dropping values or keys."""

if schema is not None:

validate(value, schema, path)

if isinstance(value, enum.Enum):

return encode_value(value.value, path=path)

if callable(getattr(value, "__native_value__", None)) and not isinstance(value, type):

return encode_value(value.__native_value__(), path=path)

if value is None or type(value) in (str, bool, int):

if type(value) is int and abs(value) > 2**53 - 1:

raise TypeError(f"{path} exceeds the portable integer range")

return value

if type(value) is float:

if not math.isfinite(value):

raise TypeError(f"{path} must be finite")

return value

if dataclasses.is_dataclass(value) and not isinstance(value, type):

return {

field.name: encode_value(getattr(value, field.name), path=f"{path}.{field.name}")

for field in dataclasses.fields(value)

if field.init

}

if isinstance(value, Mapping):

if not all(isinstance(key, str) for key in value):

raise TypeError(f"{path} requires string keys")

return {key: encode_value(item, path=f"{path}.{key}") for key, item in value.items()}

if isinstance(value, (collections.abc.Sequence, set, frozenset)) and not isinstance(value, (str, bytes, bytearray)):

items = [encode_value(item, path=f"{path}[{index}]") for index, item in enumerate(value)]

if isinstance(value, (set, frozenset)):

import json

items.sort(key=lambda item: json.dumps(item, sort_keys=True))

return items

raise TypeError(f"{path}: {type(value).__name__} isn't a native value")

def decode_value(value: Any, schema: Mapping[str, Any], path: str = "value") -> Any:

"""Validate a result and reconstruct its declared Python value types."""

validate(value, schema, path)

if "anyOf" in schema:

for alternative in schema["anyOf"]:

try:

validate(value, alternative, path)

except TypeError:

continue

return decode_value(value, alternative, path)

if schema.get("python_kind") == "enum":

return resolve_type(schema["python_type"])(value.value if isinstance(value, enum.Enum) else value)

if schema.get("type") == "object":

values = encode_value(value) if dataclasses.is_dataclass(value) else value

fields = schema.get("properties", {})

defaults = schema.get("defaults", {})

decoded = {

key: decode_value(item, fields.get(key, schema.get("additionalProperties", {})), f"{path}.{key}")

for key, item in {**defaults, **values}.items()

}

if schema.get("python_kind") == "dataclass":

return resolve_type(schema["python_type"])(**decoded)

return decoded

if schema.get("type") == "array":

prefix = schema.get("prefixItems")

items = [

decode_value(item, prefix[index] if prefix is not None else schema.get("items", {}), f"{path}[{index}]")

for index, item in enumerate(value)

]

constructor = {"tuple": tuple, "set": set, "frozenset": frozenset}.get(

str(schema.get("python_container")), list

)

return constructor(items)

if schema.get("type") == "integer":

return int(value)

if schema.get("type") == "number":

return float(value)

return value

def validate(value: Any, schema: Mapping[str, Any], path: str = "value") -> None:

"""Validate declared values without coercion or ambiguous comparisons."""

if schema.get("native", {}).get("python_only"):

return

if callable(getattr(value, "__native_value__", None)) and not isinstance(value, type):

value = value.__native_value__()

if "anyOf" in schema:

for alternative in schema["anyOf"]:

try:

validate(value, alternative, path)

return

except TypeError:

pass

raise TypeError(f"{path} does not match its annotation")

if "enum" in schema:

candidate = value.value if isinstance(value, enum.Enum) else value

if not any(

(type(candidate) is type(item) or type(candidate) in (int, float) and type(item) in (int, float))

and candidate == item

for item in schema["enum"]

raise TypeError(f"{path} must be one of {schema['enum']!r}")

kind = schema.get("type")

checks = {

"null": lambda: value is None,

"string": lambda: isinstance(value, str),

"boolean": lambda: type(value) is bool,

"integer": lambda: type(value) in (int, float) and abs(value) <= 2**53 - 1 and value == int(value),

"number": lambda: (type(value) is int and abs(value) <= 2**53 - 1)

or (type(value) is float and math.isfinite(value)),

"array": lambda: isinstance(value, (collections.abc.Sequence, set, frozenset))

and not isinstance(value, (str, bytes, bytearray)),

"object": lambda: isinstance(value, Mapping) or dataclasses.is_dataclass(value) and not isinstance(value, type),

"event": lambda: callable(value) or type(value) is bool,

}

if kind in checks and not checks[kind]():

raise TypeError(f"{path} must be {kind}, received {type(value).__name__}")

if kind == "json":

encode_value(value, path=path)

if kind == "array":

prefix = schema.get("prefixItems")

if prefix is not None and len(value) != len(prefix):

raise TypeError(f"{path} requires {len(prefix)} tuple items")

for index, item in enumerate(value):

validate(item, prefix[index] if prefix is not None else schema.get("items", {}), f"{path}[{index}]")

if kind == "object":

values = (

{f.name: getattr(value, f.name) for f in dataclasses.fields(value) if f.init}

if dataclasses.is_dataclass(value)

else value

)

missing = set(schema.get("required", ())) - values.keys()

if missing:

raise TypeError(f"{path} requires {', '.join(sorted(missing))}")

for name, item in values.items():

if not isinstance(name, str):

raise TypeError(f"{path} requires string keys")

nested = schema.get("properties", {}).get(name, schema.get("additionalProperties", {}))

if nested is False:

raise TypeError(f"Unknown {path}.{name}")

validate(item, nested if isinstance(nested, Mapping) else {}, f"{path}.{name}")

pythonnative/src/pythonnative/sdk/types.py at refs/heads/main · pythonnative/pythonnative · GitHub

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