iolabs-common (shared config layer) c080353: AI3D-379 Pydantic config layer (ConfigModel, load_config), deprecate hand-rolled coercion; 0.8.0

Importance #1: src/iolabs/common/config_model.py @@ -0,0 +1,394 @@

Base model: extra=forbid, frozen, validate_default; the before-validator routes every field through the legacy coercion matrix.

	1	"""Pydantic-v2 config layer for the pipeline packages.
	2
	3	`ConfigModel` is the base class every fleet package derives its config models
	4	from. It keeps the accepted-input matrix of the hand-rolled coercion helpers in
	5	:mod:`iolabs.common.config_loader` (see
	6	:func:`iolabs.common.config_loader.coerce_to_field_type` for the spec) while
	7	letting package authors write plain ``x: int`` / ``y: float`` / ``z: bool`` /
	8	``s: str`` fields; `Literal`, sequences, and nested models are validated by
	9	pydantic itself.
	10
	11	Canonical package pattern::
	12
	13	from collections.abc import Mapping
	14	from pathlib import Path
	15	from typing import Any, Literal
	16
	17	from iolabs.common import config_loader
	18
	19
	20	class FooGroundConfig(config_loader.ConfigModel):
	21	cell_m: float = 0.5
	22	enabled: bool = True
	23
	24
	25	class FooConfig(config_loader.ConfigModel):
	26	mode: Literal["fast", "exact"] = "fast"
	27	ground: FooGroundConfig = FooGroundConfig()
	28
	29
	30	class FooConfigError(config_loader.ConfigError):
	31	\"\"\"Raised for an invalid foo config.\"\"\"
	32
	33
	34	def build_foo_config(
	35	overrides: Mapping[str, Any] \| None = None,
	36	config_path: str \| Path \| None = None,
	37	) -> dict[str, Any]:
	38	return config_loader.load_config(
	39	FooConfig,
	40	package="iolabs_foo",
	41	filename="default_config.json",
	42	overrides=overrides,
	43	config_path=config_path,
	44	context="foo config",
	45	error_cls=FooConfigError,
	46	).model_dump()
	47
	48	Unknown keys are rejected (``extra="forbid"``) with the same message shape as
	49	:func:`iolabs.common.config_loader.validate_allowed_keys`; instances are frozen,
	50	so no field can be rebound after construction. Freezing is shallow, as in
	51	pydantic itself: a ``list``-valued field is still a mutable list, so prefer
	52	``tuple`` for sequence fields that must not change.
	53	"""
	54
	55	from __future__ import annotations
	56
	57	import json
	58	import logging
	59	from collections.abc import Mapping
	60	from pathlib import Path
	61	from typing import Any, TypeVar, get_args
	62
	63	import pydantic
	64	from pydantic import fields as pydantic_fields
	65
	66	from iolabs.common import config_loader
	67
	68	logger = logging.getLogger(__name__)
	69
	70	_M = TypeVar("_M", bound="ConfigModel")
	71
	72	_VALUE_ERROR_PREFIX = "Value error, "
	73
	74	_MODEL_REGISTRY: dict[str, type[ConfigModel] \| None] = {}
	75
	76
	77	class ConfigModel(pydantic.BaseModel):
	78	"""Frozen, extra-forbidding base model with fleet scalar coercion.
	79
	80	Every field is passed through the accepted-input matrix of
	81	:func:`iolabs.common.config_loader.coerce_to_field_type` before pydantic
	82	validates it, so ``"1e3"`` reaches an ``int`` field as ``1000``, ``"on"``
	83	reaches a ``bool`` field as ``True``, and ``True`` is rejected for an
	84	``int`` field instead of becoming ``1``.
	85	"""
	86
	87	model_config = pydantic.ConfigDict(
	88	extra="forbid",
	89	frozen=True,
	90	validate_default=True,
	91	strict=False,
	92	arbitrary_types_allowed=False,
	93	)
	94
	95	def __init_subclass__(cls, **kwargs: Any) -> None:
	96	"""Register the subclass so its error title can be resolved back to it."""
	97	super().__init_subclass__(**kwargs)
	98	_register_model(cls)
	99
	100	@pydantic.field_validator("*", mode="before")
	101	@classmethod
	102	def _coerce_fleet_scalars(cls, value: Any, info: pydantic.ValidationInfo) -> Any:
	103	"""Coerce a raw JSON/CLI value to the field's declared annotation."""
	104	field = cls.model_fields.get(info.field_name or "")
	105	if field is None or field.annotation is None:
	106	return value
	107	return config_loader.coerce_config_value(
	108	info.field_name or "", value, field.annotation
	109	)
	110
	111
	112	def _register_model(model_cls: type[ConfigModel]) -> None:
	113	"""Record model_cls under its name, flagging same-name classes ambiguous."""
	114	name = model_cls.__name__
	115	previous = _MODEL_REGISTRY.get(name, model_cls)
	116	same_origin = previous is not None and (previous.__module__, previous.__qualname__) == (
	117	model_cls.__module__,
	118	model_cls.__qualname__,
	119	)
	120	_MODEL_REGISTRY[name] = model_cls if same_origin else None
	121
	122
	123	def _model_from_title(title: str) -> type[ConfigModel] \| None:
	124	"""Return the `ConfigModel` a validation error title names, when unambiguous."""
	125	return _MODEL_REGISTRY.get(title)
	126
	127
	128	def validate_config(
	129	model_cls: type[_M],
	130	raw: Mapping[str, Any],
	131	*,
	132	context: str,
	133	error_cls: type[ValueError] = config_loader.ConfigError,
	134	) -> _M:
	135	"""Validate a raw mapping into model_cls, wrapping pydantic errors.
	136
	137	Args:
	138	model_cls: The `ConfigModel` subclass to build.
	139	raw: The merged config mapping (packaged defaults plus overrides).
	140	context: Human-readable config name used in error messages, e.g.
	141	``"foo config"``.
	142	error_cls: Exception class raised for unknown keys and bad values.
	143
	144	Returns:
	145	A validated, frozen instance of model_cls.
	146
	147	Raises:
	148	error_cls: raw holds an unknown key, misses a required key, or holds
	149	a value that is not valid for its declared field type.
	150	"""
	151	try:
	152	return model_cls.model_validate(dict(raw))
	153	except pydantic.ValidationError as exc:
	154	raise error_cls(
	155	format_validation_error(exc, context=context, model_cls=model_cls)
	156	) from exc
	157
	158
	159	def load_config(
	160	model_cls: type[_M],
	161	*,
	162	package: str,
	163	filename: str,
	164	overrides: Mapping[str, Any] \| None = None,
	165	config_path: str \| Path \| None = None,
	166	context: str,
	167	error_cls: type[ValueError] = config_loader.ConfigError,
	168	) -> _M:
	169	"""Load, merge and validate a packaged JSON config into model_cls.
	170
	171	The packaged default JSON is read from package/filename, or from
	172	config_path when that is given (the file then replaces the packaged
	173	defaults rather than extending them). overrides is deep-merged on top by
	174	:func:`iolabs.common.config_loader.deep_merge_dicts`, and the result is
	175	validated by :func:`validate_config`.
	176
	177	Args:
	178	model_cls: The `ConfigModel` subclass to build.
	179	package: Import package holding the default JSON, e.g. ``"iolabs_foo"``.
	180	filename: File name of the packaged JSON, e.g. ``"default_config.json"``.
	181	overrides: Mapping merged onto the defaults, e.g. the result of
	182	:func:`iolabs.common.config_loader.parse_set_overrides`.
	183	config_path: Path to a JSON file used instead of the packaged defaults.
	184	context: Human-readable config name used in error messages.
	185	error_cls: Exception class raised for unreadable JSON, unknown keys and
	186	bad values.
	187
	188	Returns:
	189	A validated, frozen instance of model_cls.
	190
	191	Raises:
	192	error_cls: The JSON is malformed, or the merged config is invalid.
	193	OSError: The config file could not be read.
	194	"""
	195	if config_path is not None:
	196	raw = _load_json_file(Path(config_path), error_cls=error_cls)
	197	logger.debug("Loaded %s from %s", context, config_path)
	198	else:
	199	raw = _load_packaged(package, filename, error_cls=error_cls)
	200	logger.debug("Loaded %s defaults from %s:%s", context, package, filename)
	201	if overrides:
	202	raw = config_loader.deep_merge_dicts(raw, dict(overrides))
	203	return validate_config(model_cls, raw, context=context, error_cls=error_cls)
	204
	205
	206	def format_validation_error(
	207	exc: pydantic.ValidationError,
	208	*,
	209	context: str,
	210	model_cls: type[pydantic.BaseModel] \| None = None,
	211	) -> str:
	212	"""Render a pydantic `ValidationError` as a fleet-style config message.
	213
	214	Unknown keys are grouped per section and reported as
	215	``"Unknown {context} key(s): a, b. Allowed keys: ..."``; the section path is
	216	dotted onto context (``"{context}.section"``). Value errors keep the
	217	``"Invalid <type> for '<dotted.field>': <value> ..."`` shape of the legacy
	218	coercion helpers.
	219
	220	Args:
	221	exc: The pydantic validation error.
	222	context: Human-readable config name used as the message prefix.
	223	model_cls: The validated model, used to list the allowed keys of the
	224	offending section. Defaults to the `ConfigModel` named by
	225	``exc.title``; allowed-key lists are omitted when that name is
	226	unknown or shared by several models.
	227
	228	Returns:
	229	A newline-joined message covering every error in exc.
	230	"""
	231	if model_cls is None:
	232	model_cls = _model_from_title(exc.title)
	233	unknown: dict[tuple[Any, ...], list[str]] = {}
	234	lines: list[str] = []
	235	for error in exc.errors():
	236	loc = tuple(error["loc"])
	237	if error["type"] == "extra_forbidden" and loc:
	238	unknown.setdefault(loc[:-1], []).append(str(loc[-1]))
	239	else:
	240	lines.append(_format_single_error(error, context=context))
	241	unknown_lines = [
	242	_format_unknown_keys(prefix, keys, context=context, model_cls=model_cls)
	243	for prefix, keys in sorted(unknown.items(), key=lambda item: [str(p) for p in item[0]])
	244	]
	245	return "\n".join(unknown_lines + lines)
	246
	247
	248	def _format_unknown_keys(
	249	prefix: tuple[Any, ...],
	250	keys: list[str],
	251	*,
	252	context: str,
	253	model_cls: type[pydantic.BaseModel] \| None,
	254	) -> str:
	255	"""Return the ``Unknown ... key(s)`` line for one section."""
	256	node = ".".join([context, *(str(part) for part in prefix)])
	257	message = f"Unknown {node} key(s): {', '.join(sorted(keys))}."
	258	allowed = _allowed_keys(model_cls, prefix)
	259	if allowed:
	260	message = f"{message} Allowed keys: {', '.join(sorted(allowed))}"
	261	return message
	262
	263
	264	def _format_single_error(error: Mapping[str, Any], *, context: str) -> str:
	265	"""Return one non-``extra_forbidden`` error as a readable line."""
	266	loc = tuple(error["loc"])
	267	dotted = ".".join(str(part) for part in loc)
	268	message = str(error["msg"])
	269	if error["type"] == "missing":
	270	return f"Missing required {context} key: '{dotted}'"
	271	if message.startswith(_VALUE_ERROR_PREFIX):
	272	message = message[len(_VALUE_ERROR_PREFIX):]
	273	rewritten = _rewrite_field_name(message, loc)
	274	if rewritten is not None:
	275	return rewritten
	276	return f"Invalid value for '{dotted}': {error.get('input')!r}. {message}."
	277
	278
	279	def _rewrite_field_name(message: str, loc: tuple[Any, ...]) -> str \| None:
	280	"""Replace the local field name of a coercion message with its dotted path.
	281
	282	Args:
	283	message: A coercion message such as ``"Invalid int for 'x': 3.7 ..."``.
	284	loc: The pydantic error location of the offending field.
	285
	286	Returns:
	287	The message with the dotted path substituted, or ``None`` when
	288	message does not have the coercion shape.
	289	"""
	290	head, _, tail = message.partition(" for '")
	291	name, quote, rest = tail.partition("': ")
	292	if not head.startswith("Invalid ") or not quote or "'" in name:
	293	return None
	294	dotted = ".".join([*(str(part) for part in loc[:-1]), name])
	295	return f"{head} for '{dotted}': {rest}"
	296
	297
	298	def _allowed_keys(
	299	model_cls: type[pydantic.BaseModel] \| None,
	300	loc: tuple[Any, ...],
	301	) -> list[str]:
	302	"""Return the keys accepted by the model reached by loc, if resolvable.
	303
	304	An aliased field is listed under its alias, i.e. under the key the config
	305	file must actually use, plus its field name when the model also populates
	306	by name.
	307	"""
	308	current = _model_at_loc(model_cls, loc)
	309	if current is None:
	310	return []
	311	by_name = bool(
	312	current.model_config.get("populate_by_name")
	313	or current.model_config.get("validate_by_name")
	314	)
	315	keys: list[str] = []
	316	for name, field in current.model_fields.items():
	317	alias = _validation_alias(field)
	318	if alias is None:
	319	keys.append(name)
	320	continue
	321	keys.append(alias)
	322	if by_name:
	323	keys.append(name)
	324	return keys
	325
	326
	327	def _validation_alias(field: pydantic_fields.FieldInfo) -> str \| None:
	328	"""Return the single string alias field is validated under, if any."""
	329	alias = field.validation_alias if field.validation_alias is not None else field.alias
	330	return alias if isinstance(alias, str) else None
	331
	332
	333	def _model_at_loc(
	334	model_cls: type[pydantic.BaseModel] \| None,
	335	loc: tuple[Any, ...],
	336	) -> type[pydantic.BaseModel] \| None:
	337	"""Walk loc from model_cls down to the model owning that location."""
	338	current = model_cls
	339	for part in loc:
	340	if current is None:
	341	return None
	342	if isinstance(part, int):
	343	continue
	344	field = _field_by_key(current, str(part))
	345	current = _unwrap_model(field.annotation) if field is not None else None
	346	return current
	347
	348
	349	def _field_by_key(
	350	model_cls: type[pydantic.BaseModel],
	351	key: str,
	352	) -> pydantic_fields.FieldInfo \| None:
	353	"""Return the field of model_cls addressed by key (alias or name)."""
	354	for name, field in model_cls.model_fields.items():
	355	if key in (_validation_alias(field), name):
	356	return field
	357	return None
	358
	359
	360	def _unwrap_model(annotation: Any) -> type[pydantic.BaseModel] \| None:
	361	"""Return the first `BaseModel` subclass inside annotation, if any."""
	362	if isinstance(annotation, type) and issubclass(annotation, pydantic.BaseModel):
	363	return annotation
	364	for arg in get_args(annotation):
	365	found = _unwrap_model(arg)
	366	if found is not None:
	367	return found
	368	return None
	369
	370
	371	def _load_packaged(package: str, filename: str, *, error_cls: type[ValueError]) -> dict[str, Any]:
	372	"""Load the packaged default JSON, wrapping decode errors in error_cls."""
	373	try:
	374	loaded = config_loader.load_packaged_json(package, filename)
	375	except json.JSONDecodeError as exc:
	376	raise error_cls(f"Invalid JSON in packaged config {package}:{filename}: {exc}") from exc
	377	if not isinstance(loaded, dict):
	378	raise error_cls(
	379	f"Packaged config {package}:{filename} must hold a JSON object, "
	380	f"got {type(loaded).__name__}"
	381	)
	382	return loaded
	383
	384
	385	def _load_json_file(path: Path, *, error_cls: type[ValueError]) -> dict[str, Any]:
	386	"""Load a JSON config file, wrapping decode errors in error_cls."""
	387	try:
	388	with path.open("r", encoding="utf-8") as handle:
	389	loaded = json.load(handle)
	390	except json.JSONDecodeError as exc:
	391	raise error_cls(f"Invalid JSON in config file {path}: {exc}") from exc
	392	if not isinstance(loaded, dict):
	393	raise error_cls(f"Config file {path} must hold a JSON object, got {type(loaded).__name__}")
	394	return loaded
0

Importance #2: src/iolabs/common/config_loader.py @@ -227,29 +292,34 @@

       tokens ``1/true/yes/on`` and ``0/false/no/off``. Anything else raises, so
       typos such as ``"flase"`` are rejected instead of read as ``False``.
     * ``int``: accepts ints, integral floats (``3.0``) and numeric strings
       including exponent form (``"1e3"`` -> ``1000``). Non-integral values
-      (``3.7``) and bools are rejected rather than truncated.
+      (``3.7``), bools and non-numeric types (``bytes``, ``None``, ...) are
+      rejected rather than truncated or re-parsed.
     * ``float``: accepts ints, floats and numeric strings (including ``"nan"``
       and ``"inf"``: finiteness is the caller's domain check, not this one).
-      ``bool`` is rejected, as for ``int``; conversion errors are wrapped in
+      ``bool`` and non-numeric types (``bytes``, ``None``, ...) are rejected,
-      *error_cls*.
+      as for ``int``; conversion errors are wrapped in *error_cls*.
     * ``str``: accepts ``str`` only.
     * ``X | None`` / ``Optional[X]``: ``None`` passes through, otherwise the
       value is coerced to ``X``. Unions of two or more non-``None`` types pass
       through unchanged.
     * ``tuple[...]`` / ``list[...]``: accepts a list or tuple (never a string or
       mapping), coercing each item to the declared item type. Fixed-length
       tuple annotations also check the item count.
-    * ``Literal[...]``: the value must be one of the literal options.
+    * ``Literal[...]``: the value must be one of the literal options; an
+      ``enum`` option also matches its plain value (``"fast"`` for
+      ``Mode.FAST``) and is returned as the member.
     * A nested dataclass type: a mapping value is built into that dataclass by
       :func:`dataclass_from_mapping` (unknown keys rejected, inner values
       coerced); a value that is already an instance passes through.
     Any other declared type (``dict``, ``Any``, an unresolved string
     annotation, a union of two or more non-``None`` types, ...) returns
     *value* unchanged.
+    Deprecated: declare a `ConfigModel` field and let it apply the same matrix.
     Args:
         name: Field name, used only in error messages.
         value: The raw value from JSON or a parsed ``--set`` override.
         declared: The field's declared type (``dataclasses.Field.type`` or a

Importance #3: src/iolabs/common/config_loader.py @@ -332,29 +431,30 @@

             raise error_cls(f"Invalid int for '{name}': {value!r}.") from exc
         if not as_float.is_integer():
             raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
         return int(as_float)
-    try:
+    if isinstance(value, numbers.Real):
         as_float = float(value)
-    except (TypeError, ValueError) as exc:
+        if not as_float.is_integer():
-        raise error_cls(
+            raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
-            f"Invalid int for '{name}': {value!r} ({type(value).__name__})."
+        return int(as_float)
-        ) from exc
+    raise error_cls(f"Invalid int for '{name}': {value!r} ({type(value).__name__}).")
-    if not as_float.is_integer():
-        raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
-    return int(as_float)
 def _coerce_float(name: str, value: Any, *, error_cls: type[ValueError]) -> float:
     """Parse a float; wrap conversion errors in *error_cls*."""
     if isinstance(value, bool):
         raise error_cls(f"Invalid float for '{name}': {value!r} ({type(value).__name__}).")
-    try:
+    if isinstance(value, str):
+        try:
+            return float(value)
+        except ValueError as exc:
+            raise error_cls(
+                f"Invalid float for '{name}': {value!r} ({type(value).__name__})."
+            ) from exc
+    if isinstance(value, numbers.Real):
         return float(value)
-    except (TypeError, ValueError) as exc:
+    raise error_cls(f"Invalid float for '{name}': {value!r} ({type(value).__name__}).")
-        raise error_cls(
-            f"Invalid float for '{name}': {value!r} ({type(value).__name__})."
-        ) from exc
 def _coerce_str(name: str, value: Any, *, error_cls: type[ValueError]) -> str:
     """Accept a string as-is; reject every other type."""

Importance #4: src/iolabs/common/config_loader.py @@ -1,23 +1,73 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

1	"""Packaged-JSON config loading, deep-merge, key validation and value coercion.	1	"""Packaged-JSON config loading, deep-merge, key validation and value coercion.
2		2
3	Covers the whole config path shared by the pipeline packages: load the	3	Covers the whole config path shared by the pipeline packages: load the
4	packaged default JSON, deep-merge CLI ``--set`` overrides onto it, reject	4	packaged default JSON, deep-merge CLI ``--set`` overrides onto it, reject
5	unknown keys (flat or against the defaults tree) and coerce raw JSON/CLI	5	unknown keys and coerce raw JSON/CLI values to the declared field types.
6	values to the declared dataclass field types.	6
		7	The current way to declare a config is a pydantic model derived from
		8	`ConfigModel`, validated by :func:`load_config`; both are defined in
		9	:mod:`iolabs.common.config_model` and re-exported here, together with
		10	:func:`validate_config` and :func:`format_validation_error`. The canonical
		11	package pattern is::
		12
		13	from typing import Any, Literal
		14
		15	from iolabs.common import config_loader
		16
		17
		18	class FooGroundConfig(config_loader.ConfigModel):
		19	cell_m: float = 0.5
		20
		21
		22	class FooConfig(config_loader.ConfigModel):
		23	mode: Literal["fast", "exact"] = "fast"
		24	ground: FooGroundConfig = FooGroundConfig()
		25
		26
		27	class FooConfigError(config_loader.ConfigError):
		28	\"\"\"Raised for an invalid foo config.\"\"\"
		29
		30
		31	def build_foo_config(overrides=None, config_path=None) -> dict[str, Any]:
		32	return config_loader.load_config(
		33	FooConfig,
		34	package="iolabs_foo",
		35	filename="default_config.json",
		36	overrides=overrides,
		37	config_path=config_path,
		38	context="foo config",
		39	error_cls=FooConfigError,
		40	).model_dump()
		41
		42	`ConfigError`, `default_config_path`, `load_packaged_json`, `deep_merge_dicts`
		43	and `parse_set_overrides` stay first-class. The hand-rolled dataclass helpers
		44	(`validate_allowed_keys`, `coerce_to_field_type`, `dataclass_from_mapping`,
		45	`validate_against_defaults`) still work for published leaf wheels but emit a
		46	`DeprecationWarning`.
7	"""	47	"""
8		48
9	from __future__ import annotations	49	from __future__ import annotations
10		50
		51	import enum
11	import json	52	import json
		53	import logging
		54	import numbers
12	import sys	55	import sys
		56	import warnings
13	from collections.abc import Collection, Mapping, Sequence	57	from collections.abc import Collection, Mapping, Sequence
14	from dataclasses import fields, is_dataclass	58	from dataclasses import fields, is_dataclass
15	from importlib import resources	59	from importlib import resources
16	from pathlib import Path	60	from pathlib import Path
17	from types import UnionType	61	from types import UnionType
18	from typing import Any, Literal, TypeVar, Union, get_args, get_origin, get_type_hints	62	from typing import Any, Literal, TypeVar, Union, get_args, get_origin, get_type_hints
19		63
		64	logger = logging.getLogger(__name__)
		65
		66	_PYDANTIC_EXPORTS = frozenset(
		67	{"ConfigModel", "load_config", "validate_config", "format_validation_error"}
		68	)
		69
20		70
21	class ConfigError(ValueError):	71	class ConfigError(ValueError):
22	"""Raised when a packaged-JSON config contains unsupported keys/values."""	72	"""Raised when a packaged-JSON config contains unsupported keys/values."""
23		73

Importance #5: src/iolabs/common/config_loader.py @@ -258,8 +328,37 @@

The legacy coercion matrix as a non-deprecated public function; strictness (bool never int, str only str) is preserved on purpose.

258		328
259	Returns:	329	Returns:
260	The coerced value, or value unchanged for unsupported declared types.	330	The coerced value, or value unchanged for unsupported declared types.
261		331
		332	Raises:
		333	error_cls: value is not valid for declared.
		334	"""
		335	_warn_deprecated("coerce_to_field_type")
		336	return coerce_config_value(name, value, declared, error_cls=error_cls)
		337
		338
		339	def coerce_config_value(
		340	name: str,
		341	value: Any,
		342	declared: Any,
		343	*,
		344	error_cls: type[ValueError] = ConfigError,
		345	) -> Any:
		346	"""Coerce one raw config value to declared, the fleet accepted-input matrix.
		347
		348	Implementation shared by `ConfigModel` (per-field before-validator) and the
		349	deprecated :func:`coerce_to_field_type`, whose docstring is the spec of the
		350	accepted inputs.
		351
		352	Args:
		353	name: Field name, used only in error messages.
		354	value: The raw value from JSON or a parsed ``--set`` override.
		355	declared: The field's declared type.
		356	error_cls: Exception class raised for values that cannot be coerced.
		357
		358	Returns:
		359	The coerced value, or value unchanged for unsupported declared types.
		360
262	Raises:	361	Raises:
263	error_cls: value is not valid for declared.	362	error_cls: value is not valid for declared.
264	"""	363	"""
265	if isinstance(declared, str):	364	if isinstance(declared, str):

Importance #6: src/iolabs/common/init.py @@ -4,8 +4,9 @@

     atomic_io,
     cli,
     color_intensity_data,
     config_loader,
+    config_model,
     crs,
     diagnostic_data,
     ground_mask_io,
     indexed_ordered_dict,

Importance #7: src/iolabs/common/init.py @@ -23,8 +24,9 @@

     configure_logging,
 )
 from .config_loader import (
     ConfigError,
+    coerce_config_value,
     coerce_to_field_type,
     dataclass_from_mapping,
     deep_merge_dicts,
     default_config_path,

Importance #8: src/iolabs/common/init.py @@ -32,14 +34,21 @@

     parse_set_overrides,
     validate_against_defaults,
     validate_allowed_keys,
 )
+from .config_model import (
+    ConfigModel,
+    format_validation_error,
+    load_config,
+    validate_config,
+)
 __all__ = [
     "atomic_io",
     "cli",
     "color_intensity_data",
     "config_loader",
+    "config_model",
     "crs",
     "diagnostic_data",
     "ground_mask_io",
     "indexed_ordered_dict",

Importance #9: src/iolabs/common/init.py @@ -53,13 +62,18 @@

     "LOG_LEVEL_CHOICES",
     "add_log_level_argument",
     "configure_logging",
     "ConfigError",
+    "ConfigModel",
+    "coerce_config_value",
     "coerce_to_field_type",
     "dataclass_from_mapping",
     "default_config_path",
     "deep_merge_dicts",
+    "format_validation_error",
+    "load_config",
     "load_packaged_json",
+    "validate_config",
     "parse_set_overrides",
     "validate_against_defaults",
     "validate_allowed_keys",
 ]

Importance #10: src/iolabs/common/config_loader.py @@ -81,8 +131,11 @@

     error_cls: type[ValueError] = ConfigError,
 ) -> None:
     """Raise *error_cls* when *config* contains keys outside *allowed*.
+    Deprecated: derive a `ConfigModel` (``extra="forbid"``) and validate it with
+    :func:`load_config` / :func:`validate_config` instead.
     Args:
         config: The config mapping whose keys are checked.
         allowed: The keys *config* may hold.
         context: Human-readable config name used in the error message, e.g.

Importance #11: src/iolabs/common/config_loader.py @@ -96,8 +149,20 @@

96		149
97	Raises:	150	Raises:
98	error_cls: config holds one or more keys outside allowed.	151	error_cls: config holds one or more keys outside allowed.
99	"""	152	"""
		153	_warn_deprecated("validate_allowed_keys")
		154	_validate_allowed_keys(config, allowed, context=context, error_cls=error_cls)
		155
		156
		157	def _validate_allowed_keys(
		158	config: Mapping[str, Any],
		159	allowed: frozenset[str],
		160	*,
		161	context: str,
		162	error_cls: type[ValueError],
		163	) -> None:
		164	"""Raise error_cls when config contains keys outside allowed."""
100	unknown = sorted(set(config) - allowed)	165	unknown = sorted(set(config) - allowed)
101	if unknown:	166	if unknown:
102	raise error_cls(	167	raise error_cls(
103	f"Unknown {context} key(s): {', '.join(unknown)}. "	168	f"Unknown {context} key(s): {', '.join(unknown)}. "

Importance #12: src/iolabs/common/config_loader.py @@ -285,9 +384,9 @@

285	return _coerce_sequence(	384	return _coerce_sequence(
286	name, value, get_args(declared), target=list, error_cls=error_cls	385	name, value, get_args(declared), target=list, error_cls=error_cls
287	)	386	)
288	if isinstance(declared, type) and is_dataclass(declared) and isinstance(value, Mapping):	387	if isinstance(declared, type) and is_dataclass(declared) and isinstance(value, Mapping):
289	return dataclass_from_mapping(declared, value, context=name, error_cls=error_cls)	388	return _dataclass_from_mapping(declared, value, context=name, error_cls=error_cls)
290	return value	389	return value
291		390
292		391
293	def _coerce_bool(name: str, value: Any, *, error_cls: type[ValueError]) -> bool:	392	def _coerce_bool(name: str, value: Any, *, error_cls: type[ValueError]) -> bool:

Importance #13: src/iolabs/common/config_loader.py @@ -369,12 +469,21 @@

     options: tuple[Any, ...],
     *,
     error_cls: type[ValueError],
 ) -> Any:
-    """Check *value* against the options of a ``Literal`` annotation."""
+    """Check *value* against the options of a ``Literal`` annotation.
+    An option that is an `enum.Enum` member also matches its plain
+    JSON-representable value (``"fast"`` for ``Mode.FAST``), as pydantic does;
+    the member is returned. Types must match exactly otherwise, so ``True``
+    never satisfies ``Literal[1]``.
+    """
     for option in options:
         if type(option) is type(value) and option == value:
             return option
+        if isinstance(option, enum.Enum) and type(option.value) is type(value):
+            if option.value == value:
+                return option
     allowed = ", ".join(repr(option) for option in options)
     raise error_cls(f"Invalid value for '{name}': {value!r}. Expected one of: {allowed}.")

Importance #14: src/iolabs/common/config_loader.py @@ -390,9 +499,9 @@

390	return None	499	return None
391	candidates = [member for member in members if member is not type(None)]	500	candidates = [member for member in members if member is not type(None)]
392	if len(candidates) != 1:	501	if len(candidates) != 1:
393	return value	502	return value
394	return coerce_to_field_type(name, value, candidates[0], error_cls=error_cls)	503	return coerce_config_value(name, value, candidates[0], error_cls=error_cls)
395		504
396		505
397	def _coerce_sequence(	506	def _coerce_sequence(
398	name: str,	507	name: str,

Importance #15: src/iolabs/common/config_loader.py @@ -420,9 +529,9 @@

420	item_types = [args[0]] * len(items)	529	item_types = [args[0]] * len(items)
421	if not item_types:	530	if not item_types:
422	return target(items)	531	return target(items)
423	coerced = [	532	coerced = [
424	coerce_to_field_type(f"{name}[{index}]", item, item_type, error_cls=error_cls)	533	coerce_config_value(f"{name}[{index}]", item, item_type, error_cls=error_cls)
425	for index, (item, item_type) in enumerate(zip(items, item_types, strict=True))	534	for index, (item, item_type) in enumerate(zip(items, item_types, strict=True))
426	]	535	]
427	return target(coerced)	536	return target(coerced)
428		537

Importance #16: src/iolabs/common/config_loader.py @@ -468,18 +577,33 @@

         TypeError: *cls* is not a dataclass type, a field annotation cannot be
             resolved at runtime (unless ``coerce=False``), or a required field
             is missing from *raw*.
     """
+    _warn_deprecated("dataclass_from_mapping")
+    return _dataclass_from_mapping(
+        cls, raw, context=context, error_cls=error_cls, coerce=coerce
+    )
+def _dataclass_from_mapping(
+    cls: type[_T],
+    raw: Mapping[str, Any],
+    *,
+    context: str,
+    error_cls: type[ValueError],
+    coerce: bool = True,
+) -> _T:
+    """Build a dataclass instance from a raw mapping (implementation)."""
     if not is_dataclass(cls) or not isinstance(cls, type):
         raise TypeError(f"dataclass_from_mapping requires a dataclass type, got {cls!r}")
     init_fields = [field for field in fields(cls) if field.init]
     allowed = frozenset(field.name for field in init_fields)
-    validate_allowed_keys(raw, allowed, context=context, error_cls=error_cls)
+    _validate_allowed_keys(raw, allowed, context=context, error_cls=error_cls)
     if not coerce:
         return cls(**dict(raw))
     declared_types = _resolve_field_types(cls, init_fields)
     values = {
-        name: coerce_to_field_type(name, value, declared_types[name], error_cls=error_cls)
+        name: coerce_config_value(name, value, declared_types[name], error_cls=error_cls)
         for name, value in raw.items()
     }
     return cls(**values)

Importance #17: src/iolabs/common/config_loader.py @@ -564,8 +688,11 @@

     node's keys. Recursion stops where *defaults* holds a non-mapping leaf, so
     leaf values are never inspected. The first offending node raises, naming
     the dotted context path (``"cluster-stepper config.lane_segment_width"``).
+    Deprecated: a `ConfigModel` with ``extra="forbid"`` is the schema now; use
+    :func:`load_config` / :func:`validate_config`.
     Args:
         config: The raw config node to validate (usually a dict).
         defaults: The corresponding node of the packaged defaults.
         context: Human-readable name of the root node, used as the error

Importance #18: src/iolabs/common/config_loader.py @@ -586,8 +713,9 @@

         error_cls: A node of *config* is not a mapping where *defaults* has
             one, or holds a key absent from both *defaults* and
             *allowed_extra_keys*.
     """
+    _warn_deprecated("validate_against_defaults")
     _validate_against_defaults(
         config,
         defaults,
         context=context,

Importance #19: src/iolabs/common/config_loader.py @@ -638,4 +766,28 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

638		766
639	def _dotted(prefix: str, key: str) -> str:	767	def _dotted(prefix: str, key: str) -> str:
640	"""Join a dotted path prefix with a key."""	768	"""Join a dotted path prefix with a key."""
641	return f"{prefix}.{key}" if prefix else key	769	return f"{prefix}.{key}" if prefix else key
		770
		771
		772	def _warn_deprecated(name: str) -> None:
		773	"""Emit a `DeprecationWarning` for a legacy hand-rolled config helper."""
		774	warnings.warn(
		775	f"config_loader.{name} is deprecated; derive a config_loader.ConfigModel "
		776	f"and use config_loader.load_config/validate_config instead.",
		777	DeprecationWarning,
		778	stacklevel=3,
		779	)
		780
		781
		782	def __getattr__(name: str) -> Any:
		783	"""Re-export the pydantic config layer lazily, avoiding an import cycle."""
		784	if name in _PYDANTIC_EXPORTS:
		785	from iolabs.common import config_model
		786
		787	return getattr(config_model, name)
		788	raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
		789
		790
		791	def __dir__() -> list[str]:
		792	"""List the lazy pydantic re-exports alongside the module's own names."""
		793	return sorted(set(globals()) \| _PYDANTIC_EXPORTS)

Importance #20: tests/test_config_model.py @@ -0,0 +1,584 @@

	1	"""Tests for the pydantic-v2 config layer (`config_loader.ConfigModel`)."""
	2
	3	from __future__ import annotations
	4
	5	import dataclasses
	6	import enum
	7	import json
	8	import math
	9	import warnings
	10	from pathlib import Path
	11	from typing import Any, Literal
	12	from unittest.mock import patch
	13
	14	import pydantic
	15	import pytest
	16
	17	from iolabs.common import config_loader, config_model
	18
	19	_PACKAGE = "iolabs.common"
	20	_FIXTURE_PATH = Path(__file__).parent / "fixtures" / "config_loader.fixture.json"
	21
	22
	23	class SampleMode(enum.StrEnum):
	24	"""Enum used for Literal-of-enum fields."""
	25
	26	FAST = "fast"
	27	EXACT = "exact"
	28
	29
	30	class SampleConfigError(config_loader.ConfigError):
	31	"""Consumer-style config error."""
	32
	33
	34	class GroundSection(config_loader.ConfigModel):
	35	"""Nested section mirroring a packaged JSON sub-object."""
	36
	37	cell_m: float = 0.5
	38	percentile: float = 5.0
	39
	40
	41	class SampleConfig(config_loader.ConfigModel):
	42	"""Sample config exercising every supported field kind."""
	43
	44	name: str = "run"
	45	count: int = 3
	46	threshold_m: float = 0.5
	47	enabled: bool = True
	48	mechanism: Literal["csf", "plane"] = "csf"
	49	tag: str \| None = None
	50	band_m: tuple[float, float] = (0.0, 1.0)
	51	weights: list[int] = [1, 2]
	52	ground: GroundSection = GroundSection()
	53
	54
	55	class FixtureConfig(config_loader.ConfigModel):
	56	"""Config matching ``tests/fixtures/config_loader.fixture.json``."""
	57
	58	enabled: bool = False
	59	ground: GroundSection = GroundSection()
	60
	61
	62	# --- coercion matrix ---------------------------------------------------------
	63
	64
	65	@pytest.mark.parametrize(
	66	("value", "expected"),
	67	[
	68	(True, True),
	69	(False, False),
	70	(1, True),
	71	(0, False),
	72	("1", True),
	73	("TRUE", True),
	74	(" yes ", True),
	75	("On", True),
	76	("0", False),
	77	("false", False),
	78	("NO", False),
	79	("off", False),
	80	],
	81	)
	82	def test_bool_field_accepts_matrix(value: object, expected: bool) -> None:
	83	"""bool fields accept real bools, 0/1 and the documented tokens."""
	84	assert SampleConfig(enabled=value).enabled is expected
	85
	86
	87	@pytest.mark.parametrize("value", ["flase", "y", "", 2, -1, 1.0, None, []])
	88	def test_bool_field_rejects_everything_else(value: object) -> None:
	89	"""bool fields reject typos, out-of-range ints and non-scalar values."""
	90	with pytest.raises(config_loader.ConfigError):
	91	config_loader.validate_config(
	92	SampleConfig, {"enabled": value}, context="sample config"
	93	)
	94
	95
	96	@pytest.mark.parametrize(
	97	("value", "expected"),
	98	[(7, 7), (3.0, 3), ("42", 42), (" 42 ", 42), ("1e3", 1000), ("-5", -5)],
	99	)
	100	def test_int_field_accepts_matrix(value: object, expected: int) -> None:
	101	"""int fields accept ints, integral floats and numeric strings."""
	102	assert SampleConfig(count=value).count == expected
	103
	104
	105	@pytest.mark.parametrize("value", [True, False, 3.7, "3.7", "abc", None, "1e3.5"])
	106	def test_int_field_rejects_bools_and_non_integral(value: object) -> None:
	107	"""int fields reject bools, fractional values and bad tokens."""
	108	with pytest.raises(config_loader.ConfigError):
	109	config_loader.validate_config(
	110	SampleConfig, {"count": value}, context="sample config"
	111	)
	112
	113
	114	@pytest.mark.parametrize(
	115	("value", "expected"),
	116	[(2, 2.0), (2.5, 2.5), ("2.5", 2.5), (" 1e-2 ", 0.01), ("inf", math.inf)],
	117	)
	118	def test_float_field_accepts_matrix(value: object, expected: float) -> None:
	119	"""float fields accept ints, floats and numeric strings incl. inf."""
	120	assert SampleConfig(threshold_m=value).threshold_m == expected
	121
	122
	123	def test_float_field_accepts_nan() -> None:
	124	"""float fields accept 'nan'; finiteness is a domain check, not a type one."""
	125	assert math.isnan(SampleConfig(threshold_m="nan").threshold_m)
	126
	127
	128	@pytest.mark.parametrize("value", [True, False, "abc", None, []])
	129	def test_float_field_rejects_bools_and_bad_tokens(value: object) -> None:
	130	"""float fields reject bools and non-numeric values."""
	131	with pytest.raises(config_loader.ConfigError):
	132	config_loader.validate_config(
	133	SampleConfig, {"threshold_m": value}, context="sample config"
	134	)
	135
	136
	137	@pytest.mark.parametrize("value", [b"3", b"2.5", object(), {"a": 1}])
	138	def test_numeric_fields_reject_non_numeric_types(value: object) -> None:
	139	"""int/float fields reject bytes and other types float() happens to eat."""
	140	for field in ("count", "threshold_m"):
	141	with pytest.raises(config_loader.ConfigError):
	142	config_loader.validate_config(
	143	SampleConfig, {field: value}, context="sample config"
	144	)
	145
	146
	147	@pytest.mark.parametrize("value", [3, 3.5, True, None, ["a"]])
	148	def test_str_field_rejects_non_strings(value: object) -> None:
	149	"""str fields accept strings only - no int -> str coercion."""
	150	with pytest.raises(config_loader.ConfigError):
	151	config_loader.validate_config(
	152	SampleConfig, {"name": value}, context="sample config"
	153	)
	154
	155
	156	def test_str_field_accepts_strings() -> None:
	157	"""str fields pass strings through unchanged."""
	158	assert SampleConfig(name="lidar").name == "lidar"
	159
	160
	161	def test_optional_field_accepts_none_and_inner_type() -> None:
	162	"""``str \| None`` accepts None and applies the str rules otherwise."""
	163	assert SampleConfig(tag=None).tag is None
	164	assert SampleConfig(tag="a").tag == "a"
	165	with pytest.raises(config_loader.ConfigError):
	166	config_loader.validate_config(SampleConfig, {"tag": 3}, context="sample config")
	167
	168
	169	def test_literal_field_accepts_options_and_rejects_others() -> None:
	170	"""Literal fields accept declared options only."""
	171	assert SampleConfig(mechanism="plane").mechanism == "plane"
	172	with pytest.raises(config_loader.ConfigError):
	173	config_loader.validate_config(
	174	SampleConfig, {"mechanism": "ransac"}, context="sample config"
	175	)
	176
	177
	178	def test_literal_enum_field_accepts_the_plain_option_value() -> None:
	179	"""Enum-valued Literal fields accept the JSON value, as plain pydantic does."""
	180
	181	class EnumConfig(config_loader.ConfigModel):
	182	mode: Literal[SampleMode.FAST, SampleMode.EXACT] = SampleMode.FAST
	183
	184	assert EnumConfig.model_validate({"mode": "exact"}).mode is SampleMode.EXACT
	185	assert EnumConfig(mode=SampleMode.FAST).mode is SampleMode.FAST
	186	with pytest.raises(config_loader.ConfigError):
	187	config_loader.validate_config(EnumConfig, {"mode": "ransac"}, context="enum config")
	188
	189
	190	def test_int_literal_still_rejects_bools() -> None:
	191	"""Literal[int] keeps the fleet rule that a bool is not an int."""
	192
	193	class IntLiteral(config_loader.ConfigModel):
	194	level: Literal[1, 2] = 1
	195
	196	assert IntLiteral(level=2).level == 2
	197	with pytest.raises(config_loader.ConfigError):
	198	config_loader.validate_config(IntLiteral, {"level": True}, context="int config")
	199
	200
	201	def test_sequence_items_are_coerced_with_the_same_matrix() -> None:
	202	"""tuple/list items follow the scalar matrix (and reject bools for int)."""
	203	built = SampleConfig(band_m=["0.5", 2], weights=["3", 4.0])
	204	assert built.band_m == (0.5, 2.0)
	205	assert built.weights == [3, 4]
	206	with pytest.raises(config_loader.ConfigError):
	207	config_loader.validate_config(
	208	SampleConfig, {"weights": [True]}, context="sample config"
	209	)
	210
	211
	212	def test_fixed_length_tuple_checks_item_count() -> None:
	213	"""A fixed-length tuple annotation rejects the wrong item count."""
	214	with pytest.raises(config_loader.ConfigError, match="expected 2 item"):
	215	config_loader.validate_config(
	216	SampleConfig, {"band_m": [1.0, 2.0, 3.0]}, context="sample config"
	217	)
	218
	219
	220	def test_nested_section_is_validated_and_coerced() -> None:
	221	"""Nested models are built from mappings with the same scalar rules."""
	222	built = SampleConfig(ground={"cell_m": "0.75", "percentile": 8})
	223	assert built.ground.cell_m == 0.75
	224	assert built.ground.percentile == 8.0
	225
	226
	227	# --- error message shapes ----------------------------------------------------
	228
	229
	230	def test_unknown_top_level_key_message() -> None:
	231	"""Unknown top-level keys read like validate_allowed_keys."""
	232	with pytest.raises(config_loader.ConfigError) as excinfo:
	233	config_loader.validate_config(
	234	SampleConfig, {"nope": 1, "also": 2}, context="sample config"
	235	)
	236	assert str(excinfo.value).startswith("Unknown sample config key(s): also, nope. ")
	237	assert "Allowed keys: band_m, count, enabled, ground, mechanism," in str(excinfo.value)
	238
	239
	240	def test_unknown_nested_key_uses_dotted_context() -> None:
	241	"""Unknown keys inside a section name the dotted section path."""
	242	with pytest.raises(config_loader.ConfigError) as excinfo:
	243	config_loader.validate_config(
	244	SampleConfig, {"ground": {"zzz": 1}}, context="sample config"
	245	)
	246	assert str(excinfo.value) == (
	247	"Unknown sample config.ground key(s): zzz. Allowed keys: cell_m, percentile"
	248	)
	249
	250
	251	def test_value_error_message_uses_dotted_field_path() -> None:
	252	"""Nested value errors name the dotted field path."""
	253	with pytest.raises(config_loader.ConfigError) as excinfo:
	254	config_loader.validate_config(
	255	SampleConfig, {"ground": {"cell_m": "abc"}}, context="sample config"
	256	)
	257	assert str(excinfo.value) == "Invalid float for 'ground.cell_m': 'abc' (str)."
	258
	259
	260	def test_value_error_message_top_level_shape() -> None:
	261	"""Top-level value errors keep the legacy 'Invalid <type> for ...' shape."""
	262	with pytest.raises(config_loader.ConfigError) as excinfo:
	263	config_loader.validate_config(
	264	SampleConfig, {"count": 3.7}, context="sample config"
	265	)
	266	assert str(excinfo.value) == "Invalid int for 'count': 3.7 is not an integral value."
	267
	268
	269	def test_missing_required_key_message() -> None:
	270	"""A missing required field is reported with the context name."""
	271
	272	class Required(config_loader.ConfigModel):
	273	name: str
	274
	275	with pytest.raises(config_loader.ConfigError) as excinfo:
	276	config_loader.validate_config(Required, {}, context="sample config")
	277	assert str(excinfo.value) == "Missing required sample config key: 'name'"
	278
	279
	280	def test_error_cls_override_is_used() -> None:
	281	"""validate_config raises the caller's error class."""
	282	with pytest.raises(SampleConfigError):
	283	config_loader.validate_config(
	284	SampleConfig, {"nope": 1}, context="sample config", error_cls=SampleConfigError
	285	)
	286
	287
	288	def test_format_validation_error_without_model_cls_lists_allowed_keys() -> None:
	289	"""The model is recovered from the error title, so allowed keys stay listed."""
	290	with pytest.raises(Exception) as excinfo:
	291	SampleConfig(nope=1)
	292	message = config_model.format_validation_error(
	293	excinfo.value, context="sample config"
	294	)
	295	assert message.startswith("Unknown sample config key(s): nope. Allowed keys: band_m, ")
	296
	297
	298	def test_format_validation_error_omits_allowed_keys_for_unknown_model() -> None:
	299	"""A foreign model's error still reads well, just without the key list."""
	300
	301	class Foreign(pydantic.BaseModel):
	302	model_config = pydantic.ConfigDict(extra="forbid")
	303
	304	alpha: int = 1
	305
	306	with pytest.raises(pydantic.ValidationError) as excinfo:
	307	Foreign(nope=1)
	308	message = config_model.format_validation_error(excinfo.value, context="probe config")
	309	assert message == "Unknown probe config key(s): nope."
	310
	311
	312	def test_format_validation_error_skips_ambiguous_model_names() -> None:
	313	"""Distinct ConfigModels sharing a name resolve to neither, so no key list."""
	314
	315	def _first() -> type[config_loader.ConfigModel]:
	316	class Twin(config_loader.ConfigModel):
	317	alpha: int = 1
	318
	319	return Twin
	320
	321	def _second() -> type[config_loader.ConfigModel]:
	322	class Twin(config_loader.ConfigModel):
	323	beta: int = 2
	324
	325	return Twin
	326
	327	model, _other = _first(), _second()
	328	with pytest.raises(pydantic.ValidationError) as excinfo:
	329	model(nope=1)
	330	message = config_model.format_validation_error(excinfo.value, context="twin config")
	331	assert message == "Unknown twin config key(s): nope."
	332
	333
	334	def test_format_validation_error_survives_class_redefinition() -> None:
	335	"""Re-running the same class statement is a redefinition, not an ambiguity."""
	336
	337	def _make() -> type[config_loader.ConfigModel]:
	338	class Reloaded(config_loader.ConfigModel):
	339	alpha: int = 1
	340
	341	return Reloaded
	342
	343	_stale, current = _make(), _make()
	344	with pytest.raises(pydantic.ValidationError) as excinfo:
	345	current(nope=1)
	346	message = config_model.format_validation_error(excinfo.value, context="reload config")
	347	assert message == "Unknown reload config key(s): nope. Allowed keys: alpha"
	348
	349
	350	def test_alias_field_reports_the_alias_as_the_allowed_key() -> None:
	351	"""An aliased field is listed (and reported missing) under its alias."""
	352
	353	class Aliased(config_loader.ConfigModel):
	354	internal_name: int = pydantic.Field(alias="external-name")
	355
	356	with pytest.raises(config_loader.ConfigError) as excinfo:
	357	config_loader.validate_config(Aliased, {"internal_name": 3}, context="alias config")
	358	message = str(excinfo.value)
	359	assert "Unknown alias config key(s): internal_name. Allowed keys: external-name" in message
	360	assert "Missing required alias config key: 'external-name'" in message
	361	assert config_loader.validate_config(
	362	Aliased, {"external-name": "3"}, context="alias config"
	363	).internal_name == 3
	364
	365
	366	def test_aliased_section_resolves_nested_allowed_keys() -> None:
	367	"""Unknown keys inside an aliased section list that section's own keys."""
	368
	369	class Outer(config_loader.ConfigModel):
	370	ground: GroundSection = pydantic.Field(
	371	default=GroundSection(), alias="ground-section"
	372	)
	373
	374	with pytest.raises(config_loader.ConfigError) as excinfo:
	375	config_loader.validate_config(
	376	Outer, {"ground-section": {"zzz": 1}}, context="outer config"
	377	)
	378	assert str(excinfo.value) == (
	379	"Unknown outer config.ground-section key(s): zzz. Allowed keys: cell_m, percentile"
	380	)
	381
	382
	383	# --- load_config -------------------------------------------------------------
	384
	385
	386	def test_load_config_reads_packaged_defaults() -> None:
	387	"""load_config validates the packaged JSON into the model."""
	388	with patch(
	389	"iolabs.common.config_loader.default_config_path",
	390	return_value=_FIXTURE_PATH,
	391	):
	392	built = config_loader.load_config(
	393	FixtureConfig,
	394	package=_PACKAGE,
	395	filename="config_loader.fixture.json",
	396	context="fixture config",
	397	)
	398	assert built.enabled is True
	399	assert built.ground.cell_m == 0.75
	400
	401
	402	def test_load_config_deep_merges_overrides() -> None:
	403	"""Overrides are deep-merged onto the defaults before validation."""
	404	with patch(
	405	"iolabs.common.config_loader.default_config_path",
	406	return_value=_FIXTURE_PATH,
	407	):
	408	built = config_loader.load_config(
	409	FixtureConfig,
	410	package=_PACKAGE,
	411	filename="config_loader.fixture.json",
	412	overrides={"ground": {"cell_m": "0.25"}, "enabled": "off"},
	413	context="fixture config",
	414	)
	415	assert built.enabled is False
	416	assert built.ground.cell_m == 0.25
	417	assert built.ground.percentile == 8.0
	418
	419
	420	def test_load_config_uses_config_path_when_given(tmp_path: Path) -> None:
	421	"""config_path replaces the packaged defaults."""
	422	path = tmp_path / "custom.json"
	423	path.write_text(json.dumps({"ground": {"cell_m": 1.5}}), encoding="utf-8")
	424	built = config_loader.load_config(
	425	FixtureConfig,
	426	package=_PACKAGE,
	427	filename="config_loader.fixture.json",
	428	config_path=path,
	429	context="fixture config",
	430	)
	431	assert built.enabled is False
	432	assert built.ground.cell_m == 1.5
	433
	434
	435	def test_load_config_rejects_unknown_key_from_file(tmp_path: Path) -> None:
	436	"""Unknown keys in a config file are reported with the file's context."""
	437	path = tmp_path / "custom.json"
	438	path.write_text(json.dumps({"zzz": 1}), encoding="utf-8")
	439	with pytest.raises(config_loader.ConfigError, match="Unknown fixture config key"):
	440	config_loader.load_config(
	441	FixtureConfig,
	442	package=_PACKAGE,
	443	filename="config_loader.fixture.json",
	444	config_path=path,
	445	context="fixture config",
	446	)
	447
	448
	449	def test_load_config_wraps_malformed_json(tmp_path: Path) -> None:
	450	"""Malformed JSON is wrapped in the caller's error class."""
	451	path = tmp_path / "custom.json"
	452	path.write_text("{oops", encoding="utf-8")
	453	with pytest.raises(SampleConfigError, match="Invalid JSON in config file"):
	454	config_loader.load_config(
	455	FixtureConfig,
	456	package=_PACKAGE,
	457	filename="config_loader.fixture.json",
	458	config_path=path,
	459	context="fixture config",
	460	error_cls=SampleConfigError,
	461	)
	462
	463
	464	def test_load_config_rejects_non_object_json(tmp_path: Path) -> None:
	465	"""A JSON file holding a list is rejected."""
	466	path = tmp_path / "custom.json"
	467	path.write_text("[1, 2]", encoding="utf-8")
	468	with pytest.raises(config_loader.ConfigError, match="must hold a JSON object"):
	469	config_loader.load_config(
	470	FixtureConfig,
	471	package=_PACKAGE,
	472	filename="config_loader.fixture.json",
	473	config_path=path,
	474	context="fixture config",
	475	)
	476
	477
	478	def test_load_config_rejects_non_object_packaged_json(tmp_path: Path) -> None:
	479	"""A packaged default JSON holding a list is rejected like a file one."""
	480	path = tmp_path / "defaults.json"
	481	path.write_text('[["enabled", false]]', encoding="utf-8")
	482	with patch(
	483	"iolabs.common.config_loader.default_config_path",
	484	return_value=path,
	485	):
	486	with pytest.raises(config_loader.ConfigError, match="must hold a JSON object"):
	487	config_loader.load_config(
	488	FixtureConfig,
	489	package=_PACKAGE,
	490	filename="defaults.json",
	491	context="fixture config",
	492	)
	493
	494
	495	# --- model behaviour ---------------------------------------------------------
	496
	497
	498	def test_config_is_frozen() -> None:
	499	"""Built configs cannot be mutated."""
	500	built = SampleConfig()
	501	with pytest.raises(Exception): # noqa: B017 - pydantic raises ValidationError
	502	built.count = 5
	503
	504
	505	def test_model_dump_round_trip_produces_plain_dicts() -> None:
	506	"""model_dump yields plain dicts that validate back into the same config."""
	507	built = SampleConfig(ground={"cell_m": 0.25})
	508	dumped = built.model_dump()
	509	assert isinstance(dumped, dict)
	510	assert isinstance(dumped["ground"], dict)
	511	assert dumped["ground"] == {"cell_m": 0.25, "percentile": 5.0}
	512	assert config_loader.validate_config(
	513	SampleConfig, dumped, context="sample config"
	514	) == built
	515
	516
	517	def test_defaults_are_validated() -> None:
	518	"""validate_default=True catches a bad default at model build time."""
	519
	520	class Bad(config_loader.ConfigModel):
	521	count: int = "abc" # type: ignore[assignment]
	522
	523	with pytest.raises(config_loader.ConfigError):
	524	config_loader.validate_config(Bad, {}, context="sample config")
	525
	526
	527	def test_extra_keys_forbidden_on_direct_construction() -> None:
	528	"""extra='forbid' applies to plain construction too, not just load_config."""
	529	with pytest.raises(Exception): # noqa: B017 - pydantic raises ValidationError
	530	SampleConfig(nope=1)
	531
	532
	533	# --- deprecation shims -------------------------------------------------------
	534
	535
	536	@dataclasses.dataclass(frozen=True)
	537	class LegacySample:
	538	"""Dataclass used to exercise the deprecated mapping helper."""
	539
	540	count: int
	541
	542
	543	@pytest.mark.parametrize(
	544	("name", "call"),
	545	[
	546	(
	547	"validate_allowed_keys",
	548	lambda: config_loader.validate_allowed_keys(
	549	{"a": 1}, frozenset({"a"}), context="ctx"
	550	),
	551	),
	552	("coerce_to_field_type", lambda: config_loader.coerce_to_field_type("x", 1, int)),
	553	(
	554	"dataclass_from_mapping",
	555	lambda: config_loader.dataclass_from_mapping(
	556	LegacySample, {"count": "2"}, context="ctx"
	557	),
	558	),
	559	(
	560	"validate_against_defaults",
	561	lambda: config_loader.validate_against_defaults({"a": 1}, {"a": 1}, context="ctx"),
	562	),
	563	],
	564	)
	565	def test_legacy_helpers_warn(name: str, call: Any) -> None:
	566	"""The hand-rolled helpers still work but are deprecated."""
	567	with pytest.warns(DeprecationWarning, match=name):
	568	call()
	569
	570
	571	def test_lazy_reexports_are_visible_to_dir() -> None:
	572	"""The lazily re-exported pydantic names show up in dir(config_loader)."""
	573	names = dir(config_loader)
	574	assert {"ConfigModel", "load_config", "validate_config", "format_validation_error"} <= set(
	575	names
	576	)
	577	assert names == sorted(names)
	578
	579
	580	def test_coerce_config_value_does_not_warn() -> None:
	581	"""The shared coercion entry point used by ConfigModel is not deprecated."""
	582	with warnings.catch_warnings():
	583	warnings.simplefilter("error", DeprecationWarning)
	584	assert config_loader.coerce_config_value("x", "1e3", int) == 1000
0

Importance #21: tests/test_config_loader.py @@ -1,8 +1,9 @@

1	"""Tests for packaged-JSON config loader helpers."""	1	"""Tests for packaged-JSON config loader helpers."""
2		2
3	from __future__ import annotations	3	from __future__ import annotations
4		4
		5	import enum
5	import importlib	6	import importlib
6	import json	7	import json
7	import math	8	import math
8	import sys	9	import sys

Importance #22: tests/test_config_loader.py @@ -29,8 +30,13 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

29	_PACKAGE = "iolabs.common"	30	_PACKAGE = "iolabs.common"
30	_PACKAGED_MODULE_FILENAME = "config_loader.py"	31	_PACKAGED_MODULE_FILENAME = "config_loader.py"
31		32
32		33
		34	# The hand-rolled helpers below are deprecated shims kept for published leaf
		35	# wheels; their DeprecationWarning is expected here.
		36	pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
		37
		38
33	class CustomConfigError(ConfigError):	39	class CustomConfigError(ConfigError):
34	"""Consumer-style ConfigError subclass for error_cls override tests."""	40	"""Consumer-style ConfigError subclass for error_cls override tests."""
35		41
36		42

Importance #23: tests/test_config_loader.py @@ -316,9 +322,9 @@

316	"""Ints, integral floats and numeric strings (incl. exponents) coerce."""	322	"""Ints, integral floats and numeric strings (incl. exponents) coerce."""
317	assert coerce_to_field_type("count", value, int) == expected	323	assert coerce_to_field_type("count", value, int) == expected
318		324
319		325
320	@pytest.mark.parametrize("value", [3.7, -3.7, "3.7", "abc", True, None, []])	326	@pytest.mark.parametrize("value", [3.7, -3.7, "3.7", "abc", True, None, [], b"3", object()])
321	def test_coerce_int_rejects_non_integral_and_bad_tokens(value: object) -> None:	327	def test_coerce_int_rejects_non_integral_and_bad_tokens(value: object) -> None:
322	"""Truncation, bools and bad tokens raise the config error, not ValueError."""	328	"""Truncation, bools and bad tokens raise the config error, not ValueError."""
323	with pytest.raises(ConfigError, match="Invalid int for 'count'"):	329	with pytest.raises(ConfigError, match="Invalid int for 'count'"):
324	coerce_to_field_type("count", value, int)	330	coerce_to_field_type("count", value, int)

Importance #24: tests/test_config_loader.py @@ -334,9 +340,9 @@

334	assert isinstance(result, float)	340	assert isinstance(result, float)
335	assert result == expected	341	assert result == expected
336		342
337		343
338	@pytest.mark.parametrize("value", ["abc", None, [], True])	344	@pytest.mark.parametrize("value", ["abc", None, [], True, b"2.5", object()])
339	def test_coerce_float_rejects_bad_values(value: object) -> None:	345	def test_coerce_float_rejects_bad_values(value: object) -> None:
340	"""Bad tokens and non-numeric types are wrapped in the config error."""	346	"""Bad tokens and non-numeric types are wrapped in the config error."""
341	with pytest.raises(ConfigError, match="Invalid float for 'threshold_m'"):	347	with pytest.raises(ConfigError, match="Invalid float for 'threshold_m'"):
342	coerce_to_field_type("threshold_m", value, float)	348	coerce_to_field_type("threshold_m", value, float)

Importance #25: tests/test_config_loader.py @@ -389,8 +395,28 @@

389	with pytest.raises(ConfigError, match="Expected one of: 'csf', 'plane'"):	395	with pytest.raises(ConfigError, match="Expected one of: 'csf', 'plane'"):
390	coerce_to_field_type("mechanism", "cloth", declared)	396	coerce_to_field_type("mechanism", "cloth", declared)
391		397
392		398
		399	def test_coerce_literal_enum_accepts_the_plain_option_value() -> None:
		400	"""An enum option also matches its plain value and yields the member."""
		401
		402	class Mechanism(enum.StrEnum):
		403	CSF = "csf"
		404	PLANE = "plane"
		405
		406	declared = Literal[Mechanism.CSF, Mechanism.PLANE]
		407	assert coerce_to_field_type("mechanism", "plane", declared) is Mechanism.PLANE
		408	assert coerce_to_field_type("mechanism", Mechanism.CSF, declared) is Mechanism.CSF
		409	with pytest.raises(ConfigError, match="Expected one of"):
		410	coerce_to_field_type("mechanism", "cloth", declared)
		411
		412
		413	def test_coerce_int_literal_still_rejects_bools() -> None:
		414	"""A bool never satisfies Literal[1, 2], unlike plain pydantic."""
		415	with pytest.raises(ConfigError, match="Expected one of"):
		416	coerce_to_field_type("level", True, Literal[1, 2])
		417
		418
393	def test_coerce_unknown_declared_type_passes_through() -> None:	419	def test_coerce_unknown_declared_type_passes_through() -> None:
394	"""Unsupported declared types return the value unchanged."""	420	"""Unsupported declared types return the value unchanged."""
395	payload = {"a": 1}	421	payload = {"a": 1}
396	assert coerce_to_field_type("extras", payload, dict[str, int]) is payload	422	assert coerce_to_field_type("extras", payload, dict[str, int]) is payload

Importance #26: pyproject.toml @@ -4,8 +4,9 @@

 description = "Shared data structures for the 3D AI LIDAR processing pipeline"
 requires-python = ">=3.11"
 dependencies = [
     "numpy>=1.20.0",
+    "pydantic>=2.7",
 ]
 [project.optional-dependencies]
 dev = ["pytest>=7.0.0"]
 crs = ["pyproj>=3.4.0"]

Importance #27: README.md @@ -12,4 +12,53 @@

12		12
13	```python	13	```python
14	from io_common.common_data import ColorIntensityData	14	from io_common.common_data import ColorIntensityData
15	```	15	```
		16
		17	## Config models (pydantic v2)
		18
		19	Package configs derive from `config_loader.ConfigModel` (frozen, `extra="forbid"`,
		20	fleet coercion matrix for `bool`/`int`/`float`/`str`) and are built with
		21	`config_loader.load_config(...)`:
		22
		23	```python
		24	from collections.abc import Mapping
		25	from pathlib import Path
		26	from typing import Any, Literal
		27
		28	from iolabs.common import config_loader
		29
		30
		31	class FooGroundConfig(config_loader.ConfigModel):
		32	cell_m: float = 0.5
		33
		34
		35	class FooConfig(config_loader.ConfigModel):
		36	mode: Literal["fast", "exact"] = "fast"
		37	ground: FooGroundConfig = FooGroundConfig()
		38
		39
		40	class FooConfigError(config_loader.ConfigError):
		41	"""Raised for an invalid foo config."""
		42
		43
		44	def build_foo_config(
		45	overrides: Mapping[str, Any] \| None = None,
		46	config_path: str \| Path \| None = None,
		47	) -> dict[str, Any]:
		48	return config_loader.load_config(
		49	FooConfig,
		50	package="iolabs_foo",
		51	filename="default_config.json",
		52	overrides=overrides,
		53	config_path=config_path,
		54	context="foo config",
		55	error_cls=FooConfigError,
		56	).model_dump()
		57	```
		58
		59	The hand-rolled dataclass helpers (`validate_allowed_keys`, `coerce_to_field_type`,
		60	`dataclass_from_mapping`, `validate_against_defaults`) still work for published leaf
		61	wheels but emit a `DeprecationWarning` (0.8.0).
		62
		63	Models are frozen, but only shallowly (as in pydantic itself): use `tuple` rather
		64	than `list` for sequence fields that must not be mutated after construction.

Importance #28: uv.lock @@ -18,8 +18,17 @@

18	wheels = [	18	wheels = [
19	{ url = "https://files.pythonhosted.org/packages/6a/00/b08f23b7d7e1e14ce01419a467b583edbb93c6cdb8654e54a9cc579cd61f/addict-2.4.0-py3-none-any.whl", hash = "sha256:249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc", size = 3832, upload-time = "2020-11-21T16:21:29.588Z" },	19	{ url = "https://files.pythonhosted.org/packages/6a/00/b08f23b7d7e1e14ce01419a467b583edbb93c6cdb8654e54a9cc579cd61f/addict-2.4.0-py3-none-any.whl", hash = "sha256:249bb56bbfd3cdc2a004ea0ff4c2b6ddc84d53bc2194761636eb314d5cfa5dfc", size = 3832, upload-time = "2020-11-21T16:21:29.588Z" },
20	]	20	]
21		21
		22	[[package]]
		23	name = "annotated-types"
		24	version = "0.8.0"
		25	source = { registry = "https://pypi.org/simple" }
		26	sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
		27	wheels = [
		28	{ url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
		29	]
		30
22	[[package]]	31	[[package]]
23	name = "attrs"	32	name = "attrs"
24	version = "25.4.0"	33	version = "25.4.0"
25	source = { registry = "https://pypi.org/simple" }	34	source = { registry = "https://pypi.org/simple" }

Importance #29: uv.lock @@ -370,8 +379,9 @@

 version = "0.8.0"
 source = { editable = "." }
 dependencies = [
     { name = "numpy" },
+    { name = "pydantic" },
 ]
 [package.optional-dependencies]
 crs = [

Importance #30: uv.lock @@ -390,8 +400,9 @@

 requires-dist = [
     { name = "numpy", specifier = ">=1.20.0" },
     { name = "open3d", marker = "extra == 'memory-guard'", specifier = ">=0.19.0" },
     { name = "psutil", marker = "extra == 'memory-guard'", specifier = ">=5.8.0" },
+    { name = "pydantic", specifier = ">=2.7" },
     { name = "pyproj", marker = "extra == 'crs'", specifier = ">=3.4.0" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=7.0.0" },
     { name = "scikit-learn", marker = "extra == 'memory-guard'", specifier = ">=1.0.0" },
 ]

Importance #31: uv.lock @@ -1050,8 +1061,125 @@

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		1181
1054	[[package]]	1182	[[package]]
1055	name = "pygments"	1183	name = "pygments"
1056	version = "2.19.2"	1184	version = "2.19.2"
1057	source = { registry = "https://pypi.org/simple" }	1185	source = { registry = "https://pypi.org/simple" }

Importance #32: uv.lock @@ -1552,8 +1680,20 @@

1552	wheels = [	1680	wheels = [
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1554	]	1682	]
1555		1683
		1684	[[package]]
		1685	name = "typing-inspection"
		1686	version = "0.4.4"
		1687	source = { registry = "https://pypi.org/simple" }
		1688	dependencies = [
		1689	{ name = "typing-extensions" },
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		1695
1556	[[package]]	1696	[[package]]
1557	name = "tzdata"	1697	name = "tzdata"
1558	version = "2025.3"	1698	version = "2025.3"
1559	source = { registry = "https://pypi.org/simple" }	1699	source = { registry = "https://pypi.org/simple" }

Importance #33: pyproject.toml @@ -4,8 +4,9 @@

 description = "Shared data structures for the 3D AI LIDAR processing pipeline"
 requires-python = ">=3.11"
 dependencies = [
     "numpy>=1.20.0",
+    "pydantic>=2.7",
 ]
 [project.optional-dependencies]
 dev = ["pytest>=7.0.0"]
 crs = ["pyproj>=3.4.0"]

Importance #34: src/iolabs/common/init.py @@ -4,8 +4,9 @@

     atomic_io,
     cli,
     color_intensity_data,
     config_loader,
+    config_model,
     crs,
     diagnostic_data,
     ground_mask_io,
     indexed_ordered_dict,

Importance #35: src/iolabs/common/init.py @@ -23,8 +24,9 @@

     configure_logging,
 )
 from .config_loader import (
     ConfigError,
+    coerce_config_value,
     coerce_to_field_type,
     dataclass_from_mapping,
     deep_merge_dicts,
     default_config_path,

Importance #36: src/iolabs/common/init.py @@ -32,14 +34,21 @@

     parse_set_overrides,
     validate_against_defaults,
     validate_allowed_keys,
 )
+from .config_model import (
+    ConfigModel,
+    format_validation_error,
+    load_config,
+    validate_config,
+)
 __all__ = [
     "atomic_io",
     "cli",
     "color_intensity_data",
     "config_loader",
+    "config_model",
     "crs",
     "diagnostic_data",
     "ground_mask_io",
     "indexed_ordered_dict",

Importance #37: src/iolabs/common/init.py @@ -53,13 +62,18 @@

     "LOG_LEVEL_CHOICES",
     "add_log_level_argument",
     "configure_logging",
     "ConfigError",
+    "ConfigModel",
+    "coerce_config_value",
     "coerce_to_field_type",
     "dataclass_from_mapping",
     "default_config_path",
     "deep_merge_dicts",
+    "format_validation_error",
+    "load_config",
     "load_packaged_json",
+    "validate_config",
     "parse_set_overrides",
     "validate_against_defaults",
     "validate_allowed_keys",
 ]

Importance #38: src/iolabs/common/config_loader.py @@ -1,23 +1,73 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

1	"""Packaged-JSON config loading, deep-merge, key validation and value coercion.	1	"""Packaged-JSON config loading, deep-merge, key validation and value coercion.
2		2
3	Covers the whole config path shared by the pipeline packages: load the	3	Covers the whole config path shared by the pipeline packages: load the
4	packaged default JSON, deep-merge CLI ``--set`` overrides onto it, reject	4	packaged default JSON, deep-merge CLI ``--set`` overrides onto it, reject
5	unknown keys (flat or against the defaults tree) and coerce raw JSON/CLI	5	unknown keys and coerce raw JSON/CLI values to the declared field types.
6	values to the declared dataclass field types.	6
		7	The current way to declare a config is a pydantic model derived from
		8	`ConfigModel`, validated by :func:`load_config`; both are defined in
		9	:mod:`iolabs.common.config_model` and re-exported here, together with
		10	:func:`validate_config` and :func:`format_validation_error`. The canonical
		11	package pattern is::
		12
		13	from typing import Any, Literal
		14
		15	from iolabs.common import config_loader
		16
		17
		18	class FooGroundConfig(config_loader.ConfigModel):
		19	cell_m: float = 0.5
		20
		21
		22	class FooConfig(config_loader.ConfigModel):
		23	mode: Literal["fast", "exact"] = "fast"
		24	ground: FooGroundConfig = FooGroundConfig()
		25
		26
		27	class FooConfigError(config_loader.ConfigError):
		28	\"\"\"Raised for an invalid foo config.\"\"\"
		29
		30
		31	def build_foo_config(overrides=None, config_path=None) -> dict[str, Any]:
		32	return config_loader.load_config(
		33	FooConfig,
		34	package="iolabs_foo",
		35	filename="default_config.json",
		36	overrides=overrides,
		37	config_path=config_path,
		38	context="foo config",
		39	error_cls=FooConfigError,
		40	).model_dump()
		41
		42	`ConfigError`, `default_config_path`, `load_packaged_json`, `deep_merge_dicts`
		43	and `parse_set_overrides` stay first-class. The hand-rolled dataclass helpers
		44	(`validate_allowed_keys`, `coerce_to_field_type`, `dataclass_from_mapping`,
		45	`validate_against_defaults`) still work for published leaf wheels but emit a
		46	`DeprecationWarning`.
7	"""	47	"""
8		48
9	from __future__ import annotations	49	from __future__ import annotations
10		50
		51	import enum
11	import json	52	import json
		53	import logging
		54	import numbers
12	import sys	55	import sys
		56	import warnings
13	from collections.abc import Collection, Mapping, Sequence	57	from collections.abc import Collection, Mapping, Sequence
14	from dataclasses import fields, is_dataclass	58	from dataclasses import fields, is_dataclass
15	from importlib import resources	59	from importlib import resources
16	from pathlib import Path	60	from pathlib import Path
17	from types import UnionType	61	from types import UnionType
18	from typing import Any, Literal, TypeVar, Union, get_args, get_origin, get_type_hints	62	from typing import Any, Literal, TypeVar, Union, get_args, get_origin, get_type_hints
19		63
		64	logger = logging.getLogger(__name__)
		65
		66	_PYDANTIC_EXPORTS = frozenset(
		67	{"ConfigModel", "load_config", "validate_config", "format_validation_error"}
		68	)
		69
20		70
21	class ConfigError(ValueError):	71	class ConfigError(ValueError):
22	"""Raised when a packaged-JSON config contains unsupported keys/values."""	72	"""Raised when a packaged-JSON config contains unsupported keys/values."""
23		73

Importance #39: src/iolabs/common/config_loader.py @@ -81,8 +131,11 @@

     error_cls: type[ValueError] = ConfigError,
 ) -> None:
     """Raise *error_cls* when *config* contains keys outside *allowed*.
+    Deprecated: derive a `ConfigModel` (``extra="forbid"``) and validate it with
+    :func:`load_config` / :func:`validate_config` instead.
     Args:
         config: The config mapping whose keys are checked.
         allowed: The keys *config* may hold.
         context: Human-readable config name used in the error message, e.g.

Importance #40: src/iolabs/common/config_loader.py @@ -96,8 +149,20 @@

96		149
97	Raises:	150	Raises:
98	error_cls: config holds one or more keys outside allowed.	151	error_cls: config holds one or more keys outside allowed.
99	"""	152	"""
		153	_warn_deprecated("validate_allowed_keys")
		154	_validate_allowed_keys(config, allowed, context=context, error_cls=error_cls)
		155
		156
		157	def _validate_allowed_keys(
		158	config: Mapping[str, Any],
		159	allowed: frozenset[str],
		160	*,
		161	context: str,
		162	error_cls: type[ValueError],
		163	) -> None:
		164	"""Raise error_cls when config contains keys outside allowed."""
100	unknown = sorted(set(config) - allowed)	165	unknown = sorted(set(config) - allowed)
101	if unknown:	166	if unknown:
102	raise error_cls(	167	raise error_cls(
103	f"Unknown {context} key(s): {', '.join(unknown)}. "	168	f"Unknown {context} key(s): {', '.join(unknown)}. "

Importance #41: src/iolabs/common/config_loader.py @@ -227,29 +292,34 @@

       tokens ``1/true/yes/on`` and ``0/false/no/off``. Anything else raises, so
       typos such as ``"flase"`` are rejected instead of read as ``False``.
     * ``int``: accepts ints, integral floats (``3.0``) and numeric strings
       including exponent form (``"1e3"`` -> ``1000``). Non-integral values
-      (``3.7``) and bools are rejected rather than truncated.
+      (``3.7``), bools and non-numeric types (``bytes``, ``None``, ...) are
+      rejected rather than truncated or re-parsed.
     * ``float``: accepts ints, floats and numeric strings (including ``"nan"``
       and ``"inf"``: finiteness is the caller's domain check, not this one).
-      ``bool`` is rejected, as for ``int``; conversion errors are wrapped in
+      ``bool`` and non-numeric types (``bytes``, ``None``, ...) are rejected,
-      *error_cls*.
+      as for ``int``; conversion errors are wrapped in *error_cls*.
     * ``str``: accepts ``str`` only.
     * ``X | None`` / ``Optional[X]``: ``None`` passes through, otherwise the
       value is coerced to ``X``. Unions of two or more non-``None`` types pass
       through unchanged.
     * ``tuple[...]`` / ``list[...]``: accepts a list or tuple (never a string or
       mapping), coercing each item to the declared item type. Fixed-length
       tuple annotations also check the item count.
-    * ``Literal[...]``: the value must be one of the literal options.
+    * ``Literal[...]``: the value must be one of the literal options; an
+      ``enum`` option also matches its plain value (``"fast"`` for
+      ``Mode.FAST``) and is returned as the member.
     * A nested dataclass type: a mapping value is built into that dataclass by
       :func:`dataclass_from_mapping` (unknown keys rejected, inner values
       coerced); a value that is already an instance passes through.
     Any other declared type (``dict``, ``Any``, an unresolved string
     annotation, a union of two or more non-``None`` types, ...) returns
     *value* unchanged.
+    Deprecated: declare a `ConfigModel` field and let it apply the same matrix.
     Args:
         name: Field name, used only in error messages.
         value: The raw value from JSON or a parsed ``--set`` override.
         declared: The field's declared type (``dataclasses.Field.type`` or a

Importance #42: src/iolabs/common/config_loader.py @@ -258,8 +328,37 @@

The legacy coercion matrix as a non-deprecated public function; strictness (bool never int, str only str) is preserved on purpose.

258		328
259	Returns:	329	Returns:
260	The coerced value, or value unchanged for unsupported declared types.	330	The coerced value, or value unchanged for unsupported declared types.
261		331
		332	Raises:
		333	error_cls: value is not valid for declared.
		334	"""
		335	_warn_deprecated("coerce_to_field_type")
		336	return coerce_config_value(name, value, declared, error_cls=error_cls)
		337
		338
		339	def coerce_config_value(
		340	name: str,
		341	value: Any,
		342	declared: Any,
		343	*,
		344	error_cls: type[ValueError] = ConfigError,
		345	) -> Any:
		346	"""Coerce one raw config value to declared, the fleet accepted-input matrix.
		347
		348	Implementation shared by `ConfigModel` (per-field before-validator) and the
		349	deprecated :func:`coerce_to_field_type`, whose docstring is the spec of the
		350	accepted inputs.
		351
		352	Args:
		353	name: Field name, used only in error messages.
		354	value: The raw value from JSON or a parsed ``--set`` override.
		355	declared: The field's declared type.
		356	error_cls: Exception class raised for values that cannot be coerced.
		357
		358	Returns:
		359	The coerced value, or value unchanged for unsupported declared types.
		360
262	Raises:	361	Raises:
263	error_cls: value is not valid for declared.	362	error_cls: value is not valid for declared.
264	"""	363	"""
265	if isinstance(declared, str):	364	if isinstance(declared, str):

Importance #43: src/iolabs/common/config_loader.py @@ -285,9 +384,9 @@

285	return _coerce_sequence(	384	return _coerce_sequence(
286	name, value, get_args(declared), target=list, error_cls=error_cls	385	name, value, get_args(declared), target=list, error_cls=error_cls
287	)	386	)
288	if isinstance(declared, type) and is_dataclass(declared) and isinstance(value, Mapping):	387	if isinstance(declared, type) and is_dataclass(declared) and isinstance(value, Mapping):
289	return dataclass_from_mapping(declared, value, context=name, error_cls=error_cls)	388	return _dataclass_from_mapping(declared, value, context=name, error_cls=error_cls)
290	return value	389	return value
291		390
292		391
293	def _coerce_bool(name: str, value: Any, *, error_cls: type[ValueError]) -> bool:	392	def _coerce_bool(name: str, value: Any, *, error_cls: type[ValueError]) -> bool:

Importance #44: src/iolabs/common/config_loader.py @@ -332,29 +431,30 @@

             raise error_cls(f"Invalid int for '{name}': {value!r}.") from exc
         if not as_float.is_integer():
             raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
         return int(as_float)
-    try:
+    if isinstance(value, numbers.Real):
         as_float = float(value)
-    except (TypeError, ValueError) as exc:
+        if not as_float.is_integer():
-        raise error_cls(
+            raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
-            f"Invalid int for '{name}': {value!r} ({type(value).__name__})."
+        return int(as_float)
-        ) from exc
+    raise error_cls(f"Invalid int for '{name}': {value!r} ({type(value).__name__}).")
-    if not as_float.is_integer():
-        raise error_cls(f"Invalid int for '{name}': {value!r} is not an integral value.")
-    return int(as_float)
 def _coerce_float(name: str, value: Any, *, error_cls: type[ValueError]) -> float:
     """Parse a float; wrap conversion errors in *error_cls*."""
     if isinstance(value, bool):
         raise error_cls(f"Invalid float for '{name}': {value!r} ({type(value).__name__}).")
-    try:
+    if isinstance(value, str):
+        try:
+            return float(value)
+        except ValueError as exc:
+            raise error_cls(
+                f"Invalid float for '{name}': {value!r} ({type(value).__name__})."
+            ) from exc
+    if isinstance(value, numbers.Real):
         return float(value)
-    except (TypeError, ValueError) as exc:
+    raise error_cls(f"Invalid float for '{name}': {value!r} ({type(value).__name__}).")
-        raise error_cls(
-            f"Invalid float for '{name}': {value!r} ({type(value).__name__})."
-        ) from exc
 def _coerce_str(name: str, value: Any, *, error_cls: type[ValueError]) -> str:
     """Accept a string as-is; reject every other type."""

Importance #45: src/iolabs/common/config_loader.py @@ -369,12 +469,21 @@

     options: tuple[Any, ...],
     *,
     error_cls: type[ValueError],
 ) -> Any:
-    """Check *value* against the options of a ``Literal`` annotation."""
+    """Check *value* against the options of a ``Literal`` annotation.
+    An option that is an `enum.Enum` member also matches its plain
+    JSON-representable value (``"fast"`` for ``Mode.FAST``), as pydantic does;
+    the member is returned. Types must match exactly otherwise, so ``True``
+    never satisfies ``Literal[1]``.
+    """
     for option in options:
         if type(option) is type(value) and option == value:
             return option
+        if isinstance(option, enum.Enum) and type(option.value) is type(value):
+            if option.value == value:
+                return option
     allowed = ", ".join(repr(option) for option in options)
     raise error_cls(f"Invalid value for '{name}': {value!r}. Expected one of: {allowed}.")

Importance #46: src/iolabs/common/config_loader.py @@ -390,9 +499,9 @@

390	return None	499	return None
391	candidates = [member for member in members if member is not type(None)]	500	candidates = [member for member in members if member is not type(None)]
392	if len(candidates) != 1:	501	if len(candidates) != 1:
393	return value	502	return value
394	return coerce_to_field_type(name, value, candidates[0], error_cls=error_cls)	503	return coerce_config_value(name, value, candidates[0], error_cls=error_cls)
395		504
396		505
397	def _coerce_sequence(	506	def _coerce_sequence(
398	name: str,	507	name: str,

Importance #47: src/iolabs/common/config_loader.py @@ -420,9 +529,9 @@

420	item_types = [args[0]] * len(items)	529	item_types = [args[0]] * len(items)
421	if not item_types:	530	if not item_types:
422	return target(items)	531	return target(items)
423	coerced = [	532	coerced = [
424	coerce_to_field_type(f"{name}[{index}]", item, item_type, error_cls=error_cls)	533	coerce_config_value(f"{name}[{index}]", item, item_type, error_cls=error_cls)
425	for index, (item, item_type) in enumerate(zip(items, item_types, strict=True))	534	for index, (item, item_type) in enumerate(zip(items, item_types, strict=True))
426	]	535	]
427	return target(coerced)	536	return target(coerced)
428		537

Importance #48: src/iolabs/common/config_loader.py @@ -468,18 +577,33 @@

         TypeError: *cls* is not a dataclass type, a field annotation cannot be
             resolved at runtime (unless ``coerce=False``), or a required field
             is missing from *raw*.
     """
+    _warn_deprecated("dataclass_from_mapping")
+    return _dataclass_from_mapping(
+        cls, raw, context=context, error_cls=error_cls, coerce=coerce
+    )
+def _dataclass_from_mapping(
+    cls: type[_T],
+    raw: Mapping[str, Any],
+    *,
+    context: str,
+    error_cls: type[ValueError],
+    coerce: bool = True,
+) -> _T:
+    """Build a dataclass instance from a raw mapping (implementation)."""
     if not is_dataclass(cls) or not isinstance(cls, type):
         raise TypeError(f"dataclass_from_mapping requires a dataclass type, got {cls!r}")
     init_fields = [field for field in fields(cls) if field.init]
     allowed = frozenset(field.name for field in init_fields)
-    validate_allowed_keys(raw, allowed, context=context, error_cls=error_cls)
+    _validate_allowed_keys(raw, allowed, context=context, error_cls=error_cls)
     if not coerce:
         return cls(**dict(raw))
     declared_types = _resolve_field_types(cls, init_fields)
     values = {
-        name: coerce_to_field_type(name, value, declared_types[name], error_cls=error_cls)
+        name: coerce_config_value(name, value, declared_types[name], error_cls=error_cls)
         for name, value in raw.items()
     }
     return cls(**values)

Importance #49: src/iolabs/common/config_loader.py @@ -564,8 +688,11 @@

     node's keys. Recursion stops where *defaults* holds a non-mapping leaf, so
     leaf values are never inspected. The first offending node raises, naming
     the dotted context path (``"cluster-stepper config.lane_segment_width"``).
+    Deprecated: a `ConfigModel` with ``extra="forbid"`` is the schema now; use
+    :func:`load_config` / :func:`validate_config`.
     Args:
         config: The raw config node to validate (usually a dict).
         defaults: The corresponding node of the packaged defaults.
         context: Human-readable name of the root node, used as the error

Importance #50: src/iolabs/common/config_loader.py @@ -586,8 +713,9 @@

         error_cls: A node of *config* is not a mapping where *defaults* has
             one, or holds a key absent from both *defaults* and
             *allowed_extra_keys*.
     """
+    _warn_deprecated("validate_against_defaults")
     _validate_against_defaults(
         config,
         defaults,
         context=context,

Importance #51: src/iolabs/common/config_loader.py @@ -638,4 +766,28 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

638		766
639	def _dotted(prefix: str, key: str) -> str:	767	def _dotted(prefix: str, key: str) -> str:
640	"""Join a dotted path prefix with a key."""	768	"""Join a dotted path prefix with a key."""
641	return f"{prefix}.{key}" if prefix else key	769	return f"{prefix}.{key}" if prefix else key
		770
		771
		772	def _warn_deprecated(name: str) -> None:
		773	"""Emit a `DeprecationWarning` for a legacy hand-rolled config helper."""
		774	warnings.warn(
		775	f"config_loader.{name} is deprecated; derive a config_loader.ConfigModel "
		776	f"and use config_loader.load_config/validate_config instead.",
		777	DeprecationWarning,
		778	stacklevel=3,
		779	)
		780
		781
		782	def __getattr__(name: str) -> Any:
		783	"""Re-export the pydantic config layer lazily, avoiding an import cycle."""
		784	if name in _PYDANTIC_EXPORTS:
		785	from iolabs.common import config_model
		786
		787	return getattr(config_model, name)
		788	raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
		789
		790
		791	def __dir__() -> list[str]:
		792	"""List the lazy pydantic re-exports alongside the module's own names."""
		793	return sorted(set(globals()) \| _PYDANTIC_EXPORTS)

Importance #52: src/iolabs/common/config_model.py @@ -0,0 +1,394 @@

Base model: extra=forbid, frozen, validate_default; the before-validator routes every field through the legacy coercion matrix.

	1	"""Pydantic-v2 config layer for the pipeline packages.
	2
	3	`ConfigModel` is the base class every fleet package derives its config models
	4	from. It keeps the accepted-input matrix of the hand-rolled coercion helpers in
	5	:mod:`iolabs.common.config_loader` (see
	6	:func:`iolabs.common.config_loader.coerce_to_field_type` for the spec) while
	7	letting package authors write plain ``x: int`` / ``y: float`` / ``z: bool`` /
	8	``s: str`` fields; `Literal`, sequences, and nested models are validated by
	9	pydantic itself.
	10
	11	Canonical package pattern::
	12
	13	from collections.abc import Mapping
	14	from pathlib import Path
	15	from typing import Any, Literal
	16
	17	from iolabs.common import config_loader
	18
	19
	20	class FooGroundConfig(config_loader.ConfigModel):
	21	cell_m: float = 0.5
	22	enabled: bool = True
	23
	24
	25	class FooConfig(config_loader.ConfigModel):
	26	mode: Literal["fast", "exact"] = "fast"
	27	ground: FooGroundConfig = FooGroundConfig()
	28
	29
	30	class FooConfigError(config_loader.ConfigError):
	31	\"\"\"Raised for an invalid foo config.\"\"\"
	32
	33
	34	def build_foo_config(
	35	overrides: Mapping[str, Any] \| None = None,
	36	config_path: str \| Path \| None = None,
	37	) -> dict[str, Any]:
	38	return config_loader.load_config(
	39	FooConfig,
	40	package="iolabs_foo",
	41	filename="default_config.json",
	42	overrides=overrides,
	43	config_path=config_path,
	44	context="foo config",
	45	error_cls=FooConfigError,
	46	).model_dump()
	47
	48	Unknown keys are rejected (``extra="forbid"``) with the same message shape as
	49	:func:`iolabs.common.config_loader.validate_allowed_keys`; instances are frozen,
	50	so no field can be rebound after construction. Freezing is shallow, as in
	51	pydantic itself: a ``list``-valued field is still a mutable list, so prefer
	52	``tuple`` for sequence fields that must not change.
	53	"""
	54
	55	from __future__ import annotations
	56
	57	import json
	58	import logging
	59	from collections.abc import Mapping
	60	from pathlib import Path
	61	from typing import Any, TypeVar, get_args
	62
	63	import pydantic
	64	from pydantic import fields as pydantic_fields
	65
	66	from iolabs.common import config_loader
	67
	68	logger = logging.getLogger(__name__)
	69
	70	_M = TypeVar("_M", bound="ConfigModel")
	71
	72	_VALUE_ERROR_PREFIX = "Value error, "
	73
	74	_MODEL_REGISTRY: dict[str, type[ConfigModel] \| None] = {}
	75
	76
	77	class ConfigModel(pydantic.BaseModel):
	78	"""Frozen, extra-forbidding base model with fleet scalar coercion.
	79
	80	Every field is passed through the accepted-input matrix of
	81	:func:`iolabs.common.config_loader.coerce_to_field_type` before pydantic
	82	validates it, so ``"1e3"`` reaches an ``int`` field as ``1000``, ``"on"``
	83	reaches a ``bool`` field as ``True``, and ``True`` is rejected for an
	84	``int`` field instead of becoming ``1``.
	85	"""
	86
	87	model_config = pydantic.ConfigDict(
	88	extra="forbid",
	89	frozen=True,
	90	validate_default=True,
	91	strict=False,
	92	arbitrary_types_allowed=False,
	93	)
	94
	95	def __init_subclass__(cls, **kwargs: Any) -> None:
	96	"""Register the subclass so its error title can be resolved back to it."""
	97	super().__init_subclass__(**kwargs)
	98	_register_model(cls)
	99
	100	@pydantic.field_validator("*", mode="before")
	101	@classmethod
	102	def _coerce_fleet_scalars(cls, value: Any, info: pydantic.ValidationInfo) -> Any:
	103	"""Coerce a raw JSON/CLI value to the field's declared annotation."""
	104	field = cls.model_fields.get(info.field_name or "")
	105	if field is None or field.annotation is None:
	106	return value
	107	return config_loader.coerce_config_value(
	108	info.field_name or "", value, field.annotation
	109	)
	110
	111
	112	def _register_model(model_cls: type[ConfigModel]) -> None:
	113	"""Record model_cls under its name, flagging same-name classes ambiguous."""
	114	name = model_cls.__name__
	115	previous = _MODEL_REGISTRY.get(name, model_cls)
	116	same_origin = previous is not None and (previous.__module__, previous.__qualname__) == (
	117	model_cls.__module__,
	118	model_cls.__qualname__,
	119	)
	120	_MODEL_REGISTRY[name] = model_cls if same_origin else None
	121
	122
	123	def _model_from_title(title: str) -> type[ConfigModel] \| None:
	124	"""Return the `ConfigModel` a validation error title names, when unambiguous."""
	125	return _MODEL_REGISTRY.get(title)
	126
	127
	128	def validate_config(
	129	model_cls: type[_M],
	130	raw: Mapping[str, Any],
	131	*,
	132	context: str,
	133	error_cls: type[ValueError] = config_loader.ConfigError,
	134	) -> _M:
	135	"""Validate a raw mapping into model_cls, wrapping pydantic errors.
	136
	137	Args:
	138	model_cls: The `ConfigModel` subclass to build.
	139	raw: The merged config mapping (packaged defaults plus overrides).
	140	context: Human-readable config name used in error messages, e.g.
	141	``"foo config"``.
	142	error_cls: Exception class raised for unknown keys and bad values.
	143
	144	Returns:
	145	A validated, frozen instance of model_cls.
	146
	147	Raises:
	148	error_cls: raw holds an unknown key, misses a required key, or holds
	149	a value that is not valid for its declared field type.
	150	"""
	151	try:
	152	return model_cls.model_validate(dict(raw))
	153	except pydantic.ValidationError as exc:
	154	raise error_cls(
	155	format_validation_error(exc, context=context, model_cls=model_cls)
	156	) from exc
	157
	158
	159	def load_config(
	160	model_cls: type[_M],
	161	*,
	162	package: str,
	163	filename: str,
	164	overrides: Mapping[str, Any] \| None = None,
	165	config_path: str \| Path \| None = None,
	166	context: str,
	167	error_cls: type[ValueError] = config_loader.ConfigError,
	168	) -> _M:
	169	"""Load, merge and validate a packaged JSON config into model_cls.
	170
	171	The packaged default JSON is read from package/filename, or from
	172	config_path when that is given (the file then replaces the packaged
	173	defaults rather than extending them). overrides is deep-merged on top by
	174	:func:`iolabs.common.config_loader.deep_merge_dicts`, and the result is
	175	validated by :func:`validate_config`.
	176
	177	Args:
	178	model_cls: The `ConfigModel` subclass to build.
	179	package: Import package holding the default JSON, e.g. ``"iolabs_foo"``.
	180	filename: File name of the packaged JSON, e.g. ``"default_config.json"``.
	181	overrides: Mapping merged onto the defaults, e.g. the result of
	182	:func:`iolabs.common.config_loader.parse_set_overrides`.
	183	config_path: Path to a JSON file used instead of the packaged defaults.
	184	context: Human-readable config name used in error messages.
	185	error_cls: Exception class raised for unreadable JSON, unknown keys and
	186	bad values.
	187
	188	Returns:
	189	A validated, frozen instance of model_cls.
	190
	191	Raises:
	192	error_cls: The JSON is malformed, or the merged config is invalid.
	193	OSError: The config file could not be read.
	194	"""
	195	if config_path is not None:
	196	raw = _load_json_file(Path(config_path), error_cls=error_cls)
	197	logger.debug("Loaded %s from %s", context, config_path)
	198	else:
	199	raw = _load_packaged(package, filename, error_cls=error_cls)
	200	logger.debug("Loaded %s defaults from %s:%s", context, package, filename)
	201	if overrides:
	202	raw = config_loader.deep_merge_dicts(raw, dict(overrides))
	203	return validate_config(model_cls, raw, context=context, error_cls=error_cls)
	204
	205
	206	def format_validation_error(
	207	exc: pydantic.ValidationError,
	208	*,
	209	context: str,
	210	model_cls: type[pydantic.BaseModel] \| None = None,
	211	) -> str:
	212	"""Render a pydantic `ValidationError` as a fleet-style config message.
	213
	214	Unknown keys are grouped per section and reported as
	215	``"Unknown {context} key(s): a, b. Allowed keys: ..."``; the section path is
	216	dotted onto context (``"{context}.section"``). Value errors keep the
	217	``"Invalid <type> for '<dotted.field>': <value> ..."`` shape of the legacy
	218	coercion helpers.
	219
	220	Args:
	221	exc: The pydantic validation error.
	222	context: Human-readable config name used as the message prefix.
	223	model_cls: The validated model, used to list the allowed keys of the
	224	offending section. Defaults to the `ConfigModel` named by
	225	``exc.title``; allowed-key lists are omitted when that name is
	226	unknown or shared by several models.
	227
	228	Returns:
	229	A newline-joined message covering every error in exc.
	230	"""
	231	if model_cls is None:
	232	model_cls = _model_from_title(exc.title)
	233	unknown: dict[tuple[Any, ...], list[str]] = {}
	234	lines: list[str] = []
	235	for error in exc.errors():
	236	loc = tuple(error["loc"])
	237	if error["type"] == "extra_forbidden" and loc:
	238	unknown.setdefault(loc[:-1], []).append(str(loc[-1]))
	239	else:
	240	lines.append(_format_single_error(error, context=context))
	241	unknown_lines = [
	242	_format_unknown_keys(prefix, keys, context=context, model_cls=model_cls)
	243	for prefix, keys in sorted(unknown.items(), key=lambda item: [str(p) for p in item[0]])
	244	]
	245	return "\n".join(unknown_lines + lines)
	246
	247
	248	def _format_unknown_keys(
	249	prefix: tuple[Any, ...],
	250	keys: list[str],
	251	*,
	252	context: str,
	253	model_cls: type[pydantic.BaseModel] \| None,
	254	) -> str:
	255	"""Return the ``Unknown ... key(s)`` line for one section."""
	256	node = ".".join([context, *(str(part) for part in prefix)])
	257	message = f"Unknown {node} key(s): {', '.join(sorted(keys))}."
	258	allowed = _allowed_keys(model_cls, prefix)
	259	if allowed:
	260	message = f"{message} Allowed keys: {', '.join(sorted(allowed))}"
	261	return message
	262
	263
	264	def _format_single_error(error: Mapping[str, Any], *, context: str) -> str:
	265	"""Return one non-``extra_forbidden`` error as a readable line."""
	266	loc = tuple(error["loc"])
	267	dotted = ".".join(str(part) for part in loc)
	268	message = str(error["msg"])
	269	if error["type"] == "missing":
	270	return f"Missing required {context} key: '{dotted}'"
	271	if message.startswith(_VALUE_ERROR_PREFIX):
	272	message = message[len(_VALUE_ERROR_PREFIX):]
	273	rewritten = _rewrite_field_name(message, loc)
	274	if rewritten is not None:
	275	return rewritten
	276	return f"Invalid value for '{dotted}': {error.get('input')!r}. {message}."
	277
	278
	279	def _rewrite_field_name(message: str, loc: tuple[Any, ...]) -> str \| None:
	280	"""Replace the local field name of a coercion message with its dotted path.
	281
	282	Args:
	283	message: A coercion message such as ``"Invalid int for 'x': 3.7 ..."``.
	284	loc: The pydantic error location of the offending field.
	285
	286	Returns:
	287	The message with the dotted path substituted, or ``None`` when
	288	message does not have the coercion shape.
	289	"""
	290	head, _, tail = message.partition(" for '")
	291	name, quote, rest = tail.partition("': ")
	292	if not head.startswith("Invalid ") or not quote or "'" in name:
	293	return None
	294	dotted = ".".join([*(str(part) for part in loc[:-1]), name])
	295	return f"{head} for '{dotted}': {rest}"
	296
	297
	298	def _allowed_keys(
	299	model_cls: type[pydantic.BaseModel] \| None,
	300	loc: tuple[Any, ...],
	301	) -> list[str]:
	302	"""Return the keys accepted by the model reached by loc, if resolvable.
	303
	304	An aliased field is listed under its alias, i.e. under the key the config
	305	file must actually use, plus its field name when the model also populates
	306	by name.
	307	"""
	308	current = _model_at_loc(model_cls, loc)
	309	if current is None:
	310	return []
	311	by_name = bool(
	312	current.model_config.get("populate_by_name")
	313	or current.model_config.get("validate_by_name")
	314	)
	315	keys: list[str] = []
	316	for name, field in current.model_fields.items():
	317	alias = _validation_alias(field)
	318	if alias is None:
	319	keys.append(name)
	320	continue
	321	keys.append(alias)
	322	if by_name:
	323	keys.append(name)
	324	return keys
	325
	326
	327	def _validation_alias(field: pydantic_fields.FieldInfo) -> str \| None:
	328	"""Return the single string alias field is validated under, if any."""
	329	alias = field.validation_alias if field.validation_alias is not None else field.alias
	330	return alias if isinstance(alias, str) else None
	331
	332
	333	def _model_at_loc(
	334	model_cls: type[pydantic.BaseModel] \| None,
	335	loc: tuple[Any, ...],
	336	) -> type[pydantic.BaseModel] \| None:
	337	"""Walk loc from model_cls down to the model owning that location."""
	338	current = model_cls
	339	for part in loc:
	340	if current is None:
	341	return None
	342	if isinstance(part, int):
	343	continue
	344	field = _field_by_key(current, str(part))
	345	current = _unwrap_model(field.annotation) if field is not None else None
	346	return current
	347
	348
	349	def _field_by_key(
	350	model_cls: type[pydantic.BaseModel],
	351	key: str,
	352	) -> pydantic_fields.FieldInfo \| None:
	353	"""Return the field of model_cls addressed by key (alias or name)."""
	354	for name, field in model_cls.model_fields.items():
	355	if key in (_validation_alias(field), name):
	356	return field
	357	return None
	358
	359
	360	def _unwrap_model(annotation: Any) -> type[pydantic.BaseModel] \| None:
	361	"""Return the first `BaseModel` subclass inside annotation, if any."""
	362	if isinstance(annotation, type) and issubclass(annotation, pydantic.BaseModel):
	363	return annotation
	364	for arg in get_args(annotation):
	365	found = _unwrap_model(arg)
	366	if found is not None:
	367	return found
	368	return None
	369
	370
	371	def _load_packaged(package: str, filename: str, *, error_cls: type[ValueError]) -> dict[str, Any]:
	372	"""Load the packaged default JSON, wrapping decode errors in error_cls."""
	373	try:
	374	loaded = config_loader.load_packaged_json(package, filename)
	375	except json.JSONDecodeError as exc:
	376	raise error_cls(f"Invalid JSON in packaged config {package}:{filename}: {exc}") from exc
	377	if not isinstance(loaded, dict):
	378	raise error_cls(
	379	f"Packaged config {package}:{filename} must hold a JSON object, "
	380	f"got {type(loaded).__name__}"
	381	)
	382	return loaded
	383
	384
	385	def _load_json_file(path: Path, *, error_cls: type[ValueError]) -> dict[str, Any]:
	386	"""Load a JSON config file, wrapping decode errors in error_cls."""
	387	try:
	388	with path.open("r", encoding="utf-8") as handle:
	389	loaded = json.load(handle)
	390	except json.JSONDecodeError as exc:
	391	raise error_cls(f"Invalid JSON in config file {path}: {exc}") from exc
	392	if not isinstance(loaded, dict):
	393	raise error_cls(f"Config file {path} must hold a JSON object, got {type(loaded).__name__}")
	394	return loaded
0

Importance #53: tests/test_config_loader.py @@ -1,8 +1,9 @@

1	"""Tests for packaged-JSON config loader helpers."""	1	"""Tests for packaged-JSON config loader helpers."""
2		2
3	from __future__ import annotations	3	from __future__ import annotations
4		4
		5	import enum
5	import importlib	6	import importlib
6	import json	7	import json
7	import math	8	import math
8	import sys	9	import sys

Importance #54: tests/test_config_loader.py @@ -29,8 +30,13 @@

Old helpers kept alive for published leaf wheels; warn once per call site.

29	_PACKAGE = "iolabs.common"	30	_PACKAGE = "iolabs.common"
30	_PACKAGED_MODULE_FILENAME = "config_loader.py"	31	_PACKAGED_MODULE_FILENAME = "config_loader.py"
31		32
32		33
		34	# The hand-rolled helpers below are deprecated shims kept for published leaf
		35	# wheels; their DeprecationWarning is expected here.
		36	pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
		37
		38
33	class CustomConfigError(ConfigError):	39	class CustomConfigError(ConfigError):
34	"""Consumer-style ConfigError subclass for error_cls override tests."""	40	"""Consumer-style ConfigError subclass for error_cls override tests."""
35		41
36		42

Importance #55: tests/test_config_loader.py @@ -316,9 +322,9 @@

316	"""Ints, integral floats and numeric strings (incl. exponents) coerce."""	322	"""Ints, integral floats and numeric strings (incl. exponents) coerce."""
317	assert coerce_to_field_type("count", value, int) == expected	323	assert coerce_to_field_type("count", value, int) == expected
318		324
319		325
320	@pytest.mark.parametrize("value", [3.7, -3.7, "3.7", "abc", True, None, []])	326	@pytest.mark.parametrize("value", [3.7, -3.7, "3.7", "abc", True, None, [], b"3", object()])
321	def test_coerce_int_rejects_non_integral_and_bad_tokens(value: object) -> None:	327	def test_coerce_int_rejects_non_integral_and_bad_tokens(value: object) -> None:
322	"""Truncation, bools and bad tokens raise the config error, not ValueError."""	328	"""Truncation, bools and bad tokens raise the config error, not ValueError."""
323	with pytest.raises(ConfigError, match="Invalid int for 'count'"):	329	with pytest.raises(ConfigError, match="Invalid int for 'count'"):
324	coerce_to_field_type("count", value, int)	330	coerce_to_field_type("count", value, int)

Importance #56: tests/test_config_loader.py @@ -334,9 +340,9 @@

334	assert isinstance(result, float)	340	assert isinstance(result, float)
335	assert result == expected	341	assert result == expected
336		342
337		343
338	@pytest.mark.parametrize("value", ["abc", None, [], True])	344	@pytest.mark.parametrize("value", ["abc", None, [], True, b"2.5", object()])
339	def test_coerce_float_rejects_bad_values(value: object) -> None:	345	def test_coerce_float_rejects_bad_values(value: object) -> None:
340	"""Bad tokens and non-numeric types are wrapped in the config error."""	346	"""Bad tokens and non-numeric types are wrapped in the config error."""
341	with pytest.raises(ConfigError, match="Invalid float for 'threshold_m'"):	347	with pytest.raises(ConfigError, match="Invalid float for 'threshold_m'"):
342	coerce_to_field_type("threshold_m", value, float)	348	coerce_to_field_type("threshold_m", value, float)

Importance #57: tests/test_config_loader.py @@ -389,8 +395,28 @@

389	with pytest.raises(ConfigError, match="Expected one of: 'csf', 'plane'"):	395	with pytest.raises(ConfigError, match="Expected one of: 'csf', 'plane'"):
390	coerce_to_field_type("mechanism", "cloth", declared)	396	coerce_to_field_type("mechanism", "cloth", declared)
391		397
392		398
		399	def test_coerce_literal_enum_accepts_the_plain_option_value() -> None:
		400	"""An enum option also matches its plain value and yields the member."""
		401
		402	class Mechanism(enum.StrEnum):
		403	CSF = "csf"
		404	PLANE = "plane"
		405
		406	declared = Literal[Mechanism.CSF, Mechanism.PLANE]
		407	assert coerce_to_field_type("mechanism", "plane", declared) is Mechanism.PLANE
		408	assert coerce_to_field_type("mechanism", Mechanism.CSF, declared) is Mechanism.CSF
		409	with pytest.raises(ConfigError, match="Expected one of"):
		410	coerce_to_field_type("mechanism", "cloth", declared)
		411
		412
		413	def test_coerce_int_literal_still_rejects_bools() -> None:
		414	"""A bool never satisfies Literal[1, 2], unlike plain pydantic."""
		415	with pytest.raises(ConfigError, match="Expected one of"):
		416	coerce_to_field_type("level", True, Literal[1, 2])
		417
		418
393	def test_coerce_unknown_declared_type_passes_through() -> None:	419	def test_coerce_unknown_declared_type_passes_through() -> None:
394	"""Unsupported declared types return the value unchanged."""	420	"""Unsupported declared types return the value unchanged."""
395	payload = {"a": 1}	421	payload = {"a": 1}
396	assert coerce_to_field_type("extras", payload, dict[str, int]) is payload	422	assert coerce_to_field_type("extras", payload, dict[str, int]) is payload

Importance #58: tests/test_config_model.py @@ -0,0 +1,584 @@

	1	"""Tests for the pydantic-v2 config layer (`config_loader.ConfigModel`)."""
	2
	3	from __future__ import annotations
	4
	5	import dataclasses
	6	import enum
	7	import json
	8	import math
	9	import warnings
	10	from pathlib import Path
	11	from typing import Any, Literal
	12	from unittest.mock import patch
	13
	14	import pydantic
	15	import pytest
	16
	17	from iolabs.common import config_loader, config_model
	18
	19	_PACKAGE = "iolabs.common"
	20	_FIXTURE_PATH = Path(__file__).parent / "fixtures" / "config_loader.fixture.json"
	21
	22
	23	class SampleMode(enum.StrEnum):
	24	"""Enum used for Literal-of-enum fields."""
	25
	26	FAST = "fast"
	27	EXACT = "exact"
	28
	29
	30	class SampleConfigError(config_loader.ConfigError):
	31	"""Consumer-style config error."""
	32
	33
	34	class GroundSection(config_loader.ConfigModel):
	35	"""Nested section mirroring a packaged JSON sub-object."""
	36
	37	cell_m: float = 0.5
	38	percentile: float = 5.0
	39
	40
	41	class SampleConfig(config_loader.ConfigModel):
	42	"""Sample config exercising every supported field kind."""
	43
	44	name: str = "run"
	45	count: int = 3
	46	threshold_m: float = 0.5
	47	enabled: bool = True
	48	mechanism: Literal["csf", "plane"] = "csf"
	49	tag: str \| None = None
	50	band_m: tuple[float, float] = (0.0, 1.0)
	51	weights: list[int] = [1, 2]
	52	ground: GroundSection = GroundSection()
	53
	54
	55	class FixtureConfig(config_loader.ConfigModel):
	56	"""Config matching ``tests/fixtures/config_loader.fixture.json``."""
	57
	58	enabled: bool = False
	59	ground: GroundSection = GroundSection()
	60
	61
	62	# --- coercion matrix ---------------------------------------------------------
	63
	64
	65	@pytest.mark.parametrize(
	66	("value", "expected"),
	67	[
	68	(True, True),
	69	(False, False),
	70	(1, True),
	71	(0, False),
	72	("1", True),
	73	("TRUE", True),
	74	(" yes ", True),
	75	("On", True),
	76	("0", False),
	77	("false", False),
	78	("NO", False),
	79	("off", False),
	80	],
	81	)
	82	def test_bool_field_accepts_matrix(value: object, expected: bool) -> None:
	83	"""bool fields accept real bools, 0/1 and the documented tokens."""
	84	assert SampleConfig(enabled=value).enabled is expected
	85
	86
	87	@pytest.mark.parametrize("value", ["flase", "y", "", 2, -1, 1.0, None, []])
	88	def test_bool_field_rejects_everything_else(value: object) -> None:
	89	"""bool fields reject typos, out-of-range ints and non-scalar values."""
	90	with pytest.raises(config_loader.ConfigError):
	91	config_loader.validate_config(
	92	SampleConfig, {"enabled": value}, context="sample config"
	93	)
	94
	95
	96	@pytest.mark.parametrize(
	97	("value", "expected"),
	98	[(7, 7), (3.0, 3), ("42", 42), (" 42 ", 42), ("1e3", 1000), ("-5", -5)],
	99	)
	100	def test_int_field_accepts_matrix(value: object, expected: int) -> None:
	101	"""int fields accept ints, integral floats and numeric strings."""
	102	assert SampleConfig(count=value).count == expected
	103
	104
	105	@pytest.mark.parametrize("value", [True, False, 3.7, "3.7", "abc", None, "1e3.5"])
	106	def test_int_field_rejects_bools_and_non_integral(value: object) -> None:
	107	"""int fields reject bools, fractional values and bad tokens."""
	108	with pytest.raises(config_loader.ConfigError):
	109	config_loader.validate_config(
	110	SampleConfig, {"count": value}, context="sample config"
	111	)
	112
	113
	114	@pytest.mark.parametrize(
	115	("value", "expected"),
	116	[(2, 2.0), (2.5, 2.5), ("2.5", 2.5), (" 1e-2 ", 0.01), ("inf", math.inf)],
	117	)
	118	def test_float_field_accepts_matrix(value: object, expected: float) -> None:
	119	"""float fields accept ints, floats and numeric strings incl. inf."""
	120	assert SampleConfig(threshold_m=value).threshold_m == expected
	121
	122
	123	def test_float_field_accepts_nan() -> None:
	124	"""float fields accept 'nan'; finiteness is a domain check, not a type one."""
	125	assert math.isnan(SampleConfig(threshold_m="nan").threshold_m)
	126
	127
	128	@pytest.mark.parametrize("value", [True, False, "abc", None, []])
	129	def test_float_field_rejects_bools_and_bad_tokens(value: object) -> None:
	130	"""float fields reject bools and non-numeric values."""
	131	with pytest.raises(config_loader.ConfigError):
	132	config_loader.validate_config(
	133	SampleConfig, {"threshold_m": value}, context="sample config"
	134	)
	135
	136
	137	@pytest.mark.parametrize("value", [b"3", b"2.5", object(), {"a": 1}])
	138	def test_numeric_fields_reject_non_numeric_types(value: object) -> None:
	139	"""int/float fields reject bytes and other types float() happens to eat."""
	140	for field in ("count", "threshold_m"):
	141	with pytest.raises(config_loader.ConfigError):
	142	config_loader.validate_config(
	143	SampleConfig, {field: value}, context="sample config"
	144	)
	145
	146
	147	@pytest.mark.parametrize("value", [3, 3.5, True, None, ["a"]])
	148	def test_str_field_rejects_non_strings(value: object) -> None:
	149	"""str fields accept strings only - no int -> str coercion."""
	150	with pytest.raises(config_loader.ConfigError):
	151	config_loader.validate_config(
	152	SampleConfig, {"name": value}, context="sample config"
	153	)
	154
	155
	156	def test_str_field_accepts_strings() -> None:
	157	"""str fields pass strings through unchanged."""
	158	assert SampleConfig(name="lidar").name == "lidar"
	159
	160
	161	def test_optional_field_accepts_none_and_inner_type() -> None:
	162	"""``str \| None`` accepts None and applies the str rules otherwise."""
	163	assert SampleConfig(tag=None).tag is None
	164	assert SampleConfig(tag="a").tag == "a"
	165	with pytest.raises(config_loader.ConfigError):
	166	config_loader.validate_config(SampleConfig, {"tag": 3}, context="sample config")
	167
	168
	169	def test_literal_field_accepts_options_and_rejects_others() -> None:
	170	"""Literal fields accept declared options only."""
	171	assert SampleConfig(mechanism="plane").mechanism == "plane"
	172	with pytest.raises(config_loader.ConfigError):
	173	config_loader.validate_config(
	174	SampleConfig, {"mechanism": "ransac"}, context="sample config"
	175	)
	176
	177
	178	def test_literal_enum_field_accepts_the_plain_option_value() -> None:
	179	"""Enum-valued Literal fields accept the JSON value, as plain pydantic does."""
	180
	181	class EnumConfig(config_loader.ConfigModel):
	182	mode: Literal[SampleMode.FAST, SampleMode.EXACT] = SampleMode.FAST
	183
	184	assert EnumConfig.model_validate({"mode": "exact"}).mode is SampleMode.EXACT
	185	assert EnumConfig(mode=SampleMode.FAST).mode is SampleMode.FAST
	186	with pytest.raises(config_loader.ConfigError):
	187	config_loader.validate_config(EnumConfig, {"mode": "ransac"}, context="enum config")
	188
	189
	190	def test_int_literal_still_rejects_bools() -> None:
	191	"""Literal[int] keeps the fleet rule that a bool is not an int."""
	192
	193	class IntLiteral(config_loader.ConfigModel):
	194	level: Literal[1, 2] = 1
	195
	196	assert IntLiteral(level=2).level == 2
	197	with pytest.raises(config_loader.ConfigError):
	198	config_loader.validate_config(IntLiteral, {"level": True}, context="int config")
	199
	200
	201	def test_sequence_items_are_coerced_with_the_same_matrix() -> None:
	202	"""tuple/list items follow the scalar matrix (and reject bools for int)."""
	203	built = SampleConfig(band_m=["0.5", 2], weights=["3", 4.0])
	204	assert built.band_m == (0.5, 2.0)
	205	assert built.weights == [3, 4]
	206	with pytest.raises(config_loader.ConfigError):
	207	config_loader.validate_config(
	208	SampleConfig, {"weights": [True]}, context="sample config"
	209	)
	210
	211
	212	def test_fixed_length_tuple_checks_item_count() -> None:
	213	"""A fixed-length tuple annotation rejects the wrong item count."""
	214	with pytest.raises(config_loader.ConfigError, match="expected 2 item"):
	215	config_loader.validate_config(
	216	SampleConfig, {"band_m": [1.0, 2.0, 3.0]}, context="sample config"
	217	)
	218
	219
	220	def test_nested_section_is_validated_and_coerced() -> None:
	221	"""Nested models are built from mappings with the same scalar rules."""
	222	built = SampleConfig(ground={"cell_m": "0.75", "percentile": 8})
	223	assert built.ground.cell_m == 0.75
	224	assert built.ground.percentile == 8.0
	225
	226
	227	# --- error message shapes ----------------------------------------------------
	228
	229
	230	def test_unknown_top_level_key_message() -> None:
	231	"""Unknown top-level keys read like validate_allowed_keys."""
	232	with pytest.raises(config_loader.ConfigError) as excinfo:
	233	config_loader.validate_config(
	234	SampleConfig, {"nope": 1, "also": 2}, context="sample config"
	235	)
	236	assert str(excinfo.value).startswith("Unknown sample config key(s): also, nope. ")
	237	assert "Allowed keys: band_m, count, enabled, ground, mechanism," in str(excinfo.value)
	238
	239
	240	def test_unknown_nested_key_uses_dotted_context() -> None:
	241	"""Unknown keys inside a section name the dotted section path."""
	242	with pytest.raises(config_loader.ConfigError) as excinfo:
	243	config_loader.validate_config(
	244	SampleConfig, {"ground": {"zzz": 1}}, context="sample config"
	245	)
	246	assert str(excinfo.value) == (
	247	"Unknown sample config.ground key(s): zzz. Allowed keys: cell_m, percentile"
	248	)
	249
	250
	251	def test_value_error_message_uses_dotted_field_path() -> None:
	252	"""Nested value errors name the dotted field path."""
	253	with pytest.raises(config_loader.ConfigError) as excinfo:
	254	config_loader.validate_config(
	255	SampleConfig, {"ground": {"cell_m": "abc"}}, context="sample config"
	256	)
	257	assert str(excinfo.value) == "Invalid float for 'ground.cell_m': 'abc' (str)."
	258
	259
	260	def test_value_error_message_top_level_shape() -> None:
	261	"""Top-level value errors keep the legacy 'Invalid <type> for ...' shape."""
	262	with pytest.raises(config_loader.ConfigError) as excinfo:
	263	config_loader.validate_config(
	264	SampleConfig, {"count": 3.7}, context="sample config"
	265	)
	266	assert str(excinfo.value) == "Invalid int for 'count': 3.7 is not an integral value."
	267
	268
	269	def test_missing_required_key_message() -> None:
	270	"""A missing required field is reported with the context name."""
	271
	272	class Required(config_loader.ConfigModel):
	273	name: str
	274
	275	with pytest.raises(config_loader.ConfigError) as excinfo:
	276	config_loader.validate_config(Required, {}, context="sample config")
	277	assert str(excinfo.value) == "Missing required sample config key: 'name'"
	278
	279
	280	def test_error_cls_override_is_used() -> None:
	281	"""validate_config raises the caller's error class."""
	282	with pytest.raises(SampleConfigError):
	283	config_loader.validate_config(
	284	SampleConfig, {"nope": 1}, context="sample config", error_cls=SampleConfigError
	285	)
	286
	287
	288	def test_format_validation_error_without_model_cls_lists_allowed_keys() -> None:
	289	"""The model is recovered from the error title, so allowed keys stay listed."""
	290	with pytest.raises(Exception) as excinfo:
	291	SampleConfig(nope=1)
	292	message = config_model.format_validation_error(
	293	excinfo.value, context="sample config"
	294	)
	295	assert message.startswith("Unknown sample config key(s): nope. Allowed keys: band_m, ")
	296
	297
	298	def test_format_validation_error_omits_allowed_keys_for_unknown_model() -> None:
	299	"""A foreign model's error still reads well, just without the key list."""
	300
	301	class Foreign(pydantic.BaseModel):
	302	model_config = pydantic.ConfigDict(extra="forbid")
	303
	304	alpha: int = 1
	305
	306	with pytest.raises(pydantic.ValidationError) as excinfo:
	307	Foreign(nope=1)
	308	message = config_model.format_validation_error(excinfo.value, context="probe config")
	309	assert message == "Unknown probe config key(s): nope."
	310
	311
	312	def test_format_validation_error_skips_ambiguous_model_names() -> None:
	313	"""Distinct ConfigModels sharing a name resolve to neither, so no key list."""
	314
	315	def _first() -> type[config_loader.ConfigModel]:
	316	class Twin(config_loader.ConfigModel):
	317	alpha: int = 1
	318
	319	return Twin
	320
	321	def _second() -> type[config_loader.ConfigModel]:
	322	class Twin(config_loader.ConfigModel):
	323	beta: int = 2
	324
	325	return Twin
	326
	327	model, _other = _first(), _second()
	328	with pytest.raises(pydantic.ValidationError) as excinfo:
	329	model(nope=1)
	330	message = config_model.format_validation_error(excinfo.value, context="twin config")
	331	assert message == "Unknown twin config key(s): nope."
	332
	333
	334	def test_format_validation_error_survives_class_redefinition() -> None:
	335	"""Re-running the same class statement is a redefinition, not an ambiguity."""
	336
	337	def _make() -> type[config_loader.ConfigModel]:
	338	class Reloaded(config_loader.ConfigModel):
	339	alpha: int = 1
	340
	341	return Reloaded
	342
	343	_stale, current = _make(), _make()
	344	with pytest.raises(pydantic.ValidationError) as excinfo:
	345	current(nope=1)
	346	message = config_model.format_validation_error(excinfo.value, context="reload config")
	347	assert message == "Unknown reload config key(s): nope. Allowed keys: alpha"
	348
	349
	350	def test_alias_field_reports_the_alias_as_the_allowed_key() -> None:
	351	"""An aliased field is listed (and reported missing) under its alias."""
	352
	353	class Aliased(config_loader.ConfigModel):
	354	internal_name: int = pydantic.Field(alias="external-name")
	355
	356	with pytest.raises(config_loader.ConfigError) as excinfo:
	357	config_loader.validate_config(Aliased, {"internal_name": 3}, context="alias config")
	358	message = str(excinfo.value)
	359	assert "Unknown alias config key(s): internal_name. Allowed keys: external-name" in message
	360	assert "Missing required alias config key: 'external-name'" in message
	361	assert config_loader.validate_config(
	362	Aliased, {"external-name": "3"}, context="alias config"
	363	).internal_name == 3
	364
	365
	366	def test_aliased_section_resolves_nested_allowed_keys() -> None:
	367	"""Unknown keys inside an aliased section list that section's own keys."""
	368
	369	class Outer(config_loader.ConfigModel):
	370	ground: GroundSection = pydantic.Field(
	371	default=GroundSection(), alias="ground-section"
	372	)
	373
	374	with pytest.raises(config_loader.ConfigError) as excinfo:
	375	config_loader.validate_config(
	376	Outer, {"ground-section": {"zzz": 1}}, context="outer config"
	377	)
	378	assert str(excinfo.value) == (
	379	"Unknown outer config.ground-section key(s): zzz. Allowed keys: cell_m, percentile"
	380	)
	381
	382
	383	# --- load_config -------------------------------------------------------------
	384
	385
	386	def test_load_config_reads_packaged_defaults() -> None:
	387	"""load_config validates the packaged JSON into the model."""
	388	with patch(
	389	"iolabs.common.config_loader.default_config_path",
	390	return_value=_FIXTURE_PATH,
	391	):
	392	built = config_loader.load_config(
	393	FixtureConfig,
	394	package=_PACKAGE,
	395	filename="config_loader.fixture.json",
	396	context="fixture config",
	397	)
	398	assert built.enabled is True
	399	assert built.ground.cell_m == 0.75
	400
	401
	402	def test_load_config_deep_merges_overrides() -> None:
	403	"""Overrides are deep-merged onto the defaults before validation."""
	404	with patch(
	405	"iolabs.common.config_loader.default_config_path",
	406	return_value=_FIXTURE_PATH,
	407	):
	408	built = config_loader.load_config(
	409	FixtureConfig,
	410	package=_PACKAGE,
	411	filename="config_loader.fixture.json",
	412	overrides={"ground": {"cell_m": "0.25"}, "enabled": "off"},
	413	context="fixture config",
	414	)
	415	assert built.enabled is False
	416	assert built.ground.cell_m == 0.25
	417	assert built.ground.percentile == 8.0
	418
	419
	420	def test_load_config_uses_config_path_when_given(tmp_path: Path) -> None:
	421	"""config_path replaces the packaged defaults."""
	422	path = tmp_path / "custom.json"
	423	path.write_text(json.dumps({"ground": {"cell_m": 1.5}}), encoding="utf-8")
	424	built = config_loader.load_config(
	425	FixtureConfig,
	426	package=_PACKAGE,
	427	filename="config_loader.fixture.json",
	428	config_path=path,
	429	context="fixture config",
	430	)
	431	assert built.enabled is False
	432	assert built.ground.cell_m == 1.5
	433
	434
	435	def test_load_config_rejects_unknown_key_from_file(tmp_path: Path) -> None:
	436	"""Unknown keys in a config file are reported with the file's context."""
	437	path = tmp_path / "custom.json"
	438	path.write_text(json.dumps({"zzz": 1}), encoding="utf-8")
	439	with pytest.raises(config_loader.ConfigError, match="Unknown fixture config key"):
	440	config_loader.load_config(
	441	FixtureConfig,
	442	package=_PACKAGE,
	443	filename="config_loader.fixture.json",
	444	config_path=path,
	445	context="fixture config",
	446	)
	447
	448
	449	def test_load_config_wraps_malformed_json(tmp_path: Path) -> None:
	450	"""Malformed JSON is wrapped in the caller's error class."""
	451	path = tmp_path / "custom.json"
	452	path.write_text("{oops", encoding="utf-8")
	453	with pytest.raises(SampleConfigError, match="Invalid JSON in config file"):
	454	config_loader.load_config(
	455	FixtureConfig,
	456	package=_PACKAGE,
	457	filename="config_loader.fixture.json",
	458	config_path=path,
	459	context="fixture config",
	460	error_cls=SampleConfigError,
	461	)
	462
	463
	464	def test_load_config_rejects_non_object_json(tmp_path: Path) -> None:
	465	"""A JSON file holding a list is rejected."""
	466	path = tmp_path / "custom.json"
	467	path.write_text("[1, 2]", encoding="utf-8")
	468	with pytest.raises(config_loader.ConfigError, match="must hold a JSON object"):
	469	config_loader.load_config(
	470	FixtureConfig,
	471	package=_PACKAGE,
	472	filename="config_loader.fixture.json",
	473	config_path=path,
	474	context="fixture config",
	475	)
	476
	477
	478	def test_load_config_rejects_non_object_packaged_json(tmp_path: Path) -> None:
	479	"""A packaged default JSON holding a list is rejected like a file one."""
	480	path = tmp_path / "defaults.json"
	481	path.write_text('[["enabled", false]]', encoding="utf-8")
	482	with patch(
	483	"iolabs.common.config_loader.default_config_path",
	484	return_value=path,
	485	):
	486	with pytest.raises(config_loader.ConfigError, match="must hold a JSON object"):
	487	config_loader.load_config(
	488	FixtureConfig,
	489	package=_PACKAGE,
	490	filename="defaults.json",
	491	context="fixture config",
	492	)
	493
	494
	495	# --- model behaviour ---------------------------------------------------------
	496
	497
	498	def test_config_is_frozen() -> None:
	499	"""Built configs cannot be mutated."""
	500	built = SampleConfig()
	501	with pytest.raises(Exception): # noqa: B017 - pydantic raises ValidationError
	502	built.count = 5
	503
	504
	505	def test_model_dump_round_trip_produces_plain_dicts() -> None:
	506	"""model_dump yields plain dicts that validate back into the same config."""
	507	built = SampleConfig(ground={"cell_m": 0.25})
	508	dumped = built.model_dump()
	509	assert isinstance(dumped, dict)
	510	assert isinstance(dumped["ground"], dict)
	511	assert dumped["ground"] == {"cell_m": 0.25, "percentile": 5.0}
	512	assert config_loader.validate_config(
	513	SampleConfig, dumped, context="sample config"
	514	) == built
	515
	516
	517	def test_defaults_are_validated() -> None:
	518	"""validate_default=True catches a bad default at model build time."""
	519
	520	class Bad(config_loader.ConfigModel):
	521	count: int = "abc" # type: ignore[assignment]
	522
	523	with pytest.raises(config_loader.ConfigError):
	524	config_loader.validate_config(Bad, {}, context="sample config")
	525
	526
	527	def test_extra_keys_forbidden_on_direct_construction() -> None:
	528	"""extra='forbid' applies to plain construction too, not just load_config."""
	529	with pytest.raises(Exception): # noqa: B017 - pydantic raises ValidationError
	530	SampleConfig(nope=1)
	531
	532
	533	# --- deprecation shims -------------------------------------------------------
	534
	535
	536	@dataclasses.dataclass(frozen=True)
	537	class LegacySample:
	538	"""Dataclass used to exercise the deprecated mapping helper."""
	539
	540	count: int
	541
	542
	543	@pytest.mark.parametrize(
	544	("name", "call"),
	545	[
	546	(
	547	"validate_allowed_keys",
	548	lambda: config_loader.validate_allowed_keys(
	549	{"a": 1}, frozenset({"a"}), context="ctx"
	550	),
	551	),
	552	("coerce_to_field_type", lambda: config_loader.coerce_to_field_type("x", 1, int)),
	553	(
	554	"dataclass_from_mapping",
	555	lambda: config_loader.dataclass_from_mapping(
	556	LegacySample, {"count": "2"}, context="ctx"
	557	),
	558	),
	559	(
	560	"validate_against_defaults",
	561	lambda: config_loader.validate_against_defaults({"a": 1}, {"a": 1}, context="ctx"),
	562	),
	563	],
	564	)
	565	def test_legacy_helpers_warn(name: str, call: Any) -> None:
	566	"""The hand-rolled helpers still work but are deprecated."""
	567	with pytest.warns(DeprecationWarning, match=name):
	568	call()
	569
	570
	571	def test_lazy_reexports_are_visible_to_dir() -> None:
	572	"""The lazily re-exported pydantic names show up in dir(config_loader)."""
	573	names = dir(config_loader)
	574	assert {"ConfigModel", "load_config", "validate_config", "format_validation_error"} <= set(
	575	names
	576	)
	577	assert names == sorted(names)
	578
	579
	580	def test_coerce_config_value_does_not_warn() -> None:
	581	"""The shared coercion entry point used by ConfigModel is not deprecated."""
	582	with warnings.catch_warnings():
	583	warnings.simplefilter("error", DeprecationWarning)
	584	assert config_loader.coerce_config_value("x", "1e3", int) == 1000
0

Importance #59: uv.lock @@ -18,8 +18,17 @@

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Importance #60: uv.lock @@ -370,8 +379,9 @@

 version = "0.8.0"
 source = { editable = "." }
 dependencies = [
     { name = "numpy" },
+    { name = "pydantic" },
 ]
 [package.optional-dependencies]
 crs = [

Importance #61: uv.lock @@ -390,8 +400,9 @@

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     { name = "numpy", specifier = ">=1.20.0" },
     { name = "open3d", marker = "extra == 'memory-guard'", specifier = ">=0.19.0" },
     { name = "psutil", marker = "extra == 'memory-guard'", specifier = ">=5.8.0" },
+    { name = "pydantic", specifier = ">=2.7" },
     { name = "pyproj", marker = "extra == 'crs'", specifier = ">=3.4.0" },
     { name = "pytest", marker = "extra == 'dev'", specifier = ">=7.0.0" },
     { name = "scikit-learn", marker = "extra == 'memory-guard'", specifier = ">=1.0.0" },
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Importance #62: uv.lock @@ -1050,8 +1061,125 @@

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Importance #2: src/iolabs/common/config_loader.py @@ -227,29 +292,34 @@

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