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#
# This file is licensed under the Affero General Public License (AGPL) version 3.
#
# Copyright 2020 The Matrix.org Foundation C.I.C.
# Copyright (C) 2023 New Vector, Ltd
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# See the GNU Affero General Public License for more details:
# <https://www.gnu.org/licenses/agpl-3.0.html>.
#
# Originally licensed under the Apache License, Version 2.0:
# <http://www.apache.org/licenses/LICENSE-2.0>.
#
# [This file includes modifications made by New Vector Limited]
#
#
from typing import TYPE_CHECKING, Any, Dict, Type, TypeVar
import jsonschema
from synapse._pydantic_compat import HAS_PYDANTIC_V2
if TYPE_CHECKING or HAS_PYDANTIC_V2:
from pydantic.v1 import BaseModel, ValidationError, parse_obj_as
else:
from pydantic import BaseModel, ValidationError, parse_obj_as
from synapse.config._base import ConfigError
from synapse.types import JsonDict, StrSequence
def validate_config(
json_schema: JsonDict, config: Any, config_path: StrSequence
) -> None:
"""Validates a config setting against a JsonSchema definition
This can be used to validate a section of the config file against a schema
definition. If the validation fails, a ConfigError is raised with a textual
description of the problem.
Args:
json_schema: the schema to validate against
config: the configuration value to be validated
config_path: the path within the config file. This will be used as a basis
for the error message.
Raises:
ConfigError, if validation fails.
"""
try:
jsonschema.validate(config, json_schema)
except jsonschema.ValidationError as e:
raise json_error_to_config_error(e, config_path)
def json_error_to_config_error(
e: jsonschema.ValidationError, config_path: StrSequence
) -> ConfigError:
"""Converts a json validation error to a user-readable ConfigError
Args:
e: the exception to be converted
config_path: the path within the config file. This will be used as a basis
for the error message.
Returns:
a ConfigError
"""
# copy `config_path` before modifying it.
path = list(config_path)
for p in list(e.absolute_path):
if isinstance(p, int):
path.append("<item %i>" % p)
else:
path.append(str(p))
return ConfigError(e.message, path)
Model = TypeVar("Model", bound=BaseModel)
def parse_and_validate_mapping(
config: Any,
model_type: Type[Model],
) -> Dict[str, Model]:
"""Parse `config` as a mapping from strings to a given `Model` type.
Args:
config: The configuration data to check
model_type: The BaseModel to validate and parse against.
Returns:
Fully validated and parsed Dict[str, Model].
Raises:
ConfigError, if given improper input.
"""
try:
# type-ignore: mypy doesn't like constructing `Dict[str, model_type]` because
# `model_type` is a runtime variable. Pydantic is fine with this.
instances = parse_obj_as(Dict[str, model_type], config) # type: ignore[valid-type]
except ValidationError as e:
raise ConfigError(str(e)) from e
return instances
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