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- # Copyright 2020 The Matrix.org Foundation C.I.C.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- from typing import Any, Dict, Type, TypeVar
- import jsonschema
- 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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