93 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
			
		
		
	
	
			93 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
# Copyright 2020 The Matrix.org Foundation C.I.C.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Any, Dict, Type, TypeVar
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import jsonschema
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from pydantic import BaseModel, ValidationError, parse_obj_as
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from synapse.config._base import ConfigError
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from synapse.types import JsonDict, StrSequence
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def validate_config(
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    json_schema: JsonDict, config: Any, config_path: StrSequence
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) -> None:
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    """Validates a config setting against a JsonSchema definition
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    This can be used to validate a section of the config file against a schema
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    definition. If the validation fails, a ConfigError is raised with a textual
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    description of the problem.
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    Args:
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        json_schema: the schema to validate against
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        config: the configuration value to be validated
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        config_path: the path within the config file. This will be used as a basis
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           for the error message.
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    Raises:
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        ConfigError, if validation fails.
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    """
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    try:
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        jsonschema.validate(config, json_schema)
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    except jsonschema.ValidationError as e:
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        raise json_error_to_config_error(e, config_path)
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def json_error_to_config_error(
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    e: jsonschema.ValidationError, config_path: StrSequence
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) -> ConfigError:
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    """Converts a json validation error to a user-readable ConfigError
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    Args:
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        e: the exception to be converted
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        config_path: the path within the config file. This will be used as a basis
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           for the error message.
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    Returns:
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        a ConfigError
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    """
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    # copy `config_path` before modifying it.
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    path = list(config_path)
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    for p in list(e.absolute_path):
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        if isinstance(p, int):
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            path.append("<item %i>" % p)
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        else:
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            path.append(str(p))
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    return ConfigError(e.message, path)
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Model = TypeVar("Model", bound=BaseModel)
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def parse_and_validate_mapping(
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    config: Any,
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    model_type: Type[Model],
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) -> Dict[str, Model]:
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    """Parse `config` as a mapping from strings to a given `Model` type.
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    Args:
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        config: The configuration data to check
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        model_type: The BaseModel to validate and parse against.
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    Returns:
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        Fully validated and parsed Dict[str, Model].
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    Raises:
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        ConfigError, if given improper input.
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    """
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    try:
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        # type-ignore: mypy doesn't like constructing `Dict[str, model_type]` because
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        # `model_type` is a runtime variable. Pydantic is fine with this.
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        instances = parse_obj_as(Dict[str, model_type], config)  # type: ignore[valid-type]
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    except ValidationError as e:
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        raise ConfigError(str(e)) from e
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    return instances
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