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During the migration the automated script to update the copyright headers accidentally got rid of some of the existing copyright lines. Reinstate them.
106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
#
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# This file is licensed under the Affero General Public License (AGPL) version 3.
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#
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# Copyright 2020 The Matrix.org Foundation C.I.C.
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# Copyright (C) 2023 New Vector, Ltd
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as
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# published by the Free Software Foundation, either version 3 of the
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# License, or (at your option) any later version.
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#
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# See the GNU Affero General Public License for more details:
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# <https://www.gnu.org/licenses/agpl-3.0.html>.
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#
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# Originally licensed under the Apache License, Version 2.0:
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# <http://www.apache.org/licenses/LICENSE-2.0>.
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#
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# [This file includes modifications made by New Vector Limited]
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#
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#
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from typing import TYPE_CHECKING, Any, Dict, Type, TypeVar
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import jsonschema
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from synapse._pydantic_compat import HAS_PYDANTIC_V2
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if TYPE_CHECKING or HAS_PYDANTIC_V2:
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from pydantic.v1 import BaseModel, ValidationError, parse_obj_as
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else:
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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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