1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
|
# 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
|
