JSON Schema validation with various additional features
Project description
JSON Schema Tool
JSON Schema Tool is a python implementation of JSON Schema, draft 2020-12. It offers various additional features commonly not found in other libraries
Obviously, the core of JSON Schema Tool is the validation of JSON documents. This can be done as follows:
from json_schema_tool import parse_schema
schema = {
'$schema': 'https://json-schema.org/draft/2020-12/schema',
'type': 'object',
'properties': {
'foo': {
'type': 'string'
}
}
}
validator = parse_schema(schema)
result = validator.validate({"foo": "bar"})
# result.ok == True
result = validator.validate("invalid")
# result.ok == False
Installation
You can install JSON Schema Tool via pip:
python -m pip install json_schema_tool
Features
Additional Keywords
Json Schema Tool supports OpenAPI's discriminator
keyword for improved modelling of polymorphism:
schema = {
'$schema': 'https://json-schema.org/draft/2020-12/schema',
'oneOf': [
{'$ref': '#/$defs/Cat'},
{'$ref': '#/$defs/Dog'},
],
'$defs': {
'Cat': {
'properties': {'sound': {'const': 'meow'}}
},
'Dog': {
'properties': {'sound': {'const': 'woof'}}
}
},
'discriminator': {
'propertyName': 'type'
}
}
result = validator.validate({'type': 'Cat', 'sound': '?'})
# result.ok == False
Using the discriminator type
, Json Schema Tool knows which reference to check and will only return an error for the Cat
type (and will not check Dog
).
For more information, see https://swagger.io/docs/specification/data-models/inheritance-and-polymorphism/.
Schema Coverage Measurement
You can use coverage to assess the completeness of your test data. Schema coverage works on the keyword level, i.e., JsonSchema Tool checks, how many constraints have been actually checked during instance validation:
from json_schema_tool import coverage, parse_schema
schema = {
'$schema': 'https://json-schema.org/draft/2020-12/schema',
'type': 'object',
'properties': {
'foo': {
'type': 'string'
}
}
}
validator = parse_schema(schema)
cov = coverage.SchemaCoverage(validator)
result = validator.validate({})
cov.update(result)
print(cov.coverage())
# 0.3
result = validator.validate({"foo": "bar"})
cov.update(result)
print(cov.coverage())
# 1.0
with open("schema-coverage.html", "w") as f:
cov.render_coverage(f)
Type Inference
Given a validator, you can use it to query the types of the schema. This even works for complex and composed schemas:
from json_schema_tool import parse_schema
schema = {
'$schema': 'https://json-schema.org/draft/2020-12/schema',
'anyOf': [
{"type": "object"},
{"const": "foo"}
]
}
validator = parse_schema(schema)
print(validator.get_types())
# {'object', 'string'}
Validation Performance
You can drastically increase validation performance by using short circuit evaluation (SCE). By using SCE, evaluation terminates as soon as the first error in the JSON instance is found. For example, an allOf does not visit all sub schemas, if the first sub-schema already fails. You can activate SCE as follows:
from json_schema_tool import schema
# use parse_schema to build your validator...
config = schema.ValidationConfig(short_circuit_evaluation=True)
result = validator.validate({"foo": "bar"}, config)
Please note, that SCE does not work together with coverage measurement.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file json_schema_tool-0.4.0.tar.gz
.
File metadata
- Download URL: json_schema_tool-0.4.0.tar.gz
- Upload date:
- Size: 18.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2b90109a44ae3fe6237e8da9ff313aff2eb48a4ad367ca1734e9860110f9ffb7 |
|
MD5 | 0f0a0caf7868f4dd70504d6c472db33a |
|
BLAKE2b-256 | 7b8065232d7dea33c876c17e46cb61ced5a1c3880d0f7cf160c4b2b94160f6f1 |
File details
Details for the file json_schema_tool-0.4.0-py3-none-any.whl
.
File metadata
- Download URL: json_schema_tool-0.4.0-py3-none-any.whl
- Upload date:
- Size: 16.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 140414cfffd270e3b8f0eef22213c122c60cb5a112edf9596f5816b3aff7ad59 |
|
MD5 | c98df7261ef6a29538ecce23b7c126dc |
|
BLAKE2b-256 | cd0cb6e940d93ffd6b50bad262d20f7eaeaa1dc9f4e28a84574d52daed9fed5c |