Provides randomized json data (samples) that complies with a given json schema.
from pprint import pprint
import jsonschema
import freddy
family_schema = {
"type": "array",
"items": {
"properties": {
"member": {"$ref": "#/definitions/person"},
"role": {"$ref": "#/definitions/role"},
},
"type": "object",
},
"maxItems": 5,
"minItems": 1,
"definitions": {
"person": {
"properties": {
"age": {"type": "integer"},
"name": {"type": "string"},
"pets": {
"items": {"$ref": "#/definitions/pet"},
"maxItems": 2,
"type": "array",
},
},
"type": "object",
},
"pet": {
"properties": {
"kind": {"enum": ["dog", "cat"], "type": "string"},
"name": {"type": "string"},
},
"type": "object",
},
"role": {
"enum": [
"father",
"mather",
"son",
"daughter",
"aunt",
"grandma",
"grandpa",
],
"type": "string",
},
}
}
# Get 10 random samples
for i in range(10):
sample_family = freddy.jsonschema(family_schema)
# Validate against schema
jsonschema.validate(sample_family, family_schema)
pprint(sample_family)
[
{"member": {"age": 77, "name": "k", "pets": []}, "role": "grandma"},
{"member": {"age": 64, "name": "naifvxf", "pets": []}, "role": "grandpa"},
{
"member": {
"age": 23,
"name": "itruydotrj",
"pets": [{"kind": "cat", "name": "o"}, {"kind": "cat", "name": "uonmvfgd"}],
},
"role": "son",
},
]
pip install freddy
# Clone the repo
git@github.com:lferran/freddy.git
cd freddy
make develop
# Run tests
make tests
Conforms to JSON Schema Draft 7. The following features are supported:
-
boolean type
-
null type
-
string type
-
number type
-
integer type
-
array type
-
object type
-
definitions/references
-
Boolean type
-
consts
-
exclusiveMinimum
andexclusiveMaximum
in integers and numbers. -
number
multipleOf
keyword -
required
keyword -
additionalProperties
-
string
pattern
regex keyword -
string built-in formats
-
be able to provide custom basic type factories
-
multiple types:
{"type": ["string", "array"]}
-
look into
allOf
: generate multiple objects + merge
Does not support:
- ID referencing
allOf
andnot
keywords- conditional keywords
if
,then
andelse