I have the main Json-schema. It looks like that:
{
"$schema": "http://json-schema.org/draft-04/schema#",
"type": "object",
"properties": {
"listInfo": {
"type": "object",
"properties": {
"limit": {
"type": "integer"
},
"count": {
"type": "integer"
}
},
"required": [
"offset",
"count"
]
},
"items": {
"type": ["array", "null"],
"items": {
"type": "object",
"properties": {
"startDate": {
"type": "string"
},
"customer": {
"type": "object",
"properties": {
"customerId": {
"type": "integer"
},
"name": {
"type": "string"
}
},
"required": [
"customerId",
"name"
]
}
},
"required": [
"startDate",
"customer"
]
}
}
},
"required": [
"listInfo",
"items"
]
}
Every time after sending a get query to a host I check Json on a validation with my schema.
But Sometimes I need not all fields in it. For example I can add "&fields=startDate" in the end of my GET query.
How I can generate new Json schema for my new data (I need to automatically delete lines about "customer" in my old Json schema and generate a new json-schema file)?
Related
I am trying to build schema from my json response. and I am trying to access only content from schema builder, I don't want to access any other data from it.
full_response
{
"$schema": "http://json-schema.org/schema#",
"anyOf": [
{
"type": "object"
},
{
"type": "array",
"items": {
"type": "object",
"properties": {
"response": {
"type": "integer"
},
"content": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": {
"type": "integer"
},
"title": {
"type": "string"
},
},
"required": [
"id",
"title"
]
}
}
},
"required": [
"content",
"response"
]
}
}
]
}
as you can see in response it shows all the data and I want to access only of content. But when I do it like
builder.add_schema({"type": "object", "properties": {},accitionalProperties": False})
builder.add_object(json)
builder.to_schema()
I have also tried by defining it like
builder.to_schema().content
but it says
AttributeError: 'str' object has no attribute 'content'
It is still showing everything.
I have tried many times but it still not showing. Any help would be much Appreciated. Thank You in Advance.
Sample Schema:
{
"CLASS_A" : {
"type": "object",
"properties": {
"CLASS_B": {
"type": "array",
"items": {
"type": "object",
"properties": {
"NAME1": {
"type": "string",
},
"NAME2": {
"type": "string",
},
"CLASS_C": {
"type": "array",
"items": {
"type": "object",
"properties": {
"NAME3": {
"type": "string",
},
"NAME4": {
"type": "string",
},
},
},
},
},
},
},
},
},
},
CLASS_B and CLASS_C are the table names and NAME1 and NAME2 are the column names of the table CLASS_B
I have a big JSON schema with around 600 tables....
I need to automatically retrieve table names and their corresponding columns in one place.
First, you change it to a dictionary with command
import json
with open('data.json') as json_file:
data = json.load(json_file)
Then you read it as a dictionary with:
data['CLASS_A']['properties']
...
I have a JSON schema with which I want to validate some data, using python and the jsonschema module. However, this doesn't quite work as expected, as some of the accepted data doesn't appear valid at all (to me and the purpose of my application). Sadly, the schema is provided, so I can't change the schema itself - at least not manually.
This is a shortened version of the schema ('schema.json' in code below):
{
"type": "object",
"allOf": [
{
"type": "object",
"allOf": [
{
"type": "object",
"properties": {
"firstName": {
"type": "string"
},
"lastName": {
"type": "string"
}
}
},
{
"type": "object",
"properties": {
"language": {
"type": "integer"
}
}
}
]
},
{
"type": "object",
"properties": {
"addressArray": {
"type": "array",
"items": {
"type": "object",
"properties": {
"streetNumber": {
"type": "string"
},
"street": {
"type": "string"
},
"city": {
"type": "string"
}
}
}
}
}
}
]
}
This is an example of what should be a valid instance ('person.json' in code below):
{
"firstName": "Sherlock",
"lastName": "Holmes",
"language": 1,
"addresses": [
{
"streetNumber": "221B",
"street": "Baker Street",
"city": "London"
}
]
}
This is an example of what should be considered invalid ('no_person.json' in code below):
{
"name": "eggs",
"colour": "white"
}
And this is the code I used for validating:
from json import load
from jsonschema import Draft7Validator, exceptions
with open('schema.json') as f:
schema = load(f)
with open('person.json') as f:
person = load(f)
with open('no_person.json') as f:
no_person = load(f)
validator = Draft7Validator(schema)
try:
validator.validate(person)
print("person.json is valid")
except exceptions.ValidationError:
print("person.json is invalid")
try:
validator.validate(no_person)
print("no_person.json is valid")
except exceptions.ValidationError:
print("no_person.json is invalid")
Result:
person.json is valid
no_person.json is valid
I expected no_person.json to be invalid. What can there be done to have only data such as person.json to be validated successfully? Thank you very much for your help, I'm very new to this (spent ages searching for an answer).
This is work schema and pay attention on "required" (when there is no such key - if field is doesn't get it just skipped):
{
"type": "object",
"properties": {
"firstName": {
"type": "string"
},
"lastName": {
"type": "string"
},
"language": {
"type": "integer"
},
"addresses": {
"type": "array",
"items": {
"type": "object",
"properties": {
"streetNumber": {
"type": "string"
},
"street": {
"type": "string"
},
"city": {
"type": "string"
}
},
"required": [
"streetNumber",
"street",
"city"
]
}
}
},
"required": [
"firstName",
"lastName",
"language",
"addresses"
]
}
I've got:
person.json is valid
no_person.json is invalid
If you have hardest structure of response (array of objects, which contain objects etc) let me known
I've writen a small chunk os json schema but I'm getting a validation error using python jsonschema.
Here is my schema:
{
"$schema": "http://json-schema.org/draft-04/schema#",
"definitions": {
"output": {
"type": "object",
"properties": {
"Type": {
"type": "object",
"properties": {
"Type": {
"type": "string"
},
"Value": {
"type": "string"
},
"Default": {
"type": "string"
},
"Description": {
"type": "string"
},
"Options": {
"type": "array"
}
},
"required": [
"Type",
"Value",
"Default",
"Description",
"Options"
]
},
"Inverted": {
"type": "object",
"properties": {
"Type": {
"type": "string"
},
"Value": {
"type": "bool"
},
"Default": {
"type": "bool"
},
"Description": {
"type": "string"
}
},
"required": [
"Type",
"Value",
"Default",
"Description"
]
},
"Pulse Width": {
"type": "object",
"properties": {
"Type": {
"type": "string"
},
"Value": {
"type": "number"
},
"Default": {
"type": "number"
},
"Description": {
"type": "string"
}
},
"required": [
"Type",
"Value",
"Default",
"Description"
]
}
},
"required": [
"Type",
"Inverted",
"Pulse Width"
]
}
}
}
Here is the error I'm receiving:
Failed validating u'type' in schema
I'm attempting to validate my schema with:
schema = ""
with open(jsonSchemaFilePath, 'r') as schema_file:
schema = schema_file.read()
try:
Draft4Validator.check_schema(schema)
except SchemaError as schemaError:
print schemaError
What am I doing wrong with the schema I've written? Am I not allowed to have a property named Type?
My problem was Draft4Validator.check_schema takes a dic not a string, nor a json object.
Here was my solution:
schema = {}
with open(jsonSchemaFilePath, 'r') as schema_file:
schema = json.loads(schema_file.read())
try:
Draft4Validator.check_schema(schema)
except SchemaError as schemaError:
print schemaError
I'm trying to validate a json file against a schema using python and jsonschema module. My schema is made up from a list of schemas, one of them has definitions of basic elements and the rest are collections of these elements and other objects.
I can't find the documentation for function which loads the list of schemas so that I can validate using it. I tried separating schemas into a dictionary and calling the appropriate one on a jsonObject, but that doesn't work since they cross reference each other.
How do I load/assemble all schemas into one for validation?
Part of the schema I'm trying to load:
[{
"definitions": {
"location": {
"required": [
"name",
"country"
],
"additionalProperties": false,
"properties": {
"country": {
"pattern": "^[A-Z]{2}$",
"type": "string"
},
"name": {
"type": "string"
}
},
"type": "object"
}
},
"required": [
"type",
"content"
],
"additionalProperties": false,
"properties": {
"content": {
"additionalProperties": false,
"type": "object"
},
"type": {
"type": "string"
}
},
"type": "object",
"title": "base",
"$schema": "http://json-schema.org/draft-04/schema#"
},
{
"properties": {
"content": {
"required": [
"address"
],
"properties": {
"address": {
"$ref": "#/definitions/location"
}
},
"type": {
"pattern": "^person$"
}
}
}]
And the json object would look something like this:
{
"type":"person",
"content":{
"address": {
"country": "US",
"name" : "1,Street,City,State,US"
}
}
}
You can only validate against one schema at a time, but that schema can reference ($ref) external schemas. These references are usually URIs that can be used to GET the schema. A filepath might work too if your schemas are not public. Using a fixed up version of your example, this would look something like this ...
http://your-domain.com/schema/person
{
"$schema": "http://json-schema.org/draft-04/schema#",
"title": "Person",
"allOf": [{ "$ref": "http://your-domain.com/schema/base#" }],
"properties": {
"type": { "enum": ["person"] },
"content": {
"properties": {
"address": { "$ref": "http://your-domain.com/schema/base#/definitions/location" }
},
"required": ["address"],
"additionalProperties": false
}
}
}
http://your-domain.com/schema/base
{
"$schema": "http://json-schema.org/draft-04/schema#",
"title": "base",
"type": "object",
"properties": {
"content": { "type": "object" },
"type": { "type": "string" }
},
"required": ["type", "content"],
"additionalProperties": false,
"definitions": {
"location": {
"type": "object",
"properties": {
"country": {
"type": "string",
"pattern": "^[A-Z]{2}$"
},
"name": { "type": "string" }
},
"required": ["name", "country"],
"additionalProperties": false
}
}
}
Some documentation that might be useful
https://python-jsonschema.readthedocs.org/en/latest/validate/#the-validator-interface
https://python-jsonschema.readthedocs.org/en/latest/references/
Instead of hand coding a single schema from all your schemata, you can create a small schema which refers to the other schema files. This way you can use multiple existing JSONschema files and validate against them in combination:
import yaml
import jsonschema
A_yaml = """
id: http://foo/a.json
type: object
properties:
prop:
$ref: "./num_string.json"
"""
num_string_yaml = """
id: http://foo/num_string.json
type: string
pattern: ^[0-9]*$
"""
A = yaml.load(A_yaml)
num_string = yaml.load(num_string_yaml)
resolver = jsonschema.RefResolver("",None,
store={
"http://foo/A.json":A,
"http://foo/num_string.json":num_string,
})
validator = jsonschema.Draft4Validator(
A, resolver=resolver)
try:
validator.validate({"prop":"1234"})
print "Properly accepted object"
except jsonschema.exceptions.ValidationError:
print "Failed to accept object"
try:
validator.validate({"prop":"12d34"})
print "Failed to reject object"
except jsonschema.exceptions.ValidationError:
print "Properly rejected object"
Note that you may want to combine the external using one of the schema cominators oneOf, allOf, or anyOf to combine your schemata like so:
[A.yaml]
oneOf:
- $ref: "sub-schema1.json"
- $ref: "sub-schema2.json"
- $ref: "sub-schema3.json"