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JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.NUMERIC TYPES
The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. For example, 1 and 1.0 are two ways to represent the same value in JSON.GENERIC KEYWORDS
New in draft 7 The boolean keywords readOnly and writeOnly are typically used in an API context. readOnly indicates that a value should not be modified. It could be used to indicate that a PUT request that changes a value would result in a 400 Bad Request response. writeOnly indicates that a value may be set, but will remainhidden.
ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
APPLYING SUBSCHEMAS CONDITIONALLY Applying subschemas conditionally. ¶. New in draft 7 if, then and else keywords. The if, then and else keywords allow the application of a subschema based on the outcome of another schema, much like the if/then/else constructs you’ve probably seen in traditional programming languages. If if is valid, then must also be valid (andelse is
JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.NUMERIC TYPES
The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. For example, 1 and 1.0 are two ways to represent the same value in JSON.GENERIC KEYWORDS
New in draft 7 The boolean keywords readOnly and writeOnly are typically used in an API context. readOnly indicates that a value should not be modified. It could be used to indicate that a PUT request that changes a value would result in a 400 Bad Request response. writeOnly indicates that a value may be set, but will remainhidden.
ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
APPLYING SUBSCHEMAS CONDITIONALLY Applying subschemas conditionally. ¶. New in draft 7 if, then and else keywords. The if, then and else keywords allow the application of a subschema based on the outcome of another schema, much like the if/then/else constructs you’ve probably seen in traditional programming languages. If if is valid, then must also be valid (andelse is
THE BASICS — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION When this book refers to JSON Schema “keywords”, it means the “key” part of the key/value pair in an object. Most of the work of writing a JSON Schema involves mapping a special “keyword” to a value within an object. The type keyword is described in more detail in Type-specific keywords.WHAT IS A SCHEMA?
To define what JSON Schema is, we should probably first define what JSON is. JSON stands for “JavaScript Object Notation”, a simple data interchange format. It began as a notation for the world wide web. Since JavaScript exists in most web browsers, and JSON SCHEMA REFERENCE JSON Schema Reference¶. Type-specific keywords; string; Regular Expressions; Numeric types; object; arrayIMPLEMENTATIONS
f5-json-schema draft-07 (Boost Software License 1.0) Valijson draft-07 header-only library, works with many JSON parser implementations (BSD-2-Clause) jsoncons draft-07 Header-only library (Boost Software License 1.0) Snow 2019-09, draft-07, -06 Uses Maven for the project and Gson under the hood. ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Items ¶. There are two ways in which arrays are generally used in JSON: List validation: a sequence of arbitrary length where each item matches the same schema. Tuple validation: a sequence of fixed length where each item may have a different schema. In this usage, the index (or location) of each item is meaningful as to how the value isinterpreted.
STRING — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION There is a bias toward networking-related formats in the JSON Schema specification, most likely due to its heritage in web technologies. However, custom formats may also be used, as long as the parties exchanging the JSON documents also exchange information about the custom format types.REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
STRUCTURING A COMPLEX SCHEMA Structuring a complex schema. ¶. When writing computer programs of even moderate complexity, it’s commonly accepted that “structuring” the program into reusable functions is better than copying-and-pasting duplicate bits of code everywhere they are used. Likewise in JSON Schema, for anything but the most trivial schema,it’s really
TYPE-SPECIFIC KEYWORDS Type-specific keywords. ¶. The type keyword is fundamental to JSON Schema. It specifies the data type for a schema. At its core, JSON Schema defines the following basic types: These types have analogs in most programming languages, though they may go by different names. The following table maps from the names of JavaScript types to their MEDIA: STRING-ENCODING NON-JSON DATA The contentEncoding keyword specifies the encoding used to store the contents, as specified in RFC 2054, part 6.1. The acceptable values are 7bit, 8bit, binary, quoted-printable and base64. If not specified, the encoding is the same as the containing JSON document. Without getting into the low-level details of each of these encodings, thereare
JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.NUMERIC TYPES
The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. For example, 1 and 1.0 are two ways to represent the same value in JSON.GENERIC KEYWORDS
New in draft 7 The boolean keywords readOnly and writeOnly are typically used in an API context. readOnly indicates that a value should not be modified. It could be used to indicate that a PUT request that changes a value would result in a 400 Bad Request response. writeOnly indicates that a value may be set, but will remainhidden.
ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
APPLYING SUBSCHEMAS CONDITIONALLY Applying subschemas conditionally. ¶. New in draft 7 if, then and else keywords. The if, then and else keywords allow the application of a subschema based on the outcome of another schema, much like the if/then/else constructs you’ve probably seen in traditional programming languages. If if is valid, then must also be valid (andelse is
JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.NUMERIC TYPES
The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. For example, 1 and 1.0 are two ways to represent the same value in JSON.GENERIC KEYWORDS
New in draft 7 The boolean keywords readOnly and writeOnly are typically used in an API context. readOnly indicates that a value should not be modified. It could be used to indicate that a PUT request that changes a value would result in a 400 Bad Request response. writeOnly indicates that a value may be set, but will remainhidden.
ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
APPLYING SUBSCHEMAS CONDITIONALLY Applying subschemas conditionally. ¶. New in draft 7 if, then and else keywords. The if, then and else keywords allow the application of a subschema based on the outcome of another schema, much like the if/then/else constructs you’ve probably seen in traditional programming languages. If if is valid, then must also be valid (andelse is
THE BASICS — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION When this book refers to JSON Schema “keywords”, it means the “key” part of the key/value pair in an object. Most of the work of writing a JSON Schema involves mapping a special “keyword” to a value within an object. The type keyword is described in more detail in Type-specific keywords.WHAT IS A SCHEMA?
To define what JSON Schema is, we should probably first define what JSON is. JSON stands for “JavaScript Object Notation”, a simple data interchange format. It began as a notation for the world wide web. Since JavaScript exists in most web browsers, and JSON SCHEMA REFERENCE JSON Schema Reference¶. Type-specific keywords; string; Regular Expressions; Numeric types; object; arrayIMPLEMENTATIONS
f5-json-schema draft-07 (Boost Software License 1.0) Valijson draft-07 header-only library, works with many JSON parser implementations (BSD-2-Clause) jsoncons draft-07 Header-only library (Boost Software License 1.0) Snow 2019-09, draft-07, -06 Uses Maven for the project and Gson under the hood. ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Items ¶. There are two ways in which arrays are generally used in JSON: List validation: a sequence of arbitrary length where each item matches the same schema. Tuple validation: a sequence of fixed length where each item may have a different schema. In this usage, the index (or location) of each item is meaningful as to how the value isinterpreted.
STRING — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION There is a bias toward networking-related formats in the JSON Schema specification, most likely due to its heritage in web technologies. However, custom formats may also be used, as long as the parties exchanging the JSON documents also exchange information about the custom format types.REGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
STRUCTURING A COMPLEX SCHEMA Structuring a complex schema. ¶. When writing computer programs of even moderate complexity, it’s commonly accepted that “structuring” the program into reusable functions is better than copying-and-pasting duplicate bits of code everywhere they are used. Likewise in JSON Schema, for anything but the most trivial schema,it’s really
TYPE-SPECIFIC KEYWORDS Type-specific keywords. ¶. The type keyword is fundamental to JSON Schema. It specifies the data type for a schema. At its core, JSON Schema defines the following basic types: These types have analogs in most programming languages, though they may go by different names. The following table maps from the names of JavaScript types to their MEDIA: STRING-ENCODING NON-JSON DATA The contentEncoding keyword specifies the encoding used to store the contents, as specified in RFC 2054, part 6.1. The acceptable values are 7bit, 8bit, binary, quoted-printable and base64. If not specified, the encoding is the same as the containing JSON document. Without getting into the low-level details of each of these encodings, thereare
JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.GENERIC KEYWORDS
The default keyword specifies a default value for an item. JSON processing tools may use this information to provide a default value for a missing key/value pair, though many JSON schema validators simply ignore the default keyword. It should validate against the schema in which it resides, but that isn’t required.NUMERIC TYPES
integer ¶. The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
JSON SCHEMA
JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions. GETTING STARTED STEP-BY-STEP UNDERSTANDING JSON SCHEMA Understanding JSON Schema. ¶. JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. UNDERSTANDING JSON SCHEMA Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use itby reading its
SCHEMA COMPOSITION
JSON Schema includes a few keywords for combining schemas together. Note that this doesn’t necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema.Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time.GENERIC KEYWORDS
The default keyword specifies a default value for an item. JSON processing tools may use this information to provide a default value for a missing key/value pair, though many JSON schema validators simply ignore the default keyword. It should validate against the schema in which it resides, but that isn’t required.NUMERIC TYPES
integer ¶. The integer type is used for integral numbers. JSON does not have distinct types for integers and floating-point values. Therefore, the presence or absence of a decimal point is not enough to distinguish between integers and non-integers. ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Arrays are used for ordered elements. In JSON, each element in an array may be of a different type. In Python, "array" is analogous to a list or tuple type, depending on usage. However, the json module in the Python standard library will always use Python lists to representJSON arrays.
WHAT IS A SCHEMA?
To define what JSON Schema is, we should probably first define what JSON is. JSON stands for “JavaScript Object Notation”, a simple data interchange format. It began as a notation for the world wide web. Since JavaScript exists in most web browsers, andLEARN | JSON SCHEMA
Learn. Getting Started Step-By-Step which covers a classic product catalog description. File System which uses JSON Schema to describe filesystem entries in a Unix-like file system. It is a little more in-depth / advanced than Getting Started. Miscellaneous Examples. Examples Collection. address.schema.json. JSON SCHEMA REFERENCE JSON Schema Reference¶. Type-specific keywords; string; Regular Expressions; Numeric types; object; arraySPECIFICATION LINKS
The specification links here go to the IETF-hosted documents. For links to the somewhat more readably formatted versions on this web site, and for links to the various meta-schemas and other supplemental documents, see the the following sections. IETF identifiers. meta‑schema identifiers. common name. ARRAY — UNDERSTANDING JSON SCHEMA 7.0 DOCUMENTATION Items ¶. There are two ways in which arrays are generally used in JSON: List validation: a sequence of arbitrary length where each item matches the same schema. Tuple validation: a sequence of fixed length where each item may have a different schema. In this usage, the index (or location) of each item is meaningful as to how the value isinterpreted.
GENERIC KEYWORDS
The default keyword specifies a default value for an item. JSON processing tools may use this information to provide a default value for a missing key/value pair, though many JSON schema validators simply ignore the default keyword. It should validate against the schema in which it resides, but that isn’t required. TYPE-SPECIFIC KEYWORDS Type-specific keywords. ¶. The type keyword is fundamental to JSON Schema. It specifies the data type for a schema. At its core, JSON Schema defines the following basic types: These types have analogs in most programming languages, though they may go by different names. The following table maps from the names of JavaScript types to theirREGULAR EXPRESSIONS
Regular Expressions. ¶. The pattern and Pattern Properties keywords use regular expressions to express constraints. The regular expression syntax used is from JavaScript ( ECMA 262 , specifically). However, that complete syntax is not widely supported, therefore it is recommended that you stick to the subset of that syntax describedbelow.
STRUCTURING A COMPLEX SCHEMA Structuring a complex schema. ¶. When writing computer programs of even moderate complexity, it’s commonly accepted that “structuring” the program into reusable functions is better than copying-and-pasting duplicate bits of code everywhere they are used. Likewise in JSON Schema, for anything but the most trivial schema,it’s really
MEDIA: STRING-ENCODING NON-JSON DATA The contentEncoding keyword specifies the encoding used to store the contents, as specified in RFC 2054, part 6.1. The acceptable values are 7bit, 8bit, binary, quoted-printable and base64. If not specified, the encoding is the same as the containing JSON document. Without getting into the low-level details of each of these encodings, thereare
JSON Schema
Specification Learn ImplementationsDiscussion
JSON SCHEMA
_THE CURRENT VERSION IS DRAFT-07 !_ _THE NEXT DRAFT WORK-IN-PROGRESS IS IN FINAL REVIEW!_
JSON SCHEMA is a vocabulary that allows you to ANNOTATE and VALIDATEJSON documents.
ADVANTAGES
JSON SCHEMA
* Describes your existing data format(s). * Provides clear human- and machine- readable documentation. * Validates data which is useful for: * Automated testing. * Ensuring quality of client submitted data.JSON HYPER-SCHEMA
* Make any JSON format a hypermedia format with no constraints ondocument structure
* Allows use of URI Templateswith instance data
* Describe client data for use with links using JSON Schema. * Recognizes collections and collection items.PROJECT STATUS
UPDATE AS OF 27 MAY 2019 THE FORTHCOMING DRAFT IS IN FINAL REVIEW . This draft has also taken more time than expected because it tackles deep, long-term issues that have long been a challenge for JSON Schema. This includes building in a formal extensibility mechanism so that we can more easily draw a line to finalize the contents of the Core and Validation specifications. Additionally, numerous life issues reduced the availability of key contributors during the process. THE PATH TO STANDARDIZATION The JSON Schema project intends to shepherd all four draft series to RFC status. Currently, we are continuing to improve our self-published Internet-Drafts. The next step will be to get the drafts adopted by an IETF Working Group. We are actively investigating how to accomplishthis.
If you have experience with such things and would like to help, pleasecontact us!
In the meantime, publication of Internet-Draft documents can be tracked through the IETF: * JSON Schema (core) * JSON Schema Validation* JSON Hyper-Schema
* Relative JSON Pointers Internet-Drafts expire after six months, so our goal is to publish often enough to always have a set of unexpired drafts available. There may be brief gaps as we wrap up each draft and finalize the text. The intention, particularly for vocabularies such as validation which have been widely implemented, is to remain as compatible as possible from draft to draft. However, these are still drafts, and given a clear enough need validated with the user community, major changes canoccur.
QUICKSTART
The JSON document being validated or described we call the _instance_, and the document containing the description is called the _schema_. The most basic schema is a blank JSON object, which constrains nothing, allows anything, and describes nothing:{}
You can apply constraints on an instance by adding validation keywords to the schema. For example, the “type” keyword can be used to restrict an instance to an object, array, string, number, boolean, ornull:
{ "type": "string" } JSON Schema is hypermedia ready, and ideal for annotating your existing JSON-based HTTP API. JSON Schema documents are identified by URIs, which can be used in HTTP Link headers, and inside JSON Schema documents to allow recursive definitions.MORE
Interested? Check out: * Understanding JSON Schema* The specification
* Learning resources * the growing list of JSON (Hyper-)Schema software We encourage updating to the latest specification, as described by the draft-07 meta-schemas. Questions? Feeling helpful? Get involved on:* GitHub
* Google Groups
* Slack
JSON SCHEMA
* json-schema-org
* Discussion: Slack
| Google Groups
* Site edits: GitHub repo for site The home of JSON SchemaDetails
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