June 2018 Edition
Introduction
This is the specification for GraphQL, a query language and execution engine originally created at Facebook in 2012 for describing the capabilities and requirements of data models for client‐server applications. The development of this open standard started in 2015.
GraphQL has evolved and may continue to evolve in future editions of this specification. Previous editions of the GraphQL specification can be found at permalinks that match their release tag. The latest working draft release can be found at facebook.github.io/graphql/draft/.
Copyright notice
Copyright © 2015‐present, Facebook, Inc.
As of September 26, 2017, the following persons or entities have made this Specification available under the Open Web Foundation Final Specification Agreement (OWFa 1.0), which is available at openwebfoundation.org.
You can review the signed copies of the Open Web Foundation Final Specification Agreement Version 1.0 for this specification at github.com/facebook/graphql, which may also include additional parties to those listed above.
Your use of this Specification may be subject to other third party rights. THIS SPECIFICATION IS PROVIDED “AS IS.” The contributors expressly disclaim any warranties (express, implied, or otherwise), including implied warranties of merchantability, non‐infringement, fitness for a particular purpose, or title, related to the Specification. The entire risk as to implementing or otherwise using the Specification is assumed by the Specification implementer and user. IN NO EVENT WILL ANY PARTY BE LIABLE TO ANY OTHER PARTY FOR LOST PROFITS OR ANY FORM OF INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES OF ANY CHARACTER FROM ANY CAUSES OF ACTION OF ANY KIND WITH RESPECT TO THIS SPECIFICATION OR ITS GOVERNING AGREEMENT, WHETHER BASED ON BREACH OF CONTRACT, TORT (INCLUDING NEGLIGENCE), OR OTHERWISE, AND WHETHER OR NOT THE OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Conformance
A conforming implementation of GraphQL must fulfill all normative requirements. Conformance requirements are described in this document via both descriptive assertions and key words with clearly defined meanings.
The key words “MUST”, “MUST NOT”, “REQUIRED”, “SHALL”, “SHALL NOT”, “SHOULD”, “SHOULD NOT”, “RECOMMENDED”, “MAY”, and “OPTIONAL” in the normative portions of this document are to be interpreted as described in IETF RFC 2119. These key words may appear in lowercase and still retain their meaning unless explicitly declared as non‐normative.
A conforming implementation of GraphQL may provide additional functionality, but must not where explicitly disallowed or would otherwise result in non‐conformance.
Conforming Algorithms
Algorithm steps phrased in imperative grammar (e.g. “Return the result of calling resolver”) are to be interpreted with the same level of requirement as the algorithm it is contained within. Any algorithm referenced within an algorithm step (e.g. “Let completedResult be the result of calling CompleteValue()”) is to be interpreted as having at least the same level of requirement as the algorithm containing that step.
Conformance requirements expressed as algorithms can be fulfilled by an implementation of this specification in any way as long as the perceived result is equivalent. Algorithms described in this document are written to be easy to understand. Implementers are encouraged to include equivalent but optimized implementations.
See Appendix A for more details about the definition of algorithms and other notational conventions used in this document.
Non‐Normative Portions
All contents of this document are normative except portions explicitly declared as non‐normative.
Examples in this document are non‐normative, and are presented to aid understanding of introduced concepts and the behavior of normative portions of the specification. Examples are either introduced explicitly in prose (e.g. “for example”) or are set apart in example or counter‐example blocks, like this:
Example № 1This is an example of a non-normative example.
Counter Example № 2This is an example of a non-normative counter-example.
Notes in this document are non‐normative, and are presented to clarify intent, draw attention to potential edge‐cases and pit‐falls, and answer common questions that arise during implementation. Notes are either introduced explicitly in prose (e.g. “Note: “) or are set apart in a note block, like this:
GraphQL is a query language designed to build client applications by providing an intuitive and flexible syntax and system for describing their data requirements and interactions.
For example, this GraphQL request will receive the name of the user with id 4 from the Facebook implementation of GraphQL.
Example № 3{
user(id: 4) {
name
}
}
Which produces the resulting data (in JSON):
Example № 4{
"user": {
"name": "Mark Zuckerberg"
}
}
GraphQL is not a programming language capable of arbitrary computation, but is instead a language used to query application servers that have capabilities defined in this specification. GraphQL does not mandate a particular programming language or storage system for application servers that implement it. Instead, application servers take their capabilities and map them to a uniform language, type system, and philosophy that GraphQL encodes. This provides a unified interface friendly to product development and a powerful platform for tool‐building.
GraphQL has a number of design principles:
Because of these principles, GraphQL is a powerful and productive environment for building client applications. Product developers and designers building applications against working GraphQL servers -- supported with quality tools -- can quickly become productive without reading extensive documentation and with little or no formal training. To enable that experience, there must be those that build those servers and tools.
The following formal specification serves as a reference for those builders. It describes the language and its grammar, the type system and the introspection system used to query it, and the execution and validation engines with the algorithms to power them. The goal of this specification is to provide a foundation and framework for an ecosystem of GraphQL tools, client libraries, and server implementations -- spanning both organizations and platforms -- that has yet to be built. We look forward to working with the community in order to do that.
Clients use the GraphQL query language to make requests to a GraphQL service. We refer to these request sources as documents. A document may contain operations (queries, mutations, and subscriptions) as well as fragments, a common unit of composition allowing for query reuse.
A GraphQL document is defined as a syntactic grammar where terminal symbols are tokens (indivisible lexical units). These tokens are defined in a lexical grammar which matches patterns of source characters (defined by a double‐colon ::
).
GraphQL documents are expressed as a sequence of Unicode characters. However, with few exceptions, most of GraphQL is expressed only in the original non‐control ASCII range so as to be as widely compatible with as many existing tools, languages, and serialization formats as possible and avoid display issues in text editors and source control.
Non‐ASCII Unicode characters may freely appear within StringValue and Comment portions of GraphQL.
The “Byte Order Mark” is a special Unicode character which may appear at the beginning of a file containing Unicode which programs may use to determine the fact that the text stream is Unicode, what endianness the text stream is in, and which of several Unicode encodings to interpret.
White space is used to improve legibility of source text and act as separation between tokens, and any amount of white space may appear before or after any token. White space between tokens is not significant to the semantic meaning of a GraphQL Document, however white space characters may appear within a String or Comment token.
Like white space, line terminators are used to improve the legibility of source text, any amount may appear before or after any other token and have no significance to the semantic meaning of a GraphQL Document. Line terminators are not found within any other token.
GraphQL source documents may contain single‐line comments, starting with the # marker.
A comment can contain any Unicode code point except LineTerminator so a comment always consists of all code points starting with the # character up to but not including the line terminator.
Comments behave like white space and may appear after any token, or before a line terminator, and have no significance to the semantic meaning of a GraphQL Document.
Similar to white space and line terminators, commas (,) are used to improve the legibility of source text and separate lexical tokens but are otherwise syntactically and semantically insignificant within GraphQL Documents.
Non‐significant comma characters ensure that the absence or presence of a comma does not meaningfully alter the interpreted syntax of the document, as this can be a common user‐error in other languages. It also allows for the stylistic use of either trailing commas or line‐terminators as list delimiters which are both often desired for legibility and maintainability of source code.
A GraphQL document is comprised of several kinds of indivisible lexical tokens defined here in a lexical grammar by patterns of source Unicode characters.
Tokens are later used as terminal symbols in a GraphQL Document syntactic grammars.
Before and after every lexical token may be any amount of ignored tokens including WhiteSpace and Comment. No ignored regions of a source document are significant, however ignored source characters may appear within a lexical token in a significant way, for example a String may contain white space characters.
No characters are ignored while parsing a given token, as an example no white space characters are permitted between the characters defining a FloatValue.
! | $ | ( | ) | ... | : | = | @ | [ | ] | { | | | } |
GraphQL documents include punctuation in order to describe structure. GraphQL is a data description language and not a programming language, therefore GraphQL lacks the punctuation often used to describe mathematical expressions.
GraphQL Documents are full of named things: operations, fields, arguments, types, directives, fragments, and variables. All names must follow the same grammatical form.
Names in GraphQL are case‐sensitive. That is to say name
, Name
, and NAME
all refer to different names. Underscores are significant, which means other_name
and othername
are two different names.
Names in GraphQL are limited to this ASCII subset of possible characters to support interoperation with as many other systems as possible.
A GraphQL Document describes a complete file or request string operated on by a GraphQL service or client. A document contains multiple definitions, either executable or representative of a GraphQL type system.
Documents are only executable by a GraphQL service if they contain an OperationDefinition and otherwise only contain ExecutableDefinition. However documents which do not contain OperationDefinition or do contain TypeSystemDefinition or TypeSystemExtension may still be parsed and validated to allow client tools to represent many GraphQL uses which may appear across many individual files.
If a Document contains only one operation, that operation may be unnamed or represented in the shorthand form, which omits both the query keyword and operation name. Otherwise, if a GraphQL Document contains multiple operations, each operation must be named. When submitting a Document with multiple operations to a GraphQL service, the name of the desired operation to be executed must also be provided.
GraphQL services which only seek to provide GraphQL query execution may choose to only include ExecutableDefinition and omit the TypeSystemDefinition and TypeSystemExtension rules from Definition.
query | mutation | subscription |
There are three types of operations that GraphQL models:
Each operation is represented by an optional operation name and a selection set.
For example, this mutation operation might “like” a story and then retrieve the new number of likes:
Example № 5mutation {
likeStory(storyID: 12345) {
story {
likeCount
}
}
}
Query shorthand
If a document contains only one query operation, and that query defines no variables and contains no directives, that operation may be represented in a short‐hand form which omits the query keyword and query name.
For example, this unnamed query operation is written via query shorthand.
Example № 6{
field
}
An operation selects the set of information it needs, and will receive exactly that information and nothing more, avoiding over‐fetching and under‐fetching data.
Example № 7{
id
firstName
lastName
}
In this query, the id
, firstName
, and lastName
fields form a selection set. Selection sets may also contain fragment references.
A selection set is primarily composed of fields. A field describes one discrete piece of information available to request within a selection set.
Some fields describe complex data or relationships to other data. In order to further explore this data, a field may itself contain a selection set, allowing for deeply nested requests. All GraphQL operations must specify their selections down to fields which return scalar values to ensure an unambiguously shaped response.
For example, this operation selects fields of complex data and relationships down to scalar values.
Example № 8{
me {
id
firstName
lastName
birthday {
month
day
}
friends {
name
}
}
}
Fields in the top‐level selection set of an operation often represent some information that is globally accessible to your application and its current viewer. Some typical examples of these top fields include references to a current logged‐in viewer, or accessing certain types of data referenced by a unique identifier.
Example № 9# `me` could represent the currently logged in viewer.
{
me {
name
}
}
# `user` represents one of many users in a graph of data, referred to by a
# unique identifier.
{
user(id: 4) {
name
}
}
Fields are conceptually functions which return values, and occasionally accept arguments which alter their behavior. These arguments often map directly to function arguments within a GraphQL server’s implementation.
In this example, we want to query a specific user (requested via the id
argument) and their profile picture of a specific size
:
Example № 10{
user(id: 4) {
id
name
profilePic(size: 100)
}
}
Many arguments can exist for a given field:
Example № 11{
user(id: 4) {
id
name
profilePic(width: 100, height: 50)
}
}
Arguments are unordered
Arguments may be provided in any syntactic order and maintain identical semantic meaning.
These two queries are semantically identical:
Example № 12{
picture(width: 200, height: 100)
}
Example № 13{
picture(height: 100, width: 200)
}
By default, the key in the response object will use the field name queried. However, you can define a different name by specifying an alias.
In this example, we can fetch two profile pictures of different sizes and ensure the resulting object will not have duplicate keys:
Example № 14{
user(id: 4) {
id
name
smallPic: profilePic(size: 64)
bigPic: profilePic(size: 1024)
}
}
Which returns the result:
Example № 15{
"user": {
"id": 4,
"name": "Mark Zuckerberg",
"smallPic": "https://cdn.site.io/pic-4-64.jpg",
"bigPic": "https://cdn.site.io/pic-4-1024.jpg"
}
}
Since the top level of a query is a field, it also can be given an alias:
Example № 16{
zuck: user(id: 4) {
id
name
}
}
Returns the result:
Example № 17{
"zuck": {
"id": 4,
"name": "Mark Zuckerberg"
}
}
A field’s response key is its alias if an alias is provided, and it is otherwise the field’s name.
Fragments are the primary unit of composition in GraphQL.
Fragments allow for the reuse of common repeated selections of fields, reducing duplicated text in the document. Inline Fragments can be used directly within a selection to condition upon a type condition when querying against an interface or union.
For example, if we wanted to fetch some common information about mutual friends as well as friends of some user:
Example № 18query noFragments {
user(id: 4) {
friends(first: 10) {
id
name
profilePic(size: 50)
}
mutualFriends(first: 10) {
id
name
profilePic(size: 50)
}
}
}
The repeated fields could be extracted into a fragment and composed by a parent fragment or query.
Example № 19query withFragments {
user(id: 4) {
friends(first: 10) {
...friendFields
}
mutualFriends(first: 10) {
...friendFields
}
}
}
fragment friendFields on User {
id
name
profilePic(size: 50)
}
Fragments are consumed by using the spread operator (...
). All fields selected by the fragment will be added to the query field selection at the same level as the fragment invocation. This happens through multiple levels of fragment spreads.
For example:
Example № 20query withNestedFragments {
user(id: 4) {
friends(first: 10) {
...friendFields
}
mutualFriends(first: 10) {
...friendFields
}
}
}
fragment friendFields on User {
id
name
...standardProfilePic
}
fragment standardProfilePic on User {
profilePic(size: 50)
}
The queries noFragments
, withFragments
, and withNestedFragments
all produce the same response object.
Fragments must specify the type they apply to. In this example, friendFields
can be used in the context of querying a User
.
Fragments cannot be specified on any input value (scalar, enumeration, or input object).
Fragments can be specified on object types, interfaces, and unions.
Selections within fragments only return values when concrete type of the object it is operating on matches the type of the fragment.
For example in this query on the Facebook data model:
Example № 21query FragmentTyping {
profiles(handles: ["zuck", "cocacola"]) {
handle
...userFragment
...pageFragment
}
}
fragment userFragment on User {
friends {
count
}
}
fragment pageFragment on Page {
likers {
count
}
}
The profiles
root field returns a list where each element could be a Page
or a User
. When the object in the profiles
result is a User
, friends
will be present and likers
will not. Conversely when the result is a Page
, likers
will be present and friends
will not.
Example № 22{
"profiles": [
{
"handle": "zuck",
"friends": { "count" : 1234 }
},
{
"handle": "cocacola",
"likers": { "count" : 90234512 }
}
]
}
Fragments can be defined inline within a selection set. This is done to conditionally include fields based on their runtime type. This feature of standard fragment inclusion was demonstrated in the query FragmentTyping
example. We could accomplish the same thing using inline fragments.
Example № 23query inlineFragmentTyping {
profiles(handles: ["zuck", "cocacola"]) {
handle
... on User {
friends {
count
}
}
... on Page {
likers {
count
}
}
}
}
Inline fragments may also be used to apply a directive to a group of fields. If the TypeCondition is omitted, an inline fragment is considered to be of the same type as the enclosing context.
Example № 24query inlineFragmentNoType($expandedInfo: Boolean) {
user(handle: "zuck") {
id
name
... @include(if: $expandedInfo) {
firstName
lastName
birthday
}
}
}
Field and directive arguments accept input values of various literal primitives; input values can be scalars, enumeration values, lists, or input objects.
If not defined as constant (for example, in DefaultValue), input values can be specified as a variable. List and inputs objects may also contain variables (unless defined to be constant).
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
An Int number is specified without a decimal point or exponent (ex. 1
).
+ | - |
A Float number includes either a decimal point (ex. 1.0
) or an exponent (ex. 1e50
) or both (ex. 6.0221413e23
).
true | false |
The two keywords true
and false
represent the two boolean values.
" | \ | / | b | f | n | r | t |
Strings are sequences of characters wrapped in double‐quotes ("
). (ex. "Hello World"
). White space and other otherwise‐ignored characters are significant within a string value.
Block Strings
Block strings are sequences of characters wrapped in triple‐quotes ("""
). White space, line terminators, quote, and backslash characters may all be used unescaped to enable verbatim text. Characters must all be valid SourceCharacter.
Since block strings represent freeform text often used in indented positions, the string value semantics of a block string excludes uniform indentation and blank initial and trailing lines via BlockStringValue().
For example, the following operation containing a block string:
Example № 25mutation {
sendEmail(message: """
Hello,
World!
Yours,
GraphQL.
""")
}
Is identical to the standard quoted string:
Example № 26mutation {
sendEmail(message: "Hello,\n World!\n\nYours,\n GraphQL.")
}
Since block string values strip leading and trailing empty lines, there is no single canonical printed block string for a given value. Because block strings typically represent freeform text, it is considered easier to read if they begin and end with an empty line.
Example № 27"""
This starts with and ends with an empty line,
which makes it easier to read.
"""
Counter Example № 28"""This does not start with or end with any empty lines,
which makes it a little harder to read."""
Semantics
Escaped Character | Code Unit Value | Character Name |
---|---|---|
" | U+0022 | double quote |
\ | U+005C | reverse solidus (back slash) |
/ | U+002F | solidus (forward slash) |
b | U+0008 | backspace |
f | U+000C | form feed |
n | U+000A | line feed (new line) |
r | U+000D | carriage return |
t | U+0009 | horizontal tab |
Null values are represented as the keyword null.
GraphQL has two semantically different ways to represent the lack of a value:
For example, these two field calls are similar, but are not identical:
Example № 29{
field(arg: null)
field
}
The first has explictly provided null to the argument “arg”, while the second has implicitly not provided a value to the argument “arg”. These two forms may be interpreted differently. For example, a mutation representing deleting a field vs not altering a field, respectively. Neither form may be used for an input expecting a Non‐Null type.
Enum values are represented as unquoted names (ex. MOBILE_WEB
). It is recommended that Enum values be “all caps”. Enum values are only used in contexts where the precise enumeration type is known. Therefore it’s not necessary to supply an enumeration type name in the literal.
Lists are ordered sequences of values wrapped in square‐brackets [ ]
. The values of a List literal may be any value literal or variable (ex. [1, 2, 3]
).
Commas are optional throughout GraphQL so trailing commas are allowed and repeated commas do not represent missing values.
Semantics
Input object literal values are unordered lists of keyed input values wrapped in curly‐braces { }
. The values of an object literal may be any input value literal or variable (ex. { name: "Hello world", score: 1.0 }
). We refer to literal representation of input objects as “object literals.”
Input object fields are unordered
Input object fields may be provided in any syntactic order and maintain identical semantic meaning.
These two queries are semantically identical:
Example № 30{
nearestThing(location: { lon: 12.43, lat: -53.211 })
}
Example № 31{
nearestThing(location: { lat: -53.211, lon: 12.43 })
}
Semantics
A GraphQL query can be parameterized with variables, maximizing query reuse, and avoiding costly string building in clients at runtime.
If not defined as constant (for example, in DefaultValue), a Variable can be supplied for an input value.
Variables must be defined at the top of an operation and are in scope throughout the execution of that operation.
In this example, we want to fetch a profile picture size based on the size of a particular device:
Example № 32query getZuckProfile($devicePicSize: Int) {
user(id: 4) {
id
name
profilePic(size: $devicePicSize)
}
}
Values for those variables are provided to a GraphQL service along with a request so they may be substituted during execution. If providing JSON for the variables’ values, we could run this query and request profilePic of size 60
width:
Example № 33{
"devicePicSize": 60
}
Variable use within Fragments
Query variables can be used within fragments. Query variables have global scope with a given operation, so a variable used within a fragment must be declared in any top‐level operation that transitively consumes that fragment. If a variable is referenced in a fragment and is included by an operation that does not define that variable, the operation cannot be executed.
GraphQL describes the types of data expected by query variables. Input types may be lists of another input type, or a non‐null variant of any other input type.
Semantics
Directives provide a way to describe alternate runtime execution and type validation behavior in a GraphQL document.
In some cases, you need to provide options to alter GraphQL’s execution behavior in ways field arguments will not suffice, such as conditionally including or skipping a field. Directives provide this by describing additional information to the executor.
Directives have a name along with a list of arguments which may accept values of any input type.
Directives can be used to describe additional information for types, fields, fragments and operations.
As future versions of GraphQL adopt new configurable execution capabilities, they may be exposed via directives.
The GraphQL Type system describes the capabilities of a GraphQL server and is used to determine if a query is valid. The type system also describes the input types of query variables to determine if values provided at runtime are valid.
The GraphQL language includes an IDL used to describe a GraphQL service’s type system. Tools may use this definition language to provide utilities such as client code generation or service boot‐strapping.
GraphQL tools which only seek to provide GraphQL query execution may choose not to parse TypeSystemDefinition.
A GraphQL Document which contains TypeSystemDefinition must not be executed; GraphQL execution services which receive a GraphQL Document containing type system definitions should return a descriptive error.
Type system extensions are used to represent a GraphQL type system which has been extended from some original type system. For example, this might be used by a local service to represent data a GraphQL client only accesses locally, or by a GraphQL service which is itself an extension of another GraphQL service.
A GraphQL service’s collective type system capabilities are referred to as that service’s “schema”. A schema is defined in terms of the types and directives it supports as well as the root operation types for each kind of operation: query, mutation, and subscription; this determines the place in the type system where those operations begin.
A GraphQL schema must itself be internally valid. This section describes the rules for this validation process where relevant.
All types within a GraphQL schema must have unique names. No two provided types may have the same name. No provided type may have a name which conflicts with any built in types (including Scalar and Introspection types).
All directives within a GraphQL schema must have unique names.
All types and directives defined within a schema must not have a name which begins with "__" (two underscores), as this is used exclusively by GraphQL’s introspection system.
A schema defines the initial root operation type for each kind of operation it supports: query, mutation, and subscription; this determines the place in the type system where those operations begin.
The query
root operation type must be provided and must be an Object type.
The mutation
root operation type is optional; if it is not provided, the service does not support mutations. If it is provided, it must be an Object type.
Similarly, the subscription
root operation type is also optional; if it is not provided, the service does not support subscriptions. If it is provided, it must be an Object type.
The fields on the query
root operation type indicate what fields are available at the top level of a GraphQL query. For example, a basic GraphQL query like:
Example № 34query {
myName
}
Is valid when the query
root operation type has a field named “myName”.
Example № 35type Query {
myName: String
}
Similarly, the following mutation is valid if a mutation
root operation type has a field named “setName”. Note that the query
and mutation
root types must be different types.
Example № 36mutation {
setName(name: "Zuck") {
newName
}
}
When using the type system definition language, a document must include at most one schema
definition.
In this example, a GraphQL schema is defined with both query and mutation root types:
Example № 37schema {
query: MyQueryRootType
mutation: MyMutationRootType
}
type MyQueryRootType {
someField: String
}
type MyMutationRootType {
setSomeField(to: String): String
}
Default Root Operation Type Names
While any type can be the root operation type for a GraphQL operation, the type system definition language can omit the schema definition when the query
, mutation
, and subscription
root types are named Query
, Mutation
, and Subscription
respectively.
Likewise, when representing a GraphQL schema using the type system definition language, a schema definition should be omitted if it only uses the default root operation type names.
This example describes a valid complete GraphQL schema, despite not explicitly including a schema
definition. The Query
type is presumed to be the query
root operation type of the schema.
Example № 38type Query {
someField: String
}
Schema extensions are used to represent a schema which has been extended from an original schema. For example, this might be used by a GraphQL service which adds additional operation types, or additional directives to an existing schema.
Schema Validation
Schema extensions have the potential to be invalid if incorrectly defined.
Documentation is first‐class feature of GraphQL type systems. To ensure the documentation of a GraphQL service remains consistent with its capabilities, descriptions of GraphQL definitions are provided alongside their definitions and made available via introspection.
To allow GraphQL service designers to easily publish documentation alongside the capabilities of a GraphQL service, GraphQL descriptions are defined using the Markdown syntax (as specified by CommonMark). In the type system definition language, these description strings (often BlockString) occur immediately before the definition they describe.
All GraphQL types, fields, arguments and other definitions which can be described should provide a Description unless they are considered self descriptive.
As an example, this simple GraphQL schema is well described:
Example № 39"""
A simple GraphQL schema which is well described.
"""
type Query {
"""
Translates a string from a given language into a different language.
"""
translate(
"The original language that `text` is provided in."
fromLanguage: Language
"The translated language to be returned."
toLanguage: Language
"The text to be translated."
text: String
): String
}
"""
The set of languages supported by `translate`.
"""
enum Language {
"English"
EN
"French"
FR
"Chinese"
CH
}
The fundamental unit of any GraphQL Schema is the type. There are six kinds of named type definitions in GraphQL, and two wrapping types.
The most basic type is a Scalar
. A scalar represents a primitive value, like a string or an integer. Oftentimes, the possible responses for a scalar field are enumerable. GraphQL offers an Enum
type in those cases, where the type specifies the space of valid responses.
Scalars and Enums form the leaves in response trees; the intermediate levels are Object
types, which define a set of fields, where each field is another type in the system, allowing the definition of arbitrary type hierarchies.
GraphQL supports two abstract types: interfaces and unions.
An Interface
defines a list of fields; Object
types that implement that interface are guaranteed to implement those fields. Whenever the type system claims it will return an interface, it will return a valid implementing type.
A Union
defines a list of possible types; similar to interfaces, whenever the type system claims a union will be returned, one of the possible types will be returned.
Finally, oftentimes it is useful to provide complex structs as inputs to GraphQL field arguments or variables; the Input Object
type allows the schema to define exactly what data is expected.
All of the types so far are assumed to be both nullable and singular: e.g. a scalar string returns either null or a singular string.
A GraphQL schema may describe that a field represents list of another types; the List
type is provided for this reason, and wraps another type.
Similarly, the Non-Null
type wraps another type, and denotes that the resulting value will never be null (and that an error cannot result in a null value).
These two types are referred to as “wrapping types”; non‐wrapping types are referred to as “named types”. A wrapping type has an underlying named type, found by continually unwrapping the type until a named type is found.
Types are used throughout GraphQL to describe both the values accepted as input to arguments and variables as well as the values output by fields. These two uses categorize types as input types and output types. Some kinds of types, like Scalar and Enum types, can be used as both input types and output types; other kinds types can only be used in one or the other. Input Object types can only be used as input types. Object, Interface, and Union types can only be used as output types. Lists and Non‐Null types may be used as input types or output types depending on how the wrapped type may be used.
Type extensions are used to represent a GraphQL type which has been extended from some original type. For example, this might be used by a local service to represent additional fields a GraphQL client only accesses locally.
Scalar types represent primitive leaf values in a GraphQL type system. GraphQL responses take the form of a hierarchical tree; the leaves on these trees are GraphQL scalars.
All GraphQL scalars are representable as strings, though depending on the response format being used, there may be a more appropriate primitive for the given scalar type, and server should use those types when appropriate.
GraphQL provides a number of built‐in scalars, but type systems can add additional scalars with semantic meaning. For example, a GraphQL system could define a scalar called Time
which, while serialized as a string, promises to conform to ISO‐8601. When querying a field of type Time
, you can then rely on the ability to parse the result with an ISO‐8601 parser and use a client‐specific primitive for time. Another example of a potentially useful custom scalar is Url
, which serializes as a string, but is guaranteed by the server to be a valid URL.
Example № 40scalar Time
scalar Url
A server may omit any of the built‐in scalars from its schema, for example if a schema does not refer to a floating‐point number, then it must not include the Float
type. However, if a schema includes a type with the name of one of the types described here, it must adhere to the behavior described. As an example, a server must not include a type called Int
and use it to represent 128‐bit numbers, internationalization information, or anything other than what is defined in this document.
When representing a GraphQL schema using the type system definition language, the built‐in scalar types should be omitted for brevity.
Result Coercion
A GraphQL server, when preparing a field of a given scalar type, must uphold the contract the scalar type describes, either by coercing the value or producing a field error if a value cannot be coerced or if coercion may result in data loss.
A GraphQL service may decide to allow coercing different internal types to the expected return type. For example when coercing a field of type Int
a boolean true
value may produce 1
or a string value "123"
may be parsed as base‐10 123
. However if internal type coercion cannot be reasonably performed without losing information, then it must raise a field error.
Since this coercion behavior is not observable to clients of the GraphQL server, the precise rules of coercion are left to the implementation. The only requirement is that the server must yield values which adhere to the expected Scalar type.
Input Coercion
If a GraphQL server expects a scalar type as input to an argument, coercion is observable and the rules must be well defined. If an input value does not match a coercion rule, a query error must be raised.
GraphQL has different constant literals to represent integer and floating‐point input values, and coercion rules may apply differently depending on which type of input value is encountered. GraphQL may be parameterized by query variables, the values of which are often serialized when sent over a transport like HTTP. Since some common serializations (ex. JSON) do not discriminate between integer and floating‐point values, they are interpreted as an integer input value if they have an empty fractional part (ex. 1.0
) and otherwise as floating‐point input value.
For all types below, with the exception of Non‐Null, if the explicit value null is provided, then the result of input coercion is null.
Built‐in Scalars
GraphQL provides a basic set of well‐defined Scalar types. A GraphQL server should support all of these types, and a GraphQL server which provide a type by these names must adhere to the behavior described below.
The Int scalar type represents a signed 32‐bit numeric non‐fractional value. Response formats that support a 32‐bit integer or a number type should use that type to represent this scalar.
Result Coercion
Fields returning the type Int
expect to encounter 32‐bit integer internal values.
GraphQL servers may coerce non‐integer internal values to integers when reasonable without losing information, otherwise they must raise a field error. Examples of this may include returning 1
for the floating‐point number 1.0
, or returning 123
for the string "123"
. In scenarios where coercion may lose data, raising a field error is more appropriate. For example, a floating‐point number 1.2
should raise a field error instead of being truncated to 1
.
If the integer internal value represents a value less than -231 or greater than or equal to 231, a field error should be raised.
Input Coercion
When expected as an input type, only integer input values are accepted. All other input values, including strings with numeric content, must raise a query error indicating an incorrect type. If the integer input value represents a value less than -231 or greater than or equal to 231, a query error should be raised.
The Float scalar type represents signed double‐precision fractional values as specified by IEEE 754. Response formats that support an appropriate double‐precision number type should use that type to represent this scalar.
Result Coercion
Fields returning the type Float
expect to encounter double‐precision floating‐point internal values.
GraphQL servers may coerce non‐floating‐point internal values to Float
when reasonable without losing information, otherwise they must raise a field error. Examples of this may include returning 1.0
for the integer number 1
, or 123.0
for the string "123"
.
Input Coercion
When expected as an input type, both integer and float input values are accepted. Integer input values are coerced to Float by adding an empty fractional part, for example 1.0
for the integer input value 1
. All other input values, including strings with numeric content, must raise a query error indicating an incorrect type. If the integer input value represents a value not representable by IEEE 754, a query error should be raised.
The String scalar type represents textual data, represented as UTF‐8 character sequences. The String type is most often used by GraphQL to represent free‐form human‐readable text. All response formats must support string representations, and that representation must be used here.
Result Coercion
Fields returning the type String
expect to encounter UTF‐8 string internal values.
GraphQL servers may coerce non‐string raw values to String
when reasonable without losing information, otherwise they must raise a field error. Examples of this may include returning the string "true"
for a boolean true value, or the string "1"
for the integer 1
.
Input Coercion
When expected as an input type, only valid UTF‐8 string input values are accepted. All other input values must raise a query error indicating an incorrect type.
The Boolean scalar type represents true
or false
. Response formats should use a built‐in boolean type if supported; otherwise, they should use their representation of the integers 1
and 0
.
Result Coercion
Fields returning the type Boolean
expect to encounter boolean internal values.
GraphQL servers may coerce non‐boolean raw values to Boolean
when reasonable without losing information, otherwise they must raise a field error. Examples of this may include returning true
for non‐zero numbers.
Input Coercion
When expected as an input type, only boolean input values are accepted. All other input values must raise a query error indicating an incorrect type.
The ID scalar type represents a unique identifier, often used to refetch an object or as the key for a cache. The ID type is serialized in the same way as a String
; however, it is not intended to be human‐readable. While it is often numeric, it should always serialize as a String
.
Result Coercion
GraphQL is agnostic to ID format, and serializes to string to ensure consistency across many formats ID could represent, from small auto‐increment numbers, to large 128‐bit random numbers, to base64 encoded values, or string values of a format like GUID.
GraphQL servers should coerce as appropriate given the ID formats they expect. When coercion is not possible they must raise a field error.
Input Coercion
When expected as an input type, any string (such as "4"
) or integer (such as 4
) input value should be coerced to ID as appropriate for the ID formats a given GraphQL server expects. Any other input value, including float input values (such as 4.0
), must raise a query error indicating an incorrect type.
Scalar type extensions are used to represent a scalar type which has been extended from some original scalar type. For example, this might be used by a GraphQL tool or service which adds directives to an existing scalar.
Type Validation
Scalar type extensions have the potential to be invalid if incorrectly defined.
GraphQL queries are hierarchical and composed, describing a tree of information. While Scalar types describe the leaf values of these hierarchical queries, Objects describe the intermediate levels.
GraphQL Objects represent a list of named fields, each of which yield a value of a specific type. Object values should be serialized as ordered maps, where the queried field names (or aliases) are the keys and the result of evaluating the field is the value, ordered by the order in which they appear in the query.
All fields defined within an Object type must not have a name which begins with "__" (two underscores), as this is used exclusively by GraphQL’s introspection system.
For example, a type Person
could be described as:
Example № 41type Person {
name: String
age: Int
picture: Url
}
Where name
is a field that will yield a String
value, and age
is a field that will yield an Int
value, and picture
is a field that will yield a Url
value.
A query of an object value must select at least one field. This selection of fields will yield an ordered map containing exactly the subset of the object queried, which should be represented in the order in which they were queried. Only fields that are declared on the object type may validly be queried on that object.
For example, selecting all the fields of Person
:
Example № 42{
name
age
picture
}
Would yield the object:
Example № 43{
"name": "Mark Zuckerberg",
"age": 30,
"picture": "http://some.cdn/picture.jpg"
}
While selecting a subset of fields:
Example № 44{
age
name
}
Must only yield exactly that subset:
Example № 45{
"age": 30,
"name": "Mark Zuckerberg"
}
A field of an Object type may be a Scalar, Enum, another Object type, an Interface, or a Union. Additionally, it may be any wrapping type whose underlying base type is one of those five.
For example, the Person
type might include a relationship
:
Example № 46type Person {
name: String
age: Int
picture: Url
relationship: Person
}
Valid queries must supply a nested field set for a field that returns an object, so this query is not valid:
Counter Example № 47{
name
relationship
}
However, this example is valid:
Example № 48{
name
relationship {
name
}
}
And will yield the subset of each object type queried:
Example № 49{
"name": "Mark Zuckerberg",
"relationship": {
"name": "Priscilla Chan"
}
}
Field Ordering
When querying an Object, the resulting mapping of fields are conceptually ordered in the same order in which they were encountered during query execution, excluding fragments for which the type does not apply and fields or fragments that are skipped via @skip
or @include
directives. This ordering is correctly produced when using the CollectFields() algorithm.
Response serialization formats capable of representing ordered maps should maintain this ordering. Serialization formats which can only represent unordered maps (such as JSON) should retain this order textually. That is, if two fields {foo, bar}
were queried in that order, the resulting JSON serialization should contain {"foo": "...", "bar": "..."}
in the same order.
Producing a response where fields are represented in the same order in which they appear in the request improves human readability during debugging and enables more efficient parsing of responses if the order of properties can be anticipated.
If a fragment is spread before other fields, the fields that fragment specifies occur in the response before the following fields.
Example № 50{
foo
...Frag
qux
}
fragment Frag on Query {
bar
baz
}
Produces the ordered result:
Example № 51{
"foo": 1,
"bar": 2,
"baz": 3,
"qux": 4
}
If a field is queried multiple times in a selection, it is ordered by the first time it is encountered. However fragments for which the type does not apply does not affect ordering.
Example № 52{
foo
...Ignored
...Matching
bar
}
fragment Ignored on UnknownType {
qux
baz
}
fragment Matching on Query {
bar
qux
foo
}
Produces the ordered result:
Example № 53{
"foo": 1,
"bar": 2,
"qux": 3
}
Also, if directives result in fields being excluded, they are not considered in the ordering of fields.
Example № 54{
foo @skip(if: true)
bar
foo
}
Produces the ordered result:
Example № 55{
"bar": 1,
"foo": 2
}
Result Coercion
Determining the result of coercing an object is the heart of the GraphQL executor, so this is covered in that section of the spec.
Input Coercion
Objects are never valid inputs.
Type Validation
Object types have the potential to be invalid if incorrectly defined. This set of rules must be adhered to by every Object type in a GraphQL schema.
Object fields are conceptually functions which yield values. Occasionally object fields can accept arguments to further specify the return value. Object field arguments are defined as a list of all possible argument names and their expected input types.
All arguments defined within a field must not have a name which begins with "__" (two underscores), as this is used exclusively by GraphQL’s introspection system.
For example, a Person
type with a picture
field could accept an argument to determine what size of an image to return.
Example № 56type Person {
name: String
picture(size: Int): Url
}
GraphQL queries can optionally specify arguments to their fields to provide these arguments.
This example query:
Example № 57{
name
picture(size: 600)
}
May yield the result:
Example № 58{
"name": "Mark Zuckerberg",
"picture": "http://some.cdn/picture_600.jpg"
}
The type of an object field argument must be an input type (any type except an Object, Interface, or Union type).
Fields in an object may be marked as deprecated as deemed necessary by the application. It is still legal to query for these fields (to ensure existing clients are not broken by the change), but the fields should be appropriately treated in documentation and tooling.
When using the type system definition language, @deprecated
directives are used to indicate that a field is deprecated:
Example № 59type ExampleType {
oldField: String @deprecated
}
Object type extensions are used to represent a type which has been extended from some original type. For example, this might be used to represent local data, or by a GraphQL service which is itself an extension of another GraphQL service.
In this example, a local data field is added to a Story
type:
Example № 60extend type Story {
isHiddenLocally: Boolean
}
Object type extensions may choose not to add additional fields, instead only adding interfaces or directives.
In this example, a directive is added to a User
type without adding fields:
Example № 61extend type User @addedDirective
Type Validation
Object type extensions have the potential to be invalid if incorrectly defined.
GraphQL interfaces represent a list of named fields and their arguments. GraphQL objects can then implement these interfaces which requires that the object type will define all fields defined by those interfaces.
Fields on a GraphQL interface have the same rules as fields on a GraphQL object; their type can be Scalar, Object, Enum, Interface, or Union, or any wrapping type whose base type is one of those five.
For example, an interface NamedEntity
may describe a required field and types such as Person
or Business
may then implement this interface to guarantee this field will always exist.
Types may also implement multiple interfaces. For example, Business
implements both the NamedEntity
and ValuedEntity
interfaces in the example below.
Example № 62interface NamedEntity {
name: String
}
interface ValuedEntity {
value: Int
}
type Person implements NamedEntity {
name: String
age: Int
}
type Business implements NamedEntity & ValuedEntity {
name: String
value: Int
employeeCount: Int
}
Fields which yield an interface are useful when one of many Object types are expected, but some fields should be guaranteed.
To continue the example, a Contact
might refer to NamedEntity
.
Example № 63type Contact {
entity: NamedEntity
phoneNumber: String
address: String
}
This allows us to write a query for a Contact
that can select the common fields.
Example № 64{
entity {
name
}
phoneNumber
}
When querying for fields on an interface type, only those fields declared on the interface may be queried. In the above example, entity
returns a NamedEntity
, and name
is defined on NamedEntity
, so it is valid. However, the following would not be a valid query:
Counter Example № 65{
entity {
name
age
}
phoneNumber
}
because entity
refers to a NamedEntity
, and age
is not defined on that interface. Querying for age
is only valid when the result of entity
is a Person
; the query can express this using a fragment or an inline fragment:
Example № 66{
entity {
name
... on Person {
age
}
},
phoneNumber
}
Result Coercion
The interface type should have some way of determining which object a given result corresponds to. Once it has done so, the result coercion of the interface is the same as the result coercion of the object.
Input Coercion
Interfaces are never valid inputs.
Type Validation
Interface types have the potential to be invalid if incorrectly defined.
Interface type extensions are used to represent an interface which has been extended from some original interface. For example, this might be used to represent common local data on many types, or by a GraphQL service which is itself an extension of another GraphQL service.
In this example, an extended data field is added to a NamedEntity
type along with the types which implement it:
Example № 67extend interface NamedEntity {
nickname: String
}
extend type Person {
nickname: String
}
extend type Business {
nickname: String
}
Interface type extensions may choose not to add additional fields, instead only adding directives.
In this example, a directive is added to a NamedEntity
type without adding fields:
Example № 68extend interface NamedEntity @addedDirective
Type Validation
Interface type extensions have the potential to be invalid if incorrectly defined.
GraphQL Unions represent an object that could be one of a list of GraphQL Object types, but provides for no guaranteed fields between those types. They also differ from interfaces in that Object types declare what interfaces they implement, but are not aware of what unions contain them.
With interfaces and objects, only those fields defined on the type can be queried directly; to query other fields on an interface, typed fragments must be used. This is the same as for unions, but unions do not define any fields, so no fields may be queried on this type without the use of type refining fragments or inline fragments.
For example, we might define the following types:
Example № 69union SearchResult = Photo | Person
type Person {
name: String
age: Int
}
type Photo {
height: Int
width: Int
}
type SearchQuery {
firstSearchResult: SearchResult
}
When querying the firstSearchResult
field of type SearchQuery
, the query would ask for all fields inside of a fragment indicating the appropriate type. If the query wanted the name if the result was a Person, and the height if it was a photo, the following query is invalid, because the union itself defines no fields:
Counter Example № 70{
firstSearchResult {
name
height
}
}
Instead, the query would be:
Example № 71{
firstSearchResult {
... on Person {
name
}
... on Photo {
height
}
}
}
Union members may be defined with an optional leading |
character to aid formatting when representing a longer list of possible types:
Example № 72union SearchResult =
| Photo
| Person
Result Coercion
The union type should have some way of determining which object a given result corresponds to. Once it has done so, the result coercion of the union is the same as the result coercion of the object.
Input Coercion
Unions are never valid inputs.
Type Validation
Union types have the potential to be invalid if incorrectly defined.
Union type extensions are used to represent a union type which has been extended from some original union type. For example, this might be used to represent additional local data, or by a GraphQL service which is itself an extension of another GraphQL service.
Type Validation
Union type extensions have the potential to be invalid if incorrectly defined.
GraphQL Enum types, like scalar types, also represent leaf values in a GraphQL type system. However Enum types describe the set of possible values.
Enums are not references for a numeric value, but are unique values in their own right. They may serialize as a string: the name of the represented value.
In this example, an Enum type called Direction
is defined:
Example № 73enum Direction {
NORTH
EAST
SOUTH
WEST
}
Result Coercion
GraphQL servers must return one of the defined set of possible values. If a reasonable coercion is not possible they must raise a field error.
Input Coercion
GraphQL has a constant literal to represent enum input values. GraphQL string literals must not be accepted as an enum input and instead raise a query error.
Query variable transport serializations which have a different representation for non‐string symbolic values (for example, EDN) should only allow such values as enum input values. Otherwise, for most transport serializations that do not, strings may be interpreted as the enum input value with the same name.
Type Validation
Enum types have the potential to be invalid if incorrectly defined.
Enum type extensions are used to represent an enum type which has been extended from some original enum type. For example, this might be used to represent additional local data, or by a GraphQL service which is itself an extension of another GraphQL service.
Type Validation
Enum type extensions have the potential to be invalid if incorrectly defined.
Fields may accept arguments to configure their behavior. These inputs are often scalars or enums, but they sometimes need to represent more complex values.
A GraphQL Input Object defines a set of input fields; the input fields are either scalars, enums, or other input objects. This allows arguments to accept arbitrarily complex structs.
In this example, an Input Object called Point2D
describes x
and y
inputs:
Example № 74input Point2D {
x: Float
y: Float
}
Result Coercion
An input object is never a valid result. Input Object types cannot be the return type of an Object or Interface field.
Input Coercion
The value for an input object should be an input object literal or an unordered map supplied by a variable, otherwise a query error must be thrown. In either case, the input object literal or unordered map must not contain any entries with names not defined by a field of this input object type, otherwise an error must be thrown.
The result of coercion is an unordered map with an entry for each field both defined by the input object type and for which a value exists. The resulting map is constructed with the following rules:
Following are examples of input coercion for an input object type with a String
field a
and a required (non‐null) Int!
field b
:
Example № 75input ExampleInputObject {
a: String
b: Int!
}
Literal Value | Variables | Coerced Value |
---|---|---|
{ a: "abc", b: 123 } | {} | { a: "abc", b: 123 } |
{ a: null, b: 123 } | {} | { a: null, b: 123 } |
{ b: 123 } | {} | { b: 123 } |
{ a: $var, b: 123 } | { var: null } | { a: null, b: 123 } |
{ a: $var, b: 123 } | {} | { b: 123 } |
{ b: $var } | { var: 123 } | { b: 123 } |
$var | { var: { b: 123 } } | { b: 123 } |
"abc123" | {} | Error: Incorrect value |
$var | { var: "abc123" } } | Error: Incorrect value |
{ a: "abc", b: "123" } | {} | Error: Incorrect value for field b |
{ a: "abc" } | {} | Error: Missing required field b |
{ b: $var } | {} | Error: Missing required field b. |
$var | { var: { a: "abc" } } | Error: Missing required field b |
{ a: "abc", b: null } | {} | Error: b must be non‐null. |
{ b: $var } | { var: null } | Error: b must be non‐null. |
{ b: 123, c: "xyz" } | {} | Error: Unexpected field c |
Type Validation
Input object type extensions are used to represent an input object type which has been extended from some original input object type. For example, this might be used by a GraphQL service which is itself an extension of another GraphQL service.
Type Validation
Input object type extensions have the potential to be invalid if incorrectly defined.
A GraphQL list is a special collection type which declares the type of each item in the List (referred to as the item type of the list). List values are serialized as ordered lists, where each item in the list is serialized as per the item type. To denote that a field uses a List type the item type is wrapped in square brackets like this: pets: [Pet]
.
Result Coercion
GraphQL servers must return an ordered list as the result of a list type. Each item in the list must be the result of a result coercion of the item type. If a reasonable coercion is not possible it must raise a field error. In particular, if a non‐list is returned, the coercion should fail, as this indicates a mismatch in expectations between the type system and the implementation.
If a list’s item type is nullable, then errors occuring during preparation or coercion of an individual item in the list must result in a the value null at that position in the list along with an error added to the response. If a list’s item type is non‐null, an error occuring at an individual item in the list must result in a field error for the entire list.
Input Coercion
When expected as an input, list values are accepted only when each item in the list can be accepted by the list’s item type.
If the value passed as an input to a list type is not a list and not the null value, then the result of input coercion is a list of size one, where the single item value is the result of input coercion for the list’s item type on the provided value (note this may apply recursively for nested lists).
This allow inputs which accept one or many arguments (sometimes referred to as “var args”) to declare their input type as a list while for the common case of a single value, a client can just pass that value directly rather than constructing the list.
Following are examples of input coercion with various list types and values:
Expected Type | Provided Value | Coerced Value |
---|---|---|
[Int] | [1, 2, 3] | [1, 2, 3] |
[Int] | [1, "b", true] | Error: Incorrect item value |
[Int] | 1 | [1] |
[Int] | null | null |
[[Int]] | [[1], [2, 3]] | [[1], [2, 3] |
[[Int]] | [1, 2, 3] | Error: Incorrect item value |
[[Int]] | 1 | [[1]] |
[[Int]] | null | null |
By default, all types in GraphQL are nullable; the null value is a valid response for all of the above types. To declare a type that disallows null, the GraphQL Non‐Null type can be used. This type wraps an underlying type, and this type acts identically to that wrapped type, with the exception that null is not a valid response for the wrapping type. A trailing exclamation mark is used to denote a field that uses a Non‐Null type like this: name: String!
.
Nullable vs. Optional
Fields are always optional within the context of a query, a field may be omitted and the query is still valid. However fields that return Non‐Null types will never return the value null if queried.
Inputs (such as field arguments), are always optional by default. However a non‐null input type is required. In addition to not accepting the value null, it also does not accept omission. For the sake of simplicity nullable types are always optional and non‐null types are always required.
Result Coercion
In all of the above result coercions, null was considered a valid value. To coerce the result of a Non‐Null type, the coercion of the wrapped type should be performed. If that result was not null, then the result of coercing the Non‐Null type is that result. If that result was null, then a field error must be raised.
Input Coercion
If an argument or input‐object field of a Non‐Null type is not provided, is provided with the literal value null, or is provided with a variable that was either not provided a value at runtime, or was provided the value null, then a query error must be raised.
If the value provided to the Non‐Null type is provided with a literal value other than null, or a Non‐Null variable value, it is coerced using the input coercion for the wrapped type.
A non‐null argument cannot be omitted:
Counter Example № 76{
fieldWithNonNullArg
}
The value null cannot be provided to a non‐null argument:
Counter Example № 77{
fieldWithNonNullArg(nonNullArg: null)
}
A variable of a nullable type cannot be provided to a non‐null argument:
Example № 78query withNullableVariable($var: String) {
fieldWithNonNullArg(nonNullArg: $var)
}
Type Validation
The List and Non‐Null wrapping types can compose, representing more complex types. The rules for result coercion and input coercion of Lists and Non‐Null types apply in a recursive fashion.
For example if the inner item type of a List is Non‐Null (e.g. [T!]
), then that List may not contain any null items. However if the inner type of a Non‐Null is a List (e.g. [T]!
), then null is not accepted however an empty list is accepted.
Following are examples of result coercion with various types and values:
Expected Type | Internal Value | Coerced Result |
---|---|---|
[Int] | [1, 2, 3] | [1, 2, 3] |
[Int] | null | null |
[Int] | [1, 2, null] | [1, 2, null] |
[Int] | [1, 2, Error] | [1, 2, null] (With logged error) |
[Int]! | [1, 2, 3] | [1, 2, 3] |
[Int]! | null | Error: Value cannot be null |
[Int]! | [1, 2, null] | [1, 2, null] |
[Int]! | [1, 2, Error] | [1, 2, null] (With logged error) |
[Int!] | [1, 2, 3] | [1, 2, 3] |
[Int!] | null | null |
[Int!] | [1, 2, null] | null (With logged coercion error) |
[Int!] | [1, 2, Error] | null (With logged error) |
[Int!]! | [1, 2, 3] | [1, 2, 3] |
[Int!]! | null | Error: Value cannot be null |
[Int!]! | [1, 2, null] | Error: Item cannot be null |
[Int!]! | [1, 2, Error] | Error: Error occurred in item |
QUERY |
MUTATION |
SUBSCRIPTION |
FIELD |
FRAGMENT_DEFINITION |
FRAGMENT_SPREAD |
INLINE_FRAGMENT |
SCHEMA |
SCALAR |
OBJECT |
FIELD_DEFINITION |
ARGUMENT_DEFINITION |
INTERFACE |
UNION |
ENUM |
ENUM_VALUE |
INPUT_OBJECT |
INPUT_FIELD_DEFINITION |
A GraphQL schema describes directives which are used to annotate various parts of a GraphQL document as an indicator that they should be evaluated differently by a validator, executor, or client tool such as a code generator.
GraphQL implementations should provide the @skip
and @include
directives.
GraphQL implementations that support the type system definition language must provide the @deprecated
directive if representing deprecated portions of the schema.
Directives must only be used in the locations they are declared to belong in. In this example, a directive is defined which can be used to annotate a fragment definition:
Example № 79directive @example on FIELD
fragment SomeFragment on SomeType {
field @example
}
Directive locations may be defined with an optional leading |
character to aid formatting when representing a longer list of possible locations:
Example № 80directive @example on
| FIELD
| FRAGMENT_SPREAD
| INLINE_FRAGMENT
Directives can also be used to annotate the type system definition language as well, which can be a useful tool for supplying additional metadata in order to generate GraphQL execution services, produce client generated runtime code, or many other useful extensions of the GraphQL semantics.
In this example, the directive @example
annotates field and argument definitions:
Example № 81directive @example on FIELD_DEFINITION | ARGUMENT_DEFINITION
type SomeType {
field(arg: Int @example): String @example
}
While defining a directive, it must not reference itself directly or indirectly:
Counter Example № 82directive @invalidExample(arg: String @invalidExample) on ARGUMENT_DEFINITION
Validation
directive @skip(if: Boolean!) on FIELD | FRAGMENT_SPREAD | INLINE_FRAGMENT
The @skip
directive may be provided for fields, fragment spreads, and inline fragments, and allows for conditional exclusion during execution as described by the if argument.
In this example experimentalField
will only be queried if the variable $someTest
has the value false
.
Example № 83query myQuery($someTest: Boolean) {
experimentalField @skip(if: $someTest)
}
directive @include(if: Boolean!) on FIELD | FRAGMENT_SPREAD | INLINE_FRAGMENT
The @include
directive may be provided for fields, fragment spreads, and inline fragments, and allows for conditional inclusion during execution as described by the if argument.
In this example experimentalField
will only be queried if the variable $someTest
has the value true
Example № 84query myQuery($someTest: Boolean) {
experimentalField @include(if: $someTest)
}
@skip
nor @include
has precedence over the other. In the case that both the @skip
and @include
directives are provided in on the same the field or fragment, it must be queried only if the @skip
condition is false and the @include
condition is true. Stated conversely, the field or fragment must not be queried if either the @skip
condition is true or the @include
condition is false.directive @deprecated(
reason: String = "No longer supported"
) on FIELD_DEFINITION | ENUM_VALUE
The @deprecated
directive is used within the type system definition language to indicate deprecated portions of a GraphQL service’s schema, such as deprecated fields on a type or deprecated enum values.
Deprecations include a reason for why it is deprecated, which is formatted using Markdown syntax (as specified by CommonMark).
In this example type definition, oldField
is deprecated in favor of using newField
.
Example № 85type ExampleType {
newField: String
oldField: String @deprecated(reason: "Use `newField`.")
}
A GraphQL server supports introspection over its schema. This schema is queried using GraphQL itself, creating a powerful platform for tool‐building.
Take an example query for a trivial app. In this case there is a User type with three fields: id, name, and birthday.
For example, given a server with the following type definition:
Example № 86type User {
id: String
name: String
birthday: Date
}
The query
Example № 87{
__type(name: "User") {
name
fields {
name
type {
name
}
}
}
}
would return
Example № 88{
"__type": {
"name": "User",
"fields": [
{
"name": "id",
"type": { "name": "String" }
},
{
"name": "name",
"type": { "name": "String" }
},
{
"name": "birthday",
"type": { "name": "Date" }
},
]
}
}
Types and fields required by the GraphQL introspection system that are used in the same context as user‐defined types and fields are prefixed with "__" two underscores. This in order to avoid naming collisions with user‐defined GraphQL types. Conversely, GraphQL type system authors must not define any types, fields, arguments, or any other type system artifact with two leading underscores.
All types in the introspection system provide a description
field of type String
to allow type designers to publish documentation in addition to capabilities. A GraphQL server may return the description
field using Markdown syntax (as specified by CommonMark). Therefore it is recommended that any tool that displays description
use a CommonMark‐compliant Markdown renderer.
To support the management of backwards compatibility, GraphQL fields and enum values can indicate whether or not they are deprecated (isDeprecated: Boolean
) and a description of why it is deprecated (deprecationReason: String
).
Tools built using GraphQL introspection should respect deprecation by discouraging deprecated use through information hiding or developer‐facing warnings.
GraphQL supports type name introspection at any point within a query by the meta‐field __typename: String!
when querying against any Object, Interface, or Union. It returns the name of the object type currently being queried.
This is most often used when querying against Interface or Union types to identify which actual type of the possible types has been returned.
This field is implicit and does not appear in the fields list in any defined type.
The schema introspection system is accessible from the meta‐fields __schema
and __type
which are accessible from the type of the root of a query operation.
__schema: __Schema!
__type(name: String!): __Type
These fields are implicit and do not appear in the fields list in the root type of the query operation.
The schema of the GraphQL schema introspection system:
type __Schema {
types: [__Type!]!
queryType: __Type!
mutationType: __Type
subscriptionType: __Type
directives: [__Directive!]!
}
type __Type {
kind: __TypeKind!
name: String
description: String
# OBJECT and INTERFACE only
fields(includeDeprecated: Boolean = false): [__Field!]
# OBJECT only
interfaces: [__Type!]
# INTERFACE and UNION only
possibleTypes: [__Type!]
# ENUM only
enumValues(includeDeprecated: Boolean = false): [__EnumValue!]
# INPUT_OBJECT only
inputFields: [__InputValue!]
# NON_NULL and LIST only
ofType: __Type
}
type __Field {
name: String!
description: String
args: [__InputValue!]!
type: __Type!
isDeprecated: Boolean!
deprecationReason: String
}
type __InputValue {
name: String!
description: String
type: __Type!
defaultValue: String
}
type __EnumValue {
name: String!
description: String
isDeprecated: Boolean!
deprecationReason: String
}
enum __TypeKind {
SCALAR
OBJECT
INTERFACE
UNION
ENUM
INPUT_OBJECT
LIST
NON_NULL
}
type __Directive {
name: String!
description: String
locations: [__DirectiveLocation!]!
args: [__InputValue!]!
}
enum __DirectiveLocation {
QUERY
MUTATION
SUBSCRIPTION
FIELD
FRAGMENT_DEFINITION
FRAGMENT_SPREAD
INLINE_FRAGMENT
SCHEMA
SCALAR
OBJECT
FIELD_DEFINITION
ARGUMENT_DEFINITION
INTERFACE
UNION
ENUM
ENUM_VALUE
INPUT_OBJECT
INPUT_FIELD_DEFINITION
}
__Type
is at the core of the type introspection system. It represents scalars, interfaces, object types, unions, enums in the system.
__Type
also represents type modifiers, which are used to modify a type that it refers to (ofType: __Type
). This is how we represent lists, non‐nullable types, and the combinations thereof.
There are several different kinds of type. In each kind, different fields are actually valid. These kinds are listed in the __TypeKind
enumeration.
Represents scalar types such as Int, String, and Boolean. Scalars cannot have fields.
A GraphQL type designer should describe the data format and scalar coercion rules in the description field of any scalar.
Fields
kind
must return __TypeKind.SCALAR
.name
must return a String.description
may return a String or null.Object types represent concrete instantiations of sets of fields. The introspection types (e.g. __Type
, __Field
, etc) are examples of objects.
Fields
kind
must return __TypeKind.OBJECT
.name
must return a String.description
may return a String or null.fields
: The set of fields query‐able on this type.includeDeprecated
which defaults to false. If true, deprecated fields are also returned.interfaces
: The set of interfaces that an object implements.Unions are an abstract type where no common fields are declared. The possible types of a union are explicitly listed out in possibleTypes
. Types can be made parts of unions without modification of that type.
Fields
kind
must return __TypeKind.UNION
.name
must return a String.description
may return a String or null.possibleTypes
returns the list of types that can be represented within this union. They must be object types.Interfaces are an abstract type where there are common fields declared. Any type that implements an interface must define all the fields with names and types exactly matching. The implementations of this interface are explicitly listed out in possibleTypes
.
Fields
kind
must return __TypeKind.INTERFACE
.name
must return a String.description
may return a String or null.fields
: The set of fields required by this interface.includeDeprecated
which defaults to false. If true, deprecated fields are also returned.possibleTypes
returns the list of types that implement this interface. They must be object types.Enums are special scalars that can only have a defined set of values.
Fields
kind
must return __TypeKind.ENUM
.name
must return a String.description
may return a String or null.enumValues
: The list of EnumValue
. There must be at least one and they must have unique names.includeDeprecated
which defaults to false. If true, deprecated enum values are also returned.Input objects are composite types used as inputs into queries defined as a list of named input values.
For example the input object Point
could be defined as:
Example № 89input Point {
x: Int
y: Int
}
Fields
kind
must return __TypeKind.INPUT_OBJECT
.name
must return a String.description
may return a String or null.inputFields
: a list of InputValue
.Lists represent sequences of values in GraphQL. A List type is a type modifier: it wraps another type instance in the ofType
field, which defines the type of each item in the list.
Fields
kind
must return __TypeKind.LIST
.ofType
: Any type.GraphQL types are nullable. The value null is a valid response for field type.
A Non‐null type is a type modifier: it wraps another type instance in the ofType
field. Non‐null types do not allow null as a response, and indicate required inputs for arguments and input object fields.
kind
must return __TypeKind.NON_NULL
.ofType
: Any type except Non‐null.The __Field
type represents each field in an Object or Interface type.
Fields
name
must return a Stringdescription
may return a String or nullargs
returns a List of __InputValue
representing the arguments this field accepts.type
must return a __Type
that represents the type of value returned by this field.isDeprecated
returns true if this field should no longer be used, otherwise false.deprecationReason
optionally provides a reason why this field is deprecated.The __InputValue
type represents field and directive arguments as well as the inputFields
of an input object.
Fields
name
must return a Stringdescription
may return a String or nulltype
must return a __Type
that represents the type this input value expects.defaultValue
may return a String encoding (using the GraphQL language) of the default value used by this input value in the condition a value is not provided at runtime. If this input value has no default value, returns null.The __EnumValue
type represents one of possible values of an enum.
Fields
name
must return a Stringdescription
may return a String or nullisDeprecated
returns true if this field should no longer be used, otherwise false.deprecationReason
optionally provides a reason why this field is deprecated.The __Directive
type represents a Directive that a server supports.
Fields
name
must return a Stringdescription
may return a String or nulllocations
returns a List of __DirectiveLocation
representing the valid locations this directive may be placed.args
returns a List of __InputValue
representing the arguments this directive accepts. GraphQL does not just verify if a request is syntactically correct, but also ensures that it is unambiguous and mistake‐free in the context of a given GraphQL schema.
An invalid request is still technically executable, and will always produce a stable result as defined by the algorithms in the Execution section, however that result may be ambiguous, surprising, or unexpected relative to a request containing validation errors, so execution should only occur for valid requests.
Typically validation is performed in the context of a request immediately before execution, however a GraphQL service may execute a request without explicitly validating it if that exact same request is known to have been validated before. For example: the request may be validated during development, provided it does not later change, or a service may validate a request once and memoize the result to avoid validating the same request again in the future. Any client‐side or development‐time tool should report validation errors and not allow the formulation or execution of requests known to be invalid at that given point in time.
Type system evolution
As GraphQL type system schema evolve over time by adding new types and new fields, it is possible that a request which was previously valid could later become invalid. Any change that can cause a previously valid request to become invalid is considered a breaking change. GraphQL services and schema maintainers are encouraged to avoid breaking changes, however in order to be more resilient to these breaking changes, sophisticated GraphQL systems may still allow for the execution of requests which at some point were known to be free of any validation errors, and have not changed since.
Examples
For this section of this schema, we will assume the following type system in order to demonstrate examples:
Example № 90type Query {
dog: Dog
}
enum DogCommand { SIT, DOWN, HEEL }
type Dog implements Pet {
name: String!
nickname: String
barkVolume: Int
doesKnowCommand(dogCommand: DogCommand!): Boolean!
isHousetrained(atOtherHomes: Boolean): Boolean!
owner: Human
}
interface Sentient {
name: String!
}
interface Pet {
name: String!
}
type Alien implements Sentient {
name: String!
homePlanet: String
}
type Human implements Sentient {
name: String!
}
enum CatCommand { JUMP }
type Cat implements Pet {
name: String!
nickname: String
doesKnowCommand(catCommand: CatCommand!): Boolean!
meowVolume: Int
}
union CatOrDog = Cat | Dog
union DogOrHuman = Dog | Human
union HumanOrAlien = Human | Alien
Formal Specification
Explanatory Text
GraphQL execution will only consider the executable definitions Operation and Fragment. Type system definitions and extensions are not executable, and are not considered during execution.
To avoid ambiguity, a document containing TypeSystemDefinition is invalid for execution.
GraphQL documents not intended to be directly executed may include TypeSystemDefinition.
For example, the following document is invalid for execution since the original executing schema may not know about the provided type extension:
Counter Example № 91query getDogName {
dog {
name
color
}
}
extend type Dog {
color: String
}
Formal Specification
Explanatory Text
Each named operation definition must be unique within a document when referred to by its name.
For example the following document is valid:
Example № 92query getDogName {
dog {
name
}
}
query getOwnerName {
dog {
owner {
name
}
}
}
While this document is invalid:
Counter Example № 93query getName {
dog {
name
}
}
query getName {
dog {
owner {
name
}
}
}
It is invalid even if the type of each operation is different:
Counter Example № 94query dogOperation {
dog {
name
}
}
mutation dogOperation {
mutateDog {
id
}
}
Formal Specification
Explanatory Text
GraphQL allows a short‐hand form for defining query operations when only that one operation exists in the document.
For example the following document is valid:
Example № 95{
dog {
name
}
}
While this document is invalid:
Counter Example № 96{
dog {
name
}
}
query getName {
dog {
owner {
name
}
}
}
Formal Specification
Explanatory Text
Subscription operations must have exactly one root field.
Valid examples:
Example № 97subscription sub {
newMessage {
body
sender
}
}
Example № 98subscription sub {
...newMessageFields
}
fragment newMessageFields on Subscription {
newMessage {
body
sender
}
}
Invalid:
Counter Example № 99subscription sub {
newMessage {
body
sender
}
disallowedSecondRootField
}
Counter Example № 100subscription sub {
...multipleSubscriptions
}
fragment multipleSubscriptions on Subscription {
newMessage {
body
sender
}
disallowedSecondRootField
}
Introspection fields are counted. The following example is also invalid:
Counter Example № 101subscription sub {
newMessage {
body
sender
}
__typename
}
Formal Specification
Explanatory Text
The target field of a field selection must be defined on the scoped type of the selection set. There are no limitations on alias names.
For example the following fragment would not pass validation:
Counter Example № 102fragment fieldNotDefined on Dog {
meowVolume
}
fragment aliasedLyingFieldTargetNotDefined on Dog {
barkVolume: kawVolume
}
For interfaces, direct field selection can only be done on fields. Fields of concrete implementors are not relevant to the validity of the given interface‐typed selection set.
For example, the following is valid:
Example № 103fragment interfaceFieldSelection on Pet {
name
}
and the following is invalid:
Counter Example № 104fragment definedOnImplementorsButNotInterface on Pet {
nickname
}
Because unions do not define fields, fields may not be directly selected from a union‐typed selection set, with the exception of the meta‐field __typename. Fields from a union‐typed selection set must only be queried indirectly via a fragment.
For example the following is valid:
Example № 105fragment inDirectFieldSelectionOnUnion on CatOrDog {
__typename
... on Pet {
name
}
... on Dog {
barkVolume
}
}
But the following is invalid:
Counter Example № 106fragment directFieldSelectionOnUnion on CatOrDog {
name
barkVolume
}
Formal Specification
Explanatory Text
If multiple field selections with the same response names are encountered during execution, the field and arguments to execute and the resulting value should be unambiguous. Therefore any two field selections which might both be encountered for the same object are only valid if they are equivalent.
During execution, the simultaneous execution of fields with the same response name is accomplished by MergeSelectionSets() and CollectFields().
For simple hand‐written GraphQL, this rule is obviously a clear developer error, however nested fragments can make this difficult to detect manually.
The following selections correctly merge:
Example № 107fragment mergeIdenticalFields on Dog {
name
name
}
fragment mergeIdenticalAliasesAndFields on Dog {
otherName: name
otherName: name
}
The following is not able to merge:
Counter Example № 108fragment conflictingBecauseAlias on Dog {
name: nickname
name
}
Identical arguments are also merged if they have identical arguments. Both values and variables can be correctly merged.
For example the following correctly merge:
Example № 109fragment mergeIdenticalFieldsWithIdenticalArgs on Dog {
doesKnowCommand(dogCommand: SIT)
doesKnowCommand(dogCommand: SIT)
}
fragment mergeIdenticalFieldsWithIdenticalValues on Dog {
doesKnowCommand(dogCommand: $dogCommand)
doesKnowCommand(dogCommand: $dogCommand)
}
The following do not correctly merge:
Counter Example № 110fragment conflictingArgsOnValues on Dog {
doesKnowCommand(dogCommand: SIT)
doesKnowCommand(dogCommand: HEEL)
}
fragment conflictingArgsValueAndVar on Dog {
doesKnowCommand(dogCommand: SIT)
doesKnowCommand(dogCommand: $dogCommand)
}
fragment conflictingArgsWithVars on Dog {
doesKnowCommand(dogCommand: $varOne)
doesKnowCommand(dogCommand: $varTwo)
}
fragment differingArgs on Dog {
doesKnowCommand(dogCommand: SIT)
doesKnowCommand
}
The following fields would not merge together, however both cannot be encountered against the same object, so they are safe:
Example № 111fragment safeDifferingFields on Pet {
... on Dog {
volume: barkVolume
}
... on Cat {
volume: meowVolume
}
}
fragment safeDifferingArgs on Pet {
... on Dog {
doesKnowCommand(dogCommand: SIT)
}
... on Cat {
doesKnowCommand(catCommand: JUMP)
}
}
However, the field responses must be shapes which can be merged. For example, scalar values must not differ. In this example, someValue
might be a String
or an Int
:
Counter Example № 112fragment conflictingDifferingResponses on Pet {
... on Dog {
someValue: nickname
}
... on Cat {
someValue: meowVolume
}
}
Formal Specification
Explanatory Text
Field selections on scalars or enums are never allowed, because they are the leaf nodes of any GraphQL query.
The following is valid.
Example № 113fragment scalarSelection on Dog {
barkVolume
}
The following is invalid.
Counter Example № 114fragment scalarSelectionsNotAllowedOnInt on Dog {
barkVolume {
sinceWhen
}
}
Conversely the leaf field selections of GraphQL queries must be of type scalar or enum. Leaf selections on objects, interfaces, and unions without subfields are disallowed.
Let’s assume the following additions to the query root type of the schema:
Example № 115extend type Query {
human: Human
pet: Pet
catOrDog: CatOrDog
}
The following examples are invalid
Counter Example № 116query directQueryOnObjectWithoutSubFields {
human
}
query directQueryOnInterfaceWithoutSubFields {
pet
}
query directQueryOnUnionWithoutSubFields {
catOrDog
}
Arguments are provided to both fields and directives. The following validation rules apply in both cases.
Formal Specification
Explanatory Text
Every argument provided to a field or directive must be defined in the set of possible arguments of that field or directive.
For example the following are valid:
Example № 117fragment argOnRequiredArg on Dog {
doesKnowCommand(dogCommand: SIT)
}
fragment argOnOptional on Dog {
isHousetrained(atOtherHomes: true) @include(if: true)
}
the following is invalid since command
is not defined on DogCommand
.
Counter Example № 118fragment invalidArgName on Dog {
doesKnowCommand(command: CLEAN_UP_HOUSE)
}
and this is also invalid as unless
is not defined on @include
.
Counter Example № 119fragment invalidArgName on Dog {
isHousetrained(atOtherHomes: true) @include(unless: false)
}
In order to explore more complicated argument examples, let’s add the following to our type system:
Example № 120type Arguments {
multipleReqs(x: Int!, y: Int!): Int!
booleanArgField(booleanArg: Boolean): Boolean
floatArgField(floatArg: Float): Float
intArgField(intArg: Int): Int
nonNullBooleanArgField(nonNullBooleanArg: Boolean!): Boolean!
booleanListArgField(booleanListArg: [Boolean]!): [Boolean]
optionalNonNullBooleanArgField(optionalBooleanArg: Boolean! = false): Boolean!
}
extend type Query {
arguments: Arguments
}
Order does not matter in arguments. Therefore both the following example are valid.
Example № 121fragment multipleArgs on Arguments {
multipleReqs(x: 1, y: 2)
}
fragment multipleArgsReverseOrder on Arguments {
multipleReqs(y: 1, x: 2)
}
Fields and directives treat arguments as a mapping of argument name to value. More than one argument with the same name in an argument set is ambiguous and invalid.
Formal Specification
Explanatory Text
Arguments can be required. An argument is required if the argument type is non‐null and does not have a default value. Otherwise, the argument is optional.
For example the following are valid:
Example № 122fragment goodBooleanArg on Arguments {
booleanArgField(booleanArg: true)
}
fragment goodNonNullArg on Arguments {
nonNullBooleanArgField(nonNullBooleanArg: true)
}
The argument can be omitted from a field with a nullable argument.
Therefore the following query is valid:
Example № 123fragment goodBooleanArgDefault on Arguments {
booleanArgField
}
but this is not valid on a required argument.
Counter Example № 124fragment missingRequiredArg on Arguments {
nonNullBooleanArgField
}
Providing the explicit value null is also not valid since required arguments always have a non‐null type.
Counter Example № 125fragment missingRequiredArg on Arguments {
nonNullBooleanArgField(nonNullBooleanArg: null)
}
Formal Specification
Explanatory Text
Fragment definitions are referenced in fragment spreads by name. To avoid ambiguity, each fragment’s name must be unique within a document.
Inline fragments are not considered fragment definitions, and are unaffected by this validation rule.
For example the following document is valid:
Example № 126{
dog {
...fragmentOne
...fragmentTwo
}
}
fragment fragmentOne on Dog {
name
}
fragment fragmentTwo on Dog {
owner {
name
}
}
While this document is invalid:
Counter Example № 127{
dog {
...fragmentOne
}
}
fragment fragmentOne on Dog {
name
}
fragment fragmentOne on Dog {
owner {
name
}
}
Formal Specification
Explanatory Text
Fragments must be specified on types that exist in the schema. This applies for both named and inline fragments. If they are not defined in the schema, the query does not validate.
For example the following fragments are valid:
Example № 128fragment correctType on Dog {
name
}
fragment inlineFragment on Dog {
... on Dog {
name
}
}
fragment inlineFragment2 on Dog {
... @include(if: true) {
name
}
}
and the following do not validate:
Counter Example № 129fragment notOnExistingType on NotInSchema {
name
}
fragment inlineNotExistingType on Dog {
... on NotInSchema {
name
}
}
Formal Specification
Explanatory Text
Fragments can only be declared on unions, interfaces, and objects. They are invalid on scalars. They can only be applied on non‐leaf fields. This rule applies to both inline and named fragments.
The following fragment declarations are valid:
Example № 130fragment fragOnObject on Dog {
name
}
fragment fragOnInterface on Pet {
name
}
fragment fragOnUnion on CatOrDog {
... on Dog {
name
}
}
and the following are invalid:
Counter Example № 131fragment fragOnScalar on Int {
something
}
fragment inlineFragOnScalar on Dog {
... on Boolean {
somethingElse
}
}
Formal Specification
Explanatory Text
Defined fragments must be used within a document.
For example the following is an invalid document:
Counter Example № 132fragment nameFragment on Dog { # unused
name
}
{
dog {
name
}
}
Field selection is also determined by spreading fragments into one another. The selection set of the target fragment is unioned with the selection set at the level at which the target fragment is referenced.
Formal Specification
Explanatory Text
Named fragment spreads must refer to fragments defined within the document. It is a validation error if the target of a spread is not defined.
Counter Example № 133{
dog {
...undefinedFragment
}
}
Formal Specification
DetectCycles(fragmentDefinition, visited) :
Explanatory Text
The graph of fragment spreads must not form any cycles including spreading itself. Otherwise an operation could infinitely spread or infinitely execute on cycles in the underlying data.
This invalidates fragments that would result in an infinite spread:
Counter Example № 134{
dog {
...nameFragment
}
}
fragment nameFragment on Dog {
name
...barkVolumeFragment
}
fragment barkVolumeFragment on Dog {
barkVolume
...nameFragment
}
If the above fragments were inlined, this would result in the infinitely large:
Example № 135{
dog {
name
barkVolume
name
barkVolume
name
barkVolume
name
# forever...
}
}
This also invalidates fragments that would result in an infinite recursion when executed against cyclic data:
Counter Example № 136{
dog {
...dogFragment
}
}
fragment dogFragment on Dog {
name
owner {
...ownerFragment
}
}
fragment ownerFragment on Dog {
name
pets {
...dogFragment
}
}
Formal Specification
Explanatory Text
Fragments are declared on a type and will only apply when the runtime object type matches the type condition. They also are spread within the context of a parent type. A fragment spread is only valid if its type condition could ever apply within the parent type.
In the scope of an object type, the only valid object type fragment spread is one that applies to the same type that is in scope.
For example
Example № 137fragment dogFragment on Dog {
... on Dog {
barkVolume
}
}
and the following is invalid
Counter Example № 138fragment catInDogFragmentInvalid on Dog {
... on Cat {
meowVolume
}
}
In scope of an object type, unions or interface spreads can be used if the object type implements the interface or is a member of the union.
For example
Example № 139fragment petNameFragment on Pet {
name
}
fragment interfaceWithinObjectFragment on Dog {
...petNameFragment
}
is valid because Dog implements Pet.
Likewise
Example № 140fragment catOrDogNameFragment on CatOrDog {
... on Cat {
meowVolume
}
}
fragment unionWithObjectFragment on Dog {
...catOrDogNameFragment
}
is valid because Dog is a member of the CatOrDog union. It is worth noting that if one inspected the contents of the CatOrDogNameFragment you could note that no valid results would ever be returned. However we do not specify this as invalid because we only consider the fragment declaration, not its body.
Union or interface spreads can be used within the context of an object type fragment, but only if the object type is one of the possible types of that interface or union.
For example, the following fragments are valid:
Example № 141fragment petFragment on Pet {
name
... on Dog {
barkVolume
}
}
fragment catOrDogFragment on CatOrDog {
... on Cat {
meowVolume
}
}
petFragment is valid because Dog implements the interface Pet. catOrDogFragment is valid because Cat is a member of the CatOrDog union.
By contrast the following fragments are invalid:
Counter Example № 142fragment sentientFragment on Sentient {
... on Dog {
barkVolume
}
}
fragment humanOrAlienFragment on HumanOrAlien {
... on Cat {
meowVolume
}
}
Dog does not implement the interface Sentient and therefore sentientFragment can never return meaningful results. Therefore the fragment is invalid. Likewise Cat is not a member of the union HumanOrAlien, and it can also never return meaningful results, making it invalid.
Union or interfaces fragments can be used within each other. As long as there exists at least one object type that exists in the intersection of the possible types of the scope and the spread, the spread is considered valid.
So for example
Example № 143fragment unionWithInterface on Pet {
...dogOrHumanFragment
}
fragment dogOrHumanFragment on DogOrHuman {
... on Dog {
barkVolume
}
}
is consider valid because Dog implements interface Pet and is a member of DogOrHuman.
However
Counter Example № 144fragment nonIntersectingInterfaces on Pet {
...sentientFragment
}
fragment sentientFragment on Sentient {
name
}
is not valid because there exists no type that implements both Pet and Sentient.
Format Specification
Explanatory Text
Literal values must be compatible with the type expected in the position they are found as per the coercion rules defined in the Type System chapter.
The type expected in a position include the type defined by the argument a value is provided for, the type defined by an input object field a value is provided for, and the type of a variable definition a default value is provided for.
The following examples are valid use of value literals:
Example № 145fragment goodBooleanArg on Arguments {
booleanArgField(booleanArg: true)
}
fragment coercedIntIntoFloatArg on Arguments {
# Note: The input coercion rules for Float allow Int literals.
floatArgField(floatArg: 123)
}
query goodComplexDefaultValue($search: ComplexInput = { name: "Fido" }) {
findDog(complex: $search)
}
Non‐coercible values (such as a String into an Int) are invalid. The following examples are invalid:
Counter Example № 146fragment stringIntoInt on Arguments {
intArgField(intArg: "123")
}
query badComplexValue {
findDog(complex: { name: 123 })
}
Formal Specification
Explanatory Text
Every input field provided in an input object value must be defined in the set of possible fields of that input object’s expected type.
For example the following example input object is valid:
Example № 147{
findDog(complex: { name: "Fido" })
}
While the following example input‐object uses a field “favoriteCookieFlavor” which is not defined on the expected type:
Counter Example № 148{
findDog(complex: { favoriteCookieFlavor: "Bacon" })
}
Formal Specification
Explanatory Text
Input objects must not contain more than one field of the same name, otherwise an ambiguity would exist which includes an ignored portion of syntax.
For example the following query will not pass validation.
Counter Example № 149{
field(arg: { field: true, field: false })
}
Formal Specification
Explanatory Text
Input object fields may be required. Much like a field may have required arguments, an input object may have required fields. An input field is required if it has a non‐null type and does not have a default value. Otherwise, the input object field is optional.
Formal Specification
Explanatory Text
GraphQL servers define what directives they support. For each usage of a directive, the directive must be available on that server.
Formal Specification
Explanatory Text
GraphQL servers define what directives they support and where they support them. For each usage of a directive, the directive must be used in a location that the server has declared support for.
For example the following query will not pass validation because @skip
does not provide QUERY
as a valid location.
Counter Example № 150query @skip(if: $foo) {
field
}
Formal Specification
Explanatory Text
Directives are used to describe some metadata or behavioral change on the definition they apply to. When more than one directive of the same name is used, the expected metadata or behavior becomes ambiguous, therefore only one of each directive is allowed per location.
For example, the following query will not pass validation because @skip
has been used twice for the same field:
Counter Example № 151query ($foo: Boolean = true, $bar: Boolean = false) {
field @skip(if: $foo) @skip(if: $bar)
}
However the following example is valid because @skip
has been used only once per location, despite being used twice in the query and on the same named field:
Example № 152query ($foo: Boolean = true, $bar: Boolean = false) {
field @skip(if: $foo) {
subfieldA
}
field @skip(if: $bar) {
subfieldB
}
}
Formal Specification
Explanatory Text
If any operation defines more than one variable with the same name, it is ambiguous and invalid. It is invalid even if the type of the duplicate variable is the same.
Counter Example № 153query houseTrainedQuery($atOtherHomes: Boolean, $atOtherHomes: Boolean) {
dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
}
It is valid for multiple operations to define a variable with the same name. If two operations reference the same fragment, it might actually be necessary:
Example № 154query A($atOtherHomes: Boolean) {
...HouseTrainedFragment
}
query B($atOtherHomes: Boolean) {
...HouseTrainedFragment
}
fragment HouseTrainedFragment {
dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
}
Formal Specification
Explanatory Text
Variables can only be input types. Objects, unions, and interfaces cannot be used as inputs.
For these examples, consider the following typesystem additions:
Example № 155input ComplexInput { name: String, owner: String }
extend type Query {
findDog(complex: ComplexInput): Dog
booleanList(booleanListArg: [Boolean!]): Boolean
}
The following queries are valid:
Example № 156query takesBoolean($atOtherHomes: Boolean) {
dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
}
query takesComplexInput($complexInput: ComplexInput) {
findDog(complex: $complexInput) {
name
}
}
query TakesListOfBooleanBang($booleans: [Boolean!]) {
booleanList(booleanListArg: $booleans)
}
The following queries are invalid:
Counter Example № 157query takesCat($cat: Cat) {
# ...
}
query takesDogBang($dog: Dog!) {
# ...
}
query takesListOfPet($pets: [Pet]) {
# ...
}
query takesCatOrDog($catOrDog: CatOrDog) {
# ...
}
Formal Specification
Explanatory Text
Variables are scoped on a per‐operation basis. That means that any variable used within the context of an operation must be defined at the top level of that operation
For example:
Example № 158query variableIsDefined($atOtherHomes: Boolean) {
dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
}
is valid. $atOtherHomes is defined by the operation.
By contrast the following query is invalid:
Counter Example № 159query variableIsNotDefined {
dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
}
$atOtherHomes is not defined by the operation.
Fragments complicate this rule. Any fragment transitively included by an operation has access to the variables defined by that operation. Fragments can appear within multiple operations and therefore variable usages must correspond to variable definitions in all of those operations.
For example the following is valid:
Example № 160query variableIsDefinedUsedInSingleFragment($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
since isHousetrainedFragment is used within the context of the operation variableIsDefinedUsedInSingleFragment and the variable is defined by that operation.
On the other hand, if a fragment is included within an operation that does not define a referenced variable, the query is invalid.
Counter Example № 161query variableIsNotDefinedUsedInSingleFragment {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
This applies transitively as well, so the following also fails:
Counter Example № 162query variableIsNotDefinedUsedInNestedFragment {
dog {
...outerHousetrainedFragment
}
}
fragment outerHousetrainedFragment on Dog {
...isHousetrainedFragment
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
Variables must be defined in all operations in which a fragment is used.
Example № 163query housetrainedQueryOne($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
query housetrainedQueryTwo($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
However the following does not validate:
Counter Example № 164query housetrainedQueryOne($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
query housetrainedQueryTwoNotDefined {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
This is because housetrainedQueryTwoNotDefined does not define a variable $atOtherHomes but that variable is used by isHousetrainedFragment which is included in that operation.
Formal Specification
Explanatory Text
All variables defined by an operation must be used in that operation or a fragment transitively included by that operation. Unused variables cause a validation error.
For example the following is invalid:
Counter Example № 165query variableUnused($atOtherHomes: Boolean) {
dog {
isHousetrained
}
}
because $atOtherHomes is not referenced.
These rules apply to transitive fragment spreads as well:
Example № 166query variableUsedInFragment($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
The above is valid since $atOtherHomes is used in isHousetrainedFragment which is included by variableUsedInFragment.
If that fragment did not have a reference to $atOtherHomes it would be not valid:
Counter Example № 167query variableNotUsedWithinFragment($atOtherHomes: Boolean) {
dog {
...isHousetrainedWithoutVariableFragment
}
}
fragment isHousetrainedWithoutVariableFragment on Dog {
isHousetrained
}
All operations in a document must use all of their variables.
As a result, the following document does not validate.
Counter Example № 168query queryWithUsedVar($atOtherHomes: Boolean) {
dog {
...isHousetrainedFragment
}
}
query queryWithExtraVar($atOtherHomes: Boolean, $extra: Int) {
dog {
...isHousetrainedFragment
}
}
fragment isHousetrainedFragment on Dog {
isHousetrained(atOtherHomes: $atOtherHomes)
}
This document is not valid because queryWithExtraVar defines an extraneous variable.
Formal Specification
Explanatory Text
Variable usages must be compatible with the arguments they are passed to.
Validation failures occur when variables are used in the context of types that are complete mismatches, or if a nullable type in a variable is passed to a non‐null argument type.
Types must match:
Counter Example № 169query intCannotGoIntoBoolean($intArg: Int) {
arguments {
booleanArgField(booleanArg: $intArg)
}
}
$intArg typed as Int cannot be used as a argument to booleanArg, typed as Boolean.
List cardinality must also be the same. For example, lists cannot be passed into singular values.
Counter Example № 170query booleanListCannotGoIntoBoolean($booleanListArg: [Boolean]) {
arguments {
booleanArgField(booleanArg: $booleanListArg)
}
}
Nullability must also be respected. In general a nullable variable cannot be passed to a non‐null argument.
Counter Example № 171query booleanArgQuery($booleanArg: Boolean) {
arguments {
nonNullBooleanArgField(nonNullBooleanArg: $booleanArg)
}
}
For list types, the same rules around nullability apply to both outer types and inner types. A nullable list cannot be passed to a non‐null list, and a list of nullable values cannot be passed to a list of non‐null values. The following is valid:
Example № 172query nonNullListToList($nonNullBooleanList: [Boolean]!) {
arguments {
booleanListArgField(booleanListArg: $nonNullBooleanList)
}
}
However, a nullable list cannot be passed to a non‐null list:
Counter Example № 173query listToNonNullList($booleanList: [Boolean]) {
arguments {
nonNullBooleanListField(nonNullBooleanListArg: $booleanList)
}
}
This would fail validation because a [T]
cannot be passed to a [T]!
. Similarly a [T]
cannot be passed to a [T!]
.
Allowing optional variables when default values exist
A notable exception to typical variable type compatibility is allowing a variable definition with a nullable type to be provided to a non‐null location as long as either that variable or that location provides a default value.
Example № 174query booleanArgQueryWithDefault($booleanArg: Boolean) {
arguments {
optionalNonNullBooleanArgField(optionalBooleanArg: $booleanArg)
}
}
In the example above, an optional variable is allowed to be used in an non‐null argument which provides a default value.
Example № 175query booleanArgQueryWithDefault($booleanArg: Boolean = true) {
arguments {
nonNullBooleanArgField(nonNullBooleanArg: $booleanArg)
}
}
In the example above, a variable provides a default value and can be used in a non‐null argument. This behavior is explicitly supported for compatibility with earlier editions of this specification. GraphQL authoring tools may wish to report this is a warning with the suggestion to replace Boolean
with Boolean!
.
GraphQL generates a response from a request via execution.
A request for execution consists of a few pieces of information:
Given this information, the result of ExecuteRequest() produces the response, to be formatted according to the Response section below.
To execute a request, the executor must have a parsed Document and a selected operation name to run if the document defines multiple operations, otherwise the document is expected to only contain a single operation. The result of the request is determined by the result of executing this operation according to the “Executing Operations” section below.
As explained in the Validation section, only requests which pass all validation rules should be executed. If validation errors are known, they should be reported in the list of “errors” in the response and the request must fail without execution.
Typically validation is performed in the context of a request immediately before execution, however a GraphQL service may execute a request without immediately validating it if that exact same request is known to have been validated before. A GraphQL service should only execute requests which at some point were known to be free of any validation errors, and have since not changed.
For example: the request may be validated during development, provided it does not later change, or a service may validate a request once and memoize the result to avoid validating the same request again in the future.
If the operation has defined any variables, then the values for those variables need to be coerced using the input coercion rules of variable’s declared type. If a query error is encountered during input coercion of variable values, then the operation fails without execution.
The type system, as described in the “Type System” section of the spec, must provide a query root object type. If mutations or subscriptions are supported, it must also provide a mutation or subscription root object type, respectively.
If the operation is a query, the result of the operation is the result of executing the query’s top level selection set with the query root object type.
An initial value may be provided when executing a query.
If the operation is a mutation, the result of the operation is the result of executing the mutation’s top level selection set on the mutation root object type. This selection set should be executed serially.
It is expected that the top level fields in a mutation operation perform side‐effects on the underlying data system. Serial execution of the provided mutations ensures against race conditions during these side‐effects.
If the operation is a subscription, the result is an event stream called the “Response Stream” where each event in the event stream is the result of executing the operation for each new event on an underlying “Source Stream”.
Executing a subscription creates a persistent function on the server that maps an underlying Source Stream to a returned Response Stream.
As an example, consider a chat application. To subscribe to new messages posted to the chat room, the client sends a request like so:
Example № 176subscription NewMessages {
newMessage(roomId: 123) {
sender
text
}
}
While the client is subscribed, whenever new messages are posted to chat room with ID “123”, the selection for “sender” and “text” will be evaluated and published to the client, for example:
Example № 177{
"data": {
"newMessage": {
"sender": "Hagrid",
"text": "You're a wizard!"
}
}
}
The “new message posted to chat room” could use a “Pub‐Sub” system where the chat room ID is the “topic” and each “publish” contains the sender and text.
Event Streams
An event stream represents a sequence of discrete events over time which can be observed. As an example, a “Pub‐Sub” system may produce an event stream when “subscribing to a topic”, with an event occurring on that event stream for each “publish” to that topic. Event streams may produce an infinite sequence of events or may complete at any point. Event streams may complete in response to an error or simply because no more events will occur. An observer may at any point decide to stop observing an event stream by cancelling it, after which it must receive no more events from that event stream.
Supporting Subscriptions at Scale
Supporting subscriptions is a significant change for any GraphQL service. Query and mutation operations are stateless, allowing scaling via cloning of GraphQL server instances. Subscriptions, by contrast, are stateful and require maintaining the GraphQL document, variables, and other context over the lifetime of the subscription.
Consider the behavior of your system when state is lost due to the failure of a single machine in a service. Durability and availability may be improved by having separate dedicated services for managing subscription state and client connectivity.
Delivery Agnostic
GraphQL subscriptions do not require any specific serialization format or transport mechanism. Subscriptions specifies algorithms for the creation of a stream, the content of each payload on that stream, and the closing of that stream. There are intentionally no specifications for message acknoledgement, buffering, resend requests, or any other quality of service (QoS) details. Message serialization, transport mechanisms, and quality of service details should be chosen by the implementing service.
A Source Stream represents the sequence of events, each of which will trigger a GraphQL execution corresponding to that event. Like field value resolution, the logic to create a Source Stream is application‐specific.
Each event in the underlying Source Stream triggers execution of the subscription selection set using that event as a root value.
Unsubscribe cancels the Response Stream when a client no longer wishes to receive payloads for a subscription. This may in turn also cancel the Source Stream. This is also a good opportunity to clean up any other resources used by the subscription.
To execute a selection set, the object value being evaluated and the object type need to be known, as well as whether it must be executed serially, or may be executed in parallel.
First, the selection set is turned into a grouped field set; then, each represented field in the grouped field set produces an entry into a response map.
Errors and Non‐Null Fields
If during ExecuteSelectionSet() a field with a non‐null fieldType throws a field error then that error must propagate to this entire selection set, either resolving to null if allowed or further propagated to a parent field.
If this occurs, any sibling fields which have not yet executed or have not yet yielded a value may be cancelled to avoid unnecessary work.
See the Errors and Non‐Nullability section of Field Execution for more about this behavior.
Normally the executor can execute the entries in a grouped field set in whatever order it chooses (normally in parallel). Because the resolution of fields other than top‐level mutation fields must always be side effect‐free and idempotent, the execution order must not affect the result, and hence the server has the freedom to execute the field entries in whatever order it deems optimal.
For example, given the following grouped field set to be executed normally:
Example № 178{
birthday {
month
}
address {
street
}
}
A valid GraphQL executor can resolve the four fields in whatever order it chose (however of course birthday
must be resolved before month
, and address
before street
).
When executing a mutation, the selections in the top most selection set will be executed in serial order, starting with the first appearing field textually.
When executing a grouped field set serially, the executor must consider each entry from the grouped field set in the order provided in the grouped field set. It must determine the corresponding entry in the result map for each item to completion before it continues on to the next item in the grouped field set:
For example, given the following selection set to be executed serially:
Example № 179{
changeBirthday(birthday: $newBirthday) {
month
}
changeAddress(address: $newAddress) {
street
}
}
The executor must, in serial:
changeBirthday
, which during CompleteValue() will execute the { month }
sub‐selection set normally.changeAddress
, which during CompleteValue() will execute the { street }
sub‐selection set normally.As an illustrative example, let’s assume we have a mutation field changeTheNumber
that returns an object containing one field, theNumber
. If we execute the following selection set serially:
Example № 180{
first: changeTheNumber(newNumber: 1) {
theNumber
}
second: changeTheNumber(newNumber: 3) {
theNumber
}
third: changeTheNumber(newNumber: 2) {
theNumber
}
}
The executor will execute the following serially:
changeTheNumber(newNumber: 1)
field{ theNumber }
sub‐selection set of first
normallychangeTheNumber(newNumber: 3)
field{ theNumber }
sub‐selection set of second
normallychangeTheNumber(newNumber: 2)
field{ theNumber }
sub‐selection set of third
normallyA correct executor must generate the following result for that selection set:
Example № 181{
"first": {
"theNumber": 1
},
"second": {
"theNumber": 3
},
"third": {
"theNumber": 2
}
}
Before execution, the selection set is converted to a grouped field set by calling CollectFields(). Each entry in the grouped field set is a list of fields that share a response key (the alias if defined, otherwise the field name). This ensures all fields with the same response key included via referenced fragments are executed at the same time.
As an example, collecting the fields of this selection set would collect two instances of the field a
and one of field b
:
Example № 182{
a {
subfield1
}
...ExampleFragment
}
fragment ExampleFragment on Query {
a {
subfield2
}
b
}
The depth‐first‐search order of the field groups produced by CollectFields() is maintained through execution, ensuring that fields appear in the executed response in a stable and predictable order.
@skip
, let skipDirective be that directive.@include
, let includeDirective be that directive.Each field requested in the grouped field set that is defined on the selected objectType will result in an entry in the response map. Field execution first coerces any provided argument values, then resolves a value for the field, and finally completes that value either by recursively executing another selection set or coercing a scalar value.
Fields may include arguments which are provided to the underlying runtime in order to correctly produce a value. These arguments are defined by the field in the type system to have a specific input type.
At each argument position in a query may be a literal Value, or a Variable to be provided at runtime.
While nearly all of GraphQL execution can be described generically, ultimately the internal system exposing the GraphQL interface must provide values. This is exposed via ResolveFieldValue, which produces a value for a given field on a type for a real value.
As an example, this might accept the objectType Person
, the field "soulMate", and the objectValue representing John Lennon. It would be expected to yield the value representing Yoko Ono.
After resolving the value for a field, it is completed by ensuring it adheres to the expected return type. If the return type is another Object type, then the field execution process continues recursively.
Resolving Abstract Types
When completing a field with an abstract return type, that is an Interface or Union return type, first the abstract type must be resolved to a relevant Object type. This determination is made by the internal system using whatever means appropriate.
Merging Selection Sets
When more than one fields of the same name are executed in parallel, their selection sets are merged together when completing the value in order to continue execution of the sub‐selection sets.
An example query illustrating parallel fields with the same name with sub‐selections.
Example № 183{
me {
firstName
}
me {
lastName
}
}
After resolving the value for me
, the selection sets are merged together so firstName
and lastName
can be resolved for one value.
If an error is thrown while resolving a field, it should be treated as though the field returned null, and an error must be added to the "errors" list in the response.
If the result of resolving a field is null (either because the function to resolve the field returned null or because an error occurred), and that field is of a Non-Null
type, then a field error is thrown. The error must be added to the "errors" list in the response.
If the field returns null because of an error which has already been added to the "errors" list in the response, the "errors" list must not be further affected. That is, only one error should be added to the errors list per field.
Since Non-Null
type fields cannot be null, field errors are propagated to be handled by the parent field. If the parent field may be null then it resolves to null, otherwise if it is a Non-Null
type, the field error is further propagated to it’s parent field.
If a List
type wraps a Non-Null
type, and one of the elements of that list resolves to null, then the entire list must resolve to null. If the List
type is also wrapped in a Non-Null
, the field error continues to propagate upwards.
If all fields from the root of the request to the source of the field error return Non-Null
types, then the "data" entry in the response should be null.
When a GraphQL server receives a request, it must return a well‐formed response. The server’s response describes the result of executing the requested operation if successful, and describes any errors encountered during the request.
A response may contain both a partial response as well as encountered errors in the case that a field error occurred on a field which was replaced with null.
A response to a GraphQL operation must be a map.
If the operation encountered any errors, the response map must contain an entry with key errors
. The value of this entry is described in the “Errors” section. If the operation completed without encountering any errors, this entry must not be present.
If the operation included execution, the response map must contain an entry with key data
. The value of this entry is described in the “Data” section. If the operation failed before execution, due to a syntax error, missing information, or validation error, this entry must not be present.
The response map may also contain an entry with key extensions
. This entry, if set, must have a map as its value. This entry is reserved for implementors to extend the protocol however they see fit, and hence there are no additional restrictions on its contents.
To ensure future changes to the protocol do not break existing servers and clients, the top level response map must not contain any entries other than the three described above.
errors
is present in the response, it may be helpful for it to appear first when serialized to make it more clear when errors are present in a response during debugging.The data
entry in the response will be the result of the execution of the requested operation. If the operation was a query, this output will be an object of the schema’s query root type; if the operation was a mutation, this output will be an object of the schema’s mutation root type.
If an error was encountered before execution begins, the data
entry should not be present in the result.
If an error was encountered during the execution that prevented a valid response, the data
entry in the response should be null
.
The errors
entry in the response is a non‐empty list of errors, where each error is a map.
If no errors were encountered during the requested operation, the errors
entry should not be present in the result.
If the data
entry in the response is not present, the errors
entry in the response must not be empty. It must contain at least one error. The errors it contains should indicate why no data was able to be returned.
If the data
entry in the response is present (including if it is the value null), the errors
entry in the response may contain any errors that occurred during execution. If errors occurred during execution, it should contain those errors.
Error result format
Every error must contain an entry with the key message
with a string description of the error intended for the developer as a guide to understand and correct the error.
If an error can be associated to a particular point in the requested GraphQL document, it should contain an entry with the key locations
with a list of locations, where each location is a map with the keys line
and column
, both positive numbers starting from 1
which describe the beginning of an associated syntax element.
If an error can be associated to a particular field in the GraphQL result, it must contain an entry with the key path
that details the path of the response field which experienced the error. This allows clients to identify whether a null
result is intentional or caused by a runtime error.
This field should be a list of path segments starting at the root of the response and ending with the field associated with the error. Path segments that represent fields should be strings, and path segments that represent list indices should be 0‐indexed integers. If the error happens in an aliased field, the path to the error should use the aliased name, since it represents a path in the response, not in the query.
For example, if fetching one of the friends’ names fails in the following query:
Example № 184{
hero(episode: $episode) {
name
heroFriends: friends {
id
name
}
}
}
The response might look like:
Example № 185{
"errors": [
{
"message": "Name for character with ID 1002 could not be fetched.",
"locations": [ { "line": 6, "column": 7 } ],
"path": [ "hero", "heroFriends", 1, "name" ]
}
],
"data": {
"hero": {
"name": "R2-D2",
"heroFriends": [
{
"id": "1000",
"name": "Luke Skywalker"
},
{
"id": "1002",
"name": null
},
{
"id": "1003",
"name": "Leia Organa"
}
]
}
}
}
If the field which experienced an error was declared as Non-Null
, the null
result will bubble up to the next nullable field. In that case, the path
for the error should include the full path to the result field where the error occurred, even if that field is not present in the response.
For example, if the name
field from above had declared a Non-Null
return type in the schema, the result would look different but the error reported would be the same:
Example № 186{
"errors": [
{
"message": "Name for character with ID 1002 could not be fetched.",
"locations": [ { "line": 6, "column": 7 } ],
"path": [ "hero", "heroFriends", 1, "name" ]
}
],
"data": {
"hero": {
"name": "R2-D2",
"heroFriends": [
{
"id": "1000",
"name": "Luke Skywalker"
},
null,
{
"id": "1003",
"name": "Leia Organa"
}
]
}
}
}
GraphQL services may provide an additional entry to errors with key extensions
. This entry, if set, must have a map as its value. This entry is reserved for implementors to add additional information to errors however they see fit, and there are no additional restrictions on its contents.
Example № 187{
"errors": [
{
"message": "Name for character with ID 1002 could not be fetched.",
"locations": [ { "line": 6, "column": 7 } ],
"path": [ "hero", "heroFriends", 1, "name" ],
"extensions": {
"code": "CAN_NOT_FETCH_BY_ID",
"timestamp": "Fri Feb 9 14:33:09 UTC 2018"
}
}
]
}
GraphQL services should not provide any additional entries to the error format since they could conflict with additional entries that may be added in future versions of this specification.
extensions
entry for error formatting. While non‐specified entries are not violations, they are still discouraged.Counter Example № 188{
"errors": [
{
"message": "Name for character with ID 1002 could not be fetched.",
"locations": [ { "line": 6, "column": 7 } ],
"path": [ "hero", "heroFriends", 1, "name" ],
"code": "CAN_NOT_FETCH_BY_ID",
"timestamp": "Fri Feb 9 14:33:09 UTC 2018"
}
]
}
GraphQL does not require a specific serialization format. However, clients should use a serialization format that supports the major primitives in the GraphQL response. In particular, the serialization format must at least support representations of the following four primitives:
A serialization format should also support the following primitives, each representing one of the common GraphQL scalar types, however a string or simpler primitive may be used as a substitute if any are not directly supported:
This is not meant to be an exhaustive list of what a serialization format may encode. For example custom scalars representing a Date, Time, URI, or number with a different precision may be represented in whichever relevant format a given serialization format may support.
JSON is the most common serialization format for GraphQL. Though as mentioned above, GraphQL does not require a specific serialization format.
When using JSON as a serialization of GraphQL responses, the following JSON values should be used to encode the related GraphQL values:
GraphQL Value | JSON Value |
---|---|
Map | Object |
List | Array |
Null | null |
String | String |
Boolean | true or false |
Int | Number |
Float | Number |
Enum Value | String |
Since the result of evaluating a selection set is ordered, the serialized Map of results should preserve this order by writing the map entries in the same order as those fields were requested as defined by query execution. Producing a serialized response where fields are represented in the same order in which they appear in the request improves human readability during debugging and enables more efficient parsing of responses if the order of properties can be anticipated.
Serialization formats which represent an ordered map should preserve the order of requested fields as defined by CollectFields() in the Execution section. Serialization formats which only represent unordered maps but where order is still implicit in the serialization’s textual order (such as JSON) should preserve the order of requested fields textually.
For example, if the request was { name, age }
, a GraphQL service responding in JSON should respond with { "name": "Mark", "age": 30 }
and should not respond with { "age": 30, "name": "Mark" }
.
While JSON Objects are specified as an unordered collection of key‐value pairs the pairs are represented in an ordered manner. In other words, while the JSON strings { "name": "Mark", "age": 30 }
and { "age": 30, "name": "Mark" }
encode the same value, they also have observably different property orderings.
This specification document contains a number of notation conventions used to describe technical concepts such as language grammar and semantics as well as runtime algorithms.
This appendix seeks to explain these notations in greater detail to avoid ambiguity.
A context‐free grammar consists of a number of productions. Each production has an abstract symbol called a “non‐terminal” as its left‐hand side, and zero or more possible sequences of non‐terminal symbols and or terminal characters as its right‐hand side.
Starting from a single goal non‐terminal symbol, a context‐free grammar describes a language: the set of possible sequences of characters that can be described by repeatedly replacing any non‐terminal in the goal sequence with one of the sequences it is defined by, until all non‐terminal symbols have been replaced by terminal characters.
Terminals are represented in this document in a monospace font in two forms: a specific Unicode character or sequence of Unicode characters (ex. = or terminal), and a pattern of Unicode characters defined by a regular expression (ex /[0-9]+/).
Non‐terminal production rules are represented in this document using the following notation for a non‐terminal with a single definition:
While using the following notation for a production with a list of definitions:
A definition may refer to itself, which describes repetitive sequences, for example:
The GraphQL language is defined in a syntactic grammar where terminal symbols are tokens. Tokens are defined in a lexical grammar which matches patterns of source characters. The result of parsing a sequence of source Unicode characters produces a GraphQL AST.
A Lexical grammar production describes non‐terminal “tokens” by patterns of terminal Unicode characters. No “whitespace” or other ignored characters may appear between any terminal Unicode characters in the lexical grammar production. A lexical grammar production is distinguished by a two colon ::
definition.
A Syntactical grammar production describes non‐terminal “rules” by patterns of terminal Tokens. Whitespace and other ignored characters may appear before or after any terminal Token. A syntactical grammar production is distinguished by a one colon :
definition.
This specification uses some additional notation to describe common patterns, such as optional or repeated patterns, or parameterized alterations of the definition of a non‐terminal. This section explains these short‐hand notations and their expanded definitions in the context‐free grammar.
Constraints
A grammar production may specify that certain expansions are not permitted by using the phrase “but not” and then indicating the expansions to be excluded.
For example, the production:
means that the nonterminal SafeName may be replaced by any sequence of characters that could replace Name provided that the same sequence of characters could not replace SevenCarlinWords.
A grammar may also list a number of restrictions after “but not” separated by “or”.
For example:
Optionality and Lists
A subscript suffix “Symbolopt” is shorthand for two possible sequences, one including that symbol and one excluding it.
As an example:
is shorthand for
A subscript suffix “Symbollist” is shorthand for a list of one or more of that symbol.
As an example:
is shorthand for
Parameterized Grammar Productions
A symbol definition subscript suffix parameter in braces “SymbolParam” is shorthand for two symbol definitions, one appended with that parameter name, the other without. The same subscript suffix on a symbol is shorthand for that variant of the definition. If the parameter starts with “?”, that form of the symbol is used if in a symbol definition with the same parameter. Some possible sequences can be included or excluded conditionally when respectively prefixed with “[+Param]” and “[~Param]”.
As an example:
is shorthand for
This specification describes the semantic value of many grammar productions in the form of a list of algorithmic steps.
For example, this describes how a parser should interpret a string literal:
This specification describes some algorithms used by the static and runtime semantics, they’re defined in the form of a function‐like syntax with the algorithm’s name and the arguments it accepts along with a list of algorithmic steps to take in the order listed. Each step may establish references to other values, check various conditions, call other algorithms, and eventually return a value representing the outcome of the algorithm for the provided arguments.
For example, the following example describes an algorithm named Fibonacci which accepts a single argument number. The algoritm’s steps produce the next number in the Fibonacci sequence:
! | $ | ( | ) | ... | : | = | @ | [ | ] | { | | | } |
0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
+ | - |
" | \ | / | b | f | n | r | t |
query | mutation | subscription |
true | false |
QUERY |
MUTATION |
SUBSCRIPTION |
FIELD |
FRAGMENT_DEFINITION |
FRAGMENT_SPREAD |
INLINE_FRAGMENT |
SCHEMA |
SCALAR |
OBJECT |
FIELD_DEFINITION |
ARGUMENT_DEFINITION |
INTERFACE |
UNION |
ENUM |
ENUM_VALUE |
INPUT_OBJECT |
INPUT_FIELD_DEFINITION |