JSON.swift

A production-quality Swift JSON library with type-safe schema definition, macro-driven conformance synthesis, rich validation, and schema inference.

Requirements

• Swift 5.9+
• macOS 12+ · iOS 15+ · watchOS 8+ · tvOS 15+ · visionOS 1+

Installation

Add the package to your Package.swift:

dependencies: [
    .package(url: "https://github.com/reidchatham/JSON.swift", from: "1.0.0"),
],
targets: [
    .target(name: "MyTarget", dependencies: [
        .product(name: "JSON", package: "JSON.swift"),
    ]),
]

---

Quick Start

Parsing and reading

import JSON

// Parse from a string
let json = try JSON(string: #"{"name":"Alice","age":30,"active":true}"#)

// Dynamic member lookup
print(json.name?.stringValue)   // Optional("Alice")

// Subscript
print(json["age"]?.intValue)    // Optional(30)

// Dot-path key-path subscript
let city = json[keyPath: "address.city"]  // → nil if missing

// Throwing access
let name = try json.value(forKey: "name") // throws JSONError.keyNotFound if missing

Constructing JSON

// From literals
let json: JSON = [
    "name":   "Bob",
    "scores": [98, 85, 91],
    "active": true,
]

// From any Encodable value
struct Point: Encodable { let x: Double; let y: Double }
let json = try JSON(encoding: Point(x: 1, y: 2))
// → .object(["x": .number(1.0), "y": .number(2.0)])

// From JSONSerialization-style Any
let dict: [String: Any] = ["count": 3, "flag": true]
let json = try JSON(dict)

Serialization

// Pretty-printed string (default)
let pretty = json.jsonString

// Custom formatting
let compact = json.jsonString(formatting: [])          // no whitespace
let sorted  = json.jsonString(formatting: .sortedKeys) // sorted, no indent

// Raw Data (avoids String intermediate)
let data = json.jsonData   // Data?

Mutating

var json: JSON = ["role": "user"]

// Subscript write
json["role"] = "admin"

// Key-path write (creates nested objects as needed)
json[keyPath: "settings.theme"] = "dark"

// Merge two objects (patch wins on conflict)
let base: JSON  = ["name": "Alice", "role": "user"]
let patch: JSON = ["role": "admin", "active": true]
let merged = base.merging(patch)
// → ["name": "Alice", "role": "admin", "active": true]

Iteration

let json: JSON = [1, 2, 3]

// JSON conforms to Sequence — iterate arrays directly
for item in json {
    print(item.intValue ?? 0)
}

// Or use Array/map/filter/etc.
let doubles = json.compactMap(\.doubleValue)

---

JSONSchema

Define the shape of JSON values for validation, LLM structured output, and documentation.

Factory methods

// Primitives
JSONSchema.string()
JSONSchema.string(description: "User's name", minLength: 1, maxLength: 100)
JSONSchema.string(enumValues: ["admin", "user", "guest"])
JSONSchema.string(pattern: "^[A-Z][a-z]+$")

JSONSchema.number(minimum: 0, maximum: 1)
JSONSchema.integer(minimum: 1, exclusiveMaximum: 100)
JSONSchema.boolean()
JSONSchema.null()

// Array
JSONSchema.array(items: .string(), minItems: 1, maxItems: 10, uniqueItems: true)

// Object
JSONSchema.object(
    properties: [
        "name":  .string(description: "Full name"),
        "age":   .integer(minimum: 0),
        "email": .string().nullable,   // nullable shorthand
    ],
    required: ["name", "age"],
    additionalProperties: false
)

// Composition
JSONSchema.anyOf([.string(), .null()])   // or: .string().nullable
JSONSchema.oneOf([.string(), .integer()])
JSONSchema.allOf([schemaA, schemaB])

Three ways to build object schemas

Option A — Direct factory (concise for simple schemas):

let schema = JSONSchema.object(
    properties: ["name": .string(), "age": .integer()],
    required: ["name", "age"]
)

Option B — @resultBuilder DSL (declarative, SwiftUI-style):

let schema = JSONSchema.build(title: "Person") {
    JSONSchemaProperty.string("name", description: "Full name")
    JSONSchemaProperty.integer("age", minimum: 0)
    JSONSchemaProperty.string("email", required: false, minLength: 5)
}

Option C — FluentSchemaBuilder (true method chaining):

let schema = FluentSchemaBuilder()
    .string("name", description: "Full name")
    .integer("age", minimum: 0)
    .string("email", required: false)
    .array("tags", items: .string(), minItems: 1)
    .build(title: "Person")

Option D — SchemaBuilder struct (imperative):

var builder = SchemaBuilder()
builder.string("name")
builder.integer("age")
let schema = builder.build(title: "Person")

---

Validation

let schema = JSONSchema.object(
    properties: ["score": .number(minimum: 0, maximum: 100)],
    required: ["score"],
    additionalProperties: false
)

let valid: JSON   = ["score": 85]
let invalid: JSON = ["score": 150, "extra": "field"]

// Bool check
valid.isValid(against: schema)    // true
invalid.isValid(against: schema)  // false

// Collect all errors
let result = invalid.validationResult(against: schema)
for error in result.errors {
    print("\(error.path): \(error.reason)")
    // root: value 150.0 is greater than maximum 100.0
    // root: additional property 'extra' is not allowed
}

// Throw on first error
try valid.validate(against: schema)   // no throw
try invalid.validate(against: schema) // throws ValidationError

// Schema-side equivalents
try schema.validate(invalid)
schema.isValid(valid)
schema.validationResult(for: invalid)

Supported constraints

Category	Keywords
Type	type (string/number/integer/boolean/null/array/object)
String	minLength, maxLength, pattern, enum
Number	minimum, maximum, exclusiveMinimum, exclusiveMaximum
Array	items, minItems, maxItems, uniqueItems
Object	properties, required, additionalProperties
Composition	anyOf, oneOf, allOf

---

JSONConvertible Protocol

Types that describe their own schema conform to JSONConvertible:

struct WeatherCard: JSONConvertible {
    let location: String
    let temperature: Double
    let conditions: String?

    static var jsonSchema: JSONSchema {
        .object(
            properties: [
                "location":    .string(description: "City name"),
                "temperature": .number(description: "Degrees Celsius"),
                "conditions":  .string(description: "Weather conditions"),
            ],
            required: ["location", "temperature"],
            additionalProperties: false
        )
    }
}

// Decode from string or data
let card = try WeatherCard.decode(from: jsonString)
let card = try WeatherCard.decode(from: data)

// Get schema
let schema = WeatherCard.jsonSchema
let schema = JSONSchema.from(WeatherCard.self)

---

@JSONSchema Macro

Automatically synthesize JSONConvertible conformance from stored properties:

@JSONSchema
struct Person: Codable {
    let name: String
    let age: Int
    let email: String?       // optional → excluded from required[]

    enum Status: String, Codable { case active, inactive }
    let status: Status       // → .string(enumValues: ["active", "inactive"])
}

// The macro generates:
extension Person: JSONConvertible {
    public static var jsonSchema: JSONSchema {
        .object(
            properties: [
                "name":   .string(),
                "age":    .integer(),
                "email":  .string(),
                "status": .string(enumValues: ["active", "inactive"]),
            ],
            required: ["name", "age", "status"],
            additionalProperties: false
        )
    }
}

Type mapping table

Swift Type	JSON Schema
String	.string()
Int, Int8 … Int64, UInt …	.integer()
Double, Float, CGFloat, Decimal	.number()
Bool	.boolean()
Date	.string(description: "ISO 8601 date-time")
URL	.string(description: "URL")
UUID	.string(description: "UUID")
[Element]	.array(items: <element schema>)
[String: Value]	.object(additionalProperties: true)
T? / Optional<T>	Same schema as T, excluded from required
enum Foo: String (nested)	.string(enumValues: [...])
Any other named type	.from(TypeName.self)

The macro respects CodingKeys — encoded string keys are used as JSON property names:

@JSONSchema
struct ApiResponse: Codable {
    let userId: Int
    let createdAt: Date

    enum CodingKeys: String, CodingKey {
        case userId    = "user_id"
        case createdAt = "created_at"
    }
}
// → properties: ["user_id": .integer(), "created_at": .string(description: "ISO 8601 date-time")]

The macro must be applied to a struct. Applying it to a class, enum, or actor produces a compile-time error.

---

Schema Inference

Derive a schema from any existing JSON value:

let json: JSON = ["name": "Alice", "age": 30, "scores": [98, 85]]
let schema = json.inferredSchema()
// → .object(
//       properties: [
//           "name":   .string(),
//           "age":    .integer(),
//           "scores": .array(items: .integer())
//       ],
//       required: ["age", "name", "scores"]
//   )

// The source value always passes the schema it produced
json.isValid(against: schema) // true

// Static convenience
let schema = JSONSchema.infer(from: json)

---

API Summary

JSON

API	Description
init(string:)	Parse from a JSON string
init(data:)	Decode from raw Data
init(_ value: Any)	Bridge from JSONSerialization-style Any
init(encoding:)	Encode any Encodable to JSON
jsonString	Pretty-printed, sorted-keys string
jsonString(formatting:)	String with custom output formatting
jsonData	Raw UTF-8 Data (no String intermediate)
stringValue / doubleValue / intValue / boolValue	Type-safe optional accessors
truncatedIntValue	Integer value, truncating fractional part
arrayValue / objectValue	Collection accessors
isNull	true when .null
json["key"]	Object subscript (read/write)
json[0]	Array subscript (read/write)
json[keyPath: "a.b.c"]	Dot-path subscript (read/write)
json.name	@dynamicMemberLookup shorthand
value(forKey:)	Throwing object key access
value(at:)	Throwing array index access
for item in json	Sequence iteration (arrays)
merging(_:) / merge(_:)	Merge two object nodes
jsonCompatible	Convert to JSONSerialization-compatible Any
inferredSchema()	Derive a JSONSchema from this value
validate(against:)	Throw on first schema violation
isValid(against:)	Bool — passes all constraints?
validationResult(against:)	All violations collected

JSONSchema

API	Description
.string(description:enumValues:minLength:maxLength:pattern:)	String schema
.number(description:minimum:maximum:exclusiveMinimum:exclusiveMaximum:)	Float schema
.integer(description:minimum:maximum:…)	Integer schema
.boolean() / .null()	Boolean / null schemas
.array(items:description:minItems:maxItems:uniqueItems:)	Array schema
.object(properties:required:additionalProperties:description:title:)	Object schema
.anyOf(_:) / .oneOf(_:) / .allOf(_:)	Composition
.nullable	Shorthand for anyOf([self, .null()])
.from(T.self)	Schema from any JSONConvertible type
.build(title:description:) { ... }	@resultBuilder DSL
.infer(from:)	Derive schema from a JSON value
validate(_:) / isValid(_:) / validationResult(for:)	Validation
Hashable, Equatable, Codable, CustomStringConvertible	Full protocol suite

---

License

MIT