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Ontology buildingFunctionsTypes reference

Types reference

In order to be published to the registry, a TypeScript function must have explicit type annotations on all input parameters and specify an explicit return type. Below is the full list of currently supported function registry types and their corresponding language types.

Function registry type	TypeScript v1 type	TypeScript v2 type	Python type
Attachment	`Attachment`	`Attachment`	`Attachment`	Example
Boolean	`boolean`	`boolean`	`bool`	Example
Binary	Not supported	Not supported	`bytes`	Example
Byte	Not supported	Not supported	`int*`	Example
Date	`LocalDate`	`DateISOString`	`datetime.date`	Example
Decimal	Not supported	Not supported	`decimal.Decimal`	Example
Double	`Double`	`Double`	`float*`	Example
Float	`Float`	`Float`	`float`	Example
Group	`Group`	Not supported	Not supported	Example
Integer	`Integer`	`Integer`	`int`	Example
List	`T[]` or `Array<T>`	`T[]` or `Array<T>`	`list[T]`	Example
Long	`Long`	`Long`	`int*`	Example
Map	`FunctionsMap<K, V>`	`Record<K, V>`	`dict[K, V]`	Example
Media reference	`MediaItem`	Not supported	Not supported	Example
Notification	`Notification`	Not supported	Not supported	Example
Object	`MyObjectType`	`Osdk.Instance<MyObjectType>`	`MyObjectType`	Example
Object set	`ObjectSet<MyObjectType>`	`ObjectSet<MyObjectType>`	`MyObjectTypeObjectSet`	Example
Ontology edit	`void`	`Edits`	`OntologyEdit`	Example
Optional	`T \| undefined`	`T \| undefined`	`typing.Optional` or `T \| None`	Example
Principal	`Principal`	Not supported	Not supported	Example
Range	`IRange<T>`	`Range<T>`	`Range[T]`	Example
Set	`Set<T>`	Not supported	`set[T]`	Example
Short	Not supported	Not supported	`int*`	Example
String	`string`	`string`	`str`	Example
Struct/custom type	`interface`	`interface`	`dataclasses.dataclass`	Example
Timestamp	`Timestamp`	`TimestampISOString`	`datetime.datetime`	Example
Two-dimensional aggregation	`TwoDimensionalAggregation<K, V>`	`TwoDimensionalAggregation<K, V>`	`TwoDimensionalAggregation[K, V]`	Example
Three-dimensional aggregation	`ThreeDimensionalAggregation<K, S, V>`	`ThreeDimensionalAggregation<K, S, V>`	`ThreeDimensionalAggregation[K, S, V]`	Example
User	`User`	Not supported	Not supported	Example

Although both Integer and Long correspond to the Python type int, any fields marked as int directly in your function signature will be registered with type Integer. Therefore, we instead recommend using either the Integer or Long types from the API to register numerical data types. Similar guidelines apply to Float and Double; if the Python type float is directly in your function signature, it will be registered as Float by default.

Scalar types

Scalar types represent a single value and are commonly used to hold textual, numeric, or temporal data.

In JavaScript and TypeScript, there is one number type that is commonly used to represent both integer and floating-point values. In order to provide further type validation and structure, we only support the numeric aliases exported from the @foundry/functions-api package for TypeScript v1 functions and the @osdk/functions package for TypeScript v2 functions. Similarly, when working with numeric types in Python functions we recommend using the type aliases exported from the functions.api module.

Boolean

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import { Function, Integer } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public isEven(num: Integer): boolean {
        return num % 2 === 0;
    }
}

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import { Integer } from "@osdk/functions";

function isEven(num: Integer): boolean {
    return num % 2 === 0;
}

export default isEven;

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from functions.api import function, Integer

@function
def is_even(num: Integer) -> bool:
    return n % 2 == 0

String

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import { Function } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public greet(name: string): string {
        return `Hello, ${name}!`;
    }
}

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function greet(name: string): string {
    return `Hello, ${name}!`;
}

export default greet;

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from functions.api import function

@function
def greet(name: str) -> str:
    return f"Hello, {name}!"

Short

Represents integer values from -32,768 to 32,767.

In Python functions, the Short type is an alias for the built-in int type.

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from functions.api import function, Short

@function
def increment(num: Short) -> Short:
    return num + 1

Integer

Represents integer values from (-2³¹) to (2³¹ - 1).

In both TypeScript v1 and v2 functions, the Integer type is an alias for the built-in number type.
In Python functions, the Integer type is an alias for the built-in int type.

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import { Function, Integer } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public sum(a: Integer, b: Integer): Integer {
        return a + b;
    }
}

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import { Integer } from "@osdk/functions";

function sum(a: Integer, b: Integer): Integer {
    return a + b;
}

export default sum;

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from functions.api import function, Integer

@function
def sum(a: Integer, b: Integer) -> Integer:
    return a + b

Long

Represents integer values from -(2⁵³ - 1) to (2⁵³ - 1). These bounds are equivalent to Number.MIN_SAFE_INTEGER and Number.MAX_SAFE_INTEGER in JavaScript to prevent precision loss when functions are called from browser contexts.

In TypeScript v1 functions, the Long type is an alias for the built-in number type. In TypeScript v2 functions, the Long type is an alias for the built-in string type.
In Python functions, the Long type is an alias for the built-in int type.

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import { Function, Long } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public subtract(a: Long, b: Long): string {
        return (BigInt(a) - BigInt(b)).toString();
    }
}

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import { Long } from "@osdk/functions";

function subtract(a: Long, b: Long): string {
    return (BigInt(a) - BigInt(b)).toString();
}

export default subtract;

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from functions.api import function, Long

@function
def subtract(a: Long, b: Long) -> str:
    return str(a - b)

Float

Represents a 32-bit floating-point number.

In both TypeScript v1 and v2 functions, the Float type is an alias for the built-in number type.
In Python functions, the Float type is an alias for the built-in float type.

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import { Float, Function } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public multiply(a: Float, b: Float): Float {
        return a * b;
    }
}

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import { Float } from "@osdk/functions";

function multiply(a: Float, b: Float): Float {
    return a * b;
}

export default multiply;

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from functions.api import function, Float

@function
def multiply(a: Float, b: Float) -> Float:
    return a * b

Double

Represents a 64-bit floating-point number.

In both TypeScript v1 and v2 functions, the Double type is an alias for the built-in number type.
In Python functions, the Double type is an alias for the built-in float type.

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import { Double, Function } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public divide(a: Double, b: Double): Double {
        return a / b;
    }
}

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import { Double } from "@osdk/functions";

function divide(a: Double, b: Double): Double {
    return a / b;
}

export default divide;

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from functions.api import function, Double

@function
def divide(a: Double, b: Double) -> Double:
    return a / b

Decimal

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from decimal import Decimal
from functions.api import function

@function
def return_pi() -> Decimal:
    return Decimal('3.1415926535')

Date

Represents a calendar date.

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import { Function, LocalDate } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public returnDate(): LocalDate {
        return LocalDate.fromISOString("1999-10-17");
    }
}

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import { DateISOString } from "@osdk/functions";

function returnDate(): DateISOString {
    return "1999-10-17";
}

export default returnDate;

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from datetime import date
from functions.api imports function, Date

@function
def return_date() -> Date:
    return date.fromisoformat('1999-10-17')

Timestamp

Represents an instant in time.

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import { Function, Timestamp } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getCurrentTimestamp(): Timestamp {
        return Timestamp.now();
    }
}

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import { TimestampISOString } from "@osdk/functions";

function getCurrentTimestamp(): TimestampISOString {
    const now = new Date();
    return now.toISOString();
}

export default getCurrentTimestamp;

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from datetime import datetime
from functions.api import function, Timestamp

@function
def get_current_timestamp() -> Timestamp:
    return datetime.now()

Binary

In Python functions, the Binary type is an alias for the built-in bytes type.

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from functions.api import function

@function
def encode_utf8(param: str) -> bytes:
    return param.encode('utf-8')

Byte

In Python functions, the Byte type is an alias for the built-in int type.

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from functions.api import function, Byte

@function
def get_first_byte(param: str) -> Byte:
    if len(param) == 0:
        raise Exception("String length cannot be zero.")
    return param.encode('utf-8')[0]

Collection types

Collection types are parameterized by other types. For example, Array[String] is a list of strings and Map[String, Integer] is a dictionary with string keys and integer values. The parameterized types must be specified, and the type must be another supported type. Map keys can only be scalar types or an Ontology object type.

List

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import { Function, Integer } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public filterForEvenIntegers(nums: Integer[]): Integer[] {
        return nums.filter(num => num % 2 === 0);
    }
}

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import { Integer } from "@osdk/functions";

function filterForEvenIntegers(nums: Integer[]): Integer[] {
    return nums.filter(num => num % 2 === 0);
}

export default filterForEvenIntegers;

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from functions.api import function, Integer

@function
def filter_for_even_integers(nums: list[Integer]) -> list[Integer]:
    return [n for n in nums if n % 2 == 0]

Map

Maps are commonly used to key by a scalar type and access an associated value that can be of any other function registry type.

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import { Function, FunctionsMap } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getMap(): FunctionsMap<string, string> {
        const myMap = new FunctionsMap<string, string>();

        myMap.set("Name", "Phil");
        myMap.set("Favorite Color", "Blue");

        return myMap;
    }
}

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function getMap(): Record<string, string> {
    const myMap: Record<string, string> = {};

    myMap["Name"] = "Phil";
    myMap["Favorite Color"] = "Blue";

    return myMap;
}

export default getMap;

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from functions.api import function

@function
def get_map() -> dict[str, str]:
    my_map = {}

    my_map["Name"] = "Phil"
    my_map["Favorite Color"] = "Blue"

    return my_map

Additionally, maps support Ontology objects as keys.

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import { Function, FunctionsMap } from "@foundry/functions-api";
import { Airplane } from "@foundry/ontology-api";

export class MyFunctions {
    @Function()
    public getObjectMap(aircraft: Airplane[]): FunctionsMap<Airplane, Integer | undefined> {
        const myMap = new FunctionsMap<Airplane, Integer | undefined>();

        aircraft.forEach(obj => {
            myMap.set(obj, obj.capacity);
        });

        return myMap;
    }
}

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import { ObjectSpecifier, Osdk } from "@osdk/client";
import { Integer } from "@osdk/functions";
import { Airplane } from "@ontology/sdk";

function getObjectMap(aircraft: Osdk.Instance<Airplane>[]): Record<ObjectSpecifier<Airplane>, Integer | undefined> {
    const myMap: Record<ObjectSpecifier<Airplane>, Integer | undefined> = {};
    
    aircraft.forEach(obj => {
        myMap[obj.$objectSpecifier] = obj.capacity;
    });
    
    return myMap;
}

export default getObjectMap;

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from functions.api import function, Integer
from ontology_sdk.ontology.objects import Airplane

@function
def get_object_map(aircraft: list[Airplane]) -> dict[Airplane, Integer | None]:
    my_map = {}

    for a in aircraft:
        my_map[a] = a.capacity

    return my_map

Set

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import { Function, Integer } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getSizeOfSet(mySet: Set<Integer>): Integer {
        return mySet.size;
    }
}

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from functions.api import function, Integer

@function
def get_size_of_set(my_set: set[Integer]) -> Integer:
    return len(my_set)

Optional

In TypeScript functions, optional parameters are declared as varName?: T or varName: T | undefined. For example, a function that has an optional integer parameter named value could be declared as either value?: Integer or value: Integer | undefined. TypeScript functions can also declare an optional return type by specifying a type of T | undefined. For example, a function that may return either an Integer or no value would have a return type of Integer | undefined.
In Python functions, optional parameters and return values can be declared using typing.Optional[T] or T | None. The T | None syntax requires Python 3.10 or greater.
In both TypeScript and Python functions, the parameterized type T must be specified, and it must be another supported type.

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import { Function } from "@foundry/functions-api";

export class MyFunction {
    @Function()
    public greet(name?: string): string | undefined {
        if (name === undefined) {
            return undefined;
        }
        return `Hello, ${name}!`;
    }
}

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function greet(name?: string): string | undefined {
    if (name === undefined) {
        return undefined;
    }
    return `Hello, ${name}!`;
}

export default greet;

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from functions.api import function

@function
def greet(name: str | None) -> str | None:
    if name is None:
        return None
    return f"Hello, {name}!"

Functions also support default values in the function signature.

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import { Double, Function } from "@foundry/functions-api";
import { Customer } from "@foundry/ontology-api";

export class MyFunctions {
    @Function()
    public computeRiskFactor(customer: Customer, weight: Double = 0.75): Double {
        // ...
    }
}

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import { Double } from "@osdk/functions";
import { Osdk } from "@osdk/client";
import { Customer } from "@ontology/sdk";

function computeRiskFactor(customer: Osdk.Instance<Customer>, weight: Double = 0.75): Double {
    // ...
}

export default computeRiskFactor;

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from functions.api import function, Double
from ontology_sdk.ontology.objects import Customer

@function
def compute_risk_factor(customer: Customer, weight: Double = 0.75) -> Double:
    # ...

Struct/custom type

Custom types are composed of other supported types (including other custom types) and can be used in function signatures.

In TypeScript functions, custom types are user-defined TypeScript interfaces using the interface keyword.
- Optional fields are supported through either the ? optional token or a union with undefined.
In Python functions, custom types are user-defined Python classes.
- To be a valid custom type, the class must adhere to the following:
  - The class must have type annotations on all of its fields.
  - The field types must be supported types; either the primitive API types or native Python types (as defined in the table above) may be used.
  - The __init__ method must accept only named arguments with the same names and type annotations as the fields.
- The dataclasses.dataclass ↗ decorator can be used to automatically generate an __init__ method that conforms with these requirements.

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import { Function, Integer } from "@foundry/functions-api";
import { Passenger } from "@foundry/ontology-api";

export class MyFunctions {
    @Function()
    public getPassengerInfo(passenger: Passenger): PassengerInfo {
        return {
            name: passenger.name,
            age: passenger.age,
        };
    }
}

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import { Osdk } from "@osdk/client";
import { Integer } from "@osdk/functions";
import { Passenger } from "@ontology/sdk";

interface PassengerInfo {
    name?: string;
    age?: Integer;
}

function getPassengerInfo(passenger: Osdk.Instance<Passenger>): PassengerInfo {
    return {
        name: passenger.name,
        age: passenger.age,
    };
}

export default getPassengerInfo;

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from dataclasses import dataclass
from functions.api import function, Integer
from ontology_sdk.ontology.objects import Passenger

@dataclass
class PassengerInfo:
    name: str | None
    age: Integer | None

@function
def get_passenger_info(passenger) -> PassengerInfo:
    return PassengerInfo(
        name=passenger.name,
        age=passenger.age
    )

Aggregation types

Aggregation types can be returned from functions for use in other parts of the platform, such as Charts in Workshop.

There are two supported aggregation types:

A two-dimensional aggregation maps from a single bucket key to a numeric value. For example, this could be used to represent an aggregation such as a count of employees with a specific job title.
A three-dimensional aggregation maps from two bucket keys to a numeric value. This could be used to represent an aggregation such as a count of employees by each employee's job title and home office.

Aggregations can be keyed by several types:

Boolean buckets represent values that are either true or false.
String buckets can be used to represent categorical values.
Range buckets represent aggregations where the bucket key is a range of values. These can be used to represent a histogram or date axis in a chart.
- Numeric ranges, including Integer and Double, represent bucketed aggregations on numeric values.
- Date and time ranges, including on Date and Timestamp, represent bucketed aggregations on date ranges.

Range

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import { Function, Integer, IRange } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getRange(min: Integer, max: Integer): IRange<Integer> {
        return {
            min,
            max,
        };
    }
}

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import { Integer, Range } from "@osdk/functions";

function getRange(min: Integer, max: Integer): Range<Integer> {
    return {
        min,
        max,
    };
}

export default getRange;

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from functions.api import function, Integer, Range

@function
def get_range(min: Integer, max: Integer) -> Range[Integer]:
    return Range(
        min=min,
        max=max
    )

Two-dimensional aggregation

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import { Double, Function, TwoDimensionalAggregation } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public myTwoDimensionalAggregation(): TwoDimensionalAggregation<string, Double> {
        return {
            buckets: [
                { key: "bucket1", value: 5.0 },
                { key: "bucket2", value: 6.0 },
            ],
        };
    }
}

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import { Double, TwoDimensionalAggregation } from "@osdk/functions";

function myTwoDimensionalAggregationFunction(): TwoDimensionalAggregation<string, Double> {
    return [
        { key: "bucket1", value: 5.0 },
        { key: "bucket2", value: 6.0 },
    ];
}

export default myTwoDimensionalAggregationFunction;

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from functions.api import (
    function,
    Double,
    TwoDimensionalAggregation,
    SingleBucket
)

@function
def my_two_dimensional_aggregation_function() -> TwoDimensionalAggregation[str, Double]:
    return TwoDimensionalAggregation(
        buckets=[
            SingleBucket(key="bucket1", value=Double(5.0)),
            SingleBucket(key="bucket2", value=Double(6.0)),
        ]
    )

Three-dimensional aggregation

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import { Double, Function, ThreeDimensionalAggregation } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public myThreeDimensionalAggregation(): ThreeDimensionalAggregation<string, string, Double> {
        return {
            buckets: [
                {
                    key: "group-by-1",
                    groups: [
                        { key: "partition-by-1", value: 5.0 },
                        { key: "partition-by-2", value: 6.0 },
                    ],
                },
                {
                    key: "group-by-2",
                    groups: [
                        { key: "partition-by-1", value: 7.0 },
                        { key: "partition-by-2", value: 8.0 },
                    ],
                },
            ]
        };
    }
}

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import { Double, ThreeDimensionalAggregation } from "@osdk/functions";

function myThreeDimensionalAggregation(): ThreeDimensionalAggregation<string, string, Double> {
    return [
        {
            key: "group-by-1",
            groups: [
                { key: "partition-by-1", value: 5.0 },
                { key: "partition-by-2", value: 6.0 },
            ],
        },
        {
            key: "group-by-2",
            groups: [
                { key: "partition-by-1", value: 7.0 },
                { key: "partition-by-2", value: 8.0 },
            ],
        },
    ];
}

export default myThreeDimensionalAggregation;

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from functions.api import (
    function,
    Double,
    ThreeDimensionalAggregation,
    SingleBucket,
    NestedBucket,
)

@function
def my_three_dimensional_aggregation_function() -> (
    ThreeDimensionalAggregation[str, str, Double]
):
    return ThreeDimensionalAggregation(
        buckets=[
            NestedBucket(key="group-by-1", buckets=[
                SingleBucket(key="partition-by-1", value=Double(5.0)),
                SingleBucket(key="partition-by-2", value=Double(6.0)),
            ]),
            NestedBucket(key="group-by-2", buckets=[
                SingleBucket(key="partition-by-1", value=Double(7.0)),
                SingleBucket(key="partition-by-2", value=Double(8.0)),
            ])
        ]
    )

Ontology types

Ontology imports

Object types must be imported into your repository to use them in function signatures. Learn more about Ontology imports.

Object

Object types from your ontology can be used as both inputs and outputs in your function signature. To either accept or return a single instance of an object type, import the object type from your Ontology SDK and use that type to annotate your function.

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import { Function, Integer } from "@foundry/functions-api";
import { Airplane } from "@foundry/ontology-api";

export class MyFunctions {
    @Function()
    public getCapacity(airplane: Airplane): Integer {
        return airplane.capacity;
    }
}

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import { Osdk } from "@osdk/client";
import { Integer } from "@osdk/functions";
import { Airplane } from "@ontology/sdk";

function getCapacity(airplane: Osdk.Instance<Airplane>): Integer {
    return airplane.capacity;
}

export default getCapacity;

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from functions.api import function, Integer
from ontology_sdk.ontology.objects import Airplane

@function
def get_capacity(airplane: Airplane) -> Integer:
    return airplane.capacity

Object set

There are two ways to pass a collection of objects into and out of a function: concrete collections of objects (such as arrays), or object sets.

Passing an array of objects to a function enables executing logic over a concrete list of objects at the expense of loading the objects into the function execution environment up front. An object set, however, allows you to perform filtering, search-around, and aggregation operations and only load the final result when you request it.

We recommend using an object set instead of an array because an object set often achieves better performance and allows more than 10,000 objects to be passed into the function.

The below example shows how to filter an object set without loading the objects into memory, allowing you to return the filtered object set to a different part of the application.

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import { Function } from "@foundry/functions-api";
import { Airplane, ObjectSet } from "@foundry/ontology-api";

export class MyFunctions {
    @Function()
    public filterAircraft(aircraft: ObjectSet<Airplane>): ObjectSet<Airplane> {
        return aircraft.filter(a => a.capacity.range().gt(200));
    }
}

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import { ObjectSet } from "@osdk/client";
import { Airplane } from "@ontology/sdk";

function filterAircraft(aircraft: ObjectSet<Airplane>): ObjectSet<Airplane> {
    return aircraft
        .where({
            capacity: {
                $gt: 200,
            } 
        });
}

export default filterAircraft;

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from functions.api import function
from ontology_sdk.ontology.objects import Airplane
from ontology_sdk.ontology.object_sets import AirplaneObjectSet

@function
def filter_aircraft(aircraft: AirplaneObjectSet) -> AirplaneObjectSet:
    return aircraft.where(Airplane.capacity > 200)

Ontology edit

In addition to writing functions that read data from the Ontology, you can also write functions that create objects and edit the properties and links between objects. For more details about how edit functions work, refer to the overview page.

To be registered as edit functions, TypeScript v1 functions require a void return type in the signature. TypeScript v2 and Python functions, however, require explicitly returning a list of Ontology edits.

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import { Edits, OntologyEditFunction } from "@foundry/functions-api";
import { Employee, LaptopRequest, Objects } from "@foundry/ontology-api";

export class MyFunctions {
    
    @Edits(Employee, LaptopRequest)
    @OntologyEditFunction()
    public assignEmployee(newEmployee: Employee, leadEmployee: Employee): void {

        const newLaptopRequest = Objects.create().laptopRequest(Date.now().toString());
        newLaptopRequest.employeeName = newEmployee.name;

        newEmployee.lead.set(leadEmployee);
    }
}

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import { Client } from "@osdk/client";
import { createEditBatch, Edits } from "@osdk/functions";
import { Employee, LaptopRequest } from "@ontology/sdk";

type EmployeeEdit = 
    | Edits.Object<Employee>
    | Edits.Object<LaptopRequest>
    | Edits.Link<Employee, "lead">;

function assignEmployee(
    client: Client,
    newEmployee: Osdk.Instance<Employee>,
    leadEmployee: Osdk.Instance<Employee>
): EmployeeEdit[] {

    const batch = createEditBatch<EmployeeEdit>(client);

    batch.create(LaptopRequest, {
        id: Date.now().toString(),
        employeeName: newEmployee.name,
    });
    batch.link(newEmployee, "lead", leadEmployee);

    return batch.getEdits();
}

export default assignEmployee;

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from functions.api import function, OntologyEdit
from ontology_sdk.ontology.objects import Employee, FoundryClient, LaptopRequest
from time import time

@function
def assign_employee(new_employee: Employee, lead_employee: Employee) -> list[OntologyEdit]:

    ontology_edits = FoundryClient().ontology.edits()

    new_laptop_request = ontology_edits.objects.LaptopRequest.create(str(int(time() * 1000)))
    new_laptop_request.employee_name = new_employee.name

    new_employee.lead.set(lead_employee)

    return ontology_edits.get_edits()

Attachment

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import { Attachment, Function } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public loadAttachmentContents(attachment: Attachment): Promise<string> {
        return attachment.readAsync().then(blob => blob.text());
    }
}

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import { Attachment } from "@osdk/functions";

function loadAttachmentContents(attachment: Attachment): Promise<string> {
    return attachment.fetchContents().then(response => response.text());
}

export default loadAttachmentContents;

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from functions.api import function, Attachment

@function
def load_attachment_contents(attachment: Attachment) -> str:
    return attachment.read().getvalue().decode('utf-8')

Notification

Notification types can be returned from a function to flexibly configure notifications that should be sent in the platform. For example, you can author a function that takes in parameters such as a User and an object type and returns a Notification with a configured message.

A Notification consists of two fields: a ShortNotification and EmailNotificationContent.
A ShortNotification represents a summarized version of the notification, which will be shown within the Foundry platform. It includes a short heading, content, and a collection of Links.
EmailNotificationContent represents a rich version of the notification which can be sent externally via email. It includes a subject, a body consisting of headless HTML, and a collection of Links.
A Link has a user-facing label and a linkTarget. The LinkTarget can be a URL, an OntologyObject, or a rid of any resource within Foundry.

For an example of how to use the Notifications API, review our guide.

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import {
    EmailNotificationContent,
    Function,
    Notification,
    ShortNotification,
} from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public buildNotification(): Notification {
        return Notification.builder()
            .shortNotification(ShortNotification.builder()
                .heading("Issue reminder")
                .content("Investigate this issue.")
                .build())
            .emailNotificationContent(EmailNotificationContent.builder()
                .subject("New issue")
                .body("hello")
                .build())
            .build();
    }
}

Media types

Media references

Functions can accept and return media items. For more information, review the guide on media.

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import { Function, MediaItem } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public transcribeAudioFile(file: MediaItem): Promise<string | undefined> {
        if (MediaItem.isAudio(file.mediaReference)) {
            return await file.mediaReference.transcribeAsync({
                language: TranscriptionLanguage.ENGLISH,
                performanceMode: TranscriptionPerformanceMode.MORE_ECONOMICAL,
                outputFormat: {type: "plainTextNoSegmentData", addTimestamps: true}
            });
        }

        return undefined; 
    }
}

Users, groups, and principals

A Principal represents either a Foundry user account or group. These types can be passed into a function to allow accessing information associated with a user or group, such as a group's name or a user's first and last name or email address. All Principal types are exported from the @foundry/functions-api package.

A User always has a username, and may have a firstName, lastName, or email. It also includes all fields associated with a Principal.
A Group has a name. It also includes all fields associated with a Principal.
A Principal can be either a User or a Group. You can inspect the type field to determine whether a given Principal is a User or a Group. In addition to User and Group-specific fields, a Principal has an id, realm, and dictionary of attributes.

User

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import { Function, User } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getUserEmail(user: User): string {
        return user.email;
    }
}

Group

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import { Function, Group } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getGroupName(group: Group): string {
        return group.name;
    }
}

Principal

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import { Function, Principal } from "@foundry/functions-api";

export class MyFunctions {
    @Function()
    public getPrincipalType(principal: Principal): string {

        switch (principal.type) {
            case "user":
                return "User";
            case "group":
                return "Group";
            default:
                return "Unknown";
        }
    }
}

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