Inline Functions

Functions can be used in:

  • Then cells of If/Then Rules
  • Action cells of Decision Tables, and Matrix Rules
  • Formula rules in Transformation Blocks

Most formulas are available under Autocomplete as you type in these cells.

Inline Functions

PMT - Excel Equivalent

Usage: PMT(RATE, NPER, PV)

  • Rate - interest rate for loan (expressed in terms of period, so if you're using months, you may have to divide APR by 12)
  • Nper - total number of payments for the loan.
  • Pv - present value, or the total amount that a series of future payments is worth now; also known as the principal.

PV - Excel Equivalent

Usage: PV(RATE, NPER, PMT)

  • Rate - interest rate for loan (expressed in terms of period, so if you're using months, you may have to divide APR by 12)
  • Nper - total number of payments for the loan.
  • Pmt - payment made each period and cannot change over the life of the annuity. Typically has reverse sign of PV to reflect cash inflows/outflows

NPER - Excel Equivalent

Usage: NPER(RATE, PMT, PV)

  • Rate - interest rate for loan (expressed in terms of period, so if you're using months, you may have to divide APR by 12)
  • Pmt - payment made each period and cannot change over the life of the annuity. Typically has reverse sign of PV to reflect cash inflows/outflows
  • Pv - present value, or the total amount that a series of future payments is worth now; also known as the principal.

RATE - Excel Equivalent

Usage: RATE(NPER, PMT, PV)

  • Nper - total number of payments for the loan.
  • Pmt - payment made each period and cannot change over the life of the annuity. Typically has reverse sign of PV to reflect cash inflows/outflows
  • Pv - present value, or the total amount that a series of future payments is worth now; also known as the principal.

AGE

Usage: AGE(customer.date_of_birth)

  • input date string in format '2020-05-03'
  • returns age in years

AGE_MONTH

Usage: AGE_MONTH(customer.date_of_birth)

  • input date string in format '2020-05-03'
  • returns age in months

AGE_DAY

Usage: AGE_DAY(customer.date_of_birth)

  • input date string in format '2020-05-03'
  • returns age in days

DATE_TIME_DIFF

Usage: DATE_TIME_DIFF(customer.first_transaction_time, customer.second_transaction_time, units)

  • input datetime strings in format '2018-12-11T13:49:51.141Z'
  • final parameter is units: SECONDS, NANOS, MICROS, MILLIS, MINUTES, HOURS, DAYS
  • returns difference in specified units

MAX

Usage: MAX(num1, num2)

  • input two numbers
  • returns larger of two

MIN

Usage: MIN(num1, num2)

  • input two numbers
  • returns smaller of two

RANDOM

Usage: RANDOM(percent_true)

  • returns true percent_true of the time
  • Useful for champion/challenger flows

ROUND

Usage: ROUND(customer.prop)

  • returns the customer.prop rounded to nearest whole number

Usage: ROUND(customer.prop, places, direction)

  • returns the customer.prop rounded to the places number of decimal places
  • direction can be up, down, or nearest (default)
    • Note that the direction should be in single quotes, e.g. tens = ROUND(customer.income, 1, 'up')

COALESCE

Usage: coalesce(item1, item2)

  • returns the first non-null item in the list, similar to SQL coalesce command
  • example: income = coalesce( customer.income, 5000) will return the customer’s income or 5000 if that field isn’t present in a workflow execution

ABS

Usage: ABS(transaction.amount)

  • returns the absolute value of a number

SQRT

Usage: SQRT(transaction.amount)

  • returns the square root of a number

LOG

Usage: LOG(transaction.number_field)

  • returns the natural logarithm of the number passed into the function

EXP

Usage: EXP(transaction.power)

  • returns e raised to the power of the number passed into the function

EXPM1

Usage: EXPM1(transaction.power)

  • returns e^n - 1, where n is the number passed into the function

DISTANCE

Usage: Distance(pointA.lat, pointA.lon, pointB.lat, pointB.lon)

  • returns distance in meters between two geographic points

PUT

usage: PUT( object, key, value)

  • Inserts a new key/value pair into an object
  • example: PUT(customer.car, 'model', 'ford')

String Functions

CONCAT

Usage: CONCAT(str1, str2)

  • returns a combined string

SUB_STR

Usage: SUB_STR(string, start, end)

  • returns a substring, from the starting character to ending character
    For example SUB_STR(john, 1, 3,) would return oh

SIMILARITY

Usage: SIMILARITY(string1, string2)

  • Computes the Jaro-Winkler similarity between two strings
  • Returns a number between 0 and 1, where 1 is an exact match
  • Note: ignores case
  • Example: SIMILARITY(transaction.sender.name, transaction.receiver.name)

SEARCH

Usage: SEARCH(string, exp)

  • returns true/false if the string contains the expression (accepts regular expressions)
    For example SEARCH(customer.email, 'gmail.com' would return true for gmail addresses

REPLACE

Usage: REPLACE(string, find, replace)

  • returns a new string, replacing any instances of the 'find' expression with the 'replace' expression
    For example REPLACE(customer.email, 'gmail.com', 'yahoo.com') would return a guess at a yahoo email address for a gmail user

EXTRACT

Usage: EXTRACT(string, regexp)

  • returns a new string, extracting based on the regular expression provided
  • For example EXTRACT(customer.email, '[^@]\*') would return the username before the '@' sign of an email address

JSON

Usage: blob=JSON(string_to_convert)

  • Converts a string into a JSON object
  • Note: if you try to run this function on data that isn't a string (including on other JSON objects) it will return null

length (dot function)

Usage: customer.email.length

  • returns the length of a string

List Functions

ADD

Usage: add( list, item)

  • returns a new list including every item in the original list + the new item

IN

usage: in( list, item)

  • returns true if the item is in the list, otherwise false
  • example: if: in( approved_phone_types, customer.phone_model) == true

CONCAT_LIST

usage: CONCAT_LIST(part1, part2

  • Adds two lists together, and returns a new list, preserving order.

FILTER

usage: FILTER( list, itr.field == 'value')

  • filters a list of json objects, and returns only the items with a field equal to a specific value
  • example: assuming you have a list of transactions, and want to filter by status == blocked block_list = FILTER( customer.transactions, itr.status == 'blocked')

MAP

usage: MAP( list, itr.field)

  • accepts a list of json objects, and returns a list of all the values for a specific field.
  • example: assuming you have a list of transactions with mulitiple fields, and want a list of amounts amount_list = MAP( customer.transactions, itr.amount)

ZIP_TO_MAP

usage: ZIP_TO_MAP(keylist, valuelist)

  • returns a map of key/value pairs (note: keylist must be numbers or strings, and both lists must be same length)

SUM

usage: SUM(list, itr.field)

  • Accepts a list of json objects, and returns the total of all the values for the specific field
  • example: total_debt = SUM(credit_cards, itr.balance)

GET

usage: GET( object, key)

  • returns the value for the key, in a given object. you can use this with dynamic keys
  • example: say you have a customer object, with three pet names as fields (dog, cat, and bird), and a custom variable type_of_pet in your workflow that makes it clear the pets you're interested in are dogs. You can get the customer's dog name using dog_name = GET( customer, type_of_pet). it's equivalent to dog_name = customer.dog but the benefit is that type_of_pet here is dynamic

SUBLIST

usage: sublist2( list, end_index)

  • returns a new list of the objects from the start to the end_index in the original list.

usage: sublist3( list, start_index, end_index)

  • returns a new list of the objects from the start_index to the end_index in the original list.

SORT

usage: SORT( list, field)

  • Returns a sorted copy of an array of objects, sorted by the field on each object (ascending)
  • example: SORT(customer.credit_card_list, itr.balance)

Dot Functions (run on a single variable)

to_str

Usage: customer.income.to_str

  • converts a number to a string

to_num

Usage: customer.income.to_str

  • converts a string to a number

to_dollar

Usage: customer.income.to_dollar

  • converts a number to a dollar-formatted string (e.g. 500 → $500.00)

Data Validation Functions

is_present

Usage: customer.income.is_present

  • returns true if this field is present for the current Workflow execution, or false if this field is missing

Type Functions

is_text, is_num, is_boolean, is_list

Usage: customer.name.is_text

  • returns true if this field is of type "text", "number", etc - otherwise returns false

Formatting Functions

FORMAT()

Usage: FORMAT(datasource.token, 'UTF-8')

  • returns UTF-8 formatted string from a ByteArray output