JMESpath

Overview

This guide provides practical JMESPath examples for use in Alumio. In a field that supports placeholders, wrap each JMESPath expression in &{...}.

Filtering items

Use filtering expressions to return only the array entries that meet one or more conditions.

Use case	Expression
Filter active items	`&{items[?active == \`true`]}`
Filter items by price	`&{items[?price > \`100`]}`
Filter items by category	`&{items[?contains(categories, 'featured')]}`
Filter available items	`&{items[?active == \`true` && stock > `0`]}`
Find an item by SKU	`&{items[?sku == 'SKU-001'] \| [0]}`
Filter items with no stock	`&{items[?stock == \`0`]}`
Filter items whose name contains text	`&{items[?contains(name, 'Laptop')]}`

For example, &{items[?active == \true` && stock > `0`]}returns onlySKU-001` from the sample input.

Use backticks for numeric and boolean literals, for example \100`and`true`. Use single quotes for strings, for example ’featured’`.

Select and reshape data

Use case	Expression
Select a field from all items	`&{items[].name}`
Select the first item	`&{items[0]}`
Select the last item	`&{items[-1]}`
Select the first two items	`&{items[:2]}`
Select a range of items	`&{items[1:3]}`
Create a new customer object	`&{customer.{id: id, email: email, full_name: name}}`
Select fields as an array	`&{items[0].[sku, name, price]}`
Select a field with a dot in its name	`&{"product.name"}`

Work with nested data

Use case	Expression
Extract all SKUs from order lines	`&{orders[].lines[].sku}`
Count lines per order	`&{orders[].{order_id: id, line_count: length(lines)}}`
Calculate total quantity per order	`&{orders[].{order_id: id, total_quantity: sum(lines[].quantity)}}`
Build an order summary	`&{orders[].{id: id, status: status, first_sku: lines[0].sku}}`

Aggregate and sort values

Use case	Expression
Count items	`&{length(items)}`
Calculate total price	`&{sum(items[].price)}`
Calculate average price	`&{avg(items[].price)}`
Get the highest price	`&{max(items[].price)}`
Get the lowest price	`&{min(items[].price)}`
Find the most expensive item	`&{max_by(items, &price)}`
Find the lowest-priced item	`&{min_by(items, &price)}`
Sort item names	`&{sort(items[].name)}`
Sort items by price	`&{sort_by(items, &price)}`
Reverse an array	`&{reverse(items)}`

Handle and validate values

Use case	Expression
Use the first available value	`&{not_null(customer.phone, customer.mobile, customer.email)}`
Convert a value to a string	`&{to_string(items[0].id)}`
Convert a value to an array	`&{to_array(customer.email)}`
Convert all IDs to strings	`&{map(&to_string(@), items[].id)}`
Get object keys	`&{keys(customer)}`
Get object values	`&{values(customer)}`
Get a value type	`&{type(items[0].price)}`
Merge two objects	`&{merge(customer, address)}`

Build JSON objects from tabular rows

When a parsed CSV is available in data as an array of rows, map each row into an object:

&{data[*].{"id": [0], "sku": [1], "name": [2], "qty": [3]}}

For example, a row such as ["1", "ABC123", "Product X", "23"] becomes:

{
  "id": "1",
  "sku": "ABC123",
  "name": "Product X",
  "qty": "23"
}

Use the Run Test option in Alumio after each change. This lets you validate the expression against a representative entity before enabling the configuration.

Templates

Import & Export

Packages

Example configurations

Overview

Filtering items

Select and reshape data

Work with nested data

Aggregate and sort values

Handle and validate values

Build JSON objects from tabular rows

Template Import

​Overview

​Filtering items

​Select and reshape data

​Work with nested data

​Aggregate and sort values

​Handle and validate values

​Build JSON objects from tabular rows

​Template Import

Overview

Filtering items

Select and reshape data

Work with nested data

Aggregate and sort values

Handle and validate values

Build JSON objects from tabular rows

Template Import