Humanize

Text Processing Data Analysis

Synopsis

Converts numbers to human-readable format with metric prefixes.

Schema

- humanize:
    field: <ident>
    target_field: <string>
    format: <string>
    precision: <integer>
    binary: <boolean>
    suffix: <string>
    description: <text>
    if: <script>
    ignore_failure: <boolean>
    ignore_missing: <boolean>
    on_failure: <processor[]>
    on_success: <processor[]>
    tag: <string>

Configuration

The following fields are used to define the processor:

Field	Required	Default	Description
field	Y	-	Source field containing numeric value to humanize
target_field	N	Same as field	Target field to store humanized result
format	N	size	Format type: size, number, time, frequency
precision	N	1	Decimal places to show in result
binary	N	false	Use binary (1024) instead of decimal (1000) base
suffix	N	-	Custom suffix to append to result
description	N	-	Explanatory note
if	N	-	Condition to run
ignore_failure	N	false	Continue processing if conversion fails
ignore_missing	N	false	Skip processing if referenced field doesn't exist
on_failure	N	-	See Handling Failures
on_success	N	-	See Handling Success
tag	N	-	Identifier

Details

Converts numeric values to human-readable format using appropriate metric prefixes (K, M, G, T) or time units. The processor makes large numbers more readable by automatically selecting the appropriate scale and unit.

The processor supports different format types including data sizes, general numbers, time durations, and frequencies, each with appropriate unit conventions.

note

The processor automatically selects the most appropriate unit based on the magnitude of the input number. For example, 1500000 becomes "1.5M" and 2048 becomes "2.0K" (or "2.0Ki" in binary mode).

When binary is enabled, the processor uses 1024-based calculations (Ki, Mi, Gi, Ti) instead of 1000-based (K, M, G, T), which is common for memory and storage sizes.

warning

Non-numeric input values will cause the processor to fail unless ignore_failure is set to true. Ensure the source field contains valid numeric data.

Examples

Basic Number Humanization

Converting large number to readable format...	{ "byte_count": 1048576 } - humanize: field: byte_count target_field: readable_size
creates human-readable size:	{ "byte_count": 1048576, "readable_size": "1.0MB" }

Binary Format

Using binary (1024-based) formatting...	{ "memory_bytes": 2147483648 } - humanize: field: memory_bytes binary: true precision: 2 target_field: memory_size
formats with binary units:	{ "memory_bytes": 2147483648, "memory_size": "2.00GiB" }

Time Format

Humanizing time duration in milliseconds...	{ "duration_ms": 125000 } - humanize: field: duration_ms format: time target_field: duration_human
converts to time units:	{ "duration_ms": 125000, "duration_human": "2m 5s" }

Custom Precision

Setting specific decimal precision...	{ "request_count": 1234567 } - humanize: field: request_count format: number precision: 3 target_field: formatted_count
formats with 3 decimal places:	{ "request_count": 1234567, "formatted_count": "1.235M" }

With Custom Suffix

Adding custom suffix to humanized value...	{ "frequency_hz": 2500000 } - humanize: field: frequency_hz format: frequency suffix: "Hz" target_field: readable_frequency
includes custom suffix:	{ "frequency_hz": 2500000, "readable_frequency": "2.5MHz" }