What is a fixed-width file?

A flat text format where each field sits at a fixed character position rather than being separated by commas or tabs. For example columns 1 to 4 hold an ID and columns 5 to 20 hold a name, padded with spaces. Mainframe and banking exports often use it.

Is the start position 0-based or 1-based?

1-based, the way the positions are usually documented. A field that starts at the very first character has start 1. Internally the tool subtracts one to slice the string correctly.

What does trimming do?

Fixed-width fields are padded with spaces to fill their width. With trimming on, leading and trailing whitespace is removed so JOHN SMITH does not carry trailing spaces. Turn it off when the padding is meaningful.

What if a line is shorter than the spec?

Slicing past the end of a line simply yields an empty string for that field, so short or truncated lines do not crash the parser — they just produce blank values for the missing columns.

Fixed-Width File Parser

Parse fixed-width records into a table

The Fixed-Width File Parser turns column-positional flat files — the kind produced by mainframes, banks, and legacy systems — into clean CSV or JSON. You describe each field by its name, where it starts, and how many characters it spans, and the tool slices every line accordingly.

How it works

You provide a spec with one line per field in the form name,start,length, where start is the 1-based character position of the field’s first column. The parser validates that each line has three parts and that start and length are positive integers, reporting a precise error if not.

For every input line, each field is extracted with a substring from start - 1 for length characters. Because JavaScript’s substring stops at the end of the string, lines shorter than the full record width yield empty strings for the trailing fields instead of failing. With trimming enabled, each extracted value has its surrounding whitespace removed — important because fixed-width fields are space-padded to fill their column. The records are then serialised either as a JSON array of objects or as quoted CSV.

Example and notes

For the spec:

id,1,4
name,5,16
city,21,9

the line 0001JOHN SMITH LONDON parses to id=0001, name=JOHN SMITH, city=LONDON. Keep id as a string here — leading zeros matter, and CSV/JSON text output preserves them. If your file uses a header line with column names but no explicit widths, measure the start columns of each header label to build the spec.