Trim Whitespace in YAML Files Online

Trim leading and trailing whitespace from all text columns in YAML files, directly in your browser. No upload required.

How to trim Whitespace in YAML files

Drop your file onto the upload area. The tool loads it and reports how many text columns will be trimmed.
Check the column chips. Highlighted columns are text and will be trimmed. Number, date and boolean columns are shown unhighlighted and are left alone.
Click Trim Whitespace. The preview updates to show the trimmed values.
Click Download to save the cleaned file in the same format you uploaded.

Your file is processed locally in your browser and is never uploaded. The free limit is 50 MB per file; larger files work if your device has the memory for them.

Worked example

Wholesale orders were keyed in through a web form, and some product codes and customer names picked up stray spaces. A lookup on product code is failing for those rows.

Input (YAML)

- product_code: ' PX-204'
  customer: 'Blue  Harbor Cafe '
  qty: 12
- product_code: 'PX-310 '
  customer: ' Lindqvist AB'
  qty: 4
- product_code: PX-118
  customer: Casa Moreno
  qty: 20
- product_code: '  PX-204'
  customer: Blue  Harbor Cafe
  qty: 6

Settings

No options. Every text column is trimmed: product_code and customer.

Result

product_code	customer	qty
PX-204	Blue Harbor Cafe	12
PX-310	Lindqvist AB	4
PX-118	Casa Moreno	20
PX-204	Blue Harbor Cafe	6

Spaces at the start and end of each text value are removed, so both PX-204 rows now carry the same code and the same customer name. The double space inside "Blue Harbor Cafe" is kept, because only the ends of a value are trimmed. qty is numeric, so it is not touched.

Frequently Asked Questions

Which characters are removed?

Ordinary space characters at the start and end of each text value. Tabs, line breaks and non-breaking spaces are not removed, and spaces between words are kept.

Can I choose which columns to trim?

No. Every text column is trimmed automatically, and non-text columns are left alone. To trim only some columns, use the SQL Query tool with TRIM on those columns.

Why trim before deduplicating or joining?

Matching is exact, so "PX-204" and "PX-204 " count as different values. Trimming first lets duplicates, lookups and joins match as expected.

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