Text tools for everyday cleanup and analysis
A surprising amount of work involves plain text: lists copied from spreadsheets, emails with broken line breaks, keyword lists full of duplicates, logs to filter and articles to count. These text tools each do one job quickly and predictably, and they can be chained: remove empty lines, then duplicates, then sort, and your messy list is ready.
Find the right text tool
- Change case – the case converter switches between UPPER, lower, Title, sentence case and programming styles like camelCase and snake_case.
- Clean up – remove duplicate lines, remove extra spaces, remove empty lines and remove line breaks each fix one common problem; the text formatter fixes spacing, punctuation and capitalization in one pass.
- Sort and shuffle – sort text lines alphabetically, numerically or by length, or randomize order with shuffle lines.
- Count and analyze – the word counter counts words, characters and reading time; word frequency, sentence and paragraph counters and a readability grade tool go deeper.
- Find and replace – the text replacer supports plain text and regular expressions.
- Convert – HTML to text extracts readable text from markup, and escaping tools prepare text for code.
- Just for fun – upside-down text, small caps and letter randomizers.
Useful combinations
- Cleaning an email list: trim spaces, convert to lowercase, remove empty lines, then remove duplicates.
- Preparing keywords: remove punctuation and accents, deduplicate and sort alphabetically.
- Fixing PDF text: join wrapped lines with the text formatter, collapse spaces and check the word count.
- Comparing versions: clean both texts the same way, then compare them in the diff checker.
Who uses text tools?
Writers check word counts and readability, marketers clean keyword and email lists, developers prepare test data and reformat logs, teachers create randomized word lists, and data analysts tidy exported columns before loading them into a spreadsheet. The tools are deliberately simple, so anyone can use them without learning regular expressions or spreadsheet formulas.
Tips
- Order matters: trimming and lowercasing before removing duplicates catches near-duplicates such as "Apple" and "apple ".
- For large lists, sorting after deduplication makes the result easier to review.
- Regular expressions are powerful for find and replace, but test them on a small sample first.
- Your text is processed in the browser and is not stored or uploaded, which matters for customer lists and drafts.
- Keep a copy of the original text until you are happy with the result; most cleanups cannot be undone automatically.