ToolzyLab
Remove line breaks, extra spaces, empty lines, tabs, unwanted special characters, duplicate lines, and duplicate words instantly. Also view powerful text statistics like paragraph count, average word length, and word frequency directly in your browser.
Paste messy text, upload a file, remove blank lines, compress extra spaces, normalize line breaks, strip special characters, remove duplicates, convert case, and inspect rich text statistics in one polished ToolzyLab workspace.
Paste text, upload a .txt or similar file, or drag and drop content here to clean instantly.
📄 .txt / .csv / .log / .md · ⚡ clean text · 🧠 stats · ⌨ copy · ⬇ download · 🔒 no uploadPaste raw text on the left, then inspect the cleaned result on the right.
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See exactly what changed after the cleanup process.
Most repeated words found in the cleaned text.
Use this tool for copied text from PDFs, OCR, WhatsApp, websites, forms, Excel exports, logs, and messy notes. It runs fully in your browser and never uploads your text.
Quick stats for the cleaned result so you can scan changes fast.
It removes empty lines, trims line edges, collapses repeated spaces, replaces tabs, removes unwanted special characters, removes duplicate lines or words, converts case, highlights search results, and shows paragraph count, average word length, and frequency stats in one clean screen.
Text cleanup is a sequence of transformations, and order matters. Choose case conversion, line-break replacement, trimming, tab and blank-line handling, special-character rules, duplicate lines or words, and frequency settings, then compare names, punctuation, paragraphs, code, numbers, and Unicode before using the output.
Collapsing spaces helps prose copied from inconsistent sources, while removing line breaks can destroy addresses, poetry, code, CSV, logs, and paragraph boundaries. Trim edges separately from joining lines. Decide whether tabs should become one space or preserve column meaning before processing.
Special-character removal can damage email addresses, URLs, prices, negative numbers, units, contractions, code, and non-Latin writing. Case conversion can change identifiers and proper names. Use an allowed-character set tailored to the destination and inspect Unicode rather than assuming letters means ASCII.
Case-sensitive and case-insensitive comparisons produce different results. Duplicate words may be intentional emphasis, while repeated lines may represent valid records. Keeping the first occurrence changes frequency data and can remove chronological events. Preserve the original and report counts before deduplication.
Compare structure and meaning, not just a smaller character count.
Collapse repeated spaces and trim line edges while leaving line breaks enabled. Preview paragraph boundaries before applying a line-break replacement.
Removing empty lines keeps nonempty rows separate. Removing line breaks joins rows, which can destroy paragraphs and structured data.
Use the allowed-character control to retain characters such as at-sign, period, hyphen, currency symbols, decimal marks, and punctuation required by the destination.
It keeps the first occurrence under the selected case-sensitivity rule. Review records where repeated lines may be meaningful.
Yes. Case can matter in passwords, tokens, paths, code identifiers, product codes, and some search or matching systems. Do not normalize those blindly.
That depends on the selected special-character rule and implementation. Test representative Unicode and explicitly allow the scripts and symbols your users need.