Urdu Text Formatter

The Urdu text formatter provides deterministic text normalization tailored to Urdu. It takes input Urdu text and outputs a version where spacing, diacritics, and punctuation follow consistent norms suitable for publishing, storage, and automated workflows. It is designed for editors, localization teams, and developers who ingest Urdu content into CMS, databases, or APIs. By treating Urdu as a right-to-left script with specific punctuation conventions, it reduces manual edits and guards against misrendering in downstream systems. Example: input with double spaces and a non-standard Urdu period can be normalized to a clean, standard form.
Conceptually, the tool uses Unicode normalization, the Bidirectional Algorithm, and rule-based substitutions to produce a predictable, storage-friendly output while preserving meaning. It supports configurable profiles: a default mode for general Urdu text and an advanced mode for stricter diacritic control or selective punctuation changes. The transformation focuses on text, not translation or font rendering, making it suitable for pre-publish cleanup and automated pipelines. Real-world use includes article preparation, subtitles, and data ingestion.
Core features include RTL-aware normalization, whitespace handling, diacritic preservation or removal according to policy, and punctuation standardization for Urdu typography. Optional features cover user-defined rules via a small DSL, regex-based substitutions, and API-driven batch processing. Transformations are non-destructive by default, enabling review before commit. Common workflows include cleaning imported content, standardizing editorial drafts, and ensuring consistent Urdu text across multilingual systems.
Benefit and differentiator: this tool understands Urdu-specific quirks, such as combining marks and script overlaps, and it handles mixed-script content gracefully. It enables repeatable, auditable text normalization, reduces manual edits, and improves downstream quality. It is applicable to publishing teams, software products, and data teams that require dependable, locale-aware text formatting.