Splitter Swift

A lightweight, local tool to split text or data by delimiter or pattern, returning tokens and counts for data preparation and analysis.

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About This Tool

Splitter Swift is a lightweight, deterministic string splitter designed for data engineers, developers, and editors who routinely convert unstructured text into structured tokens. It supports splitting by a fixed delimiter or by a regular expression pattern, and it returns a tokens array along with a simple count. The tool is designed to be predictable and fast, operating locally without network requests, making it suitable for sensitive data. Example: splitting 'alpha,beta,,gamma' by ',' with remove_empty enabled yields ['alpha','beta','gamma'], while leaving empties yields ['alpha','beta','','gamma'] depending on settings.
Conceptually, the tool applies a split operation, then optional post-processing steps such as trimming whitespace and discarding empty tokens. It exposes both simple usage (delimiter-based) and advanced usage (regex-based splits) to cover common data-cleaning tasks and text-processing pipelines. The core outputs are a tokens array and a numeric count, enabling downstream scripts or analytics to iterate over items efficiently. It is language-agnostic in concept; implemented logic mirrors common languages (e.g., JavaScript, Python) so users can map examples to their own code.
Who benefits: data practitioners, software engineers, QA analysts, and content teams needing quick tokenization for parsing, validation, or feature extraction. Unique value lies in its explicit handling of edge cases (empty tokens, max_splits, Unicode), its support for both simple and regex splits, and its privacy-friendly, local operation. Use cases include log parsing, CSV line tokenization, preprocessing for NLP, and data normalization for ETL pipelines.

How to Use

  1. Provide inputs: enter the text to split in input_text and specify a delimiter or switch to regex mode.
  2. Choose method: select 'delimiter' or 'regex' and set max_splits if needed.
  3. Configure options: enable removing empty tokens and trimming whitespace as required.
  4. Run calculation: the tool processes and returns the tokens array and the count.
  5. Review outputs: inspect tokens and counts; adjust delimiter or pattern if necessary.
How to use splitter swift

Frequently Asked Questions

Find Quick Answers

What inputs are required?
Inputs required are input_text and a delimiter or pattern. You may optionally specify max_splits, trim_tokens, and remove_empty. The tool validates that strings are provided and that max_splits is a non-negative integer.
Can I use regex patterns?
Yes, the regex mode interprets the provided pattern as a regular expression and splits accordingly. This enables complex boundaries, but requires escaping special characters and validating the pattern.
What outputs are produced?
The tool returns a tokens array and a numeric count. It may also provide the original input length and a sample of tokens for quick verification.
How are edge cases handled?
If the input is empty or the delimiter is missing, the tool returns an empty token list or an error, depending on configuration. Negative max_splits are treated as unlimited; empty tokens can be removed if configured.

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