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Getting Started Overview

Pretext is a text preparation and line-layout engine for any SkiaSharp-based UI that needs deterministic wrapping and visibility rules without delegating everything to a control-specific text stack.

What to expect

Pretext is built around one idea: expensive text analysis should happen once, and width-dependent layout should be cheap and repeatable after that.

The normal workflow is:

  1. Convert raw text into a prepared object with Prepare or PrepareWithSegments.
  2. Reuse that prepared object as widths change.
  3. Choose the cheapest layout API that answers your question.
  4. Draw or arrange the resulting lines in your own UI.

Package and repository map

Item Use it when
Pretext You want the reusable layout engine in any SkiaSharp-based UI, under the Pretext namespace.
Pretext.Uno You want Uno-specific controls and layout helpers layered on top of Pretext.
src/Pretext You are working on the core package source in this repository.
src/Pretext.Uno You are working on the Uno companion package source in this repository.
tests/Pretext.Uno.Tests You want the deterministic behavior checks and supported-text examples.
samples/PretextSamples You want a reference Uno app that shows the library in real layouts.

The four main API shapes

API Use it when
Prepare You only need aggregate layout metrics and do not need segment data or line text.
PrepareWithSegments You need segment metadata, materialized lines, or streamed iteration.
Layout You only need line count and total height.
LayoutWithLines You need the rendered line text and widths for each line.
LayoutNextLine You are flowing one line at a time into a custom container, obstacle map, or multi-column algorithm.
WalkLineRanges You need line widths and cursors but want to avoid allocating line strings.

When it helps

  • Shrinkwrapping cards, chips, and chat bubbles
  • Running custom justification or editorial algorithms
  • Measuring text repeatedly during responsive layout
  • Preserving tabs, hard breaks, and trailing spaces in PreWrap
  • Handling multilingual content with bidi runs and locale-aware segmentation