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FlatLaf/README.md

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FlatLaf - Flat Look and Feel

FlatLaf is a modern open-source cross-platform Look and Feel for Java Swing desktop applications.

It looks almost flat (no shadows or gradients), clean, simple and elegant. FlatLaf comes with Light, Dark, IntelliJ and Darcula themes, scales on HiDPI displays and runs on Java 8 or newer.

The look is heavily inspired by Darcula and IntelliJ themes from IntelliJ IDEA 2019.2+ and uses almost the same colors and icons.

FlatLaf Light

FlatLaf Dark

macOS Themes

FlatLaf macOS themes

IntelliJ Platform Themes

FlatLaf can use 3rd party themes created for IntelliJ Platform (see IntelliJ Themes Pack):

IntelliJ Platform Themes

Sponsors

ej-technologies         DbVisualizer         DSC Software AG

Become a Sponsor

Demo

Download Demo

Run demo with java -jar flatlaf-demo-<version>.jar (or double-click it). Requires Java 8 or newer.

Download

FlatLaf binaries are available on Maven Central.

If you use Maven or Gradle, add a dependency with following coordinates to your build script:

groupId:     com.formdev
artifactId:  flatlaf
version:     (see button below)

Otherwise download flatlaf-<version>.jar here:

Maven Central

See also Native Libraries distribution for instructions on how to redistribute FlatLaf native libraries with your application.

Snapshots

FlatLaf snapshot binaries are available on Sonatype OSSRH. To access the latest snapshot, change the FlatLaf version in your dependencies to <version>-SNAPSHOT (e.g. 0.27-SNAPSHOT) and add the repository https://oss.sonatype.org/content/repositories/snapshots/ to your build (see Maven and Gradle docs).

Addons

  • IntelliJ Themes Pack - bundles many popular open-source 3rd party themes
  • Extras - SVG icon, tri-state check box, UI inspectors, and more
  • SwingX - support for SwingX components
  • JIDE Common Layer - support for JIDE Common Layer components
  • Fonts - some font families bundled in easy-to-use and redistributable JARs

Getting started

To use FlatLaf, add following code to your main method before you create any Swing component:

FlatLightLaf.setup();

// create UI here...

Documentation

For more information and documentation visit FlatLaf Home:

Theme Editor

The Theme Editor that supports editing FlatLaf theme properties files. See Theme Editor documentation for details and downloads.

Theme Editor

Buzz

Applications using FlatLaf

  • Sponsor JFormDesigner (commercial) - Java/Swing GUI Designer (from the FlatLaf creators)
  • Sponsor JProfiler (commercial) - the award-winning all-in-one Java profiler
  • Sponsor install4j (commercial) - the powerful multi-platform Java installer builder
  • Sponsor DbVisualizer (commercial) - the universal database tool for developers, analysts and DBAs
  • Hot Apache NetBeans - IDE for Java, PHP, HTML and much more
  • Sponsor Thermo-Calc (commercial) - Thermodynamics and Properties Software

Data

  • Hot Ultorg (commercial) - a visual query system for relational databases
  • Jailer - database subsetting and relational data browsing tool
  • Hot MagicPlot (commercial) - Software for nonlinear fitting, plotting and data analysis
  • New Kafka Visualizer - Kafka GUI client

Security

Software Development

Electrical

Media

Modelling

  • IGMAS+ - Interactive Gravity and Magnetic Application System

Documents

Geo

  • Hot JOSM - an extensible editor for OpenStreetMap (requires FlatLaf JOSM plugin)
  • Mapton (source code) - some kind of map application (based on NetBeans platform)
  • MeteoInfo - GIS and scientific computation environment for meteorological community

Messaging

  • New Spark - cross-platform IM client optimized for businesses and organizations

Gaming

Utilities

  • MooInfo - visual implementation of OSHI, to view information about the system and hardware
  • Rest Suite - Rest API testing
  • SpringRemote - remote Linux SSH connections manager
  • jEnTunnel - manage SSH Tunnels made easy
  • Android Tool - makes popular adb and fastboot commands easier to use

Miscellaneous

  • MEKA - multi-label classifiers and evaluation procedures using the Weka machine learning framework