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张小白 728a874b1e Some checks are pending CI / Check Postgres and Protobuf migrations, mergability (push) Waiting to run Details CI / Check formatting and spelling (push) Waiting to run Details CI / (macOS) Run Clippy and tests (push) Waiting to run Details CI / (Linux) Run Clippy and tests (push) Waiting to run Details CI / (Linux) Build Remote Server (push) Waiting to run Details CI / (Windows) Run Clippy and tests (push) Waiting to run Details CI / Create a macOS bundle (push) Blocked by required conditions Details CI / Linux x86_x64 release bundle (push) Blocked by required conditions Details CI / Linux arm64 release bundle (push) Blocked by required conditions Details CI / Auto release preview (push) Blocked by required conditions Details Deploy Docs / Deploy Docs (push) Waiting to run Details Docs / Check formatting (push) Waiting to run Details Script / ShellCheck Scripts (push) Waiting to run Details windows: Improve foreground task dispatching on Windows (#23283 ) Closes #22653 After some investigation, I found this bug is due to that sometimes `foreground_task` is not dispatched to the main thread unless there is user input. The current Windows implementation works as follows: when the `WindowsDispatcher` receives a `foreground_task`, it adds the task to a queue and uses `SetEvent(dispatch_event)` to notify the main thread. The main thread then listens for notifications using `MsgWaitForMultipleObjects(&[dispatch_event])`. Essentially, this is a synchronous method, but it is not robust. For example, if 100 `foreground_task`s are sent, `dispatch_event` should theoretically be triggered 100 times, and `MsgWaitForMultipleObjects(&[dispatch_event])` should receive 100 notifications, causing the main thread to execute all 100 tasks. However, in practice, some `foreground_task`s may not get a chance to execute due to certain reasons. As shown in the attached video, when I don't move the mouse, there are about 20-30 `foreground_task`s waiting in the queue to be executed. When I move the mouse, `run_foreground_tasks()` is called, which processes the tasks in the queue. https://github.com/user-attachments/assets/83cd09ca-4b17-4a1f-9a2a-5d1569b23483 To address this, this PR adopts an approach similar to `winit`. In `winit`, an invisible window is created for message passing. In this PR, we use `PostThreadMessage` to directly send messages to the main thread. With this implementation, when 100 `foreground_task`s are sent, the `WindowsDispatcher` uses `PostThreadMessageW(thread_id, RUNNABLE_DISPATCHED)` to notify the main thread. This approach enqueues 100 `RUNNABLE_DISPATCHED` messages in the main thread's message queue, ensuring that each `foreground_task` is executed as expected. The main thread continuously processes these messages, guaranteeing that all 100 tasks are executed. Release Notes: - N/A		2025-01-18 23:43:56 +08:00
..
docs	Docs Party 2024 (#15876 )	2024-08-09 13:37:54 -04:00
examples	gpui: Update Shadow Example (#22434 )	2024-12-26 19:23:10 +00:00
resources/windows
src	windows: Improve foreground task dispatching on Windows (#23283 )	2025-01-18 23:43:56 +08:00
tests	Improve keymap json schema (#23044 )	2025-01-13 02:34:35 +00:00
build.rs	deps: Bump smol to 2.0 (#22956 )	2025-01-10 13:38:00 +00:00
Cargo.toml	chore: Use workspace fields for edition and publish (#23291 )	2025-01-17 17:39:22 +01:00
LICENSE-APACHE
README.md	Fix stale Discord invite links (#21074 )	2024-11-22 21:10:51 +00:00

README.md

Welcome to GPUI!

GPUI is a hybrid immediate and retained mode, GPU accelerated, UI framework for Rust, designed to support a wide variety of applications.

Getting Started

GPUI is still in active development as we work on the Zed code editor and isn't yet on crates.io. You'll also need to use the latest version of stable Rust and be on macOS or Linux. Add the following to your Cargo.toml:

gpui = { git = "https://github.com/zed-industries/zed" }

Everything in GPUI starts with an App. You can create one with App::new(), and kick off your application by passing a callback to App::run(). Inside this callback, you can create a new window with AppContext::open_window(), and register your first root view. See gpui.rs for a complete example.

Dependencies

GPUI has various system dependencies that it needs in order to work.

macOS

On macOS, GPUI uses Metal for rendering. In order to use Metal, you need to do the following:

Install Xcode from the macOS App Store, or from the Apple Developer website. Note this requires a developer account.

Ensure you launch XCode after installing, and install the macOS components, which is the default option.

Install Xcode command line tools
```
xcode-select --install
```
Ensure that the Xcode command line tools are using your newly installed copy of Xcode:
```
sudo xcode-select --switch /Applications/Xcode.app/Contents/Developer
```

The Big Picture

GPUI offers three different registers depending on your needs:

State management and communication with Models. Whenever you need to store application state that communicates between different parts of your application, you'll want to use GPUI's models. Models are owned by GPUI and are only accessible through an owned smart pointer similar to an Rc. See the app::model_context module for more information.
High level, declarative UI with Views. All UI in GPUI starts with a View. A view is simply a model that can be rendered, via the Render trait. At the start of each frame, GPUI will call this render method on the root view of a given window. Views build a tree of elements, lay them out and style them with a tailwind-style API, and then give them to GPUI to turn into pixels. See the div element for an all purpose swiss-army knife of rendering.
Low level, imperative UI with Elements. Elements are the building blocks of UI in GPUI, and they provide a nice wrapper around an imperative API that provides as much flexibility and control as you need. Elements have total control over how they and their child elements are rendered and can be used for making efficient views into large lists, implement custom layouting for a code editor, and anything else you can think of. See the element module for more information.

Each of these registers has one or more corresponding contexts that can be accessed from all GPUI services. This context is your main interface to GPUI, and is used extensively throughout the framework.

Other Resources

In addition to the systems above, GPUI provides a range of smaller services that are useful for building complex applications:

Actions are user-defined structs that are used for converting keystrokes into logical operations in your UI. Use this for implementing keyboard shortcuts, such as cmd-q. See the action module for more information.
Platform services, such as quit the app or open a URL are available as methods on the app::AppContext.
An async executor that is integrated with the platform's event loop. See the executor module for more information.,
The [gpui::test] macro provides a convenient way to write tests for your GPUI applications. Tests also have their own kind of context, a TestAppContext which provides ways of simulating common platform input. See app::test_context and test modules for more details.

Currently, the best way to learn about these APIs is to read the Zed source code, ask us about it at a fireside hack, or drop a question in the Zed Discord. We're working on improving the documentation, creating more examples, and will be publishing more guides to GPUI on our blog.