Add `serve_grpc` API (#9447) * Closes https://github.com/rerun-io/rerun/issues/9404 This PR adds the `serve_grpc` API to all our SDKs, and the `--serve-grpc` option to the CLI. It can be used to spawn a gRPC server without requiring users to also spawn a Viewer. All of this is gated behind the `server` feature in both the CLI and our SDKs. ## Examples ### Connect a native Viewer to a gRPC server hosted by the SDK Host a gRPC server, log some data to it, and then wait for incoming connections:

Python

```python import time import numpy as np import rerun as rr rr.init("rerun_example_serve_grpc") rr.serve_grpc() SIZE = 10 pos_grid = np.meshgrid(*[np.linspace(-10, 10, SIZE)] * 3) positions = np.vstack([d.reshape(-1) for d in pos_grid]).T col_grid = np.meshgrid(*[np.linspace(0, 255, SIZE)] * 3) colors = np.vstack([c.reshape(-1) for c in col_grid]).astype(np.uint8).T rr.log("my_points", rr.Points3D(positions, colors=colors, radii=0.5)) # We have to explicitly wait here, otherwise the server will shutdown immediately. while True: try: time.sleep(1) except KeyboardInterrupt: break ```

C++

```cpp #include #include #include #include using rerun::demo::grid3d; int main() { // Create a new `RecordingStream` which sends data over gRPC to the viewer process. const auto rec = rerun::RecordingStream("rerun_example_serve_grpc_cpp"); // Try to spawn a new viewer instance. rec.serve_grpc().exit_on_failure(); // Create some data using the `grid` utility function. std::vector points = grid3d(-10.f, 10.f, 10); std::vector colors = grid3d(0, 255, 10); // Log the "my_points" entity with our data, using the `Points3D` archetype. rec.log("my_points", rerun::Points3D(points).with_colors(colors).with_radii({0.5f})); // We have to explicitly wait here, otherwise the server will shutdown immediately. while (true) { std::this_thread::sleep_for(std::chrono::milliseconds(1000)); } } ```

Rust

```rust use rerun::{demo_util::grid, external::glam}; fn main() -> Result<(), Box> { let rec = rerun::RecordingStreamBuilder::new("rerun_example_serve_grpc_rs") .serve_grpc()?; let points = grid(glam::Vec3::splat(-10.0), glam::Vec3::splat(10.0), 10); let colors = grid(glam::Vec3::ZERO, glam::Vec3::splat(255.0), 10) .map(|v| rerun::Color::from_rgb(v.x as u8, v.y as u8, v.z as u8)); rec.log( "my_points", &rerun::Points3D::new(points) .with_colors(colors) .with_radii([0.5]), )?; // We have to explicitly wait here, otherwise the server will shutdown immediately. loop { std::thread::sleep(std::time::Duration::from_secs(1)); } } ```

Then connect to the server: ``` rerun --connect ``` ### Connect a native Viewer to a gRPC server hosted by the CLI, with data supplied by the Python SDK First, start the gRPC server: ``` rerun --serve-grpc ``` Then, log some data to it: ```python import numpy as np import rerun as rr rr.init("rerun_example_serve_grpc") rr.connect_grpc() SIZE = 10 pos_grid = np.meshgrid(*[np.linspace(-10, 10, SIZE)] * 3) positions = np.vstack([d.reshape(-1) for d in pos_grid]).T col_grid = np.meshgrid(*[np.linspace(0, 255, SIZE)] * 3) colors = np.vstack([c.reshape(-1) for c in col_grid]).astype(np.uint8).T rr.log("my_points", rr.Points3D(positions, colors=colors, radii=0.5)) ``` Finally, connect to the server from a native Viewer: ``` rerun --connect ``` --------- Co-authored-by: Andreas Reich Co-authored-by: Emil Ernerfeldt

Provide API to spawn a gRPC server #9404

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