Merge branch 'main' into fork/tfoldi/feat/mapbox-view

Cargo.lock

@@ -2412,8 +2412,7 @@ dependencies = [
 [[package]]
 name = "ewebsock"
 version = "0.7.0"
-source = "registry+https://github.com/rust-lang/crates.io-index"
-checksum = "735ef60c8cd338b55f972d66c95558a71298d6f8bce1e1347d4c95b082ab2c37"
+source = "git+https://github.com/rerun-io/ewebsock?rev=ac6552ecb70f058d81dd8fafaecd4b1daba24685#ac6552ecb70f058d81dd8fafaecd4b1daba24685"
 dependencies = [
  "document-features",
  "js-sys",

Cargo.toml

@@ -569,3 +569,6 @@ re_arrow2 = { git = "https://github.com/rerun-io/re_arrow2", rev = "e4717d6debc6
 
 # Commit on `main` branch of `re_mp4`
 re_mp4 = { git = "https://github.com/rerun-io/re_mp4", rev = "7d38361ee5b05f5a2b83a8029057c8a24d2e9023" }
+
+# Commit on `main` branch of `ewebsock`
+ewebsock = { git = "https://github.com/rerun-io/ewebsock", rev = "ac6552ecb70f058d81dd8fafaecd4b1daba24685" }

README.md

@@ -19,7 +19,7 @@ It's used in areas like robotics, spatial and embodied AI, generative media, ind
 Rerun is easy to use!
 Use the Rerun SDK (available for C++, Python and Rust) to log data like images, tensors, point clouds, and text.
 Logs are streamed to the Rerun Viewer for live visualization or to file for later use.
-You can also query the logged data through [our dataframe API](https://rerun.io/docs/content/howto/dataframe-api).
+You can also query the logged data through [our dataframe API](https://rerun.io/docs/howto/dataframe-api).
 
 [Get started](#getting-started) in minutes – no account needed.
 

crates/build/re_remote_store_types_builder/README.md

@@ -2,8 +2,8 @@
 
 Part of the [`rerun`](https://github.com/rerun-io/rerun) family of crates.
 
-[![Latest version](https://img.shields.io/crates/v/re_remote_store_types_builder.svg)](https://crates.io/crates/re_remote_store_types_builder)
-[![Documentation](https://docs.rs/re_remote_store_types_builder/badge.svg)](https://docs.rs/re_remote_store_types_builder)
+[![Latest version](https://img.shields.io/crates/v/re_remote_store_types_builder.svg)](https://crates.io/crates/re_remote_store_types_builder?speculative-link)
+[![Documentation](https://docs.rs/re_remote_store_types_builder/badge.svg)](https://docs.rs/re_remote_store_types_builder?speculative-link)
 ![MIT](https://img.shields.io/badge/license-MIT-blue.svg)
 ![Apache](https://img.shields.io/badge/license-Apache-blue.svg)
 

crates/store/re_remote_store_types/README.md

@@ -2,8 +2,8 @@
 
 Part of the [`rerun`](https://github.com/rerun-io/rerun) family of crates.
 
-[![Latest version](https://img.shields.io/crates/v/re_remote_store_types.svg)](https://crates.io/crates/re_remote_store_types)
-[![Documentation](https://docs.rs/re_remote_store_types/badge.svg)](https://docs.rs/re_remote_store_types)
+[![Latest version](https://img.shields.io/crates/v/re_remote_store_types.svg)](https://crates.io/crates/re_remote_store_types?speculative-link)
+[![Documentation](https://docs.rs/re_remote_store_types/badge.svg)](https://docs.rs/re_remote_store_types?speculative-link)
 ![MIT](https://img.shields.io/badge/license-MIT-blue.svg)
 ![Apache](https://img.shields.io/badge/license-Apache-blue.svg)
 

docs/content/concepts/static.md

@@ -45,7 +45,7 @@ Similarly, [coordinate systems](spaces-and-transforms.md) or [annotation context
 ### Memory savings
 
 When you store _temporal_ data in Rerun, it is always appended to the existing dataset: there is no such thing as overwriting temporal data. The dataset only grows, it never shrinks.
-To compensate for that, the Rerun viewer has a [garbage collection mechanism](../howto/limit-ram) that will drop the oldest data from the store when memory becomes scarce.
+To compensate for that, the Rerun viewer has a [garbage collection mechanism](../howto/visualization/limit-ram.md) that will drop the oldest data from the store when memory becomes scarce.
 
 For example, the following snippet stores 10 images at index `4` on the `frame` [timeline](timelines.md):
 
@@ -80,7 +80,7 @@ If you were to log the snippet above to a file (using e.g. `rr.save()`), you'd f
 
 If you wanted the recording file itself to only contain a single static value, you would need to either:
 * Stream the data to the viewer, and then save the recording directly out of the viewer using `Menu > Save recording` (or the equivalent palette command).
-* Manually recompact your recording using the [Rerun CLI](../reference/cli#rerun-rrd-compact) so that the data overwrite semantics can get appropriately applied, e.g.: `rerun rrd compact -o compacted.rrd myrecording.rrd`.
+* Manually recompact your recording using the [Rerun CLI](../reference/cli.md#rerun-rrd-compact) so that the data overwrite semantics can get appropriately applied, e.g.: `rerun rrd compact -o compacted.rrd myrecording.rrd`.
 
 
 ### In the viewer

docs/content/getting-started/data-out.md

@@ -3,13 +3,13 @@ title: Get data out of Rerun
 order: 450
 ---
 
-At its core, Rerun is a database. The viewer includes the [dataframe view](../reference/types/views/dataframe_view) to explore data in tabular form, and the SDK includes an API to export the data as dataframes from the recording. These features can be used, for example, to perform analysis on the data and send back the results to the original recording.
+At its core, Rerun is a database. The viewer includes the [dataframe view](../reference/types/views/dataframe_view.md) to explore data in tabular form, and the SDK includes an API to export the data as dataframes from the recording. These features can be used, for example, to perform analysis on the data and send back the results to the original recording.
 
 In this three-part guide, we explore such a workflow by implementing an "open jaw detector" on top of our [face tracking example](https://rerun.io/examples/video-image/face_tracking). This process is split into three steps:
 
-1. [Explore a recording with the dataframe view](data-out/explore-as-dataframe)
-2. [Export the dataframe](data-out/export-dataframe)
-3. [Analyze the data and send back the results](data-out/analyze-and-send)
+1. [Explore a recording with the dataframe view](data-out/explore-as-dataframe.md)
+2. [Export the dataframe](data-out/export-dataframe.md)
+3. [Analyze the data and send back the results](data-out/analyze-and-send.md)
 
 Note: this guide uses the popular [Pandas](https://pandas.pydata.org) dataframe package. The same concept however applies in the same way for alternative dataframe packages such as [Polars](https://pola.rs).
 

docs/content/howto/dataframe-api.md

@@ -0,0 +1,5 @@
+---
+title: Get data out of Rerun with code
+hidden: true
+redirect: howto/get-data-out
+---

docs/content/howto/embed-rerun-viewer.md

@@ -0,0 +1,5 @@
+---
+title: Embed a Rerun Viewer
+hidden: true
+redirect: howto/embed-web
+---

docs/content/howto/extend/custom-data.md

@@ -0,0 +1,5 @@
+---
+title: By logging custom data
+hidden: true
+redirect: howto/logging/custom-data
+---

docs/content/howto/extend/extend-ui.md

@@ -0,0 +1,5 @@
+---
+title: By implementing custom visualizations (Rust only)
+hidden: true
+redirect: howto/visualization/extend-ui
+---

docs/content/howto/fixed-window-plot.md

@@ -0,0 +1,5 @@
+---
+title: Create a fixed-window plot
+hidden: true
+redirect: howto/visualization/fixed-window-plot
+---

docs/content/howto/integrations/embed-notebooks.md

@@ -26,7 +26,7 @@ This installs both [rerun-sdk](https://pypi.org/project/rerun-sdk/) and [rerun-n
 When using the Rerun logging APIs, by default, the logged messages are buffered in-memory until
 you send them to a sink such as via `rr.connect()` or `rr.save()`.
 
-When using Rerun in a notebook, rather than using the other sinks, you have the option to use [`rr.notebook_show()`](https://ref.rerun.io/docs/python/stable/common/initialization_functions/#rerun.notebook_show). This method embeds the [web viewer](./embed-rerun-viewer.md) using the IPython `display` mechanism in the cell output, and sends the current recording data to it.
+When using Rerun in a notebook, rather than using the other sinks, you have the option to use [`rr.notebook_show()`](https://ref.rerun.io/docs/python/stable/common/initialization_functions/#rerun.notebook_show). This method embeds the [web viewer](./embed-web.md) using the IPython `display` mechanism in the cell output, and sends the current recording data to it.
 
 Once the viewer is open, any subsequent `rr.log()` calls will send their data directly to the viewer,
 without any intermediate buffering.
@@ -74,7 +74,7 @@ rr.notebook_show(width=400, height=400)
 
 ## Working with blueprints
 
-[Blueprints](./configure-viewer-through-code.md) can also be used with `notebook_show()` by providing a `blueprint`
+[Blueprints](../visualization/configure-viewer-through-code.md) can also be used with `notebook_show()` by providing a `blueprint`
 parameter.
 
 For example

docs/content/howto/integrations/ros2-nav-turtlebot.md

@@ -30,8 +30,8 @@ All of the code for this guide can be found on GitHub in
 
 Other relevant tutorials:
 
--   [Python SDK Tutorial](../getting-started/data-in/python.md)
--   [Viewer Walkthrough](../getting-started/navigating-the-viewer.md)
+-   [Python SDK Tutorial](../../getting-started/data-in/python.md)
+-   [Viewer Walkthrough](../../getting-started/navigating-the-viewer.md)
 
 ### ROS 2 & navigation
 
@@ -110,17 +110,17 @@ the environment.
 If you are familiar with the turtlebot nav example and rviz, this view will likely be familiar:
 
 -   `map/box` is a placeholder for the map. (This will eventually be a map: [#1531](https://github.com/rerun-io/rerun/issues/1531).)
--   `map/robot` is a transform representing the robot pose logged as a rigid [transform3d](../reference/types/archetypes/transform3d.md).
--   `map/robot/urdf` contains the `URDF` logged as a [mesh](../reference/types/archetypes/mesh3d.md).
--   `map/robot/scan` contains a `LaserScan` msg logged as a [linestrip3d](../reference/types/archetypes/line_strips3d.md). (This will eventually be a
+-   `map/robot` is a transform representing the robot pose logged as a rigid [transform3d](../../reference/types/archetypes/transform3d.md).
+-   `map/robot/urdf` contains the `URDF` logged as a [mesh](../../reference/types/archetypes/mesh3d.md).
+-   `map/robot/scan` contains a `LaserScan` msg logged as a [linestrip3d](../../reference/types/archetypes/line_strips3d.md). (This will eventually be a
     native type: [#1534](https://github.com/rerun-io/rerun/issues/1534).)
--   `map/robot/camera` contains a `CameraInfo` msg logged as a [pinhole](../reference/types/archetypes/pinhole.md) transform.
--   `map/robot/camera/img` contains an `Image` msg logged as an [image](../reference/types/archetypes/image.md).
--   `map/robot/camera/points` contains a `PointCloud2` msg logged as a [point3d](../reference/types/archetypes/points3d.md).
+-   `map/robot/camera` contains a `CameraInfo` msg logged as a [pinhole](../../reference/types/archetypes/pinhole.md) transform.
+-   `map/robot/camera/img` contains an `Image` msg logged as an [image](../../reference/types/archetypes/image.md).
+-   `map/robot/camera/points` contains a `PointCloud2` msg logged as a [point3d](../../reference/types/archetypes/points3d.md).
 -   `map/points` contains a second copy of `PointCloud2` with a different transform. (This is a workaround until Rerun
     has support for ROS-style fixed frames [#1522](https://github.com/rerun-io/rerun/issues/1522).)
--   `odometry/vel` is a plot of the linear velocity of the robot logged as a [scalar](../reference/types/archetypes/scalar.md).
--   `odometry/ang_vel` is a plot of the angular velocity of the robot logged as a [scalar](../reference/types/archetypes/scalar.md).
+-   `odometry/vel` is a plot of the linear velocity of the robot logged as a [scalar](../../reference/types/archetypes/scalar.md).
+-   `odometry/ang_vel` is a plot of the angular velocity of the robot logged as a [scalar](../../reference/types/archetypes/scalar.md).
 
 ## Code explanation
 
@@ -156,7 +156,7 @@ again.
 ### TF to rr.Transform3D
 
 Next, we need to map the [ROS TF2](https://docs.ros.org/en/humble/Concepts/About-Tf2.html) transforms to the
-corresponding [Rerun Transforms](../concepts/spaces-and-transforms.md#space-transformations).
+corresponding [Rerun Transforms](../../concepts/spaces-and-transforms.md#space-transformations).
 
 In Rerun, each path represents a coordinate frame, so we need to decide which TF frame each path will
 correspond to. In general, this is the frame_id of the sensor data that will be logged to that

docs/content/howto/limit-ram.md

@@ -0,0 +1,5 @@
+---
+title: Limit memory usage
+hidden: true
+redirect: howto/visualization/limit-ram
+---

docs/content/howto/logging/send-columns.md

@@ -9,7 +9,7 @@ Sometimes you want to send big chunks of data to Rerun efficiently. To do so, yo
 
 `send_columns` lets you efficiently log the state of an entity over time, logging multiple time and component columns in one call.
 
-In contrast to the `log` function, `send_columns` does NOT add any other timelines to the data. Neither the built-in timelines `log_time` and `log_tick`, nor any [user timelines](../concepts/timelines.md). Only the timelines explicitly included in the call to `send_columns` will be included.
+In contrast to the `log` function, `send_columns` does NOT add any other timelines to the data. Neither the built-in timelines `log_time` and `log_tick`, nor any [user timelines](../../concepts/timelines.md). Only the timelines explicitly included in the call to `send_columns` will be included.
 
 API docs of `send_columns`:
 * [🌊 C++](https://ref.rerun.io/docs/cpp/stable/classrerun_1_1RecordingStream.html#ad17571d51185ce2fc2fc2f5c3070ad65)

docs/content/howto/logging/shared-recordings.md

@@ -5,7 +5,7 @@ order: 100
 
 A common need is to log data from multiple processes and then visualize all of that data as part of a single shared recording.
 
-Rerun has the notion of a [Recording ID](../concepts/apps-and-recordings.md) for that: any recorded datasets that share the same Recording ID will be visualized as one shared dataset.
+Rerun has the notion of a [Recording ID](../../concepts/apps-and-recordings.md) for that: any recorded datasets that share the same Recording ID will be visualized as one shared dataset.
 
 The data can be logged from any number of processes, whether they run on the same machine or not, or implemented in different programming languages.
 All that matter is that they share the same Recording ID.

docs/content/howto/notebook.md

@@ -0,0 +1,5 @@
+---
+title: Embed Rerun in notebooks
+hidden: true
+redirect: howto/integrations/embed-notebook
+---

docs/content/howto/ros2-nav-turtlebot.md

@@ -0,0 +1,5 @@
+---
+title: Use Rerun with ROS 2
+hidden: true
+redirect: howto/integrations/ros2-nav-turtlebot
+---

docs/content/howto/send_columns.md

@@ -0,0 +1,5 @@
+---
+title: Efficiently log time series data using `send_columns`
+hidden: true
+redirect: howto/logging/send-columns
+---

docs/content/howto/shared-recordings.md

@@ -0,0 +1,5 @@
+---
+title: Share recordings across multiple processes
+hidden: true
+redirect: howto/logging/shared-recordings
+---

docs/content/howto/short-lived-entities.md

@@ -0,0 +1,5 @@
+---
+title: Clear out already logged data
+hidden: true
+redirect: howto/logging/clears
+---

docs/content/howto/using-native-loggers.md

@@ -0,0 +1,19 @@
+---
+title: Integrate Rerun with native loggers
+order: 700
+description: How to use the Rerun SDK as a native logger for the host language
+---
+
+The Rerun SDK implements the native logging interfaces of its supported host languages, allowing you to transparently stream text logs logged with the native APIs into the Rerun Viewer.
+
+The details of how to achieve that vary language by language, see the snippets below.
+
+snippet: archetypes/text_log_integration
+
+<picture>
+  <img src="https://static.rerun.io/text_log_integration/9737d0c986325802a9885499d6fcc773b1736488/full.png" alt="">
+  <source media="(max-width: 480px)" srcset="https://static.rerun.io/text_log_integration/9737d0c986325802a9885499d6fcc773b1736488/480w.png">
+  <source media="(max-width: 768px)" srcset="https://static.rerun.io/text_log_integration/9737d0c986325802a9885499d6fcc773b1736488/768w.png">
+  <source media="(max-width: 1024px)" srcset="https://static.rerun.io/text_log_integration/9737d0c986325802a9885499d6fcc773b1736488/1024w.png">
+  <source media="(max-width: 1200px)" srcset="https://static.rerun.io/text_log_integration/9737d0c986325802a9885499d6fcc773b1736488/1200w.png">
+</picture>

docs/content/howto/visualization/configure-viewer-through-code.md

@@ -3,7 +3,7 @@ title: Configure the Viewer through code
 order: 100
 ---
 
-As of Rerun 0.15, the state of the [blueprint](../reference/viewer/blueprint.md) can be directly manipulated using the
+As of Rerun 0.15, the state of the [blueprint](../../reference/viewer/blueprint.md) can be directly manipulated using the
 Rerun SDK.
 
 In the initial 0.15 release, the APIs are still somewhat limited and only available in the Python SDK.
@@ -139,7 +139,7 @@ Because the data in the space-view is relative to the `origin`, the `origin` wil
 in the blueprint tree, with all entities under the origin shown using relative paths.
 
 For Spatial views such as `Spatial2DView` and `Spatial3DView`, the `origin` plays an additional role with respect
-to data transforms. All data in the view will be transformed to the `origin` space before being displayed. See [Spaces and Transforms](../concepts/spaces-and-transforms.md) for more information.
+to data transforms. All data in the view will be transformed to the `origin` space before being displayed. See [Spaces and Transforms](../../concepts/spaces-and-transforms.md) for more information.
 
 For example:
 
@@ -155,7 +155,7 @@ rrb.Blueprint(
 ### `contents`
 
 If you need to further modify the contents of a space view, you can use the `contents` parameter. This parameter is
-a list of [entity query expressions](../reference/) that are either included or excluded from the
+a list of [entity query expressions](../../reference/) that are either included or excluded from the
 view.
 
 Each entity expressions starts with "+" for inclusion or "-" for an exclusion. The expressions can either be specific entity paths, or may end in a wildcard `/**` to include all entities under a specific subtree.

docs/content/howto/visualization/fixed-window-plot.md

@@ -3,7 +3,7 @@ title: Visualize fixed-window plots
 order: 200
 ---
 
-As of Rerun 0.16, the [TimeSeriesView](../reference/types/views/time_series_view.md) now supports direct
+As of Rerun 0.16, the [TimeSeriesView](../../reference/types/views/time_series_view.md) now supports direct
 manipulation of the visible time range. This allows you to create a plot that only shows a fixed window of data.
 
 ## VisibleTimeRange