Overview
Internally, the DataLoader
trait takes care of loading files into the Viewer and/or SDK.
There are 3 broad kinds of DataLoader
s: builtin, external and custom.
External and custom are the two ways of extending the file loading system that we'll describe below.
When a user attempts to open a file in the Viewer/SDK, all known DataLoader
s are notified of the path to be opened, unconditionally.
This gives DataLoader
s maximum flexibility to decide what files they are interested in, as opposed to e.g. only being able to look at a file's extension.
Once notified, a DataLoader
can return a DataLoaderError::Incompatible
error to indicate that it doesn't support a given file type.
If, and only if, all loaders known to the Viewer/SDK return an Incompatible
error code, then an error message is shown to the user indicating that this file type is not (yet) supported.
In these instances of unsupported files, we expose two ways of implementing and registering your DataLoader
s, explained below.
External data-loaders external-dataloaders
The easiest way to create your own DataLoader
is by implementing what we call an "external loader": a stand alone executable written in any language that the Rerun SDK ships for. Any executable on your $PATH
with a name that starts with rerun-loader-
will be treated as a DataLoader
.
This executable takes a file path as a command line argument and outputs Rerun logs on stdout
.
It will be called by the Rerun Viewer/SDK when the user opens a file, and be passed the path to that file.
From there, it can log data as usual, using the stdout
logging sink.
The Rerun Viewer/SDK will then automatically load the data streamed to the external loader's standard output.
Like any other DataLoader
, an external loader will be notified of all file openings, unconditionally.
To indicate that it does not support a given file, the loader has to exit with a dedicated status code.
When the Viewer and/or SDK executes an external loader, it will pass to it a set of recommended settings in the form of CLI parameters (in addition to the file path to be loaded, which is passed as the one and only positional argument):
--application-id <application_id>
The recommended
ApplicationId
to log the data to.--opened-application-id <opened_application_id>
(optional)The
ApplicationId
that is currently opened in the viewer, if any.--recording-id <store_id>
The recommended
RecordingId
to log the data to.Log data to this recording if you want it to appear in a new recording shared by all data-loaders for the current loading session.
--opened-recording-id <opened_store_id>
(optional)The
RecordingId
that is currently opened in the viewer, if any.--entity-path-prefix <entity_path_prefix>
(optional)Recommended prefix to prepend to all entity paths.
--static
(optional)The data is expected to be logged as static.
--time <timeline1>=<time1> <timeline2>=<time2> …
(optional)The data is expected to be logged at these specific temporal timestamps.
The timestamps are expected to be in nanoseconds: use
rr.set_time_nanos
(Python) /RecordingStream::set_time_nanos
(C++, Rust) appropriately.--sequence <timeline1>=<seq1> <timeline2>=<seq2> …
(optional)The data is expected to be logged at these specific sequence timestamps.
Check out our examples for C++, Python and Rust that cover every steps in details.
Custom Rust data-loaders custom-rust-dataloaders
Another Rust-specific approach is to implement the DataLoader
trait yourself and register it in the Rerun Viewer/SDK.
To do so, you'll need to import rerun
as a library, register your DataLoader
and then start the Viewer/SDK from code.
Check out our example that cover all these steps in details.