Columnar API

rerun

class TimeNanosColumn

Bases: TimeColumnLike

A column of time values that are represented as integer nanoseconds.

Columnar equivalent to rerun.set_time_nanos.

def __init__(timeline, times)

Create a column of integer nanoseconds time values.

PARAMETER	DESCRIPTION
timeline	The name of the timeline. TYPE: str
times	An iterable of integer nanosecond time values. TYPE: Iterable[int]

def timeline_name()

Returns the name of the timeline.

class TimeSecondsColumn

Bases: TimeColumnLike

A column of time values that are represented as floating point seconds.

Columnar equivalent to rerun.set_time_seconds.

def __init__(timeline, times)

Create a column of floating point seconds time values.

PARAMETER	DESCRIPTION
timeline	The name of the timeline. TYPE: str
times	An iterable of floating point second time values. TYPE: Iterable[float]

def timeline_name()

Returns the name of the timeline.

class TimeSequenceColumn

Bases: TimeColumnLike

A column of time values that are represented as an integer sequence.

Columnar equivalent to rerun.set_time_sequence.

def __init__(timeline, times)

Create a column of integer sequence time values.

PARAMETER	DESCRIPTION
timeline	The name of the timeline. TYPE: str
times	An iterable of integer time values. TYPE: Iterable[int]

def timeline_name()

Returns the name of the timeline.

def send_columns(entity_path, times, components, recording=None, strict=None)

Send columnar data to Rerun.

Unlike the regular log API, which is row-oriented, this API lets you submit the data in a columnar form. Each TimeColumnLike and ComponentColumnLike object represents a column of data that will be sent to Rerun. The lengths of all of these columns must match, and all data that shares the same index across the different columns will act as a single logical row, equivalent to a single call to rr.log().

Note that this API ignores any stateful time set on the log stream via the rerun.set_time_* APIs. Furthermore, this will not inject the default timelines log_tick and log_time timeline columns.

When using a regular ComponentBatch input, the batch data will map to single-valued component instances at each timepoint.

For example, scalars would be logged as:

times = np.arange(0, 64)
scalars = np.sin(times / 10.0)

rr.send_columns(
    "scalars",
    times=[rr.TimeSequenceColumn("step", times)],
    components=[rr.components.ScalarBatch(scalars)],
)

In the viewer this will show up as 64 individual scalar values, one for each timepoint.

However, it is still possible to send temporal batches of batch data. To do this the source data first must be created as a single contiguous batch, and can then be partitioned using the .partition() helper on the ComponentBatch objects.

For example, to log 5 batches of 20 point clouds, first create a batch of 100 (20 * 5) point clouds and then partition it into 5 batches of 20 point clouds:

times = np.arange(0, 5)
positions = rng.uniform(-5, 5, size=[100, 3])

rr.send_columns(
    "points",
    times=[rr.TimeSequenceColumn("step", times)],
    components=[
        rr.Points3D.indicator(),
        rr.components.Position3DBatch(positions).partition([20, 20, 20, 20, 20]),
    ],
)

In the viewer this will show up as 5 individual point clouds, one for each timepoint.

PARAMETER	DESCRIPTION
entity_path	Path to the entity in the space hierarchy. See https://www.rerun.io/docs/concepts/entity-path for more on entity paths. TYPE: str
times	The time values of this batch of data. Each TimeColumnLike object represents a single column of timestamps. Generally, you should use one of the provided classes: TimeSequenceColumn, TimeSecondsColumn, or TimeNanosColumn. TYPE: Iterable[TimeColumnLike]
components	The columns of components to log. Each object represents a single column of data. If a batch of components is passed, it will be partitioned with one element per timepoint. In order to send multiple components per time value, explicitly create a ComponentColumn either by constructing it directly, or by calling the .partition() method on a ComponentBatch type. TYPE: Iterable[ComponentBatchLike]
recording	Specifies the rerun.RecordingStream to use. If left unspecified, defaults to the current active data recording, if there is one. See also: rerun.init, rerun.set_global_data_recording. TYPE: RecordingStream | None DEFAULT: None
strict	If True, raise exceptions on non-loggable data. If False, warn on non-loggable data. if None, use the global default from rerun.strict_mode() TYPE: bool | None DEFAULT: None