SDK reference | Docs

Client

Python

rayform.Client(api_key=None, base_url=None, cache_dir=None, cache_max_gb=200, offline=False, timeout_s=60)

The entry point. Resource namespaces hang off it: client.sessions, client.segments, client.slices, client.exports, client.assets. List methods return lazy iterators that fetch pages as you go.

Sessions

`client.sessions.upload`

Python

client.sessions.upload(path, *, site, device=None, notes=None, part_size=64 * 2**20, wait=False, timeout=None) -> Session

Uploads a file, resuming if an earlier attempt was interrupted, and completes the session. With wait=True it blocks until processing finishes and raises ProcessingError if the session fails.

`client.sessions.get`, `list`, `delete`

Python

client.sessions.get(id) -> Session
client.sessions.list(site=None, status=None) -> Iterator[Session]
client.sessions.delete(id) -> None

`Session`

Member	Type	Description
`id`, `site`, `status`	`str`	As in the session object
`issues`	`list[Issue]`	Problems found while processing
`segments()`	`list[Segment]`	Segments produced from this session
`wait(timeout=None)`	`Session`	Block until `processed` or `failed`
`refresh()`	`Session`	Re-read from the API

Segments

`client.segments.search`

Python

client.segments.search(
    *, site=None, event=None, object=None, text=None, near=None, context=None,
    recorded=None, quality_min=None, has_channels=None, session=None,
) -> SegmentResults

Arguments accept a value or a list. SegmentResults is iterable, sliceable, and has total.

`client.segments.get`

Python

client.segments.get(id, version=None) -> Segment

`Segment`

Member	Returns	Description
`id`, `version`, `session`, `site`	`str`	Identifiers
`t0_ns`, `t1_ns`, `duration_s`	`int`, `int`, `float`	Time window
`events()`	`pyarrow.Table`	Interaction events, time-ordered
`entities()`	`list[Entity]`	People, objects and robots
`channel(name, t0_ns=None, t1_ns=None, frame="rayform")`	`pyarrow.Table`	One channel's samples
`frames(camera, every=1)`	`Iterator[Frame]`	Decoded images with timestamps
`scene_at(t_ns)`	`Scene`	The scene with moving objects posed at `t_ns`
`quality`, `context`	`dict`	Scores and labels

Scenes

`Scene`

Member	Returns	Description
`splats`	`dict[str, numpy.ndarray]`	`means`, `scales`, `quats` (wxyz), `opacities`, `sh`
`collision_mesh()`	`trimesh.Trimesh`	Requires `trimesh`
`to_usd(path)`	`None`	Write OpenUSD for Isaac Sim (`rayform[usd]`)
`to_mjcf(dir)`	`None`	Write MJCF for MuJoCo (`rayform[mujoco]`)

Slices

Python

client.slices.create(*, query=None, segments=None, exclude=None, name=None) -> Slice
client.slices.get(id) -> Slice
client.slices.list(name=None) -> Iterator[Slice]

`Slice`

Member	Returns	Description
`id`, `hash`, `name`	`str`	Identifiers
`segment_count`, `duration_s`	`int`, `float`	Size
`segments()`	`Iterator[Segment]`	Exact versions in the slice
`pull(workers=8)`	`None`	Download everything into the cache

Exports

Python

client.exports.create(slice, *, format, options=None, destination=None) -> Export
client.exports.get(id) -> Export

`Export`

Member	Returns	Description
`status`, `progress`	`str`, `float`	State and fraction done
`wait(timeout=None)`	`Export`	Block until finished; raises `ExportError` on failure
`files()`	`Iterator[ExportFile]`	Paths, sizes and signed URLs
`download(dir)`	`None`	Download files kept in Rayform storage

Assets

Python

client.assets.get(id) -> Asset             # metadata and a signed URL
client.assets.load(id) -> dict | bytes     # decoded content, verified against the ID

PyTorch

`rayform.torch.EpisodeDataset`

Python

rayform.torch.EpisodeDataset(
    slice, *, obs, action=None, fps=None, horizon=1, frame="rayform",
    quat_order="wxyz", image_size=None, transform=None, seed=0,
)

A map-style torch.utils.data.Dataset. See Training with PyTorch for the sample layout. set_epoch(epoch) fixes the order for distributed training.

Visualisation

`rayform.rerun.show`

Python

rayform.rerun.show(segment, *, channels=None, with_scene=True, spawn=True)

Logs a segment's cameras, poses, events and scene to the Rerun viewer.