Changes in version 0.1.0 (2026-06-22)                  

First release. lstar is a uniform data model (L*) and a Zarr interchange
format for single-cell / spatial omics, with a shared C++ core (libstar)
and bindings in R, Python and C++.

Data model & store

  - Datasets of axes (labelled sets you index by) and fields (typed data
    over a tuple of axes, with a role / span / encoding / state /
    coverage / provenance).
  - Read / write .lstar.zarr stores (lstar_read, lstar_write),
    multi-chunk and gzip-compressed, byte-compatible with the Python and
    C++ readers.
  - Collections of heterogeneous samples (kind = "collection") —
    per-sample cells.<s>/genes.<s> axes over gene sets that may overlap,
    differ, or be disjoint, plus a union cells axis carrying the joint
    embedding / clustering / integration graph. Build one from any list
    of per-sample objects with collection_from().

Format converters (profiles)

  - Seurat (legacy v2 through v5; a split v5 assay is read as a
    collection, and a collection is written back as a split assay) —
    read_seurat / write_seurat. Cell-cell graphs round-trip as Graphs().
  - SingleCellExperiment — read_sce / write_sce.
  - Conos — write_conos (Conos → L*) and read_conos (L* → a live Conos),
    preserving the per-sample data and the joint graph / embedding /
    clustering.
  - The shared vocabulary keeps the common core (counts, data/X, pca +
    loadings, umap, labels, metadata) lossless across conversions; what
    a target cannot hold is recorded in dropped, never lost silently.

Performance

  - Streamed, multi-threaded (OpenMP) per-gene/per-cell reductions over
    the compiled core (lstar_read_block, lstar_stream_col_sum_by_group,
    col_sum_by_group), with bounded memory and thread-invariant results.