When should you reach for the advanced tools? | What will the execution plan do? | How do you let delarr choose a chunk size? | How do you compute several summaries in one pass? | How do you work block-by-block? | How do delayed matrix products fit into a pipeline? | How do you stream a transformed matrix to disk? | How do you use shared-memory workers? | How do you profile a candidate pipeline? | Where should you go after this?
Package: delarr 0.1.0
Bradley Buchsbaum
delarr: Lazy Delayed Arrays with Fused Execution
Provides a lightweight delayed array abstraction for lazy, fused evaluation of multi-dimensional numeric data. Compared with Bioconductor's 'DelayedArray', it offers a small S3 API with tidy-friendly verbs, chunked materialisation, and optional backends for HDF5, memory mapping, and shared-memory parallelism. Expression trees are optimised before streaming evaluation, and results can be written directly to disk without fully materialising arrays in memory.
Authors:
delarr_0.1.0.tar.gz
delarr_0.1.0.tar.gz(r-4.7-any)delarr_0.1.0.tar.gz(r-4.6-any)
delarr_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
delarr/json (API)
| # Install 'delarr' in R: |
| install.packages('delarr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bbuchsbaum/delarr/issues
Pkgdown/docs site:https://bbuchsbaum.github.io
Last updated from:434d861666. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 200 | ||
| source / vignettes | OK | 167 | ||
| linux-release-x86_64 | OK | 175 | ||
| wasm-release | OK | 113 |
Exports:block_applycollectcollect_shardcolMeans2d_apermd_centerd_detrendd_mapd_map2d_matmuld_reduced_reduce_manyd_scaled_transposed_whered_zscoredelarrdelarr_backenddelarr_hdf5delarr_memdelarr_mmapdelarr_seeddelarr_seed_nddelarr_shardexplainhdf5_writeroptimize_delarrprofile_collectread_hdf5rowMeans2shard_writerwrite_hdf5
Dependencies:rlang
Advanced Chunking and Backends in delarr
Last update: 2026-06-30
Started: 2026-06-30
Getting Started with delarr
What problem does delarr solve? | What does a lazy pipeline look like? | How do row and column vectors broadcast? | How do you stream a result to HDF5? | How do you wrap your own storage layer? | Where should you go next?
Last update: 2026-06-30
Started: 2026-06-30
