Package: h5lite 2.1.1.1

Daniel P. Smith

h5lite: Simplified 'HDF5' Interface

A user-friendly interface for the Hierarchical Data Format 5 ('HDF5') library designed to "just work." It bundles the necessary system libraries to ensure easy installation on all platforms. Features smart defaults that automatically map R objects (vectors, matrices, data frames) to efficient 'HDF5' types, removing the need to manage low-level details like dataspaces or property lists. Uses the 'HDF5' library developed by The HDF Group <https://www.hdfgroup.org/>.

Authors:Daniel P. Smith [aut, cre], Alkek Center for Metagenomics and Microbiome Research [cph, fnd]

h5lite_2.1.1.1.tar.gz
h5lite_2.1.1.1.zip(r-4.7)h5lite_2.1.1.1.zip(r-4.6)h5lite_2.1.1.1.zip(r-4.5)
h5lite_2.1.1.1.tgz(r-4.6-x86_64)h5lite_2.1.1.1.tgz(r-4.6-arm64)h5lite_2.1.1.1.tgz(r-4.5-x86_64)h5lite_2.1.1.1.tgz(r-4.5-arm64)
h5lite_2.1.1.1.tar.gz(r-4.7-arm64)h5lite_2.1.1.1.tar.gz(r-4.7-x86_64)h5lite_2.1.1.1.tar.gz(r-4.6-arm64)h5lite_2.1.1.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
h5lite/json (API)

# Install 'h5lite' in R:
install.packages('h5lite', repos = c('https://cmmr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cmmr/h5lite/issues

Pkgdown/docs site:https://cmmr.github.io

On CRAN:

Conda:

6.62 score 3 stars 14 scripts 521 downloads 20 exports 1 dependencies

Last updated from:90fc2d8084. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK329
linux-devel-x86_64OK291
source / vignettesOK344
linux-release-arm64OK295
linux-release-x86_64OK304
macos-release-arm64OK95
macos-release-x86_64OK193
macos-oldrel-arm64OK98
macos-oldrel-x86_64OK182
windows-develOK107
windows-releaseOK105
windows-oldrelOK98
wasm-releaseFAIL320

Exports:h5_attr_namesh5_classh5_compressionh5_create_fileh5_create_grouph5_deleteh5_dimh5_existsh5_inspecth5_is_dataseth5_is_grouph5_lengthh5_lsh5_moveh5_namesh5_openh5_readh5_strh5_typeofh5_write

Dependencies:hdf5lib

Organization
The Hierarchical Model | Creating Groups | Implicit Creation (Recommended) | Explicit Creation | Using Lists as Groups | Inspecting Structure | Moving and Renaming | Deleting Objects
Rendered fromorganization.Rmdusingknitr::rmarkdown

Last update: 2026-04-15
Started: 2026-04-15

Compression
The compress Argument and h5_compression() | Valid Compression Strings Reference | Choosing a Codec: Modern vs. Legacy | 1. Blosc2 (Highly Recommended) | 2. Standalone Modern Codecs | 3. Gzip (The Universal Standard) | 4. Legacy Codecs (Obsolete or Niche) | Lossy Compression: ZFP and Scale-Offset | ZFP (Floating-Point & Integer) | Scale-Offset (Integer Packing & Float Rounding) | Filter Interactions & Invalid Combinations | Tuning Chunk Size | Evaluating Results with h5_inspect()
Rendered fromcompression.Rmdusingknitr::rmarkdown

Last update: 2026-03-26
Started: 2026-03-26

Get Started with h5lite
HDF5 for R Users | Basic Usage | Writing Numeric Data | Reading Data | Data Type Mapping | Complex Data Structures | Lists as Groups | Data Frames as Compound Datasets | Attributes | File Inspection
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Last update: 2026-03-26
Started: 2025-11-14

Partial Reading
Why Partial Reading Matters | The HDF5 Storage Model: Chunking and Compression | Designing for Partial Reading | Memory Efficiency of start and count | The "Smart" start Parameter | Single-Value Examples | Dimension Simplification (Exact vs. Range Indexing) | Drilling Down: Multi-Value start and N-Dimensional Arrays
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Last update: 2026-03-03
Started: 2026-03-03

Atomic Vectors
Basic Usage | Scalars vs. 1D Arrays | Numeric and Logical Data | Automatic Type Selection | Handling Missing Values (NA) | Forcing Specific Types | Character Vectors (Strings) | Variable-Length | Fixed-Length | Compression | 64-bit Integers
Rendered fromatomic-vectors.Rmdusingknitr::rmarkdown

Last update: 2026-03-02
Started: 2025-11-18

Data Types & Compression
Supported Data Types | Dimensions: Scalars, Vectors, and Arrays | Numeric Data | 64-bit Integers (integer64) | Double (Numeric) Data | Logical Data | Character Data | Variable-Length: | Fixed-Length: | Dates and Times (POSIXt) | Complex Data | Raw Data | Factors | Lists | Data Frames | NULL | Compression | The Shuffle Filter
Rendered fromdata-types.Rmdusingknitr::rmarkdown

Last update: 2026-03-02
Started: 2026-01-13

Matrices and Arrays
Writing Matrices | Writing N-Dimensional Arrays | Dimension Names (dimnames) | Dimension Ordering (Row-Major vs. Column-Major) | How h5lite handles it | Interoperability with Python | Compression and Chunking | Partial I/O
Rendered frommatrices.Rmdusingknitr::rmarkdown

Last update: 2026-03-02
Started: 2025-11-18

Attributes In-Depth
Writing Attributes | 1. Explicit Writing | 2. Implicit Writing (R Attributes) | Reading Attributes | 1. Accessing Specific Attributes | 2. Reading with the Dataset | Managing Attributes | Listing Attributes | Deleting Attributes | Important Limitations | 1. No Dimension Scales (Loss of Names) | 2. No Attributes on Attributes (Nesting) | Controlling Attribute Types | Customizing Storage Type | Customizing Read Type | Special Note: Dimensions
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Last update: 2026-01-13
Started: 2025-11-18

Data Frames
Basic Usage | Customizing Column Types | Row Names
Rendered fromdata-frames.Rmdusingknitr::rmarkdown

Last update: 2026-01-13
Started: 2025-11-18

Object-Oriented Interface
Basic Usage | Navigation and Working Directories | Reference Semantics | Closing the Handle | Method Reference
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Last update: 2026-01-13
Started: 2025-12-09

Parallel Processing
The Safety Rule: Always Lock | Recommended Strategy: File Locking with flock
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Last update: 2026-01-13
Started: 2025-11-18