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Port details

filesystems/py-kerchunk 0.2.10

Functions to make reference descriptions for ReferenceFileSystem

Port info

Maintainer
sunpoet@FreeBSD.org
Packages
latest: 0.2.10
Upstream
up to date
Last update
to 0.2.10 · 3c78a09f62
Quarterly
2026Q4: 0.2.10
WWW
https://fsspec.github.io/kerchunk/
Links
cgit · VuXML

Install

Package
# pkg install py312-kerchunk
installs 0.2.10 from latest; from quarterly (2026Q4) 0.2.10
Port
# cd /usr/ports/filesystems/py-kerchunk && make install clean
# make -C /usr/ports/filesystems/py-kerchunk config  # change options first
Size
147 KiB download · 708 KiB installed
Depends on
devel/py-ujson 6.0.0, devel/py-zarr 3.4.1, filesystems/py-fsspec 2026.9.0, lang/python312 3.12.15, math/py-numpy 2.4.6_1,1, misc/py-numcodecs 0.17.1
License
MIT
Options
0 of 5 on in the package
Show the 5 options that are off
CFTIME FITS GRIB2 HDF NETCDF3

Packages by version and architecture

latest

FreeBSD versionamd64aarch64i386
FreeBSD 160.2.100.2.10–
FreeBSD 150.2.100.2.10–
FreeBSD 140.2.100.2.100.2.10

quarterly (2026Q4)

FreeBSD versionamd64aarch64i386
FreeBSD 150.2.100.2.10–
FreeBSD 140.2.100.2.100.2.10

version as in the ports tree (latest) or the most common one (quarterly) · different version · ✗ not built · – no packages for this platform. Package sets that have not been rebuilt for 60 days are left out.

Unaddressed and VuXML only (0)

No unaddressed CVE and nothing reported by pkg audit for the packaged version 0.2.10.

Fixed (0)

No VuXML entries for this package.

Problem reports (0) · open in Bugzilla, most recently changed first

None.

Commits (7)

Po-Chuan Hsieh (sunpoet) · 0.2.10
filesystems/py-kerchunk: Update to 0.2.10

Changes:	https://github.com/fsspec/kerchunk/commits/main
3c78a09f62
Po-Chuan Hsieh (sunpoet) · 0.2.7_2
*/py-*: Update version requirement of *_DEPENDS
01291f5d60
Max Brazhnikov (makc) · 0.2.7_2
*/*: bump PORTREVISION after switching to NumPy 2.x
2bf3834a19
Max Brazhnikov (makc) · 0.2.7_1
*/*: Switch to NumPy 2.x

PR:		294328
Exp-run:	antoine
b0b4d9e1ea
Charlie Li (vishwin) · 0.2.7_1
math/py-numpy: switch all consumers to math/py-numpy1

...and bump PORTREVISIONs of consumers with hard RUN_DEPENDS

PR: 281470
d4bd5ba72e
Po-Chuan Hsieh (sunpoet) · 0.2.7
filesystems/py-kerchunk: Add CFTIME, FITS, GRIB2, HDF and NETCDF3 options
8f0f5b7ca1
Po-Chuan Hsieh (sunpoet) · 0.2.7
filesystems/py-kerchunk: Add py-kerchunk 0.2.7

Kerchunk is a library that provides a unified way to represent a variety of
chunked, compressed data formats (e.g. NetCDF, HDF5, GRIB), allowing efficient
access to the data from traditional file systems or cloud object storage. It
also provides a flexible way to create virtual datasets from multiple files. It
does this by extracting the byte ranges, compression information and other
information about the data and storing this metadata in a new, separate object.
This means that you can create a virtual aggregate dataset over potentially many
source files, for efficient, parallel and cloud-friendly in-situ access without
having to copy or translate the originals. It is a gateway to in-the-cloud
massive data processing while the data providers still insist on using legacy
formats for archival storage.

We provide the following things:
- completely serverless architecture
- metadata consolidation, so you can understand a many-file dataset (metadata
  plus physical storage) in a single read
- read from all of the storage backends supported by fsspec, including object
  storage (s3, gcs, abfs, alibaba), http, cloud user storage (dropbox, gdrive)
  and network protocols (ftp, ssh, hdfs, smb...)
- loading of various file types (currently netcdf4/HDF, grib2, tiff, fits,
  zarr), potentially heterogeneous within a single dataset, without a need to go
  via the specific driver (e.g., no need for h5py)
- asynchronous concurrent fetch of many data chunks in one go, amortizing the
  cost of latency
- parallel access with a library like zarr without any locks
- logical datasets viewing many (>~millions) data files, and direct
  access/subselection to them via coordinate indexing across an arbitrary number
  of dimensions
49cf560f18