cf-python

A CF-compliant Earth Science data analysis library.
https://github.com/ncas-cms/cf-python

Category: Climate Change
Sub Category: Climate Data Standards

Keywords

cf cfdm cfunits data-analysis earth-science metadata netcdf pp python um

Keywords from Contributors

climate earth-system-model data-compression atmospheric-science ocean aggregation ugrid zarr archival hydrology

Last synced: about 22 hours ago
JSON representation

Repository metadata

A CF-compliant Earth Science data analysis library

Host: GitHub
URL: https://github.com/ncas-cms/cf-python
Owner: NCAS-CMS
License: mit
Created: 2019-09-13T08:57:37.000Z (over 6 years ago)
Default Branch: main
Last Pushed: 2025-10-24T13:44:45.000Z (2 months ago)
Last Synced: 2025-10-24T15:34:13.047Z (2 months ago)
Topics: cf, cfdm, cfunits, data-analysis, earth-science, metadata, netcdf, pp, python, um
Language: Python
Homepage: http://ncas-cms.github.io/cf-python
Size: 143 MB
Stars: 144
Watchers: 3
Forks: 23
Open Issues: 118
Releases: 22
Metadata Files:
- Readme: README.md
- Changelog: Changelog.rst
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md

cf-python

The Python cf package is an Earth Science data analysis library that
is built on a complete implementation of the CF data model.

References

Dask

From version 3.14.0 the cf package uses
Dask for all of its data manipulations.

Documentation

http://ncas-cms.github.io/cf-python

Installation

http://ncas-cms.github.io/cf-python/installation.html

Cheat Sheet

https://ncas-cms.github.io/cf-python/cheat_sheet.html

Recipes

https://ncas-cms.github.io/cf-python/recipes

Tutorial

https://ncas-cms.github.io/cf-python/tutorial.html

Functionality

The cf package implements the CF data
model
for its internal data structures and so is able to process any
CF-compliant dataset. It is not strict about CF-compliance, however,
so that partially conformant datasets may be ingested from existing
datasets and written to new datasets. This is so that datasets which
are partially conformant may nonetheless be modified in memory.

A simple example of reading a field construct from a file and
inspecting it:

>>> import cf
>>> f = cf.read('file.nc')
>>> print(f[0])
Field: air_temperature (ncvar%tas)
----------------------------------
Data            : air_temperature(time(12), latitude(64), longitude(128)) K
Cell methods    : time(12): mean (interval: 1.0 month)
Dimension coords: time(12) = [1991-11-16 00:00:00, ..., 1991-10-16 12:00:00] noleap
                : latitude(64) = [-87.8638, ..., 87.8638] degrees_north
                : longitude(128) = [0.0, ..., 357.1875] degrees_east
                : height(1) = [2.0] m

The cf package uses
Dask for all
of its array manipulation and can:

read field constructs from netCDF, CDL, Zarr, PP and UM datasets with a
choice of netCDF backends,and in local, http, and s3 locations,
create new field constructs in memory,
write and append field and domain constructs to netCDF datasets on disk,
read, create, and manipulate UGRID mesh topologies,
read, write, and create coordinates defined by geometry cells,
read netCDF and CDL datasets containing hierarchical groups,
inspect field constructs,
test whether two field constructs are the same,
modify field construct metadata and data,
create subspaces of field constructs,
write field constructs to netCDF datasets on disk,
incorporate, and create, metadata stored in external files,
read, write, and create data that have been compressed by convention
(i.e. ragged or gathered arrays, or coordinate arrays compressed by
subsampling), whilst presenting a view of the data in its
uncompressed form,
combine field constructs arithmetically,
manipulate field construct data by arithmetical and trigonometrical
operations,
perform weighted statistical collapses on field constructs,
including those with geometry cells and UGRID mesh topologies,
perform histogram, percentile and binning operations on field
constructs,
regrid structured grid, mesh and DSG field constructs with
(multi-)linear, nearest neighbour, first- and second-order
conservative and higher order patch recovery methods, including 3-d
regridding, and large-grid support,
apply convolution filters to field constructs,
create running means from field constructs,
apply differential operators to field constructs,
create derived quantities (such as relative vorticity).
read and write data that are quantized to eliminate false
precision.

Visualization

Powerful and flexible visualizations of cf field constructs,
designed to be produced and configured in as few lines of code as
possible, are available with the cf-plot
package, which needs to be
installed separately to the cf package.

Example outputs of cf-plot displaying selected aspects of cf field constructs

Command line utilities

During installation the cfa command line utility is also
installed, which

generates text descriptions of field constructs contained in files,
and
creates new datasets aggregated from existing files.

Tests

Tests are run from within the cf/test directory:

python run_tests.py

Owner metadata

Name: NCAS CMS
Login: NCAS-CMS
Email:
Kind: organization
Description: Useful tools to support NERC weather and climate research
Website: http://cms.ncas.ac.uk/
Location: UK
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/31280705?v=4
Repositories: 10
Last ynced at: 2023-03-02T02:05:18.504Z
Profile URL: https://github.com/NCAS-CMS

GitHub Events

Total

Create event: 3
Release event: 2
Issues event: 46
Watch event: 15
Issue comment event: 95
Push event: 46
Pull request event: 47
Pull request review comment event: 92
Pull request review event: 105
Fork event: 2

Last Year

Create event: 3
Release event: 2
Issues event: 44
Watch event: 15
Issue comment event: 85
Push event: 44
Pull request review comment event: 48
Pull request review event: 63
Pull request event: 43
Fork event: 2

Committers metadata

Last synced: about 2 months ago

Total Commits: 4,357
Total Committers: 14
Avg Commits per committer: 311.214
Development Distribution Score (DDS): 0.322

Commits in past year: 339
Committers in past year: 4
Avg Commits per committer in past year: 84.75
Development Distribution Score (DDS) in past year: 0.31

Name	Email	Commits
David Hassell	d**l@n**k	2953
Sadie Louise Bartholomew	s**w@n**k	1120
Ankit Bhandekar	8****t	219
Thibault Hallouin	t**n@u**e	13
Bruno P. Kinoshita	k****w	11
Oliver Kotla	5****t	11
Charles Roberts	c**s@r**k	10
Matt	m**3@g**m	9
Natalia Hunt		5
Tyge Løvset	t**o@n**o	2
William McGinty	3****S	1
Sharar-A	s**i@n**k	1
Alexander James Phillips	a**l@g**m	1
Alan Iwi	a**i@s**k	1

Committer domains:

Issue and Pull Request metadata

Last synced: about 2 months ago

Total issues: 371
Total pull requests: 566
Average time to close issues: 3 months
Average time to close pull requests: 12 days
Total issue authors: 43
Total pull request authors: 11
Average comments per issue: 1.9
Average comments per pull request: 1.37
Merged pull request: 516
Bot issues: 0
Bot pull requests: 0

Past year issues: 39
Past year pull requests: 54
Past year average time to close issues: 14 days
Past year average time to close pull requests: 7 days
Past year issue authors: 9
Past year pull request authors: 4
Past year average comments per issue: 1.64
Past year average comments per pull request: 0.59
Past year merged pull request: 43
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/ncas-cms/cf-python

Top Issue Authors

davidhassell (142)
sadielbartholomew (126)
bnlawrence (23)
JonathanGregory (13)
dlrhodson (7)
ThibHlln (6)
bewithankit (6)
AJamesPhillips (3)
ThatDesert (3)
lguo-uk (3)
m-couldrey (2)
ellgil82 (2)
dwest77a (2)
mattjbr123 (2)
matthew-shin (2)

Top Pull Request Authors

davidhassell (400)
sadielbartholomew (108)
bewithankit (36)
kinow (6)
mattjbr123 (5)
alaniwi (3)
ThibHlln (2)
tylov (2)
ThatDesert (2)
Sharar-A (1)
AJamesPhillips (1)

Top Issue Labels

enhancement (140)
bug (115)
question (36)
documentation (28)
aggregation (23)
dask (22)
testing (16)
performance (16)
um/pp (13)
netCDF read (11)
CFA (9)
regridding (9)
API review (4.0.0) (9)
code tidy (8)
installation (8)
netCDF write (8)
GitHub Actions (6)
dataset write (5)
release (4)
dataset read (4)
CI (3)
UGRID (3)
low priority (2)
high priority (2)
active storage (2)
bug? (2)
zarr (2)
good first issue (1)
compression (1)
dependency (1)

Top Pull Request Labels

dask (196)
enhancement (63)
documentation (52)
bug (46)
low priority (28)
code tidy (23)
aggregation (17)
regridding (14)
performance (13)
testing (10)
CFA (9)
high priority (9)
netCDF read (8)
netCDF write (7)
CI (6)
installation (6)
dataset write (5)
dataset read (4)
release (3)
GitHub Actions (3)
question (3)
UGRID (3)
um/pp (3)
active storage (3)
linting (2)
top priority (1)
compression (1)
dependency (1)

Package metadata

Total packages: 1
Total downloads:
- pypi: 6,691 last-month
Total dependent packages: 1
Total dependent repositories: 9
Total versions: 115
Total maintainers: 2

pypi.org: cf-python

A CF-compliant earth science data analysis library

Homepage: https://ncas-cms.github.io/cf-python
Documentation: https://cf-python.readthedocs.io/
Licenses: MIT
Latest release: 3.18.2 (published 2 months ago)
Last Synced: 2025-10-29T20:18:29.763Z (about 2 months ago)
Versions: 115
Dependent Packages: 1
Dependent Repositories: 9
Downloads: 6,691 Last month
Rankings:
- Dependent packages count: 4.787%
- Dependent repos count: 4.847%
- Average: 7.042%
- Stargazers count: 7.771%
- Forks count: 8.544%
- Downloads: 9.262%
Maintainers (2)
- davidhassell
- sadielbartholomew

Dependencies

requirements.txt pypi

cfdm >=1.9.0.2,<1.9.1.0
cftime >=1.5.0
cfunits >=3.3.4
netCDF4 >=1.5.4
numpy >=1.15
packaging >=20.0
psutil >=0.6.0

setup.py pypi

ESMF >=8.0
cfdm >=1.8.5,
cftime >=1.1.3
cfunits >=3.2.7
matplotlib >=3.0.0
mpi4py >=3.0.0
netCDF4 >=1.5.3
numpy >=1.15
psutil >=0.6.0
scipy >=1.1.0
udunits2 ==2.2.25

.github/workflows/linting.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
pre-commit/action v3.0.0 composite

.github/workflows/run-test-suite.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
codecov/codecov-action v3 composite
conda-incubator/setup-miniconda v2 composite

.github/workflows/test-source-dist.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite
conda-incubator/setup-miniconda v2 composite

docker/Dockerfile docker

continuumio/miniconda3 latest build

pyproject.toml pypi

Score: 17.017712299734313

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cf-python

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README.md

cf-python

References

Dask

Documentation

Installation

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Tutorial

Functionality

Visualization

Command line utilities

Tests

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