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 ocean archival earth-system-model climate-model units atmospheric-science training featured feature-flag
Last synced: about 17 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 5 years ago)
- Default Branch: main
- Last Pushed: 2025-04-04T15:08:49.000Z (23 days ago)
- Last Synced: 2025-04-25T14:07:58.760Z (1 day 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: 134 MB
- Stars: 137
- Watchers: 3
- Forks: 21
- Open Issues: 114
- Releases: 19
-
Metadata Files:
- Readme: README.md
- Changelog: Changelog.rst
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
README.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, 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, - 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).
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.
See the cf-plot
gallery for a
range of plotting possibilities with example code.
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: 30
- Watch event: 11
- Issue comment event: 69
- Push event: 31
- Pull request event: 34
- Pull request review comment event: 83
- Pull request review event: 96
- Fork event: 1
Last Year
- Create event: 3
- Release event: 2
- Issues event: 30
- Watch event: 11
- Issue comment event: 69
- Push event: 31
- Pull request event: 34
- Pull request review comment event: 83
- Pull request review event: 96
- Fork event: 1
Committers metadata
Last synced: 7 days ago
Total Commits: 4,192
Total Committers: 13
Avg Commits per committer: 322.462
Development Distribution Score (DDS): 0.321
Commits in past year: 431
Committers in past year: 6
Avg Commits per committer in past year: 71.833
Development Distribution Score (DDS) in past year: 0.406
Name | Commits | |
---|---|---|
David Hassell | d****l@n****k | 2846 |
Sadie Louise Bartholomew | s****w@n****k | 1073 |
Ankit Bhandekar | 8****t | 219 |
Thibault Hallouin | t****n@u****e | 13 |
Bruno P. Kinoshita | k****w | 11 |
Charles Roberts | c****s@r****k | 10 |
Matt | m****3@g****m | 9 |
Natalia Hunt | 5 | |
Tyge Løvset | t****o@n****o | 2 |
Alan Iwi | a****i@s****k | 1 |
Alexander James Phillips | a****l@g****m | 1 |
Sharar-A | s****i@n****k | 1 |
William McGinty | 3****S | 1 |
Committer domains:
- ncas.ac.uk: 3
- stfc.ac.uk: 1
- norceresearch.no: 1
- reading.ac.uk: 1
- ucdconnect.ie: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 375
Total pull requests: 502
Average time to close issues: 3 months
Average time to close pull requests: 11 days
Total issue authors: 40
Total pull request authors: 10
Average comments per issue: 2.05
Average comments per pull request: 1.42
Merged pull request: 465
Bot issues: 0
Bot pull requests: 0
Past year issues: 65
Past year pull requests: 45
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 23 days
Past year issue authors: 13
Past year pull request authors: 5
Past year average comments per issue: 2.08
Past year average comments per pull request: 1.38
Past year merged pull request: 39
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- davidhassell (139)
- sadielbartholomew (133)
- bnlawrence (24)
- JonathanGregory (14)
- dlrhodson (7)
- ThibHlln (6)
- bewithankit (6)
- AJamesPhillips (3)
- lguo-uk (3)
- mattjbr123 (3)
- m-couldrey (2)
- ellgil82 (2)
- dwest77a (2)
- Nemo1166 (2)
- matthew-shin (2)
Top Pull Request Authors
- davidhassell (354)
- sadielbartholomew (93)
- bewithankit (37)
- kinow (6)
- mattjbr123 (3)
- tylov (3)
- ThibHlln (2)
- alaniwi (2)
- AJamesPhillips (1)
- Sharar-A (1)
Top Issue Labels
- enhancement (141)
- bug (121)
- question (39)
- documentation (31)
- aggregation (25)
- dask (22)
- API review (4.0.0) (18)
- testing (18)
- performance (15)
- CFA (12)
- netCDF read (12)
- um/pp (11)
- netCDF write (11)
- code tidy (9)
- regridding (8)
- installation (7)
- GitHub Actions (6)
- release (3)
- CI (3)
- UGRID (3)
- high priority (2)
- low priority (2)
- active storage (2)
- good first issue (1)
- work in in progress (1)
Top Pull Request Labels
- dask (193)
- documentation (45)
- enhancement (34)
- bug (33)
- low priority (28)
- code tidy (23)
- aggregation (13)
- performance (11)
- testing (10)
- regridding (9)
- high priority (9)
- CFA (8)
- netCDF read (8)
- netCDF write (7)
- CI (7)
- installation (5)
- GitHub Actions (4)
- question (3)
- release (2)
- UGRID (2)
- um/pp (2)
- active storage (2)
- linting (2)
- top priority (1)
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 2,791 last-month
- Total dependent packages: 1
- Total dependent repositories: 9
- Total versions: 112
- 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: 3.17.0 (published 24 days ago)
- Last Synced: 2025-04-25T14:05:08.102Z (1 day ago)
- Versions: 112
- Dependent Packages: 1
- Dependent Repositories: 9
- Downloads: 2,791 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)
Dependencies
- 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
- 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
- actions/checkout v3 composite
- actions/setup-python v4 composite
- pre-commit/action v3.0.0 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- codecov/codecov-action v3 composite
- conda-incubator/setup-miniconda v2 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- conda-incubator/setup-miniconda v2 composite
- continuumio/miniconda3 latest build
Score: 16.028847847758108