Binder Examples
Link |
Provider |
Description |
|---|---|---|
mybinder.org |
Basic self-contained example |
Description
xgcm is a python package for working with the datasets produced by numerical General Circulation Models (GCMs) and similar gridded datasets that are amenable to finite volume analysis. In these datasets, different variables are located at different positions with respect to a volume or area element (e.g. cell center, cell face, etc.) xgcm solves the problem of how to interpolate and difference these variables from one position to another.
xgcm consumes and produces xarray data structures, which are coordinate and metadata-rich representations of multidimensional array data. xarray is ideal for analyzing GCM data in many ways, providing convenient indexing and grouping, coordinate-aware data transformations, and (via dask) parallel, out-of-core array computation. On top of this, xgcm adds an understanding of the finite volume Arakawa Grids commonly used in ocean and atmospheric models and differential and integral operators suited to these grids.
xgcm was motivated by the rapid growth in the numerical resolution of ocean, atmosphere, and climate models. While highly parallel supercomputers can now easily generate tera- and petascale datasets, common post-processing workflows struggle with these volumes. Furthermore, we believe that a flexible, evolving, open-source, python-based framework for GCM analysis will enhance the productivity of the field as a whole, accelerating the rate of discovery in climate science. xgcm is part of the Pangeo initiative.
Getting Started
To learn how to install and use xgcm for your dataset, visit the xgcm documentation.
5 maintainers
Metadata
5 maintainers
Release files for xgcm 0.10.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| xgcm-0.10.1.tar.gz | 4.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| xgcm-0.10.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.0 MB
Release files / xgcm-0.10.1.tar.gz
| Download URL | xgcm-0.10.1.tar.gz |
|---|---|
| Size | 4.8 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7d3ee2ac859ff3821589b9a55f51b0867a1af688d687c54c5be5b289c4163c5f
|
|
BLAKE2b-256 checksum How to use checksums |
57735eb8e3fc0a0877abbbd909965d80b07c312de377dc6346e8bc8cc2230856
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.13
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 21, 2026.
Transparency logRelease files / xgcm-0.10.1-py3-none-any.whl
| Download URL | xgcm-0.10.1-py3-none-any.whl |
|---|---|
| Size | 132.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
773878df5edb7fa16734eb5a776b684f163b1ec0597cc0e098d1be07dba0e184
|
|
BLAKE2b-256 checksum How to use checksums |
5870a7396b6fad2d7b8a866aadc6d5dd4b20fceea136b8d4914192f3c45ef847
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.13
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 21, 2026.
Transparency log
