icclim is a Python library to compute climate indices. icclim name stands for index, calculation, climate.
Installation
From conda-forge (recommended): conda install -c conda-forge icclim.
From pypi: pip install icclim.
- From sources:
Clone the repository git clone https://github.com/cerfacs-globc/icclim.git
Install icclim pip install .
Compatibility
icclim is designed to stay compatible with the standard Python scientific stack:
Python: Supports Python 3.10 and above.
Core dependencies: Minimum supported versions are declared in pyproject.toml (for example numpy>=1.21, xarray>=2022.6, xclim>=0.45).
Recent stacks: Continuous integration tracks current supported Python versions and the maintained dependency range.
For production environments, prefer current stable dependency releases within the supported range.
How to use icclim
Let’s count the number of days above 25°C for each year, which corresponds to the index SU, from a tasmax variable scattered in multiple netcdf files.
SU is one of the many index that can be computed with icclim. See the documentation to explore what other index you can compute with icclim.
import icclim
summer_days = icclim.su(
"netcdf_files/tasmax_1990-2100.nc", out_file="summer_days.nc"
)For more examples on how to use icclim, see icclim’s How to … documentation or our notebooks.
Who use icclim
icclim is part of C4I platform backend and is integrated in CLIPC Portal. icclim is also used by independent researchers.
Who made icclim
icclim has always been an open source project and was successfully made thanks to the joint effort of all its contributors. The lead development is made at CERFACS, a research institution located in Toulouse, France.
Grants
This open-source project has been possible thanks to funding by the European Commission projects:
FP7 CLIPC (2013-2016)
FP7 IS-ENES2 (2013-2017)
H2020 EUDAT2020 (2015-2018)
H2020 IS-ENES3 (2019-2023)
Horizon Europe FUTURA and ENES-RISe (2026-2029)
This project also receives funding from Agence Nationale de la Recherche - France 2030 as part of the PEPR TRACCS programme under grant number ANR-22-EXTR-0003 (PC2-INVEST 2024-2032).
The beautiful icclim logo is a creation of Carole Petetin and has been funded by the H2020 IS-ENES3 project grant agreement No 824084 (2019-2023).
Indices
For a detailed description of each ECA&D index, please visit: https://www.ecad.eu/documents/atbd.pdf
Release files for icclim 7.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| icclim-7.2.1.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| icclim-7.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.4 MB
Release files / icclim-7.2.1.tar.gz
| Download URL | icclim-7.2.1.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / icclim-7.2.1-py3-none-any.whl
| Download URL | icclim-7.2.1-py3-none-any.whl |
|---|---|
| Size | 176.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
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 Oct 1, 2026.
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