earthkit-utils
Utilities for the Earthkit ecosystem
Decision gist · record as of 2026-08-14
Yes—if you are using other earthkit packages or building Earth science applications. The package is production-stable, actively maintained, permissively licensed, and has low installation friction. Install it as a dependency of other earthkit tools or when you need the shared utilities it provides; standalone use is unclear from the fact sheet.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later; supports CPython and PyPy implementations.
- Low friction installation with only two runtime dependencies (array-api-compat and pint).
- Repository is actively maintained with a recent commit on 2026-06-29, and the package is marked as Production/Stable.
License · maintenance · safety
Apache-2.0 (permissive) — Licensed under Apache-2.0 (permissive), allowing free use, modification, and distribution with minimal restrictions—suitable for both commercial and open-source projects.
last release 2026-06-29 (46 days) · last repo commit 2026-06-29 · 3 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 76,202 downloads/mo, #14,646 on PyPI
Alternatives
Verify before relying
pip install earthkit-utils
import earthkit_utils
# Use utilities from the earthkit ecosystem- What specific utilities and helper functions are included in the package—the description does not detail the API surface.
- Whether array-api-compat and pint are used for specific data handling tasks or are optional dependencies for certain features.
What it is and what it does
earthkit-utils is a utility library for the earthkit ecosystem, a suite of tools developed by ECMWF for Earth science and weather forecasting applications. It provides shared helper functions and utilities that other earthkit packages depend on, reducing code duplication across the ecosystem. The package is marked as Graduated under ECMWF's Software Maturity guidelines, indicating it has reached a stable, production-ready state.
The package depends on array-api-compat and pint, suggesting it handles array operations and physical unit conversions—common tasks in scientific computing. It supports modern Python versions (3.10 through 3.14) and runs on both CPython and PyPy. The low installation friction and active maintenance make it a straightforward addition to projects that use other earthkit components.
Use it for
- Shared utility functions for earthkit-based Earth science data processing workflows.
- Unit conversion and physical quantity handling in weather and climate applications.
- Array operations and data manipulation following the array API standard.
- Building blocks for other earthkit packages that depend on common utilities.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes—if you are using other earthkit packages or building Earth science applications.
The package is production-stable, actively maintained, permissively licensed, and has low installation friction. Install it as a dependency of other earthkit tools or when you need the shared utilities it provides; standalone use is unclear from the fact sheet.
Install
earthkit-utils on PyPI
Before you install
Low friction installation with only two runtime dependencies (array-api-compat and pint). Repository is actively maintained with a recent commit on 2026-06-29, and the package is marked as Production/Stable.
Requires Python 3.10 or later; supports CPython and PyPy implementations.
License in practice
Licensed under Apache-2.0 (permissive), allowing free use, modification, and distribution with minimal restrictions—suitable for both commercial and open-source projects.
Quickstart
pip install earthkit-utils
import earthkit_utils
# Use utilities from the earthkit ecosystem
Verify before relying
- What specific utilities and helper functions are included in the package—the description does not detail the API surface.
- Whether array-api-compat and pint are used for specific data handling tasks or are optional dependencies for certain features.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesarray-api-compatpint |
| Maintenance | Actively maintained 46 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 76,202 / month, #14,646 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Scientific/Engineering |
Evidence: earthkit_utils-1.0.2-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “earthkit utilities”
- earthkit-utilsProvides shared utilities and helper functions for the earthkit…
- earthkit-meteoComputes meteorological quantities (potential temperature,…
- arcosparseDownloads and subsets sparse geospatial datasets stored in ARCO…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also AI-WQ-package · earthkit-data · earthkit-meteo · eccodeslib · eckitlib · ecmwf-datastores-client · ecmwf-opendata · ecmwf-api-client · eccodes · cdsapi