xee
A Google Earth Engine extension for Xarray.
Decision gist · record as of 2026-08-14
Yes, if you work with Google Earth Engine data and want to use the scientific Python stack. The package is actively maintained, has no known vulnerabilities, and low install friction. The v0.1.0 breaking changes are a consideration—check the migration guide if upgrading—but the permissive license and modern Python support (3.11+) make it a solid choice for geospatial analysis workflows.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Google Earth Engine authentication via earthengine authenticate and a registered Google Cloud project ID.
- Low install friction with a pure-Python wheel.
- Actively maintained with a recent release (31 days old) and active repository status.
License · maintenance · safety
Apache-2.0 (permissive) — Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but there are no copyleft obligations.
last release 2026-07-14 (31 days) · last repo commit 2026-08-05 · 370 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 90,898 downloads/mo, #13,557 on PyPI
Alternatives
Verify before relying
pip install xee
import xarray as xr
from xee import helpers
# After earthengine authenticate and project setup
ic = ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR')
grid = helpers.extract_grid_params(ic)
ds = xr.open_dataset(ic, engine='ee', **grid)- Whether the breaking changes in v0.1.0 affect common workflows or only edge cases
- Performance characteristics and memory overhead for typical petabyte-scale queries
- Dask integration specifics and recommended chunking strategies
What it is and what it does
Xee bridges Google Earth Engine and the scientific Python ecosystem by implementing an Xarray backend engine. It lets you treat Earth Engine Image and ImageCollection objects as lazy Xarray Datasets, deferring computation until you explicitly request data. This means you can use familiar Xarray, NumPy, and Dask workflows on Earth observation data without downloading entire collections locally.
The package handles the complexity of grid definition, coordinate reference systems, and parallel pixel retrieval through Earth Engine's API. It supports flexible output grids (fixed resolution or fixed shape), maintains CF-compliant dimension ordering (time, y, x), and integrates with Dask for distributed computation. You authenticate once to Earth Engine, then open datasets by specifying grid parameters—Xee handles lazy loading and chunked retrieval in the background.
Use it for
- Load monthly climate data as an Xarray Dataset and perform time-series analysis without downloading gigabytes locally.
- Define a fixed-resolution grid over a region of interest and retrieve satellite imagery in parallel chunks.
- Combine multiple Earth Engine collections into a single Xarray Dataset for multi-source geospatial analysis.
- Prototype Earth observation workflows interactively using Xarray's labeled arrays and familiar operations.
- Build production pipelines that lazily stream Earth Engine data into scientific Python tools.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with Google Earth Engine data and want to use the scientific Python stack.
The package is actively maintained, has no known vulnerabilities, and low install friction. The v0.1.0 breaking changes are a consideration—check the migration guide if upgrading—but the permissive license and modern Python support (3.11+) make it a solid choice for geospatial analysis workflows.
Install
xee on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained with a recent release (31 days old) and active repository status. Requires Python 3.11 or later and five runtime dependencies: xarray, earthengine-api, pyproj, affine, and shapely.
Requires Google Earth Engine authentication via earthengine authenticate and a registered Google Cloud project ID.
License in practice
Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but there are no copyleft obligations.
Quickstart
pip install xee
import xarray as xr
from xee import helpers
# After earthengine authenticate and project setup
ic = ee.ImageCollection('ECMWF/ERA5_LAND/MONTHLY_AGGR')
grid = helpers.extract_grid_params(ic)
ds = xr.open_dataset(ic, engine='ee', **grid)Verify before relying
- Whether the breaking changes in v0.1.0 affect common workflows or only edge cases
- Performance characteristics and memory overhead for typical petabyte-scale queries
- Dask integration specifics and recommended chunking strategies
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesxarrayearthengine-apipyprojaffineshapely |
| Maintenance | Actively maintained 31 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 90,898 / month, #13,557 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Information TechnologyIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIXProgramming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Atmospheric Science |
Evidence: xee-0.1.2-py3-none-any.whl
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