Climakitae

Enable a transition from climate vulnerability assessments to decision support for investor-owned utilities and other stakeholders.
https://github.com/cal-adapt/climakitae

Category: Climate Change
Sub Category: Climate Data Processing and Analysis

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A Python toolkit for retrieving, visualizing, and performing scientific analyses with data from the Cal-Adapt Analytics Engine.

README.md

Climakitae

codecov
CI
Documentation Status
PyPI version
Python
License
Code style: black
DOI:10.5281/zenodo.18111936

A powerful Python toolkit for climate data analysis and retrieval from the Cal-Adapt Analytics Engine (AE).

Climakitae provides intuitive tools for accessing, analyzing, and visualizing downscaled CMIP6 data, enabling researchers and practitioners to perform comprehensive climate impact assessments for California.

[!WARNING]
This package is under active development. APIs may change between versions.

Key Features

  • 🌑️ Comprehensive Climate Data Access: Retrieve climate variables from hosted climate models
  • πŸ“Š Downscaled Climate Models: Access dynamical (WRF) and statistical (LOCA2) downscaling methods
  • πŸ—ΊοΈ Spatial Analysis Tools: Built-in support for geographic subsetting and spatial aggregation
  • πŸ“ˆ Climate Indices: Calculate heat indices, warming levels, and extreme event metrics
  • πŸ”§ Flexible Data Export: Export to NetCDF, CSV, and Zarr
  • πŸ“± GUI Integration: Works seamlessly with climakitaegui for interactive analysis

About Cal-Adapt

Climakitae is developed as part of the Cal-Adapt Analytics Engine, a platform for California climate data and tools. Cal-Adapt provides access to cutting-edge climate science to support adaptation planning and decision-making.

Getting Started

Installation via Conda

Prerequisites

Install latest release with conda on Linux

For additional details on the latest version and step-by-step installation instructions please visit the wiki

# create a conda environment with 
conda create -n climakitae python=3.13 -y
conda activate climakitae
pip install climakitae

Installation via Pip

Prerequisites

  • Python 3.12
  • pip

Install latest release with pip on Linux

For additional details on the latest version and step-by-step installation instructions please visit the wiki

pip install --upgrade pip
pip install climakitae

Basic Usage

from climakitae.core.data_interface import get_data

# Retrieve temperature data for California
data = get_data(
    variable="Air Temperature at 2m",
    downscaling_method="Dynamical", 
    resolution="9 km",
    timescale="monthly",
    scenario="SSP 3-7.0",
    cached_area="CA"
)

# Data is returned as an xarray Dataset
print(data)

Documentation

Resource Description
AE Navigation Guide Interactive notebook tutorial
API Reference Complete API documentation
AE Notebooks Sample notebooks and scripts
Contributing Development guidelines

Development Setup

Prerequisites

Dev Environment Setup (Linux)

git clone https://github.com/cal-adapt/climakitae.git
cd climakitae
conda create -n climakitae --file conda-linux-64.lock
conda activate climakitae

Running Tests

# Run basic tests
pytest -m "not advanced"

# Run all tests
pytest

# Run with coverage
pip install pytest-cov
pytest --cov=climakitae --cov-report=html

Code Formatting (pre-commit hook)

This repo uses Black for code formatting. To ensure your commits are formatted consistently with CI, install the pre-commit hook:

pip install pre-commit
pre-commit install

Black will now run automatically on every commit. To run it manually:

pre-commit run black --all-files

Contributing

We welcome contributions! Please see our contributing guidelines for details on:

  • πŸ› Reporting bugs
  • πŸ’‘ Requesting features
  • πŸ”§ Submitting code changes
  • πŸ“– Improving documentation

Quick Development Workflow

Open a βš™οΈ code improvement issue describing the feature you'd like to develop.

Then, checkout and setup your branch:

# Fork the repo and create a feature branch
git checkout -b feature/your-feature-name

# Make your changes and add tests
# ...

# Run tests and linting
pytest
pre-commit run black --all-files

# Submit a pull request

When submitting a pull request, please tag at least two project maintainers/developers for review.

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.

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Last synced: about 1 month ago

Total Commits: 4,593
Total Committers: 21
Avg Commits per committer: 218.714
Development Distribution Score (DDS): 0.796

Commits in past year: 1,975
Committers in past year: 11
Avg Commits per committer in past year: 179.545
Development Distribution Score (DDS) in past year: 0.632

Name Email Commits
claalmve c****9@b****u 937
Nicole Keeney n****y@g****m 909
neilSchroeder n****r@g****m 726
Eric Lehmer e****r@b****u 440
Ana Ordonez a****z@e****m 366
Victoria Ford f****o@g****m 301
neilSchroeder n****r@g****m 250
naomi t****g 139
name v****a@e****m 138
Tianchi-Liu l****c@b****u 92
Cora Kingdon c****n@b****u 89
bethem b****h@e****m 58
Brian Galey b****y@g****m 39
Nabig Chaudhry n****g@l****v 33
Will Krantz k****w@g****m 24
Owen Doherty o****y@g****m 22
Grace Di Cecco 3****o 12
Calvin Chen c****n@C****l 9
Brian Galey b****y@b****u 5
copilot-swe-agent[bot] 1****t 3
dependabot[bot] 4****] 1

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Issue and Pull Request metadata

Last synced: about 2 months ago

Total issues: 55
Total pull requests: 618
Average time to close issues: 3 months
Average time to close pull requests: 8 days
Total issue authors: 15
Total pull request authors: 12
Average comments per issue: 1.64
Average comments per pull request: 1.1
Merged pull request: 460
Bot issues: 0
Bot pull requests: 0

Past year issues: 27
Past year pull requests: 198
Past year average time to close issues: 28 days
Past year average time to close pull requests: 6 days
Past year issue authors: 11
Past year pull request authors: 8
Past year average comments per issue: 1.56
Past year average comments per pull request: 1.21
Past year merged pull request: 134
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/cal-adapt/climakitae

Top Issue Authors

  • elehmer (14)
  • vicford (12)
  • neilSchroeder (6)
  • acordonez (5)
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  • nathancoliver (2)
  • rd1l (2)
  • janluong (1)
  • nicolejkeeney (1)
  • mirachokshi (1)
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Top Pull Request Authors

  • claalmve (201)
  • elehmer (148)
  • nicolejkeeney (84)
  • neilSchroeder (69)
  • acordonez (39)
  • vicford (33)
  • Tianchi-Liu (26)
  • wkrantz (7)
  • thenaomig (7)
  • gdicecco (2)
  • vdmachuca (1)
  • corakingdon (1)

Top Issue Labels

  • bug (27)
  • enhancement (7)
  • environment (3)
  • Release 1.2.0 (2)
  • Release 1.2.2 (2)
  • question (1)

Top Pull Request Labels

  • Advanced Testing (39)
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  • Urgent (2)
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Package metadata

proxy.golang.org: github.com/cal-adapt/climakitae

  • Homepage:
  • Documentation: https://pkg.go.dev/github.com/cal-adapt/climakitae#section-documentation
  • Licenses:
  • Latest release: v1.5.2 (published about 2 months ago)
  • Last Synced: 2026-03-03T19:07:55.723Z (about 2 months ago)
  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent packages count: 5.103%
    • Average: 5.274%
    • Dependent repos count: 5.445%
pypi.org: climakitae

Climate data analysis toolkit

  • Homepage: https://github.com/cal-adapt/climakitae
  • Documentation: https://climakitae.readthedocs.io
  • Licenses: BSD-3-Clause
  • Latest release: 1.5.2 (published about 2 months ago)
  • Last Synced: 2026-03-03T19:07:10.104Z (about 2 months ago)
  • Versions: 14
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 469 Last month
  • Rankings:
    • Dependent packages count: 10.329%
    • Average: 34.233%
    • Dependent repos count: 58.137%
  • Maintainers (1)

Dependencies

.github/workflows/ci.yaml actions
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  • psf/black stable composite
docs/requirements.txt pypi
  • Sphinx ==4.4.0
  • sphinx-book-theme ==0.2.0
  • sphinx-design *
requirements.txt pypi
  • cartopy ==0.20.1
  • dask-gateway ==0.9.0
  • geopandas ==0.10.2
  • geoviews ==1.9.2
  • holoviews ==1.14.6
  • hvplot ==0.7.3
  • intake ==0.6.4
  • intake-xarray ==0.5.0
  • jinja2 ==3.0.2
  • matplotlib ==3.4.3
  • metpy ==1.1.0
  • numpy ==1.21.2
  • pandas ==1.3.4
  • panel ==0.12.4
  • param ==1.11.1
  • psutil ==5.8.0
  • pyproj ==3.2.1
  • pytest ==7.1.3
  • rioxarray ==0.7.1
  • s3fs ==2021.10.1
  • scipy ==1.7.1
  • shapely ==1.7.1
  • xarray ==0.19.0
setup.py pypi
environment.yml conda
  • cartopy
  • geopandas
  • geoviews
  • holoviews
  • hvplot
  • intake
  • intake-esm
  • intake-geopandas
  • intake-xarray
  • jinja2
  • matplotlib
  • metpy
  • numpy
  • pandas
  • panel
  • param
  • pip
  • proj
  • psutil
  • pygeos
  • pyproj
  • pytest
  • python
  • rioxarray
  • s3fs
  • scipy
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  • xarray
  • xmip

Score: 12.72361565704369