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

Keywords from Contributors

pangeo

Last synced: about 23 hours ago
JSON representation

Repository metadata

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

README.md

Climakitae

codecov
CI
docs
PyPI version
Python
License
Code style: black
DOI:10.5281/zenodo.18111935

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 model, weather station, and renewable energy datasets
  • 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

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

Climakitae requires Python 3.12 or 3.13. We recommend uv on Linux/macOS and conda on Windows or when native geospatial dependencies cause trouble.

Quick install of the latest release:

# with uv
uv pip install climakitae

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

For editable installs, developer dependencies, and platform-specific tips, see the Installation Guide on the wiki.

Basic Usage

from climakitae.new_core.user_interface import ClimateData

# Retrieve monthly max temperature for Los Angeles in 2015
data = (
    ClimateData()
    .catalog("cadcat")
    .activity_id("WRF")
    .institution_id("UCLA")
    .table_id("mon")
    .grid_label("d03")
    .variable("t2max")
    .processes({
        "time_slice": ("2015-01-01", "2015-12-31"),
        "clip": "Los Angeles",
    })
    .get()
)

# Data is returned as a lazy xarray Dataset
print(data)

The legacy climakitae.core.data_interface.get_data API is still supported for backward compatibility, but new work should use ClimateData from climakitae.new_core.

Documentation

Resource Description
Installation Guide Casual, power-user, and developer installs
AE Navigation Guide Interactive notebook tutorial
API Reference Complete API documentation
AE Notebooks Sample notebooks and scripts
Contributing Development guidelines

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

For setting up a development environment (editable install, tests, formatters), see the Installation Guide on the wiki.

When opening a pull request, please tag at least two project maintainers for review.

License

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

Support


Contributors

Contributors


Owner metadata


GitHub Events

Total
Last Year

Committers metadata

Last synced: 2 days ago

Total Commits: 5,204
Total Committers: 21
Avg Commits per committer: 247.81
Development Distribution Score (DDS): 0.814

Commits in past year: 2,149
Committers in past year: 11
Avg Commits per committer in past year: 195.364
Development Distribution Score (DDS) in past year: 0.668

Name Email Commits
claalmve c****9@b****u 967
Nicole Keeney n****y@g****m 948
neilSchroeder n****r@g****m 726
Ana Ordonez a****z@e****m 566
Eric Lehmer e****r@b****u 440
neilSchroeder n****r@g****m 368
name v****a@e****m 345
Victoria Ford f****o@g****m 318
naomi t****g 139
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

Committer domains:


Issue and Pull Request metadata

Last synced: 2 days ago

Total issues: 61
Total pull requests: 677
Average time to close issues: 2 months
Average time to close pull requests: 8 days
Total issue authors: 15
Total pull request authors: 13
Average comments per issue: 1.52
Average comments per pull request: 1.16
Merged pull request: 513
Bot issues: 0
Bot pull requests: 1

Past year issues: 14
Past year pull requests: 128
Past year average time to close issues: 8 days
Past year average time to close pull requests: 6 days
Past year issue authors: 6
Past year pull request authors: 9
Past year average comments per issue: 1.57
Past year average comments per pull request: 1.41
Past year merged pull request: 93
Past year bot issues: 0
Past year bot pull requests: 1

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

Top Issue Authors

  • elehmer (14)
  • vicford (12)
  • neilSchroeder (10)
  • acordonez (7)
  • zladwp (4)
  • claalmve (3)
  • nathancoliver (2)
  • rd1l (2)
  • janluong (1)
  • nicolejkeeney (1)
  • mirachokshi (1)
  • thenaomig (1)
  • alwils916 (1)
  • GondekNP (1)
  • dlebauer (1)

Top Pull Request Authors

  • claalmve (220)
  • elehmer (148)
  • nicolejkeeney (92)
  • neilSchroeder (79)
  • acordonez (55)
  • vicford (34)
  • Tianchi-Liu (26)
  • wkrantz (7)
  • thenaomig (7)
  • vdmachuca (5)
  • gdicecco (2)
  • dependabot[bot] (1)
  • corakingdon (1)

Top Issue Labels

  • bug (30)
  • enhancement (9)
  • environment (3)
  • Release 1.2.2 (2)
  • Release 1.2.0 (2)
  • question (1)

Top Pull Request Labels

  • Advanced Testing (53)
  • backburner (10)
  • bug (2)
  • Urgent (2)
  • enhancement (2)
  • dependencies (1)
  • github_actions (1)

Package metadata

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

pypi.org: climakitae

Climate data analysis toolkit

  • Homepage: https://github.com/cal-adapt/climakitae
  • Documentation: https://cal-adapt.github.io/climakitae/dev/
  • Licenses: BSD-3-Clause
  • Latest release: 1.5.6 (published 6 days ago)
  • Last Synced: 2026-08-17T16:03:02.641Z (2 days ago)
  • Versions: 18
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 419 Last month
  • Rankings:
    • Dependent packages count: 10.329%
    • Average: 34.233%
    • Dependent repos count: 58.137%
  • Maintainers (1)

Dependencies

.github/workflows/ci.yaml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • conda-incubator/setup-miniconda v2 composite
  • 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
  • shapely
  • xarray
  • xmip

Score: 12.868966782919099