CloudDrift

Accelerates the use of Lagrangian data for atmospheric, oceanic, and climate sciences.
https://github.com/Cloud-Drift/clouddrift

Category: Atmosphere
Sub Category: Atmospheric Dispersion and Transport

Keywords

climate-data climate-science data-structures oceanography python

Last synced: about 17 hours ago
JSON representation

Repository metadata

CloudDrift accelerates the use of Lagrangian data for atmospheric, oceanic, and climate sciences.

Host: GitHub
URL: https://github.com/Cloud-Drift/clouddrift
Owner: Cloud-Drift
License: mit
Created: 2021-11-03T14:43:06.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2025-04-21T20:45:03.000Z (5 days ago)
Last Synced: 2025-04-22T07:48:07.358Z (5 days ago)
Topics: climate-data, climate-science, data-structures, oceanography, python
Language: Python
Homepage: https://clouddrift.org/
Size: 6.04 MB
Stars: 38
Watchers: 6
Forks: 9
Open Issues: 62
Releases: 51
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Zenodo: .zenodo.json

`clouddrift`

📦 Distributions

👥 Social

Join the Email Distribution List

📚 Binders and examples

: MOSAiC get started (🧊 sea ice trajectories)
: GDP get started (🌊 ocean drifter trajectories)
: HURDAT2 get started (🌀 cyclone/hurricane trajectories from 1852 - 2022)
HYCOM-OceanTrack: A repository with notebook examples using clouddrift with a very large , analysis-ready cloud-optimized, Lagrangian dataset hosted in the cloud: HYCOM OceanTrack: Integrated HYCOM Eulerian Fields and Lagrangian Trajectories Dataset.

clouddrift is a Python package that accelerates the use of Lagrangian data for atmospheric, oceanic, and climate sciences.
It is funded by NSF EarthCube through the
EarthCube Capabilities Grant No. 2126413.

Read the documentation.

Using `clouddrift`

Start by reading the documentation.

Example Jupyter notebooks that showcase the library, as well as scripts
to process various Lagrangian datasets, can be found in gdp-get-started, mosaic-get-started, hurdat2-get-started, or a demo for the EarthCube community workshop 2023.

Contributing and scope

We welcome and invite contributions from the community in any shape or form! Please visit our Contributing Guide to get Started 😃

The scope of clouddrift includes:

Working with contiguous ragged-array data; for example, see the
clouddrift.ragged module.
Common scientific analysis of Lagrangian data, oceanographic or otherwise;
for example, see the
clouddrift.kinematics,
clouddrift.signal, and
clouddrift.wavelet modules.
Processing existing Lagrangian datasets into a common data structure and format;
for example, see the clouddrift.adapters.mosaic module.
Making cloud-optimized ragged-array datasets easily accessible; for example,
see the clouddrift.datasets module.

If you have an idea that does not fit into the scope of clouddrift but you think
it should, please open an issue to discuss it.

Getting started

Install `clouddrift`

You can install the latest release of clouddrift using pip or conda.

Latest official release:

pip:

In your virtual environment, type:

pip install clouddrift

To install optional dependencies needed by the clouddrift.plotting module,
type:

pip install clouddrift[plotting]

Conda:

First add conda-forge to your channels in your Conda configuration (~/.condarc):

conda config --add channels conda-forge
conda config --set channel_priority strict

then install clouddrift:

conda install clouddrift

To install optional dependencies needed by the clouddrift.plotting module,
type:

conda install matplotlib cartopy

Development branch:

If you need the latest development version, you can install it directly from this GitHub repository.

pip:

In your existing virtual environment, you can use pip as follows.

Get the code:

git clone https://github.com/cloud-drift/clouddrift
cd clouddrift/

Install dependencies and local version of clouddrift:

pip install .

Conda:

Using conda, you can proceed as follows.

Get the code:

git clone https://github.com/cloud-drift/clouddrift
cd clouddrift/

Create an environment as specified in the yml file with the required library dependencies:

conda env create -f environment.yml # creates a new env with the dependencies
conda env update -f environment.yml # install dependencies in current environment

2a. Make sure you created the environment by activating it:

conda activate clouddrift

Finally, install the local version of clouddrift:

pip install .

Installing `clouddrift` on unsupported platforms

One or more dependencies of clouddrift may not have pre-built wheels for
platforms like IBM Power9 or Raspberry Pi.
If you are using pip to install clouddrift and are getting errors during the
installation step, try installing clouddrift using Conda.
If you still have issues installing clouddrift, you may need to install system
dependencies first.
Please let us know by opening an
issue and we will do our
best to help you.

Found an issue or need help?

Please create a new issue here
and provide as much detail as possible about your problem or question.

Owner metadata

Name: CloudDrift
Login: Cloud-Drift
Email:
Kind: organization
Description: A platform for accelerating research with Lagrangian climate data
Website: https://cloud-drift.github.io/clouddrift/
Location: United States of America
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/91622877?v=4
Repositories: 4
Last ynced at: 2023-06-13T03:24:03.828Z
Profile URL: https://github.com/Cloud-Drift

GitHub Events

Total

Create event: 1
Release event: 1
Issues event: 14
Watch event: 2
Member event: 1
Issue comment event: 47
Push event: 6
Pull request event: 17
Pull request review comment event: 17
Pull request review event: 17
Fork event: 2

Last Year

Create event: 1
Release event: 1
Issues event: 14
Watch event: 2
Member event: 1
Issue comment event: 47
Push event: 6
Pull request event: 17
Pull request review comment event: 17
Pull request review event: 17
Fork event: 2

Committers metadata

Last synced: 4 days ago

Total Commits: 419
Total Committers: 8
Avg Commits per committer: 52.375
Development Distribution Score (DDS): 0.618

Commits in past year: 83
Committers in past year: 4
Avg Commits per committer in past year: 20.75
Development Distribution Score (DDS) in past year: 0.663

Name	Email	Commits
Philippe Miron	p**n@g**m	160
Milan Curcic	c**o@g**m	104
Shane Elipot	s**t@m**u	59
Kevin Santana	k**1@g**m	49
Kevin	k**7@g**m	28
Philippe Miron	p**n@d**m	13
Vadim BERTRAND	3****r	4
Philippe Miron	p**n@C**l	2

Committer domains:

dtn.com: 1
miami.edu: 1

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 231
Total pull requests: 268
Average time to close issues: about 2 months
Average time to close pull requests: 8 days
Total issue authors: 9
Total pull request authors: 7
Average comments per issue: 2.01
Average comments per pull request: 3.16
Merged pull request: 231
Bot issues: 0
Bot pull requests: 0

Past year issues: 68
Past year pull requests: 81
Past year average time to close issues: 24 days
Past year average time to close pull requests: 12 days
Past year issue authors: 7
Past year pull request authors: 5
Past year average comments per issue: 0.88
Past year average comments per pull request: 1.65
Past year merged pull request: 67
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/Cloud-Drift/clouddrift

Top Issue Authors

kevinsantana11 (77)
selipot (62)
milancurcic (54)
philippemiron (20)
malmans2 (7)
KevinShuman (4)
vadmbertr (4)
miniufo (2)
rcaneill (1)

Top Pull Request Authors

philippemiron (70)
milancurcic (66)
kevinsantana11 (65)
selipot (55)
KevinShuman (8)
vadmbertr (3)
rcaneill (1)

Top Issue Labels

enhancement (82)
bug (35)
question (17)
analysis-functions (17)
documentation (14)
tooling (14)
data-adapters (10)
outreach (4)
help wanted (3)
good first issue (1)
example (1)

Top Pull Request Labels

enhancement (61)
documentation (26)
analysis-functions (22)
bug (18)
data-adapters (18)
help wanted (4)
arhicved-label-data-adapters (3)

Package metadata

Total packages: 1
Total downloads:
- pypi: 1,983 last-month
Total docker downloads: 27
Total dependent packages: 0
Total dependent repositories: 1
Total versions: 50
Total maintainers: 3

pypi.org: clouddrift

Accelerating the use of Lagrangian data for atmospheric, oceanic, and climate sciences

Homepage: https://github.com/Cloud-Drift/clouddrift
Documentation: https://cloud-drift.github.io/clouddrift
Licenses: MIT License
Latest release: 0.44.0 (published 2 months ago)
Last Synced: 2025-04-25T13:05:30.970Z (1 day ago)
Versions: 50
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 1,983 Last month
Docker Downloads: 27
Rankings:
- Docker downloads count: 4.154%
- Dependent packages count: 7.303%
- Downloads: 9.394%
- Average: 12.021%
- Stargazers count: 12.269%
- Forks count: 16.94%
- Dependent repos count: 22.068%
Maintainers (3)

Dependencies

docs/requirements.txt pypi

pydata_sphinx_theme *
sphinx *

.github/workflows/black.yml actions

actions/checkout v3 composite
psf/black stable composite

.github/workflows/ci.yml actions

actions/checkout v3 composite
codecov/codecov-action v3 composite
mamba-org/setup-micromamba v1 composite

.github/workflows/docs.yml actions

actions/checkout v3 composite
actions/upload-artifact v3 composite
ad-m/github-push-action master composite
mamba-org/setup-micromamba v1 composite

.github/workflows/pypi.yml actions

actions/checkout v3 composite
actions/download-artifact v3 composite
actions/setup-python v4 composite
actions/upload-artifact v3 composite
pypa/gh-action-pypi-publish release/v1 composite

pyproject.toml pypi

aiohttp >=3.8.4
awkward >=2.0.0
fsspec >=2022.3.0
netcdf4 >=1.6.4
numpy >=1.22.4
pandas >=1.3.4
pyarrow >=8.0.0
requests >=2.31.0
scipy >=1.11.2
tqdm >=4.64.0
xarray >=2023.5.0
zarr >=2.14.2

environment.yml conda

Score: 14.292986202048711

CloudDrift

Keywords

Repository metadata

README.md

clouddrift

📦 Distributions

👥 Social

📚 Binders and examples

Using clouddrift

Contributing and scope

Getting started

Install clouddrift

Latest official release:

pip:

Conda:

Development branch:

pip:

Conda:

Installing clouddrift on unsupported platforms

Found an issue or need help?

Owner metadata

GitHub Events

Total

Last Year

Committers metadata

Committer domains:

Issue and Pull Request metadata

Top Issue Authors

Top Pull Request Authors

Top Issue Labels

Top Pull Request Labels

Package metadata

pypi.org: clouddrift

Dependencies

`clouddrift`

Using `clouddrift`

Install `clouddrift`

Installing `clouddrift` on unsupported platforms