Intake-esm
An intake plugin for parsing an Earth System Model catalog and loading assets into xarray datasets.
https://github.com/intake/intake-esm
Category: Climate Change
Sub Category: Climate Data Access and Visualization
Keywords
cesm-lens climate-datasets cmip6 data-access data-catalog earth-system-model hacktoberfest intake pangeo
Keywords from Contributors
climate archiving climate-model climate-analysis compressed climate-science zarr observations catalogs intake-esm
Last synced: about 13 hours ago
JSON representation
Repository metadata
An intake plugin for parsing an Earth System Model (ESM) catalog and loading assets into xarray datasets.
- Host: GitHub
- URL: https://github.com/intake/intake-esm
- Owner: intake
- License: apache-2.0
- Created: 2018-12-31T16:42:54.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2025-04-14T04:13:30.000Z (13 days ago)
- Last Synced: 2025-04-21T11:07:50.231Z (6 days ago)
- Topics: cesm-lens, climate-datasets, cmip6, data-access, data-catalog, earth-system-model, hacktoberfest, intake, pangeo
- Language: Python
- Homepage: https://intake-esm.readthedocs.io
- Size: 11.7 MB
- Stars: 149
- Watchers: 14
- Forks: 48
- Open Issues: 36
- Releases: 27
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
README.md
Intake-esm
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Motivation
Computer simulations of the Earth’s climate and weather generate huge amounts of data.
These data are often persisted on HPC systems or in the cloud across multiple data
assets of a variety of formats (netCDF, zarr, etc...). Finding, investigating,
loading these data assets into compute-ready data containers costs time and effort.
The data user needs to know what data sets are available, the attributes describing
each data set, before loading a specific data set and analyzing it.
Finding, investigating, loading these assets into data array containers
such as xarray can be a daunting task due to the large number of files
a user may be interested in. Intake-esm aims to address these issues by
providing necessary functionality for searching, discovering, data access/loading.
Overview
intake-esm
is a data cataloging utility built on top of intake, pandas, and xarray, and it's pretty awesome!
-
Opening an ESM catalog definition file: An Earth System Model (ESM) catalog file is a JSON file that conforms
to the ESM Collection Specification. When provided a link/path to an esm catalog file,intake-esm
establishes
a link to a database (CSV file) that contains data assets locations and associated metadata
(i.e., which experiment, model, the come from). The catalog JSON file can be stored on a local filesystem
or can be hosted on a remote server.In [1]: import intake In [2]: import intake_esm In [3]: cat_url = intake_esm.tutorial.get_url("google_cmip6") In [4]: cat = intake.open_esm_datastore(cat_url) In [5]: cat Out[5]: <GOOGLE-CMIP6 catalog with 4 dataset(s) from 261 asset(s>
-
Search and Discovery:
intake-esm
provides functionality to execute queries against the catalog:In [5]: cat_subset = cat.search( ...: experiment_id=["historical", "ssp585"], ...: table_id="Oyr", ...: variable_id="o2", ...: grid_label="gn", ...: ) In [6]: cat_subset Out[6]: <GOOGLE-CMIP6 catalog with 4 dataset(s) from 261 asset(s)>
-
Access: when the user is satisfied with the results of their query, they can load data assets (netCDF and/or Zarr stores) into xarray datasets:
In [7]: dset_dict = cat_subset.to_dataset_dict() --> The keys in the returned dictionary of datasets are constructed as follows: 'activity_id.institution_id.source_id.experiment_id.table_id.grid_label' |███████████████████████████████████████████████████████████████| 100.00% [2/2 00:18<00:00]
See documentation for more information.
Installation
Intake-esm can be installed from PyPI with pip:
python -m pip install intake-esm
It is also available from conda-forge
for conda installations:
conda install -c conda-forge intake-esm
Owner metadata
- Name: Intake
- Login: intake
- Email: [email protected]
- Kind: organization
- Description: Taking the pain out of data access and distribution
- Website: https://intake.readthedocs.io/en/latest/
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/1469464?v=4
- Repositories: 29
- Last ynced at: 2023-03-02T23:30:46.422Z
- Profile URL: https://github.com/intake
GitHub Events
Total
- Create event: 20
- Release event: 1
- Issues event: 15
- Watch event: 11
- Delete event: 15
- Member event: 3
- Issue comment event: 66
- Push event: 60
- Pull request review comment event: 2
- Pull request review event: 12
- Pull request event: 45
- Fork event: 3
Last Year
- Create event: 20
- Release event: 1
- Issues event: 15
- Watch event: 11
- Delete event: 15
- Member event: 3
- Issue comment event: 66
- Push event: 60
- Pull request review comment event: 2
- Pull request review event: 12
- Pull request event: 45
- Fork event: 3
Committers metadata
Last synced: 4 days ago
Total Commits: 1,011
Total Committers: 25
Avg Commits per committer: 40.44
Development Distribution Score (DDS): 0.275
Commits in past year: 35
Committers in past year: 9
Avg Commits per committer in past year: 3.889
Development Distribution Score (DDS) in past year: 0.657
Name | Commits | |
---|---|---|
Anderson Banihirwe | a****e@u****u | 733 |
mclong | m****g@u****u | 77 |
pre-commit-ci[bot] | 6****] | 64 |
dependabot[bot] | 4****] | 46 |
Max Grover | m****x@g****m | 19 |
bonnland | b****d@u****u | 14 |
Julia Kent | 4****t | 13 |
Pascal Bourgault | b****l@o****a | 12 |
Charles Turner | 5****1 | 5 |
AS | a****g@m****e | 4 |
Paul Branson | b****7@o****u | 4 |
Dougie Squire | 4****e | 4 |
jbusecke | j****s@l****u | 2 |
Trevor James Smith | 1****e | 2 |
Paul Branson | p****n@c****u | 2 |
Aaron Spring | a****g | 1 |
Hauke Schulz | 4****s | 1 |
Jared Lewis | j****d@j****z | 1 |
Romain Beucher | r****r@a****u | 1 |
RondeauG | 3****G | 1 |
Sadie L. Bartholomew | s****w@n****k | 1 |
Sebastián Blanco | s****g@e****m | 1 |
Joseph Hamman | j****n@u****u | 1 |
Tobias Kölling | t****i@d****e | 1 |
garciampred | 9****d | 1 |
Committer domains:
- ucar.edu: 3
- die70.de: 1
- ext.inditex.com: 1
- ncas.ac.uk: 1
- anu.edu.au: 1
- jared.kiwi.nz: 1
- csiro.au: 1
- ldeo.columbia.edu: 1
- oa-31-mel.it.csiro.au: 1
- mpimet.mpg.de: 1
- ouranos.ca: 1
- ualr.edu: 1
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 228
Total pull requests: 454
Average time to close issues: 3 months
Average time to close pull requests: 5 days
Total issue authors: 64
Total pull request authors: 28
Average comments per issue: 3.73
Average comments per pull request: 1.02
Merged pull request: 427
Bot issues: 0
Bot pull requests: 114
Past year issues: 12
Past year pull requests: 40
Past year average time to close issues: about 1 month
Past year average time to close pull requests: 6 days
Past year issue authors: 8
Past year pull request authors: 10
Past year average comments per issue: 3.75
Past year average comments per pull request: 0.63
Past year merged pull request: 36
Past year bot issues: 0
Past year bot pull requests: 22
Top Issue Authors
- andersy005 (42)
- jbusecke (23)
- matt-long (19)
- aulemahal (17)
- ahuang11 (8)
- naomi-henderson (7)
- aaronspring (7)
- mgrover1 (7)
- dougiesquire (6)
- wachsylon (6)
- charles-turner-1 (5)
- fanchic (4)
- aradhakrishnanGFDL (4)
- jukent (4)
- dcherian (3)
Top Pull Request Authors
- andersy005 (238)
- pre-commit-ci[bot] (66)
- dependabot[bot] (48)
- mgrover1 (20)
- matt-long (17)
- jukent (14)
- aulemahal (13)
- charles-turner-1 (7)
- dougiesquire (5)
- aaronspring (3)
- bonnland (3)
- Zeitsperre (2)
- sadielbartholomew (2)
- jbusecke (2)
- d70-t (1)
Top Issue Labels
- enhancement (41)
- bug (33)
- usage question (28)
- documentation (7)
- discuss (3)
- good first issue (3)
- needs triage (3)
- feature (2)
- awaiting more information (2)
- upstream issue (2)
- help wanted (1)
Top Pull Request Labels
- dependencies (57)
- maintenance (51)
- enhancement (36)
- CI (26)
- documentation (22)
- usage question (14)
- bug-fix (12)
- feature (6)
- internal-change (5)
Package metadata
- Total packages: 2
-
Total downloads:
- pypi: 14,974 last-month
- Total docker downloads: 1,563
- Total dependent packages: 18 (may contain duplicates)
- Total dependent repositories: 86 (may contain duplicates)
- Total versions: 46
- Total maintainers: 3
pypi.org: intake-esm
An intake plugin for parsing an Earth System Model (ESM) catalog and loading netCDF files and/or Zarr stores into Xarray datasets.
- Homepage: https://intake-esm.readthedocs.io
- Documentation: https://intake-esm.readthedocs.io
- Licenses: Apache Software License 2.0
- Latest release: 2025.2.3 (published 3 months ago)
- Last Synced: 2025-04-25T13:05:31.974Z (1 day ago)
- Versions: 27
- Dependent Packages: 15
- Dependent Repositories: 22
- Downloads: 14,974 Last month
- Docker Downloads: 1,563
-
Rankings:
- Dependent packages count: 1.596%
- Downloads: 1.872%
- Docker downloads count: 2.319%
- Dependent repos count: 3.12%
- Average: 3.631%
- Forks count: 6.29%
- Stargazers count: 6.588%
- Maintainers (3)
conda-forge.org: intake-esm
An intake plugin for parsing an Earth System Model (ESM) collection/catalog and loading assets (netCDF files and/or Zarr stores) into xarray data sets.
- Homepage: https://github.com/intake/intake-esm
- Licenses: Apache-2.0
- Latest release: 2022.9.18 (published over 2 years ago)
- Last Synced: 2025-04-25T13:05:45.443Z (1 day ago)
- Versions: 19
- Dependent Packages: 3
- Dependent Repositories: 64
-
Rankings:
- Dependent repos count: 4.392%
- Dependent packages count: 15.638%
- Average: 20.327%
- Forks count: 28.355%
- Stargazers count: 32.922%
Dependencies
- dask >=2021.9
- fastprogress >=1.0.0
- fsspec >=2021.7.0
- intake >=0.6.5
- netCDF4 >=1.5.5
- pydantic >=1.8.2
- requests >=2.24.0
- xarray >=0.19,
- xcollection *
- zarr >=2.5
- actions/checkout v3 composite
- codecov/codecov-action v3.1.1 composite
- mamba-org/provision-with-micromamba main composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- pypa/gh-action-pypi-publish v1.6.4 composite
- cftime
- codecov
- fastprogress >=1.0.0
- fsspec >=2022.11.0
- gcsfs >=2022.11.0
- h5netcdf >=0.8.1
- intake <2.0
- ipython
- matplotlib
- netcdf4 >=1.5.5
- pandas >=2.1.0
- pip
- pooch
- pre-commit
- pydantic >=2.0
- pydap
- pytest
- pytest-cov
- pytest-mock
- pytest-sugar
- pytest-xdist
- s3fs >=2022.11.0
- scipy
- xarray >=2022.06
- xarray-datatree
- zarr >=2.12
Score: 18.15963735674229