JOSS: https://github.com/MLMI2-CSSI/foundry
chemistry data-science datasets machine-learning materials-science
Score: 13.834277354855677
Last synced: about 2 hours ago
JSON representation
Repository metadata:
Simplifying the discovery and usage of machine-learning ready datasets in materials science and chemistry
- Host: GitHub
- URL: https://github.com/MLMI2-CSSI/foundry
- Owner: MLMI2-CSSI
- License: mit
- Created: 2020-01-24T20:24:53.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2026-01-22T23:07:40.000Z (5 months ago)
- Last Synced: 2026-06-16T19:03:19.095Z (5 days ago)
- Topics: chemistry, data-science, datasets, machine-learning, materials-science
- Language: Python
- Homepage:
- Size: 46.4 MB
- Stars: 86
- Watchers: 6
- Forks: 18
- Open Issues: 36
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Support: docs/support/faq.md
Owner metadata:
- Name: Machine Learning Materials Innovation Infrastructure - NSF CSSI Project
- Login: MLMI2-CSSI
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/60273950?v=4
- Repositories: 3
- Last Synced at: 2023-03-05T08:04:20.920Z
- Profile URL: https://github.com/MLMI2-CSSI
GitHub Events
Total
- Create event: 4
- Fork event: 3
- Issue comment event: 4
- Pull request event: 4
- Push event: 24
- Release event: 1
- Watch event: 3
- Total: 43
Last Year
- Create event: 1
- Fork event: 1
- Issue comment event: 1
- Pull request event: 2
- Push event: 11
- Release event: 1
- Watch event: 2
- Total: 19
Committers metadata
Last synced: 3 days ago
Total Commits: 1,301
Total Committers: 24
Avg Commits per committer: 54.208
Development Distribution Score (DDS): 0.77
Commits in past year: 11
Committers in past year: 2
Avg Commits per committer in past year: 5.5
Development Distribution Score (DDS) in past year: 0.182
| Name | Commits | |
|---|---|---|
| Ben Blaiszik | b****k@u****u | 299 |
| Aristana Scourtas | a****s@g****m | 242 |
| Ribhav Bose | b****v@g****m | 130 |
| KJ | k****3@g****m | 112 |
| zk794 | z****k@g****m | 108 |
| Ethan Truelove | e****e@u****u | 108 |
| Aadit-Ambadkar | a****r@g****m | 62 |
| Marcus Schwarting | m****s@M****l | 54 |
| repo-visualizer | r****r | 40 |
| Isaac Darling | 6****g | 34 |
| Aristana Scourtas | a****a@u****u | 30 |
| Steven Wangen | i****2@g****m | 23 |
| ZKatok | z****k@s****g | 14 |
| github-actions[bot] | 4****] | 11 |
| Ribhav Bose | b****r@u****u | 6 |
| Marcus Schwarting | m****t@M****l | 6 |
| BraedenCu | b****0@g****m | 4 |
| Logan Ward | W****T | 4 |
| Nathaniel Martinez | n****3@u****u | 4 |
| C. Y. Schneck | 2****k | 2 |
| Ian Foster | f****r@a****v | 2 |
| NathanPruyne | n****e@g****m | 2 |
| Ryan | r****d@a****v | 2 |
| Sterling G. Baird | 4****d | 2 |
Issue and Pull Request metadata
Last synced: 24 days ago
Total issues: 148
Total pull requests: 126
Average time to close issues: 8 months
Average time to close pull requests: 9 days
Total issue authors: 11
Total pull request authors: 16
Average comments per issue: 1.82
Average comments per pull request: 1.3
Merged pull request: 96
Bot issues: 0
Bot pull requests: 18
Past year issues: 0
Past year pull requests: 7
Past year average time to close issues: N/A
Past year average time to close pull requests: about 2 hours
Past year issue authors: 0
Past year pull request authors: 1
Past year average comments per issue: 0
Past year average comments per pull request: 0.71
Past year merged pull request: 6
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- kjschmidt913 (53)
- ascourtas (51)
- blaiszik (22)
- WardLT (9)
- BenGalewsky (5)
- marshallmcdonnell (3)
- blue442 (1)
- vsoch (1)
- zyygh (1)
- rabernat (1)
- leschultz (1)
Top Pull Request Authors
- blaiszik (50)
- ascourtas (18)
- allcontributors[bot] (16)
- blue442 (12)
- kjschmidt913 (10)
- Aadit-Ambadkar (5)
- WardLT (3)
- dependabot[bot] (2)
- wdwzyyg (2)
- isaac-darling (2)
- cyschneck (1)
- marshallmcdonnell (1)
- kurtmckee (1)
- ianfoster (1)
- rjacobs914 (1)
Top Issue Labels
- enhancement (17)
- refactor (16)
- documentation and examples (15)
- bug (9)
- testing and deployment (3)
- good first issue (2)
- v-Automate (2)
- v-UI-overhaul (2)
- data (2)
- Summer-2023 (2)
- dataset (2)
- planning (1)
- higher-priority (1)
- publish data (1)
- outreach (1)
- OSS-prep (1)
Top Pull Request Labels
- DO NOT MERGE (3)
- dependencies (2)
Package metadata
- Total packages: 2
-
Total downloads:
- pypi: 276 last-month
- Total docker downloads: 66
- Total dependent packages: 1 (may contain duplicates)
- Total dependent repositories: 1 (may contain duplicates)
- Total versions: 47
- Total maintainers: 3
pypi.org: foundry-ml
Package to support simplified application of machine learning models to datasets in materials science
- Homepage: https://github.com/MLMI2-CSSI/foundry
- Documentation: https://foundry-ml.readthedocs.io/
- Licenses: MIT License
- Latest release: 1.2.2 (published 5 months ago)
- Last Synced: 2026-06-18T20:00:35.864Z (3 days ago)
- Versions: 43
- Dependent Packages: 1
- Dependent Repositories: 1
- Downloads: 276 Last month
- Docker Downloads: 66
-
Rankings:
- Docker downloads count: 4.648%
- Dependent packages count: 4.786%
- Stargazers count: 8.469%
- Forks count: 9.326%
- Downloads: 9.719%
- Average: 9.75%
- Dependent repos count: 21.552%
- Maintainers (3)
conda-forge.org: foundry_ml
- Homepage: https://github.com/MLMI2-CSSI/foundry
- Licenses: MIT
- Latest release: 0.5.0 (published over 3 years ago)
- Last Synced: 2026-04-01T01:58:43.652Z (3 months ago)
- Versions: 4
- Dependent Packages: 0
- Dependent Repositories: 0
-
Rankings:
- Dependent repos count: 34.025%
- Stargazers count: 43.05%
- Average: 43.565%
- Forks count: 46.009%
- Dependent packages count: 51.175%
Dependencies
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- foundry_ml *
- matplotlib *
- foundry_ml *
- matminer *
- matplotlib *
- pandas *
- pymatgen *
- scikit-learn *
- foundry_ml *
- keras-unet *
- opencv-python *
- scikit-image *
- scikit-learn *
- tensorflow *
- foundry_ml *
- pandas *
- foundry_ml *
- matplotlib *
- seaborn *
- dlhub_sdk >=1.0.0
- globus-sdk >=3,<4
- h5py >=2.10.0
- json2table >=1.1.5
- mdf-connect-client >=0.4.0
- mdf_forge >=0.8.0
- numpy >=1.15.4
- pandas >=0.23.4
- pydantic >=1.6.1
- requests >=2.18.4
- scikit-learn >=1.0
- six >=1.11.0
- tensorflow >=2
- torch >=1.8.0
- tqdm >=4.19.4
- tqdm >=4.64
- dlhub_sdk >=1.0.0
- globus-sdk >=3,<4
- h5py >=2.10.0
- json2table *
- mdf_connect_client >=0.4.0
- mdf_forge >=0.8.0
- numpy >=1.15.4
- pandas >=0.23.4
- pydantic >=1.4
- flake8 * test
- jsonschema * test
- pytest >=7 test
- pytest-cov >=2.12 test