connectome
A library for datasets containing heterogeneous data
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
2 of 11 committers (18.2%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.1%) to scientific vocabulary
Keywords
data-processing
pipelines
python
Last synced: 6 months ago
·
JSON representation
Repository
A library for datasets containing heterogeneous data
Basic Info
- Host: GitHub
- Owner: neuro-ml
- License: apache-2.0
- Language: Python
- Default Branch: master
- Homepage: https://neuro-ml.github.io/connectome/
- Size: 2.75 MB
Statistics
- Stars: 13
- Watchers: 6
- Forks: 1
- Open Issues: 15
- Releases: 34
Topics
data-processing
pipelines
python
Created over 5 years ago
· Last pushed over 1 year ago
Metadata Files
Readme
License
README.md
Connectome is a framework for datasets management with strong emphasis on simplicity, composability and reusability.
Features
- Self-consistency: connectome encourages data transformations that keep entries' fields consistent
- Caching: transformations' caching works out of the box and supports both caching to RAM and to Disk
- Automatic cache invalidation: connectome tracks all the changes made to a dataset and automatically invalidates the cache when something changes, making sure that your cache is always consistent with the data
- Invertible transformations: write consistent pre- and post- processing to build production-ready pipelines
Install
The simplest way is to get it from PyPi:
shell
pip install connectome
Or if you want to try the latest version from GitHub:
```shell git clone https://github.com/neuro-ml/connectome.git cd connectome pip install -e .
or let pip handle the cloning:
pip install git+https://github.com/neuro-ml/connectome.git ```
Getting started
The docs are located here
Also, you can check out our Intro to connectome series of
tutorials here
Acknowledgements
Some parts of our automatic cache invalidation machinery vere heavily inspired by the cloudpickle project.
Owner
- Name: NeuroML
- Login: neuro-ml
- Kind: organization
- Location: Moscow, Russia
- Website: https://neuro.ml/
- Repositories: 20
- Profile: https://github.com/neuro-ml
GitHub Events
Total
- Issues event: 1
- Watch event: 1
Last Year
- Issues event: 1
- Watch event: 1
Issues and Pull Requests
Last synced: over 1 year ago
All Time
- Total issues: 62
- Total pull requests: 41
- Average time to close issues: 4 months
- Average time to close pull requests: 2 days
- Total issue authors: 3
- Total pull request authors: 5
- Average comments per issue: 0.1
- Average comments per pull request: 0.9
- Merged pull requests: 40
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: 9 minutes
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- maxme1 (58)
- samokhinv (2)
- mridula28 (1)
- kurmukovai (1)
Pull Request Authors
- maxme1 (35)
- STNLd2 (4)
- samokhinv (2)
- alimbfromlimb (1)
- Ganddalf (1)
Top Labels
Issue Labels
enhancement (9)
bug (5)
usability (5)
optimization (4)
safety (1)
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 99 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 34
- Total maintainers: 2
pypi.org: connectome
A library for datasets containing heterogeneous data
- Homepage: https://github.com/neuro-ml/connectome
- Documentation: https://connectome.readthedocs.io/
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Latest release: 0.10.0
published almost 2 years ago
Rankings
Dependent packages count: 10.1%
Downloads: 12.4%
Stargazers count: 16.6%
Average: 16.7%
Dependent repos count: 21.6%
Forks count: 22.7%
Last synced:
6 months ago
Dependencies
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