# Clustered Hierarchical Entropy-Scaling Search of Astrophysical and Biological Data
CHESS is a search algorithm for large data sets when the data exhibits certain geometric properties.
All classes and functions are very well documented in the code. If you want more details, read them. The [paper](https://arxiv.org/pdf/1908.08551.pdf) is available on the arXiv.
[](https://lgtm.com/projects/g/nishaq503/CHESS/context:python) [](https://codecov.io/gh/thoward27/chess) [](https://clustered-hierarchical-entropy-scaling-search.readthedocs.io/en/latest/?badge=latest)
## Installation
Download this repository…
`bash git clone https://github.com/nishaq503/CHESS.git `
## Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
## License [MIT](https://choosealicense.com/licenses/mit/)
1 maintainer
Metadata
1 maintainer
Release files for CHESS-python-nightly 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| CHESS-python-nightly-1.1.0.tar.gz | 19.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| CHESS_python_nightly-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 32.1 kB
Release files / CHESS-python-nightly-1.1.0.tar.gz
| Download URL | CHESS-python-nightly-1.1.0.tar.gz |
|---|---|
| Size | 19.7 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.8.0
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Release files / CHESS_python_nightly-1.1.0-py3-none-any.whl
| Download URL | CHESS_python_nightly-1.1.0-py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.2.0 requests-toolbelt/0.9.1 tqdm/4.39.0 CPython/3.8.0
|
](https://lgtm.com/projects/g/nishaq503/CHESS/context:python){kind=link}
](https://codecov.io/gh/thoward27/chess){kind=link}