mmseqspy provides utilities for clustering protein sequences and creating train-test splits that respect sequence similarity. It requires MMseqs2 to be installed and in your PATH. Features include sequence clustering, cluster-aware train/test splits, k-fold cross-validation, and constrained dataset splitting.
Metadata
Release files for mmseqspy 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| mmseqspy-0.2.0.tar.gz | 10.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mmseqspy-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.3 kB
Release files / mmseqspy-0.2.0.tar.gz
| Download URL | mmseqspy-0.2.0.tar.gz |
|---|---|
| Size | 10.0 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.1
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Release files / mmseqspy-0.2.0-py3-none-any.whl
| Download URL | mmseqspy-0.2.0-py3-none-any.whl |
|---|---|
| Size | 8.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.1
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