kbow

Minimal fuss Python implementation of a Kmer bag of words model.

Strictly this does not do anything Scikit-Learn's CountVectorizer could also do. However, the purpose of this implementation is to be explicit, and to aid pedagogically in the construct of these models.

Metadata

Release files for kbow 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for kbow 0.1.0
File	Size	Uploaded
kbow-0.1.0.tar.gz	4.2 kB	Jun 2, 2025	Details

Built distribution (wheel)

Table of built distributions (wheels) for kbow 0.1.0
File	Interpreter	ABI	Platform	Reset
kbow-0.1.0-py3-none-any.whl 4.4 kB Jun 2, 2025	Python 3	none	any	Details

Total release size: 8.6 kB

Release files / kbow-0.1.0.tar.gz

Download URL	kbow-0.1.0.tar.gz
Size	4.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`24d9f182eec01a96fda45294c7660cc231356047f31c1b98df93eb410e932f82`
BLAKE2b-256 checksum How to use checksums	`ebab381139562da3f51db92a2b081b4567eff0488b3d481a56d39b1138573062`
Upload date	Jun 2, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.3`

Release files / kbow-0.1.0-py3-none-any.whl

Download URL	kbow-0.1.0-py3-none-any.whl
Size	4.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`4a28d16f76ea3bac67c0fd46535b86dcc7740bdd885c589992d5624863655124`
BLAKE2b-256 checksum How to use checksums	`62ee32130b4d3e2269c0384d59227ab28cf9f4c3c0dc368a37eab2d2c54a452a`
Upload date	Jun 2, 2025
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.1.0 CPython/3.13.3`

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This release

0.1.0 This release

Jun 2, 2025 2 release files

kbow 0.1.0