Shikaku (詩客)
Toolbox for Japanese text.
Example
from shikaku import load_aozorabunko, TextModel, WordCloud
import matplotlib.pyplot as plt
# Aozora Bunko, author_id = 35, work_id = 1567 ==> Run, Melos!
text = load_aozorabunko(35, 1567)
# Text generator using Markov chains.
model = TextModel()
model.fit(text)
result = model.generate()
print(result)
# Word cloud.
wc = WordCloud()
wc.fit(text)
result = wc.generate()
result.to_file("wc.png")
# Visualize Markov chains (preliminary).
model = TextModel(state_size=1)
model.fit("吾輩は猫である。名前はまだない。")
model.plot()
plt.savefig("model.png")
1 maintainer
Metadata
1 maintainer
Release files for shikaku 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| shikaku-0.2.4.tar.gz | 9.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| shikaku-0.2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 19.7 kB
Release files / shikaku-0.2.4.tar.gz
| Download URL | shikaku-0.2.4.tar.gz |
|---|---|
| Size | 9.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
15dd54445f5f5a5bf715efa6ba80545f44dd7581bff923bc3ec238fe40e0a8b0
|
|
BLAKE2b-256 checksum How to use checksums |
05141410a896c8890fed84a9715ffd4e037f7e92b199c7d466dd08d9a6e785e6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
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Transparency logRelease files / shikaku-0.2.4-py3-none-any.whl
| Download URL | shikaku-0.2.4-py3-none-any.whl |
|---|---|
| Size | 10.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9f76eb1146a5951a7dbe5f67d03833cdf30e36b47cc32e31c86adf2747fc5dcd
|
|
BLAKE2b-256 checksum How to use checksums |
a2e702e7792e60c5f9b2fc2d550fc09d05d1b0fe85a17e7fb583172778fb840e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 9, 2025.
Transparency log
