Metadata-Version: 2.4
Name: nlpkit14
Version: 0.3.1
Summary: Execute fourteen NLP practical programs with commented source and expected outputs
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: nltk<4,>=3.9
Requires-Dist: spacy<4,>=3.8
Requires-Dist: scikit-learn<2,>=1.5
Requires-Dist: requests<3,>=2.32
Requires-Dist: beautifulsoup4<5,>=4.12
Requires-Dist: torch<3,>=2.4
Requires-Dist: transformers<5,>=4.45
Requires-Dist: benepar<0.3,>=0.2.0
Requires-Dist: sentencepiece<1,>=0.2
Provides-Extra: models
Requires-Dist: torch<3,>=2.4; extra == "models"
Requires-Dist: transformers<5,>=4.45; extra == "models"
Requires-Dist: benepar<0.3,>=0.2.0; extra == "models"
Requires-Dist: sentencepiece<1,>=0.2; extra == "models"

# nlpkit14

Install once:

```sh
pip install --upgrade nlpkit14
```

Use directly:

```python
import nlpkit14 as n
n.q1()
```

No setup() call is required in version 0.3.1. The question automatically downloads any missing language resources or models on first use. The installation includes the Python dependencies for all fourteen exercises, including large neural packages. First-time downloads require internet and may take time and disk space. After preparation, most exercises work offline; q8 fetches a live website and still needs internet.

Use q1() through q14(). n.questions() lists questions. n.source(1) displays runnable source with the question, expected output, and extra notes as comments. Questions execute real code and print computed results, rather than printing sample answers.

Resources are cached under ~/.nlpkit14 by default; set NLPKIT14_DATA before first use for a different location. spaCy models are installed into the active Python environment automatically by its official download command. A writable environment is required. Existing caches are reused. Offline installation needs local copies of all dependency wheels, spaCy model wheels, and the model/data cache; an initial empty offline machine cannot download missing files.

## Release status and limits

0.3.1 is prepared locally and must be uploaded before pip can obtain it publicly. This release changes automatic preparation and dependency metadata. Full dependency resolution, all large model downloads, and all model inferences have not been tested end to end. See TEST_RESULTS.md. Reference outputs can vary by model version; no zero-error or every-platform guarantee is claimed.
