semvec/pypi-packages huggingface dataset:
lzwfile 0.1.5
Python module for decoding compressed lzw files
License: MIT
Requires Python: >=3.6.0
Keywords: lzw

# LZWFILE
Python module for decoding lzw files. This is based directly off Mark Adler's C library for decoding lzw files.
Some slight modifications were done for my own use case.

## Getting Started

```Python
from lzwfile import decompress

# File name can be used if located within same directory,
# if not please use the absolute path.

file_name = 'compressed_file.Z'

decompressed_data = decompress(file_name)
```

## Notes

I'm planning on adding encoding functionality to this package as well to further my understanding
of the lzw compression algorithm.
py-lingo 0.0.1b1
Utilities for saving Scikit-Learn Linear Models in HDF5 format.
License: MIT

# py-lingo

Utilities for helping you deploy a subset of Scikit-Learn linear models in Go. See the 
`lingo` repository for more details.

This package is particularly focussed on saving linear models _for inference_ purposes.

The package has been tested and supports the following Linear Model variants:

* **LinearRegression**
* **LogisticRegression**
* **Ridge**
* **RidgeClassifier**
* **Lasso**
* **SGDRegressor**
* **SGDClassifier**

## Quickstart

You can install `py-lingo` with.

```bash
pip install py-lingo
```  

You'll then be able to import it in your code with:

```python
import pylingo
from sklearn.linear_model import LinearRegression

model = LinearRegression()

pylingo.dump(model, "model.h5")

loaded_model = pylingo.load("model.h5")
```