semvec/pypi-packages huggingface dataset:
tcp-reader 0.1.0.post1
TCP Stream Reader
License: MIT

# TCP Stream Reader

## Description

Reads raw ethernet data, splits them by TCP stream and use a TCPReader per stream.

## Example

Example usage of TCPManager with win_pcap:

```python
from tcp_reader import TCPManager
from winpcapy import WinPcapUtils

def print_callback(host, port, data):
    print('Received data from', host, 'on Port', port + ':', str(data))

tcp_manager = TCPManager(callback=print_callback, host=['93.184.216.34/32'], client=['192.168.0.0/16'])
WinPcapUtils.capture_on('*Ethernet*', tcp_manager.receive_raw_win_pcap)
```
sklearn2gem 0.1.1
sklearn2gem converts a Pickle'd scikit-learn model into a rubygem
License: MIT
Requires Python: >=3.6.0

# sklearn2gem

[![Build Status](https://travis-ci.org/stewartpark/sklearn2gem.svg?branch=master)](https://travis-ci.org/stewartpark/sklearn2gem)
[![Requirements Status](https://requires.io/github/stewartpark/sklearn2gem/requirements.svg?branch=master)](https://requires.io/github/stewartpark/sklearn2gem/requirements/?branch=master)
[![PyPI version](https://badge.fury.io/py/sklearn2gem.svg)](https://badge.fury.io/py/sklearn2gem)

⚡ sklearn2gem ports your scikit-learn model into a fast ruby C binding!

# Getting started

Install sklearn2gem using `pip`:

```
pip install sklearn2gem
```

or via `easy_install`:

```
easy_install sklearn2gem
```

After that, dump your scikit-learn model with `sklearn.externals.joblib`, and run `sklearn2gem model_name@version your_model.pkl foo/bar/model_name`. You should be able to see a newly created folder named `model_name` under `foo/bar/`.

See [`examples/iris.py`](https://github.com/stewartpark/sklearn2gem/blob/master/examples/iris.py) to try it out.

To produce a pre-compiled binary gem, use [gem-compiler](https://github.com/luislavena/gem-compiler).

# What machine learning algorithms are supported?

Since sklearn2gem uses `nok/sklearn-porter` to convert a model into a C file, you can refer to [this page](https://github.com/nok/sklearn-porter#machine-learning-algorithms).