semvec/pypi-packages huggingface dataset:
dhnn 0.1.12
A Discrete Hopfield Neural Network Framework in python.
License: MIT

# DHNN

A **D**iscrete **H**opfield **N**eural **N**etwork Framework in python.

[![Build Status](https://travis-ci.com/Zeroto521/DHNN.svg?branch=master)](https://travis-ci.com/Zeroto521/DHNN) [![codecov](https://codecov.io/gh/Zeroto521/dhnn/branch/master/graph/badge.svg)](https://codecov.io/gh/Zeroto521/dhnn) [![](https://img.shields.io/pypi/v/dhnn.svg)](https://pypi.org/project/dhnn/) [![PyPI pyversions](https://img.shields.io/pypi/pyversions/ansicolortags.svg)](https://pypi.org/project/dhnn/)

## Introduction

DHNN is a minimalistic and Numpy based implementation of the [Discrete Hopfield Network](http://en.wikipedia.org/wiki/Hopfield_network). DHNN can learn (memorize) patterns and remember (recover) the patterns when the network feeds those with noises.

## Installation

Just use pip:

```bash
pip install dhnn
```

Or download `dhnn` to a directory which your choice and use `setup` to install script:

```bash
>>> git clone https://github.com/Zeroto521/DHNN.git
>>> python setup.py install
```

## Authors

| <img src="https://avatars3.githubusercontent.com/u/4463558?v=4" alt="yosukekatada" width="100px" height="100px"/> | <img src="https://avatars1.githubusercontent.com/u/25895405?v=4" alt="Zeroto521" width="100px" height="100px"/> |
| :---------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------: |
|                                  [yosukekatada](https://github.com/yosukekatada)                                  |                                    [Zeroto521](https://github.com/Zeroto521)                                    |

## TODO

-   [x] more flag, add 0/1 flag or other flag.
-   [ ] optimize loop, try numba, Cpython or any other ways.
-   [ ] optimize memory.

## License

MIT License. [@yosukekatada](https://github.com/yosukekatada), [@Zeroto521](https://github.com/Zeroto521)

## References

-   http://rishida.hatenablog.com/entry/2014/03/03/174331
genconminer 0.1.7
Wraps Pip packages (beautifulsoup and requests) to a more concise content extractor
License: MIT
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*

# Gencon Miner

A general content miner that leverages on Beautiful Soup and Requests to handle extraction. The main goal is to always imagine in terms of targetting parent elements in an HTML form then getting group of tags given that parent.

```python
from gencon_miner import GenconMiner
```

## From URL

```python
url_miner = GenconMiner(url="http://google.com")
txt = url_miner.extract('title')
print(txt[0].text) # Google
```

## From text

```python
text_miner = GenconMiner(text="<p class='myclass'>Hello</p>")
txt = text_miner.extract('.myclass')
print(txt[0].text) # Hello
```

## Convert all tag content to string

Note that contents in a tag will be delimited using newline.

```python
meaning_of_life = """
    <p class='myclass'>
        Hello
        <span>darkness my old friend</span>
    </p>
    <b>And another one</b>
"""
bulk_miner = GenconMiner(text=meaning_of_life)
print(bulk_miner.to_text()) # Hello\ndarkness my old friend\nAnd another one
```

## Parent to target

Use-case on walking document and extracting the targets.

```python
song_of_the_day = """
    <table id="mother">
        <tr>
            <td class="target-1">Mamma Mia</td>
            <td class="target-2">Here I go again</td>
            <td class="target-3">My my</td>
            <td class="target-4">How can I resist you</td>
        </tr>
    </table>
"""
walk_miner = GenconMiner(text=song_of_the_day)
print(walk_miner.extract('#mother', '.target-1')[0].text) # Mamma Mia
print(walk_miner.extract('#mother', '.target-3')[0].text) # My my
print(walk_miner.extract('#mother', 'td'))
# [
#   <td class="target-1">Mamma Mia</td>,
#   <td class="target-2">Here I go again</td>,
#   <td class="target-3">My my</td>,
#   <td class="target-4">How can I resist you</td>
# ]
```

## Author

Almer Mendoza
ezhashlib 1.1.0
Convenience wrapper around the hashlib library
License: MIT



# Convenience wrapper around the hashlib library.


## Requirements:
**_hashlib_**



## Usage:



**import _ezhashlib_ as _ehl_**



## Hash functions available

ehl.sha3_224()

ehl.sha224()

ehl.shake_256()

ehl.sha512()

ehl.sha384()

ehl.sha3_384()

ehl.sha1()

ehl.sha3_512()

ehl.sha256()

ehl.blake2b()

ehl.blake2s()

ehl.md5()

ehl.sha3_256()