semvec/pypi-packages huggingface dataset:
ciphon 0.1.0
A package containing ciphers, what did you expect?
Requires Python: >=3.6

WARNING: this package contains bad programming and probably nonsense errors because of that.\
if you haven't already guessed from the name, this package contains ciphers(encryption/decryption methods for text)\
it currently has 7 of them:
- Simple substitution cipher
- Caesar cipher
- ROT13
- ROT5
- ROT18
- ROT47
- Vigenère cipher\
they all have a function and that's it\
they are explained both in Wikipedia(ROT5, ROT18, ROT7 are explained in the "Variants"section of ROT13) and the description of the their funtions\
i probably will be adding more soon, but for now this is all i got\
and if you want you can contact me on discord adam_Barfi#3279
py-discord 0.0.1
A Discord API wrapper.
Requires Python: >=3.9.0

# PyDiscord

A simple Discord API that uses the new interactions framework. 

## Installing

Python 3.9 or higher is required. It may work on earlier versions; but they are untested.

To install the library:

-- to do later -- 


## Versioning Policy

PyDiscord may work on earlier versions of Python, but is currently developed with Python 3.9. 

The project uses semantic versioning - MAJOR.MINOR.PATCH-prerelease. 

Compatibility will be maintained with Python versions on major versions - for example, all 1.x.y versions will 
support Python 3.9, and only considered for being dropped at 2.x.y. Discord may change their API from time to time, forcing breaking updates. These are outside the project's control.
loris 0.5.3
read and write files from neuromorphic cameras

# Loris
[![Travis](https://img.shields.io/travis/neuromorphic-paris/loris/master.svg?label=Travis%20CI)](https://www.travis-ci.org/neuromorphic-paris/loris)

With loris you can read and write different file formats from neuromorphic cameras such as **.aedat4**, **.dat**, [.es](https://github.com/neuromorphic-paris/event_stream) or **.csv**. Loris is also an [amazing animal](https://giphy.com/search/slow-loris)

### Supported formats
|           | version | read    | write   |
|-----------|--------:|:-------:|:-------:|
| .aedat4   | 4       | &#9745; | &#9744; |
| .dat      | 1/2     | &#9745; | &#9744; |
| .es       | 2.x     | &#9745; | &#9745; |
| .csv      | -       | &#9745; | &#9744; |

### Install
~~~python
pip install loris
~~~

### How to loris
##### Read a file, for example a .dat file and loop over all events
~~~python
import loris
my_file = loris.read_file("/path/to/my-file.dat")
events = my_file['events']

for event in events:
    print("ts:", event.t, "x:", event.x, "y:", event.y, "p:", event.p)
~~~

##### Write events from an array to an .es file
~~~python
ordering = "xytp"  # corresponds to the order in your array
loris.write_events_to_file(event_array, "/path/to/my-file.es", ordering)
~~~

##### Write structured events (with dtypes) to an .es file
~~~python
loris.write_events_to_file(structured_event_array, "/path/to/my-file.es")
~~~

### Windows test (for developers)

To make sure the library works on Windows (if you use macOS or Linux), follow these steps:

1. Download Vagrant (https://www.vagrantup.com/)
2. `cd windows`
3. `vagrant up` (this will download a virtual machine and build the package)
4. `vargrant ssh` (optional, to inspect the Windows VM)
5. `vagrant destroy -f` (cleanup)

![loris](loris.gif "The Loris Banner")
sqlmakeuper 0.1.4
SQL Formatter based on sqlparse
Requires Python: >=3.6

# sqlmakeuper

Python library with CLI interface for sql formatting based on [sqlparse](https://github.com/andialbrecht/sqlparse)

## Installation

```bash
pip install sqlmakeuper
```

## Using

### Format with default parameters

```bash
sqlmakeup --path /path/with/files/to/format
```

- Default parameters are `(reindent=True, indent_width=4, keyword_case="lower", identifier_case="lower", comma_first=True,)`

### Format with custom parameters

```bash
sqlmakeup --path /path/with/files/to/format --parameters '{"comma_first":0}'
```

### Check with custom parameters

```bash
sqlmakeup --path /path/with/files/to/format --check
```
yknsshanalysis 1.3.0
Analyze auth.log
Requires Python: >=3.6

# yknsshanalysis

Linuxサーバの一つであるUbuntu OSにおいてsshアクセスが記録されるauth.logを読み込み、不正ログインを分析する。
sshによるログイン試行のうち、ログイン失敗が記録されたものについて、IPアドレスの所属国と出現回数を分析し、視覚化する。
出力はCSVリストおよび円グラフ。

# install
pip install -U yknsshanalysis

# uninstall
pip uninstall -y yknsshanalysis


# オプション
## addr
auth.logファイルの場所を指定。初期値は/var/log/auth.log

## show_top
解析結果のグラフ表示の際、アクセス元上位何カ国を表示するか指定。初期値は5カ国。

## ignore_less
同一IPからのアクセスが指定回数以下の場合カウントから除外する。初期値は50回。

## expire_whois
WHOIS で取得した値を保持する期間。期限が過ぎた参照値は取得し直す。デフォルト値は30日。

## whois_url
IPアドレスからアクセス元の国名を取得する際に参照するAPIのアドレス。"whois_url=auto"を指定するとリストから正しく取得できるものを巡回する。

## ip_dict
WHOIS APIで判明した国名を保存し、次回以降キャッシュを利用することで高速化をはかる。デフォルトはキャッシュONでファイル名は"ip_whois_history.pkl"

キャッシュを利用しない場合は"ip_dict=None"と入力する

## group_by_ip
分析内容を変更するフラグ。このフラグが存在する場合、国別の集計を行わなわず、アクセス元IPアドレスと所属国および攻撃数を表示する。

## export_graph_name
分析内容（デフォルトではsshでのログイン試行のうち、ログインに失敗したパターンにおけるアクセス元IPアドレスの所属国分析）を示すグラフのファイル名を変更する。デフォルトは"sshanalysis_result.png"

## export_csv_name
グラフの示す数値がリスト形式で出力される。本設定で出力されるCSVファイル名を指定できる。デフォルトは"sshanalysis_result.csv"

## export_all_ip:
ログファイル内に存在するすべてのIPアドレスと出現回数のリストを出力するフラグ。出力先は"export_iplist_name"で指定する。

## export_iplist_name
"export_all_ip"オプションを指定した場合、ログファイル内のすべてのIPアドレスと出現回数のリストをCSV形式で保存する。本設定で出力されるCSVファイル名を指定できる。
デフォルトは"sshanalysis_ip_countlist.csv"

# Example
yknsshanalysis addr='./auth.log' show_top=6 ignore_less=100 whois_url="http://ipwhois.app/json/xxx" ip_dict="dict.pkl" export_graph_name="result.png" export_all_ip
pylint_aiida 0.1.1
A small plugin for aiida-core related linting.
Requires Python: >=3.7

# pylint-aiida

[![PyPI version][pypi-badge]][pypi-link]

A small plugin for aiida-core related linting.

## Usage

```console
$ pip install pylint_aiida
```

Then add to your pylint configuration, e.g. in `pyproject.toml`:

```toml
[tool.pylint.master]
load-plugins = ["pylint_aiida"]
```

[pypi-badge]: https://img.shields.io/pypi/v/pylint_aiida.svg
[pypi-link]: https://pypi.org/project/pylint_aiida
colorcluster 1.2.1
Reduce color of the picture
Requires Python: >=3.6

# colorcluster

Reducing Color of pictures by KMeans clustering.

# Options

## input_fig_path
The file path of the image to be processed.

## color_num
Set the number of colors to be reduced. Default:8

## show_img
Pop up the processed picture when descripted.

## export_fig_path
Set the file path of output picture. Default:"result.jpg"

## export_color_array
Outputs the central color obtained by clustering in CSV format when descripted.

## export_array_path
Set  the file path of output of the above CSV file. Default:"array.csv"
pysvgexport 1.2.2
A package for exporting svg format
Requires Python: >=3.6

# PySVGExport

![Python Version Support](https://img.shields.io/badge/python-3.6+-blue)
![PyPI Version](https://img.shields.io/pypi/v/pysvgexport?label=PyPI&logo=pypi)
[![GitHub license](https://img.shields.io/github/license/vantrong291/pysvgexport)](https://github.com/vantrong291/pysvgexport/blob/main/LICENSE)

## _SVGExport for Python_

Idea from [svgexport] using for nodejs

### Install via pip

```shell
pip3 install pysvgexport
```

### Usage

##### 1. Command-line

```shell
# See instruction
svgexport -h

# Export command example
svgexport -f SVG_FILE_PATH -s SCALE -o OUT_PUT_PNG
```

##### 2. Inside a Python project

```python
from pysvgexport import SVGExport

svg_data = '''
    <svg xmlns="http://www.w3.org/2000/svg"
         xmlns:xlink="http://www.w3.org/1999/xhtml" width="235.6875px" 
         height="112.37257096319047px" 
         viewBox="0 0 235.6875 112.37257096319047">
        <defs>
            <path d="M 29.050328462552656,81.24213909012583 A 120.43422075282764 
                     120.43422075282764 0&#10;    
                     0  1 206.63717153744733,81.24213909012583 Z" 
                  id="svg-text" />
        </defs>
        <text>
            <textPath xmlns:xlink="http://www.w3.org/1999/xhtml" 
                      xlink:href="#svg-text" lengthAdjust="spacing" 
                      fill="#1ebb6a" method="stretch" 
                      textLength="199.6875" spacing="auto" 
                      xml:space="preserve" 
                      style="font-size: 30px; 
                             letter-spacing: 0px; 
                             font-family: &quot;Aclonica.ttf&quot;;"
            >LALALALA text</textPath>
        </text>
    </svg>
'''
capture_options = {"scale": 20}
output_options = {"omitBackground": True}
svg_exporter = SVGExport(svg_data=svg_data, 
                         capture_options=capture_options, 
                         output_options=output_options)
image = svg_exporter.execute()
```

[svgexport]: <https://github.com/shakiba/svgexport>