semvec/pypi-packages huggingface dataset:
autodraft 0.0.3
A small package for the AutoDraft streamlit app as well as working with the NHL's API.
Requires Python: >=3.6

# AutoDraft Package
This package contains the necessary modules for running the various scripts within the [AutoDraft](https://github.com/j4th/AutoDraft) project. Namely:
 - `api.py`: Wrapper for the NHL's undocumented (mostly, shout-out to [dword4](https://gitlab.com/dword4/nhlapi)) API.
 - `arima.py`: Module for performing Auto-ARIMA modelling and predictions using [pmdarima](https://www.alkaline-ml.com/pmdarima/).
 - `gluonts.py`: Module for performing DeepAR modelling and predictions; could be extended to any [GluonTS](https://gluon-ts.mxnet.io/) model.
 - `visualization.py`: Module for visualizing model output and performance, largely through leveraging [Bokeh](https://bokeh.pydata.org/en/latest/index.html).
unstdio 0.0.4
unstdio for inplace manipulation of stdio
Requires Python: >=3.6

[github](https://github.com/eaybek/unstdio/) | 
[PyPi](https://pypi.org/project/unstdio/) | 
[ReadTheDocs](https://mvrt-unstdio.readthedocs-hosted.com/en/latest/)  

unstdio  

manipulate stdio  



```python3
from unstdio.unstdio import Unstdio
from unstdio.handlers import Out
from unstdio.formats import DictFormatter
import io

with Unstdio(stdout=Out(frmt=DictFormatter())) as unstdio:
    print("{Hello World!}")  # out to Unstdio instance
print(isinstance(unstdio.stdout, io.StringIO))
print(unstdio.stdout.getvalue())  # out to system stdout

```
hidio 0.1.0b1
HID-IO Python Library
Requires Python: >=3.7

# hidio Client Python Library
HID-IO Client Side Library for Python

[![Linux Status](https://github.com/hid-io/hid-io/workflows/Rust%20Linux/badge.svg)](https://github.com/hid-io/hid-io/actions)
[![macOS Status](https://github.com/hid-io/hid-io/workflows/Rust%20macOS/badge.svg)](https://github.com/hid-io/hid-io/actions)
[![Windows Status](https://github.com/hid-io/hid-io/workflows/Rust%20Windows/badge.svg)](https://github.com/hid-io/hid-io/actions)

[![Visit our IRC channel](https://kiwiirc.com/buttons/irc.freenode.net/hid-io.png)](https://kiwiirc.com/client/irc.freenode.net/#hid-io)

## Getting

```bash
pip install hidio
```


## Overview

This is a convenience Python library for the HID-IO daemon which handles automatic reconnection if the server goes down for any reason.
The library also handles the HID-IO authentication procedure (key negotiation and TLS wrapping).


## Usage

```python
import asyncio
import sys

import hidio.client

# Optional callbacks
class MyHIDIOClient(hidio.client.HIDIOClient):
    async def on_connect(self, cap):
        print("Connected!")
        print("Connected API Call", await cap.alive().a_wait())


    async def on_disconnect(self):
        print("Disconnected!")


async def main():
    client = MyHIDIOClient('Python example.py')
    # Connect the client to the server using a background task
    # This will automatically reconnect
    tasks = [asyncio.gather(*[client.connect(auth=hidio.client.HIDIOClient.AUTH_BASIC)], return_exceptions=True)]
    while client.retry_connection_status():
        if client.capability_hidioserver():
            try:
                print("API Call", await asyncio.wait_for(
                    client.capability_hidioserver().alive().a_wait(),
                    timeout=2.0
                ))
                print("API Call", await asyncio.wait_for(
                    client.capability_authenticated().nodes().a_wait(),
                    timeout=2.0
                ))
            except asyncio.TimeoutError:
                print("Alive timeout.")
                continue
        await asyncio.sleep(5)


try:
    loop = asyncio.get_event_loop()
    loop.run_until_complete(main())
except KeyboardInterrupt:
    print("Ctrl+C detected, exiting...")
    sys.exit(1)
```
arachniclient 0.3
REST API client for arachni.

# arachniclient

Arachni REST client to control arachni vulnerability scanners.

## Usage

Command Line Interface (CLI) options may be listed:

```sh
arachni-client --help
```

## Examples

Adding a scan:

```sh
arachni-client --url "https://[target server]/"
```

Listing currently running scans:

```sh
arachni-client --fetch
```

Fetching a report from a running or completed scan in a zipped HTML format:

```sh
arachni-client --report [scan id] --format html.zip
```
traintorch 1.0.2
Package for live visualization of metrics during training of a machine learning model
Keywords: training,visualization,loss,plot,live,jupyter notebook,matplotlib

# Traintorch (alpha)
[![Codacy Badge](https://api.codacy.com/project/badge/Grade/d4b74c08973343128d17532b4b84e154)](https://www.codacy.com/manual/rouzbeh-afrasiabi/traintorch?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=rouzbeh-afrasiabi/traintorch&amp;utm_campaign=Badge_Grade)


<p align="justify">
Package for live visualization of model validation metrics during training of a machine learning model in jupyter notebooks. The package utilizes a sliding window mechanism to reduce memory usage.
</p> 

## Requirements:

```
pandas==0.25.1
matplotlib==3.1.1
ipython==7.8.0
numpy==1.17.2
pycm==2.2
```
 ## Installation:
 
 ### Latest release:
 ```
 pip install traintorch
  ```
  
### Latest Version

 ```
 pip install git+https://github.com/rouzbeh-afrasiabi/traintorch.git
 ```

## Example 

### Simple Usage
```python
from traintorch import *

#custom metrics
first=metric('Loss',w_size=10,average=False)
second=metric('Accuracy',w_size=10,average=False)


#create an instance of traintorch
tracker=traintorch(n_custom_plots=2,main_grid_hspace=.1, figsize=(15,10),show_table=True)
#combine all metrics together
tracker.append([first,second])


range_max=1000
for i in range(0,range_max,1):
    
    first.update(train_loss=1/(i+1),test_loss=1/(i**2+1))
    second.update(y=i/(i*2+1))
    tracker.plot()
```
 <p align='center'>
 <img src='./images/dash_a.png'></img>
 
 </p>



### Using pycm metrics and doing comparison


```python
from traintorch import *


#custom metric
first=metric('Loss',w_size=10,average=False)

#pycm metrics
overall_selected=['ACC Macro']
cm_metrics_a=pycmMetrics(overall_selected,name='train',w_size=10)
cm_metrics_b=pycmMetrics(overall_selected,name='test',w_size=10)

#compare two metrics of the same kind
compare_a=collate(cm_metrics_a,cm_metrics_b,'ACC Macro')

#create an instance of traintorch
tracker=traintorch(n_custom_plots=1,main_grid_hspace=.1,figsize=(15,15),show_table=True)

#combine all metrics together
tracker.append([first,cm_metrics_a,cm_metrics_b,compare_a])


range_max=1000
for i in range(0,range_max,1):
    
    actual_a=np.random.choice([0, 1], size=(20,), p=[1./3, 2./3])
    predicted_a=np.random.choice([0, 1], size=(20,),p=[1-(i/range_max), i/range_max])
    actual_b=np.random.choice([0, 1], size=(20,), p=[1./3, 2./3])
    predicted_b=np.random.choice([0, 1], size=(20,),p=[1-(i/range_max), i/range_max])
    cm_metrics_a.update(actual_a,predicted_a)
    cm_metrics_b.update(actual_b,predicted_b)
    first.update(train=1/(i+1),test=1/(i**2+1))
    compare_a.update()
    tracker.plot()

```
 <p align='center'>
 <img src='./images/dash.png'></img>
 
 </p>
hard 0.0.2
hard variables: they dumping when the set time
Requires Python: >=3.6

[github](https://github.com/eaybek/hard/) | 
[PyPi](https://pypi.org/project/hard/) | 
[ReadTheDocs](https://mvrt-hard.readthedocs-hosted.com/en/latest/)  

hard  

this package provide hard variable implementation
which they are dumped when set and loaded when they get
urlp 0.0.3
A simple command-line utility for parsing URLs.
Requires Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4
Keywords: url parse command-line

# urlp
A simple command-line utility for parsing URLs, written in Python. Inspired by [urlp](https://github.com/clayallsopp/urlp).

```bash
$ urlp --host "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
www.cnn.com
$ urlp --registered_domain "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
cnn.com
$ urlp --path "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
/service/alert.jsp
$ urlp --path -i 0 "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
service
$ urlp --query "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
s=cnn&v=a
$ urlp --query --query_field=s "http://www.cnn.com/service/alert.jsp?s=cnn&v=a"
cnn
```
urlp often works together with other unix command-line tools. For example:
* Find all hosts in urls, sorted by count.
```bash
cat urlfile | urlp --host | sort | uniq -c | sort -nr -k1,1
```
* Find all url path words (separated by "/"), sorted by count.
```bash
cat urlfile | urlp --path | tr / \\n | awk '$1!=""' | sort | uniq -c | sort -nr -k1,1
```

## Install
```
pip install urlp
```

## Usage
```
$ urlp --help
usage: urlp [-h] [--host] [-p] [-i path_index] [-q] [-k query_field] [-r]
            [urls [urls ...]]

A command line url parser

positional arguments:
  urls                  URLs to parse

optional arguments:
  -h, --help            show this help message and exit
  --host                hostname
  -p, --path            Path
  -i path_index, --path_index path_index
                        filter parsed path by index
  -q, --query           query string
  -k query_field, --query_field query_field
                        value for the specified query field
  -r, --registered_domain
                        registered domain
```
shadowsocksr-tools 1.3.3
Python Shadowsocksr tools.
Keywords: Proxy,Shadowsocks,Shadowsocksr,IP,GEO_IP

# Shadowsocks(R) tools

[![PyPi Version](http://img.shields.io/pypi/v/shadowsocksr-tools.svg)](https://pypi.python.org/pypi/shadowsocksr-tools/)