semvec/pypi-packages huggingface dataset:
instahack 0.4
Powerful Termux Tool for Hacking Device ;)

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[![](https://img.shields.io/pypi/pyversions/readme-generator.svg?longCache=True)](https://pypi.org/project/readme-generator/)

#### Installation
```bash
$ pip install instahack
```

#### Features
+   **`instahack`**, **Powerful Phone Hacker tool for Termux.**


#### How it works
```
$ instahack

Created by Parixit Sutariya
Github : github.com/Bhai4You
Youtube : youtube.com/BullAnonymous
Blogspot : https://bhai4you.blogspot.com

```

<p align="center">
    <a href="https://github.com/Bhai4You">Github</a>
</p>
apply-pandas 0.0.1
Functor to convert string boolean expressions into Pandas DataFrame filters.
Requires Python: >=3.6

# apply-pandas 
## Generic Apply Function for Pandas DataFrames

This repo demonstrates a powerful, simple and generic way to make an `apply` function for Pandas DataFrames. `apply` takes in a list of conditions (**as strings**) to apply to a dataframe, and returns the result of those applications.

This can be useful when you want to avoid writing huge chunks of code to filter data, or when you want to construct code based on other factors to give you a properly formatted result. Case in point - user input can be turned into well-defined string queries/filters on your DataFrame, with which you can return the appropriate data, *without* knowing those queries in advance.

## Overview and Usage
--- 

The Apply function is wrapped in a functor so that we can cleanly separate verification and application. Furthermore, this also allows us to clearly bind the target DatFrame and the desired conditions together; something that might not always be easy when dealing with rapidly changing variables, while giving the programmer the option to call it when desired. 

In effect, you can bind at creation, but can safely get the computation much, much later. Here's a code snippet that illustrates the usage of this method.

```python 
# First, we create our dummy data
df = pd.DataFrame(list(range(0, 100)), columns=["Slice"])

# Then a list of conditions to apply.
list_condns = ["frame['Slice']<5", "frame['Slice']%3==1"]

# To use the Apply() class,
# First create an object that binds DataFrame and conditions,
Applicator = Apply(df, list_condns)

# Call for the result when needed.
result = Applicator() #<--- returns pandas DataFrame
``` 

**Notice** that in `list_condns`, all of our conditions are made out to `frame`, regardless of the actual name of the actual target frame. This means that when you generate these conditions in real-time, you do not ever have to worry about getting the name of the variable - just make out the filter for `frame`, and we'll take care of the rest :)

## Bugfixes and Improvements 

This code is always ready for improvements, and to get rid of bugs - so please let me know if you've found anything, or how you've used this project! Hope you have fun with it :)
hexafonter 0.1.2
Generate a C font file for a small LCD from a PNG image
Requires Python: >=3.6

# Hexafonter

A command-line tool that will convert a PNG file with a fixed-width pixel font
for small LCD displays, to a C file with a sideways preview and a character
code legend.

See [GitHub](https://github.com/encukou/hexafonter) for more info.
caterpillarouxx 0.0.1
Python bindings for the Qt cross platform application toolkit thank you !

# vidstream
Fuck the judget
Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine

markdown_code_exec
Execute Python code in Markdown files and captures the output

Copyright 2022 Sebastiaan Mathôt

Command-line usage
usage: markdown_code_exec.py [-h] [-i INPUT] [-o OUTPUT]

optional arguments: -h, --help show this help message and exit -i INPUT, --input INPUT input markdown file -o OUTPUT, --output OUTPUT output markdown file

Function reference
markdown_code_exec.parse_text(md)

Takes a str containing markdown text, finds code blocks in the markdown, executes these code blocks and captures the output, and then embeds the captured output in the markdown.

Parameters
md: str : The input markdown string
Returns
str The compiled markdown string

markdown_code_exec.parse_file(src, dst)

Takes a markdown input file, executes code blocks while capturing output and writes the result to a new output file.

src: str The full path to the input file dst: str The full path to the output file

License
GNU General Public License 3
scalcbr 0.0.1
Simple Calc
Requires Python: >=3.7

# scalcbr

Description. 
The package simple_calculator is used to:
	- simple calc operation
	- sum, subtract, multiply or divide
	![import and call](scalcbr/image/import_and_calls.png)

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install scalcbr
```

## Author
Daniel Victor

## License
[MIT](https://choosealicense.com/licenses/mit/)

###### Folder old
First package version - don't exist more, but if you execute file call_calculator.py
will have a iterative, interactive simple calculator