semvec/pypi-packages huggingface dataset:
nit-udasitharani 0.1.0
A tool to generate tiles from name initials.
Requires Python: >=3.6

# Name Initials Tile Generator

This is a tool to generate tiles from name initials.

##### Usage:

`nit [options] name save_path`

`name`: Name to generate initials. <br />
`save_path`: Path where the generated tile should be saved.

###### Options:

`bg`: Background color to be used in tile. <br />
`fg`: Color of the text to be used in tile.

Hope you like it!
SubFucker 1.0.2
SubFucker is simple tool designed to help bughunters with enumerating subdomain status codes
Requires Python: >=3.6

# SubFucker

SubFUcker is a tool desinged to help bughunters enumirate subdomain statuscodes.
You can use this tool when you want to test a target and that target has more than 1000 subdomains or 
more to get status codes and http schema of the subdomains without needing to open them manualy 

![alt tag](https://github.com/TheXerr0r/SubFucker/blob/main/SubFuckerScreenShoot.png)

# Usage

  - subfucker -f inputfile -o outfile -t thread

# Installation

 - git clone https://github.com/TheXerr0r/SubFucker
 - cd SubFucker
 - python3 setup.py install
 
## or
- python3 -m pip install SubFucker

![alt tag](https://image.ibb.co/i4ES3U/bc.png)

![alt tag](https://raw.githubusercontent.com/ehs4nnn/EY-Console/master/BITCOIN%20QR.png)
                 
 If You Want To See Our Private Tools, Please Send Your Donates To Montivate Us Publish Our Private Tool :)
 
 
 BitCoin Address: 1NZtHATWTyzmb1PghFrvwDDmVUCfCLNQWm
pyStreamer 0.4.1
A lazy evaluating, memory friendly, chainable stream solution
Keywords: stream generator chain

# pystreamer
![Build Status](https://travis-ci.com/Arnoldosmium/pystreamer.svg?branch=develop)

A lazy evaluating, memory friendly, chainable stream solution.

Inspired by the syntactical sugar of Java stream.

```python
from streamer import Stream
with open("myfile.txt") as f_input:
    uniq = Stream(f_input) \
        .map(str.strip) \
        .flat_map(str.split) \
        .collect(set)   # uniq tokens in a file
```
TensorState 0.3.0
Tools for analyzing neural network architecture.
Requires Python: >=3.6

# TensorState - Neural Network Efficiency Tools

TensorState is a toolbox to capture neural network information to better
understand how information flows through the network. The core of the toolbox is
the ability to capture and analyze neural layer state space, which logs unique
firing states of neural network layers. This repository implements and extends
the work by Schaub and Hotaling in their paper,
[Assessing Intelligence in Artificial Neural Networks](https://arxiv.org/abs/2006.02909).

## Installation

Precompiled wheels exist for Windows, Linux, and MacOS for Python 3.6-3.8. No
special installation instructions are required in most cases:

`pip install pip --upgrade`

`pip install TensorState`

If the wheels don't download or you run into an error, try installing the
pre-requisites for compiling before installing with `pip`.

`pip install pip --upgrade`

`pip install numpy==1.19.2 Cython==3.0a1`

`pip install TensorState`

## Documentation

https://tensorstate.readthedocs.io/en/latest/