semvec/pypi-packages huggingface dataset:
plasmaapi 0.1.0
Web Library API
Requires Python: >=3.6

# PlasmaAPI

### PlasmaAPI is a simple fast and reliable web library API built with Python 3.10+ and using Django 4.0+ 

## Why should I use this API? 

1. **Fast:** This library or Django (App) is using all the power of Django 4.0 by allowing high performance and use of the framework properties. Note this has been tested 100% with Axious using JavaScript   
2. **Easy to code:** Neat documentation that saves you time while integrating the source to your projects. It is as simple as adding the app (email_api) to seetings.py 
3. **Short:** Avoiding complex functions, easy, fast and well-documented reducing bugs and allowing scalability 

**Easy Email Template:** This API integrates a default HTML template, so you are freely to include your own customized email template.   

## Installation

 1. Create and activate a virtual environment using commands: python3 -m venv env and source /bin/activate 
 2. Pip install -r requirements.txt 
 3. Pip install plasmaapi
 4. Run your server using command: python manage.py runserver 

### Please note the complete documentation is located on index page. If you need help or assistance, please contact the user sgonzalezdev or email him at sgonzalezdev@gmail.com
unity-cv-datasetvisualizer 0.1.2
This Python based tool allows you to visualize datasets created using Unity Computer Vision tools.
Requires Python: >=3.7, !=3.9.*

# Unity Computer Vision Dataset Visualizer

This Python based tool allows you to visualize datasets created using Unity Computer Vision tools.

## Requirements

* Windows 10 or OSX
* Chrome, Firefox, or Safari 14 and newer (Older versions of Safari are not supported)
* Python 3.7 or 3.8. Note that this application is not compatible with Python 3.9.

## Running the visualizer

Run the command:

```bash
datasetvisualizer
```

Or if you want to specify a path to a dataset:

```bash
datasetvisualizer --data="<path_to_dataset>"
```

This command may take a few seconds to execute. Once it is done, your browser will automatically open to `http://localhost:8501/` and display the application. If that does not happen, open a new browser tab and manually navigate to that address.

Once in the application, you will be prompted to select a dataset folder. Click ***Change Dataset*** at the left side of the screen and then select the root folder of your Unity Computer Vision dataset.

## Known issues

* The tool cannot open a dataset that has no labeler data (bounding boxes, semantic segmentation, etc.)
* On Windows: a warning appears when launching the app (This can be ignored)
* 3D bounding boxes are not rendered properly when the camera is inside the box.
* Opening a folder that isn't a dataset folder may hang the program (The workaround is: kill the process and start it again)
py-wordle-helper 0.0.1
The package targets protocol for uploading and reusing task and libraries

# Wordle Helper 

A python application to help solving puzzle for https://www.nytimes.com/games/wordle/index.html

## How it words

To call wordlehelper use command 

```
% wordle-helper search
```

**output**

```    
Type first letter, blank if unknown >> a
Type second letter, blank if unknown >> 
Type third letter, blank if unknown >> 
Type fourth letter, blank if unknown >> t
Type fifth letter, blank if unknown >> 

List with Position Characters ['abate', 'abets', 'abote', 'abstr', 'abuta', 'abuts', 'acate', 'accts', 'aceta', 'acute', 'adati', 'adaty', 'adyta', 'adits', 'agata', 'agate', 'agaty', 'agete', 'airth', 'airts', 'alate', 'alite', 'ality', 'aluta', 'amate', 'amati', 'amita', 'amity', 'anita', 'aorta', 'apptd', 'arati', 'arete', 'arite', 'arith', 'aueto', 'aunty', 'aunts', 'aweto', 'axite', 'azote', 'azoth'] 

Type all character that has to be included in word (separated with comma) >> r

List After Filter 2, included character ['abstr', 'airth', 'airts', 'aorta', 'arati', 'arete', 'arite', 'arith'] 

Type all character that has to be excluded from word (separated with comma) >> o, e,z

List After Filter 1, excluded character ['abstr', 'airth', 'airts', 'arati', 'arith'] 

Final List ['abstr', 'airth', 'airts', 'arati', 'arith']
```
saildb 0.2
A high performing JSON alternative for speed and stability.
Keywords: python,database

# SailDB
The succesor to ReflectDB. Sail (Space and Integer Interaction Language) is a custom made language than uses seperate spaces as a type of directory system. The code to SailDB is fully open-source and light weight.
## Performance
All tests were run on a 2017 MacBook Pro with 256gb of Flash Storage
| Database          | Benchmark Score |
|-------------------|-----------------|
| SAIL (Python)     | 250000/s        |
| Reflect           | 9975/s          |
| JSON              | 400000/s        |
| JSON Indented (2) | 142857/s        |    


NOTE: JSON is a builtin library that probably is running C instead of just Python