semvec/pypi-packages huggingface dataset:
visionFusion 0.1.8
visionFusion é um conjunto de ferramentas de ocr para facilitar o processo de extração de texto em diferentes cenarios   
Requires Python: <4.0,>=3.11

# Visão Geral

Este projeto fornece um conjunto de ferramentas para capturar regiões da tela e detectar texto dentro de imagens usando dois métodos diferentes de OCR (Reconhecimento Óptico de Caracteres): Google Cloud Vision API e Tesseract.

## Uso
### screenGrabber

Esta classe inicializa um aplicativo simples de captura de tela usando Tkinter.
Exemplo:

```python
from visionFusion import ScreenGrabber

grabber = screenGrabber()
```

### visionai

Esta classe usa a API Google Cloud Vision para detectar texto em imagens de diferentes fontes.
Inicialização


```python
from pathlib import Path
from visionFusion import visionai

# Inicialize com credenciais do Google Cloud e proxy opcional
vision = visionai(creds=Path('caminho/para/creds.json'), proxy='http://seu.proxy:porta')
```

#### Métodos:

- __detect_text_from_file(path: Path) -> Union[List, None]__

    Detecta texto em um arquivo de imagem.

    
    ```python
    textos = vision.detect_text_from_file(Path('caminho/para/imagem.png'))
    ```
- __detect_text_from_url(url: str) -> Union[List, None]__

    Detecta texto em uma imagem a partir de uma URL.

    
    ```python
    textos = vision.detect_text_from_url('https://exemplo.com/imagem.png')
    ```
- __detect_text_from_screen_region(coordenadas: Tuple[int]) -> Union[List, None]__

    Detecta texto em uma região específica da tela.

    
    ```python
    textos = vision.detect_text_from_screen_region((0, 0, 100, 100))
    ```

### tesseract

Esta classe usa Tesseract OCR para detectar texto em imagens de diferentes fontes.
Inicialização


```python
from pathlib import Path
from visionFusion import tesseract


Inicialize com o caminho do executável do Tesseract
tess = tesseract(tesseract_executable=Path('caminho/para/tesseract'))
```
#### Métodos:

- __detect_text_from_file(path: Path) -> Union[str, None]__

    Detecta texto em um arquivo de imagem.

    
    ```python
    texto = tess.detect_text_from_file(Path('caminho/para/imagem.png'))
    ```
- __detect_text_from_url(url: str) -> Union[str, None]__

    Detecta texto em uma imagem a partir de uma URL.

    
    ```python
    texto = tess.detect_text_from_url('https://exemplo.com/imagem.png')
    ```

- __detect_text_from_screen_region(coordenadas: Tuple[int]) -> Union[str, None]__

    Detecta texto em uma região específica da tela.

    
    ```python
    texto = tess.detect_text_from_screen_region((0, 0, 100, 100))
    ```

## Licença

Este projeto está licenciado sob a Licença MIT. Veja o arquivo LICENSE para mais detalhes.

## Autor

Desenvolvido por Guilherme Eduardo Poças.

Sinta-se à vontade para entrar em contato com qualquer dúvida ou feedback!
pyspliter 1.0.2
Cool package.

ï»¿# sss
>An API Management tool written in Python.

[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://lbesson.mit-license.org/)
![PyPI](https://img.shields.io/badge/pypi-v1.0.0-blue)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/requests.svg)
![PyPI - Wheel](https://img.shields.io/pypi/wheel/pywol.svg)
![CircleCI branch](https://img.shields.io/circleci/project/github/erberlin/pywol/master.svg)

pystob allows for API Authorization Management and allows to build REST-Based API with custom JSON syntax.
pystob can be used as a plugin for many API Repository such as [FRPC](https://github.com/seznam/fastrpc) and many others.

## Installation

```console
$ pip install pystob
```

## Usage examples
As an API Management Tool :
```console
$ pywool -u api.redacted.com -t "FRPC_BASED" -l -vv
Retrieve list from [api.redacted.com] | AUTHORIZATION: None | BASED: FRPC_TECH
$
$ pywool -u api.redacted.com -t "REST_BASED" -d "JSON" -auth <AUTH_EXAMPLE> -l -vv
Retrieve list from [api.redacted.com] | AUTHORIZATION: <AUTH_EXAMPLE> | BASED: REST_API
$
$ pywool --help
Usage: pywool -u API_URL [OPTIONS]

  API Management for the Pywool package.

  Please don't type any hypertext protocol such as "https://" or "http://" because they can 
  corrupt the results. The standard URL_TYPE is <SUBDOMAIN>.<BASE>.<DOMAIN>:<PORT>

Options:
  -u, --url URL  Please respect the standards described above
  -p, --port PORT      Target port.
  -vv, --verbose
  -t, --technology OPTIONS
  -l, --list
  -b, --build URL Please check documentation to build your own API with Pywool Tool
  -d, --data OPTIONS
  --help                   Show this message and exit.
```
## Why create API Builder and Manager ?
I needed one and this was an opportunity to learn some stuff.

## Meta

 Kevin Jonsson- jonsson.dev@gmail.com

Distributed under the MIT license. See ``LICENSE`` for more information.
django-crispy-tableselect 0.1.0
Crispy layout object for selecting rows in a table
Requires Python: >=3.9
Keywords: crispy-forms, django

# Django Crispy TableSelect
[![CI](https://github.com/techonomydev/django-tableselect/actions/workflows/ci.yml/badge.svg)](https://github.com/techonomydev/django-tableselect/actions/workflows/ci.yml)

*Note:* this package is under heavy development and currently in proof-of-concept phase.

Crispy layout object for selecting rows in a [django-tables2](https://github.com/jieter/django-tables2/) data table.

<center>
    <img width="900" src="./docs/images/demo.gif" alt="Animation showing a table with rows that are selected all at once and then unchecked one-by-one.">
</center>

## Todo list

- [ ] Write documentation (d'oh)
- [ ] Publish to PyPI
- [ ] Add checkbox in table header to select/de-select all rows at once.
- [ ] Add tests
- [ ] Audit accessibility

## Development setup

### Requirements
- At least python 3.9 (pyenv managed recommended)


### Install the django app with poetry
```bash
pyenv virtualenv 3.9 django-tableselect  # or your alternative to create a venv
pyenv activate django-tableselect
pip install poetry
make install

# Optional, when you're not creating the virtualenv yourself poetry will do it for you.
# You can activate the poetry venv like so:
source $(poetry env info --path)/bin/activate
```

### Linting
`flake8-black` and `flake8-isort` are installed and configured
```bash
make lint
```

### Formatting
`black` and `isort` are configured
```bash
make format
```


### Test
Pytest with coverage is default enabled
```bash
make test
```

### Run the django development server (sandbox)
First run the migrations:
```bash
make migrate
```

Now create a superuser:
```bash
sandbox/manage.py createsuperuser
```

Finally run the django dev server:
```bash
sandbox/manage.py runserver
```

You can now go to the django admin site: http://localhost:8000/admin