semvec/pypi-packages huggingface dataset:
LogQS-Client 0.0.1
Log Query System Client
Requires Python: >=3.9

<p align="center">
  <br/>
  <img src="misc/images/logqs_logo.png?raw=true" alt="LogQS Logo" width="250"/>
</p>

# LogQS Client


## Setup

The LogQS Client module source is located in `lqs-client` and it's Python requirements are listed in the `requirements.txt` file.  You can install it locally with `pip install .`.

#### Development

The project uses Python 3.9, which may require some dependencies to be required.  In one go,

    sudo apt install python3.9 python3.9-dev python3.9-distutils python3.9-venv

To run the application from this directory (i.e., for development):

1. Create a virtual environment:

    `python3.9 -m venv venv`

2. Source the environment:

    `source venv/bin/activate`

3. Install the requirements:
    
    `pip install -r requirements.txt`

4. Install LogQS Client in develop mode:
    
    `pip install -e .`

5. Run the module:
    
    `python -m lqs-client`
Orange3-MNE 1.0.13
Electrophysiological data processing widgets for Orange 3 based on the MNE for Python library.
Requires Python: >=3.7
Keywords: orange3 add-on,mne,eeg,electrophysiology

## MNE Widgets for Orange 3 (Orange3-MNE)
[![PyPI version](https://badge.fury.io/py/Orange3-MNE.svg)](https://badge.fury.io/py/Orange3-MNE) [![Downloads](https://pepy.tech/badge/orange3-mne)](https://pepy.tech/project/orange3-mne)

Orange3-MNE is a python package, that provides methods from MNE for Python for Orange 3 in a form of widgets, 
to allow for electrophysiological data processing.

> *Note: This library was created as a part of the master's thesis to show that it is possible to use Orange 3 as a workflow management system for electrophysiological data processing. The widgets' functionality was verified on three existing experiments. Nevertheless, the library requires further development.* 

### Installation
The installation process is quite straightforward, first we need to install the Orange 3 tool:
> *Note: If you have Orange 3 already installed, you can skip this step.*
```bash
    virtualenv orange          # Create a virtual environment
    ./orange/Scripts/activate  # Activate the environment (source ./orange/Scripts/activate for linux)
    pip install Orange3 PyQt5  # Install Orange 3 and PyQt library
```

Then it is possible to install the library using one of the following methods.


##### Pip Method
```bash
   pip install Orange3-MNE
```

##### GUI Method
1. Run Orange: `python -m Orange.canvas`
2. In Orange navigate to Options -> Add-ons
3. Click on `Add more...` and enter the package name: `Orange3-MNE`
4. Confirm the settings and Orange will install the library
5. Restart Orange and the electrophysiological data processing library will be available

### User's guide
The documentation on how to use Orange 3 is available on its [homepage](https://orange.biolab.si/docs/).

The documentation to widgets in this library can be found [here](https://fifal.gitlab.io/orange-mne-library/), and [here](https://gitlab.com/fifal/orange-mne-library/-/blob/master/docs/widgets.md).

## Change Log
### 1.0.13
- Updated MNE version to 1.1.1, keras to 2.10.0, and tensorflow to 2.10.0

### 1.0.12
- Updated MNE version to 0.20.7 which resolves matplotlib problem
rastreio-correios-async 1.0.1
Programa não oficial de rastreio de encomendas dos correios.
Requires Python: >=3.10,<4.0

# 🐍 Rastreador de Encomendas

## Esse programa tem como seu intuito fazer o rastreio de encomendas dos correios

- Rastreio de encomendas

## Como utilizar?

```shell
$ pip install rastreio-correios-async
```

```Python
from asyncio import run

from rastreio_correios import Rastreio


async def main():
    rastreio = Rastreio()
    codigo = 'LB526033530HK'
    resultado = await rastreio.rastrear(codigo)
    print(resultado)


run(main())
```

### O que usamos na infraestrutura?

- [Utilizamos a linguagem Python](https://www.python.org/)