semvec/pypi-packages huggingface dataset:
mmoran0032 2024.12
whoami in Python
Requires Python: >=3.8

# mmoran0032

![PyPI](https://img.shields.io/pypi/v/mmoran0032)

`whoami` but for me and within Python for all to see.

## Install

`python -m pip install mmoran0032`

## Run

`mmoran0032`

## Contact

Please reach out on any of the provided channels.
datamodel-orm 1.0.0
A fast and efficient way to interact with databases using pydantic models
Requires Python: >=3.11

# DataModel ORM

DataModel ORM is a Python library that provides a fast and efficient way to interact with databases using Pydantic models.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install DataModel.

    pip install datamodel_orm

## Usage

This example demonstrates how to use the User data model in Python. The User data model is defined using Pydantic and includes fields for id, name, and age.

### Setup
First, import the necessary modules and define the User data model.

    from typing import Optional
    from pydantic import Field
    from data_model_orm import DataModel

    class User(DataModel):
        id: Optional[int] = Field(json_schema_extra={"primary_key": True}, default=None)
        name: str
        age: int

### Creating the Data Source
Create the data source for the User model. If the data source already exists, this operation will be ignored.

    User.create_source(ignore_if_exists=True)

### Saving a New User
To save a user, instantiate the User class and call the save method.

    user = User(name="John", age=30)
    user.save()
    print(user.id)  # Prints the ID of the newly created user

### Retrieving a User
To retrieve a user, use the get_one method and provide the user's name.

    user = User.get_one(name="John")

### Retrieving All Users with a Specific Name
To retrieve all users with a specific name, use the get_all method and provide the name.

    users = User.get_all(name="John")

### Deleting a User
To delete a user, call the delete method on a User instance.

    user.delete()

Please note that the actual usage may vary depending on the implementation of the DataModel class and the data source.

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.
mdtoword 0.1.0
A Python package to convert Markdown files to Word documents with advanced formatting
Requires Python: >=3.6

# MDToWord

A Python package that converts Markdown files to Word documents with advanced formatting options.

## Installation

```bash
pip install mdtoword
```

## Usage

```python
from mdtoword import MarkdownToDocxConverter

# Create a converter instance
converter = MarkdownToDocxConverter()

# Convert markdown to docx
converter.convert_file("input.md", "output.docx")

# Or convert markdown string directly
markdown_text = "# Hello World\nThis is a **bold** text"
converter.convert_string(markdown_text, "output.docx")
```

## Features

- Converts Markdown to Word documents (.docx)
- Supports various Markdown formatting:
  - Headers
  - Bold and italic text
  - Lists (ordered and unordered)
  - Code blocks
  - Tables
  - Links
  - Images
- Customizable styles and formatting
- Page numbering support
- Table of contents generation

## Configuration

You can customize the document styling:

```python
converter = MarkdownToDocxConverter(
    styles={
        'document': {
            'font_name': 'Arial',
            'font_size': 12,
            'margins': {
                'top': 1.0,
                'bottom': 1.0,
                'left': 1.0,
                'right': 1.0
            }
        }
    }
)
```

## License

This project is licensed under the MIT License - see the LICENSE file for details.
streamdeckapi 0.0.13
Stream Deck API Library


[![PyPI version](https://badge.fury.io/py/streamdeckapi.svg)](https://badge.fury.io/py/streamdeckapi)

# streamdeckapi
Stream Deck API Library for Home Assistant Stream Deck Integration

Only compatible with separate [Stream Deck Plugin](https://github.com/Patrick762/streamdeckapi-plugin) or the bundled server.

## Server inside docker container
The docker image allows you to use the streamdeckapi server inside a docker container.

### Usage
```shell
docker run -v /dev/hidraw7:/dev/hidraw7 -v ./data/streamdeckapi:/streamdeckapi/data -p 6153:6153 --privileged ghcr.io/patrick762/streamdeckapi:main
```

**Note:** You have to change `hidraw7` to the path of your Stream Deck. You can find this path by using `lshid` (https://pypi.org/project/lshid/).

## Limitations
- No zeroconf discovery
- No `doubleTap` event

## Server without docker
This library also contains a server to use the streamdeck with Linux or without the official Stream Deck Software.

For this to work, the following software is required:

- LibUSB HIDAPI [Installation instructions](https://python-elgato-streamdeck.readthedocs.io/en/stable/pages/backend_libusb_hidapi.html) or [Installation instructions](https://github.com/jamesridgway/devdeck/wiki/Installation)
- cairo [Installation instructions for Windows](https://stackoverflow.com/a/73913080)

Cairo Installation for Windows:
```bash
pip install pipwin

pipwin install cairocffi
```

### Limitations
- No `doubleTap` event

### Installation on Linux / Raspberry Pi

Install requirements:
`sudo apt install -y libudev-dev libusb-1.0-0-dev libhidapi-libusb0 libjpeg-dev zlib1g-dev libopenjp2-7 libtiff5 libgtk-3-dev python3-pip`

Allow all users non-root access to Stream Deck Devices:
```bash
sudo tee /etc/udev/rules.d/10-streamdeck.rules << EOF
SUBSYSTEMS=="usb", ATTRS{idVendor}=="0fd9", GROUP="users", TAG+="uaccess"
EOF
```

Reload access rules:
`sudo udevadm control --reload-rules`

Install the package:
`pip install streamdeckapi`

Reboot your system

Start the server:
`streamdeckapi-server`

### Example service
To run the server on startup, you can use the following config in the file `/etc/systemd/system/streamdeckapi.service`:

```conf
[Unit]
Description=Stream Deck API Service
Wants=network-online.target
After=network.target

[Service]
WorkingDirectory=/home/pi
ExecStart=/home/pi/.local/bin/streamdeckapi-server
User=pi
StandardOutput=console

[Install]
WantedBy=multi-user.target
```

To start the service, run `sudo systemctl start streamdeckapi.service`.

To enable the service, run `sudo systemctl enable streamdeckapi.service`.
visibl 1.0.0
A CLI tool for Visibl
Requires Python: >=3.7

TO test locally:

# 1. First, uninstall the package
pip uninstall visibl

# 2. Clean up all cached files and build artifacts
rm -rf build/ dist/ *.egg-info/
find . -type d -name "__pycache__" -exec rm -r {} +
rm -rf ~/.visibl/config.json  # Remove any existing config

# 3. Reinstall the package in editable mode
pip install -e .




Publishing to pypi:

# 1. Make sure you're in your virtual environment
source venv/bin/activate  # On Windows: venv\Scripts\activate

# 2. Install required packages
pip install build wheel pyinstaller

# 3. Run the build script
python build_wheels.py
feno 0.6.2
feno: Flexible Exercise Notation Organizer
Requires Python: <4,>=3.7
Keywords: programming, learning

# feno - Flexible Exercise Notation Organizer

A ferramenta `feno` é um formatador de atividades de programação e conta com uma série de ferramentas integradas.

- Um preprocessador de Markdown (toc, include).
- Um gerador de arquivos html usando pandoc.
- Um gerador de links absolutos para arquivos locais.
- Uma ferramenta para filtrar rascunhos de código.
- Um indexador de questões.
- Um gerador de arquivos para serem utilizados no VPL do Moodle ou via tko.

## Instalação

Se estiver no windows, instale o [WSL](https://docs.microsoft.com/pt-br/windows/wsl/install) e utilize o Ubuntu.

```bash
pip install feno

# ou diretamente do github
pip install git+https://github.com/senapk/feno.git

# tko para gerar e converter os testes e testar os códigos
pip install tko

# pandoc para gerar os htmls se quiser htmls de qualidade e com suporte a latex
sudo apt install pandoc
```

## Modo básico

Crie um arquivo `Readme.md` com o seguinte formato:

    # Título da atividade

    A descrição que você quiser

    ```txt
    >>>>>>>> teste 1
    entrada
    entrada
    ========
    saida
    saida
    <<<<<<<<
    
    >>>>>>>> teste 2
    entrada
    entrada
    ========
    saida
    saida
    <<<<<<<<

    ```

- A primeira linha é o título da atividade.
- Você pode inserir quantos testes quiser.
- Execute o `feno` na pasta local com:

```bash
feno .
```

Ele vai criar uma pasta `.cache` com:

- `q.html` - Um arquivo html com a descrição do problema.
- `q.tio` - Um arquivo com as questões no formato tio.
- `mapi.json` - Um arquivo com os testes formatado para o moodle, que pode ser utilizado pelo projeto [mula](https://github.com/senapk/mula).

## Utilizando TOC e rascunhos