semvec/pypi-packages huggingface dataset:
quizzy 0.6.0
A Python TUI quiz app
Requires Python: >=3.10

# Quizzy

A quiz app using [textual](https://textual.textualize.io/).

![Question board](assets/game.gif)

## Configuration and Questions

Create a YAML file to define the teams participating, the questions and their answers.

```yaml
teams:
  - name: "Team 1"
  - name: "Team 2"
categories:
  - name: "General Knowledge"
    questions:
      - question: "What is the capital of France?"
        answer: "Paris"
        value: 100
      - question: "What is the capital of Germany?"
        answer: "Berlin"
        value: 200
  - name: "Science"
    questions:
      - question: "What is the chemical symbol for gold?"
        answer: "Au"
        value: 100
      - question: "What is the chemical symbol for silver?"
        answer: "Ag"
        value: 200
```

See [examples/quizzy.yaml](examples/quizzy.yaml) for an example.

## Running it

Run the latest PyPI release using *uvx*:

```sh
uvx quizzy projects/gh/quizzy/examples/quizzy.yaml
```

Run the local version using *uv*:

``` sh
uv run quizzy examples/quizzy.yaml
```

Serve on a webserver using textual:

``` sh
uvx quizzy --serve examples/quizzy.yaml
```

Run in development mode:

``` sh
uv run textual run --dev quizzy.app:QuizzyApp examples/quizzy.yaml
```
barre 1.1.0
Minimal progress bar
Requires Python: >=3.8

# barre

<div align="center">

[![PyPI version](https://badge.fury.io/py/barre.svg?icon=si%3Apython&icon_color=%2354cf73)](https://badge.fury.io/py/barre)
[![CI](https://github.com/FeelTheFonk/barre/workflows/CI/badge.svg)](https://github.com/FeelTheFonk/barre/actions)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A lightweight progress bar. One line, zero config, zero dependencies.

[![Demo](https://raw.githubusercontent.com/FeelTheFonk/barre/main/demo.gif)](https://github.com/FeelTheFonk/barre)

</div>

## Install
```bash
pip install barre
```

## Usage
Simple and intuitive:
```python
from barre import b
from time import sleep

# Simple iteration
for x in b(range(100)):
    sleep(0.1)  # your work here

# With any iterable
items = ["item1", "item2", "item3"]
for x in b(items):
    process(x)
```

Output:
```
[||||||||||||||||||||                    ] 50/100
```

## Real-world Examples

### Processing Files
```python
from barre import b
import os

# Process all images in a directory
image_files = [f for f in os.listdir("images/") if f.endswith((".jpg", ".png"))]
for file in b(image_files):
    with open(f"images/{file}", "rb") as img:
        # Your image processing here
        pass
```

### API Requests
```python
from barre import b
import requests

# Download multiple URLs with progress
urls = [
    "https://api.example.com/data1",
    "https://api.example.com/data2",
    "https://api.example.com/data3",
]
responses = []
for url in b(urls):
    response = requests.get(url)
    responses.append(response.json())
```

### Data Processing
```python
from barre import b
import pandas as pd

# Process chunks of a large DataFrame
df = pd.read_csv("large_file.csv")
chunk_size = 1000
chunks = [df[i:i+chunk_size] for i in range(0, len(df), chunk_size)]
results = []
for chunk in b(chunks):
    result = chunk.groupby('category').sum()
    results.append(result)
```

### Long Computations
```python
from barre import b
import numpy as np

# Heavy computations with visual feedback
matrices = []
for i in b(range(100)):
    matrix = np.random.rand(100, 100)
    result = np.linalg.eig(matrix)
    matrices.append(result)
```

### Training ML Models
```python
from barre import b

# Training epochs with progress
epochs = 100
for epoch in b(range(epochs)):
    model.train_epoch()
    loss = model.evaluate()
```

## Features
- **Minimal**: Single file (<1KB)
- **Fast**: Zero dependencies
- **Simple**: No configuration needed
- **Clean**: Professional ASCII output
- **Universal**: Works with any iterable

## License
[MIT](LICENSE)

---

<div align="center">
Made with pragmatism in France 🇫🇷
</div>
mp3art 1.0.3
A terminal command to add or remove cover art for MP3 files.

# MP3Art
A python module terminal command to add or remove cover art for MP3 files.


```
usage: mp3art [-h] {add,remove} ...

Add or remove cover art to MP3 files.

options:
  -h, --help    show this help message and exit

Subcommands:
  Which operation to perform.

  {add,remove}  Add or remove cover art for an MP3 file.
    add         Add cover art to an MP3 file.
    remove      Remove cover art to an MP3 file.
```


### Installation:
Simply install with `pip install mp3art`.


<br>


## Add Cover Art
```
usage: mp3art add [-h] mp3 cover

positional arguments:
  mp3         Path to the MP3 file.
  cover       Path to the cover art file.

options:
  -h, --help  show this help message and exit
```


<br>


## Remove Cover Art
```
usage: mp3art remove [-h] mp3

positional arguments:
  mp3         Path to the MP3 file.

options:
  -h, --help  show this help message and exit
```


<br>


### Links:
- GitHub: https://github.com/rynstwrt/mp3art
- PyPi: https://pypi.org/project/mp3art