semvec/pypi-packages huggingface dataset:
footballtestdata 1.3
A package to generate fake footballer data
Keywords: python,football,soccer,data

# Football Test Data

[![PyPI Version](https://img.shields.io/pypi/v/fake-footballer.svg)](https://pypi.org/project/footballtestdata/)
[![License](https://img.shields.io/pypi/l/fake-footballer.svg)](https://github.com/mazarzycki/footballtestdata/blob/main/LICENSE)

Generate fake footballer data with this Python package.

## Installation
You can install the package using pip:

```
pip install footballtestdata
```
## Usage
Import the FootballerGenerator class and other necessary modules to generate fake footballer data:

```
from footballtestdata import FootballerGenerator, position
from footballtestdata.data import ENG, ITA, SPA, GER
```

Initialize the FootballerGenerator object with the desired data for a specific country:

```
country = 'ENG'
footballer_generator = FootballerGenerator(ENG[0], ENG[1], ENG[2], ENG[3], position)
```
Generate fake footballer data:

```
num_footballers = 10
fake_footballers = [footballer_generator.generate_fake_footballer(country) for _ in range(num_footballers)]
```
Create a pandas DataFrame from the generated data:

```
import pandas as pd
df = pd.DataFrame(fake_footballers)
```
Save the DataFrame to an Excel file:

```
filename = f'fake_{country}_footballers.xlsx'
df.to_excel(filename, index=False)
```
For more usage examples and customization options, please refer to the documentation.

## Documentation
For detailed documentation, refer to the official documentation.

## Contributing
Contributions are welcome! If you would like to contribute to the project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make the necessary changes and commit them.
4. Open a pull request on the main branch.
5. Please review the contribution guidelines for more details.

## License
This project is licensed under the MIT License.
pydlmodels 0.1.4
A package for deep learning models and data preprocessing
Requires Python: >=3.6
Keywords: python,pandas,numpy,basic libraries,models,deep learning,resnet,nlp

# pydlmodels

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.10](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/)   

## Functionality of the pydlmodels

- Train Deep Learning Models
- Get the original word from the many forms of words

## Documentation 
- [Click here for full documentation](https://www.drateendrajha.com/blog/tags/pydlmodels)
simpleroute 0.0.3
A simple router / treelib for python.
Requires Python: >=3.7

# SimpleRoute <img src=https://openclipart.org/download/245411 height=40 align=top>
A simple router / treelib for python.

## Usage

### Installation
```
pip install simpleroute
```

### Import
*Note: as simpleroute uses two dictionaries internally rather than an OOP-based node system,*

*Traverse replaces the standard "Node" class present in most other tree libraries.*
```python
from simpleroute import BaseRouter, Router, Traverse
```

### Classes
```python
router = BaseRouter([]) # list of paths sep by /
path, kwargs = router.match("SOME_STR_HERE") #match wildcards, eg /etc/1 to /etc/:num
```

```python
router = Router({}) # dict of paths:datavals sep by /
path, kwargs, data = router.match("SOME_STR_HERE") #match wildcards, eg /etc/1 to /etc/:num
```

```python
traverse = Traverse.go(router, path="SOME_PATH_HERE") #returns an object of Traverse, optional path to go
#use get_child, get_children, get_parent, get_data, get_path, get_sub to manipulate the object
```
drxtract-system25 0.1.0
titanic_ml example package
Requires Python: >=3.10.6

# drxtract
Macromedia Director 5 DRI and DRX files data extractor.

# This software needs:
* ImageMagic to transform BMP images into PNG.
* FFmpeg to transform WAV files into MP3.

# Mac "snd " file format:
* https://developer.apple.com/library/archive/documentation/mac/Sound/Sound-60.html#MARKER-9-400

# Lingo script decompilation references:
* http://fileformats.archiveteam.org/wiki/Lingo_bytecode
* LscrToScript tool (http://alex-dev.org/lscrtoscript/)

# Other interesting projects (also used as reference):
* D4Player (https://github.com/renaldobf/D4Player)
* Continuity (https://github.com/scummvm-director/continuity)
* Scummvm Director engine (https://github.com/scummvm/scummvm/tree/master/engines/director)