semvec/pypi-packages huggingface dataset:
dataset-cat 0.0.6
A tool for fetching and organizing anime datasets for training.
License: MIT
Requires Python: <4.0,>=3.8
Keywords: anime, dataset, fetcher, training

# Python Package Template

This sample repo contains the recommended structure for a Python package.

## Setup Instructions 

This sample makes use of Dev Containers, in order to leverage this setup, make sure you have [Docker installed](https://www.docker.com/products/docker-desktop).

The code in this repo aims to follow Python style guidelines as outlined in [PEP 8](https://peps.python.org/pep-0008/).

To successfully run this example, we recommend the following VS Code extensions:

- [Dev Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers)
- [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
- [Python Debugger](https://marketplace.visualstudio.com/items?itemName=ms-python.debugpy)
- [Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance) 

In addition to these extension there a few settings that are also useful to enable. You can enable to following settings by opening the Settings editor (`Ctrl+,`) and searching for the following settings:

- Python > Analysis > **Type Checking Mode** : `basic`
- Python > Analysis > Inlay Hints: **Function Return Types** : `enable`
- Python > Analysis > Inlay Hints: **Variable Types** : `enable`

## Running the Sample
- Open the template folder in VS Code (**File** > **Open Folder...**)
- Open the Command Palette in VS Code (**View > Command Palette...**) and run the **Dev Container: Reopen in Container** command
- Run the app using the Run and Debug view
- To test, navigate to the Test Panel to configure your Python test or by triggering the **Python: Configure Tests** command from the Command Palette
- Run tests in the Test Panel or by clicking the Play Button next to the individual tests in the `test_date_time.py` and `test_developer.py` file