semvec/pypi-packages huggingface dataset:
onyx-mclib 2.1.3
A python library to create minecraft data packs
Requires Python: >=3.6

# Onyx
A python library to create minecraft data packs

## Documentation
You can view the documentation [here](https://doublef3lix.github.io/onyx/index.html).

## Getting Started
First, install the package with `pip install onyx-mclib`.
Next, create a python script and import onyx. It is also recommended you import all of `nbtlib.tag` like so: `from nbtlib.tag import *`.

Here's a sample script to get you started:
```python
import onyx

class MyPack(onyx.DataPack):
    def __init__(self):
        super().__init__("My data pack name")

        self.function("namespace:function", self.function_obj)

        self.generate()

    def function_obj(self):
        onyx.commands.say("Hello, World!")

MyPack()
```

## Credits
* [fizzy/vberlier](https://github.com/vberlier) - Creator of [nbtlib](https://github.com/vberlier/nbtlib), [beet](https://github.com/mcbeet/beet), and [mudkip](https://github.com/vberlier/mudkip), helped walk me through using GitHub actions
* Arcensoth, rx, vdvman1 - Library design help
* Jayfin, Lue, lolad/lolgeny, MulverineX, Speedy2025 - Motivating me to work on this project after nearly abandoning it
* You - For using this (hopefully, heh)
helpu 0.0.102
Class containing super convenience methods.
Requires Python: >=3.5

# lib-py-helpu (not stable right now)
Phonetic - *| help juː |*

Library on PYPI that contains some very lazy but safe methods.
It's a tradition I wanted to follow my very first development team. Miss you guys.

I did document this, but I'm not sure how to use auto docs on Python, so this is really just for my usage for now.
I highly doubt anyone would really want to use this besides me.

Use case example:
```
import helpu

data_lists = [["header1", "header2"], ["value1", "value3"]]
file_path = "C:\yourfile.csv"

helpu.write_to_csv(file_path, data_lists)
```

Examples of functions:
```
def write_to_csv(self, file_path, lists):

def timestamp(self, formatting="%Y%m%d"):
```
subtitle-api 0.0.1
this module provide unofficial subscene.com api for python
Requires Python: >=3.7

# Browse and Download from subscene.com with just a few lines of python

SubtitleAPI is a python package provide direct access to subscene.com content using scraping techniques! You can search for any subtitle you want to download , also add query filters to remove unwanted content!
## Intsall SubtitleAPI using pip
```
pip install SubtitleAPI
```
Get Movie Subtitles:
```
from subtitleAPI import SubtitleAPI

subscene = SubtitleAPI('english','farsi/persian') # pass languages you want to have in results

subscene.movie(title='Tenet',year=2020,release_type='bluray')
subscene.download()
```
# search IMdB ID
```
subscene.movie(imdb_id='6723592',release_type='bluray')
```
# search for TV Shows

```

subscene.tvshow(title='Game of Thrones',release_type='bluray',season=2,episode=3)

# or

subscene.tvshow(imdb_id='0944947',release_type='bluray',season=2,episode=3)

```
# export zip files After download is Finished !
this method extract all zip files.
```
subscene.download().extract()

```
# some useful properties:
```
subscene.subtitles # all subtitle objects in memory
subscene.zip_files # downloaded zip files!
subscene.all_subtitle_files # all extracted subtitle files
```
jpaulorc-puc-csv-converter 0.1.5
Convert csv to json. Publishin only for leaning purposes.
Requires Python: >=3.9,<4.0

# File Converter

CSV to JSON converter.

## Introduction

Teaching how to deploy a lib on PyPi at PUC using Poetry.



### What this project can do

Read a **csv** file or a **folder** with csv`s and convert them to **JSON**.
This project is a program running on terminal, preferably install with pipx:


```bash
pipx install jpaulorc-puc-csv-converter
```

To use, just type in:

```bash
csv_converter --help
```

This will list all available options.
pelican-markdown-unrendered-metadata 0.1.1
Read Pelican metadata from link references
Requires Python: >=3.9

# Pelican Markdown Unrendered Metadata

Read Pelican metadata from link references.

## Usage

Write metadata in the form `[//Pelican/KEY]: # (VALUE)`.
They can be placed anywhere in the document.
If the first text content is a top-level heading,
the heading is removed from the document, and used as the title.
For example,

```md
# Hello, world!

[//Pelican/date]: # (2000-10-31 00:00)
[//Pelican/author]: # (Noname)

Goodbye, world!
```

The equivalent MultiMarkdown document used by Pelican would be

```md
title: Hello, world!
date: 2000-10-31 00:00
author: Noname

Goodbye, world!
```

If a key has multiple sources (references, MultiMarkdown, heading),
the order of stored value is unspecified.

## Installation

If `PLUGINS` is not specified inside `pelicanconf.py`,
then installing this package should be sufficient setup.

```sh
python -m pip install pelican-markdown-unrendered-metadata
```

Otherwise, inside `pelicanconf.py`,
add `markdown_unrendered_metadata` to the `PLUGINS` list variable.

## Raison d'être

Pelican metadata of Markdown documents
are colon-separated key-value pairs at the beginning of the document.
Markdown parsers see them as a block of text
and generate an unintended paragraph when rendered.

To mitigate this, the metadata can be embedded
inside a form of Markdown comments.
This plugin uses link references as comments, suggested by a
[StackOverflow answer](https://stackoverflow.com/a/20885980):

```md
[//]: # (This may be the most platform independent comment)
```