semvec/pypi-packages huggingface dataset:
nicoclient 1.1.9
A python client to interact with nicovideo.jp

# nicoclient

[![codecov](https://codecov.io/gh/jaeseopark/nicoclient/branch/master/graph/badge.svg)](https://codecov.io/gh/jaeseopark/nicoclient) ![PyPI](https://img.shields.io/pypi/v/nicoclient.svg)

A python client to interact with [nicovideo.jp](https://nicovideo.jp).

## Installation

```bash
pip install nicoclient
```

## Features

### Get video metadata

```python
metadata = nicoclient.get_video('sm34734479')
```

```json
{
  "id": "sm34734479",
  "views": 3033,
  "likes": 163,
  "thumbnail_url": "http://tn.smilevideo.jp/smile?i=34734479.81262",
  "title": "出来るだけ感情的に「ヘイトクライム」を歌いました。",
  "uploader_id": "33765098",
  "description": "最後まで聴いてもらえると嬉しいです。素晴らしい原曲  sm33841308MIX　みけ　mylist/58924781　https://twitter.com/rnike_san 歌　ててて　mylist/41403147　https://twitter.com/tetete2525"
}
```

### Get trending videos

```python
videos = nicoclient.get_daily_trending_utattemita_videos()
for video in videos:
    print(f"'{video['id']}' has {video['views']} views and {video['likes']} likes")
```
```
'sm34658459' has 40057 views and 1293 likes
'sm34248511' has 278194 views and 14274 likes
'sm34676260' has 96529 views and 6554 likes
...
```

### Get videos in a playlist

```python
playlist = nicoclient.get_playlist('58924781')
for video in playlist.videos:
    print(f"'{video.id}' has {video.views} views and {video.likes} likes")
```
```
'sm29118726' has 1104 views and 28 likes
'sm29299741' has 837 views and 19 likes
'sm29816849' has 1476 views and 32 likes
...
```

### Get related videos

#### Use case 1

If the video is a Vocaloid Original, then the function returns Utattemita videos.

```python
related_videos = nicoclient.get_related_videos('sm32076378')
print('\n'.join([v['title'] for v in related_videos]))
```
```
"ドラマツルギー 歌ってみた【りぶ】",
"ドラマツルギー　歌ってみた【そらる】",
"【ウォルピス社】ドラマツルギーを歌ってみました【提供】",
"【浦島坂田船歌ってみたツアー】ドラマツルギー【うらたぬき】",
"【爽快に】ドラマツルギー 歌ってみた ver.Sou",
"『ドラマツルギー』を 歌ってみた。by天月",
...
```

#### Use case 2

If the video is _NOT_ a Vocaloid Original, then the function returns other videos by the uploader.

```python
related_videos = nicoclient.get_related_videos('sm32103696')
print('\n'.join([v['title'] for v in related_videos]))
```
```
"Marygold 歌ってみた【りぶ】",
"沙上の夢喰い少女 歌ってみた【りぶ】",
"BEAUTIFUL DREAMER 歌ってみた【りぶ】",
"夜と虹色 歌ってみた【りぶ】",
"Starduster 歌ってみた【りぶ】",
"ピエロ 歌ってみた【りぶ】",
...
```
computex-cli 0.2.0
ComputeX CLI tool
Requires Python: >=3.8.1,<4.0.0

# cx
The ComputeX Python CLI lets you interact with ComputeX REST APIs and push images for your models to the ComputeX container registry.

## Installation

### Requirements
- Python >= 3.8

Run `pip install cx`.

## Command Line Interface
At any time, you can utilize the `--help` flag with any command or subcommand:

```shell
$ cx --help
Usage: cx [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  login
  ...
```

### Logging In
```shell
$ cx login --username {username} --password {password}
```

### Building an Image
WIP

### Pushing an Image
WIP

## Development
To test locally, run the following:
```shell
$ source setup_env.sh
$ python -m cxcli.cli
```

### Publishing to PyPI
The process for publishing to PyPI works as follows:

- Pull down the `main` branch.
- Tag it with the current version as specified in `pyproject.toml`.
- Push that tag to the repo, which...
- Triggers a GitHub Action workflow (`pypi.yml`) that pushes it to PyPI.

This can all be done simply by running the following `make` command:

```shell
make pypi-publish 
```

Assuming you have the ability to push a tag to the repo, you'll be able to publish to PyPI.

**WARNING:** if you do not specify a new version in `pyproject.toml`, the GHA workflow will fail due to an existing package being on PyPI.
revoltbots.py 0.0.2
A small package for the revoltbots api!

# RevoltBots.py
For Use with the RevoltBotList API!


## Installation
```bash
pip3 install revoltbots.py
```

## Example Usage:
```py
from revoltbots import RBL
RBList = RBL.RevoltBots(ApiKey="xxxxx", botId="xxxxx")

def post():
    """ POST Stats """
    res = RBList.postStats(3)
    print(res)

def getStats():
    """ GET Stats """
    res = RBList.getStats()
    print(res)


def checkVotes():
    """ GET Votes """
    res = RBList.checkVotes()
    print(res)


def getVoter():
    """ Check Voter """
    res = RBList.checkVoter(userId="id")
    print(res)

```
ulf2english 0.1.1
A Python port of the Lisp ulf2english package by Gene Kim.
Requires Python: >=3.7

# Python ULF-to-English

Maps Unscoped Logical Form (ULF) formulas to English sentences. A Python port of the original [Common Lisp ulf2english implementation](https://github.com/genelkim/ulf2english) by Gene Kim.

## Dependencies

* [pattern](https://github.com/clips/pattern); If using Python 3, install with `pip install pattern`.
* [ulflib](https://pypi.org/project/ulflib/)
* [transduction](https://pypi.org/project/transduction/)
* [memoization](https://pypi.org/project/memoization/)

## Summary

Install the package using `pip install ulf2english`.

The following example shows how to convert ULF to English using the package:

```python
from ulf2english import ulf2english

ulf = ['this.pro', [['pres', 'be.v'], ['=', ['a.d', ['test.n', 'ulf.n']]]]]
ulf2english.convert(ulf)
# -> "This is a test ulf."
```

The following optional parameters can be given to the convert function:

* `add_punct = False` : omit any final punctuation in the generated sentence.
* `capitalize_front = False` : do not capitalize the first word in the generated sentence.
* `add_commas = True` : add commas to the generated sentence in particular sub-expressions.
* `standardize = True` : standardize the generated sentence by converting to all-lowercase and adding space around all punctuation.
* `verbose = True` : print the intermediate staged output after each processing stage.
wf-honeycomb-io 2.1.2
Tools for working with data in Wildflower's Honeycomb database
Keywords: database

# honeycomb_io

Tools for working with data in Wildflower's Honeycomb database

## Installation

`pip install wf-honeycomb-io`

## Task list
* Integrate Honeycomb IO functions from `wf-inference-helpers`
* Integrate Honeycomb IO functions from `cuwb_sensor`
* Integrate Honeycomb IO functions from `wf-inference-airflow`?
* Integrate Honeycomb IO functions from `wf-video-stream-consumer`?
* Integrate Honeycomb IO functions from `wf-pose-producer`?
* Integrate Honeycomb IO functions from `honeycomb-geom-processor`?
* Integrate Honeycomb IO functions from `honeycomb-video-streamer`?
* Integrate Honeycomb IO functions from `wf-honeycomb-service-event-producer`?
* Integrate Honeycomb IO functions from `classroom-video-uploader`?
* Redesign architecture so user doesn't need to create a client
* Create a function for each basic verb:
  - objects()
  - get_object()
  - find_objects()
* Create corresponding functions for each verb/object combination?
* Rewrite existing external functions to use the basic functions above
* Consider replacing existing external functions with the basic functions above (changes API)