semvec/pypi-packages huggingface dataset:
yasg-util 0.2.0
Injecting parameters through annotations based on drf-yasg
License: MIT
Requires Python: >=3.6

# yasg-util

Injecting parameters through annotations based on drf-yasg

## Requirements

- Python 3.6+
- drf-yasg

## Installation

```shell
$ pip install yasg-util
```

## Start

settings.py

```python
INSTALLED_APPS = [
   ...
   'django.contrib.staticfiles',  # required for serving swagger ui's css/js files
   'drf_yasg',
   ...
]
```

urls.py

```python
from django.urls import path, re_path
from drf_yasg import openapi
from rest_framework import permissions
from drf_yasg.views import get_schema_view
from rest_framework.fields import IntegerField, CharField, DictField
from rest_framework.serializers import Serializer
from rest_framework.views import APIView
from yasg_util import restapi, Location

schema_view = get_schema_view(
    openapi.Info(
        title="Snippets API",
        default_version='v1',
        description="Test description",
        terms_of_service="https://www.google.com/policies/terms/",
        contact=openapi.Contact(email="contact@snippets.local"),
        license=openapi.License(name="BSD License"),
    ),
    public=True,
    permission_classes=(permissions.AllowAny,),
)


class DemoSerializer(Serializer):
    name = CharField(required=True, min_length=2, max_length=20, help_text='name')
    age = IntegerField(required=True, min_value=0, max_value=150, help_text='ahe')

    class Meta:
        location = Location.BODY


class ResponseSerializer(Serializer):
    code = IntegerField(default=200, help_text='status code')
    msg = CharField(default='success', help_text='response message')
    data = DictField(help_text='response data')


class DemoAPIView(APIView):
    @restapi(response_model=ResponseSerializer)
    def post(self, request, pk: int, serializer: DemoSerializer):
        return {'code': 0, 'msg': 'success', 'data': {"pk": pk, "info": serializer.data}}


urlpatterns = [
    re_path(r'^swagger(?P<format>\.json|\.yaml)$', schema_view.without_ui(cache_timeout=0), name='schema-json'),
    path('doc/', schema_view.with_ui('swagger', cache_timeout=0), name='schema-swagger-ui'),
    path('redoc/', schema_view.with_ui('redoc', cache_timeout=0), name='schema-redoc'),
    path('demo/<int:pk>', DemoAPIView.as_view()),
]
```

go to http://127.0.0.1:8000/doc
copilotcleaner 0.1
Python tool to clean copilot comments
License: MIT

# Copilot Cleaner

A simple command line tool to clean all the comments from Python project that are used by GitHub's copilot to generate code. These comments are not useful mostly and manual cleaning of these comments from large codebases is not an easy task, hence this tool.

This works only with <strong>Python</strong> projects as of now. Support for other languages will be added soon.

# Usage

```bash
user@programmer~:$ ccc -dir <path-to-project>
```

This cleans all comments that start with "#\$", so instead of just # you have to start copilot comments with "#\$".
trical 0.0.7
Find the relevant content from large text files using natural language processing
License: MIT
Keywords: nltk,article,content finder


<h2>Trical</h2>

<h4>Trical Finder</h4>

<h5>Find the relevant information from large text files using natural language processing.</h5>

<h3>Example</h3>



```` 
from trical import Trical

content = "Some random text that we dont need in our result. Often when we see drawings of the Earth and the Moon, they look really close together. But the average distance between the Earth and the Moon is 384 400 km (238 855 miles)."
    
ignore = [
    "when",
    "What",
    "how"
    "is"
] # list of words to ignore to simplify the answer more and to avoid unnecessary output (optional)


t = Trical(content) #this can extended to big text files

match_with_default_mode = t.match("what is the distance between earth and moon", ignore=ignore, mode=0)
match_with_paragraph_mode = t.match("what is the distance between earth and moon", ignore=ignore, mode=1)
score = t.total_match

print(score)
print(match_with_default_mode) #output: Often when we see drawings of the Earth and Moon, they look really close together. But average distance between Moon is 384 400 km (238 855 miles).
print(match_with_paragraph_mode) #output: Often when we see drawings of the Earth and the Moon, they look really close together. But the average distance between the Earth and the Moon is 384 400 km (238 855 miles).

````


<h5>mode=0</h5>
<h6>DEFAULT_MODE</h6>
<p>This mode Works fine on most cases if you dont care about the grammer it will be straight forward</p>

<h5>mode=1</h5>
<h6>PARAGRAPH_MODE</h6>
<p>This will work fine on text content with mostly accurate grammer these modes are used to filter duplicates so if you use this mode on contents with inaccurate grammers it might give return the answer being repeated again at the last line</p>

<h5>total_match</h5>
<p>Count of total words matched in Content</p>
humor-langs 1.0.1
Translate your string to humorous text!
License: MIT
Requires Python: >=3.6.0
Keywords: Humor owo translate copypasta emojis

<h1 align="center">humor_langs</h1>
<h4 align="center">Translate your string to humorous text!</h4>

<p align="center">
    <img alt="PyPI Version" src="https://img.shields.io/pypi/v/humor_langs">
    <img alt="Package Downloads" src="https://static.pepy.tech/personalized-badge/humor-langs?period=total&units=international_system&left_color=grey&right_color=blue&left_text=Downloads">
    <!-- <a href="https://www.codacy.com/gh/Makiyu-py/humor_langs/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=Makiyu-py/humor_langs&amp;utm_campaign=Badge_Grade"><img src="https://app.codacy.com/project/badge/Grade/3ddaa678c3414eb7befa42dbad026d40"/></a> -->
    <img alt="Package License" src="https://img.shields.io/github/license/Makiyu-py/humor_langs">
</p>

<br>

## What This Package Can Give You

- [ ] Self-Worth
- [ ] A Significant Other
- [x] Some Funny, Humorous Text. Haha!

## Installation

| Operating System | Installation via pip       |
| :--------------: | :------------------------- |
|     Windows      | `pip install humor-langs`  |
|   MacOS/Linux    | `pip3 install humor-langs` |

## Examples

### Converting a list of sentences to owo

```python
import humor_langs

humor_langs.owofy(["what are you doing over there?",
       "hello there reader!",
       "See you in the terminal!"
       ],
      _print=True)
```

This will return...

```
Hewoooooo >w< what awe u doing ovew thewe? O·w·O
Haiiiiii 0w0 hewwo thewe weadew! ^w^
*W* See u in the tewminyaw! ;;w;;
```

### Adding a list of sentences _clap_ emojis on every other word

```python
from humor_langs import clap_emojifier

clap_emojifier(["what are you doing over there?",
       "hello there reader!",
       "See you in the terminal!"
       ],
      _print=True)
```

then this would return...

```
what 👏 are 👏 you 👏 doing 👏 over 👏 there?
hello 👏 there 👏 reader!
See 👏 you 👏 in 👏 the 👏 terminal!
```

> **NOTE**:\
> When testing it out, if the outputs look like some random question marks,
> _then your console probably doesn't support emojis._

### Converting a list of sentences to a kind-of strong british accent

```python
from humor_langs import strong_british_accent

strong_british_accent(["what are you doing over there?",
       "hello there reader!",
       "See you in the terminal!"
       ],
      _print=True)
```

then this'll return...

```
whaht -ahe you doing ov-ah th-ahe?
helloh th-ahe reahd-ah!
Seah you in the t-ahminahl!
```

(yea, it's kind of bad~)

### Converting a sentence to emojis

```python
from humor_langs import text_to_emoji

text_to_emoji("hello world! <3", _print=True)
```

then this'll return...

```
🇭️ 🇪️ 🇱️ 🇱️ 🇴️  🇼️ 🇴️ 🇷️ 🇱️ 🇩️ ❗️  ❤️
```

## License

This package is [currently under the MIT License](https://github.com/Makiyu-py/humor_langs/blob/master/LICENSE).
[Click here](https://choosealicense.com/licenses/mit/)
to learn more about the license.
3y 2.6.4
三圆计算器,cmd或命令行 python 3y 命令开始运行
License: MIT
Keywords: 3y

# 3yzh

A three-circle calculator, It contains Circle Circles and Cylinders.
It is in Chinese.If you konw how to speak and write or mean these,you can use

Now,you can Download and input python 3y and then it will running

Please comply with local laws and regulations, 
User only has the right to use 
The final interpretation belongs to the author 
For mainland China only. 
You can see or read the log in log.py
This means that you have read and agreed to all the above regulations. 

Welcome Download and use!