semvec/pypi-packages huggingface dataset:
django-graphiql-debug-toolbar 0.2.0
Django Debug Toolbar for GraphiQL IDE.
License: MIT
Requires Python: >=3.6,<4.0
Keywords: django,graphql,graphiql,debug

# Django GraphiQL Debug Toolbar

[![Tests](https://github.com/flavors/django-graphiql-debug-toolbar/actions/workflows/test-suite.yml/badge.svg)](https://github.com/flavors/django-graphiql-debug-toolbar/actions)
[![Coverage](https://img.shields.io/codecov/c/github/flavors/django-graphiql-debug-toolbar?color=%2334D058)](https://codecov.io/gh/flavors/django-graphiql-debug-toolbar)
[![Codacy](https://app.codacy.com/project/badge/Grade/354f70cdefda40938c397d8651a2a06c)](https://www.codacy.com/gh/flavors/django-graphiql-debug-toolbar/dashboard)
[![Package version](https://img.shields.io/pypi/v/django-graphiql-debug-toolbar.svg)](https://pypi.python.org/pypi/django-graphiql-debug-toolbar)

[Django Debug Toolbar](https://github.com/jazzband/django-debug-toolbar) for [GraphiQL](https://github.com/graphql/graphiql) IDE.

![Graphiql Debug Toolbar](https://user-images.githubusercontent.com/5514990/36340937-1937ee68-1419-11e8-8477-40622e98c312.gif)

## Dependencies

*   Python ≥ 3.6
*   Django ≥ 2.2

## Installation

Install last stable version from Pypi.

```sh
pip install django-graphiql-debug-toolbar
````

See the [documentation](https://django-debug-toolbar.readthedocs.io/en/stable/installation.html) for further guidance on setting *Django Debug Toolbar*.

Add `graphiql_debug_toolbar` to your *INSTALLED_APPS* settings:

```py
INSTALLED_APPS = [
    'debug_toolbar',
    'graphiql_debug_toolbar',
]
```

**Replace** the Django Debug Toolbar **middleware** with the GraphiQL Debug Toolbar one. 

```py
MIDDLEWARE = [
    # 'debug_toolbar.middleware.DebugToolbarMiddleware',
    'graphiql_debug_toolbar.middleware.DebugToolbarMiddleware',
]
```

Credits to [@jazzband](https://jazzband.co) / [django-debug-toolbar](https://github.com/jazzband/django-debug-toolbar).
aqualogic-wireless 3.0
Library for interfacing with a Hayward/Goldline AquaLogic/ProLogic pool controller.
License: MIT

A python library to interface with Hayward/Goldline AquaLogic/ProLogic pool controllers. Note that the Goldline protocol uses RS-485 so a hardware interface that can provide the library with reader and writer file objects is required. The simplest solution for this is an RS-485 to Ethernet adapter connected via a socket.
crtsearch 1.0.1
A Tool written in Python3 for scraping data from crt.sh
License: MIT
Keywords: crt.sh,subdomains,thehackersbrain,gauravraj,python3

# CRTSH
> crt.sh data scraping script in python

<br/>

Simple Python3 Script for scraping data from `crt.sh`.

<br/>

## Usage
- `python3 main.py -d 'gauravraj.tech'`
```bash
[elliot@archlinux]  crtsh python main.py -d 'gauravraj.tech'
╭───────────────────────────────────────────────────────────────────────────────────────────────────────╮
│                                       Found Subdomains - CRT.SH                                       │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────╯

[+] gauravraj.tech
[+] blog.gauravraj.tech
[+] *.gauravraj.tech
```

<br/>

- `python3 main.py -d 'gauravraj.tech' -r`
```bash
[elliot@archlinux]  crtsh python main.py -d 'gauravraj.tech' -r
╭───────────────────────────────────────────────────────────────────────────────────────────────────────╮
│                                           Raw Data - CRT.SH                                           │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────╯

[
    {
        'issuer_ca_id': 183267,
        'issuer_name': "C=US, O=Let's Encrypt, CN=R3",
        'common_name': 'gauravraj.tech',
        'name_value': 'gauravraj.tech\nwww.gauravraj.tech',
        'id': 4875700034,
        'entry_timestamp': '2021-07-15T08:11:14.637',
        'not_before': '2021-07-15T07:11:14',
        'not_after': '2021-10-13T07:11:13',
        'serial_number': '0356c649bd123e7773333fb45324e776f294'
    },
    {
        'issuer_ca_id': 183267,
        'issuer_name': "C=US, O=Let's Encrypt, CN=R3",
        'common_name': 'gauravraj.tech',
        'name_value': 'gauravraj.tech\nwww.gauravraj.tech',
        'id': 4868425658,
        'entry_timestamp': '2021-07-15T08:11:14.235',
        'not_before': '2021-07-15T07:11:14',
        'not_after': '2021-10-13T07:11:13',
        'serial_number': '0356c649bd123e7773333fb45324e776f294'
    },
	...........
```

------

## Credits

- Creator: [Gaurav Raj](https://github.com/thehackersbrain/)
- Portfolio: [gauravraj.tech](https://gauravraj.tech/)
- Blog: [blog.gauravraj.tech](https://blog.gauravraj.tech/)
- TryHackMe: [hackersbrain](https://tryhackme.com/p/hackersbrain)
- HackTheBox: [hackersbrain](https://app.hackthebox.eu/profile/303514)
- Twitter: [thehackersbrain](https://twitter.com/thehackersbrain)
- Instagram: [thehackersbrain](https://instagram.com/thehackersbrain)
- Projects: [GitHub](https://github.com/thehackersbrain?tab=repositories)

--------
fumigate 0.1.8
Fumigate text
License: MIT

Fumigate

A small demo library to help in NLP's most tedious task, text cleaning.

Installation
pip install fumigate

#Get started

How to fumigate(clean) your text data

    1.  from fumigate import Fumes

    2. Instantiate a Fumes object
        fumes = Fumes()

    3. Call the purge method to clean everything.
        result = fumes.purge(<text>)
       
    4. Call the clean method to clean specific things from the methods available.

        ## methods is a list containing one or multiple methods available for fumigation.
        result = fumes.clean(<text>, methods=["url" | "sym" | "num" | "emo"], extract=False)
        
        # if extract=True returns tuple with removed characters/strings
        result, garbage = fumes.clean(<text>, methods=["url" | "sym" | "num" | "emo"], extract=True)

    5. Call the stem method for stemming.
        result = fumes.stem(<text>)

    6. Call the lemm method for lemmatizing.
        result = fumes.lemm(<text>)
aiomoe 1.0.4
Fully asynchronous trace.moe API wrapper
License: MIT
Requires Python: >=3.6.1,<4.0.0
Keywords: api,aiomoe,async,asyncio,trace.moe,tracemoe,tracemoe-api

# AioMoe

Fully asynchronous trace.moe API wrapper

## Installation

You can install the stable version from PyPI:

    $ pip install aiomoe

Or get it from github:

    $ pip install https://github.com/FeeeeK/aiomoe/archive/refs/heads/master.zip

## Usage

### Get info about your account

```python
import asyncio
from aiomoe import AioMoe

tm = AioMoe() # or AioMoe(token="xxxxxxxx")

async def main():
    me = await tm.me()
    print(me)
    print(f"Used quota: {me.quota_used}/{me.quota}")

asyncio.run(main())
```
The output will be like this:
```
User(error=None, id='your ip', priority=0, concurrency=1, quota=1000, quota_used=0)
Used quota: 0/1000
```

### Search anime
```python
import asyncio
from aiomoe import AioMoe

tm = AioMoe()

async def main():
    image = "https://i.imgur.com/Xrb06w5.png"
    search_results = await tm.search(file_source=image, anilist_info=True)
    print(search_results.result[0].anilist.title.romaji)
    # 'Steins;Gate 0'

asyncio.run(main())
```
You can pass a link to an image, bytes or file-like object (`io.BytesIO`)
```python
    with open("image.png", "rb") as file:
        search_results = await tm.search(file)
```
And use additional parameters such as:
 - anilist_info - Return an `Anilist` object instead of anilist id
 - cut_borders - Cut out black borders from screenshots
 - anilist_id - Filter results by anilist id

## See Also
  - [Response objects](https://github.com/FeeeeK/aiomoe/blob/master/aiomoe/models/models.py)
  - [trace.moe API docs](https://soruly.github.io/trace.moe-api/#/docs)
  - [trace.moe API swagger docs](https://app.swaggerhub.com/apis/soruly/api.trace.moe)

## Contributing

1.  Fork it
2.  Create your feature branch (`git checkout -b my-new-feature`)
3.  Commit your changes (`git commit -am 'Add some feature'`)
4.  Push to the branch (`git push origin my-new-feature`)
5.  Create new Pull Request

## License

Released under the MIT license.

Copyright by [FeeeeK](https://github.com/feeeek).