semvec/pypi-packages huggingface dataset:
aniffinity 0.2.0
Calculate affinity between anime list users
License: MIT
Keywords: anilist affinity kitsu myanimelist scores pearson

|ftb1| |ftb2| |ftb3|


aniffinity
==========

|pypi| |travis| |rtd|

*"An-knee-fin-knee-tea"*.

Calculate affinity between anime list users.


What is this?
-------------

Calculate affinity between a user and another user on anime list
services. Refer to the `docs <#documentation>`__ for more info.


Install
-------

..  code-block:: bash

    pip install aniffinity


Dependencies
------------

* json-api-doc
* requests


Example Usage
-------------

..  code-block:: python

    from aniffinity import Aniffinity

    af = Aniffinity("Xinil", base_service="MyAnimeList")

    affinity, shared = af.calculate_affinity("Josh", service="AniList")

    print(affinity)
    # 32.15230953451651
    print(shared)
    # 31


Available Services
------------------

* `AniList <https://anilist.co>`__
* `Kitsu <https://kitsu.io>`__
* `MyAnimeList <https://myanimelist.net>`__

For more info, read the `docs <#documentation>`__.


Documentation
-------------

Documentation at https://aniffinity.readthedocs.io


Legal Stuff
-----------

Licensed under MIT. See `LICENSE <LICENSE>`__ for more info.


Cat Gif
-------

..  figure:: https://i.imgur.com/sq42SnU.gif
    :alt:


..  |ftb1| image:: http://forthebadge.com/images/badges/made-with-python.svg
    :target: http://forthebadge.com
..  |ftb2| image:: http://forthebadge.com/images/badges/contains-cat-gifs.svg
    :target: http://forthebadge.com
..  |ftb3| image:: http://forthebadge.com/images/badges/built-with-love.svg
    :target: http://forthebadge.com

..  |pypi| image:: https://img.shields.io/pypi/v/aniffinity.svg
    :target: https://pypi.org/project/aniffinity/
..  |travis| image:: https://travis-ci.org/erkghlerngm44/aniffinity.svg?branch=master
    :target: https://travis-ci.org/erkghlerngm44/aniffinity?branch=master
..  |rtd| image:: https://readthedocs.org/projects/aniffinity/badge/?version=latest
    :target: https://aniffinity.readthedocs.io/en/latest/
noisify 1.0
Framework for creating synthetic data with realistic errors for refining data science pipelines.
License: MIT

# Noisify

Noisify is a simple light weight library for augmenting and modifying data by adding realistic noise.

## Introduction

Add some human noise (typos, things in the wrong boxes etc.)

    >>> from noisify.recipes import human_error
    >>> test_data = {'this': 1.0, 'is': 2, 'a': 'test!'}
    >>> human_noise = human_error(5)
    >>> print(list(human_noise(test_data)))
    [{'a': 'tset!', 'this': 2, 'is': 1.0}]
    >>> print(list(human_noise(test_data)))
    [{'a': 0.0, 'this': 'test!', 'is': 2}]

Add some machine noise (gaussian noise, data collection interruptions etc.)

    >>> from noisify.recipes import machine_error
    >>> machine_noise = machine_error(5)
    >>> print(list(machine_noise(test_data)))
    [{'this': 1.12786393038729, 'is': 2.1387080616716307, 'a': 'test!'}]

If you want both, just add them together

    >>> combined_noise = machine_error(5) + human_error(5)
    >>> print(list(combined_noise(test_data)))
    [{'this': 1.23854334573554, 'is': 20.77848220943227, 'a': 'tst!'}]

Add noise to numpy arrays

    >>> import numpy as np
    >>> test_array = np.arange(10)
    >>> print(test_array)
    [0 1 2 3 4 5 6 7 8 9]
    >>> print(list(combined_noise(test_array)))
    [[0.09172393 2.52539794 1.38823741 2.85571154 2.85571154 6.37596668
                      4.7135771  7.28358719 6.83600156 9.40973018]]

Read an image

    >>> from PIL import Image
    >>> test_image = Image.open(noisify.jpg)
    >>> test_image.show()



And now with noise

    >>> from noisify.recipes import human_error, machine_error
    >>> combined_noise = machine_error(5) + human_error(5)
    >>> for out_image in combined_noise(test_image):
    ...     out_image.show()


*Noisify* allows you to build flexible data augmentation pipelines for arbitrary objects.
All pipelines are built from simple high level objects, plugged together like lego.
Use noisify to stress test application interfaces, verify data cleaning pipelines, and to make your ML algorithms more
robust to real world conditions.

## Installation

#### Prerequisites
Noisify relies on Python 3.5+

#### Installation from pipy
    $ pip install noisify

## Additional Information

Full documentation is available at TODO ReadTheDocs Link.
## Licence

Dstl (c) Crown Copyright 2019

Noisify is released under the MIT licence
tornado-swagger-ui 0.1
Swagger UI for Tornado
License: MIT
Keywords: tornado,swagger,tornado-swagger

# tornado-swagger-ui

Simple Tornado Handler for adding [Swagger UI](https://github.com/swagger-api/swagger-ui) to your tornado application.

Included Swagger UI version: 3.22.1.

## Installation

`pip install git+https://gitlab.com/api-projects-boilerplates/tornado-swagger-ui.git`

## Usage

Example application:

```python
import tornado.ioloop
import tornado.web
from tornado_swagger_ui import get_tornado_handler

SWAGGER_URL = '/api/docs'  # URL for exposing Swagger UI (without trailing '/')
# Our API url (can of course be a local resource)
API_URL = 'http://petstore.swagger.io/v2/swagger.json'

# Call factory function to create our handler
swagger_handlers = get_tornado_handler(
    base_url=SWAGGER_URL,
    api_url=API_URL,
    config={
        "app_name": "Test application"
    },
    # oauth_config={  # OAuth config. See https://github.com/swagger-api/swagger-ui#oauth2-configuration .
    #    'clientId': "your-client-id",
    #    'clientSecret': "your-client-secret-if-required",
    #    'realm': "your-realms",
    #    'appName': "your-app-name",
    #    'scopeSeparator': " ",
    #    'additionalQueryStringParams': {'test': "hello"}
    # }
)


class IndexHandler(tornado.web.RequestHandler):
    def get(self):
        self.finish("Tornado Swagger UI")

handlers = [
    (r"/", IndexHandler)
]

handlers.extend(swagger_handlers)

def make_app():
    return tornado.web.Application(handlers)


if __name__ == "__main__":
    app = make_app()
    app.listen(5000)
    tornado.ioloop.IOLoop.current().start()

# Now point your browser to localhost:5000/api/docs/

```

## Configuration

The handler supports overloading all Swagger UI configuration options that can be JSON serialized.
See https://github.com/swagger-api/swagger-ui#parameters for options.

Plugins and function parameters are not supported at this time.

OAuth2 parameters can be found at https://github.com/swagger-api/swagger-ui#oauth2-configuration .

## 

Based on the package:

* https://github.com/sveint/flask-swagger-ui