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BastinRobin committed Jul 7, 2020
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29 changes: 29 additions & 0 deletions LICENSE
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BSD 3-Clause License

Copyright (c) 2020, CleverInsight
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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70 changes: 70 additions & 0 deletions README.rst
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.. image:: https://cognito.readthedocs.io/en/latest/_images/logo.png
:target: http://cognito.readthedocs.org
:width: 200pt

predicteasy : powerful autoML toolkit
==========================================


+----------------------+------------------------+
| Deployment | |pypi| |conda| |
+----------------------+------------------------+
| Build Status | |travis| |
+----------------------+------------------------+
| Metrics | |coverall| |
+----------------------+------------------------+
| GitHub | |contributors| |stars| |
+----------------------+------------------------+
| License | |BSD| |
+----------------------+------------------------+
| Community | |gitter| |
+----------------------+------------------------+


PredictEasy is an exclusive python autoML library and command line utility that helps any developer to transform raw data into a machine-learning format.


Installation
------------

**Prerequisite**

- Python3.

Install the extension by using pip.

.. code:: bash
$ pip install predicteasy
Contributors
==============

.. image:: https://avatars3.githubusercontent.com/u/3523655?s=60&v=4
:target: https://github.com/BastinRobin
.. image:: https://avatars2.githubusercontent.com/u/59742431?s=60&v=4
:target: https://github.com/nibir-paul
.. image:: https://avatars0.githubusercontent.com/u/32188887?s=60&v=4
:target: https://github.com/tanvirath
.. image:: https://avatars1.githubusercontent.com/u/29769264?s=60&v=4
:target: https://github.com/vandana-11



Core Lead
----------
* `Bastin Robins J <https://github.com/bastinrobin>`__ <robin@cleverinsight.co>

Development Leads
--------------------

* `Vandana Bhagat <https://github.com/vandana-11>`__ <vandana.bhagat@christuniversity.in>


Data Science Team
-----------------

* `Nibir Paul <https://github.com/nibir-paul>`__ <nibirpaul491@gmail.com>
* `Tanvi Rath <https://github.com/tanvirath>`__ <rath.t98@gmail.com>
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5 changes: 5 additions & 0 deletions predicteasy/core/nlp/__init__.py
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from predicteasy.core.nlp.sentiment import *
from predicteasy.core.nlp.summarize import *
from predicteasy.core.nlp.spelling import *


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31 changes: 31 additions & 0 deletions predicteasy/core/nlp/sentiment.py
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from textblob import TextBlob




class SentimentClassifier:

def __init__(self, text):
self.data = text


def __str__(self):
return '{self.data} module'.format(self=self)


def predict(self):

_txt = TextBlob(self.data)

if _txt.sentiment.polarity == 0:
result = 'neutral'

if _txt.sentiment.polarity > 0:
result = 'positive'

if _txt.sentiment.polarity < 0:
result = 'negative'

return dict(polarity=_txt.sentiment.polarity,
subjectivity=_txt.sentiment.subjectivity,
sentiment=result)
41 changes: 41 additions & 0 deletions predicteasy/core/nlp/spelling.py
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import io
import pandas as pd
from textblob import TextBlob

class SpellCheck:

def __init__(self, text, multiple=False, column=""):
self.data = text
self.multiple = multiple
self.column = column



def spell_apply(self, data):
"""
spell_apply takes incorrect text and
correct the spell and returns it
:param data: The data
:type data: { type_description }
:returns: { description_of_the_return_value }
:rtype: { return_type_description }
"""
return str(TextBlob(data).correct())

def correct(self):
"""
Correct method helps us to loop throught the
given dataframe and correct the grammer
:returns: { description_of_the_return_value }
:rtype: { return_type_description }
"""
if self.multiple:
data = pd.read_csv(io.StringIO(self.data), lineterminator='\n')
data.rename(columns=lambda x: x.strip(), inplace=True)
data[self.column.strip()].apply(self.spell_apply).apply(pd.Series)
return dict(data=data.to_json(orient='records'), summary=[])
else:
return self.spell_apply(self.data)
12 changes: 12 additions & 0 deletions predicteasy/core/nlp/summarize.py
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from pprint import pprint as print
from gensim.summarization import summarize


class TextSummarize:

def __init__(self, text):
self.data = text


def summary(self, **kwargs):
return summarize(self.data, **kwargs)
8 changes: 8 additions & 0 deletions setup.cfg
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[egg_info]
tag_build = dev

[upload]
dry-run = 1

[metadata]
description-file = README.rst
84 changes: 84 additions & 0 deletions setup.py
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"""
Cognito module
"""
from codecs import open as codecs_open
from setuptools import setup, find_packages



# Get the long description from the relevant file
with codecs_open('README.rst', encoding='utf-8') as f:
LONG_DESCRIPTION = f.read()


REQUIRES = [
'tqdm',
'numpy', # REQ: vector algebra operations
'scipy',
'numpy',
'click', # REQ: command line interfacing
'pandas', # REQ: (conda) sparx.data.filter()
'textblob', # REQ: report generation engine
'PyYAML', # REQ: configuration management
'pyfiglet', # REQ: better cli interface
'PrettyTable', # REQ: CLI based table structure
'scikit-learn', # REQ: simplified unity for all ML need
]


CLASSIFIERS = [
'Development Status :: 4 - Beta',
'Environment :: Console',
'Intended Audience :: Developers',
"Operating System :: OS Independent",
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python',
'Topic :: Internet :: WWW/HTTP',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Utilities',
'Topic :: Scientific/Engineering'

]


DOWNLOAD_URL = ""
PROJECT_URLS = {
"Bug Tracker": "https://github.com/CleverInsight/predicteasy-core",
"Documentation": "https://predicteasy.readthedocs.io/en/latest/",
"Source Code": "https://github.com/CleverInsight/predicteasy-core",
}


setup(name='predicteasy',
version='0.0.1',
description=u"Auto ML simplified",
long_description=LONG_DESCRIPTION,
classifiers=CLASSIFIERS,
keywords=['AutoML', 'Automated Data Storyteller', 'Data Wrangler', 'Data Preprocessing',\
'Machine Learning', 'Hot Encoder', 'Outlier Detection'],
author=u"Bastin Robins .J",
author_email='robin@cleverinsight.co',
url='https://github.com/cleverinsight',
download_url='https://github.com/CleverInsight/predicteasy-core/releases',
project_urls=PROJECT_URLS,
license='BSD',
packages=[pkg for pkg in find_packages() if not pkg.startswith('test')],
include_package_data=True,
zip_safe=False,
install_requires=REQUIRES,

extras_require={
'test': ['pytest'],
},

entry_points="""
[console_scripts]
cognito=cognito.scripts.cli:cli
""")
9 changes: 9 additions & 0 deletions tests/test_cli.py
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from click.testing import CliRunner

# from cognito.scripts.cli import cli


# def test_cli_count():
# runner = CliRunner()
# result = runner.invoke(cli, ['3'])
# assert result.exit_code == 0
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