Metadata-Version: 2.1
Name: statprly
Version: 0.1.2
Summary: Python package with recognition tools.
Home-page: https://github.com/Alladin9393/statprly
Author: Alladin9393
Author-email: ember.toon@protonmail.com
License: MIT
Description: ## STATPRLY
        
        [![Release](https://img.shields.io/github/release/alladin9393/statprly.svg)](https://github.com/alladin9393/statprly/releases)
        [![PyPI version shields.io](https://img.shields.io/pypi/v/statprly.svg)](https://pypi.python.org/pypi/statprly/)
        [![Build Status](https://travis-ci.com/Alladin9393/statprly.svg?branch=develop)](https://travis-ci.com/Alladin9393/statprly)
        [![CodeFactor](https://www.codefactor.io/repository/github/alladin9393/statprly/badge)](https://www.codefactor.io/repository/github/alladin9393/statprly)
        
        [![PyPI pyversions](https://img.shields.io/pypi/pyversions/statprly.svg)](https://pypi.python.org/pypi/statprly/)
        
        `STATPRLY` - is a python package with recognition tools.
        
        Set of tools:
        
            * Bayesian recognition digit based on standards
            
          * [Getting started](#getting-started)
            * [Requirements](#getting-started-requirements)
              * [Ubuntu 16.04 & 18.04](#ubuntu-1604--1804)
              * [MacOS](#macos)
            * [Installation](#installation)
          * [Usage](#usage)
            * [Bayesian Recognition Digit](#bayesian-recognition-digit-usage)
          * [Development](#development)
          * [Production](#production)
          * [Contributing](#contributing)
            * [Request pull request's review](#request-pull-requests-review)
        
        ## Getting started
        
        <h3 id="getting-started-requirements">Requirements</h4>
        
        #### Ubuntu 16.04 & 18.04
        
        If you have 16.04 version, install system requirements with the following terminal commands:
        
        ```bash
        $ sudo apt update && sudo apt install -y software-properties-common build-essential
        ```
        
        #### MacOS
        
        Install Python 3.7 (also, we support 3.6):
        ```bash
        $ brew install python3
        ```
        
        ## Installation
        
        Install the package from the [PyPi](https://pypi.org/project/statprly) through pip:
        
        ```bash
        $ pip3 install statprly
        ```
        
        ## Usage
        
        #### Bayesian Recognition Digit
        <a name="bayesian-recognition-digit-usage"></a>
        
        Recognize random digit with noise:
        
        ```python
        import numpy
        
        from statprly import MonoDigitRecognizer
        
        if __name__ == '__main__':
            recognizer = MonoDigitRecognizer()
            noise = 0.1
            with open('path_to_digit_to_recognize') as f:
                digit_to_predict = f.read()
            
            digit_to_predict = numpy.array(digit_to_predict)
            recognized_digit = recognizer.recognize(
                digit_to_predict_data=digit_to_predict,
                noise_probability=noise,
            )
        
            print(recognized_digit)    
        ```
        
        Recognize random digit with noise with data from `Pattern Recognition Server`:
        
        Install requirements to interact with server:
        ```bash
        $ pip3 install websockets
        ```
        
        Example code can be found here:
        [Link to github gist](https://gist.github.com/Alladin9393/52c22ac263684d878ce8819642a07f1a).
        
        ## Development
        
        Clone the project and move to project folder:
        
        ```bash
        $ git clone https://github.com/Alladin9393/statprly.git && cd statprly
        ```
        
        Create virtualenv and install requirements:
        
        ```bash
        $ virtualenv venv -p python3 && source venv/bin/activate
        $ pip3 install -r requirements/development.txt
        ```
        
        To run tests use:
        
        ```bash
        $ coverage run -m pytest -vv tests
        ```
        
        When you have developed new functionality, check it with the following command. This command creates the Python 
        package from source code instead of installing it from the PyPi:
        
        ```bash
        $ pip3 uninstall -y statprly && rm -rf dist/ statprly.egg-info && \
              python3 setup.py sdist && pip3 install dist/*.tar.gz
        ```
        ## Production
        
        To build the package and upload it to [PypI](https://pypi.org/) to be accessible through 
        [pip](https://github.com/pypa/pip), use the following commands. [Twine](https://twine.readthedocs.io/en/latest/) 
        requires the username and password of the account package is going to be uploaded to.
        
        ```bash
        $ python3 setup.py sdist
        $ twine upload dist/*
        username: alladin9393
        password: ******
        ```
        
        ## Contributing
        
        #### Request pull request's review
        
        If you want to your pull request to be review, ensure you:
        
        If you want to your pull request to be review, ensure you:
        1. [Branch isn't out-of-date with the base branch](https://habrastorage.org/webt/ux/gi/wm/uxgiwmnft08fubvjfd6d-8pw2wq.png).
        2. [Have written the description of the pull request and have added at least 2 reviewers](https://camo.githubusercontent.com/55c309334a8b61a4848a6ef25f9b0fb3751ae5e9/68747470733a2f2f686162726173746f726167652e6f72672f776562742f74312f70792f63752f7431707963753162786a736c796f6a6c707935306d7862357969652e706e67).
        3. [Continuous integration has been passed](https://habrastorage.org/webt/oz/fl/-n/ozfl-nl-jynrh7ofz8yuz9_gapy.png).
        
Platform: UNKNOWN
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
