Metadata-Version: 2.1
Name: covid19-data
Version: 1.1.2
Summary: A fast, powerful, and flexible way to get up to date COVID-19 data for any major city, state, country, and total world wide data, with just one line of code
Home-page: http://github.com/binarynightowl/covid19_python
Author: Taylor Dettling
Author-email: taylor@binarynightowl.com
License: MIT
Description: # COVID19-Data
        ![Build Status](https://github.com/binarynightowl/covid19_python/workflows/Build%20Status/badge.svg)
        <img alt="GitHub issues" src="https://img.shields.io/github/issues/binarynightowl/covid19_python">
        <img alt="PyPI - Python Version" src="https://img.shields.io/pypi/pyversions/covid19-data?logo=python">
        <img alt="GitHub release (latest by date)" src="https://img.shields.io/github/v/release/binarynightowl/covid19_python?logo=github">
        <img alt="PyPI" src="https://img.shields.io/pypi/v/covid19-data?label=PyPi&logo=PyPi">
        <img alt="GitHub release (latest by date including pre-releases)" src="https://img.shields.io/github/v/release/binarynightowl/covid19_python?include_prereleases&label=pre-release&logo=github">
        
        ## Overview
        covid19-data is a powerful and easy to use Python client for getting COVID-19 data (*see sources below
        for more information on how data is obtained*)
        * Uses a fast method of getting data
            * Does not rely on scraping sites, parsing files, or getting (old) data from a repository, so you do not depend on the 
            repository being updated to get up to date data
        * Very fast and responsive
            * The client only gets the data once, and parses it into a search friendly format in the backend, so once the data is 
            loaded ( *~* 1 second ), data for the World or any Country/State can be retrieved instantly
        * User friendly and simple to implement into your application
        * Very flexible and will return the data in multiple forms (*read documentation section for more info*)
            * Can return data as a "Class Style Object" with attributes (*only requires one line of code, and is super easy to
             read!*)
            * Can return an object with the data as attributes
            * Can return a JSON document
        * Super simplistic and lightweight and does not rely on any external python packages
        
        
        ## Installing
        covid19-data can be installed with [pip](https://pypi.org/project/covid19-data/):
        ```
        $ pip install covid19-data
        ```
        Alternatively, you can grab the latest source code from [GitHub](https://github.com/binarynightowl/covid19_python):
        ```
        $ git clone git://github.com/binarynightowl/covid19_python
        $ python setup.py install
        ```
        
        
        # Documentation
        
        ## Usage
        There are multiple ways of getting data with covid19-data
        1. Object/parameter style retrieval
            * Gets the data by calling the class of the desired information source and the statistics for any location. *As of now, only John Hopkins University
             (__JHU__) is
             supported but in
             a future release, multiple sources will be supported*.
              ```python
              from covid19_data import JHU
            
              # Format: <Data Source>.<Location>.<Statistic>
              # For example to get data from John Hopkins University, review the following example:
              # JHU.China.deaths
                
              print("The number of COVID-19 recoveries in the US: " + str(JHU.US.recovered))
              print("The number of confirmed COVID-19 cases in Texas: " + str(JHU.Texas.confirmed))
              print("The number of COVID-19 deaths in California: " + str(JHU.California.deaths))
              print("The number of worldwide COVID-19 deaths: " + str(JHU.Total.deaths))
              print("The number of COVID-19 deaths in China: " + str(JHU.China.deaths))
              print("The number of COVID-19 deaths in UK: " + str(JHU.UnitedKingdom.deaths))
                ```
                Sample Output:
                ```
                The number of COVID-19 recoveries in the US : 685164
                The number of confirmed COVID-19 cases in Texas : 150851
                The number of COVID-19 deaths in California : 5935
                The number of worldwide COVID-19 deaths : 502947
                The number of COVID-19 deaths in China : 4641
                The number of COVID-19 recoveries in the United Kingdom : 1364
                ```
              
        2. As an object with attributes of COVID data
            * Get the data by name (*note: spacing and capitalization do not matter, EX: `total = covid19_data.dataByName("New 
            York")`, 
            `total = covid19_data.dataByName("newyork")`, and `total = covid19_data.dataByName("NEW YORK")` are all interchangable*)
                ```python
                import covid19_data
            
                # example of how to get data by name
                # .dataByName([string of item to find: any state, country, or total amount (spacing and capitalization do not matter)])
                # object has three useful attributes: .deaths, .cases (.confirmed also works), and .recovered
                
                total = covid19_data.dataByName("Total")    # create an object for our total data
                china = covid19_data.dataByName("China")
                US = covid19_data.dataByName("US")
                new_york = covid19_data.dataByName("NewYork")
                print(total.deaths, china.recovered, US.cases)
                ```
                Sample Output:
                ```
                22184 74181 69246
                ```
            * Get the data by abbreviation (*note: spacing and capitalization do not matter, EX: `total = covid19_data.dataByName("New 
            York")`, 
            `total = covid19_data.dataByName("newyork")`, and `total = covid19_data.dataByName("NEW YORK")` are all interchangable*)
                ```python
                import covid19_data        
                
                # example of how to get data by abbreviated name
                # .dataByNameShort([two letter string of item you want to find, can be any state])
                # object has three useful attributes: .deaths, .cases (.confirmed also works), and .recovered
                
                texas = covid19_data.dataByNameShort("TX")    # create an object for our total data
                california = covid19_data.dataByNameShort("CA")
                new_york = covid19_data.dataByNameShort("NY")
                print(texas.cases, california.deaths, new_york.cases)
                ```
                Sample Output:
                ```
                1353 67 33033
                ```
        3. As a JSON document 
            * Get the json by name (*note: spacing and capitalization do not matter, EX: `total = covid19_data.dataByName("New 
            York")`, 
            `total = covid19_data.dataByName("newyork")`, and `total = covid19_data.dataByName("NEW YORK")` are all interchangable*)
                ```python
                import covid19_data
                
                # example of how to get json by name
                # .jsonByName([string of item you want to find, can be any state, country, or total amount (spacing and capitalization do not matter)])
                # object has three useful attributes: .deaths, .cases (.confirmed also works), and .recovered
                
                total = covid19_data.jsonByName("Total")    # create an object for our total data
                china = covid19_data.jsonByName("China")
                US = covid19_data.jsonByName("US")
                new_york = covid19_data.jsonByName("NewYork")
                print(total, china, US, new_york)
                ```
                Sample Output::
                ```
                {'Confirmed': 492603, 'Deaths': 22184, 'Recovered': 119918}
                {'Confirmed': 81782, 'Deaths': 3291, 'Recovered': 74181, 'Active': 4310}
                {'Confirmed': 69246, 'Deaths': 1046, 'Recovered': 619, 'Active': 0}
                {'Confirmed': 33033, 'Deaths': 366, 'Recovered': 0, 'Active': 0}
                ```
            * Get the json by abbreviation (*note: spacing and capitalization do not matter, EX: `total = covid19_data.dataByName("New 
            York")`, 
            `total = covid19_data.dataByName("newyork")`, and `total = covid19_data.dataByName("NEW YORK")` are all interchangable*)
                ```python
                import covid19_data
                
                # example of how to get json by abbreviated name
                # .jsonByNameShort([two letter string of item you want to find, can be any state])
                # object has three useful attributes: .deaths, .cases (.confirmed also works), and .recovered
                
                texas = covid19_data.jsonByNameShort("TX")    # create an object for our total data
                california = covid19_data.jsonByNameShort("CA")
                new_york = covid19_data.jsonByNameShort("NY")
                print(texas, california, new_york)
                ```
                Sample Output::
                ```
                {'Confirmed': 1353, 'Deaths': 17, 'Recovered': 0, 'Active': 0}
                {'Confirmed': 3172, 'Deaths': 67, 'Recovered': 0, 'Active': 0}
                {'Confirmed': 33033, 'Deaths': 366, 'Recovered': 0, 'Active': 0}
                ```
          
        #### Sources
        This package utilizes [John Hopkins University's](https://coronavirus.jhu.edu/map.html) [ArcGIS data layer](https://services1.arcgis.com/0MSEUqKaxRlEPj5g/ArcGIS/rest/services/ncov_cases/FeatureServer) 
        to get its data. Please follow their terms of service and licensing when using their data in your application. The data layer 
        pulls data from the 
        following sources:
        - [World Health Organization (WHO)](https://www.who.int/)
        - [DXY.cn. Pneumonia. 2020.](http://3g.dxy.cn/newh5/view/pneumonia)
        - [BNO News](https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/)
        - [National Health Commission of the People’s Republic of China (NHC)](http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml)
        - [China CDC (CCDC)](http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm)
        - [Hong Kong Department of Health](https://www.chp.gov.hk/en/features/102465.html)
        - [Macau Government](https://www.ssm.gov.mo/portal/)
        - [Taiwan CDC](https://sites.google.com/cdc.gov.tw/2019ncov/taiwan?authuser=0)
        - [US CDC](https://www.cdc.gov/coronavirus/2019-ncov/index.html)
        - [Government of Canada](https://www.canada.ca/en/public-health/services/diseases/coronavirus.html)
        - [Australia Government Department of Health](https://www.health.gov.au/news/coronavirus-update-at-a-glance)
        - [European Centre for Disease Prevention and Control (ECDC)](https://www.ecdc.europa.eu/en/geographical-distribution-2019-ncov-cases)
        - [Ministry of Health Singapore (MOH)](https://www.moh.gov.sg/covid-19)
        - [Italy Ministry of Health](http://www.salute.gov.it/nuovocoronavirus)
        
Keywords: covid covid-19 corona coronavirus query hopkins python attribute fast easy powerful flexible json data statistics city state total world john hopkins scraping
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
