Coronavirus App

coronaApp.py

from flask import Flask, render_template
import requests
from bs4 import BeautifulSoup
import dateutil.parser
import pandas as pd
import plotly
from plotly import graph_objs as go
import json

app = Flask(__name__)

def data_scrape():
    base_url = 'https://www.worldometers.info/coronavirus/'
    response = requests.get(base_url, headers={
            'User-agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:61.0) Gecko/20100101 Firefox/61.0'})
    soup = BeautifulSoup(response.text, 'html.parser')
    table = soup.find('table', id=["main_table_countries_today"])
    table_rows = table.find_all('tr')
    data = []
    for tr in table_rows:
        td = tr.find_all('td')
        row = [i.text.strip().replace("+","") for i in td]
        data.append(row)
    return data

def data_cleanup():
    data = data_scrape()
    cleaned_data = []
    for row in data:
        row_list = []
        for i in row:
            i = i.replace("+","")
            i = i.replace("-","")
            i = i.replace(",","")
            if i == "":
                i = "0"
            row_list.append(i.strip())
        row_list[1:8] = map(int, row_list[1:8])
        cleaned_data.append(row_list)
    return cleaned_data

def news_scrape():
    secret = '2ab6926b9fac414faa1471562bcd2f60'
    url = 'http://newsapi.org/v2/top-headlines?country=in&category=health&apiKey=2ab6926b9fac414faa1471562bcd2f60'
    parameters = {
        'q': 'coronavirus',
        'pageSize': 40,
        'apiKey': secret,
    }
    response = requests.get(url,
                            params=parameters)
    response_json = response.json()
    article = response_json['articles']
    return article

def india_statewise():
    base_url = 'https://www.mohfw.gov.in/'
    response = requests.get(base_url, headers={
        'User-agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:61.0) Gecko/20100101 Firefox/61.0'})
    soup = BeautifulSoup(response.text, 'html.parser')
    div = soup.find('div', {'class': 'content newtab'})
    tbody = div.find('tbody')
    state_rows = tbody.find_all('tr')
    state_num = []
    for tr in state_rows[:-2]:
        td = tr.find_all('td')
        row = [i.text.strip() for i in td]
        row[2:5] = map(int, row[2:5])
        state_num.append(row)
    state_num.sort(key=lambda x: x[2], reverse=True)
    return state_num

@app.route('/')
def home():
    data = data_scrape()
    for row in data:
        if 'India' in row:
            country = row[0]
            total_cases = row[1]
            new_cases = row[2]
            total_deaths = row[3]
            new_deaths = row[4]
            active_cases = row[6]
            total_recovered = row[5]
            serious_critical = row[7]

    state_num = india_statewise()

    return render_template('index.html', country=country, total_cases=total_cases, new_cases=new_cases,
                           total_deaths=total_deaths, new_deaths=new_deaths,
                           active_cases=active_cases, total_recovered=total_recovered,
                           serious_critical=serious_critical,
                           state_num=state_num)

@app.route('/global_data')
def global_data():
    data = data_scrape()
    return render_template('global_data.html', data=data)

@app.route('/comparative_chart')
def comparative_chart():
    data = data_cleanup()
    df = pd.DataFrame(data[:15], columns=['Country', 'Total Cases', 'New Cases', 'Total Deaths', 'New Deaths',
                                     'Total Recovered', 'Active Cases', 'Serious Cases', 'Total Cases/ 1mn',
                                     'Total Deaths/ 1mn','1st Case'])
    df.head()
    to_drop = ['Total Cases/ 1mn', 'Total Deaths/ 1mn', '1st Case']
    df.drop(to_drop, inplace=True, axis=1)
    # print(df)
    df.sort_values(['Total Cases'], ascending=True, inplace=True)

    marker1 = dict(
        color='#1B4079',
        line=dict(color='#1B4079', width=3)
    )
    marker2 = dict(
        color='#4D7C8A',
        line=dict(color='#4D7C8A', width=3)
    )
    marker3 = dict(
        color='#7F9C96',
        line=dict(color='#7F9C96', width=3)
    )
    trace1 = go.Bar(y=df['Country'], x=df['Active Cases'], name='Active Cases', orientation='h', marker=marker1,
                    text=df['Active Cases'], texttemplate='%{text:.2s}', textposition='outside', width=0.8)
    trace2 = go.Bar(y=df['Country'], x=df['Total Recovered'], name='Total Recovered', orientation='h', marker=marker2,
                    text=df['Total Recovered'], texttemplate='%{text:.2s}', textposition='outside', width=0.8)
    trace3 = go.Bar(y=df['Country'], x=df['Total Deaths'], name='Total Deaths', orientation='h', marker=marker3,
                    text=df['Total Deaths'], texttemplate='%{text:.2s}', textposition='outside', width=0.8)

    layout = go.Layout(barmode='stack',
                       font=dict(family="Courier New, monospace", size=20, color="#1E2019"),
                       legend=dict(x=0.1, y=1.09,
                                   traceorder="normal",
                                   font=dict(family="sans-serif", size=20, color="black"),
                                   bordercolor="Black",
                                   borderwidth=1),
                       legend_orientation='h',
                       autosize=True,
                       xaxis_showgrid=False, yaxis_showgrid=False,
                       xaxis_showticklabels=False,
                       bargap=0.6,height=800,
                       margin=dict(
                           l=150,
                           r=50,
                           b=100,
                           t=100,
                           pad=10
                       )
                       )

    data = [trace1, trace2, trace3]
    fig = dict(data=data, layout=layout)
    graphJSON = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)

    return render_template('comparative_chart.html', graphJSON=graphJSON)

@app.route('/india_news')
def india_news():
    article = news_scrape()
    title = []
    description = []
    link = []
    published = []
    for ar in article:
        title.append(ar["title"])
        description.append(ar["description"])
        d = dateutil.parser.parse(ar["publishedAt"])
        published.append(d.strftime('%d-%m-%Y %H:%M:%S'))
        link.append(ar["url"])
    return render_template('india_news.html', title=title, description=description, published=published, link=link)

if __name__ == '__main__':
    app.run()