We are living in a modernization and industrialization era. Our life becomes more and more convenient. But the problem is Air Pollution arise with time. This Pollution makes us unhealthy, Air is a Lifeline for our life.
In this article, we are going to write python scripts to get live air quality information and bind it with GUI Application.
Modules Needed
- bs4: Beautiful Soup(bs4) is a Python library for pulling data out of HTML and XML files. To install this type the command below in the terminal.
pip install bs4
- requests: This allows you to send HTTP/1.1 requests very easily. To install this type the command below in the terminal.
pip install requests
Approach:
- Extract data form given URL. Copy the URL, after selecting the desired location.
- Scrape the data with the help of requests and Beautiful Soup module.
- Convert that data into HTML code.
- Find the required details and filter them.
Implementation:
Step 1: Import all the modules required
Python3
# import module import requests from bs4 import BeautifulSoup |
Step 2: Create a URL get function
Python3
# link to extract html data def getdata(url): r = requests.get(url) return r.text |
Step 3: Now pass the URL into the getdata function and convert that data into HTML code. The URL used here is “https://weather.com/en-IN/forecast/air-quality/l/3dbed5c769584b3604a70d40a1a0a9f6ebc99c253d955b548f4978ca101eeca1”
Python3
htmldata = getdata( # write the URL ) soup = BeautifulSoup(htmldata, 'html.parser' ) result = (soup.find_all( "div" , class_ = "styles__primaryPollutantGraphNumber__2WgP9" )) result |
Output:
[<div class=”styles__primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>67</div>,
<div class=”styles__primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>22</div>,
<div class=”styles__primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>13</div>,
<div class=”styles_N_primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>30</div>,
<div class=”styles__primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>45</div>,
<div class=”styles__primaryPollutantGraphNumber__2WgP9″ classname=”styles__primaryPollutantGraphNumber__2WgP9″>479</div>]
Step 4: Filter your data and Check your Air Quality according to the given data :
Python3
# Traverse the air quality for item in (soup.find_all( "div" , class_ = "styles__aqiGraphNumber__2R6Y9" )): res_data = item.get_text() # traverse the content data = '' for item in (soup.find_all( "div" , class_ = "styles__primaryPollutantGraphNumber__2WgP9" )): data + = item.get_text() data + = " " air_data = data.split( " " ) print ( "Air Quality :" , res_data) print ( "O3 level :" , air_data[ 0 ]) print ( "NO2 level :" , air_data[ 1 ]) print ( "SO2 level :" , air_data[ 2 ]) print ( "PM2.5 level :" , air_data[ 3 ]) print ( "PM10 level :" , air_data[ 4 ]) print ( "co level :" , air_data[ 5 ]) |
Output:
Air Quality : 85 O3 level : 67 NO2 level : 22 SO2 level : 13 PM2.5 level : 30 PM10 level : 45 co level : 479
Step 5: Now Analyze the Air Quality with the given data:
Python3
res = int (res_data) if res < = 50 : remark = "Good" impact = "Minimal impact" elif res < = 100 and res > 51 : remark = "Satisfactory" impact = "Minor breathing discomfort to sensitive people" elif res < = 200 and res > = 101 : remark = "Moderate" impact = "Breathing discomfort to the people with lungs, asthma and heart diseases" elif res < = 400 and res > = 201 : remark = "Very Poor" impact = "Breathing discomfort to most people on prolonged exposure" elif res < = 500 and res > = 401 : remark = "Severe" impact = "Affects healthy people and seriously impacts those with existing diseases" print (remark) print (impact) |
Output:
Satisfactory Minor breathing discomfort to sensitive people
Application for the live Air Quality information with Tkinter: This Script implements the above Implementation into a GUI.
Python3
# import modules from tkinter import * import requests from bs4 import BeautifulSoup # link for extract html data def getdata(url): r = requests.get(url) return r.text def airinfo(): htmldata = getdata( soup = BeautifulSoup(htmldata, 'html.parser' ) # Traverse the air quality for item in (soup.find_all( "div" , class_ = "styles__aqiGraphNumber__2R6Y9" )): res_data = item.get_text() # traverse the content data = '' for item in (soup.find_all( "div" , class_ = "styles__primaryPollutantGraphNumber__2WgP9" )): data + = item.get_text() data + = " " air_data = data.split( " " ) ar. set (res_data) o3. set (air_data[ 0 ]) no2. set (air_data[ 1 ]) so2. set (air_data[ 2 ]) pm. set (air_data[ 3 ]) pml. set (air_data[ 4 ]) co. set (air_data[ 5 ]) res = int (res_data) if res < = 50 : remark = "Good" impact = "Minimal impact" elif res < = 100 and res > 51 : remark = "Satisfactory" impact = "Minor breathing discomfort to sensitive people" elif res < = 200 and res > = 101 : remark = "Moderate" impact = "Breathing discomfort to the people with lungs, asthma and heart diseases" elif res < = 400 and res > = 201 : remark = "Very Poor" impact = "Breathing discomfort to most people on prolonged exposure" elif res < = 500 and res > = 401 : remark = "Severe" impact = "Affects healthy people and seriously impacts those with existing diseases" res_remark. set (remark) res_imp. set (impact) # object of tkinter # and background set to grey master = Tk() master.configure(bg = 'light grey' ) # Variable Classes in tkinter air_data = StringVar() ar = StringVar() o3 = StringVar() no2 = StringVar() so2 = StringVar() pm = StringVar() pml = StringVar() co = StringVar() res_remark = StringVar() res_imp = StringVar() # Creating label for each information # name using widget Label Label(master, text = "Air Quality : " , bg = "light grey" ).grid(row = 0 , sticky = W) Label(master, text = "O3 (μg/m3) :" , bg = "light grey" ).grid(row = 1 , sticky = W) Label(master, text = "NO2 (μg/m3) :" , bg = "light grey" ).grid(row = 2 , sticky = W) Label(master, text = "SO2 (μg/m3) :" , bg = "light grey" ).grid(row = 3 , sticky = W) Label(master, text = "PM2.5 (μg/m3) :" , bg = "light grey" ).grid(row = 4 , sticky = W) Label(master, text = "PM10 (μg/m3) :" , bg = "light grey" ).grid(row = 5 , sticky = W) Label(master, text = "CO (μg/m3) :" , bg = "light grey" ).grid(row = 6 , sticky = W) Label(master, text = "Remark :" , bg = "light grey" ).grid(row = 7 , sticky = W) Label(master, text = "Possible Health Impacts :" , bg = "light grey" ).grid(row = 8 , sticky = W) # Creating lebel for class variable # name using widget Entry Label(master, text = "", textvariable = ar, bg = "light grey" ).grid( row = 0 , column = 1 , sticky = W) Label(master, text = "", textvariable = o3, bg = "light grey" ).grid( row = 1 , column = 1 , sticky = W) Label(master, text = "", textvariable = no2, bg = "light grey" ).grid( row = 2 , column = 1 , sticky = W) Label(master, text = "", textvariable = so2, bg = "light grey" ).grid( row = 3 , column = 1 , sticky = W) Label(master, text = "", textvariable = pm, bg = "light grey" ).grid( row = 4 , column = 1 , sticky = W) Label(master, text = "", textvariable = pml, bg = "light grey" ).grid( row = 5 , column = 1 , sticky = W) Label(master, text = "", textvariable = co, bg = "light grey" ).grid( row = 6 , column = 1 , sticky = W) Label(master, text = "", textvariable = res_remark, bg = "light grey" ).grid(row = 7 , column = 1 , sticky = W) Label(master, text = "", textvariable = res_imp, bg = "light grey" ).grid(row = 8 , column = 1 , sticky = W) # creating a button using the widget b = Button(master, text = "Check" , command = airinfo, bg = "Blue" ) b.grid(row = 0 , column = 2 , columnspan = 2 , rowspan = 2 , padx = 5 , pady = 5 ,) mainloop() |
Output:
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.