Beautiful Soup is a popular Python library that makes web scraping by traversing the DOM (document object model) easier to implement.
The Selenium package is used to automate web browser interaction from Python. With Selenium, programming a Python script to automate a web browser is possible. Afterward, those pesky JavaScript links are no longer an issue.
Code:-
| from selenium import webdriver |
| from selenium.webdriver.common.keys import Keys |
| from bs4 import BeautifulSoup |
| import re |
| import pandas as pd |
| from tabulate import tabulate |
| import os |
| #launch url |
| url = “http://kanview.ks.gov/PayRates/PayRates_Agency.aspx” |
| # create a new Firefox session |
| driver = webdriver.Firefox() |
| driver.implicitly_wait(30) |
| driver.get(url) |
| #After opening the url above, Selenium clicks the specific agency link |
| python_button = driver.find_element_by_id(‘MainContent_uxLevel1_Agencies_uxAgencyBtn_33’) #FHSU |
| python_button.click() #click fhsu link |
| #Selenium hands the page source to Beautiful Soup |
| soup_level1=BeautifulSoup(driver.page_source, ‘lxml’) |
| datalist = [] #empty list |
| x = 0 #counter |
| #Beautiful Soup finds all Job Title links on the agency page and the loop begins |
| for link in soup_level1.find_all(‘a’, id=re.compile(“^MainContent_uxLevel2_JobTitles_uxJobTitleBtn_”)): |
| #Selenium visits each Job Title page |
| python_button = driver.find_element_by_id(‘MainContent_uxLevel2_JobTitles_uxJobTitleBtn_’ + str(x)) |
| python_button.click() #click link |
| #Selenium hands of the source of the specific job page to Beautiful Soup |
| soup_level2=BeautifulSoup(driver.page_source, ‘lxml’) |
| #Beautiful Soup grabs the HTML table on the page |
| table = soup_level2.find_all(‘table’)[0] |
| #Giving the HTML table to pandas to put in a dataframe object |
| df = pd.read_html(str(table),header=0) |
| #Store the dataframe in a list |
| datalist.append(df[0]) |
| #Ask Selenium to click the back button |
| driver.execute_script(“window.history.go(-1)”) |
| #increment the counter variable before starting the loop over |
| x += 1 |
| #end loop block |
| #loop has completed |
| #end the Selenium browser session |
| driver.quit() |
| #combine all pandas dataframes in the list into one big dataframe |
| result = pd.concat([pd.DataFrame(datalist[i]) for i in range(len(datalist))],ignore_index=True) |
| #convert the pandas dataframe to JSON |
| json_records = result.to_json(orient=‘records’) |
| #pretty print to CLI with tabulate |
| #converts to an ascii table |
| print(tabulate(result, headers=[“Employee Name”,“Job Title”,“Overtime Pay”,“Total Gross Pay”],tablefmt=‘psql’)) |
| #get current working directory |
| path = os.getcwd() |
| #open, write, and close the file |
| f = open(path + “\fhsu_payroll_data.json”,“w”) #FHSU |
| f.write(json_records) |
| f.close() |
