Python Beautifulsoup Selenium
Better web scraping in Python with Selenium, Beautiful Soup
by Dave GrayWeb ScrapingUsing the Python programming language, it is possible to “scrape” data from the web in a quick and efficient scraping is defined as:a tool for turning the unstructured data on the web into machine readable, structured data which is ready for analysis. (source)Web scraping is a valuable tool in the data scientist’s skill, what to scrape? “Search drill down options” == Keep clicking until you find what you licly Available DataThe KanView website supports “Transparency in Government”. That is also the slogan of the site. The site provides payroll data for the State of Kansas. And that’s great! Yet, like many government websites, it buries the data in drill-down links and tables. This often requires “best guess navigation” to find the specific data you are looking for. I wanted to use the public data provided for the universities within Kansas in a research project. Scraping the data with Python and saving it as JSON was what I needed to do to get Script links increase the complexityWeb scraping with Python often requires no more than the use of the Beautiful Soup module to reach the goal. Beautiful Soup is a popular Python library that makes web scraping by traversing the DOM (document object model) easier to ever, the KanView website uses JavaScript links. Therefore, examples using Python and Beautiful Soup will not work without some extra additions. to the rescueThe Selenium package is used to automate web browser interaction from Python. With Selenium, programming a Python script to automate a web browser is possible. Afterwards, those pesky JavaScript links are no longer an selenium import webdriver
from import Keys
from bs4 import BeautifulSoup
import re
import pandas as pd
import osSelenium will now start a browser session. For Selenium to work, it must access the browser driver. By default, it will look in the same directory as the Python script. Links to Chrome, Firefox, Edge, and Safari drivers available here. The example code below uses Firefox:#launch url
url = ”
# create a new Firefox session
driver = refox()
plicitly_wait(30)
(url)
python_button = nd_element_by_id(‘MainContent_uxLevel1_Agencies_uxAgencyBtn_33’) #FHSU
() #click fhsu linkThe () above is telling Selenium to click the JavaScript link on the page. After arriving at the Job Titles page, Selenium hands off the page source to Beautiful Soup. to Beautiful SoupBeautiful Soup remains the best way to traverse the DOM and scrape the data. After defining an empty list and a counter variable, it is time to ask Beautiful Soup to grab all the links on the page that match a regular expression:#Selenium hands the page source to Beautiful Soup
soup_level1=BeautifulSoup(ge_source, ‘lxml’)
datalist = [] #empty list
x = 0 #counter
for link in nd_all(‘a’, mpile(“^MainContent_uxLevel2_JobTitles_uxJobTitleBtn_”)):
##code to execute in for loop goes hereYou can see from the example above that Beautiful Soup will retrieve a JavaScript link for each job title at the state agency. Now in the code block of the for / in loop, Selenium will click each JavaScript link. Beautiful Soup will then retrieve the table from each page. #Beautiful Soup grabs all Job Title links
#Selenium visits each Job Title page
python_button = nd_element_by_id(‘MainContent_uxLevel2_JobTitles_uxJobTitleBtn_’ + str(x))
() #click link
#Selenium hands of the source of the specific job page to Beautiful Soup
soup_level2=BeautifulSoup(ge_source, ‘lxml’)
#Beautiful Soup grabs the HTML table on the page
table = nd_all(‘table’)[0]
#Giving the HTML table to pandas to put in a dataframe object
df = ad_html(str(table), header=0)
#Store the dataframe in a list
(df[0])
#Ask Selenium to click the back button
driver. execute_script(“(-1)”)
#increment the counter variable before starting the loop over
x += 1 Python Data Analysis LibraryBeautiful Soup passes the findings to pandas. Pandas uses its read_html function to read the HTML table data into a dataframe. The dataframe is appended to the previously defined empty the code block of the loop is complete, Selenium needs to click the back button in the browser. This is so the next link in the loop will be available to click on the job listing the for / in loop has completed, Selenium has visited every job title link. Beautiful Soup has retrieved the table from each page. Pandas has stored the data from each table in a dataframe. Each dataframe is an item in the datalist. The individual table dataframes must now merge into one large dataframe. The data will then be converted to JSON format with _json:#loop has completed
#end the Selenium browser session
()
#combine all pandas dataframes in the list into one big dataframe
result = ([Frame(datalist[i]) for i in range(len(datalist))], ignore_index=True)
#convert the pandas dataframe to JSON
json_records = _json(orient=’records’)Now Python creates the JSON data file. It is ready for use! #get current working directory
path = ()
#open, write, and close the file
f = open(path + “\”, “w”) #FHSU
(json_records)
()The automated process is fastThe automated web scraping process described above completes quickly. Selenium opens a browser window you can see working. This allows me to show you a screen capture video of how fast the process is. You see how fast the script follows a link, grabs the data, goes back, and clicks the next link. It makes retrieving the data from hundreds of links a matter of single-digit full Python codeHere is the full Python code. I have included an import for tabulate. It requires an extra line of code that will use tabulate to pretty print the data to your command line interface:from selenium import webdriver
from tabulate import tabulate
import os
#launch url
#After opening the url above, Selenium clicks the specific agency link
() #click fhsu link
#Selenium hands the page source to Beautiful Soup
#Beautiful Soup finds all Job Title links on the agency page and the loop begins
x += 1
#end loop block
#loop has completed
json_records = _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
()Photo by Artem Sapegin on UnsplashConclusionWeb scraping with Python and Beautiful Soup is an excellent tool to have within your skillset. Use web scraping when the data you need to work with is available to the public, but not necessarily conveniently available. When JavaScript provides or “hides” content, browser automation with Selenium will insure your code “sees” what you (as a user) should see. And finally, when you are scraping tables full of data, pandas is the Python data analysis library that will handle it ference:The following article was a helpful reference for this project: out to me any time on LinkedIn or Twitter. And if you liked this article, give it a few claps. I will sincerely appreciate it. Gray (@yesdavidgray) | TwitterThe latest Tweets from Dave Gray (@yesdavidgray). Instructor @FHSUInformatics * Developer * Musician * Entrepreneur *…
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In 10 minutes: Web Scraping with Beautiful Soup and …
Definitive Guide to AnalyticsExtract Critical Information from Wikipedia and eCommerce Quickly with BS4 and SeleniumWebScraping — Free ImageWeb Scraping is a process to extract valuable information from websites and online contents. It is a free method to extract information and receive datasets for further analysis. In this era where information is practically highly related to each other, I believe that the need for Web Scraping to extract alternative data is enormous especially for me as a data objective for this publication is for you to understand several ways on scraping any publicly available information using quick and dirty Python Code. Just spend 10 minutes to read this article — or even better, contribute. Then you could get a quick glimpse to code your first Web Scraping this article, we are going to learn how to scrape data from Wikipedia and e-commerce (Lazada). We will clean up, process, and save the data into file. We will use Beautiful Soup and Selenium as our main Web Scraping autiful SoupBeautiful Soup parses HTML into an easy machine readable tree format to extract DOM Elements quickly. It allows extraction of a certain paragraph and table elements with certain HTML ID/Class/rsing of DOM elements compared to Tree Dir FolderWhenever I need a quick and dirty way approach to extract information online. I will always use BS as my first approach. Usually it would take me in less than 10 minutes within 15 lines of codes to leniumSelenium is a tool designed to automate Web Browser. It is commonly used by Quality Assurance (QA) engineers to automate their testings Selenium Browser ditionally, it is very useful to web scrape because of these automation capabilities:Clicking specific form buttonsInputting information in text fieldsExtracting the DOM elements for browser HTML code(Github is available at the end of this article)Problem StatementImagine you were UN ambassadors, aiming to make visits on cities all around the world to discuss about the Kyoto Protocol status on Climate Changes. You need to plan your travel, but you do not know the capital city for each of the country. Therefore, you googled and found this link on this link, there is a table which maps each country to the capital city. You find this is good, but you do not stop there. As a data scientist and UN ambassador, you want to extract the table from Wikipedia and dump it into your data application. You took up the challenge to write some scripts with Python and epsWe will leverage on the following steps:Pip install beautifulsoup4 and pip install requests. Requests would get the HTML element from URL, this will become the input for BS to which DOM element the table is referring to. Right click on your mouse and click on inspect element. Shortcut is CTRL+I (inspect) for Chrome on the inspect button at the top left corner to highlight the elements you want to extract. Now you know that the element is a table element in the HTML tional Capitals Elements Wikipedia4. Add header and url into your requests. This will create a request into the wikipedia link. The header would be useful to spoof your request so that it looks like it comes from a legitimate Wikipedia, it might not matter as all the information is open sourced and publicly available. But for some other sites such as Financial Trading Site (SGX), it might block the requests which do not have legitimate headers. headers = {‘User-Agent’: ‘Mozilla/5. 0 (Windows NT 6. 3; Win64; x64) AppleWebKit/537. 36 (KHTML, like Gecko) Chrome/54. 0. 2840. 71 Safari/537. 36’}url = “r = (url, headers=headers)itiate BS and list element to extract all the rows in the tablesoup = BeautifulSoup(ntent, “”)table = nd_all(‘table’)[1]rows = nd_all(‘tr’)row_list = list()6. Iterate through all of the rows in table and get through each of the cell to append it into rows and row_listfor tr in rows: td = nd_all(‘td’) row = [ for i in td] (row)7. Create Pandas Dataframe and export data into csv. df_bs = Frame(row_list, columns=[‘City’, ‘Country’, ‘Notes’])t_index(‘Country’, inplace=True)_csv(”)Result of web scraping in csvCongratulations! You have become a web scraper professional in only 7 steps and within 15 lines of codeThe Limitations of Beautiful SoupSo far BS has been really successful to web scrape for us. But I discovered there are some limitations depending on the problems:The requests takes the html response prematurely without waiting for async calls from Javascript to render the browser. This means it does not get the most recent DOM elements that is generated by Javascript async calls (AJAX, etc) retailers, such as Amazon or Lazada put anti-bot software throughout the websites which might stop your crawler. These retailers will shut down any requests from Beautiful Soup as it knows that it does not come from legitimate we run Beautiful Soup in e commerce websites such as Lazada and Amazon, we will run to this Connection Error which is caused by their anti scraping software to deter bots from making TPSConnectionPool(host=’’, port=443): Max retries exceeded with url: / (Caused by SSLError(SSLError(1, ‘[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed (_ssl. c:833)’), ))One way to fix it is to use client browsers and automate our browsing behavior. We can achieve this by using hail Selenium!! Problem StatementImagine you were creating price fluctuation model to analyze e-Commerce providers such as Lazada and Amazon. Without Web Scraping tool, you would need to hire somebody to manually browse through numerous product pages and copy paste the pricing one by one into Excelsheet. This process would be very repetitive, especially if you’d like to collect the data point every day/every hour. This would also be a very time consuming process as it involves many manual clicks and browses to duplicate the if I tell you, you can automate this process:By having Selenium doing the exploration of products and clicking for having Selenium opening your Google Chrome Browser to mimic legitimate user browsing having Selenium pump all of the information into lists and csv files for you’re in luck, because all you need to do is write a simple Selenium script and you can now run the web scraping program while having a good night sleep. Extracting Lazada Information and Products are time consuming and repetitiveSetting UpPip install stall the Selenium Browser. Please refer to this link to identify your favorite browser (Chrome, Firefox, IE, etc). Put that in the same directory as your project. Feel free to download it from my Github link below if you are not sure which one to clude these importfrom selenium import webdriverfrom import Byfrom import WebDriverWaitfrom pport import expected_conditions as ECfrom import TimeoutException4. Drive Selenium Chrome Browser by inserting the executable path and url. In my case, I used the relative path to find the located in the same directory as my = (executable_path=’chromedriver’)(‘#’)Selenium Running Chrome and Extract Lazada and Redmart page to load and find the element. This is how Selenium could be different from Requests and BS. You could instruct the page to wait until a certain DOM element is renderred. After that, it would continue running its web scraping can stop the wait until Expected Conditions (EC) is met to find by ID “Level_1_Category_No1”. If 30 seconds already passed without finding such element, then pass TimeoutException to shut the browser. timeout = 30try: WebDriverWait(driver, timeout)(sibility_of_element_located((, “Level_1_Category_No1″)))except TimeoutException: ()Congrats. We have setup Selenium to use our Chrome Browser. Now we are ready to automate the Information formation ExtractionLet us identify several attributes from our Lazada Websites and extract their DOM Elements. Extracting the DOM Elements via ID, Class, and XPATH Attributesfind_element by ID to return the relevant category tegory_element = nd_element(, ‘Level_1_Category_No1’);#result — Electronic Devices as the first category listing2. Get the unordered list xpath (ul) and extract the values for each list item (li). You could inspect the element, right click, and select copy>XPATH to easily generate the relevant XPATH. Feel free to open the following link for further st_category_elements = nd_element(, ‘//*[@id=”J_icms-5000498-1511516689962”]/div/ul’)links = nd_elements(ASS_NAME, “lzd-site-menu-root-item”)for i in range(len(links)): print(“element in list “, links[i])#result {Electronic Devices, Electronic Accessories, etc}Clicks and ActionsAutomate Actions. Supposedly you want to browse to Redmart from Lazada Homepage, you can mimic the click in the ActionChains Object. element = nd_elements_by_class_name(‘J_ChannelsLink’)[1]tionChains(driver). move_to_element(element)(element). perform()Extracting all product listings from RedmartCreate lists of product title. We can extract and print them as followingproduct_titles = nd_elements_by_class_name(‘title’)for title in product_titles: print()2. Extract the product title, pack size, price, and rating. We will open several lists to contain every item and dump them into a oduct_containers = nd_elements_by_class_name(‘product_container’)for container in product_containers: (nd_element_by_class_name(‘title’))(nd_element_by_class_name(‘pack_size’)) (nd_element_by_class_name(‘product_price’))(nd_element_by_class_name(‘ratings_count’))data = {‘product_title’: product_titles, ‘pack_size’: pack_sizes, ‘product_price’: product_prices, ‘rating_count’: rating_counts}3. Dump the information into a Pandas Dataframe and csvdf_product = om_dict(data)_csv(”)CSV Dump for each of the product in Best Seller RedmartCongrats! You have effectively expanded your skills to extract any information found online! The purpose for this Proof Of Concepts (POC) was created as a part of my own side project. The goal of this application is to use web scraping tool to extract any publicly available information without much cost and this POC, I used Python as the scripting language, Beautiful Soup and Selenium library to extract the necessary Github Python Code is located free to clone the repository and contribute whenever you have lieu with today’s topics about python and web scraping. You could also visit another of my publication regarding web scraping for aspiring investors. You should try this walk through to guide you to code quick and dirty Python to scrape, analyze, and visualize stocks. Hopefully from this relevant publication, you could learn how to scrape critical information and develop an useful application. Please read and reach out to me if you like nally…Whew… That’s it, about my idea which I formulated into writings. I really hope this has been a great read for you guys. With that, I hope my idea could be a source of inspiration for you to develop and Comment out below to suggest and coding:)Vincent Tatan is a Data and Technology enthusiast with relevant working experiences from Visa Inc. and Lazada to implement microservice architectures, data engineering, and analytics pipeline ncent is a native Indonesian with a record of accomplishments in problem solving with strengths in Full Stack Development, Data Analytics, and Strategic has been actively consulting SMU BI & Analytics Club, guiding aspiring data scientists and engineers from various backgrounds, and opening up his expertise for businesses to develop their products reach out to Vincent via LinkedIn, Medium or Youtube ChannelDisclaimerThis disclaimer informs readers that the views, thoughts, and opinions expressed in the text belong solely to the author, and not necessarily to the author’s employer, organization, committee or other group or individual. References are picked up from the list and any similarities with other works are purely coincidentalThis article was made purely as the author’s side project and in no way driven by any other hidden agenda.
Web Scraping using Beautiful Soup and Selenium for dynamic …
Web scraping can be defined as:“the construction of an agent to download, parse, and organize data from the web in an automated manner. ”Or in other words: instead of a human end-user clicking away in their web browser and copy-pasting interesting parts into, say, a spreadsheet, web scraping offloads this task to a computer program which can execute it much faster, and more correctly, than a human scraping is very much essential in data science has the most elaborate and supportive ecosystem when it comes to web scraping. While many languages have libraries to help with web scraping, Python’s libraries have the most advanced tools and python libraries for web scraping:Beautiful SoupScrapyRequestsLXMLSeleniumIn this guide, we will be using Beautiful Soup and Selenium to scrap one of the review pages of Trip scraping with Python often requires no more than the use of the Beautiful Soup to reach the goal. Beautiful Soup is a very powerful library that makes web scraping by traversing the DOM (document object model) easier to implement. But it does only static scraping. Static scraping ignores JavaScript. It fetches web pages from the server without the help of a browser. You get exactly what you see in “view page source”, and then you slice and dice it. If the data you are looking for is available in “view page source” only, you don’t need to go any further. But if you need data that are present in components which get rendered on clicking JavaScript links, dynamic scraping comes to the rescue. The combination of Beautiful Soup and Selenium will do the job of dynamic scraping. Selenium automates web browser interaction from python. Hence the data rendered by JavaScript links can be made available by automating the button clicks with Selenium and then can be extracted by Beautiful stallationpip install bs4 seleniumFirst, we will use Selenium to automate the button clicks required for rendering hidden but useful data. In review page of Trip Advisor, the longer reviews are partially available in the final DOM. They become fully available only on clicking “More” button. So, we will automate the clicking of all “More” buttons with Selenium to work, it must access the browser, Selenium accesses the Chrome browser driver in incognito mode and without actually opening a browser window(headless argument) Trip Advisor review page and click relevant buttonsHere, Selenium web driver traverses through the DOM of Trip Advisor review page and finds all “More” buttons. Then it iterates through all “More” buttons and automates their clicking. On the automated clicking of “More” buttons, the reviews which were partially available before becomes fully this, Selenium hands off the manipulated page source to Beautiful page source received from Selenium now contains full, Beautiful Soup loads the page source. It extracts the reviews texts by iterating through all review divs. The logic in the above code is for the review page of Trip Advisor. It can vary according to the HTML structure of the page. For future use, you can write the extracted reviews to a file. I scraped one page of Trip Advisor reviews, extracted the reviews and wrote them to a llowing are the reviews I have extracted from one of the Trip Advisor of an airline. You act like you have such low fares, then turn around and charge people for EVERYTHING you could possibly think of. $65 for carry on, a joke. No seating assignments without an upcharge for newlyweds, a joke. Charge a veteran for a carry on, a f***ing joke. Personally, I will never fly spirit again, and I’ll gladly tell everyone I know the kind of company this airline is. No room, no amenities, nothing. A bunch of penny pinchers, who could give two sh**s about the customers. Take my flight miles and shove them, I won’t be using them with this pathetic a** airline first travel experience with NK. Checked in on the mobile app and printed the boarding pass at the airport kiosk. My fare was $30. 29 for a confirmed ticket. I declined all the extras as I would when renting a car. No, no, no and no. My small backpack passed the free item test as a personal item. I was a bit thirsty so I purchased a cold bottle of water in flight for $3. 00 but I brought my own snacks. The plane pushed off the gate in Las Vegas on time and arrived in Dallas early. Overall an excellent flight. Original flight was at 3:53pm and now the most recent time in 9:28pm. Have waisted an entire day on the airport. Worst airline. I have had the same thing happen in the past were it feels like the are trying to combine two flights to make more money. If I would have know it would have taken this long I would have booked a different airline without a a bad weather flight great. Bumpy weather but they got the beverage and snack service done in styleFlew Spirit January 23rd and January 26th (flights 1672 from MCO to CMH and 1673 CMH to MCO). IF you plan accordingly you will have a good flight. We made sure our bag was correct, and checked in online. I do think the fees are ridiculous and aren’t needed. $10 to check in at the terminal? Really.. That’s dumb in my opinion. Frontier does not do that, and they are a no frill airline (pay for extras). I will say the crew members were very nice, and there was decent leg room. We had the Airbus A320. Not sure if I’d fly again because I prefer Frontier Airlines, but Spirit wasn’t bad for a quick flight. If you get the right price on it, I would recommend it… just prepare accordingly, and get your bags early. Print your boarding pass at home! worst flight i have ever been on. the rear cabin flight attendents were the worst i have sever seen. rude, no help. the seats are the most cramped i have every seen. i looked up the seat pitch is the smallest in the airline industry. 28″ delta and most other arilines are 32″ plus. maybe ok for a short hop but not for a 3 or 4 hour flight no free water or anything. a manwas trying to get settle in with his kids and asked the male flight attendent for some help with luggage in the overhead andthe male flight attendent just said put your bags in the bin and offered no assitance. my son got up and help the manget the kidscarryons put awayI was told incorrect information by the flight counter representative which costed me over $450 i did not have. I spoke with numerous customer service reps who were all very rude and unhelpful. It is not fair for the customer to have to pay the price for being told incorrect got a great price on this flight. Unfortunately, we were going on a cruise and had to take luggage. By the time we added our luggage and seats the price more than crew. Very friendly and happy–from the tag your bag kiosk to the ticket desk to the flight crew–everyone was exceptionally happy to help and friendly. We find this to be true of the many Spirit flights we’ve impressed with the Spirit check-in staff at either airport. Very rude and just not inviting. The seats were very comfortable and roomy on my first flight in the exit row. On the way back there was very little cushion and narrow seats. The flight attendants and pilots were respectful, direct, and welcoming. Overall would fly Spirit again, but please improve airport staff at autiful Soup is a very powerful tool for web scraping. But when JavaScript kicks in and hides content, Selenium with Beautiful Soup does the job of web scraping. Selenium can also be used to navigate to the next page. You can also use Scrapy or some other scraping tools instead of Beautiful Soup for web scraping. And finally after collecting the data, you can feed the data for data science work.
Frequently Asked Questions about python beautifulsoup selenium
Can I use Beautiful Soup with Selenium?
Dynamic Scraping With Selenium WebDriver In this case, if you attempt to parse the data using Beautiful Soup, your parser won’t find any data. The information first must be rendered by JavaScript. In this type of application, you can use Selenium to get prices for cards.Feb 18, 2021
What is Selenium Beautiful Soup?
When used together, Selenium and Beautiful Soup are powerful tools that allow the user to web scrape data efficiently and quickly.Mar 14, 2021
Is Selenium better than Beautiful Soup?
Comparing selenium vs BeautifulSoup allows you to see that BeautifulSoup is more user-friendly and allows you to learn faster and begin web scraping smaller tasks easier. Selenium on the other hand is important when the target website has a lot of java elements in its code.Feb 10, 2021
