Trending December 2023 # Do You Need Proxies For Web Scraping? # Suggested January 2024 # Top 19 Popular

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Data lies at the heart of every successful business. You need relevant competitor data to outperform your direct competitors. You need customer data to understand your target market’s needs and desires. Job market data helps you improve recruitment processes, and pricing data enables you to keep your products and services affordable to your audiences while maximizing your profits.

At first, glance, collecting relevant data seems easy enough – all you have to do is Google the information you need, and you’ll find thousands of results. However, when you need larger volumes of data, such a manual approach will not cut it. You’ll need to automate this process with web scraping bots, and you’ll need to use a proxy service to do it right.

Learn why proxies are critical to your web scraping efforts and how they can help you make the most of the data you have available.

About Web Scraping

First thing’s first, you need to understand what web scraping is. Put plainly, it’s the process of gathering and later analyzing data that’s freely available on one of the millions of websites that are currently online. It’s valuable for lead generation, competitor research, price comparison, marketing, and target market research.

Even manual data extraction, such as searching for product pricing information yourself and exporting it to your Excel file, counts as a type of web scraping. However, web scraping is more commonly automated since manual data extraction is slow and prone to human error.

Web scraping automation involves scraper bots that crawl dozens of websites simultaneously, loading their HTML codes, and extracting the relevant information. The bots then present the data in a readable form that’s easy to understand and analyze when needed.

Depending on your needs, you have access to several different types of web scrapers:

Browser Extensions

Like any other type of browser extension, such as an ad block, web scraper browser plug-ins simply need to be installed on your browser of choice. They’re affordable, easy to use, and effective for smaller data volumes.

Installable Software

Installable scrapers are much more powerful. Installed directly on your device, they can go through larger quantities of data without a hitch. The only problem is that they tend to be somewhat slower.

Cloud-Based Solutions

The best of the bunch is cloud-based scrapers. Built for significant data volumes, they are fast, reliable, and more expensive than the rest. They can extract data into any format type you prefer and completely automate every aspect of scraping.

You can also build your own scraping bots from scratch if you have the required skills.

Challenges of Web Scraping

Although web scraping seems like a cut-and-dried process, it’s rarely so. You’ll come across numerous challenges when you first get into it, some of the greatest ones being:

Prevented Bot Access

Few sites will willingly allow bot access as it can cause many problems. Bots create unwanted traffic, which can overwhelm servers and even cause analytics issues to the site in question. Not to mention that there are numerous malicious bots designed to cause Distributed Denial of Service (DDoS) attacks, steal information, and more. Therefore, if a site identifies your web scrapers as bots, your access will immediately be prevented.

IP Blocks

Geo-Restrictions

Proxies as A Solution

If you want to go around the aforementioned web scraping challenges, you need a dependable proxy service, such as Oxylabs. Proxies are the middle-men between your device and the internet, forwarding all information requests from you to the site you’re trying to scrape and back.

Depending on the proxy server you choose, you can receive multiple fake IP addresses that help hide your actual location and allow you to scrape data seamlessly.

How They Can Help

By hiding your IP address and giving you a new, fake one, proxies can help you overcome the main challenges of web scraping:

Make as Many Information Requests as Needed

Your proxy can provide you with changing IP addresses, allowing you to present yourself as a unique site visitor every time you make an information request. The site will have a more challenging time identifying whether you’re using bots or not.

Go Around IP Blocks

another IP address, allowing you to continue scraping without issues.

Bypass Geo-Restrictions

Conclusion

You're reading Do You Need Proxies For Web Scraping?

A Tool For Investor – The Art Of Web Scraping

This article was published as a part of the Data Science Blogathon

if you want to know this, then you are in the right place….

I the industries, then one has to research about a particular industry, then google about the different companies after that, using NSE or BSE website analyze the stock by going to different tabs & links.

Imagine having the power to speed up this process by analyzing BSE/NSE website in a few seconds. I am sure now you surely have thought of it, so let me help you with it.

online source.

WHAT IS WEB SCRAPING?

Web scratching is an important method since it licenses quickly and is capable of extracting online data. Such data would then have the option to be taken care of to assemble bits of knowledge as required. In this manner, it furthermore makes it possible to screen the brand and reputation of an association.

How To Perform Web Scraping?

After understanding web-scraping, the most common question is – How do I learn web scraping?

The process of web-scraping is really simple. To extract data using web scraping with python, you need to follow these basic steps:

1. Find the URL that you want to scrape.

2. Inspecting the Page.

3. Find the data you want to extract.

4. Write the code.

5. Run the code and extract the data.

6. Store the data in the desired format

All the steps mentioned above as shown below by performing actual web-scraping that will help in investing.

Let’s begin with the Art of Web Scraping

With the help of web scraping one can understand – when people are scared and in which stock one can invest and earn more even in the bearish market.

For performing the above-mentioned process of extracting data from the web i.e., web scraping, first we need to install some necessary libraries like:

· Pandas

· Bs4

· BeautifulSoup

· Webdriver_manager.chrome

· ChromeDriveManager

The code for importing the same is:

import pandas as pd from bs4 import BeautifulSoup from selenium import webdriver from webdriver_manager.chrome import ChromeDriverManager driver = webdriver.Chrome(ChromeDriverManager().install()) html=driver.page_source soup = BeautifulSoup(html,'html.parser')

Now, let’s check whether we are on the correct website or not…..

For checking, we will be using Beautiful Soup Library

The code for the same is:

print("Title of the website is : ") for title in soup.find_all('title'): print(title.get_text()) OUTPUT: Title of the website is :

Now, we have to open the NSE site on the other tab, let’s look at it for a second and try to observe different tags. To look for the tag names that are used in the actual website one needs to open inspect element.

What is Inspect Element?

Inspect element is one of the designer devices consolidated into Google Chrome, Firefox, Safari, and Internet Explorer internet browsers. By getting this instrument, one can really see — and even alter — the HTML and CSS source code behind the web content.

Inspect Element is a source that helps in viewing the source code of the website. There are two ways to open inspect element:

2. Use shortcut key – Ctrl + Shift + I

Source – It is a screenshot from my Laptop

After opening Inspect Element, search for the market/Index for which you want to extract data. Generally, all these types of information are known as a class and all classes are at the ‘P’ tag. Hence to extract information that is on the ‘P’ tag we will use the code:

para=soup.select('p') para

OUTPUT:

Now, it can be observed that we got all the information about different markets with dates + timings but this is not very readable/understandable. To make it easy to understand we will use code:

para = soup.findAll('p') for p in para: print(p.get_text())

OUTPUT:

Finally, we can now read it and understand it.

Now, let’s deep-dive into the same and now let us search for Index – I will choose NIFTY index, you can choose according to your own desire.

To get the NIFTY Index information we will use the code:

Nifty = soup.findAll('p', {'class':'tb_name'}) for name in Nifty: print(name.get_text())

OUTPUT:

NIFTY 50 NIFTY NEXT 50 NIFTY MIDCAP 50 NIFTY BANK NIFTY FINANCIAL SERVICES

Now let’s find out the value of each NIFTY Index for the same, we’ll use code:

Nifty = soup.findAll('p', {'class':'tb_name'}) value = soup.findAll('p', {'class':'tb_val'}) for Nifty_name in Nifty: print(Nifty_name.get_text()) for Nifty_value in value: print(Nifty_value.get_text())

OUTPUT:

NIFTY 50 NIFTY NEXT 50 NIFTY MIDCAP 50 NIFTY BANK NIFTY FINANCIAL SERVICES 17,802.00 42,443.10 8,606.30 39,400.55 18,829.70

Therefore, we got all the information we need to understand today’s Index for options trading.

In this article, we extracted a few pieces of information, but you can use the same technique to extract more data.

Another example for web scraping can be:

Let’s use the “DIV” tag now,

For this let’s use the code:

div=soup.find_all("div") div

OUTPUT:

(The output for this is also not readable and understandable)

Let’s make it easy to understand

For this we’ll use the code:

t = soup.body for T in t.find_all('div'): print(T.text)

OUTPUT:

Now, It can be observed that everything is readable and easy to understand…..

ABOUT THE AUTHOR

A 3rd-year (5th Semester) Student at CHRIST University, Lavasa, Pune Campus. Currently Pursuing BBA (BUSINESS ANALYTICS).

Website – chúng tôi (CHECK THIS OUT)

Contacts:

If you want to keep updated with my latest articles and projects, .

Connect with me via:

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Do You Need An Antivirus For Windows 10/11?

Do you need an antivirus for Windows 10/11? [We Answer]

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If you’re wondering if need an antivirus for Windows 10, then join our discussion here.

Windows Defender is considered by many as the Windows 10 antivirus.

The evolutions of antiviruses and online threats prove Defender is not enough.

ESET has created a perfect candidate for the best antivirus for Windows 10, and you should give it a try too.

The term antivirus has become so ingrained in tech culture, that almost everyone is familiar with its meaning. Chances are you have a PC running Windows 10, and you’re wondering if you still need one.

Do you need antivirus for Windows 10?

1. Microsoft itself ships Windows 10 with a built-in antivirus

The most obvious reason why antivirus software is still a necessity for most users is Windows Defender.

Yes, even Microsoft – the company behind the Windows operating system that currently runs on over 1.5 billion PC – began integrating a basic antivirus solution with the release of Windows Vista in 2006.

Years later, things haven’t changed all that much, except for the explosion of security threats.

Today we have hundreds of millions of new PCs shipping every year with Windows Defender as an integral part of Windows 10, which comes pre-installed on many of these devices.

It provides a basic layer of security until you install your own choice of antivirus.

However, this isn’t ideal for everyone since the built-in security Windows security tool actually performs basic tasks when compared to other premium antiviruses.

For this reason, you should choose a professional antivirus that will keep your operating system virus-free.

Use a third-party antivirus

To be sure your computer’s operating system is free of errors, viruses and that your sensitive data will not be obtained by unauthorized sources, you must take a little bit further. Windows Defender cannot handle all of these issues alone,, which means you have to use a professional software.

If you need a fast and light software to keep your computer healthy, safe and optimized, then ESET NOD32 is just what you need.

This performant antivirus is the perfect tool for gamers as well as average users wishing to have uninterrupted sessions of work or gaming at their computers. It is compatible with Windows, Mac, and Linux operating systems.

ESET has created NOD32 to run without requiring a lot from your computer resources. This means you can play, watch movies or work at your computer while this antivirus is active without experiencing any slowdowns.

Once ESET NOD32 has been downloaded and installed, let it scan and he will do what he knows best: to clean your computer of viruses, worms, ransomware, spyware, and all types of malware.

ESET NOD32

ESET NOD32 is your computer’s best ally as it will detect and remove any virus, malware, worms, ransomware and spyware.

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2. An antivirus can be used for easy setup of security rules

If you’re running the latest version of Windows 10, you can use the new Windows Defender Security Center to do more than just scanning for viruses.

Additional features include Device performance & health, Firewall and network protection, App and browser control, and Family options.

The Windows Defender Security Center can provide you with additional tools, which is pretty good for a free tool, but still not enough when it comes to traditional, paid third-party solutions.

There’s a good reason why some antivirus vendors have changed the branding of their products to reflect how paid tiers of their products provide you with more than a simple virus scanner tool.

Some even offer mail spam protection, web browsing privacy protection, or use your mobile device as a strengthening tool for your PC’s security.

3. Antiviruses have evolved to match new security threats

Expert tip:

Microsoft has been improving the security of Windows with each new release, rendering many of the classic viruses obsolete. In turn, the bad guys have devised new ways to attack and take over control of your PC.

One notable example is ransomware, which steals your data and makes it technically impossible to access unless you pay the thieves in a way that makes it very unlikely to ever identify them.

In the meantime, antivirus software has evolved to deal with such threats. It can now provide special protection for your important folders, prevent malware from starting with Windows, and set up a trusted application whitelist.

Some antiviruses even prevent an attacker from modifying their settings or uninstalling by locking things under a user password.

4. Your web browser is not as secure as you think

Chances are you spend the most time using a web browser, and this is also one of the main targets for the bad guys. As much as Google, Microsoft, and others like to tout how safe their browser is, the reality is that all of them have flaws.

That leaves you vulnerable until you get an update, which can take some time depending on the complexity of fixing the flaw.

Some attacks involve redirects that take you from a legitimate service to an infected or masquerading web page.

As you’re trying to log in, you basically give away your credentials to the bad guys. Good antiviruses typically analyze the web page code and will warn you if it’s malicious.

5. The antivirus as an additional layer of security

But I’m careful what I do with my PC and on the web is what some users may say. But you can never be too careful about security, and good practices are not enough to keep your PC safe. Thinking proactively about security will lower the risk of data and financial theft, or identity fraud.

As medics say: prevention is better than the cure. Here are some of the situations where an antivirus can provide some precious additional security:

Some of you may even think that antiviruses can catch malware only after the fact. In reality, the best security solutions today analyze the behavior of any app you run.

This increases the chances of discovering a security threat before it even has a chance to do any harm.

What about Windows 10 S?

Microsoft says that Windows 10 S is more secure because it only runs sandboxed apps from the Microsoft Store. That’s true to some extent, but it’s not the whole story.

You’re only less likely to get spyware and adware from the Store – which is curated by Microsoft.

You’ll only be able to use Microsoft’s Edge browser in Windows 10 S, which is still vulnerable to attacks. Your important files still need protection from ransomware.

Even sandboxed apps from the Store are not the holy grail of security. On top of that, the default account on Windows 10 S is still is vulnerable to attacks.

The takeaway is this: an antivirus is still as important as being careful and keeping your software up to date. Also, there’s no need to spend a fortune on an antivirus.

Companies like Bullguard or Bitdefender offer more affordable tiers that fit your specific needs. What do you use as a security solution?

Protect your PC now!ESET Antivirus comes with all the security tools that you may ever need to protect your data and privacy, including:

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Why Do You Need Mentorship For Day Trading In Stock Market?

In childhood, we learn everything with the help of elders, parents constantly guide us and provide assistance. We hear numerous words of support and enthusiasm, and we feel that there is always a person nearby who makes sure that we feel good. In adulthood, such relationships are established much more difficult. Wouldn’t it be nice to have someone who would support us in life and help us achieve success in all our endeavors?

Related: – Is It Time We Should Start Worrying About the Stock Market?

The Role of a Mentor in Day Trading

Why is it so difficult for those who want to become a day trader to achieve stable profits? You got all the necessary knowledge, but for some reason, you can’t connect it with practice in order to earn money. Why is that? A lot of novice day traders ask this question. And the answer, in fact, is very simple.

A common mistake is that they believe that they are able to independently come up with rules and develop strategies. As a result, they lose not only time but also most (if not all) of the money in their trading account, trying to reinvent the wheel. Almost everyone goes through it.

There are many websites on the Internet where they will provide you stock market tips regarding how to trade stocks, currencies and the crypto-currency market. But the real secret is that you need to find not only the right training for day trading in the stock markets but also the right mentor. Building a solid base on which to base your trade is paramount for survival in this industry. A mentor will help you to create it. His task is to properly educate a trader in trading in today’s market and help him build that solid foundation, which, in the end, will allow him to make a stable income. Simply put, he will help to combine theory with practice.

If you analyze, almost all successful day traders have one thing in common – the presence of a mentor. History shows that almost every successful person had someone whom he could trust in difficult times and who he could learn from. To be successful in life, it is very important to have a mentor, coach or just a more experienced friend. This should be a person who was previously in your situation, and now occupies the position in life that you aspire to. Most people do not understand the value of a mentor, and this is one of the main reasons for the failure of any undertaking, especially when it comes to day trading. The mentor gives a valuable understanding of those things that can be learned only with experience, as well as a lot of useful related nuances. The mentor will help you select stocks, listen carefully and push in the right direction.

Training with a good mentor or trainer is one of the best investments you can make in your success in the long run. Taking golf lessons or working with a coach, you invest in yourself. So why not invest in your financial future by finding someone who will help you use your existing knowledge and connect them with practical skills, which will allow you to earn in the stock market for many years? Most people are unable to provide for themselves through trade because they cannot apply their knowledge and skills as required by the rules of this game. Why doom yourself to failure? Working with a mentor is designed to transfer knowledge from an experienced day trader to someone who is only at the beginning of this journey. You should see how he interprets market movements and how he plays this game.

Related: – The Stock Market is Still All Over the Place: Report

Types of Mentoring

Mentoring can be carried out in two forms: individual training in trade and employment in small groups. It is obvious that private stock market tips are more expensive. But a good mentor is able to adapt them to your specific skills, problems, and goals. On the other hand, classes in a small group allow for joint work and discussion, which can not only serve as an incentive but also reveal to you other day trading methods that, under other circumstances, would remain unknown to you. The most important thing when choosing a mentor for day trading is to understand whether he will be able to teach you what you will be comfortable working with, and not just what he wants to present to you. Poor mentors usually have a very limited set of tricks and just try to make money on gullible amateur traders.

How to Find a Legitimate Day Trading Mento

Mentors can be very different. Some will be with you daily, while others will offer services at a distance and will be available if necessary, but in other situations, you will be left to your own devices. Many will let you decide how to approach mentoring programs.

There are two ways to consider such programs. On the one hand, someday traders are looking for mentors who earn mainly on training. On the other hand, some traders are looking for mentors who earn their living solely by training. They believe that such traders know options and can train instead of earning them a living. Such mentors may be able to earn money by day trading for a living, but it is mentoring that may be their most basic gift.

Among the mentoring programs, there are also fraudulent, as well as fraudulent trading systems for selling signals and alerts, and brokers are not worth mentioning. This does not mean that most training programs are fraudulent, or simply a waste of money. The sad thing is that many traders create such programs, while they can’t even make a living by day trading, they blame the mentors for this instead of blaming themselves (namely they are to blame). And that is what makes it difficult to determine if mentorship is legitimate or not.

Related: – What is Day Trading System? How it Works? The Good and Bad of a Trading Systems

Conclusion

A mentor who knows you well will help you make full use of your strengths and overcome difficult career stages. The mentor whom you admire trading will serve as a source of inspiration for you. Thanks to the help of a good mentor, your day trading will be more effective and consistent with the goals that you set for yourself. Working with a mentor is not just a good idea, but a proven concept.

Jay Potter

Hi, This is Jay potter from Day Trader Architects. I love to write content about trends, tech, finance, and other categories. I have been writing for the past four years

Beginner’s Guide To Web Scraping In Python Using Beautifulsoup

Overview

Learn web scraping in Python using the BeautifulSoup library

Web Scraping is a useful technique to convert unstructured data on the web to structured data

BeautifulSoup is an efficient library available in Python to perform web scraping other than urllib

A basic knowledge of HTML and HTML tags is necessary to do web scraping in Python

Introduction

The need and importance of extracting data from the web is becoming increasingly loud and clear. Every few weeks, I find myself in a situation where we need to extract data from the web to build a machine learning model.

For example, last week we were thinking of creating an index of hotness and sentiment about various data science courses available on the internet. This would not only require finding new courses, but also scraping the web for their reviews and then summarizing them in a few metrics!

This is one of the problems / products whose efficacy depends more on web scraping and information extraction (data collection) than the techniques used to summarize the data.

Note: We have also created a free course for this article – Introduction to Web Scraping using Python. This structured format will help you learn better.

Ways to extract information from web

There are several ways to extract information from the web. Use of APIs being probably the best way to extract data from a website. Almost all large websites like Twitter, Facebook, Google, Twitter, StackOverflow provide APIs to access their data in a more structured manner. If you can get what you need through an API, it is almost always preferred approach over web scraping. This is because if you are getting access to structured data from the provider, why would you want to create an engine to extract the same information.

Sadly, not all websites provide an API. Some do it because they do not want the readers to extract huge information in a structured way, while others don’t provide APIs due to lack of technical knowledge. What do you do in these cases? Well, we need to scrape the website to fetch the information.

There might be a few other ways like RSS feeds, but they are limited in their use and hence I am not including them in the discussion here.

What is Web Scraping?

You can perform web scraping in various ways, including use of Google Docs to almost every programming language. I would resort to Python because of its ease and rich ecosystem. It has a library known as ‘BeautifulSoup’ which assists this task. In this article, I’ll show you the easiest way to learn web scraping using python programming.

For those of you, who need a non-programming way to extract information out of web pages, you can also look at import.io . It provides a GUI driven interface to perform all basic web scraping operations. The hackers can continue to read this article!

Libraries required for web scraping

As we know, Python is an open source programming language. You may find many libraries to perform one function. Hence, it is necessary to find the best to use library. I prefer BeautifulSoup (Python library), since it is easy and intuitive to work on. Precisely, I’ll use two Python modules for scraping data:

Urllib2: It is a Python module which can be used for fetching URLs. It defines functions and classes to help with URL actions (basic and digest authentication, redirections, cookies, etc). For more detail refer to the documentation page. Note: urllib2 is the name of the library included in Python 2. You can use the urllib.request library included with Python 3, instead. The urllib.request library works the same way urllib.request works in Python 2. Because it is already included you don’t need to install it.

BeautifulSoup: It is an incredible tool for pulling out information from a webpage. You can use it to extract tables, lists, paragraph and you can also put filters to extract information from web pages. In this article, we will use latest version BeautifulSoup 4. You can look at the installation instruction in its documentation page.

BeautifulSoup does not fetch the web page for us. That’s why, I use urllib2 in combination with the BeautifulSoup library.

Python has several other options for HTML scraping in addition to BeatifulSoup. Here are some others:

Basics – Get familiar with HTML (Tags)

While performing web scarping, we deal with html tags. Thus, we must have good understanding of them. If you already know basics of HTML, you can skip this section. Below is the basic syntax of HTML:This syntax has various tags as elaborated below:

Other useful HTML tags are:

If you are new to this HTML tags, I would also recommend you to refer HTML tutorial from W3schools. This will give you a clear understanding about HTML tags.

Scraping a web page using BeautifulSoup

Here, I am scraping data from a Wikipedia page. Our final goal is to extract list of state, union territory capitals in India. And some basic detail like establishment, former capital and others form this wikipedia page. Let’s learn with doing this project step wise step:

#import the library used to query a website import urllib2 #if you are using python3+ version, import urllib.request #specify the url #Query the website and return the html to the variable 'page' page = urllib2.urlopen(wiki) #For python 3 use urllib.request.urlopen(wiki) #import the Beautiful soup functions to parse the data returned from the website from bs4 import BeautifulSoup #Parse the html in the 'page' variable, and store it in Beautiful Soup format soup = BeautifulSoup(page) Above, you can see that structure of the HTML tags. This will help you to know about different available tags and how can you play with these to extract information.

Work with HTML tags

In[30]:soup.title

In [38]:

soup

title

string

Out[38]:u'List of state and union territory capitals in India - Wikipedia, the free encyclopedia'

In [40]:

soup

Above, it is showing all links including titles, links and other information. Now to show only links, we need to iterate over each a tag and then return the link using attribute “href” with get.

Find the right table: As we are seeking a table to extract information about state capitals, we should identify the right table first. Let’s write the command to extract information within all table tags. all_tables=soup.find_all('table') right_table=soup.find('table', class_='wikitable sortable plainrowheaders') right_table Above, we are able to identify right table.

#Generate lists A=[] B=[] C=[] D=[] E=[] F=[] G=[] for row in right_table.findAll("tr"): cells = row.findAll('td') states=row.findAll('th') #To store second column data if len(cells)==6: #Only extract table body not heading A.append(cells[0].find(text=True)) B.append(states[0].find(text=True)) C.append(cells[1].find(text=True)) D.append(cells[2].find(text=True)) E.append(cells[3].find(text=True)) F.append(cells[4].find(text=True)) G.append(cells[5].find(text=True)) #import pandas to convert list to data frame import pandas as pd df=pd.DataFrame(A,columns=['Number']) df['State/UT']=B df['Admin_Capital']=C df['Legislative_Capital']=D df['Judiciary_Capital']=E df['Year_Capital']=F df['Former_Capital']=G df

Similarly, you can perform various other types of web scraping using “BeautifulSoup“. This will reduce your manual efforts to collect data from web pages. You can also look at the other attributes like .parent, .contents, .descendants and .next_sibling, .prev_sibling and various attributes to navigate using tag name. These will help you to scrap the web pages effectively.-

But, why can’t I just use Regular Expressions?

Now, if you know regular expressions, you might be thinking that you can write code using regular expression which can do the same thing for you. I definitely had this question. In my experience with BeautifulSoup and Regular expressions to do same thing I found out:

Code written in BeautifulSoup is usually more robust than the one written using regular expressions. Codes written with regular expressions need to be altered with any changes in pages. Even BeautifulSoup needs that in some cases, it is just that BeautifulSoup is relatively better.

Regular expressions are much faster than BeautifulSoup, usually by a factor of 100 in giving the same outcome.

So, it boils down to speed vs. robustness of the code and there is no universal winner here. If the information you are looking for can be extracted with simple regex statements, you should go ahead and use them. For almost any complex work, I usually recommend BeautifulSoup more than regex.

End Note

In this article, we looked at web scraping methods using “BeautifulSoup” and “urllib2” in Python. We also looked at the basics of HTML and perform the web scraping step by step while solving a challenge. I’d recommend you to practice this and use it for collecting data from web pages.

Note: We have also created a free course for this article – Introduction to Web Scraping using Python. This structured format will help you learn better.

If you like what you just read & want to continue your analytics learning, subscribe to our emails, follow us on twitter or like our facebook page.

Top 7 Python Web Scraping Libraries & Tools In 2023

When it comes to web scraping, there are four common approaches for gathering data:

Developers use web scraping libraries to create in-house web crawlers. In-house web crawlers can be highly customized, requiring significant development and maintenance time. Building a web scraper in a language you are familiar with will allow you to reduce the development time and resources needed to build the scraper.

Python is the most commonly used programming language of 2023.

In this article, we summarized the main features, pros and cons of the most common open-source Python web scraping libraries.

1. Beautiful Soup

Beautiful Soup is a Python web scraping library that extracts data from HTML and XML files.

Beautiful Soup Installation: You can install Beautiful Soup 4 with “the pip install beautifulsoup4″ script.

Prerequisites:

Python

Pip: It is a Python-based package management system.

Supported features of Beautiful Soup:

Beautiful Soup works with the built-in HTML parser in Python and other third-party Python parsers, such as HTML5lib and lxml.

Beautiful Soup uses a sub-library like Unicode and Dammit to detect the encoding of a document automatically.

BeautifulSoup provides a Pythonic interface and idioms for searching, navigating and modifying a parse tree.

Beautiful Soup converts incoming HTML and XML entities to Unicode characters automatically.

Benefits of Beautiful Soup:

Provides Python parsers like”lxml” package for processing xml data and specific data parsers for HTML.

Parses documents as HTML. You need to install lxml in order to parse a document as XML.

Reduces time spent on data extraction and parsing the web scraping output.

Lxml parser is built on the C libraries libxml2 and libxslt, allowing fast and efficient XML and HTML parsing and processing.

The Lxml parser is capable of handling large and complex HTML documents. It is a good option if you intend to scrape large amounts of web data.

Can deal with broken HTML code.

Challenges of Beautiful Soup:

BeautifulSoup html.parser and html5lib are not suitable for time-critical tasks. If response time is crucial, lxml can accelerate the parsing process.

Most websites employ detection techniques like browser fingerprinting and bot protection technology, such as Amazon’s, to prevent users from grabbing a web page’s HTML. For instance, when you send a get request to the target server, the target website may detect that you are using a Python script and block your IP address in order to control malicious bot traffic.

Bright Data provides a residential proxy network with 72+ million IPs from 195 countries, allowing developers to circumvent restrictions and IP blocks.

2. Requests

Requests is an HTTP library that allows users to make HTTP calls to collect data from web sources.

Requests Installation: Requests’s source code is available on GitHub for integration into your Python package. Requests officially supports Python 3.7+.

Prerequisites:

Python

Pip: You can import Requests library with the “pip install requests” command in your Python package.

Features of Requests:

Requests automatically decode web content from the target server. There’s also a built-in JSON decoder if you’re working with JSON data.

It uses a request-response protocol to communicate between clients and servers in a network.

Requests provides in-built Python request modules, including GET, DELETE, PUT, PATCH and HEAD, for making HTTP requests to the target web server.

GET: Is used to extract data from the target web server.

POST: Sends data to a server to create a resource.

PUT: Deletes the specified resource.

PATCH: Enables partial modifications to a specified resource.

HEAD: Used to request data from a particular resource, similar to GET, but does not return a list of users.

Benefits of Requests:

Requests supports SOCKS and HTTP(S) proxy protocols.

Figure 2: Showing how to import proxies into the user’s coding environment

Source: Requests

It supports Transport Layer Security (TLS) and Secure Sockets Layer (SSL) verification. TLS and SSL are cryptographic protocols that establish an encrypted connection between two computers on a network.

Challenges of Requests:

It is not intended for data parsing.

It does not render JavaScript web pages.

3. Scrapy

Scrapy is an open-source web scraping and web crawling framework written in Python.

Scrapy installation: You can install Scrapy from PyPI by using the “pip install Scrapy” command. They have a step-by-step guideline for installation for more information.

Features of Scrapy:

Extract data from HTML and XML sources using XPath and CSS selectors.

Offer a built-in telnet console for monitoring and debugging your crawler. It is important to note that using the telnet console over public networks is not secure because it does not provide transport-layer security.

Include built-in extensions and middlewares for handling:

Robots.txt

User-agent spoofing

Cookies and sessions

Support for HTTP proxies.

Save extracted data in CSV, JSON, or XML file formats.

Benefits of Scrapy:

Scrapy shell is an in-built debugging tool. It allows users to debug scraping code without running the spider to figure out what needs to be fixed.

Support robust encoding and auto-detection to handle foreign, non-standard, and broken encoding declarations.

Challenges of Scrapy:

Python 3.7+ is necessary for Scrapy.

4. Selenium

Selenium offers different open-source extensions and libraries to support web browser automation.

WebDriver APIs: Utilizes browser automation APIs made available by browser vendors for browser automation and web testing.

IDE (Integrated Development Environment): Is a Chrome and Firefox extension for creating test cases.

Grid: Make it simple to run tests on multiple machines in parallel.

Figure 3: Selenium’s toolkit for browser automation

Source: Selenium

Prerequisites:

Eclipse

Selenium Web Driver for Python

To learn how to setup Selenium, check Selenium for beginners.

Features of Selenium:

Provides testing automation features

Capture Screenshots

Provide JavaScript execution

Supports various programming languages such as Python, Ruby, chúng tôi and Java.

Benefits of Selenium:

Offers headless browser testing. A headless web browser lacks user interface elements such as icons, buttons, and drop-down menus. Headless browsers extract data from web pages without rendering the entire page. This speeds up data collection because you don’t have to wait for entire web pages to load visual elements like videos, gifs, and images.

Can scrape JavaScript-rich web pages.

Operates in multiple browsers (Chrome, Firefox, Safari, Opera and Microsoft Edge).

Challenges of Selenium:

Taking screenshots of PDFs is not possible.

5. Playwright

Playwright is an open-source framework designed for web testing and automation. It is maintained by Microsoft team.

Features of Playwright:

Three things are required to install Playwright:

Python

Pytest plugin

Required browsers

Benefits of Playwright:

Are capable of scraping JavaScript-rendered websites.

Takes a screenshot of either a single element or the entire scrollable page.

Challenges of Playwright:

It does not support data parsing.

6. Lxml

Lxml is another Python-based library for processing and parsing XML and HTML content. Lxml is a wrapper over the C libraries libxml2 and libxslt. Lxml combines the speed of the C libraries with the simplicity of the Python API.

Lxml installation: You can download and install the lxml library from Python Package Index (PyPI).

Requirements

Python 2.7 or 3.4+

Pip package management tool (or virtualenv)

Features of LXML:

Lxml provides two different API for handling XML documents:

lxml.etree: It is a generic API for handling XML and HTML. lxml.etree is a highly efficient library for XML processing.

lxml.objectify: It is a specialized API for handling XML data in Python object syntax.

Lxml currently supports DTD (Document Type Definition), Relax NG, and XML Schema schema languages.

Benefits of LXML:

The key benefit of lxml is that it parses larger and more complex documents faster than other Python libraries. It performs at C-level libraries, including libxml2 and libxslt, making lxml fast.

Challenges of LXML:

lxml does not parse Python unicode strings. You must provide data that can be parsed in a valid encoding.

The libxml2 HTML parser may fail to parse meta tags in broken HTML.

Lxml Python binding for libxml2 and libxslt is independent of existing Python bindings. This results in some issues, including manual memory management and inadequate documentation.

7. Urllib3

Python Urllib is a popular Python web scraping library used to fetch URLs and extract information from HTML documents or URLs.

urllib.request: for opening and reading URLs (mostly HTTP).

urllib.parse: for parsing URLs.

urllib.error: for the exceptions raised by urllib.request.

urllib.robotparser: for parsing chúng tôi files. The chúng tôi file instructs a web crawler on which URLs it may access on a website.

Urllib has two built-in Python modules including urllib2 and urllib3.

urllib2: Sends HTTP requests and returns the page’s meta information, such as headers. It is included in Python version 2’s standard library.

Figure 4: urllib2 sends request to retrive the target page’s meta information

Source: Urllib2

urllib3: urllib3 is one of the most downloaded PyPI (Python Package Index) packages.

Urllib3 installation: Urllib3 can be installed using pip (package installer for Python). You can execute the “pip install urllib3” command to install urllib in your Python environment. You can also get the most recent source code from GitHub.

Figure 5: Installing Urllib3 using pip command

Source: GitHub

Features of Urllib3:

Proxy support for HTTP and SOCKS.

Provide client-side TLS/SSL verification.

Benefits of Urllib3:

Urllib3’s pool manager verifies certificates when making requests and keeps track of required connection pools.

Urllib allows users to access and parse data from HTTP and FTP protocols.

Challenges of Urllib3:

It might be challenging than other libraries such as Requests.

8. MechanicalSoup

MechanicalSoup is a Python library that automates website interaction.

MechanicalSoup installation: Install Python Package Index (Pypi), then write “pip install MechanicalSoup” script to locate MechanicalSoup on PyPI.

Features of MechanicalSoup:

Mechanicalsoup uses BeautifulSoup (BS4) library. You can navigate through the tags of a page using BeautifulSoup.

Automatically stores and sends cookies.

Utilizes Beautiful Soup’s find() and find all() methods to extract data from an HTML document.

Allows users to fill out forms using a script.

Benefits of MechanicalSoup:

Supports CSS and XPath selectors. XPaths and CSS Selectors enable users to locate elements on a web page.

Challenges of MechanicalSoup:

MechanicalSoup is only compatible with HTML pages. It does not support JavaScript. You cannot access and retrieve elements on JavaScript-based web pages.

Does not support JavaScript rendering and proxy rotation.