1. Web Scraping Using Python For Beginners Free
2. Web Scraping Using Python Code
3. Web Scraping Using Python For Beginners For Beginners
4. Web Scraping Using Python For Beginners Free
5. Web Scraping Python Example
6. Web Scraping Using Python For Beginners Using
7. Web Scraping Using Python For Beginners Tutorial

Have you ever thought of all the possibilities web scraping provides and how many benefits it can unlock for your business? Surely, you have!

But at the same time there were a lot of thoughts about the hurdles appearing – possible blocking, the system being sophisticated, difficulties in getting JS/AJAX data, scaling up challenges, maintaining, requiring above-the-average skill. And even if you don’t give up and keep working, your efforts can be completely derailed by the structure changes in the website. Don’t worry about that! There’s a simple Beginners Guide to web scraping. We did our best to put it together so even if you don’t have a technical background or lack relevant experience, you can still use it as a handbook. So you can get all the advantages web scraping provides and implement the juicy features into your business.

Let’s get started!

What is web scraping?

In short, web scraping allows you to extract data from the websites, so it can be saved in a file on your machine, so it can be accessed on a spreadsheet later on.

Usually you can only view the downloaded web page but not extract data. Yes, it is possible to copy some parts of it manually but this way is too time-consuming and not scalable. Web scraping extracts reliable data from the picked pages, so the process becomes completely automated. The received data can be used for business intelligence later on.

Feb 09, 2018 Prerequisite: Downloading files in Python, Web Scraping with BeautifulSoup. We all know that Python is a very easy programming language but what makes it cool are the great number of open source library written for it. Requests is one of the most widely used library. Some titles associated with Web Scraping include Data Scientist, Web Developer, Web Collection Specialist, Research Assistant, Application Developer, Web Mining Developer, Site Merchandiser, Market Intelligence Analyst, and of course, Web Scraper. In the U.S., Web Scraping can earn learners an average of $79,018 per year, according to ZipRecruiter.

In other words, one can work with any kind of data, as far web scraping works perfectly fine with vast quantities of data, as well as different data types.

Images, text, emails, even phone numbers – all will be extracted up to your business’ needs. For some projects specific data can be needed, for example, financial data, real estate data, reviews, price or competitor data whatever. Using web scraping tools it is fast and easy to extract it as well. But the best thing is that at the end you get the extracted data in a format of your choice. It can be plain text, JSON or CSV.

How does web scraping work?

Surely, there are lots of ways to extract data, but here there’s the easiest and the most reliable one. Here’s how it works.

Prerequisite: Downloading files in Python, Web Scraping with BeautifulSoup. We all know that Python is a very easy programming language but what makes it cool are the great number of open source library written for it. Requests is one of the most widely used library. Web Scraping Reference: A Simple Cheat Sheet for Web Scraping with Python October 24, 2018 Once you’ve put together enough web scrapers, you start to feel like you can do it in your sleep.

1. Request-response

The first simple step in any web scraping program (also called a “scraper”) is to request the target website for the contents of a specific URL.

In return, the scraper gets the requested information in HTML format. Remember, HTML is the file type used to display all the textual information on a webpage.

2. Parse and extract

HTML is a markup language, having a simple and clear structure. Parsing applies to any computer language, taking the code as bunches of text. It produces a structure in memory, which the computer can understand and work with.

Sounds too difficult? Wait a second. To make it simple we can say that HTML parsing takes HTML code, expects it and extracts the relevant information – title, paragraphs, headings. Links and formatting like bold text.

So all you need is a regular expression, defining the regular language, so a regular expression engine can generate a parser for this specific language. Thus pattern matching becomes possible, as well as text extraction.

3. Download data

The last step - downloading and saving the data in the format of your choice (CSV, JSON or in a database). After it becomes accessible, it can be retrieved, implemented in other programs.

In other words, scrapping allows you not just to extract data, but to store it into a central local database or spreadsheet and use it later when you need.

Advanced techniques for web scraping using python

Today computer vision technologies, as well as machine learning is used to distinguish and scrape data from the images, similar to the way a human being could do.

All it works quite straightforward. A machine learning system has its own classifications to which it assigns a so-called confidence score. It is a measure of the statistical likelihood. So if the classification is considered to be correct, it means it is close to the patterns discerned in the training data

In case the confidence score is too low, the system initiates a new search query to pick the bunch of text which will most likely contain the previously requested data.

Web Scraping Using Python For Beginners Free

After the system makes an attempt to scrap the relevant data from the text considered to be new and reconciles the received result with the data in the initial scraping. In case the confidence score is still too low it processes further on, working on the next pulled text.

What is web scraping used for?

There are numerous ways how web scraping python can be used, basically it can be implemented in every known domain. But let’s have a closer look at some areas where web scraping is considered to be the most efficient.

Price monitoring

Competitive pricing is the main strategy for e-commerce businesses. The only way to succeed here is to keep a constant track of the competitors and their pricing strategy. Parsed data can help to define your own pricing strategy. It is much faster than manual comparing and analysis. When it comes to price monitoring web scraping can be surprisingly efficient.

Lead generation

Marketing is essential for any business. For marketing strategy to be successful one needs not just to have the contact details of the parties involved but to reach them. It is the essence of lead generation. And web scraping can improve the process, making it more efficient.

Leads are the very first thing needed for marketing campaign acceleration.

To reach the target audience you most likely need tons of data such as phone numbers, emails etc. And of course to collect it manually over the thousands of websites all over the web is impossible.

Web scraping is here to help! It extracts the data. The process is not just accurate but quick and takes just a fraction of time.

The received data can be easily integrated into your sales tools as far you can pick a format you are comfortable with.

Competitive analysis

Competition has always been the flesh and blood of any business, but today it is critically important to know the competitors well. It allows us to understand their strong and weak points, strategies and evaluate risks in a more efficient way. Of course it is possible only if you possess a lot of relevant data. And web scraping helps here as well.

Any strategy starts with analysis. But how to work with the data spread everywhere? Sometimes it is even impossible to access it manually.

If it is difficult to do manually, use web scraping. So you get the required data and can start working over almost immediately.

A good point here – the faster your scraping tool, the better competitive analysis will be.

Fetching images and product description

When the customer enters any e-commerce website the first thing he sees is the visual content, e.g. pictures. Tons and tons of them. But how to create all this amount of product descriptions and pictures overnight? With web scraping of course!

So, when you come up to the idea of launching a brand new e-commerce website you face a content issue – all these pictures, descriptions and so on.

Old good way of hiring somebody just to copy and paste or write the content from scratch might work but will take forever. Use web scraping instead and see the result.

In other words, web scraping makes your life as an e-commerce website owner much easier, right?

Is data scraping software legal?

Web scraping software is working with data – it is, technically, a process of data extraction. But what if it is protected by law or copyrighted? It is quite natural that one of the first appearing questions is ‘Is it legal?’. The issue is tricky, as far here’s no certain opinion on this point even between the layers. Here are a few points to consider:

• Public data can be scrapped without any limits and there will be no restrictions. But if you step into the private data, it might land you in trouble.
• Abusive manner or using personal data for commercial purposes is the best way to end up in violation of CFAA, so avoid it.
• Scrapping copyrighted data is illegal and, well, unethical.
• To stay on the safe side, follow Robots.txt requirements, as well as Terms of Service (ToS).
• Using API for scraping is fine as well.
• Consider the crawl rate as 1 in 10-15 seconds. Otherwise you can be blocked.
• Don’t hit servers too often and do not process web scraping in an aggressive manner if you want to be safe.

Challenges in web scraping

Some aspects of web scraping are challenging, though it is relatively simple in general. See below a short list of major challenges you can face:

1. Frequent structure changes

After the scrapper is set up the big game only begins. In other words, setting up the tool is the first step so you can face some unexpected challenges:

All websites keep updating their UI and features. It means that the website structure is changing all the time. As far the crawler keeps in mind the existing structure, any change might upset your plans. The issue will be solved as soon as you change the crawler accordingly.

So to get complete and relevant data you should keep changing your scrapper again and again as soon as structure changes appear.

2. HoneyPot traps

Keep in mind that all the websites with sensitive data take precautions to protect the data in this or that way and they are called HoneyPots. It means that all your web scraping efforts can simply be thwarted and you will be surfing the web in attempts to figure out what’s wrong this time.

• HoneyPots are the links, accessible for crawlers, but developed to detect crawlers and prevent them from extracting data.
• They are in most cases the links with CSS style set to display:none. Another way to hide them is to remove them from the visible area or make them the color of background.
• When your crawler gets trapped, the IP becomes flagged or even blocked.
• Deep directory tree is another way to detect a crawler.
• So the number of retrieved pages or limit the traversal depth has to be limited.

3. Anti-scraping technologies

Anti-scrapping technologies evolve as well as web scraping does as far as there's a lot of data that should not be shared, and it is fine. But if you do not keep this in mind you can end up blocked. See below a short list of the most essential points you should know:

• The bigger the website is, the better it protects the data and defines crawlers. For example, LinkedIn, Stubhub and Crunchbase use powerful anti-scraping technologies.
• In case of such websites, bot access is prevented by using dynamic coding algorithms and IP blocking mechanisms implementation.
• It is clear that it is a huge challenge – to avoid blocking, so the solution, working against all the odds, turns out to become a time consuming and pretty expensive project.

4. Data quality

To get the data is just one of the points to achieve. For efficient work the data should be clean and accurate. In other words, if the data is incomplete or there are tons of mistakes, it is of no use. From a business perspective data quality is the main criteria, as far in the end of the day you need data ready to work with.

How can I start web scraping?

We are pretty sure – the question spinning round in your head is something like “How can I start web scraping and enhance my marketing strategy?”

Coding your own

Web Scraping Using Python Code

• Prefer DIY-approach? Then go on and code your own scraper.
• Open-source products are an option as well.
• A host is another essential chain in the link. It enables the scraper to run round the clock.
• Robust server infrastructure is a must. However, you will need some kind of storage for the data.
• One of the greatest things in DIY-approach and coding your own scraper is the fact that you are in absolute control of every single bit of functionality.
• Weak point here is an immense amount of needed resources.
• You should not forget about monitoring and improving your system from time to time, and it also requires resources.
• Coding your own scraper might be a good option for a small, short-term project.

Web scraping tools & web scraping service

Another way to reach the same result is just to use existing tools for scraping.

• Invest a bit and try existing tools to find the one, meeting your requirements best.
• You can get a lot of benefits the power of web scraping in case you find a reliable, scalable and affordable tool among the ones available in the market
• There are free tools or the ones with a substantial trial period. They are worth giving a try if you need to extract a lot of data.
• Try to work with ProWebScraper for the quick start. It's free, intuitive and allows python scrape website with the first 1000 pages for free.

Web Scraping Using Python For Beginners For Beginners

Custom solution

Web Scraping Using Python For Beginners Free

There’s another way, something in between the previous two.

It is simple – get the team of developers, so they will code a scraping tool specifically for your business’ needs.

Web Scraping Python Example

So you get a unique tool without the stress caused by accrual DIY approach. And the total cost will be much lower than in case you decide to subscribe to some existing scrapers.

Web Scraping Using Python For Beginners Using

Freelance developers can match too and create a good scrapper upon request, why not.

A SaaS MVP based on web scraping, data analytics, and data visualization

To sum up

Web Scraping Using Python For Beginners Tutorial

Web scraping is an extremely powerful tool for extracting data and getting additional advantages over the competitors. The earlier you start exploring, the better for your business.

There are different ways to start exploring the world of web scrapers and you can start with free ones shifting to unique tools, developed in accordance with your needs and requirements.