Parameters to Select the Best Programming Language
So what can you look for in a programming language for extracting data?
How well you can do web crawling will depend on the language and the framework that you use.
Well, there are some well-defined parameters you can use to select the appropriate programming language. Here’s a shortlist:
- Operational ability to feed database
- Crawling effectiveness
- Ease of coding
The most important part of a high performance web-wide crawler is synchronization of (many) parallel instances, running on multiple machines.
A very rough rule of thumb is that a single machine saturating a 10Mbps connection is good performance. Big search engines run hundreds of them.
The basic functionality of every crawler is very simple, almost trivial as it consists of fetching pages and extracting links from them.
With multiple instances running in parallel, the main challenge is to detect duplicates in real-time, as you definitely do not want hitting target pages multiple times, and obey robots.txt constraints across all those instances, in real-time.
All of this is rather tricky as timing across instances in non-deterministic and unpredictable so there has to be significant synchronization to make sure robots.txt constraints are conformed to for each site.
For this reason, languages with built-in threads such as Java are very well suited. At both Vast.com and Wowd we used Java for crawling exclusively.
It is important not to confuse crawling with scraping/wrappers/web clients where you want to do some extraction/processing.
In a crawler you do not want to do that as you want to just fetch the pages and perhaps do some very basic stuff in preparation for the next step of processing.
Early crawlers used to be done in C/C++, people also used Java a lot, it is certainly possible to use well designed scripting languages such as Python, but scripting features do not mean much for the raw performance of lots of parallel instances.
So I guess you made the right choice by starting to learn Python because Python is the world’s fastest and most popular programming language not just among SDE’s but also among Mathematicians, Data Analysts, Scientists and even Kids too!!! The reason is simple because Python is a very beginner-friendly programming language.
Python is mostly known as the best web scraper language. It’s more like an all-rounder and can handle most of the web crawling related processes smoothly. Beautiful Soup is one of the most widely used frameworks based on Python that makes scraping using this language such an easy route to take.
There are too many sub-questions in this question. Let me try to answer some of these :
What is exactly a web crawler?- Web crawler is an ‘agent’ or program that navigates through the pages of one or more websites and possibly stores the data sent by the server. These agents are also called bots or robots and their ‘ethics’ are generically governed by robots.txt given on the site. For example, search engines like Google have bots that crawl and get data from all over the web and store it. They do further processing (indexing) to enable search on this data.
Which language are they usually programmed in? – There was an earlier question on the same lines here- Which is the best programming language for developing a most efficient web crawler?
What are the algorithms which are used to better parse an HTML document- This is technically not related to crawling but to extraction i.e. extracting useful data from the crawled data. Regex is only used in bits and pieces for this and is not used as a primary tool for extraction. Using regex to parse HTML is too fragile a thing to attempt (see the discussion here- An alternate and more reliable model is to deal with the DOM of the page and then parse it as per your specs. There is some template matching algorithms too which can be used.
How do they store the indexed information- that depends upon the goal. If the search is the goal then ‘inverted index’ is the approach.
Regarding Google crawler- we should see the whole picture. Their initial edge came from ‘page rank’ which treats web as a graph and gives weight to websites and pages based on how and which other websites are pointing to them. This resulted in a great improvement in relevance of the search results. Later, map-reduce helped them to make the crawls faster and increase the freshness of the results. With map-reduce, they could use commodity hardware and the robustness of the crawling and indexing process increased multifold.
Top 5 most popular scraping languages-
Web scraping would be impossible without scraper bots. Bots are scraping tools that need to be properly coded to perform certain operations. They can also be AI-powered, but either option will require some basic programming to make them feasible and viable data extracting tools. Here is our list of the best scraping languages.
C# was developed by Anders Hejlsberg in 1999. He was a vital contributor to C# language development. C# is an object-oriented, general-purpose, modern, and simple, high-level programming language that compiles down to CRL and can be interpreted by JIT in ASP.NET. It runs memory management automatically.
It doesn’t come with complex features, which is why it’s the most popular coding language in the world. You can find C# in almost every application, and you can use C# to create high-end scraping bots for large-scale C# web scraping operations.
Python is a general-purpose, high-level, and popular coding language that is probably one of the most used languages in the world. It’s one of the most commonly used languages for data scraping as it makes the entire process of targeting websites, crawling content, and harvesting data streamlined, efficient, and undetectable.
Last in line in PHP. Although not as popular as other languages mentioned here, you can use it to create intuitive scraper bots for specific web scraping purposes, such as harvesting data from websites with academic literature, papers, e-books, and so on.
Ruby is perfect for those who need a simple and easy-to-use programming language for creating scraper bots. Ruby offers something that other languages don’t – the ability to create bots that can search HTML documents by CSS selectors.