Parsing Tools
What Is Parsing of Data? – Blog | Oxylabs
If you work with development (whether part of the team or work in a company where you need to communicate with the tech team often), you’ll most likely come across the term data parsing. Simply put, it’s a process when one data format is transformed into another, more readable data format. But that’s a rather straightforward explanation.
In this article we’ll dig a little deeper on what is parsing of data, and discuss whether building an in-house data parser is more beneficial to a business, or is it better to buy a data extraction solution that already does the parsing for you.
What is data parsing?
Data parsing is a widely used method for data structuring; thus, you may discover many different descriptions while trying to find out what exactly it is. To make understanding this concept easier, we’ve put it into a simple definition.
What is data parsing? Data parsing is a method where one string of data gets converted into a different type of data. So let’s say you receive your data in raw HTML, a parser will take the said HTML and transform it into a more readable data format that can be easily read and understood.
What does a parser do?
A well-made parser will distinguish which information of the HTML string is needed, and in accordance to the parsers pre-written code and rules, it will pick out the necessary information and convert it into JSON, CSV or a table, for example.
It’s important to mention that a parser itself is not tied to a data format. It’s a tool that converts one data format into another, how it converts it and into what depends on how the parser was built.
Parsers are used for many technologies, including:
Java and other programming languagesHTML and XMLInteractive data language and object definition languageSQL and other database languagesModeling languagesScripting languagesHTTP and other internet protocols
To build or to buy?
Now, when it comes to the business side of things, an excellent question to ask yourself is, “Should my tech team build their own parser, or should we simply outsource? ”
As a rule of thumb, it’s usually cheaper to build your own, rather than to buy a premade tool. However, this isn’t an easy question to answer, and a lot more things should be taken into consideration when deciding to build or to buy.
Let’s look into the possibilities and outcomes with both options.
Building a data parser
Let’s say you decide to build your own parser. There are a few distinct benefits if making this decision:
A parser can be anything you like. It can be tailor-made for any work (parsing) you require. It’s usually cheaper to build your own ’re in control whatever decisions need to be made when updating and maintaining your parser.
But, like with anything, there’s always a downside of building your own parser:
You’ll need to hire and train a whole in-house team to build the intaining the parser is necessary – meaning more in house expenses and time resources ’ll need to buy and build a server that will be fast enough to parse your data in the speed you in control isn’t necessarily easy or beneficial – you’ll need to work closely with the tech team to make the right decisions to create something good, spending a lot of your time planning and testing.
Building your own has its benefits – but it takes a lot of your resources and time. Especially if you need to develop a sophisticated parser for parsing large volumes. That will require more maintenance and human resources, and valuable human resources because building one will require a highly-skilled developer team.
Buying a data parser
So what about buying a tool that parses your data for you? Let’s start with the benefits:
You won’t need to spend any money on human resources, as everything will be done for you, including maintaining the parser and the issues that arise will be solved a lot faster, as the people you buy your tools from have extensive know-how and are familiarized with their technology. It’s also less likely that the parser will crash or experience issues in general, as it will be tested and perfected to fit the markets’ requirements. You’ll save a lot on human resources and your own time, as the decision making on how to build the best parser will come from the outsourcing.
Of course, there are a few downsides to buying a parser as well:
It will be slightly more won’t have too much control over it.
Now, it seems that there are a lot of benefits to simply just buy one. But one thing that might make things easier to choose is to consider what sort of parser you’ll need. An expert developer can make an easy parser probably within a week. But if it’s a complex one, it can take months – that’s a lot of time, and resources.
It also falls to whether you’re a big business that has a lot of time and resources on their hands to build and maintain a parser. Or you’re a smaller business that needs to get things done to be able to grow within the market.
How we do it: Real-Time Crawler
Here at Oxylabs, we have a data gathering tool called Real-Time Crawler. This product is specifically built to scrape search engines and e-commerce websites on a large scale. We covered what Real-Time Crawler is and how it works in great detail in one of our articles, so make sure to check it out. Also, here’s a video below:
But why are we bringing up this tool? Well, Real-Time Crawler not only gathers the data – it also has a built-in parser that turns your HTML into JSON. If you choose to use Real-Time Crawler Callback method, after every job request, you’ll be provided with a URL to download the results in HTML or parsed JSON format.
Our built-in parser handles quite a lot of data daily. On February, 12 billion requests were made! And that’s back in February! Based on our 2019, Q1 statistics, the total requests grew by 7. 02% in comparison to Q4 2018. And these numbers continue to rise in accordance in Q2, 2019.
Our tech team has been working with this project for a few years now, and having this much experience we can say with confidence that the parser we built can handle any volume of data one might request.
So – to build or to buy? Well, building several years of experience, improvements, and maintenance of a tool that does its job to perfection – honestly, quite expensive.
Wrapping up
Hopefully, now you have a decent understanding of what is parsing of data. Taking everything into account, keep in mind whether you’re building a very sophisticated parser or not. If you are parsing large volumes of data, you will need good developers on your team to develop and maintain the parser. But, if you need a less complicated, smaller parser – probably best to build your own.
Also be mindful if you are a large company with a lot of resources, or a smaller one, that needs the right tools to keep things growing.
Oxylabs’ clients have significantly increased growth with Real-Time Crawler! If you are also looking for ways to improve your business, register here to start using our tools. Also, if you have more questions about data parsing, book a call with our sales team!
People also ask
What tools are required for data parsing?
After web scraping tools provide the required data, there are several options for data parsing. BeautifulSoup and LXML are two commonly used data parsing tools.
How to use a data parser?
Every data parsing tool will come with its own manual. Most of them will require some technical knowledge such as understanding Python and data from a web scraper.
What is data scraping?
Data scraping is the process of acquiring large amounts of data from the web through the use of automation and rotating IP address.
Gabija Fatenaite is a Product Marketing Manager at Oxylabs. Having grown up on video games and the internet, she grew to find the tech side of things more and more interesting over the years. So if you ever find yourself wanting to learn more about proxies (or video games), feel free to contact her – she’ll be more than happy to answer you.
All information on Oxylabs Blog is provided on an “as is” basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Oxylabs Blog or any third-party websites that may be linked therein. Before engaging in scraping activities of any kind you should consult your legal advisors and carefully read the particular website’s terms of service or receive a scraping license.
4. Basic Parsing Techniques – Express Learning: Principles of Compiler …
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Basic Parsing Techniques
1. Define parsing. What is the role of a parser?
Ans: Parsing (also known as syntax analysis) can be defined as a process of analyzing a text which contains a sequence of tokens, to determine its grammatical structure with respect to a given grammar.
Figure 4. 1 Parsing
Depending upon how the parse tree is built, parsing techniques are classified into three general categories, namely, universal parsing, top-down parsing, and bottom-up parsing. The most commonly used parsing techniques are top-down parsing and bottom-up parsing. Universal parsing is not used as it is not an efficient technique. The hierarchical classification…
Types of Parsers in Compiler Design – GeeksforGeeks
Parser is that phase of compiler which takes token string as input and with the help of existing grammar, converts it into the corresponding parse tree. Parser is also known as Syntax Analyzer. Attention reader! Don’t stop learning now. Practice GATE exam well before the actual exam with the subject-wise and overall quizzes available in GATE Test Series all GATE CS concepts with Free Live Classes on our youtube of Parser: Parser is mainly classified into 2 categories: Top-down Parser, and Bottom-up Parser. These are explained as following below. 1. Top-down Parser: Top-down parser is the parser which generates parse for the given input string with the help of grammar productions by expanding the non-terminals i. e. it starts from the start symbol and ends on the terminals. It uses left most derivation. Further Top-down parser is classified into 2 types: Recursive descent parser, and Non-recursive descent parser. (i). Recursive descent parser: It is also known as Brute force parser or the with backtracking parser. It basically generates the parse tree by using brute force and backtracking. (ii). Non-recursive descent parser: It is also known as LL(1) parser or predictive parser or without backtracking parser or dynamic parser. It uses parsing table to generate the parse tree instead of backtracking. 2. Bottom-up Parser: Bottom-up Parser is the parser which generates the parse tree for the given input string with the help of grammar productions by compressing the non-terminals i. it starts from non-terminals and ends on the start symbol. It uses reverse of the right most derivation. Further Bottom-up parser is classified into 2 types: LR parser, and Operator precedence parser. LR parser: LR parser is the bottom-up parser which generates the parse tree for the given string by using unambiguous grammar. It follow reverse of right most derivation. LR parser is of 4 types: (a). LR(0)
(b). SLR(1)
(c). LALR(1)
(d). CLR(1) (ii). Operator precedence parser: It generates the parse tree form given grammar and string but the only condition is two consecutive non-terminals and epsilon never appear in the right-hand side of any production.
Frequently Asked Questions about parsing tools
What is a parsing tool?
It’s a tool that converts one data format into another, how it converts it and into what depends on how the parser was built. Parsers are used for many technologies, including: Java and other programming languages. … Interactive data language and object definition language. SQL and other database languages.Sep 13, 2021
What are parsing techniques?
Ans: Parsing (also known as syntax analysis) can be defined as a process of analyzing a text which contains a sequence of tokens, to determine its grammatical structure with respect to a given grammar.
Which is best parser?
1. Top-down Parser: Top-down parser is the parser which generates parse for the given input string with the help of grammar productions by expanding the non-terminals i.e. it starts from the start symbol and ends on the terminals. It uses left most derivation.Mar 22, 2021
