Not all parsers adopt this two-steps schema: some parsers do not depend on a separate lexer and they combine the two steps. The parser needs the lexer because it does not work directly on the text, but on the output produced by the lexer. A complete parser is usually composed of two parts: a lexer, also known as scanner or tokenizer, and the proper parser. Having now clarified the role of regular expressions, we can look at the general structure of a parser. However usually the regular expressions defined in the grammar are actually converted to a finite-state machine to gain better performance. You can implement a lexer using the regular expression engine provided by your language. The definition of the rule should not be confused with how the actual lexer or parser is implemented. For example, the Kleene star( *) is used in a rule to indicate that a particular element can be present zero or an infinite amount of times. More precisely, their syntax is used to define the rules of a lexer or a parser. The familiarity of a typical programmer with regular expressions often lends them to be used to define the grammar of a language. For instance, HTML can contain an arbitrary number of tags inside any tag, therefore is not a regular language and it cannot be parsed using solely regular expressions, no matter how clever. A simple rule of thumb is: if a grammar of a language has recursive, or nested, elements it is not a regular language. This is the reason why they are used to implement lexers, as we are going to see later.Ī regular language can be defined by a series of regular expressions, while more complex languages need something more. That is to say regular expressions and finite state machines are equally powerful. Though one important consequence of the theory is that regular languages can be parsed or expressed also by a finite state machine. There is a formal mathematical definition, but that is beyond the scope of this article. In fact, languages that can be parsed with just regular expressions are called regular languages. You can use regular expressions to parse some simpler languages, but this excludes most programming languages, even the ones that look simple enough like HTML. The result is usually a series of regular expressions hacked together, that are very fragile. So they use them to try to parse everything, even the things they should not. The problem is that some programmers only know regular expressions. This is not strictly correct, because you can use regular expressions for parsing simple input. Regular expression are often touted as the thing you should not use for parsing. Regular ExpressionsĪ sequence of characters that can be defined by a pattern We are not trying to give you formal explanations, but practical ones. In this section we are going to describe the fundamental components of a parser. For instance, it is needed when you have to serialize or deserialize a class. However parsing might be necessary even when passing data between two software that have different needs. So humans write them in a form that they can understand, then software transforms them in a way that can be used by a computer. The obvious example are programs: they are written by humans, but they must be executed by computers. Parsing allows to transform data in a way that can be understood by a specific software. Raw representation is usually text, but it can also be binary data.įundamentally parsing is necessary because different entities need the data to be in different forms. While for templating you have to combine the data with the model, to create the raw representation. In the case of parsing you have to determine the model from the raw representation. In templating we have a structure and we fill it with data instead. In a way parsing can be considered the inverse of templating: identifying the structure and extracting the data.
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