Implementación del pratt parser

What is Pratt parsing and how is it applied?

Pratt parsing is a popular top-down parsing technique, developed by the creator Pratt Baum. Through it, we iteratively build the abstract syntax tree (AST) from the beginning of the program. This technique has become well known, especially thanks to its use in important parsers such as JSON.

Pratt parsing is closely linked to the JavaScript programming language. When we work with a JSON parser in JavaScript or Python, what we do is convert a string into a data structure, for example, an object with properties.

How do you assign functions to tokens?

One of the most prominent features of Pratt parsing is that it assigns specific functions to each token. These functions can be of two types: infix (infix) or prefix (prefix). For example:

• Prefix: The operator "not" or the prefix "-" means negation.
• Infix: The "-" operator represents a subtraction between two numbers.

The position of the operator is critical. For example, a function call where the opening parenthesis acts as an infix operator in an expression.

How are aliased types implemented in Python?

To make our code more readable, we use aliases to identify whether we are dealing with a prefix or infix function. In Python, we can create type aliases using the typing module. Here are some examples:

from typing import Callable, Optional, Dict
 # Aliases for prefix functionsPrefixParseFunction = Callable[[], Optional['Expression']]
 # Aliases for infix functionsInfixParseFunction = Callable[[['Expression']],Optional['Expression']]
 # Dictionary for prefix functionsPrefixParseFunctions = Dict['TokenType',PrefixParseFunction]
  # Dictionary for infix functions InfixParseFunctions = Dict['TokenType', InfixParseFunction] # Dictionary for infix fun c tions InfixParseFu nctions = Dict['TokenType', InfixParseFunction] # Aliases for infix functions

How do we register parsing functions?

When initializing the parser, it is essential to register the functions to be executed for each token type. We implement lists that will allow to fill these dictionaries with the corresponding parsing functions.

class Parser: def __init__(self): self.prefix_parse_functions = self.register_prefix_functions() self.infix_parse_functions = self.register_infix_functions()
 def register_prefix_functions(self)-> PrefixParseFunctions: return {}
 def register_infix_functions(self)-> InfixParseFunctions: return {}

This forms the basic infrastructure for parsers, allowing us to later establish connections between token types and specific functions.

What are the considerations when using Pratt parsing?

Within Pratt parsing, it is crucial to keep in mind the following token using peek_token. This aspect is vital to verify if the syntactic order of the tokens is correct. The iterative process of parsing is a journey of adjustment and improvement. Initial doubts that arise will be clarified as the learning and development of the parser progresses.

Although the complexity of the subject may seem daunting, Pratt parsing provides the tools necessary to do efficient parsing. It is exciting to explore more about these techniques and how they can be applied in professional life. Join this exploration by sharing your experiences and the types of parsing you have encountered along the way - the learning never stops!