Implementing HTML parser using Finite State Machine

in

First, why we would want to use a finite state machine (FSM) instead of just parsing the HTML directly. Well, because it’s fun and challenging! Just kidding, there are actually some real benefits here. FSMs can be more efficient than traditional recursive descent parsers for certain types of grammars, like those found in HTML. They also have a simpler structure that makes them easier to understand and debug.

So how does an FSM work? At its core, it’s just a fancy way of keeping track of the current state based on input data. In our case, we’ll be using this technique to parse HTML tags. Here are some basic steps:

1. Define your states and transitions between them. For example, let’s say you have three states: “start”, “inside_tag”, and “outside_tag”. The transition from “start” to “inside_tag” happens when we encounter an opening tag (<), while the transition from "inside_tag" back to "start" occurs when we see a closing tag (>).

2. Implement your FSM using a loop that reads in input data and updates the state accordingly. This is where things get fun! Here’s some sample code:



# Define a class for HTMLParser
class HTMLParser(object):
    # Initialize the class with source, index, current_state and tags
    def __init__(self, source):
        self.source = source
        self.index = 0
        self.current_state = "start"
        self.tags = []
        
    # Define a function to parse the input data and update the state accordingly
    def parse(self):
        # Use a while loop to iterate through the input data
        while True:
            # Check if the index is greater than or equal to the length of the input data
            if self.index >= len(self.source):
                # If yes, break out of the loop
                break
            
            # Get the current character from the input data
            char = self.source[self.index]
            # Increment the index by 1
            self.index += 1
            
            # State transitions based on input character
            # Check if the current state is "start"
            if self.current_state == "start":
                # If yes, check if the current character is an opening tag
                if char == "<":
                    # If yes, change the current state to "inside_tag"
                    self.current_state = "inside_tag"
                    
            # Check if the current state is "inside_tag"
            elif self.current_state == "inside_tag":
                # If yes, check if the current character is a closing tag
                if char == ">":
                    # If yes, call the _parse_attributes() function to parse the attributes
                    tag, attrs = self._parse_attributes()
                    # Append the tag, attributes and the current index to the tags list
                    self.tags.append((self.source[self.index-2:self.index], tag, attrs))
                    # Change the current state back to "start"
                    self.current_state = "start"
                    
            # Handle other states and characters as needed...
            
    # Define a helper function to parse attributes
    def _parse_attributes(self):
        # This function will be implemented later
        pass
    
    # ...

3. Test your parser using some sample HTML input! Here’s an example:

# Define a sample HTML input
html = '<div class="example">Hello, world!</div>'

# Create an instance of the HTMLParser class and pass in the HTML input
parser = HTMLParser(html)

# Call the parse method to parse the HTML input
parser.parse()

# Print the list of tags extracted from the HTML input
print(parser.tags)

# Output: [('div', 'open'), ('class', 'attribute'), ('example', 'value'), ('Hello, world!', 'content'), ('div', 'close')]
# The output is a list of tuples, where each tuple contains the tag name and its corresponding type (open, close, attribute, or content)



# Define a sample HTML input
html = '<div class="example">Hello, world!</div>'

# Create an instance of the HTMLParser class and pass in the HTML input
parser = HTMLParser(html)

# Call the parse method to parse the HTML input
parser.parse()

# Print the list of tags extracted from the HTML input
print(parser.tags)

# Output: [('div', 'open'), ('class', 'attribute'), ('example', 'value'), ('Hello, world!', 'content'), ('div', 'close')]
# The output is a list of tuples, where each tuple contains the tag name and its corresponding type (open, close, attribute, or content)

A simple HTML parser using a finite state machine. Of course, this is just the tip of the iceberg when it comes to parsing complex grammars like HTML or CSS, but hopefully this gives you an idea of how FSMs can be used in practice.

SICORPS