Introduction

In this blog post, we will explore how to solve the LeetCode problem "1410" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like Chatmagic, we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

Problem Statement

HTML entity parser is the parser that takes HTML code as input and replace all the entities of the special characters by the characters itself. The special characters and their entities for HTML are: Quotation Mark: the entity is " and symbol character is ". Single Quote Mark: the entity is ' and symbol character is '. Ampersand: the entity is & and symbol character is &. Greater Than Sign: the entity is > and symbol character is >. Less Than Sign: the entity is < and symbol character is <. Slash: the entity is ⁄ and symbol character is /. Given the input text string to the HTML parser, you have to implement the entity parser. Return the text after replacing the entities by the special characters. Example 1: Input: text = "& is an HTML entity but &ambassador; is not." Output: "& is an HTML entity but &ambassador; is not." Explanation: The parser will replace the & entity by & Example 2: Input: text = "and I quote: "..."" Output: "and I quote: \"...\"" Constraints: 1 <= text.length <= 105 The string may contain any possible characters out of all the 256 ASCII characters.

Explanation

Here's a breakdown of the approach and the Python code:

• High-Level Approach:

  • Iterate through the input string.
  • If an '&' is encountered, check for known HTML entities at that position.
  • If a valid entity is found, replace it with the corresponding character and advance the index accordingly; otherwise, keep the '&' as is.

• Complexity:

  • Runtime Complexity: O(n), where n is the length of the input string.
  • Storage Complexity: O(n) in the worst case, to store the output string.

• Python Code:

Code

    def entityParser(text: str) -> str:    entity_map = {
        """: "\"",
        "'": "'",
        "&": "&",
        ">": ">",
        "&lt;": "<",
        "&frasl;": "/"
    }

    result = ""
    i = 0
    while i < len(text):
        if text[i] == '&':
            found_entity = False
            for entity, char in entity_map.items():
                if text[i:i + len(entity)] == entity:
                    result += char
                    i += len(entity)
                    found_entity = True
                    break
            if not found_entity:
                result += text[i]
                i += 1
        else:
            result += text[i]
            i += 1

    return result