feat: improve text parsing performance

[geclos]

From AI:

1. Escape Checking: The code rechecks all trailing backslashes in the accumulated data string for every character, which becomes increasingly expensive as data grows.

2. String Slicing: When an escape character is found, data = data.slice(0, -1) creates a new string by copying almost the entire accumulated text.

3. Repeated String Concatenation: Adding to data one character at a time with data += char creates a new string object each time.

4. Regular Expression Replacements: At the end, it uses complex regex replacements that need to scan the entire string.

5. Repeated Delimiter Checking: For each character, it checks against multiple delimiters with template.startsWith(), which involves multiple string comparisons.

Our optimization approach for the text method focused on several improvements:

1. Simplified Escape Handling:

   • Instead of recounting backslashes for every character, we now use a boolean flag isEscaped to track whether the current character is escaped
   • When we encounter a backslash, we toggle the escape state and skip adding it to the data string directly
   • This eliminates the expensive backslash counting operation that grew in cost with the size of the text

2. Eliminated String Slicing:

   • We no longer use data.slice(0, -1) which was creating a new string by copying almost the entire accumulated text
   • Instead, we simply don't add the backslash to the data string at all

3. More Efficient Processing Flow:

   • The code now has a clearer path for handling escaped characters
   • We continue to the next iteration immediately after processing an escape sequence, reducing unnecessary checks

4. Simplified Data Processing:

   • We removed the complex regular expression replacements at the end
   • Since we're already handling escape sequences correctly during parsing, we don't need additional processing

[csansoon]

looks good