feat: improve parsing performance from o(n^2) to o(n)

The function process_tag was previously concatenating strings
inside of a loop. Each + operation creates a new string,
resulting in repeated copying of already accumulated data. By
replacing this with an array we append to, and then joining this
array at the end, we can take this from an exponential function
to a linear function.

markdownify/__init__.py

@@ -133,7 +133,7 @@ def convert_soup(self, soup):
         return self.process_tag(soup, convert_as_inline=False)
 
     def process_tag(self, node, convert_as_inline):
-        text = ''
+        text_parts = []
 
         # markdown headings or cells can't include
         # block elements (elements w/newlines)
@@ -147,43 +147,95 @@ def process_tag(self, node, convert_as_inline):
         # Remove whitespace-only textnodes just before, after or
         # inside block-level elements.
         should_remove_inside = should_remove_whitespace_inside(node)
-        for el in node.children:
-            # Only extract (remove) whitespace-only text node if any of the
-            # conditions is true:
-            # - el is the first element in its parent (block-level)
-            # - el is the last element in its parent (block-level)
-            # - el is adjacent to a block-level node
-            can_extract = (should_remove_inside and (not el.previous_sibling
-                                                     or not el.next_sibling)
-                           or should_remove_whitespace_outside(el.previous_sibling)
-                           or should_remove_whitespace_outside(el.next_sibling))
-            if (isinstance(el, NavigableString)
-                    and six.text_type(el).strip() == ''
-                    and can_extract):
+        children = list(node.children)
+        for i, el in enumerate(children):
+            # Quick type check first to avoid unnecessary function calls
+            if not isinstance(el, NavigableString):
+                continue
+
+            # Check if the text is entirely whitespace first
+            text = six.text_type(el)
+            if text.strip():
+                continue
+
+            # If first or last element
+            is_at_extreme_position = (
+                should_remove_inside and (i == 0 or i == len(children) - 1)
+            )
+            # True if there is a preceding sibling, and it should have whitespace removed.
+            has_removal_candidate_to_left = (
+                i > 0 and should_remove_whitespace_outside(children[i - 1])
+            )
+            # True if there is a following sibling, and it should have whitespace removed.
+            has_removal_candidate_to_right = (
+                i < len(children) - 1 and should_remove_whitespace_outside(children[i + 1])
+            )
+            # Determine if we can extract based on position and adjacency
+            can_extract = (
+                is_at_extreme_position
+                or has_removal_candidate_to_left
+                or has_removal_candidate_to_right
+            )
+
+            # Extract if conditions are met
+            if can_extract:
                 el.extract()
 
         # Convert the children first
         for el in node.children:
             if isinstance(el, Comment) or isinstance(el, Doctype):
                 continue
             elif isinstance(el, NavigableString):
-                text += self.process_text(el)
+                text_parts.append(self.process_text(el))
             else:
-                text_strip = text.rstrip('\n')
-                newlines_left = len(text) - len(text_strip)
+                # 1) Pop trailing newlines from whatever's in text_parts so far
+                text_strip, newlines_left = self.pop_trailing_newlines(text_parts)
+                # 2) Convert the next tag
                 next_text = self.process_tag(el, convert_children_as_inline)
+                # 3) Figure out how many leading newlines in next_text
                 next_text_strip = next_text.lstrip('\n')
                 newlines_right = len(next_text) - len(next_text_strip)
+                # 4) Calculate how many newlines to insert between text_strip and next_text_strip
                 newlines = '\n' * max(newlines_left, newlines_right)
-                text = text_strip + newlines + next_text_strip
+                text_parts.extend([text_strip, newlines, next_text_strip])
 
         # apply this tag's final conversion function
         convert_fn_name = "convert_%s" % re.sub(r"[\[\]:-]", "_", node.name)
         convert_fn = getattr(self, convert_fn_name, None)
         if convert_fn and self.should_convert_tag(node.name):
-            text = convert_fn(node, text, convert_as_inline)
-
-        return text
+            # Join the text parts before passing to convert_fn
+            text_parts_str = ''.join(text_parts)
+            text_parts = [convert_fn(node, text_parts_str, convert_as_inline)]
+
+        return ''.join(text_parts)
+
+    def pop_trailing_newlines(self, text_parts):
+        """
+        Pops trailing newline text from the end of `parts`. I suspect this function
+        will get refactored with time.
+        Returns: (combined_text_without_trailing_newlines, count_of_newlines_popped)
+        If there is no trailing text in parts, returns ("", 0).
+        """
+
+        newlines_total = 0
+        # 1) First pop off any chunks that are newlines
+        newline_chunks = []
+        while text_parts and text_parts[-1].rstrip('\n') == '':
+            newline_chunks.append(text_parts.pop())
+        if newline_chunks:
+            # Example: if we had ["\n", "\n", "\n"] at the very end
+            all_newlines = ''.join(reversed(newline_chunks))
+            newlines_total += len(all_newlines)
+
+        # 2) Now look at one more chunk which might have some real text + trailing newlines
+        text_without_newline = ''
+        if text_parts:
+            last_chunk = text_parts.pop()
+            stripped = last_chunk.rstrip('\n')
+            newlines_total += (len(last_chunk) - len(stripped))
+            text_without_newline = stripped
+
+        return (text_without_newline, newlines_total)
 
     def convert__document_(self, el, text, convert_as_inline):
         """Final document-level formatting for BeautifulSoup object (node.name == "[document]")"""