From 68d864f2b4db86826ea840bda9780a086e5f8fe9 Mon Sep 17 00:00:00 2001
From: "codeflash-ai[bot]"
 <148906541+codeflash-ai[bot]@users.noreply.github.com>
Date: Fri, 19 Dec 2025 04:03:24 +0000
Subject: [PATCH] Optimize is_text_element
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The optimization achieves a **189% speedup** by eliminating expensive repeated operations and leveraging Python's built-in performance characteristics.

**Key optimizations:**

1. **Module-level constant definition**: Moved `text_classes` and `text_categories` to module scope as tuples instead of recreating them on every function call. This eliminates ~70% of the original runtime spent reconstructing these collections (8.7ms → 0ms in line profiler).

2. **Tuple vs List optimization**: Changed from lists to tuples, which are more memory-efficient and faster for `isinstance()` checks since Python can optimize tuple-based type checking.

3. **Eliminated generator expressions**: Replaced `any(isinstance(...) for ...)` with direct `isinstance(ontology_element, text_classes)`, which is significantly faster as it avoids generator overhead and uses Python's optimized C implementation for multiple type checking.

4. **Direct indexing**: Replaced `any(... for category in text_categories)` with direct comparison `ontology_element.elementType == text_categories[0]` since there's only one category, eliminating loop overhead.

**Performance impact**: The line profiler shows the critical path went from 52.3% + 15.9% = 68.2% of runtime in generator expressions to 67.5% + 32.5% = 100% in just two optimized operations, but with 7.8x less total time.

**Hot path relevance**: Based on `function_references`, this function is called from `can_unstructured_elements_be_merged()` within a loop processing multiple HTML elements. The optimization will significantly speed up HTML parsing workflows where element classification happens frequently.

**Test case performance**: All test cases show consistent 140-213% speedups, with the optimization being particularly effective for large-scale processing (800+ elements) showing ~190% improvements, making it ideal for batch document processing scenarios.
---
 .../partition/html/transformations.py         | 29 ++++++++++---------
 1 file changed, 15 insertions(+), 14 deletions(-)

diff --git a/unstructured/partition/html/transformations.py b/unstructured/partition/html/transformations.py
index 6006cf9905..60437e3ee4 100644
--- a/unstructured/partition/html/transformations.py
+++ b/unstructured/partition/html/transformations.py
@@ -15,6 +15,19 @@
     ONTOLOGY_CLASS_TO_UNSTRUCTURED_ELEMENT_TYPE,
 )
 
+text_classes = (
+    ontology.NarrativeText,
+    ontology.Quote,
+    ontology.Paragraph,
+    ontology.Footnote,
+    ontology.FootnoteReference,
+    ontology.Citation,
+    ontology.Bibliography,
+    ontology.Glossary,
+)
+
+text_categories = (ontology.ElementTypeEnum.metadata,)
+
 RECURSION_LIMIT = 50
 
 
@@ -186,22 +199,10 @@ def can_unstructured_elements_be_merged(
 def is_text_element(ontology_element: ontology.OntologyElement) -> bool:
     """Categories or classes that we want to combine with inline text"""
 
-    text_classes = [
-        ontology.NarrativeText,
-        ontology.Quote,
-        ontology.Paragraph,
-        ontology.Footnote,
-        ontology.FootnoteReference,
-        ontology.Citation,
-        ontology.Bibliography,
-        ontology.Glossary,
-    ]
-    text_categories = [ontology.ElementTypeEnum.metadata]
-
-    if any(isinstance(ontology_element, class_) for class_ in text_classes):
+    if isinstance(ontology_element, text_classes):
         return True
 
-    return any(ontology_element.elementType == category for category in text_categories)
+    return ontology_element.elementType == text_categories[0]
 
 
 def is_inline_element(ontology_element: ontology.OntologyElement) -> bool: