Profile and adjust for performance, add bugfix to parse out mitechie …

…blog post

src/breadability/document.py

@@ -1,3 +1,5 @@
+"""Generate a clean nice starting html document to process for an article."""
+
 import chardet
 import logging
 import re

src/breadability/readable.py

@@ -12,6 +12,7 @@
 from breadability.scoring import is_unlikely_node
 from breadability.utils import cached_property
 
+
 html_cleaner = Cleaner(scripts=True, javascript=True, comments=True,
                   style=True, links=True, meta=False, add_nofollow=False,
                   page_structure=False, processing_instructions=True,
@@ -149,7 +150,7 @@ def prep_article(doc):
 
     """
     def clean_document(node):
-        """Remove the style attribute on every element."""
+        """Clean up the final document we return as the readable article"""
         clean_list = ['object', 'h1']
         keep_keywords = ['youtube', 'blip.tv', 'vimeo']
 
@@ -158,9 +159,10 @@ def clean_document(node):
         if len(node.findall('.//h2')) == 1:
             clean_list.append('h2')
 
-        for n in node.getiterator():
+        for n in node.iter():
             # clean out any incline style properties
-            n.set('style', '')
+            if 'style' in n.attrib:
+                n.set('style', '')
 
             # remove all of the following tags
             # Clean a node of all elements of type "tag".
@@ -187,7 +189,9 @@ def clean_document(node):
                 # if the heading has no css weight or a high link density,
                 # remove it
                 if get_class_weight(n) < 0 or get_link_density(n) > .33:
-                    n.drop_tree()
+                    # for some reason we get nodes here without a parent
+                    if n.getparent() is not None:
+                        n.drop_tree()
 
             # clean out extra <p>
             if n.tag == 'p':
@@ -205,29 +209,22 @@ def clean_conditionally(doc, clean_el):
     return doc
 
 
-def process(doc):
-    """Process this doc to make it readable.
+def find_candidates(doc):
+    """Find cadidate nodes for the readable version of the article.
 
     Here's we're going to remove unlikely nodes, find scores on the rest, and
     clean up and return the final best match.
 
     """
-    unlikely = []
     scorable_node_tags = ['p', 'td', 'pre']
     nodes_to_score = []
 
-    for node in doc.getiterator():
+    for node in doc.iter():
         if is_unlikely_node(node):
-            unlikely.append(node)
-
-        if node.tag in scorable_node_tags:
+            node.drop_tree()
+        elif node.tag in scorable_node_tags:
             nodes_to_score.append(node)
-
-    # process our clean up instructions
-    [n.drop_tree() for n in unlikely]
-
-    candidates = score_candidates(nodes_to_score)
-    return candidates
+    return score_candidates(nodes_to_score)
 
 
 class Article(object):
@@ -250,7 +247,7 @@ def readable(self):
         html_cleaner(doc)
         doc = drop_tag(doc, 'noscript')
         doc = transform_misused_divs_into_paragraphs(doc)
-        candidates = process(doc)
+        candidates = find_candidates(doc)
 
         if candidates:
             # right now we return the highest scoring candidate content

src/breadability/scoring.py

@@ -1,3 +1,6 @@
+"""Handle dealing with scoring nodes and content for our parsing."""
+import re
+
 # A series of sets of attributes we check to help in determining if a node is
 # a potential candidate or not.
 CLS_UNLIKELY = set([
@@ -32,7 +35,7 @@ def get_link_density(node):
     :returns float:
 
     """
-    link_length = len("".join([a.text or "" for a in node.findall(".//a")]))
+    link_length = sum([len(a.text_content()) or 0 for a in node.findall(".//a")])
     text_length = len(node.text_content())
     return float(link_length) / max(text_length, 1)
 
@@ -152,6 +155,3 @@ def __init__(self, node):
             content_score = -5
         content_score += get_class_weight(node)
         self.content_score = content_score
-
-
-