diff --git a/post_stats/__init__.py b/post_stats/__init__.py
new file mode 100644
index 0000000..2313bd5
--- /dev/null
+++ b/post_stats/__init__.py
@@ -0,0 +1 @@
+from .post_stats import *
diff --git a/post_stats/post_stats.py b/post_stats/post_stats.py
new file mode 100644
index 0000000..7ab30af
--- /dev/null
+++ b/post_stats/post_stats.py
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+# -*- coding: utf-8 -*-
+"""
+Post Statistics
+========================
+
+This plugin calculates various Statistics about a post and stores them in an article.stats disctionary.
+
+wc: how many words
+read_minutes: how many minutes to read this article, based on 250 wpm (http://en.wikipedia.org/wiki/Words_per_minute#Reading_and_comprehension)
+word_count: frquency count of all the words in the article; can be used for tag/word clouds/
+
+"""
+
+from pelican import signals, contents
+
+# import nltk
+
+from bs4 import BeautifulSoup
+
+# import lxml.html
+# from lxml.html.clean import Cleaner
+
+import re
+from collections import Counter
+
+
+def calculate_stats(instance):
+
+    WPM = 250
+
+    if instance._content is not None:
+        stats = {}
+        content = instance._content
+
+        # print content
+        entities = r'\&\#?.+?;'
+        content = content.replace(' ', ' ')
+        content = re.sub(entities, '', content)
+        # print content
+
+        # Pre-process the text to remove punctuation
+        drop = u'.,?!@#$%^&*()_+-=\|/[]{}`~:;\'\"‘’—…“”'
+        content = content.translate(dict((ord(c), u'') for c in drop))
+
+        # nltk
+        # raw_text = nltk.clean_html(content)
+
+        # BeautifulSoup
+        raw_text = BeautifulSoup(content).getText()
+        # raw_text = ''.join(BeautifulSoup(content).findAll(text=True))
+
+        # lxml
+        # cleaner = Cleaner(style=True)
+        # html = lxml.html.fromstring(content)
+        # raw_text = cleaner.clean_html(html).text_content()
+
+        # stats['wc'] = len(re.findall(r'\b', raw_text)) >> 1
+
+        # print raw_text
+
+        words = raw_text.lower().split()
+        word_count = Counter(words)
+        # print word_count
+
+        stats['word_counts'] = word_count
+        stats['wc'] = sum(word_count.values())
+        stats['read_minutes'] = (stats['wc'] + WPM // 2) // WPM
+
+        instance.stats = stats
+        instance.raw_text = raw_text
+
+
+def register():
+    signals.content_object_init.connect(calculate_stats)