diff --git a/bonobo/examples/datasets/spam.tgz b/bonobo/examples/datasets/spam.tgz
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Binary files /dev/null and b/bonobo/examples/datasets/spam.tgz differ
diff --git a/bonobo/examples/files/pickle_handlers.py b/bonobo/examples/files/pickle_handlers.py
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+++ b/bonobo/examples/files/pickle_handlers.py
@@ -0,0 +1,58 @@
+import bonobo
+from fs.tarfs import TarFS
+import os
+
+
+def cleanse_sms(row):
+
+    if row['category'] == 'spam':
+        row['sms_clean'] = '**MARKED AS SPAM** ' + row['sms'][0:50] + ('...' if len(row['sms']) > 50 else '')
+    else:
+        row['sms_clean'] = row['sms']
+
+    return row['sms_clean']
+
+
+graph = bonobo.Graph(
+    bonobo.PickleReader('spam.pkl'),        # spam.pkl is within the gzipped tarball
+    cleanse_sms,
+    print
+)
+
+
+if __name__ == '__main__':
+
+    '''
+    This example shows how a different file system service can be injected
+    into a transformation (as compressing pickled objects often makes sense
+    anyways).  The pickle itself contains a list of lists as follows:
+
+    ```
+    [
+        ['category', 'sms'],
+        ['ham', 'Go until jurong point, crazy..'],
+        ['ham', 'Ok lar... Joking wif u oni...'],
+        ['spam', 'Free entry in 2 a wkly comp to win...'],
+        ['ham', 'U dun say so early hor... U c already then say...'],
+        ['ham', 'Nah I don't think he goes to usf, he lives around here though'],
+        ['spam', 'FreeMsg Hey there darling it's been 3 week's now...'],
+        ...
+    ]
+    ```
+
+    where the first column categorizes and sms as "ham" or "spam".  The second
+    column contains the sms itself.
+
+    Data set taken from:
+    https://www.kaggle.com/uciml/sms-spam-collection-dataset/downloads/sms-spam-collection-dataset.zip
+
+    The transformation (1) reads the pickled data, (2) marks and shortens
+    messages categorized as spam, and (3) prints the output.
+    '''
+
+    services = {
+        'fs': TarFS(
+            os.path.join(bonobo.get_examples_path(), 'datasets', 'spam.tgz')
+        )
+    }
+    bonobo.run(graph, services=services)