ENH: Adds quantopian-quandl bundle as new default.

This data bundle will use the quantopian mirror of the quandl WIKI data
instead of downloading from quandl directly. This dramatically improves
the speed because we do not pay the rate limiting for quandl and we can
send the data in the format zipline expects.

tests/test_examples.py

@@ -12,9 +12,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
-# This code is based on a unittest written by John Salvatier:
-# https://github.com/pymc-devs/pymc/blob/pymc3/tests/test_examples.py
+from functools import partial
 import tarfile
 
 import matplotlib
@@ -22,6 +20,7 @@ from nose_parameterized import parameterized
 import pandas as pd
 
 from zipline import examples, run_algorithm
+from zipline.data.bundles import register, unregister
 from zipline.testing import test_resource_path
 from zipline.testing.fixtures import WithTmpDir, ZiplineTestCase
 from zipline.testing.predicates import assert_equal
@@ -76,6 +75,9 @@ class ExamplesTests(WithTmpDir, ZiplineTestCase):
     def init_class_fixtures(cls):
         super(ExamplesTests, cls).init_class_fixtures()
 
+        register('test', lambda *args: None)
+        cls.add_class_callback(partial(unregister, 'test'))
+
         with tarfile.open(test_resource_path('example_data.tar.gz')) as tar:
             tar.extractall(cls.tmpdir.path)