Changed zipline -> catalyst import paths

* Updated cython build scripts
 * Updated setup.py to to install catalyst package
 * Updated momentum example to use catalyst package
 * catalyst executable now supports loading pipelines from multiple bundles

catalyst/data/benchmarks.py

@@ -0,0 +1,61 @@
+#
+# Copyright 2013 Quantopian, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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.
+import numpy as np
+import pandas as pd
+
+import pandas_datareader.data as pd_reader
+
+
+def get_benchmark_returns(symbol, first_date, last_date):
+    """
+    Get a Series of benchmark returns from Google associated with `symbol`.
+    Default is `SPY`.
+
+    Parameters
+    ----------
+    symbol : str
+        Benchmark symbol for which we're getting the returns.
+    first_date : pd.Timestamp
+        First date for which we want to get data.
+    last_date : pd.Timestamp
+        Last date for which we want to get data.
+
+    The furthest date that Google goes back to is 1993-02-01. It has missing
+    data for 2008-12-15, 2009-08-11, and 2012-02-02, so we add data for the
+    dates for which Google is missing data.
+
+    We're also limited to 4000 days worth of data per request. If we make a
+    request for data that extends past 4000 trading days, we'll still only
+    receive 4000 days of data.
+
+    first_date is **not** included because we need the close from day N - 1 to
+    compute the returns for day N.
+    """
+    data = pd_reader.DataReader(
+        symbol,
+        'google',
+        first_date,
+        last_date
+    )
+
+    data = data['Close']
+
+    data[pd.Timestamp('2008-12-15')] = np.nan
+    data[pd.Timestamp('2009-08-11')] = np.nan
+    data[pd.Timestamp('2012-02-02')] = np.nan
+
+    data = data.fillna(method='ffill')
+
+    return data.sort_index().tz_localize('UTC').pct_change(1).iloc[1:]