BUG: Fixing bitness issues on 32-bit systems

by being explicit with sizes

tests/test_algorithm.py

@@ -1131,15 +1131,15 @@ class TestBeforeTradingStart(TestCase):
         # Mergers and Dividends are not tested, but we need to have these
         # anyway
         mergers = pd.DataFrame({}, columns=['effective_date', 'ratio', 'sid'])
-        mergers.effective_date = mergers.effective_date.astype(int)
-        mergers.ratio = mergers.ratio.astype(float)
-        mergers.sid = mergers.sid.astype(int)
+        mergers.effective_date = mergers.effective_date.astype(np.int64)
+        mergers.ratio = mergers.ratio.astype(np.float64)
+        mergers.sid = mergers.sid.astype(np.int64)
 
         dividends = pd.DataFrame({}, columns=['ex_date', 'record_date',
                                               'declared_date', 'pay_date',
                                               'amount', 'sid'])
-        dividends.amount = dividends.amount.astype(float)
-        dividends.sid = dividends.sid.astype(int)
+        dividends.amount = dividends.amount.astype(np.float64)
+        dividends.sid = dividends.sid.astype(np.int64)
 
         adj_writer.write(splits, mergers, dividends)
 

tests/test_api_shim.py

@@ -203,15 +203,15 @@ class TestAPIShim(TestCase):
         # Mergers and Dividends are not tested, but we need to have these
         # anyway
         mergers = pd.DataFrame({}, columns=['effective_date', 'ratio', 'sid'])
-        mergers.effective_date = mergers.effective_date.astype(int)
-        mergers.ratio = mergers.ratio.astype(float)
-        mergers.sid = mergers.sid.astype(int)
+        mergers.effective_date = mergers.effective_date.astype(np.int64)
+        mergers.ratio = mergers.ratio.astype(np.float64)
+        mergers.sid = mergers.sid.astype(np.int64)
 
         dividends = pd.DataFrame({}, columns=['ex_date', 'record_date',
                                               'declared_date', 'pay_date',
                                               'amount', 'sid'])
-        dividends.amount = dividends.amount.astype(float)
-        dividends.sid = dividends.sid.astype(int)
+        dividends.amount = dividends.amount.astype(np.float64)
+        dividends.sid = dividends.sid.astype(np.int64)
 
         adj_writer.write(splits, mergers, dividends)
 

tests/utils/daily_bar_writer.py

@@ -1,6 +1,7 @@
 from numpy import (
     float64,
-    uint32
+    uint32,
+    int64,
 )
 from bcolz import ctable
 
@@ -37,8 +38,9 @@ class DailyBarWriterFromDataFrames(BcolzDailyBarWriter):
             return array.astype(uint32)
         elif colname == 'day':
             nanos_per_second = (1000 * 1000 * 1000)
-            self.check_uint_safe(arrmax.view(int) / nanos_per_second, colname)
-            return (array.view(int) / nanos_per_second).astype(uint32)
+            self.check_uint_safe(arrmax.view(int64) / nanos_per_second,
+                                 colname)
+            return (array.view(int64) / nanos_per_second).astype(uint32)
 
     @staticmethod
     def check_uint_safe(value, colname):

zipline/data/minute_bars.py

@@ -163,10 +163,10 @@ class BcolzMinuteBarMetadata(object):
             'first_trading_day': str(self.first_trading_day.date()),
             'market_opens': self.market_opens.values.
             astype('datetime64[m]').
-            astype(int).tolist(),
+            astype(np.int64).tolist(),
             'market_closes': self.market_closes.values.
             astype('datetime64[m]').
-            astype(int).tolist(),
+            astype(np.int64).tolist(),
             'ohlc_ratio': self.ohlc_ratio,
         }
         with open(self.metadata_path(rootdir), 'w+') as fp:
@@ -603,10 +603,10 @@ class BcolzMinuteBarReader(object):
 
         self._market_opens = metadata.market_opens
         self._market_open_values = metadata.market_opens.values.\
-            astype('datetime64[m]').astype(int)
+            astype('datetime64[m]').astype(np.int64)
         self._market_closes = metadata.market_closes
         self._market_close_values = metadata.market_closes.values.\
-            astype('datetime64[m]').astype(int)
+            astype('datetime64[m]').astype(np.int64)
 
         self._ohlc_inverse = 1.0 / metadata.ohlc_ratio
 
@@ -643,7 +643,7 @@ class BcolzMinuteBarReader(object):
         """
         market_opens = self._market_opens.values.astype('datetime64[m]')
         market_closes = self._market_closes.values.astype('datetime64[m]')
-        minutes_per_day = (market_closes - market_opens).astype(int)
+        minutes_per_day = (market_closes - market_opens).astype(np.int64)
         early_indices = np.where(
             minutes_per_day != US_EQUITIES_MINUTES_PER_DAY - 1)[0]
         regular_closes = market_opens[early_indices] + timedelta64(

zipline/testing/core.py

@@ -45,7 +45,8 @@ from zipline.utils.tradingcalendar import trading_days
 import numpy as np
 from numpy import (
     float64,
-    uint32
+    uint32,
+    int64,
 )
 
 
@@ -456,8 +457,9 @@ def make_trade_data_for_asset_info(dates,
     sids = asset_info.keys()
     date_field = 'day' if frequency == 'daily' else 'dt'
 
-    price_sid_deltas = np.arange(len(sids), dtype=float) * price_step_by_sid
-    price_date_deltas = np.arange(len(dates), dtype=float) * price_step_by_date
+    price_sid_deltas = np.arange(len(sids), dtype=float64) * price_step_by_sid
+    price_date_deltas = (np.arange(len(dates), dtype=float64) *
+                         price_step_by_date)
     prices = (price_sid_deltas + price_date_deltas[:, None]) + price_start
 
     volume_sid_deltas = np.arange(len(sids)) * volume_step_by_sid
@@ -723,8 +725,9 @@ class DailyBarWriterFromDataFrames(BcolzDailyBarWriter):
             return array.astype(uint32)
         elif colname == 'day':
             nanos_per_second = (1000 * 1000 * 1000)
-            self.check_uint_safe(arrmax.view(int) / nanos_per_second, colname)
-            return (array.view(int) / nanos_per_second).astype(uint32)
+            self.check_uint_safe(arrmax.view(int64) / nanos_per_second,
+                                 colname)
+            return (array.view(int64) / nanos_per_second).astype(uint32)
 
     @staticmethod
     def check_uint_safe(value, colname):
@@ -1198,8 +1201,8 @@ def create_mock_adjustments(tempdir, days, splits=None, dividends=None,
             'pay_date': np.array([], dtype='datetime64[ns]'),
             'record_date': np.array([], dtype='datetime64[ns]'),
             'declared_date': np.array([], dtype='datetime64[ns]'),
-            'amount': np.array([], dtype=float),
-            'sid': np.array([], dtype=int),
+            'amount': np.array([], dtype=float64),
+            'sid': np.array([], dtype=int64),
         }
         dividends = pd.DataFrame(
             data,
@@ -1360,9 +1363,9 @@ def create_empty_splits_mergers_frame():
     return pd.DataFrame(
         {
             # Hackery to make the dtypes correct on an empty frame.
-            'effective_date': np.array([], dtype=int),
-            'ratio': np.array([], dtype=float),
-            'sid': np.array([], dtype=int),
+            'effective_date': np.array([], dtype=int64),
+            'ratio': np.array([], dtype=float64),
+            'sid': np.array([], dtype=int64),
         },
         index=pd.DatetimeIndex([]),
         columns=['effective_date', 'ratio', 'sid'],