use dt.normalize() in pd>=0.20

tests/finance/test_slippage.py

@@ -21,7 +21,6 @@ import datetime
 from math import sqrt
 
 from nose_parameterized import parameterized
-from pandas.tslib import normalize_date
 import numpy as np
 import pandas as pd
 import pytz
@@ -1108,8 +1107,8 @@ class OrdersStopTestCase(WithSimParams,
             )),
         )
         days = pd.date_range(
-            start=normalize_date(self.minutes[0]),
-            end=normalize_date(self.minutes[-1])
+            start=self.minutes[0].normalize(),
+            end=self.minutes[-1].normalize()
         )
         with tmp_bcolz_equity_minute_bar_reader(
                 self.trading_calendar, days, assets) as reader:

tests/pipeline/test_pipeline_algo.py

@@ -27,7 +27,6 @@ from pandas import (
     Series,
     Timestamp,
 )
-from pandas.tseries.tools import normalize_date
 from six import iteritems, itervalues
 
 from catalyst.algorithm import TradingAlgorithm
@@ -530,7 +529,7 @@ class PipelineAlgorithmTestCase(WithBcolzEquityDailyBarReaderFromCSVs,
             attach_pipeline(pipeline, 'test')
 
         def handle_data(context, data):
-            today = normalize_date(get_datetime())
+            today = get_datetime().normalize()
             results = pipeline_output('test')
             expect_over_300 = {
                 AAPL: today < self.AAPL_split_date,

tests/test_fetcher.py

@@ -395,7 +395,6 @@ def handle_data(context, data):
 
             algocode = """
 from pandas import Timestamp
-from pandas.tseries.tools import normalize_date
 from catalyst.api import fetch_csv, record, sid, get_datetime
 
 def initialize(context):
@@ -411,7 +410,7 @@ def initialize(context):
     context.bar_count = 0
 
 def handle_data(context, data):
-    expected = context.expected_sids[normalize_date(get_datetime())]
+    expected = context.expected_sids[get_datetime().normalize()]
     actual = data.fetcher_assets
     for stk in expected:
         if stk not in actual: