content: #
  # Copyright 2014 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.
  
  from unittest import TestCase
  from nose.tools import (
      timed,
      nottest
  )
  
  from datetime import datetime
  import pandas as pd
  
  import pytz
  from zipline.finance import trading
  from zipline.algorithm import TradingAlgorithm
  from zipline.finance import slippage
  from zipline.utils import factory
  from zipline.utils.factory import create_simulation_parameters
  from zipline.utils.test_utils import (
      setup_logger,
      teardown_logger
  )
  from zipline.protocol import (
      Event,
      DATASOURCE_TYPE
  )
  
  DEFAULT_TIMEOUT = 15  # seconds
  EXTENDED_TIMEOUT = 90
  
  
  class RecordDateSlippage(slippage.FixedSlippage):
      def __init__(self, spread):
          super(RecordDateSlippage, self).__init__(spread=spread)
          self.latest_date = None
  
      def simulate(self, event, open_orders):
          self.latest_date = event.dt
          result = super(RecordDateSlippage, self).simulate(event, open_orders)
          return result
  
  
  class TestAlgo(TradingAlgorithm):
  
      def __init__(self, asserter, *args, **kwargs):
          super(TestAlgo, self).__init__(*args, **kwargs)
          self.asserter = asserter
  
      def initialize(self, window_length=100):
          self.latest_date = None
  
          self.set_slippage(RecordDateSlippage(spread=0.05))
          self.stocks = [self.sid(8229)]
          self.ordered = False
          self.num_bars = 0
  
      def handle_data(self, data):
          self.num_bars += 1
          self.latest_date = self.get_datetime()
  
          if not self.ordered:
              for stock in self.stocks:
                  self.order(stock, 100)
  
              self.ordered = True
  
          else:
  
              self.asserter.assertGreaterEqual(
                  self.latest_date,
                  self.slippage.latest_date
              )
  
  
  class AlgorithmGeneratorTestCase(TestCase):
      def setUp(self):
          setup_logger(self)
  
      def tearDown(self):
          teardown_logger(self)
  
      @nottest
      def test_lse_algorithm(self):
  
          lse = trading.TradingEnvironment(
              bm_symbol='^FTSE',
              exchange_tz='Europe/London'
          )
  
          with lse:
  
              sim_params = factory.create_simulation_parameters(
                  start=datetime(2012, 5, 1, tzinfo=pytz.utc),
                  end=datetime(2012, 6, 30, tzinfo=pytz.utc)
              )
              algo = TestAlgo(self, identifiers=[8229], sim_params=sim_params)
              trade_source = factory.create_daily_trade_source(
                  [8229],
                  200,
                  sim_params
              )
              algo.set_sources([trade_source])
  
              gen = algo.get_generator()
              results = list(gen)
              self.assertEqual(len(results), 42)
              # May 7, 2012 was an LSE holiday, confirm the 4th trading
              # day was May 8.
              self.assertEqual(results[4]['daily_perf']['period_open'],
                               datetime(2012, 5, 8, 8, 31, tzinfo=pytz.utc))
  
      @timed(DEFAULT_TIMEOUT)
      def test_generator_dates(self):
          """
          Ensure the pipeline of generators are in sync, at least as far as
          their current dates.
          """
          sim_params = factory.create_simulation_parameters(
              start=datetime(2011, 7, 30, tzinfo=pytz.utc),
              end=datetime(2012, 7, 30, tzinfo=pytz.utc)
          )
          algo = TestAlgo(self, identifiers=[8229], sim_params=sim_params)
          trade_source = factory.create_daily_trade_source(
              [8229],
              sim_params
          )
          algo.set_sources([trade_source])
  
          gen = algo.get_generator()
          self.assertTrue(list(gen))
  
          self.assertTrue(algo.slippage.latest_date)
          self.assertTrue(algo.latest_date)
  
      @timed(DEFAULT_TIMEOUT)
      def test_handle_data_on_market(self):
          """
          Ensure that handle_data is only called on market minutes.
  
          i.e. events that come in at midnight should be processed at market
          open.
          """
          from zipline.finance.trading import SimulationParameters
          sim_params = SimulationParameters(
              period_start=datetime(2012, 7, 30, tzinfo=pytz.utc),
              period_end=datetime(2012, 7, 30, tzinfo=pytz.utc),
              data_frequency='minute'
          )
          algo = TestAlgo(self, identifiers=[8229], sim_params=sim_params)
  
          midnight_custom_source = [Event({
              'custom_field': 42.0,
              'sid': 'custom_data',
              'source_id': 'TestMidnightSource',
              'dt': pd.Timestamp('2012-07-30', tz='UTC'),
              'type': DATASOURCE_TYPE.CUSTOM
          })]
          minute_event_source = [Event({
              'volume': 100,
              'price': 200.0,
              'high': 210.0,
              'open_price': 190.0,
              'low': 180.0,
              'sid': 8229,
              'source_id': 'TestMinuteEventSource',
              'dt': pd.Timestamp('2012-07-30 9:31 AM', tz='US/Eastern').
              tz_convert('UTC'),
              'type': DATASOURCE_TYPE.TRADE
          })]
  
          algo.set_sources([midnight_custom_source, minute_event_source])
  
          gen = algo.get_generator()
          # Consume the generator
          list(gen)
  
          # Though the events had different time stamps, handle data should
          # have only been called once, at the market open.
          self.assertEqual(algo.num_bars, 1)
  
      @timed(DEFAULT_TIMEOUT)
      def test_progress(self):
          """
          Ensure the pipeline of generators are in sync, at least as far as
          their current dates.
          """
          sim_params = factory.create_simulation_parameters(
              start=datetime(2008, 1, 1, tzinfo=pytz.utc),
              end=datetime(2008, 1, 5, tzinfo=pytz.utc)
          )
          algo = TestAlgo(self, sim_params=sim_params)
          trade_source = factory.create_daily_trade_source(
              [8229],
              sim_params
          )
          algo.set_sources([trade_source])
  
          gen = algo.get_generator()
          results = list(gen)
          self.assertEqual(results[-2]['progress'], 1.0)
  
      def test_benchmark_times_match_market_close_for_minutely_data(self):
          """
          Benchmark dates should be adjusted so that benchmark events are
          emitted at the end of each trading day when working with minutely
          data.
          Verification relies on the fact that there are no trades so
          algo.datetime should be equal to the last benchmark time.
          See https://github.com/quantopian/zipline/issues/241
          """
          sim_params = create_simulation_parameters(num_days=1,
                                                    data_frequency='minute')
          algo = TestAlgo(self, sim_params=sim_params, identifiers=[8229])
          algo.run(source=[], overwrite_sim_params=False)
          self.assertEqual(algo.datetime, sim_params.last_close)
  