class_docstr: Fixture for generating international daily bars.
  
  Eventually this should be moved into zipline.testing.fixtures and should
  replace most of the existing machinery
code: def make_daily_bar_data(cls, assets, calendar, sessions):
      # Generate prices corresponding to uniform random returns with a slight
      # positive tendency.
      start = cls.INTERNATIONAL_PRICING_STARTING_PRICES[calendar.name]
  
      closes = random_tick_prices(start, len(sessions))
      opens = closes - 0.05
      highs = closes + 0.10
      lows = closes - 0.10
      volumes = np.arange(10000, 10000 + len(closes))
  
      base_frame = pd.DataFrame(
          {
              "close": closes,
              "open": opens,
              "high": highs,
              "low": lows,
              "volume": volumes,
          },
          index=sessions,
      )
  
      for asset in assets:
          sid = asset.sid
          yield sid, base_frame + sid
  
imports: from itertools import cycle, islice
  from nose_parameterized import parameterized
  import numpy
  import pandas
  from trading_calendars import get_calendar
  from zipline.assets.synthetic import make_rotating_equity_info
  from zipline.data.in_memory_daily_bars import InMemoryDailyBarReader
  from zipline.pipeline.domain import CA_EQUITIES, GB_EQUITIES, US_EQUITIES
  from zipline.pipeline import Pipeline
  from zipline.pipeline.data import EquityPricing, USEquityPricing
  from zipline.pipeline.engine import SimplePipelineEngine
  from zipline.pipeline.loaders.equity_pricing_loader import EquityPricingLoader
  from zipline.pipeline.loaders.synthetic import NullAdjustmentReader
  from zipline.testing.predicates import assert_equal
  from zipline.testing.core import parameter_space, random_tick_prices
  import zipline.testing.fixtures
label_desc: Use image node_id 1 for calling the WithInternationalDailyBarData obj's underlying member method code with example usage: obj.make_daily_bar_data(cls, assets, calendar, sessions) without return types