class_docstr: PipelineLoader for Crypto Pricing data
  
  Delegates loading of baselines and adjustments.
class_docstr_tok: ["PipelineLoader","for","Crypto","Pricing","data","Delegates","loading","of","baselines","and","adjustments","."]
code: def __init__(self, bundle, data_frequency, dataset):
      cal = get_calendar("OPEN")
  
      if data_frequency == "daily":
          reader = bundle.daily_bar_reader
          all_sessions = cal.all_sessions
  
      elif data_frequency == "minute":
          reader = bundle.minute_bar_reader
          all_sessions = cal.all_minutes
  
      else:
          raise ValueError(
              "Invalid data frequency: {}".format(data_frequency)
          )
  
      self.raw_price_loader = reader
      self._columns = dataset.columns
      self._all_sessions = all_sessions
  
file_path: catalyst/catalyst/pipeline/loaders/crypto_pricing_loader.py
imports: from numpy import iinfo, uint32
  from catalyst.data.us_equity_pricing import BcolzDailyBarReader
  from catalyst.lib.adjusted_array import AdjustedArray
  from catalyst.errors import NoFurtherDataError
  from catalyst.utils.calendars import get_calendar
  from .base import PipelineLoader
label_desc: Use image node_id 1 to create a new CryptoPricingLoader object from inherited base classes: PipelineLoader with example: obj = CryptoPricingLoader(bundle, data_frequency, dataset)