__init__.py 文件源码

def vectorize (f):
  from functools import wraps
  try:
    from pandas import Series, unique
    @wraps(f)
    def vectorized_f (x):
      # If we're given a scalar value, then simply return it.
      if not hasattr(x,'__len__'):
        return f(x)
      # Get unique values
      inputs = unique(x)
      outputs = map(f,inputs)
      table = dict(zip(inputs,outputs))
      result = Series(x).map(table)
      return result.values
  except ImportError:
    def cached_f(x, cache={}):
      if x not in cache:
        cache[x] = f(x)
      return cache[x]
    @wraps(f)
    def vectorized_f (x):
      # If we're given a scalar value, then simply return it.
      if not hasattr(x,'__len__'):
        return cached_f(x)
      return map(cached_f,x)
  return vectorized_f


# The type of data returned by the Buffer iterator.