无法打开旧的泡菜文件

Question

我正在尝试加载包含航空公司数据集 (https://arxiv.org/abs/1611.06740) 的旧泡菜文件。泡菜很旧，我无法访问它。如果我尝试：

objects = []
with (open("airline.pickle", "rb")) as openfile:
    while True:
        try:
            objects.append(pickle.load(openfile))
        except EOFError:
            break

我收到以下警告和错误：

FutureWarning: pandas.core.index is deprecated and will be removed in a future version.  The public classes are available in the top-level namespace.
  objects.append(pickle.load(openfile))
Traceback (most recent call last):
  File "c:\Users\LocalAdmin\surfdrive\Code\Python\Airline\pickleToCSV.py", line 9, in <module>
    objects.append(pickle.load(openfile))
TypeError: _reconstruct: First argument must be a sub-type of ndarray

尝试使用 pandas 不起作用：

  File "C:\Users\LocalAdmin\surfdrive\Code\Python\Airline\Airline\lib\site-packages\pandas\io\pickle.py", line 203, in read_pickle
    return pickle.load(handles.handle)  # type: ignore[arg-type]
TypeError: _reconstruct: First argument must be a sub-type of ndarray

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "c:\Users\LocalAdmin\surfdrive\Code\Python\Airline\pickleToCSV.py", line 7, in <module>
    df = pd.read_pickle('airline.pickle')
  File "C:\Users\LocalAdmin\surfdrive\Code\Python\Airline\Airline\lib\site-packages\pandas\io\pickle.py", line 208, in read_pickle
    return pc.load(handles.handle, encoding=None)
  File "C:\Users\LocalAdmin\surfdrive\Code\Python\Airline\Airline\lib\site-packages\pandas\compat\pickle_compat.py", 
line 249, in load
    return up.load()
  File "C:\Users\LocalAdmin\AppData\Local\Programs\Python\Python39\lib\pickle.py", line 1212, in load
    dispatch[key[0]](self)
  File "C:\Users\LocalAdmin\AppData\Local\Programs\Python\Python39\lib\pickle.py", line 1725, in load_build
    for k, v in state.items():
AttributeError: 'tuple' object has no attribute 'items'

如何访问该文件并将其保存为 csv？我需要那里包含的数据。我正在使用熊猫 1.2.4 和 python 3.6。

Answer 1

语法应该比你的例子更简单

with open("airline.pickle", "rb") as f:
    objects = pickle.load(f)

如果失败，那么我会查看pickle documentation，它涵盖了一些可用于解码由 python2 创建的泡菜文件的可选参数。