Python列表转换为XML，反之亦然 [英] Python list to XML and vice versa

问题描述

我编写了一些python代码，用于将python列表转换为XML元素.它是用于与LabVIEW交互的，因此是怪异的XML数组格式.无论如何，这是代码:

I have some python code that I wrote to convert a python list into an XML element. It's meant for interacting with LabVIEW, hence the weird XML array format. Anyways, here's the code:

def pack(data):
  # create the result element
  result = xml.Element("Array")

  # report the dimensions
  ref = data
  while isinstance(ref, list):
    xml.SubElement(result, "Dimsize").text = str(len(ref))
    ref = ref[0]

  # flatten the data
  while isinstance(data[0], list):
    data = sum(data, [])

  # pack the data
  for d in data:
    result.append(pack_simple(d))

  # return the result
  return result

现在，我需要编写一个unpack()方法，将打包的XML数组转换回python列表.我可以很好地提取数组维度和数据:

Now I need to write an unpack() method to convert the packed XML Array back into a python list. I can extract the array dimensions and data just fine:

def unpack(element):
  # retrieve the array dimensions and data
  lengths = []
  data = []
  for entry in element:
    if entry.text == "Dimsize":
      lengths.append(int(entry.text))

    else:
      data.append(unpack_simple(entry))

  # now what?

但是我不确定如何展开数组.一种有效的方法是什么?

But I am not sure how to unflatten the array. What would be an efficient way to do that?

这是python列表和相应XML的外观.注意:数组是n维的.

Here's what the python list and corresponding XML looks like. Note: the arrays are n-dimensional.

data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]

然后是XML版本:

<Array>
  <Dimsize>2</Dimsize>
  <Dimsize>2</Dimsize>
  <Dimsize>2</Dimsize>
  <I32>
    <Name />
    <Val>1</Val>
  </I32>

  ... 2, 3, 4, etc.
</Array>

实际的格式并不重要，我只是不知道如何展开以下列表:

The actual format isn't important though, I just don't know how to unflatten the list from:

data = [1, 2, 3, 4, 5, 6, 7, 8]

返回至:

data = [[[1, 2], [3, 4]], [[5, 6], [7, 8]]]

给定:

lengths = [2, 2, 2]

对于基本数据类型(int，long，string，boolean)，假设pack_simple()和unpack_simple()与pack()和unpack()相同.

Assume pack_simple() and unpack_simple() do the same as pack() and unpack() for the basic data types (int, long, string, boolean).

推荐答案

尝试以下操作:

from operator import mul

def validate(array, sizes):
    if reduce(mul, sizes) != len(array):
        raise ValueError("Array dimension incompatible with desired sizes")

    return array, sizes

def reshape(array, sizes):
    for s in sizes:
        array = [array[i:i + s] for i in range(0, len(array), s)]

    return array[0]

data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
length = [2, 2, 3]

print reshape(validate(data, length))

length = [2, 2, 2]

print reshape(validate(data, length))

输出为:

[[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[9, 10], [11, 12]]]
Traceback:
   (...)
ValueError: Array dimension incompatible with desired sizes

---

一种替代方法是使用numpy数组.请注意，对于这个简单的任务，numpy是一个相当大的依赖项，尽管您会发现大多数(常见)与数组相关的任务/问题已经在此处实现:

---

An alternative is using numpy arrays. Note that for this simple task, numpy is a rather big dependency, though you will find that most (common) array related tasks/problems already have an implementation there:

from numpy import array

print array(data).reshape(*length)  # optionally add .tolist() to convert to list

编辑:添加了数据验证

编辑:使用numpy数组的示例(感谢J.F. Sebastian的提示)

EDIT: Example using numpy arrays (thanks to J.F.Sebastian for the hint)

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